Inflammation-Associated Mood Deterioration and the Degradation of Affective Climate: an Agent-Based Model
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INFLAMMATION-ASSOCIATED MOOD DETERIORATION AND THE DEGRADATION OF AFFECTIVE CLIMATE: AN AGENT-BASED MODEL by GARETH JOHN CRAZE Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Organizational Behavior CASE WESTERN RESERVE UNIVERSITY August, 2020 CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES We hereby approve the thesis/dissertation of Gareth John Craze candidate for the degree of Doctor of Philosophy*. Committee Chair Corinne Coen Committee Member Ronald E. Fry Committee Member Kurt C. Stange Committee Member Youngjin Yoo Date of Defense Thursday July 16th, 2020 *We also certify that written approval has been obtained for any proprietary material contained therein 2 DEDICATION I dedicate this dissertation to everyone in the world suffering from mental illness. And to Dora the Explorer, who represents everything most noble about intellectual pursuits: feverish curiosity, a sense of wonder and adventure, and having a monkey for a sidekick. 3 TABLE OF CONTENTS CHAPTER 1: INTRODUCTION 12 CHAPTER 2: LITERATURE REVIEW 20 2.1 Affective Climate 20 2.2 Affective Events 22 2.3 Mood and Affective Climate 24 2.4 Mood Contagion 25 2.5 The Role of Leader Mood 28 2.6 Inflammation-Associated Mood Deterioration 30 CHAPTER 3: METHOD OVERVIEW 33 3.1 Agent-Based Modeling: General Overview 33 3.2 Agent-Based Modeling: Present Study Justification 35 CHAPTER 4: MODEL ASSUMPTIONS AND PARAMETERIZATION 45 4.1 Model Assumptions 45 4.2 Mood States and Affective Climate 47 4.3 Inflammation-Associated Mood Deterioration 49 4.4 Affective Events 56 4.5 Mood Contagion and Leader Mood 59 4.6 Spatial and Temporal Variance 60 CHAPTER 5: MODEL IMPLEMENTATION, VERIFICATION, AND VALIDATION 63 5.1 Model Implementation 63 5.1.1 Turtles and Patches 64 5.1.2 Time 64 4 5.1.3 Tasks 65 5.1.4 Turtle Values 61 5.1.5 Input Parameters 61 5.2 Model Verification 68 5.3 Model Validation 69 5.3.1 Face validity 70 5.3.2 Internal validity 72 5.3.3 Sensitivity analysis 73 CHAPTER 6: STUDY 1 EXPERIMENTATION AND RESULTS 76 6.1 Experimental Design 77 6.2 Experimental Analysis 79 6.3 Results 81 6.3.1 Interaction Effects 81 6.3.2 Time Series Analyses 86 CHAPTER 7: STUDY 2 EXPERIMENTATION AND RESULTS 94 7.1 Model Changes 94 7.2 Experimental Design and Analysis 98 7.3 Results 101 CHAPTER 8: DISCUSSION 109 7.1 Discussion of Results 111 7.2 Contributions 120 7.3 Limitations 126 7.4 Future Research 128 7.5 Conclusion 131 REFERENCES 132 5 LIST OF TABLES Table 1: Examples of studies highlighting the relationship between inflammation and mood deterioration. 50 Table 2: List of parameters used in model. 66 Table 3: PARTE Framework outlining the Properties, Actions, Rules, Time, and Environment of present model. 67 Table 4: Unpaired Two-Sample t-Tests for Affective Climate and Focal Leader Mood 76 Table 5: Single Team IAMD Time Series Comparison Sensitivity Analysis Results 87 Table 6: Comparison of IAMD Conditions Across Runs (Single Team) 87 Table 7: Multiple Team IAMD Time Series Comparison Sensitivity Analysis Results 88 Table 8: Comparison of IAMD Conditions Across Runs (Two Teams) 89 Table 9: Between-Team Comparison Runs – Affective Climate 91 Table 10: Between-Team Comparison Runs – Affective Climate Variability 92 Table 11: Other Leader IAMD Time Series Comparison Sensitivity Analysis Results 94 Table 12: Comparison of Other Leader IAMD Conditions Across Runs 94 6 LIST OF FIGURES Figure 1: Model of emergent affective climate used in study. 48 Figure 2: Teams follow leaders to offices to perform tasks and return to common space for social interaction. 57 Figure 3: Conceptual diagram of affective events and mood contagion within the model. 59 Figure 4: Spatial and temporal variance in the model. 62 Figure 5: NetLogo Behavioral Output for Affective Climate 70 Figure 6: Results of internal validity Monte Carlo procedure. 73 Figure 7: OFAT Sensitivity Analyses Results of Base and Experimental Validation Conditions 75 Figure 8: Number of Teams x Focal Leader IAMD x Affective Climate 82 Figure 9: Number of Teams x Focal Leader IAMD x Affective Climate Variability 83 Figure 10: Focal Leader IAMD x Follower Mood Range Differential x Affective Climate (Single-Team Condition) 84 Figure 11: Focal Leader IAMD x Follower Mood Range Differential x Affective Climate (3-Team Condition) 85 Figure 12: Single Team IAMD Time Series Comparison 86 Figure 13: 2-Team IAMD Time Series Comparison 88 Figure 14: Between-Team IAMD Time Series Climate Comparison 90 Figure 15: Between-Team IAMD Time Series Climate Variability Comparison 91 Figure 16: Other Leader IAMD Condition 93 Figure 17: Revised model structure used for Study 2 96 Figure 18: Focal Team Affective Climate 101 7 Figure 19: Non-Focal Team Affective Climate Time Series 102 Figure 20: Distance Between Teams Time Series 103 Figure 21: Cluster Graph Comparison of Focal and Non-Focal Team Affective Climates 104 Figure 22: Comparison of Focal and Non-Focal Team Affective Climates 105 Figure 23: Study 2 Experiment 2 Affective Climate Time Series 106 Figure 24: Study 2 Experiment 2 Distance Between Teams 107 Figure 25: Study 2 Experiment 2 Cluster Graph 108 8 ACKNOWLEDGEMENTS The pursuit of this dissertation was a wavering bend in the path of my life. I tried to follow that bend in my own way, but even taking an idiosyncratic approach is still made better by having a colourful cast of supporting characters with you along the way. To my advisor and committee chair, Professor Corinne Coen, thank you for being an invaluable thought and support partner to me throughout this process. If I were able to share only one piece of advice with aspiring doctoral students to be, it would be this: make sure your dissertation advisor is someone who allows your ideas to be their own, while gently corralling the excesses of your thinking. Corinne, you ensured this dissertation was a real piece of me, while also ensuring it became a real piece of scholarship. I am indebted to you for that, and grateful for all the many absorbing conversations we have had together - both deep and dark, levitous and light. To the rest of my dissertation committee, Professors Ronald Fry, Kurt Stange, and Youngjin Yoo, my endless gratitude to each of you for taking the time out of your busy lives and careers in order to provide generous advice, pointed critiques, and a careful, scholarly treatment of my work. Working with you all made me feel like a real part of a real scientific conversation. To the Organizational Behavior department at the Weatherhead School of Management at Case Western Reserve University, thank you for taking a chance on me. I 9 hope that I can repay the opportunity by making some small dent in the series of puzzles and problems that are our world. To my mother, Christine Craze, who helped keep my ship afloat through rocky waters pre-dating my time in this program, thank you for being a bottomless source of love, warmth, humour, and belief in me throughout my life. Finally, to my life partner and adventure buddy, Cadia Wheeler. Your love, your compassion, your encouragement, and your understanding have truly helped to lay the foundation for me to pursue this part of my life, comfortable in the knowledge that I have the most amazing support person I could ever ask for waiting for me at the end of every day. I truly cannot wait to see what life brings us next. I love you with all my being. 10 Inflammation-Associated Mood Deterioration and the Degradation of Affective Climate: An Agent-Based Model Abstract by GARETH JOHN CRAZE Affective climate constitutes the collective mood of organizational members. A positive affective climate has been viewed as a prerequisite of a healthy organization in which employees can achieve individual and collective goals, and is associated with greater individual loyalty to the organization and improved team performance, among other positive organizational outcomes. Leaders are the architects of the affective climate in teams, and through the process of mood contagion, the moods of leaders typically exert an outsized influence on the moods of those that they lead. Inflammation-associated mood deterioration (IAMD) has been demonstrated under experimental conditions, and has been linked to an increased incidence of mood disorder symptomatology. Across two studies, I use agent-based modeling to model affective climate, and its potential degradation over time via IAMD, as an emergent phenomenon that can be generated through the interaction of team members based on simple local rules. I simulate an organizational environment in which tasks and social interactions represent affective events, resulting in subsequent affective responses in the form of altered mood states via mood contagion. In Study 1, by employing parametric sensitivity analyses and the criterion of generative sufficiency, I found that increases in focal leader IAMD resulted in affective climate degradation over time. Increases in focal leader IAMD also resulted in climates that were more variable over time, and for which a more pronounced differential in follower moods also drove climate degradation. Increasing the number of teams within the simulated environment buffered against climate degradation and produced climates that were relatively more stable. In Study 2, non-linear patterns in affective climate were observed which reflected variations in distance between teams interacting with the effects of IAMD on the focal leader over time, resulting in non-linear degradations of climate. Findings from Study 1 suggest that IAMD is sufficient to generate affective climate degradation over time, which can be offset in the socio-structural environment through positive inter-team interactions.