The Roles of Attachment, Depression, and the Working Alliance in Predicting Treatment Outcomes

110 Pages·2017·0.95 MB·English

by  Ethan Loper Bliss

University of Miami
Scholarly Repository
Open Access Dissertations Electronic Theses and Dissertations
2009-09-23
The Roles of Attachment, Depression, and the
Working Alliance in Predicting Treatment
Outcomes in Chronic Pain Patients Seeking
Physical Therapy Services
Ethan Loper Bliss
University of Miami, [email protected]
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Bliss, Ethan Loper, "The Roles of Attachment, Depression, and the Working Alliance in Predicting Treatment Outcomes in Chronic
Pain Patients Seeking Physical Therapy Services" (2009).Open Access Dissertations. 301.
https://scholarlyrepository.miami.edu/oa_dissertations/301
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UNIVERSITY OF MIAMI

THE ROLES OF ATTACHMENT, DEPRESSION, AND THE WORKING ALLIANCE
IN PREDICTING TREATMENT OUTCOMES IN CHRONIC PAIN PATIENTS
SEEKING PHYSICAL THERAPY SERVICES

By

Ethan L. Bliss

A DISSERTATION

Submitted to the Faculty
of the University of Miami
in partial fulfillment of the requirements for
the degree of Doctor of Philosophy

Coral Gables, Florida

December 2009
©2009
Ethan L. Bliss
All Rights Reserved
UNIVERSITY OF MIAMI

A dissertation submitted in partial fulfillment of
the requirements for the degree of
Doctor of Philosophy

THE ROLES OF ATTACHMENT, DEPRESSION, AND THE WORKING ALLIANCE
IN PREDICTING TREATMENT OUTCOMES IN CHRONIC PAIN PATIENTS
SEEKING PHYSICAL THERAPY SERVICES

Ethan L. Bliss

Approved:

________________________ ________________________
Brian Lewis, Ph.D. Terri A. Scandura, Ph.D.
Assistant Clinical Professor of Dean of the Graduate School
Educational and Psychological Studies

________________________ ________________________
Blaine Fowers, Ph.D. Kent Burnett, Ph.D.
Professor of Educational and Associate Professor of Educational
Psychological Studies and Psychological Studies

________________________
Carol Davis, DPT, Ed.D.
Professor of Physical Therapy
BLISS, ETHAN (Ph.D., Counseling Psychology)
The Roles of Attachment, Depression and the Working (December 2009)
Alliance in Predicting Treatment Outcomes in Chronic
Pain Patients Seeking Physical Therapy Services.

Abstract of a dissertation at the University of Miami.

Dissertation supervised by Professors Brian Lewis and Blaine Fowers.
No. of pages in text. (102)

Psychosocial variables such as attachment style, depression and the working alliance
were examined as predictors of treatment outcomes in the context of chronic pain patients
receiving physical therapy. Four treatment outcomes were examined: change in pain
severity, change in pain interference, patient satisfaction with physical therapy services
and patient compliance with treatment recommendations. A model of the interplay
between depression and chronic illness presented by Katon (2003) was used as a
framework for the current model.
Two main hypotheses were suggested. (1) The working alliance is positively related
to treatment outcomes. (2) Depression is negatively associated with treatment outcomes.
Data were gathered at three outpatient rehabilitation clinics and the physical therapy unit
of a multidisciplinary pain clinic in two Midwestern cities. A total of 59 subjects
participated and regression analyses found evidence supporting both main hypotheses.
The working alliance was found to be positively correlated to the change in pain severity,
the change in pain interference, patient satisfaction and patient compliance. Depression
was found to be negatively correlated to the change in pain interference, patient
satisfaction and patient compliance. Implications for physical therapists working with
chronic pain patients include clinical recommendations for developing a good working
alliance and screening for depression.
Dedication

For Katie, Noah and Aidan
iii
Acknowledgements

Many people supported me during the preparation of this document. I can only
hope to name a few and beg forgiveness from the ones I miss. First, I would like to thank
my family, Katie, Noah and Aidan, for their love and support during the entire process. I
want to acknowledge the co-chairs of my committee, Brian Lewis and Blaine Fowers,
whose patience and diligence were essential to the completion of my degree. All the
people at Bloomington Hospital and Indianapolis’ Center of Pain Management who
helped me gather my data deserve more than my gratitude, because without them I would
have languished in ABD limbo forever! The Center for Aging at UM also provided me
with grant money for my data collection. My peers during my coursework and internship
taught me that I was not alone during this journey. Thanks to my supervisors that assured
me that finishing the degree was not only possible but worthwhile! Finally, I need to
thank the University of Miami’s Graduate School and Wanda McSwiney, specifically, for
supporting my graduate education through the UM Fellowship and with an assistantship
that allowed me to attend classes and have a family with a modicum of grace. Thank you
all. We did it!
iv
TABLE OF CONTENTS

Page

Chapter

1 INTRODUCTION ......................................................................................... 1

2 LITERATURE REVIEW .............................................................................. 5

3 METHODS ...................................................................................................... 29

4 RESULTS ........................................................................................................ 36

5 DISCUSSION .................................................................................................. 52

References .............................................................................................................. 68

Appendix

A Changes made to research protocol in chronological order ............................. 76

B Demographics Form......................................................................................... 78

C Phone script used with participants for informed consent and data collection 80

D Self-report measures ........................................................................................ 87

E An illustration of a reflected inverse transformation of data ........................... 93

F Results using raw WAI and PSQ18 data ......................................................... 96

v
Chapter 1

Introduction

Healthcare providers recognize the power of the current model of medicine and
also struggle with its limitations. For example, ―The medical model is dead - Long live
the medical model,‖ reads the title of a recent British Journal of Psychiatry article (Shah
& Mountain, 2007) that discusses the ambivalent feelings surrounding current medical
practice. The prevalent medical model, sometimes called the biomedical model, stresses
the importance of scientifically based diagnoses and the application of tested therapies to
achieve medical cures. Critics of the diagnose-treat-cure model such as Engle (1977) do
not argue with the powerful results of the biomedical model, but point out that many
diseases do not fit into its mechanistic assumptions. Ill people should not be treated like
broken machines. Unlike malfunctioning machines, the causes of certain illnesses are
often unclear. Examples include chronic conditions such as chronic pain, depression and
diabetes, which have unclear etiologies and are often unresponsive to treatments (Turk &
Melzach, 2001). Engel (1977) called for the development of a biopsychosocial model of
medicine that incorporates social and psychological aspects of disease genesis and
treatment. Katon (2003) developed one such model that examines the interplay between
chronic illness, psychological conditions such as depression, and the social context of the
person being treated.
Two aspects of the biopsychosocial model are understudied. The first is related to
how the relationship between patient and healer influences treatment outcomes. The
second is connected to how psychological illness influences physical illness.
1
2
Some of the loudest critics of the biomedical model have been mental heath
service providers (e.g., Engel, 1977; Shah & Mountain, 2007) due to the nature of the
illnesses these medical professionals treat. With advances in technology and knowledge,
more biological causes of mental illnesses will be found. However, mental health
providers have relied on non-targeted treatments like talk therapy and tranquilizing
medications to address their patients’ illnesses. Both the causes of mental illness and the
effective treatments seemed non-specific and necessitated the development of a
biopsychosocial model that focused on aspects of healing beyond specific diagnosis and
targeted therapies (Engel, 1977). The therapeutic relationship or working alliance that
occurs between psychotherapists and their patients is one such biopsychosocial variable
that has been the focus of study for over 30 years (Martin et al., 2000).
In their review article, Martin et al. (2000) determine that the working alliance
accounts for about 5% of the variance in treatment outcomes in psychotherapy. The
current study seeks to determine whether a similar relationship occurs in a non-mental
health patient/provider relationship. Research related to the working alliance in medical
settings is not as focused as it is in the mental-health field. However, aspects of the
working alliance construct have been shown to influence medical outcomes. Examples
include: communication (Hurwitz et al., 2005); agreement on treatment (Kerese et al.,
2004), and treatment adherence (Pulliman et al., 2003). A study that directly measures the
working alliance construct as defined within the significant body of psychotherapy
research in a non-mental health setting is needed.
The second central question addressed in this study is how depression influences
the treatment outcomes of illnesses like chronic pain. Chronic illnesses account for 75%