Relationships among patient's expectations, nurse's performance of family nursing interventions, and adherence/compliance

MISSING IMAGE

Material Information

Title:
Relationships among patient's expectations, nurse's performance of family nursing interventions, and adherence/compliance a gap analysis
Physical Description:
xi, 112 leaves : ill. ; 29 cm.
Language:
English
Creator:
Sutherland, Rita E. K
Publication Date:

Subjects

Subjects / Keywords:
Family Nursing   ( mesh )
Patient Compliance   ( mesh )
Diabetes Mellitus -- nursing   ( mesh )
Nurse-Patient Relations   ( mesh )
Sick Role   ( mesh )
Caregivers   ( mesh )
Cardiovascular Diseases -- nursing   ( mesh )
Genre:
bibliography   ( marcgt )
theses   ( marcgt )
non-fiction   ( marcgt )

Notes

Thesis:
Thesis (Ph. D.)--University of Florida, 2001.
Bibliography:
Includes bibliographical references (leaves 105-111).
Statement of Responsibility:
by Rita E.K. Sutherland.
General Note:
Typescript.
General Note:
Vita.

Record Information

Source Institution:
University of Florida
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
oclc - 50820725
ocm50820725
System ID:
AA00011166:00001

Full Text











RELATIONSHIPS AMONG PATIENTS' EXPECTATIONS, NURSES'
PERFORMANCE OF FAMILY NURSING INTERVENTIONS, AND
ADHERENCE/COMPLIANCE: A GAP ANALYSIS













By

RITA E. K. SUTHERLAND


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


2001































Copyright 2001

By

Rita E. K. Sutherland














ACKNOWLEDGMENTS


This work could not have been completed without the support of my committee

chair, Dr. Sandra Seymour. I thank her for her guidance, support and optimistic attitude. I

want to thank my other committee members, Dr. Jo Snider, Dr. Claydell Home, Dr.

David Miller and Dr. Leonard Beeghley, for their time and support. I extend my gratitude

to the nurse practitioners and patients who participated in this study. These nurses are

examples of what makes nursing one of the best professions in the world. The time I

spent with the patients will always be special to me because of the unique memories of

their days in military service that they shared with me. Most of all I am grateful to my

family: to John, for being my "friend" and to Joe and Kate for being themselves!














TABLE OF CONTENTS

page

ACKN OW LED GM EN TS .................. .................. .................. ........................ ... iii

LIST O F TA B LE S .......................... .................. ............................................... vii

LIST O F FIG U R E S.................................................................................................... ix

A B ST R A C T .......................................................................... ................................. x

CHAPTERS

1 STATEMENT OF PROBLEM: COMPLIANCE & FAMILY NTERVENTIONS..... 1

C om pliance ....................................................................................................... 1
Incidence of Compliance and Noncompliance ...................................................
Effects of N oncom pliance .................................................................................. 3
Nonjudgmental/Ethical Perspective of Compliance................... ........................ 4
Operationalizations of the Concept: Compliance....................................................... 4
Managing Compliance..................... ............. ............................. 6
Research on Variables Related to Compliance .....................................................7
Knowledge and Understanding ........................................ ....................... 8
Q quality of Interaction ........................................................................................ 11
Social Isolation and Social Support....................... ..... ........... ............. 12
H health Beliefs and Attitudes ............................................... ................... 13
Illness and Treatm ent........................................................... ......................... 13
Interaction of Health Beliefs, Attitudes, & Family Interventions: An Opportunity.... 14
G ap A analysis ........................... ....................................................... .. ................ 15
Problem Statement......................................................... ......... .... 16
Significance for N using ...................................................................................... 17

2 LITERATURE REVIEW ......................................................... ................... 18

H health B relief M odel ............................. .............................. .......................... 18
Components of the Health Belief Model...................................................... 18
Perceived Susceptibility ................................................... ............... 19
Perceived Severity.................................................................. ......................... 20
Perceived Benefits.................................................................. ....................... 20
Perceived Barriers/Costs............................................................................... 21
Interaction of Components ..........................................................21









C ues to B behavior ............................................................................................. 22
Evaluation of the Health Belief Model............................................................. 22
Family and Nursing ............................ ....... ...................... 23
Family Care Giving: Theory and Practice.............................. ..................... 24
Compliance and Nursing Interventions.................................................................... 26
Effects of Family Interventions on Individual Patient in Context of Family ...... 26
Effects of Family Interventions on the Family ................... .................... 27
Effects of the Family on Family Interventions .......................................... 28
F am ily Interventions .......................... .. ...... ...................................... ................... 28
Need for Research on Family Interventions....................................................32
G ap A analysis ........................................................................................................... 33
H ypotheses ..................................................................... ............... ................ 35

3 M E TH O D O LO G Y ............................ .................................... ..........................38

Purpose of the Study................................... ...... .......................................... 38
Instrumentation: Family Interventions and Their Gaps: Independent Variables........39
Relevant to the Patient Sample .......... ............ ......................... ...... ..........39
Interventions Attributable by the Patient to the Nurse....................................40
Intervention Content Validity (ICV) Scores............................. ..............41
Measurement of Importance and Performance of Family Interventions.............41
Factor Analysis of Family Interventions ... .................................. .... 42
Gap Scores: the Independent Variables......................... .................... 50
Indicators of Compliance: the Dependent Variables.............................................. 51
Reliability of Subjective (Indirect) Evaluation of Compliance Scale ............... 53
Reliability of Measured (Pseudo-Direct) Evaluation of Compliance Scale........ 56
Summary of Study's Instrumentation: Variables ................................................... 58
Sam ple Selection ........................................................................... ....................... 60
Protection of Human Subjects............................................. 61
Statistical T ests........................................................ .................. .......................... 62
Assumptions of Statistical Tests: Repeated Measures Analysis of Variance...... 63
Assumptions of Statistical Tests: Multiple Regression...................................... 65
L im stations .................... ........................... ................. .... ........................ ................. 67

4 R E SU L T S ...................................................................................... .. ................... 70

Purpose of the Study .................................................................. .......................... 70
Nurse Practitioner Profile .......................... .............................................. .... 70
Patient Profile.......... .................... ..... ...................... ...........................71
Hypothesis 1: Differences in Importance of Family Interventions ......................... 73
Hypothesis 2: Differences in Performance of Family Interventions.......................... 75
Hypothesis 3: Patients' Gaps and Patients' Perceived Compliance.......................77
Patients' Perceived Compliance with the Nonmedication Regimens Factor ......78
Patients' Compliance with the Medications Regimens Factor....................... 78









Hypothesis 4: Nurses' Gaps and Nurses' Perceived Compliance............................. 79
Nurses' Perception of Patients' Compliance with Nonmedication Factor.......... 79
Nurses' Perception of Patients' Compliance with the Medication Factor.......... 80
Hypothesis 5: Patients' Gaps and Patients' Measured Evaluation of Compliance..... 81
Patients' Gaps as Predictors of Nurses' Nonmedication Compliance ...............81
Patients' Gaps as Predictors of Nurses' Medication Compliance..................... 82
Hypothesis 6: Nurses' Gaps as Predictors of the Measured Patients' Compliance .... 83
Nurse Gaps as Predictors of Nonmedication Compliance.................................. 83
Nurse Gaps as Predictors of Medication Compliance........................................ 84

5 SUMMARY, CONCLUSIONS, AND IMPLICATIONS...................................... 85

Sum m ary of Findings ..................................................................... ..................... 85
Family Interventions More Relevant to Married Patients and Their Nurses....... 85
Patients' Gap Not Related to Patients' Perceived Compliance ...................... 86
Patients' Gap II: "Strategizing" Related Nurses' Nonmedication Compliance .. 86
Patients' Gaps Not Related to Nurses' Pseudo-Direct Compliance Measures.... 86
Nurses' Gap I: "Teaching" Related to Nurses' Medication Compliance.......... 87
C conclusions .......................... .............. ................................................ ................. 87
Implications for Nursing Education and Practice ..................................................89
Family Interventions May Contribute to Compliance...................................... 89
Family Interventions May Be More Simple than Currently Conceived ............90
Compliance May Be More Complex than Currently Conceived........................90
Patients and Their Nurses May Have a Simple Conception of Family.............. 91
Implications for Future Research ........... ................... ................ .................. .. 92

APPENDICES

A Nurse's Background and Family Intervention Questionnaire................................ 93

B Patient's Background and Family Intervention Questionnaire..................................97

C Nurse Practitioner Recruiting Letter............................................... 100

R E FE R EN CE S............................................................................. ......................... 105

BIOGRAPHICAL SKETCH .................. ......... .................................................. 112















LIST OF TABLES


Table page

3-1 Fam ily Interventions ........................... .... ... ............ .. ...... ............ 42

3-2 Factor Analysis with Varimax Rotation of Importance
of Family Intervention Items ................................................................. 46

3-3 Factor Analysis with Varimax Rotation of Performance
of Family Intervention Items ............................. ...................... 47

3-4 Nurses' and Patients' Importance and Performance Factor
Loadings A analysis ............................................................ ..................... 48

3-5 Cronbach's Alpha and Alpha if Item Deleted for Family
Intervention Factors ............................................................................... 49

3-6 Factor Analysis of Gap Scores .................................... ........................... 52

3-7 Gap Factors and Their Loadings ............................................................... 53

3-8 Cronbach's Alpha for Nurses' Subjective (Indirect) Evaluation
of Com pliance Item s ............................................................................ .. 54

3-9 Cronbach's Alpha for Nurses' Subjective (Indirect) Evaluation
of Com pliance Item s ............................................................................ ... 54

3-10 Varimax Rotation of Nurses' and Patients' Subjective
Evaluation of Compliance Items........................................................... 55

3-11 Cronbach's Alpha for Nurses' Pseudo-Direct Evaluation
of Com pliance................................. .......................... .......................... 56

3-12 Varimax Rotation of Nurses' Pseudo-Direct Evaluation
of Com pliance................................ .................... .......... .. .......... 58

3-13 Completed versus Usable Questionnaires..................... ................... 61

4-1 Sample Profile .................................. ............. ........................... 72









4-2 Correlation of Importance and Performance Factors with Age and
Number of Previous Appointments with the Nurse Practitioner ................ 73

4-3 Repeated Measures Test of Difference between Importance Scales ............ 74

4-4 Repeated Measures Test of Differences between Importance Scales
Between Patent and Nurse Marital Groups............................................74

4-5 Mean Scores for Importance Scales by Marital Group.................................. 74

4-6 Repeated Measures Test of Difference between Performance Scales............ 76

4-7 Repeated Measures Test of Differences in Performance Scales
Between Patient and Nurse Marital Groups ..................................... 76

4-8 Mean Scores for Performance Scales by Marital Group................................ 77

4-9 Patient Gap, Patient Age and Marital Status as a Predictor of
Patients' Perceived Compliance with the Non-Medication
Compliance Factor........ .......... ......... ............................................ 78

4-10 Patient Gap, Patient Age and Marital Status as a Predictor of
Patients' Perceived Compliance with the Medication
Com pliance Factor.......................................................... ....................... 79

4-11 Nurse Gap, Patient Age and Martial Status as a Predictor of
Nurses' Perception of Patients' Compliance with the Nurses'
M education Compliance Factor........ ..................... ........ ............ 81

4-12 Nurse Gap, Patient Age and Martial Status as a Predictor of
Nurses' Perception of Patients' Compliance with the Nurses'
Non-Medication Compliance Factor................. ................. ... 81

4-13 Patient Gap, Patient Age and Marital Status as a Predictor of
Nurses' Measured Evaluation of Patients' Non-Medication
Compliance ....... .............. .. ..... ............ ........................ 82

4-14 Patient Gap, Patient Age and Marital Status as a Predictor of
Nurses' Measured Evaluation of Patients' Medication Compliance ..........82

4-15 Nurse Gap, Patient Age and Martial Status as a Predictor of
Nurses' Measured Evaluation of Patients' Non-Medication Compliance... 83

4-16 Nurse Gap, Patient Age and Martial Status as a Predictor of
Nurses' Measured Evaluation of Patients' Non-Medication Compliance ... 84















LIST OF FIGURES


Figures pge

2-1 The H health B elief M odel.............................................................................20

2-2 Gap Model of Patient's and Nurse's Expectations and
Performance Evaluation Leading to Compliance ...................................... 37

4-1 Importance and Performance Means........................................................... 75














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

RELATIONSHIPS AMONG PATIENTS' EXPECTATIONS, NURSES'
PERFORMANCE OF FAMILY INTERVENTIONS, AND
ADHERENCE/COMPLIANCE: A GAP ANALYSIS

By

Rita E. Krull Sutherland

August 2001

Chairperson: Sandra Seymour, PhD
Major Department: Nursing

This study used a gap analysis to examine the differences between patients' and

nurses' perceptions of importance and nurses' performance of family interventions and

the relationship among patients' and nurses' importance and performance gaps and

indirect and pseudo-direct measures of compliance.

In a cohort design, personal surveys were conducted with a convenience sample of

10 nurse practitioners and 169 patients between June 1999 and October 1999. The nurse

sample was restricted to nurse practitioners with at least 2 years of experience treating

adult patients with cardiovascular disease or diabetes. The patient sample was restricted to

patients under treatment for cardiovascular disease (CVD) or diabetes who had completed

at least three prescheduled clinic appointments with the nurse practitioner at the clinics

used in this study. Both CVD and diabetes require multiple interventions and are common

causes of morbidity and mortality.









The results provided evidence of two major dimensions and gaps in nursing family

interventions: Teaching and Strategizing. The Teaching gap factor was composed of items

related to teaching the family about the patient's condition. The Strategizing gap factor

was composed of items related to helping the family develop strategies for coping with the

situation and supporting the patient. The results also suggested nurses' perception of their

patients' compliance with nonmedication regimens was related to how well the nurse

helped the patient's family develop strategies for dealing with the patient's condition. The

nurses' Teaching gap factor was related to nurses' pseudo-direct measures of patients'

compliance with medication regimens.

The results of this study provided positive, yet limited, support for the use of

family interventions to enhance patients' compliance. The results also suggested that

nursing theory and research may need to treat the concept of family interventions as a

more simple concept than is currently conceived and may need to treat compliance as a

more complex concept than is currently conceived. Lastly, the results suggested the need

for reciprocal information transfer among family intervention theorists and researchers and

nurse practitioners and their patients. Directions for future research are discussed.














CHAPTER 1
STATEMENT OF THE PROBLEM


Compliance

Patient compliance, conceptually defined as .. the extent to which a person's

behavior (in terms of taking medications, following diets, or executing lifestyle changes)

coincides with medical or health advice" (Haynes 1979, pp. 1-2), has long been a

significant concern in healthcare. Hippocrates is reportedly to have remarked, "(The

physician) should keep aware of the fact that patients often lie when they state that they

have taken certain medicines" (Gordis, 1979, p.35).

Although Haynes' (1979) definition has been criticized because of the

paternalistic role given to healthcare provider, reviewers often overlooked that Haynes

added adherence to the definition, "The term adherence may be used interchangeably

with compliance" (p. 2). Madden (1990) argued that compliance and adherence referred

to the outcomes of the patient-provider interaction, while therapeutic alliance referred to

the process of the interaction itself. Some authors prefer to use the term adherence

because it is less judgmental (Moore, 1995; Ward-Collins, 1998). Interestingly, Kyngas,

Duffy and Kroll (2000), in an article published after this study's data collection ended

and analysis began in October 1999, noted that there was no generally accepted definition

of compliance. The authors (Kyngas, Duffy & Kroll, 2000) noted the use of alternative

terms including adherence, cooperation, mutuality and therapeutic alliance. Kyngas et al.

(2000) concluded that the concept of compliance related to patients' self-care









responsibilities, their role in the treatment process, and their collaboration with health care

providers. This is the perspective that was used for this study. Likewise, the term

compliance was used with respect to patients' right to choose.

Regardless of the specific term used, compliance is critical to the success of

therapeutic health regimens and treatment plans (Clark & Becker, 1998). When

compliance is absent or low (noncompliance), therapeutic goals go unmet or, at best, are

only partially achieved (Becker & Maiman, 1980; Dracup & Meleis, 1982).

Compliance can be viewed as an attitude or as a behavior. As an attitude,

compliance is a willingness or intention to follow health prescriptions. As a behavior,

compliance is the actual carrying out of prescriptions (Davis, 1968). Whether conceived of

as an attitude or a behavior, the effects of even the most well designed health care

regimens are mediated by the patients' attitudes and behaviors toward compliance.

Incidence of Compliance and Noncompliance

Haynes (Sackett & Haynes, 1976) review of compliance studies found that 50% of

patients do not take prescribed medications. Silverman (1982) reported that patient's

compliance at mental health centers showed a 20 to 50% dropout rate for psychotherapy

session attendance. Sachs (1982) reported a 30 to 70% dropout rate for exercise type

health related programs. Dunbar (1990) estimated that nonadherence rates ranged from

20% to 80%. Simons (1992) reported that patient compliance ranged from 10 to 94%.

More recently, Fishman, Finney, Rapoff& Christophersen (1995) found that at least one-

third of patients fail to comply with their specific healthcare regimens. Clark and Becker

(1998) estimated that only one-third of patients correctly follow physicians' directives.

More recent research, meaning studies published after this study's data collection had









ended and analysis began in October 1999, reinforced the challenge of compliance. For

example, Evangelista & Dracup (2000) estimated that one-third to one-half of all patients

are noncompliant.

Effects ofNoncompliance

In addition to the obvious risks of noncompliance for the patient and the patient's

social support, noncompliance affects the U.S. economy. Baer (1986) pointed out that

when approximately 39.7% of health care costs are paid for by federal and state

governments, society pays for the largest portion of hospital-incurred health care costs. To

the degree that compliant behavior leads to healthy citizens who do not return to the

hospital, these governmental expenditures contribute to society and its economy, and to

the degree that noncompliant behavior leads to returns to the hospital, these governmental

expenditures lead to economic waste. Baer (1986) also suggested that noncompliance

could lead to increased medical costs and loss of productivity of the individual due to

exacerbation of preventable diseases. Currently, in areas of health care where cost-

containment is at the core of delivery, the main approach is to insure quality when defining

basic health care services. This is accomplished by incorporating interventions that are

effective, efficient, appropriate and desired by the patients (Walters & Morgan, 1995).

Today's rapidly changing health care environment in the United States is an

important reason to define aspects of care needed to provide comprehensive quality care.

Nurses, the largest segment of health care providers, have an opportunity to enhance

patient care and affect the economics of the health care delivery system by increasing

compliance among patients (Simons, 1992).









Nonjudgmental/Ethical Perspective of Compliance

It is important for the reader to understand that compliance is generally used as a

nonjudgmental concept. It is not used to connote fault or to be interpreted as judgmental.

The reader should not perceive that a compliant patient is "good" or that a noncompliant

patient is "bad." In any one situation, a number of environmental factors and individuals,

including the patient and the health care worker, influence compliance. Likewise, the

reader should not perceive compliance as something a patient must be. An individual in

our society has the right to refuse to follow health advice in all but a few legally defined

situations. Compliance is a choice an individual has the freedom to make.

The term compliance is used in this study from a nonjudgmental perspective to

keep important ethical and social issues in the forefront of compliance research and

management (Haynes, Taylor & Sackett, 1979). The focus of this study is on ethical

compliance. Specifically, this study was built on the following assumptions about the

patients' conditions (Sackett & Haynes, 1976):

1. The diagnosis was correct;

2. The prescribed therapy would do more good than harm; and

3. The patient was an informed willing partner in the execution of all efforts designed to
alter compliance behavior.

Operationalizations of the Concept: Compliance

Generally, compliance is measured by one of two approaches: Direct or Indirect.

Direct measures, including results of lab tests (e.g., blood and urine, weight, etc.) are

essential but not without difficulties. From the positive perspective, direct measures tend

to be more objective and offer methods of assessing compliance without the patient being









aware that compliance is being assessed. For example, a patient may not be aware that the

presence of a medication would appear in a urinalysis. Gordis (1979) cautioned

researchers to be aware of the two major limitations of direct measures of compliance:

sensitivity of tests and specificity of detection and subjective judgments must be used to

determine how to define or classify a patient as compliant or noncomplaint on the basis of

test results.

Indirect methods include therapeutic or preventive outcome, such as keeping

appointments, opinion of the health care provider, opinion of the patient, filling a

prescription and pill count. While the use of the therapeutic or preventive outcome may

seem obvious, Gordis (1979) suggested that outcomes are best considered indirect

because outcomes may be affected by factors other than the prescribed regimen. For

example, a person with multiple medications may achieve a positive outcome because of a

medication other than the one prescribed. Similarly, other external factors, such as

socioeconomic and cultural variables may affect the outcome.

One of the more widely used methods of measuring compliance is interviewing the

patient and/or health care provider. Since there is little or no evidence that complying

patients misrepresent themselves as noncompliers or that noncompliers misrepresent

themselves as compliers, Gordis (1979) concluded that while there are serious questions

of the validity of patients' opinions as measures of compliance, patients' opinions are

useful indicators of compliance, especially when the objective is to identify noncompliers.

Rand and Weeks (1998) reported that patient self-reports were highly accurate and

probably a necessity in most studies.









Physician (health care provider) interviews have also been used to assess

compliance. Generally, findings on physician interviews suggest that the physician's

estimate of patient compliance is of very limited value in research (Gordis, 1979). Rand

and Weeks (1998) concluded that even nurse practitioners were not good judges of

patient adherence.

Managing Compliance

Most authors agree that managing compliance requires a multi-faceted approach.

Becker & Maiman's (1980) review of existing theory and research led them to recommend

the following ten interventions for health care workers:

1. Improving patients' level of information concerning the specifics of their regimens,
reinforcing essential points with review, discussion and written instructions, and
emphasizing the importance of the therapeutic plan.

2. Taking clinically appropriate steps to reduce the cost, complexity, duration, and
amount of behavioral change required by the regimen and increasing the regimen's
convenience through "tailoring" and other approaches.

3. Obtaining a compliance-oriented history of the patient's prior experiences and present
health beliefs and, when necessary, employing strategies to modify those perceptions
likely to inhibit compliance.

4. Improving levels of patient satisfaction, particularly with the provider-patient
relationship.

5. Arranging for the continued monitoring of the patient's subsequent compliance with
treatment.

6. Increasing staff awareness of the magnitude and determinants of the noncompliance
phenomenon and attempting to develop an "active influence orientation" in each
member of the health care team.

7. Using such techniques as patient-provider contracts to involve therapeutic decisions in
the setting of treatment objectives and creating incentives (through rewards and
reinforcements) for achieving these objectives.

8. Arranging for as much continuity of provider (and other staff) as possible.










9. Establishing methods of supervising the patient, including involvement of the patient's
social support network.

10. Involving fully the assistance of all health care providers, assigning specific roles and
responsibilities for activities directed at improving adherence to treatment.

Research on Variables Related to Compliance

Although few studies have reported significant correlation between compliance

and demographics, disease features, and side effects (Fishman, Finney, Rapoff&

Christophersen, 1995), social and psychological factors have produced more significant

results. Cameron (1996) suggested five major areas of focus for research on the social and

psychological aspects of compliance. While these categories are not mutually exclusive,

they provide a useful framework for organizing previous research and developing focus

for future research:

1. Knowledge and understanding refers to patients' knowledge and understanding of
their health and/or disease;

2. Quality of interaction is the quality of the interaction between the patient and provider;

3. Social isolation and social support refers to the family environment and the
patient-provider partnership;

4. Health beliefs and attitudes are the beliefs and attitudes, or existing patient
predispositions, affecting health behavior and compliance; and

5. Illness and treatment is the severity, complexity, and duration of the medical and health
regimens.

Knowledge and Understanding

Although the results of research on knowledge and understanding are

contradictory, there is evidence that nurses and patients value knowledge and

understanding; nurses and patients benefit from training of nurses; and knowledge and









understanding are related to readmission rates and taking medications. Grant, Ferrell,

Rivera and Lee (1995) tested the effect of an educational program for nurses, not patients,

on readmissions for uncontrolled pain. The Pain Resource Training Program reduced the

number of patients readmitted for uncontrolled pain. Interestingly, while patients were not

the direct focus of the training, patients seemed to benefit from the nurses' training.

Vivian (1996) found that both nurses and patients had a strong belief in patient

education, supporting a pro-social, collaborative model of compliance. In addition,

Vivian's (1996) results revealed that most of the nurses' time was spent educating

patients. In a survey of nurses in Scotland, Thomson and Kohli (1997) found that most

(67%) agreed that health promotion (education) was an important function of the nurse

and that 60% were interested in developing their health promotion role in clinical care.

Donlevy and Peitruch (1996) reported efforts of a nursing quality improvement

program focused on educating patients and their family members about diet, medications,

activity restrictions and anatomy and physiology in hopes of improving compliance. While

the effects of the program were not statistically tested, the authors reported that 120

patients in the program had a readmission rate of only 2% with average charges per

readmission of $7,272.83 compared to $12,004.60 for nonteam patients. They also noted

that the program improved patient satisfaction scores.

Fitzgerald and Freedman (1994) conducted a case manager intervention study

using education materials and contacts related to patient information to study these

interventions in reducing readmission rates. Case managers mailed educational materials to

patients 24 hours after discharge and contacted patients within 5 days to review

educational materials. Intervention patients had more frequent visits to clinics post









discharge but there was no significant difference between groups in total readmissions.

Contacts for education, along with contacts for care and using protocols were ineffective

in reducing nonelective readmissions (Fitzgerald, 1994).

On the basis of a study of a neighborhood health clinic, Becker and Maiman (1979)

concluded that patients' lack of understanding or knowledge related to their prescribed

treatments) was an important contributor to compliance. Lack of knowledge and

understanding was found in patients' knowing the purpose of their prescribed medications,

their prescribed dosages, how often to take the medications, and how long to take their

medications. Overall, 73% of the patients, who were able to correctly describe their

doctor's instructions, actually complied with the prescribed regimen. Only 16% of the

patients, who made one or more mistakes about their doctor's instructions, followed the

prescribed regimen. Mulaik (1992), based on a study of 11 triads, each composed of a

noncompliant schizophrenic patient, a family member and a primary nurse, concluded that

patients and families could benefit from more knowledge of the disease, treatment, signs

and symptoms.

The results of Becker and Maiman's (1980) review of 14 different studies on

knowledge and understanding were less conclusive. However, they did conclude that

providing knowledge to patients who wish to comply but do not have sufficient

information, would contribute to compliance and providing less motivated patients with

knowledge and information would not contribute to compliance.

Haynes et al. (1976) compared and contrasted 16 educational strategy studies to

20 behavioral studies. They concluded that using both educational and behavioral

strategies improved compliance better than using educational strategies alone.









Green (1979) cautioned that many of the studies of the effects of educational

strategies often had problems with the understanding and application of educational

principles rather than with flaws in the educational strategy. Green (1979) further

cautioned that studies and reviews did not define or use the term, education, in a

consistent manner. Because information exchange and behavioral approaches used

educational techniques, the distinction between educational and behavioral strategies was

not clear. Cameron (1996) attributed the contradictory results to the use of a broad range

of conceptual and operational definitions for knowledge and understanding.

Although the research on relationships among compliance and knowledge and

understanding seems to have produced contradictory results, the results suggested that

knowledge and understanding are related to compliance. The implications are that

adequate information should be provided to the patients and their caregivers and that

instructions and directions should be provided in both verbal and written formats using

language understood by the patients and their caregivers.

An interesting, and important consideration, in research on the effect of knowledge

and understanding on compliance is the concept of "intelligent noncompliance" (Becker &

Maiman, 1980). The health care provider and the health care system seems obligated to

assure the patient knows about and understands his/her condition. However, many would

argue from an ethical perspective that a patient has the right not to comply for reasons

important to him/herself









Quality of Interaction

Much of the research on quality of interaction (i.e., how well the patient and

provider communicate in a manner acceptable to both parties) has focused on the effect of

the behavior and attitude of the health care provider and the behavior and attitude of the

patient. Coe and Wessen (1965) and Becker and Maiman (1975) concluded that

impersonality, brevity of encounter and lack of communication, particularly of an

emotional nature, were related to noncompliance.

Gillum and Barsky (1974) found that two-thirds of physicians studied attributed

lack of compliance to the uncooperative nature of their patients, and one-fourth attributed

the lack of compliance to the attitudes and behaviors of the physicians themselves. Levy

(1988) found that satisfaction was related to compliance. Davis and von der Lippe (1968)

concluded that the physician's optimism and attitude toward the efficacy of the treatment

were related to compliance.

Haynes et al. (1976) found the degree of supervision, a component of the concept

of a therapeutic or contingency contract between patient and provider, was related to

compliance and corresponding degree of supervision. Similarly, Hare and Willcox (1967)

attributed the difference in compliance between day-patients and outpatients to the lack of

supervision among outpatients.

Overall, existing research suggests that providers who treat patients as active

participants in the treatment process and have favorable attitudes toward actively

influencing their patients were more likely to have patients with appropriate health

attitudes and compliance behaviors (Becker & Maiman, 1980). These conclusions,

however, overlook the patients' attitudes toward the treatment process and view the









patient-healthcare-worker interaction as a one-way model of communication. Patients'

attitudes toward being active participants and toward the treatment process are likely to

affect the relationship and compliance.

Social Isolation and Social Support

Social isolation and social support, conceptualized as the patient-provider

partnership and the family environment (Cameron, 1996) have been found to be related to

compliance. Porter (1969) found that living alone contributed to nonadherence among

general practice patients who were taking long-term chronic medication. Stuart and Davis

(1972) found that weight losers and lost-weight maintainers were more likely to

acknowledge help from other family members in cueing and reinforcement than nonlosers

and nonmaintainers. On the basis of their review of the literature, Baekeland and Lundwall

(1975) concluded that dropping out of treatment was associated with low social support.

Haynes' (1976) literature review led to the conclusion that family influence was

considerable with supportive families being associated with compliance in five of six

studies reviewed. Doherty and Baird (1983) concluded that there was reasonably strong

evidence linking family support and patient adherence. Haynes, Taylor and Sackett's

(1979) historical review identified a positive relationship between social support and

adherence. Ramsey (1989) stated that there is considerable evidence from a variety of

investigators, in different settings, using multiple illnesses with many research methods, to

show that the family plays a significant role in the process of caring for an individual.

Compliance research shows that the patient's larger context of family, friends, and

social support system offers a significant contribution to compliance, and therefore, to

improved health (Fishman, 1995). "Family," a concept Dunbar and Stunkard (1979)









suggested was one of the most promising areas for studies on compliance is discussed

more extensively in Chapter 2.

Health Beliefs and Attitudes

Health beliefs and attitudes, for most researchers, have been incorporated into a

health belief model (Rosenstock, 1966) that is also reviewed at length in Chapter 2.

Becker, Maiman, Kirscht, Haefner, Drachman & Taylor, 1979) concluded that, in general,

research in this area showed that patients are more likely to comply when they believe the

health care provider is correct; the illness can cause harm; and the prescribed therapy will

reduce the risk of death or improve the chance that their health will improve. The multi-

faceted nature of the health belief model approach offers strong potential for future

research on the prediction and understanding of compliance.

Illness and Treatment

The focus of this area of compliance research has been on the effects of the

complexity of the regimen, duration of the prescribed regimen, and requirements for

changes in lifestyle (Haynes et al., 1976). While it is often impossible or difficult to alter a

particular regimen, Becker (1974) found that reducing complexity, duration, costs, and

inconvenience could have a positive effect on compliance. Dunbar and Stunkard (1979)

viewed "the regimen itself' as the single most important determinant of compliance. Levy

(1988) found that when the degree of change in a patient's lifestyle was reduced,

compliance increased. While an illness and its treatment is an important factor in

understanding compliance, the potential of this area is limited by the inability to alter

particular regimens and control for type of illness. Compliance research on illness and

treatment within particular illnesses offers more potential than studying compliance across









illnesses and treatments. Meta-analysis of compliance research offers a potential solution

to this challenge.

Interaction of Health Beliefs and Attitudes and Family Interventions: A New Opportunity

Among the five areas of focus for compliance research (Knowledge and

understanding, Quality of interaction, Social isolation and social support, Health beliefs

and attitudes, and Illness and treatment), two seem to offer the strongest potential for

nursing: health beliefs and attitudes and social support. A better understanding of the

interaction between health beliefs and attitudes and family interventions should provide

nursing direction for the development of strategies to improve compliance.

Unfortunately, the research on patient interventions that include family is limited

(Saylor et al., 1990). LaGreca & Schuman (1995) criticized compliance researchers for

not including contextual, family and developmental variables. While current nursing

practice suggests that nurses consider the involvement of family an important contributor

to compliance, there is limited research to support the suggestion that nurses are including

the patient's family when planning nursing interventions (Frost, Brueggen & Mangan,

1997). Reasons for not using family in planned interventions are multiple and varied

including lack of time, inexperience and/or limited knowledge, short time frame, limited

resources, lack of continuity of care and lack of communication between healthcare

providers (Frost et al., 1997).

Another, less cited, but more obvious reason for not using family interventions is

their lack of importance for a particular patient. When a nurse does not believe an

intervention is important for a patient, she/he will not likely give full support to the

intervention. An examination of the importance of various family interventions to nurses









for individual patients may provide insight into this problem. Similarly, from a patient

quality-of-care perspective, an examination of the differences between what patients'

believe is important regarding family interventions and what they believe the nurse actually

does may shed light on the effect of family interventions on compliance.

Gap Analysis

Gap analysis (Dyck, 1996) offers a useful approach to the study of the differences

between the importance of family interventions to the nurse and the patient and the family

interventions nurse actually uses, as perceived by the nurse and the patient. This approach

is based on traditional attitude models (Fishbein, 1963; Rosenberg, 1956) and has been

used in patient satisfaction research (Brown & Swartz, 1989; Dyck, 1996). The basic

notion of gap analysis in quality of health care is that a high quality service effectively and

efficiently alleviates health problems to the satisfaction of the patient (Walters & Mangan,

1995). Janda, Wang and Rao (1996), in a study of importance and performance of dental

offerings, found significant differences between what was important to patients and what

was important to dentists. Level of quality of service was related to patients' perceptions

of the actual service compared to what they expected (Dyck, 1996; McAlexander,

Kaldenburg & Koenig, 1994; Parasuraman, Zeithaml & Berry, 1986).

Bowen, Stowe and Shumaker (1998) used a gap analysis of what guests at a hotel

said were important attributes and the guests' rating of the hotels' performance on those

attributes. They suggested that this gap provided direction for building customer loyalty

by identifying the attributes upon which the hotel should improve. In a health care setting,

Hill and McCrory (1997) compared the importance of various attributes to the perceptions

of the hospital's performance (very poor to very good) to identify the importance-









performance gaps related to length of stay in the hospital and whether the patient had

previously been a customer of the hospital.

In the context of family interventions, gap analysis suggests that patients are more

satisfied and thus more compliant when their expectations regarding family interventions

are met. Likewise, nurses are more supportive of family interventions when what they

believe is important to an individual patient fits their use of a family intervention.

The results of family interventions that meet both the patient's and nurse's

expectations should be a more satisfied patient and a more supportive nurse. The result of

a more satisfied patient and a more supportive nurse should be mutual respect and

cooperation. Mutual respect and cooperation should lead to compliance.

Problem Statement

The relationship between family interventions and compliance may be found in a

gap analysis of the difference between what is important to nurses and patients and how

well the nurses and patients perceive that the family intervention is being used. This study

was designed to address the following questions:

1. Is there a difference between patients' perceived importance of family nursing
interventions and nurses' perceived importance of the same family interventions in a
plan of care?

2. Is there a difference between the patients' perception of how well a nurse implements
family interventions and nurses' self-evaluation of implementing the same family
interventions?

3. Is the difference between the importance of family interventions to patients and
patients' ratings of their nurses' performance in implementing the interventions related
to how compliant the patients perceive themselves?

4. Is the difference between the importance of family interventions to nurses and nurses'
self-rating of their own performance in implementing the interventions related to how
compliant nurses perceive their patients?









5. Is the difference between the importance of family interventions to patients and
patients' ratings of their nurses' performance in implementing the interventions related
to patients' compliance as indicated by measured health indicators?

6. Is the difference between the importance of family interventions to nurses and the
nurses' self-rating of their own performance in implementing the interventions related
to patients' compliance as indicated by measured health indicators?

Significance for Nursing

Current research on compliance suggested the importance of involving family to

increase compliant behavior of patients. Research related to family interventions in nursing

practice, however, is limited (Craft & Willadsen, 1992). While nurses recognize the

importance of family and agree that psychosocial aspects of care are an important part of

their practice, there is limited nursing research demonstrating the actual use of family

interventions in clinical practice (Frost et al., 1997). Findings from this study were

expected to identify specific family nursing interventions that were:

1. Being used by nurse practitioners;

2. Perceived as important by both the patients and nurses;

3. Performed by nurses as identified by the patients and the nurses themselves; and

4. Related to compliance.

The identification of family interventions actually used in clinical practice was

expected to provide the foundation for the development of taxonomy of practical family

nursing interventions. Further, the identification of significant correlations between family

intervention gaps and compliance was expected to provide indicators of the effectiveness

of family interventions. The result would be the beginning of taxonomy of nursing family

interventions related to compliance.














CHAPTER 2
LITERATURE REVIEW

Health Belief Model

Among the various areas of compliance research, health beliefs and attitudes and social

support offer a strong potential for nursing. Health beliefs and attitudes and social support have

been conceptualized with the Health Belief Model (HBM) (Rosenstock, 1966). This multi-

faceted model provides a strong framework for the study of health beliefs and attitudes and

social support as they affect compliance (Doherty & Baird, 1983). An understanding of patients'

and nurses' beliefs and attitudes toward health care regimens and their attitudes toward the use of

family interventions should provide a better understanding of compliance and thereby facilitate

the development of nursing strategies to enhance compliance.

Components of the Health Belief Model

The Health Belief Model (HBM) (Rosentock, 1966) is a cognitive-motivational model

based on work from social psychologists in the 1950s working with a federal research program

to explore why people did not accept disease prevention strategies (obtaining immunizations) or

screening tests for early detection of preventable or initially asymptotic diseases. Becker and

colleagues (Becker, Drachman & Kirscht, 1974; Becker, Maiman, Kirscht, Haefner, Drachman

& Taylor, 1979) have done extensive refining and empirical testing of the HBM.

The essential components of the HBM are from the psychological and behavioral theories

hypothesizing that behavior is dependent on the "value" placed on a particular goal by an

individual and the individual's determination of the change that a given action will achieve that









"goal." In the context of health-related behavior (Clark & Becker, 1998), these

components are the desire to avoid disease/illness (or get well if already ill) and the

person's "belief' that a particular health behavior will prevent illness (or cure the person).

Together these two variables represent the individual's estimation of the threat of the

illness and the likelihood of being able to reduce the threat of the illness through some

action that the person takes (Schumaker et al., 1990). This approach is consistent with gap

analysis (Dyck, 1966). The gap is the difference between the threat and the likelihood of

being able to reduce the threat. In terms of family interventions, patients are hypothesized

to have different levels of value (importance) for different family interventions and

different levels of belief that their nurses actually performed the family intervention

(performance). Compliance is hypothesized to be related to how well the nurses'

performances fit the patients' expectations (the importance-performance gap).

This model proposes that patients' health beliefs and expectations affect the

likelihood that the patients will adhere to prescribed strategies. The beliefs, perceived

susceptibility, perceived severity, perceived benefits, and perceived barriers/costs

(Figure 2.1) and their structure have been supported by confirmatory factor analysis

(Weissfeld, Brock, Kirscht & Hawthorne, 1987).

Perceived Susceptibility

Perceived susceptibility is the extent to which patients believe they will acquire a disease, a

person's subjective perception of the risk of contracting a condition (Schumaker et al.,

1990). In the situation where the disease has been diagnosed, perceived susceptibility is

redefined to include estimates of re-susceptibility, belief in the diagnosis itself, and the

overall sense of susceptibility to an illness in general.











INDIVIDUAL PERCEPTIONS MODIFYING FACTORS LIKELIHOOD OF ACTION


Perceived benefits of
Demorahic Variables preventive action
(age, sex, race, ethnicity, etc.)
minus
Sociopscholoical Varibles Perceived barners to
preventive action




Perceived susceptibility to Disease "X"
Perceived Threatof
Disease "X" Likelihood ofTaking
Perceived Seiousness (Seveity) of Recommended Preventive
ase "X" Health Action





Cues to Actirc
Mass Media Campaigns
Advice fom others
Reminder postcard rom physician or dentist
lnes of family member or friend
Newspaper or magazine article





Figure 2-1. The Health Belief Model (Becker, Drachman & Kirscht, 1974).

Perceived Severity


The effects of an individual's perceptions, feelings, and concerns related to the


seriousness of getting a disease or leaving it untreated and the anticipated consequences of


the disease, including pain, loss of function or death as well as negative social


consequences on family and social relations, are referred to as "perceived severity"


(Shumaker et al., 1990). Essentially, perceived severity is the patient's assessment of


contracting an illness (Doherty & Baird, 1983). Higher levels of perceived severity are


more likely than lower levels of perceived severity to lead to compliant behavior.


Perceived Benefits


Perceived benefits refer to the positive outcomes of following a prescribed health


regimen or the feasibility and efficacy of following various actions (Doherty & Baird,









1983). While acceptance of personal susceptibility to a condition one thinks is serious may

lead to behavior, it does not define the particular action likely to be taken.

The specific action is dependent upon the perceived effectiveness (benefits) of the

actions available to reduce the threat of the disease or condition. A person threatened by a

disease or condition would not be expected to act on the health recommendation unless

they perceived the action to be effective, or beneficial (Schumaker et al., 1990).

Perceived Barriers/Costs

Perceived barriers and costs refer to the patient's perception of the disadvantages

of adhering to the regimen, the perceived negative aspects of following a particular health

regimen (Doherty & Baird, 1983). The barriers, or costs, are impediments to acting on a

recommended health action or behavior. Compliance is based upon a "cost/benefit"

analysis of the perceived positive effects against the perceived negative effects, including

expense, dangerous due to side effects, inconvenience, and time required.

Interaction of Components

Essentially, the Health Belief Model proposes that individuals will comply with

recommended health regimens when the individuals believe that they are susceptible to the

disease or illness, that the results or consequences of the disease/illness or noncompliance

are serious, that the action recommended is beneficial or effective in reducing the risk or

seriousness of the illness/disease, and that the barriers/costs of action do not exceed the

benefits (Schumaker et al., 1990).

These components of the HBM are hypothesized to interact to affect health

behavior. The combination of susceptibility and severity levels provides the individual the









energy or necessary force for action. The comparison of perceived benefits to perceived

barriers provides direction for specific behavior.

Cues to Behavior

The HBM also includes "cues to action, stimuli that "trigger" the action, or

behavior, by the individual. This trigger makes individuals consciously aware of their

feelings about the disease or threat to their state of health (Haynes, Taylor & Sackett,

1979). The cues to action may be internal or external. Internal cues include signs or

symptoms of the disease or state of health. External cues include mass media

communications or campaigns such as reminder literature, or interpersonal interactions

(Schumaker et al., 1990). Demographic and psychosocial variables are in the HBM as

they affect an individual's perceived threat, perceived benefits, and perceived barriers

(Becker, Maiman, Kirscht, Haefner, Drachman & Taylor, 1979).

Evaluation of the Health Belief Model

Early research on the health belief model suggested that the relationship between

health beliefs and compliance may be bi-directional, with health beliefs becoming

congruent with actual compliance as well as the reverse of this (Becker et al., 1979). Janz

and Becker's (1984) analysis of 46 different Health Belief Model studies found a

"significance ratio" for each health belief model dimension. In most cases, each health

belief model dimension was significant. The significance ratio orderings for the four

dimensions were (1) barriers (89%), (2) susceptibility (81%), (3) benefits (78%), and

severity (65%). In concluding their evaluation of the research, Janz and Becker (1984)

noted that the health belief model was limited to accounting for the variance in individuals'

health-related behaviors that can be attributed to beliefs and attitudes. Janz and Becker









(1984) concluded that the health belief model did not account for habitual behaviors

(cigarette smoking), economic factors and/or environmental factors that may prevent

compliant behavior. Dunbar-Jacob, Schlenk, Burke and Matthews' (1998) review of

cognitive-motivational predictors related to adherence produced similar conclusions. They

found strong evidence that susceptibility, perceived severity, perceived benefits, and

perceived barriers were related to compliance.

The HBM provided a theoretical framework for this study. The model suggested

that nursing family interventions, valued by patients and performed by their nurses, should

affect individuals' psychosociological factors and cues to action which in turn should

affect patients' perceived susceptibility, perceived severity, perceived benefits, and

perceived barriers/costs. The net effect was expected to be compliant patients.

Family and Nursing

Family has long been a topic of research in many disciplines including

anthropology, sociology and psychology (Lavee & Dollahite, 1991). This interest stems

from the long recognized belief that family is one of the most important contextual

influences on human growth and development (Murphy, 1986). The inclusion of family in

nursing research occurs primarily in community health, midwifery, and psychiatric settings

(Mirr, 1992). Currently, the American Nurses' Association (ANA), the American

Association of Critical Care Nurses (AACN), and the Association of Operating Room

Nurses (AORN) include family in their standards of care.

Nursing research has focused on a variety of family issues, including family

responses) to illness, disease states or health conditions, health maintenance, and family

coping characteristics, family transition states and new family structures, for example,









"blended and intergenerational" families, single parent families, public policy affecting

family, and cross-cultural family research (Murphy, 1986, p. 172). Fisher and Ransom's

(1995) research as part of the California Family Health Project is a classical example of

cross discipline family research. This study produced a typology of families that were

significantly different on health and other well-being measures. This typology of family

provides a framework for explaining health behavior and developing interventions to

promote health-seeking behaviors in families.

Family Care Giving: Theory and Practice

Family care giving, providing assistance and support to one member in the family

by another, is a prevalent and regular part of current family research. While this is not a

new phenomenon, there is a growing acknowledgement among providers and researchers

that recent demographic, economic, and social changes will make family care giving a

public and health policy issue of ever increasing importance (Biegel & Schultz, 1999).

Family care giving is another example of a family theory concept, requiring the attention

of multiple disciplines and professions, including nursing. Currently, care giving

intervention programs encompass various modalities and show the need for the

development and testing of family interventions across related professions and disciplines.

Historically, family has been part of nursing since Nightingale first identified the

concept of nursing. Early in its development, nursing adopted theories of family

functioning from sociology and psychology (Whall, 1980). Nursing practice has

consistently expected families to play a participatory role in the health and caring for sick

family members (Hiestand, 1982). More recently, nursing theory and research has

suggested that patients must be viewed in their family context (Murphy, 1986). As health









care evolves in ambulatory, home, and long-term care, the importance of family will

increase (Craft & Willadsen, 1992). "Nursing's Agenda for Health Care Reform"

published by the American Nurses Association (1991) specifically identified the need for

care delivery in schools, workplaces and homes.

Although the early work in family by nurse scholars and researchers incorporated

family theories from related disciplines, various nurse theorists, including Neuman, King,

Rogers and Roy, have incorporated family as an important and distinct unit in their nursing

theories (Craft & Willadsen, 1992). Other nurse theorists, such as Newman, Roberts and

Black, have applied their work to families by viewing the family as the patient (Gilliss,

1991).

Nursing interventions related to family are needed now and will be of increasing

need in the future (Craft & Willadsen, 1992). Gilliss (1991), concluding that nursing must

move beyond the declaration of intentions to include family in nursing practice to the

actual demonstration of family nursing and outcomes, proposed eight areas of nursing and

family that needed further development in theory, research and practice:

1. The examination and definition of family nursing;

2. The determination of whether a family nurse is a generalist or a specialist practicing
nursing;

3. The preparation of the specialist practice in family nursing;

4. The isolation and identification of the phenomena of interest in family nursing,
focusing on family as the unit, and what is empirically based;

5. The accumulation of knowledge about families and related nursing practice across all
areas in nursing;

6. The establishment of priorities for research in family nursing;









7. The identification of the significant outcomes of family nursing practice; and

8. The evaluation of clinical work and research data for policy implications.

Compliance and Nursing Family Interventions

Historical reviews, such as Haynes, Taylor and Sackett (1979) and Doherty and

Baird (1983), concluded that there was reasonably strong research evidence linking family

support and patient adherence. Ramsey (1989) reported that there was considerable

evidence from a variety of investigators, in different settings, using multiple illnesses with

many research methods, to demonstrate that the family plays a significant role in the

process of caring for an individual. Fishman (1995) concluded that treating patients in the

larger context of the patient's family, friends, and social support system offered a

significant contribution to compliance and to improved health. Generally, these studies

examined the effects of family interventions (psychosocial support) on the individual

patient in the context of family, the effects on and the effects of the family itself, as a unit

analysis, and the effects of the family on family interventions.

Effects of Family Interventions on the Individual Patient: Patient in Context of Family

Findings from research on the effects of family interventions on the individual

patient provided evidence that family interventions are related to improvements in the

health of the individual patient. To understand family interventions in terms of benefit to

the individual patient, Droogan and Brannigan (1997) conducted a meta-analysis of twelve

studies incorporating psychosocial family-based interventions to improve the relapse rate

of schizophrenia patients. They concluded that the rate of relapse could be reduced by

psychosocial interventions such as constructing alliances with relatives, reducing adverse

family atmosphere, reducing expressions of anger and guilt, maintaining reasonable









expectations of the ill family member, encouraging relatives to set and keep appropriate

limits, and enhancing the family's capacity to anticipate and problem solve. On the basis of

their study of 157 youths with insulin-dependent diabetes mellitus, Hanson, De Guire,

Schinkel and Kolterman (1995) concluded that a family-centered approach to care

contributed to desired health outcomes in the youths while increasing positive family

functioning and decreasing levels of family-life stress.

Effects of Family Interventions on the Family

Existing research revealed that family interventions have positive effects on

families. From the results of their qualitative study designed to examine changes in families

during times when a family member was ill, Johnson, Craft, Titiler, Halm, Kleiber,

Montogmery, Megivern, Nicholson and Buckwalter (1995) concluded that nurses'

implementing family-centered interventions, such as including identification of support

systems and initiating role supplementation programs, was associated with the decline in

role strain and role overload among family members. In a more recent study, Powers,

Goldstein, Plank Thomas and Conkright (2000) tested the effects of interactive sessions

designed to encourage and elicit patient's and their families' active involvement in

providing and deciding the needed plan of care. Prior to implementation of the "plan of

care sessions," the plan of care was reviewed with family members only 50% of the time.

After the implementation of the sessions, plans of care were reviewed with family

members more than 90% of the time. Patient, family, and nurse interviews revealed that

the plans-of-care sessions encouraged patient and family involvement in planning and

decision leading to increased patient satisfaction and positive outcomes in the patient

(Powers et al., 2000).









Effects of the Family on Family Interventions

Most studies treated family interventions as the stimulus for change, but some

researchers examined the effect of the family itself on family interventions. Fink (1995)

studied the effect of family resources, including social support and internal family system,

family demands, and family well-being. Results showed increased family strain when

caring for an ill family member and suggested that outside services (counseling) could help

a family cope with the complex situation of having an ill family member. Ford-Gilboe

(1997) provided an excellent example of the effects of the nature of the family. The results

of the Ford-Gilboe (1997) study provided evidence that family pride, family cohesion,

network support, community support, and family income taken together were predictive

of the extent of family participation in health-related problem solving and goal attainment

behaviors (Ford-Gilboe, 1997).

Family Interventions

Although current research shows positive effects of family interventions, research

on the development and testing of family interventions is limited. Published interventions

related to family may not mirror the current practice of nursing (Craft & Willadsen, 1992).

Determination of family related outcomes and measurements in research was encouraged

at a meeting sponsored by the National Center for Nursing Research in 1991. While it

might be accepted that nurses should and actually use psychosocial (family) interventions,

whether nurses consistently and actually include the family in the treatment plan is unclear.

The results of Chesla's (1996) interpretive phenomenological study of 130 nurses

caring for families in critical care units provided evidence of the need for reciprocal

knowledge transfer between nurses working in family practice and nurses skilled and









knowledgeable about family interventions. Frost, Brueggen, and Mangan (1997)

conducted a survey of nurses to examine the gap between theoretical literature and clinical

nursing. The results showed that nurses thought each psychosocial need identified was

"quite important" when giving care to cancer patients and their families; yet the nurses

believed that they had only a "moderate skill level" for providing interventions for these

needs (Frost et al., 1997). Nursing interventions related to family will continue to be

required for nursing practice in the future. These specific interventions and their validation

and testing are critical to the nursing profession and healthcare consumers (Craft &

Willadsen, 1992).

While many nurses accept and embrace models and theories that include family

participation, there is limited research on patient interventions that include family (Saylor,

Elksnin, Farah & Pope, 1990). Current nursing practice shows that nurses view

involvement of family, as it relates to the psychosocial aspect of care of their patient, as an

important aspect to assist the patient in being compliant. However, there is limited

quantitative research to validate that nurses are including patient's family when planning

nursing interventions (Frost et al., 1997). Robinson's (1996) qualitative study is typical of

most research in this area. Robinson's (1996) results suggested four specific relational

nursing interventions the nurse as the curious listener, the nurse as the compassionate

stranger, the nurse as the nonjudgmental collaborator, and the nurse as the mirror of

family strengths. The study revealed that the families in the study believed that nurses'

relational interventions were helpful to families caring for an ill family member (Robinson,

1996). While informative, these results were not generalizable.









Nurses have a variety of reasons for not including family in planned interventions,

including lack of time, inexperience and/or limited knowledge, short time frame, limited

resources, lack of continuity of care, and lack of communication between healthcare

providers (Frost et al., 1997). Another, less cited, but more obvious reason for not using

family interventions is their lack of importance to a particular patient. When a nurse does

not believe an intervention is important, she/he will not likely give full support to the

intervention. This lack of support or follow-up on an intervention will likely suggest to the

patient that compliance is not so important. An examination of the importance of various

family interventions to nurses for individual patients may provide insight into this problem.

Similarly, from a patient quality of care perspective, an examination of the differences

between what patients expect regarding family interventions and what they receive from

their nurses may shed light on the effect of family interventions on compliance.

Historically, family has been perceived to be an integral part of nursing. However,

in acute care settings, nursing care remains focused on individuals rather than the inclusion

of patients and their families (Mirr, 1992). The importance for all nurses, in all settings, to

recognize the importance of families in the care of patients is essential in all of today's

health care settings.

Currently, discussion on compliance focuses on the expanded view that includes

client participation in health care decision, as well as the trend toward health promotion

and wellness, rather than the more traditional view of a prescribed regimen by the

healthcare provider. This view recognizes that compliance is not the sole responsibility of

the patient, but a "by-product" of the interaction between the patient and their healthcare

provider (Hays & DiMatteo, 1989). The most cited predictors of patient compliance are









related to a person's health beliefs and expectations, including Rosenstock's Health Belief

Model (1966). Although research has been done to identify determinants of and ways to

measure compliance, little has been done in the area of developing specific strategies and

interventions designed to assist clients in following their healthcare regimens. Nurses are

in a unique position to offer interventions to patients that willenhance a client's ability to

follow their prescribed regimens (Simons, 1992).

To address the lack of quantitative research on nursing family interventions, Craft

and Willadsen (1992) surveyed nurses to determine the specific family interventions nurses

were using. Using systems theory and an ecologic framework, Craft and Willadsen (1992)

defined family as a social context of two or more people characterized by ". mutual

attachment, caring, long-term commitment, and responsibility to provide individual

growth, supportive relationships, health of members and of the unit, and maintenance of

the organization and system during constant individual, family and societal change"

(p. 519).

Craft and Willadsen (1992) attempted to identify the nurse family interventions

actually being used in a survey of nurses. They constructed their questionnaire on the basis

of an extensive literature review and pilot testing of their instrument among educators,

researchers and clinical specialists to assure content validity of the family interventions.

One hundred and thirty nurse experts on interventions related to family were surveyed.

These nurse experts were from diverse health care settings and levels of nurse education

with specialty areas including education, administration, ambulatory care, pediatrics,

obstetrics, family health, rehabilitation, general medical and surgical nursing, and

specialized areas such as Alzheimer and neonatal intensive care units.









The survey instrument included intervention labels, their conceptual definitions,

and their defining activities and questions regarding the nurses' practice experience and

education. Nurse respondents rated activities for each intervention using a Likert-scale of

1 for "not at all characteristic" to 5 for "very characteristic" of their nursing practice.

Findings clearly showed that nursing interventions related to family could be specified

in a way that has universal meaning to nurses in family nursing. In addition, Craft and

Willadsen (1992) identified nine general types of specific family nursing interventions:

1. Family support with promotion of family interests and goals;

2. Family process maintenance with minimization of family process disruptive effects;

3. Family integrity promotion with promotion of family cohesion and unity;

4. Family involvement with family participation in the emotional and physical care of the
patient;

5. Family mobilization with utilization of family strengths to influence patient's health in a
positive direction;

6. Caregiver support with provision of the necessary information, advocacy and support
to facilitate primary patient care by people other than health care professionals;

7. Family therapy with interaction with the family as a change agent to move the family
toward a more productive way of living;

8. Sibling support with promotion of interests of siblings when a brother or sister
experiences an illness; and

9. Parent education with provision of assistance to help parents understand and help their
adolescent children.

Need for Research on Family Interventions

Craft and Willadsen (1992) concluded that their research was "a beginning" for

nursing research on family interventions and that further research was needed. An

important "next" step is to understand the relationship between the interventions and









compliance. The interventions clearly fit in the psychosociological and social support

aspects of the Health Belief Model. However, the importance and delivery of these

interventions as perceived by nurses and their patients is not known. When a nurse does

not believe an intervention is important, she/he will not likely give full support to the

intervention. This lack of support or follow-up on an intervention will likely suggest to the

patient that compliance is not so important. Similarly, from a patient quality of care

perspective, an examination of the differences between what patients' believe is important

regarding family interventions and what they believe the nurse actually does may shed light

on the effect of family interventions on compliance. A useful approach to the study of the

differences between the importance of family to the nurse and the patient and the family

interventions nurses actually use, as perceived by the nurse and the patient, is gap analysis

(Dyck, 1996).

Gap Analysis

Gap theory (Gronoss, 1982; Parasuraman et al., 1985) proposes that consumers'

perceptions of service quality result from comparing expectations prior to receiving the

service and their actual experience of the service. If consumer expectations are met,

service quality is perceived to be satisfactory. The gap is simply the perceptions minus

expectations (P E). This conceptualization is essentially the foundation of the Health

Belief Model (HBM). The HBM proposes that health behavior (compliance) is affected by

the "value" placed on a particular goal by an individual and the individual's determination

of the change that a given action will achieve that "goal" (Rosenstock, 1966).

The P E perspective has been challenged by Cronin and Taylor (1992 and 1994)

and Teas (1993 and 1994) arguing that an unweighted performance-based measure is









more valid than the P E approach. Further, Cronin and Taylor (1992 and 1994)

questioned the validity of measuring expectations contemporaneously with perceptions

(i.e., after a service has been consumed rather than before) and the validity of measuring

the expectations of consumers who have had no prior experience of a service. Carman

(1990) argued that quality is an attitude that may be expressed as: Q = Y Ii (Pi-Ei) where

I is the importance of attribute i; P is the perception of attribute i; and E is the expectation

of service attribute i. The sum is over the total number of relevant service attributes.

Carman (1990) suggested that for most service providers, the importance of a particular

attribute is more relevant than its expected level. Furthermore, when the service is new, E

may be set to zero. Similarly, Hill and McCrory (1997) suggested that expectations may

be inferred from importance ratings. If a consumer believes a service attribute is important,

the consumer should expect the quality of that attribute to be good. For these reasons, this

study used the P-I (performance importance) approach. The measures will be taken after

the patient has had sufficient contact with the nurse practitioner (service). Conversely, to

enhance the interpretation of the data, this study used the more general gap approach of

expectations minus performance or I P rather than the P I approach. With the I P

approach, the difference indicates performance has not met importance while in the P I

approach the difference indicates performance has exceeded importance. This is the

mathematical representation recommended by Parasuraman et al. (1985).

Gap analysis can be used to explain the effectiveness of family interventions

(Figure 2-2). Nurses and patients have expectations of family interventions. Patients'

levels of satisfaction are dependent upon how well the nurses' performance meets or

exceeds their expectations. Likewise, levels of nurses' satisfaction are dependent on how









well the nurses' performance meets or exceeds the nurses' own expectations. Over time,

as the nurses' and patients' expectations are confirmed, levels of satisfaction are affected.

As levels of expectation are confirmed, satisfaction grows or is reinforced. As

expectations are disconfirmed, satisfaction declines, or dissatisfaction increases. Satisfied

patients and nurses have positive attitudes toward family interventions. These positive

attitudes toward the use of family interventions contribute to compliance because both

nurses' and patients' are acting upon interventions in which they both believe. In summary

(Figure 2-2), the result of family interventions that meet both the patient's and nurse's

expectations should be patients and nurses who are satisfied with nursing family

interventions. Satisfaction with the nursing family intervention leads to compliance and a

nurse-patient relationship of mutual respect and cooperation.

Hypotheses

The review of theory and research on compliance, the Health Belief Model, nursing

family interventions and gap analysis led to the development of six hypotheses tested by

this study:

1. Importance of Family Interventions: There will be no difference between patients'
perceived importance of family nursing interventions and nurses' perceived importance
of the same family interventions in a plan of care.

2. Performance of implementing family interventions: There will be no difference
between the patients' perception of how well a nurse implements family interventions
and the nurses' self-evaluation of implementing the same family interventions.

3. Patients' gap (importance performance) = patients' perceived compliance: The
difference between the importance of family interventions to patients and patients'
ratings of their nurse's performance in implementing the interventions will be related
to how compliant the patients perceive themselves to be.






36

4. Nurses' gap (importance performance) = nurses' perception of patients' compliance:
The difference between the importance of a family intervention to nurses and nurses'
self-ratings of their own performance in implementing the interventions will be related
to how compliant nurses rates their patients.

5. Patients' gap (importance performance) = patients' measured compliance: The
difference between the importance of family interventions to patients and patients'
ratings of their nurse's performance in implementing the intervention will be related to
patients' compliance as indicated by measured health indicators.

6. Nurses' gap (importance performance) = patients' measured compliance: The
difference between the importance of family interventions to nurses and nurses' self-
rating of their own performance in implementing the intervention will be related to
patients' compliance as indicated by measured health indicators.








37










u
o







4-.
U











o
0








0


I-
















C4

-d
0
0I
I
















mc


Qi
<-i-

0;














CHAPTER 3
METHODOLOGY


Purpose of the Study

An expostfacto/correlational design (Polit & Hungler, 1999) was used to

examine the differences between patients' and nurses' perceptions of importance and

nurses' performance of selected family interventions and the relationship among

importance and performance gaps for both patients and nurses and direct and in-direct

measures of compliance. The major limitation of this design, relative to experimental and

quasi-experimental designs, is its ability to reveal casual relationships (Polit & Hungler,

1999). Conversely, the purpose of this study was to examine relationships between a

number of variables in a non-artificial setting. This design is well suited to this objective

(Polit & Hungler, 1999). Data, collected through a self-administered personal survey of

nurse practitioners and their patients conducted between June 1999 and October 1999,

were analyzed using the Statistical Package for the Social Sciences (SPSS, 1990). The

first step in data entry was to assure that all patients had completed the questionnaire.

Fifteen patients and/or the nurse practitioner indicated that the patient had no family or

other social support and therefore did not meet this study's criteria. These patients and

their corresponding nurse questionnaires were not included in the data analysis. This

produced a final sample of 169 patients and 10 nurse practitioners. To assure accuracy of

data entry, entered numerical responses were checked against original questionnaires.









Instrumentation: Family Interventions and Their Gaps. The Independent Variables

After a review of the literature and an elimination of duplicate interventions, over

225 possible family interventions for nurses were identified (Craft & Willadsen, 1992;

Frost et al., 1997; Snyder, 1995). These 225 interventions provided the initial inventory of

family interventions for nurses to be used in this study. The Craft and Willadsen (1992)

inventory was the most comprehensive and best structured taxonomy of family

interventions. Their inventory included 9 defining family interventions (Family Support,

Family Process Maintenance, Family Integrity Promotion, Family Involvement, Family

Mobilization, Family Therapy, Care Giver Support, Sibling Support, and Parent

Education) and their accompanying activities.

To reduce the identified family interventions to a manageable number for the

questionnaire, interventions were included according to the following three criteria:

1. Family interventions must be relevant to this study's patient sample;

2. The interventions must be attributable by the patient to the nurse; and

3. The intervention content validity (ICV) scores from both surveys must average greater
than .80 and be among the top three rated interventions.

Relevant to the Patient Sample

Because this study focused on adults with cardiovascular disease and/or diabetes in

an outpatient setting, non-related family interventions were deleted. Family interventions

related to sibling support and parent education (Craft & Willadsen, 1992) were excluded.

Likewise, family interventions related to hospitalization and/or deaths were excluded. This

reduced the Craft and Willadsen (1992) family interventions to a set of six defining

interventions.









Interventions Attributable by the Patient to the Nurse

Family interventions not directly attributable to the nurse's actions) were

excluded. While Feetham (1984) and Craft and Willadsen (1992) have noted that that it is

possible for a nurse's assessment to lead to a family's taking productive actions, such

assessments were excluded. For example, a question, such as "What changes have

occurred in your family?", provides assessment data and may initiate family self-

examination and family problem solving. However, such a serendipitous family behavior

may occur without the patient and/or family realizing the action is in response to the

nurse's assessment question. The family behavior is productive, but it is not necessarily

attributable by the patient to the nurse. Since this study focused on patients' perceptions

of nurse behaviors, assessments were excluded. Interventions suggesting "identify" or

"determine" were excluded. Only family interventions considered directly attributable by

the patient to the nurse were included.

Because the focus of this study was on patients' perceptions of nurse behavior, it

was not considered appropriate to ask patients to rate nurse actions that patients would

not have the opportunity to observe and rate. Using this criterion, family interventions

likely to be known only by the nurse, such as "Incorporate therapeutic use of self as nurse

change agent," were excluded. Family interventions between the nurse and family

members or caregivers that might not be known by the patient, such as "Explore with the

caregiver his or her strengths and weaknesses," were excluded from the family

intervention inventory.









Intervention Content Validity (ICV) Scores

Using the first two criteria, family interventions were reduced to a list of over 100

specific actions. All of these were represented in the Craft and Willadsen (1992) inventory.

To reduce the number of interventions in this list, the following rules were used with the

intervention content validity (ICV) scores reported by Craft and Willadsen (1992):

1. Use intervention activities whose combined ICV scores from both surveys averaged
.80 or greater.

2. Use the top three rated interventions from each of the six defining family interventions,
family support, family process maintenance, family integrity promotion, family
involvement, family mobilization and family therapy.

The resulting inventory of family interventions contained 15 interventions for 6

defining family interventions (Table 3-1). These were the family interventions selected for

the gap analysis for this study. Questionnaire instructions and family intervention

descriptions were written at a Flesch-Kincaid reading grade level 6.7 (Microsoft Word,

1995). The nurse practitioner questionnaire is presented in Appendix A and the patient

questionnaire is presented in Appendix B.

Measurement of the Importance and Performance of Family Interventions, The
Independent Variables

Nurses and patients were asked to rate the importance and performance of family

interventions on 9-point scales. Importance of family interventions was measured on a 9-

point "Not at all Important" to "Very Important" scale. Performance was measured on a

9-point "Never" to "Always" scale. The specific measures are shown in the nurses'

questionnaire (Appendix A) and the patients' questionnaire (Appendix B).









Table 3-1: Family Interventions

Family Support Intervention
1. Listen to concerns, feelings and questions of the patient's family
2. Respect and support patient's family's ways of coping
3. Include family members in decision making regarding patient care when appropriate

Family Process Maintenance Intervention
1. Discuss strategies for normalizing family life with family members

Family Integrity Promotion Intervention
1. Establish trusting relationship between nurse practitioner and family members
2. Respect the privacy of individual family members
3. Encourage open communication between family members

Family Involvement Intervention
1. Encourage family members to keep or maintain family relationships as appropriate
2. Provide information to family members about patient in accordance with patient
preference
3. Facilitate family understanding of the medical aspects of illness

Family Mobilization Intervention
1. Teach family members ways for health recovery and health maintenance
2. Discuss with patient's family members how strengths and available resources can be
used to enhance the patient's health
3. Support family efforts to promote patient's health or management of patient's
condition when appropriate

Family Therapy Intervention
1. Encourage family members to recognize and reward positive patient behaviors
2. Facilitate family discussion, as members prioritize data and select the most immediate
family issue to address

Factor Analysis of Family Intervention Items

To reduce Type I Error caused by repeated testing across the 15 family

interventions (Blalock, 1972) as well as to examine the underlying structure of the family

interventions to overcome challenges of multicollinearity, factor analysis was used to

identify independent dimensions (combinations) of family interventions and the dependent

variables (compliance measures). The results of the factor analyses were used to transform









the original data into statistically independent factors as well as to identify variables that

could be used together (summed) in a reliable measure. While representing the original

variables, the transformed factor variables were weighted and standardized by factor

loadings thereby producing new variables with different metrics than the original raw data.

The result is that interpretations can be made to the original theoretical concepts but not

to the original scaled values obtained as responses to the questionnaire (Norusis, 1990a).

Separate analyses were conducted on the nurses' importance ratings, the nurses'

performance ratings, the patients' importance ratings, the patients' performance ratings,

the combined nurses' and patients' importance ratings, and the combined nurses' and

patients' performance ratings.

Significance of factor loadings was determined using a criterion recommended by

Schlinger (1969). The criterion was 2.58 (1/ -n) where n is the number of subjects. In this

case, with an n of 169, to be significant a factor loading had to be at least .198 (rounded to

.20) to be significant.

If items were significantly loaded on two or more factors, Humphrey's Rule

(Fruchter, 1954) was used:

1. Square the two significant loadings.

2. Divide the larger squared factor loading by the smaller.

3. If the result of Step 2 is 1.5 or greater, consider the larger loading the more significant.
The value of 1.5 means that the larger loading accounts for 1V/ as much variance as
the smaller. This is similar to an F test which divides one variance by another: where
nl = 50, n2 = 50, F = 1.50 is significant at the .75 level of significance.

4. If the result of Step 2 is less than 1.5, the loadings are confounded. In other words, the
item is not significantly loaded on any factor.









The results of these analyses suggested there were two factors underlying the

importance and performance ratings. Based upon these findings, separate factor analyses

with varimax rotation were completed to identify these two factors such that they were

statistically independent variables.

The results of factor analysis with varimax rotation for importance ratings are

presented in Table 3-2. The initial, un-rotated, solution provided evidence of two factors.

The first factor, as expected, accounted for most of the variance with an eigenvalue

greater than one (Table 3-2). The second factor produced eigenvalues of 1.2, .5 and .6.

While the .5 and .6 values are less than the typical 1.0 default eigenvalue (Norusis, 1990a),

the results of the other factor analysis suggested the default should be ignored. In addition,

the size of the factor loadings and clarity of factors supported this decision.

Across the nurse, patient and combined factor analyses, the items were loaded

fairly consistently with some confounded loadings. The following items were judged to

compose each importance factor:

Factor I (8 items)
1. Listens to concerns, feelings and questions of the patient's family

2. Respect and support the patient's family's ways of coping

3. Include family members in decision making regarding patient care when appropriate

4. Establish trusting relationship between nurse practitioner and family members

5. Respect the privacy of individual family members

6. Provide information to family members about patient in accordance with patient
preference

7. Facilitate understanding of the medical aspects of illness

8. Teach family members ways for health recovery and health maintenance









Factor II (7 items)
1. Discuss strategies for normalizing family life with family members

2. Encourage open communication between family members

3. Encourage family members to keep or maintain family relationships as appropriate

4. Discuss with patient's family members how strengths and available resources can be
used to enhance patient's health

5. Support family efforts to promote patient's health or management of patient's
condition when appropriate

6. Encourage family members to recognize and reward positive patient behaviors

7. Facilitate family discussion, as members prioritize data and select the most immediate
family issue to address

The factor analyses of the performance ratings produced similar results to the

factor analyses of the importance ratings. The eigenvalues of the initial, un-rotated, factors

were greater than one and the eigenvalues of the second factor were .4, .2 and .3, all less

than one. More items were confounded in these analyses than in the analyses of the

importance ratings (Table 3-3). While some of the items were more obvious members of a

particular factor, it was concluded that the items factored together in a similar fashion as

they had in the importance factor analyses. Table 3-4 presents items and their factor

loadings from the factor analysis of the importance scores and from the factor analysis of

the performance scores.

To assess reliability of the proposed scales, Cronbach's alpha (Norusis, 1990a)

was calculated (Table 3-5). The results provided alphas in excess of .9, well in excess of

the .60 minimum for exploratory research suggested by Hair et al. (1998).









Table 3-2: Factor Analysis with Varimax Rotation of Importance of Family Intervention
Items

Item Nurses Patients Total
FI FII FI FII FI FII
Listens to concerns, feelings and questions .44 .77* .55 .80* .82* .49
of the patient's family
Respect and support the patient's family's .36 .71* .70c .67c .74* .58
ways of coping
Include family members in decision making .65 .63 .61 .75* .76* .58
regarding patient care when appropriate
Discuss strategies for normalizing family life .85* .34 .85* .49 .45 .86*
with family members
Establish trusting relationship between nurse .28 .77* .69c .69c .77* .55
practitioner and family members
Respect the privacy of individual family .34 .63 .62 .75* .78* .54
members
Encourage open communication between .85* .36 .85* .49 .48 .84*
Family members
Encourage family members to maintain .82* .37 .83* .51 .48 .84*
Family relationships as appropriate
Provide information to family members .19 .82* .47 .86* .87* .40
about patient in accordance with patient
preference
Facilitate understanding of the medical .55 .72* .51 .85* .84* .49
aspects of illness
Teach family members ways for health .69* .56 .53 .81* .77* .56
recovery and health maintenance
Discuss with patient's family members how .83* .33 .72c .63c .59 .73*
strengths and available resources can be
used to enhance patient's health
Support family efforts to promote patient's .76* .52 .77* .60 .65c .72c
health or management of patient's
condition when appropriate
Encourage family members to recognize and .84* .28 .80* .56 .52 .81*
reward positive patient behaviors
Facilitate family discussion, as members .88* .36 .70c .67c .59 .74*
prioritize data and select the most
immediate family issue to address'


Eigenvalue** 10.3 1.2 13.8 .5 13.1 .6
% of Variance** 68.9 8.2 91.9 3.0 87.6 4.0


*Significant (greater than .20 and accounts for 1.5% more variance than other loading).
CConfounded loadings: Both significant, but not significantly different from each other.
**Eigenvalue and corresponding % of variance report the results of the initial, un-rotated,
factor solutions, not the rotated solution.









Table 3-3: Factor Analysis with Varimax Rotation of Performance of Family Intervention
Items

Nurses Patients Total
ItemFI FII FI FII FI FII
Listens to concerns, feelings and questions .85* 49 .76* .64 79*
of the patient's family
Respect and support the patient's family's 73c .64c 70c .69c .73* .65
ways of coping
Include family members in decision making c 77*
regarding patient care when appropriate .
Discuss strategies for normalizing family life .49 .84* c .79 .56 .80*
it .fe49 .84* .61 .79c .56 .80*
with family members
Establish trusting relationship between nurse 9 c c .*
.76* .59 .76 .64o .76* .61
practitioner and family members
Respect the privacy of individual family .76* .60 .82* .56 .81* .56
members
Encourage open communication between c .70 .58 .81 .60 .77*
Family members
Encourage family members to keep or
.56 .80* .57 .81* .57 .80*
maintain family relationships as appropriate
Provide information to family members
about patient in accordance with patient .83* .51 .82* .57 .82* .54
preference
Facilitate understanding of the medical .
fn .79* .55 .81* .58 .82* .54
aspects of illness
Teach family members ways for health 71c .63c .78* .62 .76* .62
recovery and health maintenance
Discuss with patient's family members how
strengths and available resources can be .70 c .67 c .61 .79* .66c .73c
used to enhance patient's health
Support family efforts to promote patient's
health or management of patient's .79* .57 .66c .72c .73c .65c
condition when appropriate
Encourage family members to recognize and
.49 .86* .59 .80* .55 .83*
reward positive patient behaviors
Facilitate family discussion, as members
prioritize data and select the most .68c .65c .74c .66c .70c 67c
immediate family issue to address __
Eigenvalue** 13.6 .4 14.5 .2 14.1 .3
% of Variance** 90.7 2.6 96.5 1.6 94.1 1.8
*Significant (greater than .20 and accounts for 1.5% more variance than other loading).
CConfounded loadings: Both significant, but not significantly different from each other.
**Eigenvalue and corresponding % of variance report the results of the initial, un-rotated,
factor solutions, not the rotated solution.









Table 3-4: Nurses' and Patients' Importance and Performance Factor Loadings Analysis


Family Interventions Items: Factor I Combined Nurses & Patients Total
(8 items) Factor Loadings
Importance Performance
Provide information to family members about
patient in accordance with patient .87* .82*
preference
Facilitate understanding of the medical
aspects of illness
Listens to concerns, feelings and questions of82* 79*
the patient's family
Respect the privacy of individual family .78 .81*
Members
Establish trusting relationship between nurse77* 76*
practitioner and family members
Teach family members ways for health77* 76*
recovery and health maintenance
Include family members in decision making .76* 77
regarding patient care when appropriate
Respect and support the patient's family's .74 .73
ways of coping

Family Interventions Items: Factor II Combined Nurses & Patients Total
(7 items) Factor Loadings

Importance Performance
Discuss strategies for normalizing family life86* 80*
with family members
Encourage family members to keep or .84* .83*
maintain family relationships as appropriate
Encourage open communication between* 77*
family members
Encourage family members to recognize and .81 .83
reward positive patient behaviors
Facilitate family discussion, as members
prioritize data and select the most immediate .74* .67c
family issue to address
Discuss with patient's family members how
strengths and available resources can be .73* .73*
used to enhance patient's health
Support family efforts to promote patient's
health or management of patient's condition .72* .65
when appropriate











Table 3-5: Cronbach's Alpha and Alpha if Item Deleted for Family Intervention Factors


Family Interventions Patient Factor I: Alpha if Nurse Factor I: Alpha if item
Items: Factor I item deleted deleted
(8 items)
Importance Performance Importance Performance
Listens to concerns,
feelings and questions of .9201 .9965 .9893 .9520
the patient's family
Respect and support the
patient's family's ways of .9297 .9973 .9900 .9514
coping
Include family members in
decision making
decision making .9205 .9966 .9895 .9535
regarding patient care
when appropriate
Establish trusting
relationship between .9
.9293 .9965 .9897 .9524
nurse practitioner and
family members
Respect the privacy of
individual family .9386 .9965 .9891 .9528
members
Provide information to
family members about
family members about .9322 .9965 .9898 .9547
patient in accordance
with patient preference
Facilitate family
understanding of the .9169 .9966 .9891 .9534
medical aspects of illness
Teach family members
ways for health recovery .9229 .9965 .9901 .9834
and health maintenance


Standardized Alpha


.9344


.9970


.9909


.9545









Table 3-5 continued.


Family Interventions Patient Factor II: Alpha if Nurse Factor II: Alpha if
Items: Factor II item deleted item deleted
itemsm)
Importance Performance Importance Performance
Discuss strategies for
normalizing family life .9881 .9943 .9564 .9845
with family members
Encourage open
communication between .9884 .9944 .9553 .9827
family members
Encourage family members
to keep or maintain
.9889 .9948 .9563 .9829
family relationships as
appropriate
Discuss with patient's
family members how
strengths and available .9898 .9940 .9611 .9837
resources can be used to
enhance patient's health
Support family efforts to
promote patient's health
or management of .9883 .9953 .9615 .9840
patient's condition when
appropriate
Encourage family members
to recognize and reward .9878 .9942 .9601 .9827
positive patient behaviors
Facilitate family
discussion, as members
prioritize data and select .9894 .9955 .9539 .9842
the most immediate
family issue to address
Standardized Alpha .9903 .9954 .9659 .9859

Gap Scores: Independent Variables

To control for the effect of multicollinearity, factor analysis was conducted on the

gap scores calculated by (Teas, 1994): Gap = -1(Importance- Performance). The resulting

factors were transformed into statistically independent variables. These factor variables









were utilized as independent variables in a multiple regression whose dependent variable

would be patient's perceptions of their own compliance, the nurse's perception of the

patient's compliance, and the measured health indicators of compliance. The resulting

regression coefficients provided evidence of the amount of variance in compliance

explained by each family intervention factor. To explore the dimensionality of the gap

scores, factor analysis with a varimax rotation was used. The results (Table 3-6) provided

evidence of two factors. The resulting factors, while less clearly loaded as they were in the

factor analysis of the importance scores and in the factor analysis of the performance

scores, produced similar factors as in the factor analyses of the importance and

performance items. Factor I was related to teaching and Factor II was related to support

and helping families develop strategies (Table 3-7). Factor scores for each of these two

gap factors were calculated and utilized to minimize multicollinearity effects in the

multiple regressions on compliance measures

Indicators of Compliance: The Dependent Variables

Compliance, measured from three perspectives: as perceived by the patient (an

indirect measure), as rated by the nurse (indirect indicator), and as indicated by measured

health indicators (direct indicator), was the dependent variable. Patients' perceived

compliance was measured by across four items, medication, diet, and exercise along with a

single overall subjective self-evaluation of compliance. Patients' rated their compliance on

each item on a 9-point "Never" to "Always" scale (Appendix B). Nurses' perceived

patient compliance was measured across the same four items as used for patients

(Appendix A). The difference was that this measure asked nurses to rate how well the

patients followed their recommendations on a 9-point "Never' to "Always" scale.









Table 3-6: Factor Analysis of Gap Scores


Nurses Patients Total
Item
_FI FII FI FII FI FII
Listens to concerns, feelings and questions .7 .* .6c c
of the patient's family
Respect and support the patient's family's .88* .40 .70c .64c .58 .74*
ways of coping
Include family members in decision making 47 .81* .62 .72c .71c .60c
regarding patient care when appropriate
Discuss strategies for normalizing family life .67 .60c .85* .48 .79* .51
with family members
Establish trusting relationship between .* .4 .5c
.77* .54 .65 .69c .60 .74*
nurse practitioner and family members
Respect the privacy of individual family 90* .38 .56 .78* .48 .85*
Members
Encourage open communication between .8 .
f l. m e .50 .81* .86* .46 .85* .46
family members
Encourage family members to maintain .
.74* .59 .85* .44 .75* .56
family relationships as appropriate
Provide information to family members
about patient in accordance with patient .77* .57 .43 .87* .51 .82*
preference
Facilitate understanding of the medical .78* .55 .45 .87* .51 .82*
aspects of illness
Teach family members ways for health73 .58 .53 .80* .6 .73
.73* .58 .53 .80* .60 .7Ic
recovery and health maintenance
Discuss with patient's family members how
strengths and available resources can be .62c .67c .74* .60 .76* .56
used to enhance patient's health
Support family efforts to promote patient's
health or management of patient's .56 .80* .72c .60c .75* .59
condition when appropriate
Encourage family members to recognize .70c .63c .79* .56 .75* .59
and reward positive patient behaviors
Facilitate family discussion, as members
prioritize data and select the most .35 .87* .68c .67c .80* .48
immediate family issue to address'___ __
Eigenvalue** 12.7 .6 13.2 .6 13.3 .4
% of Variance** 84.9 4.2 88.3 3.7 86.9 2.9
*Significant (greater than .20 and accounts for 1.5% more variance than other loading).
CConfounded loadings: Both significant, but not significantly different from each other.
**Eigenvalue and corresponding % of variance report the results of the initial, un-rotated,
factor solutions, not the rotated solution.









Table 3-7: Gap Factors and Their Factor Loadings


Nurses Patients Total
Item
Gap Factor I: Teaching FI FII FI FII FI FII
Respect the privacy of individual family* .38 .56 .78* .48 .85*
Members
Facilitate understanding of the medical
Sfn .78* .55 .45 .87* .51 .82*
aspects of illness
Provide information to family members about
patient in accordance with patient .77* .57 .43 .87* .51 .82*
preference
Teach family members ways for health* .58 .3 .80*
.73* .58 .53 .80* .60c .73
recovery and health maintenance
Establish trusting relationship between nurse .* .4 c .60
.77* .54 .65 .69c .60 .74
practitioner and family members
Gap Factor II: Support FI FII FI FII FI FII
Encourage open communication between .50 .8 .86* .46 .85* .46
fm mmbe .50 .81* .86* .46 .85* .46
family members
Discuss with patient's family members how
strengths and available resources can be .62c .67c .74* .60 .76* .56
used to enhance patient's health
Support family efforts to promote patient's
health or management of patient's condition .56 .80* .72c .60c .75* .59
when appropriate
Facilitate family discussion, as members
prioritize data and select the most .35 .87* .68c .67c .80* .48
immediate family issue to address__

Reliability of the Subjective (Perceived or Indirect) Evaluation of Compliance Scale

The standardized Cronbach's alpha for the Nurses' Subjective (indirect)

Evaluation of Compliance was .906 (Table 3-8), well in excess of the general lower limit

of .70 and in excess of the .60 for exploratory research suggested by Hair et al. (1998).

However, the "alpha if item deleted" for Medications was .921 indicating that deleting this

item from the scale would improve the standardized alpha.

Similar results occurred for the Patients' Subjective (indirect) Evaluation of

Compliance items (Table 3-9). The overall standardized alpha for the scale was .618 in









excess of the minimum .60 for exploratory research. The "alpha if item deleted" for

Medications was .647 indicating the standardized alpha would improve if Medications

were deleted from the scale.

Table 3-8: Cronbach's Alpha for Nurses' Subjective (Indirect) Evaluation of Compliance
Items

How well does this patient follow your Mean Alpha if Item
recommendations for (1 = Never and 9 = Always): Deleted
Diet 6.70 .839
Exercising 6.65 .870
Medications 7.60 .921
Overall, how well does this patient follow your 7.18 .850
7.18 .850
prescribed health regimens
TOTAL 7.03 Std. Alpha =.906

Table 3-9: Cronbach's Alpha for Patients' Subjective (Indirect) Evaluation of Compliance
Items

How well do you follow your nurses' recommendations Mean Alpha if Item
for (1 = Never and 9 = Always): Deleted
Diet 6.08 .367
Exercising 6.62 .413
Medications 8.10 .647
Overall, how well doe you follow your nurse's
Recommendations
TOTAL 7.38 Std. Alpha =.618

Factor analysis was conducted to explore the underlying structure of the subjective

evaluation of compliance items for both nurses and patients. The results, based upon the

"alpha if item deleted" scores, were expected to produce at least two factors. The results

of this analysis confirmed this possibility (Table 3-10). Diet and Exercising were

significantly loaded together for both nurses and patients. Likewise, Medications was

significantly loaded on a separate factor. The overall measure was confounded for nurses

and loaded on Factor I for patients. Based upon these results, two separate indicators of

subjective compliance were calculated using the original scale values. The Nonmedication









Scale was calculated by adding Diet and Exercise ratings and dividing by two (to convert

the sum to the original scale values). The original Medications rating was used for the

Medications Scale. Separating medication from nonmedication compliance items was

supported by the factor analysis of the objective evaluation of compliance items. The

overall rating was not used because of its confounded nature. Factor scores, individual

scores weighted by factor loadings, were generated for the two perceived compliance

scales (Perceived Compliance Factor I Nonmedication Regimens and Perceived

Compliance Factor II Medication Regimen) to be used in the multiple regression. These

scores, while not in the same scale value as in the original question, are composites of all

the items in the scale, weighted by their contribution to the factor (factor loading). As a

result, there were two indicators of patient perceived or subjective compliance. The first

was a summed measure based upon original scale values. The second was the factor score,

the sum of the weighted scores of the original scale values.

Table 3-10: Varimax Rotation of Nurses' and Patients' Subjective Evaluation of
Compliance Items

How well does this patient follow your Nurse Nurse Patient Patient
recommendations for... Factor Factor Factor Factor
(1 = Never and 9 = Always): I II I II
Diet .90* .35 .80* .19
Exercising .93* .26 .88* -.11
Medications .25 .95* .07 .96*
Overall, how well does this patient follow .64 .69c .60* .37
Your prescribed health regimens
Eigenvalue** 3.14 .58 1.91 .96
% of Variance** 78.51 14.52 47.82 24.07
*Significant (greater than .20 and accounts for 1.5% more variance than other loading).
CConfounded loadings: Both significant, but not significantly different from each other.
**Eigenvalue and corresponding % of variance report the results of the initial, un-rotated,
factor solutions, not the rotated solution.











Reliability of the Measured (Pseudo-Direct) Evaluation of Compliance Scale

Compliance was also assessed among nurses using a pseudo-direct measure. These

measured health indicators were vital sign readings, lab reports, weight, medication

regimen, dietary intake and exercise regimen along with the nurse's overall subjective

rating of the patient's health. The measures are considered direct because the nurse

practitioner completed the patient's questionnaire after the patient's current visit and

evaluation had been completed. While there is no guarantee the nurse specifically

examined the patient's chart, this approach assured the nurse's familiarity with the

patient's current status. Each items was measured on a 9-point scale from "Not Improved"

to "Improved as much as I can expect" (Appendix A). The Cronbach's alpha for the

nurses' observed compliance was .935, well in excess of the lower limit of.70

(Table 3-11) suggested by Hair et al. (1998). However, because of the performance of the

Medications rating in the subjective evaluation scale, factor analysis was used to explore

the underlying structure of the scale's items.

Table 3-11: Cronbach's Alpha for Nurses' Pseudo-Direct Evaluation of Compliance

How well does this patient follow your Mean Alpha if Item Deleted
recommendations for (1 = Not improved and
9 = Improved as much as I can expect):
Vital signs 7.05 .925
Lab reports 7.08 .928
Weight 6.24 .919
Medication regimen 7.29 .922
Dietary intake 6.56 .909
Exercise regime 6.60 .916
Overall health 6.92 .914
TOTAL 6.82 Std. Alpha =.935











The results of this factor analysis (Table 3-12) provided evidence that the objective

scale items should also be split into two items rather than treated as a single factor. While

the overall indicator was confounded, Weight, Dietary Intake and Exercise regime clearly

factored together as did Vital Signs, Lab Reports and Medication regimen. Given that

Medications factored alone in the Subjective Evaluation of Compliance scale and that

Medications factored with similar items among the observed evaluation of compliance

items, the observed evaluation items were divided into two separate indicators of objective

evaluation. First, the nonmedication items (Weight, Dietary Intake and Exercise Regimen)

were summed and divided by three (to convert the sum to the original scale) to create the

Measured (Pseudo-Direct) Nonmedication Evaluation of Compliance Scale. The

medication-related items (Vital Signs, Lab reports and Medication regimen) were summed

and divided by three (to convert the sum to the original scale) to create the Measured

(Pseudo-Direct) Medication Evaluation of Compliance Scale. The overall evaluation item

was not used because of its confounded nature. Factor scores, individual scores weighted

by factor loadings, were generated for the two objective compliance scales to be used in

the multiple regression. These scores, while not in the same scale value as in the original

question, are composites of all the items in the scale, weighted by their contribution to the

factor (factor loading). As a result, there were two indicators of patient perceived or

subjective compliance: a summed measure based upon original scale values and factor

scores based upon weighted scores of the original scale values.









Table 3-12: Varimax Rotation of Nurses' Pseudo-Direct Evaluation of Compliance

How well does this patient follow your recommendations Nurse Nurse
Nurse Nurse
for (1 = Not improved and 9 = Improved as much as I Factor I Factor
an expectFactor I Factor II
can expect):
Vital signs .32 .84*
Lab reports .26 .85*
Weight .85* .33
Medication regimen .39 .81*
Dietary intake .90* .37
Exercise regimen .90* .31
Overall health .62c .66c
Eigenvalue** 5.07 .84
% of Variance** 72.37 11.97
*Significant (greater than .20 and accounts for 1.5% more variance than other loading).
CConfounded loadings: Both significant, but not significantly different from each other.
**Eigenvalue and corresponding % of variance report the results of the initial, un-rotated,
factor solutions, not the rotated solution.

Summary of Study's Instrumentation: Independent and Dependent Variables

To summarize the study's instrumentation, factor analyses and Cronbach's

alphas were used to develop independent and reliable measures of the independent and

dependent variables. For hypothesis testing, this study had the following measures:

1. Nurses: Dependent Measures

a. Subjective Medication Compliance Evaluation Scale: Single item scale: How often
does this patient follow your recommendations for medications? Range: 1-9 with
l=Never and 9=Always

b. Subjective Medication Compliance Evaluation Factor Score Scale: Factor loading
weighted scores on all items in the scale, weighted to Medication Compliance.

c. Subjective Nonmedication Compliance Evaluation Scale: Two-item scale: How
often does this patient follow your recommendations for (1) diet and (2) exercise?
(Range: 1-9 with 1=Never and 9=Always)

d. Subjective Nonmedication Compliance Evaluation Factor Score Scale: Factor
loading weighted scores on all items in the scale, weighted to Nonmedication
Compliance.









e. Pseudo-Direct (Measured) Medication Compliance Evaluation Scale: Three-item
scale: Since I began treating this patient, his/her (1) vital signs, (2) lab reports and
(3) medication regimen has not or has improved as much as I can expect. (Range:
1-9 with 1=Not Improved and 9=Improved as much as I can expect)

f. Pseudo-Direct (Measured) Medication Compliance Evaluation Factor Score Scale:
Factor Score Scale: Factor loading weighted scores on all items in the scale,
weighted to Measured Medication Compliance.

g. Pseudo-Direct (Measured) Nonmedication Compliance Evaluation Scale: Three-
item scale: Since I began treating this patient, his/her (1) weight, (2) dietary intake
and (3) exercise regimen has not or has improved as much as I can expect. (Range:
1-9 with l=Not Improved and 9=Improved as much as I can expect)

h. Pseudo-Direct (Measured) Nonmedication Compliance Evaluation Factor Score
Scale: Factor loading weighted scores on all items in the scale, weighted to
Nonmedication Compliance.

2. Patients: Dependent Measures

a. Subjective Medication Compliance Evaluation Scale: Single item scale: How often
do you follow your nurse's recommendations for medications? (Range: 1-9 with
1=Never and 9=Always)

b. Subjective Medication Compliance Evaluation Factor Score Scale: Factor loading
weighted scores on all items in the scale, weighted to Medication Compliance.

c. Subjective Nonmedication Compliance Evaluation Scale: Two-item scale: How
often do you follow your nurse's recommendations for (1) diet and (2) exercise?
(Range: 1-9 with l=Never and 9=Always)

d. Subjective Nonmedication Compliance Evaluation Factor Score Scale: Factor
loading weighted scores on all items in the scale, weighted to Nonmedication
Compliance.

3. Nurses and Patients Gap Scores and Gap Factor Scores: Independent Measures
To compare importance and performance, this study utilized four summed scales
identified by the factor analysis. In addition, factor score-created Gap Factors were
used as indicators of the importance and performance gaps.

a. Nurse and Patient Sample
i. Factor I: Importance Scale 1
ii. Factor II: Importance Scale 2
iii. Factor I: Performance Scale 1
iv. Factor II: Performance Scale 2









b. Nurse and Patient Sample
i. Factor I: Gap Scale 1
ii. Factor II: Gap Scale 2

Sample Selection

A two-stage convenience sample provided nurse and patient participants with

the objective of completing 20 patient interviews for each of 10 nurse practitioners to

meet the study's objectives and provide adequate power for statistical tests (Agresti &

Finlay, 1986). First, the principal investigator recruited registered nurse practitioners

through letters and personal contacts (Appendix C). Second, the principal investigator and

nurse practitioner identified patients who fit the study's criteria:

1. Under treatment for cardiovascular disease (CVD) or diabetes, diagnoses that require
multiple interventions. CVD and diabetes are common causes of morbidity and
mortality. Dietary management, exercise, medications and lifestyle changes, such as
smoking cessation, stress management and weight control, are interventions used to
reduce the effects of CVD and diabetes (Phipps, Cassmeyer, Sands & Lehman, 1995).

2. A minimum of three prior scheduled clinic appointments with the nurse practitioner.

3. Patient had a scheduled appointment on the days data were collected.

Although eleven nurse practitioners agreed to participate, 10 nurse practitioners

actually participated. One of the volunteers, who had not been in the clinic long enough to

have sufficient numbers of patients who met the patient selection criteria, was eliminated.

Nine nurse practitioners were female and 1 was male. All were Caucasian. Nine of the

practitioners had a master's degree. The other nurse was a post-baccalaureate certified

nurse practitioner. All were from Veteran's Administration clinics (6 in Gainesville, 2 in

Daytona Beach and 2 in Lake City). The patients were predominantly white males being

treated for cardiovascular disease (CVD) or diabetes at the Veteran's clinics used in this

study. Results should not be generalized beyond these groups.









Among the 10 nurse practitioners a total of 184 interviews (an average of 18.4

patient interviews per nurse practitioner) were completed with a total of 169 usable

patient and corresponding nurse questionnaires (an average of 16.9 usable interviews per

nurse practitioner [clinic]) (Table 3-13). This produced a total of 338 questionnaires for

analysis (169 patient questionnaires and 169 corresponding nurse practitioner

questionnaires). Fifteen completed interviews (8.2% of the 184 total pairs of interviews)

were deleted from the analysis because the nurse practitioner reported the patient had no

family with whom the nurse practitioner could intervene.

Table 3-13: Completed versus Usable Questionnaires

ents Patients Without Total Patients for
Patients
Com g Family or Social Data Analysis
Nus Completing
Nurse Support
Questionnaire Sup o% %
# % # %
1 19 19 100.0
2 19 19 100.0
3 22 8 36.4 14 63.6
4 13 13 100.0
5 12 -- 12 100.0
6 23 23 100.0
7 15 7 46.7 8 53.3
8 20 20 100.0
9 22 -- 22 100.0
10 19 19 100.0
TOTAL 184 15 8.2 169 91.8

Protection of Human Subjects

Prior to data collection, permission for the study was obtained from the University

of Florida's Institutional Review Board and the Subcommittee for Clinical Investigation

from the Malcom Randall Veteran's Administration Medical Center, Gainesville. Florida.

As directed by the research protocol and for the protection of subjects' confidentiality,

informed consent was obtained from all nurses and patients participating in the study.









Statistical Tests

Level of significance for the statistical tests used by this study was .05. This means

the study accepted the risk that out of 100 samples, a true null hypothesis would be

rejected five times (Polit & Hungler, 1999).

To address the first hypothesis (There is a significant difference between patients'

perceived importance of family nursing interventions and nurses' perceived importance of

the same family interventions in a plan of care.), patients' ratings of the importance of each

family intervention were compared to their nurses' ratings of importance using repeated

measures of analysis of variance (Norusis, 1990b).

The second hypothesis (There is a significant difference between the patient's

perception of how well a nurse implements family interventions and the nurse's self-

evaluation of implementing the same family interventions.) also used the repeated

measures analysis of variance (Norusis, 1990b) to compare patients' ratings of their

nurses' performance to the nurses' ratings of their own performance.

The third hypothesis (The difference between the importance of a family

intervention to patients and patients' ratings of their nurse's performance in implementing

the intervention is related to patient's level of perceived compliance.) was addressed by

regressing the two patients' importance-performance factor gaps with their ratings of their

own compliance (Nonmedication regimen factor and Medication regimen factor) (Norusis,

1990b).

The fourth hypothesis (The difference between the importance of a family

intervention to patients and patients' ratings of their nurse's performance in implementing

the intervention is significantly related to how compliant the nurse rates their patients'









compliance.) was addressed with the same multiple regression approach used for the third

hypothesis. The difference was the source of the ratings. For the fourth hypothesis, the

two factors of the nurse's ratings of the importance-performance gap of the family

interventions served as the independent variable and the two factors of the nurse's rating

of the patient's compliance (nonmedication regimens and medication regimens) were the

dependent variables.

The fifth hypothesis (The difference between the importance of a family

intervention to patients and patients' ratings of their nurse's performance in implementing

the intervention is significantly related to patients' compliance as indicated by measured

health indicators.) and the sixth hypothesis (The difference between the importance of a

family intervention to a nurse and the nurse's self-rating of their nurse's performance in

implementing the intervention is significantly related to patients' compliance as indicated

by measured health indicators.) were similar to questions three and four and used multiple

regression. The two gap factors were regressed against the two measured-compliance

factors (nonmedication regimens and medication regimens) produced by the factor analysis

of the measured compliance indicators (e.g., vital signs, lab reports, weight, medication

regimen, dietary intake and exercise regimen).

Assumptions of Statistical Tests: Repeated Measures Analysis of Variance

This study utilized a repeated measures analysis of variance (Norusis, 1990b)

because the same subject (the nurse-patient pair constitutes a subject) is measured multiple

times (importance and performance ratings). This means that patients' and nurses'

responses are related as are the importance and performance ratings.









As the name suggests, repeated measures analysis of variance is useful for the

analysis of differences between groups when the groups are measured repeatedly or, in

essence, compared to themselves (Norusis, 1990b). The issue is that the measures of the

dependent variable(s) may be related because they are obtained from the same subjects.

This also makes repeated measures analysis of variance useful for this study. Measures of

nurses' and their patients' ratings of compliance and importance and performance of

family interventions are likely to be related. As a result, repeated measures analysis of

variance was used to compare nurses' and patients' ratings.

The major assumptions of the repeated measures analysis of variance (Norusis,

1990b) are that the data are measured at the interval level; the population distributions on

the response variable for the groups are normal in form; the standard deviations of the

population distributions for the groups are equal; and the groups are independent random

samples from the populations being compared (Agresti & Finlay, 1986). The null

hypothesis is that population means are equal. Agresti & Finlay (1986) pointed out that

analysis of variance is a robust test when considering violations of assumptions, "

Moderate departures from normality of the populations and equality of the standard

deviations can be tolerated, in the sense that the F distribution still provides a good

approximation to the actual sampling distribution of the ratio of the variance estimates"

(pp. 405-406). Agresti & Finlay added, "In the special case in which the sample sizes are

equal, the F test is particularly robust to violations of the assumption of equal standard

deviations" (p. 406). ACITS (1997) suggested that repeated measures ANOVA is robust

to violations of the assumptions of multivariate normality and homogeneity of covariance

matrices.









Assumptions of Statistical Tests: Multiple Regression

Stepwise multiple regression was the primary method for testing the regression-

related hypotheses (Norusis, 1990a). The assumptions underlying multiple regression

apply both to the dependent and independent variables and to the relationship as a whole.

The analysis of assumption violations must be performed after the regression model has

been estimated. The major assumptions to be analyzed are (Hair et al., 1998):

1. Linearity of the phenomenon: There is an assumed linear relationship between the
group of independent variables as well as between each independent variable and the
dependent variable. Hair et al. (1998) recommended an analysis of partial regression
plots between each independent variable and the dependent variable to assess this
assumption. A curvilinear pattern of residuals indicates a non-linear relationship
(Hair et al., 1998).

2. Constant variance of the error term: This is an assumption of equal variance
(homoscedasticity). Hair et al. (1998) recommended plotting the studentized residuals
against the predicted dependent variable values and comparing them to a null plot (a
random plot of points).

3. Independence of error terms: Regression analysis assumes that each predicted value is
independent. In other words, the predictions are not sequenced by any variable. Plots
of residuals against possible sequencing variables are useful in identifying non-
independence.

4. Normality of the Error Term Distribution: Normal probability plots, which compare
standardized residuals to a normal distribution (a straight line), is a useful method for
identifying this condition (Hair et al., 1998).

Unlike many other statistical tests, tests for violations of assumptions in multiple

regression are performed after the regression model has been estimated. Hair et al. (1998),

in describing this approach, wrote, "The basic issue is whether, in the course of calculating

the regression coefficients and predicting the dependent variable, the assumptions of

regression analysis have been met (p. 172)." This study tested for violations of

assumptions by examining studentized residuals, outliers, influential observations and









multicollinearity with the process outlined by Hair et al. (1998). As discussed above,

partial regression plots were used to examine the linearity of relationships. The objective

of these analyses is to identify cases (nurses or patients), or outliers, that contribute to the

violation of the assumptions. These cases are deleted from further model specification

(Hair et al., 1998).

To identify outliers, the study used visual inspection of partial regression plots as

well as individual leverage values, which indicate the distance between a single case and

the center of all observations (Neter, Wasserman and Kutner, 1990). Leverage values

were scanned for values greater than 2p/n where p = the number of regression parameters

in the regression function including the intercept term and n = sample size (Neter et al.,

1990, p.; 394). The typical regression function for this study included the intercept, a

dummy variable for marital status, age, and two gaps for a total of five regression

parameters with a sample of 169. The leverage value used by this study was .059,

rounded to .06.

Studentized deleted residuals were also used to detect outliers. Absolute values of

the studentized deleted residuals were compared to a t distribution with n p -1 degrees

of freedom (Neter et al., 1990, p. 400). The t-value for this study was 1.645 at 95%

probability with df =169 5 1.

The influential nature of outlying cases was assessed with Cook's Distance

(Neter et al., 1990, p. 403), a measure of the combined effect of a particular case on all of

the estimated regression coefficients.

The existence of a multicollinearity effect was determined with the Variance

Inflation Factor (VIF). Neter et al. (1990) suggested that a VIF value in excess of 10 for









any of the independent variables was evidence of multicollinearity. This study followed the

process suggested by Hair et al. (1998). First, all condition indices above a threshold value

of 15, a conservative value (Hair et al., 1998), were identified. Among condition indices

exceeding 15, variables with variance proportions above 90% were identified. A .90 or

higher between two or more coefficients indicates multicollinearity.

Multicollinearity did not surface as a problem in the analyses conducted in this

study. This was in part due to the use of composite factor scores from the factor analyses

previously discussed. Since varimax rotation was used, the factor scores produced new

scores, the sum of individual scores on the items weighted by the items factor loading

(Hair et al., 1998 and Norusis, 1990a), which were statistically independent of each other.

For each regression, the Enter variable entry function was used. This approach,

consistent with the hypotheses of this study, enters all variables simultaneously. A second

analysis was completed after the data were adjusted for violations of assumptions. In all

cases, the first elimination of outliers produced results that were judged to adequately

meet the assumptions of multiple regression.

Limitations

The major limitation of this study was that it used a convenience sample of nurse

practitioners, who volunteered to participate, from VA clinics in north central Florida. The

patients included in this study were those of the nurse practitioner who volunteered to

participate and who were scheduled for an appointment on the days data were collected.

Neither the nurse practitioners nor their patients were randomly selected. This reduced the

ability to generalize to populations outside the study. Because nurses and patients for this

study were not randomly selected, generalizations are limited by differences between









nurses' interactions with their patients and differences between nurses used in this study

and the population of nurses using family interventions for the sampled patient group. This

limitation is somewhat counterbalanced by this study's approach of comparing nurses to

their specific patients rather than comparing a sample of nurses to a sample of patients.

This comparison of related-samples of nurses and their specific patients was more realistic,

but precluded, without substantial time and costs, a traditional random sample.

A second limitation was also related to the study's sample. The sample for the

study was a sample of nurse practitioners and their patients. Nine nurse practitioners were

female and 1 was male. All were Caucasian. Nine of the practitioners held master's

degrees. The other nurse was a post-baccalaureate certified nurse practitioner. All were

from Veteran's Administration clinics (6 in Gainesville, 2 in Daytona Beach and 2 in Lake

City).The patients were predominantly white males being treated for cardiovascular

disease (CVD) or diabetes at the Veteran's clinics used in this study. Results should not be

generalized beyond these groups.

The nature of the family intervention items was also a limitation. While created on

the basis of substantial research in this area, the items produced very similar results. In

other words, the items seemed to measure the same concept. The factor analyses of

importance, performance and gap scores revealed at best two independent factors. Fifteen

items were reduced to two major factors. This provides evidence that the fifteen items are

not unique but, rather, highly related. The mean scores on the items also produced high

levels of importance. These two findings suggested that the items were all important and

that they represented only two dimensions. The result of this limited the amount of

variance in the independent variables. Thus, the amount of variance to be shared with the









dependent variable was reduced limiting the variance that could be explained by Pearson's

r or multiple regression. Future research should utilize more variance producing items.

Another obvious, but important limitation to acknowledge is the violations of

statistical assumptions. Of particular importance to this study was multiple regression

analysis. This analysis requires a subjective evaluation of post-analysis indicators to

determine if the data violated key assumptions. While there are statistical indicators of

violations (e.g., leverage scores and residual plots), the interpretation of these indicators is

subjective, based largely upon the researcher's expertise and experience. A more

knowledgeable and/or more experienced researcher may have made different decisions

than the principal investigator for this study.














CHAPTER 4
RESULTS

Purpose of the Study

This study used an expostfacto/correlational design (Polit & Hungler, 1999) to

examine the differences between patients' and nurses' perceptions of importance and

nurses' performance of selected family interventions and the relationships among

importance and performance gaps for both patients and nurses and alternative measures

of compliance. Personal surveys were conducted in a cohort design with nurse

practitioners and their patients to assess the perceived importance and performance of

nursing family interventions and direct and indirect measures of compliance.

Nurse Practitioner Profile

The nurse practitioners' ranged in age from 28-59 (mean=47) with 5-33 years

(mean=24.3) experience in nursing and 2-23 years (mean=7.4) experience as a nurse

practitioner. Nine were female and 1 was male. All were Caucasian. Nine of the

practitioners held master's degrees. The other nurse was a post-baccalaureate certified

nurse practitioner. All the nurse practitioners were from Veteran's Administration clinics

in the southeastern United States.









Patient Profile

The sample was predominantly white, married males (96.4%) aged 55-74

(Table 4-1). The minimum number of previous visits was 3, with an average of 7.1 visits,

indicating that the sample met the study's criterion that patient subjects had at least three

prior visits with their nurse practitioner. Simple one-way analysis of variance provided

evidence of significant differences between clinics and patient age and number of

previous appointments. A Chi-square test indicated there were different distributions of

marital status groups across the clinics. Because of the significant differences between

clinics and age of patients and between clinics and numbers of appointments, Pearson

correlation coefficients (Table 4-2) were calculated for the relationships among the Nurse

Importance Scale I, the Nurse Importance Scale II, the Nurse Performance Scale I, the

Nurse Performance Scale II, the Patient Importance Scale I, the Patient Importance Factor

II, the Patient Performance Scale I, the Patient Performance Scale II, age; and the number

of previous appointments with the nurse practitioner. The assumption was that if the

variables were not significantly related, there would be no need to control for age or

number of appointments. The Pearson's r for patients' age and Nurses' Performance

Scales I and II was significant. Age was therefore included as a covariate in the repeated

measures analysis of variance and as an independent variable in the multiple regressions.

Number of appointments was not related and therefore not used in the tests of the

hypotheses. The differences in marital status was controlled for in the repeated measures

of analysis of variance by collapsing the four marital status groups into two independent

groups: single patients (n = 59) and married patients, including married, widowed and

divorced/separated patients (n = 110).









Table 4-1: Sample Profile


Age _# % ANOVA for Age by Nurse Clinic
26-44 8 4.7 F = 4.739, df= 9, sig. = .000
45-54 26 15.4 High = 89
55-64 43 25.5 Low = 26
65-74 57 33.7 Average = 64.8 Std. Deviation = 11.53
75 and older 35 20.7
Total 169 100.0

Gender # % Chi Test for Gender by Nurse Clinic
Male 163 96.4 Chi2 = 14.189, df= 9, sig. =.116
Female 6 3.6 50% of cells had expected count less than 5.
Total 169 100.0

Race # % Chi2 Test for Race by Nurse Clinic
Caucasian 147 87.0 Chi2 = 26.535, df= 36, sig. = .875
Native American 2 1.2 80% of cells had expected count less than 5.
African-American 13 7.7
Hispanic 6 3.6
Other 1 .6
Total 169 100.0

Marital Status # % Chi2 Test for Marital Status by Nurse Clinic
Single 17 10.1 Chi2 = 41.777, df= 27, sig. = .035
Married 110 65.1 75% of cells had expected count less than 5.
Widowed 14 8.3
Divorced/Separated 28 16.6
Total 169 100.0

# Previous Appointments # % ANOVA for Appointments by Nurse Clinic
3-5 78 46.1 F = 3.954, df= 9, sig = .000
6-9 49 29.0 High = 7.1
10 or more 42 24.9 Low = 3
Total 169 100.0 Average = 7.1 Std. Deviation = 4.36









Table 4-2: Correlation of Importance and Performance Factors with Age and Number
of Previous Appointments with the Nurse Practitioner

Pearson Correlation Coefficient
Nurse Age Number of Previous Appointments
Importance Scale I Not Sig. Not Sig.
Performance Scale I .229* Not Sig.
Importance Scale II Not Sig. Not Sig.
Performance Scale II .208* Not Sig.

Patient Age Number of Previous Appointments
Importance Scale I Not Sig. Not Sig.
Importance Scale II Not Sig. Not Sig.
Performance Scale I Not Sig. Not Sig.
Performance Scale I Not Sig. Not Sig.
*p<.01

Hypothesis 1: Differences in Importance of Family Interventions

The first hypothesis (There will be significant differences between patients'

perceived importance of family nursing interventions and nurses' perceived importance

of the same family interventions in a plan of care.) was tested with repeated measures of

analysis of variance, with age as a covariate to control for the influence of age. To control

for marital status, the analysis of variance compared the Importance Scales I and II scores

of single patients, nurses of the single patients, married patients and nurses of the married

patients. The test of differences between Importance scores for Scale I (Mean = 7.791)

and Scale II (Mean = 7.357) provided evidence of a significant difference in the

importance of the factors (Table 4-3). Scale I, Teaching, was more important than Scale

II, Strategizing. Age did not have a significant effect as a covariate. The repeated

measures test of differences between groups (single patients, nurses of single patients,

married patients and nurses of married patients) provided evidence of differences

between groups (Table 4-4). Table 4-5 presents the each group's scores for the two

scales.






74

Table 4-3: Repeated Measures Test of Difference between Importance Scales

Type III Sum Df Mean _
Source of Error Type IIIF Sig.
of Squares Square
Importance 1.485 1 1.485 4.376 .037
Scale and Age .006 1 .006 .177 .674
Importance and Marital Status 3 .006 .002 .910
Error 333 .339

Table 4-4: Repeated Measures Test of Differences in Importance Scales between Patient
and Nurse Marital Groups


Source of Error Type III Sum MeaF Sig.
of Squares Square
Intercept 1317.200 1 1317.200 193.711 .000
Marital Group 4.891 1 4.891 .719 .397
Age 367.249 3 367.249 18.003 .000
Error 2264.340 333 2264.340

Table 4-5: Means and Confidence Intervals for Importance Scales by Marital Group


Marital Group FI FI-Imp FII FII-Imp
Importance 95% C.I. Importance 95% C.I.
Nurse Single Patient 8.32 7.86-8.78 7.86 7.34-8.37
Nurse Married Patient 8.30 7.97-8.64 7.91 7.53-8.29
Married Patient 8.23 7.89-8.56 7.76 7.38-8.14
Single Patient 6.31 5.86-6.77 5.90 5.39-6.42

Nurses of single patients and single patients did not rate Importance Scale I

significantly more important than Importance Scale II. The Scale I mean (8.32) for nurses

of single patients was within the 95% confidence interval for the Scale II score

(7.34-8.37). Likewise, the Scale I mean for single patients (6.31) was within the 95%

confidence interval for the Scale II scores (5.39-6.42). Conversely, married patients and

nurses of married patients rated Scale I significantly more important than Scale II. For

single patients and their nurses, the importance of Scale I was not significantly greater

than Scale II. For married patients and their nurses, Scale I was significantly more

important than Scale II.









Nurses of single patients (mean = 8.32), nurses of married patients (mean = 8.30)

and married patients (mean = 8.23), rated Scale I significantly as more important than did

single patients (mean = 6.31). The ratings for Scale II were the same. Nurses of single

patients (mean = 7.86), nurses of married patients (mean = 7.91) and married patients

(mean = 7.76) rated Scale II significantly more important that single patients (mean =

5.90) (Figure 4-1). These results, in part, supported the hypothesis. Nurses rated Scale I

and Scale II more important than their single patients. Nurses' importance ratings were

not different from married patients.


Importance Scale I
Means








Importance Scale II

6/ Performance Scale I


5 Performance Scale II


41
Nurse Single Single Patient Nurse Married Married Patient
Patient Patient


Figure 4-1: Importance and Performance Means

Hypothesis 2: Differences in Performance of Family Interventions

The second hypothesis (There will be significant differences between the patients'

perception of how well a nurse implements family interventions and the nurses' self-

evaluation of implementing the same family interventions.) was tested with repeated









measures of analysis of variance. There were no significant differences between

Performance Scale I and Scale II (Table 4-6). Age was a significant covariate for the

between groups analysis, and there were significant differences between the groups

(Table 4-7).

Table 4-6: Repeated Measures Test of Difference between Performance Scales


Source of Error Type III Df Mea F Sig.
of Squares Square


Performance Scale I and II .007 1 .007 .281 .596
Performance and Age .006 1 .006 .226 .634
Performance and Marital Status .525 3 .175 .647 .585
Error 90.020 333 .270

Table 4-7: Repeated Measures Test of Differences in Performance Scales between Patient
and Nurse Marital Groups


Source of Error Type III Sum MeanSig.
of Squares Square
Intercept 641.386 1 641.386 40.657 .000
Marital Group 10.673 1 10.673 .677 .411
Age 717.883 3 239.234 15.169 .000
Error 5253.235 333 15.775

Married patients (mean = 7.84) rated their nurses' performances on Scale I

significantly greater than their nurses rated themselves (mean = 7.09) (Table 4-8).

Conversely, single patients (mean = 4.88) rated their nurses' performances on Scale I

significantly less than the nurses rated themselves (mean = 6.05) (Table 4-8). There were

differences between nurses and patients but in unexpected ways. Married patients were

higher than their nurses while single patients were lower than their nurses. In other

words, married patients believed their nurses were doing more than the nurses believed,

and single patients believed their nurses were doing less than the nurses believed

(Figure 4-1).









For Scale II, the results were similar. Married patients (mean = 7.55) rated their

nurses performance on Scale II significantly higher than the nurses rated themselves

(mean = 6.83) (Table 4-8). Likewise, single patients (mean = 4.62) rated their nurses'

performance lower than the nurses rated themselves (mean = 5.92) on Scale II

(Figure 4-1).

Table 4-8: Means and Confidence Intervals for Performance Scales by Marital Group

Marital Group FI FI-Perf FII FII-Perf
Performance 95% C.I. Performance 95% C.I.
Nurse Single Patient 6.05 5.32-6.78 5.92 5.19-6.65
Nurse Married Patient 7.09 6.56-7.62 6.83 6.30-7.37
Married Patient 7.84 7.31-8.37 7.55 7.01-8.08
Single Patient 4.88 4.15-5.61 4.62 3.89-5.35

Hypothesis 3: Patients' Gaps and Patients' Perceived Compliance

This hypothesis (The difference between the importance of a family intervention

to patients and patients' ratings of their nurse's performance in implementing the

intervention will be significantly related to how compliant the patients perceive

themselves.) was tested with multiple regression. The dependent variables were patients'

perceived compliance with nonmedication regimens factor score and patients' perceived

compliance with medication regimens factor score. These scores were generated by the

factor analysis with varimax rotation and resulting factor loading weighting. The

independent variables were Gap Factor I and Gap Factor II. Both of these were also

generated by the factor analysis with varimax rotation. They are statistically independent

composite variables from the raw gap scores. Age and marital status were also included

as independent variables. Marital status was entered as a dummy variable with 0 = not

married and 1 = married.









Patients' Perceived Compliance with the Nonmedications Regimens Factor

The initial regression analysis provided evidence of six outliers. The regression

with the six outliers deleted produced a non-significant R = .193 (p = .195). While the

overall regression was not significant, Patient Gap II (Beta = -. 174, p = .029) was

significant. A second regression analysis was completed using stepwise variable entry

(Table 4-9). This regression was significant (R = -. 170, p = .03) with Gap II the only

variable entered. The relationship between patients' gaps and compliance was as not

expected: as the patients' importance-performance gap for nonmedication regimens

widened, compliance increased. This finding did not provide support for the hypothesis.

Since both Gap I and Gap II were not significant, the hypothesis was not supported.

Table 4-9: Patient Gap, Patient Age and Marital Status as a Predictor of Patients'
Perceived Compliance with the Nonmedication Compliance Factor

R=-.170 Beta
R2 = .029 (Standardized Significance Tolerance VIF
Sig. = .03 Coefficients)
Constant .066 .369 NA NA
Gap II -.174 .030 .976 1.025
Gap I -.069 .377 Not in Equation Not in Equation
Patient Age .055 .479 Not in Equation Not in Equation
Marital Status .011 .893 Not in Equation Not in Equation
F = 1.532, df= 4, 158
*Not standardized.

Patients' Compliance with the Medication Regimens Factor

With three outliers removed, this regression, patients' gap on patients' compliance

with medication regimens, was not significant (Table 4-10). The hypothesis was not

supported.









Table 4-10: Patient Gap, Patient Age and Marital Status as a Predictor of Patients'
Perceived Compliance with the Medication Compliance Factor

R=.161 Beta
R2 = .026 (Standardized Significance Tolerance VIF
Sig. = .376 Coefficients)
Constant -.178 .493 NA NA
Gap I -.137 .083 .979 1.022
Gap II .005 .948 .967 1.034
Patient Age .088 .271 .961 1.041
Marital Status -.018 .827 .917 1.091


F = 1.065, df= 4, 161
*Not standardized.

Hypothesis 4: Nurse' Gaps and Nurses' Perceived Compliance

Hypothesis 4 (The difference between the importance of a family intervention to

nurses and nurses' ratings of their performance in implementing the intervention will be

significantly related to how compliant the nurses rate their patients.) was tested with

multiple regression. The independent variables were nurses' Gap Factor I, nurses' Gap

Factor II, age and marital status (dummy variable: 0 = single and 1 = married). The

dependent variables were created by the factor analysis with varimax rotation of the

nurses' perceived compliance ratings of their patients.

Nurses' Perception of Patients' Compliance with the Nonmedication Regimens Factor

The initial regression of the nurse's subjective evaluation of the patients'

nonmedication compliance produced diagnostic results suggesting the deletion of seven

cases. The multiple regression with the cases deleted better met the statistical

assumptions and produced a significant model with R = .265 (p = .021) accounting for

7.0% of the variance in the dependent variable, the nurse's subjective evaluation of the

patient's nonmedication compliance (Table 4-11). Patient's age (Beta = .193, p = .017)

was significant: the older the patient, the more likely the nurse was to rate the patient as









compliant with nonmedication regimens. Gap II (Beta = .168, p = .033) was also

significant: as the gap increased, compliance increased. This was the predicted

relationship. The results suggested a positive relationship. This was attributed to the ideal

measure used in this study. The value of this measure was negative for a performance less

than importance and positive for a performance that exceeded importance. An analysis of

variance comparing nurses who believed their performance either met or exceeded

importance to nurses who believed their performances had not met importance was

conducted to examine the positive Beta.

The results of the analysis of variance was significant (p = .009, F = 6.929,

df= 1, 167). Nurses who met or exceeded importance scores (n = 104) had an average

perceived nonmedication compliance score for their patients of 6.95 compare to nurses

who had not met expectations (n = 65) of 6.23. The results provided evidence that the

significant regression supported the hypothesis: as the gap declined, or exceeded

importance, perceived nonmedication compliance increased. These results suggested that

a positive Beta indicated that as expectations, or importance, were met, compliance

increased. Conversely, a negative Beta indicated that as expectations were not met,

compliance increased. These results led to the conclusion that this hypothesis was

partially supported because only one Gap was significant.

Nurses' Perception of Patients' Compliance with the Medication Regimens Factor

The initial regression results suggested deleting seven cases. After these cases

were deleted, the regression analysis was not significant, R = .236, p = .061 (Table 4-12).

Similarly, none of the individual variables were significant. The hypothesis was not

supported.









Table 4-11: Nurse Gap, Patient Age and Marital Status as a Predictor of Nurses'
Perception of Patients' Compliance with Nurses' Nonmedication Compliance Factor

R =.265 Beta
R = .070 (Standardized Significance Tolerance VIF
Sig. = .021 Coefficients)
Constant -.742 .071 NA NA
Patient Age .193 .017 .919 1.088
Gap II .168 .033 .926 1.079
Gap I .004 .959 .931 1.074
Marital Status -.123 .125 .926 1.079
F = 2.973, df= 4, 157
*Not standardized.

Table 4-12: Nurse Gap, Patient Age and Marital Status as a Predictor of Nurses'
Perception of Patients' Compliance with the Nurses' Medication Compliance
Factor

R =.236 Beta
R2 = .056 (Standardized Significance Tolerance VIF
Sig. = .061 Coefficients)
Constant .052 .897 NA NA
Marital Status .125 .121 .934 1.071
Gap I .132 .103 .930 1.075
Gap II .124 .114 .981 1.019
Patient Age -.031 .703 .934 1.071
F = 2.307, df= 4, 157
*Not standardized.

Hypothesis 5: Patients' Gaps and Patients' Measured (Pseudo-Direct) Evaluation
of Patients' Compliance

This hypothesis (The difference between the importance of a family intervention

to patients and patients' ratings of their nurse's performance in implementing the

intervention will be significantly related to patients' compliance as indicated by measured

health indicators.) was also tested with multiple regression.

Patients' Gaps as Predictors of Nurse's Measured (Pseudo-Direct) Evaluation of
Patient's Nonmedication Compliance

The initial regression identified six cases for deletion. The final multiple

regression (Table 4-13) was significant (R = .326, p = .001) but did not support the









hypothesis. The only significant independent variable was age (Beta = .317): as age

increased, the more likely the nurse was to rate the patient as compliant on the pseudo-

direct measure of nonmedication compliance.

Table 4-13: Patient Gap, Patient Age and Marital Status as a Predictor of Nurses'
Measured Evaluation of Patients' Nonmedication Compliance

R=.326 Beta
R2 = .107 (Standardized Significance Tolerance VIF
Sig. = .001 Coefficients)
Constant -1.541 .000 NA NA
Patient Age .317 .000 .963 1.039
Gap I -.102 .127 .953 1.049
Gap II -.027 .560 .954 1.048
Marital Status -.089 .148 .889 1.124
F = 4.710, df= 4, 158
*Not standardized.

Patients' Gaps as Predictors of the Nurses' Measured (Pseudo-Direct) Evaluation of
Patients' Medication Compliance

After deleting the five cases suggested by the diagnostic analyses, the multiple

regression of patients' gaps against nurses' measured evaluation of patients' compliance

was not significant (Table 4-14). The hypothesis was not supported.

Table 4-14: Patient Gap, Patient Age and Marital Status as a Predictor of Nurses'
Measured Evaluation of Patients' Medication Compliance

R=.138 Beta
R = .019 (Standardized Significance Tolerance VIF
Sig. = .540 Coefficients)
Constant -.374 .373 NA NA
Gap I -.006 .936 .977 1.024
Gap II -.061 .445 .953 1.049
Marital Status .119 .151 .906 1.104
Patient Age .050 .528 .966 1.035
F = .780, df= 4, 160
*Not standardized.









Hypothesis 6: Nurses' Gaps and Nurses' Measured (Pseudo-Direct) Evaluation
of Patients' Compliance

Hypothesis 6 (The difference between the importance of a family intervention to

nurses and the nurses' self-rating of their performance in implementing the intervention

will be significantly related to patients' compliance as indicated by measured health

indicators.) was addressed with multiple regression. The independent variables were age,

marital status, nurses' Gap I and nurses' Gap II. The dependent variables were composite

factor variables, measured (pseudo-direct) compliance with nonmedication regimens and

measured (pseudo-direct) compliance with medication regimens.

Nurse Gaps as Predictors of the Measured (Pseudo-Direct) Nonmedication Compliance
Factor

After five cases were deleted as influential outliers, this regression was significant

with an R = .339 (p = .001) (Table 4-15). While the regression was significant, the results

did not support the hypothesis. The gaps were not related to the nurse's objective

evaluation of the patient's measured medication compliance. The only significant

variable was age (Beta = .332, p = .000).

Table 4-15: Nurse Gap, Patient Age and Marital Status as a Predictor of Nurses'
Measured Evaluation of Patients' Nonmedication Compliance

R =.339 Beta
R =.115 (Standardized Significance Tolerance VIF
Sig. = .001 Coefficients)
Constant -1.343 .004 NA NA
Patient Age .298 .000 .924 1.082
Gap I -.016 .551 .734 1.362
Gap II -.017 .131 .787 1.271
Marital Status .091 .123 .923 1.083
F = 15.844, df= 4, 159
*Not standardized.









Nurse Gaps as Predictors of the Measured (Pseudo-Direct) Medication Compliance
Factor

After deleting the five outliers identified in the initial regression analysis, the

regression analysis produced a non-significant R = .237 (p = .055). Gap I was significant

(Beta = .212, p = .017). The results of a follow-up stepwise regression (Table 4-16)

produced a significant regression (R = 232, p = .003) Gap I produced a significant and

positive relationship (Beta = .232, p = .003): as Gap I increased from negative to positive

(narrowed), patient compliance increased. Since only one of the gaps was significant, the

hypothesis was partially supported.

Table 4-16: Nurse Gap, Patient Age and Marital Status as a Predictor of Nurses'
Measured Evaluation of Patients' Medication Compliance

R = .232 Beta
R2 = .054 (Standardized Significance Tolerance VIF
Sig. = .003 Coefficients)
Constant -.000 .996 NA NA
Gap I .232 .003 1.000 1.000
Gap II .043 .604 Not in equation Not in equation
Patient Age -.009 .906 Not in equation Not in equation
Marital Status .027 .738 Not in equation Not in equation
F = 9.241, df= 1, 163
*Not standardized.

As with the other positive gap Betas, this one was also examined with ANOVA of

measured medication compliance scores from nurses who had met or exceeded

expectations (n = 123) compared to the measured medication compliance scores from

nurses whose performance had not met or exceeded importance scores (n = 46). The

results were significant (p = .000, F = 16.622, df= 1, 167). Nurses who met or exceeded

importance scores rated their patients measured medication compliance an average of

7.38 compared to an average of 6.54 for nurses who had not met expectations. This

provided evidence that as the gap narrowed, measured compliance increased.















CHAPTER 5
SUMMARY, CONCLUSIONS, AND IMPLICATIONS


Summary of Findings

This study used an expostfacto/correlational design (Polit & Hungler, 1999) to

examine the differences between patients' and nurses' perceptions of importance and

nurses' performance of selected family interventions and the relationships among

importance and performance gaps for both patients and nurses and alternative measures

of compliance. A summary of the major findings of the study is presented below. The

reader is reminded that these findings were produced by a convenience sample of nurse

practitioners and their patients. Nine of the practitioners were female; 1 was male. Nine

held master's degrees, and 1 was a post-baccalaureate certified nurse practitioner. All

were from Veteran's Administration clinics (6 in Gainesville, 2 in Daytona Beach and 2

in Lake City). The patients were predominantly white males being treated for

cardiovascular disease (CVD) or diabetes at the Veteran's clinics used in this study.

Results should not be generalized beyond these groups.

Family Interventions More Relevant to Married Patients and Their Nurse

This study's results showed that nurses and married patients valued family intervention

more than single patients. Married patients rated their nurses' performance on family

interventions higher than the nurses rated their own performance. Conversely, single

patients rated their nurses' performance significantly lower than the nurses rated their

own performance.









Patients' Gap Not Related to Patients' Perceived Compliance

Gap II was the only gap significantly related to patients' perceived

compliance of with nonmedication regimens. However, the relationship was negative,

rather than positive. This did not support the hypothesis. Neither Gap I or Gap II were

related to perceived compliance with medication regimens. As a result, the findings of

this study did not provide evidence that patients' gaps were related to perceived

compliance.

Nurses' Gap I: Strategizing with the Family Related to Nurses' Perceptions of
Their Patients' Compliance with Nonmedication Regimens

The nurses' Gap II score, the Strategizing with the Family factor, was related to

the nurses' perceptions that their patients were compliant with the nurses' evaluation of

their patients' perceived nonmedication compliance. Similarly, patient age was related to

nonmedication compliance: as age of the patient increased, the more likely the nurse was

to rate the patient as compliant on the perceived nonmedication compliance measure. In

terms of patients' and nurses' perceived compliance with medication regimens, there

were no significant relationships.

Patients' Gaps Not Related to Nurses' Pseudo-Direct Measures of Compliance

The regressions of the patients' gap scores on the measured (pseudo-direct)

evaluation of nonmedication compliance measure indicated that patient age was the only

significant predictor: as patient age increased, the more likely the nurse was to rate the

patient as compliant on the pseudo-direct measure of nonmedication compliance. None of

the variables were significantly related to the nurses' pseudo-direct measures of

compliance with medication regimens.









Nurses' Gap I: Teaching the Family Related to Nurses' Pseudo-Direct Measures of
Patients' Compliance with Medication Regimens

Nurses' Gap I, Teaching the Family, was the only significant variable in the

regression of nurses' gap on nurses' pseudo-direct measures of medication and

nonmedication compliance. When the nurses' Teaching gap met or exceeded

expectations, the nurse was more likely to rate the patient as compliant with the pseudo-

direct measure of compliance with medication regimens.

Conclusions

The purpose of this study was to examine the relationship between family

interventions and compliance. A gap analysis, the difference between the importance of

family interventions to nurses and patients and the degree to which nurses and patients

perceive the family interventions were used by the nurse, was used. Personal surveys

were conducted in a cohort design with nurse practitioners and their patients to assess the

perceived importance and performance of nursing family interventions and direct and

indirect measures of compliance. Data were collected with a convenience sample of nurse

practitioners and their patients. Nine of the practitioners were female; 1 was male. Nine

held master's degrees, and 1 was a post-baccalaureate certified nurse practitioner. All

were from Veteran's Administration clinics. The patients were predominantly white

males being treated for cardiovascular disease (CVD) or diabetes at the Veteran's clinics

used in this study. Results should not be generalized beyond these groups.

Since only two of the study's four gap hypotheses were only partially supported,

there was not substantial evidence to support strong conclusions. However, the results do

provide tentative findings, implications for education and practice, and direction for

future research in the gap analysis of nursing family interventions.









In general, the results suggested that nurses' perception of their patients'

compliance with nonmedication regimens were related to how well the nurse helped the

patient's family develop strategies for dealing with the patient's condition (Gap II).

Nurses' Gap I, Teaching the Family, was related to nurses' pseudo-direct measures of

patients' compliance with medication regimens. Nurses' pseudo-direct measures of

compliance with nonmedication regimens were affected only by the patients' age: the

older the patient, the more likely the nurse was to rate the patient as compliant with

nonmedication regimens.

These results are consistent with the theoretical foundations of this study. Family

interventions contribute to compliance when the family interventions meet or exceed

patients' and nurses' expectations. In other words, family interventions are likely to have

specific functions. The results of this study provided evidence that family interventions

related to strategizing with families was important to compliance with nonmedication

regimens. Nonmedication regimens for the patients used in this study are familiar to and

easily understood by families. On the other hand, the significance of Gap II suggested

helping families work with the patient to develop strategies for complying with

nonmedication regimens contributed to compliance. Developing these strategies is

something with which these families were less familiar and had little experience.

Strategizing was thus more important to compliance than teaching. Conversely, Teaching

the Family, Nurses' Gap I, was related to the pseudo-direct measures of medication

compliance. This also supports the foundation of this study. Practitioners who perceive

families are not likely to be familiar with medications and their effects are likely to

emphasize "teaching" to achieve compliance.









Implications for Nursing Education and Practice

The results of this study suggested four major implications for nursing education

and practice. The first implication is the support for the use of family interventions in

building compliance. The next two implications relate to the conceptualization of family

interventions and compliance. The results suggested that nursing theory and research may

need to treat the concept of family interventions as a more simple concept than it is

currently conceived and treat compliance as a more complex concept than it is currently

conceived. The fourth implication related to the knowledge gap between patients and

their nurses and family intervention theorists and researchers. These two groups have

different conceptualizations of family. Reciprocal information transfer

should help bridge this gap as well as provide direction for future conceptualizations and

measures in family intervention research.

Family Interventions May Contribute to Compliance

While the results do not provide resounding support for the use of family

interventions to build compliance, they do provide some support. The literature review,

Chapter II, demonstrated that there are a number of factors related to compliant behavior.

This study examined only family intervention gaps. It did not control for or measure all

factors that might affect compliance. It was not expected that the family interventions

alone would account for a large amount of explained variance. This was true. Yet, the

family intervention gaps were, in at least two instances, related to different measures of

compliance. These significant relationships suggest the opportunity for further

development of the gap analysis of nursing family interventions.