Examining a Hierarchical Linear Regression Model of Overgeneral Memory

Abstract

Overgeneral memory (OGM) is a phenomenon of reduced autobiographical memory specificity observed in major depressive disorder (MDD) and post-traumatic stress disorder (PTSD). Individuals demonstrating OGM tend to describe past events generally rather than specifically recalling single memory occurrences. Research shows that OGM is perpetuated by three mechanisms: capture in the memory hierarchy due to trait rumination (CaR), functional avoidance of specific memory retrieval (FA), and impaired executive control (X), which together make up the CaR-FAX model of OGM. Research on the CaR-FAX model has historically looked at each mechanism in isolation. The current research aimed to compare the contributions of all three mechanisms to a measure of OGM, as well as to investigate possible interactions between the mechanisms, and compare the contributions of the CaR-FAX model to those of an encoding predictor. Psychometric data on the three CaR-FAX mechanisms, autobiographical memory specificity, cognitive attributional style, and mental health were collected from 107 undergraduate psychology students via online surveys, then analyzed in a hierarchical linear regression model. Executive control explained significant unique variance in OGM, with rumination making an indirect contribution. No other anticipated contributions from the CaR-FAX model or memory encoding were observed. Methodological issues in non-clinical and computerized OGM research are highlighted. v ACKNOWLEDGMENTS This thesis is the culmination of my time in the Master of Arts in Research and Experimental Psychology program. I count my time in this program as a success, which would not have been possible without the help and support of numerous individuals. First, I would like to thank my parents, Mark and Carrie Davis, for their continued love and support throughout my studies leading up to and including this graduate program. I would not have been able to make it this far if not for their constant encouragement and their insistence on prioritizing my studies. For that, I am eternally grateful. Second, I would like to thank my thesis committee. Special thanks to Dr. Mark Van Selst for agreeing to support this thesis topic and for painstakingly combing through this document with me on multiple occasions. Great appreciation is also due to Dr. Annabel Prins for her involvement in this project and continued thoughtful feedback regarding the clinical implications of this research. Thanks also to Drs. Sean Laraway and Greg Feist for their assistance in the editing phase of this project. Thank you to all four of you for helping me create a thesis that I am proud of. I would also like to thank all of the SJSU faculty under whom I have had the opportunity to study during this program for equipping me with the skills necessary to complete this study. Thanks also to Rob Most of Mind Garden, Inc. for his guidance and use of the WAYS Escape-Avoidance subscale, and to Ashleigh King for her assistance in rating the AMT responses. Finally, I would like to thank my friends...