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By Dana Tzur-Bitan Is the Looming Maladaptive Cognitive Style a Central Mechanism in the (Generalized) Anxiety – (Major) Depression Comorbidity: An Intra-Individual, Time Series Study Thesis submitted in partial fulfillment of the requirements for the degree of “DOCTOR OF PHILOSOPHY” by Dana Tzur-Bitan Submitted to the Senate of Ben-Gurion University of the Negev May 2011 Beer-Sheva Is the Looming Maladaptive Cognitive Style a Central Mechanism in the (Generalized) Anxiety – (Major) Depression Comorbidity: An Intra-Individual, Time Series Study Thesis submitted in partial fulfillment of the requirements for the degree of “DOCTOR OF PHILOSOPHY” by Dana Tzur-Bitan Submitted to the Senate of Ben-Gurion University of the Negev Approved by the advisor Approved by the Dean of the Kreitman School of Advanced Graduate Studies May 2011 Beer-Sheva ii This work was carried out under the supervision of Prof. Nachshon Meiran and Prof. Golan Shahar In the Department of psychology Faculty of Humanities and Social Sciences. iii Acknowledgments First and foremost, I would like to thank my advisors, Professor Nachshon Meiran and Professor Golan Shahar, for their guidance and support throughout the past six years. To Proffesor Meiran, who has constantly challenged me to critical thinking and encouraged me to experiment, for carrying a positive and optimistic view, and for balancing my emotionality with a rationale and professional attitude. To professor Shahar, for mentoring my development as a psychologist and encouraging me to peruse my inner passions, for being genuinely interested in my success, and for taking an active part in my professional and personal growth. Thank you both for fruitful discussions, financial and moral support, and for sharing your knowledge and skills with me. I would like to deeply thank Professor David Steinberg, the head of school of mathematics in Tel Aviv University, for providing statistical and mathematical consultation. I would like to express my gratitude to the ISEF foundation, for providing me with financial support through 4 years of my phd studies. Not less important, I would like to thank the longitudinal phase participants, RG, RS, and HB, for letting me into their world and sharing their thoughts, feelings and experiences with me. To my dearest Colleagues, who are in essence my friends, for truly being there for me when I needed the most. Last but not least, I would like to thank my family: my mother, for baring the anxiety of my long distance travelling and for constantly praying, literally, for my health and success; to my mother and father in law, for countless hours of babysitting. To my wonderful husband, Daniel, for providing me with everything I need, and not a thing less. You have been the most stable and closest comfort, a true partner, and I love you. And for my beautiful, intelligent sons, Har’el and Yali, for making this journey a challenge at which I am especially proud to surmount. iv To the men in my life: Daniel, Har’el and Yali v Contents Abstract …………………………………………………………….……….………1 1. Introduction …………………………………………………………….……....……5 1.1 The Co occurrence of Anxiety and Depression Disorders……………........……5 1.2 The need for multidimentional assessment of anxiety and depression….....……6 1.3 Explanatory models for the study of anxiety and depression comorbidity…...…8 1.4 The dynamic nature of anxiety and depression…………………………..…..…10 1.5 Exploring intra-individual dynamics using time series analysis…………..……11 1.6 Application of TS analysis in human behavioral sciences………….…....……..12 1.7 Summary of study objectives…………………………………….……………..15 2. Methods …………………………………………………………………….……….. 16 2.1 Participants………………………………………………………………..…….16 2.2 Procedure……………………………………………………………….….……17 2.3 Assessment…………………………………………………………...…..….….17 2.4 Data Analysis………………………………………………………………..….19 2.4.1 General overview of statistical methodology……………......…...19 2.4.2 Statistical analysis and mathematical procedure………….….…..22 2.4.2.1 Stationarity examination and pre-transformations……….….…...24 2.4.2.2 ARIMA(p,d,q) modeling…………………………………...……27 2.4.2.3 Granger Causality Test……………………………………..…….33 2.4.2.4 Transfer Function Modeling……………………………….....….34 3. Results ………………………………………………………………………..…...…38 3.1 Step 1: Modeling each series separately………………………………..……....38 (how past levels of the series determine its current levels)…………………..…….38 3.2 Step 2: Granger Causality Tests…………………………………………...……40 vi 3.3 Step 3: TFM……………………………………………………………..….....…43 Estimating the size and positive/negative directionality of the causal influences.......43 3.3.1 Within disorders…………………………………………….…...45 3.3.1.1 Within depression………………………………...…...45 3.3.1.2 Within anxiety…………………………………...……46 3.3.2 Between disorders………………………………………….……47 4. Discussion ……………………………………….……………………………...……. 48 5. Limitations ....................................................................................................................51 6. Conclusions ...................................................................................................................53 7. References ……………………………………………………………………....……. 55 8. Appendixes ……………………………………………………………………………………..……..67 - Appendix I……………………………………………………………………..……68 Summary of ARIMA models fitted to 8 collected series of each participant …. ……...…….68 -Appendix II…………………………………………………………………….…….70 Final transfer and noise function for between anxiety and depression components…….…. …70 -Appendix III………………………………………………………………......71 Final transfer and noise function within anxiety and depression components .......................71 vii List of Tables Table 1. Summary of collected series in each data set………………….......….………22 Table 2. Mathematical formulation of MA, AR, and ARMA processes….…........……29 Table 3. Parameter Estimates and diagnostics statistics for Hopelessness in Participant RS…………………………………………………………….................…...........……30 Table 4. Estimated models, parameter diagnostics and correlations for the series Hopelessness in Participant RS………………………………………....…..........……..32 Table 5. Mathematical formulation of the Granger Causality Test………….........……34 Table 6. Mathematical formulation of the transfer and noise function…….......………35 Table 7. Model Testing in of “Helplessness” as input and “Depression Symptoms” as output in participant HB……………………………………………….......…..……38 Table 8. Summary of ARIMA models fitted to 8 collected series of each participant…………………………………………………………………….......…….39 Table 9. Significant and marginal Granger’s causality (F-tests)………….….......…….41 Table 10. Transfer and Noise Function Models of pairs showing Granger Causality within each disorder construct…………………………………….......…….44 Table 11. Transfer and Noise Function Models of pairs showing Granger Causality between anxiety components and depression components…………………….......…..45 viii List of Figures Figure 1. Flow chart of overall Analytic procedure in the current study…...……….23 Figure 2. Plots of the original series of participant RS, for evaluation of Stationarity………………………………………………………………….………..24 Figure 3. Autocorrelation and Partial autocorrelation plots for series Hopelessness in participant RS……………………………………………………………...……..25 Figure 4. Hopelessness series pre and post first order differencing and stationarity tests of the series after differencing……………………………....….….26 Figure 5. Cross Correlation Function of series “helplessness” as input and series “depression symptoms” as output in participant HB…………………………..37 Figure 6-8. Visual representation of causal network as detected by Granger Causality Test in participants RS, HB, RG, respectively………….…………………42 ix Abstract The high prevalence of anxiety and depression co-occurrence has been investigated and documented extensively in the past two decades. The disabling nature and poor prognosis in comparison to its pure presentation, along with the familial and financial burden associated with it, has caused the question of etiology to be a topic for ongoing research. Yet, in spite of ongoing and persistent clinical and empirical search, it seems that the underlying mechanisms of anxiety and depression comorbidity are still poorly understood. Integrating the various findings related to this complex and multi-dimentional phenomena, explanatory models focus on the exploration of the underlying mechanism causing these two clusters of disorder to co-appear. The more traditional approach is based on the shared factor hypothesis, which pertains to the possibility that a higher order psychopathological factor underlies both disorders. Yet, recent approaches suggest the exploration of causation models, which targets one disorder (or one of its components) as the cause of the other, or, alternatively, suggest reciprocal causality. Such causal relations are usually established by the temporal precedence of one disorder relative to the other, yet longitudinal studies have yielded mixed results regarding the exact pattern of presentation and failed to give a clear answer regarding the causal trajectory of these two disorders. Exploring such possible causal trajectories, I examined the dynamic unfolding of anxiety-depression comorbidity while emphasizing its multifaceted and intraindividual nature. An intensive time series design was employed, whereby three young adult patients diagnosed as suffering from co-morbid Generalized Anxiety Disorder (GAD) and Major Depression Disorder (MDD) were followed daily for a 1 period of 6 months. Daily reports included affective states, cognitive vulnerability, and symptoms
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