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1 A STRESS DIATHESIS EXAMINATION OF INTERNET ADDICTION: PERCEIVED STRESS, THE BIG FIVE PERSONALITY FACTORS, PERFECTIONISM AND INTERNET ADDICTION AMONG COLLEGE STUDENTS By T ONG AN SHUEH 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 2 01 1
2 2011 Tong An Shueh
3 To my father in heaven, Tso Y un
4 ACKNOWLEDGMENTS I thank the chair, Dr. Kenneth G. Rice, and the members of my supervisory committee, Dr. Jiunn Jye Sheu Dr. David Suchman, and Dr. Catherine Cottrell, for their mentoring. I also thank the staff and professors at the UF for their research assistance, the participants in my surveys for their honest and open participations, and the lab members, Timothy Delgado, Danielle DeMatas, and Siyang Lu for assisting me through the data collecting process. I especially appreciate Dr. Frederic Desmond for his ongoing listening and support through my dissertation writing process. Most of all, I thank my family for their loving encouragement, which motivated me to complete my study.
5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 LIST OF FIGURES ................................ ................................ ................................ .......... 9 LIST OF ABBREVIATIONS ................................ ................................ ........................... 10 ABSTRACT ................................ ................................ ................................ ................... 11 CHAPTER 1 INT RODUCTION ................................ ................................ ................................ .... 12 Internet Addiction ................................ ................................ ................................ .... 13 Defining Internet Addiction ................................ ................................ ............... 13 Terminology ................................ ................................ ............................... 13 Definition ................................ ................................ ................................ .... 14 Conceptualization ................................ ................................ ...................... 14 Diagnosis of Internet addiction ................................ ................................ ... 15 Symptoms of Internet Addiction ................................ ................................ ........ 19 Poor time management ................................ ................................ .............. 20 Poor academic performance ................................ ................................ ...... 21 Increased unhealthy behaviors ................................ ................................ .. 22 Disrupted interpersonal relationships ................................ ......................... 22 Psychological distress ................................ ................................ ................ 23 Demographic Factors Associated with Internet Addiction ................................ 24 Gender ................................ ................................ ................................ ....... 24 Age ................................ ................................ ................................ ............ 26 Years of Internet use ................................ ................................ .................. 27 Stress and Internet Addiction ................................ ................................ .................. 28 Internet Use and Stress Coping ................................ ................................ ....... 28 Internet Addiction as A Way of Stress Coping among College Students .......... 29 The Stress Diathesis Perspective ................................ ................................ .... 31 Stress Response Dampening Model ................................ ................................ 31 Personality Factors of Internet Addiction ................................ ................................ 33 The Big Five Personality Traits ................................ ................................ ......... 33 Extraversion and related traits ................................ ................................ ... 33 Extraversion and neuroticism ................................ ................................ ..... 35 The co nscientiousness related trait: s ensation seeking ............................. 36 Other related personality factors ................................ ................................ 38 Perfectionism and Internet Addiction ................................ ................................ ...... 41 Dimensions of Perfectionism ................................ ................................ ............ 41 Maladaptive perfectionism and adaptive perfectionism .............................. 42
6 Procrastination as one dimension of perfectionism ................................ .... 43 Perfectionism and Substance Abuse Addiction ................................ ................ 44 Perfectionism and Behavioral Addiction ................................ ........................... 45 Perfectionism and Internet Addiction among College Students ........................ 4 6 Current Study ................................ ................................ ................................ .......... 47 2 METHODS ................................ ................................ ................................ .............. 51 Participants ................................ ................................ ................................ ............. 51 Measures ................................ ................................ ................................ ................ 53 Demographic Questionnaire ................................ ................................ ............. 53 The Internet Addiction Scale (IAS) ................................ ................................ ... 53 The Perceived Stress Scale (PSS) ................................ ................................ ... 54 The Mini International Per sonality Item Pool (Mini IPIP) ................................ .. 55 The Almost Perfect Scale Revised (APS R) ................................ ..................... 57 The Tuckman Procrastination Scale (TPS) ................................ ...................... 58 The Impulsive Sensation Seeking Scale (ImpSS) ................................ ............ 58 Quality Testing Items ................................ ................................ ........................ 59 Procedure ................................ ................................ ................................ ............... 59 3 RESULTS ................................ ................................ ................................ ............... 62 Preliminary Analyses ................................ ................................ .............................. 62 Normality A ssumption ................................ ................................ ...................... 62 Reliability of Variables in the Analyses ................................ ............................. 64 Prevalence of Internet Addiction among College Students .............................. 64 Regression Assumption ................................ ................................ .................... 64 Stress and Internet Addiction ................................ ................................ .................. 65 Big Five Personali ty Factors and Internet Addiction ................................ ............... 66 Perfectionism and Internet Addiction ................................ ................................ ...... 67 Moderating effect of Perfectionism on the Relations hip between Perceived Stress and Internet Addiction ................................ ................................ ............... 68 Exploratory Analysis ................................ ................................ ............................... 70 4 DISCUSSION ................................ ................................ ................................ ......... 81 Prevalence and Demographic Variables ................................ ................................ 81 Perceived Stress ................................ ................................ ................................ ..... 82 The Big Five Personality Factors ................................ ................................ ............ 83 Perfectionism ................................ ................................ ................................ .......... 84 Exploratory Analysis ................................ ................................ ............................... 87 Significance of Current Study ................................ ................................ ................. 90 5 LIMITATIONS, FUTURE RESEARCH DIRECTIONS, AND PRACTICE IMPLICATIONS ................................ ................................ ................................ ...... 92
7 APPENDIX A DEMOGRAPHIC QUESTIONNAIRE ................................ ................................ ...... 97 B INTERNET ADDICTION SCALE (IAS) ................................ ................................ 100 C THE PERCEIVED STRESS SCALE (PSS) ................................ .......................... 104 D THE MINI INTERPERSONAL PERSONALITY ITEM POOL (MINI IPIP) ........... 106 E THE ALMOST PERFECTION SCALE REVISED (APS R) ................................ ... 109 F THE T UCKMAN PROCRASTINATION SCALE (TPS) ................................ .......... 112 G THE IMPULSIVE SEN S ATION SEEKING SCALE ................................ ............... 114 LIST OF REFERENCES ................................ ................................ ............................. 117 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 127
8 LIST OF TABLES Table page 2 1 Participant demographics compared to UF student population Fall 2010. .......... 61 3 1 Mean, 5% trimmed mean, and standard devia tion, s kewness, kurtosis and reliability of all variables. ................................ ................................ ..................... 74 3 2 Correlations between the transformed variables and the corresponding original variables. ................................ ................................ ................................ 75 3 3 Final model of the hierarchical regression analysis using age, the Big Five personality factors, perfectionism variables in predicting Internet addiction. ...... 76 3 4 Final model of the hierarchical regression analysis using age, perceived stress, perfectionism variables in predicting Internet add iction. .......................... 76 3 5 Correlations between Internet addiction and personality variables. .................... 77
9 LIST OF FIGURES Figure page 3 1 Moderating effect of Discrepancy (t APS R D) on the r elation ship between Standards (t APS R S) and Internet addiction (t IAS) controlling age, the Big Five personality variables (t Intellect/Imaginati on, t Conscientiousness, Extraversion, t Agreeableness, and Neuroticism) ................................ .............. 78 3 2 Moderating effect of Discrepancy (t APS R D) on the r elation ship between Standards (t APS R S) and Internet add iction (t IAS) controlling age, perceived stress (PSS10), PSS X t APS R D, PSS X t APS R D, and PSS X t APS R S X t APS R D ................................ ................................ .................... 79 3 3 Moderating effect of Neuroticism on the r elation ship between perceived stress (PSS10) and Internet addiction (t IAS) ................................ .................... 80
10 LIST OF ABBREVIATION S APS R The Almost Perfect Scale Revised APS R D The Almost Perfect Scale Revised Discrepancy APS R S The Al most Perfect Scale Revised Sta ndards APS R O The Almost Perfect Scale Revised Order IAS The Internet Addiction Scale Imp Impulsivity ImpSS The Impulsive Sensation Seeking Scale Mini IPIP The Mini International Personality Item Pool PSS The Perceived Stress Scale SRD Stress respo nse dampening SS Sensation Seeking t Agreeableness The transformed Agreeableness t APS R S The transformed Almost Perfect Scale Revised Standards t APS R D The transformed Al most Perfect Scale Revised Discrepancy t Conscientiousness The transformed Con scientiousness t IAS The transformed Internet Addiction Scale score t Intellect/Imagination The transformed Intellect/Imagination t Imp The transformed impulsivity TPS The Tuckman Procrastination Scale ZKPQ The Zuckerman Kuhlman Personality Questionnai re
11 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctoral of Philosophy A STRESS DIATHESIS EXAMINATION OF INTERNET ADDICTION: PERCEIVED STRESS, THE BIG FIVE PERSONALITY FACTORS, PERFECTIONISM AND INTERNET ADDICTION AMONG COLLEGE STUDENTS By T ong An Shueh December 2011 Chair: Kenneth G. Rice Major: Counseling Psychology Internet addiction has been a growing concern in the United St ates and college students may be especially at risk This study focused on examining Internet addiction and its relationships with perceived stress, the Big Five personality factors, perfectionism, and other theoretically related personality variables amo ng 1465 college students Bivariate correlation analysis revealed that perceived stress was positively correlated with Internet addiction level. Results from hierarchical multiple regression analyses showed that Internet addiction was positively associated with neuroticism (higher order personality factor) and maladaptive perfectionism (lower order personality factor). Internet addiction also was negatively correlated with conscientiousness, extraversion, and openness (higher order personality factors) and adaptive perfectionism (lower order personality factor). A significant interaction was observed Internet addiction. The findings are discussed in light of the stress diathesis perspective and the Stress Response Dampening Model. Limitations, futu re research directions, and implication s for counseling practice are also addressed
12 CHAPTER 1 INTRODUCTION Since the Internet was first developed in 1966 (Roberts, 1995) it has grown rapidly and become the most domi nant media for new generations. A s the number of Internet users grows some negative psychological symptoms among users have prompted psyc hologists to study Internet in the last two decades. Internet addiction has also been proposed for inclusion in the upcoming Diagnostic and Statistic s Manual of Mental Disorder s Fifth Edition (DSM V) (Young, 2007). C ollege students ha ve been considered as the most at risk for Interne t addiction Young (2007) suggested that college students are more vulnerable to Internet addiction because of free and unlimited Internet access, huge blocks of unstructured time, their newly experienced freedom from parental control, no monitoring or cen soring of their online behavior full encouragement from faculty and administrators, social intimidation and alienation, and also a higher legal drinking age that results in fewer stress relief outlet s Although c ollege students ha ve been suspected to be a t high risk for Internet addiction (Castiglione, 2008) studies show that the prevalence rate of Internet addiction among that group has varied considerably, from less than 1% (Nichols & Nicki, 2004) to over 18% (Niemz, Griffiths, & Banyard, 2005) The inconsistent prevalence estimates may ing and assess ing Internet addiction. M any studies about Internet addiction have been conducted on college students. R esults indicate that Internet addiction is related to factors such as time spent on the Internet gender, attitudes toward computer s and to some other social psychological vari ables and problems (Chou, Condron, & Belland, 2005) Although various traditional
13 addiction theories and models have been used to explain Internet addiction among college students, a theoretically based investigation fro m the stress diathesis perspective ha s not been explored Therefore, this study aims to examine Internet addiction among college students focusing on both stress and pre dispositional personality factors and to especially explore the potential moderati ng r ole s of lower order personal ity variabl es such as perfectionism In the following sections, the literature regarding conceptualization, diagnosis, and symptoms of Internet addiction will be reviewed. In addition, possible factors associated with college s Internet addiction will be examined. Internet Addiction Defining Internet Addiction Terminology Although Internet addiction is now widely recognized, scientific studies for this phenomenon only started a little over a decade ago Various terms ha ve been used by researchers studying problematic Internet use (Byun et al., 2009; Chou et al., 2005) Although Internet (Byun et al., 2009; Chou & Hsiao, 2000; Chou et al., 2005; Soule, Shell, & Kleen, 2003; Thatcher & Goolam, 2005; Young, 1998b) other common terms have been use d including Internet addiction (Goldberg, 1996) Internet (Davis, 2001; Morahan Martin & Schumacher, 2000) and Inte rnet (Anderson, 1998, March; Scherer, 1997) This literature revie w will include studies using the se common terms; however, Internet out the writing for the ease of discussion
14 Definition There is not a standardized definition of Internet addiction among researchers ; although most agree that the phenomenon does exist (Chou et al., 2005) In Chou and review, they mentioned that Internet psychological dependence on the Internet regardless of the type of activity once logged (Kandell, 1998 p 12 ) Problematic use of the Internet inability to control the dependence and therefore leads to emotional distress and daily function impairment (Shapira et al., 2000) Internet addiction is also characterized by the compulsive use of the Internet normal life ( Rice, 2005) A more holistic definition of Internet addiction suggests that overuse of the Internet can impa psychological states, which includes both mental and emotional states, as well as their scholastic, occupational, and social interactions (Beard, 2005) Conceptualization A ddiction has been commonly an d sometimes exclusively applied to the pathological dependence on a chemical substance (Bratter & Forrest, 1985; Marlatt & Witkiewitz, 2008) However compulsive, uncontrollable dependence on a chemical substance, habit, or practice to such a degree that either the means of obtaining or ceasing use may cause several emotional, mental, or physiological reactions (Myer s, 2006) Based on this definition of addiction, compulsive and uncontrollable dependence on the Internet can legitimately be conceptu alized as a kind of addiction. In fact, it has been speculated that excessive Internet use similar to other out of contro l behavioral tendencies may share the same neurological mechanism with substance abuse (Holden, 2001) Widyanto and Griffiths
15 (2006) pointed out that Internet addiction can be conceptualized as a form of behavioral a ddi c tion (Douglas et al., 2008; Marks, 1990) under the generic umbrella term of (Griffiths, 1996b 1998 2003) ; t echnology addictions are defined as behavioral addictions that involve human machine interaction which can be passive such as watching television, or active such as surfing online (Griffiths, 1995) Widyanto and Griffiths mentioned that t echnology addictions can exhibit typical addiction characteristics such as salience, mood modification, tolerance, withdrawal, conflict, and relapse (Griff iths, 1996a) The common component of both behavioral addiction and substance addiction is psychological dependence (Bradley, 1990; Marks, 1990 ; Shapira et al, 2003 ) Diagnosis of I nternet a ddi ction Young (1998 b ) m entioned that the diagnosis as well as the treatment of Internet addiction ha s been complicated due to the fact that the term, addiction, is not used in the Diagnostic and Statistical Manual of Mental Disorders, F ourth E dition (DSM IV ) (American Psychiatric Association, 1994) Therefore, there are no official diagnostic criteria for Internet addiction. Kaltiala Heino, Lintonen, and Rimpel (2004) pointed out that s ome researc hers adopt ed the diagnos t i c criteria of impulse control disorder such as compulsive gambling for the diagnosis of Internet addiction whereas diagnostic criteria of substance ab use disorder s were used by other researchers Diagnosis of Internet addiction u sing criteria of substance use disorders Based on the rationale that substance dependence is the most similar term capturing the essence of addiction in the diagnos i s of mental disorders (Walters, 1996) the seven diagnostic criteria of substance dependence in the DSM IV were proposed as the workable model for the diagnosis of Internet addiction ( Anderson, 2001; Young, 1996)
16 With the same underlying addiction conceptualization, Young (1996 ) suggested that people may develop Internet addiction as a substitute to other common addictions such as chemical dependencies and pathological gambling. Internet addiction as a kind of impulse control disorders Th e d iagnostic criteria of impulse control disorders have also been adapted for the diagnosis of Internet addiction (Young & Rogers, 1998; Young, 1998a; Young, 1998b) It has b een pointed out that the main diagnostic features for the impulse control disorder of pathological gambling closely resemble the main features of pathological Internet use (Young, 1998b) Shapira, Goldsmith, Keck, Kho sla, & McElroy (2000) found that all subjects in their study of Internet addiction met the diagnostic criteria for an impulse control disorder (ICD) not otherwise specified. A high prevalence of features of impulse control disorders was also found among 86 Internet users who completed an evaluative online survey (Treuer, Fbin, & Fredi, 2001) To diagnose Internet addiction, Young (1998) proposed adapting eight of the ten criteria used for diagnosing compulsive gam bling ; the diagnosis would be warranted if five of the eight criteria were met (Young, 1998b) In an attempt to stre ngthen the theoretical stance, Y necessary criteria (Beard & Wolf, 2001) Based on the diagnostic criteria of impulse control disorders in the Diagnostic and Statistical Manual of Mental Disorders Fourth E dition, text revision (DSM IV TR, American Psychiatric Association, 2000) and the proposed compulsive buying diagnostic criteria (McElroy, Keck Jr, Pope Jr, Smith, & Strakowski, 1994) Shapira and colleagues argued that Internet addiction is a kind of
17 before Internet (Shapira et al., 2003 p. 212 ) Integrated diagnostic criteria from various disorders. Internet addiction was once thought to be a variant on the spectrum of obsessive compulsive disorders (OCD) (Goldsmith, Shapira, Phillips, & McElroy, 1998) that are often co morbid with depressive disorders (Shapira et al., 2000) However, Shapira et al. found that Internet addiction among the 20 interviewed participan ts was more closely related to the symptoms of ICD rather than OCD in DSM IV. Another surpr ising finding is the high percentage (80%) of participants meeting the lifetime criteria of bipolar disorder or schizoaffective disorder, bipolar t ype but the relat ively low lifetime rates of co morbid major depressive disorder (15%) and OCD (20%) among these participants. Therefore, Shapira et al. concluded that Internet addiction can be better diagnosed with the criteria of impulse control di sorder, not otherwise s pecified. Although this study used the somewhat qualitative semi structured diagnostic interview to assess Internet addiction, Shapira et al. did not clearly describe their methodology and limitations. Th e conclusion seems rather dogmatic with such a small sample that consisted of participants with many comorbid psychiatric disorders such as bipolar disorders. Based on previous diagnostic criteria, studies, and clinical observation s a set of Internet addiction diagnostic criteria specific for adolescents int egrated the criteria of substance dependence and impulsive control disorders (Ko, Yen, Chen, Chen, & Yen, 2005) Ko and colleague s indicated that t hese empirically verified criteria could be grouped into three main ca tegories. C riterion A contains previous ly proposed symptoms such as preoccupation, uncontrolled impulse, usage more than intended, tolerance,
18 withdrawal, impairment of control, excessive time and effort spent on the Internet and impairment of decision mak ing ability (Christensen, Orzack, Babington, & Patsoaughter, 2001; Hall & Parsons, 2001; Shapira et al., 2003) T hey mentioned that t hese symptoms are mostly in line w ith previously proposed criteria for behavior addi c tion (Goodman, 1993) and the diagnostic criteria for compulsive gambling in the DSM IV (American Psychiat ric Association, 1994) ; h owever one symptom in Criterion A : spent on activities necessary to obtain access to the Internet was modified based on the diagnostic criteria of substance dependence in the DSM IV They also proposed that on e has to meet at least six out of the nine listed symptoms in Criterion A to be diagnosed as having Internet addiction In addition, C riterion B includes the symptoms related to functional impairment whereas Criterion C concludes with the exclusive criteri a to eliminate the possibility of psychotic disorders and bipolar I disorder (Ko et al., 2005) More recently Ko et a l. (2009) modified their earlier criteria to be applicable to college students The y included two symp toms, preoccupation and uncontrolled impulse, which resemble diagnostic criteria of pathological gambling as well as seven other diagnostic criteria that are similar to the diagnostic criteria for substance dependence in the DSM IV TR. Ko et al. (2005) arg ued that Internet addiction seems to share core symptoms of substance abuse dependence and impulse control disorder and that there is no sufficient evidence to classify Internet addiction only as an impulse control disorder Due to the absence of validate d diagnostic criteria, other researchers have incorporated diagnostic criteria from impulse control disorders, substance abuse, and obsessive compulsive disorder in their description of Internet addiction
19 (Aboujaoud e, Koran, Gamel, Large, & Serpe, 2006) However, Ko and colleague s (2005) suggested that including the criteria from multiple other disorders might set the diagnostic bar too high for the diagnosis of Internet addiction For example, Aboujaoude et al. (20 06) used four similar sets of criteria based on the three types of disorders and found that 3.7% to 13.7% of the participants endorsed one or more criteria whereas only 0.3% to 0.7% of the participants met the four sets of criteria entirely Overall def initions of Internet addiction may vary due to various theoretical (2005) definition of Internet addiction because it has a more holistic view that encompasses both psyc holog ical aspects and daily functioning regarding Internet addiction. Conceptually, this study takes the stance that Internet addiction is a form of behavioral addiction (Douglas et al., 2008; Ma rks, 1990) that has the same psychological dependence as substance addiction (Bradley, 1990; Marks, 1990) Based on this conceptualization, this study adopts the diagnostic proposition of Inter net addiction that follows the diagnostic criteria of substance use disorders because impulsive symptoms can be explained as the result of psychological dependence. It should be kept in mind that although this study uses the above mentioned definition of I nternet addiction, there will be some variations in the literature reviewed. Symptoms of Internet Addiction Based on (2005) review and other the empirical studies that have been conducted regarding Internet addiction, there are the fo llowing main symptoms of Internet addiction.
20 Poor time management Because problematic Internet use is typically characterized by prolonged time spent on the Internet, time spent online was suggested as an important index to decipher Internet addiction (Chou et al., 2005) Many studies regarding Internet addiction have reported excess ive time spent online among Internet addicts. For example, Young (1998) reported that Internet dependent participants spent a staggering 39 h ours online per week whereas Internet non dependents only spent 5 hours online per week (Young, 1998b) In another study which attempted to develop an Internet addiction diagnostic instrument (Chen & Chou, 1999, August) it was found that the high risk group spent 20 hours online per week, significantly more than the nine hours spent online per week by the none high risk group. In addition, the degree of Internet addictio use hours. Another study on Internet addiction among Taiwanese college students also found that the average time that Internet addicts spent online, 20 to 25 hours per week, was nearly tri ple the time of non addicts (Chou & Hsiao, 2000) The most obvious symptoms for p eople with Internet addiction is that they spend an excessive amount of time on the Internet and often have trouble managing time. Brenne r ( 1997) argued that Internet dependent participants seemed to demonstrate some behavioral symptoms similar to tolerance, withdrawal, and caving that led to more time spent online. For example, 55% of the respon dents have been told by others that they spen d too much time on the Internet 28% find it hard to stop thinking about the Internet if they had not used it in a while and 22% of participants indicated that they attempted to spend less time online but were unable to d o so Significant differences abou t time management between Internet dependent and non dependent students have
21 also been found. found that self identified Internet dependent college students were statistically more likely than non dependent students to agree on questions regarding time management such as have suggested to me that I spend too much time on the Internet feel a little guilty about the amount of time I spend on the Internet ly these Internet d ependent students spent almost three times as much recreational time online each week, 11.18 hours, compared to 3.84 hours for non dependent students. Because of poor time management these Internet dependent students reported that the Internet usually kee ps them up late and they often feel tired th e next day due to the excessive Internet use until late night T hey indicated that it would be better if they spent less time on the Internet and admitted that they lacked control over Internet use Poor academic performance Poor academic and professional performances have often been noted among Internet dependent users. In study on college students, a staggering 58% of the participants reported that they suffered from poor study habits, poor grade s, or failed school due to excessive Internet use. Kubey et al. (2001) found that 14% or 80 of the 572 college students in their study indicated that their school work had been negatively affected due to Internet use. The students who were most negatively affected reported more than double the Internet usage time than the average usage reported for the entire sample. Internet dependent students were almost four times more likely than non Internet dependent students to report these academic impairments. When compared with students with no academic impairments, academically impaired students showed significant differences on many Internet related symptoms. They were more likely to stay up late and feel tired the next day due to Internet use
22 Increased unhealth y behaviors People with Internet addiction also seem to engage in many unhealthy behaviors. J.S. Kim and Chung (2005) studied Korean high school students and found that Internet addiction was negatively correlated to perceived health status. Compared with non addicted students, those students with severe Internet addiction reported having poorer diet and nutrition intake, less regular exercise and sleep, reduced personal hygiene fewer social relationships, less self regulation less emotional support from others, and less self realization J.H. Kim et al. (2009) examined 2427 college students heavy Internet use and their health risk behaviors and health promoting behaviors in a Hong Kong university The result also showed that heavy Internet use was assoc iated with significant ly lower likelihood of engaging in health promoting behaviors including attempting to eat a healthier diet, taking nutritional supplement s trying to increase physical activity levels, exercising regularly and seeking immediate medic al care when ill. Students with heavy Internet use were also less likely to adopt healthier personal habits including improving maintain a regular daily routine. In addition, h eavy Internet use was also associated with multiple health risk behaviors such as skipping meals and sleeping late as well as poor health outcomes such as obesity and hypersomnia. Disrupted interpersonal relationships People with Internet addiction also seem to lose social interactions with others. In study, 396 Internet dependent users reported their interpersonal relationship such as marriages, dating relationships, parent child relationship and close friendships were disrupted by excess ive use of the Internet
23 (1998) longitudinal study investigating 98 families and a total of 169 participants in their first year or two of Internet use, results showed that Internet use was consistently associated with small but st atistically significant decrease s in social involvement networks. Greater Internet use was also found to negatively relate to distant social circle, soci al support, and stress level although the associations were not statistically significant. Based on the results, the researchers suggest that Internet use yet it tends to actually reduce cial involvement. Although Internet users usually report using the Internet to engage in social activity online and therefore derive a sense of communication pleasure, this process results in self confi ne ment to virtual communications and reduc tion in time engaging in real life face to face social interactions (Davis, Flett, & Besser, 2002b) P sychological distress Based on longitudinal study more Internet use significantly increases feel ing s of loneliness and depression Kraut and his colleagues used path analysi s to test relationships between Internet use, loneliness, depression and other personal and demographic variables among the participants. They also found that initial loneliness and depression did not predict subsequent Internet use. However Internet use significantly predicted increased loneliness and depression at a subsequent time after controlling demographic variables. Therefore, Kraut et al. conclude d that loneliness and d epression are consequences but not causes of Internet use Kraut and colleagues (1998) also tested the relationship between Internet use and subsequent perceived stress ( e.g., daily hassles ) Although more Internet use
24 marginally predicted greater numbe r of reported daily life stressors at the subsequent time ( p = .08), the post hoc analysis of specific stressors did not reveal significant increase of any single stressor. Kraut et al. suggested that Internet use may increase aggregate stress but it d oes not follow a common path to a specific stressor among the participants. T he researchers did not report whether initial stress predicted subsequent Internet use. Demographic Factors Associated with Internet Addiction Am ong demographic factors, gender, age years of Internet use have been associated with Internet addiction in previous studies. Therefo re, these factors will be discussed in detail below. Gender There seem to be gender difference s regarding Internet addiction vulnerability and types of Interne t addicti on. As Chou and colleague s (2005) pointed out in their review, m ost of the studies revealed that men are more likely to have Internet addiction. For example, Scherer (1997) found that 71% of dependent Internet users in her sample were men, whereas among non dependent users, the gender ratio was evenly distributed at 50% Another study also found that males were more likely to be pathological Internet users than females (12% males versus 3% females), whereas females compared to males were more likel y to show limited symptoms (69% versus 61%) or no symptoms (28% versus 26%). In addition, males had a significantly higher average number of pathological symptoms than females (Morahan Martin & Schumacher, 2000) However, there might be some sample problem s for this difference. For example, even though regression analysis indicated males were more likely than females to be Internet addicts in one study (Chou & Hsiao, 2000) t here were
25 only three female respondents out of the 54 Internet addiction case s in that study (Chou et al., 2005) Interestingly, Chou and colleague s this gender difference i n Internet addic tion did not show up in some other studies. For example, Brenner (1997) found that men and women did not differ in time spent online or in the number of problem s they experience d (Brenner, 1997) In another study Yo ung (1998) found that t here were even more Internet dependent women than men (Young, 1998b) However, these findings were criticized for using self selected online samples which might have introduced stronger sampling bias (Chou et al., 2005) I t was also pointed out that female researchers might have been able to recruit more female Internet addicts and that women are generally more willing to express their emotional problems than m en (Griffiths, 1998) Overall, it was noted that different methodologies and sample methods might have affected whether gender differences were found For instance, studies using paper and pencil questionnaires on college campuses tend to show that males are more likely to be addicted to the Internet whereas online studies with a diverse population usually revealed no gender differences (Chou et al., 2005) This could be due to ei ther sampling issue s or social desirability factor s ender differences may be reflected in unique patterns of Internet addiction. More men than women appeared drawn to the interactive online games t hat highlight power, dominance, control, and/or violence. In addition, although men would tend to explore sexual fantasies online, women sought out close friendships and romances through anonymous online communication (Young, 1998b) Another study indicated that although time
26 management problems and compulsion symptoms served as common predictors for both men and women some unique factors predicted the time spent online for each gender. Specifically, shyness and withd rawal symptoms were the only predictive factors among the female college participants whereas previous Internet experiences and tolerance symptoms were only predictive for male participants (Chen, 2000 ) Age I nternet usage seems to vary among people of different ages. In a national representative study in Italy, time spent on the Internet seemed significant ly elevated for the adolescen ts and adults (Bricolo, Gentile, Smels er, & Serpelloni, 2007) Specifically, children aged 2 to 11 on average spent a total of 13 hours online each month whereas adolescents aged 12 to 20 spent 39 hours online per month. Adult males in two age groups, 35 to 44 and 45 to 55, spent 41 and 45 ho urs online whereas adult females in two age groups, 30 to 40 and 41 to 51, spent 30 and 26 hours online per month. When examining the age group differences on their frequencies of staying online, about 23% of adolescents compared to 28% of adult males vis ited the Internet on any given day whereas only 4% of children stayed on the Internet every day. Based on these descriptive statistics and the associations found between Internet addiction and time spent online, the likelihood of having Internet addiction seems to escalate since adolescence In another study exploring the demographic characteristics of heavy Internet users, Internet users who were 20 or younger spent significantly more recreational hours online than users over age 20 (Soule et al., 2003) These studies suggested that age may relate to Internet addiction; however, these results have serious limitations because they are cross sectional so there is possibility that the
27 differences can be due to other ge neration related factors experience. Years of Internet use Internet addicts seem to have longer Internet using history than non depend e nt people. Kubey et al. (2001) examined Internet addiction among college students and found t hat the ratio between Internet addicts and non dependent Internet users became larger as the years of Internet using experience increased Specifically, 79.2% of Internet dependent students indicated they had used the Internet for two to three years or lon ger, whereas only 55.1% of non dependent students said the same Among the Internet users who had used the Internet for four years or longer, there were almost five times more Internet dependent students (35.9%) than non dependent students (7.5%) Lin and Tsai (2002) examined Internet use and they also found that Internet dependent students had longer Internet experience. Among these Internet dependent students 32% used the Internet for more than 2 years and almost 14% of th em used the Internet for mo re than 3 years. Lin and Tsai interpreted th ese findings as indicative that the younger the individuals were when they started using the Internet the more easily they became addicted to it. Although these studies show years of I nternet use is related to Internet addiction the results were only presented in simple descriptive analysis and t test in categorical comparison between Internet dependent participants and non Internet dependent participants. Studies using dimensional app roaches can potentially clarify the relationship between years of Internet experiences and Internet addiction.
28 Stress and Internet Addiction A ddictions may develop in reaction to stressful and unpleasant life events such as marriage problems or career iss ues (Fanning & John, 1996) Internet addiction, just like substance abuse addictions, may occur when people cope with stressful situations through temporarily relieving, escaping, or avoiding the unpleasant feelings (Young, 1999) Castiglione (2008) proposed the conceptual framework to view Internet addiction as a result of maladaptive stress coping. However, due to the lack of research on the relationship between stress and Int ernet addiction, the relevant theories and research regarding stress and substance abuse addictions will be reviewed below. Internet Use and Stress Coping People may use the Internet to reduce their stress. Study results on Internet procrastination indire ctly impl y that Internet addiction may be a maladaptive stress coping s online procrastination, attitudes and emotion revealed that 50.7% of the respondents reported frequent Internet procrastination and on ave rage respondents spent 47% of time online procrastinating Specifically, Internet procrastination was positively correlated with perceiving the Internet as a relief from stress ( r = .57 ), as entertaining ( r = .35 ), and as an important tool ( r = .24 ). In ad dition, using Internet to relieve stress was also positively and independently related to online entertainment ( r = .46). Lavoie and Pychyl suggested that Internet users may procrastinate online by temporarily diminishing stress through entertaining distra ctions because procrastination in task avoidance serves to relieve task anxiety (Ferrari, Johnson, & McCown, 1995) and procrastinators would engage in some less stressful activity (McCown & Johnson, 1991) This hypothesis was adopted by researchers who studied Internet addiction (Davis, Flett, & Besse r, 2002a 2002b)
29 Distraction, procrastination, and problematic Inte rnet use were found to be highly correlated (Davis, Flett, & Besser, 2002b) Whang, Lee, and Chang (2002) conducted a large scale study investigating psychological features of Internet users in Korea and found intere sting associations between stress and Internet use They divided participants into three groups based on their Internet addiction level: the addicted group (IA), the possible addicts (PA), and non addicts (NA). When participants felt stressed by people, bo th the IA and PA groups reported more Internet use (IA, 21.2%; PA 14.3%) than the NA group (8.6%), whereas the IA and PA group reported a lower chance of meeting people (IA, 2.8%; PA 5.2%) than the NA group (6.2%). When participants felt stressed by work, again both the IA and PA groups had more Internet use (IA, 20.4%, PA, 16.6%) than the NA group (NA, 5.0%); however, the NA group reported more drinking of alcohol than the IA and PA groups ( NA, 18.8%; PA, 16%; IA: 14.2%). Overall, the rates of reported Int ernet use were two to four times more for the Internet addicted group than the non addicted group in stres sful situations. Whang et al. suggested that people use different behavioral repertoires in different stressful situations depending on their Internet addiction level. Therefore, Internet addicts seem more likely to use Internet than other activities (such as drinking) to relieve their stress. This finding could be well explained by the Stress Response Dampening Model However, the researchers in this s tudy did not try to further examine which personality factors were related to the Internet addiction level. Internet Addiction as A Way of Stress Coping among College Students College students may be more vulnerable to developing Internet addiction due to various stresses they face. Kandell (1998) theorized that college students may develop Internet addiction to cope or resolve stressful challenges such as identity and intimacy
30 development along with academic pressure. Kandell suggested that the developmen t of Internet addiction among college students due to these psychological and developmental dynamics seems especially facilitated by the ready access to the Internet and the expectation of computer/Internet use in college. A study investigating excess Inte rnet use among undergraduate students in Pakistan found that 61% of the respondents indicated that they stayed online to forget their real life problems or to avoid stress, and 52.5% of them reported gaining great pleasure and satisfaction by being online. The researchers pointed out that more than half of the respondents they found the Internet consoling during times of stress (Suhail & Bargees, 2006) Li, Wang, and Wang (2009) studied problematic Internet use and found that stressful life events seemed to contribute to Internet addiction. When comparing the 13.6% of respondents who were class ified as Internet addicts with the other respondents, it was found that the frequency of stressful life events over the past 6 months was significantly higher in the Internet addicted group than the non Internet addicted group. Group differences were most prominent in terms of academic stress, job related stress, socio communication, daily hassles and major life events In addition, the Internet addicted group also tended to use more avoidant coping such as self blame, fantasy, withdrawal, and rationalizat ion as well as less positive coping such as problem solving and help seeking. Further path analysis addiction through those avoidant coping styles.
31 The Stress Diathes is Perspective The stress diathesis perspective has been used to explain the development of Internet addiction (Davis, 2001) Based on the stress diathesis theory (Rosenthal, 1963) Internet addiction could also be conceptualized as resulting from an interaction between pre dispositions and stress. Finding pre dispositional factors of Internet addiction is of tremendous value to help identify people who might be vulnerable to developing Internet addiction when facing stress. Although Davis (2001) theorized that the predisposition of Internet addiction could be attributed to the presence of another mental disorder and/or maladaptive cognition, most empirical studies have focused on predispositions in terms of personality tendencies. Based on the stress diathesis perspective, the interaction effect of stress and the pre dispositional personality factors regarding addiction has been intricately presented by the Stress Response Damp ening Model Stress Response Dampening Model Framing on the tension reduction theory of alcoholism, the Stress Response Dampening Model was proposed by Sher and Levenson (1982). In their initial two experiments, individual differences of physiological and affective responses to alcohol under stress conditions were found between high risk and low risk groups of alcoholism. Specifically, the high risk group showed pronounced reduction of stress responses in regards to cardiovascular readings and reported affe ctive changes compared to the low response dampening (SRD) effect was more prominent for the high risk group. The researchers concluded with three findings. First, SRD effect. Second, these individual
32 difference response patterns in the high risk group and the low risk group. Third, the individual differences were related to cha racteristics sampled by personality measures because the division of high risk and low risk groups were based on these personality measures. Although the physiological mechanisms are not clearly specified in the SRD model, the researchers proposed three ba sic components of the SRD model: a) risk for alcoholism is associated with certain personality traits, b) there are individual alcoholism can be conceptualized in terms of rein forcement. They argued that biologically and thus, they would have great reinforcement for drinking. Once the reinforcement pattern had been established through the proc ess of increased tolerance, it would lead to greater consumption, unpleasant withdrawal symptoms during attempts to stop drinking, and generalization of drinking behavior to a greater range of potentially stressful situations (Sher & Levenson, 1982) Sher and Levenson (1982) proposed that individuals with outgoing, aggressive, impulsive, and antisocial personality characteristics would be predisposed to develop ents. However, the personality measures they used could not differentiate risk to alcoholism from other types of drug addictions. Therefore, this opens up the applicability of the SRD model to other types of addiction. The SRD model could potentially be us ed to explain behavioral addictions such as Internet addiction, in light of the behavioral reinforcement conceptualization of addiction.
33 Personality Factors of Internet Addiction Based on the stress diathesis perspective, it would be important to explore h ow diatheses would contribute to the development of Internet addiction in addition to examining the relationship between stress and Internet addiction. Biological diatheses are usually represented by various pre di spositional personality factors in the fie ld of psychology. According to the SRD model (Sher & Levenson, 1982) it would also be important to figure out how individual differences regarding pre dispositional personality factors result in addictive tendency wh en facing stress. Several pre dispositional personality characteristics have been explored in the attempt of figuring out what may contribute to Internet addiction. And r esearchers have also started to explore what personality attributes may put certain in dividuals more vulnerable to Internet addiction than others The Big F ive P ersonality T raits (Goldberg, 1981, p. 159) personality theory provides a structural framework that is widely recognized. Although there are still arguments among researchers regarding the names of the five personality traits, the most known lexical labels of the five version, Openness Agreeableness, and Conscientiousness (McCrae & Costa, 1990, p. 176 ) several studies. Extra version and related traits longitudinal follow up study by found a m oderating effect of extraversion on the rela tionship between Internet use and well being. Specifically, extraverts who used the Internet more reported improved well being such
34 as decreased loneliness, less negative affect, decreased time pressure, and greater self esteem; however, introverts who use d more Internet showed decreased well being on these same indexes. A study of 122 German adolescents found that extraversion was only associated with greater motive to use Internet for interpersonal communication; however, neuroticism was associated with g reater motivation to use Internet for entertainment purposes (Wolfradt & Doll, 2001) Social anxiety has also been suggested to be one of the causes of Internet addiction. study examined the relatio nship between social anxiety and Internet addiction among 343 undergraduate college students (Caplan, 2007) The results indicated that social anxiety highly explained the positive correlation between loneliness and interaction was twice as strong as a predictor for problematic Internet use. Based on the results, the researchers suggested that socially anxious individuals would prefer online social interaction which would further lead to Internet addiction. A similar construct, shyness, has also been proposed to predict Internet addiction. In 4) study of 722 Internet users, shyness was found to be associated with a moderate but statistically significant increase in Internet addiction; however, interestingly, shyness did not seem to predispose them to higher communicative Internet usage. This co ntradicts previous allegations that Internet addicts seek out online communications (Chou, 2001) Surprisingly, shy male participants actually used e mail, ICQ, and chat room services less. The researchers commented that the results indicate that shy people may not find it easier to
35 communicate online; they may not seek out online communication, but rather they may be addicted to the other Internet applications for recreational or leisure purposes. In addition, the study did not find a significant relationship between shyness and time spent online. It is worth noting that the researchers also explored a related personality construct, locus of control and discovered similar patterns: participants with external oriented lotu s control were more prone to Internet addiction and online gaming but not Internet use in general. Extr a version and neuroticism Hamburger and Ben (2000) revealed that extraversion was positively associ ated with the use of leisure services online but neuroticism was negatively related to the use of information services online. Furthermore, men and women showed different patterns regarding the relationships between personality traits and Internet usage. F or men, extraversion was positively associated with use of leisure services online whereas neuroticism was negatively associated with use of information services. For women, extraversion was negatively related to use of social services online but neurotic ism was positively related to use of social services online. Amichai Hamburger and Ben study on 85 Internet users that examined the patterns mentioned above found similar but somewhat different results. For the whole sample and for male pa rticipants only, extraversion was positively related to use of information and leisure services online. For women, neuroticism was positively related to use of social services online. online survey on 96 adults examined the role of personality, loneliness, and social support networks for Internet addiction. This study revealed that Internet addicts and over users compared to average Internet users were
36 significantly more neurotic, less extraverted, and more socially anxious. However, based on a hierarchical multiple regression analysis, only neuroticism and perceived support from online social networks were significant predictors for Internet addiction (Hardie & Tee, 2007) Although these findi ngs are informative, the smaller sample sizes of these studies raise some questions whether these findings are reliable and/or generalizable. The c onscientiousness related trait: s ensation seeking Zucke rman, Kuhlman, Joireman, Teta, and Kraft (1993) propo sed the Alternative Five factor model that has four comparable constructs with the Big Five model. The expected to be negatively related to conscientiousness in the Big Five mod el. Since this sensation seeking will be categorized under the label of conscientiousness. As in the literature regarding substance abuse addiction, sensation seeking h as been suspected as an important reason for Internet addiction However, the results have been inconsistent (Chou et al., 2005) Lavin and colleague s investigated the association between sensation seeking and Internet dependence on 342 college students. Contra ry to the researchers the findings show ed that Internet dependent students actually scored significantly lower than non dependent students not only on the overall sensation seeking score but also on t he thrill and adventure seeking and excitement seeking. The researchers explained that the surprising results could stem from various sources First, the Internet dependent students characteristic s could be conceptualized as sociable rather than sensation seeking. Second, the instrument used to measure sensation seeking might not be able
37 to assess non physical sensation seeking behaviors (Lavin, Marvin, McLarney, Nola, & Scott, 1999) Chou et al. (2005) also pointed ou t that the measure used to differentiate non dependent and dependent Internet users in this study lacks some Internet addiction component s such as tolerance, withdrawal, and other related problems. Lin and Tsai (2002) found somewhat different results in t heir study of 753 Taiwanese high school students Specifically Internet dependents had significantly higher overall sensation seeking score s and higher dis inhibition score s (a subscale of sensation seeking) than the non dependents; however, no group dif ferences were found on sensation seeking in terms of the life experience seeking and thrill and adventure seeking. The researchers suggested that Internet addiction could result from the developmental need for these Internet dependent Taiwanese adolescent s to strive for personal identity through breaking social inhibition online. Another characteristic similar to sensation seeking for Internet addiction is pleasure seeking and gratification of needs. examined the relatio nship between communication pleasure and Internet addiction. The Internet addiction scores were positively related to their scores on escape pleasure, interpersonal relationship pleasure, and total communication pleasure. The researchers interpreted the findings based on Play Theory of Mass Communication (Stephenson, 1988) and concluded that Internet addiction resulted from individuals who used the Internet to seek com munication pleasure experience. large scale longitudinal study was conducted on 910 Taiwanese college students to further examine Internet addiction and pleasure gratification. This study found that Internet addicted students
38 had si gnificantly higher communication pleasure and satisfaction scores than the non addicted students. Communication pleasure score s and satisfaction scores along with BBS use hours, email use hours, and gender were found to be the most powerful predictors for Internet addiction among the participants. These findings suggest that tendency on the aspect of communication pleasure. Other related personality factors online survey study investigated 259 Internet the Sixteen Personality Factor Inventory (16PF). The study results showed that Internet dependent users ranked high on personality traits such as self reliance, emotional sensitivity and reactivity, vigilance, low self disclosure, and non conformist. The authors indicate d people with such personality traits may be predisposed to fulfill their unmet psychological needs through online stimulation. Ko and colleague (2006) cross sectio nal study compared the different patterns of personality characteristics among 3412 Taiwanese high school students who either had Internet addiction, substance abuse addiction, or both. The results indicated that there were no significant personality diffe rences between the substance abuse group and the co morbid group. When compared with students without substance abuse addiction, students with substance addiction had significantly higher novelty seeking, lower harm avoidance, and lower reward dependence. Interestingly, students with Internet addiction also had higher novelty seeking and lower reward dependence compared with students without Internet addiction; however, students with Internet addiction in particular showed higher harm avoidance than their c ounterparts. The researchers suggested that
39 individuals with Internet addiction might use the Internet to avoid stress and to alleviate a fear of real life harm (Ko et al., 2006) Ko and colleagues (2007) conducted anothe r longitudinal study examined how personality factors might affect the occurrence and remission of Internet addiction among 517 high school students in southern Taiwan (Ko, Yen, Yen, Lin, & Yang, 2007) For those parti cipants who did not have Internet addiction initially high exploratory excitability, and low reward dependence predicted the emergenc e of Internet addiction Specifically within the construct of reward dependence, these participants had significantly low er scores on sentimentality and persistence subscales. The researchers explained that the immediacy and predictability of Internet activities might have rewarded these adolescents with impaired reward response. For those participants who initially had Inte rnet addiction, low hostility and low interpersonal sensitivity predicted remission of Internet addiction. The researchers interpreted low interpersonal sensitivity as low interpersonal anxiety and indicated that these two personality characteristics could be protective factors for Internet addiction. The noteworthy non significant findings in this study are that the scores of overall novelty seeking and harm avoidance did not predict the occurrence of Internet addiction, which contradict the previous cross sectional findings (Ko et al., 2006) In conclusion the studies exploring the effects of personality factors on Internet addiction have been inconsistent. One study actually found no associations between the Big Five per sonality dimensions and Internet addiction measures (Engelberg & Sjoberg, 2004) However, this inconsistency is not that surprising when considering the literature regarding the effects of personality factors on su bstance abuse addiction. Personality
40 factors such as neuroticism or negative emotionality, impulsivity or disinhibition ( e.g., sensation seeking) and extraversion or positive emotionality have been suggested to potentially predispose people in developing alcoholism or substance abuse addiction; however, the attempt to find an addictive personality has been not successful (Ibez, Ruiperez, Villa, Moya, & Ortet, 2008) There have been great inconsistencies across studi es for the link between these main personality dimensions and substance abuse addiction even though some combination of these higher order personality traits could be carefully interpreted as risk factors for the later development of alcoholism and substan ce abuse addiction (Chassin, Flora, & King, 2004) Due to the inconsistent results regarding proposed higher order personality factors for addictive personality Rice and Van Arsdale (2010) have recently suggested t hat a refined examination of personality factors focusing more on lower order ed personality factors and their m oderating effect s can better reveal the contributions of personality on addict ive behaviors Perfectionism is one of the promising lower order pe rsonality factors that may be closely related to addictive behaviors. Clinically, many substance abuse addiction patients exhibit characteristics of pe rfectionism such as extreme ly high standards and distress for the discrepancy between standards and behav iors. Surprisingly, there is a lack of theories and studies regarding this common clinical observation. In one recent study, Rice and Van Arsdale proposed that perfectionism as a lower order personality factor is a good candidate in studying addiction beca use it relates to higher order personality factors such as conscientiousness and neuroticism which are conceptually related to substance abuse addiction. Therefore, focusing on
41 perfectionism may potentially bridge the literature gap regarding addictive per sonality factors for Internet addiction. In addition to exploring the high associations with Internet addiction the effect of perfectionism on Internet addiction would also be one main area that could possibl y further the litera ture of Internet addiction The construct of perfectionism as an important lower order personality factor for Internet addiction will be discussed in the following section. Perfectionism and Internet Addiction T he relationship between perfectionism and In ternet addiction has not been specifically ex amined in published literature; therefore, literature regarding to substance abuse addiction and behavioral addictions will be reviewed to help understand the possible relationship between perfectionism and Inte rnet addiction. Specifically the relationship between perfectionism and Internet addiction will be discussed through the stress diathesis perspective. Among the lower order personality factors, perfectionism is a good candidate predictor because it has be en found to significantly correlate with neurotic ism and conscientiousness (Rice & Van Arsdale, 2010) the two main hypothesized addictive personality components theoretically in addition to extraversion ( Ibez et al., 2008). To start with the exploration, the construct of perfectionism is first discussed below. Dimensions of Perfectionism Perfectionism is a personality trait that has been observed and studied extensively. One of the first and clearer definitions describes perfectionism as demanding of self or others a higher quality of performance than required by the situation (Hollender, 1978) Based on their literature review of the concept of perfectionism, Slaney an d Ashby (1996) also pointed out that perfectionism mostly
42 involves excessively high personal standards (Slaney & Ashby, 1996) Researchers have found support to view perfectionism as a multidimensional construct (Flett & Hewitt, 2002; Frost, Marten, Lahart, & Rosenblate, 1990; Slaney, Rice, Mobley, Trippi, & Ashby, 2001) Maladaptive p erfectionism and a daptive p erfectionism Although perfectionism was proposed to encompass a number of dimensions, factor analyses and cluster analyses in the literature on perfection ism has generally shown two major dimensions: the adaptive or positive aspects of perfectionism versus the maladaptive or n egative aspects of perfectionism (Frost, Heimberg, Holt, & Mattia, 1993; Rice, Ashby, & Slaney, 1998; Rice & Slaney, 2002; Slaney, Ashby, & Trippi, 1995 ) Slaney, Rice, and Ashby (2002) proposed that a dimension referred to as tandards one distinguishes positive adaptive perfectionism and negative ma ladaptive perfectionism. With the additional dimension of discrepancy, Slaney and colleagues argued that people could be divided into three groups in terms of perfectionism: adaptive perfectionists who have high personal standards and low discrepancy, mala daptive perfectionists who have high personal standards and high discrepancy, and non perfectionists who have low personal standards regardless of discrepancy level. Although adaptive perfectionism has been usually related to positive functioning indicato rs such as good affect regulation and coping, high self esteem, and good interpersonal adjustment, m aladaptive perfectionism has been linked to many negative indicators of neuroticism and problematic coping styles such as self criticism, more perceived st ress anxiety, emotional dysregulation, and depression (Aldea & Rice, 2006;
43 Dunkley, Zuroff, & Blankstein, 2003; Grzegorek, Slaney, Franze, & Rice, 2004; Mobley, Slaney, & Rice, 2005; Slaney, Pincus, Uliaszek, & Wang, 2006) Although perfectionism in general has been found to significantly correlate with the higher order personality factors such as neuroticism and conscientio usness, the moderate sized correlations suggest that perfectionism is a distinct personality construct (Enns & Cox, 2002) In addition, perfectionism was also found to further explain variance that could not be explai ned by these higher ordered personality dimensions when they were used to predict outcome variable s such as self esteem (Rice, Ashby, & Slaney, 2007) Perfectionism as a lower order personality factor especially may b e related to addiction because its related higher order factors, neuroticism and conscientiousness, are also traits conceptually and theoretically related to some of proposed addictive personality traits such as negative emotionality, impulsivity or disinh ibition ( Ibez, et al., 2008) Therefore, perfectionism compared to other lower ordered personality factors seems especially a good candidate that may relate to Internet addiction. Procrastination as one dimension of perfectionism It should be noted that procrastination ha s been proposed as one of the dimensions of perfectionism. In their attempt to develop a theoretically based scale to measure perfectionism, Johnson and Slaney (1996), include d items regarding procrastination because perfectionists usual ly experience procrastination. However, the ir were mixed and inconclusive thus the procrastination subscale was subsequently dropped. Hypothesis linking procrastination to p erfection ism infer s that procrastinating allows the individual to avoid less than perfect performance. Previous findings suggested that procrastination is positively related to the maladaptive aspects of
44 perfectionism but negatively associated with the ada ptive characteristics of perfectionism (Frost et al., 1990) Procrastination has been linked to Internet addiction. For example, in decreased impulse control together appeared to predict Internet addiction. Because procrastination is a factor that is closely related to the construct of perfectionism, it could be interesting to explore it as a lower order personality factor to Internet addiction as well. Because the main focus of this study is perfectionism, the relationship between procrastination and Internet addiction will only be examined explanatorily in the present study. Perfectionism and Substance Abuse Addiction Currently, there is essen tially only one published article s examining the relationship between perfectionism and Internet addiction. In addition there are only a few studies that have examined the link between perfectionism and substance abuse addiction. In an early attempt to f ind personality types of alcoholics, destructive drinking was found to occur among psychiatric patients with the obsessive perfectionist trait (Nerviano & Gross, 1983) In study examining the relationships between psychopathologies and different types of perfectionism, alcohol abuse was significantly and positively correlated with self oriented perfectionism and socially prescribed perfectionism However, it should be noted that its signif icant positive correlation with self oriented perfectionism was actually only demonstrated in men whereas the significant positive correlation with socially prescribe d perfectionism happened only among women. Self oriented perfectionism and drug abuse was also significant ly and positively related among men. O ther oriented perfectionism was significantly and positively related to drug abuse in general.
45 However, recent study about perfectionism and binge drinking among college s tudents, only self oriented perfectionism was found to be negative ly correlate d with binge drinking In perfectionism was also negatively associated with frequency o f drinking. These inconsistent findings could be due to the lack of differentiation between adaptive perfectionism and maladaptive perfectionism. In a study investi gati ng whether perfectionist college students drink alcohol to cope, it was found that adapt ive perfectionists had less likelihood of drinking to cope, and fewer alcohol related problems. On the other hand, maladaptive perfectionists appeared to have a significantly more elevated risk of drinking to cope but reported no more alcohol related prob lems than non perfectionists (Rice & Van Arsdale, 2010 ) This finding seems to confirm that different dimensions of perfectionism may relate to addiction differently and maladaptive perfectionism might especially addictive behaviors Perfectionism and Behavioral Addiction As for the link between perfectionism and behavioral addiction, there have been preliminary studies that focus on computer game addiction which is more similar to Internet add iction than other kinds of behavioral addiction In a study examining personality characteristics and computer game addiction among 471 college students in Beijing, China, Shi et al. (2007) used the Sixteen Personality Factor Questionnaire to explore which personality factors were significantly related to computer game addiction. The results indicated that perfectionism was significantly and negatively related to game addiction ( r = 0.21, p < 0.01). Another related construct, rule consciousness, was also significantly and negatively related to game addiction ( r = 0.20, p < 0.01). Other
46 personality factors that were also significantly related to game addiction were tension ( r = 0.21, p < 0.01), vigilance ( r = 0.20, p < 0.01), emotional stability ( r = 0. 19, p < 0.01), warmth ( r = 0.18, p < 0.01), dominance ( r = 0.13, p < 0.01), and apprehension ( r = 0.12, p < 0.05). Th ese finding s seem to be in line with the previous finding s on substance abuse addiction, which found that self oriented perfectionism was negatively associated with binge drinking (Flett et al., 2008) Although the effect sizes of these relationships were considered small ( J. Cohen, 1992), perfectionism and the related rule consciousness compared to other personality factors examined had relatively larger effect. Flett, Hewitt, Blankstein, and Dynin (1994) examined Type A personality a similar construct to perfectionism, and its relationship with game addiction. T heoretically Type A personality and perfectionism seem to be related constructs and various Type A behavior components were found to be significantly associate d with perfectionism dimensions. This experimental study examined the arousal of computer game playing among 24 undergraduate studen ts. The results indicated that subjects with Type A personality experienced significantly more arousal through increased hea r t rate when playing computer games than subjects with Type B personality. Griffiths and Dancaster (1995 ) suggested that Type A indi viduals might develop behavioral addiction more easily because they experience more arousal from playing computer games. Perfectionism and Internet Addiction among College Students There is only one recent study exploring the relationship between the rela tionship between perfectionism and Internet addiction among college students Lehmann and Konstam (2011) examined how perfectionism and problematic Internet use might contribut e to career indecision among 486 college educated adults between the ages of
47 25 and 30 years old. The results indicated that problematic Internet use was substantially correlated with maladaptive perfectionism ( r = .49 p < .0 0 1) but it was not significantly related to adaptive perfectionism. This finding confirmed that perfectionism is an important personality trait that may relate to Internet addiction and malad aptive perfectionism specifically seems a strong predictor for Internet addiction among college students. Current Study One of the merits of the Stress Response Dampening Mo del is that it links the relationship between stress and addictions to personality factors. With this more comprehensive view of the three domains, researchers might have a better chance to reveal the complicated development of addictive behaviors. A recen t study on college quoting the Stress Response Dampening Model (Rice & Van Arsdale, 2010) Focusing on the lower ordered personalit revealed that adaptive perfectionists had lower reported stress, lower rates of using drinking as the way to cope, and lower rates of alcohol related problems than maladaptive perfectionists, and non perf ectionists. Maladaptive perfectionists had highest reported stress and drinking to cope although they showed about the same level of alcohol related problems as non perfectionists. Based on the framework of the Stress Response Dampening Model the results would support that maladaptive perfectionists would be the most likely group to use alcohol to cope with stress compared to adaptive perfectionists and non perfectionists. This result also highlighted that the all three domains: personality factors, stress and addictive behaviors, interact with each other.
48 Although there has been some research on the psychological and personality correlates of Internet addiction during the last decade there has not been much research directly address ing the contribution of stress to Internet addiction development among college students (Li et al., 2009) Among the limited studies on stress coping and Internet addiction, the interaction between pre dispositional personality factors and str ess factors has yet to be explored. Therefore, the goal of the current study is to explore how perceived stress together with certain specific personality factors, such as perfectionism and procrastination or other relevant personality factors may contrib ute to Internet addiction among college students. Based on the literature review above, the research questions of the current study are : 1) What are the demographic characteristics and the prevalen ce rate of Internet addiction among college student s ? 2) Does perceived stress contribute to increased Internet addiction? 3 ) Which of the Big Fi ve personality dimensions are relate d to Internet addiction? 4 ) How do different dimensions of perfectionism associate with Internet addiction? 5 ) How do maladaptive pe rfectionism and perceived stress interact to contribute to the development of Internet addiction? For the above research questions, the hypotheses based on the literature reviewed are : Question 1: T he overall prevalence rate of Internet addiction among the college population could be over 10 % (Niemz et al., 2005) Compared to non Internet addicted college students, Internet addicted college students would be mostly male (Scherer, 1997) an d they would have had significantly more years of experience using Internet (Kubey et al., 2001; Lin & Tsai, 2002)
49 Q uestion 2: Perceived stress would be positively correlated with Internet addiction. La voie and Pychyl (2001) found that Internet procrastination was positively correlated with perceiving the Internet as a relief from stress ( r = .57, p < .0001). Because the researchers suggested that Internet procrastination could be a kind of Internet addi ction, it is expected that perceived stress would also be positively correlated with Internet addiction. Q uestion 3: Internet addiction would be negatively related to conscientiousness and positively relate d to extraversion and neuroticism T heorists have suggest ed that impulsivity or disinhibition ( e.g. sensation seeking), extraversion or positive emotionality, and neuroticism or negative emotionality can potentially predispose people to develop addiction (Ibez et al., 200 8) Question 4 : Internet addiction would be associated with maladaptive perfectionism but not adaptive perfectionism. As Lehmann & Konstam ( 2011 ) found problematic Internet use was significantly correlated with mala daptive perfectionism ( r = .49 p < 00 1) but it was not significantly re lated to adaptive perfectionism in their pilot study. Therefore, t he same pattern of relationships between different types of perfectionism and Internet addiction can be expected. Question 5 : P erfectionism would moderate the relationship b etween stress and Internet addiction. T he SRD model suggests that certain personality traits may (2010) study pointed out that maladaptive perfectionism seemed to be the key personality trait that moderated the paths from perceived stress to alcohol related
50 problems Therefore, it would be expected that maladaptive perfectionism may moderate the relationship between perceived stress and Internet addiction
51 CHAPTER 2 METHODS Pa rticipants This study focused on studying undergraduate college stu dents because they are the most susceptible group ( Young 2007 ) Two sources were used to recruit participants All participants were undergraduate students at the Unive rsity of Florida (UF) First, partic ipants were recruited from the UF psychology participant pool which is composed of mostly first or second year college students from various majors. Second participants were recruited from various classes by email reque sts sent to instructors. A total of 179 3 entries were recorded on the survey website One hundred and seventeen (6.5 %) of the 179 3 entries did not finish the survey meaning at least one of the measures were completely unanswered, and 188 entries (10.5 %) did not answer both of the two quality testing items correctly. Eight entries were recognized as duplicated because they had the exact same demographic information and the exact same IP address Two participant s were under 18 year old another is an audito r, and 12 others were graduate students Therefore, these 328 entries were excluded from the data analysis. Among the se remaining 14 65 participants, 0.1% were American Indian or Alaskan Native 9.4% were Asian, 7. 4 % were Black or African American, 15.3 % w ere Hispanic, Latino( a), and/ or of Spanish origin 0.3% were Native Hawaiian or Other Pacific Islander 61. 4 % were White, 4.4 % were Bi racial or Multi racial 1. 5 % were other race/ethnicity and 0. 2 % did not report their race/ethnicity According to UF und ergraduate student enrollment facts for Fall 2010 ( University of Florida, Office of
52 Institutional Planning and Research. 2011 ) there are 9.4% of Asian students, 10.0 % of Black /African American students, 16.8 % of Latino ( a) students, 0.7 % o f Native America n students, 59.5 % of White/Caucasian students, 2.7 % of not reported race and ethnicity, and 0.9 % with non resident alien status that could be of any above mentioned race and ethnicity categories Compared to the information above, the racial/ethnicity comp osition of the sample is roughly similar to the current UF undergraduate student populations although there were slightly fewer participants who were Black or African American but more Bi racial or Multi racial participants in the current sample In terms of gender, 66. 6 % of the p articipants were female and 33. 0 % were male. Two participants identified themselves as transgender ; two participants indicated their gender as other but did not specify; and two other participants declined to answer on this item. According to UF student enrollment fac ts for f all 2010 ( University of Florida, Office of Institutional Planning and Research. 2011 ) there are 55.1% of female students and 44.9 % of male undergraduate students at UF. Compared to the UF undergraduate student population, there were more female participants in this sample. There were 23. 3 % of the participants in their freshman year, 12. 2 % in their sophomore year, 34. 7 % in their junior year, and 29.4 % in their senior year ; five participants specified their acade mic classification as other and one participant did not specify the academic status According to UF student enrollment facts for fall 2010 ( University of Florida, Office of Institutional Planning and Research. 2011 ) there were 12.4% of freshmen, 20.3% o f sophomores, 29.7% of juniors, and 37.6 % of seniors. Compared to the UF undergraduate student population, there were more freshmen and juniors but fewer
53 sophomores and seniors in our sample. These statistics with comparable UF demographic data are present ed in Table 2 1. In addition, other demographic information of this sample without comparable UF data is described below. Regarding sexual orientation, 1.6% described their sexual orientation as bisexual, 93.7% as heterosexual, 2.0% as homosexual, 0.5% sa id they were unsure about their sexual orientation, 0.3% described their sexual orientation as other, 1.7% decline to answer their sexual orientation, and two participants did not answer this question. There were 29.7 % of the parti cipants lived on campus, 70 .3 % of them lived off campus and four participants did no t specify their residence The mean age of the sample was 20.71 years ( SD = 4.03), with the range from 18 to 56. Measures Demographic Questionnaire The participants were asked to complete a demogr aphic questionnaire at the end GPA, gender, sexual orientation, race/ethnicity, living situation, and Internet usage. A copy of the demographic questionnaire is located in Appendix A The Internet Addiction Scale (IAS) Internet addiction level was measure d by the Internet Addiction Scale (IAS, Nichols & Nicki, 2004) The IAS was developed by adapting seven criteria f or substance dependence on the DSM IV and two additional criteria including salience and mood modification suggested by Griffiths (1996 a ). The IAS contains 31 items in which response options are in a five point Likert scale ranging from 1 (never), 2 (rarel y), 3 (sometimes), 4 (frequently), to 5 (always). Hig h er scores represent a more serious degree of Internet addiction and the total score greater than the suggested cut off score
54 of 93 (3X31 items) would indicate possible Internet addiction. In the test no rm sample of 207 undergraduate students in the United States, factor analyses of IAS revealed a one factor model pertaining to negative consequences of excessive Internet use and demonstrated high internal consistency reliability ; coefficient al pha = .95. As for validity, the IAS also showed good content validity by using DSM IV and theoretically reviewed criteria. It also demonstrated good construct validity among the norming undergraduate college students because the theoretically related const ructs such as family loneliness, social loneliness, and boredom proneness were found to be significantly related to the IAS scores (Nichols & Nicki, 2004) A copy of the IAS is located in Appendix B. The Perceived Stress Scale (PSS) vel was measured by the Perceived Stress Scales (PSS, S. Cohen, Kamarck, & Mermelstein, 1983) The PSS contains 14 items in 5 point Likert scale format with response options from never (0) to very often (5). Higher sco res on the PSS represent more perceived stress internal consistency reliability for the initial two independent college samples were high retest r eliability with another college student sample ( r = .84) at two day and six week periods. The PSS showed good construct validity with its significant associations with negative life events and also demonstrated good criterion related validity with its sign ificant correlations with depressive and physical symptoms among the norm college student samples. With a sample of 2387 participants with ages over 18 in a phone interview study, principal component factor analysis revealed two potential factors that toge ther accounted for 41.6% of variance. However, the researchers concluded that the
55 distinction between the two factors is irrelevant for the purpose of measuring the perceived stress; therefore, a total score summing all 14 items was suggested to represent the construct in the analysis ( S. Cohen & Williamson, 1988) In addition, S. Cohen and Williamson suggested using the ten item version of P SS (PS S10) because it has slightly tighter factor structure and slightly better internal reliability while still providing an adequate measure of perceived st ress. Therefore, the total of PS S10 will be used in the analysis. A copy of the PSS is located in Appendix C. The Mini International Personality Item Pool (Mini IPIP) Participan sonality characteristics were assessed by the Mini International Personality Item Pool ( Mini IPIP, Donnellan, Oswald, Baird, & Lucas, 2006) The Mini IPIP is a 20 item short form of the 50 item Internation al Personality Item Pool Five Factor Model (IPIP FFM) measure (Goldberg, 1999) The Mini IPIP ha s four items per Big Five trait and similar coverage of each trait as other broad Big Five personality measures. Th e subscales of Mini IPIP are Intellect/Imagination ( openness ), Conscientiousness, Extraversion, Agreeableness, and Neuroticism. Respondents were asked to describe themselves in current state and relative to people with the same demographic background using the statement in each item. The response options for each item range from very inaccurate, moderately inaccurate, neither accurate nor inaccurate, moderately accurate, to very accurate. The scoring of each item is based on the five point Likert scale rang 20 and high score represents higher degree of the corresponding Big Five trait. The Mini IPIP was developed and validated across five studies and showed reasonable reliability and validity with its r educed length (Donnellan, Oswald, Baird, & Lucas, 2006) In the norm sample of 2663 freshman undergraduate students, the
56 I ntellect/Imagination to .77 for E xtraversion. Discriminant validity with this sample was also evident with smaller average absolute scale inter correlation ( r = .13 and r = .18 ) for the Mini IPIP compared to the original IPIP FFM. In a sample of 329 underg raduate students, the Mini IPIP also showed good reliability coefficients ranging from .70 for Intellect/Imagination to .82 for E xtraversion. The Mini IPIP also demonstrated reasonable content and convergent validity with similar and high correlations with other Big Five personality scales such as IPIP FFM and Ten Item Personality Inventory (TIPI). In another sample of 300 undergraduate students, the Mini IPIP once again showed reasonable reliability coefficients from .70 for Intellect/Imagination to .82 fo r extraversion. In addition, it demonstrated good convergent validity with its similar and high correlation with IPIP FFM and the Big Five Inventory (BFI); it also showed good criterion related validity with its similar correlation patterns compared to oth er Big Five measures using the three criteria of self esteem, behavioral approach, and behavioral avoidance. In the fourth test validation study with 216 undergraduate students, the Mini IPIP showed acceptable test retest reliability of a three week period on subscales that ranged from .62 for A greeableness to .87 for E xtraversion. In addition, it also had similar correlation patterns as with psychopathology related variables like IPIP FFM, implying good criterion related validity for criteria such as anxie ty, depression, hostility/aggression, and psychological entitlement. In the last test validation study with 148 undergraduate students, the Mini IPIP showed reasonable test retest reliability with a six to nine month period for subscales that had coefficie nts ranging from .68 for agreeableness to .86 for extraversion. It also showed similar correlations with criteria
57 such as positive affect, negative affect, and life satisfaction as IPIP FFM did, which indicated good criterion related validity for these var iables. A copy of the Mini IPIP is located in Appendix D The Almost Perfect Scale Revised (APS R) Participa measure by the Almos t Perfect Scale Revised (APS R, Slaney et al., 2001) It contains 23 Likert scale items with response option s that range from strongly disagree (1) to strongly agree (7). Different dimensions of perfectionism are indicated with its three subscales: 1) St andards (7 items), sonal performance and achievement, 2) Discrepancy (12 items), tapping the negative/maladaptive aspect of perfectionism and (Slaney et al., 2002) need for orderline ss, neatness, and organization. ranged from .82 to .92 for the norm sample of 809 undergraduate students, indicatin g good internal consistency reliability. In addition, the significant correlations of APS R validity; APS subsca les also demonstrated good criterion related validity in terms of adjustment and well being indexes such as achievement, self esteem, depression, and anxiety. Whereas the Discrepancy subscale of APS R seems to capture a maladaptive or negative aspect of pe rfectionism, Standards and Order subscales of APS R seem to measure more positive and adaptive aspects of perfectionism (Slaney et al., 2001) However, based on Stoeber and Order subscale m ay be discarded when conceptualizing or differentiating between adaptive perfectionism and
58 maladaptive perfectionism. Therefore, only the subscales, Standards and Discrepancy would be used in the analyses to distinguish adaptive perfectionism and maladapti ve perfectionism. A copy of the APS R is located in Appendix E The Tuckman Procrastination Scale (TPS) endency was measured by the Tuckman Procrastination Scale ( TPS, Tuckman, 1991) This self report scale contains 16 items to point L ikert scale without the option of a neutral point The possible score range from 16 to 64 and high scores indicate a higher degree of procrastination. The Cronbach alpha reliability co efficient of .86 was reported in the in i tial scale development study on 183 college students in the teach education program Its construct validity was demonstrated by a correlation of .54 between scores on the scale and scores on a voluntary task representing motivational tendency of self reg ulation Its concurrent validity on college students was shown through a correlation of .47 between the scores on the scare and a self efficacy scale (Tuckman, 1991) A copy of the TPS is located in Appendix F Th e Impulsive Sensation Seeking Scale (ImpSS) Impulsive Sensation See king Scale (ImpSS, Zuckerman et al. 1993) ImpSS is a 19 item self sivity and sensation s eeking. The ImpSS is actually a subscale of the Zuckerman Kuhlman Personality Questionnaire (ZKPQ; Zuckerman et al., 1993). Factor analysis revealed that the two factors, impulsivity and sensation seeking. Whereas the impulsivity subs cale measures the
59 tendency to act impulsively without thinking or planning, the sensation seeking subscale situations and friends, and need for change and novelty. The adv antage of this instrument is that it has no mention of specific activities like drinking, drug use, sex, or risky sports so that it can be applied to most people. Based on a sample of 2969 college lphas for the sensation seeking subscale were .77 among females, and .74 among males; the reliability of the ImpSS is located in Appendix G Quality Testing Items T wo quality testing items were respo nses are valid. The first quality testing item was worded as It was located in the IAS as item 23. The second q uality testing item was worded question; R as item 18. If participants fail ed to answer both of the quality item s correctly, their responses were excluded from my analyses. Procedure Purposive sampling was conducted to recruit UF students to take the survey. An online survey development program, Qualt r ics, was used to develop the online study. For participants from various courses, an IRB approved invitatio n letter was sent out to professors and graduate student instructors. The pro fessors and instructors were asked to forward the email in the class listservs and also make an announcement in class about participating in the study. The professors and instruct ors individually decided
60 whether to provide stude nts extra credit and an alternative extra credit opportunity or not Participating students then took the online survey by clicking the link in the email. P articipants from the psychology participant pool to ok the survey by clicking the link in the study descrip tion posted on the SONA system. The first p age of the online survey was the IRB proved informed consent. At the end of that page, there is a description urvey bu tton below, you give your consent to participa te in this study on your will consent was recorded as studen ts click that button which led them to the actual survey. All participants filled out the demographic information in the end of the sur vey. However, p articipants might have take n the measures in this study in different orders because Qualtrics randomize d the sequence of the measures so that the results were not affected by a specific sequence of the measures. After participants completed the survey, they were redirected to a page that showed the link of another survey that recorded their course information (for participants from the courses) so that students would get participation credits or extra credit provided by the ir professors and i nstructors. Because this survey was separated from the study su rvey, the information they provided w as not linked to the answers they provide d in the actual survey
61 Table 2 1. Participant demographics compared to UF student population Fall 2010. Variabl e UF # UF % Sample # Sample % Gender Female 17666 5 5.1 976 66.6 Male 14398 4 4.9 483 33.0 Race/Ethnicity American Indian or Alaskan Native 215 7 2 .1 Asian 2982 9.4 138 9.4 Black or African American 3195 10.0 108 7.4 Hispanic, Latino(a), a nd/or of Spanish Origin 5347 16.8 224 15.3 White 18939 59.5 900 61.4 Other 1155 3.6 89 6.1 Academic Status Freshman 3964 12.4 342 23.3 Sophomore 6516 20.3 178 12.2 Junior 9520 29.7 509 34.7 Senior 12064 37.6 430 29.4
62 CHAPTER 3 RESULTS P reliminary Analyses A total of 1793 survey entries were recorded but the preliminary analyses were run on 1465 participants after excluding duplicate entries, participants who did not answer the quality testi ng items correctly and complete the survey succ essful ly participants who were under 18, and participants who were auditors or gradua te students Normality Assumption The normality assumption of the variables was checked. According to Field (2000 p. 72 ), large sample s with 200 participants or more us ually result in smaller standard errors and significant values arise from even s mall deviations from normality. Therefore, it is more important to check the shape of distribution and the actual skewness and kurtosis statistics than judging based on the sig nificance level Based on the skewness and kurtosis Z scores (over 3.29, p <. 001) I ntellect/ Imagination, Conscientiousness Agreeableness APS R Standards ( APS R S ) and Sensation Seeking (SS) appeared somewhat negatively skewed ; Internet addiction ( IAS ) perceived stress (PSS10), APS R D iscrepancy ( APS R D ), and Impulsivity ( Imp ) appeared somewhat positively skewed A ll of the variables Kolmogorov Smirnov tests for normality were significant ( p < .05) but t he normal Q Q plots and detrended normal Q Q p l ots were acceptable. J udging from the histograms only Intellect/ Imagination, Conscientiousness Agreeableness APS R S IAS, APS R D and Imp showed some noticeable non normality in distribution but the shape s of PSS10 and SS appeared roughly normal
63 T he re were some outliers detected for IAS, PSS, Intellect/Imagination Conscientiousness Agreeableness APS R Standards and TPS. Ho wever, as Table 3 1 indicates, there were not much difference s between all v Mean s and 5% Trimmed Mean s (the mean s af ter deleting the 5% outliers), and the differences were all well below one standard deviatio n. Because the outliers did not seem to alter the means much they were all kept in the analyses. Overall, based on the various criteria discussed above, PSS, Mini IPIP Extra version, Neuroticism TPS, and SS seemed roughly normally distributed, but Intellect/Imagination Conscientiousness Agreeableness and APS R Standards were negatively skewed ; and IAS, APS R D and Imp were positively skewed. To address the non normality of Intellect/Imagination Conscientiousness Agreeableness APS R S IAS, APS R D and Imp, I transformed these variables with square root transformation and necessary reflect procedures suggested by Tabachnick and Fidell (2006 p.92 ) After tra nsformation, only the transformed APS R S (t APS R S) still appeared somewhat negatively skewed although it was much improved from the original APS R S. Logarithm and inverse transformation s were also tested on APS R S but they did not derive better skewne ss and kurtosis numbers The most deviant skewness value of the variables in analysis after transformation is .32 ( t APS R S ) and the most deviant kurtosis value (t Imp) is 1.25. Table 3 1 shows the skewness and kurtosis values of all the variables inclu ding the transformed variables. These actual skewness and kurtosis statistics seem acceptable for this large sample size. Tabachnick and Fidell (p. 80) indicated that deviation of skewness and kurtosis in large sample s would not make substantial difference s in analysis as long as the absolute
64 skewness and kurtosis values are not far away from zero. Kline (2005) also indicated that only absolute values of kurtosis higher than 10 would suggest a problem for univariate normality. T he transformed variables all had highly significant positive correlation s with the ir corresponding original variable s as indicated in Table 3 2 Reliability of Variables in the Analyses satisfactory and ranged from 72 to .95 f or this sample. all t he scales are also shown in Table 3 1 Prevalence of Internet Addiction among College Students The prevalence rate and demographic characteristics of Internet addiction were al so examined. Using the cutoff score of 93 suggested (Nichols & Nicki, 2004) the prevalence rate of Internet addiction in this sample is 10.4 %. Regression Assumption Related demographic variables would be controlle d in the main regression analyse s. According to previous studies, demographic variables including gender, age, and years of Internet use would be related to Internet addiction. Therefore, the relationships between t IAS and these demographic variables were examined. Regarding gender, due to the small sample sizes of the categories for transgender, other, and decline to answer ( two participants for each category), these six participants would not be included in the analyses because statistical analy ses with such small sample sizes may not be reliable. An independent samples t test was conducted to compare the t IAS scores for males and females among the remaining 1459 participants. There was no significant difference in t IAS scores for females ( M = 8.16, SD = 1.17) and males [ M = 8.16, SD = 1.18; t (1457) = .04, p = .97]. The magnitude of
65 the differences in the means was very small (eta squared < .001 ). A nother bivariate correlation analysis was run to explore how age and years of Internet use correlated with t IAS. It turned out that t IAS was significantly and negatively related to age ( r = .15 p < 0005 ) but not to years of Internet use ( r = 05 p > .05 ). Therefore, only age would be controlled in the regression analyses. To examine multivariate outlie rs a multiple regression model was run by entering age and all the main variables including PPS10, t Intellect/Imagination, t Conscientiousness, Extraversion, t Agreeableness, Neuroticism, APS R S, APS R D, TPS, Imp, and SS as independent variables and t IAS as the dependent variable. R egression diagnostics revealed no significant concerns regarding multicollinearity because none of the Tolerance values were below .10. In addition, the bivariate correlations between all entered demographic variables were a ll lower than .70 (Tabachnick & Fidell, 2006, p. 90). Examination of the normal probability plot of the standardized residuals did not show signs of violation for normality. Examination of the scatter plot of the standardized residuals also did not show si gns of violation for linearity or homoscedasticity. In terms of standardized residual values, there was only four none of the values exceeded 1. In terms of Mahalanobi s distance values, there were 26 cases whose values exceeded the critical value for 1 3 independent variables 32.91 ( df = 12 p < .001); these multivaria te outliers were deleted and only the remaining 1429 cases were included in the hierarchical multiple r egression analyses Stress and Internet Addiction A bivariate correlation analysis was conducted to test the hypothesis whether perceived stress (PSS10) in the past month would be associated with Internet addiction
66 (t IAS) I chose the two tailed test of s ignificance for this bivariate correlation because a directional hypothesis could not be clearly supported by previous literature The result indicated that PSS10 was positively correlated with t IAS ( r = 34 p < .0005 ). The effect size is considered medi um ( J. Cohen, 1992). Big Five Personality Factors and Internet Addiction A hierarchical multiple regression analysis was run to examine how the Big F ive personality factors relate to Internet addiction. Age was entered in the first block and the Mini IPIP subscales (t Intellect/Imagination, t Conscientiousness, Extraversion, t A g reeableness, and Neuroticism) were entered in the second block. T IAS was the dependent variable. This overall regression model associating Internet addiction with the Big F ive per sonality factors by age was significant ( R 2 = 15 F [ 6 141 8 ] = 42 26 p < .0 0 05 ). The first block result showed that age account ed for significant but small variation in t IAS, R 2 = 01 F ( 1 142 3 ) = 17 34 p < .0 0 05 The R 2 change of the added Big F ive personality factors in the second block was significant ( R 2 = .14 p < 0 .0005 ) a lthough the effect size of the Big F i ve factors was considered medium according to J. (1992) standard on R 2 Specifically, there was a significant positive effect of N euroticism on t IAS ( = 19 t = 7 50 p < .0005 ) and a significant negative effect of t Conscientiousness on t IAS ( = 27 t = 10 74 p < .0005 ) ; and there were smaller negative effects of t Extraversion ( = .09 t = 3.65 p < .0005 ) and t Intellect/Imagination ( = .07, t = 2. 57 p < .05 ) on t IAS; but there were no significant effect s of t Agreeableness ( = .04 t = 1.6 1 p = 11 on t IAS in the second block of the equation. In summary, high neuroticism and lack of conscientiousness and, to some degree, lower extraversion and openness wer e associated with Internet addiction when c ontrolling age
67 Perfectionism and Internet Addiction H ierarchical multiple regression was used to examine the effect of the APS R subscales, Standards and Discrepancy and their interaction on Internet addiction F entered t APS R S and t APS R D were entered in the third block and their interaction term was entered in the fourth block based on the previous model. This overall regression mode l a ssociating perfectionism subscales with Internet addiction by controlling age and the Big F ive personality factors was significant ( R 2 = 22 F [ 9 1415 ] = 45 22 p < .0005 ). The first and second blocks with age and Big Five personality factors produced the same results as described in the section above. The R 2 change of the third block with centered t APS R S and t APS R D was signi ficant, F (2, 1416 ) = 60.71 p < 0 0005 Standards and Discrepancy together accounted for an additional 7 % of the variatio n in t IAS a lthough the effect size of the APS R subscales was considered small to medium ( J. Cohen, 1992) Specifically, there was a significant positive effect of centered t APS R D on t IAS ( = 25 t = 9.49 p < .0005 ) and there was a significant nega tive effect of centered t APS R S on t IAS ( = 14 t = 5.63 p < .0005 ) in the third block of the equation. Therefore, regardin g the main effect, Discrepancy was positively related to Internet addiction and Standards was negatively associated to Inter net addiction when controlling age and the Big Five personality factors. In addition, the interaction term of centered t APS R S multiplied by centered t APS R R 2 = .0 05 F (1, 1415 ) = 8.49 p < 0 .005 although the effect size is considered very small. Specifically, this interaction term had a significant negative effect on t IAS ( = 07 t = 2.91, p < .005) Tab le 3 3 shows the complete results in the final model. The interaction effect indicated that Discr epancy
68 moderated the negative relationship between Standards and Internet addiction. To illustrate the relationship clearly, I explored the significant interaction effect with the MODPROBE SPSS macro developed by Hayes and Matthes (2009). This macro helped generate the scores of the focal predictor (Standards) and the corresponding t IAS scores by controlling age and the Big Five personality factors as covariates when the moderator (Discrepancy) was at low ( 1 SD below its mean), average (mean), and high (+ 1 SD above its mean) values At low level of Discrepancy, the effect of Standards on Internet addiction was not significant ( B = .07, p > .05), but it was significant at average and high levels of Discrepancy ( B = .16 and .24, p < .05). This interactio n effect was plotted based on the values generated by the MODPROBE macro. Figure 3 1 displays this effect. When Discrepancy was higher the negative association between Standards and Internet addiction also became stronger When Standards was low, t he diff erence between high Discrepancy and low Discrepancy IAS scores ( 1.17 ) was almost equal to one full standard deviation (1.18 ), which suggested a large effect size difference. This confirmed that the m oderating effect of Discrepancy on the re lationship between Standards and Internet addiction was valid although the effect was small Moderating effect of Perfectionism on the Relationship between Perceived Stress and Internet Addiction A hierarch ical multiple regression analysi s was conducted to test wheth er perfectionism (t APS R S and t APS R D) would moderate the relationship between perceived stress (PPS10) an d Internet addiction (t IAS) To deal with the collinearity problem of the interaction product term in the regression, every entered in dependent variable was centered from their mean (Aiken & West, 1991) I n this hierarchical multiple regression analysis testing the m oderating effect of perfectionism centered t
69 PSS 10 centered t APS R S, and centered t APS R D along with age were entered in the first block while their two way centered product term s ( PSS10 X t APS R S, PSS10 X t APS R D, and t APS R S X t APS R D) were entered in the second block and their three way product term ( PSS10 X t APS R S X t APS R D) was entered in the third bloc k. The t IAS served as the dependent variable Results indicated a lack of si gnificant m oderating effect s of t APS R S and t APS R D on the relat ionship between PSS 10 and t IAS The first block of results showed that the regression model with centered t P SS t APS R D, and t APS R D along wi th age as was significant, F ( 4 1420 ) = 91.71 p < .0005 A combination of centered PSS 10, centered t APS R D, and t APS R D and age accounted for 20.5 % of the variance of t IAS. The second block results showed that ad ding the addition al products of centered terms including PSS10 X t APS R S PSS10 X t APS R D and t APS R S and t APS R D altogether was significant However, t here was only additional .005 of effect size change in R 2 in th e se cond block, F (3 1417 ) = 3. 19 p < 05 Specifically, the products of centered terms, PSS10 X t APS R S and PSS10 X t APS R D were not significant but the product of centered t APS R S and t APS R D was significant ( = .08, t = 2.81, p < .01 ) The results indicated that Standard s and Discrepancy did not moderate the relationship between perceived stress and Internet addict ion; however, Discrepancy did show a m oderating effect on the relationship between Standards and Internet addiction that is similar to the one presented in the previous analysis The third block results showed that the additional three way interaction term of PSS10 X t APS R S X t APS R D was not significant. There was no change in R 2 F (1, 1416 ) = .07 p > 05 This result indicated that Standards Discrepancy and perceived stress did not interact
70 altogether in the relationship between perceived stress and Internet addiction. Table 3 4 displays the complete results in the final model. The significant interaction effect of centered t APS R S and t APS R D on t I AS was also further explored with the MODPROBE SPSS macro by Hayes and Matthes (2009). By controlling the covariates including age, the centered PSS10, APS R S, APSR D, the two way interaction centered terms, PSS X APS R S and PSS X APS R D, and the three way interaction centered term PSS X APS R S X APS R D, the MODPROBE macro generated the scores of the focal predictor (Standards) and the corresponding t IAS scores when the moderator (Discrepancy) was at low ( 1 SD below its mean), average (mean), and hig h (+ 1 SD above its mean) values At low average and high level of Discrepancy, the effect s of Standards on t IAS were all significant ( B = 12, p < .05; B = .21 p < .0005; B = .31, p < .0005 respectively ). F igure 3 2 displays this effect. When Discre pancy was higher, the negative association Standards between Standards and Internet addiction also became stronger. When Standards was low, t he difference between high Discrepancy and low t IAS scores ( 1. 21 ) was more than one full standard deviation (1.18 ), which suggested a large effect size difference. This once again confirmed that the moderating effect of Discrepancy on the relationship between Standards and Internet addiction was valid. Ex ploratory Analysis Other personality f actors such as procrastination ( TPS ) sensat ion seeking ( SS ), and impulsivity (t Imp ) along with the Big Five personality factors (t Intellect/Imagination t Conscientiousness, Extraversion, t Agreeableness, and Neuroticism) were also exa mined in the explo ratory analyse s. First the b ivariate correlation analyses were conducted to examine the relationships between t IAS and these personality variables
71 All personality factors tested showed significant relat ionship with Internet addition. However, except TPS APS R D, t Imp, and t Conscientiousness, all the other IAS exhibited small effect sizes. Among the variables with smaller effect sizes, neuroticism and sensation seeking had positively correlati ons whereas Intel lect/Imagination (openness), Extraversion, t Agreeableness, and APS R S had negative correlations with t IAS. Conscientiousness and t IAS were negatively correlated and t Imp and t IAS were positively related; their effect sizes are considered as medium ac (1992) standards for r. Especially, TPS was significantly related to t IAS ( r = .48 p < .0005 ). T here was also a large effect size in terms of the relationship between t APS R D and t IAS ( r = .36, p < .0005) The r esults imply that pe rfectionism related constructs, specifically maladaptive perfectionism and procrastination, seem to serve as better predictors for Internet addiction than other personality factors. The correlations between t IAS and all the personality factors are present ed in Table 3 5. Second, in addition to testing the m oderating effect of perfectionism, all other personality factors included in this study were also tested for their m oderating effect s on the relationship between perceived stress and Internet addiction. Along with the demographic variable, age, e ach personality factor was centered from its mean (Aiken & West, 1991) and entered with centered PSS and their product terms in a hierarchical multiple regression model The t IAS served as the dependent variable. Among all the personality variables, procras tination did not seem to have a m oderating effect as expected; only neuroticism appeared to moderate the relationship between perceived stress and Internet addiction. Specifically, in the hierarchical multiple r egression
72 analysis examining the m oderating effect of neuroticism The first block of results showed that the regression model with centered t PSS and Neuroticism along age as independent variables was significant, F ( 3, 142 1) = 68.71 p < .0005. A combina tion of centered t PSS and Neuroticism and demographic factors accounted for 12.7 % of the variance of t IAS. The second block results showed that the additional interaction term of centered t PSS and Neuroticism was significant. There was only additional 006 change in R 2 F (1, 142 0 ) = 9.47 p < 0 05 This effect size of the m oderating effect of neuroticism was considered very small according to J. (1992) standard on R 2 The significant interaction effect of centered perceived stress and neurotici sm on t IAS was also further explored with the MODPROBE SPSS macro by Hayes and Matthes (2009). By controlli ng the covariates including age the MODPROBE macro generated the scores of the focal predictor ( PSS10 ) and the corresponding t IAS scores when the moderator ( Neuroticism ) was at low ( 1 SD below its mean), average (mean), and high (+ 1 SD above its mean) values. At low, average and high level of Neuroticism the effects of stress on t IAS were all significant ( B = .07, .06, and .05 respectively p < 0005). Figure 3 3 displays this effect. When Neuroticism was higher, the negative association Standards between Standards and Internet addiction also became weaker However, w hen perceived stress was low, t he difference between high Neuroticism and low Neu roticism IAS scores ( 0.55 ) was much less than the standard deviation of t IAS (1.18 ), which indicated a small effect size difference. This result suggests that the very small significant R 2 change (.006) of the m oderating effect found in th e regression might have result ed from the excessive statistical power due to the
73 very large sample size rather than the actual m oderating effect of Neuroticism on the relationship between perceived stress and Internet addiction.
74 Table 3 1 Mean, 5% t rimm ed m ean, and s t andard d eviation, s kewness, k urtosis and reliability of all v ariables Variable Mean 5% t rimmed m ean St andard d eviation Skew ness Kurtosis C c oefficient IAS 67.95 67.41 19.44 .37 .34 .95 t IAS 8.16 8.15 1.18 .06 .59 PSS10 18.58 18.48 6.50 .21 .07 .89 Mini IPIP Intellect/Imagination 14.97 15.08 3.03 .49 .01 .73 t Intellect/Imagination 2.75 2.74 .65 .21 .27 Conscientiousness 14.55 14 .65 3.34 .41 .43 .78 t Conscientiousness 2.68 2.67 .69 .20 .51 Extraversion 12.82 12.87 3.82 .18 .71 .83 Agreeableness 15.88 16.04 2.86 .69 .53 .74 t Agreeableness 2.96 2.96 .65 .06 .41 Neuroticism 10.99 10.95 3.40 .16 .37 .72 APS R APS R S 42.75 43.25 5.52 1.24 1.88 .87 t APS R S 4.34 4.38 1.01 .32 .40 APS R D 44.30 43.95 15.57 .35 .50 .94 t APS R D 6.55 6.56 1.19 .05 .50 ImpSS Imp 1.86 1.70 1.92 .96 .03 .75 t Imp 1.07 1.04 0.85 .01 1.24 SS 6.62 6.66 3.07 .22 .72 .78 TPS 36.74 36.65 8.82 .16 .09 .93 Note : Standard error of skewness for all variables was .06 and standard error of kurtosis for all variables was .13
75 Table 3 2 Correlations between the transformed variables and the corresponding original var iables Variable p air Pearson c orrelation Significance (2 tailed) t IAS and IAS 1.00 .00 t Intellect/Imagination and Intellect/Imagination .98 .00 t Conscientiousness and Conscientiousness .99 .00 t Agreeableness and Agreeableness .9 8 .00 t APS R S and APS R S .9 7 .00 t APS R D and APS R D .9 9 .00 t Imp and Imp .95 .00
76 Table 3 3. Final model of the hierarchical regression analysis using age, the Big Five personality factors, perfectionism variables in predicting Internet addiction. Variable B S td. e rr or of B Beta t Significance Age 04 .0 1 10 4 22 00 t Intellect/Imagination 10 .0 4 .05 2.19 .0 3 t Conscientiousness .30 .04 .18 7.11 .00 Extraversion .02 .01 .05 2.11 .04 t Agreeableness .01 .05 .01 .18 .86 Neuroticism .04 .01 .10 3.91 .00 Centered t APS R S .16 .03 .14 5.42 .00 Centered t APS R D .27 .03 .27 9.92 .00 Centered t APS R S X Centered t APS R D .07 .02 .07 2.91 .004 Table 3 4 Final model of the hierarchical regression analysis using age, perceived st ress perfectionism variables in predicting Internet addiction. Variable B S td. e rr or of B Beta t Significance Age .04 .01 .10 4. 11 .00 Centered PSS10 .04 .01 .20 6.87 .00 Centered t APS R S .21 .03 .19 7.07 .00 Centered t APS R D .25 .03 .25 8. 78 .00 Centered PSS10 X Centered t APS R S .004 .01 .02 .68 .50 Centered PSS10 X Centered t APS R D .004 .003 .03 1.24 .22 Centered t APS R S X Centered t APS R D .08 .03 .08 2.78 .0 1 Centered PSS10 X Centered t APS R S X Centered t APS R D .001 .003 .007 .26 .80
77 Table 3 5 Correlations between Internet addiction and per sonality variables Variables 1 2 3 4 5 6 7 8 9 10 11 1. t IAS -.08** .29** .14** .08** .23** .22** .36** .10** .30** .48** 2. t Intellect/Imagination -.07** .12 ** .21** .09** .06* .07** .18** .07* .02 3. t Conscientiousness -.03 .09** .09** .30** .23** .17** .37** .51** 4. Extraversion -.23** .10** .14** .17** .34** .17** .16** 5. t Agreeableness -.04 .21** .14** .01 .12** .10** 6. Neuroticism -.01 .39** .07**. .01 .20** 7. t APS R S -.09** .07** .24** .36** 8. t APS R D -.03 .15** .38** 9. SS -.51** .13** 10. t Imp -.34** 11. TPS -Note. ** Correlation is signifi cant at the 0.01 level (2 tailed). Correl ation is significant at the 0.05 level (2 tailed).
78 Figure 3 1. Moderating effect of Discrepancy ( t APS R D ) on the r elation ship between Standards ( t APS R S ) and Internet a ddiction ( t IAS ) controlling age, the Big Five personality variables (t Intellect/Imagination, t Conscientiousness, Extraversion, t Agreeableness, and Neuroticism)
79 Figure 3 2 Moderating effect of Discrepancy ( t APS R D ) o n the r elation ship between Standards ( t APS R S ) and Internet a ddiction ( t IAS ) controlling age, perceived stress (PSS10) PSS X t APS R D, PSS X t APS R D, and PSS X t APS R S X t APS R D
80 Figure 3 3 Moderating effect of Neuroticism on the r elation sh ip between perceived stress (PSS10 ) and Internet a ddiction ( t IAS )
81 CHAPTER 4 DISCUSSION Specific findings from this study are further discussed in the context of the existing literature below. Especially, the stress diathesis perspective and the Stress Response Dampening Model are used to explain findings regarding to the interaction of stress and personality factors. Prevalence and Demographic Variables T he associations between Internet addiction and demographic factors in this sample showed some inter esting results. First, this study found a higher prevalence rate of Internet addiction among college students. The possible reason could be that Internet is more accessible nowadays so that this generation of college students showed a much higher Internet addiction prevalence rate, 10.4 %, compared to the only less than 1% prevalence rate found using the same Internet Addiction Scale (Nichols & Nicki, 2004) This finding of high prevalence rate is closer to the 18% In ternet addiction prevalence rate found by Niemz, Griffiths, & Banyard (2005). Gender did not appear to significantly relate to Internet addiction for this sample. This could be due to the fact that there were more female participants in this sample than the previous studies. Chou et al (2005) pointed out that the studies that showed male s more vulnerable to Internet addiction usually had more ma le participants in the sample. This r (2005) review that online studi es with a diverse population usually revealed no gender differences. Age was negatively related to the degree of Internet addiction in the bivariate correlation analyse s This result seems to be different from the p re vious cross sectional study conducted by Bricolo et al. (2007) that found participants who were in their
82 adulthood used Internet more than the participants in their adolescence My study result suggests that younger college students may experience more Internet addiction problem than the o lder colle ge students. This finding fits the common thought that younger individuals might have less self control or mature personality to curb Internet use. It could also be due to the fact that young college students may have more time or more exposure to th e new functions of the Internet and therefore they become more addicted to the Internet. However, it should be noted that the relationship between age and Internet addiction had relatively small effect size. So readers should be careful about generalizing these results to other college students Surprisingly, years of Internet use was not related to Internet addiction. Pre vious studies suggested that Internet addiction is more prevalent among people with more years of Internet use (Kubey et al., 2001; Lin & Tsai, 2002). This could also be due to that Internet is more prevalent nowadays so that it eliminates the effect of difference of Internet use experience Compared to ten years ago, Internet a ccess and its functions are more closely intertwined with our da ily life nowadays Therefore, ye using Internet may not matter anymore because most participants in this sample probably started around the same early age. years of Internet use because Internet is so much accessible for all age groups nowadays. In the study conducted by Kubey and his colleagues limited Internet access might have caused the lower reported incidence of Internet addiction for participants with fewer years of Internet use Perceived Stress Th e bivariate correlation analysis revealed that stress was positively related to Internet addiction and the effect size was quite respectable. Although the association is
83 correlational in nature, previous research suggested that stress causes Internet addic tion rather than the other way around because frequency of Internet use was two to four times more when participants experienced stress from work (Whang, Lee, & Chang, 2003) and various stressors seemed to contribute to the incident of Internet addiction ( Li, Wang, & Wang, 2009). Other studies also suggested that Internet dependent people may use the Internet to release stress (Davis, Flett, & Besser, 2002a; Davis, Flett, & Besser, 2002b; Ferrari, Johnson, & McCown, 1995; McCown & Johnson, 1991) Some of th e shortcomings of these previous studies were that stress was not measured by standardized instruments and that number of stressors or stressful events was used to represent perceived stressed. This study used the Perceived Stress Scale to avoid the above issues and the results provided a more quantifiable way to explain use or Internet addiction. The Big Five Personality Factors Regarding the relationships between the Big F ive personality factors and Internet addiction, the hierarchical multiple regression analysis revealed that these five higher order personality traits together along with age formed a significant model to predict Internet addiction. Specifically consci entiousness actually showed a significant negative association with Internet addiction. This direct association between conscientiousness and Internet addiction has not been reported although a conscientiousness related construct, sensation seeking, showed inconsistent relationship with Internet addiction (Chou et al., 2005) This result definitely calls for more studies about the relationship between conscientiousness on Internet addiction. This finding actually might no t be so surprising consider ing that impulsivity or dis inhibition ( e.g., sensation seeking), which is
84 conceptually opposite of conscientiousness, is one of the hypothesi zed addictive personality traits like neuroticism and extraversion (Ibez, Ruiperez, V illa, Moya, & Ortet, 2008) Among the other Big F ive personality factors, neuroticism was positively related to relationship between neuroticism and Internet addiction (Ami chai Hamburger & Ben artzi, 2003; Hamburger & Ben Artzi, 2000; Wolfradt & Doll, 2001). Whereas the previous studies also found significant but inconsistent relationships between extraversion and Internet addiction, this study revealed a negative significan t relationship between extraversion and Internet addiction. This support s shy individuals exhibited more Internet addiction in general. This result also fits to would prefer online social interaction which would further lead to Internet addiction. Additionally, lower level of openness was also found to predict Internet add iction although the effect was small and the significance may be due to the large sample siz e There were no previous findings relating Openness to Internet addiction. One possible explanation of this finding could be that less open minded and more defiant individuals may find some comfort on the Internet that they could not find in their daily l ife and therefore they become more de pendent staying on the Internet. Perfectionism The results also showed that m aladaptive perfectionism in term of discrepancy had a significant positive relationship with Internet addiction whereas perfectionism regardi ng high standards had a significant negative relationship with Internet addiction This result partially confirms the only previous study about perfectionism and Internet
85 addiction in which maladaptive perfectionism was positively related to problematic In ternet use but there was no significant relationship between adaptive perfectionism and problematic Internet use (Lehmann & Konstam, 2011). The different findings could be due to different measures used. However, the current finding g oes along with previou s theories and finding regarding the dichotomous structure of perfectionism which linked maladaptive perfectionism to many negative psychological indicators and adaptive perfectionism to positive psychological factors (Aldea & Rice, 2006; Dunkley, Zuroff, & Blankstein, 2003; Grzegorek, Slaney, Franze, & Rice, 2004; Mobley, Slaney, & Rice, 2005; Slaney, Pincus, Uliaszek, & Wang, 2006) The results also suggest that perfectionism may be a better choice among the lower personality factor s of predict ing Interne t addiction because perfectionism has been found to significantly correlate with ne uroticism and consc ientiousness (Enns & Cox, 2002) which are two main hypothesized addictive personality components theoretic ally ( Ibez et al., 2008). It makes sense that perfectionism can serve as the predictor for Internet addiction than the B ig Five personality factors. Th e fact that maladaptive perfectionism, neuroticism, and conscientiousness were all found to significantly and negatively associate with Internet addic tion in the current study implies that maladaptive perfectionis m specifically has the potential to serve as a single personality index to detect people with Internet addiction. The bivariate correlation between maladaptive perfectionism and Internet suppor t this argument bec ause maladaptive perfectionism comp ared to adaptive perfectionism, conscientiousness, and neuroticism showed a large r effect size in terms of its relationship with Internet addiction.
86 Regarding the analyses examining the m oderating effe ct of maladaptive perfectionism on the relationship between perceived stress and Internet addiction the result showed that neither Discrepancy nor Standards serve d as the moderator s as hypothesized This insignificant result may still help us explain Int ernet addiction among college students with the stress diathesis perspective According to this result the additive but not int eractive. Therefore, the result do es not go against the fundamental conceptualization of stress diathesis perspective because both stress ( e.g., perceived stress) and diathesis ( e.g., maladaptive perfectionism) contribute to the development of psychological disorders ( e.g., Internet addiction ). Howe ver, the result do es not seem to support maladaptive perfectionism as a relevant moderator under the framework of the Stress Response Dampening Model Originally, maladaptive perfectionism was hypothesized to be the more likely moderator among the lower or der personality factors because it showed significant relationships with the major components of proposed addictive personality constructs such as neuroticism and conscientiousness. However, the result did not support this choice of moderator under the SRD model Although the two aspects of perfectionism, Dis crepancy and Standards, did not serve as moderators individually, the significant interaction effect in regression analyses in predicting Internet addiction suggests these two dimensions can be combine d to predict Internet addiction. These two dimensions categorize participants into four different types of perfectionists that may have different vulnerability to Internet addiction. Recent studies have supported using the two perfectionism dimensions to f orm four clusters in predicting eating disorders (Boone, Soenens, Braet, & Goosens, 2010) and
87 adolescent adjustment (Rice, Ashby, & Gilman, 2011). Rice et al. pointed out that this approach can distinguish the two different groups of participants that were traditionally categorized as one maladaptive perfectionist umbrella. They suggested that the four cluster can be label as maladaptive perfectionists (high Standards and high Discrepancy), adaptive perfectionist (high Standards and low Discrepancy), non pe rfectionists (low Standards and low Discrepancy), and negative self ev aluation group. As shown in Figure 3 1 and 3 2 regarding the interaction effect of the two perfectionism dimensions, this four cluster model seem to help explain why participants who had low Standards and high Discrepancy showed the highest scores on Internet addiction. Exploratory A nalysis Exploratory analyses conducted to examine the relationship between Internet addiction and other relevant personality factors found that procrastinatio n was significantly correlated with Internet addiction in the bivariate analysis and the effect size is large. The effect size was even larger than the one for maladaptive perfectionism and Internet addiction. The result suggests that procrastination and m aladaptive perfectionism together seemed to be the best predictors for Internet addiction. Frost et al (1990) found that procrastination was positively related to maladaptive perfectionism and hypothesized that procrast inating people delay work to avoid l ess than perfect performance. Procrastination was even included as one dimension of perfectionism when the APS R was first constructed (Joh n son & Slaney, 1996). With such close relationship between maladaptive perfectionism and procrastin ation, procrastina tion seem s to be a good personality moderator candidate like maladaptive perfectionism. However, an exploratory hierarchical multiple relationship showed that procrastination
88 also was not the right moderator for the relationship between stress an d Internet addiction under SRD framework Sensation seeking was also linked to Internet addiction although results have been inconsistent (Chou et al., 2005). The bivariate analysis of sensation seeking and Internet addiction did reveal a signif icant result ; howeve r, the effect size was small This could be due to measurement issue that traditional sensation seeking scale could not detect non physical type of sensation seeking online (Lavin, et al., 1999). Sensation seeking also did not seem to moderate the relation ship between perceived stress and Internet addiction. Finally, impulsivity was found to have a small but significant association with Internet addiction. This result confirms that impulsivity is one of the personality factors that predispose people for add ictive behaviors ( Ibez, et al., 2008). It also seems to somewhat support the theory that Internet addiction can be interpreted as a k ind of Impulse control disorder (Young & Rogers, 1998; Young, 1998a; Young, 1998b) although the result can also be interpreted to support conceptualizing Internet addiction with the addictive personality model. Although impulsivity is one of the hypothesized addictive personality factors in the SRD model (Sher & Levenson, 1982), examination of impulsivity as a moderator between perceived stress and Internet addiction also did not reveal a significant result. Additionally, each of the Big Five personality factors was also explored to see whether any of them would moderate the relationship between perceived stress and Internet addiction. Based on the proposed addictive personality dimensions in the SRD model, outgoing (extraversion), aggressive (agreeableness), impulsive (conscientiousness), and a ntisocial (agreeableness and conscientiousness) personality
89 characteristics would moderate the relationship between perceived stress and Internet addiction (Sher & Levenson, 1982) .However, the results showed that none of these related Big Five factors had moderating effects; only neuroticism turned out to be a n ambiguous moderator between the relationship of perceived stress and Internet addiction under the SRD model. It exhibited a very small m oderating effect on the relationship between perceived stress and Internet addiction and the plot of the moderating effect suggested that the significance might have resulted from the large sample size In addition, the effect of neuroticism was actually the opposite of what the addictive perso nality theory would hypothesize ( Ibez, et al., 2008). This result could be due to that neuroticism was not specifically purposed as one of the predisposing personality characteristics in the initial SRD model (Sher & Levenson, 1982) although it has been hypothesized as one of the main additive personality dimensions by theorists ( Ibez, et al., 2008). There could be several reasons why the initially purposed personality moderators ( e.g., impulsivity, low agreeableness/antisocial and aggressive personality, and outgoingness/extraversion which were examined in the current study) that did not turn out to be relevant. First, the SRD model was initially developed to explain alcoholism but not behavioral ad diction like Internet addiction. There could be other personality moderators relevant to Internet addiction that are different from the ones for alcoholism. Second, the SRD model measure s stress through biological ge. However, in the current study, stressed reported perceived stress during
90 the past month. Further research is needed to explore the applicability of using SRD model to explain Internet addiction. Sig nificance of Current Study In conclusion, t his study contributes to the literature regarding Inte rnet addiction in several ways. First, the study result regarding preva lence suggests that Internet addiction is indeed a mental condition worth more attention in research and practice. The alarming high Internet addiction prevalence rate among college students found in this study demands the field of psychology address the unresolved diagnos tic and con ceptualization issues in research so that many individuals w ith Internet addiction can receive proper assessment and treatment. Second, this study contributes to understanding the etiology of Internet addiction. Previous studies regarding Internet addiction focused more on its symptoms and demographic characterist ics of those with Internet addiction, but rarely adopted theoretical approaches In contrast the current study is the first study to employ a stress diathesis perspective to explore how stress and personalit y factors may together predict Internet addictio n As Li et al. (2009) pointed out, there has not been much research directly addressing the contribution of stress to Internet addiction development among college students. Findings from the present study indicate the importance of consider ing stress as t he main predictor for Internet addiction. Third, this study highlights the importance of studying lower order personality factors for Internet addiction. Previous studies of the relationship between personality and Internet addiction focused more on highe r order personality factors and had inconsistent results (e.g., Amichai Hamburger & Ben Artzi, 2003; Hamburger & Ben Artzi, 2000; Ko et al. 2006; Ko et al., 2007). This study also examined higher order
91 personality factors (e.g., the Big Five personality fa ctors) and helped clarify previous ly inconsistent result s possibly due to smaller sample size s In addition, this study examined the lower order personality factors ( i.e., perfectionism and procrastination) and the results show that they may be very import ant f actors for Internet addiction. Fo u supports the new approach to conceptual ize perfectionism. For example following the conventional categorization derived from APS R scores perfectionists can be distinguished from non perfectionists with higher scores on Standards and then among the perfectionists, maladaptive perfectionists can be distinguished from adaptive perfectionist s by higher scores on Discrepancy (Rice & Slaney, 20 02). However, this three cluster categorization is not able to predict why the participants who had low Standards scores and high Discrepancy scores had the highest level of Internet addiction whereas the four cluster dimensional categorization recommended by Rice and colleague s addiction level in this study. Finally, this study also tested the SRD model on Internet addiction. Although the results were not expected, they raised sever al possible research questions for future studies to explore the addiction s Overall, t his study bridges many gaps in the Internet addiction literature by employing a theoretical orientatio n and testing empirical model s with standardized instruments. The results of this study set some important foundations for Internet addiction that future studies can build upon
92 CHAPTER 5 LIMITATIONS, FUTURE RESEARCH DIRECTIONS, AND PRACTICE IMPLICATIONS Although this study bridged several important literature gaps and had a rather large sample, t here are the following limitations that need to be noted. One of the obvious limitations of this study is that it used a convenience sample The study invitation them did not respond and some of them did not offer extra credit as the incentive for their student s ins tructors in the psychology department, there were many participants recruited from undergraduate class in the psychology department and from the psychology participant pool. Therefore, there were more female participants than ma le participants in this samp le. Compared to most of the previous studies on Internet addiction that had more male participants, this difference needs to be taken into account when the readers interpret or generalize the results to another population. Another limitation of the study is its correlational design. Although the time sequence was mentioned in the perceived stress measure to suggest a causal inference indicating the influence of perceived stress on current Internet use, it is possible that some participants might have had m ore perceived stress caused by chaotic lifestyle due to serious Internet addiction symptoms in the first place. The solution to address the question lies in the design of study for future research ; only l ongitudinal and experimental designs could further a scertain the direction of the relationship. One of the improvements of this study from previous studies is that it used a standardized instrument to measure perceived stress. Although this approach managed onal stress experience compared to merely counting stressors
93 or stressful event s stress level. Participants who had similar number or degree of stressful events might have a very different reported perceived stre ss. The reported perceived stress could be highly related to other factors such as personality characteristics. This could be the reason why that many of the personality factors examined in this study did not show m oderating effect on the relationship betw een stress and In ternet addiction. Previous studies using responses such as heart rate, sweating, muscle tension, etc. in the experimental design This measurement and design difference could be the reason why this study could not find the moderating effect s of some personality factors between stress and Internet addiction. Future studie s may be able to improve with an experimental and/or longitudinal design to incorporate mea sure of response s. Finally, the use of self report measures in this study might also have been s ubject to social desirability and cultural values For example, agreeableness conscientiousness, and agreeableness wer e negatively skewed, which might be the result s perfection dimensions such as standards and order are all socially desirable tendencies that participants may endorse more tha n some other less desirable personality characteristics such as procrastination impulsivity and neuroticism. Therefore, it is under standable that adaptive perfectionism was severely negatively skewed. Interestingly, cultural values may also play a role fo r the positive skewness on the variable Impulsivity. Theoretically and clinically sensation seeking is not considered as
94 a positive personality characteristic; however, contemporary popular culture may have transformed sensation seeking into a desirable c haracteristic. Therefore, including a social desira bility and/or a cultural value measure in future research may be a viable way to a ddress the issue. There are several interesting finding s from this study that call for fur ther research. First, compared t o other related Big Five personality characteristics, conscientiousness showed the strongest correlation with Internet addiction in term of effect size whereas the related const ruct maladaptive perfectionism and procrastination also exhibited the two stron g bivariate correlations with Internet addiction compared to other theoretically related personality constructs. This suggests conscientiousness, maladaptive perfectionism, and procrastination are very important factors for Internet addiction. The f urther investigation of these constructs and their relationships not only may further clarify the relationships between higher order and lower order personality factors but also may elucidate the difference between substance abuse addiction and behavioral addicti on s such as Internet addiction. Finally, procrastination, w hich had the strongest correlation with Internet addiction definitely calls for more examination of its effect on Internet addiction. Although the re have already been some studies about Internet a ddiction and procrastination as a personality trait (Davis et al., 2002b) p rocrastination can be a difficult concept to define and measure. It is inconclusive in literature whether procrastination should be classified as a personality trait, a behavioral tendency, or merely a symptom of other psychological disorders. In order to define this construct and its relationship with Internet add iction more clearly, the measures and study design in future research should be carefully selected.
95 Regarding counselin g practice, the findings from this study can contribute to help prevent, assess, and treat Internet addiction among college students. Internet addiction can be as stigmatizing a label as traditional substance abuse addiction, or even more stigmatizing for college students. The general public often holds this stereotyped image of the person with Internet addiction as someone who is addicted to online pornography when in fact there are many more common types of addictive online activities (e.g., social networ k sites, online gaming, etc.). Internet addiction may not be easily or readily addiction are ashamed of, or trying to hide/minimize, their Internet use. Identifying coll ege students who might develop Internet addiction early would be very helpful in preventing these college students from suffering serious symptoms or consequences. The results from this study suggest that experiencing high stress, having personality charac teristics such as low conscientiousness, high neuroticism, low extraversion, and low openness, being mal adaptively perfectionistic, showing signs of procrastination and sensation seeking, and being impulsive would be the risk factors for college students to develop Internet addiction. Therapists could pay attention to clients with many of these risk factors during intake sessions and inquire about potentially problematic Internet use. In addition, therapists can use relatively brief measures of personality perfectionism, procrastination, and/or Internet addiction to screen at risk students for preventative interventions. In terms of treatment, therapists might be advised, from the d certain personality factors (e.g., maladaptive perfectionism) may lead to maladaptive coping with online activities.
96 In conclusion, this study not only revealed a relatively high level of Internet addiction among college students but also elucidated the relationships between Internet addiction and perceived stress, higher order personality factors such as the Big Five personality factors, and lower order personality factors such as perfectionism. The results bridged gaps in the Internet addiction literatu re and provided practical information that can aid in the assessment and treatment of Internet addiction. Hopefully, this study can spawn further research regarding Internet addiction among the college student population
97 APPENDIX A DEMOGRAPHIC QUESTIONNA IRE Please complete the following information. Click on the item that best describes you or fill in the blank. Please answer each question as accurately as you can. Remember that all your answers are strictly confidential. 1. What is your age? _______ __ 2. Student Status: (a) What is your academic classification ? A. Freshman B. Sophomore C. Junior D. Senior E F. Doctoral student G. Other (b) How many semester s have you finished here at University of Florida? ______________. (c) H ow many semesters in college have you finished a ltogether? ______________. 3. What is your major or intended major? ________ _______________________________ 4. GPA: (a) What is your current GPA? _____________ (out of 4.0 scale). (b) If this is your first semester, please indicate your most recent other GPA here ( e.g., high school GPA, undergraduate GPA) ___________________ (out of 4.0 scale / non weighted) 5. What is your gender ? A. Female B. Male C. Transgender D. Other please specify and write here ____________ E. Decline to answer 6. What is your sexual orientation? A. Bisexual B. Heterosexual C. Homosexual D. Unsure E. Other please specify and write here ____________ F. Decline to answer
98 7. Race and ethnicity: (a) Are you Hispanic, Latino(a), and / or of Spanish origin ? American, or other Spa nish culture or origin, regardless of race.) A. Yes B. No (b) In terms of race, please describe the specific group that you identify with the most: A. American Indian or Alaskan Native B. Asian C. Black or African American D. Native Hawaiian or Other Pacific Islander E. White F. Bi racial or Multi racial G. Other (c) Are you an international student? A. Yes B. No 8. Living Situation: (a) What is your living situation? A. Off campus B. On campus (b)Who do you live with? A. I live alone B. I live with my family C. I live with roommates D. Other please specify and write here ____________ 9. What is your relationship status? A. Single B. In a relationship (including dating, marriage, or civil union, etc.) C. Other please specify and w rite here ____________ 10. What was your age when you first started using the Internet? ________________. 11. Internet Use: (a) Approximately, how many hours in total per week do you use the internet ? (please include the hours of multi taski ng ) ________ ______ ( b ) Among the total hours of using the I nternet, how many hours do you usually use the internet for leisure and/or entertainment purposes? (please include the hours of multi tasking ; for example, studying and listening to an Internet radio station, such as Pandora, at the same time .) _____________
99 12. Internet Experience: (a) Do you have internet access at the place you live now? A. Yes B. No (b) Do you have a data plan for Internet access with your cell phone plan? A. Yes B. No (c)What activity most often keeps you on the Internet? A. Academic work B. Online dating C. Adult content D. Information surfing (such as reading news or browsing websites) E. Job requirements / professional needs F. Online gambling, shopping, and / or st ock trading G. Online game playing and / or programming H. Social networking (such as using Facebook, MySpace, or MSN, etc.) I. Other please specify and write here ____________
100 APPENDIX B INTERNET ADDICTION SCALE (IAS) INSTRUCTIONS: The following questions are written in the form of statements. Please read each statement carefully and completely. Indicate the extent to which each statement applies to you by clicking on the option that best reflects the strength of your response. Be sure to respond to the total item and not just a certain part of it. Internet use refers to anything you do online ( e.g., email, world wide web, chat rooms, games, cybersex, cyber porn, newsgroups, multi user dungeons, listservs Internet Relay Chat etc.). 1. When I attempt to cut back or stop using the Internet I find that the irritability that I experience is relieved by going back on the Internet. Never Rarely Sometimes Frequently Always 2. When I use the Internet now, I do not feel as good as I used to. Never Rarely Sometimes Frequently Always 3. I have stayed on the Internet longer than I intended to. Never Rarely Sometimes Frequently Always 4. I would like to spend less time on the Internet. Never Rarely Sometimes Frequently Always 5. At times I have tried to conceal how long I have been on the Internet. Neve r Rarely Sometimes Frequently Always 6. I have given up a particular recreational activity in order that I would have more time on the Internet. Nev er Rarely Sometimes Frequently Always 7. My grades/work have suffered because of my Internet use. Never Rarely Sometimes Frequently Always 8. Never Rarely Sometimes Fr equently Always
101 9. I have lost sleep because of my Internet use. Never Rarely Sometimes Frequently Always 10. I see my friends less often because of the time that I spend on the Internet. Never Rarely Sometimes Frequently Always 11. I feel t hat life without the Internet would be boring and empty. Never Rarely Sometimes Frequently Always 12. I have neglected things, which are important and need doing. Never Rarely Sometimes Frequently Always 13. I find that I need to use the Inter net more to get the same enjoyment as before. Never Rarely Sometimes Frequently Always 14. The more time I spend away from the Internet, the more irritable I feel. Never Rarely Sometimes Frequently Always 15. When I use the Internet, I experien ce a buzz or a high (i.e., feeling elated). Never Rarely Sometimes Frequently Always 16. I have missed class/work so that I would have more time to spend on the Internet. Never Rarely Sometimes Frequently Always 17. The Internet has affected m y life in a negative way. Never Rarely Sometimes Frequently Always 18. Once I am on the Internet, I seem to stay on for a long time. Never Rarely Sometimes Frequently Always 19. I have attempted to spend less time on the Internet but I have be en unable to do so. Never Rarely Sometimes Frequently Always
102 20. After being on the Internet late into the night I sleep late the next morning because of my Internet use. Never Rarely Sometimes Frequently Always 21. I find myself doing more thi ngs on the Internet than I had intended to. Never Rarely Sometimes Frequently Always 22. Never Rarely Sometimes Frequently Always 23. answer. Never Rarely Sometimes Frequently Always 24. I find myself thinking/longing about when I will go on the Internet again. Never Rarely Sometimes Frequently Always 25 I enjoy the pleasure/excitement of being on the Intern et. Never Rarely Sometimes Frequently Always 26 I feel distressed when I am unable to spend as much time on the Internet as I usually do. Never Rarely Sometimes Frequently Always 27 I have tried unsuccessfully to restrict my Internet use be cause of previous over use. Never Rarely Sometimes Frequently Always 28 Since I first began using the Internet I would say that the amount of time I spend on line has increased but not the satisfaction. Never Rarely Sometimes Frequentl y Always
103 29 I find myself accessing more information on the Internet than I had planned to. Never Rarely Sometimes Frequently Always 30 I have felt a persistent desire to cut down or control my use of the Internet. Never Rarely Sometimes F requently Always 31 When I feel lonely, I use the Internet to talk to others. Never Rarely Sometimes Frequently Always 32 I am on the Internet so much that I have to make up for the lost time Never Rarely Sometimes Frequently Always
104 APPENDIX C THE PERCEIVED STRESS SCALE (PSS) INSTRUCTIONS: The questions in this scale ask you about your feelings and thoughts during THE LAST MONTH. In each case, indicate your response by clicking on the circle representing HOW OFTEN you felt o r thought a certain way. Although some of the questions are similar, there are differences between them and you should treat each one as a separate question. The best approach is to answer fairly quickly. you felt a particular way, but rather indicate the alternative that seems like a reasonable estimate. 1. In the last month, how often have you been upset because of something that happened unexpectedly? Never Almost Never Sometimes Fa irly Often Very Often 2. In the last month, how often have you felt that you were unable to control the important things in your life? Never Almost Never Sometimes Fairly Often Very Often 3. In the last month, how often have y Never Almost Never Sometimes Fairly Often Very Often 4. In the last month, how often have you dealt successfully with day to day problems and annoyances? Never Almost Never Sometimes Fairly Often Very Often 5. In the last month, how often have you felt that you were effectively coping with important changes that were occurring in your life? Never Almost Never Sometimes Fairly Often Very Often 6. In the last month, how often have you felt confident about your ability to handle your personal problems? Never Almost Never Sometimes Fairly Often Very Often 7. In the last month, how often have you felt that things were going your way? Never Almost Never Sometimes Fairly Often Very Often 8. In the last month, how often have you found that you could not cope with all the things that you had to do? Never Almost Never Sometimes Fairly Often Very Often 9. In the last month, how often have you been able to control irritations in your life? Never Almost Never Sometimes Fairly Often Very Often
105 10. In the last month, how often have you felt that you were on top of things? Never Almost Never Sometimes Fairly Often Very Often 11. In the last month, how often have you been angered because of things that happened that were outside of your control? Never Almost Never Sometimes Fairly Often Very Often 12. In the last month, how often have you found yourself thinking about things that you have to accomplish? Never Almost Never Sometimes Fairly Often Very Often 13. In the last month, how often have you been able to control the way you spend your time? Never Almost Never Sometimes Fairly Often Very Often 14. In the last month, how often have you felt difficulties were piling up so high that you could not overcome them? Never Almost Never Sometimes Fairly Often Very Often
106 APPENDIX D THE MINI INTERPERSONAL PERSONALITY ITEM POOL (MINI IPIP) Mini Interpersonal Personality Item Pool (Mini IPIP) How Accurately Can You Describe Yourself? Describe yourself as you ge nerally are now, not as you wish to be in the future. Describe yourself as you honestly see yourself, in relation to other people you know of the same sex as you are, and roughly your same age. So that you can describe yourself in an honest manner, your re sponses will be kept in absolute confidence. Indicate for each statement whether it is Very Inaccurate, Moderately Inaccurate, Neither Accurate Nor Inaccurate, Moderately Accurate, or Very Accurate as a description of you. 1. Am the life of the party. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate 2. Sympathize with other Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate 3. Get chores done right away. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accu rate 4. Have frequent mood swings. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate 5. Have a vivid imagination. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurat e Accurate 6. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accur ate Accurate 7. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor In accurate Accurate Accurate 8. Often forget to put things back in their proper place. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate
107 9. Am relaxed most of the time. Very Moderately Neither Accurate Moderately Very Inaccur ate Inaccurate Nor Inaccurate Accurate Accurate 10. Am not interested in abstract ideas. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate 11. Talk to a lot of different people at parties. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate 12. Very Moderately Neither Ac curate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate 13. Like order. Very Moderately Neither Accur ate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate 14. Get upset easily. Very Moderately Neither Ac curate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate 15. Have difficulty understanding abstract ideas. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate 16. Keep in the background. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate 17. Am not really interested in others. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate 18. Make a mess of things. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate 19. Seldom feel blue. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate
108 20. Do not have a good imagination. Very Moderately Neither Accurate Moderately Very Inaccurate Inaccurate Nor Inaccurate Accurate Accurate
109 APPENDIX E THE ALMOST PERFECTION SCALE REVISED (APS R) The following items are designed to measure certain attitudes people have toward themselves, their performance, and toward others. It is important that your answers be true and accurate fo 1. I have high standards for my performance at work or at school. Strongly Disagree Slightly Neu tral Slightly Agree Strongly Disagree Disagree Agree Agree 2. I am an orderly person. Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree St rongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 4. Neatness is imp ortant to me. Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 5 Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 6. My best just never seems to be good enough for me. Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 7. I think things should be put away in their place. Strongly Disagree Slightly Neutral Slightly Agree Strongl y Disagree Disagree Agree Agree 8. I have high expectations for myself. Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 9. I rarely live up to my high standards. Strongly Disagree Slightly Neutr al Slightly Agree Strongly
110 Disagree Disagree Agree Agree 10. I like to always be organized and disciplined. Strongly Disag ree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 11. Doing my best never seems to be eno ugh. Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 12. I set very high standards for myself. Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 13. I am never satisfied with my accomplishments. Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 14. I expect the best from myself. Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 15. I often worry about not measuring up to my own expectations. Strongly Disagree Slightly Neutral Slightly Agree Strongly Disag ree Disagree Agree Agree 16. My performance rarely measures up to my standards. Strongly Disagree Slightly Neutral Slightl y Agree Strongly Disagree Disagree Agree Agree 17. I am not satisfied even when I know I have done my best. Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 18. This is a quality testing question; please c Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 19. I am seldom able to meet my own high standards for performance. Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree
111 20. I try to do my best at everything I do. Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 21. I am hardly ever satisfied with my performance. Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree Strongly Disagree Slightly N eutral Slightly Agree Strongly Disagree Disagree Agree Agree 23. I have a strong need to strive for excellence. Strongly D isagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 24. I often feel disappointment aft er completing a task because I know I could have done better. Strongly Disagree Slightly Neutral Slightly Agree Strongly Disagree Disagree Agree Agree 25. Using the scale below, please rate the degree to which you agree that you are perfectionistic. Strongly Disagree Slightly Neutral Slightly Agree Stron gly Disagree Disagree Agree Agree
112 APPENDIX F THE TUCKMAN PROCRASTINATION SCALE (TPS) Mark the place for each item that corresponds to yourself. 1. I needlessly delay finishing jobs, even when they're important. 2. I postpone starting in on things I don't like to do. 3. When I have a deadline, I wait till the last minute. 4. I delay maki ng tough decisions. 5. I keep putting off improving my work habits. 6. I manage to find an excuse for not doing something. 7. I put the necessary time into even boring tasks, like studying. 8. I am an incurable time waster. 9. I'm a time waste r now but I can't seem to do anything about it. 10. When something's too tough to tackle, I believe in postponing it. 11. I promise myself I'll do something and then drag my feet. 12. Whenever I make a plan of action, I follow it. 13. Even though I hate myself if I don't get started, it doesn't get me going. 14. I always finish important jobs with time to spare.
113 15. I get stuck in neutral even tho ugh I know how important it is to get started. 16. Putting something off until tomorrow is not the way I do it.
114 APPENDIX G THE IMPULSIVE SEN S ATION SEEKING SCALE DIRECTIONS: Below you will find a series of statements that persons might use to describe themselves. Read each statement and decide whether or not it describes you. If you agree with a statement or decide that it describes you, answer TRUE by clicking on the circle representing rue If you disagree with a statement or feel that it is not descriptive of you, answer FALSE by clicking on the cir cle representing alse Answer every statement either True or False even if you are not entirely sure of your answer. 1. I like to have new and exciting experiences and sensations even if they are a little frightening. True False 2. I like doing things just for the thrill of it. True False 3. I sometimes do "crazy" things just for fun. True False 4. I sometimes like to do things that are a little frightening. True False 5. I enjoy getting into new situations whe re you can't predict how things will turn out. True False 6. I'll try anything once. True False 7. I prefer fri ends who are excitingly unpredictable. True False 8. I like "wild" uninhibited parties.
115 True False 9. I would li ke the kind of life where one is on the move and traveling a lot, with lots of change and excitement. True False 10. I am an impulsive person. True False 11. I like to explore a strange city or section of town by myself, even if it means getting lost. True False 12. I would like to take off on a tr ip with no preplanned or definite routes or timetables. True False 13. Before I begin a complicated job, I make careful plans. True False 14. I very seldom spend much time on the details of planning ahead. True False 15. I tend to begin a new job without much advance planning on how I will do it. True False 16. I usually think about what I am going to do before doing it. True False 17. I often do things on impu lse. True False
116 18. I often get so carried away by new and exciting things and ideas that I never think of possible complications. True False 19. I tend to change interests frequently. True False
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127 BIOGRAPHICAL SKETCH To ng An Shueh was born in Taipei Taiwan. He grew up with his parents, one elder sister and one elder brother. He attended National Central University in Tao Yuan, Taiwan and graduated in 1998 with a B.A. in English and American l iterature along with t eacher e ducation p rogram. After grad uating, Tong An taught in m iddle s chool as an English t eacher and a t rainee c ounselor for one year. Tong An served in the Taiwan Army for two years as a counselor officer. In 2002, he came to the United States to study at Indiana University Bloomington, w here he completed his M.S. in c ommunity c ounseling in 2004 and Ed.S. in m ental h ealth c ounseling in 2005. Tong An started his doctoral study in c ounseling p sychology program at the University of Florida from Fall 2005. Tong An received his M.S in Psycholo gy in 2007 and expect s to receive his Ph.D. in c ounseling p sychology in 2011.