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This is to certify that the
thesis entitled

Patient’s Trust and Distrust of Physicians:
Polar or Separate Constructs?

presented by
Caroline A. Greenldge, M.D., M.A.

has been accepted towards fulfillment
of the requirements for the

Master of degree in Bioethics, Humanities and
Arts Society

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5108 K.IProj/Aoc&Pres/ClRC/Date0ue.indd

PATIENTS’ TRUST AND DISTRUST OF PHYSICIANS:
POLAR 0R SEPARATE CONSTRUCTS?

By

Caroline A. Greenidge, MD.

A THESIS
Submitted to
Michigan State University
in partial fiilfillment of the requirements
for the degree of
MASTERS OF ARTS
Bioethics, Humanities and Society

2009

Copyright by
CAROLINE A. GREENIDGE, MD.
2009

ABSTRACT
PATIENTS’ TRUST AND DISTRUST OF
PHYSICIANS: POLAR OR SEPARATE
CONSTRUCTS?
By
Caroline A. Greenidge. MD.

Trust relations lay the foundation for the covemmt between society and the
profession of medicine and yet it remains an enigmatic concept although it has been
studied in multiple disciplines. It is generally assumed that distrust is the absence of
trust; and therefore, distrust has had very little systematic research on its own antecedents
and effects (Cook, Kramer, Thom, Stepanikova, Mollborn and Cooper, 2004). Current
research supports that the constructs of trust and distrust although related are distinct
(Benamati, Serva, Fuller, 2006; Lewicki, McAllister and Bies, 1998). Subsequently, the
antecedents and effects of distrust are difi‘erent from the antecedents and effects of trust

and should be studied independently.

DEDICATION

Dedicated to my faithful and loving husband Stephen, Sr.; our children: Stephen, Jr.
“Tristan”, Ariane, Ayodele, Jemila-Okera, our angel Gabriel; my parents by marriage
Everton and Ianthe Coppin; my father Edward B. Thomas; and in loving memory of my

mother, Jasmine K. Thomas.

The Lord is my rock, and my fortress, and my deliverer; my God, my strength, in whom I

WILL TRUST...

Psalm I 8:2

ACKNOWLEDGMENTS

The author expresses sincere appreciation to the many individuals who helped me to
develop the passion I now feel in seeking a deeper understanding of trust and distrust. To
my thesis advisor, Professor Harry Perlstadt, thank you for the hours spent listening, and
guiding. To Professor David Todem, thanks for sharing with me your statistical insight. To
my research mentor Professor Charles W. Given, I am grateful for the practical experience
of being a part of cutting-edge research. Your research guidance over the years of study
was invaluable. Also, a special thank you to my statistical tutors German Alvarado and Ron
Powers. To Maria Struck, thank you for your editing expertise. The following entities and
members all shared their resources with me and therefore I am eternally grateful: the
Program in Bioethics, Humanities, and Society (BHS) in alliance with the Center for Ethics
and Humanities in the Life Sciences (CEHLS), College of Human Medicine, Michigan
State University (MSU); the Departments of Family Medicine, and Epidemiology, MSU,
College of Human Medicine (CHM); Center of Excellence in Minority Medical Education,
MSU, CHM; Training Researchers in Community Settings (TRECOS) Program,
Departments of Biostatistics and Epidemiology, MSU, CHM; and the National Institute of
Health (NIH), National Center on Minority Health and Health Disparities, (NCMHD) Loan
Repayment Program. Primary research funding provided by the National Institute of Health
(NIH), National Cancer Institute (NCI), Research Supplements for Underrepresented

Minorities Program, Grant number 3R01CA03724-0481.

TABLE OF CONTENTS

LIST OF TABLES .............................................................................. vii
LIST OF FIGURES ........................................................................... viii
1. INTRODUCTION ....................................................................... 1-32
1.1. Statement of Problem ............................................................... 1-5
1.2. Research Significance ............................................................... 5-9
1.3. Purpose of Study ................................................................... 9-10
1.4. Study Null Hypotheses ............................................................. 10-11
1.5. Definition: Trust, Distrust and Trustworthiness ............................... 11-16
1.6. Conceptual Framework of Coexisting Trust and Distrust .................... 16-24
1.7. Theories on Trust and Distrust in the Interpersonal Interaction ............ 24-30
1.8. Measurement of Trust ................................................................................. 30-32
2. Chapter]: Methods ............................................................................................. 33-45
2.1. Summary of Design ................................................................. 33-38
2.2. Participants and their Participation in the RCCT ........................................ 38-42
2.3. Materials ............................................................................. 42—45
3. Chapter 2: Analyses and Results ...................................................... 46-56
3.1. Quantitative Analyses and Results ................................................ 46-52
3.2. Qualitative Analyses and Results ................................................ 52-56
4. Chapter 3: Conclusions and Contributions ........................................... 57-67
4.1 . Substantive Contribution .......................................................... 57-60
4.2. Limitations to the Study ................................................................. 60
4.3. Future Study ......................................................................... 60-61
4.4. Theoretical Contribution ........................................................... 61-67
4.5. Concluding Statement ................................................................. 67
5. APPENDIX A: Data Tables and Figures .............................................. 68-77
6. APPENDIX B: Wake Forest Trust in Physician Scale .............................. 78-79
7. REFERENCES ........................................................................... 80-89

Table Number Page Number

1. Patients’ Demographics

(Categorical Variables) .............................................. 68
2. Patients’ Demographics

(Continuous Variables) .............................................. 69
3. Patients’ Characteristics Association

with Patients’ Trust ..................................................... 70
4. Patients’ Characteristics Association

with Patients’ Distrust ................................................ 71
5. Patients’ Characteristics Association

with Clinical Trial Participation Grouping:

Retention, Attrition and Death (categorical variables) .......... 72
6. Patients’ Characteristics Association

with Clinical Trial Participation Grouping:

Retention, Attrition and Death (continuous variables) .......... 73
7. Multinomial Logistic Regression Model of

Patients’ Attrition Referenced to Retained ........................ 74
8. Multinomial Logistic Regression Model

of Patients Attrition Referenced to Death ......................... 75

LIST OF TABLES

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LIST OF FIGURES

Figure Number Page Number
1. A Model of an Alternate Social Reality of
Coexisting Trust and Distrust ................................................ 17
2. A Model of Coexisting Trust and Distrust .................................. 19
3. A Conceptual Model of Coexisting Trust and Distrust .................. 22
4. A Schema of the Secondary Analysis and Measured Variables ......... 34

5. A Schema of the Randomized Controlled Clinical Trial (RCCT) ........ 37

6. A Modified Consort E Flowchart of
Patients’ Participation in the RCCT .......................................... 40

7. A Screen Plot of the Wake Forest Physician Trust Scale .................. 54
8. A Conceptual Model of Coexisting Trust and Distrust Relations ....... 63

9. A Game Theoretic Representation of

Coexisting Trust and Distrust ................................................ 66
10. Clinical Trial Retention, Attrition, Death,

and Patients’ Level of Trust and Distrust ................................... 76
11. Trust-Distrust Type by Race77

viii

INTRODUCTION

1.] Statement of Problem

The patient-physician relationship serves as the Ark of the Covenant (a sacred
container holding the tablets of stones containing the Ten Commandments) in that it
holds a sacred interaction whose basis stems from a covenant of trust between society and
the profession of medicine. This sacred interaction is grounded in the physician’s
fiduciary obligation to patient health and healing. The covenant of trust is therefore the
foundation upon which the patient-physician relationship is built (Bailey, 1996; Brody,
1992; Caterinicchio, 1979; Mechanic and Schlesinger, 1996; Pearson and Raeke, 2000).

Our Western ideal of the physician healer predates Christianity and even
Hippocrates, deemed to be the father of Western medicine. Asklepios, a revered mythical
physician-god of ancient Greece was the physician role model for great physicians such
as Hippocrates and Galen (Bailey, 1996). The Hipprocratic Oath, (circa 400 BC) which
begins with: “I swear by Apollo the physician, and Aesculapius, and Hygeia , and
Panacea and all the gods and goddesses, making them my witnesses, that I will firlfill,
according to my ability and judgment, this Oath and covenant: . . .” (Chadwick and Mann,
1950), underscores the ancient Greek influence upon current medical practice. Note that
Greek mythology deemed Apollo to be the father of Asklepios (the god of healing), and
Hygiea and Panacea the daughters of Asklepios (goddesses of health). Physician

followers of the Asklepian tradition were “expected to practice their craft without

 

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primary regard for the social status of their patients, personal risk or financial gain”
(Bailey, 1996, p. 261). Medical ethics demands that a physician should serve the less
fortunate and practice with integrity, compassion and even sacrifice. Recently health care
reform, health disparities and economic pressures have greatly diminished the practice of
Asklepiad traditions of selfless service by physicians.

The covenant of bust exists in medicine because patient vulnerability is primary
and unavoidable (Clark, 2002; Hall, Dugan, Zheng, Mishra, 2001). Trust serves to
establish social order (Miszal, 1996: Chapter 3) and the social basis of the trust covenant
in medicine can be described as: “A contractual arrangement that tenders service in trust
in exchange for the social largess of professional autonomy” (Clark, 2002). An awareness
of this contractual agreement brings to light the self-interest of members of the medical
profession in preserving a patient-physician relationship that is based on trust and not
distrust. The preservation of trust and professional autonomy is diflicult in a social matrix
of distrust; but be as it may, patient fidelity is still the primary duty of the physician
because, willing or not, the vulnerability of the patient necessitates trust in the physician.
The medical profession must therefore hold unto its virtues of benevolence, integrity and
competence, and its initial mandate of selfless service to mankind, forsaking gain and
profit, and reining in self-interest.

Community perceptions, public opinion and the media fuel the deteriorating trust
in the medical profession and medical research (Mechanic, 1998). Patient vulnerability is

shrouded in a camouflage of an educated consumer and physicians have metamorphosed

into contracted technical advisors. This is exemplified by the malpractice crisis, and the
focus on specialty care and not primary care (Pelligrino, 1999). Idealistically, a trusting
patient and a trustworthy physician are necessary and sufficient for an effective
therapeutic patient-physician relationship.

Conversely, a distrusting patient and an untrustworthy physician may be engaged
in a formal contractual patient-physician relationship that may be perceived of lesser
therapeutic value. Distrust promotes an atmosphere of societal caution and “wariness
replaces trust” (Pelligrino, 1991, p.77). Should a covenant of distrust replace the covenant
of trust that is the foundation upon which the profession of medicine was built, and if so
will this be in the best interest of the autonomous yet still vulnerable patient? Those who
doubt physicians’ trustworthiness and believe that increased patient vulnerability would
produce lower trust should consider the value of trust. “On balance, an ethic of trust is
more realistic, conceptually sounder and phenomenologically more consistent than an
ethic of distrust” (Pelligrino, 1991, p. 84). An ethic based on wariness and distrust is
“really no ethic at all, but an illusory relationship of mutual self—defense” (Pelligrino,
1991 , p. 84). Changing the covenant of trust to one of distrust diminishes the sacred
responsibility of a virtuous physician as a healer, care provider, advocate for the sick and
promoter of health.

An evaluation of the patient-physician interaction, a major component of the
interpersonal aspect of health care reveals significant disparities in trust and mistrust.

Afiican Americans, Latinos and others when compared to Caucasians in the United

States reported a 13 to 18 percent less positive perceptions of physician in terms of
satisfaction with style and trust (Cooper-Patrick, et al., 1999). The level of patient’s trust
is not only associated with ethnicity (LaVeist, Nickerson and Bowie, 2000) but other
demographic factors as well, such as: patients’ age, gender, education and occupation
(Cook et al., 2004). The level of patient’s distrust is associated with physician behaviors
such as: negative non-verbal cues, lack of availability, a lack of time, lack of
explanations, lack of respect and showing signs of distrust of the patient (Cook et a1.
2004). The profession of medicine cannot afford to lose trust and a low level of trust can
be improved upon. It’s believed that trust reduces health disparities, improves access to
health care and improves health outcomes (Thom, Hall and Pawlson, 2004).

A major contributor to the deterioration of trust in the medical profession and
medical research is the extensive documentation of racial and ethnic disparities in health,
health care and health outcomes. In the Institute of Medicine (IOM) reports: Unequal
Treatment — C onfionting Racial and Ethnic Disparities in Healthcare (Smedley, Stith,
and Nelson, 2003) and The Unequal Burden of Cancer — An Assessment of NIH Research
and Programs for Ethnic Minorities and the Medically Underserved (Haynes and
Smedley, 1999) differences in the interpersonal aspect of health care are felt to contribute
to the documented disparities between Caucasian and ethnic minorities in health care and
health care outcomes in the United States (Smedley, et al.); and cancer care and cancer
outcomes (Haynes and Smedley). Both IOM committees recommended an increase in

clinical research for improved understanding and elimination of the disparities and

generalizability of research findings in minority populations (Smedley, et al.; Haynes and

Smedley); but minority population’s distrust of medical research impedes successful
clinical trial recruitment and retention.

The Senate hearings in the 19703 on human experimentation included poignant
testimonies by survivors of The Tuskegee Study. In Bad Blood —— The Tuskeegee Smhilis
Experiment (Jones, 1993 p.214), James H. Jones recounted the loss of trust by study
participants, exemplified by this statement by study survivors lawyer, Lester Scott, “They
have no faith, trust, nor confidence that the Public Health Service will properly examine
them and give them proper treatment” (“Quality of Health Care: Human
Experimentation, ” 1973). There are many barriers to the successful recruitment and
retention of minority patients in clinical trials; but a major divide is caused by previous
betrayal of trust and the resultant distrust that minority populations holds for medical
research and the medical community (Corbie-Smith, Thomas and St George, 2002,

Corbie-Smith, Thomas, Williams and Moody-Ayers, 1999).

1.2 Research Significance

Trust plays a central role in the patient-physician relationship and this has long
been acknowledged and well documented (Bailey, 1996; Barber, 1983; Brody, 1992;
Caterinicchio, 1979; Mechanic and Schlesinger, 1996; Pearson and Raeke, 2000,
Pellegrino, in Veatch, and Langan, Eds., 1991). In this climate of deteriorating trust, we
possess limited knowledge on patients’ trust and distrust in their physicians, and their

effect on patients’ attitudes, behaviors and health outcome. There is limited research on

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the antecedents and consequences of trust and even more so distrust in the patient-
physician relationship.

Trust has been hypothesized or shown to affect patient’s behaviors and attitudes
such as patients’ continuity with the physician, self-reported adherence to medication,
satisfaction with physician care (Thom, Ribisl, Stewart and Luke, 1999); loyalty and
satisfaction with physician, self reported health improvement (Kao, Green, Davis, Koplan
and Cleary, 1998; Kan, Green, Zaslavsky, Koplan and Cleary, 1998); willingness to seek
care, share confidential information, (Hall, Dugan, Zheng, et al. 2001); accept and adhere
to treatment (Altice et al., 2001; Hall, Dugan, Zheng, et al. 2001), following physician
recommendations (Safran, Taira, Rogers, et al., 1998;_Hal1 et al., 2001); remain with
physician (Safian, Montgomery, Chang, Murphy, and Rogers, 2001; and changing
physician (Keating, et al.,2002).

Patients in two managed care settings with a low level of trust reported less
satisfaction with care, lower intention to follow doctors’ advice, and lower reports of
symptom improvement (Thom, Kravitz, Bell, Krupat and Azari, 2002). Low levels of
trust in people of color, especially African Americans is associated with lower levels of
care seeking, preventive service and surgical treatments when compared to Caucasians
(LaVeist, et al., 2000). Lower trust and higher distrust in African Americans is also
linked to: lower use of preventive services (O’Malley et a1 2004); less satisfaction with
care and unwillingness to share information (LaVeist et a1, 2000); patient consent and
adherence (Altice et al 2001). African American distrust of the medical profession is a

long held attitude based on historical racial abuses and discrimination (Gamble, 1997 and

Gamble, 1993). This attitude of distrust also labeled as mistrust, is associated with lower
levels of satisfaction with medical care (LaVeist et al., 2000). A focus group study
reported that Afiican American patient’s distrust “inhibits care seeking, can result in a
change in physician and may lead to non-adherence” (Jacobs, Rolle, Ferrans, Whitaker
and Warnecke, 2006). African American distrust of the medical community is also a
deterent to participation in medical research (Corbie-Smith, et al.,l999).

Researchers in medicine and related fields agree that trust, distrust and
trustworthiness impact not only organization endpoints but the interpersonal also
(Mechanic & Schlesinger 1996; Anderson and Dedrick, 1990; Safran, Kosinski, et
al.,l998; Hall, Zheng et al., 2002 and Thom and Campbell, 1997). One aim of this
research is to evaluate cancer patients’ trust and distrust of their physician in the clinical
trial research setting involving a behavioral intervention; and to document the impact of
patients’ trust and distrust on patient retention, attrition or death during the trial. Another
aim of the study is to evaluate whether cancer patients’ trust and distrust of their
physician serve as predictors for patient retention, attrition or death during the trial.

Attrition occurs frequently in randomized controlled clinical trials (RCCT) due to
its longitudinal design (Given, Keilman, Collins and Given, 1990) but few studies report
analyses of attrition rates (Bottomley, Aflicace, Thomas, Vanvoorden and Ahmedzai,
2003) including cancer longitudinal studies (Cooley, 2000) and studies utilizing
behavioral interventions (case management, crisis counseling, cognitive-behavioral
therapy) (Gilbar and Neuman, 2002). Behavioral intervention cancer longitudinal studies

attrition rates range from 30 % in a multi-site RCCT study of cancer patients receiving

chemotherapy (Given, and Sherwood, 2005) to 61% (Gilbar and Neuman, 2002) and
84% (Chandra, et al., 1998) in prospective observational studies of newly diagnosed
cancer patients receiving treatment. Reviews on attrition rates in cognitive-behavioral
non-cancer longitudinal studies reported ranges fiom 10-59% (Davis and Addis, 1999),
and 30 -60% (Garfield, 1994).

Reported attrition predictors include demographic variables such as: younger age,
Canadian aboriginal status and involvement in manual labor (Mumaghan and Buckley,
2002); gender, education and socio—economic status (Marsh et al., 1989; Difianciso, et
al., 1998; McMahon, Kelly and Kouzekanam, 1993; Mosher Ashley 1994; and Scogin,
Harnblin, Beutler, 1986). Also reported are psychological and symptom severity variables
such as: depression, mania, paranoia, anticipated weight loss or gain (Davis and Addis,
1999); asthma symptom severity (Bender, Ikle, DuHamel, and Tinkelman, 1997) as well
as personal and other variables such as caretaker status, depression, hostility, and
assignment to experimental group (Moser, Dracup and Doering, 2000). It is the aim of
this research study to explore whether patients’ trust in and distrust of physicians served
as significant predictor variables for attrition.

Currently there is a lack of consistent/gold standard predictors for attrition fiom
longitudinal behavioral intervention clinical trials (Gilbar and Neuman, 2002; Kendall
and Sugarman 1997). In behavioral intervention trials attrition predictive factors covers a
wide spectrum, researchers have reported: participation in the control group; perceived
dietary compliance, symptom severity, and disease knowledge, (Given, Given and Coyle,

1985), age, race/ethnicity, cancer diagnosis, caregiver, and recruitment staff factors

(Neumark, Strommel, Given and Given, 2001 ). Other researchers have reported the status
of being a single parent, ethnic minority and lower anxiety (Kendall and Sugarman 1998)
and lower household income and negative treatment attitude (Grilo et al., 1998).
Although potentially challenging, the identification of predictors of attrition can help to

target and retain at risk populations in randomized controlled clinical trials (RCCT).

1.3 Purpose of Study

This study serves as an exploration of health behaviors of cancer patients (more
specifically patients’ retention, attrition and death during the trial) as influenced by a
patient’s level of trust and distrust in their physician in a clinical trial.
Objective: The objective of this research project is to examine Caucasian and Afiican
American cancer patients’ trust and distrust in their physicians and its effect on patient
participation in a randomized controlled clinical trial (RCCT) utilizing a behavioral
intervention for symptom control.
Specific Aims:

1. To examine the Wake Forest Physician Trust Scales’ factor structure internal
consistency and construct validity in measuring both cancer patients’ trust and
distrust in their physicians.

2. To examine cancer patients’ trust and distrust in their physicians, controlling for:
race/ethnicity (Caucasian! African American), age, gender (male/female),
education level (some college or more, high school graduate, less than high school

graduate), trial group assignment (experimental or control), Center for

[Er—mm-

1.4

Epidemiological Studies Depression (CES-D) measure of depression, satisfaction
with physician communication, patient mastery, and symptom severity mean

SCOTC.

. To examine the relationship between patients’ trust and distrust in their

physicians; and patients’ retention, attrition or death during the clinical trial.
Patients’ race/ethnicity (Caucasian/African American), age, gender (male/female),
education level (some college or more, high school graduate, less than high school
graduate), trial group assignment (experimental or control), Center for
Epidemiological Studies Depression (CBS-D) measure of depression, satisfaction
with physician communication, patient mastery, and symptom severity mean
score; variables that may serve as determinants of patients’ retention, attrition or

death will be included in the model.

Study Null Hypothesis:

. The Wake Forest Physician Trust Scale is not a reliable measure of Caucasian and

African American cancer patients’ trust and distrust in their physicians.

. Cancer patients’ trust and distrust will not vary by race/ethnicity

(Caucasian/African American), age, gender (male/female), education level (some
college or more, high school graduate, less than high school graduate), trial group
assignment (experimental/control), CBS-D measure of depression, patient

satisfaction with physician communication, patient mastery, and patient symptom

severity mean score.

10

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3. Patients’ trust and distrust will not significantly affect the outcomes of patients’
retention in, attrition from and death during the clinical trial after adjusting for

other significant variables.

1.5 Definition: Trust, Distrust and Trustworthiness

Trust as defined by Webster’s Dictionary is “a firm belief or confidence in the
honesty, integrity, reliability, justice etc., of another person or thing; faith; reliance”
(Webster’s New World Dictionary, 1964).Trust has also been defined as placing one’s
confidence in someone or an entity; the trustor is willing to be vulnerable without
measures in place, to monitor or control the actions of the trustee (Mayer, Davis and
Schoorman, 1995). A third definition of trust as an essential component in the patient-
physician relationship (Mechanic, 1996; Mechanic and Schlesinger, 1996), is “the
optimistic acceptance of a vulnerable situation in which the trustor believes the trustee
will care for the trustor’s interest” (Hall, Dugan, et al., 2001). Current theories about
patient trust in a physician describes it as a set of beliefs or expectations that a physician
will behave in ways that protects the best interest of the patient (Anderson and Dedrick,
1990; Thom and Campbell, 1997); or as a feeling of confidence or reliance in a physician
and the physician’s intent (Caterinicchio, 1979).

The following describes four commonly proposed pre-conditions of trust. First,
inter-relational trust emerges when there is a need by the trustor that only a trustee can
fulfill; this creates dependency of the trustor on the trustee. Second, with trust, there is an

optimistic assumption by the trustor that the trustee has his/her best interest at heart.

11

Third, the trustor also believes that the trustee is competent. However belief in
competence is not usually all encompassing (i.e. A simply trust B). Belief in competence
is usually limited, “trust is generally a three-part relation: A trusts B to do X” (Hardin
2002, 9). Fourth, trust involves risk of betrayal; the trustor can withdraw or lose what is
entrusted to the trustee if the trustee fails to keep trust.

Trustworthiness has been proposed to be a predominant determinant of trust and
has been defined as the beliefs about another party’s ability, benevolence and integrity
(Serva, Benamati and Fuller, 2005; Mayer, et al. 1995). Trustworthiness is believed to
function as a second order antecedent, and represents beliefs which lead to the formation
of a trusting attitude(Serva, Benamati and Fuller, 2005). Trustworthiness has been
defined as a virtue/moral disposition, not as an attitude (Potter 2002, p25; Hardin 2002,
p3 2). Virtue has been defined as, moral excellence; goodness; righteousness; conformity
of one’s life and conduct to moral and ethical principles; uprightness; rectitude (Random
House Dictionary, 1987). Others have described trustworthiness not as a virtue but based
on self-interest. External forces such as social norms or constraints; and shared interest or
“encapsulation interest,” which are both deemed to be based on self-interest drives
trustworthiness (Hardin 2002, 53). The trustee is motivated by norms to be trustworthy;
the trustor uses social constraints as a contract with the trustee. The trustee is interested in
preserving a relationship with the trustor and therefore “encapsulates” the interests of the
trustor as his/her interest; but trustworthiness based on a “social contract,” or
“encapsulated interest” does not capture the caring component of trustworthiness

therefore a definition based on “goodwill” also exists (Baier, 1986, Jones, 1999).

12

Trustworthiness therefore encompasses motivation, caring, competence, and action and in
its purest form, is a virtue (McLeod, 2006). The underlying motive of the trustee
determines whether trustworthiness is based on self-interests such as social norms or
shared interest; goodwill or a virtue. Trustworthiness as a virtue will be the definition of
trustworthiness used in this thesis. Also in this thesis the measure of physician
trustworthiness is defined based on technical competence, interpersonal competence and
agency/ fiduciary responsibility.

For the purpose of measuring trust, researchers have focused on physician
attributes that merits trust and in the medical profession, over the last decade, the work of
multiple research teams have advanced our knowledge of the measurement of patient’s
trust: Thom, Hall, Pawlson, (2004); Zheng, Hall, Dugan, Kidd and Levine,( 2002);
Anderson and Dedrick, (1990); Safran, Taira et al., (1998); Kao, Green; Davis, et
al.,(l998); Kao, Green, Zaslavsky, et al.,(l998). The theory of trust in medicine is based
on general trust in physicians as well as trust in specific physicians. A brief summary of
their conceptual framework of trust follows. They initially proposed five potentially
overlapping domains/dimensions of physician attributes identified by patients, that
engenders trust: (1) fidelity involves loyalty, caring, respect, advocating for patients
interest and avoiding conflicts in interest; (2) competence involves good practice and
interpersonal skills (communication which enhances the technical aspects of care),
correct decision-making and the avoidance of mistakes (both technical and cognitive); (3)
honesty involves telling the truth and avoiding intentional falsehood; (4) confidentiality

involves the proper use of sensitive information; and (5) global trust is described as “ the

13

soul of trust” which is a combination of some or all of the aspects of the separate
dimensions (Hall, Dugan, et al., 2001; Hall, Zheng et al., 2002; Anderson and Dedrick,
1990; Safran, Taira et al., 1998; Kao, Green, Davis, et al.,l998; Kao, Green, Zaslavsky,
eta1.,1998; Mechanic, 1996). Note should be made, that to date, none withstanding the
proposed trust domains, all trust is an unidimentional construct (Zheng, et al., 2002; Kao,
Green, Zaslavsky, et a1. 1998; Safran, Kosinski, et al., 1998) , suggesting that “these
domains are all part of a single “glo ” concept” (Thom et al., 2004, p125-126).

Thom and Campbell (1997) have identified seven categories of physician
behavior that increased patient’s trust. Two were related to technical competence and the
other five were related to interpersonal competence. Technical competence: (1) provide
a thorough evaluation of problems; (2) provide appropriate and affective treatment; and
interpersonal competence: (3) provide communication that is clear and complete; (4)
encourage partnership building; (5) express caring; (6) and show respect and
understanding of the patient’s experience; and (7) demonstrate honesty. Thorn, Bloch
and Segal (1999) then focused on improving patients’ trust by changing physician
behavior based on their seven physician behavioral categories, however; they did not
show a significant change in the outcomes measures of: patients’ trust, patients’ and
physicians’ satisfaction with the office visit, continuity in the patient physician
relationship, adherence to treatment plan and the number of diagnostic tests and referrals,
all measures that have been shown to be related to patient trust in physicians in the
literature. The researchers proposed a possible explanation of the negative finding,

arguing that the seven behavioral categories were determined fi'om analysis of four focus

14

group data, and therefore did not allow for the determination of a predictive value of the
individual behaviors.

Distrust as a polar construct of trust has been defined as a negative belief that the
trustee will act in the best interest of the trustor; and the trustor has an unwillingness to be
vulnerable or dependent upon the goodwill of the trustee (Hall, Dugan, et al., 2001).
Simplistically, distrust describes a lack of trust and earlier research placed them as
extremes of a single dimension (Rotter, 1967). However, it has been proposed that trust
and distrust although related are distinct constructs (Benamati et al., 2006; Cho, 2006;
Huang and Dastrnalchian, 2006; McKnight, Kacmar and Choudhury, 2004; Kramer,
1999; Lewicki, et al. 1998; Sitkin & Roth, 1993).

Distrust as a separate construct from trust has been defined as “a positive
expectation of an injurious action,” (Luhmann, 1979). Distrust therefore is not simply an
absence of trust but distrust is an active expectation that the trustee’s behavior will be
irresponsible, incompetent, or cause harm (Lewicki, et al. 1998). If trust and distrust
firnction as separate constructs then theoretically a patient can be both trusting and
distrusting of the physician who will be perceived as being both trustworthy and
untrustworthy. The trustor therefore engages in behaviors balancing risk (trust) and
sanctions (distrust). The patient and physician may then engage in the explicit
negotiation of a formal contractual interaction that may or may not engender an effective
therapeutic patient-physician relationship. Inter-relational distrust is based on risk of
failure and reliance. Understanding the role that patients’ trust and distrust play in the

patient-physician interaction may allow improvement in the patient-physician

15

relationship, patient behaviors and health outcomes.

1.6 Conceptual Framework of Coexisting Trust and Distrust

In the past researchers have conceptualized the attitudes of trust and distrust along a
bipolar continuum; but currently, models show co-existing trust and distrust as distinct
constructs (Benamati, et al.2006; and Lewicki et al. 1998). A model of trust and distrust
not as polar attitudes but as attitudes that possess positive and negative features, results in
a conflicting attitude. Trust, distrust and trustworthiness was examined in the setting of
consumer use of online banking services and commerce (Benamati, et al.2006; Cho,
2006; McKnight, et al., 2004; Lewicki, et al., 1998; Sitkin & Roth, 1993), and the
researchers provided further evidence to support that trust and distrust exist as related yet
separate constructs. This research was designed to show both trust and distrust
independently exerting a positive or negative influence on consumer decisions and
behaviors (Benamati, et al., 2006; Cho, 2006). Benamati et al. were not able to determine
the relative contribution of both trust and mistrust on the intentions of the consumer to
use of online banking services because in their study trust overwhelmed distrust. Trust
and trustworthiness was found to have a positive impact on intention to use; but in the
presence of trust, distrust became insignificant (Benamati, et al., 2006).

Cho (2006), however, reported that trust and distrust impacted different

behavioral intentions, trust predicted a consumers’ willingness to commit to a business-
to-consumer intemet exchange relationship and distrust predicted a consumers’ self-

disclosure of personal information. Data therefore exist to support that the attitude of trust

16

Figure 1. A Model of an Alternate Social Reality of Coexisting Trust and Distrust.
(Adapted fiom Benamati, et al., 2006 and Lewiciki, et al., 1998)

 

 

 

 

 

 

 

 

 

 

 

Low or No High
DISTRUST DISTRUST
(d) (D)
Absence of: Presence of:
Fear, skepticism, and Fear, skepticism and
monitoring. monitoring.
Low or No DISENGAGED UNBOUNDED
TRUST TRUST & DISTRUST DISTRUST
(t)
(“Detachment”) (“Blind Suspicion”)
Absence of:
Low or No Trust (t) Low or No Trust (T)
Hope
Faith & &
Confidence Low or No Distrust ((1) High Distrust (D)
td tD
High UNBOUNDED TRUST BOUNDED TRUST
TRUST
(T)
(“Blind Trust”) (“Tn-st but verify”)
Presence of:
High Trust
Hope High Trust (T)
Faith (T) &
Confidence & High Distrust
Low or No Distrust (d) (D)
Td TD

 

 

 

 

 

17

 

 

 

and the attitude of distrust are based on separate positive and negative components
(Cacioppo and Berston, 1994). Figure 1 is adapted from Benamati, et al., (2006) and
Lewicki et al., (1998), and illustrates the concept of trust and distrust as separate positive
and negative components. It also, delineates the coexistence of trust and distrust leading
to four states described as unbounded trust, bounded trust, unbounded distrust, and
disengaged trust and distrust. Trust and distrust exhibits positive and negative
components; trust exudes the positive emotions of “hope, faith, and confidence;” while
distrust on the other hand exudes the negative emotions of “fear skepticism and
monitoring.” Trust co-existing with low or no distrust is labeled unbounded trust, which
leads to complete faith or “blind trust” in the trustee or by a buster who then abdicates all
responsibility. Distrust co-existing with low or no trust is labeled unbounded distrust, and
described as “blind suspicion.”

A distrusting trustor assumes harmful motives by the trustee and the bustor
therefore engages in a bounded fashion with the trustee. The coexistence of low or no
trust and low or no distrust is labeled a disengaged state; and is also described as
detached. A disengaged state leads to minimal interdependence between buster and
trustee. Bounded trust has been described as the healthy temperance of trust with distrust,
called “prudent paranoia” (Kramer, 2002). Blind trust may not be deemed as prudent
because the patient is depending upon of the competence, compassion and character of
the physician; who is after all, a fallible human being; but bounded trust which is bust
bounded by distrust may impose upon the bustee the necessary mantle of fiduciary

responsibility (Pelligrino, 1992).

18

Figure 2, depicts the trustor evaluating the trustworthiness of the trustee. It also
illustrates trust and distrust co-existing in a nomological system that includes
trustworthiness and behavioral intention. The attitudes of bust and disbust are formed
based on the bustor’s judgment of the trustee’s trustworthiness which is based on a
determination of competence and intention. This model utilizes an evaluation of
competence and fidelity to determine bustworthiness. The trustor then decides to place

trust in the bustee.

Figure 2. A Model of Coexisting Trust and Distrust.
(Adapted fiom Benamati, et. al., 2006)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Trustor evaluates the Outcome 1
trustworthiness of the trustee
and decrdes to place trust . TRU ST OR’S
/ T...
TRUSTEE deemed
TRUSTOR TRUSTEE Trustworthy
TRUSTEE deemed
Untrustworthy
Domalns: . Trust & Disbust
1. F rdelrty
2. Technical Competence
3. Interpersonal Competence Outcome 2

 

 

 

 

 

 

In Figure 2, the following assumptions exist: (a) trust and distrust are related but distinct
constructs; (b) trust and distrust are co-existing constructs and (c) bust and distrust exist
within an interaction of a minimum of two parties, with a minimal willingness to be in

19

contact over a period of time and also involves a minimal ability and willingness to
communicate. The patient physician relationship is bounded by both bust and distrust.
The vulnerability of the patient necessitates bust but possible violation of bust may
generate distrust. Both bust and distrust are learned attitudes, emotionsln distrust, there is
an assumption by the bustor that the trustee does or does not have his/her best interest at
heart; and in trust it is the opposite. However, we cannot just will ourselves to trust; cause
must exist in order for trust to develop. “Trust but verify,” a rational trustor is open to
evidence that contradicts his or her trust theory, therefore rational or bounded trust is
partial trust. The rational bustor evaluates the trustworthiness of the trustee based on
perceived evidence and past experience and is constantly up-dating whether or not to
trust; therefore, the attitude of bust can be desboyed by rational justification of the
attitude (McLeod, 2006). “Blind trust,” the faith component of trust (. . .faith is the
substance of things hoped for the evidence of things not seen) limits rational thinking on
trust, because trust inherently involves risk (if verification was possible there would be no
need for trust); attempts to rationalize away the risk also destroy bust.

Unbounded bust that is honored can be valuable because of the tangible and intangible
“goods of trust,” such as “opportunities for cooperative activity, knowledge, autonomy,
self-respect and overall moral maturity;” unbounded bust as a virtue is valuable in and of
itself (McLeod, 2006). Trust allows us to form relationships with others and to depend on
others. Trust leads to cooperative work, and cooperative work provides goods. Trust
minimizes monitoring, which complicates cooperative work. Trust is a form of “social

capital” (Fukuyarna 1995, Hardin 2002). “High-trust” societies have stronger economics

20

and stronger social networks in general than “low-trust” societies (Fukuyama 1995;
Inglehart 1999). Philosophers argue that knowledge depends on bust in the testimony of
others. St Augustine of Hippo, 345 -430 AD, wrote “crede, ut intelligas - believe in order
that you may understand;” and St Anselm of Cantebury, 1133-1109 AD, wrote “For I do
not seek to understand that I may believe but I believe in order to understand. For this I
believe that unless I believe, I should not understand.” Therefore some level of “blind
trust” must exist in addition to rational belief, because an individual cannot verify the
truth of all knowledge. In order to act on one’s belief or to be autonomous one must
“chose and act in accordance with our values, we need to bust ourselves to do so” (
Grovier 1993; McLeod, 2002). Trust therefore is “the very basis of morality” (Baier,
1986)

The following brief discussion highlights four components conbibuting to the
multiplicity of components within the patient-physician interaction. Figure 3, depicts a
conceptual model of coexisting bust and distrust with the selected components of
communication, expectations, valence and congruence. The attitudes determined by bust
and disbust have been described as a positive and negative valence. Expectancy
Violations Theory by M. Burgoon (1991) and JK Burgoon (1993), propose interacting
individuals have pre-interaction expectancies about communication behaviors of another.
An individual perceiving violation of expected communication behavior of another enters
a cognitive-evaluative process wherein the violation is valenced as a positive
confirmation of pre-interaction expectancies or a negative confirmation of pre-interaction

expectancies.

21

Figure 3. A Conceptual Model of Coexisting Trust and Distrust.

 

 

 

 

 

 

 

 

 

Positive or negative valencing of the violation tends to have greater impact
(whether positive or negative) than conformity to expectation. In health communication
attitudinal and behavioral change occurs more fiequently with positive violations of
expectancies (Burgoon, M., 1991). The following relationship is hypothesized. The more
the bustor perceives the trustee’s communication as being congruent and the greater the

meeting of the bustor's expectations by the trustee, then the greater the number of

 

 

 

 

 

 

 

 

 

 

 

 

 

PATIENTS TRUST
Expectation
PHYSICIAN’S O
TRUSTWORTHINESS a
3 Patient- <2 ,Patient’s
L Competence .. g Physician E Decisions
. 5‘ Relationship 5; & Behaviors
Technical a
Q
2.Competence — 5
Interpersonal Congruence
3.Fide1ity
PATIENTS DISTRUST

 

 

22

 

positive expectancy violation the more positive the valence and the more likely the
growth in trust. The more the bustor perceives the trustee’s communication as being
incongruent and the greater the lack in meeting of the bustor's expectations by the bustee,
then, the number of negative expectancy violation is greater. The more negative the
valence, then the more likely the growth in distrust. Research suggests that the human
cognitive system reacts to a state of distrust by automatically inducing the consideration
of incongruent associations or opposite associations to a given message (Schul, Mayo &
Bumstein, 2004). It has been proposed that a state of distrust leads to a difference in
processing information than a state of trust (Schul, et al., 2004). The extent to which
message-incongruent associations are activated differs under the condition of bust and
disbust. A state of distrust appears to generate the question “and what if the information
were false” (Schul, et al., 2004, p678).

The constructs of expectation, congruence, valencing and communication can
serve as theoretical building blocks for tackling the problem of whether bust and distrust
are polar or distinct constructs. They can aid in determining what elements influences the
ratio of coexistence of the bust and disbust within an interpersonal relationship.
Variables define the way a consbuct is to be measured in a specific situation and it is
necessary to match variables to constructs when identifying what needs to be assessed
during the development of theoretical model. Inbritively we believe that trust and distrust
are key consbucts determining the behaviors and choices of individuals.The proposed
conceptual or theoretical framework may be useful when applied to areas of concern such

as the patient-physician interaction and patient participation in clinical bials because it

23

offers potential variables to consider patients’ bust and disbust. The difficulty still
remains in finding more variables that can serve as the operational forms of the two

CODSII'UCIS.

1.7 Theories on Trust, and Distrust in the Interpersonal Interactions

In order to better understand the constructs of trust and distrust within the patient-
physician relationship, this research drew from a number of theories on interpersonal
interactions and trust and distrust that was generated by various disciplines, including
communication, psychology, sociology, anthropology, consumer behavior, marketing,
nursing and medicine. Some of the theories used may not be highly developed or
rigorously tested, however, the utilization of knowledge sterruning from the
epidemiological and the biological sciences aided the adaptation and application of these
theories to this clinical research issue.

It is a general belief that a therapeutic patient-physician relationship engenders
not only healing but also influences health behaviors. The whys and wherefores on how
this occurs, simplistically put, remains puzzling. Scientists in various disciplines have
proposed many theories or systematic methods to help our understanding of events or
situations within the patient-physician interaction. Previous research in this area narrowly
focused on the setting within which the patient-physician interaction occurs and
researchers often ignored the complexity of the system within which the interaction took
place. A broad theory that may aid researchers in an approach to this problem is the
ecological perspective of levels of influence (McLeroy, Bibeau, Steckler and Glanz,

1988)
24

The ecological perspective describes a multi-level interacting approach
emphasizing multiple factors within and across various levels of influence: inbapersonal,
interpersonal, institutional, community factors, and public policy. This research
evaluates the inbapersonal consbucts of patient’s trust and distrust within the context of
the interpersonal patient-physician relationship and their impact on cancer patients’
behaviors as they relate to their retention, attrition and death during a clinical trial. In the
discipline of nursing, (Hupcey and Penrod, 2003; Hupcey, Penrod and Morse, 2000;
Hupcey, Penrod, Morse and Mitcharn, 2001) has served to clarify varying discipline-
specific (medicine, nursing, psychiatry and sociology) scientific concepts of bust and
proposed a more mature interdisciplinary concept of the process of establishing bust.
Their evaluation of hospitalized patients’ trust in health care providers has led to further
development of a model of the process of establishing bust in the patient-provider
relationship with the following structural features: (1) Trust emerges when an identified
health care need can only be met by an health care provider; (2) Trust involves
assessment of risk when relying on another to meet this need; (3) Trust involves
monitoring or testing behaviors that can be both overt and covert; (4) Trust involves a
willing dependence on someone else’s action; (5) Trust evolves with congruent
expectations of actual behaviors of health care providers. Hupcey et al. (2001) identified
“meeting expectations,” as core in the process of developing bust.

Expectation as defined by Random House (2000) is the act of looking for with \
reason or justification. The consbuct of expectation, exemplifies the temporal, attitudinal

and cognitive dimensions of trust. This theoretical model proposes a process of

25

meeting/rewarding expectations over time and the successes or failures in this endeavor
leads to the building or the diminution of trust. Bell, Krazitz, Thom, Krupat and Azari,
(2002) found statistically significant association between unmet expectations within the
context of visit specific value expectations and low patient satisfaction with care, poor
symptom improvement and weaker intention to adhere to physicians’ advice. Unmet
expectations occurred more frequently in younger patients, unmarried patients and
patients with decreased level of bust in their physicians. Patients with a lower level of
trust were more likely to communicate less, have more unmet expectations and
subsequent diminution of trust and subsequent greater symptom severity.

Research in the field of addiction has shown that unmet expectations alter neural
signals within the brain’s reward circuitry, (Sutton, et al. 2003) and signify a
physiological response (neuronal adaptation) to a psychological experience (an un-
rewarded expectation) (Carlezon, Jr. and Wise, 2003). Behavioral changes occur with
repeated un-rewarded expectations; in addiction medicine this process is called
“extinction” (Carlezon, Jr. et al.,2003). Extinction in addiction medicine describes the
decrease in drug seeking behavior by rats repeatedly denied drugs via a mechanism that
previously supplied an addictive drug (an un-rewarded expectation) (Sutton et. al., 2003).
This neuronal adaptation in the brain of rats is biggered by a memory of a rewarded
expectation changing to an un-rewarded expectation (Carlezon, Jr., et al., 2003). Consider
a parallel to “extinction,” not of drug seeking behavior but of bust, repetitive un-
rewarded or unmet expectations results in a decline or “extinction” of bust.

Patient-physician expectations in the context of the clinical relationship carry both

26

psychological and communicative properties and shape the cognitive and affective
aspects of the relationship (Cegela, Socha McGee and McNeilis, et al., 1996;
Cegala,l997). Communication expectancies are functions of cultural and sociological
norms and communication behaviors vary for individuals and groups, and O’Hair (1996)
showed that patients’ preferred certain styles of communication and these preferences
were in actuality expectations. His relational expectancy model, describes both affective
and cognitive processing impacted by previous experiences, expectations and relatiorml
knowledge. The individual subsequently develops goals/plans and a formulated
expectation that is then carried into the interaction. A key feature of the relational
expectancy model is that of expectancy violation, negative expectancy violations
generates relational dissatisfaction in patient—provider communicators; and expectancy
violations induces a level of arousal leading to cognitive and behavioral change.

Carl Rogers, a psychotherapist, proposed an influential theory on the therapeutic
process within interpersonal relationships. Although from a psychotherapy point of view,
this theory is also applicable to human relationships in general. He posited an “underlying
orderliness” in all human relationships that either facilitated relational/personal growth
and openness or inhibited relational/personal growth, facilitating defensiveness and
blockage. Roger’s primary element was labeled congruence and this concept of
congruence was defined as “an accurate matching of experiencing and awareness”
(Rogers, 1961, p339). Congruence was also extended by Rogers to include
communication “an accurate matching of experiencing, awareness and communication”

(Rogers, 1961, p339).

27

Rogers gave the example of a hungry infant, firlly aware of his/her hunger and
expressing this awareness verbally, and was deemed a “congruent” or genuine response.
He then proceeded to give an example of a man exhibiting anger by his tone and gestures
in a discussion with fiiends, but when his actions were labeled as angry he denied with
apparent surprise and sincerity being angry and his fiiends responded by laughing in
disbelief. This example was labeled as “incongruent.” Rogers described the man’s
response as incongruent because of the mismatching of experience and awareness. The
man’s fiiends experience was his angry tones and gestures but the man’s response
described a lack of awareness of his angry tone and gestures. This lack of awareness was
described as “defensiveness or denial.” Roger’s presented yet another example of a
woman at a party exhibiting behaviors signaling boredom by yawning and looking at her
watch. Upon her departure she stated her enjoyment and described the party as delightful.
Rogers labeled this behavior as incongruence between awareness and communication and
described it as “falseness or deceit,” because the woman was aware of her experience of
. boredom but chose to label it otherwise.

An important corollary of the construct of congruence is if a person is fully
congruent then all communication should be within the context of personal perception.
To be fully congruent means all communication describes personal awareness of personal
experience, for example instead of saying “he is stupid” one might say, “I believe he is
stupid.” Increased congruence at any or all level(s) (experience, awareness,
communication) on one or both sides of an interpersonal interaction can lead to: clearer

communication, improved clarity in response, lowered defenses, diminished facades,

28

genuine expressions, accurate listening, increased empathy, understanding, and a positive
regard leading into a relationship with greater unity, integration, and lower conflict and
increased energy for “effective living; change in a direction of greater maturity,” in other
words a highly therapeutic interaction. Incongruence at any or all level(s) can lead to the
opposite.

Rogers, (1961,p344-345) “general law of interpersonal relationships,” assumes
that (a) two people possess a minimal level of willingness to be in contact (b) the ability
and minimum level of willingness to commrmicate with each other, and (c) this occurs
over a period of time. If the previously stated assumptions hold then the following
relationship is proposed to be true. The higher the level of congruence of experience,
awareness and communication of an individual in a relationship, the better the reciprocal
communication which leads to improved psychological adjusbnent and functioning in
both individuals and greater satisfaction in the relationship on both sides. The converse
holds, in that the higher the level of incongruence of experience, awareness and
communication of an individual in a relationship, the lesser the reciprocal communication
which leads to lesser understanding, maladaptive psychological adjusbnent and
functioning in both individuals and greater dissatisfaction in the relationship on both
sides. Roger’s “general law of interpersonal relationships” appears to be another potential
crucial piece of the puzzle, which helps to clarify potential mechanism by which bust and
disbust co-exists in an interpersonal relationship. The following definition of trust
supports this. Trust is conceptualized to exist in an interaction wherein there is a

perception of vulnerability by an individual, the trustor, who after evaluating certain

29

characteristics of another (trustworthiness); the bustor then becomes a willing dependent
upon the goodwill of the trustee (Bair 1986; Jones, 1996 and 1999; Mayer, Davis,

Schoorman, 1995).

1.8 Measurement of Trust and Distrust

Current available scales for measuring patients’ trust in physicians differ in
content, and suffer fi'om limited testing and development (Pearson and Raeke, 2000).
Previously developed scales include: the interpersonal bust measure of Trust in Physician
Scale (Anderson and Dedrick, 1990); the Primary Care Assessment Survey, (PCAS)
(Safran, Kosinski et al, 1998); the Kao-Green Patient Trust Scale (Kao, Green, Davis, et
al., 1998) and the Wake Forest Physician Trust Scale (Hall, Dugan et al, 2001; Hall,
Zheng et al., 2002). The Trust in Physician Scale, a validated 11- item interview-
administered tool with a minimum reported Cronbach or of 0.85, was designed to measure
an individual’s trust in their own primary care physician and consisted of the 3 domains
of dependability, confidence and confidentiality of information (Anderson and Dedrick,
1990). The Primary Care Assessment Survey (PCAS), a validated self-administered
written questionnaire designed to measure primary care performance across different
types of indemnity and managed care delivery systems and consisting of 11 unique
summary scales, 51 questions and 7 distinct elements of primary care performance of
which bust was one. The PCAS bust subscale consisted of 8-items, Cronbach or range of
0.81 - 0.95 with three trust domains of, integrity, agency and competence (Safran,

Kosinski et al, 1998). The Kao-Green Patient Trust Scale is a validated 16-item, later

30

trimmed to 10-item modification of the Trust in Physician Scale designed to measure the
effect of payment method and other elements of managed care on patient bust (Kao,
Green, Davis, et al., 1998, and Kao, Green, Zaslavsky, et al., 1998). The subsequent 10-
item Patient Trust Scale added items to evaluate patient bust, and patient evaluation of
physician confidentiality and reliability in the setting of possible managed care cost and
administrative resbictions and reported Cronbach or of 0.94. The Wake Forest Physician
Trust Scale (Hall, Zheng et al., 2002) is a validated 10-item scale designed to measure
patient bust in physicians in general and consist of four of the five trust domains: fidelity
with two items, competence with three items, honesty with one item, and global with four
items. It excludes the domain of confidentiality.

Thom and Campbell (1997) and Thom, Bloch and Segal (1999) identified seven
behavioral categories of physician behavior that increased patient’s trust from analysis of
focus group data: (1) provide a thorough evaluation of problems; (2) provide appropriate
and affective treabnent; (3) provide communication that is clear and complete (4)
encourage partnership building; (5) express caring; (6) show respect and understanding of
the patient’s experience and (7) demonstrate honesty. The seven behavioral categories
were determined from analysis of four focus group data, and were not clearly defined,
validated or tested for reliability and therefore this did not allow for the determination of
a predictive value of the individual behaviors. In 2001, Thom, et al., reported that
“caring and comfort, technical competency and communication are the physician
behaviors most strongly associated with patient bust.” It is of great interest to note that a

Cochran Review (McKinsby, Ashcroft, Car, Freeman and Sheikh , 2007) reported not

31

finding any published reports of a successful intervention designed to positively impact
patients’ trust in physicians.

The Wake Forest Physician Trust Scale was chosen for this study because it was
developed to measure interpersonal trust and not social trust; and may be more applicable
to our proposed conceptual model. The Wake Forest Physician Trust Scale (Anderson
and Dedrick, 1990; Safi'an, Taira etal., 1998; Kao, Green, Davis, et al.,l998; Kao, Green,
Zaslavsky, et al., 1998) is more strongly correlated with patient satisfaction, patient desire
to remain with a physician, patient willingness to recommend physician to friends and
patient not seeking second opinions, but is less correlated with social bust measures such
as insurer bust, membership in managed care and choice of physician; and equivalent
correlation with lack of disputes with physician, length of patient-physician relationship
and number of patient visits (Mark, Zheng, et. al., 2002) .

Furthermore, in medicine bust, distrust and trustworthiness have been examined
in limited patient populations, and few clinical and organizational context (Cook,
Kramer, Thom et al., 2004). The trustworthiness of medical organizations although an
important research focus in the last decade (Mechanic & Schlesinger 1996; Anderson and
Dedrick, 1990; Safran, Kosinski, et al, 1998), should not preclude vital research on
patient trust and distrust in individual medical personnel (Hall, Zheng et al., 2002 and
Thom and Campbell, 1997). Very few studies have simultaneously evaluated physician
and patient’s trust and disbust (Cook, et al. 2004). This study expands our knowledge on
cancer patient’s bust and distrust in their physician by the simultaneous measurement of

and evaluation of both their effects.

32

Chapter 1

METHODS

2.1 Summary of Design.

Secondary Analysis of a RCCT Data-set.

This study was a secondary analysis of a completed longitudinal randomized
controlled clinical bial (RCCT). The institutional review board at Michigan State
University and all the sites participating in the RCCT project approved this study.
Following consent the enrollment and interview data was entered into a secure web-based
data collecting system. The subsequent data was processed and all possible identifying
data was removed from the data-set used in the secondary analysis.

This secondary analysis evaluated the relationships between the dependent
variable of patient retention, atbition or death during the RCCT and the two independent
variables of patients’ trust and distrust, conbolling for patients’: age, ethnicity, gender,
levels of satisfaction with physician communication, conb'olled and experimental
grouping, symptom severity score, patient mastery and depression (CES-D-20 score). All
data analyses were performed with SAS software, version 9.

The overall study design had two major components. As shown in Figure 4, the
descriptive portion of our study delineated whether there was any relationship between
age/ethnicity/ gender etc. and patient bust, and distrust at baseline before enb'y into the

RCCT.

33

Figure 4. A Schema of the Secondary Analysis and Measured Variables.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

DESCRIPT IVE EXPERIMENTAL STUDY
STUDY
Pre-Intervention: Experiment - Post-Intervention
Baseline Measures Behavioral Outcome
Intervention Measures:
Patient Retention
Patient Attrition
Patient Death
Potential Predictors
T Experimental
Patients’: R Intervention: Patient age, gender,
ethnicity, education
Age U 1). Provide
S Information Patient Trust and
Gender Distrust in Physician
T 2). Assist in
Ethnicity Communication Patient Satisfaction
& with Physician
Education 3). Train in Self— Communication
D care
Depression Patient Symptom
I .
Seventy Scores
Symptom 5
Severity T Control Patient Mastery
R Intervention:
Mastery U Patient Depression
_ _ _ s 1). Provide SW8 ((3539-20)
Satrsfacbon wrth Information only _
physrcran T Patient Group
communication Assignment (conbol,
experimental)

 

 

 

 

 

 

 

 

 

 

The experimental portion of the study tested the propositions that after adjusting for site
of cancer; pre-intervention patients’ bust and distrust conbolled for previously proposed
predictors for attrition, predicted the post-intervention measured outcome of: retention,
atbition and death during the study.

The dependent or outcome variable of patient retention, atbition or death during
the RCCT was determined as follows. Patients were classified as retained in the study if
they completed all three interviews at baseline (prior to randomization), week 10 and
week 20 of the bial. Patients were classified in the atbition group if they refirsed to
continue in the study, to continue the experimental intervention, or to complete any one
of three interviews. Patients were classified in the death group based on reports of
patients’ death and a review of medical records after participants signed consent forms.

The independent or predictor variables of patients’ bust and disbust in the
analyses were treated in three different ways: first as two separate continuous variables,
second as two separate categorical variables with two levels of low or high trust (low
trust [t] /high bust [T']) and low or high distrust (low distrust [d] /high disbust [D]), and
third as two co-existing categorical variables with the four levels of co-existing low or
high bust and low or high disbust: low bust [t]/low distrust[d] or [td]; high bust [T]/low
distrust[d] or [Td]; low bust [t]/ high disbust[D] or [tD]; high bust [T]/high
disbust[D)]or (TD).

The independent conbolling variable of patients’ depression was treated both as a
continuous variable quantified as a mean score and as a categorical variable with two

levels depressed or not depressed. A score _>_ 16 was labeled depressed and < 16 was

35

labeled not depressed. The independent conb‘olling variables of patient mastery, patient
satisfaction with physician communication and symptom severity in the analyses were
always beated as continuous variables and quantified as mean scores. In the analyses the
independent conbolling variables of gender, race/ethnicity, education and intervention
grouping were always treated as categorical variables. Gender had two levels, male or
female; race/ethnicity had two levels, Caucasian or Afiican American, education had 3
levels, some college or more, high school graduate, less than high school graduate; and

intervention grouping had two levels, experimental or control.

The RCCT: Automated Telephone Symptom Management (ATSM)

The RCCT was designed to evaluate the impact of an automated telephone
symptom management program as a behavioral intervention to aide patients’ in the
management of thirteen commonly occurring cancer treabnent related symptoms. The
study utilized the Homelink Service, an automated monitoring and biage system
developed by the University of Michigan Health System. The automated monitoring and
triage system served three main functions: 1) eligibility checking, 2) initial 6-week
screening and event notification and 3) upon reaching threshold, preparation of data for
delivery to either experimental or conb'ol arm of the bial. An Interactive/Automated
Voice Response System (AVR) version of the MD. Anderson Symptom Inventory
(Paice, 2004), provided weekly monitoring of patients’ symptom severity. Patients’
reporting a predetermined symptom severity score threshold score of 2 or greater on a

scale of 0-10 were selected to enter the RCCT. Patients were randomized to the two arms

36

of the bial, consisting of an automated telephone
symptom management (ATS M) — experimental
arm and a nurse-assisted symptom management
(N ASM) — control arm.

In ATSM, patients were referred by the
AVR to the accompanying symptom management
area in the symptom management guide (SMG) if
they reported a symptom severity score or 4 or
greater. ATSM provided information and
education support by directing patients to printed
information provided in the symptom
management guide (SMG). SMG provided written
insbuctions for the management the cancer
b'eabnent related symptoms. Referrals to tabs in
the SMG were recorded by ATSM. Patients were
also reminded to contact their oncologist when
symptoms were urgent (deemed to be a score of 7
on a scale of 0 to 10). SMG was designed to
complement the information and education

provided by medical-caretakers. The symptom

 

Figure 5. A Schema of the
Randomized Controlled Clinical

Trial (RCCT)

 

Patient Consent

 

SCREENING AND TRIAGE
Twice weekly automated telephone
calls for up to 6 weeks to monitor
severity of 13 prevalent symptoms.
1 + symptom 2 2 on a severity scale
of 0—10, patient enters trial

 

Baseline interview

 

Random Assignment

 

SMG sent

 

RAN DOMIZED TRIAL
ATSM

6 weekly automated calls

(week 1-4,6 &8)

Referral to SMG

Oncologist — calls as needed

7 + symptom severity referred to
oncologist

Versus

NASM

6 nurse calls

(week 1-4,6 &8)

Individualized symptom
management

Use of SMG

Oncologist - calls as needed

7 + symptom severity referred to
oncologist

 

Interview week 10 and week 20

 

 

Medical record audit

 

management approaches in SMG is based on National Comprehensive Cancer network

(N CCN) guidelines, evidence-based efficacy provided by RCT, and information form

quasi-experimental studies for the non-pharmacological management of the 17 prevalent

37

 

cancer symptoms. SMG has been used in five previous studies and was well utilized by
the study subjects.

The NASM is a cognitive behavioral problem-solving intervention delivered by
telephone over a period of 8 weeks by a nurse specially b'ained to implement a multi-
dimensional protocol for the management of 17 common cancer and chemotherapy
related symptoms. Interventions are standardized protocols and computer software allows
tracking of the number and severity of all symptoms during the course of the
intervention. Each week all 17 symptoms are assessed, together the subject and the nurse
select and individualize standardized strategies from the intervention themes to address
symptoms at threshold. Components of the four intervention themes includes: 1) self-
care; 2) information, decision-making and problem solving; 3) communication with
providers and 4) counseling and support. The value of NASM as a conbol is based on
proven efficacy of an oncology nurse utilizing a problem solving approach to symptom
management that individualized to the patients’ situation (Given et al., 2004).

The RCCT project was designed to facilitate patient communication with their
providers, with a focus on the development of patients’ communication skills, in order to
improve the treatment and management of their illness. The reader is referred to

Sikorskii, Given, Given, Icon and McCorkle, (2007) for results on the RCCT study.

2.2 Participants and their Participation in the RCCT
The participants selected for this secondary analysis included all the research

patients enrolled in the RCCT study at the time of the secondary analysis. Research study

38

participants were recruited to the RCCT study fiom two comprehensive cancer centers, a
community cancer oncology program and six hospital-affiliated community oncology
centers in the Mid-West. Patient eligibility for study participation was determined by
patient’s care providers and based on information in their medical record. Inclusion
criteria included: age equal or over 21 years, cancer patients who were undergoing a
course of chemotherapy for common solid tumor cancers, including breast, colorectal,
lung and non-Hodgkin’s lymphoma, cognitively intact, English speaking/reading, the
ability to hear and speak via telephone and the possession of a touch-tone telephone.
Patients were excluded if they had other hematological malignancy, beatrnent that
includes bone marrow bansplant or stem cell rescue, and any diagnosis of active (under
beatment) emotional or psychological disorder.

Figure 6, delineates the flow of patient participation (recruitment, retention,
attrition and death) during the entire RCCT (for RCCT details see, Sikorskii, 2007).
Nurse recruiters approached 1,605 eligible cancer patients of which 815 signed informed
consent forms. Nine patients failed to enter the screening and of the 806 patients
screened, 76 patients atbited, two failed to meet the symptom threshold, and 257 entered
a simultaneously run companion bial. Entering the ATSM, RCCT were 471 patients, 34
of which attrited prior to the baseline interview, therefore 437 completed the baseline
interview. The patients were then randomized, 219 to ATSM or experimental arm and
218 to NASM or the control arm. Between the baseline interview and the second
interview at week ten, a total of 41 patients either atbited or died in the ATSM group and

35 patients either atbited or died in the NASM group.

39

Figure 6. A Modified Consort E-Flowchart of Patients’ Participation in the RCCT.
(Modified data from Sikorskii et al. 2007 manuscript.)

Eligible and Approached: N= I605

Consented, N= 815 — 9 (failed to enter screening)
Screened, N=806

Entered study, N=47 1;

Note N=257 entered companion trial

Atb'ition after consent N=76 + 2 (missed symptom
threshold)

 

 

 

 

 

 

 

 

 

NO N/A Is it randomized? YES

 

 

 

 

 

 

 

 

 

 

[ Enrollment ]

Pre-randomization atbition
N=34
No baseline interview

2’ A

Allocated to control NASM, Allocated to intervention ATSM,
N=218 N=218+la

 

 

]

 

 

 

Started first contact N=l9l Started first contact N=200

Allocation

No baseline survey, N= 15 No baseline survey, N= 17
No week 10 survey, N= 20 No week 10 survey, N= 24

 

 

Analyzed N=l75 Analyzed N= 196
(available data at time of analysis) (available data at time of analysis)

it

Note ( la): one patient received no
intervention but completed interviews
at baseline & 20 weeks

i V
Completed intervention, N=167 Completed intervention, N: 180

 

 

 

 

 

 

 

Follow-Up

No intervention but completed N0 intervention but completed
interview N=3 interview N=10

v v

Analyzed N=37l (a total of 437 patients completed the baseline interview)
Excluded from analysis, N= 67 (data collected after analysis)
Excluded from analysis, N= 34 (pm-randomization attrition)

Data Analysis N=37l

Analyzed 196 in conbol and 175 in experimental
Conbol ( 168 retained, 22 attritted and 6 died)
Experimental (150 retained, l9 atbitted and 6 died)

 

 

 

 

 

 

 

 

 

 

 

 

 

Im- II

 

Completing the second interview at 10 weeks, were 167 patients in the ATSM group and
180 patients in the NASM group. In the secondary the numbers differ because the
analysis was conducted prior to the end of the data collection. The actual accrual number
at time of analysis was 434 cancer patients. Note in the qualitative analysis, the sample
size was, n=434; analyzed were n=48 for African Americans and n=368 for Caucasians.
In the quantitative analysis the sample size was, n=371, with n=43 for Afiican Americans
and n=328 for Caucasians. In the secondary analysis conbol or NASM n=196 and
experimental or ATSM n=l 75.

The RCCT research study was powered to detect a statistically significant
difference in the primary outcome measure of the severity index of the 17 core cancer
related symptoms between the experimental and conventional care control group. Power
calculations projected the need for accrual of 175 subjects per group to detect a
meaningful difference. Projected minority accrual of 10-15% of the total study sample
was based on previous accrual rates.

In order to improve data collection and limit missing data points the instruments
was administered via a telephone interview. Patients reported to an interviewer: gender,
birth date, education level, ethnic background, current marital status and number and age
range of household members. Each participant’s medical record was audited following
the end of the 8-week observation, and the status of the patient recorded as continuing in
the study, withdrawal from the study or death.

Information also collected/extracted included: co-morbidities, symptoms,

complications and treatment plans. Data regarding cancer stage, site, and recurrence was

41

collected from medical records after participants signed consent forms. Cancer stage was
coded as early (stage 1 or 2) or late (stage 3 or 4), according to the TNM staging criteria
of the American Joint Committee on Cancer (2003).

The study covered 6 contacts over a period of 8-weeks with data collected at
baseline (after consent but before randomization), at lO-weeks and at 20-weeks. This
timing was implemented in order to evaluate the randomization process, the initial impact
of the measurement and probable drift, and deferred or sustained impact of the
intervention. Prior to randomized assignment to control or experimental group,
consented patients were screened over the telephone to assess the presence of one or
more of the seventeen cancer-related symptoms. Patients scoring a two or higher on one
or more of seventeen cancer-related symptoms were enrolled in the study and

subsequently interviewed.

2.3 Materials
All patient reported data was collected via a telephone interview at baseline (after

consent but before randomization), at 10-weeks and at 20-weeks.

Wake Forest Physician Trust Scale (WFPT S)

The Wake Forest Physician Trust Scale was developed for measuring patients’
trust in their primary care providers (physicians as well as non-physician). The Wake
Forest Physician Trust Scale was chosen for this study because it was developed to

measure interpersonal trust and not social bust, and may be more applicable to our

42

proposed conceptual model. The original scale consists of 10-items with four response
categories: (i) fidelity - 2 items, (ii) competence — 3 items, (iii) honesty - 1 item, and (iv)
global — 4 items with an overall alpha of 0.93 (Hall et al., 2002). The 10-item
questionnaire WFPT S utilizes a Likert 1-5 response categories (strongly agree, agree,
neub'al, disagree, and strongly disagree). Three items (#2, 3, and 8) are negatively
worded. In previous reports, trust was measured by the sum of the 10 item scores, with a
higher score indicating more trust. The Wake Forest Physician Trust Scale has previously
established reliability and validity in a random national sample of HMO members asking
about their primary care providers. At the time of the study no reports were found of the
instrument being used among cancer patients. The coefficient alpha for the patients in

the RCCT was 0.91 in Caucasians and 0.88 in African Americans.

Princess Margaret Hospital Patient Satisfaction with Doctor Questionnaire

(PMH/PSQ—MD) (Loblaw, Bezjak and Bunston, 1999).

A modified version of the PMH/PSQ-MD was used to determine patients’
satisfaction with physician communication in the study. The PMH/PSQ-MD was
developed for use in the outpatient oncology setting, and is specific to patient-physician
interaction. The original scale consists of 29-items asking patients about their satisfaction
with information exchange, interpersonal skills, empathy, and quality of time. Our
modified version consists of the 10 items evaluating information exchange, with an alpha

of 0.92 and established convergent and divergent validity.

43

Symptom Experience Inventory

The cancer symptom inventory was developed by Given et al. (2004).
The inventory measured 17 symptoms (fatigue, pain, dyspnea, insomnia, distress, nausea,
fever, difficulty remembering, lack of appetite, dry mouth, vomiting, numbness and
tingling, diarrhea, cough, constipation, weakness, and alopecia) and related concepts and
includes the 7 most prevalent symptoms (fatigue, pain, dry mouth, insomnia, poor
appetite, constipation, and nausea) experienced by cancer patients undergoing
chemotherapy. Patients were asked whether in a 1-2-week period they experienced a
symptom, yes or no; if yes, they reported fi'equency, severity and limitation imposed
upon daily activity on a scale of 0 (not present) to 10 (as severe as it possibly could be).
For statistical analysis a sum score was calculated and a sum mean score across all
seventeen symptoms was generated. Reliability coefficients of number of symptoms,
severity of symptoms and limitations imposed upon daily activity are 0.71 , 0.78 and 0.71

respectively

Depression — CES-D-20

The Center for Epidemiological Studies-Depression scale (CBS-D) was used to
evaluate patients’ reports of depressive symptoms (Radloff 1977). The CES-D was
developed to measure depression within non-psychiatric general population. The scale
consists of 20-items with four specific response categories: depressed affect, positive
affect, somatic/vegetative, and interpersonal, and one non-specific category. This 20-item

scale assesses the depressive symptoms on a 4-point Likert-type scale (“almost all of the

44

time,” “most of the time,” “some of the time,” and “rarely/none of the time”). The fill!
version of the CES-D20 scale was utilized. A pre-determined score of S 16 dichotomized
the sample as depressed and > 16 as not depressed. The CBS-D has a reliability range of

0.85 to 0.92.

Patient Mastery

The mastery scale is a modified seven-item measure which assesses patient
psychological coping resources or self-care mastery on a 5-point Likert-type scale
(“strongly disagree,” “disagree,” “no opinion,” “agree” and “strongly agree”). The initial
development of this instrument was done by Pearlin and Schooler, 1978. The original
questions were modified to specifically address patients’ mastery of cancer care. The

alpha coefficients for this modified instrument were 0.73 among patients’ in the RCCT.

45

Chapter 2

ANALYSIS AND RESULTS

3.1 Quantitative Analyses and Results.

Basic Descriptive Analyses

In the final tabulation, (see Sikorskii et al., 2007), the RCCT reported that a total
of 437 patients completed the baseline interview and were randomized to the control
(n=218) and experimental (219) groups. The data used for this secondary analysis comes
from 328 Caucasians and 43 African American cancer patients. Note that for this
research, which is a secondary analysis of the RCCT data, the variations in the number
(n) are due to the conduction of the secondary analysis prior to final completion of the
data collection and also some missing data points. Basic descriptive analyses of the socio-
demographic characteristics of the research subjects included: percentage, mean, standard
deviation, and range. The characteristics of the research participants are summarized in
Tables 1, categorical variables reported as percentages and Table 2, continuous variables
reported as mean, range, and standard deviation.

In Table l, Caucasians were approximately seven and a half times more (n=328,
88.4%) than African Americans (n=43, 11.6%). There were three times as many women
(n = 282, 76%) as men (n=89, 24%) in the study. Greater than two thirds the participants
had some college education or higher (11 = 255, 69%). Eighty percent of the participants
were in the high trust group (T) (n=298) and eighty one percent of the participants were

in the high distrust group (D) (n=301). Almost one third the participants were categorized

46

as depressed (n = 115, 31%). Approximately three quarters of the participants were in the
high trust-distrust type (TD, n=270, 73%), eleven percent in the low trust-distrust type
(td, n=42), and eight percent in both the high-trust-low—distrust type (Td, n=28) and low-
trust-high-distrust type (tD, n=31).

In Table 2, the mean age of the participants was about 60 years old, with a range
of 35-89 years old). The mean trust score of study participants was 26.2 out of a
maximum of 30, while the mean distrust score was 17.4 out of a maximum of 20. The
mean for depression score was 12.5 with a wide minimum and maximum score range of 0
- 39. The mean cancer related symptom severity score was 4.3 with a range of 0 - 8.63.
The mean for patient mastery score was 25.9 with a minimum and maximum score range
of 11 - 35. The mean for patient satisfaction with physician communication was 43.3,
with a minimum and maximum score range of 27-50.

Other socio-demographic data not included in Tables 1 and 2 due to higher patient
numbers in a later analysis (Caucasian, n=370 and African Americans, n=49) included:
over half of the participants were married (11 = 253, 60%); the most common site of
cancer among participants was breast (n = 167, 40%), followed by lung (11 = 70, 17%)
then colon (n = 60, 14%); and the vast majority of participants had a diagnosis of late
stage cancer (n = 339, 81%) with 21% of participants having had a recurrence in their
cancer (n = 89).

Descriptive statistics comparing means of patients’ trust by patients’
characteristics are summarized in Tables 3. The level of patients trust was significantly

related to patients’ race/ethnicity, Caucasians were significantly more trusting

47

(mean=26.3) than Afi'ican Americans (mean=24.8), p value 0.009. Second, the level of
patients trust was also significantly related to patients’ depression with a mean trust score
of 26.1 and a p value of 0.052. Third, the level of patients trust was also significantly
related to patients’ mastery, with a mean trust score of 26.2 and a p value of < 0.0001.
Finally, the level of patients trust was also significantly related to patients’ satisfaction
with physician communication, with a mean trust score of 26.2 and a p value of < 0.0001.
Descriptive statistics comparing means of patients’ distrust by patients’
characteristics are summarized in Tables 4. The level of patients distrust was
significantly related to patients’ race/ethnicity, Caucasians were significantly more
distrusting (mean=l 7.5) than Afiican Americans (mean=16.5), p value 0.009. Second, the
level of patients distrust was also significantly related to patients’ depression with a mean
distrust score of 17.4 and a p value of 0.008. Third, the level of patients distrust was also
significantly related to patients’ mastery, with a mean distrust score of 17.4 and a p value
of < 0.0001. Finally, the level of patients distrust was also significantly related to
patients’ satisfaction with physician communication, with a mean distrust score of 17.4

and a p value of< 0.0001 .

Bivariate Analysis

Bivariate analyses of research subject characteristics by clinical trial participation
grouping (retention, attrition and death) were also performed. The p values for the
categorical variables were calculated using Fisher Exact Test (using Proc Freq in SAS)

instead of the Chi square test due to the small sample size. The p values for the

48

continuous variables were calculated using multiple comparison procedures (MCPs) such
as analysis of variance (ANOVA) using Proc AN OVA in SAS and Tukey’s Studentized
Range (BSD-honestly significant difference) test using Proc GLM in SAS. The following
statistical associations between study participants characteristics and clinical trial
participation grouping of retention, attrition, and death of study participants are
summarized in Tables 5 and 6.

Retention, attrition, and death for study participants were n=3 1 8 (86%), n=41
(11%) and n=12 (3%), respectively. In Table 5, females were more likely to stay in the
study when compared to male counterparts 87% versus 82%, with a p value of 0.024.
Non-depressed participants were less likely to drop out of the study than depressed
participants, 7% versus 19% with a p value of 0.002. Participants with a high level of
distrust were less likely to drop out of the study than participants with a low level of
distrust, 9% versus 20% with a p value of 0.002. There were also statistically significant
differing percentages in retention, attrition, and death for study participants by distrust
type (td=low-trust/low-distrust; Td=high-trust/low-distrust; tD=low—trust/high—distrust;
TD=high-trust/high-distrust). Participants with high distrust and low or high trust were
more likely to stay in RCCT when compared to participants with low distrust and high or
low trust, p value 0.008. African Americans were more likely than Caucasians to leave
the study, 33% versus 10 % with a borderline p value of 0.052. Trust category (both high
and low), p value 0.131; ethnicity, p value, 0.052, education, p value 0.353 and
intervention group, p value 1; were not statistically significantly associated with the

clinical trial participation grouping of retention, attrition, and death.

49

In Table 6, the patients who stayed in the study when compared to patients who
left the study were less likely to be depressed (mean score 12.03 versus 15.24, p value
0.032), and had a higher level of distrust (mean score 17.57 versus 16.27, p value
<0.001). Also the patients who stayed in the study when compared to patients who died
during the study had lower total symptom severity score (mean score 4.22 versus 4.80, p
value 0.026), a higher level of mastery (mean score 26.21 versus 21.83, p value <0.001),
and a higher level of trust (mean score 26.26 versus 23.58, p value 0.031).

A higher level of mastery was not associated with patients who stayed or left the trial
(mean score 26.21 versus 24.47, C10.124, 3.354). Age was also not statistically

associated with patient retention, attrition or death during the RCCT, p value 0.495.

Multinomial Logistic Regression

To address our research question we compared research patients who were
retained in the trial (reference group) to patients who attrite from the trial and patients
who died during the trial, utilizing multinomial logistic regression to control for potential
confounders. Study participation (retention, attrition, death) was treated as the dependent
variable in the following analyses. The results explain the odds ratios (OR) of retained
subjects to subjects who attrite and subjects who die. Retained subjects were treated as
the reference class. The exp 0” coefficients in multinomial logistic regression are
interpreted in a similar fashion to odds ratios. Evaluation of patient trust and distrust
controlled by gender, age, race/ethnicity, education, mean symptom severity score, group

assignment (experimental/control), depression/CESD score), patient satisfaction with

50

physician communication and patient mastery were evaluated and included in the model
based on literature support and/or statistical significance at the level of £0.25 in the
bivariate analyses. Reliable income data was not available at time of the analysis. Cancer
stage, cancer site, recruitment site and marital status were evaluated for any significant
contribution to the attrition model; they were not significant predictors for patient
retention, attrition or death, and were not included in our current attrition model. As
supported in the literature, possible interactions between the independent variables (such
as gender and education level or race, and education level) were tested for significant
contribution to the attrition model and none was found. Variance inflation factors were
used to test for collinearity, with a threshold value >5 used for exclusion of candidate
variables from the model. The goodness of fit for the various models was assessed using
the Akaike Information Criterion (AIC) statistic. All models were fitted with the use of
the Proc logistic, link=glogit procedure in SAS (version 9.1.2).

The multinomial logistic regression results are summarized in Tables 7 and 8 and
Figure 10. In Table 7, attrition was referenced to retention. Research subjects ethnicity
(OR 2.890, CI 1.125, 7.427; p-value 0.028), trust (OR 1.270, CI 1.027, 1.597; p-value
0.039) and distrust (OR 0.685, CI 0.559, 0.846, p value 0.0003 were statistically
associated with attrition referenced to retention. In other words: Afiican American
participants were 2.9 times more likely to leave the trial when compared to their
Caucasian counterparts; participants with higher levels of trust were 1.2 times more likely
to leave the trial when compared to their less trusting counterparts and participants with

lower levels of distrust were 1.5 times more likely to leave the trial when compared to

51

their greater distrusting counterparts that stayed in the trial. Patients’ age, gender,
education, symptom severity mean score, intervention grouping (experimental or
control), patients’ satisfaction with physician communication and patients’ mastery were
not statistically associated with attrited referenced to retained participants.

In Table 8, death was referenced to retention. Research subjects female gender
(OR 0.225, CI 0.059, 0.862, p-valuc 0.02); and mastery (OR 0.791, CI 0.656, 0.953, p
value 0.014), were found to be statistically associated with death referenced to retained.
In other words, female participants were 4.4 times less likely to die than their male
counterparts and patients with higher levels of mastery were 1.3 less likely to die than

their counterparts with lower levels of mastery during the RCCT.

3.2 Qualitative Analysis and Results

Validation of the Wake Forest Trust in Physician Scale (WFI‘ PS)
Principal Component and Common Factor Analyses

Principal component analysis and common factor analysis were used to determine
the factor structure underlying the 10 questions/variables of the Wake Forest Physician
Trust Scale (WFTPS). Principal component and common factor analysis are advanced
statistical procedures which can be used in the social sciences to reduce the number of
observed variables into a smaller number of artificial variables (called principal
components or factors) that account for most of the variance in a data set. Principal
component analysis is an orthogonal model and assumes no correlation between the
principal components; this method is used for uncorrelated components. Common factor

52

analysis is an oblique model, assuming correlation between the factors; this method is
used for correlated components. There is evidence to support that trust and distrust are
correlated but distinct constructs and not two extremes of the same construct, (McKnight

et al., 2004; Lewicki et al, 1998; Sitkin et al., 1993) Therefore in our validation analysis

we used common factor analysis.

Common Factor Analysis Steps:

The initial extraction of the factors was undertaken and 10 factors were extracted
and their Eigenvalues determined. The following procedure was followed in order to
determine the number of “meaningful” factors to retain: (a) Eigenvalue-one criterion,
(b) The scree test, (0) the proportion of variance accounted for. The interpretability
criteria that were followed included: (i) minimum of 3 variables with significant loadings
on each retained factor; (ii) determining whether the variables that loaded on a given
factor shared the same conceptual meaning (iii) evaluating whether the variables that
loaded on a different factor measured different constructs (iv) evaluating whether the
rotated factor pattern demonstrated “simple structure,” as defined by: (a) a variable
loading high on one factor and low to zero on others and (b) demonstrating that the

factors load high on some variables and low to zero on others.

Factor Analysis
An a priori criterion of 0.40 was used for inclusion of an item in a factor.

Adequacy of sample size for performing factor analysis indicates about 5 times more

53

Figure 7. Wake Forest Trust Scale Scree Plot

9)

mfidf><2"‘ffl
N

A

 

l (Eigenvalue 4.76)

2 (Eigenvalue 0.96)

8 9
0

V

 

012345678910

NUMBER OF FACTORS

54

 

observations than items are needed for analysis (McCallum, Widaman, Zhang, & Hong,
1999). In this analysis the sample size was 368 Caucasian and 48 Afiican American
cancer patients for 10 items indicating that the sample size was adequate for factor
analysis (>5:1 ratio). Additionally, the Kaiser-Meyer-Olkin measure of sampling
adequacy was .91 in the Caucasian group and .81 in the Afiican American group. These
measures of sampling adequacy are well above the .60 that is recommended by (Kaiser,
1974, see Hatcher, 1994).

Responses to the 10 item Wake Forest Trust Scale were evaluated using squared
multiple correlations as prior communality estimates in common factor analysis. The
principal factor method was used to extract the factors and this was followed by a promax
(oblique) rotation. A scree test (see, Figure 6) suggested two meaningful factors, which
were retained for the rotation. In interpreting the rotated factor pattern, an item was said
to load on a given factor if the factor loading was 0.4 or greater, and was less than 0.4 for
the other. Using these criteria, 6 items loaded on the first factor and 4 items loaded on the
second factor. In reviewing the items that loaded on the two factors there appeared to be a
sharing of some conceptual meaning. In other words the grouped items appeared to
measure the same underlying construct and items for each factor appeared to be
measuring different constructs. The rotated factor pattern did not demonstrate “simple
structure” since most of the items had high factor loading on one factor and near-zero
loadings on the other factor. Therefore we utilized a rotated factor structure matrix; which
is based on standardized regression coefficients and this did demonstrate “simple

structure.” There were at least 3 variables with significant loading on each retained

55

factor; factor 1 consists of 6 variables and factor 2 consists of 4 variables. The variables
loading on a retained factor appeared to have similar conceptual meaning. Factor 1
included, Questions l,5,6,7,9,and 10 and factor 2 included Questions 2,3,4, and 8. The
variables appeared to load on the different factors and appeared to support different
constructs. Question 3, 4 and 5 asked the patient to evaluate, their doctor’s medical skill,
thoroughness and carefulness and his decisions about which medical treatment was best
for the patient. The variables loading on the retained factor 2 had similar conceptual
meaning. The inter-F actor Correlation was 0.52 for factor 1 and factor 2. Factor 1 was

labeled trust and factor 2 was labeled distrust.

56

Chapter 3

CONCLUSION AND CONTRIBUTIONS

4.1 Substantive Contribution

These research findings support the novel use of the previously validated Wake
Forest Trust in Physician Scale as a valid scale for measuring both patients’ trust and
distrust in their physicians. The assumptions of trust and distrust as opposite ends of a
single continuum were not supported by common factor analysis. Subsequent in depth
analyses and a more in-depth review of the literature supported discarding the initial
assumption of trust and distrust as opposite ends of a single continuum and replacing it
with the assumption that trust and distrust are related but distinct constructs. The use of
the 10 item Wake Forest Trust in Physician Scale in the simultaneous measurement of
both patients’ trust and distrust in their physicians makes it a more versatile and efficient
instrument; allowing a more expedient measurement of trust and distrust as related yet
separate constructs.

The results of the factor analysis of the WFTPS support a two factor model in
both Caucasians and Afiican American patients in the RCCT. A comparison factor
analysis was performed on a national dataset utilizing the WFTPS; n=903, with

Caucasians, n=808 and African Americans, n=95. The coefficient alpha for the total

57

population was 0.92, for the Caucasian population 0.93 and for the Afiican American
population 0.88. The WFTPS therefore exhibits internal consistency, with good internal
consistency reliability estimates. A two factor model was also supported by this analysis.
Theoretically there may be two explanations for this result. First, this result may be due
to a response pattern bias, wherein people tend to agree with the wording of the question,
which can lead to a separation of the 10 items in the WFTPS into two factors. The second
explanation could be that the scale is actually measuring both trust and distrust.

This study also contributes to the growing literature on patient trust by examining
cancer patients’ trust and distrust in their physician. The setting was that of a behavioral
intervention randomized controlled clinical trial of cancer patients actively undergoing
clinical treatment. The Wake Forest Trust in Physician Scale was developed in the
general population and an HMO patient population (Hall et al., 2001 and 2002). In the
setting of a cancer diagnosis, trust assumes an even greater significance due to the greater
emotional dimension of the patient-provider interaction; (Arora, 2003) however, there has
been limited reliable and valid measurement of patient’s trust (Pearson and Raeke, 2000).
It was quite reassuring to frnd that 80% of patients in the study reported a high level of
trust in their physician but it was quite surprising to also find that 81% of patients
reported a high level of distrust of their physician. However, only 73% of patients
reported a co—existing high level of trust and distrust. It is therefore important to
understand patients’ trust in and distrust of physicians in the setting of cancer in order to
delineate the impact of an interpersonal interaction on cancer patients’ attitudes and

behaviors.

58

An association exists between patients’ trust, distrust and patients’ satisfaction
(Safran, Taira et al., 1998, Laveist, et al., 2000) but no one has simultaneously evaluated
the three factors in the setting of cancer. This study supports a robust and significant
association between patients’ satisfaction with physician communication and both
patients’ trust and distrust. However, patients’ satisfaction with their physicians’
communication was not a significant predictor on patients’ retention, attrition and death
during the 8-week period of the behavioral intervention in the clinical trial. Previous
research reports a disappearance of race/ethnic difference in patient satisfaction with
adjustments for patients’ trust and medical (hospital) distrust (Laveist, et al., 2000);
however in this research patients’ trust and distrust and patients’ race/ethnicity were
significant predictors for retention and attrition fi'om the clinical trial after controlling for
patients’ satisfaction with physician communication. It is important to note that the effect
of race/ethnicity as a significant factor impacting patients’ retention/attrition fiom the
trial withstood taking into consideration patients’ trust and mistrust.

Finally, our data suggest that for cancer patients participating in a behavioral
clinical trial the level of both trust and distrust was significantly higher in Caucasians
compared to Afiican Americans. Higher distrust and not higher trust was significantly
associated with retention in the clinical trial, and higher trust was associated with attrition
from the clinical trial. In seeking to explain the unexpected phenomena of distrust and not
trust acting as the protective factor in clinical trial participation it may be helpful to
consider that African Americans attrited more than their Caucasian counterparts and were

also both significantly less distrustful and less trusting. Therefore, African American

59

patients were still more likely to leave the trial than Caucasian patients even when their
level of trust and distrust was taken into account. This unexpected turn of event is
revisited in the theoretical contribution section.

Researchers have reported medical mistrust as being independent of race (LaVeist
et al, 2000) but past research also documents that trust differs by race/ethnicity
(Boulware, et al, 2003; Doescher, et al., 2000).The conflicting data on race/ethnicity and
patients’ trust and distrust levels supports the importance of the continued and

simultaneous measurement of trust and mistrust in heterogeneous populations.

4.2 Limitations to the study

We support the use of the Wake Forest Trust in Physician Scale in measuring cancer
patients’ trust and distrust in physicians based on our common factor and confirmatory
analyses; but this is a single study with a relatively small dataset (N=419). Continued and
repeated use of the Wake Forest Trust in Physician Scale in larger data sets will help to
confirm these novel findings. Confirming and extending the trust and distrust constructs
and indicators utilizing path analysis with trust and mistrust as latent variables should

also be undertaken with a larger patient population in the future.

4.3 F uturc Study
A few studies have looked at patient’s trust in their physicians over time (trust as

a “state” versus a “trait”) but have focused on primary care physicians (Thom et al.

60

1999; Hall et al., 2002). This study contributed to the growing literature on patient trust
by examining cancer patients’ trust and distrust in their physicians and has the future
potential to examine cancer patients’ trust in and distrust of their physicians over time.
The development of trust is impacted by time; spanning minutes, hours, days, weeks,
months, and years; and in times of crisis and critical illness the shorter time spans
predominate. (Hupcey, et al., 2001) This investigation of trust is performed in the setting
of patients undergoing chemotherapy, and typifies both a personal crisis and a critical
illness; and an 8-week intervention study should represent a dynamic model in which to
assess the flux of trust and distrust.

The RCCT study utilized a behavioral intervention that provided information and
assistance in communication to randomized intervention and control groups. It is
anticipated that the intervention should positively impact patient trust by improving the
congruence between patient-physician expectations through improved communication.
Increased understanding of the impact of the interpersonal interaction on trust and distrust
over time, should aide in the shedding of light on the concept of patients’ trust in and

distrust of their physicians in the setting of cancer.

4.4 Theoretical Contribution

Supporting Literature
The patient-physician relationship is an interdependent relationship that is also

categorized as a trust relationship. Some essential characteristics of trust are: 1) system

61

level integration; 2) reduction of complexity and 3) a lubricant for cooperation. The
integrative and reductive firnction of trust benefits the social system but the cooperative
function of trust benefits the individual. At the individual level it is assumed that the
individual makes a rational choice to place trust. A proposed model of four elements that
define a trust situation includes: first, a trustor places trust and this allows the trustee to
honor or violate trust. The trustee cannot honor or violate trust without its placement by
the trustor; second, if the trustee honors trust the trustor benefits but if trust is violated the
trustor regrets the placement of trust; third, the trustor voluntarily places resources in the
hands of the trustee without formal safeguards or sanctions; and fourth, a time delay
occurs between the placement of trust by the trustor and the action of the trustee
(Coleman, 1990:97-99).

Figure 8, seeks to summarize a proposed literature-based model of co-existing
trust and distrust relations. It is assumed that trust and distrust are related but distinct
constructs. Trust exists when an individual chooses to be dependent upon another for the
fulfillment of a need and there is no guarantee that the individual will not be at risk for
harm. For a trust relation to exist the trustor must place trust in the trustee. The trustor
can enter the relationship with high trust and low or no distrust or the trustor can have
both high trust and high distrust. Note only the Td and TD trust-distrust type was
considered in this model. The trustee has the choice of honoring or violating the trust of
the trustor. The trustor’s choice of unbounded trust or trust bounded by distrust and the
trustee’s choice to honor or violate the trustor’s trust determine the outcomes for the

trustor and the trustee. The outcomes are labeled: benefits, sufferings and sanctions.

62

Figure 8.

A Conceptual Model of Coexisting Trust and Distrust Relations.

 

Preconditions
l. Trustor must be vulnerable &placing trust in trustee puts trustor at risk

2. Trustor has a need that only the trustee can fulfill.

3. Trustor is willing to be dependent upon the trustee.

4. A Guarantor or third party monitors & sanctions the trustee for trustor.

5. Trustor & trustee possess pre-existing expectations.

6. Trustor & trustee have a minimum level of willingness to be in contact with each
other and possess the ability to comrmmicate with each other

7. Trustor & trustee possess a level of congruence or incongruence of experience,

awareness and communication

 

 

 

 

 

 

 

 

 

 

 

g
E
“5
E
I:
O
U
'U
5
00
.S
.. E; Trustor believes Trustor believes
g “m Trustee is Trustee is
= g, Trustworthy Trustworthy and Untrustworthy
E g Trust >Distrust Trash-Distrust
g :5 ml) or»
‘0—
£ .12
E E UNBOUNDED TRUST BOUNDED TRUST
a a Td)
5 e
I" 3 Trustor Places Trust in Trustee Trustor Places Trust in Trustee
.‘E.’
§ Expectation: Good Outcome Expectation= Good & Bad Outcome
‘3.
E No Monitoring by Tmstor Monitoring by Trustor
E No Sanctions in Place Trustor’s Sanctions in Place
3 Monitoring by Guarantor Monitoring by Guarantor
g Guarantor’s Sanctions in Place 1 I Guarantor’s Sanctions in Place
"3
g The Trustee The Trustee The Trustee The Trustee
g Honors Trust Violates Trust Honors Trust Violate: Trust
Trustor &Trustee Trustor Tmstor &. Trustee Tmstor Experiences
Experience E 'ences Experience Limited Suffering
Un—lirnited Great Suffering Limited Benefits & Trustee Experiences
Benefits & Trustee &Very Limited Greater suffering
Very Limited Experiences Suffering Sanctions
Suffering Limited Benefits
Sanctions
Network Embeddedness:

Social network linkage between the trustor, the trustee and Guarantor.

 

63

 

Benefits are greatest with unbounded trust and honored trust, but are the least with
unbounded trust and violated trust. The mathematics is simple, in a state of unbounded
trust more is invested therefore the potential for loss is greater. Suffering is greatest for
the trustor when unbounded trust is violated; on the other hand the potential for trustee’s
greatest suffering can occur if sanctions are imposed by both the trustor and a third party
acting as a guarantor.

Facilitators of trust within the social context rest upon sanctions for untrustworthy
behavior. Trust emerges, and is established within the social context of an interdependent
relationship and the behavior of the individuals is influenced by the social context within
which the relationship exists. In “Social Networks and Trust,” Buskens (2002) theorizes
that the social context: can provide information to trustors so that they can learn whether
the trustee is trustworthy or not; and also help trustors control an untrustworthy trustee
through sanctions. Buskens, also describes an aspect of the social context labeled network
embeddedness that describes the extent to which the trustor and the trustee are linked to a
third party or guarantor in a social network.

Network embeddedness is weighted by whether the relationship extends past a
business network into a personal network. Knowledge of the individual is also influenced
by the frequency of the interaction. The trustor takes the risk when trust is placed but the
trustee is open to sanctions when trust is violated. Sanctions if perceived as threatening
by the trustee will lead to defensive behaviors that may interfere with the fiduciary
responsibility of the trustee towards the trustor. Another aspect of the social context is

labeled temporal, which describes the interaction over a period of time. Temporal

o4

embeddedness influences the trustor’s opportunities for learning about and controlling the
trustee. The Trustor utilizes their network embeddedness and temporal embeddedness to
gain knowledge of the trustee. Buskens, (2002) proposes that improved understanding of
the precise effect of the social network on trust including the constructs of network and
temporal embeddedness may serve to solve and control trust problems.

A trustee’s trustworthiness is influenced by the short-term and long-term
incentives to honor or violate trust. Figure 9, delineates a game theoretic representation of
coexisting trust and distrust. In this scenario, all four trust-distrust types are represented:
low-trust/low—distrust (td), low-trust/high-distrust (tD), high-trust/low-distrust (Td) and
high-trust/high-distrust (TD). A patient with the td or trust-distrust type invests the least
amount in the trust relation. As documented in figure 9, the payoff amount is minimal,
but the loss to the patient is also minimal. A patient with the tD or low-trust/high-distrust
invests more than the td type but still significantly less than the Td type who invests the
most and therefore has the most to lose. Please note the simplistic mathematical
modeling: suffering is modeled as loses to the patient and benefits modeled as payoff to
both patient and physician. Sanctions are not overtly modeled but sanctions influence the
physician’s decision to honor or violate patient’s trust and also influence the payoff to the
physician.

In revisiting the unexpected result of distrust being a protective factor against
attrition fi'om the RCCT, if one places the patients in the trust-distrust game, then it may
be logical for the Td type patient to be more likely to attrite compared to the tD type who

may have less invested in the study. The expectation of the Td type will be different than

65

the expectation of the tD type; the Td type is more likely to be disappointed than the tD

type and this could lead to attrition from the RCCT.

 

_F_igure 9. A Game Theoretic Representation of a Trust and Distrust Interaction

 

Patient with
Low Trust & Low Distrust
(“0

Patient Places Trust in Physician

Physician
Honors Trust or Violates Trust

Payoff
($5, $5) (-$5, $10)
(Patient Benefits, Physician Benefits)
(Patient Loss, Physician Benefits)

Patient with
Low Trust &High Distrust
(tD)

Patient Places Trust in Physician

Physician
Honors Trust or Violates Trust

Payoff
($10, $10) (-$5, $15)
(Patient Benefits, Physician Benefits)
(Patient Loss, Physician Benefits)

 

Patient with
High Trust &Low Distrust

(Td)

Patient places Trust in Physician
Physician

Honors Trust or Violates Trust
Payoff
($40, $40) (-$20, $60)
(Patient Benefits, Physician Benefits)
(Patient Loss, Physician Benefits)

 

 

Patient with
High Trust & High Distrust
(TD)

Patient places Trust in Physician
Physician
or Violates Trust

Honors Trust

Payoff
($20, $20) (-$10, $30)
(Patient Benefits, Physician Benefits)
(Patient Loss, Physician Benefits)

 

66

 

The tD type is more likely to enter the trial with preconceived sanctions in place, which
may engender a greater sense of control, and foster a greater likelihood of staying in the

RCCT.

4.5. Concluding Statement

This is the first report on the use of the Wake Forest Trust in Physician Scale (WFTPS) in
cancer patients in a RCCT. The WFTPS is a valid measure of patients’ trust in physician.
This research supports that the WFTPS is also a valid measure of both patients’ trust and
distrust in their physicians. In medicine researchers have not wholly embraced the
concept of trust and distrust as related but unique constructs. This novel concept of the
coexistence of trust and distrust in the patient physician relationship shows promise, and
may increase our understanding of why interventions targeting patients’ trust in
physicians alone, have failed in the past (McKinstry et al., 2007; Thorn, 2000; Thom,
Bloch, et al., 1999) to improve patients’ trust in physicians and subsequently alter

measured outcomes.

67

Appendix A- Data Tables and Figures

 

Table 1 - Patients’ Demographics (Categorical Variables)

 

 

Research Subject Characteristics Number Percentage
(N) (%)
Gender
Female N=282 76%
Male N=89 24%
Ethnicity
Caucasian N=328 88.4%
African American N=43 11.6%
Education
Some College or more N=255 69%
High School Graduate N=84 23%
Not High School Graduate N=32 8%
Intervention
Group Control N=l96 53%
Experimental N=l75 47%
Depression
(PCES-D score) Greater than 16 — Depressed N=115 31%
Less than 16 — Not Depressed N=256 69%
Trust Level
High Trust (T) N: 298 80%
Low Trust (t) N= 73 20%
Distrust Level
High Distrust (D) N= 30] 81%
Low Distrust (d) N= 70 19%
Trust and
Distrust Type Low Trust/ Low Distrust (td) N= 42 11%
High Trust! Low Distrust (Td) N= 28 8%
Low Trust/High Distrust (tD) N= 31 8%
High Trust/ High Distrust (TD) N= 270 73%

68

 

Table 2 — Patients’ Demographics (Continuous Variables)

 

 

Research Subject Nmnber Mean and Range Standard

Characteristics (N) Deviation (SD)

Age N=370 Mean=60.1 SD= 12.4
Range 35 — 89 years

Trust N=370 Mean=26.2 SD= 3.5
Range 12 — 30

Distrust N= 369 Mean= 17.4 SD= 2.4
Range 9 —- 20

Depression N=- 366 Mean=12.5 SD= 8.5

Measure Range 0 - 39

CES-D Score

Symptom Measure N= 364 Mean= 4.3 SD= 1.6

(Mean Sum Score) Range 0 — 8.63

Patient Mastery N= 365 Mean=25.9 SD= 4.1
Range 11 - 35

Patient N= 371 Mean= 43.3 SD= 5.3

Satisfaction Range 27 - 50

With Physician

Communication

 

69

 

Table 3 — Patients’ Characteristics Association with Patients’ Trust

 

 

Characteristics N Mean P- value(p)
R — Square (R2)
062516" 231 26.101 0.889
male 89 26 160

Male '

Eflg'mty‘. 328 26.314 0.009
““8”" 42 24 833

African American '
Education
Some College or more :24 :23: 0209
High School Graduate 3 2 25’250
Not High School Graduate '
Intervention Group:

Control 196 25.480 0.0496

Experimental 1 74 26.428
Patient Age 369 26.136 0.086
Depression Measure:

Total CES-D Score 366 26.131 0.052
Symptom Severity
Mean Score 363 26.102 0.707
Patient Mastery 365 26.161 <0.0001, R’= .147
Patient Satisfaction with 370 26.146 < 0.0001, R’ = .690

Physician Communication

70

 

Table 4 — Patients’ Characteristics Association with Patients’ Distrust

 

 

Characteristics N Mean P- value(p)
R - Square (R2)

Gender‘ 280 17.303 0.707

Female 89 17 414

Male '
Eflg'c'w’. 327 17.505 0.009

aucasian 42 16 476

African American ’
Education
Some College or more {2:3 3:3: 0'1 10
High School Graduate 32 16531
Not High School Graduate ’
Intervention Group: 195 1 7.544 0.1 89

Control 174 17.213

Experimental
Patient Age 368 17.380 0.708
Depression Measure: 365 17.389 0.008

Total CES—D

Score
Symptom Severity
Mean Score 362 17.367 0.784
Patient Mastery 364 17.434

< 0.0001, 1?.2 = .090

Patient Satisfaction with 369 17.388 < 0.0001, R2 = .445

Physician Communication

71

 

Table 5 - Patients’ Characteristics Association with Clinical Trial
Participation Grouping: Retention, Attrition and Death

 

 

(Categorical Variables).
Retention Attrition Death P— value
Characteristics N=318 N=41 N=12 (p)
N (%) N (%) N (%)
Gegifgge 245 (87%) 32 (10%) 5 (8%) 0024*"
Male 73 824%) 9 (10%) 7 (8%)
mafia; an 286 (87%) 32 (10%) 10 (3%) 0052*”
African American 32 (44%) 9 (33%) 2 (5%)
Education
Some College or more 221 (87%) 27 (10%) 7 (3%) 0353*"
. 72 (86%) 10 (12%) 2 (2%)
Hrgh School Graduate 25 78°/ 4 130/ 3 190/
Not High School Graduate ( °) 1 °) ( °)
Intervention Group:
Control 168 (74%) 22 (11%) 6 (3%) <.999***
Experimental 150 (65%) 19 (11%) 6 (3%)
Depression Measure:
CES-D Score _>_ 16 88 (77%) 22 (19%) 5 (4%) 0.002***
CBS-D Score < 16 230 (90%) 19 (7%) 7 (3%)
Trust Category
High Trust 2 24 (T) 259 (87%) 32 (11%) 7 (2%) 0.131 ***
Low Trust <24 (t) 59 (81%) 9 (12%) 5 (7%)
Distrust Category
High Distrust 2 16 (D) 267 (89%) 27 (9%) 7 (2%) 0002*“
Low Distrust < 16 (d) 51 (73%) 14 (20%) 5 (7%)
Trust Distrust Type
Low Trust / Low Distrust (td) 32 (76%) 7 (17%) 3 (7%)
High Trust / Low Distrust (Td) 19 (68%) 7 (25%) 2 (7%) 0008*"

High Distrust/Low Trust (tD) 27 (87%) 2 (6.5%) 2(6.5%)
High Trust /High Distrust (TD) 240 (89%) 25 (9%) 5 (1%)

*** P values obtained by Fisher Exact Test, using Proc Freq in SAS

72

 

Table 6 - Patients’ Characteristics Association with Clinical Trial
Participation Grouping: Retention, Attrition and Death

 

 

(Continuous Variables)
Characteristics Retention Attrition Death P- value (p)
N=318 N=41 N=12
Mean Mean Mean
Standard Standard Standard
Deviation Deviation Deviation
Age:
Mean (Std 57.01(11.78) 57.51 (14.05) 61.17(11.54) 0495*
Deviation)
Depression Measure:
Total CES-D Score 12.03(7.56) 15.24 (8.23) l4.17(9.45) 0.032M
Mean (Std Retain-Attrite
Deviation) (CI 0.205, 6.225)
Total Symptom
Severity Score 4.22 (1.56) 4.26 (1.32) 4.80 (1.63) 0.026"
Mean (Std Retain-Death
Deviation) (CI)
Patient Mastery 26.21 (3.90) 24.47 (3.90) 21.83 (6.36) <0.001"
Retain-Attrite
(C10.124, 3.354)
Retain-Death
(CI 1.614, 7.145)
Trust 26.26 (3.42) 26.02 (3.61%) 23.58 0.031"
12 (50%) (3.70%) Retain-Death
4 (17%) (CI 0.289, 5.062)
Distrust 17.57 (2.34) 16.27 (2.73) 16.33 (3.90) <0.001"
Retain-Attrite
(CI 0.375, 2.234)

* P values obtained by using Proc ANOVA in SAS

** P values obtained by Tukey’s Studentized Range (HSD) test using Proc GLM in SAS

73

 

 

Table 7 - Multinomial Logistic Regression Model of Patients’ Attrition

 

 

Referenced to Retained.
Covariates Odds Ratio 95% CI p — value
Age 0.994 0.964, 1.026 0.728
Gender:
Male 1.070 0.419, 2.731 0.888
Female 1.000
Ethnicity:
African American 2.890 1.125, 7.427 0.028*
Caucasian 1.000
Education:
Some College or more 1.000
High School Graduate 1.105 0.461, 2.649 0.982
Not High School Graduate 1.248 0.352, 4.425 0.788
Symptom Severity
Mean Score 1.182 0.895, 1.561 0.240
Intervention Group:
Experimental 0.951 0.456, 1.983 0.893
Control 1.0
Depression 1.017 0.961, 1.076 0.563
Trust 1.270 1.012, 1.594 0.039*
Distrust 0.685 0.559, 0.846 0.0003*
Patient Satisfaction with 0.991 0.872, 1.126 0.888
Physician Communication
Patient Mastery 0.936 0.834, 1.049 0.254
*statistically significant

 

74

 

Table 8 - Multinomial Logistic Regression Model of Patients’ Death

 

 

Referenced to Retained.
Covariates Odds Ratio 95% CI p-value
Age 1.013 0.959, 1.071 0.638
Gender:
Female 0.225 0.059, 0.862 0.030*
Male 1.000
Ethnicity:
Afiican American 2.405 0.450, 12.857 0.305
Caucasian 1.000
Education:
Some College or more 1.000
High School Graduate 0.957 0.175, 5.240 0.151
Not High School Graduate 3.141 0.662, 14.903 0.477
Symptom Severity 1.024 0.646, 1.622 0.921
Mean Score
Intervention Group:
Experimental 0.751 0.198, 2.850 0.674
Control 1.0
Depression 0.966 0.873, 1.068 0.501
Trust 0.978 0.705, 1.356 0.893
Distrust 0.978 0.666, 1.435 0.908
Patient Satisfaction with 0.976 0.787, 1.210 0.823
Physician Communication
Patient Mastery 0.791 0.656, 0.953 0.014*
*statistically significant

 

75

 

Figure 10. Clinical Trial Retention, Attrition. Death & Patients‘ Levels of Trust 81 Distrust

 
   

 
  
  
  

Caucasian Race

 

Attrite from
Clinical Trial

Remain in
Clinical Trial

Male Gender

Die During

  

Distrust Die During

Clinical Trial Clinical Trial

 

   
    
   
 

Low
Patient Mastery

  
  

Remain in Attrite from

\
‘ Clinical Trial

   
    

  

’African American Race —>

76

Figure 11. Trust-Distrust Type by Race.

Trust-Distrust Type by Race

F
r
e
q
u
e
n
c
Y

 

Trust-Distrust

 

77

Appendix B — WFTPS
Wake Forest Trust in Physician Scale (10 item scale)

1. [Your doctor] will do whatever it takes to get you all the care you need.
0 Agree

Strongly Agree

Neutral

Disagree

Strongly Disagree

0000

2. Sometimes [your doctor] cares more about what is convenient to him/her than
about your medical needs.

Agree

Strongly Agree
Neutral

Disagree

Strongly Disagree

130000

3. [Your doctor]’s medical skills are not as good as they should be
Agree

Strongly Agree

Neutral

Disagree

Strongly Disagree

D

01300

4. [Your doctor] is extremely thorough and careful.
Agree

Strongly Agree

Neutral

Disagree

Strongly Disagree

D

[31300

5. You completely trust your doctor’s decisions about which medical treatments are
best for you.
D Agree

Strongly Agree

Neutral

Disagree

Strongly Disagree

001313

78

Wake Forest Trust in Physician Scale (10 item scale, continued).

6.

10.

[Your doctor] is totally honest in telling you about all the different treatment
options available for your condition.

Cl Agree

Strongly Agree

Neutral

Disagree

Strongly Disagree

00013

[Your doctor] only thinks about what is best for you
Agree

Strongly Agree

Neutral

Disagree

Strongly Disagree

El

[3000

Sometimes [your doctor] does not pay full attention to what you are trying to tell
him or her

0 Agree
D Strongly Agree
Cl Neutral
El Disagree

:1 Strongly Disagree

You have no worries about putting your life in [your doctor]’s hands
Agree

Strongly Agree

Neutral

Disagree

Strongly Disagree

D

00130

All in all, you have complete trust in [your doctor]
Agree

Strongly Agree

Neutral

Disagree

Strongly Disagree

D

DUDE!

79

 

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