TREATMENT DELIVERY: IMPROVING PSYCHOTHERAPEUTIC RESULTS BY INTEGRATING AFFECTIVE FORECASTING PRINCIPLES By EMILIA RUTH BROWN A dissertation submitted in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY WASHINGTON STATE UNIVERSITY Department of Psychology JULY 2016 © Copyright by EMILIA RUTH BROWN, 2016 All Rights Reserved © Copyright by EMILIA RUTH BROWN, 2016 All Rights Reserved To the Faculty of Washington State University: The members of the Committee appointed to examine the dissertation of EMILIA RUTH BROWN find it satisfactory and recommend that it be accepted. _____________________________________ Paul Kwon, Ph.D., Chair _____________________________________ Bruce R. Wright, M.D. _____________________________________ Sarah L. Tragesser, Ph.D. ii ACKNOWLEDGMENT I would like to thank my advisor, Paul Kwon, Ph.D., for his mentorship and help on this project. In addition, I would like to thank my committee that included Bruce R. Wright, M.D., and Sarah L. Tragesser, Ph.D. for their time and energy. A special thanks goes out to Melissa Falkenstern for her partnership in creating the overall research study in which my data was collected. iii TREATMENT DELIVERY: IMPROVING PSYCHOTHERAPEUTIC RESULTS BY INTEGRATING AFFECTIVE FORECASTING PRINCIPLES Abstract by Emilia Ruth Brown, Ph.D. Washington State University July 2016 Chair: Paul Kwon Research suggests that factors within the therapeutic environment such as the therapeutic alliance and client motivation are strongly tied to treatment success, yet the majority of psychotherapy research focuses on overall treatment modules and/or intervention tasks rather than the specific ways therapists might influence their clients through the way treatments are delivered. This research experiment integrates affective forecasting (AF) research to study whether the delivery of a psychotherapeutic intervention affects participants’ level of impact bias, treatment participation, and outcome. Analyses were conducted on data collected from a longitudinal online experiment completed Fall 2013 – Spring 2014 that randomly assigned participants to one of three conditions: delivery, delivery AF, or control. It was predicted that delivery condition and AF levels would affect participation and outcome variables. Analyses revealed that the manipulation was unsuccessful at creating a significant difference in AF levels across the intervention groups. Levels of AF were associated with length of time spent on the task at T-1 and college adjustment. Results had small effect sizes, suggesting that significance was related to the large sample size. Limitations of the study and future directions were discussed. iv TABLE OF CONTENTS Page ACKNOWLEDGEMENTS ....................................................................................................... iii ABSTRACT ............................................................................................................................. iv-v LIST OF TABLES ...................................................................................................................... vi CHAPTER 1. INTRODUCTION ................................................................................................ 1-15 Affective Forecasting: Impact Bias .................................................................. 4-8 Delivery of a Task: Adjusting for Impact Bias ............................................... 8-12 Intervention Task: Pennebaker’s Expressive Writing Task .......................... 12-14 Present Study ................................................................................................ 14-15 2. METHOD ........................................................................................................... 15-17 3. MEASURES ....................................................................................................... 17-19 4. RESULTS ........................................................................................................... 19-23 5. DISCUSSION ..................................................................................................... 23-26 REFERENCES ..................................................................................................................... 27-35 APPENDIX A. APPENDIX A: THREE EXPERIMENTAL CONDITIONS ............................. 36-39 B. APPENDIX B: INTERVENTION AND CONTROL TASKS .......................... 40-41 C. TABLES ............................................................................................................. 42-49 v LIST OF TABLES 1. Table 1. Means and Standard Deviations of Variables .......................................42 2. Table 2a. Summary of Multiple Regression Analysis for Effects of AF and Delivery Group on Time Spent on Task at Time-1 ............................................43 3. Table 2b. Summary of Multiple Regression Analysis for Effects of AF and Delivery Group on Time Spent on Task at Time-2 ............................................44 4. Table 3. Correlations Between Outcome Variables at T-1 ................................45 5. Table 4a. Summary of Multiple Regression Analysis for Effects of AF and Delivery Group on Change in Anxiety Symptoms .............................................46 6. Table 4b. Summary of Multiple Regression Analysis for Effects of AF and Delivery Group on Change in Depression Symptoms ........................................47 7. Table 4c. Summary of Multiple Regression Analysis for Effects of AF and Delivery Group on Change in Satisfaction with Life .........................................48 8. Table 4d. Summary of Multiple Regression Analysis for Effects of AF and Delivery Group on Change in College Adjustment ............................................49 vi Introduction Use of stereotypically female and racial minority names in an email request to meet with professors resulted in biased responding from professors in more lucrative academic departments across the United States (Milkman, Akinola, & Chugh, 2012). When providing one’s name, including a middle initial resulted in being rated higher in status and receiving higher scores on writing evaluations (Van Tilburg & Igou, 2014). These headlining articles and others have made social cognitive research a hot topic in recent years due to the emphasis on how seemingly miniscule differences in the delivery of information can affect perception. This research highlights the malleability of our thoughts, emotions, and behaviors based on subconscious responses to the manner in which information is provided. Despite the variety of areas in which this information could be used, as of yet most of this research has remained in the general domains of social psychology and business. Evidence has been accumulating that suggests the need for integrating this information into the domain of clinical psychology in order to ascertain the role of social cognitive factors in the psychotherapeutic process. Specifically, researchers have found little difference between the overall efficacy and effectiveness of the evidence-based treatments used today, often finding variability between therapists rather than treatment type (Luborsky et al., 2002; Kim, Wampold, Bolt, 2006; Serlin, Wampold, & Levin, 2003). When differences have been found, many of these findings have been variable and appear to largely result from therapist allegiance, as the psychotherapy found to be statistically superior is typically the one most used and researched by those conducting the experiments (Elkin, 1999; Falkenström, Markowitz, Jonker, Philips, & Holmqvist, 2013; Luborsky et al., 1999). However, evidence has been found for psychotherapeutic variability among therapists, despite trends to increase standardization (Elkin, 1 1999; Kim et al., 2006). In fact, superior therapeutic outcomes have even been found for a subset of therapists that is independent of theoretical orientation and treatment style (Okiishi, Lambert, Nielsen, & Ogles, 2003). Given this evidence, researchers have been exploring alternative components of therapy. Despite the tendency to ignore the variability in therapists within intervention studies, research has revealed that therapists often should be considered a random factor in statistical analysis due to their variability (Elkin, 1999; Serlin et al., 2003). The magnitude of the therapist effect varies between studies; however, the average therapist effect in treatment outcome studies is believed to be between 5-10% (Crits-Christoph & Mintz, 1991; Wampold & Brown, 2005). One of the primary causes of this therapist effect may be between-therapist differences in ability to implement Rogerian techniques (Zuroff, Kelly, Leybman, Blatt, & Wampold, 2010) and develop the therapeutic alliance (Baldwin, Wampold, & Imel, 2007). However, in terms of explaining the actual differences in this ability, researchers of the therapist effect note that “a wide variety of characteristics could be pertinent, including personality traits, interpersonal styles, interpersonal skills, and preferred therapeutic strategies and interventions” (Zuroff et al., 2010, p. 693). In fact, for decades researchers and clinicians have noted the importance of social influence within the context of psychotherapy (Goldfried & Davila, 2005; Goldstein, 1966; Strong, 1968). In this paper, I argue for the further incorporation of social cognition concepts into research on psychotherapy in order to identify and better understand the variability between therapists. Specifically, I am suggesting