Publication Date
Fall 2017
Degree Type
Thesis
Degree Name
Master of Arts (MA)
Department
Psychology
Advisor
Mark Van Selst
Keywords
CaR-FA-X model, Depression, Memory encoding, Minimal instructions autobiographical memory test, Overgeneral memory, PTSD
Subject Areas
Psychology; Cognitive psychology; Clinical psychology
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-FA-X model of OGM. Research on the CaR-FA-X 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-FA-X model to those of an encoding predictor. Psychometric data on the three CaR-FA-X 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-FA-X model or memory encoding were observed. Methodological issues in non-clinical and computerized OGM research are highlighted.
Recommended Citation
Davis, Carrie Adrian, "Examining a Hierarchical Linear Regression Model of Overgeneral Memory: Methodological Issues, CaR-FA-X Model Mechanisms, and Memory Encoding as Represented by Cognitive Attributional Style" (2017). Master's Theses. 4871.
DOI: https://doi.org/10.31979/etd.v6f4-8qj2
https://scholarworks.sjsu.edu/etd_theses/4871