Citation
The impact of residential environment on psychological adjustment of college students

Material Information

Title:
The impact of residential environment on psychological adjustment of college students
Creator:
Campbell, Michael Harry, 1969-
Publication Date:
Language:
English
Physical Description:
vi, 80 leaves : 29 cm.

Subjects

Subjects / Keywords:
Cognitive psychology ( jstor )
College students ( jstor )
Colleges ( jstor )
Commuters ( jstor )
Commuting students ( jstor )
Emotional adjustment ( jstor )
Psychological counseling ( jstor )
Psychological research ( jstor )
Psychology ( jstor )
Psychometrics ( jstor )
Counseling Psychology thesis, Ph.D ( lcsh )
Dissertations, Academic -- Counseling Psychology -- UF ( lcsh )
Genre:
bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

Notes

Thesis:
Thesis (Ph. D.)--University of Florida, 1998.
Bibliography:
Includes bibliographical references (leaves 74-79).
Additional Physical Form:
Also available online.
General Note:
Typescript.
General Note:
Vita.
Statement of Responsibility:
by Michael Harry Campbell.

Record Information

Source Institution:
University of Florida
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
0029220508 ( ALEPH )
39540325 ( OCLC )

Downloads

This item has the following downloads:


Full Text







THE IMPACT OF RESIDENTIAL ENVIRONMENT ON
PSYCHOLOGICAL ADJUSTMENT OF COLLEGE STUDENTS
























By

MICHAEL HARRY CAMPBELL










A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE
UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 1998














ACKNOWLEDGEMENTS


I extend sincere thanks to Dorothy Nevill and Franz Epting for their assistance

with this manuscript and, more generally, for their guidance during my graduate career. I am indebted to Shawn Prichard for friendship and intellectual stimulation, as well as, more concretely, technical assistance with the data analysis here presented. My thanks for the extraordinary support provided by my family-especially my parents, Don and Sylvia Campbell, and my grandmother, Mary Alice Knight-cannot be adequately acknowledged here,














TABLE OF CONTENTS





ACKNOWLEDGEMENTS .................................................................

A B ST R A C T ................................ I ................................................. v

CHAPTERS

I INTRODUCTION ....................................................................... 1

2 REVIEW OF LITERATURE ........................................................... 7

Campus Ecology as Context ....................................................... 7
The Interface of Research in Environmental and Counseling/Clinical
P sychology ......................................................................... 10
Residential Status and the Welfare of Commuter Students .................. 12
The Impact of Physical Environmental Features on Well-Being ............ 22
Rationale for the Present Study ......... ........................................ 26

3 M E T H O D ................................................................................ 30

P articip ants ......................................................................... 30
M aterials ............................................................................ 3 1
Design and Procedure ............................................................. 33
A nalytic Strategy .................................................................. 34

4 R E SU L T S .................................................................... ........... 37

Descriptive Characteristics of the Variable Set ............................... 37
O m nibus A nalyses ................................................................ 41
Follow-up Analyses ............................................................... 43
Factor Structure of the College Adjustment Scales ........................... 50
Summary of Hypotheses .......................................................... 56
Psychological Treatment Effects Revisited ..................................... 60

5 DISCUSSION ................................ ...... ....... 62
iii








Environment versus Treatment Effects and Student Characteristics ...... 62 Environment and Adjustment ................................................... 64
Implications for Policy ........................................................... 66
Directions for Future Research ................................................. 67


APPENDICES

A INFORMED CONSENT STATEMENT .......................................... 70

B QUESTIONNAIRE ................................................................... 71

R EFER EN C E S ............................................................................. 74

BIOGRAPHICAL SKETCH ............................................................. 80
































iv














Abstract of Dissertation Presented to the Graduate School of the University of Florida in
Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy


THE IMPACT OF RESIDENTIAL ENVIRONMENT ON
PSYCHOLOGICAL ADJUSTMENT OF COLLEGE STUDENTS By

Michael Harry Campbell

May 1998


Chair: Dorothy D. Nevill, Ph.D.
Major Department: Counseling Psychology

This study investigated the relationship of residential environment and location to the psychological adjustment of college undergraduates. Students from several institutions were asked to provide information about their housing environments (e.g., location, noise estimates, light levels, number of roommates, and contents of the visual landscape) and to complete a multiple-scale measure of psychological adjustment: the College Adjustment Scales. The contribution of residential environment to psychological well-being was demonstrated via multiple multivariate analyses controlling for the influence of psychological treatment history and demographic characteristics. Results demonstrated that environmental variables, particularly the presence of grass in window vistas and lower subjective ratings of noise and light levels, were positively associated

v










with psychological adjustment. In addition, the association of treatment history with current adjustment was elucidated through post-hoc analyses. Finally, this study addresses the psychometric properties of the College Adjustment Scales, underscoring their limitation as a research instrument. The discussion addresses the theoretical implications of the findings in terms of the extant literature on psychological benefits of natural landscape elements. The conclusion addresses potential contributions of qualitative approaches as a compliment to quantitative landscape research.





























Vi














CHAPTER
INTRODUCTION



The interface of counseling or clinical psychology with the broader perspective of environmental or ecological approaches has generated a number of novel research questions regarding the impact of environmental features on psychological well-being. The present study is a contribution to this tradition, although the geographic domain of this researchthe campus community-has been relatively, and surprisingly, neglected in previous work. This paucity of research is peculiar for a number of reasons. First, of course, is the irony that most academic researchers in psychology, of any specialty, work in a campus setting. Certainly psychologists have ample exposure to campus environments; in fact, one could effectively argue that the campus context shapes the process and outcome of research in environmental psychologyjust as it does for other fields. Second, student affairs personnel have secured a prominent place in higher education. These professionals, whose mandate includes responsibility for administration of campus living spaces, activities, and conduct have evidenced interest in ecological perspectives and recognized clearly that a student's collegiate experience is contextualized by a campus system comprised of social, (multi) cultural, spatial, and physical factors. Indeed, the academic and professional journals in college student personnel have endorsed ecological approaches to campus design (e.g., Banning & Kaiser, 1974). Third, campus mental health professionals, particularly counseling psychologists, whose training usually affords substantial exposure to college-age
1







2

populations, are keenly aware of mental health issues on campus and often work from a developmental perspective concerned with psychological (and geographical) transitions. Fourth, other researchers, principally geographers and sociologists concerned with the impact of place, could contribute to the understanding not only of measurable environmental impact but also, more qualitatively, of genius loci, the spirit of place, the totality of a landscape, encompassing intangible and transcendent qualities that account for the uniqueness of place (Seamon, 1989).

Given the diversity of intellectual traditions that can profitably address the role of

physical environment in the psychological experience of college students, the relative dearth of research is disappointing. Perhaps the relevant disciplines are so divergent in training and practice that fruitful cross-disciplinary collaboration is seldom afforded. Indeed, the current study is, of necessity, focused on a limited number of research perspectives and analytical methodologies. Taylor, Zube, and Sell (1987) offer a useful classification system for research evaluating landscapes. Their nomenclature distinguishes four approaches to landscape research: the psychophysical, cognitive, expert, and experiential. The psychophysical and cognitive approaches both focus on human responses as measured by quantitative techniques, often self-report of scenic beauty estimates or landscape preference; the two approaches are distinguished from each other chiefly by the emphasis placed on human information processing theory. Whereas the psychophysical approach typically assumes that humans are passive (and unconscious) responders to the environment, the cognitive approach holds that structures and needs of our information processing systems mediate our experience of the environment. Thus, in the psychophysical paradigm, psychological responses to environmental stimuli are measured; in the cognitive paradigm,







3

however, theory derived from cognitive psychology helps explain why certain psychological responses are obtained. The expert paradigm holds that those best qualified to evaluate landscape achieve such status only through heightened sensitivity inculcated by professional training. Such evaluations may be more subjective that those of psychophysical and cognitive methods, but the persons making decisions presumably have a more sophisticated perspective derived ftorn education and work experience. The fourth paradigm, the experiential approach, focuses on the experience of diverse individuals or groups and usually employs qualitative, often phenomenological, methodology. A graphical summary of these approaches is presented in Table 1-1.



Table 1 1: Paradigms for Landscape Evaluation Paradigm Methodology Ratings given by Theoretical focus
Psychophysical quantitative laypersons stimulus-response

Cognitive quantitative laypersons information processing

Expert qualitative/quantitative experts expert design

Experiential qualitative laypersons humanistic/phenomenological





The approach taken in the present research is best represented by the psychophysical and cognitive paradigms. The approach is psychophysical because it attempts to demonstrate linkages between specific environmental features and psychological outcomes. However, it is cognitive, as well, inasmuch as theoretical assumptions about psychological reaction to environmental stimuli were used to generate hypotheses. In another manner, this







4

study is conceptually distinct from "mainstream" landscape research. The latter tends to operationalize psychological reaction in terms of preference; in contrast, the present study is expressly concerned with psychological adjustment as a criterion measure. Thus, psychological outcomes of importance here include not preference but impact on mental health in the domains of depression, anxiety, substance abuse, interpersonal distress, among other areas.

In the chapters that follow, these issues are addressed both theoretically and

empirically. Chapter 2 reviews the extant literature in counseling/clinical psychology, environmental psychology and college student personnel. The chapter begins with a treatment of ecological approaches that place the student into an integrated, transactional environmental system (e.g., Kaiser, 1977). The subsequent section reviews existing research on the impact of environmental features on psychological well-being and recent calls for a more transactional understanding of psychological funrctioning. The following sections summarize findings of the student affairs literature (e.g., Chickering & Reisser, 1993) regarding characteristics and needs that distinguish commuters from residential students, concluding that the extant literature has neglected, for the most part, psychological measures of differences. A methodological critique then proposes alternative measures of adjustment that would better operationalize psychological status: the College Adjustment Scales (CAS; Anton & Reed, 199 1) and the College Maladjustment Scale (Mt; Kleinmuntz, 1960). The next sections summarize the psychological benefit of specific environmental features, such as nature scenes (Kaplan & Kaplan, 1989; Ulrich, 1981), windows (Butler & Biner, 1989), and configural aspects of landscape (Campbell, 1994; Herzog, 1989, 1992; Kaplan & Kaplan, 1989). In addition, this section includes a brief review of detrimental







5

features, such as crowding (Evans & Lepore, 1993; Krupat, 1985; Milgram, 1970), noise (Levy-Loboyer & Naturel, 1991) and barriers to commuting (Novaco, Kiewer, & Broquet, 1991). Chapter 2 concludes with a summary of the rationale for the present study and a series of tentative research hypotheses.

Chapter 3 details methods and research design, including sample characteristics, psychometric characteristics of the research instruments, procedural protocol, and the general strategy for data analysis. This last topic includes discussion of the methodological challenges inherent in multivariate quasiexperimental design, as well as the rationale for use of multivariate analysis of variance (LA!NOVA) with a series of follow-up stepwise multiple regression equations. This section also reviews some unanticipated problems in protocol administration leading to the exclusion of College Maladjustment Scale scores from the final data set.

Chapter Four presents results in several sections. First, a descriptive summary of predictor and criterion variables is offered. Second, results of IVANOVA analyses demonstrate the significance of predictor variables for scores on the nine-scale College Adjustment Scales. Third, a series of stepwise multiple regression models for each of the nine CAS scales follows the MANOVA in order to model specific environmental effects on anxiety, depression, suicidal ideation, substance abuse, self-esteem, interpersonal problems, family problems, academic problems, and career problems. A fourth set of analyses examines multicolinearity among the nine CAS scales, as well, via principal components analysis of the factor structure underlying the CAS. Inadequacies of the factor structure are discussed, and an alternative measure of global adjustment is proposed. Finally, a regression model of global adjustment is offered, although this new model, contrary to






6

expectation, offers little additional information relative to models of scores on each of the nine component CAS scales

The final chapter is a discussion of the present findings and argues that, although treatment indicators and subject variables are most predictive of adjustment, some environmental variables (e.g., grass, noise, light, residential satisfaction and, to a lesser extent, number of roommates) also manifest a relationship with psychological functioning. The implication of these finding for campus architects, student affairs professionals, mental health providers, and educational policy makers is discussed. Additionally, the psychometric inadequacy of the CAS is discussed. The conclusion advocates the use of alternative measures for future research (1) to avoid the stringency imposed by NLANOVA and (2) to achieve better discriminant validity. The final sections suggest directions for future research, particularly the integration of quantitative and qualitative approaches pioneered by researchers such as Schroeder (1991). Such integration simultaneously offers both testable hypotheses and a fuller understanding of the more intangible, subjective, and transcendent qualities of place (Relph, 1985; Seamon, 1984, 1989).














CHAPTER 2
REVIEW OF LITERATURE



Ca=us Ecology as Contex

The psychological adjustment of college students has received substantial attention in the literatures of counseling psychology and college student personnel. However, comparatively scant research focus has been directed toward the impact of residential environment on psychological adjustment. This trend is manifest in spite of a relatively well-known literature of campus ecology, in which college environments are viewed as interactive environmental systems (Banning & Kaiser, 1974; Morrill, Oetting, & Hurst, 1974; Pace, Stamler, Yarris, & June, 1996). Although the importance of physical environment is usually acknowledged in ecological models, greater emphasis has been placed on sociocultural, interpersonal, and academic factors; as a result, physico-spatial aspects of college student adjustment have been relatively neglected.

Nonetheless, it is appropriate to begin this review with an explication of campus ecology as context for the present study. Although this research focuses on one, relatively narrow, aspect of college environment, the study here presented is most thoroughly understood in the context of campus ecological systems which are integrative, comprehensive, and most especially, transactional in nature.

Campus ecology is concerned both with the student's "consciousness" and the environment in which he or she lives (Kaiser, 1977). The campus environment consists
7







8

of varied spaces: the personal, the social, the physical, the academic and any number of others relevant to the experience of the student. Campus spaces are settings for student growth and development and, thus, are integral parts of the college experience. This view obviates the need for considered attention to space by campus designers and policy makers:

Every learning space has a demand load. It calls for certain responses from the
student entering the space. A student and campus may be matched or mismatched.
A mismatched space is one that fails to provide what the student needs or demands a
response the student cannot give. Too great a mismatch is stressful for the student
and may generate a negative reaction (Kaiser, 1977, p. 24).


The student's experience is shaped by the college environment, but the relationship is not simply one of causative factor to responding organism. Rather, a more dynamic, holistic conceptualization, in which students in environment are the primary unit of analysis, is taken here. This approach, developed by Altman (see Altman & Rogoff, 1987 for delineation of this view) and expanded by others (cf. Wapner, 1995), is characterized by a systems-centered perspective that, when applied to campus environments, holds that students are integral components of the larger campus environmental system. Such an approach suggests that the process of influence is mutual among interconnected elements. That is, a college student's experience is molded by multiple elements of the environment, but that same student--and, by extension, larger groups of students--is also an active shaper of the envirom-nental system, because he or she belongs to that system. This view implies that the personal characteristics which students bring to college, including life history, personality traits, and psychological (dys)ftmction become important influences in the person-envirom-nent system. In terms of the present study, this theoretical perspective







9

suggests that the decisions students make about their residential choice will be impacted by personal and environmental factors, and that students' college housing environments will act to shape their educational experience and psychological well-being.

Campus mental health professionals have shown some interest in an ecological conceptualization. of student functioning, although a review of the literature suggests that this perspective has been limited in scope and influence. Morrill, Oetting, and Hurst (1974) proposed a framework for counseling interventions not limited to the therapy room. Their model, delineated in terms of target, purpose and method of intervention, expands the target domain of campus counseling staff from the traditional individual client to include primary groups (friends and family), associational groups (e.g., classes, student organizations and residence-based groups), and, most broadly, the institution or campus community. This model also expands method of service delivery beyond direct therapeutic contact to consultation, training and use of media. Finally, the purpose of intervention is defined to include, in addition to remediation of psychological difficulties, the more proactive goals of prevention of mental health problems and development of individuals and campus systems. This framework justifies, from the perspective of campus mental health providers, the need for collaborative systems-focused research and intervention in a number of areas relevant to the psychological health of students. A recent expansion of this model (Pace, Stamler, Yarris, & June, 1996) places campus counseling centers in a more dynamic ecological system, allowing greater flexibility to adapt functions to changing campus needs. That is, campus mental health professionals are seen as connected to multiple constituencies and facets of the campus system; services evolve as a function of these interrelationships. Although these models certainly broaden the legitimate domain of college mental health,







10

neither addresses explicitly the psychological aspects of residential environent. Similarly, a recent prescription for expansion and adaption of college counseling center services (Bishop, 1990) advocates broader collaboration and consultation with other campus entities; again, however, the psychological aspects of place and physical environment are not explicitly addressed. The interface of college counseling and environmental psychology is best described as a legitimate but largely unexplored area of inquiry. I now turn to a review of available literature in this and allied areas.



The Interface of Research in Environmental and Counseling /Clinical Psychology

The environmental psychology literature is a potential arena in which to address the psychological impact of campus residential environments. Indeed, recent appraisals of the field have stressed the potential for fruitful integration of environmental and counseling or clinical psychology. Stokols (1995) highlights recent trends and prospects for future work in the application of environmental psychology research to community problems, including the development of environmental strategies in health promotion. He cites several recent theoretical and basic research endeavors to document the contributions of psychology to social and psychological welfare. These include a number of efforts to understand the processes by which environmental stress can be ameliorated, through reduction of crowding (Aiello & Baum, 1979), better management policy for environmental hazards (e.g., Cvetkovich & Earle, 1992), and increased exposure to natural environents in offices and health care settings (Kaplan & Kaplan, 1989; Ulrich, 1981, 1984, 1991).

Demick and Andreoletti (1995) review a number of recent studies in order to elucidate connections between environmental and clinical psychology. The authors







11

distinguish between fields in terms of content and method, positing that clinical psychology is defined by its content area (i.e., diagnosis and treatment of psychological conditions) as well as a method of research and clinical practice. Environmental psychology, similarly, is identified by its concern with physical, interpersonal, and sociocultural environmental factors and by a more general world view of organism-environment functioning.

Demick and Andreoletti posit several conclusions regarding the integration of clinical and environmental theoretical perspectives and research methodologies. First, they suggest that broad, integrative perspectives in both fields tend to produce novel research foci, such as the impact of physical relocation on an inpatient psychiatric community (Demick & Wapner, 1980) or the role of personal space in therapy or clinical supervision. The present study is one attempt to respond to the call for cross-disciplinary research. Second, Demick and Andreoletti conceptualize environental perspectives as an alternative to traditional person-centered approaches to diagnosis and treatment; that is, "the unit of analysis in psychopathology might more aptly be conceptualized as the person-inenvironment system" (1995, p. 65). Although the research cited to support this notion focuses primarily on quite disturbed psychiatric patients, particularly those with schizophrenic diagnoses, this conceptualization applies analagously to college students, for whom adjustment, in this model, would be a function of the student-in-campus-community system. Finally, Demnick and Andreoletti propose a model of psychological functioning in terms of a series of environmental transitions throughout the lifespan. The transition to a college community (and developmental transitions within the community) are relevant to the present study, which focuses on the role of residential environent in transition to and function in the college setting.







12

Interestingly, the initial base of college environment research comes not from environmental or clinical psychology but rather from the fields of higher education and college student personnel. These early investigators were motivated by pragmatic concerns in response to the changing demographic characteristics of American undergraduates in the 1960s; they sought to provide empirical bases for policy adjustment both in academic affairs and in student life as colleges and universities struggled with the influx of commuter and part-time students. This new wave of students, as a group, entered higher education with significant differences from traditional residential students in educational background, family experience, and perhaps most importantly for policy makers, educational goals and expectations. These new students encountered a number of difficulties relative to the modal college student of the 1950s and challenged core assumptions of traditional policy makers in higher education. The challenge was met with empirical research.



Residential Status and the Welfare of Commuter Students

Student development researchers and professionals have devoted considerable attention to the divergent experiences of commuter and residential college students during the last three decades. Chickening (1974) provides the first book-length treatment of the subject in a comprehensive account of a large-scale study involving over 160,000 students from 270 diverse post-secondary institutions. Most publications have stressed the benefits afforded to students whose on-campus residence facilitates access to peer networks and to residence life programs offered by student affairs staff. With few exceptions, the distinction between off-campus residents and commuters living at home has been neglected; this is a crucial shortcoming, because it confounds the impact of family influence with residential







13

location. Moreover, increasing numbers of college students have elected to live offcampus, even when they are in school a long distance from their family's home, in response to rising room and board costs as well as campus housing shortages. I begin with Chickering's work, which has provided the base-line for subsequent investigation. I consider additional research in the paragraphs that follow, in order to generate hypotheses regarding the psychological impact of residential location.

Chickering (1974; see also Chickering & Reisser, 1993) provides a thorough empirical summary of significant differences in demographic background and college experience between commuter students and on-campus residents. Commuter students, in his sample, reported lower high school grades, and increased financial and interpersonal stressors. Their families of origin were of lower socioeconomic status, measured in terms both of reported income and of paternal occupation (fathers of commuters were more likely to be skilled, semiskilled, or unskilled workers). Chickering also reported that the majority of commuter students applied only to the college or university which they currently attended. Their educational goals were more focused on vocational preparation than those of residential students; in fact, commuters more frequently majored in business administration or engineering. Moreover, commuters were less likely to report plans to seek an advanced degree. Thus, Chickering's data suggest that commuter students enter college significantly constrained by contingencies external to their educational environments and tend to plan their education on the basis of proximity of available programs and the practicality of their degrees. Many of these students attend institutions with primarily or exclusively commuter populations; of course, many also enroll in colleges







14

or universities with strong residential traditions. Indeed, increasing numbers of students are members of the latter group.

Chickening asserts that commuter students enrolled in residential institutions experience many of the same external pressures reported by those enrolled in commuter schools. These contingencies make for an educational experience more fraught with challenges than that typically experienced by their residential classmates. Moreover, commuter students often have difficulty developing attachment to the university and its people as a function of their somewhat marginalized status and limited opportunities for involvement in campus life. There is good reason, therefore, to expect that commuter students, whether they attend commuter or residential schools, will report greater difficulties in tennis of personal and psychological adjustment. In fact, Chickering found that cominuters living with family had the least frequent interactions with faculty when compared to residential students or those living in off-campus housing. This deficit was not confined to relationships with faculty, since commuters living at home were also the least likely to study with their classmates. Moreover, students living in private off-campus residences were the least satisfied with their college experience and the least likely to report plans to continue full-time study. These myriad differences in experience held true for students enrolled in every category of educational institution included in Chickering's sample, including universities and colleges, public and private schools, two-year and fouryear programs, and Protestant and Catholic institutions.

Other researchers have demonstrated similar differences, though not with absolute consistency. Graff and Cooley (1970) assessed differences between dormitory residents and commuter students (living at home) using the College Inventory of Academic







15

Adjustment (Borow, 1951). At the conclusion of the first semester of their first year, the two groups did not differ significantly on scale measures of study habits, interpersonal relationships with faculty and peers, or personal efficiency (time management). However, commuter students reported poorer curricular adjustment, in terms of satisfaction with course work and maturity of goals and aspirations. Moreover, commuters reported poorer mental health on a scale associated with poor self-confidence, feelings of failure and excessive worry. These differences were independent of ability levels measured by the verbal section of the Scholastic Aptitude Test. On the basis of these results, Graff and Cooley recommend that college counseling centers promote the availability of services for commuters, that special orientation programs be targeted to conimuter students, that faculty be sensitive to the needs of their commuter advisees, that student unions provide special facilities for off-campus students, and that campus activities personnel endeavor to make commuters aware of available programs.

George (1971) found few significant personality differences on the Edwards Personal Preference Schedule (1959) between high school seniors planning to live on campus during their freshman year and those planning to commute from home. In fact, the most powerful predictor of students' decisions was not a personality trait but, rather, the socioeconomic status of their family of origin. Commuters students did show greater needs for autonomy and dominance, while residential students showed greater needs for change and aggression. However, the importance of these personality differences is questionable, given the very small magnitude of their impact. George's statistical analysis is reported rather telegraphically, but his research nonetheless makes clear that the predictive utility of the model is low. An aggregate stepwise multiple regression procedure, in which familial







16

socioeconomic status accounted for the lion's share of the variance, explained only about 9 percent of the variation in residential choice.

In a similar study, Welty (1976) reported a number of significant personality differences between first-year students living in dormitories and those living with parents. Commuters had lower scores on the intellectual disposition, thinking introversion, estheticism, complexity, autonomy, and altruism scales of the Omnibus Personality Inventory. Each of these differences, with the exception of autonomy scores, was maintained when the students were retested at the end of two quarters. In addition, dormitory residents participated more frequently in extracurricular activities and forined more new relationships with students and faculty. Welty concludes that student growth is not simply a function of living situation but rather that the formation of these relationships (presumably afforded by on-campus residence) is a critical developmental factor.

More recently, Wilson, Anderson, and Fleming (1987) found that commuter students reported more psychological difficulties than residential students, in terms both of personal maladjustment and of overinvolvement with parents. Their research

operationalized adjustment in terms of family systems theory, particularly the concept of fusion, which is defined as the tendency for two individuals to blend in such a way that emotional and psychological boundaries between them become blurred, confused, or overlapped. Family therapy research suggests that such relationships are unhealthy because they inhibit self-determined, goal-directed activity. Using the Intergenerational Fusion subscale of the Personal Authority in the Family System Questionnaire (Bray, Williamson, & Malone, 1984), Wilson and colleagues demonstrated that first-year college commuter students had significantly higher fusion scores than those of dormitory residents; this trend







17

was not observed, however, in more advanced students. This study also measured more general psychological adjustment using the College Maladjustment Scale (Mt; Kleinmuntz, 1960, 1961) of the Minnesota Multiphasic Personality Inventory (Hathaway & McKinley, 1943). Students living with their parents reported greater levels of maladjustment than oncampus residents, regardless of their year in school.

Finally, Pascarella, Edison, Nora, Hagedorn, and Terenzini (1996) found, in a largescale correlational study, that on-campus residence was an important predictor of openness to diversity and challenge among first-year college students. Controlling for the contribution of multiple other predictors, including demographic variables, institutional environment, social life, and academic experiences, Pascarella and colleagues found that on-campus residence was a significant predictor of students' openness to ethnic and cultural diversity, as measured at the conclusion of the freshman year. Thus, campus residence may play a role not only in current levels of psychological adjustment but also in future ability to maintain interpersonal adjustment in an increasingly multicultural environment.

The research reviewed thus far provides empirical documentation of the differences between students living with family and those residing in college dormitories. The problematic position of these commuters is assumed to have some relationship with variables intrinsic to the family of origin, primarily socioeconomic context or some functional pathology in the family system (especially with regard to the student's ability to develop a well-defined extra-familial identity). What of the growing number of commuters choosing to live off-campus in private housing, away from family? These students may experience difficulties solely as a function of their relative isolation from the campus







18

community. Are the psychological correlates of commuter status observable independently of students' relationships with their families?

Scant study of this group of students is reported in the literature. However, the stressful consequences of commuting have been observed in other settings and with other populations. For example, Novaco and colleagues (1990, 199 1) have conducted an ongoing research program demonstrating the deleterious effects of objective and subjective impedances encountered by commuters who drive daily to and from work. The negative impact of these impedances is evident in terms of commuters' negative mood at home, measured using a short semantic differential scale, and dysphoria, measured using a sub-set of items from the Global Stress Scale (Cohen, Kamarck, & Mermelstein, 1983). In the present study, off-cainpus residents should experience impeded access to campus relative to their peers residing in dormitories; thus, such students should report greater adjustment difficulties, especially as the distance of their residence from campus increases. Methodological Critiques

The existing research on commuter students has stimulated greater awareness, policy changes and impetus for farther inquiry. However, the literature is subject to critique for a number of reasons. First, most research has failed to make explicit distinctions between commuters residing with their family of origin and those simply electing to live off campus alone or with non-family members. This latter group is likely to continue to increase at institutions whose enrollment expansion is outpacing construction of new dormitories. Second, a shared definition of adjustment has been evident neither in multiple research conceptualizations nor in the wide variety of criterion measures used to operationalize student functioning. This phenomenon is due, in part, to the multifaceted







19

nature of adjustment, a concept which connotes multiple domains of student well-being. However, extant shortcomings in the measurement and conceptualization of adjustment limit our understanding of environmental impact.

Psychological adjustment is an important component of comprehensive adjustment, but psychological measurement probably has not been adequately operationalized in the studies reviewed. First, many of the measures are not well-validated clinically, because their primary application has been as research scales (e.g., the Global Stress Scale). Second, many measures address differences in personality style or preference. These differences provide interesting information, but they do not address psychological problems directly; that is, differences in personality styles do not necessarily offer information regarding the presence of, or even the potential for, psychological difficulties. Thus, personality measures have limited utility for clinicians seeking to understand any hypothesized negative consequence of living environments, as well as for policy makers seeking more conclusive demonstration of environmental impact. The clinical scales that have been employed, such as the family fusion measure used by Wilson, Anderson and Fleming (1987), tend to focus on narrowly-defined criterion variables rather than on the typical range of mental health problems seen in a college population.

A broad-based, well-validated clinical measure of psychological adjustment would provide a more useful measure of residential impact. Only one of the reviewed studies (Wilson, Anderson, & Fleming, 1987) has employed such a general clinical measure, the College Maladjustment Scale (Kleinmuntz, 1960) of the NUVIPI. The College







20

Maladjustment Scale (Mt) is a 41-item1 supplementary scale embedded in the original MMvPI (Hathaway & McKinley, 1943) and retained in the revised Minnesota Multiphasic Personality Inventory-2 (Butcher, Dahlstrom, Graham, Tellegen, & Kraemmer, 1989). The scale was developed by Kleinmuntz (1960) via item analysis of the original MMPI to differentiate college students seeking psychotherapy from the general student population. The items tap diverse issues, including perceived ineffectualness, diminished interest, procrastination, life strain and anxiety. Efforts to develop criterion cutoff scores have been problematic (Kleinmuntz, 1961; Kuczka & Handal, 1990). The scale is not a particularly good predictor of potential psychological difficulties (Parker, 1961; Dahlstrom, Welsh, & Dahlstrom, 1975) but has utility in terms of identifying levels of current maladjustment among students in a college setting (Graham, 1993). Importantly, the Mt, because it is an omnibus scale, does not allow distinctions among different types of psychological difficulties. The scale criterion is simply the prediction of seeking counseling center services; the clinical interpretation of high Mt scores was based only on informal content analysis of the component items. Thus, the Mt is a poor research instrument if one wishes to make distinctions among the qualitatively distinct adjustment issues (e.g., depression, anxiety, self-esteem, substance abuse) that students experience in college.

Until recently, a comprehensive instrument to measure psychological problems of college students has been unavailable. The MM\PI-2 is certainly a potential candidate, but it was designed for persons experiencing a greater degree of pathology than is typical for college counseling centers. When used with a less disturbed population the psychiatric




'The original MMPI (Hathaway & McKinley, 1943) Mt scale contained 43 items.







21

norms of the MMPI tend to exaggerate individuals' level of psychopathology. Moreover, the length of administration required for a fall MMPI can be nearly two hours, making the instrument impractical for a time-limited data collection. The California Psychological Inventory (CPI; Gough, 1987) is another potential candidate and has been widely-used with the demographic group targeted in the current study. In fact, CPI normative data are more appropriate for college students; however, the constructs measured by the instrument are more descriptive than diagnostic.

A more recent instrument, the College Adjustment Scales (CAS; Anton & Reed, 1991) seems a better candidate for research with college populations. The CAS is a 108item screening instrument designed to identify and categorize types of psychological maladjustment presented by students at university counseling centers. The scales were developed and formed specifically for college populations. The CAS content areas were selected on the basis of a principal components analysis of an intake problem checklist at a college counseling center (Hicks, Reed, & Anton, 1989, cited in manual) and on a survey of assessment needs endorsed by campus counseling center care providers. The final version of the CAS included nine classes of psychological difficulty: anxiety, depression, suicidal ideation, substance abuse, self-esteem problems, interpersonal problems, family problems, academic problems, and career problems. Each scale consists of an equal number of 4-point Likert scale items; the entire CAS can be administered to participants in 15-20 minutes.

The CAS was formed on a sample of 1,146 students from a geographically diverse group of U.S. colleges. The sample was representative of the gender and ethnic composition of the American college student population. The CAS Manual (Anton & Reed, 1991) contains a fall description of the initial validity studies. Internal consistency







22

reliability ranged from .80 to .92 for the component scales; Anton and Reed also provide preliminary convergent and discriminant validity data. Although a relatively new instrument, the CAS has been used in several recent studies of college age populations (Chandler & Gallagher, 1996; Heppner et al., 1994; Street, Kromrey, Reed, & Anton, 1993; Turner, Valtierra, Talken, Miller, & DeAnda, 1996).



The I=act of Physical Environmental Features on Well-Being

The preceding section examined the effects of residential location and commuting on psychological adjustment. Another important question regards the contribution of housing environment. The second area of focus in the present study regards the influence of specific environmental characteristics of student housing on personal and psychological adjustment. This area of inquiry is better grounded theoretically than that, previously discussed, of residential location. As a group, the studies discussed in the following sections are vulnerable, to some degree, to the same criticism regarding the operational definitions of adjustment that were noted in the review of commuter research. That is, although a number of different measures, often simply preference scores for particular environmental features, have been employed, specific measures of psychological problems have seldom been used. However, the relationship of environment to well-being has often been more compellingly demonstrated, especially through use of psychophysiological correlates of stress (i.e., autonomic responses). What follows is a review of empirical research on the environmental characteristics of housing which are potentially relevant to the psychological well-being of college students.






23

Windows

Early literature in this area suggests that windows, particularly those that afford a view of natural landscape elements, have a dramatic positive impact on well-being. Ulrich (1981) demonstrated that the beneficial impact of natural scenes can be measured in terms of psychophysiological. correlates of relaxation, such as respiration rate, heart rate and galvanic skin response. Subsequently, Ulrich (1984) demonstrated that window views of nature positively influence the recovery of surgical patients. Patients whose hospital rooms afforded views of nature scenes (e.g., water and deciduous trees) had more positive postsurgical prognosis as measured by a number of measures, including recovery time, need for medication, and report of pain.

More recent research (see Sundstrom, Bell, Busby, & Adams,1996, for a review) suggests that the impact of windows is more complex and is mediated by social, contextual and environmental variables. For example, Butler and Biner (1989) found that students did not prefer window views in spaces where they might provide a functional impediment, such as computer workrooms. Previous work in this area raises the possibility that the presence of windows will influence both students' ratings of residential satisfaction and associated psychological adjustment.

Natural Landscape Elements

Stephen and Rachel Kaplan have published decades of research on the psychological benefits of nature. Their theory posits that natural environments are preferred because they facilitate restoration of attention capacity, fatigued by the sustained focus often required by the myriad competing stimuli of the modem world (Kaplan & Kaplan, 1989). The negative impact of sensory overload in modem urban environments-socially







24

and psychologically-has been identified as a major quality of life issue (Milgram, 1970; Krupat, 1985). Natural environments, in contrast, elicit effortless attention fascination, processes central to the Kaplans' theory. That is, natural landscape elements promote the recovery of attention through the effortless engagement of sensory systems, resulting in an experience both pleasurable and restorative. This restorative experience has tangible impact on psychological and physiological wellness.

On the physiological level, natural environments promote stress reduction through stimulation of the parasympathetic nervous system (Ulrich et al., 1993). The calming effects of exposure to natural scenes have been documented repeatedly (e.g., Ulrich, 1981). Natural landscapes, especially those including water and biomatter, appear to reduce blood pressure, galvanic skin response, respiration rate and self-report of stress. Additional evidence (Ulrich, 1984), mentioned in the previous section, suggests that natural views positively influence the recovery of post-surgical patients.

Which elements of the natural landscape are most important? A useful distinction between configural elements and primary content of landscape clarifies the question. The former refers to the way in which objects are arranged in the stimulus array. Research has shown that landscapes that provide a sense of coherence (hanging together) and mystery (the promise of new information to be gained by exploration) are especially preferred (e.g., Campbell, 1994; Herzog, 1989, 1992; Kaplan & Kaplan, 1989). Primary content includes the specific objects present in a given landscape. Research has consistently indicated that humans prefer both greenery, particularly tended nature (i.e., manicured gardens), and water scenes.







25

Crow~ding

Two decades of study have documented the deleterious effects of residential overcrowding on the psychological well-being of dwellers. A number of studies have demonstrated the association of crowding with residential dissatisfaction (see Krupat, 1985; Sundstrom, Bell, Busby, & Asmus, 1996). This dissatisfaction is associated with increased levels of psychological stress experienced by persons living in such conditions. Moreover, there is considerable theoretical and empirical evidence that crowding negatively impacts willingness to offer and accept social support. Milgram (1970), in an analysis of the experience of urbanites, suggests that this effect is a function of overload on individuals! social and cognitive capacities; the result is a social withdrawal to manage inputs to an overtaxed sensory system. In a study of college students, Lepore, Evans, and Schneider (1991) demonstrated that persons living in crowded environments experience greater psychological distress, even when controlling for levels of distress prior to their current living arrangements. Evans and Lepore (1993) found that college students from crowded residences were less likely to offer, accept, or perceive social support in a laboratory experiment. The robustness of crowding effects underscores their relevance for the proposed study; a measure of residential population density should be included as a predictor variable.

Noise

The detrimental impact of noise has been demonstrated in a variety of contexts, including neighborhoods (Levy-Leboyer & Naturel, 1991) and shopping malls (Hopkins, 1994). The modal investigation of ambient noise has operationalized impact in terms of task performance or self-report of annoyance. Thus, examination of effects in terms of







26

psychological adjustment is a somewhat novel approach. An objective measure of decibel level in housing environments is beyond the logistical scope of the proposed study. However, incorporating students' Likert-scale ratings of noise level in their homes as a predictor variable should yield important information about the subjective importance of ambient noise to participants.



Rationale for the Present Stu

This study is distinguished from previous work on residential satisfaction of college students by an explicit focus on psychological adjustment as a dependent measure. While the importance of satisfaction ratings is salient to planners, architects and housing directors, the psychological impact of residential environment is important not only to these groups but also to mental health professionals. Thus, I propose to incorporate, in addition to a measure of simple satisfaction, two psychometrically validated measures of adjustment: the College Maladjustment Scale of the Minnesota Multiphasic Personality Inventory (Mt; Kleinmuntz, 1960) and the College Adjustment Scales (CAS; Anton & Reed, 1992). Each measure will be described more fully in the materials section of this paper. This emphasis on psychological fimetioning fills a theoretical vacuum in the existing literature on college residential environments. More specifically, the current study allows an evaluation of environmental factors not limited to simple preference, but concerned as well with the psychosocial correlates of environmental design. A psychological evaluation of housing environments forms a more direct link between the structure of a home and the adaptive functioning of its residents.







27

The current study examines two primary aspects of the relationship of residential environment with psychological adjustment of college students. First, this study will provide the opportunity to assess the relative importance of residential crowding, residential location, noise level, distance from campus, and access to windows in predicting current levels of psychological adjustment. My decision to incorporate these predictor variables (and, consequently, to exclude others of potential importance) is a function both of pragmatism and of attention to the existing literature on residential envirom-nents. A limited number of variables is necessary to ensure the feasibility of this study. Moreover, these particular variables were chosen in part because they are amenable to quantitative analysis. More abstract phenomena (e.g., sense of place, architectural coherence, and the like) are certainly of great interest but would require a fundamentally different, more qualitative, analytic strategy. An additional consideration was the particular relevance of these variables for prescriptive policy recommendations. Change of each variable in the proposed study is readily accomplished via either architectural design or modification of residence life policy. Finally, this set of variables is clearly consistent with the "mainstream" literature on residential environments and, therefore, is an appropriate point of departure for an investigation into this special type of home, the campus community.

Second, this study provides a geography of student adjustment that allows formulation of spatially targeted interventions by counseling center or other university staff. That is, this analysis should provide a rough map of the need for psychological services and, perhaps, the differential spatial distribution of certain types of psychological distress.

An understanding of the impact of residential environment on the psychological functioning of college students should be useful for a diverse group of professionals,







28

including campus psychologists or counselors, student affairs professionals, campus planners and dormitory architects. One goal of this study is to elaborate a geography of college student adjustment that will allow spatially targeted interventions. In addition, such information may be of use to prospective and current college students making decisions to enhance their academic and personal functioning. Research Hypotheses

1. Resident students should report greater overall levels of psychological adjustment than commuters. If this effect is independent of psychological status at time of admission, then this hypothesis will remain viable even when pre-college mental health care is entered as a covariate. This procedure will control for the possibility that maladjusted students show a greater tendency to isolate themselves geographically from campus life. Since this is not a longitudinal study, the control procedure is necessary for this and all subsequent comparisons of adjustment levels.

2. If proximity to campus facilitates social integration, then, among off-campus residents, those living closer to campus should report fewer adjustment difficulties.

3. Students living with their family should report more adjustment difficulties than those living on-campus or off-campus not in the family home.

4. Residential population density should be negatively associated with psychological adjustment and residential satisfaction. Previous research suggests a ceiling effect such that levels of satisfaction cease to decline beyond a certain density; however, extremely high residential densities are probably not common in a population with these demographic characteristics.







29

5. Reported level of noise should be inversely related both to overall levels of psychological adjustment and satisfaction with living environment.

6. Elements of natural landscape visible from residences should correlate positively with adjustment; that is, the presence of adequate light, water, trees and grass in residential window vistas should be associated with better overall levels of psychological adjustment.














CHAPTER 3
METHOD



Participants

Participants were undergraduate volunteers from psychology classes at the University of Florida (a large state university with approximately 40,000 students), the University of Wyoming (a small state university with approximately 10,000 students), and New College of the University of South Florida (a primarily residential liberal arts honors college with approximately 600 students). Research instruments were distributed to 206 students from these institutions; 191 forms were returned; seven forms were incomplete and unusable, leaving 184 cases included in the data analysis.

Participation was subject to Institutional Research Board approval and the ethical guidelines of the American Psychological Association. Participants were provided with both written and verbal informed consent statements. Students did not receive monetary compensation for their participation; on two occasions, however, extra credit points were awarded to students who completed the survey. A copy of the informed consent statement is included in Appendix A.

Institution. Of the 184 participants in the final sample, 125 (68%) were students at the University of Florida. Thirty-five (19%) were from New College of the University of South Florida; the remaining 24 students (13%) were from the University of Wyoming.


30







31

Ethnii. One hundred forty-six participants (79%) reported white/non-Hispanic ethnicity. The second largest group (15 students or 8%) endorsed Asian/Pacific Islander. Nine Hispanic/Latino(a) students constituted 5% of the sample. Four percent (n7-7) students were African-American. Four students (2%) reported ethnicity as "other." Three students declined to indicate ethnic background.

Gender. Sixty-seven percent (n=124) of respondents were women. Men comprised 32% (n--60) of the sample.

Age. Reported age ranged from 17 to 49 years for the 183 participants who provided information. Mean age was 19.75; standard deviation was 3.68.

Year in college. Students' number of semesters in college ranged from one to 14. The mean number of terms in college was 3.04; the standard deviation was 2.57.

Marital status. Only 2.7% (n--5) of the sample endorsed the "married" category.

Sexual orientation. One hundred eighty-three participants indicated their sexual orientation. The vast majority of students (95%) endorsed the "heterosexual (straight)" category. Six students (3%) reported they were bisexual. Three students (2%) endorsed the "gay/lesbian" category.

Fraternity or sorority membership. Only two students (1.1%) reported membership in a campus Greek organization.



Materials

Participants first completed a 25-item written questionnaire including demographic items as well as questions regarding predictor variables and potential covariates. The latter sections included information about residential location, type of accommodation, physical







32

aspects of housing environment, residential satisfaction, year in college, and psychological treatment history. The questionnaire is included in Appendix B.

Criterion measures of adjustment included the 41-item College Maladjustment Scale (Mt; Kleinmuntz, 1960) of the Minnesota Multiphasic Personality Indicator-2 (MMPI-2; Butcher et al., 1989). A 43-item Mt was developed for the original MMPI (Hathaway and McKinley, 1943); a 41-item scale was retained in the 1989 revision. Although the scale is typically administered in embedded form (i.e., as part of the full 567item MMPI-2, Kleinmuntz (1961) provides norms and validation for short-form administration of the scale including only the 43 original Mt items and 42 items from standard MMPI validity scales.' The stand-alone Mt was selected for the present study to ensure single-session administration of the research protocol; the entire MMPI-2 typically requires the majority of two hours to complete. To further expedite

administration, the MMPI validity items were omitted. Although the stand-alone Mt without validity items has never been validated with reference to the full MMPI, this type of validation has been performed using other MMPI supplementary scales (cf., Herman, Weathers, Litz, & Keane, in press); moreover, Kuczka and Handal (1990) provide validational data for the stand-alone Mt with reference to Langer Symptom Survey (Langer, 1962). Thus, the use of the stand-alone Mt scale can be defended on both empirical and pragmatic grounds.




'The additional items comprise the 15-item L scale and the 27-item K-scale. Briefly, the former is designed to identify persons attempting to fake good by presenting themselves in an overly-virtuous light; the latter is associated with defensiveness regarding the presence of psychological problems. These are extensively covered in the MMPI literature (e.g., Graham, 1993).







33

The second criterion measure was the 108-item College Adjustment Scales (CAS; Anton and Reed, 1991). The CAS, described in Chapter 2, is a relatively new instrument designed to assist college counseling center professionals in screening the mental health needs of students. As such, the instrument was normed on a sample composed primarily of college student, and, therefore, is a logical choice for use in this investigation.

Although the GAS is not a diagnostic instrument, it offers normed data regarding the type and magnitude of a student's self-reported adjustment difficulties. The GAS offers raw scale scores and linearly-transformed McCall's T-scores (mean-=50; SD=1 0) for nine aspects of college student adjustment rationally selected on the basis of screening needs reported by campus mental health providers. The GAS scales include Anxiety (AN), Depression (DP), Suicidal Ideation (SI), Substance Abuse (SA), Self-esteem (SE), Interpersonal Problems (IP), Family Problems (FP), Academic Problems (AP), and Career Problems (CP). Students respond to twelve four-point likert scale items for each scale; responses are summed to yield a raw scale score.



Design and Procedure


Participants completed written survey items in class. Students were informed that this is a study of campus living arrangements and their impact on student life. First, each participant was provided with written and oral informed consent statements. After item packets were distributed, students were instructed to first complete the sections requesting demographic and predictor variable information. Since the psychological items were potentially evocative of emotional reactions affecting student's ratings of housing







34

environments, the Mt and CAS were presented last in the packet. Students recorded responses on an anonymous answer sheet. The time required for administration, including instructions, ranged from 30 to 40 minutes.



Analytic Strategy

The Mt items proved unexpectedly problematic for students to complete, apparently because answers were to be recorded on a separate scan-tron answer sheet. As a result, a number of students either skipped the Mt all-together or failed to complete the entire scale. These procedural difficulties cast serious doubt on the validity of the Mt data; for this reason, and because the Mt's predictive validity has been questioned in the literature (Dahlstrom, Welsh, & Dahlstrom, L.E., 1975), Mt scores were removed from the data set.

A visual examination of the distribution of CAS scale scores revealed that the distribution of McCall's T-scores approximated normality more closely than that of raw scores; therefore, T-scores were chosen as the unit of analysis in the criterion data set. Since the remaining data set contained multiple conceptually-related dependent variables (i.e., the nine CAS scales, which are intercorrelated; Anton & Reed, 1991), the first-line analytic procedure was a multivariate analysis of variance (MANO VA) including all predictor variables and each scale of the CAS in the criterion variable set.. The MANOVA was followed by a series of step-wise multiple regression analyses for each predictor variable that achieved significance in the initial multivariate analysis.

The pairing of an omnibus MANOVA with follow-up univariate analyses is quite common in the psychology literature and has typically been thought to control for Type-I statistical error resulting from multiple univariate tests. This assumption has been







35

challenged by Huberty and Morris (1989), who argue that multivariate and univariate techniques address distinct research questions. The former analyses are appropriate to address overall effects and, less directly, to explore patterns among and contributions of outcome variables; the multiple univariate strategy is appropriate when outcome variables are conceptually distinct, when research is exploratory, or when the dependent variables of interest have been previously studied in univariate contexts. In this last case, Huberty and Morris (1989) contend that MANOVAs may be used in conjunction with ANOVAs, if the appropriate assumptions for each are met. In the present study, the dependent measures are designed to tap constructs (e.g., depression, anxiety, substance abuse) that have repeatedly been investigated singularly via univariate analysis. Thus, the two-prong multivariateunivariate strategy seems justifiable.

A second set of analyses examined the structure of the outcome variable set. This was accomplished with presentation of a Pearson product-moment correlation matrix of tscores for all CAS scales and with presentation of a principal components factor solution describing the internal structure of the CAS. Principal components analysis is a factoranalytic technique that reduces a data set to a smaller number of factors that account for a significant proportion of the overall variance. The procedure yields eigenvalues, which indicate the relative importance of each factor and factor loadings, which are essentially correlations indicating the strength and direction of the association of individual variables with a given factor (Dunteman, 1989).

As is described more fully in the next chapter, the preceding analysis revealed significant overlap among the CAS scales, casting doubt upon the status of each scale as a conceptually distinct measure. Since this result implies that the variation in each scale may






36

be attributed to a single factor underlying overall adjustment, a third analysis used a composite criterion variable intended to measure overall level of college adjustment. This variable was rationally constructed by computing the average t-score elevation on the CAS. The single composite measure was amenable to multiple regression; therefore, the final analysis was a stepwise multiple regression. A stepwise procedure was chosen because the model allows independent variables to enter the equation in stages according to their predictive strength. The technique identifies those variables making the most important contributions to adjustment while simultaneously accounting for both multicolinearity in the predictor set and the contributions of other variables.













CHAPTER 4
RESULTS


Deghptive Characteristics of the Variable Se

Descriptive statistics for predictor and criterion variables are reported in this section. Table 4-1 is a summary of the housing types reported by students. The figures reflect a roughly even split between on-campus and off-campus residents in the final sample. The majority of on-campus residents resided in a single-room dormitory, although a significant number reported living in a dormitory suite (i.e., a multiple-room residence, often with a shared common area). Suite-style accommodations are increasingly popular dormitory designs; in fact, dormitories currently under construction at New College will offer suitestyle dormitories by fall, 1998. Among the 48.4 % of students residing in off-campus housing, only a minority (n--10) were living with their family of origin. The remaining offcampus residents lived alone or with roommates; a very small number of married students lived with their spouses.


Table 4-1: Types of Housing Units

Type Frequency %
On-campus 95 51.6
Single-room dormitory 59 32.1
University apartment 2 1.1
Suite (multiple rooms) 23 12.5
Other 11 6.0
Off-campus 89 48.4
Without parent(s) 79 42.9
With parent(s) 10 5.4

37







38

Table 4-2 summarizes selected environmental features reported by students. The modal student reported one or two roommates, although other living arrangements are represented in the sample. Mean distance from campus was 2.77 miles; in all cases in which students resided in on-campus housing, a distance of zero miles was assigned. Distance from campus varied widely, primarily because a small number of participants in the University of Florida sample were first-terrn summer students living at home. Students reported an average of 2.13 windows in the room in which they spent the most time. The remaining variables summarized in this section (light, noise, and satisfaction) were each rated on a seven-point likert scale.



Table 4-2: Environmental Characteristics of Housing Units

Characteristic N Min Max Mean SD Roommates 184 0 16 1.71 1.59
Distance 184 0 55 2.77 8.33
Windows 181 0 15 2.13 1.82
Light 183 2 7 5.00 1.21
Noise 184 1 7 3.72 1.53
Satisfaction 184 1 7 4.73 1.40
Note: Cases of N<184 are due to missing values. Light, noise, and satisfaction were rated on a 7-point likert scale.



The rooms in which students reported spending the most time are shown in Table 4-3. The classification of rooms was derived from participants' unstructured self-report, and categories are therefore tentative. Nonetheless, results indicate that three living spaces were most utilized by students; these rooms, in order of importance, are bedrooms, family (living) rooms, and as anticipated for on-campus residents, dormitory rooms. Other types







39

of rooms were cited much less frequently; a small number of blank or ambiguous responses were placed in the other/not reported category.



Table 4-3: Most Commonly Used Rooms Room Type Frequency %
Bedroom 80 43.5
Study 2 1.1
Family or Living Room 58 31.5
Kitchen 5 2.7
Dormitory Room 34 18.5
Bathroom 1 .5
Other/Not Reported 4 2.2




Table 4-4 summarizes the landscape elements that students reported were visible from the room in which they spent the majority of time. Trees and grass were the most common landscape features, reported by 91.3% and 84.8% of students, respectively. A smaller -number of students (14.1 %) indicated that water was visible. In addition, the majority of students noted the presence of built structures (buildings and concrete) in their window vistas.



Table 4-4: Visible Landscape Elements in Most Commonly Used Room Feature % Reporting
Water 14.1
Trees 91.3
Grass 84.8
Other Buildings 67.4
Concrete 63.6







40

The psychological treatment history of study participants is reported in Table 4-5. A surprisingly large number of students (28.3%) indicated that they had received some form of mental health services prior to enrolling at their present educational institution; mental health services were defined work with a "psychologist, psychiatrist, or other type of mental health professional for a psychological or personal problem." Additionally, 12.5 % reported treatment since beginning study at their current college or university; 8.2 % were currently in treatment or were planning to seek services within thirty days of the study.



Table 4-5: Psychological Treatment History of Participants

Time of Treatment %

Prior to entering college 28.3
Since entering college 12.5
Currently in treatment a 8.2
'Includes those planning to seek treatment within 30 days



Table 4-6 lists mean t-scores and standard deviations for each of the nine College Adjustment Scales (CAS) subscales. A visual examination of this data suggests that the perfon-nance of students in the current study was similar to that of students in the CAS non-native sample, in which the mean t-score and standard deviation for each scale were 50 and 10, respectively. Scale t-score means in the current study ranged from 48.73 (SE) to 51.59 (SI); standard deviations ranged from 9.32 (CP) to 11.43 (SE). Thus, the central tendency and distribution of scores in the present sample appear comparable to those previously reported for the general college population.







41

Table 4-6: Summary of McCall's T-scores on CAS Scales

Scale Mean SD
Anxiety (AN) 50.57 10.33
Depression (DP) 50.30 11.00
Suicidal Ideation (SI) 51.59 9.59
Substance Abuse (SA) 51.03 9.60
Self Esteem (SE) 48.73 11.43
Interpersonal Problems (IP) 50.72 9.63
Family Problems (FP) 50.12 9.54
Career Problems (CP) 50.93 9.32
Academic Problems (AP) 48.73 11.20





Omnibus Analyses

The first stage of analysis employed an omnibus multivariate analysis of variance (MANOVA) including predictor variables as well as the criterion set, which included all nine sub scales of the CAS. The MANOVA procedures determine the statistical significance of individual predictors when covariation in the criterion variable set is controlled. Since a visual examination of scores on the CAS sub scales revealed that the McCall's t-score distributions more closely approximated normality than those of raw scale scores, t-scores are used in the criterion variable set for this and all subsequent analyses.

Names of predictor variables are abbreviated as follows. SCHOOL represents the institution presently attended (University of Florida, New College, or University of Wyoming). SEX denotes reported gender; AGE is reported age in years. TERMS represents the number of semesters attended at the student's current institution. TXPRIOR is a dummy variable representing psychotherapy or counseling prior to enrolling in the student's present school. TXSJNCE and TXINOW are dummy variables denoting psychological treatment since enrollment or at the present time, respectively. MATES







42

represents the number of roommates reported. DISTANCE is a measure of distance from campus (rounded to the nearest half mile); on-campus residents received a score of zero on this variable. PARENTS is a dichotomous measure indicating whether the student resided with his or her family of origin. ON-OFF refers to location of the student's current residence (on or off-campus). WATER, GRASS, BUILDING, and CONCRETE are dummy codes representing the presence or absence of each landscape feature in the student's residential window vista. NOISE and LIGHT are 7-point Likert scale ratings of noise and light levels in the student's current residence. SATIS is a Likert scale rating of reported residential satisfaction.

MANOVA results for all predictor variables are summarized in Table 4-7, which includes values for Wilks' Lambda, an F statistic, degrees of freedom and significance level. Since the present study is largely exploratory, variables significant at the 10 level were included for follow-up analyses. However, these variables are distinguished from those achieving significance at the .05 convention in the following table. Significant predictors can be placed in three categories. First, the demographic variables of institution attended, gender and age had statistically significant impact on adjustment as measured by the CAS scales. Second, psychological treatment history was related to current adjustment. Current treatment was the most significant predictor; however, treatment since enrollment and treatment prior to college also made significant contributions. Finally, a number of environmental variables achieved significance. These included number of room-mates; subjective ratings of noise, light, and satisfaction; and the presence of grass in residential window vistas.







43

Follow-= Analyses

The next stage of analysis employed a series of step-wise regression equations to more fully elucidate the impact of predictor variables on each scale of the CAS. Only variables that achieved significance at the 10 or higher level in the omnibus MANOVA were retained in these subsequent analyses. As a group, this series of analyses provides greater elaboration of environmental impact on specific facets of college adjustment. However, a preliminary note of caution is warranted; as demonstrated later in this paper, the psychometric properties of the CAS render conclusions regarding specific adjustment difficulties problematic, since a single factor of distress appears to underlie the vast majority of variation on purportedly specific subscales. Nonetheless, the following regression analyses contribute to a fuller understanding of the present data by offering tentative models of scores on individual subscales.

Anxie

The CAS Anxiety (AN) scale reflects "physical and psychological correlates of anxiety" (Ariton & Reed, 1991, p. 5). High scorers may exhibit bodily tension, autonomic hyperarousal, hypervigilance, worries or intrusive thoughts. Results of stepwise regression of predictors on the AN scale are presented in Table 4-8. Current treatment was the most powerful predictor, followed by the presence of grass in window views. Although the impact of grass was of lesser magnitude than that of current treatment, the effect remained statistically significant even when the variation in AN predicted by treatment status is taken into account. Those students currently in psychological treatment tended to report higher levels of anxiety, while the presence of grass, as predicted, was associated with reduced levels of reported anxiety. The R-square value for this model is .112; thus current







44

treatment status and the presence of grass together account for 11.2% of the total variation

in AN scores.



Table 4-7: MANOVA Test Statistics by Predictor

Variable Lambda F Num DF Den DF p
SCHOOL .744 2.62 18 296 .0004*
SEX .809 3.89 9 148 .0002*
AGE .896 1.91 9 148 .0540*
TERMS .975 .42 9 148 .9214
TXPRIOR .909 1.64 9 148 .1089*
TXSINCE .870 2.46 9 148 .0122*
TXNOW .866 2.55 9 148 .0093*
ONOFF .947 .92 9 148 .5061
MATES .909 1.65 9 148 .1048"*
NOISE .903 1.76 9 148 .0811 **
LIGHT .900 1.82 9 148 .0684**
SATIS .848 2.94 9 148 .0031*
WINDOWS .966 .56 9 148 .8078
WATER .965 .96 9 148 .7949
GRASS .878 2.28 9 148 .0202*
TREES .935 1.14 9 148 .3386
BUILDING .936 1.13 9 148 .3445
CONCRETE .945 .96 9 148 .4720
DISTANCE .945 .95 9 148 .4848
PARENTS .949 .89 9 148 .5385
*Significant at .05 level "Significant at. 10 level



Table 4-8: Prediction of AN Scores

Variable Parameter Estimate Std. Error Partial R2 F P
Intercept 54.36 1.89 824.5 .0001
TXNOW 11.19 2.74 .0769 16.7 .0001
GRASS -5.44 2.05 .0350 7.0 .0088







45

Del2ressio

The Depression (DP) scale of the CAS purports to measure the "physical and psychological correlates of depression" (Anton & Reed, 1991, p. 5), including fatigue, sadness, hopelessness, isolation and anhedonia.' A summary of the regression equation predicting DP scores is presented in Table 4-9. Older participants tended to achieve lower DP scores than those of younger students, indicating a negative relationship of age and report of depressive symptoms or experiences. In addition, students who had sought psychological treatment since enrolling in their current institution achieved significantly higher DP scores, even when the effects of age were simultaneously controlled. However, none of the environmental variables (including reported light level) made a contribution beyond that of age and treatment effects. This model accounts for 12.4% of the variation of depression scores.



Table 4-9: Prediction of DP Scores

Variable Parameter Estimate Std. Error Partial R2 F P
Intercept 64.44 4.48 206.8 .0001
AGE -0.79 .23 .0650 11.9 .0007
TXSINCE 12.14 2.05 .0585 22.1 .0001











'Anhedonia, the marked loss of interest or pleasure in activities previously enjoyed, is a key diagnostic criterion for Major Depressive Disorder (American Psychiatric Association, 1994).







46

Suicidal Ideatio

Suicidal Ideation (SI) scores are indicative of suicidal thoughts or suicidal

behaviors. Anton& Reed (1991) recommend that even moderate elevations should signal the need for further psychological evaluation. As shown in Table 4-10, younger students reported higher levels of suicidal ideation. As with DP, students who reported psychological treatment subsequent to entering college were more likely to produce elevated scores. Together, age and treatment effect account for 5.2% of the variation in suicidal ideation scores. One environmental feature, grass, approached significance (p=.09) and would have explained an additional 2.4% of variation in SI scores.



Table 4-10: Prediction of SI Scores

Variable Parameter Estimate Std. Error Partial R2 F P
Intercept 65.24 4.23 237.6 .0001
AGE -0.58 .21 .0218 8.1 .0050
TXSINCE 5.60 2.33 .0301 5.8 .0173
GRASS -3.34 1.96 .0238 2.9 .0903*
*Approached significance



Substance Abuse

The SA scale is designed to reflect difficulties in a number of areas negatively impacted by substance abuse, including academics, social behavior and relationships. Regression modeling of SA scores is summarized in Table 4-11. When the effects of TXPRIOR are accounted for, no other variables have additional predictive power. Although this model is significant, TXPFJOR explains only 3.8% of the variation in SA







47

scores, clearly indicating that factors external to the present study are more relevant to substance abuse scores.


Table 4-11: Prediction of SA Scores

Variable Parameter Estimate Std. Error Partial R2 F P
Intercept 49.85 .83 3602.5 .0001
TXPRIOR 4.19 1.56 .0384 7.2 .0082


Self Esteem

Table 4-12 summarizes the prediction of SE scores. The SE scale is designed to measure global self-esteem. High scorers tend to have poor self-esteem and selfconfidence, which are reflected in their own opinions of their abilities, achievements, and attractiveness.

Younger students tended to report more problems with self-esteem, as did students who had received psychological treatment since coming to college. Additionally, even with the effects of age and treatment history simultaneously controlled, ratings of home light level were correlated with SE scores. The direction of this relationship was in the expected direction; namely, poor lighting was associated with increased problems with self-esteem. The model of self-esteem is the strongest in this series; treatment, light, and age effects together account for 14.7% of the variation in SE scores.


Table 4-12: Prediction of SE Scores

Variable Parameter Estimate Std. Error Partial R2 F P
Intercept 68.09 5.28 166.4 .0001
AGE -0.59 0.24 .0295 6.1 .0144
TXSINCE 11.30 2.68 .0688 17.8 .0001
LIGHT -1.82 0.67 .0485 7.3 .0074







48

Int=ersonal -Problems

The IP scale measures "the degree to which the student has difficulty relating to others" (Anton & Reed, 1991, p. 6), which may be reflected in dependency, distrust, vulnerability or argumentativeness. A regression summary for IP scores is presented in Table 4-13. As evident in the summary, age was again a significant factor, and the trend for younger participants to report greater difficulties was continued. Furthermore, treatment since entering college continued to play an important role; students who had sought counseling or psychotherapy evidenced higher IP scores. Overall, this model is of moderate predictive strength, accounting for approximately 8.2 % of the total variation in IP scores.



Table 4-13: Prediction of IP Scores

Variable Parameter Estimate Std. Error Partial R2 F P
Intercept 64.66 4.02 259.0 .0001
AGE -0.74 0.21 .0371 13.2 .0004
TXSINCE 6.78 2.31 .0444 8.6 .0038




Family Problems

The CAS FP scale purports to measure a variety of family concerns, including

difficulty with individuation and worry regarding family conflict (Anton & Reed, 1991). A model of FP scores is presented in Table 4-14. Interestingly, the presence of grass in window vistas was associated with lower scores. This finding is consistent that the presence of natural environmental features should ameliorate psychological distress, although the specific relationship of grass and family conflict is difficult to place in a







49

theoretical context. Moreover, this model is among the weakest in the series, accounting for only 2.7% of the variation in FP scores.



Table 4-14: Prediction of FP Scores

Variable Parameter Estimate Std. Error Partial R2 IT P
Intercept 53.85 1.82 871.2 .0001
GRASS -4.36 1.98 .0265 4.9 .0286



Academic Problems

The Academic Problems (AP) scale of the CAS is associated with poor study skills, inefficient time management and concentration difficulties. A summary of regression on AP scores is presented in Table 4-15. The presence of grass was associated with lower levels of reported academic difficulties. However, contrary to expectation, residential satisfaction (SATIS) was associated with increased academic difficulty. This counterintuitive finding will be explored more fully in the following chapter. Grass and satisfaction together account for 5.4% of the variation in AP scores.



Table 4-15: Prediction of AP Score

Variable Parameter Estimate Std. Error Partial R2 F P
Intercept 48.19 3.23 222.7 .0001
SATIS 1.28 0.60 .0540 4.5 .0349
GRASS -6.54 2.35 .0300 7.7 .0061







50

Career Problems

The Career Problems (CP) scale of the CAS is designed to measure difficulties in vocational goal setting and decision making (Anton & Reed, 1991). Although high scores on this scale may be associated with anxiety regarding career planning or decision making, the CP scale seems logically less strongly associated with psychological disturbance or, for that matter, the impact of home environment. Not surprisingly, perhaps, no predictor variable in the model achieved or approached significance at the .05 level for Career Problems.



Factor Structure of the College Adjustment Scales

The forgoing analyses raised important questions regarding the psychometric adequacy and factor structure of the CAS. As noted, the initial series of MANOVA analyses yielded only a small number of significant predictors. Since MANOVA procedures test for predictor effects while controlling for intercorrelation in the criterion variable set, the likelihood of significant results decreases as multicolinearity increases. Anton and Reed cite scale intercorrelation as an important limitation in the CAS Manual (199 1), and the present study replicates their finding. T-score intercorrelations for all nine CAS subscales are presented in Table 4-16. The strong interrelationships among CAS scales are evident on first examination of the correlation matrix. All individual correlations are in the moderate or higher range. In fact, the lowest correlation, between SA and CP tscores, was .28, indicating that 7.8% of the variation of each scale is shared between both. All other correlations were higher, including several in excess of .70. T-scores for







51

depression and anxiety evidenced the strongest relationship (r--.77), indicating nearly 60% of shared variation between the scales.



Table 4-16: Correlation Matrix of CAS Scale T-Scores

AN DP SI SA SE IP FP CP AP
AN 1.0000 0.7673 0.4699 0.3335 0.7132 0.6984 0.5686 0.4925 0.5786
DP 0.7673 1.0000 0.5444 0.3524 0.7440 0.6441 0.5516 0.5305 0.5889
SI 0.4699 0.5444 1.0000 0.4021 0.5029 0.4901 0.4804 0.4167 0.3295
SA 0.3335 0.3524 0.4021 1.0000 0.3399 0.4376 0.4343 0.2753 0.4037
SE 0.7132 0.7440 0.5029 0.3399 1.0000 0.5995 0.5171 0.5018 0.5285
IP 0.6984 0.6441 0.4901 0.4376 0.5995 1.0000 0.6348 0.4801 0.4936
FP 0.5686 0.5516 0.4804 0.4343 0.5171 0.6348 1.0000 0.4226 0.5369
CP 0.4925 0.5305 0.4167 0.2753 0.5018 0.4801 0.4226 1.0000 0.4625
AP 0.5786 0.5889 0.3295 0.4037 0.5285 0.4936 0.5369 0.4625 1.0000
Note: Values represent Pearson product-moment correlation coefficients.



The level of intercorrelation among CAS scales is a serious psychometric limitation of the instrument. First, strong relationships among scales suggest that a smaller number of constructs underlie responses and, therefore, that distinctions based on individual scale scores may be unwarranted in some cases. The possibility exists that all CAS scales are measuring the same thing or, at least, that the scales are tapping very similar phenomena. More succinctly: If one scale score is known, others can be predicted. Second, these interrelationships raise questions about the discriminant validity of the CAS. That is, if the subscales are, in fact, primarily measuring a single phenomenon (or small set of related phenomena), then the names of individual scales may be clinically misleading. This is the case when the underlying structure of the CAS is not sufficiently sensitive to distinguish among the nine subscales. More concretely, the difference between depression and anxiety scores becomes less meaningful when more than half of their variation is shared. Since this







52

possibility was evident in the correlation matrix, a factor-analytic procedure was employed to determine in fuller detail the underlying structure of the CAS.

A principal components analysis was performed on the correlation matrix of tscores for each scale of the CAS. Principal components analysis, like classical factor analysis, is essentially a data reduction technique (Dunteman, 1989) that extracts a smaller number of uncorrelated, or orthogonal, factors that are linear transformations of observed variables. In the present analysis, a varimax rotation procedure was chosen, in order to achieve maximum separation of any factors underlying the CAS data. This procedure is intended to minimize the number of variables associated with each factor and, therefore, to facilitate interpretation of the resultant components of the data set (Norusis, 1994).

Extracted components, associated eigenvalues, and proportion of variance

accounted for by each component are listed in Table 4-17. Bigenvalues, which represent the relative strength of a factor, are used as criteria for inclusion of a given factor into the model. Although different eigenvalue scores have been employed, a cutoff value of 1.0 is a widely-accepted convention. When this convention is applied to the current model, only one factor meets inclusion criteria. This factor accounts for 57% of the variation in subscale t-scores and is by far the strongest component of the model. Three additional factors, which do not meet inclusion criteria, are listed for purposes of comparison. Although eigenvalues for these factors approach 1.0, note that each of the subsequent factors accounts for less than 10% of the total variation in the data set.







53



Table 4-17: Components and Eigenvalues of the Correlation Matrix

Component Eigenvalue Difference % Variation Cum %
FACTOR 1* 5.12857 4.28076 0.569841 0.56984

FACTOR 2 0.84781 0.17261 0.094201 0.66404

FACTOR 3 0.67520 0.06846 0.075022 0.73906

FACTOR 4 0.60673 0.09979 0.0674 15 0.80648
Note: varimax rotation ~ meets inclusion criterion



Table 4-18 shows factor loadings for all nine CAS subscales on the four strongest factors. Factor loading values represent a correlation between a given variable and factor and, thus, are a measure of the strength of association. Table 4-18 underscores the problematic nature of the CAS factor structure by demonstrating that most CAS subscales are moderately correlated with Factor 1. Only suicidal ideation, substance abuse and career problems have factor loadings less than .30. Thus, the factor accounting for the majority of variation in the data set is nebulously defined by moderate association with the majority of variables.

To understand the problematic nature of this factor structure, consider a

hypothetical alternative. If the factor structure of the CAS were such that factors were defined by a small number of variables, the structure of the data set could be said to correspond to the purported scale structure of the CAS. However, in the present case, in which the factors are not clearly defined by their association with subscales, the empirical meaning of individual scales becomes ambiguous. Since the majority of variables are







54

related to only one common factor, the possibility exists that a single psychological dimension underlies the majority of variation on the CAS, regardless of scale.

The above critique notwithstanding, Factors Two through Four in Table 4-18,

although quite weak, demonstrate some dimensionality that should be noted. Factor Two is characterized primarily by a strong association with SA scores (r--.8 1), suggesting a weak trend for substance abuse scores to vary somewhat independently of other scales. Factor Three is positively related to suicidal ideation (r--.75) and, less strongly, negatively related to academic problems (r---.6 1). Factor Four is defined primarily by a strong association with career problems (r--.87). Given their weakness, these factors should be interpreted with caution. However, their structure raises some interesting tentative hypotheses, namely, that student report of substance abuse and career problems may be independent, to some degree, of scores on other scales.



Table 4-18: Factor Loadings for CAS Scale T-Scores

VAR Factor 1 Factor 2 Factor 3 Factor 4
T_-Anxiety .37477 -.26351 -.07139 -.27052
T-Depression .3 8034 -.24773 .05367 -.13570
T Suicidal Ideation .29839 .22942 .74634 .03305
TSubstance Abuse .24637 .80586 -.13563 .10660
TSelf-esteem .36159 -.26104 .08631 -.15787
Tlnterpersonal Problems .36 130 04206 .00043 -.24224
TFamily Problems .33600 .22023 -.13517 -.16589
TCareer Problems .29645 -.22049 .09892 .86555
T Academic Problems .32108 -.01077 -.61733 .18879







55

Creation and Prediction of a Composite Measure of Global Distress

This section reports an attempt to respond to problems created by the

multicolinearity of CAS scales, which negatively impacted the likelihood of finding significant results in the initial series of MANOVAs and confuses the interpretation of individual scales. The factor structure reported in the previous section warrants the assumption that a single psychological phenomenon is responsible for the majority of variation on the CAS subscales. Since the face content of the CAS taps a broad range of functioning, it is logical to assume that this underlying factor may be a measure of global psychological distress. On the basis of this assumption, a composite measure of distress was formulated by computing the average t-score elevation across the nine CAS subscales. This number, which represents a mean standardized level of symptom reporting, was then used as the single criterion variable in a final stepwise regression analysis. A second advantage of this single-criterion analysis was the ability to forgo the use of MANOVA, which substantially limited the number of predictor variables. Thus, this last analysis included all predictor variables, regardless of their performance on the initial MANOVA.

Regression results are summarized in Table 449. Surprisingly, only two

variables-age and psychological treatment since enrollment-are significant predictors of global distress. The meaning of this result is unclear, since environmental variables were significant predictors in previous analyses. Apparently, environmental predictors have no additional explanatory power for scores on the global distress measure. However, these results should be viewed with caution, given that the composite distress







56

measure was a post-hoc creation for the present study and has not been validated. This model accounts for 10.3% of the total variation in average t-score elevation.



Table 4-19: Prediction of Global Distress

Variable Parameter Estimate Std. Error Partial R2 F P
Intercept 60.64 3.18 364.0 .0001
AGE -0.56 0.16 .0411 12.1 .0007
TXSINCE 7.31 1.83 .0614 15.0 .0001




Although no environmental variables entered the stepwise regression equation, bivariate results were significant for grass (t=2.24, p=.03) and concrete (t-t.94, p=.05). This suggests that, although grass and concrete may have some relationship to global distress scores, neither variable contributes more predictive power than the simple combination of age and treatment since enrollment. Thus, using the global distress measure criterion affords little additional understanding of environmental impact on adjustment.



Summai:y of Hypotheses

Taken together, this series of analyses provides limited evidence of the impact of environmental variables on psychological adjustment. The most reasonable summary statement is that, although subject and treatment variables have the most powerful association with psychological status, some environmental variables (especially grass, noise, light, residential satisfaction and, to a lesser degree, number of roommates) may account for additional variation in student adjustment. Let us revisit the original set of research hypotheses.







57

The first hypothesis predicted that residential students should show greater levels of adjustment than off-campus residents. The present results do not provide support for this hypotheses. First, NLANOVA analyses failed to demonstrate the significance of residential location. Second, residential location did not enter the regression equation predicting global distress. In fact, even a simple univariate test failed to show predictive significance (t=.25, p=.80) of residential location for global distress.

The second hypotheses, that psychological adjustment should be inversely related to distance of home from campus, was not supported in the NLANOVA analysis. Nor was distance significantly correlated with global distress in the multiple or bivariate regression analysis; in fact, a simple bivariate correlation (in which on-campus residents received a value of zero) indicated no relationship (r-.002, p .98).

A third hypothesis, based on the work of Wilson, Anderson, and Fleming (1987), predicted that students living with family would report more adjustment difficulties than those living at home, primarily as a function of enmeshment. This hypothesis, too, was supported neither in the omnibus MANOVA nor in the prediction of global distress. This result was not the consequence of predictive overlap with other factors, since a simple t-test showed that family of origin had no relationship with global distress (t=.32, t=.75). However, any actual effect may be obscured by skewed sampling, since only ten students of 184 reported living with their families of origin.

A fourth hypotheses suggested a curvilinear relationship between number of

roommates and adjustment. As noted in Chapter 2, such a hypothesis is difficult to test in this population, because the number of roommates is restricted in range. The mean number of mates was 1.70, with a standard deviation of 1.6. Participants reported in nearly all cases







58

a number ranging from zero to four (an outlier of 16 was an exception), In spite of this restricted range, number of roommates approached significance in the initial NIANOVA (F=l.65,p=.l0). Although the specific effects of roommates were not demonstrated in the follow-up analyses reported above, mates were a small but significant predictor of substance abuse scores in a preliminary analysis, which excluded treatment since enrollment as a predictor (r=.025, F=4.60, p=.03). The relationship was negative, raising the tentative but interesting possibility that those living alone are more likely to report substance abuse problems.

A fifth hypotheses regarding the relationship of noise level to adjustment received limited empirical support as well. Noise effects neared significance in the omnibus MANOVA (F=1.76, p=.081 1). Specific effects of noise were not of sufficient strength to achieve significance in the follow-up analyses. However, effects were in the hypothesized direction; for example, reported noise level was positively (but insignificantly) correlated with global distress.

A sixth hypothesis, or set of related hypotheses, regarded the impact of natural landscape elements in student residences on psychological well-being. Specifically, the presence of water, trees, grass, and adequate light were hypothesized to promote psychological health (cf. Kaplan & Kaplan, 1989). Conversely, the presence of concrete and buildings was predicted to have a detrimental effect on adjustment. This set of hypotheses received the strongest empirical support.

First, grass achieved significance in the omnibus MANOVA (F=2.28, p=.02). The beneficial impact of grass was evident in its association with lower levels of anxiety (F=7.0, p=.01), fewer reports of family problems (F=4.9, p.=.03), and lower levels of academic







59

distress (F=7.7, p=.01). In addition, grass approached significance in the model of suicidal ideation scores (F=2.9, p=.09); the direction of relationship was in the hypothesized direction. In a preliminary model excluding treatment since enrollment as a predictor, grass was the only significant negative predictor of suicidal ideation (F=4.14, p=.04). That analysis also demonstrated that grass was negatively associated with global distress (F=5.57, p=.02).

Reported light levels approached significance in the initial MANOVA (F=1.82, p=.07) and produced significant results in the follow-up analyses. In the results reported above, higher light levels were associated with better self-esteem scores (F=7.3, p=.01). In the analyses excluding treatment since enrollment, poor lighting was associated with increased report of depressive symptoms (F=5.08, p=.03).

Finally, self-report of residential satisfaction ("Overall, how satisfied are you with your current residence?") achieved significance in the MANOVA (F 2.94, p .003). This likert-scale question, included at the end of the section on housing environment, was intended to represent a global self-assessment of residential satisfaction. In the regression results here reported, the influence of residential satisfaction was evident in its ability to predict academic problems, although the direction of association was counterintuitive (Beta:----l.28, F=4.5, p=.03). That is, residential satisfaction was associated with an increased level of reported academic problems. Although the reason for this unexpected result is unclear, apost hoc speculation is that, for a certain segment of the sample, satisfaction reflects residential life distracting rather than promoting academic focus.







60

Psychological Treatment Effects Revisited

Since treatment effects played a significant role in most of the models tested above, a decision was made to investigate in more detail the overall impact of time of treatment on adjustment scores. The following hypothesis emerged from the previous data analyses: recency of treatment should be inversely related to overall adjustment. That is, those students currently in psychological treatment should report more difficulties than those who had treatment earlier in their college years and those who received treatment before college. Those with no treatment history should report the highest level of adjustment. This hypothesis is relevant at present because it (1) provides some indication of criterion validity for the CAS and (2) ties this study more closely to clinical services provided by college counseling centers.

A MANOVA testing for overall effects of the four levels of treatment history (none, before college, since college, and current) on the nine CAS scales yielded significant results (Lambda7-.72, F=2.18, p=.0006). Follow-up analyses of variance (ANOVAs) demonstrated specific treatment effects on t-scores for anxiety (F=7.78, p=.0001), depression (F=5.41, p=.001), substance abuse (F=2.81, p=.04), and self-esteem (F=4.79, p=.003). Post-hoc tests for anxiety scores revealed that students in current treatment had higher t-scores (mean=60. 0) than those who had treatment prior to college (mean=-52. 1) or never (mean=-48.3).' For depression, those in current treatment scored significantly higher (mean-5 9.0) than those who reported therapy before college (mean-5 1.4) or never





2 In a few cases, participants who reported two or more separate episodes of treatment fell into more than one group (i.e., current treatment and treatment before or since college).






61

(mean=48.3). In addition, students currently in treatment reported poorer self-esteem (mean=55.7) than those who had treatment prior to college (mean=48.7) or not at all (mean=46.9). These results provide criterion validity evidence for the CAS scales measuring depression, anxiety and self-esteem.














CHAPTER 5
DISCUSSION



Environment versus Treatment Effects and Student Characteristics

The role of environmental features-specifically, grass views, lighting, and noise level-in psychological well-being was documented in the previous section. In the models presented, environmental conditions were far from predominate determinants of psychological status, but the impact of environmental features made a significant, if small, incremental increase in the prediction of adjustment. Before proceeding with a discussion of the theoretical significance of these limited findings, it is appropriate to revisit methodological issues that may be relevant to the interpretation of results. Psychological treatment histo

Three dichotomous variables (treatment prior to college, treatment since enrollment and current treatment) were used as predictors in the analysis presented here. The nature of these measures is somewhat ambiguous. The first two variables were intended to control for level of psychological adjustment prior to the student's current living arrangements. The last, however, could be conceptualized as either a predictor or an outcome variable. That is, current psychological treatment is likely to result from psychological distress; the reverse case, in which treatment causes distress, is (we hope) less plausible, assuming that competent clinicians are providing services. However, since even current treatment adds some additional strength to most of the models here presented, a decision was made to 62







63

retain each variable in the current model. The decision to incorporate treatment as a predictor at all reflects a conservative analytic strategy, since the variation accounted for by treatment could possibly obscure more subtle environmental effects. However, such a conservative approach has the advantage of documenting environmental impact independent of the decision to seek mental health treatment and, thus, speaks to the broadest possible range of college students. Finally, since this study employs an expostfacto correlational design, the decision to incorporate as many potential predictors as possible compensates for the lack of experimental control. Moreover, the inclusion of all treatment variables as well as environmental predictors increases the relevance of this study to both environmental and counseling psychology, because the strategy allows for the simultaneous assessment of treatment history and envirom-nental or geographical factors.

With regard to this last point, the analysis of the relationship between recency of treatment and adjustment ads an important, more explicitly clinical dimension to our models of adjustment. These results indicate that those students in current treatment (or planning to seek treatment within 30 days) tend to report more difficulties than those who have never sought treatment or those whose treatment episode took place prior to college. Although this trend was not significant for all areas of adjustment measured by the CAS, it was significant for anxiety, depression and self-esteem. Given the assumption that current psychological discomfort is a primary motivation to seek treatment, this result supports the utility and validity of these scales.

Limitations of the sg=le and the criterion measure

Although the total sample size was fairly large (n--1 84), some groups relevant to the research hypotheses were inadequately represented. The most notable among these was







64

students living with their family of origin (n--1O). Also, only a small portion of students reported no exposure to trees (n=l 5). These small cell sizes may have provided insufficient power to detect potential effects.

A more important limitation is the psychometric inadequacy of the College

Adjustment Scales. The intercorrelation among the nine subscales is problematic in two areas. First, multicolinearity necessitates the use of MIANOVA, which has a net effect of reducing the number of environmental variables included for regression analysis. Second, strong intercorrelations render clinical interpretations confusing. Scales strongly related to each other are likely to measure the same underlying construct; therefore, the differential meaning of individual scales is unclear.



Environment and Adjustment

In spite of the rather conservative research strategy, several environmental variables showed promise as predictors of adjustment. The presence of grass was chief among these, achieving overall significance in the MANOVA as well as significance in predictive models for anxiety, suicidal ideation and academic problems. The importance of grass as a predictor of lower levels of psychological distress is consistent with mainstream theoretical and empirical models of landscape preference, which indicate that nature scenes are sought by humans because exposure to such vistas (a) facilitates recovery from fatigue through restorative imp act on information processing systems (Kaplan & Kaplan, 1989) and (b) produces measurable physiological changes associated with autonomic relaxation responses (Ulrich, 1981, 1991; Ulrich et al., 1991). However, the landscape research cited has found that the beneficial impact of nature exposure includes not only grass but also other natural







65

elements, especially trees and water, which had no significant effects in the present study. Perhaps the failure to find convergent effects for these other natural landscape elements stems from methodological shortcomings described above; an alternative possibility is that the benefits of water and trees are more transitory than those of grass.

The presence of light was associated with self-esteem and, more weakly, with depression. This finding is convergent with research suggesting that lower light levels, especially those associated with winter, may play an etiological role in the development of mood disorders. In fact, exposure to light has been repeatedly shown to treat winter depression. Rosenthal, Sock, Skwerer, Jacobson, and Wehr (1988) provide a meta-analysis of clinical research on the effectiveness of phototherapy for Seasonal Affective Disorder (SAD).' They report that light intensity is an important predictor of antidepressant effect. Typically, patients respond best to bright florescent light (about 2,500 lux), while ordinary room light (500 lux or less) has little or no effect on symptoms. A minority of subjects, however, has responded favorably to low-intensity light; some SAD patients may benefit



' The DSM-IV does not list SAD as a separate disorder; rather, a seasonal pattern specifier may be added to a mood disorder diagnosis. The criteria for such a specification are as follows:
A. There has been a regular temporal relationship between the onset of Major Depressive Episodes in Bipolar I or Bipolar H Disorder or Major Depressive Disorder, Recurrent, and a particular time of the year (e.g., regular appearance of the Major Depressive Episode in the fall or winter [in the absence of psychosocial. stressors].
B. Full remissions (or a change from depression to mania or hypomania) also occur at a characteristic time of the year.
C. In the last two years, two Major Depressive Episodes have occurred that demonstrate the temporal seasonal relationships defined in Criteria A and B, and no nonseasonal episodes have occurred during that same period.
D. Seasonal Major Depressive Episodes substantially outnumber the nonseasonal Major Depressive Episodes that may have occurred over the individual's lifetime (American Psychological Association, 1994, p. 390).







66

most from extremely high-intensity light (e.g., 10,000 lux). This finding implicates the neurotransmitter melatonin in SAD, because high-intensity light is required to suppress nocturnal melatonin secretion. The biological substrate of SAD is far from understood, and the debate is outside the scope of this paper. It is sufficient to note that, whatever the underlying mechanism, the antidepressant effects of light have been well-documented in the literature and were reflected in this correlational study.



I=Iications for Policy

The results of this study underscore the importance of an ecological perspective on campus design. Some elements of this perspective have been studied in great detail and, consequently, have had far-reaching influence on policy makers. Examples of these widely acknowledged areas include academics, social life, extracurricular activities, counseling, multicultural awareness, sexual and gender dynamics, campus safety, and to some degree dormitory design. This study focuses attention on the last category by highlighting the impact of environmental content on student adjustment. More specifically, the importance of greenspace and adequate lighting are supported not simply because of their aesthetic value, but rather because their association with psychological fimctioning has been documented empirically, although admittedly in a correlational manner. From an architect's perspective, these findings provide relevant prescriptions for landscape design, although the importance of light and greenspace is certainly not a novel notion. From an ecological perspective, however, the relationship of environmental features to psychological







67

well-being is perhaps more noteworthy, since the results underscore the interconnectedness of the campus system. Student well-being is not simply a function of prior psychological make-up and interaction with mental health professionals. Rather, well-being is influenced by a system of dynamic environmental factors. Physical environment and the microgeography of homespace have a role in this ecological system. Although their impact may be small relative to other factors, their importance is certainly magnified in aggregate; this seems particularly relevant when one considers the task of designing dormspace for hundreds, or even thousands, of students.

One unexpected finding was the absence of significant differences among dormitory and off-campus residents. This result is inconsistent with classic and recent research on the experience of commuter students (Chickenng, 1974; Wolfe, 1992), although much existing research has used indicators of social integration and academic progress rather than explicitly psychological measures. One conclusion is that dormitory residence promotes important connections to campus, but that these benefits are independent of psychological or psychiatric fimctioning. Thus, although off-carnpus residents may feel disconnected from campus, such disconnectedness is not necessarily reflected in increased need for psychotherapy.



Directions for Future Researc

Alternative research instruments should be considered. Well-validated singlecriterion measures are good candidates, because they simplify analytic strategy and afford clearer clinical interpretation. The Mt scale of the NINIPI-2 (Kleinmuntz, 1960), which was problematic in the present study, remains a viable candidate, since it produces a single







68

measure of adjustment associated with a clinical picture of anxiety and feelings of ineffectualness.

A second consideration is the need for designs affording experimental control. The present study was correlational in nature and, therefore, illustrates relationships rather than causal mechanisms. While these exploratory results are an important first step, more rigorously controlled designs would provide clearer elucidation of causal impact. Of course, the logistical and ethical considerations involving random assignment to experimental living conditions make experimental studies a daunting task. Nonetheless, such design options merit ftirther study.

Finally, qualitative approaches can yield richer knowledge of the experience of

lifespace than the quantitative approach here employed. A critical point is that qualitative and quantitative approaches need not be discreet alternatives Rather, the complimentary use of each technique has the potential to provide a more thorough understanding of campus environments.

Such an approach is not unprecedented in environmental psychology. For example, Schroeder (199 1) has combined quantitative and qualitative analysis to model preference and meaning of arboretum landscapes. His approach used keywords from spontaneous descriptions of landscapes to predict environmental preferences. Work focusing on explicitly psychological issues has received attention from humanistic geographers. For example, Tuan (1974) has written extensively on topophilia, or love of place, as a reflection of the emotional ties between humans and landscape. Topophilic experiences might include feelings of at-homeness, acceptance, spiritual well-being, or even transcendency.







69

A more qualitative approach rounds out the ecological context of this paper; an experiential analysis goes beyond this useful, but rather mechanistic, approach by grounding aggregate results in the day-to-day lives of students. Moreover, qualitative clarifications of environmental experience add theoretical sophistication to our understanding. Witness the distinction made by Relph (1985), following Heidegger, between presence-at-hand and readiness-to-hand in the environment. The former denotes a conscious awareness, an objectification of an environmental feature. The latter connotes more subtle meaning; that is, it does not require conscious reflection but rather affords a more fundamental, direct experience of landscape. Quantitative landscape research seems to focus more intently on the present-at-hand world through the conscious examination of environmental features. This bias affects research questions as surely as it does individual responses. A more qualitative conceptualization augments the understanding derived from quantitative research through shifting attention of researcher and subject to more subtle, less conscious, aspects of place.

Few landscapes afford the variety of emotional experiences that may be encountered in a college community; few developmental periods afford as much new experience as the transition from family of origin to the university or college. Thus, campus landscapes seem uniquely positioned in the life experience of students; this context magnifies the importance of campus design, My hope is that this study provides impetus for fartlier interdisciplinary focus on the ecology of student well-being, and that the knowledge gained will be manifest in the life space of campus communities.














APPENDIX A

Informed Consent Statement

Principal Investigator: Michael H. Campbell, MS, Graduate Student, Department Psychology, University of Florida
Supervisor: Dorothy D. Nevill, Ph.D., Professor of Psychology, University of Florida

If you wish to participate in this study, you will be asked to fill out a questionnaire about personal characteristics, the place where you live, your psychological and emotional health, and whether or not you have had counseling. The entire process should take about 30 minutes.

Although you will be asked to provide personal information (such as age, gender, and year in school), you will not be asked to identify yourself. When the results are published, personal information will be reported only for the group. The data for this study will be kept confidential to the extent provided by law.


We do not anticipate that participation in this study will result in any discomfort or risk to you. However, you do not have to answer any question you do not wish to answer, and you may stop participating at any time without penalty of any kind.


No immediate benefits are expected from participation in the study. You will not receive compensation for your efforts.

If you have any questions about the procedures in the study, you may contact: Dorothy Nevill, Ph.D. Mike Campbell, M.S.

114 Psychology Building, Box 112250 or University Counseling Center University of Florida P.O. Box 3708
Gainesville, FL 32611-2250 Laramie, WY 82071
(352) 392-0617 (307) 766-2187

Questions or concerns about the rights of research participants can be directed to: University of Florida IRB Office
Box 112250
University of Florida
Gainesville, FL 32611-2250
70















APPENDIX B



Please answer the following questions about yourself and the place where you live. If choices are provided, circle the appropriate answer. If blanks are provided, fill in the appropriate answer.

Information about you:



1. What is your age? __2. What is your gender? a. Male b. Female

3. Which best describes the ethnic group to which you belong?

a. White (non-Hispanic) b. African American, c. Asian/Pacific Islander d. Hispanic/Latino(a)
e. other

4. How many terms have you been a student at UE/UTW/NC?__5. What is your grade point average?__6. Which best describes your sexual orientation?

a. Heterosexual (straight) b. Bisexual c.Gay/Lesbian



Information about your home:

1. Do you live on campus or off campus? a. on campus b. off campus

2. If off campus, how far away from campus is your home located? (to the nearest
1/2 mile)__71







72



3. If off campus, do you live with your family? a. Yes b. No



4. How many persons in addition to you live in your place of residence
(your dorm room, house or apartment)? _5. If you live on campus, which best describes your residence?

a. dormn b. suite c. university apartment d. other

Optional--What is the name of your building?_______6. Do you live in a fraternity or sorority? a. Yes b. No

Optional--What is the name of your house? _______7. In the room where you spend most of your time at home, are there windows?

a. Yes b. No

If yes, how many?

a. Which of the following are visible from the room in which you spend the most time?
(circle all that are appropriate)water trees grass buildings concrete


8. How well-lit is the place that you live?

1 2 3 4 5 6 7
poorly lit well-lit



9. In your opinion, how noisy is the place that you live?

1 2 3 4 5 6 7
not at all noisy extremely noisy







73



10. Overall, how satisfied are you with your current residence?

1 2 3 4 5 6 7
not at all satisfied extremely satisfied



Information about your use of counseling or psychotherapy:

1. BEFORE you came to UF/UW/NC, had you ever seen a psychologist,
psychiatrist or other type of mental health professional for a psychological or
personal problem? a. Yes b. No
2. SINCE you came to UF/UWNC, have you ever seen a psychologist,
psychiatrist or other type of mental health professional for a psychological or
personal problem? a. Yes
b. No
3. Are you currently seeing (or planning to see within the next month) a mental
health professional? a. Yes b. No











REFERENCES

Aiello, J., & Baum, A. (Eds.). (1979). Residential crowding and design. New York: Plenum.

Altman, I., & Rogoff, B. (1987). World views in psychology and environmental psychology: Trait, interactional, organismic, and transactional perspectives. In D. Stokols & I. Altman (Eds.). Handbook of environmental psychology (pp.7-40). New York: Wiley.

American Psychiatric Association (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author.

Anton, W.D., & Reed, J.R. (1991). College adjustment scales professional manual. Odessa, FL: Psychological Assessment Resources.

Banning, J., & Kaiser, L. (1974). An ecological perspective and model for campus design. The Personnel and Guidance Journal, 52, 370-375.

Bishop, J.B. (1990). The university counseling center: An agenda for the 1990s. Journal of Counseling and Development, 68, 408-413.

Borow, H. (1951). Manual for the college inventory of academic adjustment. Stanford, CA: Stanford University Press.

Bray, J, Williamson, D, & Malone, P. (1984). Personal authority in the family system: Development of a questionnaire to measure personal authority in intergenerational family processes. Journal of Marital and Family Therapy, 10, 167-178.

Brooks, J.H., II, & DuBois, D.L. (1995). Individual and environmental predictors of adjustment during the first year of college. Journal of College Student Development, 36. 347-360.

Butcher, J., Dahlstrom W.G., Graham, J.R., & Tellegen, A. (1989). Minnesota Multiphasic Personality Inventory-2. Minneapolis: University of Minnesota Press.

Butcher, J.N., Dahlstrom, W.G., Graham, J.R., Tellegen, A., & Kraemmer, B. (1989). Minnesota Multiphasic Personality Inventory-2 (MMPI-2): Manual for administration and scoring. Minneapolis: University of Minnesota Press.

Butler, D.L., & Biner, P.M. (1989). Effects of setting on window preferences and factors associated with those preferences. Environment and Behavior. 21. 17-31.


74







75

Campbell, M.H. (1994, August). An informational model of visual preference for urban waterscapes. Paper presented at the 102nd convention of the American Psychological Association, Los Angeles, CA.

Chandler, L.A., & Gallagher, R.P. (1996). Developing a taxonomy for problems seen at a university counseling center. Measurement and Evaluation in Counseling and Development, 29, 4-12.

Chickering, A.W. (1974). Commuting versus resident students. San Francisco: Jossey-Bass.

Chickering, A.W., & Reisser, L. (1993). Education and identity (2nd ed.). San Francisco: Jossey-Bass.

Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24. 385-396.

Cvetkovitch, G, & Earle, T. (1992). Environmental hazards and the public. Journal of Social Issues, 48, 1-20.

Dahlstrom, W.G., Welsh, G.S., & Dahlstrom, L.E. (1975). An MMPI handbook, vol. II: Research applications. Minneapolis: University of Minnesota Press.

Demick, J., & Andreoletti, C. (1995). Some relations between clinical and environmental psychology. Environment and Behavior, 27, 56-72.

Demick, J., & Wapner, S. (1980). Effects of environmental relocation on a psychiatric therapeutic community. Journal of Abnormal Psychology. 89. 444-452.

Dunteman, G.H. (1989). Principal components analysis (Sage university paper series on quantitative applications in the social sciences, 07-069). Beverly Hills: Sage Publications.

Edwards, A.L. (1959). Edwards Personal Preference Schedule manual. New York: Psychological Corporation.

Evans, G.W., & Lepore, S.J. (1993). Household crowding and social support: A quasiexperimental analysis. Journal of Personality and Social Psychology, 65, 308-316.

George, R.L. (1971). Resident or commuter: A study of personality differences. Journal of College Student Personnel, 12, 216-219.

Gough, H.G. (1987). California Psychological Inventory, revised manual. Palo Alto, CA: Consulting Psychologists Press.







76

Graff, R.W., & Cooley, G.R. (1970). Adjustment of commuter and resident students. Journal of College Student Personnel, 11. 54-57.

Graham, J.R. (1993). MMPI-2: Assessing personality and psychopathology (2nd ed.). New York: Oxford University Press.

Hathaway, S. R., & McKinley, J.C. (1943). Minnesota Multiphasic Personality Inventory. Minneapolis: University of Minnesota Press.

Haulman, S.R. (1978). A comparison of self-concepts, peer relationships, persistence and extracurricular involvement of University of Florida freshmen with differing housing arrangements. (Doctoral dissertation, University of Florida, 1978). University Microforms International.

Herman, D.S., Weathers, F.W., Litz, B.T., & Kean, T.M. (1997). Psychometric properties of the embedded and stand-alone versions of the MiMPI-2 Keane PTSD Scale. Assessment. 3. 437-442.

Herzog, T.R. (1989). A cognitive analysis of preference for urban nature. Journal of Environmental Psychology, 9 27-43.

Herzog, T.R. (1992). A cognitive analysis of preference for urban spaces. Journal of Environmental Psychology. 12, 237-48.

Hicks, D., Reed, J., & Anton, W. (1989, October). The intake for as a diagnostic tool. Paper presented at the meeting of the Southeastern Conference of Counseling Center Personnel, Chattanooga, TN.

Hopkins, J. (1994). Orchestrating an indoor city: Ambient noise in a megamall. Environment and Behavior, 26, 785-812.

Huberty, C.J., & Morris, J.D (1989). Multivariate analysis versus multiple univariate analysis. Psychological Bulletin, 105. 302-308.

Kaczmarek, P.G., Matlock, C.G., & Franco, J.N. (1990). Assessment of college adjustment in three freshmen groups. Psychological Reports, 66, 1195-1202.

Kaiser, L.R. (1977). Campus ecology and campus design. NASPA monograph.

Kaplan, R., & Kaplan, S. (1989). The experience of nature: A psychological perspective. New York: Cambridge University Press.

Kleinmuntz, B. (1960). Identification of maladjusted college students. Journal of Counseling Psychology. 7. 209-211.







77

Kleinmuntz, B. (1961). The College Maladjustment Scale (Mt): Norms and predictive validity. Educational and Psychological Measurement, 21, 1029-1033.

Krupat, E. (1985). People in cities. New York: Cambridge University Press.

Kuczka, T., & Handal, P. (1990). Validity of the college maladjustment scale for identification of distressed students. Psychological Reports, 67, 730.

Langer, T.S. (1962). A twenty-two item screening score of psychiatric symptoms indicating impairment. Journal of Health and Human Behavior, 3. 269-276.

Lepore, S.J., Evans, G.W., & Schneider, M. (1991). Dynamic role of social support in the link between chronic stress and psychological distress. Journal of Personality and Social Psychology. 61, 899-909.

Levy-Leboyer, C., & Naturel, V. (1991). Neighborhood noise annoyance. Journal of Environmental Psychology, 11, 75-86.

Milgram, S. (1970). The experience of living in cities. Science, 167, 1461-1468.

Morrill, W.H., Oetting, E.R., & Hurst, J.C. (1974). Dimensions of counselor functioning. Personnel and Guidance Journal. 52. 354-359.

Murphy, M.C., & Archer, J., Jr. (1996). Stressors on the college campus: A comparison of 1985 and 1993. Journal of College Student Development. 37. 20-27.

Norusis, M.J. (1994). SPSS professional statistics 6.1. Chicago: SPSS, Inc.

Novaco, R.W., Kliewer, W., & Broquet, A. (1991). Home environmental consequences of commute travel impedance. American Journal of Community Psychology. 19, 881-909.

Novako, R.W., Stokols, D., & Milanesi, L. (1990). Objective and subjective dimensions of travel impedance as determinants of commuting stress. American Journal of Community Psychology. 18. 231-257.

Pace, D., Stamler, V.L., Yarris, E., & June, L. (1996). Rounding out the cube: Evolution to a global model for counseling centers. Journal of Counseling and Development, 74, 321-325.

Parker, C.A. (1961). The predictive use of the MMPI in a college counseling center. Journal of Counseling Psychology, 8. 154-158.







78

Pascarella, E.T., & Chapman, D.W. (1983). Validation of a theoretical model of college withdrawal: Interaction effects in a multi-institutional sample. Research in Higher Education. 19. 25-48.

Pascarella, E.T., Duby, P.B., & Iverson, B.K. (1983). A test and
reconceptualization of a theoretical model of college withdrawal in a commuter institution setting. Sociology of Education, 56, 88-100.

Pascarella, E.T., Edison, M., Nora, A., Hagedom, L.S., & Terenzini, P.T. (1996). Influences on students' openness to diversity and challenge in the first year of college. Journal of Higher Education, 67, 174-190.

Relph, E. (1985). Geographical experiences and being-in-the-world: The phenomenological origins of geography. In D. Seamon & Mugerauer (Eds.), Dwelling. Place, and Environment: Towards a Phenomenology of Person and World (pp. 15-33). Dordrecht: Nijhoff.

Rosenthal, N., Sock, D., Skwerer, R., Jacobson, F., & Wehr, T. (1988). Phototherapy for seasonal affective disorder. Journal of Biological Rhythms. 3. 101-120.


Schroeder, H.W. (1991). Preference and meaning of arboretum landscapes: Combining quantitative and qualitative data. Journal of Environmental Psychology,11, 231-248.

Seamon, D. (1984). Emotional experience of the environment. American Behavioral Scientist, 27, 757-770.

Seamon, D. (1989). Humanistic and phenomenological advances in environmental design. The Humanistic Psychologist, 17. 280-293.

Stokols, D. (1995). The paradox of environmental psychology. American Psychologist, 50, 821-827.

Street, S., Kromrey, J.D., Reed, J., & Anton, W. (1993, December/January). A phenomenological perspective of problems experienced by high school students. High School Journal, pp. 129-13 8.

Sundstrom, E., Bell, P.A., & Asmus, C. (1996). Environmental psychology: 19891994. Annual Review of Psychology, 47, 485-512.

Taylor, J.G., Zube, E.H., & Sell, J.L. (1987). Landscape assessment and perception research methods. In R.B. Bechtel, R.W. Marans, & W. Michelson (Eds.), Methods in environmental and behavioral research (pp. 361-393). New York: Van Nostrand Reinhold Company.







79


Turner, P.R., Valtierra, M., Talken, T.R., Miller, V.I., & De Anda, J.R. (1996). Effect of session length on treatment outcome for college students in brief therapy. Journal of Counseling Psychology, 43, 228-232.

Ulrich, R.S. (1981). Natural versus urban scenes: Some psychophysiological effects. Environment and Behavior, 13, 523-556.

Ulrich, R.S. (1984). View through a window may influence recovery from surgery. Science, 224, 420-421.

Ulrich, R.S. (1991). Effects of interior design on wellness: Theory and recent scientific research. Journal of Health Care Interior Design, 3, 97-109.

Ulrich, R.S., Simons, R.F., Losito, B.D., Fiorito, E., Miles, M.A., & Zelson, M. (1991). Stress recovery during exposure to natural and urban environments. Journal of Environmental Psychology, 11, 201-30.

Wapner, S. (1995). Toward integration: Environmental psychology in relation to other subfields of psychology. Environment and Behavior, 27, 9-32.

Welty, J.D. (1976). Resident or commuter students: Is it only the living situation? Journal of College Student Personnel, 17, 465-468.

Wilson, R.J., Anderson, S.A., & Fleming, W.M. (1987). Commuter and resident students' personal and family adjustment. Journal of College Student Personnel. 28, 229233.

Wolfe, J.S. (1992). The relationship of a freshman year experience for resident and commuter students to the social and academic integration, commitment, academic success and persistence of first-year college students (Doctoral dissertation, University of Maryland, College Park, 1991). Dissertation Abstracts International, 53, 1079-A.













BIOGRAPHICAL SKETCH

Mike Campbell was born at McCoy Air Force Base, Orlando, Florida on October 30, 1969 to Capt. Donald F. and Sylvia Campbell. During childhood, he accompanied his parents on a variety of assignments in the continental U.S. and Republic of Panama. After graduating from Rome Free Academy (Rome, N-Y) in 1987, Mike enrolled at New College of the University of South Florida (Sarasota, FL) where he completed a B.A. in psychology/Latin American studies in 1991. He received a M.S. in geography from The Florida State University (Tallahassee, FL) in 1993; his master's thesis, 4n Informational approachh to Visual Preference of Urban Waterscapes, was presented at the 102",Ouinual Convention of the American Psychological Association (Population and Environtnental Psychology Division) in 1994. Mike completed pre-doctoral internship training at the University of Wyoming (Laramie, WY) in 1997 and received a Ph.D. in counseling psychology from the University of Florida (Gainesville, FL) in 1998.

Mike currently lives in Sarasota, FL, where he is a therapist at the New College/USF Counseling and Wellness Center. He is also an adjunct faculty member at the University of Tampa. His professional memberships include the American Psychological Association, American Society of Clinical Hypnosis, Southeastern Psychological Association, and Southeastern Council on Latin American Studies. Previously, Mike served as a trustee of New College Foundation, and he is currently a director and secretary of the New College Alumnae/i Association.


80









I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy.

Dorothy D. vill, Chair/
Professor of sychology

I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosoph




I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy.

Mary Fuk yarna
Clinical Professor of Psychology

I certify that 1 have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope id quality, as a dissertation for the degree of Doctor of Philosophy ,/ 9

Irafischler
Professor of Psychology

I certify that I have read this study and that in my o 'i i ifcoi Forms to
acceptable standards of scholarly presentation and is fully ade u in scope and quality, as a dissertation for the degree of Doctor of Philosophy.

Ary Lamme
Associate Professor of Geography

This dissertation was submitted to the Graduate Faculty of the Department of Psychology in the College of Liberal Arts and Sciences and to the Graduate School and was accepted as partial fulfillment for the requirements for the degree of Doctor of Philosophy.


May 1998
Dean, Graduate School




Full Text
xml version 1.0 encoding UTF-8
REPORT xmlns http:www.fcla.edudlsmddaitss xmlns:xsi http:www.w3.org2001XMLSchema-instance xsi:schemaLocation http:www.fcla.edudlsmddaitssdaitssReport.xsd
INGEST IEID EB09GX3JM_TV3HNH INGEST_TIME 2014-08-22T19:47:22Z PACKAGE AA00024961_00001
AGREEMENT_INFO ACCOUNT UF PROJECT UFDC
FILES



PAGE 1

7+( ,03$&7 2) 5(6,'(17,$/ (19,5210(17 21 36<&+2/2*,&$/ $'-8670(17 2) &2//(*( 678'(176 %\ 0,&+$(/ +$55< &$03%(// $ ',66(57$7,21 35(6(17(' 72 7+( *5$'8$7( 6&+22/ 2) 7+( 81,9(56,7< 2) )/25,'$ ,1 3$57,$/ )8/),//0(17 2) 7+( 5(48,5(0(176 )25 7+( '(*5(( 2) '2&725 2) 3+,/2623+< 81,9(56,7< 2) )/25,'$

PAGE 2

$&.12:/('*(0(176 H[WHQG VLQFHUH WKDQNV WR 'RURWK\ 1HYLOO DQG )UDQ] (SWLQJ IRU WKHLU DVVLVWDQFH ZLWK WKLV PDQXVFULSW DQG PRUH JHQHUDOO\ IRU WKHLU JXLGDQFH GXULQJ P\ JUDGXDWH FDUHHU DP LQGHEWHG WR 6KDZQ 3ULFKDUG IRU IULHQGVKLS DQG LQWHOOHFWXDO VWLPXODWLRQ DV ZHOO DV PRUH FRQFUHWHO\ WHFKQLFDO DVVLVWDQFH ZLWK WKH GDWD DQDO\VLV KHUH SUHVHQWHG 0\ WKDQNV IRU WKH H[WUDRUGLQDU\ VXSSRUW SURYLGHG E\ P\ IDPLO\f§HVSHFLDOO\ P\ SDUHQWV 'RQ DQG 6\OYLD &DPSEHOO DQG P\ JUDQGPRWKHU 0DU\ $OLFH .QLJKWf§FDQQRW EH DGHTXDWHO\ DFNQRZOHGJHG KHUH

PAGE 3

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

PAGE 4

(QYLURQPHQW YHUVXV 7UHDWPHQW (IIHFWV DQG 6WXGHQW &KDUDFWHULVWLFV (QYLURQPHQW DQG $GMXVWPHQW ,PSOLFDWLRQV IRU 3ROLF\ 'LUHFWLRQV IRU )XWXUH 5HVHDUFK $33(1',&(6 $ ,1)250(' &216(17 67$7(0(17 % 48(67,211$,5( 5()(5(1&(6 %,2*5$3+,&$/ 6.(7&+ LY

PAGE 5

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f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

PAGE 6

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

PAGE 7

&+$37(5 ,1752'8&7,21 7KH LQWHUIDFH RI FRXQVHOLQJ RU FOLQLFDO SV\FKRORJ\ ZLWK WKH EURDGHU SHUVSHFWLYH RI HQYLURQPHQWDO RU HFRORJLFDO DSSURDFKHV KDV JHQHUDWHG D QXPEHU RI QRYHO UHVHDUFK TXHVWLRQV UHJDUGLQJ WKH LPSDFW RI HQYLURQPHQWDO IHDWXUHV RQ SV\FKRORJLFDO ZHOOEHLQJ 7KH SUHVHQW VWXG\ LV D FRQWULEXWLRQ WR WKLV WUDGLWLRQ DOWKRXJK WKH JHRJUDSKLF GRPDLQ RI WKLV UHVHDUFKf§ WKH FDPSXV FRPPXQLW\f§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fV FROOHJLDWH H[SHULHQFH LV FRQWH[WXDOL]HG E\ D FDPSXV V\VWHP FRPSULVHG RI VRFLDO PXOWLf FXOWXUDO VSDWLDO DQG SK\VLFDO IDFWRUV ,QGHHG WKH DFDGHPLF DQG SURIHVVLRQDO MRXUQDOV LQ FROOHJH VWXGHQW SHUVRQQHO KDYH HQGRUVHG HFRORJLFDO DSSURDFKHV WR FDPSXV GHVLJQ HJ %DQQLQJ t .DLVHU f 7KLUG FDPSXV PHQWDO KHDOWK SURIHVVLRQDOV SDUWLFXODUO\ FRXQVHOLQJ SV\FKRORJLVWV ZKRVH WUDLQLQJ XVXDOO\ DIIRUGV VXEVWDQWLDO H[SRVXUH WR FROOHJHDJH

PAGE 8

SRSXODWLRQV DUH NHHQO\ DZDUH RI PHQWDO KHDOWK LVVXHV RQ FDPSXV DQG RIWHQ ZRUN IURP D GHYHORSPHQWDO SHUVSHFWLYH FRQFHUQHG ZLWK SV\FKRORJLFDO DQG JHRJUDSKLFDOf WUDQVLWLRQV )RXUWK RWKHU UHVHDUFKHUV SULQFLSDOO\ JHRJUDSKHUV DQG VRFLRORJLVWV FRQFHUQHG ZLWK WKH LPSDFW RI SODFH FRXOG FRQWULEXWH WR WKH XQGHUVWDQGLQJ QRW RQO\ RI PHDVXUDEOH HQYLURQPHQWDO LPSDFW EXW DOVR PRUH TXDOLWDWLYHO\ RI JHQLXV ORFL WKH VSLULW RI SODFH WKH WRWDOLW\ RI D ODQGVFDSH HQFRPSDVVLQJ LQWDQJLEOH DQG WUDQVFHQGHQW TXDOLWLHV WKDW DFFRXQW IRU WKH XQLTXHQHVV RI SODFH 6HDPRQ f *LYHQ WKH GLYHUVLW\ RI LQWHOOHFWXDO WUDGLWLRQV WKDW FDQ SURILWDEO\ DGGUHVV WKH UROH RI SK\VLFDO HQYLURQPHQW LQ WKH SV\FKRORJLFDO H[SHULHQFH RI FROOHJH VWXGHQWV WKH UHODWLYH GHDUWK RI UHVHDUFK LV GLVDSSRLQWLQJ 3HUKDSV WKH UHOHYDQW GLVFLSOLQHV DUH VR GLYHUJHQW LQ WUDLQLQJ DQG SUDFWLFH WKDW IUXLWIXO FURVVGLVFLSOLQDU\ FROODERUDWLRQ LV VHOGRP DIIRUGHG ,QGHHG WKH FXUUHQW VWXG\ LV RI QHFHVVLW\ IRFXVHG RQ D OLPLWHG QXPEHU RI UHVHDUFK SHUVSHFWLYHV DQG DQDO\WLFDO PHWKRGRORJLHV 7D\ORU =XEH DQG 6HOO f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f UHVSRQGHUV WR WKH HQYLURQPHQW WKH FRJQLWLYH DSSURDFK KROGV WKDW VWUXFWXUHV DQG QHHGV RI RXU LQIRUPDWLRQ SURFHVVLQJ V\VWHPV PHGLDWH RXU H[SHULHQFH RI WKH HQYLURQPHQW 7KXV LQ WKH SV\FKRSK\VLFDO SDUDGLJP SV\FKRORJLFDO UHVSRQVHV WR HQYLURQPHQWDO VWLPXOL DUH PHDVXUHG LQ WKH FRJQLWLYH SDUDGLJP

PAGE 9

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

PAGE 10

VWXG\ LV FRQFHSWXDOO\ GLVWLQFW IURP fPDLQVWUHDPf ODQGVFDSH UHVHDUFK 7KH ODWWHU WHQGV WR RSHUDWLRQDOL]H SV\FKRORJLFDO UHDFWLRQ LQ WHUPV RI SUHIHUHQFH LQ FRQWUDVW WKH SUHVHQW VWXG\ LV H[SUHVVO\ FRQFHUQHG ZLWK SV\FKRORJLFDO DGMXVWPHQW DV D FULWHULRQ PHDVXUH 7KXV SV\FKRORJLFDO RXWFRPHV RI LPSRUWDQFH KHUH LQFOXGH QRW SUHIHUHQFH EXW LPSDFW RQ PHQWDO KHDOWK LQ WKH GRPDLQV RI GHSUHVVLRQ DQ[LHW\ VXEVWDQFH DEXVH LQWHUSHUVRQDO GLVWUHVV DPRQJ RWKHU DUHDV ,Q WKH FKDSWHUV WKDW IROORZ WKHVH LVVXHV DUH DGGUHVVHG ERWK WKHRUHWLFDOO\ DQG HPSLULFDOO\ &KDSWHU UHYLHZV WKH H[WDQW OLWHUDWXUH LQ FRXQVHOLQJFOLQLFDO SV\FKRORJ\ HQYLURQPHQWDO SV\FKRORJ\ DQG FROOHJH VWXGHQW SHUVRQQHO 7KH FKDSWHU EHJLQV ZLWK D WUHDWPHQW RI HFRORJLFDO DSSURDFKHV WKDW SODFH WKH VWXGHQW LQWR DQ LQWHJUDWHG WUDQVDFWLRQDO HQYLURQPHQWDO V\VWHP HJ .DLVHU f 7KH VXEVHTXHQW VHFWLRQ UHYLHZV H[LVWLQJ UHVHDUFK RQ WKH LPSDFW RI HQYLURQPHQWDO IHDWXUHV RQ SV\FKRORJLFDO ZHOOEHLQJ DQG UHFHQW FDOOV IRU D PRUH WUDQVDFWLRQDO XQGHUVWDQGLQJ RI SV\FKRORJLFDO IXQFWLRQLQJ 7KH IROORZLQJ VHFWLRQV VXPPDUL]H ILQGLQJV RI WKH VWXGHQW DIIDLUV OLWHUDWXUH HJ &KLFNHULQJ t 5HLVVHU f UHJDUGLQJ FKDUDFWHULVWLFV DQG QHHGV WKDW GLVWLQJXLVK FRPPXWHUV IURP UHVLGHQWLDO VWXGHQWV FRQFOXGLQJ WKDW WKH H[WDQW OLWHUDWXUH KDV QHJOHFWHG IRU WKH PRVW SDUW SV\FKRORJLFDO PHDVXUHV RI GLIIHUHQFHV $ PHWKRGRORJLFDO FULWLTXH WKHQ SURSRVHV DOWHUQDWLYH PHDVXUHV RI DGMXVWPHQW WKDW ZRXOG EHWWHU RSHUDWLRQDOL]H SV\FKRORJLFDO VWDWXV WKH &ROOHJH $GMXVWPHQW 6FDOHV &$6 $QWRQ t 5HHG f DQG WKH &ROOHJH 0DODGMXVWPHQW 6FDOH 0W .OHLQPXQW] f 7KH QH[W VHFWLRQV VXPPDUL]H WKH SV\FKRORJLFDO EHQHILW RI VSHFLILF HQYLURQPHQWDO IHDWXUHV VXFK DV QDWXUH VFHQHV .DSODQ t .DSODQ 8OULFK f ZLQGRZV %XWOHU t %LQHU f DQG FRQILJXUDO DVSHFWV RI ODQGVFDSH &DPSEHOO +HU]RJ .DSODQ t .DSODQ f ,Q DGGLWLRQ WKLV VHFWLRQ LQFOXGHV D EULHI UHYLHZ RI GHWULPHQWDO

PAGE 11

IHDWXUHV VXFK DV FURZGLQJ (YDQV t /HSRUH .UXSDW 0LOJUDQD f QRLVH /HY\/RER\HU t 1DWXUHO f DQG EDUULHUV WR FRPPXWLQJ 1RYDFR .OLHZHU t %URTXHW f &KDSWHU FRQFOXGHV ZLWK D VXPPDU\ RI WKH UDWLRQDOH IRU WKH SUHVHQW VWXG\ DQG D VHULHV RI WHQWDWLYH UHVHDUFK K\SRWKHVHV &KDSWHU GHWDLOV PHWKRGV DQG UHVHDUFK GHVLJQ LQFOXGLQJ VDPSOH FKDUDFWHULVWLFV SV\FKRPHWULF FKDUDFWHULVWLFV RI WKH UHVHDUFK LQVWUXPHQWV SURFHGXUDO SURWRFRO DQG WKH JHQHUDO VWUDWHJ\ IRU GDWD DQDO\VLV 7KLV ODVW WRSLF LQFOXGHV GLVFXVVLRQ RI WKH PHWKRGRORJLFDO FKDOOHQJHV LQKHUHQW LQ PXOWLYDULDWH TXDVLH[SHULPHQWDO GHVLJQ DV ZHOO DV WKH UDWLRQDOH IRU XVH RI PXOWLYDULDWH DQDO\VLV RI YDULDQFH 0$129$f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

PAGE 12

H[SHFWDWLRQ RIIHUV OLWWOH DGGLWLRQDO LQIRUPDWLRQ UHODWLYH WR PRGHOV RI VFRUHV RQ HDFK RI WKH QLQH FRPSRQHQW &$6 VFDOHV 7KH ILQDO FKDSWHU LV D GLVFXVVLRQ RI WKH SUHVHQW ILQGLQJV DQG DUJXHV WKDW DOWKRXJK WUHDWPHQW LQGLFDWRUV DQG VXEMHFW YDULDEOHV DUH PRVW SUHGLFWLYH RI DGMXVWPHQW VRPH HQYLURQPHQWDO YDULDEOHV HJ JUDVV QRLVH OLJKW UHVLGHQWLDO VDWLVIDFWLRQ DQG WR D OHVVHU H[WHQW QXPEHU RI URRPPDWHVf DOVR PDQLIHVW D UHODWLRQVKLS ZLWK SV\FKRORJLFDO IXQFWLRQLQJ 7KH LPSOLFDWLRQ RI WKHVH ILQGLQJ IRU FDPSXV DUFKLWHFWV VWXGHQW DIIDLUV SURIHVVLRQDOV PHQWDO KHDOWK SURYLGHUV DQG HGXFDWLRQDO SROLF\ PDNHUV LV GLVFXVVHG $GGLWLRQDOO\ WKH SV\FKRPHWULF LQDGHTXDF\ RI WKH &$6 LV GLVFXVVHG 7KH FRQFOXVLRQ DGYRFDWHV WKH XVH RI DOWHUQDWLYH PHDVXUHV IRU IXWXUH UHVHDUFK f WR DYRLG WKH VWULQJHQF\ LPSRVHG E\ 0$129$ DQG f WR DFKLHYH EHWWHU GLVFULPLQDQW YDOLGLW\ 7KH ILQDO VHFWLRQV VXJJHVW GLUHFWLRQV IRU IXWXUH UHVHDUFK SDUWLFXODUO\ WKH LQWHJUDWLRQ RI TXDQWLWDWLYH DQG TXDOLWDWLYH DSSURDFKHV SLRQHHUHG E\ UHVHDUFKHUV VXFK DV 6FKURHGHU f 6XFK LQWHJUDWLRQ VLPXOWDQHRXVO\ RIIHUV ERWK WHVWDEOH K\SRWKHVHV DQG D IXOOHU XQGHUVWDQGLQJ RI WKH PRUH LQWDQJLEOH VXEMHFWLYH DQG WUDQVFHQGHQW TXDOLWLHV RI SODFH 5HOSK 6HDPRQ f

PAGE 13

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t .DLVHU 0RUULOO 2HWWLQJ t +XUVW 3DFH 6WDPOHU
PAGE 14

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f 7KH VWXGHQWfV H[SHULHQFH LV VKDSHG E\ WKH FROOHJH HQYLURQPHQW EXW WKH UHODWLRQVKLS LV QRW VLPSO\ RQH RI FDXVDWLYH IDFWRU WR UHVSRQGLQJ RUJDQLVP 5DWKHU D PRUH G\QDPLF KROLVWLF FRQFHSWXDOL]DWLRQ LQ ZKLFK VWXGHQWV LQ HQYLURQPHQW DUH WKH SULPDU\ XQLW RI DQDO\VLV LV WDNHQ KHUH 7KLV DSSURDFK GHYHORSHG E\ $OWPDQ VHH $OWPDQ t 5RJRII IRU GHOLQHDWLRQ RI WKLV YLHZf DQG H[SDQGHG E\ RWKHUV FI :DSQHU f LV FKDUDFWHUL]HG E\ D V\VWHPVFHQWHUHG SHUVSHFWLYH WKDW ZKHQ DSSOLHG WR FDPSXV HQYLURQPHQWV KROGV WKDW VWXGHQWV DUH LQWHJUDO FRPSRQHQWV RI WKH ODUJHU FDPSXV HQYLURQPHQWDO V\VWHP 6XFK DQ DSSURDFK VXJJHVWV WKDW WKH SURFHVV RI LQIOXHQFH LV PXWXDO DPRQJ LQWHUFRQQHFWHG HOHPHQWV 7KDW LV D FROOHJH VWXGHQWfV H[SHULHQFH LV PROGHG E\ PXOWLSOH HOHPHQWV RI WKH HQYLURQPHQW EXW WKDW VDPH VWXGHQWf§DQG E\ H[WHQVLRQ ODUJHU JURXSV RI VWXGHQWVf§LV DOVR DQ DFWLYH VKDSHU RI WKH HQYLURQPHQWDO V\VWHP EHFDXVH KH RU VKH EHORQJV WR WKDW V\VWHP 7KLV YLHZ LPSOLHV WKDW WKH SHUVRQDO FKDUDFWHULVWLFV ZKLFK VWXGHQWV EULQJ WR FROOHJH LQFOXGLQJ OLIH KLVWRU\ SHUVRQDOLW\ WUDLWV DQG SV\FKRORJLFDO G\VfIXQFWLRQ EHFRPH LPSRUWDQW LQIOXHQFHV LQ WKH SHUVRQHQYLURQPHQW V\VWHP ,Q WHUPV RI WKH SUHVHQW VWXG\ WKLV WKHRUHWLFDO SHUVSHFWLYH

PAGE 15

VXJJHVWV WKDW WKH GHFLVLRQV VWXGHQWV PDNH DERXW WKHLU UHVLGHQWLDO FKRLFH ZLOO EH LPSDFWHG E\ SHUVRQDO DQG HQYLURQPHQWDO IDFWRUV DQG WKDW VWXGHQWVf FROOHJH KRXVLQJ HQYLURQPHQWV ZLOO DFW WR VKDSH WKHLU HGXFDWLRQDO H[SHULHQFH DQG SV\FKRORJLFDO ZHOOEHLQJ &DPSXV PHQWDO KHDOWK SURIHVVLRQDOV KDYH VKRZQ VRPH LQWHUHVW LQ DQ HFRORJLFDO FRQFHSWXDOL]DWLRQ RI VWXGHQW IXQFWLRQLQJ DOWKRXJK D UHYLHZ RI WKH OLWHUDWXUH VXJJHVWV WKDW WKLV SHUVSHFWLYH KDV EHHQ OLPLWHG LQ VFRSH DQG LQIOXHQFH 0RUULOO 2HWWLQJ DQG +XUVW f SURSRVHG D IUDPHZRUN IRU FRXQVHOLQJ LQWHUYHQWLRQV QRW OLPLWHG WR WKH WKHUDS\ URRP 7KHLU PRGHO GHOLQHDWHG LQ WHUPV RI WDUJHW SXUSRVH DQG PHWKRG RI LQWHUYHQWLRQ H[SDQGV WKH WDUJHW GRPDLQ RI FDPSXV FRXQVHOLQJ VWDII IURP WKH WUDGLWLRQDO LQGLYLGXDO FOLHQW WR LQFOXGH SULPDU\ JURXSV IULHQGV DQG IDPLO\f DVVRFLDWLRQDO JURXSV HJ FODVVHV VWXGHQW RUJDQL]DWLRQV DQG UHVLGHQFHEDVHG JURXSVf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
PAGE 16

QHLWKHU DGGUHVVHV H[SOLFLWO\ WKH SV\FKRORJLFDO DVSHFWV RI UHVLGHQWLDO HQYLURQPHQW 6LPLODUO\ D UHFHQW SUHVFULSWLRQ IRU H[SDQVLRQ DQG DGDSWLRQ RI FROOHJH FRXQVHOLQJ FHQWHU VHUYLFHV %LVKRS f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f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t %DXP f EHWWHU PDQDJHPHQW SROLF\ IRU HQYLURQPHQWDO KD]DUGV HJ &YHWNRYLFK t (DUOH f DQG LQFUHDVHG H[SRVXUH WR QDWXUDO HQYLURQPHQWV LQ RIILFHV DQG KHDOWK FDUH VHWWLQJV .DSODQ t .DSODQ 8OULFK f 'HPLFN DQG $QGUHROHWWL f UHYLHZ D QXPEHU RI UHFHQW VWXGLHV LQ RUGHU WR HOXFLGDWH FRQQHFWLRQV EHWZHHQ HQYLURQPHQWDO DQG FOLQLFDO SV\FKRORJ\ 7KH DXWKRUV

PAGE 17

GLVWLQJXLVK EHWZHHQ ILHOGV LQ WHUPV RI FRQWHQW DQG PHWKRG SRVLWLQJ WKDW FOLQLFDO SV\FKRORJ\ LV GHILQHG E\ LWV FRQWHQW DUHD LH GLDJQRVLV DQG WUHDWPHQW RI SV\FKRORJLFDO FRQGLWLRQVf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t :DSQHU f RU WKH UROH RI SHUVRQDO VSDFH LQ WKHUDS\ RU FOLQLFDO VXSHUYLVLRQ 7KH SUHVHQW VWXG\ LV RQH DWWHPSW WR UHVSRQG WR WKH FDOO IRU FURVVGLVFLSOLQDU\ UHVHDUFK 6HFRQG 'HPLFN DQG $QGUHROHWWL FRQFHSWXDOL]H HQYLURQPHQWDO SHUVSHFWLYHV DV DQ DOWHUQDWLYH WR WUDGLWLRQDO SHUVRQFHQWHUHG DSSURDFKHV WR GLDJQRVLV DQG WUHDWPHQW WKDW LV fWKH XQLW RI DQDO\VLV LQ SV\FKRSDWKRORJ\ PLJKW PRUH DSWO\ EH FRQFHSWXDOL]HG DV WKH SHUVRQLQ HQYLURQPHQW V\VWHPf S f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f DUH UHOHYDQW WR WKH SUHVHQW VWXG\ ZKLFK IRFXVHV RQ WKH UROH RI UHVLGHQWLDO HQYLURQPHQW LQ WUDQVLWLRQ WR DQG IXQFWLRQ LQ WKH FROOHJH VHWWLQJ

PAGE 18

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f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

PAGE 19

ORFDWLRQ 0RUHRYHU LQFUHDVLQJ QXPEHUV RI FROOHJH VWXGHQWV KDYH HOHFWHG WR OLYH RII FDPSXV HYHQ ZKHQ WKH\ DUH LQ VFKRRO D ORQJ GLVWDQFH IURP WKHLU IDPLO\fV KRPH LQ UHVSRQVH WR ULVLQJ URRP DQG ERDUG FRVWV DV ZHOO DV FDPSXV KRXVLQJ VKRUWDJHV EHJLQ ZLWK &KLFNHULQJfV ZRUN ZKLFK KDV SURYLGHG WKH EDVHOLQH IRU VXEVHTXHQW LQYHVWLJDWLRQ FRQVLGHU DGGLWLRQDO UHVHDUFK LQ WKH SDUDJUDSKV WKDW IROORZ LQ RUGHU WR JHQHUDWH K\SRWKHVHV UHJDUGLQJ WKH SV\FKRORJLFDO LPSDFW RI UHVLGHQWLDO ORFDWLRQ &KLFNHULQJ VHH DOVR &KLFNHULQJ t 5HLVVHU f SURYLGHV D WKRURXJK HPSLULFDO VXPPDU\ RI VLJQLILFDQW GLIIHUHQFHV LQ GHPRJUDSKLF EDFNJURXQG DQG FROOHJH H[SHULHQFH EHWZHHQ FRPPXWHU VWXGHQWV DQG RQFDPSXV UHVLGHQWV &RPPXWHU VWXGHQWV LQ KLV VDPSOH UHSRUWHG ORZHU KLJK VFKRRO JUDGHV DQG LQFUHDVHG ILQDQFLDO DQG LQWHUSHUVRQDO VWUHVVRUV 7KHLU IDPLOLHV RI RULJLQ ZHUH RI ORZHU VRFLRHFRQRPLF VWDWXV PHDVXUHG LQ WHUPV ERWK RI UHSRUWHG LQFRPH DQG RI SDWHUQDO RFFXSDWLRQ IDWKHUV RI FRPPXWHUV ZHUH PRUH OLNHO\ WR EH VNLOOHG VHPLVNLOOHG RU XQVNLOOHG ZRUNHUVf &KLFNHULQJ DOVR UHSRUWHG WKDW WKH PDMRULW\ RI FRPPXWHU VWXGHQWV DSSOLHG RQO\ WR WKH FROOHJH RU XQLYHUVLW\ ZKLFK WKH\ FXUUHQWO\ DWWHQGHG 7KHLU HGXFDWLRQDO JRDOV ZHUH PRUH IRFXVHG RQ YRFDWLRQDO SUHSDUDWLRQ WKDQ WKRVH RI UHVLGHQWLDO VWXGHQWV LQ IDFW FRPPXWHUV PRUH IUHTXHQWO\ PDMRUHG LQ EXVLQHVV DGPLQLVWUDWLRQ RU HQJLQHHULQJ 0RUHRYHU FRPPXWHUV ZHUH OHVV OLNHO\ WR UHSRUW SODQV WR VHHN DQ DGYDQFHG GHJUHH 7KXV &KLFNHULQJfV GDWD VXJJHVW WKDW FRPPXWHU VWXGHQWV HQWHU FROOHJH VLJQLILFDQWO\ FRQVWUDLQHG E\ FRQWLQJHQFLHV H[WHUQDO WR WKHLU HGXFDWLRQDO HQYLURQPHQWV DQG WHQG WR SODQ WKHLU HGXFDWLRQ RQ WKH EDVLV RI SUR[LPLW\ RI DYDLODEOH SURJUDPV DQG WKH SUDFWLFDOLW\ RI WKHLU GHJUHHV 0DQ\ RI WKHVH VWXGHQWV DWWHQG LQVWLWXWLRQV ZLWK SULPDULO\ RU H[FOXVLYHO\ FRPPXWHU SRSXODWLRQV RI FRXUVH PDQ\ DOVR HQUROO LQ FROOHJHV

PAGE 20

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fV VDPSOH LQFOXGLQJ XQLYHUVLWLHV DQG FROOHJHV SXEOLF DQG SULYDWH VFKRROV WZR\HDU DQG IRXU \HDU SURJUDPV DQG 3URWHVWDQW DQG &DWKROLF LQVWLWXWLRQV 2WKHU UHVHDUFKHUV KDYH GHPRQVWUDWHG VLPLODU GLIIHUHQFHV WKRXJK QRW ZLWK DEVROXWH FRQVLVWHQF\ *UDII DQG &RROH\ f DVVHVVHG GLIIHUHQFHV EHWZHHQ GRUPLWRU\ UHVLGHQWV DQG FRPPXWHU VWXGHQWV OLYLQJ DW KRPHf XVLQJ WKH &ROOHJH ,QYHQWRU\ RI $FDGHPLF

PAGE 21

$GMXVWPHQW %RURZ f $W WKH FRQFOXVLRQ RI WKH ILUVW VHPHVWHU RI WKHLU ILUVW \HDU WKH WZR JURXSV GLG QRW GLIIHU VLJQLILFDQWO\ RQ VFDOH PHDVXUHV RI VWXG\ KDELWV LQWHUSHUVRQDO UHODWLRQVKLSV ZLWK IDFXOW\ DQG SHHUV RU SHUVRQDO HIILFLHQF\ WLPH PDQDJHPHQWf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f IRXQG IHZ VLJQLILFDQW SHUVRQDOLW\ GLIIHUHQFHV RQ WKH (GZDUGV 3HUVRQDO 3UHIHUHQFH 6FKHGXOH f EHWZHHQ KLJK VFKRRO VHQLRUV SODQQLQJ WR OLYH RQ FDPSXV GXULQJ WKHLU IUHVKPDQ \HDU DQG WKRVH SODQQLQJ WR FRPPXWH IURP KRPH ,Q IDFW WKH PRVW SRZHUIXO SUHGLFWRU RI VWXGHQWVf GHFLVLRQV ZDV QRW D SHUVRQDOLW\ WUDLW EXW UDWKHU WKH VRFLRHFRQRPLF VWDWXV RI WKHLU IDPLO\ RI RULJLQ &RPPXWHUV VWXGHQWV GLG VKRZ JUHDWHU QHHGV IRU DXWRQRP\ DQG GRPLQDQFH ZKLOH UHVLGHQWLDO VWXGHQWV VKRZHG JUHDWHU QHHGV IRU FKDQJH DQG DJJUHVVLRQ +RZHYHU WKH LPSRUWDQFH RI WKHVH SHUVRQDOLW\ GLIIHUHQFHV LV TXHVWLRQDEOH JLYHQ WKH YHU\ VPDOO PDJQLWXGH RI WKHLU LPSDFW *HRUJHfV VWDWLVWLFDO DQDO\VLV LV UHSRUWHG UDWKHU WHOHJUDSKLFDOO\ EXW KLV UHVHDUFK QRQHWKHOHVV PDOHHV FOHDU WKDW WKH SUHGLFWLYH XWLOLW\ RI WKH PRGHO LV ORZ $Q DJJUHJDWH VWHSZLVH PXOWLSOH UHJUHVVLRQ SURFHGXUH LQ ZKLFK IDPLOLDO

PAGE 22

VRFLRHFRQRPLF VWDWXV DFFRXQWHG IRU WKH OLRQfV VKDUH RI WKH YDULDQFH H[SODLQHG RQO\ DERXW SHUFHQW RI WKH YDULDWLRQ LQ UHVLGHQWLDO FKRLFH ,Q D VLPLODU VWXG\ :HOW\ f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f LV D FULWLFDO GHYHORSPHQWDO IDFWRU 0RUH UHFHQWO\ :LOVRQ $QGHUVRQ DQG )OHPLQJ f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t 0DORQH f :LOVRQ DQG FROOHDJXHV GHPRQVWUDWHG WKDW ILUVW\HDU FROOHJH FRPPXWHU VWXGHQWV KDG VLJQLILFDQWO\ KLJKHU IXVLRQ VFRUHV WKDQ WKRVH RI GRUPLWRU\ UHVLGHQWV WKLV WUHQG

PAGE 23

ZDV QRW REVHUYHG KRZHYHU LQ PRUH DGYDQFHG VWXGHQWV 7KLV VWXG\ DOVR PHDVXUHG PRUH JHQHUDO SV\FKRORJLFDO DGMXVWPHQW XVLQJ WKH &ROOHJH 0DODGMXVWPHQW 6FDOH 0W .OHLQPXQW] f RI WKH 0LQQHVRWD 0XOWLSKDVLF 3HUVRQDOLW\ ,QYHQWRU\ +DWKDZD\ t 0F.LQOH\ f 6WXGHQWV OLYLQJ ZLWK WKHLU SDUHQWV UHSRUWHG JUHDWHU OHYHOV RI PDODGMXVWPHQW WKDQ RQ FDPSXV UHVLGHQWV UHJDUGOHVV RI WKHLU \HDU LQ VFKRRO )LQDOO\ 3DVFDUHOOD (GLVRQ 1RUD +DJHGRP DQG 7HUHQ]LQL f IRXQG LQ D ODUJH VFDOH FRUUHODWLRQDO VWXG\ WKDW RQFDPSXV UHVLGHQFH ZDV DQ LPSRUWDQW SUHGLFWRU RI RSHQQHVV WR GLYHUVLW\ DQG FKDOOHQJH DPRQJ ILUVW\HDU FROOHJH VWXGHQWV &RQWUROOLQJ IRU WKH FRQWULEXWLRQ RI PXOWLSOH RWKHU SUHGLFWRUV LQFOXGLQJ GHPRJUDSKLF YDULDEOHV LQVWLWXWLRQDO HQYLURQPHQW VRFLDO OLIH DQG DFDGHPLF H[SHULHQFHV 3DVFDUHOOD DQG FROOHDJXHV IRXQG WKDW RQFDPSXV UHVLGHQFH ZDV D VLJQLILFDQW SUHGLFWRU RI VWXGHQWVf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fV DELOLW\ WR GHYHORS D ZHOOGHILQHG H[WUDIDPLOLDO LGHQWLW\f :KDW RI WKH JURZLQJ QXPEHU RI FRPPXWHUV FKRRVLQJ WR OLYH RIIFDPSXV LQ SULYDWH KRXVLQJ DZD\ IURP IDPLO\" 7KHVH VWXGHQWV PD\ H[SHULHQFH GLIILFXOWLHV VROHO\ DV D IXQFWLRQ RI WKHLU UHODWLYH LVRODWLRQ IURP WKH FDPSXV

PAGE 24

FRPPXQLW\ $UH WKH SV\FKRORJLFDO FRUUHODWHV RI FRPPXWHU VWDWXV REVHUYDEOH LQGHSHQGHQWO\ RI VWXGHQWVf UHODWLRQVKLSV ZLWK WKHLU IDPLOLHV" 6FDQW VWXG\ RI WKLV JURXS RI VWXGHQWV LV UHSRUWHG LQ WKH OLWHUDWXUH +RZHYHU WKH VWUHVVIXO FRQVHTXHQFHV RI FRPPXWLQJ KDYH EHHQ REVHUYHG LQ RWKHU VHWWLQJV DQG ZLWK RWKHU SRSXODWLRQV )RU H[DPSOH 1RYDFR DQG FROOHDJXHV f KDYH FRQGXFWHG DQ RQJRLQJ UHVHDUFK SURJUDP GHPRQVWUDWLQJ WKH GHOHWHULRXV HIIHFWV RI REMHFWLYH DQG VXEMHFWLYH LPSHGDQFHV HQFRXQWHUHG E\ FRPPXWHUV ZKR GULYH GDLO\ WR DQG IURP ZRUN 7KH QHJDWLYH LPSDFW RI WKHVH LPSHGDQFHV LV HYLGHQW LQ WHUPV RI FRPPXWHUVf QHJDWLYH PRRG DW KRPH PHDVXUHG XVLQJ D VKRUW VHPDQWLF GLIIHUHQWLDO VFDOH DQG G\VSKRULD PHDVXUHG XVLQJ D VXEVHW RI LWHPV IURP WKH *OREDO 6WUHVV 6FDOH &RKHQ .DPDUFN t 0HUPHOVWHLQ f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

PAGE 25

QDWXUH RI DGMXVWPHQW D FRQFHSW ZKLFK FRQQRWHV PXOWLSOH GRPDLQV RI VWXGHQW ZHOOEHLQJ +RZHYHU H[WDQW VKRUWFRPLQJV LQ WKH PHDVXUHPHQW DQG FRQFHSWXDOL]DWLRQ RI DGMXVWPHQW OLPLW RXU PLGHUVWDQGLQJ RI HQYLURQPHQWDO LPSDFW 3V\FKRORJLFDO DGMXVWPHQW LV DQ LPSRUWDQW FRPSRQHQW RI FRPSUHKHQVLYH DGMXVWPHQW EXW SV\FKRORJLFDO PHDVXUHPHQW SUREDEO\ KDV QRW EHHQ DGHTXDWHO\ RSHUDWLRQDOL]HG LQ WKH VWXGLHV UHYLHZHG )LUVW PDQ\ RI WKH PHDVXUHV DUH QRW ZHOOYDOLGDWHG FOLQLFDOO\ EHFDXVH WKHLU SULPDU\ DSSOLFDWLRQ KDV EHHQ DV UHVHDUFK VFDOHV HJ WKH *OREDO 6WUHVV 6FDOHf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f WHQG WR IRFXV RQ QDUURZO\GHILQHG FULWHULRQ YDULDEOHV UDWKHU WKDQ RQ WKH W\SLFDO UDQJH RI PHQWDO KHDOWK SUREOHPV VHHQ LQ D FROOHJH SRSXODWLRQ $ EURDGEDVHG ZHOOYDOLGDWHG FOLQLFDO PHDVXUH RI SV\FKRORJLFDO DGMXVWPHQW ZRXOG SURYLGH D PRUH XVHIXO PHDVXUH RI UHVLGHQWLDO LPSDFW 2QO\ RQH RI WKH UHYLHZHG VWXGLHV :LOVRQ $QGHUVRQ t )OHPLQJ f KDV HPSOR\HG VXFK D JHQHUDO FOLQLFDO PHDVXUH WKH &ROOHJH 0DODGMXVWPHQW 6FDOH .OHLQPXQW] f RI WKH 003, 7KH &ROOHJH

PAGE 26

0DODGMXVWPHQW 6FDOH 0Wf LV D LWHP VXSSOHPHQWDU\ VFDOH HPEHGGHG LQ WKH RULJLQDO 003, +DWKDZD\ t 0F.LQOH\ f DQG UHWDLQHG LQ WKH UHYLVHG 0LQQHVRWD 0XOWLSKDVLF 3HUVRQDOLW\ ,QYHQWRU\ %XWFKHU 'DKOVWURP *UDKDP 7HOOHJHQ t .UDHPPHU f 7KH VFDOH ZDV GHYHORSHG E\ .OHLQPXQW] f YLD LWHP DQDO\VLV RI WKH RULJLQDO 003, WR GLIIHUHQWLDWH FROOHJH VWXGHQWV VHHNLQJ SV\FKRWKHUDS\ IURP WKH JHQHUDO VWXGHQW SRSXODWLRQ 7KH LWHPV WDS GLYHUVH LVVXHV LQFOXGLQJ SHUFHLYHG LQHIIHFWXDOQHVV GLPLQLVKHG LQWHUHVW SURFUDVWLQDWLRQ OLIH VWUDLQ DQG DQ[LHW\ (IIRUWV WR GHYHORS FULWHULRQ FXWRII VFRUHV KDYH EHHQ SUREOHPDWLF .OHLQPXQW] .XF]OFD t +DQGDO f 7KH VFDOH LV QRW D SDUWLFXODUO\ JRRG SUHGLFWRU RI SRWHQWLDO SV\FKRORJLFDO GLIILFXOWLHV 3DUNHU 'DKOVWURP :HOVK t 'DKOVWURP f EXW KDV XWLOLW\ LQ WHUPV RI LGHQWLI\LQJ OHYHOV RI FXUUHQW PDODGMXVWPHQW DPRQJ VWXGHQWV LQ D FROOHJH VHWWLQJ *UDKDP f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f WKDW VWXGHQWV H[SHULHQFH LQ FROOHJH 8QWLO UHFHQWO\ D FRPSUHKHQVLYH LQVWUXPHQW WR PHDVXUH SV\FKRORJLFDO SUREOHPV RI FROOHJH VWXGHQWV KDV EHHQ XQDYDLODEOH 7KH 003, LV FHUWDLQO\ D SRWHQWLDO FDQGLGDWH EXW LW ZDV GHVLJQHG IRU SHUVRQV H[SHULHQFLQJ D JUHDWHU GHJUHH RI SDWKRORJ\ WKDQ LV W\SLFDO IRU FROOHJH FRXQVHOLQJ FHQWHUV :KHQ XVHG ZLWK D OHVV GLVWXUEHG SRSXODWLRQ WKH SV\FKLDWULF 7KH RULJLQDO 003, +DWKDZD\ t 0F.LQOH\ f 0W VFDOH FRQWDLQHG LWHPV

PAGE 27

QRUPV RI WKH 003, WHQG WR H[DJJHUDWH LQGLYLGXDOVf OHYHO RI SV\FKRSDWKRORJ\ 0RUHRYHU WKH OHQJWK RI DGPLQLVWUDWLRQ UHTXLUHG IRU D IXOO 003, FDQ EH QHDUO\ WZR KRXUV PDNLQJ WKH LQVWUXPHQW LPSUDFWLFDO IRU D WLPHOLPLWHG GDWD FROOHFWLRQ 7KH &DOLIRUQLD 3V\FKRORJLFDO ,QYHQWRU\ &3, *RXJK f LV DQRWKHU SRWHQWLDO FDQGLGDWH DQG KDV EHHQ ZLGHO\XVHG ZLWK WKH GHPRJUDSKLF JURXS WDUJHWHG LQ WKH FXUUHQW VWXG\ ,Q IDFW &3, QRUPDWLYH GDWD DUH PRUH DSSURSULDWH IRU FROOHJH VWXGHQWV KRZHYHU WKH FRQVWUXFWV PHDVXUHG E\ WKH LQVWUXPHQW DUH PRUH GHVFULSWLYH WKDQ GLDJQRVWLF $ PRUH UHFHQW LQVWUXPHQW WKH &ROOHJH $GMXVWPHQW 6FDOHV &$6 $QWRQ t 5HHG f VHHPV D EHWWHU FDQGLGDWH IRU UHVHDUFK ZLWK FROOHJH SRSXODWLRQV 7KH &$6 LV D LWHP VFUHHQLQJ LQVWUXPHQW GHVLJQHG WR LGHQWLI\ DQG FDWHJRUL]H W\SHV RI SV\FKRORJLFDO PDODGMXVWPHQW SUHVHQWHG E\ VWXGHQWV DW XQLYHUVLW\ FRXQVHOLQJ FHQWHUV 7KH VFDOHV ZHUH GHYHORSHG DQG QRUPHG VSHFLILFDOO\ IRU FROOHJH SRSXODWLRQV 7KH &$6 FRQWHQW DUHDV ZHUH VHOHFWHG RQ WKH EDVLV RI D SULQFLSDO FRPSRQHQWV DQDO\VLV RI DQ LQWDNH SUREOHP FKHFNOLVW DW D FROOHJH FRXQVHOLQJ FHQWHU +LFNV 5HHG t $QWRQ FLWHG LQ PDQXDOf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t 5HHG f FRQWDLQV D IXOO GHVFULSWLRQ RI WKH LQLWLDO YDOLGLW\ VWXGLHV ,QWHUQDO FRQVLVWHQF\

PAGE 28

UHOLDELOLW\ UDQJHG IURP WR IRU WKH FRPSRQHQW VFDOHV $QWRQ DQG 5HHG DOVR SURYLGH SUHOLPLQDU\ FRQYHUJHQW DQG GLVFULPLQDQW YDOLGLW\ GDWD $OWKRXJK D UHODWLYHO\ QHZ LQVWUXPHQW WKH &$6 KDV EHHQ XVHG LQ VHYHUDO UHFHQW VWXGLHV RI FROOHJH DJH SRSXODWLRQV &KDQGOHU t *DOODJKHU +HSSQHU HW DO 6WUHHW .URPUH\ 5HHG t $QWRQ 7XUQHU 9DOWLHUUD 7DONHQ 0LOOHU t 'H$QGD f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f :KDW IROORZV LV D UHYLHZ RI HPSLULFDO UHVHDUFK RQ WKH HQYLURQPHQWDO FKDUDFWHULVWLFV RI KRXVLQJ ZKLFK DUH SRWHQWLDOO\ UHOHYDQW WR WKH SV\FKRORJLFDO ZHOOEHLQJ RI FROOHJH VWXGHQWV

PAGE 29

:LQGRZV (DUO\ OLWHUDWXUH LQ WKLV DUHD VXJJHVWV WKDW ZLQGRZV SDUWLFXODUO\ WKRVH WKDW DIIRUG D YLHZ RI QDWXUDO ODQGVFDSH HOHPHQWV KDYH D GUDPDWLF SRVLWLYH LPSDFW RQ ZHOOEHLQJ 8OULFK f GHPRQVWUDWHG WKDW WKH EHQHILFLDO LPSDFW RI QDWXUDO VFHQHV FDQ EH PHDVXUHG LQ WHUPV RI SV\FKRSK\VLRORJLFDO FRUUHODWHV RI UHOD[DWLRQ VXFK DV UHVSLUDWLRQ UDWH KHDUW UDWH DQG JDOYDQLF VNLQ UHVSRQVH 6XEVHTXHQWO\ 8OULFK f GHPRQVWUDWHG WKDW ZLQGRZ YLHZV RI QDWXUH SRVLWLYHO\ LQIOXHQFH WKH UHFRYHU\ RI VXUJLFDO SDWLHQWV 3DWLHQWV ZKRVH KRVSLWDO URRPV DIIRUGHG YLHZV RI QDWXUH VFHQHV HJ ZDWHU DQG GHFLGXRXV WUHHVf KDG PRUH SRVLWLYH SRVW VXUJLFDO SURJQRVLV DV PHDVXUHG E\ D QXPEHU RI PHDVXUHV LQFOXGLQJ UHFRYHU\ WLPH QHHG IRU PHGLFDWLRQ DQG UHSRUW RI SDLQ 0RUH UHFHQW UHVHDUFK VHH 6XQGVWURP %HOO %XVE\ t $GDPV IRU D UHYLHZf VXJJHVWV WKDW WKH LPSDFW RI ZLQGRZV LV PRUH FRPSOH[ DQG LV PHGLDWHG E\ VRFLDO FRQWH[WXDO DQG HQYLURQPHQWDO YDULDEOHV )RU H[DPSOH %XWOHU DQG %LQHU f IRXQG WKDW VWXGHQWV GLG QRW SUHIHU ZLQGRZ YLHZV LQ VSDFHV ZKHUH WKH\ PLJKW SURYLGH D IXQFWLRQDO LPSHGLPHQW VXFK DV FRPSXWHU ZRUNURRPV 3UHYLRXV ZRUN LQ WKLV DUHD UDLVHV WKH SRVVLELOLW\ WKDW WKH SUHVHQFH RI ZLQGRZV ZLOO LQIOXHQFH ERWK VWXGHQWVn UDWLQJV RI UHVLGHQWLDO VDWLVIDFWLRQ DQG DVVRFLDWHG SV\FKRORJLFDO DGMXVWPHQW 1DWXUDO /DQGVFDSH (OHPHQWV 6WHSKHQ DQG 5DFKHO .DSODQ KDYH SXEOLVKHG GHFDGHV RI UHVHDUFK RQ WKH SV\FKRORJLFDO EHQHILWV RI QDWXUH 7KHLU WKHRU\ SRVLWV WKDW QDWXUDO HQYLURQPHQWV DUH SUHIHUUHG EHFDXVH WKH\ IDFLOLWDWH UHVWRUDWLRQ RI DWWHQWLRQDO FDSDFLW\ IDWLJXHG E\ WKH VXVWDLQHG IRFXV RIWHQ UHTXLUHG E\ WKH P\ULDG FRPSHWLQJ VWLPXOL RI WKH PRGHP ZRUOG .DSODQ t .DSODQ f 7KH QHJDWLYH LPSDFW RI VHQVRU\ RYHUORDG LQ PRGHUQ XUEDQ HQYLURQPHQWVf§VRFLDOO\

PAGE 30

DQG SV\FKRORJLFDOO\f§KDV EHHQ LGHQWLILHG DV D PDMRU TXDOLW\ RI OLIH LVVXH 0LOJUDUQ .UXSDW f 1DWXUDO HQYLURQPHQWV LQ FRQWUDVW HOLFLW HIIRUWOHVV DWWHQWLRQ R[ IDVFLQDWLRQ SURFHVVHV FHQWUDO WR WKH .DSODQVf WKHRU\ 7KDW LV QDWXUDO ODQGVFDSH HOHPHQWV SURPRWH WKH UHFRYHU\ RI DWWHQWLRQ WKURXJK WKH HIIRUWOHVV HQJDJHPHQW RI VHQVRU\ V\VWHPV UHVXOWLQJ LQ DQ H[SHULHQFH ERWK SOHDVXUDEOH DQG UHVWRUDWLYH 7KLV UHVWRUDWLYH H[SHULHQFH KDV WDQJLEOH LPSDFW RQ SV\FKRORJLFDO DQG SK\VLRORJLFDO ZHOOQHVV 2Q WKH SK\VLRORJLFDO OHYHO QDWXUDO HQYLURQPHQWV SURPRWH VWUHVV UHGXFWLRQ WKURXJK VWLPXODWLRQ RI WKH SDUDV\PSDWKHWLF QHUYRXV V\VWHP 8OULFK HW DO f 7KH FDOPLQJ HIIHFWV RI H[SRVXUH WR QDWXUDO VFHQHV KDYH EHHQ GRFXPHQWHG UHSHDWHGO\ HJ 8OULFK f 1DWXUDO ODQGVFDSHV HVSHFLDOO\ WKRVH LQFOXGLQJ ZDWHU DQG ELRPDWWHU DSSHDU WR UHGXFH EORRG SUHVVXUH JDOYDQLF VNLQ UHVSRQVH UHVSLUDWLRQ UDWH DQG VHOIUHSRUW RI VWUHVV $GGLWLRQDO HYLGHQFH 8OULFK f PHQWLRQHG LQ WKH SUHYLRXV VHFWLRQ VXJJHVWV WKDW QDWXUDO YLHZV SRVLWLYHO\ LQIOXHQFH WKH UHFRYHU\ RI SRVWVXUJLFDO SDWLHQWV :KLFK HOHPHQWV RI WKH QDWXUDO ODQGVFDSH DUH PRVW LPSRUWDQW" $ XVHIXO GLVWLQFWLRQ EHWZHHQ FRQILJXUDO HOHPHQWV DQG SULPDU\ FRQWHQW RI ODQGVFDSH FODULILHV WKH TXHVWLRQ 7KH IRUPHU UHIHUV WR WKH ZD\ LQ ZKLFK REMHFWV DUH DUUDQJHG LQ WKH VWLPXOXV DUUD\ 5HVHDUFK KDV VKRZQ WKDW ODQGVFDSHV WKDW SURYLGH D VHQVH RI FRKHUHQFH KDQJLQJ WRJHWKHUf DQG P\VWHU\ WKH SURPLVH RI QHZ LQIRUPDWLRQ WR EH JDLQHG E\ H[SORUDWLRQf DUH HVSHFLDOO\ SUHIHUUHG HJ &DPSEHOO +HU]RJ .DSODQ t .DSODQ f 3ULPDU\ FRQWHQW LQFOXGHV WKH VSHFLILF REMHFWV SUHVHQW LQ D JLYHQ ODQGVFDSH 5HVHDUFK KDV FRQVLVWHQWO\ LQGLFDWHG WKDW KXPDQV SUHIHU ERWK JUHHQHU\ SDUWLFXODUO\ WHQGHG QDWXUH LH PDQLFXUHG JDUGHQVf DQG ZDWHU VFHQHV

PAGE 31

&URZGLQJ 7ZR GHFDGHV RI VWXG\ KDYH GRFXPHQWHG WKH GHOHWHULRXV HIIHFWV RI UHVLGHQWLDO RYHUFURZGLQJ RQ WKH SV\FKRORJLFDO ZHOOEHLQJ RI GZHOOHUV $ QXPEHU RI VWXGLHV KDYH GHPRQVWUDWHG WKH DVVRFLDWLRQ RI FURZGLQJ ZLWK UHVLGHQWLDO GLVVDWLVIDFWLRQ VHH .UXSDW 6XQGVWURP %HOO %XVE\ t $VPXV f 7KLV GLVVDWLVIDFWLRQ LV DVVRFLDWHG ZLWK LQFUHDVHG OHYHOV RI SV\FKRORJLFDO VWUHVV H[SHULHQFHG E\ SHUVRQV OLYLQJ LQ VXFK FRQGLWLRQV 0RUHRYHU WKHUH LV FRQVLGHUDEOH WKHRUHWLFDO DQG HPSLULFDO HYLGHQFH WKDW FURZGLQJ QHJDWLYHO\ LPSDFWV ZLOOLQJQHVV WR RIIHU DQG DFFHSW VRFLDO VXSSRUW 0LOJUDP f LQ DQ DQDO\VLV RI WKH H[SHULHQFH RI XUEDQLWHV VXJJHVWV WKDW WKLV HIIHFW LV D IXQFWLRQ RI RYHUORDG RQ LQGLYLGXDOVn VRFLDO DQG FRJQLWLYH FDSDFLWLHV WKH UHVXOW LV D VRFLDO ZLWKGUDZDO WR PDQDJH LQSXWV WR DQ RYHUWD[HG VHQVRU\ V\VWHP ,Q D VWXG\ RI FROOHJH VWXGHQWV /HSRUH (YDQV DQG 6FKQHLGHU f GHPRQVWUDWHG WKDW SHUVRQV OLYLQJ LQ FURZGHG HQYLURQPHQWV H[SHULHQFH JUHDWHU SV\FKRORJLFDO GLVWUHVV HYHQ ZKHQ FRQWUROOLQJ IRU OHYHOV RI GLVWUHVV SULRU WR WKHLU FXUUHQW OLYLQJ DUUDQJHPHQWV (YDQV DQG /HSRUH f IRXQG WKDW FROOHJH VWXGHQWV IURP FURZGHG UHVLGHQFHV ZHUH OHVV OLNHO\ WR RIIHU DFFHSW RU SHUFHLYH VRFLDO VXSSRUW LQ D ODERUDWRU\ H[SHULPHQW 7KH UREXVWQHVV RI FURZGLQJ HIIHFWV XQGHUVFRUHV WKHLU UHOHYDQFH IRU WKH SURSRVHG VWXG\ D PHDVXUH RI UHVLGHQWLDO SRSXODWLRQ GHQVLW\ VKRXOG EH LQFOXGHG DV D SUHGLFWRU YDULDEOH 1RLVH 7KH GHWULPHQWDO LPSDFW RI QRLVH KDV EHHQ GHPRQVWUDWHG LQ D YDULHW\ RI FRQWH[WV LQFOXGLQJ QHLJKERUKRRGV /HY\/HER\HU t 1DWXUHO f DQG VKRSSLQJ PDOOV +RSNLQV f 7KH PRGDO LQYHVWLJDWLRQ RI DPELHQW QRLVH KDV RSHUDWLRQDOL]HG LPSDFW LQ WHUPV RI WDVN SHUIRUPDQFH RU VHOIUHSRUW RI DQQR\DQFH 7KXV H[DPLQDWLRQ RI HIIHFWV LQ WHUPV RI

PAGE 32

SV\FKRORJLFDO DGMXVWPHQW LV D VRPHZKDW QRYHO DSSURDFK $Q REMHFWLYH PHDVXUH RI GHFLEHO OHYHO LQ KRXVLQJ HQYLURQPHQWV LV EH\RQG WKH ORJLVWLFDO VFRSH RI WKH SURSRVHG VWXG\ +RZHYHU LQFRUSRUDWLQJ VWXGHQWVn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f DQG WKH &ROOHJH $GMXVWPHQW 6FDOHV &$6 $QWRQ t 5HHG f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

PAGE 33

7KH FXUUHQW VWXG\ H[DPLQHV WZR SULPDU\ DVSHFWV RI WKH UHODWLRQVKLS RI UHVLGHQWLDO HQYLURQPHQW ZLWK SV\FKRORJLFDO DGMXVWPHQW RI FROOHJH VWXGHQWV )LUVW WKLV VWXG\ ZLOO SURYLGH WKH RSSRUWXQLW\ WR DVVHVV WKH UHODWLYH LPSRUWDQFH RI UHVLGHQWLDO FURZGLQJ UHVLGHQWLDO ORFDWLRQ QRLVH OHYHO GLVWDQFH IURP FDPSXV DQG DFFHVV WR ZLQGRZV LQ SUHGLFWLQJ FXUUHQW OHYHOV RI SV\FKRORJLFDO DGMXVWPHQW 0\ GHFLVLRQ WR LQFRUSRUDWH WKHVH SUHGLFWRU YDULDEOHV DQG FRQVHTXHQWO\ WR H[FOXGH RWKHUV RI SRWHQWLDO LPSRUWDQFHf LV D IXQFWLRQ ERWK RI SUDJPDWLVP DQG RI DWWHQWLRQ WR WKH H[LVWLQJ OLWHUDWXUH RQ UHVLGHQWLDO HQYLURQPHQWV $ OLPLWHG QXPEHU RI YDULDEOHV LV QHFHVVDU\ WR HQVXUH WKH IHDVLELOLW\ RI WKLV VWXG\ 0RUHRYHU WKHVH SDUWLFXODU YDULDEOHV ZHUH FKRVHQ LQ SDUW EHFDXVH WKH\ DUH DPHQDEOH WR TXDQWLWDWLYH DQDO\VLV 0RUH DEVWUDFW SKHQRPHQD HJ VHQVH RI SODFH DUFKLWHFWXUDO FRKHUHQFH DQG WKH OLNHf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

PAGE 34

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

PAGE 35

5HSRUWHG OHYHO RI QRLVH VKRXOG EH LQYHUVHO\ UHODWHG ERWK WR RYHUDOO OHYHOV RI SV\FKRORJLFDO DGMXVWPHQW DQG VDWLVIDFWLRQ ZLWK OLYLQJ HQYLURQPHQW (OHPHQWV RI QDWXUDO ODQGVFDSH YLVLEOH IURP UHVLGHQFHV VKRXOG FRUUHODWH SRVLWLYHO\ ZLWK DGMXVWPHQW WKDW LV WKH SUHVHQFH RI DGHTXDWH OLJKW ZDWHU WUHHV DQG JUDVV LQ UHVLGHQWLDO ZLQGRZ YLVWDV VKRXOG EH DVVRFLDWHG ZLWK EHWWHU RYHUDOO OHYHOV RI SV\FKRORJLFDO DGMXVWPHQW

PAGE 36

&+$37(5 0(7+2' 3DUWLFLSDQWV 3DUWLFLSDQWV ZHUH XQGHUJUDGXDWH YROXQWHHUV IURP SV\FKRORJ\ FODVVHV DW WKH 8QLYHUVLW\ RI )ORULGD D ODUJH VWDWH XQLYHUVLW\ ZLWK DSSUR[LPDWHO\ VWXGHQWVf WKH 8QLYHUVLW\ RI :\RPLQJ D VPDOO VWDWH XQLYHUVLW\ ZLWK DSSUR[LPDWHO\ VWXGHQWVf DQG 1HZ &ROOHJH RI WKH 8QLYHUVLW\ RI 6RXWK )ORULGD D SULPDULO\ UHVLGHQWLDO OLEHUDO DUWV KRQRUV FROOHJH ZLWK DSSUR[LPDWHO\ VWXGHQWVf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bf ZHUH VWXGHQWV DW WKH 8QLYHUVLW\ RI )ORULGD 7KLUW\ILYH bf ZHUH IURP 1HZ &ROOHJH RI WKH 8QLYHUVLW\ RI 6RXWK )ORULGD WKH UHPDLQLQJ VWXGHQWV bf ZHUH IURP WKH 8QLYHUVLW\ RI :\RPLQJ

PAGE 37

(WKQLFLW\ 2QH KXQGUHG IRUW\VL[ SDUWLFLSDQWV bf UHSRUWHG ZKLWHQRQ+LVSDQLF HWKQLFLW\ 7KH VHFRQG ODUJHVW JURXS VWXGHQWV RU bf HQGRUVHG $VLDQ3DFLILF ,VODQGHU 1LQH +LVSDQLF/DWLQRDf VWXGHQWV FRQVWLWXWHG b RI WKH VDPSOH )RXU SHUFHQW Q f VWXGHQWV ZHUH $IULFDQ$PHULFDQ )RXU VWXGHQWV bf UHSRUWHG HWKQLFLW\ DV fRWKHUf 7KUHH VWXGHQWV GHFOLQHG WR LQGLFDWH HWKQLF EDFNJURXQG *HQGHU 6L[W\VHYHQ SHUFHQW Q f RI UHVSRQGHQWV ZHUH ZRPHQ 0HQ FRPSULVHG b Q f RI WKH VDPSOH $JH 5HSRUWHG DJH UDQJHG IURP WR \HDUV IRU WKH SDUWLFLSDQWV ZKR SURYLGHG LQIRUPDWLRQ 0HDQ DJH ZDV VWDQGDUG GHYLDWLRQ ZDV
PAGE 38

DVSHFWV RI KRXVLQJ HQYLURQPHQW UHVLGHQWLDO VDWLVIDFWLRQ \HDU LQ FROOHJH DQG SV\FKRORJLFDO WUHDWPHQW KLVWRU\ 7KH TXHVWLRQQDLUH LV LQFOXGHG LQ $SSHQGL[ % &ULWHULRQ PHDVXUHV RI DGMXVWPHQW LQFOXGHG WKH LWHP &ROOHJH 0DODGMXVWPHQW 6FDOH 0W .OHLQPXQW] f RI WKH 0LQQHVRWD 0XOWLSKDVLF 3HUVRQDOLW\ ,QGLFDWRU 003, %XWFKHU HW DK f $ LWHP 0W ZDV GHYHORSHG IRU WKH RULJLQDO 003, +DWKDZD\ DQG 0F.LQOH\ f D LWHP VFDOH ZDV UHWDLQHG LQ WKH UHYLVLRQ $OWKRXJK WKH VFDOH LV W\SLFDOO\ DGPLQLVWHUHG LQ HPEHGGHG IRUP LH DV SDUW RI WKH IXOO LWHP 003, .OHLQPXQW] f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t .HDQH LQ SUHVVf PRUHRYHU .XF]ND DQG +DQGDO f SURYLGH YDOLGDWLRQDO GDWD IRU WKH VWDQGDORQH 0W ZLWK UHIHUHQFH WR /DQJHU 6\PSWRP 6XUYH\ /DQJHU f 7KXV WKH XVH RI WKH VWDQGDORQH 0W VFDOH FDQ EH GHIHQGHG RQ ERWK HPSLULFDO DQG SUDJPDWLF JURXQGV 7KH DGGLWLRQDO LWHPV FRPSULVH WKH LWHP / VFDOH DQG WKH LWHP .VFDOH %ULHIO\ WKH IRUPHU LV GHVLJQHG WR LGHQWLI\ SHUVRQV DWWHPSWLQJ WR IDNH JRRG E\ SUHVHQWLQJ WKHPVHOYHV LQ DQ RYHUO\YLUWXRXV OLJKW WKH ODWWHU LV DVVRFLDWHG ZLWK GHIHQVLYHQHVV UHJDUGLQJ WKH SUHVHQFH RI SV\FKRORJLFDO SUREOHPV 7KHVH DUH H[WHQVLYHO\ FRYHUHG LQ WKH 003, OLWHUDWXUH HJ *UDKDP f

PAGE 39

7KH VHFRQG FULWHULRQ PHDVXUH ZDV WKH LWHP &ROOHJH $GMXVWPHQW 6FDOHV &$6 $QWRQ DQG 5HHG f 7KH &$6 GHVFULEHG LQ &KDSWHU LV D UHODWLYHO\ QHZ LQVWUXPHQW GHVLJQHG WR DVVLVW FROOHJH FRXQVHOLQJ FHQWHU SURIHVVLRQDOV LQ VFUHHQLQJ WKH PHQWDO KHDOWK QHHGV RI VWXGHQWV $V VXFK WKH LQVWUXPHQW ZDV QRQQHG RQ D VDPSOH FRPSRVHG SULPDULO\ RI FROOHJH VWXGHQW DQG WKHUHIRUH LV D ORJLFDO FKRLFH IRU XVH LQ WKLV LQYHVWLJDWLRQ $OWKRXJK WKH &$6 LV QRW D GLDJQRVWLF LQVWUXPHQW LW RIIHUV QRUPHG GDWD UHJDUGLQJ WKH W\SH DQG PDJQLWXGH RI D VWXGHQWfV VHOIUHSRUWHG DGMXVWPHQW GLIILFXOWLHV 7KH &$6 RIIHUV UDZ VFDOH VFRUHV DQG KQHDUO\WUDQVIRUPHG 0F&DOOfV 7VFRUHV PHDQ 6' f IRU QLQH DVSHFWV RI FROOHJH VWXGHQW DGMXVWPHQW UDWLRQDOO\ VHOHFWHG RQ WKH EDVLV RI VFUHHQLQJ QHHGV UHSRUWHG E\ FDPSXV PHQWDO KHDOWK SURYLGHUV 7KH &$6 VFDOHV LQFOXGH $Q[LHW\ $1f 'HSUHVVLRQ '3f 6XLFLGDO ,GHDWLRQ 6,f 6XEVWDQFH $EXVH 6$f 6HOIHVWHHP 6(f ,QWHUSHUVRQDO 3UREOHPV ,3f )DPLO\ 3UREOHPV )3f $FDGHPLF 3UREOHPV $3f DQG &DUHHU 3UREOHPV &3f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nV UDWLQJV RI KRXVLQJ

PAGE 40

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fV SUHGLFWLYH YDOLGLW\ KDV EHHQ TXHVWLRQHG LQ WKH OLWHUDWXUH 'DKOVWURP :HOVK t 'DKOVWURP /( f 0W VFRUHV ZHUH UHPRYHG IURP WKH GDWD VHW $ YLVXDO H[DPLQDWLRQ RI WKH GLVWULEXWLRQ RI &$6 VFDOH VFRUHV UHYHDOHG WKDW WKH GLVWULEXWLRQ RI 0F&DOOfV 7VFRUHV DSSUR[LPDWHG QRUPDOLW\ PRUH FORVHO\ WKDQ WKDW RI UDZ VFRUHV WKHUHIRUH 7VFRUHV ZHUH FKRVHQ DV WKH XQLW RI DQDO\VLV LQ WKH FULWHULRQ GDWD VHW 6LQFH WKH UHPDLQLQJ GDWD VHW FRQWDLQHG PXOWLSOH FRQFHSWXDOO\UHODWHG GHSHQGHQW YDULDEOHV LH WKH QLQH &$6 VFDOHV ZKLFK DUH LQWHUFRUUHODWHG $QWRQ t 5HHG f WKH ILUVWOLQH DQDO\WLF SURFHGXUH ZDV D PXOWLYDULDWH DQDO\VLV RI YDULDQFH 0$129$f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

PAGE 41

FKDOOHQJHG E\ +XEHUW\ DQG 0RUULV f ZKR DUJXH WKDW PXOWLYDULDWH DQG XQLYDULDWH WHFKQLTXHV DGGUHVV GLVWLQFW UHVHDUFK TXHVWLRQV 7KH IRUPHU DQDO\VHV DUH DSSURSULDWH WR DGGUHVV RYHUDOO HIIHFWV DQG OHVV GLUHFWO\ WR H[SORUH SDWWHUQV DPRQJ DQG FRQWULEXWLRQV RI RXWFRPH YDULDEOHV WKH PXOWLSOH XQLYDULDWH VWUDWHJ\ LV DSSURSULDWH ZKHQ RXWFRPH YDULDEOHV DUH FRQFHSWXDOO\ GLVWLQFW ZKHQ UHVHDUFK LV H[SORUDWRU\ RU ZKHQ WKH GHSHQGHQW YDULDEOHV RI LQWHUHVW KDYH EHHQ SUHYLRXVO\ VWXGLHG LQ XQLYDULDWH FRQWH[WV ,Q WKLV ODVW FDVH +XEHUW\ DQG 0RUULV f FRQWHQG WKDW 0$129$V PD\ EH XVHG LQ FRQMXQFWLRQ ZLWK $129$V LI WKH DSSURSULDWH DVVXPSWLRQV IRU HDFK DUH PHW ,Q WKH SUHVHQW VWXG\ WKH GHSHQGHQW PHDVXUHV DUH GHVLJQHG WR WDS FRQVWUXFWV HJ GHSUHVVLRQ DQ[LHW\ VXEVWDQFH DEXVHf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f $V LV GHVFULEHG PRUH IXOO\ LQ WKH QH[W FKDSWHU WKH SUHFHGLQJ DQDO\VLV UHYHDOHG VLJQLILFDQW RYHUODS DPRQJ WKH &$6 VFDOHV FDVWLQJ GRXEW XSRQ WKH VWDWXV RI HDFK VFDOH DV D FRQFHSWXDOO\ GLVWLQFW PHDVXUH 6LQFH WKLV UHVXOW LPSOLHV WKDW WKH YDULDWLRQ LQ HDFK VFDOH PD\

PAGE 42

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

PAGE 43

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f 6XLWHVW\OH DFFRPPRGDWLRQV DUH LQFUHDVLQJO\ SRSXODU GRUPLWRU\ GHVLJQV LQ IDFW GRUPLWRULHV FXUUHQWO\ XQGHU FRQVWUXFWLRQ DW 1HZ &ROOHJH ZLOO RIIHU VXLWH VW\OH GRUPLWRULHV E\ IDOO $PRQJ WKH b RI VWXGHQWV UHVLGLQJ LQ RIIFDPSXV KRXVLQJ RQO\ D PLQRULW\ Q O f ZHUH OLYLQJ ZLWK WKHLU IDPLO\ RI RULJLQ 7KH UHPDLQLQJ RII FDPSXV UHVLGHQWV OLYHG DORQH RU ZLWK URRPPDWHV D YHU\ VPDOO QXPEHU RI PDUULHG VWXGHQWV OLYHG ZLWK WKHLU VSRXVHV 7DEOH 7\SHV RI +RXVLQJ 8QLWV 7\SH )UHTXHQF\ b 2QFDPSXV 6LQJOHURRP GRUPLWRU\ 8QLYHUVLW\ DSDUWPHQW 6XLWH PXOWLSOH URRPVf 2WKHU 2IIFDPSXV :LWKRXW SDUHQWVf :LWK SDUHQWVf

PAGE 44

7DEOH VXPPDUL]HV VHOHFWHG HQYLURQPHQWDO IHDWXUHV UHSRUWHG E\ VWXGHQWV 7KH PRGDO VWXGHQW UHSRUWHG RQH RU WZR URRPPDWHV DOWKRXJK RWKHU OLYLQJ DUUDQJHPHQWV DUH UHSUHVHQWHG LQ WKH VDPSOH 0HDQ GLVWDQFH IURP FDPSXV ZDV PLOHV LQ DOO FDVHV LQ ZKLFK VWXGHQWV UHVLGHG LQ RQFDPSXV KRXVLQJ D GLVWDQFH RI ]HUR PLOHV ZDV DVVLJQHG 'LVWDQFH IURP FDPSXV YDULHG ZLGHO\ SULPDULO\ EHFDXVH D VPDOO QXPEHU RI SDUWLFLSDQWV LQ WKH 8QLYHUVLW\ RI )ORULGD VDPSOH ZHUH ILUVWWHUP VXPPHU VWXGHQWV OLYLQJ DW KRPH 6WXGHQWV UHSRUWHG DQ DYHUDJH RI ZLQGRZV LQ WKH URRP LQ ZKLFK WKH\ VSHQW WKH PRVW WLPH 7KH UHPDLQLQJ YDULDEOHV VXPPDUL]HG LQ WKLV VHFWLRQ OLJKW QRLVH DQG VDWLVIDFWLRQf ZHUH HDFK UDWHG RQ D VHYHQSRLQW OLNHUW VFDOH 7DEOH (QYLURQPHQWDO &KDUDFWHULVWLFV RI +RXVLQJ 8QLWV &KDUDFWHULVWLF 1 0LQ 0D[ 0HDQ 6' 5RRPPDWHV 'LVWDQFH :LQGRZV /LJKW 1RLVH 6DWLVIDFWLRQ 1RWH &DVHV RI 1 DUH GXH WR PLVVLQJ YDOXHV /LJKW QRLVH DQG VDWLVIDFWLRQ ZHUH UDWHG RQ D SRLQW OLNHUW VFDOH 7KH URRPV LQ ZKLFK VWXGHQWV UHSRUWHG VSHQGLQJ WKH PRVW WLPH DUH VKRZQ LQ 7DEOH 7KH FODVVLILFDWLRQ RI URRPV ZDV GHULYHG IURP SDUWLFLSDQWVf XQVWUXFWXUHG VHOIUHSRUW DQG FDWHJRULHV DUH WKHUHIRUH WHQWDWLYH 1RQHWKHOHVV UHVXOWV LQGLFDWH WKDW WKUHH OLYLQJ VSDFHV ZHUH PRVW XWLOL]HG E\ VWXGHQWV WKHVH URRPV LQ RUGHU RI LPSRUWDQFH DUH EHGURRPV IDPLO\ OLYLQJf URRPV DQG DV DQWLFLSDWHG IRU RQFDPSXV UHVLGHQWV GRUPLWRU\ URRPV 2WKHU W\SHV

PAGE 45

RI URRPV ZHUH FLWHG PXFK OHVV IUHTXHQWO\ D VPDOO QXPEHU RI EODQN RU DPELJXRXV UHVSRQVHV ZHUH SODFHG LQ WKH RWKHUQRW UHSRUWHG FDWHJRU\ 7DEOH 0RVW &RPPRQO\ 8VHG 5RRPV 5RRP 7\SH )UHTXHQF\ b %HGURRP 6WXG\ )DPLO\ RU /LYLQJ 5RRP .LWFKHQ 'RUPLWRU\ 5RRP %DWKURRP 2WKHU1RW 5HSRUWHG 7DEOH VXPPDUL]HV WKH ODQGVFDSH HOHPHQWV WKDW VWXGHQWV UHSRUWHG ZHUH YLVLEOH IURP WKH URRP LQ ZKLFK WKH\ VSHQW WKH PDMRULW\ RI WLPH 7UHHV DQG JUDVV ZHUH WKH PRVW FRPPRQ ODQGVFDSH IHDWXUHV UHSRUWHG E\ b DQG b RI VWXGHQWV UHVSHFWLYHO\ $ VPDOOHU QXPEHU RI VWXGHQWV bf LQGLFDWHG WKDW ZDWHU ZDV YLVLEOH ,Q DGGLWLRQ WKH PDMRULW\ RI VWXGHQWV QRWHG WKH SUHVHQFH RI EXLOW VWUXFWXUHV EXLOGLQJV DQG FRQFUHWHf LQ WKHLU ZLQGRZ YLVWDV 7DEOH 9LVLEOH /DQGVFDSH (OHPHQWV LQ 0RVW &RPPRQO\ 8VHG 5RRP )HDWXUH b 5HSRUWLQJ :DWHU 7UHHV *UDVV 2WKHU %XLOGLQJV &RQFUHWH

PAGE 46

7KH SV\FKRORJLFDO WUHDWPHQW KLVWRU\ RI VWXG\ SDUWLFLSDQWV LV UHSRUWHG LQ 7DEOH $ VXUSULVLQJO\ ODUJH QXPEHU RI VWXGHQWV bf LQGLFDWHG WKDW WKH\ KDG UHFHLYHG VRPH IRUP RI PHQWDO KHDOWK VHUYLFHV SULRU WR HQUROOLQJ DW WKHLU SUHVHQW HGXFDWLRQDO LQVWLWXWLRQ PHQWDO KHDOWK VHUYLFHV ZHUH GHILQHG ZRUN ZLWK D fSV\FKRORJLVW SV\FKLDWULVW RU RWKHU W\SH RI PHQWDO KHDOWK SURIHVVLRQDO IRU D SV\FKRORJLFDO RU SHUVRQDO SUREOHPf $GGLWLRQDOO\ b UHSRUWHG WUHDWPHQW VLQFH EHJLQQLQJ VWXG\ DW WKHLU FXUUHQW FROOHJH RU XQLYHUVLW\ b ZHUH FXUUHQWO\ LQ WUHDWPHQW RU ZHUH SODQQLQJ WR VHHN VHUYLFHV ZLWKLQ WKLUW\ GD\V RI WKH VWXG\ 7DEOH 3V\FKRORJLFDO 7UHDWPHQW +LVWRU\ RI 3DUWLFLSDQWV 7LPH RI 7UHDWPHQW b 3ULRU WR HQWHULQJ FROOHJH 6LQFH HQWHULQJ FROOHJH &XUUHQWO\ LQ WUHDWPHQWD f,QFOXGHV WKRVH SODQQLQJ WR VHHN WUHDWPHQW ZLWKLQ GD\V 7DEOH OLVWV PHDQ WVFRUHV DQG VWDQGDUG GHYLDWLRQV IRU HDFK RI WKH QLQH &ROOHJH $GMXVWPHQW 6FDOHV &$6f VXEVFDOHV $ YLVXDO H[DPLQDWLRQ RI WKLV GDWD VXJJHVWV WKDW WKH SHUIRUPDQFH RI VWXGHQWV LQ WKH FXUUHQW VWXG\ ZDV VLPLODU WR WKDW RI VWXGHQWV LQ WKH &$6 QRUPDWLYH VDPSOH LQ ZKLFK WKH PHDQ WVFRUH DQG VWDQGDUG GHYLDWLRQ IRU HDFK VFDOH ZHUH DQG UHVSHFWLYHO\ 6FDOH WVFRUH PHDQV LQ WKH FXUUHQW VWXG\ UDQJHG IURP 6(f WR 6,f VWDQGDUG GHYLDWLRQV UDQJHG IURP &3f WR 6(f 7KXV WKH FHQWUDO WHQGHQF\ DQG GLVWULEXWLRQ RI VFRUHV LQ WKH SUHVHQW VDPSOH DSSHDU FRPSDUDEOH WR WKRVH SUHYLRXVO\ UHSRUWHG IRU WKH JHQHUDO FROOHJH SRSXODWLRQ

PAGE 47

7DEOH 6XPPDUY RI 0F&DOOfV 7 fVFRUHV RQ &$6 6FDOHV 6FDOH 0HDQ 6' $Q[LHW\ $1f 'HSUHVVLRQ '3f 6XLFLGDO ,GHDWLRQ 6,f 6XEVWDQFH $EXVH 6$f 6HOI (VWHHP 6(f ,QWHUSHUVRQDO 3UREOHPV ,3f )DPLO\ 3UREOHPV )3f &DUHHU 3UREOHPV &3f $FDGHPLF 3UREOHPV $3f 2PQLEXV $QDO\VHV 7KH ILUVW VWDJH RI DQDO\VLV HPSOR\HG DQ RPQLEXV PXOWLYDULDWH DQDO\VLV RI YDULDQFH 0$129$f LQFOXGLQJ SUHGLFWRU YDULDEOHV DV ZHOO DV WKH FULWHULRQ VHW ZKLFK LQFOXGHG DOO QLQH VXEVFDOHV RI WKH &$6 7KH 0$129$ SURFHGXUHV GHWHUPLQH WKH VWDWLVWLFDO VLJQLILFDQFH RI LQGLYLGXDO SUHGLFWRUV ZKHQ FRYDULDWLRQ LQ WKH FULWHULRQ YDULDEOH VHW LV FRQWUROOHG 6LQFH D YLVXDO H[DPLQDWLRQ RI VFRUHV RQ WKH &$6 VXEVFDOHV UHYHDOHG WKDW WKH 0F&DOOfV WVFRUH GLVWULEXWLRQV PRUH FORVHO\ DSSUR[LPDWHG QRQQDOLW\ WKDQ WKRVH RI UDZ VFDOH VFRUHV WVFRUHV DUH XVHG LQ WKH FULWHULRQ YDULDEOH VHW IRU WKLV DQG DOO VXEVHTXHQW DQDO\VHV 1DPHV RI SUHGLFWRU YDULDEOHV DUH DEEUHYLDWHG DV IROORZV 6&+22/ UHSUHVHQWV WKH LQVWLWXWLRQ SUHVHQWO\ DWWHQGHG 8QLYHUVLW\ RI )ORULGD 1HZ &ROOHJH RU 8QLYHUVLW\ RI :\RPLQJf 6(; GHQRWHV UHSRUWHG JHQGHU $*( LV UHSRUWHG DJH LQ \HDUV 7(506 UHSUHVHQWV WKH QXPEHU RI VHPHVWHUV DWWHQGHG DW WKH VWXGHQWfV FXUUHQW LQVWLWXWLRQ 7;35,25 LV D GXPP\ YDULDEOH UHSUHVHQWLQJ SV\FKRWKHUDS\ RU FRXQVHOLQJ SULRU WR HQUROOLQJ LQ WKH VWXGHQWfV SUHVHQW VFKRRO 7;6,1&( DQG 7;12: DUH GXPP\ YDULDEOHV GHQRWLQJ SV\FKRORJLFDO WUHDWPHQW VLQFH HQUROOPHQW RU DW WKH SUHVHQW WLPH UHVSHFWLYHO\ 0$7(6

PAGE 48

UHSUHVHQWV WKH QXPEHU RI URRPPDWHV UHSRUWHG ',67$1&( LV D PHDVXUH RI GLVWDQFH IURP FDPSXV URXQGHG WR WKH QHDUHVW KDOI PLOHf RQFDPSXV UHVLGHQWV UHFHLYHG D VFRUH RI ]HUR RQ WKLV YDULDEOH 3$5(176 LV D GLFKRWRPRXV PHDVXUH LQGLFDWLQJ ZKHWKHU WKH VWXGHQW UHVLGHG ZLWK KLV RU KHU IDPLO\ RI RULJLQ 21B2)) UHIHUV WR ORFDWLRQ RI WKH VWXGHQWfV FXUUHQW UHVLGHQFH RQ RU RIIFDPSXVf :$7(5 *5$66 %8,/',1* DQG &21&5(7( DUH G XPP\ FRGHV UHSUHVHQWLQJ WKH SUHVHQFH RU DEVHQFH RI HDFK ODQGVFDSH IHDWXUH LQ WKH VWXGHQWfV UHVLGHQWLDO ZLQGRZ YLVWD 12,6( DQG /,*+7 DUH SRLQW /LNHUW VFDOH UDWLQJV RI QRLVH DQG OLJKW OHYHOV LQ WKH VWXGHQWfV FXUUHQW UHVLGHQFH 6$7,6 LV D /LNHUW VFDOH UDWLQJ RI UHSRUWHG UHVLGHQWLDO VDWLVIDFWLRQ 0$129$ UHVXOWV IRU DOO SUHGLFWRU YDULDEOHV DUH VXPPDUL]HG LQ 7DEOH ZKLFK LQFOXGHV YDOXHV IRU :LONVf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

PAGE 49

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f VFDOH UHIOHFWV fSK\VLFDO DQG SV\FKRORJLFDO FRUUHODWHV RI DQ[LHW\f $QWRQ t 5HHG S f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n OHYHOV RI DQ[LHW\ ZKLOH WKH SUHVHQFH RI JUDVV DV SUHGLFWHG ZDV DVVRFLDWHG ZLWK UHGXFHG OHYHOV RI UHSRUWHG DQ[LHW\ 7KH 5VTXDUH YDOXH IRU WKLV PRGHO LV WKXV FXUUHQW

PAGE 50

WUHDWPHQW VWDWXV DQG WKH SUHVHQFH RI JUDVV WRJHWKHU DFFRXQW IRU b RI WKH WRWDO YDULDWLRQ LQ $1 VFRUHV 7DEOH 0$129$ 7HVW 6WDWLVWLFV EY 3UHGLFWRU 9DULDEOH /DPEGD ) 1XP ') 'HQ') 3 6&+22/ 6(; $*( 7(506 7;35,25 r 7;6,1&( 7;12: r 21 2)) 0$7(6 rr 12,6( rr /,*+7 f 6$7,6 R R :,1'2:6 :$7(5 *5$66 r 75((6 %8,/',1* &21&5(7( ',67$1&( 3$5(176 6LJQLILFDQW DW OHYHO 6LJQLILFDQW DW OHYHO 9DULDEOH 7DEOH 3UHGLFWLRQ RI $1 6FRUHV 3DUDPHWHU (VWLPDWH 6WG (UURU 3DUWLDO 5 ) 3 ,QWHUFHSW 7;12: *5$66

PAGE 51

'HSUHVVLRQ 7KH 'HSUHVVLRQ '3f VFDOH RI WKH &$6 SXUSRUWV WR PHDVXUH WKH fSK\VLFDO DQG SV\FKRORJLFDO FRUUHODWHV RI GHSUHVVLRQf $QWRQ t 5HHG S f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f PDGH D FRQWULEXWLRQ EH\RQG WKDW RI DJH DQG WUHDWPHQW HIIHFWV 7KLV PRGHO DFFRXQWV IRU b RI WKH YDULDWLRQ RI GHSUHVVLRQ VFRUHV 7DEOH 3UHGLFWLRQ RI '3 6FRUHV 9DULDEOH 3DUDPHWHU (VWLPDWH 6WG (UURU 3DUWLDO 5 ) 3 ,QWHUFHSW $*( 7;6,1&( $QKHGRQLD WKH PDUNHG ORVV RI LQWHUHVW RU SOHDVXUH LQ DFWLYLWLHV SUHYLRXVO\ HQMR\HG LV D NH\ GLDJQRVWLF FULWHULRQ IRU 0DMRU 'HSUHVVLYH 'LVRUGHU $PHULFDQ 3V\FKLDWULF $VVRFLDWLRQ f

PAGE 52

6XLFLGDO ,GHDWLRQ 6XLFLGDO ,GHDWLRQ 6,f VFRUHV DUH LQGLFDWLYH RI VXLFLGDO WKRXJKWV RU VXLFLGDO EHKDYLRUV $QWRQ t 5HHG f UHFRPPHQG WKDW HYHQ PRGHUDWH HOHYDWLRQV VKRXOG VLJQDO WKH QHHG IRU IXUWKHU SV\FKRORJLFDO HYDOXDWLRQ $V VKRZQ LQ 7DEOH \RXQJHU VWXGHQWV UHSRUWHG KLJKHU OHYHOV RI VXLFLGDO LGHDWLRQ $V ZLWK '3 VWXGHQWV ZKR UHSRUWHG SV\FKRORJLFDO WUHDWPHQW VXEVHTXHQW WR HQWHULQJ FROOHJH ZHUH PRUH OLNHO\ WR SURGXFH HOHYDWHG VFRUHV 7RJHWKHU DJH DQG WUHDWPHQW HIIHFW DFFRXQW IRU b RI WKH YDULDWLRQ LQ VXLFLGDO LGHDWLRQ VFRUHV 2QH HQYLURQPHQWDO IHDWXUH JUDVV DSSURDFKHG VLJQLILFDQFH S f DQG ZRXOG KDYH H[SODLQHG DQ DGGLWLRQDO b RI YDULDWLRQ LQ 6, VFRUHV 7DEOH 3UHGLFWLRQ RI 6, 6FRUHV 9DULDEOH 3DUDPHWHU (VWLPDWH 6WG (UURU 3DUWLDO 5 ) 3 ,QWHUFHSW $*( 7;6,1&( *5$66 r $SSURDFKHG VLJQLILFDQFH 6XEVWDQFH $EXVH 7KH 6 $ VFDOH LV GHVLJQHG WR UHIOHFW GLIILFXOWLHV LQ D QXPEHU RI DUHDV QHJDWLYHO\ LPSDFWHG E\ VXEVWDQFH DEXVH LQFOXGLQJ DFDGHPLFV VRFLDO EHKDYLRU DQG UHODWLRQVKLSV 5HJUHVVLRQ PRGHOLQJ RI 6$ VFRUHV LV VXPPDUL]HG LQ 7DEOH :KHQ WKH HIIHFWV RI 7;35,25 DUH DFFRXQWHG IRU QR RWKHU YDULDEOHV KDYH DGGLWLRQDO SUHGLFWLYH SRZHU $OWKRXJK WKLV PRGHO LV VLJQLILFDQW 7;35,25 H[SODLQV RQO\ b RI WKH YDULDWLRQ LQ 6$

PAGE 53

VFRUHV FOHDUO\ LQGLFDWLQJ WKDW IDFWRUV H[WHUQDO WR WKH SUHVHQW VWXG\ DUH PRUH UHOHYDQW WR VXEVWDQFH DEXVH VFRUHV 7DEOH 3UHGLFWLRQ RI 6$ 6FRUHV 9DULDEOH 3DUDPHWHU (VWLPDWH 6WG (UURU 3DUWLDO 5 ) 3 ,QWHUFHSW 7 7;35,25 6HOI (VWHHP 7DEOH VXPPDUL]HV WKH SUHGLFWLRQ RI 6( VFRUHV 7KH 6( VFDOH LV GHVLJQHG WR PHDVXUH JOREDO VHOIHVWHHP +LJK VFRUHUV WHQG WR KDYH SRRU VHOIHVWHHP DQG VHOI FRQILGHQFH ZKLFK DUH UHIOHFWHG LQ WKHLU RZQ RSLQLRQV RI WKHLU DELOLWLHV DFKLHYHPHQWV DQG DWWUDFWLYHQHVV
PAGE 54

,QWHUSHUVRQDO 3UREOHPV 7KH ,3 VFDOH PHDVXUHV fWKH GHJUHH WR ZKLFK WKH VWXGHQW KDV GLIILFXOW\ UHODWLQJ WR RWKHUVf $QWRQ t 5HHG S f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b RI WKH WRWDO YDULDWLRQ LQ ,3 VFRUHV 7DEOH 3UHGLFWLRQ RI ,3 6FRUHV 9DULDEOH 3DUDPHWHU (VWLPDWH 6WG (UURU 3DUWLDO 5 ) 3 ,QWHUFHSW $*( 7;6,1&( )DPLO\ 3UREOHPV 7KH &$6 )3 VFDOH SXUSRUWV WR PHDVXUH D YDULHW\ RI IDPLO\ FRQFHUQV LQFOXGLQJ GLIILFXOW\ ZLWK LQGLYLGXDWLRQ DQG ZRUU\ UHJDUGLQJ IDPLO\ FRQIOLFW $QWRQ t 5HHG f $ PRGHO RI )3 VFRUHV LV SUHVHQWHG LQ 7DEOH ,QWHUHVWLQJO\ WKH SUHVHQFH RI JUDVV LQ ZLQGRZ YLVWDV ZDV DVVRFLDWHG ZLWK ORZHU VFRUHV 7KLV ILQGLQJ LV FRQVLVWHQW WKDW WKH SUHVHQFH RI QDWXUDO HQYLURQPHQWDO IHDWXUHV VKRXOG DPHOLRUDWH SV\FKRORJLFDO GLVWUHVV DOWKRXJK WKH VSHFLILF UHODWLRQVKLS RI JUDVV DQG IDPLO\ FRQIOLFW LV GLIILFXOW WR SODFH LQ D

PAGE 55

WKHRUHWLFDO FRQWH[W 0RUHRYHU WKLV PRGHO LV DPRQJ WKH ZHDNHVW LQ WKH VHULHV DFFRXQWLQJ IRU RQO\ b RI WKH YDULDWLRQ LQ )3 VFRUHV 7DEOH 3UHGLFWLRQ RI )3 6FRUHV 9DULDEOH 3DUDPHWHU (VWLPDWH 6WG (UURU 3DUWLDO 5 ) 3 ,QWHUFHSW *5$66 $FDGHPLF 3UREOHPV 7KH $FDGHPLF 3UREOHPV $3f VFDOH RI WKH &$6 LV DVVRFLDWHG ZLWK SRRU VWXG\ VNLOOV LQHIILFLHQW WLPH PDQDJHPHQW DQG FRQFHQWUDWLRQ GLIILFXOWLHV $ VXPPDU\ RI UHJUHVVLRQ RQ $3 VFRUHV LV SUHVHQWHG LQ 7DEOH 7KH SUHVHQFH RI JUDVV ZDV DVVRFLDWHG ZLWK ORZHU OHYHOV RI UHSRUWHG DFDGHPLF GLIILFXOWLHV +RZHYHU FRQWUDU\ WR H[SHFWDWLRQ UHVLGHQWLDO VDWLVIDFWLRQ 6$7,6f ZDV DVVRFLDWHG ZLWK LQFUHDVHG DFDGHPLF GLIILFXOW\ 7KLV FRXQWHULQWXLWLYH ILQGLQJ ZLOO EH H[SORUHG PRUH IXOO\ LQ WKH IROORZLQJ FKDSWHU *UDVV DQG VDWLVIDFWLRQ WRJHWKHU DFFRXQW IRU b RI WKH YDULDWLRQ LQ $3 VFRUHV 7DEOH 3UHGLFWLRQ RI $3 6FRUHV 9DULDEOH 3DUDPHWHU (VWLPDWH 6WG (UURU 3DUWLDO 5 ) 3 ,QWHUFHSW 6$7,6 *5$66

PAGE 56

&DUHHU 3UREOHPV 7KH &DUHHU 3UREOHPV &3f VFDOH RI WKH &$6 LV GHVLJQHG WR PHDVXUH GLIILFXOWLHV LQ YRFDWLRQDO JRDO VHWWLQJ DQG GHFLVLRQ PDNLQJ $QWRQ t 5HHG f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f DQG WKH SUHVHQW VWXG\ UHSOLFDWHV WKHLU ILQGLQJ 7VFRUH LQWHUFRUUHODWLRQV IRU DOO QLQH &$6 VXEVFDOHV DUH SUHVHQWHG LQ 7DEOH 7KH VWURQJ LQWHUUHODWLRQVKLSV DPRQJ &$6 VFDOHV DUH HYLGHQW RQ ILUVW H[DPLQDWLRQ RI WKH FRUUHODWLRQ PDWUL[ $OO LQGLYLGXDO FRUUHODWLRQV DUH LQ WKH PRGHUDWH RU KLJKHU UDQJH ,Q IDFW WKH ORZHVW FRUUHODWLRQ EHWZHHQ 6$ DQG &3 W VFRUHV ZDV LQGLFDWLQJ WKDW b RI WKH YDULDWLRQ RI HDFK VFDOH LV VKDUHG EHWZHHQ ERWK $OO RWKHU FRUUHODWLRQV ZHUH KLJKHU LQFOXGLQJ VHYHUDO LQ H[FHVV RI 7VFRUHV IRU

PAGE 57

GHSUHVVLRQ DQG DQ[LHW\ HYLGHQFHG WKH VWURQJHVW UHODWLRQVKLS U f LQGLFDWLQJ QHDUO\ b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f WKHQ WKH QDPHV RI LQGLYLGXDO VFDOHV PD\ EH FOLQLFDOO\ PLVOHDGLQJ 7KLV LV WKH FDVH ZKHQ WKH XQGHUO\LQJ VWUXFWXUH RI WKH &$6 LV QRW VXIILFLHQWO\ VHQVLWLYH WR GLVWLQJXLVK DPRQJ WKH QLQH VXEVFDOHV 0RUH FRQFUHWHO\ WKH GLIIHUHQFH EHWZHHQ GHSUHVVLRQ DQG DQ[LHW\ VFRUHV EHFRPHV OHVV PHDQLQJIXO ZKHQ PRUH WKDQ KDOI RI WKHLU YDULDWLRQ LV VKDUHG 6LQFH WKLV

PAGE 58

SRVVLELOLW\ ZDV HYLGHQW LQ WKH FRUUHODWLRQ PDWUL[ D IDFWRUDQDO\WLF SURFHGXUH ZDV HPSOR\HG WR GHWHUPLQH LQ IXOOHU GHWDLO WKH XQGHUO\LQJ VWUXFWXUH RI WKH &$6 $ SULQFLSDO FRPSRQHQWV DQDO\VLV ZDV SHUIRUPHG RQ WKH FRUUHODWLRQ PDWUL[ RI W VFRUHV IRU HDFK VFDOH RI WKH &$6 3ULQFLSDO FRPSRQHQWV DQDO\VLV OLNH FODVVLFDO IDFWRU DQDO\VLV LV HVVHQWLDOO\ D GDWD UHGXFWLRQ WHFKQLTXH 'XQWHPDQ f WKDW H[WUDFWV D VPDOOHU QXPEHU RI XQFRUUHODWHG RU RUWKRJRQDO IDFWRUV WKDW DUH OLQHDU WUDQVIRUPDWLRQV RI REVHUYHG YDULDEOHV ,Q WKH SUHVHQW DQDO\VLV D YDULPD[ URWDWLRQ SURFHGXUH ZDV FKRVHQ LQ RUGHU WR DFKLHYH PD[LPXP VHSDUDWLRQ RI DQ\ IDFWRUV XQGHUO\LQJ WKH &$6 GDWD 7KLV SURFHGXUH LV LQWHQGHG WR PLQLPL]H WKH QXPEHU RI YDULDEOHV DVVRFLDWHG ZLWK HDFK IDFWRU DQG WKHUHIRUH WR IDFLOLWDWH LQWHUSUHWDWLRQ RI WKH UHVXOWDQW FRPSRQHQWV RI WKH GDWD VHW 1RUXVLV f ([WUDFWHG FRPSRQHQWV DVVRFLDWHG HLJHQYDOXHV DQG SURSRUWLRQ RI YDULDQFH DFFRXQWHG IRU E\ HDFK FRPSRQHQW DUH OLVWHG LQ 7DEOH (LJHQYDOXHV ZKLFK UHSUHVHQW WKH UHODWLYH VWUHQJWK RI D IDFWRU DUH XVHG DV FULWHULD IRU LQFOXVLRQ RI D JLYHQ IDFWRU LQWR WKH PRGHO $OWKRXJK GLIIHUHQW HLJHQYDOXH VFRUHV KDYH EHHQ HPSOR\HG D FXWRII YDOXH RI LV D ZLGHO\DFFHSWHG FRQYHQWLRQ :KHQ WKLV FRQYHQWLRQ LV DSSOLHG WR WKH FXUUHQW PRGHO RQO\ RQH IDFWRU PHHWV LQFOXVLRQ FULWHULD 7KLV IDFWRU DFFRXQWV IRU b RI WKH YDULDWLRQ LQ VXEVFDOH WVFRUHV DQG LV E\ IDU WKH VWURQJHVW FRPSRQHQW RI WKH PRGHO 7KUHH DGGLWLRQDO IDFWRUV ZKLFK GR QRW PHHW LQFOXVLRQ FULWHULD DUH OLVWHG IRU SXUSRVHV RI FRPSDULVRQ $OWKRXJK HLJHQYDOXHV IRU WKHVH IDFWRUV DSSURDFK QRWH WKDW HDFK RI WKH VXEVHTXHQW IDFWRUV DFFRXQWV IRU OHVV WKDQ b RI WKH WRWDO YDULDWLRQ LQ WKH GDWD VHW

PAGE 59

7DEOH &RPSRQHQWV DQG (LJHQYDOXHV RI WKH &RUUHODWLRQ 0DWUL[ &RPSRQHQW (LJHQYDOXH 'LIIHUHQFH b 9DULDWLRQ &XP b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

PAGE 60

UHODWHG WR RQO\ RQH FRPPRQ IDFWRU WKH SRVVLELOLW\ H[LVWV WKDW D VLQJOH SV\FKRORJLFDO GLPHQVLRQ XQGHUOLHV WKH PDMRULW\ RI YDULDWLRQ RQ WKH &$6 UHJDUGOHVV RI VFDOH 7KH DERYH FULWLTXH QRWZLWKVWDQGLQJ )DFWRUV 7ZR WKURXJK )RXU LQ 7DEOH DOWKRXJK TXLWH ZHDN GHPRQVWUDWH VRPH GLPHQVLRQDOLW\ WKDW VKRXOG EH QRWHG )DFWRU 7ZR LV FKDUDFWHUL]HG SULPDULO\ E\ D VWURQJ DVVRFLDWLRQ ZLWK 6$ VFRUHV U f VXJJHVWLQJ D ZHDN WUHQG IRU VXEVWDQFH DEXVH VFRUHV WR YDU\ VRPHZKDW LQGHSHQGHQWO\ RI RWKHU VFDOHV )DFWRU 7KUHH LV SRVLWLYHO\ UHODWHG WR VXLFLGDO LGHDWLRQ U f DQG OHVV VWURQJO\ QHJDWLYHO\ UHODWHG WR DFDGHPLF SUREOHPV U f )DFWRU )RXU LV GHILQHG SULPDULO\ E\ D VWURQJ DVVRFLDWLRQ ZLWK FDUHHU SUREOHPV L f *LYHQ WKHLU ZHDNQHVV WKHVH IDFWRUV VKRXOG EH LQWHUSUHWHG ZLWK FDXWLRQ +RZHYHU WKHLU VWUXFWXUH UDLVHV VRPH LQWHUHVWLQJ WHQWDWLYH K\SRWKHVHV QDPHO\ WKDW VWXGHQW UHSRUW RI VXEVWDQFH DEXVH DQG FDUHHU SUREOHPV PD\ EH LQGHSHQGHQW WR VRPH GHJUHH RI VFRUHV RQ RWKHU VFDOHV 7DEOH )DFWRU /RDGLQJV IRU &$6 6FDOH 76FRUHV 9$5 )DFWRU )DFWRU )DFWRU )DFWRU 7B$Q[LHW\ 7 'HSUHVVLRQ 7 6XLFLGDO ,GHDWLRQ 7 6XEVWDQFH $EXVH 7 6HOIHVWHHP 7 ,QWHUSHUVRQDO 3UREOHPV 7 )DPLO\ 3UREOHPV 7 &DUHHU 3UREOHPV 7$FDGHPLF 3UREOHPV

PAGE 61

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f§DJH DQG SV\FKRORJLFDO WUHDWPHQW VLQFH HQUROOPHQWf§DUH VLJQLILFDQW SUHGLFWRUV RI JOREDO GLVWUHVV 7KH PHDQLQJ RI WKLV UHVXOW LV XQFOHDU VLQFH HQYLURQPHQWDO YDULDEOHV ZHUH VLJQLILFDQW SUHGLFWRUV LQ SUHYLRXV DQDO\VHV $SSDUHQWO\ HQYLURQPHQWDO SUHGLFWRUV KDYH QR DGGLWLRQDO H[SODQDWRU\ SRZHU IRU VFRUHV RQ WKH JOREDO GLVWUHVV PHDVXUH +RZHYHU WKHVH UHVXOWV VKRXOG EH YLHZHG ZLWK FDXWLRQ JLYHQ WKDW WKH FRPSRVLWH GLVWUHVV

PAGE 62

PHDVXUH ZDV D SRVWKRF FUHDWLRQ IRU WKH SUHVHQW VWXG\ DQG KDV QRW EHHQ YDOLGDWHG 7KLV PRGHO DFRXQWV IRU b RI WKH WRWDO YDULDWLRQ LQ DYHUDJH WVFRUH HOHYDWLRQ 7DEOH 3UHGLFWLRQ RI *OREDO 'LVWUHVV 9DULDEOH 3DUDPHWHU (VWLPDWH 6WG (UURU 3DUWLDO 5 ) 3 ,QWHUFHSW $*( 7;6,1&( $OWKRXJK QR HQYLURQPHQWDO YDULDEOHV HQWHUHG WKH VWHSZLVH UHJUHVVLRQ HTXDWLRQ ELYDULDWH UHVXOWV ZHUH VLJQLILFDQW IRU JUDVV W S f DQG FRQFUHWH W S f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f PD\ DFFRXQW IRU DGGLWLRQDO YDULDWLRQ LQ VWXGHQW DGMXVWPHQW /HW XV UHYLVLW WKH RULJLQDO VHW RI UHVHDUFK K\SRWKHVHV

PAGE 63

7KH ILUVW K\SRWKHVLV SUHGLFWHG WKDW UHVLGHQWLDO VWXGHQWV VKRXOG VKRZ JUHDWHU OHYHOV RI DGMXVWPHQW WKDQ RIIFDPSXV UHVLGHQWV 7KH SUHVHQW UHVXOWV GR QRW SURYLGH VXSSRUW IRU WKLV K\SRWKHVHV )LUVW 0$129$ DQDO\VHV IDLOHG WR GHPRQVWUDWH WKH VLJQLILFDQFH RI UHVLGHQWLDO ORFDWLRQ 6HFRQG UHVLGHQWLDO ORFDWLRQ GLG QRW HQWHU WKH UHJUHVVLRQ HTXDWLRQ SUHGLFWLQJ JOREDO GLVWUHVV ,Q IDFW HYHQ D VLPSOH XQLYDULDWH WHVW IDLOHG WR VKRZ SUHGLFWLYH VLJQLILFDQFH W Sf RI UHVLGHQWLDO ORFDWLRQ IRU JOREDO GLVWUHVV 7KH VHFRQG K\SRWKHVHV WKDW SV\FKRORJLFDO DGMXVWPHQW VKRXOG EH LQYHUVHO\ UHODWHG WR GLVWDQFH RI KRPH IURP FDPSXV ZDV QRW VXSSRUWHG LQ WKH 0$129$ DQDO\VLV 1RU ZDV GLVWDQFH VLJQLILFDQWO\ FRUUHODWHG ZLWK JOREDO GLVWUHVV LQ WKH PXOWLSOH RU ELYDULDWH UHJUHVVLRQ DQDO\VLV LQ IDFW D VLPSOH ELYDULDWH FRUUHODWLRQ LQ ZKLFK RQFDPSXV UHVLGHQWV UHFHLYHG D YDOXH RI ]HURf LQGLFDWHG QR UHODWLRQVKLS U S f $ WKLUG K\SRWKHVLV EDVHG RQ WKH ZRUN RI :LOVRQ $QGHUVRQ DQG )OHPLQJ f SUHGLFWHG WKDW VWXGHQWV OLYLQJ ZLWK IDPLO\ ZRXOG UHSRUW PRUH DGMXVWPHQW GLIILFXOWLHV WKDQ WKRVH OLYLQJ DW KRPH SULPDULO\ DV D IXQFWLRQ RI HQPHVOLPHQW 7KLV K\SRWKHVLV WRR ZDV VXSSRUWHG QHLWKHU LQ WKH RPQLEXV 0$129$ QRU LQ WKH SUHGLFWLRQ RI JOREDO GLVWUHVV 7LQV UHVXOW ZDV QRW WKH FRQVHTXHQFH RI SUHGLFWLYH RYHUODS ZLWK RWKHU IDFWRUV VLQFH D VLPSOH WWHVW VKRZHG WKDW IDPLO\ RI RULJLQ KDG QR UHODWLRQVKLS ZLWK JOREDO GLVWUHVV W W f +RZHYHU DQ\ DFWXDO HIIHFW PD\ EH REVFXUHG E\ VNHZHG VDPSOLQJ VLQFH RQO\ WHQ VWXGHQWV RI UHSRUWHG OLYLQJ ZLWK WKHLU IDPLOLHV RI RULJLQ $ IRXUWK K\SRWKHVHV VXJJHVWHG D FXUYLOLQHDU UHODWLRQVKLS EHWZHHQ QXPEHU RI URRPPDWHV DQG DGMXVWPHQW $V QRWHG LQ &KDSWHU VXFK D K\SRWKHVLV LV GLIILFXOW WR WHVW LQ WKLV SRSXODWLRQ EHFDXVH WKH QXPEHU RI URRPPDWHV LV UHVWULFWHG LQ UDQJH 7KH PHDQ QXPEHU RI PDWHV ZDV ZLWK D VWDQGDUG GHYLDWLRQ RI 3DUWLFLSDQWV UHSRUWHG LQ QHDUO\ DOO FDVHV

PAGE 64

D QXPEHU UDQJLQJ IURP ]HUR WR IRXU DQ RXWOLHU RI ZDV DQ H[FHSWLRQf ,Q VSLWH RI WKLV UHVWULFWHG UDQJH QXPEHU RI URRPPDWHV DSSURDFKHG VLJQLILFDQFH LQ WKH LQLWLDO 0$129$ ) Sa f $OWKRXJK WKH VSHFLILF HIIHFWV RI URRPPDWHV ZHUH QRW GHPRQVWUDWHG LQ WKH IROORZXS DQDO\VHV UHSRUWHG DERYH PDWHV ZHUH D VPDOO EXW VLJQLILFDQW SUHGLFWRU RI VXEVWDQFH DEXVH VFRUHV LQ D SUHOLPLQDU\ DQDO\VLV ZKLFK H[FOXGHG WUHDWPHQW VLQFH HQUROOPHQW DV D SUHGLFWRU U ) S f 7KH UHODWLRQVKLS ZDV QHJDWLYH UDLVLQJ WKH WHQWDWLYH EXW LQWHUHVWLQJ SRVVLELOLW\ WKDW WKRVH OLYLQJ DORQH DUH PRUH OLNHO\ WR UHSRUW VXEVWDQFH DEXVH SUREOHPV $ ILIWK K\SRWKHVHV UHJDUGLQJ WKH UHODWLRQVKLS RI QRLVH OHYHO WR DGMXVWPHQW UHFHLYHG OLPLWHG HPSLULFDO VXSSRUW DV ZHOO 1RLVH HIIHFWV QHDUHG VLJQLILFDQFH LQ WKH RPQLEXV 0$129$ ) O S f 6SHFLILF HIIHFWV RI QRLVH ZHUH QRW RI VXIILFLHQW VWUHQJWK WR DFKLHYH VLJQLILFDQFH LQ WKH IROORZXS DQDO\VHV +RZHYHU HIIHFWV ZHUH LQ WKH K\SRWKHVL]HG GLUHFWLRQ IRU H[DPSOH UHSRUWHG QRLVH OHYHO ZDV SRVLWLYHO\ EXW LQVLJQLILFDQWO\f FRUUHODWHG ZLWK JOREDO GLVWUHVV $ VL[WK K\SRWKHVLV RU VHW RI UHODWHG K\SRWKHVHV UHJDUGHG WKH LPSDFW RI QDWXUDO ODQGVFDSH HOHPHQWV LQ VWXGHQW UHVLGHQFHV RQ SV\FKRORJLFDO ZHOOEHLQJ 6SHFLILFDOO\ WKH SUHVHQFH RI ZDWHU WUHHV JUDVV DQG DGHTXDWH OLJKW ZHUH K\SRWKHVL]HG WR SURPRWH SV\FKRORJLFDO KHDOWK FI .DSODQ t .DSODQ f &RQYHUVHO\ WKH SUHVHQFH RI FRQFUHWH DQG EXLOGLQJV ZDV SUHGLFWHG WR KDYH D GHWULPHQWDO HIIHFW RQ DGMXVWPHQW 7KLV VHW RI K\SRWKHVHV UHFHLYHG WKH VWURQJHVW HPSLULFDO VXSSRUW )LUVW JUDVV DFKLHYHG VLJQLILFDQFH LQ WKH RPQLEXV 0$129$ ) S f 7KH EHQHILFLDO LPSDFW RI JUDVV ZDV HYLGHQW LQ LWV DVVRFLDWLRQ ZLWK ORZHU OHYHOV RI DQ[LHW\ ) Sf IHZHU UHSRUWV RI IDPLO\ SUREOHPV ) S f DQG ORZHU OHYHOV RI DFDGHPLF

PAGE 65

GLVWUHVV ) S f ,Q DGGLWLRQ JUDVV DSSURDFKHG VLJQLILFDQFH LQ WKH PRGHO RI VXLFLGDO LGHDWLRQ VFRUHV ) S f WKH GLUHFWLRQ RI UHODWLRQVKLS ZDV LQ WKH K\SRWKHVL]HG GLUHFWLRQ ,Q D SUHOLPLQDU\ PRGHO H[FOXGLQJ WUHDWPHQW VLQFH HQUROOPHQW DV D SUHGLFWRU JUDVV ZDV WKH RQO\ VLJQLILFDQW QHJDWLYH SUHGLFWRU RI VXLFLGDO LGHDWLRQ ) S f 7KDW DQDO\VLV DOVR GHPRQVWUDWHG WKDW JUDVV ZDV QHJDWLYHO\ DVVRFLDWHG ZLWK JOREDO GLVWUHVV ) S f 5HSRUWHG OLJKW OHYHOV DSSURDFKHG VLJQLILFDQFH LQ WKH LQLWLDO 0$129$ ) S f DQG SURGXFHG VLJQLILFDQW UHVXOWV LQ WKH IROORZXS DQDO\VHV ,Q WKH UHVXOWV UHSRUWHG DERYH KLJKHU OLJKW OHYHOV ZHUH DVVRFLDWHG ZLWK EHWWHU VHOIHVWHHP VFRUHV ) S f ,Q WKH DQDO\VHV H[FOXGLQJ WUHDWPHQW VLQFH HQUROOPHQW SRRU OLJKWLQJ ZDV DVVRFLDWHG ZLWK LQFUHDVHG UHSRUW RI GHSUHVVLYH V\PSWRPV ) S f )LQDOO\ VHOIUHSRUW RI UHVLGHQWLDO VDWLVIDFWLRQ f2YHUDOO KRZ VDWLVILHG DUH \RX ZLWK \RXU FXUUHQW UHVLGHQFH"ff DFKLHYHG VLJQLILFDQFH LQ WKH 0$129$ ) S f 7KLV OLNHUWVFDOH TXHVWLRQ LQFOXGHG DW WKH HQG RI WKH VHFWLRQ RQ KRXVLQJ HQYLURQPHQW ZDV LQWHQGHG WR UHSUHVHQW D JOREDO VHOIDVVHVVPHQW RI UHVLGHQWLDO VDWLVIDFWLRQ ,Q WKH UHJUHVVLRQ UHVXOWV KHUH UHSRUWHG WKH LQIOXHQFH RI UHVLGHQWLDO VDWLVIDFWLRQ ZDV HYLGHQW LQ LWV DELOLW\ WR SUHGLFW DFDGHPLF SUREOHPV DOWKRXJK WKH GLUHFWLRQ RI DVVRFLDWLRQ ZDV FRXQWHULQWXLWLYH %HWD ) S f 7KDW LV UHVLGHQWLDO VDWLVIDFWLRQ ZDV DVVRFLDWHG ZLWK DQ LQFUHDVHG OHYHO RI UHSRUWHG DFDGHPLF SUREOHPV $OWKRXJK WKH UHDVRQ IRU WKLV XQH[SHFWHG UHVXOW LV XQFOHDU D SRVW KRF VSHFXODWLRQ LV WKDW IRU D FHUWDLQ VHJPHQW RI WKH VDPSOH VDWLVIDFWLRQ UHIOHFWV UHVLGHQWLDO OLIH GLVWUDFWLQJ UDWKHU WKDQ SURPRWLQJ DFDGHPLF IRFXV

PAGE 66

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f SURYLGHV VRPH LQGLFDWLRQ RI FULWHULRQ YDOLGLW\ IRU WKH &$6 DQG f WLHV WKLV VWXG\ PRUH FORVHO\ WR FOLQLFDO VHUYLFHV SURYLGHG E\ FROOHJH FRXQVHOLQJ FHQWHUV $ 0$129$ WHVWLQJ IRU RYHUDOO HIIHFWV RI WKH IRXU OHYHOV RI WUHDWPHQW KLVWRU\ QRQH EHIRUH FROOHJH VLQFH FROOHJH DQG FXUUHQWf RQ WKH QLQH &$6 VFDOHV \LHOGHG VLJQLILFDQW UHVXOWV /DPEGD ) S f )ROORZXS DQDO\VHV RI YDULDQFH $129$Vf GHPRQVWUDWHG VSHFLILF WUHDWPHQW HIIHFWV RQ WVFRUHV IRU DQ[LHW\ ) S f GHSUHVVLRQ ) S f VXEVWDQFH DEXVH ) S f DQG VHOIHVWHHP ) S f 3RVWKRF WHVWV IRU DQ[LHW\ VFRUHV UHYHDOHG WKDW VWXGHQWV LQ FXUUHQW WUHDWPHQW KDG KLJKHU WVFRUHV PHDQ f WKDQ WKRVH ZKR KDG WUHDWPHQW SULRU WR FROOHJH PHDQ f RU QHYHU PHDQ f )RU GHSUHVVLRQ WKRVH LQ FXUUHQW WUHDWPHQW VFRUHG VLJQLILFDQWO\ KLJKHU PHDQ f WKDQ WKRVH ZKR UHSRUWHG WKHUDS\ EHIRUH FROOHJH PHDQ f RU QHYHU ,Q D IHZ FDVHV SDUWLFLSDQWV ZKR UHSRUWHG WZR RU PRUH VHSDUDWH HSLVRGHV RI WUHDWPHQW IHOO LQWR PRUH WKDQ RQH JURXS LH FXUUHQW WUHDWPHQW DQG WUHDWPHQW EHIRUH RU VLQFH FROOHJHf

PAGE 67

PHDQ f ,Q DGGLWLRQ VWXGHQWV FXUUHQWO\ LQ WUHDWPHQW UHSRUWHG SRRUHU VHOIHVWHHP PHDQ f WKDQ WKRVH ZKR KDG WUHDWPHQW SULRU WR FROOHJH PHDQ f RU QRW DW DOO PHDQ f 7KHVH UHVXOWV SURYLGH FULWHULRQ YDOLGLW\ HYLGHQFH IRU WKH &$6 VFDOHV PHDVXULQJ GHSUHVVLRQ DQ[LHW\ DQG VHOIHVWHHP

PAGE 68

&+$37(5 ',6&866,21 (QYLURQPHQW YHUVXV 7UHDWPHQW (IIHFWV DQG 6WXGHQW &KDUDFWHULVWLFV 7KH UROH RI HQYLURQPHQWDO IHDWXUHVf§VSHFLILFDOO\ JUDVV YLHZV OLJKWLQJ DQG QRLVH OHYHOf§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f ZHUH XVHG DV SUHGLFWRUV LQ WKH DQDO\VLV SUHVHQWHG KHUH 7KH QDWXUH RI WKHVH PHDVXUHV LV VRPHZKDW DPELJXRXV 7KH ILUVW WZR YDULDEOHV ZHUH LQWHQGHG WR FRQWURO IRU OHYHO RI SV\FKRORJLFDO DGMXVWPHQW SULRU WR WKH VWXGHQWfV FXUUHQW OLYLQJ DUUDQJHPHQWV 7KH ODVW KRZHYHU FRXOG EH FRQFHSWXDOL]HG DV HLWKHU D SUHGLFWRU RU DQ RXWFRPH YDULDEOH 7KDW LV FXUUHQW SV\FKRORJLFDO WUHDWPHQW LV OLNHO\ WR UHVXOW IURP SV\FKRORJLFDO GLVWUHVV WKH UHYHUVH FDVH LQ ZKLFK WUHDWPHQW FDXVHV GLVWUHVV LV ZH KRSHf OHVV SODXVLEOH DVVXPLQJ WKDW FRPSHWHQW FOLQLFLDQV DUH SURYLGLQJ VHUYLFHV +RZHYHU VLQFH HYHQ FXUUHQW WUHDWPHQW DGGV VRPH DGGLWLRQDO VWUHQJWK WR PRVW RI WKH PRGHOV KHUH SUHVHQWHG D GHFLVLRQ ZDV PDGH WR

PAGE 69

UHWDLQ HDFK YDULDEOH LQ WKH FXUUHQW PRGHO 7KH GHFLVLRQ WR LQFRUSRUDWH WUHDWPHQW DV D SUHGLFWRU DW DOO UHIOHFWV D FRQVHUYDWLYH DQDO\WLF VWUDWHJ\ VLQFH WKH YDULDWLRQ DFFRXQWHG IRU E\ WUHDWPHQW FRXOG SRVVLEO\ REVFXUH PRUH VXEWOH HQYLURQPHQWDO HIIHFWV +RZHYHU VXFK D FRQVHUYDWLYH DSSURDFK KDV WKH DGYDQWDJH RI GRFXPHQWLQJ HQYLURQPHQWDO LPSDFW LQGHSHQGHQW RI WKH GHFLVLRQ WR VHHN PHQWDO KHDOWK WUHDWPHQW DQG WKXV VSHDNV WR WKH EURDGHVW SRVVLEOH UDQJH RI FROOHJH VWXGHQWV )LQDOO\ VLQFH WKLV VWXG\ HPSOR\V DQ H[ SRVW IDFWR FRUUHODWLRQDO GHVLJQ WKH GHFLVLRQ WR LQFRUSRUDWH DV PDQ\ SRWHQWLDO SUHGLFWRUV DV SRVVLEOH FRPSHQVDWHV IRU WKH ODFN RI H[SHULPHQWDO FRQWURO 0RUHRYHU WKH LQFOXVLRQ RI DOO WUHDWPHQW YDULDEOHV DV ZHOO DV HQYLURQPHQWDO SUHGLFWRUV LQFUHDVHV WKH UHOHYDQFH RI WLQV VWXG\ WR ERWK HQYLURQPHQWDO DQG FRXQVHOLQJ SV\FKRORJ\ EHFDXVH WKH VWUDWHJ\ DOORZV IRU WKH VLPXOWDQHRXV DVVHVVPHQW RI WUHDWPHQW KLVWRU\ DQG HQYLURQPHQWDO RU JHRJUDSKLFDO IDFWRUV :LWK UHJDUG WR WKLV ODVW SRLQW WKH DQDO\VLV RI WKH UHODWLRQVKLS EHWZHHQ UHFHQF\ RI WUHDWPHQW DQG DGMXVWPHQW DGV DQ LPSRUWDQW PRUH H[SOLFLWO\ FOLQLFDO GLPHQVLRQ WR RXU PRGHOV RI DGMXVWPHQW 7KHVH UHVXOWV LQGLFDWH WKDW WKRVH VWXGHQWV LQ FXUUHQW WUHDWPHQW RU SODQQLQJ WR VHHN WUHDWPHQW ZLWKLQ GD\Vf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f VRPH JURXSV UHOHYDQW WR WKH UHVHDUFK K\SRWKHVHV ZHUH LQDGHTXDWHO\ UHSUHVHQWHG 7KH PRVW QRWDEOH DPRQJ WKHVH ZDV

PAGE 70

VWXGHQWV OLYLQJ ZLWK WKHLU IDPLO\ RI RULJLQ Q f $OVR RQO\ D VPDOO SRUWLRQ RI VWXGHQWV UHSRUWHG QR H[SRVXUH WR WUHHV Q f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f IDFLOLWDWHV UHFRYHU\ IURP IDWLJXH WKURXJK UHVWRUDWLYH LPSDFW RQ LQIRUPDWLRQ SURFHVVLQJ V\VWHPV .DSODQ t .DSODQ f DQG Ef SURGXFHV PHDVXUDEOH SK\VLRORJLFDO FKDQJHV DVVRFLDWHG ZLWK DXWRQRPLF UHOD[DWLRQ UHVSRQVHV 8OULFK 8OULFK HW DO f +RZHYHU WKH ODQGVFDSH UHVHDUFK FLWHG KDV IRXQG WKDW WKH EHQHILFLDO LPSDFW RI QDWXUH H[SRVXUH LQFOXGHV QRW RQO\ JUDVV EXW DOVR RWKHU QDWXUDO

PAGE 71

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f SURYLGH D PHWDDQDO\VLV RI FOLQLFDO UHVHDUFK RQ WKH HIIHFWLYHQHVV RI SKRWRWKHUDS\ IRU 6HDVRQDO $IIHFWLYH 'LVRUGHU 6$'f 7KH\ UHSRUW WKDW OLJKW LQWHQVLW\ LV DQ LPSRUWDQW SUHGLFWRU RI DQWLGHSUHVVDQW HIIHFW 7\SLFDOO\ SDWLHQWV UHVSRQG EHVW WR EULJKW IORUHVFHQW OLJKW DERXW OX[f ZKLOH RUGLQDU\ URRP OLJKW OX[ RU OHVVf KDV OLWWOH RU QR HIIHFW RQ V\PSWRPV $ PLQRULW\ RI VXEMHFWV KRZHYHU KDV UHVSRQGHG IDYRUDEO\ WR ORZLQWHQVLW\ OLJKW VRPH 6$' SDWLHQWV PD\ EHQHILW 7KH '60,9 GRHV QRW OLVW 6$' DV D VHSDUDWH GLVRUGHU UDWKHU D VHDVRQDO SDWWHUQ VSHFLILHU PD\ EH DGGHG WR D PRRG GLVRUGHU GLDJQRVLV 7KH FULWHULD IRU VXFK D VSHFLILFDWLRQ DUH DV IROORZV $ 7KHUH KDV EHHQ D UHJXODU WHPSRUDO UHODWLRQVKLS EHWZHHQ WKH RQVHW RI 0DMRU 'HSUHVVLYH (SLVRGHV LQ %LSRODU RU %LSRODU ,, 'LVRUGHU RU 0DMRU 'HSUHVVLYH 'LVRUGHU 5HFXUUHQW DQG D SDUWLFXODU WLPH RI WKH \HDU HJ UHJXODU DSSHDUDQFH RI WKH 0DMRU 'HSUHVVLYH (SLVRGH LQ WKH IDOO RU ZLQWHU >LQ WKH DEVHQFH RI SV\FKRVRFLDO VWUHVVRUV@ % )XOO UHPLVVLRQV RU D FKDQJH IURP GHSUHVVLRQ WR PDQLD RU K\SRPDQLDf DOVR RFFXU DW D FKDUDFWHULVWLF WLPH RI WKH \HDU & ,Q WKH ODVW WZR \HDUV WZR 0DMRU 'HSUHVVLYH (SLVRGHV KDYH RFFXUUHG WKDW GHPRQVWUDWH WKH WHPSRUDO VHDVRQDO UHODWLRQVKLSV GHILQHG LQ &ULWHULD $ DQG % DQG QR QRQVHDVRQDO HSLVRGHV KDYH RFFXUUHG GXULQJ WKDW VDPH SHULRG 6HDVRQDO 0DMRU 'HSUHVVLYH (SLVRGHV VXEVWDQWLDOO\ RXWQXPEHU WKH QRQVHDVRQDO 0DMRU 'HSUHVVLYH (SLVRGHV WKDW PD\ KDYH RFFXUUHG RYHU WKH LQGLYLGXDOnV OLIHWLPH $PHULFDQ 3V\FKRORJLFDO $VVRFLDWLRQ S f

PAGE 72

PRVW IURP H[WUHPHO\ KLJKLQWHQVLW\ OLJKW HJ OX[f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fV SHUVSHFWLYH WKHVH ILQGLQJV SURYLGH UHOHYDQW SUHVFULSWLRQV IRU ODQGVFDSH GHVLJQ DOWKRXJK WKH LPSRUWDQFH RI OLJKW DQG JUHHQVSDFH LV FHUWDLQO\ QRW D QRYHO QRWLRQ )URP DQ HFRORJLFDO SHUVSHFWLYH KRZHYHU WKH UHODWLRQVKLS RI HQYLURQPHQWDO IHDWXUHV WR SV\FKRORJLFDO

PAGE 73

ZHOOEHLQJ LV SHUKDSV PRUH QRWHZRUWK\ VLQFH WKH UHVXOWV XQGHUVFRUH WKH LQWHUFRQQHFWHGQHVV RI WKH FDPSXV V\VWHP 6WXGHQW ZHOOEHLQJ LV QRW VLPSO\ D IXQFWLRQ RI SULRU SV\FKRORJLFDO PDNHXS DQG LQWHUDFWLRQ ZLWK PHQWDO KHDOWK SURIHVVLRQDOV 5DWKHU ZHOOEHLQJ LV LQIOXHQFHG E\ D V\VWHP RI G\QDPLF HQYLURQPHQWDO IDFWRUV 3K\VLFDO HQYLURQPHQW DQG WKH PLFURn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f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n FULWHULRQ PHDVXUHV DUH JRRG FDQGLGDWHV EHFDXVH WKH\ VLPSOLI\ DQDO\WLF VWUDWHJ\ DQG DIIRUG FOHDUHU FOLQLFDO LQWHUSUHWDWLRQ 7KH 0W VFDOH RI WKH 003, .OHLQPXQW] f ZKLFK ZDV SUREOHPDWLF LQ WKH SUHVHQW VWXG\ UHPDLQV D YLDEOH FDQGLGDWH VLQFH LW SURGXFHV D VLQJOH

PAGE 74

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f KDV FRPELQHG TXDQWLWDWLYH DQG TXDOLWDWLYH DQDO\VLV WR PRGHO SUHIHUHQFH DQG PHDQLQJ RI DUERUHWXP ODQGVFDSHV )OLV DSSURDFK XVHG NH\ZRUGV IURP VSRQWDQHRXV GHVFULSWLRQV RI ODQGVFDSHV WR SUHGLFW HQYLURQPHQWDO SUHIHUHQFHV :RUN IRFXVLQJ RQ H[SOLFLWO\ SV\FKRORJLFDO LVVXHV KDV UHFHLYHG DWWHQWLRQ IURP KXPDQLVWLF JHRJUDSKHUV )RU H[DPSOH 7XDQ f KDV ZULWWHQ H[WHQVLYHO\ RQ WRSRSKLOLD RU ORYH RI SODFH DV D UHIOHFWLRQ RI WKH HPRWLRQDO WLHV EHWZHHQ KXPDQV DQG ODQGVFDSH 7RSRSKLOLF H[SHULHQFHV PLJKW LQFOXGH IHHOLQJV RI DWKRPHQHVV DFFHSWDQFH VSLULWXDO ZHOOEHLQJ RU HYHQ WUDQVFHQGHQF\

PAGE 75

$ PRUH TXDOLWDWLYH DSSURDFK URXQGV RXW WKH HFRORJLFDO FRQWH[W RI WKLV SDSHU DQ H[SHULHQWLDO DQDO\VLV JRHV EH\RQG WKLV XVHIXO EXW UDWKHU PHFKDQLVWLF DSSURDFK E\ JURXQGLQJ DJJUHJDWH UHVXOWV LQ WKH GD\WRGD\ OLYHV RI VWXGHQWV 0RUHRYHU TXDOLWDWLYH FODULILFDWLRQV RI HQYLURQPHQWDO H[SHULHQFH DGG WKHRUHWLFDO VRSKLVWLFDWLRQ WR RXU XQGHUVWDQGLQJ :LWQHVV WKH GLVWLQFWLRQ PDGH E\ 5HOSK f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

PAGE 76

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f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
PAGE 77

$33(1',; % 3OHDVH DQVZHU WKH IROORZLQJ TXHVWLRQV DERXW \RXUVHOI DQG WKH SODFH ZKHUH \RX OLYH ,I FKRLFHV DUH SURYLGHG FLUFOH WKH DSSURSULDWH DQVZHU ,I EODQNV DUH SURYLGHG ILOO LQ WKH DSSURSULDWH DQVZHU ,QIRUPDWLRQ DERXW \RX :KDW LV \RXU DJH" :KDW LV \RXU JHQGHU" D 0DOH E )HPDOH :KLFK EHVW GHVFULEHV WKH HWKQLF JURXS WR ZKLFK \RX EHORQJ" D :KLWH QRQ+LVSDQLFf E $IULFDQ $PHULFDQ F $VLDQ3DFLILF ,VODQGHU G +LVSDQLF/DWLQRDf H RWKHU +RZ PDQ\ WHUPV KDYH \RX EHHQ D VWXGHQW DW 8)8:1&" B :KDW LV \RXU JUDGH SRLQW DYHUDJH" :KLFK EHVW GHVFULEHV \RXU VH[XDO RULHQWDWLRQ" D +HWHURVH[XDO VWUDLJKWf E %LVH[XDO F*D\/HVELDQ ,QIRUPDWLRQ DERXW \RXU KRPH 'R \RX OLYH RQ FDPSXV RU RII FDPSXV" D RQ FDPSXV E RII FDPSXV ,I RII FDPSXV KRZ IDU DZD\ IURP FDPSXV LV \RXU KRPH ORFDWHG" WR WKH QHDUHVW PLOHf

PAGE 78

,I RII FDPSXV GR \RX OLYH ZLWK \RXU IDPLO\" D
PAGE 79

2YHUDOO KRZ VDWLVILHG DUH \RX ZLWK \RXU FXUUHQW UHVLGHQFH" QRW DW DOO VDWLVILHG H[WUHPHO\ VDWLVILHG ,QIRUPDWLRQ DERXW \RXU XVH RI FRXQVHOLQJ RU SV\FKRWKHUDS\ %()25( \RX FDPH WR 8)8:1& KDG \RX HYHU VHHQ D SV\FKRORJLVW SV\FKLDWULVW RU RWKHU W\SH RI PHQWDO KHDOWK SURIHVVLRQDO IRU D SV\FKRORJLFDO RU SHUVRQDO SUREOHP" D
PAGE 80

5()(5(1&(6 $LHOOR t %DXP $ (GVf f 5HVLGHQWLDO FURZGLQJ DQG GHVLJQ 1HZ
PAGE 81

&DPSEHOO 0+ $XJXVWf $Q LQIRUPDWLRQDO PRGHO RI YLVXDO SUHIHUHQFH IRU XUEDQ ZDWHUVFDSHV 3DSHU SUHVHQWHG DW WKH QG FRQYHQWLRQ RI WKH $PHULFDQ 3V\FKRORJLFDO $VVRFLDWLRQ /RV $QJHOHV &$ &KDQGOHU /$ t *DOODJKHU 53 f 'HYHORSLQJ D WD[RQRP\ IRU SUREOHPV VHHQ DW D XQLYHUVLW\ FRXQVHOLQJ FHQWHU 0HDVXUHPHQW DQG (YDOXDWLRQ LQ &RXQVHOLQJ DQG 'HYHORSPHQW &KLFNHULQJ $: f &RPPXWLQJ YHUVXV UHVLGHQW VWXGHQWV 6DQ )UDQFLVFR -RVVH\%DVV &KLFNHULQJ $: t 5HLVVHU / f (GXFDWLRQ DQG LGHQWLW\ QG HGf 6DQ )UDQFLVFR 7RVVH\%DVV &RKHQ 6 .DPDUFN 7 t 0HUPHOVWHLQ 5 f $ JOREDO PHDVXUH RI SHUFHLYHG VWUHVV -RXUQDO RI +HDOWK DQG 6RFLDO %HKDYLRU &YHWNRYLWFK t (DUOH 7 f (QYLURQPHQWDO KD]DUGV DQG WKH SXEOLF -RXUQDO RI 6RFLDO ,VVXHV 'DKOVWURP :* :HOVK *6 t 'DKOVWURP /( f $Q 003, KDQGERRN YRO ,, 5HVHDUFK DSSOLFDWLRQV 0LQQHDSROLV 8QLYHUVLW\ RI 0LQQHVRWD 3UHVV 'HPLFN t $QGUHROHWWL & f 6RPH UHODWLRQV EHWZHHQ FOLQLFDO DQG HQYLURQPHQWDO SV\FKRORJ\ (QYLURQPHQW DQG %HKDYLRU 'HPLFN t :DSQHU 6 f (IIHFWV RI HQYLURQPHQWDO UHORFDWLRQ RQ D SV\FKLDWULF WKHUDSHXWLF FRPPXQLW\ -RXUQDO RI $EQRUPDO 3V\FKRORJ\ 'XQWHPDQ *+ f 3ULQFLSDO FRPSRQHQWV DQDO\VLV 6DJH XQLYHUVLW\ SDSHU VHULHV RQ TXDQWLWDWLYH DSSOLFDWLRQV LQ WKH VRFLDO VFLHQFHV f %HYHUO\ +LOOV 6DJH 3XEOLFDWLRQV (GZDUGV $/ f (GZDUGV 3HUVRQDO 3UHIHUHQFH 6FKHGXOH PDQXDO 1HZ
PAGE 82

*UDII 5: t &RROH\ *5 f $GMXVWPHQW RI FRPPXWHU DQG UHVLGHQW VWXGHQWV -RXUQDO RI &ROOHJH 6WXGHQW 3HUVRQQHO *UDKDP -5 f 003, $VVHVVLQJ SHUVRQDOLW\ DQG SV\FKRSDWKRORJ\ QG HGf 1HZ
PAGE 83

.OHLQPXQW] % f 7KH &ROOHJH 0DODGMXVWPHQW 6FDOH 0Wf 1RUPV DQG SUHGLFWLYH YDOLGLW\ (GXFDWLRQDO DQG 3V\FKRORJLFDO 0HDVXUHPHQW .UXSDW ( f 3HRSOH LQ FLWLHV 1HZ
PAGE 84

3DVFDUHOOD (7 t &KDSPDQ ': f 9DOLGDWLRQ RI D WKHRUHWLFDO PRGHO RI FROOHJH ZLWKGUDZDO ,QWHUDFWLRQ HIIHFWV LQ D PXOWLLQVWLWXWLRQDO VDPSOH 5HVHDUFK LQ +LJKHU (GXFDWLRQ 3DVFDUHOOD (7 'XE\ 3% t ,YHUVRQ %. f $ WHVW DQG UHFRQFHSWXDOL]DWLRQ RI D WKHRUHWLFDO PRGHO RI FROOHJH ZLWKGUDZDO LQ D FRPPXWHU LQVWLWXWLRQ VHWWLQJ 6RFLRORJ\ RI (GXFDWLRQ 3DVFDUHOOD (7 (GLVRQ 0 1RUD $ +DJHGRP /6 t 7HUHQ]LQL 37 f ,QIOXHQFHV RQ VWXGHQWVf RSHQQHVV WR GLYHUVLW\ DQG FKDOOHQJH LQ WKH ILUVW \HDU RI FROOHJH -RXUQDO RI +LJKHU (GXFDWLRQ 5HOSK ( f *HRJUDSKLFDO H[SHULHQFHV DQG EHLQJLQWKHZRUOG 7KH SKHQRPHQRORJLFDO RULJLQV RI JHRJUDSK\ KU 6HDPRQ t 0XJHUDXHU (GVf 'ZHOOLQJ 3ODFH DQG (QYLURQPHQW 7RZDUGV D 3KHQRPHQRORJ\ RI 3HUVRQ DQG :RUOG SS f 'RUGUHFKW 1LMKRII 5RVHQWKDO 1 6RFN 6NZHUHU 5 -DFREVRQ ) t :HKU 7 f 3KRWRWKHUDS\ IRU VHDVRQDO DIIHFWLYH GLVRUGHU -RXUQDO RI %LRORJLFDO 5K\WKPV 6FKURHGHU +: f 3UHIHUHQFH DQG PHDQLQJ RI DUERUHWXP ODQGVFDSHV &RPELQLQJ TXDQWLWDWLYH DQG TXDOLWDWLYH GDWD -RXUQDO RI (QYLURQPHQWDO 3VYFKRORJYLO 6HDPRQ f (PRWLRQDO H[SHULHQFH RI WKH HQYLURQPHQW $PHULFDQ %HKDYLRUDO 6FLHQWLVW 6HDPRQ f +XPDQLVWLF DQG SKHQRPHQRORJLFDO DGYDQFHV LQ HQYLURQPHQWDO GHVLJQ 7KH +XPDQLVWLF 3V\FKRORJLVW 6WRNROV f 7KH SDUDGR[ RI HQYLURQPHQWDO SV\FKRORJ\ $PHULFDQ 3V\FKRORJLVW 6WUHHW 6 .URPUH\ -' 5HHG t $QWRQ : 'HFHPEHU-DQXDU\f $ SKHQRPHQRORJLFDO SHUVSHFWLYH RI SUREOHPV H[SHULHQFHG E\ KLJK VFKRRO VWXGHQWV +LJK 6FKRRO -RXUQDO SS 6XQGVWURP ( %HOO 3$ t $VPXV & f (QYLURQPHQWDO SV\FKRORJ\ $QQXDO 5HYLHZ RI 3V\FKRORJ\ 7D\ORU -* =XEH (+ t 6HOO -/ f /DQGVFDSH DVVHVVPHQW DQG SHUFHSWLRQ UHVHDUFK PHWKRGV ,Q 5% %HFKWHO 5: 0DUDQV t : 0LFKHOVRQ (GVf 0HWKRGV LQ HQYLURQPHQWDO DQG EHKDYLRUDO UHVHDUFK SS f 1HZ
PAGE 85

7XUQHU 35 9DOWLHUUD 0 7DONHQ 75 0LOOHU 9, t 'H $QGD -5 f (IIHFW RI VHVVLRQ OHQJWK RQ WUHDWPHQW RXWFRPH IRU FROOHJH VWXGHQWV LQ EULHI WKHUDS\ -RXUQDO RI &RXQVHOLQJ 3V\FKRORJ\ 8OULFK 56 f 1DWXUDO YHUVXV XUEDQ VFHQHV 6RPH SV\FKRSK\VLRORJLFDO HIIHFWV (QYLURQPHQW DQG %HKDYLRU 8OULFK 56 f 9LHZ WKURXJK D ZLQGRZ PD\ LQIOXHQFH UHFRYHU\ IURP VXUJHU\ 6FLHQFH 8OULFK 56 f (IIHFWV RI LQWHULRU GHVLJQ RQ ZHOOQHVV 7KHRU\ DQG UHFHQW VFLHQWLILF UHVHDUFK -RXUQDO RI +HDOWK &DUH ,QWHULRU 'HVLJQ 8OULFK 56 6LPRQV 5) /RVLWR %' )LRULWR ( 0LOHV 0$ t =HOVRQ 0 f 6WUHVV UHFRYHU\ GXULQJ H[SRVXUH WR QDWXUDO DQG XUEDQ HQYLURQPHQWV -RXUQDO RI (QYLURQPHQWDO 3V\FKRORJ\ :DSQHU 6 f 7RZDUG LQWHJUDWLRQ (QYLURQPHQWDO SV\FKRORJ\ LQ UHODWLRQ WR RWKHU VXEILHOGV RI SV\FKRORJ\ (QYLURQPHQW DQG %HKDYLRU :HOW\ -' f 5HVLGHQW RU FRPPXWHU VWXGHQWV ,V LW RQO\ WKH OLYLQJ VLWXDWLRQ" -RXUQDO RI &ROOHJH 6WXGHQW 3HUVRQQHO :LOVRQ 5$QGHUVRQ 6$ t )OHPLQJ :0 f &RPPXWHU DQG UHVLGHQW VWXGHQWVn SHUVRQDO DQG IDPLO\ DGMXVWPHQW -RXUQDO RI &ROOHJH 6WXGHQW 3HUVRQQHO :ROIH -6 f 7KH UHODWLRQVKLS RI D IUHVKPDQ \HDU H[SHULHQFH IRU UHVLGHQW DQG FRPPXWHU VWXGHQWV WR WKH VRFLDO DQG DFDGHPLF LQWHJUDWLRQ FRPPLWPHQW DFDGHPLF VXFFHVV DQG SHUVLVWHQFH RI ILUVW\HDU FROOHJH VWXGHQWV 'RFWRUDO GLVVHUWDWLRQ 8QLYHUVLW\ RI 0DU\ODQG &ROOHJH 3DUN f 'LVVHUWDWLRQ $EVWUDFWV ,QWHUQDWLRQDO $

PAGE 86

%,2*5$3+,&$/ 6.(7&+ 0LNH &DPSEHOO ZDV ERP DW 0F&R\ $LU )RUFH %DVH 2UODQGR )ORULGD RQ 2FWREHU WR &DSW 'RQDOG ) DQG 6\OYLD &DPSEHOO 'XULQJ FKLOGKRRG KH DFFRPSDQLHG KLV SDUHQWV RQ D YDULHW\ RI DVVLJQPHQWV LQ WKH FRQWLQHQWDO 86 DQG 5HSXEOLF RI 3DQDPD $IWHU JUDGXDWLQJ IURP 5RPH )UHH $FDGHP\ 5RPH 1
PAGE 87

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+ $U\ /DPPH $VVRFLDWH 3URIHVVRU RI *HRJUDSK\ 7KLV GLVVHUWDWLRQ ZDV VXEPLWWHG WR WKH *UDGXDWH )DFXOW\ RI WKH 'HSDUWPHQW RI 3V\FKRORJ\ LQ WKH &ROOHJH RI /LEHUDO $UWV DQG 6FLHQFHV DQG WR WKH *UDGXDWH 6FKRRO DQG ZDV DFFHSWHG DV SDUWLDO IXOILOOPHQW IRU WKH UHTXLUHPHQWV IRU WKH GHJUHH RI 'RFWRU RI 3KLORVRSK\ 0D\ 'HDQ *UDGXDWH 6FKRRO


THE IMPACT OF RESIDENTIAL ENVIRONMENT ON
PSYCHOLOGICAL ADJUSTMENT OF COLLEGE STUDENTS
By
MICHAEL HARRY CAMPBELL
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE
UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE
REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
1998

ACKNOWLEDGEMENTS
I extend sincere thanks to Dorothy Nevill and Franz Epting for their assistance
with this manuscript and, more generally, for their guidance during my graduate career. I
am indebted to Shawn Prichard for friendship and intellectual stimulation, as well as,
more concretely, technical assistance with the data analysis here presented. My thanks
for the extraordinary support provided by my family—especially my parents, Don and
Sylvia Campbell, and my grandmother, Mary Alice Knight—cannot be adequately
acknowledged here.
n

TABLE OF CONTENTS
page
ACKNOWLEDGEMENTS ii
ABSTRACT v
CHAPTERS
1 INTRODUCTION 1
2 REVIEW OF LITERATURE 7
Campus Ecology as Context 7
The Interface of Research in Environmental and Counseling/Clinical
Psychology 10
Residential Status and the Welfare of Commuter Students 12
The Impact of Physical Environmental Features on Well-Being 22
Rationale for the Present Study 26
3 METHOD 30
Participants 30
Materials 31
Design and Procedure 33
Analytic Strategy 34
4 RESULTS 37
Descriptive Characteristics of the Variable Set 37
Omnibus Analyses 41
Follow-up Analyses 43
Factor Structure of the College Adjustment Scales 50
Summary of Hypotheses 56
Psychological Treatment Effects Revisited 60
5DISCUSSION
62

Environment versus Treatment Effects and Student Characteristics 62
Environment and Adjustment 64
Implications for Policy 66
Directions for Future Research 67
APPENDICES
A INFORMED CONSENT STATEMENT 70
B QUESTIONNAIRE 71
REFERENCES 74
BIOGRAPHICAL SKETCH 80
iv

Abstract of Dissertation Presented to the Graduate School of the University of Florida in
Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
THE IMPACT OF RESIDENTIAL ENVIRONMENT ON
PSYCHOLOGICAL ADJUSTMENT OF COLLEGE STUDENTS
By
Michael Harry Campbell
May 1998
Chair: Dorothy D. Nevill, Ph.D.
Major Department: Counseling Psychology
This study investigated the relationship of residential environment and location to
the psychological adjustment of college undergraduates. Students from several
institutions were asked to provide infonnation about their housing environments (e.g.,
location, noise estimates, light levels, number of roommates, and contents of the visual
landscape) and to complete a multiple-scale measure of psychological adjustment: the
College Adjustment Scales. The contribution of residential environment to psychological
well-being was demonstrated via multiple multivariate analyses controlling for the
influence of psychological treatment history and demographic characteristics. Results
demonstrated that environmental variables, particularly the presence of grass in window
vistas and lower subjective ratings of noise and light levels, were positively associated
v

with psychological adjustment. In addition, the association of treatment history with
current adjustment was elucidated through post-hoc analyses. Finally, this study
addresses the psychometric properties of the College Adjustment Scales, underscoring
their limitation as a research instrument. The discussion addresses the theoretical
implications of the findings in tenns of the extant literature on psychological benefits of
natural landscape elements. The conclusion addresses potential contributions of
qualitative approaches as a compliment to quantitative landscape research.
vi

CHAPTER 1
INTRODUCTION
The interface of counseling or clinical psychology with the broader perspective of
environmental or ecological approaches has generated a number of novel research questions
regarding the impact of environmental features on psychological well-being. The present
study is a contribution to this tradition, although the geographic domain of this research—
the campus community—has been relatively, and surprisingly, neglected in previous work.
This paucity of research is peculiar for a number of reasons. First, of course, is the irony
that most academic researchers in psychology, of any specialty, work in a campus setting.
Certainly psychologists have ample exposure to campus environments; in fact, one could
effectively argue that the campus context shapes the process and outcome of research in
environmental psychology just as it does for other fields. Second, student affairs personnel
have secured a prominent place in higher education. These professionals, whose mandate
includes responsibility for administration of campus living spaces, activities, and conduct,
have evidenced interest in ecological perspectives and recognized clearly that a student’s
collegiate experience is contextualized by a campus system comprised of social, (multi)
cultural, spatial, and physical factors. Indeed, the academic and professional journals in
college student personnel have endorsed ecological approaches to campus design (e.g.,
Banning & Kaiser, 1974). Third, campus mental health professionals, particularly
counseling psychologists, whose training usually affords substantial exposure to college-age
1

2
populations, are keenly aware of mental health issues on campus and often work from a
developmental perspective concerned with psychological (and geographical) transitions.
Fourth, other researchers, principally geographers and sociologists concerned with the
impact of place, could contribute to the understanding not only of measurable
environmental impact but also, more qualitatively, of genius loci, the spirit of place, the
totality of a landscape, encompassing intangible and transcendent qualities that account for
the uniqueness of place (Seamon, 1989).
Given the diversity of intellectual traditions that can profitably address the role of
physical environment in the psychological experience of college students, the relative dearth
of research is disappointing. Perhaps the relevant disciplines are so divergent in training
and practice that fruitful cross-disciplinary collaboration is seldom afforded. Indeed, the
current study is, of necessity, focused on a limited number of research perspectives and
analytical methodologies. Taylor, Zube, and Sell (1987) offer a useful classification system
for research evaluating landscapes. Their nomenclature distinguishes four approaches to
landscape research: the psychophysical, cognitive, expert, and experiential. The
psychophysical and cognitive approaches both focus on human responses as measured by
quantitative techniques, often self-report of scenic beauty estimates or landscape preference;
the two approaches are distinguished from each other chiefly by the emphasis placed on
human information processing theory. Whereas the psychophysical approach typically
assumes that humans are passive (and unconscious) responders to the environment, the
cognitive approach holds that structures and needs of our information processing systems
mediate our experience of the environment. Thus, in the psychophysical paradigm,
psychological responses to environmental stimuli are measured; in the cognitive paradigm,

3
however, theory derived from cognitive psychology helps explain why certain
psychological responses are obtained. The expert paradigm holds that those best qualified
to evaluate landscape achieve such status only through heightened sensitivity inculcated by
professional training. Such evaluations may be more subjective that those of
psychophysical and cognitive methods, but the persons making decisions presumably have
a more sophisticated perspective derived from education and work experience. The fourth
paradigm, the experiential approach, focuses on the experience of diverse individuals or
groups and usually employs qualitative, often phenomenological, methodology. A
graphical summary of these approaches is presented in Table 1-1.
Table 1-1: Paradigms for Landscape Evaluation
Paradigm Methodology Ratings given by Theoretical focus
Psychophysical
quantitative
laypersons
stimulus-response
Cognitive
quantitative
laypersons
infonnation processing
Expert
qualitative/quantitative experts
expert design
Experiential
qualitative
laypersons
humanistic/phenomenological
The approach taken in the present research is best represented by the psychophysical
and cognitive paradigms. The approach is psychophysical because it attempts to
demonstrate linkages between specific environmental features and psychological outcomes.
However, it is cognitive, as well, inasmuch as theoretical assumptions about psychological
reaction to environmental stimuli were used to generate hypotheses. In another manner, this

4
study is conceptually distinct from “mainstream” landscape research. The latter tends to
operationalize psychological reaction in terms of preference; in contrast, the present study is
expressly concerned with psychological adjustment as a criterion measure. Thus,
psychological outcomes of importance here include not preference but impact on mental
health in the domains of depression, anxiety, substance abuse, interpersonal distress,
among other areas.
In the chapters that follow, these issues are addressed both theoretically and
empirically. Chapter 2 reviews the extant literature in counseling/clinical psychology,
environmental psychology and college student personnel. The chapter begins with a
treatment of ecological approaches that place the student into an integrated, transactional
environmental system (e.g., Kaiser, 1977). The subsequent section reviews existing
research on the impact of environmental features on psychological well-being and recent
calls for a more transactional understanding of psychological functioning. The following
sections summarize findings of the student affairs literature (e.g., Chickering & Reisser,
1993) regarding characteristics and needs that distinguish commuters from residential
students, concluding that the extant literature has neglected, for the most part, psychological
measures of differences. A methodological critique then proposes alternative measures of
adjustment that would better operationalize psychological status: the College Adjustment
Scales (CAS; Anton & Reed, 1991) and the College Maladjustment Scale (Mt; Kleinmuntz,
1960). The next sections summarize the psychological benefit of specific environmental
features, such as nature scenes (Kaplan & Kaplan, 1989; Ulrich, 1981), windows (Butler &
Biner, 1989), and configural aspects of landscape (Campbell, 1994; Herzog, 1989, 1992;
Kaplan & Kaplan, 1989). In addition, this section includes a brief review of detrimental

5
features, such as crowding (Evans & Lepore, 1993; Krupat, 1985; Milgrana, 1970), noise
(Levy-Loboyer & Naturel, 1991) and barriers to commuting (Novaco, Kliewer, & Broquet,
1991). Chapter 2 concludes with a summary of the rationale for the present study and a
series of tentative research hypotheses.
Chapter 3 details methods and research design, including sample characteristics,
psychometric characteristics of the research instruments, procedural protocol, and the
general strategy for data analysis. This last topic includes discussion of the methodological
challenges inherent in multivariate quasiexperimental design, as well as the rationale for use
of multivariate analysis of variance (MANOVA) with a series of follow-up stepwise
multiple regression equations. This section also reviews some unanticipated problems in
protocol administration leading to the exclusion of College Maladjustment Scale scores
from the final data set.
Chapter Four presents results in several sections. First, a descriptive summary of
predictor and criterion variables is offered. Second, results of MANOVA analyses
demonstrate the significance of predictor variables for scores on the nine-scale College
Adjustment Scales. Third, a series of stepwise multiple regression models for each of the
nine CAS scales follows the MANOVA in order to model specific environmental effects on
anxiety, depression, suicidal ideation, substance abuse, self-esteem, interpersonal problems,
family problems, academic problems, and career problems. A fourth set of analyses
examines multicolinearity among the nine CAS scales, as well, via principal components
analysis of the factor structure underlying the CAS. Inadequacies of the factor structure are
discussed, and an alternative measure of global adjustment is proposed. Finally, a
regression model of global adjustment is offered, although this new model, contrary to

6
expectation, offers little additional information relative to models of scores on each of the
nine component CAS scales
The final chapter is a discussion of the present findings and argues that, although
treatment indicators and subject variables are most predictive of adjustment, some
environmental variables (e.g., grass, noise, light, residential satisfaction and, to a lesser
extent, number of roommates) also manifest a relationship with psychological functioning.
The implication of these finding for campus architects, student affairs professionals, mental
health providers, and educational policy makers is discussed. Additionally, the
psychometric inadequacy of the CAS is discussed. The conclusion advocates the use of
alternative measures for future research (1) to avoid the stringency imposed by MANOVA
and (2) to achieve better discriminant validity. The final sections suggest directions for
future research, particularly the integration of quantitative and qualitative approaches
pioneered by researchers such as Schroeder (1991). Such integration simultaneously offers
both testable hypotheses and a fuller understanding of the more intangible, subjective, and
transcendent qualities of place (Relph, 1985; Seamon, 1984, 1989).

CHAPTER 2
REVIEW OF LITERATURE
Campus Ecology as Context
The psychological adjustment of college students has received substantial attention
in the literatures of counseling psychology and college student personnel. However,
comparatively scant research focus has been directed toward the impact of residential
environment on psychological adjustment. This trend is manifest in spite of a relatively
well-known literature of campus ecology, in which college environments are viewed as
interactive environmental systems (Banning & Kaiser, 1974; Morrill, Oetting, & Hurst,
1974; Pace, Stamler, Yarris, & June, 1996). Although the importance of physical
environment is usually acknowledged in ecological models, greater emphasis has been
placed on sociocultural, interpersonal, and academic factors; as a result, physico-spatial
aspects of college student adjustment have been relatively neglected.
Nonetheless, it is appropriate to begin this review with an explication of campus
ecology as context for the present study. Although this research focuses on one, relatively
narrow, aspect of college environment, the study here presented is most thoroughly
understood in the context of campus ecological systems which are integrative,
comprehensive, and most especially, transactional in nature.
Campus ecology is concerned both with the student’s “consciousness” and the
environment in which he or she lives (Kaiser, 1977). The campus environment consists
7

8
of varied spaces: the personal, the social, the physical, the academic and any number of
others relevant to the experience of the student. Campus spaces are settings for student
growth and development and, thus, are integral parts of the college experience. This view
obviates the need for considered attention to space by campus designers and policy
makers:
Every learning space has a demand load. It calls for certain responses from the
student entering the space. A student and campus may be matched or mismatched.
A mismatched space is one that fails to provide what the student needs or demands a
response the student cannot give. Too great a mismatch is stressful for the student
and may generate a negative reaction (Kaiser, 1977, p. 24).
The student’s experience is shaped by the college environment, but the relationship
is not simply one of causative factor to responding organism. Rather, a more dynamic,
holistic conceptualization, in which students in environment are the primary unit of
analysis, is taken here. This approach, developed by Altman (see Altman & Rogoff, 1987
for delineation of this view) and expanded by others (cf. Wapner, 1995), is characterized by
a systems-centered perspective that, when applied to campus environments, holds that
students are integral components of the larger campus environmental system. Such an
approach suggests that the process of influence is mutual among interconnected elements.
That is, a college student’s experience is molded by multiple elements of the environment,
but that same student—and, by extension, larger groups of students—is also an active shaper
of the environmental system, because he or she belongs to that system. This view implies
that the personal characteristics which students bring to college, including life history,
personality traits, and psychological (dys)function become important influences in the
person-environment system. In terms of the present study, this theoretical perspective

9
suggests that the decisions students make about their residential choice will be impacted by
personal and environmental factors, and that students’ college housing environments will
act to shape their educational experience and psychological well-being.
Campus mental health professionals have shown some interest in an ecological
conceptualization of student functioning, although a review of the literature suggests that
this perspective has been limited in scope and influence. Morrill, Oetting, and Hurst (1974)
proposed a framework for counseling interventions not limited to the therapy room. Their
model, delineated in terms of target, purpose and method of intervention, expands the target
domain of campus counseling staff from the traditional individual client to include primary
groups (friends and family), associational groups (e.g., classes, student organizations and
residence-based groups), and, most broadly, the institution or campus community. This
model also expands method of service delivery beyond direct therapeutic contact to
consultation, training and use of media. Finally, the purpose of intervention is defined to
include, in addition to remediation of psychological difficulties, the more proactive goals of
prevention of mental health problems and development of individuals and campus systems.
This framework justifies, from the perspective of campus mental health providers, the need
for collaborative systems-focused research and intervention in a number of areas relevant to
the psychological health of students. A recent expansion of this model (Pace, Stamler,
Yarris, & June, 1996) places campus counseling centers in a more dynamic ecological
system, allowing greater flexibility to adapt functions to changing campus needs. That is,
campus mental health professionals are seen as connected to multiple constituencies and
facets of the campus system; services evolve as a function of these interrelationships.
Although these models certainly broaden the legitimate domain of college mental health,

10
neither addresses explicitly the psychological aspects of residential environment. Similarly,
a recent prescription for expansion and adaption of college counseling center services
(Bishop, 1990) advocates broader collaboration and consultation with other campus entities;
again, however, the psychological aspects of place and physical environment are not
explicitly addressed. The interface of college counseling and environmental psychology is
best described as a legitimate but largely unexplored area of inquiry. I now turn to a review
of available literature in this and allied areas.
The Interface of Research in Environmental and Counseling /Clinical Psychology
The environmental psychology literature is a potential arena in which to address the
psychological impact of campus residential environments. Indeed, recent appraisals of the
field have stressed the potential for fruitful integration of environmental and counseling or
clinical psychology. Stokols (1995) highlights recent trends and prospects for future work
in the application of enviromnental psychology research to community problems, including
the development of environmental strategies in health promotion. He cites several recent
theoretical and basic research endeavors to document the contributions of psychology to
social and psychological welfare. These include a number of efforts to understand the
processes by which environmental stress can be ameliorated, through reduction of crowding
(Aiello & Baum, 1979), better management policy for environmental hazards (e.g.,
Cvetkovich & Earle, 1992), and increased exposure to natural environments in offices and
health care settings (Kaplan & Kaplan, 1989; Ulrich, 1981, 1984, 1991).
Demick and Andreoletti (1995) review a number of recent studies in order to
elucidate connections between environmental and clinical psychology. The authors

11
distinguish between fields in terms of content and method, positing that clinical psychology
is defined by its content area (i.e., diagnosis and treatment of psychological conditions) as
well as a method of research and clinical practice. Environmental psychology, similarly, is
identified by its concern with physical, interpersonal, and sociocultural environmental
factors and by a more general world view of organism-environment functioning.
Demick and Andreoletti posit several conclusions regarding the integration of
clinical and environmental theoretical perspectives and research methodologies. First, they
suggest that broad, integrative perspectives in both fields tend to produce novel research
foci, such as the impact of physical relocation on an inpatient psychiatric community
(Demick & Wapner, 1980) or the role of personal space in therapy or clinical supervision.
The present study is one attempt to respond to the call for cross-disciplinary research.
Second, Demick and Andreoletti conceptualize environmental perspectives as an alternative
to traditional person-centered approaches to diagnosis and treatment; that is, “the unit of
analysis in psychopathology might more aptly be conceptualized as the person-in-
environment system” (1995, p. 65). Although the research cited to support this notion
focuses primarily on quite disturbed psychiatric patients, particularly those with
schizophrenic diagnoses, this conceptualization applies analagously to college students, for
whom adjustment, in this model, would be a function of the student-in-campus-community
system. Finally, Demick and Andreoletti propose a model of psychological functioning in
terms of a series of environmental transitions throughout the lifespan. The transition to a
college community (and developmental transitions within the community) are relevant to
the present study, which focuses on the role of residential environment in transition to and
function in the college setting.

12
Interestingly, the initial base of college environment research comes not from
environmental or clinical psychology but rather from the fields of higher education and
college student personnel. These early investigators were motivated by pragmatic concerns
in response to the changing demographic characteristics of American undergraduates in the
1960s; they sought to provide empirical bases for policy adjustment both in academic
affairs and in student life as colleges and imiversities struggled with the influx of commuter
and part-time students. This new wave of students, as a group, entered higher education
with significant differences from traditional residential students in educational background,
family experience, and perhaps most importantly for policy makers, educational goals and
expectations. These new students encountered a number of difficulties relative to the modal
college student of the 1950s and challenged core assumptions of traditional policy makers
in higher education. The challenge was met with empirical research.
Residential Status and the Welfare of Commuter Students
Student development researchers and professionals have devoted considerable
attention to the divergent experiences of commuter and residential college students during
the last three decades. Chickering (1974) provides the first book-length treatment of the
subject in a comprehensive account of a large-scale study involving over 160,000 students
from 270 diverse post-secondary institutions. Most publications have stressed the benefits
afforded to students whose on-campus residence facilitates access to peer networks and to
residence life programs offered by student affairs staff. With few exceptions, the distinction
between off-campus residents and commuters living at home has been neglected; this is a
crucial shortcoming, because it confounds the impact of family influence with residential

13
location. Moreover, increasing numbers of college students have elected to live off-
campus, even when they are in school a long distance from their family’s home, in response
to rising room and board costs as well as campus housing shortages. I begin with
Chickering’s work, which has provided the base-line for subsequent investigation. I
consider additional research in the paragraphs that follow, in order to generate hypotheses
regarding the psychological impact of residential location.
Chickering (1974; see also Chickering & Reisser, 1993) provides a thorough
empirical summary of significant differences in demographic background and college
experience between commuter students and on-campus residents. Commuter students, in
his sample, reported lower high school grades, and increased financial and interpersonal
stressors. Their families of origin were of lower socioeconomic status, measured in terms
both of reported income and of paternal occupation (fathers of commuters were more likely
to be skilled, semiskilled, or unskilled workers). Chickering also reported that the majority
of commuter students applied only to the college or university which they currently
attended. Their educational goals were more focused on vocational preparation than those
of residential students; in fact, commuters more frequently majored in business
administration or engineering. Moreover, commuters were less likely to report plans to
seek an advanced degree. Thus, Chickering’s data suggest that commuter students enter
college significantly constrained by contingencies external to their educational
environments and tend to plan their education on the basis of proximity of available
programs and the practicality of their degrees. Many of these students attend institutions
with primarily or exclusively commuter populations; of course, many also enroll in colleges

14
or universities with strong residential traditions. Indeed, increasing numbers of students are
members of the latter group.
Chickering asserts that commuter students enrolled in residential institutions
experience many of the same external pressures reported by those enrolled in commuter
schools. These contingencies make for an educational experience more fraught with
challenges than that typically experienced by their residential classmates. Moreover,
commuter students often have difficulty developing attachment to the university and its
people as a function of their somewhat marginalized status and limited opportunities for
involvement in campus life. There is good reason, therefore, to expect that commuter
students, whether they attend commuter or residential schools, will report greater
difficulties in terms of personal and psychological adjustment. In fact, Chickering found
that commuters living with family had the least frequent interactions with faculty when
compared to residential students or those living in off-campus housing. This deficit was not
confined to relationships with faculty, since commuters living at home were also the least
likely to study with their classmates. Moreover, students living in private off-campus
residences were the least satisfied with their college experience and the least likely to report
plans to continue full-time study. These myriad differences in experience held true for
students enrolled in every category of educational institution included in Chickering’s
sample, including universities and colleges, public and private schools, two-year and four-
year programs, and Protestant and Catholic institutions.
Other researchers have demonstrated similar differences, though not with absolute
consistency. Graff and Cooley (1970) assessed differences between dormitory residents
and commuter students (living at home) using the College Inventory of Academic

15
Adjustment (Borow, 1951). At the conclusion of the first semester of their first year, the
two groups did not differ significantly on scale measures of study habits, interpersonal
relationships with faculty and peers, or personal efficiency (time management). However,
commuter students reported poorer curricular adjustment, in terms of satisfaction with
course work and maturity of goals and aspirations. Moreover, commuters reported poorer
mental health on a scale associated with poor self-confidence, feelings of failure and
excessive worry. These differences were independent of ability levels measured by the
verbal section of the Scholastic Aptitude Test. On the basis of these results, Graff and
Cooley recommend that college counseling centers promote the availability of services for
commuters, that special orientation programs be targeted to commuter students, that faculty
be sensitive to the needs of their commuter advisees, that student unions provide special
facilities for off-campus students, and that campus activities personnel endeavor to make
commuters aware of available programs.
George (1971) found few significant personality differences on the Edwards
Personal Preference Schedule (1959) between high school seniors planning to live on
campus during their freshman year and those planning to commute from home. In fact, the
most powerful predictor of students’ decisions was not a personality trait but, rather, the
socioeconomic status of their family of origin. Commuters students did show greater needs
for autonomy and dominance, while residential students showed greater needs for change
and aggression. However, the importance of these personality differences is questionable,
given the very small magnitude of their impact. George’s statistical analysis is reported
rather telegraphically, but his research nonetheless malees clear that the predictive utility of
the model is low. An aggregate stepwise multiple regression procedure, in which familial

16
socioeconomic status accounted for the lion’s share of the variance, explained only about 9
percent of the variation in residential choice.
In a similar study, Welty (1976) reported a number of significant personality
differences between first-year students living in dormitories and those living with parents.
Commuters had lower scores on the intellectual disposition, thinking introversion,
estheticism, complexity, autonomy, and altruism scales of the Omnibus Personality
Inventory. Each of these differences, with the exception of autonomy scores, was
maintained when the students were retested at the end of two quarters. In addition,
dormitory residents participated more frequently in extracurricular activities and fonned
more new relationships with students and faculty. Welty concludes that student growth is
not simply a function of living situation but rather that the formation of these relationships
(presumably afforded by on-campus residence) is a critical developmental factor.
More recently, Wilson, Anderson, and Fleming (1987) found that commuter
students reported more psychological difficulties than residential students, in terms both of
personal maladjustment and of overinvolvement with parents. Their research
operationalized adjustment in terms of family systems theory, particularly the concept of
fusion, which is defined as the tendency for two individuals to blend in such a way that
emotional and psychological boundaries between them become blurred, confused, or
overlapped. Family therapy research suggests that such relationships are unhealthy because
they inhibit self-determined, goal-directed activity. Using the Intergenerational Fusion
subscale of the Personal Authority in the Family System Questionnaire (Bray, Williamson,
& Malone, 1984), Wilson and colleagues demonstrated that first-year college commuter
students had significantly higher fusion scores than those of dormitory residents; this trend

17
was not observed, however, in more advanced students. This study also measured more
general psychological adjustment using the College Maladjustment Scale (Mt; Kleinmuntz,
1960, 1961) of the Minnesota Multiphasic Personality Inventory (Hathaway & McKinley,
1943). Students living with their parents reported greater levels of maladjustment than on-
campus residents, regardless of their year in school.
Finally, Pascarella, Edison, Nora, Hagedom, and Terenzini (1996) found, in a large-
scale correlational study, that on-campus residence was an important predictor of openness
to diversity and challenge among first-year college students. Controlling for the
contribution of multiple other predictors, including demographic variables, institutional
environment, social life, and academic experiences, Pascarella and colleagues found that
on-campus residence was a significant predictor of students’ openness to ethnic and cultural
diversity, as measured at the conclusion of the freshman year. Thus, campus residence may
play a role not only in current levels of psychological adjustment but also in future ability
to maintain interpersonal adjustment in an increasingly multicultural environment.
The research reviewed thus far provides empirical documentation of the differences
between students living with family and those residing in college dormitories. The
problematic position of these commuters is assumed to have some relationship with
variables intrinsic to the family of origin, primarily socioeconomic context or some
functional pathology in the family system (especially with regard to the student’s ability to
develop a well-defined extra-familial identity). What of the growing number of commuters
choosing to live off-campus in private housing, away from family? These students may
experience difficulties solely as a function of their relative isolation from the campus

18
community. Are the psychological correlates of commuter status observable independently
of students’ relationships with their families?
Scant study of this group of students is reported in the literature. However, the
stressful consequences of commuting have been observed in other settings and with other
populations. For example, Novaco and colleagues (1990, 1991) have conducted an ongoing
research program demonstrating the deleterious effects of objective and subjective
impedances encountered by commuters who drive daily to and from work. The negative
impact of these impedances is evident in terms of commuters’ negative mood at home,
measured using a short semantic differential scale, and dysphoria, measured using a sub-set
of items from the Global Stress Scale (Cohen, Kamarck, & Mermelstein, 1983). In the
present study, off-campus residents should experience impeded access to campus relative to
their peers residing in dormitories; thus, such students should report greater adjustment
difficulties, especially as the distance of their residence from campus increases.
Methodological Critiques
The existing research on commuter students has stimulated greater awareness,
policy changes and impetus for further inquiry. However, the literature is subject to critique
for a number of reasons. First, most research has failed to make explicit distinctions
between commuters residing with their family of origin and those simply electing to live off
campus alone or with non-family members. This latter group is likely to continue to
increase at institutions whose enrollment expansion is outpacing construction of new
dormitories. Second, a shared definition of adjustment has been evident neither in multiple
research conceptualizations nor in the wide variety of criterion measures used to
operationalize student functioning. This phenomenon is due, in part, to the multifaceted

19
nature of adjustment, a concept which connotes multiple domains of student well-being.
However, extant shortcomings in the measurement and conceptualization of adjustment
limit our miderstanding of environmental impact.
Psychological adjustment is an important component of comprehensive adjustment,
but psychological measurement probably has not been adequately operationalized in the
studies reviewed. First, many of the measures are not well-validated clinically, because
their primary application has been as research scales (e.g., the Global Stress Scale). Second,
many measures address differences in personality style or preference. These differences
provide interesting information, but they do not address psychological problems directly;
that is, differences in personality styles do not necessarily offer information regarding the
presence of, or even the potential for, psychological difficulties. Thus, personality measures
have limited utility for clinicians seeking to understand any hypothesized negative
consequence of living environments, as well as for policy makers seeking more conclusive
demonstration of environmental impact. The clinical scales that have been employed, such
as the family fusion measure used by Wilson, Anderson and Fleming (1987), tend to focus
on narrowly-defined criterion variables rather than on the typical range of mental health
problems seen in a college population.
A broad-based, well-validated clinical measure of psychological adjustment would
provide a more useful measure of residential impact. Only one of the reviewed studies
(Wilson, Anderson, & Fleming, 1987) has employed such a general clinical measure, the
College Maladjustment Scale (Kleinmuntz, 1960) of the MMPI. The College

20
Maladjustment Scale (Mt) is a 41-item1 supplementary scale embedded in the original
MMPI (Hathaway & McKinley, 1943) and retained in the revised Minnesota Multiphasic
Personality Inventory-2 (Butcher, Dahlstrom, Graham, Tellegen, & Kraemmer, 1989). The
scale was developed by Kleinmuntz (1960) via item analysis of the original MMPI to
differentiate college students seeking psychotherapy from the general student population.
The items tap diverse issues, including perceived ineffectualness, diminished interest,
procrastination, life strain and anxiety. Efforts to develop criterion cutoff scores have been
problematic (Kleinmuntz, 1961; Kuczka & Handal, 1990). The scale is not a particularly
good predictor of potential psychological difficulties (Parker, 1961; Dahlstrom, Welsh, &
Dahlstrom, 1975) but has utility in terms of identifying levels of current maladjustment
among students in a college setting (Graham, 1993). Importantly, the Mt, because it is an
omnibus scale, does not allow distinctions among different types of psychological
difficulties. The scale criterion is simply the prediction of seeking counseling center
services; the clinical interpretation of high Mt scores was based only on informal content
analysis of the component items. Thus, the Mt is a poor research instrument if one wishes
to make distinctions among the qualitatively distinct adjustment issues (e.g., depression,
anxiety, self-esteem, substance abuse) that students experience in college.
Until recently, a comprehensive instrument to measure psychological problems of
college students has been unavailable. The MMPI-2 is certainly a potential candidate, but it
was designed for persons experiencing a greater degree of pathology than is typical for
college counseling centers. When used with a less disturbed population the psychiatric
1 The original MMPI (Hathaway & McKinley, 1943) Mt scale contained 43 items.

21
norms of the MMPI tend to exaggerate individuals’ level of psychopathology. Moreover,
the length of administration required for a full MMPI can be nearly two hours, making the
instrument impractical for a time-limited data collection. The California Psychological
Inventory (CPI; Gough, 1987) is another potential candidate and has been widely-used with
the demographic group targeted in the current study. In fact, CPI normative data are more
appropriate for college students; however, the constructs measured by the instrument are
more descriptive than diagnostic.
A more recent instrument, the College Adjustment Scales (CAS; Anton & Reed,
1991) seems a better candidate for research with college populations. The CAS is a 108-
item screening instrument designed to identify and categorize types of psychological
maladjustment presented by students at university counseling centers. The scales were
developed and normed specifically for college populations. The CAS content areas were
selected on the basis of a principal components analysis of an intake problem checklist at a
college counseling center (Hicks, Reed, & Anton, 1989, cited in manual) and on a survey of
assessment needs endorsed by campus counseling center care providers. The final version
of the CAS included nine classes of psychological difficulty: anxiety, depression, suicidal
ideation, substance abuse, self-esteem problems, interpersonal problems, family problems,
academic problems, and career problems. Each scale consists of an equal number of 4-point
Likert scale items; the entire CAS can be administered to participants in 15-20 minutes.
The CAS was normed on a sample of 1,146 students from a geographically diverse
group of U.S. colleges. The sample was representative of the gender and ethnic
composition of the American college student population. The CAS Manual (Anton &
Reed, 1991) contains a full description of the initial validity studies. Internal consistency

22
reliability ranged from .80 to .92 for the component scales; Anton and Reed also provide
preliminary convergent and discriminant validity data. Although a relatively new
instrument, the CAS has been used in several recent studies of college age populations
(Chandler & Gallagher, 1996; Heppner et al., 1994; Street, Kromrey, Reed, & Anton, 1993;
Turner, Valtierra, Talken, Miller, & DeAnda, 1996).
The Impact of Physical Environmental Features on Well-Being
The preceding section examined the effects of residential location and commuting
on psychological adjustment. Another important question regards the contribution of
housing environment. The second area of focus in the present study regards the influence of
specific environmental characteristics of student housing on personal and psychological
adjustment. This area of inquiry is better grounded theoretically than that, previously
discussed, of residential location. As a group, the studies discussed in the following
sections are vulnerable, to some degree, to the same criticism regarding the operational
definitions of adjustment that were noted in the review of commuter research. That is,
although a number of different measures, often simply preference scores for particular
enviromnental features, have been employed, specific measures of psychological problems
have seldom been used. However, the relationship of environment to well-being has often
been more compellingly demonstrated, especially through use of psychophysiological
correlates of stress (i.e., autonomic responses). What follows is a review of empirical
research on the environmental characteristics of housing which are potentially relevant to
the psychological well-being of college students.

23
Windows
Early literature in this area suggests that windows, particularly those that afford a
view of natural landscape elements, have a dramatic positive impact on well-being. Ulrich
(1981) demonstrated that the beneficial impact of natural scenes can be measured in terms
of psychophysiological correlates of relaxation, such as respiration rate, heart rate and
galvanic skin response. Subsequently, Ulrich (1984) demonstrated that window views of
nature positively influence the recovery of surgical patients. Patients whose hospital rooms
afforded views of nature scenes (e.g., water and deciduous trees) had more positive post-
surgical prognosis as measured by a number of measures, including recovery time, need for
medication, and report of pain.
More recent research (see Sundstrom, Bell, Busby, & Adams, 1996, for a review)
suggests that the impact of windows is more complex and is mediated by social, contextual
and environmental variables. For example, Butler and Biner (1989) found that students did
not prefer window views in spaces where they might provide a functional impediment, such
as computer workrooms. Previous work in this area raises the possibility that the presence
of windows will influence both students' ratings of residential satisfaction and associated
psychological adjustment.
Natural Landscape Elements
Stephen and Rachel Kaplan have published decades of research on the
psychological benefits of nature. Their theory posits that natural environments are preferred
because they facilitate restoration of attentional capacity, fatigued by the sustained focus
often required by the myriad competing stimuli of the modem world (Kaplan & Kaplan,
1989). The negative impact of sensory overload in modern urban environments—socially

24
and psychologically—has been identified as a major quality of life issue (Milgrarn, 1970;
Krupat, 1985). Natural environments, in contrast, elicit effortless attention ox fascination,
processes central to the Kaplans’ theory. That is, natural landscape elements promote the
recovery of attention through the effortless engagement of sensory systems, resulting in an
experience both pleasurable and restorative. This restorative experience has tangible impact
on psychological and physiological wellness.
On the physiological level, natural environments promote stress reduction through
stimulation of the parasympathetic nervous system (Ulrich et al., 1993). The calming
effects of exposure to natural scenes have been documented repeatedly (e.g., Ulrich, 1981).
Natural landscapes, especially those including water and biomatter, appear to reduce blood
pressure, galvanic skin response, respiration rate and self-report of stress. Additional
evidence (Ulrich, 1984), mentioned in the previous section, suggests that natural views
positively influence the recovery of post-surgical patients.
Which elements of the natural landscape are most important? A useful distinction
between configural elements and primary content of landscape clarifies the question. The
former refers to the way in which objects are arranged in the stimulus array. Research has
shown that landscapes that provide a sense of coherence (hanging together) and mystery
(the promise of new information to be gained by exploration) are especially preferred (e.g.,
Campbell, 1994; Herzog, 1989, 1992; Kaplan & Kaplan, 1989). Primary content includes
the specific objects present in a given landscape. Research has consistently indicated that
humans prefer both greenery, particularly tended nature (i.e., manicured gardens), and water
scenes.

25
Crowding
Two decades of study have documented the deleterious effects of residential
overcrowding on the psychological well-being of dwellers. A number of studies have
demonstrated the association of crowding with residential dissatisfaction (see Krupat, 1985;
Sundstrom, Bell, Busby, & Asmus, 1996). This dissatisfaction is associated with increased
levels of psychological stress experienced by persons living in such conditions. Moreover,
there is considerable theoretical and empirical evidence that crowding negatively impacts
willingness to offer and accept social support. Milgram (1970), in an analysis of the
experience of urbanites, suggests that this effect is a function of overload on individuals'
social and cognitive capacities; the result is a social withdrawal to manage inputs to an
overtaxed sensory system. In a study of college students, Lepore, Evans, and Schneider
(1991) demonstrated that persons living in crowded environments experience greater
psychological distress, even when controlling for levels of distress prior to their current
living arrangements. Evans and Lepore (1993) found that college students from crowded
residences were less likely to offer, accept, or perceive social support in a laboratory
experiment. The robustness of crowding effects underscores their relevance for the
proposed study; a measure of residential population density should be included as a
predictor variable.
Noise
The detrimental impact of noise has been demonstrated in a variety of contexts,
including neighborhoods (Levy-Leboyer & Naturel, 1991) and shopping malls (Hopkins,
1994). The modal investigation of ambient noise has operationalized impact in terms of
task performance or self-report of annoyance. Thus, examination of effects in terms of

26
psychological adjustment is a somewhat novel approach. An objective measure of decibel
level in housing environments is beyond the logistical scope of the proposed study.
However, incorporating students' Likert-scale ratings of noise level in their homes as a
predictor variable should yield important information about the subjective importance of
ambient noise to participants.
Rationale for the Present Study
This study is distinguished from previous work on residential satisfaction of college
students by an explicit focus on psychological adjustment as a dependent measure. While
the importance of satisfaction ratings is salient to planners, architects and housing directors,
the psychological impact of residential environment is important not only to these groups
but also to mental health professionals. Thus, I propose to incorporate, in addition to a
measure of simple satisfaction, two psychometrically validated measures of adjustment: the
College Maladjustment Scale of the Minnesota Multiphasic Personality Inventory (Mt;
Kleinmuntz, 1960) and the College Adjustment Scales (CAS; Anton & Reed, 1992). Each
measure will be described more fully in the materials section of this paper. This emphasis
on psychological functioning fills a theoretical vacuum in the existing literature on college
residential environments. More specifically, the current study allows an evaluation of
environmental factors not limited to simple preference, but concerned as well with the
psychosocial correlates of environmental design. A psychological evaluation of housing
environments forms a more direct link between the structure of a home and the adaptive
functioning of its residents.

27
The current study examines two primary aspects of the relationship of residential
environment with psychological adjustment of college students. First, this study will
provide the opportunity to assess the relative importance of residential crowding, residential
location, noise level, distance from campus, and access to windows in predicting current
levels of psychological adjustment. My decision to incorporate these predictor variables
(and, consequently, to exclude others of potential importance) is a function both of
pragmatism and of attention to the existing literature on residential environments. A limited
number of variables is necessary to ensure the feasibility of this study. Moreover, these
particular variables were chosen in part because they are amenable to quantitative analysis.
More abstract phenomena (e.g., sense of place, architectural coherence, and the like) are
certainly of great interest but would require a fundamentally different, more qualitative,
analytic strategy. An additional consideration was the particular relevance of these
variables for prescriptive policy recommendations. Change of each variable in the proposed
study is readily accomplished via either architectural design or modification of residence
life policy. Finally, this set of variables is clearly consistent with the "mainstream"
literature on residential environments and, therefore, is an appropriate point of departure for
an investigation into this special type of home, the campus community.
Second, this study provides a geography of student adjustment that allows
formulation of spatially targeted interventions by counseling center or other university staff.
That is, this analysis should provide a rough map of the need for psychological services
and, perhaps, the differential spatial distribution of certain types of psychological distress.
An understanding of the impact of residential environment on the psychological
functioning of college students should be useful for a diverse group of professionals,

28
including campus psychologists or counselors, student affairs professionals, campus
planners and dormitory architects. One goal of this study is to elaborate a geography of
college student adjustment that will allow spatially targeted interventions. In addition, such
information may be of use to prospective and current college students making decisions to
enhance their academic and personal functioning.
Research Hypotheses
1. Resident students should report greater overall levels of psychological adjustment
than commuters. If this effect is independent of psychological status at time of admission,
then this hypothesis will remain viable even when pre-college mental health care is entered
as a covariate. This procedure will control for the possibility that maladjusted students
show a greater tendency to isolate themselves geographically from campus life. Since this
is not a longitudinal study, the control procedure is necessary for this and all subsequent
comparisons of adjustment levels.
2. If proximity to campus facilitates social integration, then, among off-campus
residents, those living closer to campus should report fewer adjustment difficulties.
3. Students living with their family should report more adjustment difficulties than
those living on-campus or off-campus not in the family home.
4. Residential population density should be negatively associated with
psychological adjustment and residential satisfaction. Previous research suggests a ceiling
effect such that levels of satisfaction cease to decline beyond a certain density; however,
extremely high residential densities are probably not common in a population with these
demographic characteristics.

29
5. Reported level of noise should be inversely related both to overall levels of
psychological adjustment and satisfaction with living environment.
6. Elements of natural landscape visible from residences should correlate positively
with adjustment; that is, the presence of adequate light, water, trees and grass in residential
window vistas should be associated with better overall levels of psychological adjustment.

CHAPTER 3
METHOD
Participants
Participants were undergraduate volunteers from psychology classes at the
University of Florida (a large state university with approximately 40,000 students), the
University of Wyoming (a small state university with approximately 10,000 students), and
New College of the University of South Florida (a primarily residential liberal arts honors
college with approximately 600 students). Research instruments were distributed to 206
students from these institutions; 191 forms were returned; seven forms were incomplete
and unusable, leaving 184 cases included in the data analysis.
Participation was subject to Institutional Research Board approval and the ethical
guidelines of the American Psychological Association. Participants were provided with
both written and verbal informed consent statements. Students did not receive monetary
compensation for their participation; on two occasions, however, extra credit points were
awarded to students who completed the survey. A copy of the informed consent statement
is included in Appendix A.
Institution. Of the 184 participants in the final sample, 125 (68%) were students at
the University of Florida. Thirty-five (19%) were from New College of the University of
South Florida; the remaining 24 students (13%) were from the University of Wyoming.
30

31
Ethnicity. One hundred forty-six participants (79%) reported white/non-Hispanic
ethnicity. The second largest group (15 students or 8%) endorsed Asian/Pacific Islander.
Nine Hispanic/Latino(a) students constituted 5% of the sample. Four percent (n=7)
students were African-American. Four students (2%) reported ethnicity as “other.” Three
students declined to indicate ethnic background.
Gender. Sixty-seven percent (n=124) of respondents were women. Men comprised
32% (n=60) of the sample.
Age. Reported age ranged from 17 to 49 years for the 183 participants who
provided information. Mean age was 19.75; standard deviation was 3.68.
Year in college. Students’ number of semesters in college ranged from one to 14.
The mean number of terms in college was 3.04; the standard deviation was 2.57.
Marital status. Only 2.7% (n=5) of the sample endorsed the “married” category.
Sexual orientation. One hundred eighty-three participants indicated their sexual
orientation. The vast majority of students (95%) endorsed the “heterosexual (straight)”
category. Six students (3%) reported they were bisexual. Three students (2%) endorsed the
“gay/lesbian” category.
Fraternity or sorority membership. Only two students (1.1%) reported membership
in a campus Greek organization.
Materials
Participants first completed a 25-item written questionnaire including demographic
items as well as questions regarding predictor variables and potential covariates. The latter
sections included infonnation about residential location, type of accommodation, physical

32
aspects of housing environment, residential satisfaction, year in college, and psychological
treatment history. The questionnaire is included in Appendix B.
Criterion measures of adjustment included the 41-item College Maladjustment
Scale (Mt; Kleinmuntz, 1960) of the Minnesota Multiphasic Personality Indicator-2
(MMPI-2; Butcher et ah, 1989). A 43-item Mt was developed for the original MMPI
(Hathaway and McKinley, 1943); a 41-item scale was retained in the 1989 revision.
Although the scale is typically administered in embedded form (i.e., as part of the full 567-
item MMPI-2, Kleinmuntz (1961) provides norms and validation for short-fonn
administration of the scale including only the 43 original Mt items and 42 items from
standard MMPI validity scales.1 The stand-alone Mt was selected for the present study
to ensure single-session administration of the research protocol; the entire MMPI-2
typically requires the majority of two hours to complete. To further expedite
administration, the MMPI validity items were omitted. Although the stand-alone Mt
without validity items has never been validated with reference to the full MMPI, this type of
validation has been performed using other MMPI supplementary scales (cf., Herman,
Weathers, Litz, & Keane, in press); moreover, Kuczka and Handal (1990) provide
validational data for the stand-alone Mt with reference to Langer Symptom Survey (Langer,
1962). Thus, the use of the stand-alone Mt scale can be defended on both empirical and
pragmatic grounds.
1 The additional items comprise the 15-item L scale and the 27-item K-scale. Briefly, the
former is designed to identify persons attempting to fake good by presenting themselves in
an overly-virtuous light; the latter is associated with defensiveness regarding the presence of
psychological problems. These are extensively covered in the MMPI literature (e.g.,
Graham, 1993).

33
The second criterion measure was the 108-item College Adjustment Scales (CAS;
Anton and Reed, 1991). The CAS, described in Chapter 2, is a relatively new instrument
designed to assist college counseling center professionals in screening the mental health
needs of students. As such, the instrument was nonned on a sample composed primarily of
college student, and, therefore, is a logical choice for use in this investigation.
Although the CAS is not a diagnostic instrument, it offers normed data regarding
the type and magnitude of a student’s self-reported adjustment difficulties. The CAS offers
raw scale scores and hnearly-transformed McCall’s T-scores (mean=50; SD=10) for nine
aspects of college student adjustment rationally selected on the basis of screening needs
reported by campus mental health providers. The CAS scales include Anxiety (AN),
Depression (DP), Suicidal Ideation (SI), Substance Abuse (SA), Self-esteem (SE),
Interpersonal Problems (IP), Family Problems (FP), Academic Problems (AP), and Career
Problems (CP). Students respond to twelve four-point likert scale items for each scale;
responses are summed to yield a raw scale score.
Desi gn and Procedure
Participants completed written survey items in class. Students were informed that
this is a study of campus living arrangements and their impact on student life. First, each
participant was provided with written and oral informed consent statements. After item
packets were distributed, students were instructed to first complete the sections requesting
demographic and predictor variable information. Since the psychological items were
potentially evocative of emotional reactions affecting student's ratings of housing

34
environments, the Mt and CAS were presented last in the packet. Students recorded
responses on an anonymous answer sheet. The time required for administration, including
instructions, ranged from 30 to 40 minutes.
Analytic Strategy
The Mt items proved unexpectedly problematic for students to complete, apparently
because answers were to be recorded on a separate scan-tron answer sheet. As a result, a
number of students either skipped the Mt all-together or failed to complete the entire scale.
These procedural difficulties cast serious doubt on the validity of the Mt data; for this
reason, and because the Mt’s predictive validity has been questioned in the literature
(Dahlstrom, Welsh, & Dahlstrom, L.E., 1975), Mt scores were removed from the data set.
A visual examination of the distribution of CAS scale scores revealed that the
distribution of McCall’s T-scores approximated normality more closely than that of raw
scores; therefore, T-scores were chosen as the unit of analysis in the criterion data set.
Since the remaining data set contained multiple conceptually-related dependent variables
(i.e., the nine CAS scales, which are intercorrelated; Anton & Reed, 1991), the first-line
analytic procedure was a multivariate analysis of variance (MANOVA) including all
predictor variables and each scale of the CAS in the criterion variable set.. The MANOVA
was followed by a series of step-wise multiple regression analyses for each predictor
variable that achieved significance in the initial multivariate analysis.
The pairing of an omnibus MANOVA with follow-up univariate analyses is quite
common in the psychology literature and has typically been thought to control for Type-I
statistical error resulting from multiple univariate tests. This assumption has been

35
challenged by Huberty and Morris (1989), who argue that multivariate and univariate
techniques address distinct research questions. The former analyses are appropriate to
address overall effects and, less directly, to explore patterns among and contributions of
outcome variables; the multiple univariate strategy is appropriate when outcome variables
are conceptually distinct, when research is exploratory, or when the dependent variables of
interest have been previously studied in univariate contexts. In this last case, Huberty and
Morris (1989) contend that MANOVAs may be used in conjunction with ANOVAs, if the
appropriate assumptions for each are met. In the present study, the dependent measures are
designed to tap constructs (e.g., depression, anxiety, substance abuse) that have repeatedly
been investigated singularly via univariate analysis. Thus, the two-prong multivariate-
univariate strategy seems justifiable.
A second set of analyses examined the structure of the outcome variable set. This
was accomplished with presentation of a Pearson product-moment correlation matrix of t-
scores for all CAS scales and with presentation of a principal components factor solution
describing the internal structure of the CAS. Principal components analysis is a factor-
analytic technique that reduces a data set to a smaller number of factors that account for a
significant proportion of the overall variance. The procedure yields eigenvalues, which
indicate the relative importance of each factor and factor loadings, which are essentially
correlations indicating the strength and direction of the association of individual variables
with a given factor (Dunteman, 1989).
As is described more fully in the next chapter, the preceding analysis revealed
significant overlap among the CAS scales, casting doubt upon the status of each scale as a
conceptually distinct measure. Since this result implies that the variation in each scale may

36
be attributed to a single factor underlying overall adjustment, a third analysis used a
composite criterion variable intended to measure overall level of college adjustment. This
variable was rationally constructed by computing the average t-score elevation on the CAS.
The single composite measure was amenable to multiple regression; therefore, the final
analysis was a stepwise multiple regression. A stepwise procedure was chosen because the
model allows independent variables to enter the equation in stages according to their
predictive strength. The technique identifies those variables making the most important
contributions to adjustment while simultaneously accounting for both multicolinearity in
the predictor set and the contributions of other variables.

CHAPTER 4
RESULTS
Descriptive Characteristics of the Variable Set
Descriptive statistics for predictor and criterion variables are reported in this section.
Table 4-1 is a summary of the housing types reported by students. The figures reflect a
roughly even split between on-campus and off-campus residents in the final sample. The
majority of on-campus residents resided in a single-room dormitory, although a significant
number reported living in a dormitory suite (i.e., a multiple-room residence, often with a
shared common area). Suite-style accommodations are increasingly popular dormitory
designs; in fact, dormitories currently under construction at New College will offer suite-
style dormitories by fall, 1998. Among the 48.4 % of students residing in off-campus
housing, only a minority (n=l 0) were living with their family of origin. The remaining off-
campus residents lived alone or with roommates; a very small number of married students
lived with their spouses.
Table 4-1: Types of Housing Units
Type
Frequency
%
On-campus
95
51.6
Single-room dormitory
59
32.1
University apartment
2
1.1
Suite (multiple rooms)
23
12.5
Other
11
6.0
Off-campus
89
48.4
Without parent(s)
79
42.9
With parent(s)
10
5.4
37

38
Table 4-2 summarizes selected environmental features reported by students. The
modal student reported one or two roommates, although other living arrangements are
represented in the sample. Mean distance from campus was 2.77 miles; in all cases in
which students resided in on-campus housing, a distance of zero miles was assigned.
Distance from campus varied widely, primarily because a small number of participants in
the University of Florida sample were first-term summer students living at home. Students
reported an average of 2.13 windows in the room in which they spent the most time. The
remaining variables summarized in this section (light, noise, and satisfaction) were each
rated on a seven-point likert scale.
Table 4-2: Environmental Characteristics of Housing Units
Characteristic N Min Max Mean SD
Roommates
184
0
16
1.71
1.59
Distance
184
0
55
2.77
8.33
Windows
181
0
15
2.13
1.82
Light
183
2
7
5.00
1.21
Noise
184
1
7
3.72
1.53
Satisfaction
184
1
7
4.73
1.40
Note: Cases of N<184 are due to
missing
values. Light, noise, and satisfaction were rated
on a 7-point likert scale.
The rooms in which students reported spending the most time are shown in Table
4-3. The classification of rooms was derived from participants’ unstructured self-report,
and categories are therefore tentative. Nonetheless, results indicate that three living spaces
were most utilized by students; these rooms, in order of importance, are bedrooms, family
(living) rooms, and as anticipated for on-campus residents, dormitory rooms. Other types

39
of rooms were cited much less frequently; a small number of blank or ambiguous responses
were placed in the other/not reported category.
Table 4-3: Most Commonly Used Rooms
Room Type
Frequency
%
Bedroom
80
43.5
Study
2
1.1
Family or Living Room
58
31.5
Kitchen
5
2.7
Dormitory Room
34
18.5
Bathroom
1
.5
Other/Not Reported
4
2.2
Table 4-4 summarizes the landscape elements that students reported were visible
from the room in which they spent the majority of time. Trees and grass were the most
common landscape features, reported by 91.3% and 84.8% of students, respectively. A
smaller number of students (14.1 %) indicated that water was visible. In addition, the
majority of students noted the presence of built structures (buildings and concrete) in their
window vistas.
Table 4-4: Visible Landscape Elements in Most Commonly Used Room
Feature
% Reporting
Water 14.1
Trees 91.3
Grass 84.8
Other Buildings 67.4
Concrete 63.6

40
The psychological treatment history of study participants is reported in Table 4-5.
A surprisingly large number of students (28.3%) indicated that they had received some form
of mental health services prior to enrolling at their present educational institution; mental
health services were defined work with a “psychologist, psychiatrist, or other type of mental
health professional for a psychological or personal problem.” Additionally, 12.5 % reported
treatment since beginning study at their current college or university; 8.2 % were currently
in treatment or were planning to seek services within thirty days of the study.
Table 4-5: Psychological Treatment History of Participants
Time of Treatment %
Prior to entering college
28.3
Since entering college
12.5
Currently in treatmenta
8.2
“Includes those planning to seek treatment within 30 days
Table 4-6 lists mean t-scores and standard deviations for each of the nine College
Adjustment Scales (CAS) subscales. A visual examination of this data suggests that the
performance of students in the current study was similar to that of students in the CAS
normative sample, in which the mean t-score and standard deviation for each scale were 50
and 10, respectively. Scale t-score means in the current study ranged from 48.73 (SE) to
51.59 (SI); standard deviations ranged from 9.32 (CP) to 11.43 (SE). Thus, the central
tendency and distribution of scores in the present sample appear comparable to those
previously reported for the general college population.

41
Table 4-6:
Summarv of McCall’s T-
•scores on CAS Scales
Scale
Mean
SD
Anxiety (AN)
50.57
10.33
Depression (DP)
50.30
11.00
Suicidal Ideation (SI)
51.59
9.59
Substance Abuse (SA)
51.03
9.60
Self Esteem (SE)
48.73
11.43
Interpersonal Problems (IP)
50.72
9.63
Family Problems (FP)
50.12
9.54
Career Problems (CP)
50.93
9.32
Academic Problems (AP)
48.73
11.20
Omnibus Analyses
The first stage of analysis employed an omnibus multivariate analysis of variance
(MANOVA) including predictor variables as well as the criterion set, which included all
nine subscales of the CAS. The MANOVA procedures determine the statistical
significance of individual predictors when covariation in the criterion variable set is
controlled. Since a visual examination of scores on the CAS subscales revealed that the
McCall’s t-score distributions more closely approximated nonnality than those of raw scale
scores, t-scores are used in the criterion variable set for this and all subsequent analyses.
Names of predictor variables are abbreviated as follows. SCHOOL represents the
institution presently attended (University of Florida, New College, or University of
Wyoming). SEX denotes reported gender; AGE is reported age in years. TERMS
represents the number of semesters attended at the student’s current institution. TXPRIOR
is a dummy variable representing psychotherapy or counseling prior to enrolling in the
student’s pi'esent school. TXSINCE and TXNOW are dummy variables denoting
psychological treatment since enrollment or at the present time, respectively. MATES

42
represents the number of roommates reported. DISTANCE is a measure of distance from
campus (rounded to the nearest half mile); on-campus residents received a score of zero on
this variable. PARENTS is a dichotomous measure indicating whether the student resided
with his or her family of origin. ON_OFF refers to location of the student’s current
residence (on or off-campus). WATER, GRASS, BUILDING, and CONCRETE are
d ummy codes representing the presence or absence of each landscape feature in the
student’s residential window vista. NOISE and LIGHT are 7-point Likert scale ratings of
noise and light levels in the student’s current residence. SATIS is a Likert scale rating of
reported residential satisfaction.
MANOVA results for all predictor variables are summarized in Table 4-7, which
includes values for Wilks’ Lambda, an F statistic, degrees of freedom and significance
level. Since the present study is largely exploratory, variables significant at the .10 level
were included for follow-up analyses. However, these variables are distinguished from
those achieving significance at the .05 convention in the following table. Significant
predictors can be placed in three categories. First, the demographic variables of institution
attended, gender and age had statistically significant impact on adjustment as measured by
the CAS scales. Second, psychological treatment history was related to current adjustment.
Current treatment was the most significant predictor; however, treatment since enrollment
and treatment prior to college also made significant contributions. Finally, a number of
environmental variables achieved significance. These included number of roommates;
subjective ratings of noise, light, and satisfaction; and the presence of grass in residential
window vistas.

43
Follow-up Analyses
The next stage of analysis employed a series of step-wise regression equations to
more fully elucidate the impact of predictor variables on each scale of the CAS. Only
variables that achieved significance at the .10 or higher level in the omnibus MANOVA
were retained in these subsequent analyses. As a group, this series of analyses provides
greater elaboration of environmental impact on specific facets of college adjustment.
However, a preliminary note of caution is warranted; as demonstrated later in this paper, the
psychometric properties of the CAS render conclusions regarding specific adjustment
difficulties problematic, since a single factor of distress appears to underlie the vast majority
of variation on purportedly specific subscales. Nonetheless, the following regression
analyses contribute to a fuller understanding of the present data by offering tentative models
of scores on individual subscales.
Anxiety
The CAS Anxiety (AN) scale reflects “physical and psychological correlates of
anxiety” (Anton & Reed, 1991, p. 5). High scorers may exhibit bodily tension, autonomic
hyperarousal, hypervigilance, worries or intrusive thoughts. Results of stepwise regression
of predictors on the AN scale are presented in Table 4-8. Current treatment was the most
powerful predictor, followed by the presence of grass in window views. Although the
impact of grass was of lesser magnitude than that of current treatment, the effect remained
statistically significant even when the variation in AN predicted by treatment status is taken
into account. Those students currently in psychological treatment tended to report higher
' levels of anxiety, while the presence of grass, as predicted, was associated with reduced
levels of reported anxiety. The R-square value for this model is .112; thus current

44
treatment status and the presence of grass together account for 11.2% of the total variation
in AN scores.
Table 4-7: MANOVA Test Statistics bv Predictor
Variable
Lambda
F
Num DF
DenDF
P
SCHOOL
.744
2.62
18
296
.0004"
SEX
.809
3.89
9
148
.0002"
AGE
.896
1.91
9
148
.0540"
TERMS
.975
.42
9
148
.9214
TXPRIOR
.909
1.64
9
148
.1089"*
TXSINCE
.870
2.46
9
148
.0122"
TXNOW
.866
2.55
9
148
.0093*
ON OFF
.947
.92
9
148
.5061
MATES
.909
1.65
9
148
.1048**
NOISE
.903
1.76
9
148
.0811**
LIGHT
.900
1.82
9
148
.0684“
SATIS
.848
2.94
9
148
.0031*
WINDOWS
.966
.56
9
148
.8078
WATER
.965
.96
9
148
.7949
GRASS
.878
2.28
9
148
.0202*
TREES
.935
1.14
9
148
.3386
BUILDING
.936
1.13
9
148
.3445
CONCRETE
.945
.96
9
148
.4720
DISTANCE
.945
.95
9
148
.4848
PARENTS
.949
.89
9
148
.5385
"Significant at .05 level
""Significant at .10 level
Variable
Table 4-8: Prediction of AN Scores
Parameter Estimate Std. Error Partial R2
F
P
Intercept
54.36
1.89
824.5
.0001
TXNOW
11.19
2.74
.0769
16.7
.0001
GRASS
-5.44
2.05
.0350
7.0
.0088

45
Depression
The Depression (DP) scale of the CAS purports to measure the “physical and
psychological correlates of depression” (Anton & Reed, 1991, p. 5), including fatigue,
sadness, hopelessness, isolation and anliedonia.1 A summary of the regression equation
predicting DP scores is presented in Table 4-9. Older participants tended to achieve lower
DP scores than those of younger students, indicating a negative relationship of age and
report of depressive symptoms or experiences. In addition, students who had sought
psychological treatment since enrolling in their current institution achieved significantly
higher DP scores, even when the effects of age were simultaneously controlled. However,
none of the environmental variables (including reported light level) made a contribution
beyond that of age and treatment effects. This model accounts for 12.4% of the variation of
depression scores.
Table 4-9: Prediction of DP Scores
Variable
Parameter Estimate
Std. Error
Partial R2
F
P
Intercept
64.44
4.48
206.8
.0001
AGE
-0.79
.23
.0650
11.9
.0007
TXSINCE
12.14
2.05
.0585
22.1
.0001
1 Anhedonia, the marked loss of interest or pleasure in activities previously enjoyed, is a
key diagnostic criterion for Major Depressive Disorder (American Psychiatric
Association, 1994).

46
Suicidal Ideation
Suicidal Ideation (SI) scores are indicative of suicidal thoughts or suicidal
behaviors. Anton & Reed (1991) recommend that even moderate elevations should signal
the need for further psychological evaluation. As shown in Table 4-10, younger students
reported higher levels of suicidal ideation. As with DP, students who reported
psychological treatment subsequent to entering college were more likely to produce
elevated scores. Together, age and treatment effect account for 5.2% of the variation in
suicidal ideation scores. One environmental feature, grass, approached significance (p=.09)
and would have explained an additional 2.4% of variation in SI scores.
Table 4-10: Prediction of SI Scores
Variable
Parameter Estimate
Std. Error
Partial R2
F
P
Intercept
65.24
4.23
237.6
.0001
AGE
-0.58
.21
.0218
8.1
.0050
TXSINCE
5.60
2.33
.0301
5.8
.0173
GRASS
-3.34
1.96
.0238
2.9
.0903*
Approached significance
Substance Abuse
The S A scale is designed to reflect difficulties in a number of areas negatively
impacted by substance abuse, including academics, social behavior and relationships.
Regression modeling of SA scores is summarized in Table 4-11. When the effects of
TXPRIOR are accounted for, no other variables have additional predictive power.
Although this model is significant, TXPRIOR explains only 3.8% of the variation in SA

scores, clearly indicating that factors external to the present study are more relevant to
substance abuse scores.
47
Table 4-11: Prediction of SA Scores
Variable Parameter Estimate Std. Error Partial R2 F P
Intercept 49.85 T3 3602.5 .0001
TXPRIOR 4.19 1.56 .0384 7.2 .0082
Self Esteem
Table 4-12 summarizes the prediction of SE scores. The SE scale is designed to
measure global self-esteem. High scorers tend to have poor self-esteem and self-
confidence, which are reflected in their own opinions of their abilities, achievements, and
attractiveness.
Younger students tended to report more problems with self-esteem, as did students who had
received psychological treatment since coming to college. Additionally, even with the
effects of age and treatment history simultaneously controlled, ratings of home light level
were correlated with SE scores. The direction of this relationship was in the expected
direction; namely, poor lighting was associated with increased problems with self-esteem.
The model of self-esteem is the strongest in this series; treatment, light, and age effects
together account for 14.7% of the variation in SE scores.
Table 4-12: Prediction of SE Scores
Variable
Parameter Estimate
Std. Error
Partial R2
F
P
Intercept
68.09
5.28
166.4
.0001
AGE
-0.59
0.24
.0295
6.1
.0144
TXSINCE
11.30
2.68
.0688
17.8
.0001
LIGHT
-1.82
0.67
.0485
7.3
.0074

48
Interpersonal Problems
The IP scale measures “the degree to which the student has difficulty relating to
others” (Anton & Reed, 1991, p. 6), which may be reflected in dependency, distrust,
vulnerability or argumentativeness. A regression summary for IP scores is presented in
Table 4-13. As evident in the summary, age was again a significant factor, and the trend for
younger participants to report greater difficulties was continued. Furthermore, treatment
since entering college continued to play an important role; students who had sought
counseling or psychotherapy evidenced higher IP scores. Overall, this model is of moderate
predictive strength, accounting for approximately 8.2 % of the total variation in IP scores.
Table 4-13: Prediction of IP Scores
Variable
Parameter Estimate
Std. Error
Partial R2
F
P
Intercept
64.66
4.02
259.0
.0001
AGE
-0.74
0.21
.0371
13.2
.0004
TXSINCE
6.78
2.31
.0444
8.6
.0038
Family Problems
The CAS FP scale purports to measure a variety of family concerns, including
difficulty with individuation and worry regarding family conflict (Anton & Reed, 1991). A
model of FP scores is presented in Table 4-14. Interestingly, the presence of grass in
window vistas was associated with lower scores. This finding is consistent that the
presence of natural environmental features should ameliorate psychological distress,
although the specific relationship of grass and family conflict is difficult to place in a

49
theoretical context. Moreover, this model is among the weakest in the series, accounting
for only 2.7% of the variation in FP scores.
Table 4-14: Prediction of FP Scores
Variable Parameter Estimate Std. Error Partial R2 F P
Intercept 53.85 1.82 871.2 .0001
GRASS -4.36 1.98 .0265 4.9 .0286
Academic Problems
The Academic Problems (AP) scale of the CAS is associated with poor study skills,
inefficient time management and concentration difficulties. A summary of regression on
AP scores is presented in Table 4-15. The presence of grass was associated with lower
levels of reported academic difficulties. However, contrary to expectation, residential
satisfaction (SATIS) was associated with increased academic difficulty. This
counterintuitive finding will be explored more fully in the following chapter. Grass and
satisfaction together account for 5.4% of the variation in AP scores.
Table 4-15: Prediction of AP Scores
Variable
Parameter Estimate
Std. Error
Partial R2
F
P
Intercept
48.19
3.23
222.7
.0001
SATIS
1.28
0.60
.0540
4.5
.0349
GRASS
-6.54
2.35
.0300
7.7
.0061

50
Career Problems
The Career Problems (CP) scale of the CAS is designed to measure difficulties in
vocational goal setting and decision making (Anton & Reed, 1991). Although high scores
on this scale may be associated with anxiety regarding career planning or decision making,
the CP scale seems logically less strongly associated with psychological disturbance or, for
that matter, the impact of home environment. Not surprisingly, perhaps, no predictor
variable in the model achieved or approached significance at the .05 level for Career
Problems.
Factor Structure of the College Adjustment Scales
The forgoing analyses raised important questions regarding the psychometric
adequacy and factor structure of the CAS. As noted, the initial series of MANOVA
analyses yielded only a small number of significant predictors. Since MANOVA
procedures test for predictor effects while controlling for intercorrelation in the criterion
variable set, the likelihood of significant results decreases as multicolinearity increases.
Anton and Reed cite scale intercorrelation as an important limitation in the CAS Manual
(1991), and the present study replicates their finding. T-score intercorrelations for all nine
CAS subscales are presented in Table 4-16. The strong interrelationships among CAS
scales are evident on first examination of the correlation matrix. All individual correlations
are in the moderate or higher range. In fact, the lowest correlation, between SA and CP t-
scores, was .28, indicating that 7.8% of the variation of each scale is shared between both.
All other correlations were higher, including several in excess of .70. T-scores for

51
depression and anxiety evidenced the strongest relationship (r=. 77), indicating nearly 60%
of shared variation between the scales.
Table 4-16: Correlation Matrix of CAS Scale T-Scores
AN
DP
SI
SA
SE
IP
FP
CP
AP
AN
1.0000
0.7673
0.4699
0.3335
0.7132
0.6984
0.5686
0.4925
0.5786
DP
0.7673
1.0000
0.5444
0.3524
0.7440
0.6441
0.5516
0.5305
0.5889
SI
0.4699
0.5444
1.0000
0.4021
0.5029
0.4901
0.4804
0.4167
0.3295
SA
0.3335
0.3524
0.4021
1.0000
0.3399
0.4376
0.4343
0.2753
0.4037
SE
0.7132
0.7440
0.5029
0.3399
1.0000
0.5995
0.5171
0.5018
0.5285
IP
0.6984
0.6441
0.4901
0.4376
0.5995
1.0000
0.6348
0.4801
0.4936
FP
0.5686
0.5516
0.4804
0.4343
0.5171
0.6348
1.0000
0.4226
0.5369
CP
0.4925
0.5305
0.4167
0.2753
0.5018
0.4801
0.4226
1.0000
0.4625
AP
0.5786
0.5889
0.3295
0.4037
0.5285
0.4936
0.5369
0.4625
1.0000
Note: Values represent Pearson product-moment correlation coefficients.
The level of intercorrelation among CAS scales is a serious psychometric limitation
of the instrument. First, strong relationships among scales suggest that a smaller number of
constructs underlie responses and, therefore, that distinctions based on individual scale
scores may be unwarranted in some cases. The possibility exists that all CAS scales are
measuring the same thing or, at least, that the scales are tapping very similar phenomena.
More succinctly: If one scale score is known, others can be predicted. Second, these
interrelationships raise questions about the discriminant validity of the CAS. That is, if the
subscales are, in fact, primarily measuring a single phenomenon (or small set of related
phenomena), then the names of individual scales may be clinically misleading. This is the
case when the underlying structure of the CAS is not sufficiently sensitive to distinguish
among the nine subscales. More concretely, the difference between depression and anxiety
scores becomes less meaningful when more than half of their variation is shared. Since this

52
possibility was evident in the correlation matrix, a factor-analytic procedure was employed
to determine in fuller detail the underlying structure of the CAS.
A principal components analysis was performed on the correlation matrix of t-
scores for each scale of the CAS. Principal components analysis, like classical factor
analysis, is essentially a data reduction technique (Dunteman, 1989) that extracts a smaller
number of uncorrelated, or orthogonal, factors that are linear transformations of observed
variables. In the present analysis, a varimax rotation procedure was chosen, in order to
achieve maximum separation of any factors underlying the CAS data. This procedure is
intended to minimize the number of variables associated with each factor and, therefore, to
facilitate interpretation of the resultant components of the data set (Norusis, 1994).
Extracted components, associated eigenvalues, and proportion of variance
accounted for by each component are listed in Table 4-17. Eigenvalues, which represent the
relative strength of a factor, are used as criteria for inclusion of a given factor into the
model. Although different eigenvalue scores have been employed, a cutoff value of 1.0 is a
widely-accepted convention. When this convention is applied to the current model, only
one factor meets inclusion criteria. This factor accounts for 57% of the variation in subscale
t-scores and is by far the strongest component of the model. Three additional factors, which
do not meet inclusion criteria, are listed for purposes of comparison. Although eigenvalues
for these factors approach 1.0, note that each of the subsequent factors accounts for less than
10% of the total variation in the data set.

53
Table 4-17: Components and Eigenvalues of the Correlation Matrix
Component
Eigenvalue
Difference
% Variation
Cum %
FACTOR r
5.12857
4.28076
0.569841
0.56984
FACTOR 2
0.84781
0.17261
0.094201
0.66404
FACTOR 3
0.67520
0.06846
0.075022
0.73906
FACTOR 4
0.60673
0.09979
0.067415
0.80648
Note: varimax rotation
meets inclusion criterion
Table 4-18 shows factor loadings for all nine CAS subscales on the four strongest
factors. Factor loading values represent a correlation between a given variable and factor
and, thus, are a measure of the strength of association. Table 4-18 underscores the
problematic nature of the CAS factor structure by demonstrating that most CAS subscales
are moderately correlated with Factor 1. Only suicidal ideation, substance abuse and
career problems have factor loadings less than .30. Thus, the factor accounting for the
majority of variation in the data set is nebulously defined by moderate association with
the majority of variables.
To understand the problematic nature of this factor structure, consider a
hypothetical alternative. If the factor structure of the CAS were such that factors were
defined by a small number of variables, the structure of the data set could be said to
correspond to the purported scale structure of the CAS. Flowever, in the present case, in
which the factors are not clearly defined by their association with subscales, the empirical
meaning of individual scales becomes ambiguous. Since the majority of variables are

54
related to only one common factor, the possibility exists that a single psychological
dimension underlies the majority of variation on the CAS, regardless of scale.
The above critique notwithstanding, Factors Two through Four in Table 4-18,
although quite weak, demonstrate some dimensionality that should be noted. Factor Two
is characterized primarily by a strong association with SA scores (r=.81), suggesting a
weak trend for substance abuse scores to vary somewhat independently of other scales.
Factor Three is positively related to suicidal ideation (r=75) and, less strongly, negatively
related to academic problems (r=-.61). Factor Four is defined primarily by a strong
association with career problems (i=.87). Given their weakness, these factors should be
interpreted with caution. However, their structure raises some interesting tentative
hypotheses, namely, that student report of substance abuse and career problems may be
independent, to some degree, of scores on other scales.
Table 4-18: Factor Loadings for CAS Scale T-Scores
VAR
Factor 1
Factor 2
Factor 3
Factor 4
T_Anxiety
.37477
-.26351
-.07139
-.27052
T Depression
.38034
-.24773
.05367
-.13570
T Suicidal Ideation
.29839
.22942
.74634
.03305
T Substance Abuse
.24637
.80586
-.13563
.10660
T Self-esteem
.36159
-.26104
.08631
-.15787
T Interpersonal Problems
.36130
.04206
.00043
-.24224
T Family Problems
.33600
.22023
-.13517
-.16589
T Career Problems
.29645
-.22049
.09892
.86555
TAcademic Problems
.32108
-.01077
-.61733
.18879

55
Creation and Prediction of a Composite Measure of Global Distress
This section reports an attempt to respond to problems created by the
multicolinearity of CAS scales, which negatively impacted the likelihood of finding
significant results in the initial series of MANOVAs and confuses the interpretation of
individual scales. The factor structure reported in the previous section warrants the
assumption that a single psychological phenomenon is responsible for the majority of
variation on the CAS subscales. Since the face content of the CAS taps a broad range of
functioning, it is logical to assume that this underlying factor may be a measure of global
psychological distress. On the basis of this assumption, a composite measure of distress
was formulated by computing the average t-score elevation across the nine CAS
subscales. This number, which represents a mean standardized level of symptom
reporting, was then used as the single criterion variable in a final stepwise regression
analysis. A second advantage of this single-criterion analysis was the ability to forgo the
use of MANOVA, which substantially limited the number of predictor variables. Thus,
this last analysis included all predictor variables, regardless of their performance on the
initial MANOVA.
Regression results are summarized in Table 4-19. Surprisingly, only two
variables—age and psychological treatment since enrollment—are significant predictors
of global distress. The meaning of this result is unclear, since environmental variables
were significant predictors in previous analyses. Apparently, environmental predictors
have no additional explanatory power for scores on the global distress measure.
However, these results should be viewed with caution, given that the composite distress

measure was a post-hoc creation for the present study and has not been validated. This
model acounts for 10.3% of the total variation in average t-score elevation.
56
Table 4-19: Prediction of Global Distress
Variable
Parameter Estimate
Std. Error
Partial R2
F
P
Intercept
60.64
3.18
364.0
.0001
AGE
-0.56
0.16
.0411
12.1
.0007
TXSINCE
7.31
1.83
.0614
15.0
.0001
Although no environmental variables entered the stepwise regression equation,
bivariate results were significant for grass (t=2.24, p=03) and concrete (t=1.94, p=.05).
This suggests that, although grass and concrete may have some relationship to global
distress scores, neither variable contributes more predictive power than the simple
combination of age and treatment since enrollment. Thus, using the global distress measure
criterion affords little additional understanding of environmental impact on adjustment.
Summary of Hypotheses
Taken together, this series of analyses provides limited evidence of the impact of
environmental variables on psychological adjustment. The most reasonable summary
statement is that, although subject and treatment variables have the most powerful
association with psychological status, some environmental variables (especially grass,
noise, light, residential satisfaction and, to a lesser degree, number of roommates) may
account for additional variation in student adjustment. Let us revisit the original set of
research hypotheses.

57
The first hypothesis predicted that residential students should show greater levels of
adjustment than off-campus residents. The present results do not provide support for this
hypotheses. First, MANOVA analyses failed to demonstrate the significance of residential
location. Second, residential location did not enter the regression equation predicting
global distress. In fact, even a simple univariate test failed to show predictive significance
(t=25, p-80) of residential location for global distress.
The second hypotheses, that psychological adjustment should be inversely related to
distance of home from campus, was not supported in the MANOVA analysis. Nor was
distance significantly correlated with global distress in the multiple or bivariate regression
analysis; in fact, a simple bivariate correlation (in which on-campus residents received a
value of zero) indicated no relationship (r=.002, p=,98).
A third hypothesis, based on the work of Wilson, Anderson, and Fleming (1987),
predicted that students living with family would report more adjustment difficulties than
those living at home, primarily as a function of enmesliment. This hypothesis, too, was
supported neither in the omnibus MANOVA nor in the prediction of global distress. Tins
result was not the consequence of predictive overlap with other factors, since a simple t-test
showed that family of origin had no relationship with global distress (t=.32, t=. 75).
However, any actual effect may be obscured by skewed sampling, since only ten students of
184 reported living with their families of origin.
A fourth hypotheses suggested a curvilinear relationship between number of
roommates and adjustment. As noted in Chapter 2, such a hypothesis is difficult to test in
this population, because the number of roommates is restricted in range. The mean number
of mates was 1.70, with a standard deviation of 1.6. Participants reported in nearly all cases

58
a number ranging from zero to four (an outlier of 16 was an exception). In spite of this
restricted range, number of roommates approached significance in the initial MANOVA
(F=1.65, p~ 10). Although the specific effects of roommates were not demonstrated in the
follow-up analyses reported above, mates were a small but significant predictor of
substance abuse scores in a preliminary analysis, which excluded treatment since
enrollment as a predictor (r2=.025, F=4.60, p=. 03). The relationship was negative, raising
the tentative but interesting possibility that those living alone are more likely to report
substance abuse problems.
A fifth hypotheses regarding the relationship of noise level to adjustment received
limited empirical support as well. Noise effects neared significance in the omnibus
MANOVA (F=1.76, p=.0811). Specific effects of noise were not of sufficient strength to
achieve significance in the follow-up analyses. However, effects were in the hypothesized
direction; for example, reported noise level was positively (but insignificantly) correlated
with global distress.
A sixth hypothesis, or set of related hypotheses, regarded the impact of natural
landscape elements in student residences on psychological well-being. Specifically, the
presence of water, trees, grass, and adequate light were hypothesized to promote
psychological health (cf. Kaplan & Kaplan, 1989). Conversely, the presence of concrete
and buildings was predicted to have a detrimental effect on adjustment. This set of
hypotheses received the strongest empirical support.
First, grass achieved significance in the omnibus MANOVA (F=2.28, p=.02). The
beneficial impact of grass was evident in its association with lower levels of anxiety (F=7.0,
p=.01), fewer reports of family problems (F=4.9, p.=.03), and lower levels of academic

59
distress (F-7.7, p=.01). In addition, grass approached significance in the model of suicidal
ideation scores (F=2.9, p=. 09); the direction of relationship was in the hypothesized
direction. In a preliminary model excluding treatment since enrollment as a predictor, grass
was the only significant negative predictor of suicidal ideation (F=4.14, p=.04). That
analysis also demonstrated that grass was negatively associated with global distress
(F=5.57, p=.02).
Reported light levels approached significance in the initial MANOVA (F=1.82,
p=.07) and produced significant results in the follow-up analyses. In the results reported
above, higher light levels were associated with better self-esteem scores (F=7.3, p=.01). In
the analyses excluding treatment since enrollment, poor lighting was associated with
increased report of depressive symptoms (F=5.08, p=.03).
Finally, self-report of residential satisfaction (“Overall, how satisfied are you with
your current residence?”) achieved significance in the MANOVA (F=2.94, p=.003). This
likert-scale question, included at the end of the section on housing environment, was
intended to represent a global self-assessment of residential satisfaction. In the regression
results here reported, the influence of residential satisfaction was evident in its ability to
predict academic problems, although the direction of association was counterintuitive
( Beta-1.28, F=4.5, p=.03). That is, residential satisfaction was associated with an increased
level of reported academic problems. Although the reason for this unexpected result is
unclear, a post hoc speculation is that, for a certain segment of the sample, satisfaction
reflects residential life distracting rather than promoting academic focus.

60
Psychological Treatment Effects Revisited
Since treatment effects played a significant role in most of the models tested above,
a decision was made to investigate in more detail the overall impact of time of treatment on
adjustment scores. The following hypothesis emerged from the previous data analyses:
recency of treatment should be inversely related to overall adjustment. That is, those
students currently in psychological treatment should report more difficulties than those who
had treatment earlier in their college years and those who received treatment before college.
Those with no treatment history should report the highest level of adjustment. This
hypothesis is relevant at present because it (1) provides some indication of criterion validity
for the CAS and (2) ties this study more closely to clinical services provided by college
counseling centers.
A MANOVA testing for overall effects of the four levels of treatment history (none,
before college, since college, and current) on the nine CAS scales yielded significant results
(Lambda=. 72, F=2.18, p=.0006). Follow-up analyses of variance (ANOVAs) demonstrated
specific treatment effects on t-scores for anxiety (F=7.78, p=.0001), depression (F=5.41,
p=.001), substance abuse (F=2.81, p=.04), and self-esteem (F=4.79, p=.003). Post-hoc
tests for anxiety scores revealed that students in current treatment had higher t-scores
(mean=60.0) than those who had treatment prior to college (mean=52.1) or never
(mean=48.3).2 For depression, those in current treatment scored significantly higher
(mean=59.0) than those who reported therapy before college (mean=51.4) or never
2 In a few cases, participants who reported two or more separate episodes of treatment fell
into more than one group (i.e., current treatment and treatment before or since college).

61
(mean=48.3). In addition, students currently in treatment reported poorer self-esteem
(mean=55.7) than those who had treatment prior to college (mean=48.7) or not at all
(mean=46.9). These results provide criterion validity evidence for the CAS scales
measuring depression, anxiety and self-esteem.

CHAPTER 5
DISCUSSION
Environment versus Treatment Effects and Student Characteristics
The role of environmental features—specifically, grass views, lighting, and noise
level—in psychological well-being was documented in the previous section. In the models
presented, environmental conditions were far from predominate determinants of
psychological status, but the impact of environmental features made a significant, if small,
incremental increase in the prediction of adjustment. Before proceeding with a discussion
of the theoretical significance of these limited findings, it is appropriate to revisit
methodological issues that may be relevant to the interpretation of results.
Psychological treatment history
Three dichotomous variables (treatment prior to college, treatment since enrollment
and current treatment) were used as predictors in the analysis presented here. The nature of
these measures is somewhat ambiguous. The first two variables were intended to control
for level of psychological adjustment prior to the student’s current living arrangements.
The last, however, could be conceptualized as either a predictor or an outcome variable.
That is, current psychological treatment is likely to result from psychological distress; the
reverse case, in which treatment causes distress, is (we hope) less plausible, assuming that
competent clinicians are providing services. However, since even current treatment adds
some additional strength to most of the models here presented, a decision was made to
62

63
retain each variable in the current model. The decision to incorporate treatment as a
predictor at all reflects a conservative analytic strategy, since the variation accounted for by
treatment could possibly obscure more subtle environmental effects. However, such a
conservative approach has the advantage of documenting environmental impact
independent of the decision to seek mental health treatment and, thus, speaks to the broadest
possible range of college students. Finally, since this study employs an ex post facto
correlational design, the decision to incorporate as many potential predictors as possible
compensates for the lack of experimental control. Moreover, the inclusion of all treatment
variables as well as environmental predictors increases the relevance of tins study to both
environmental and counseling psychology, because the strategy allows for the simultaneous
assessment of treatment history and environmental or geographical factors.
With regard to this last point, the analysis of the relationship between recency of
treatment and adjustment ads an important, more explicitly clinical dimension to our
models of adjustment. These results indicate that those students in current treatment (or
planning to seek treatment within 30 days) tend to report more difficulties than those who
have never sought treatment or those whose treatment episode took place prior to college.
Although this trend was not significant for all areas of adjustment measured by the CAS, it
was significant for anxiety, depression and self-esteem. Given the assumption that current
psychological discomfort is a primary motivation to seek treatment, this result supports the
utility and validity of these scales.
Limitations of the sample and the criterion measure
Although the total sample size was fairly large (n=184), some groups relevant to the
research hypotheses were inadequately represented. The most notable among these was

64
students living with their family of origin (n=10). Also, only a small portion of students
reported no exposure to trees (n=15). These small cell sizes may have provided insufficient
power to detect potential effects.
A more important limitation is the psychometric inadequacy of the College
Adjustment Scales. The intercorrelation among the nine subscales is problematic in two
areas. First, multicolinearity necessitates the use of MANOVA, which has a net effect of
reducing the number of environmental variables included for regression analysis. Second,
strong intercorrelations render clinical interpretations confusing. Scales strongly related to
each other are likely to measure the same underlying construct; therefore, the differential
meaning of individual scales is unclear.
Environment and Adjustment
In spite of the rather conservative research strategy, several environmental variables
showed promise as predictors of adjustment. The presence of grass was chief among these,
achieving overall significance in the MANOVA as well as significance in predictive models
for anxiety, suicidal ideation and academic problems. The importance of grass as a
predictor of lower levels of psychological distress is consistent with mainstream theoretical
and empirical models of landscape preference, which indicate that nature scenes are sought
by humans because exposure to such vistas (a) facilitates recovery from fatigue through
restorative impact on information processing systems (Kaplan & Kaplan, 1989) and (b)
produces measurable physiological changes associated with autonomic relaxation responses
(Ulrich, 1981, 1991; Ulrich et al., 1991). However, the landscape research cited has found
that the beneficial impact of nature exposure includes not only grass but also other natural

65
elements, especially trees and water, which had no significant effects in the present study.
Perhaps the failure to find convergent effects for these other natural landscape elements
stems from methodological shortcomings described above; an alternative possibility is that
the benefits of water and trees are more transitory than those of grass.
The presence of light was associated with self-esteem and, more weakly, with
depression. This finding is convergent with research suggesting that lower light levels,
especially those associated with winter, may play an etiological role in the development of
mood disorders. In fact, exposure to light has been repeatedly shown to treat winter
depression. Rosenthal, Sock, Skwerer, Jacobson, and Wehr (1988) provide a meta-analysis
of clinical research on the effectiveness of phototherapy for Seasonal Affective Disorder
(SAD).1 They report that light intensity is an important predictor of antidepressant effect.
Typically, patients respond best to bright florescent light (about 2,500 lux), while ordinary
room light (500 lux or less) has little or no effect on symptoms. A minority of subjects,
however, has responded favorably to low-intensity light; some SAD patients may benefit
1 The DSM-IV does not list SAD as a separate disorder; rather, a seasonal pattern specifier
may be added to a mood disorder diagnosis. The criteria for such a specification are as
follows:
A. There has been a regular temporal relationship between the onset of Major
Depressive Episodes in Bipolar I or Bipolar II Disorder or Major Depressive Disorder,
Recurrent, and a particular time of the year (e.g., regular appearance of the Major
Depressive Episode in the fall or winter [in the absence of psychosocial stressors].
B. Full remissions (or a change from depression to mania or hypomania) also occur
at a characteristic time of the year.
C. In the last two years, two Major Depressive Episodes have occurred that
demonstrate the temporal seasonal relationships defined in Criteria A and B, and no
nonseasonal episodes have occurred during that same period.
D. Seasonal Major Depressive Episodes . . . substantially outnumber the
nonseasonal Major Depressive Episodes that may have occurred over the individual's
lifetime (American Psychological Association, 1994, p. 390).

66
most from extremely high-intensity light (e.g., 10,000 lux). This finding implicates the
neurotransmitter melatonin in SAD, because high-intensity light is required to suppress
nocturnal melatonin secretion. The biological substrate of SAD is far from understood, and
the debate is outside the scope of this paper. It is sufficient to note that, whatever the
underlying mechanism, the antidepressant effects of light have been well-documented in the
literature and were reflected in this correlational study.
Implications for Policy
The results of this study underscore the importance of an ecological perspective on
campus design. Some elements of this perspective have been studied in great detail and,
consequently, have had far-reaching influence on policy makers. Examples of these widely
acknowledged areas include academics, social life, extracurricular activities, counseling,
multicultural awareness, sexual and gender dynamics, campus safety, and to some degree
dormitory design. This study focuses attention on the last category by highlighting the
impact of environmental content on student adjustment. More specifically, the importance
of greenspace and adequate lighting are supported not simply because of their aesthetic
value, but rather because their association with psychological functioning has been
documented empirically, although admittedly in a correlational manner. From an
architect’s perspective, these findings provide relevant prescriptions for landscape design,
although the importance of light and greenspace is certainly not a novel notion. From an
ecological perspective, however, the relationship of environmental features to psychological

67
well-being is perhaps more noteworthy, since the results underscore the interconnectedness
of the campus system. Student well-being is not simply a function of prior psychological
make-up and interaction with mental health professionals. Rather, well-being is influenced
by a system of dynamic environmental factors. Physical environment and the micro¬
geography of homespace have a role in this ecological system. Although their impact may
be small relative to other factors, their importance is certainly magnified in aggregate; this
seems particularly relevant when one considers the task of designing dormspace for
hundreds, or even thousands, of students.
One unexpected finding was the absence of significant differences among dormitory
and off-campus residents. This result is inconsistent with classic and recent research on the
experience of commuter students (Chickering, 1974; Wolfe, 1992), although much existing
research has used indicators of social integration and academic progress rather than
explicitly psychological measures. One conclusion is that dormitory residence promotes
important connections to campus, but that these benefits are independent of psychological
or psychiatric functioning. Thus, although off-campus residents may feel disconnected
from campus, such disconnectedness is not necessarily reflected in increased need for
psychotherapy.
Directions for Future Research
Alternative research instruments should be considered. Well-validated single¬
criterion measures are good candidates, because they simplify analytic strategy and afford
clearer clinical interpretation. The Mt scale of the MMPI-2 (Kleinmuntz, 1960), which was
problematic in the present study, remains a viable candidate, since it produces a single

68
measure of adjustment associated with a clinical picture of anxiety and feelings of
ineffectualness.
A second consideration is the need for designs affording experimental control. The
present study was correlational in nature and, therefore, illustrates relationships rather than
causal mechanisms. While these exploratory results are an important first step, more
rigorously controlled designs would provide clearer elucidation of causal impact. Of
course, the logistical and ethical considerations involving random assignment to
experimental living conditions make experimental studies a daunting task. Nonetheless,
such design options merit further study.
Finally, qualitative approaches can yield richer knowledge of the experience of
lifespace than the quantitative approach here employed. A critical point is that qualitative
and quantitative approaches need not be discreet alternatives . Rather, the complimentary
use of each technique has the potential to provide a more thorough understanding of campus
enviromnents.
Such an approach is not unprecedented in enviromnental psychology. For example,
Schroeder (1991) has combined quantitative and qualitative analysis to model preference
and meaning of arboretum landscapes. Flis approach used keywords from spontaneous
descriptions of landscapes to predict environmental preferences. Work focusing on
explicitly psychological issues has received attention from humanistic geographers. For
example, Tuan (1974) has written extensively on topophilia, or love of place, as a reflection
of the emotional ties between humans and landscape. Topophilic experiences might include
feelings of at-homeness, acceptance, spiritual well-being, or even transcendency.

69
A more qualitative approach rounds out the ecological context of this paper; an
experiential analysis goes beyond this useful, but rather mechanistic, approach by
grounding aggregate results in the day-to-day lives of students. Moreover, qualitative
clarifications of environmental experience add theoretical sophistication to our
understanding. Witness the distinction made by Relph (1985), following Heidegger,
between presence-at-hand and readiness-to-hand in the environment. The former denotes a
conscious awareness, an objectification of an environmental feature. The latter connotes
more subtle meaning; that is, it does not require conscious reflection but rather affords a
more fundamental, direct experience of landscape. Quantitative landscape research seems
to focus more intently on the present-at-hand world through the conscious examination of
environmental features. This bias affects research questions as surely as it does individual
responses. A more qualitative conceptualization augments the understanding derived from
quantitative research through shifting attention of researcher and subject to more subtle, less
conscious, aspects of place.
Few landscapes afford the variety of emotional experiences that may be encountered
in a college community; few developmental periods afford as much new experience as the
transition from family of origin to the university or college. Thus, campus landscapes seem
uniquely positioned in the life experience of students; this context magnifies the
importance of campus design. My hope is that this study provides impetus for further
interdisciplinary focus on the ecology of student well-being, and that the knowledge gained
will be manifest in the life space of campus communities.

APPENDIX A
Informed Consent Statement
Principal Investigator: Michael H. Campbell, MS, Graduate Student, Department
Psychology, University of Florida
Supervisor: Dorothy D. Nevill, Ph.D., Professor of Psychology, University of Florida
If you wish to participate in this study, you will be asked to fill out a questionnaire about
personal characteristics, the place where you live, your psychological and emotional
health, and whether or not you have had counseling. The entire process should take about
30 minutes.
Although you will be asked to provide personal information (such as age, gender, and
year in school), you will not be asked to identify yourself. When the results are
published, personal information will be reported only for the group. The data for this
study will be kept confidential to the extent provided by law.
We do not anticipate that participation in this study will result in any discomfort or risk to
you. However, you do not have to answer any question you do not wish to answer, and
you may stop participating at any time without penalty of any kind.
No immediate benefits are expected from participation in the study. You will not receive
compensation for your efforts.
If you have any questions about the procedures in the study, you may contact:
Dorothy Nevill, Ph.D. Mike Campbell, M.S.
114 Psychology Building, Box 112250 or University Counseling Center
University of Florida P.O. Box 3708
Gainesville, FL 32611-2250 Laramie, WY 82071
(352) 392-0617 (307) 766-2187
Questions or concerns about the rights of research participants can be directed to:
University of Florida IRB Office
Box 112250
University of Florida
Gainesville, FT 32611-2250
70

APPENDIX B
Please answer the following questions about yourself and the place where you live. If
choices are provided, circle the appropriate answer. If blanks are provided, fill in the
appropriate answer.
Information about you:
1. What is your age?
2. What is your gender? a. Male b. Female
3. Which best describes the ethnic group to which you belong?
a. White (non-Hispanic) b. African American,
c. Asian/Pacific Islander d. Hispanic/Latino(a)
e. other
4. How many terms have you been a student at UF/UW/NC? _
5. What is your grade point average?
6. Which best describes your sexual orientation?
a. Heterosexual (straight) b. Bisexual c.Gay/Lesbian
Information about your home:
1. Do you live on campus or off campus? a. on campus
b. off campus
2. If off campus, how far away from campus is your home located? (to the nearest
1/2 mile)
71

72
3. If off campus, do you live with your family? a. Yes b. No
4. How many persons in addition to you live in your place of residence
(your dorm room, house or apartment)?
5. If you live on campus, which best describes your residence?
a. dorm b. suite c. university apartment d. other
Optional—What is the name of your building?
6. Do you live in a fraternity or sorority? a. Yes b. No
Optional—What is the name of your house?
7. In the room where you spend most of your time at home, are there windows?
a. Yes b. No
If yes, how many?
a. Which of the following are visible from the room in which you spend the most time?
(circle all that are appropriate^
water trees grass buildings concrete
8. How well-lit is the place that you live?
1 2 3 4 5 6 7
poorly lit well-lit
9. In your opinion, how noisy is the place that you live?
1 2 3 4 5 6 7
not at all noisy extremely noisy

73
10. Overall, how satisfied are you with your current residence?
1 2 3 4 5 6 7
not at all satisfied extremely satisfied
Information about your use of counseling or psychotherapy:
1. BEFORE you came to UF/UW/NC, had you ever seen a psychologist,
psychiatrist or other type of mental health professional for a psychological or
personal problem? a. Yes
b. No
2. SINCE you came to UF/UW/NC, have you ever seen a psychologist,
psychiatrist or other type of mental health professional for a psychological or
personal problem? a. Yes
b. No
3. Are you currently seeing (or planning to see within the next month) a mental
health professional? a. Yes
b. No

REFERENCES
Aiello, J., & Baum, A. (Eds.). (1979). Residential crowding and design. New
York: Plenum.
Altman, L, & Rogoff, B. (1987). World views in psychology and environmental
psychology: Trait, interactional, organismic, and transactional perspectives. In D. Stokols
& I. Altman (Eds.). Handbook of environmental psychology (pp.7-40). New York: Wiley.
American Psychiatric Association (1994). Diagnostic and statistical manual of
mental disorders (4th ed.). Washington, DC: Author.
Anton, W.D., & Reed, J.R. (1991). College adjustment scales professional manual.
Odessa, FL: Psychological Assessment Resources.
Banning, J., & Kaiser, L. (1974). An ecological perspective and model for campus
design. The Personnel and Guidance Journal. 52. 370-375.
Bishop, J.B. (1990). The university counseling center: An agenda for the 1990s.
Journal of Counseling and Development. 68. 408-413.
Borow, H. (1951). Manual for the college inventory of academic adjustment.
Stanford, CA: Stanford University Press.
Bray, J, Williamson, D, & Malone, P. (1984). Personal authority in the family
system: Development of a questionnaire to measure personal authority in intergenerational
family processes. Journal of Marital and Family Therapy. 10.167-178.
Brooks, J.H., II, & DuBois, D.L. (1995). Individual and environmental predictors
of adjustment during the first year of college. Journal of College Student Development. 36.
347-360.
Butcher, J., Dahlstrom W.G., Graham, J.R., & Tellegen, A. (1989). Minnesota
Multiphasic Personality Inventory-2. Minneapolis: University of Minnesota Press.
Butcher, J.N., Dahlstrom, W.G., Graham, J.R., Tellegen, A., & Kraemmer, B.
(1989). Minnesota Multiphasic Personality Inventorv-2 (MMPI-21: Manual for
administration and scoring. Minneapolis: University of Minnesota Press.
Butler, D.L., & Biner, P.M. (1989). Effects of setting on window preferences and
factors associated with those preferences. Environment and Behavior. 21. 17-31.
74

75
Campbell, M.H. (1994, August). An informational model of visual preference for
urban waterscapes. Paper presented at the 102nd convention of the American Psychological
Association, Los Angeles, CA.
Chandler, L.A., & Gallagher, R.P. (1996). Developing a taxonomy for problems
seen at a university counseling center. Measurement and Evaluation in Counseling and
Development. 29. 4-12.
Chickering, A.W. (1974). Commuting versus resident students. San Francisco:
Jossey-Bass.
Chickering, A.W., & Reisser, L. (1993). Education and identity (2nd ed.). San
Francisco: Jossey-Bass.
Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived
stress. Journal of Health and Social Behavior. 24. 385-396.
Cvetkovitch, G, & Earle, T. (1992). Environmental hazards and the public. Journal
of Social Issues. 48. 1-20.
Dahlstrom, W.G., Welsh, G.S., & Dahlstrom, L.E. (1975). An MMPI handbook,
vol. II: Research applications. Minneapolis: University of Minnesota Press.
Demick, J., & Andreoletti, C. (1995). Some relations between clinical and
environmental psychology. Environment and Behavior. 27. 56-72.
Demick, J., & Wapner, S. (1980). Effects of environmental relocation on a
psychiatric therapeutic community. Journal of Abnormal Psychology. 89. 444-452.
Dunteman, G.H. (1989). Principal components analysis (Sage university paper
series on quantitative applications in the social sciences, 07-069). Beverly Hills: Sage
Publications.
Edwards, A.L. (1959). Edwards Personal Preference Schedule manual. New York:
Psychological Corporation.
Evans, G.W., & Lepore, S.J. (1993). Household crowding and social support: A
quasiexperimental analysis. Journal of Personality and Social Psychology. 65. 308-316.
George, R.L. (1971). Resident or commuter: A study of personality differences.
Journal of College Student Personnel. 12. 216-219.
Gough, H.G. (1987). California Psychological Inventory, revised manual. Palo
Alto, CA: Consulting Psychologists Press.

76
Graff, R.W., & Cooley, G.R. (1970). Adjustment of commuter and resident
students. Journal of College Student Personnel. 11. 54-57.
Graham, J.R. (1993). MMPI-2: Assessing personality and psychopathology (2nd
ed.). New York: Oxford University Press.
Hathaway, S. R., & McKinley, J.C. (1943). Minnesota Multiphasic Personality
Inventory. Minneapolis: University of Minnesota Press.
Haulman, S.R. (1978). A comparison of self-concepts, peer relationships,
persistence and extracurricular involvement of University of Florida freshmen with
differing housing arrangements. (Doctoral dissertation, University of Florida, 1978).
University Microforms International.
Herman, D.S., Weathers, F.W., Litz, B.T., & Kean, T.M. (1997). Psychometric
properties of the embedded and stand-alone versions of the MMPI-2 Keane PTSD Scale.
Assessment. 3. 437-442.
Herzog, T.R. (1989). A cognitive analysis of preference for urban nature. Journal
of Environmental Psychology. 9. 27-43.
Herzog, T.R. (1992). A cognitive analysis of preference for urban spaces. Journal
of Environmental Psychology. 12. 237-48.
Hicks, D., Reed, J., & Anton, W. (1989, October). The intake for as a diagnostic
tool. Paper presented at the meeting of the Southeastern Conference of Counseling Center
Personnel, Chattanooga, TN.
Hopkins, J. (1994). Orchestrating an indoor city: Ambient noise in a megamall.
Environment and Behavior. 26. 785-812.
Huberty, C.J., & Morris, J.D (1989). Multivariate analysis versus multiple
univariate analysis. Psychological Bulletin. 105. 302-308.
Kaczmarek, P.G., Matlock, C.G., & Franco, J.N. (1990). Assessment of college
adjustment in three freshmen groups. Psychological Reports. 66. 1195-1202.
Kaiser, L.R. (1977). Campus ecology and campus design. NASPA monograph.
Kaplan, R., & Kaplan, S. (1989). The experience of nature: A psychological
perspective. New York: Cambridge University Press.
Kleinmuntz, B. (1960). Identification of maladjusted college students. Journal of
Counseling Psychology. 7. 209-211.

77
Kleinmuntz, B. (1961). The College Maladjustment Scale (Mt): Norms and
predictive validity. Educational and Psychological Measurement. 21. 1029-1033.
Krupat, E. (1985). People in cities. New York: Cambridge University Press.
Kuczlca, T., & Handal, P. (1990). Validity of the college maladjustment scale for
identification of distressed students. Psychological Reports. 67, 730.
Langer, T.S. (1962). A twenty-two item screening score of psychiatric symptoms
indicating impairment. Journal of Health and Human Behavior. 3, 269-276.
Lepore, S J., Evans, G.W., & Schneider, M. (1991). Dynamic role of social support
in the link between chronic stress and psychological distress. Journal of Personality and
Social Psychology. 61. 899-909.
Levy-Leboyer, C., & Naturel, V. (1991). Neighborhood noise annoyance. Journal
of Environmental Psychology. 11. 75-86.
Milgram, S. (1970). The experience of living in cities. Science. 167. 1461-1468.
Morrill, W.H., Oetting, E.R., & Hurst, J.C. (1974). Dimensions of counselor
functioning. Personnel and Guidance Journal 52. 354-359.
Murphy, M.C., & Archer, J., Jr. (1996). Stressors on the college campus: A
comparison of 1985 and 1993. Journal of College Student Development. 37. 20-27.
Norusis, M.J. (1994). SPSS professional statistics 6.1. Chicago: SPSS, Inc.
Novaco, R.W., Kliewer, W., & Broquet, A. (1991). Home environmental
consequences of commute travel impedance. American Journal of Community Psychology.
12» 881-909.
Novalco, R.W., Stokols, D., & Milanesi, L. (1990). Objective and subjective
dimensions of travel impedance as determinants of commuting stress. American Journal of
Community Psychology. 18. 231-257.
Pace, D., Stamler, V.L., Yarns, E., & June, L. (1996). Rounding out the cube:
Evolution to a global model for counseling centers. Journal of Counseling and
Development. 74. 321-325.
Parker, C.A. (1961). The predictive use of the MMPI in a college counseling
center. Journal of Counseling Psychology. 8. 154-158.

78
Pascarella, E.T., & Chapman, D.W. (1983). Validation of a theoretical model of
college withdrawal: Interaction effects in a multi-institutional sample. Research in Higher
Education. 19. 25-48.
Pascarella, E.T., Duby, P.B., & Iverson, B.K. (1983). A test and
reconceptualization of a theoretical model of college withdrawal in a commuter institution
setting. Sociology of Education. 56. 88-100.
Pascarella, E.T., Edison, M, Nora, A., Hagedom, L.S., & Terenzini, P.T. (1996).
Influences on students’ openness to diversity and challenge in the first year of college.
Journal of Higher Education. 67. 174-190.
Relph, E. (1985). Geographical experiences and being-in-the-world: The
phenomenological origins of geography, hr D. Seamon & Mugerauer (Eds.), Dwelling-
Place, and Environment: Towards a Phenomenology of Person and World (pp. 15-33).
Dordrecht: Nijhoff.
Rosenthal, N., Sock, D., Skwerer, R., Jacobson, F., & Wehr, T. (1988).
Phototherapy for seasonal affective disorder. Journal of Biological Rhythms. 3. 101-120.
Schroeder, H.W. (1991). Preference and meaning of arboretum landscapes:
Combining quantitative and qualitative data. Journal of Environmental Psvchologv.il.
231-248.
Seamon, D. (1984). Emotional experience of the environment. American
Behavioral Scientist. 27. 757-770.
Seamon, D. (1989). Humanistic and phenomenological advances in environmental
design. The Humanistic Psychologist, 17. 280-293.
Stokols, D. (1995). The paradox of environmental psychology. American
Psychologist. 50. 821-827.
Street, S., Kromrey, J.D., Reed, J., & Anton, W. (1993, December/January). A
phenomenological perspective of problems experienced by high school students. High
School Journal, pp. 129-138.
Sundstrom, E., Bell, P.A., & Asmus, C. (1996). Environmental psychology: 1989-
1994. Annual Review of Psychology. 47. 485-512.
Taylor, J.G., Zube, E.H., & Sell, J.L. (1987). Landscape assessment and
perception research methods. In R.B. Bechtel, R.W. Marans, & W. Michelson (Eds.),
Methods in environmental and behavioral research (pp. 361-393). New York: Van
Nostrand Reinhold Company.

79
Turner, P.R., Valtierra, M., Talken, T.R., Miller, V.I., & De Anda, J.R. (1996).
Effect of session length on treatment outcome for college students in brief therapy. Journal
of Counseling Psychology. 43. 228-232.
Ulrich, R.S. (1981). Natural versus urban scenes: Some psychophysiological
effects. Environment and Behavior. 13. 523-556.
Ulrich, R.S. (1984). View through a window may influence recovery from surgery.
Science. 224. 420-421.
Ulrich, R.S. (1991). Effects of interior design on wellness: Theory and recent
scientific research. Journal of Health Care Interior Design. 3. 97-109.
Ulrich, R.S., Simons, R.F., Losito, B.D., Fiorito, E., Miles, M.A., & Zelson, M.
(1991). Stress recovery during exposure to natural and urban environments. Journal of
Environmental Psychology. 11.201-30.
Wapner, S. (1995). Toward integration: Environmental psychology in relation to
other subfields of psychology. Environment and Behavior. 27. 9-32.
Welty, J.D. (1976). Resident or commuter students: Is it only the living situation?
Journal of College Student Personnel. 17. 465-468.
Wilson, R.J., Anderson, S.A., & Fleming, W.M. (1987). Commuter and resident
students' personal and family adjustment. Journal of College Student Personnel. 28. 229-
233.
Wolfe, J.S. (1992). The relationship of a freshman year experience for resident and
commuter students to the social and academic integration, commitment, academic success
and persistence of first-year college students (Doctoral dissertation, University of Maryland,
College Park, 1991). Dissertation Abstracts International. 53, 1079-A.

BIOGRAPHICAL SKETCH
Mike Campbell was bom at McCoy Air Force Base, Orlando, Florida on October
30, 1969 to Capt. Donald F. and Sylvia Campbell. During childhood, he accompanied his
parents on a variety of assignments in the continental U.S. and Republic of Panama. After
graduating from Rome Free Academy (Rome, NY) in 1987, Mike enrolled at New College
of the University of South Florida (Sarasota, FL) where he completed a B. A. in
psychology/Latin American studies in 1991. He received a M.S. in geography from The
Florida State University (Tallahassee, FL) in 1993; his master’s thesis, An Informational
Approach to Visual Preference of Urban Waterscapes, was presented at the 102nd Annual
Convention of the American Psychological Association (Population and Environmental
Psychology Division) in 1994. Mike completed pre-doctoral internship training at the
University of Wyoming (Laramie, WY) in 1997 and received a Ph.D. in counseling
psychology from the University of Florida (Gainesville, FL) in 1998.
Mike currently lives in Sarasota, FL, where he is a therapist at the New
College/USF Counseling and Wellness Center. He is also an adjunct faculty member at the
University of Tampa. His professional memberships include the American Psychological
Association, American Society of Clinical Hypnosis, Southeastern Psychological
Association, and Southeastern Council on Latin American Studies. Previously, Mike
served as a trustee of New College Foundation, and he is currently a director and secretary
of the New College Alumnae/i Association.
80

I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy^
Dorothy D.
Professor of 1
O.fLu
11 Chair/
jvi 11, Chair
Psychology
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy
I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy. —,— «
Mary Fukuyama
Clinical Professor of Psychology
l certify that 1 have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope^id quality,
as a dissertation for the degree of Doctor of Philosophy/ Cy
Ira nschler
Professor of Psychology
I certify that I have read this study and that in my oppi
acceptable standards of scholarly presentation and is fully ^de
as a dissertation for the degree of Doctor of Philosophy. / / /
cori forms to
n scope and quality,
Ary Lamme
Associate Professor of Geography
This dissertation was submitted to the Graduate Faculty of the Department of
Psychology in the College of Liberal Arts and Sciences and to the Graduate School and
was accepted as partial fulfillment for the requirements for the degree of Doctor of
Philosophy.
May 1998
Dean, Graduate School