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The ability to construct coherent narratives about significant personal experiences, commonly referred to as autobiographical memory coherence, has been related to various emotional disorders, though insight regarding mechanisms that might underlie this relation is scarce. The present study contributes to this growing body of research by examining the relation between memory coherence and both depression and PTSD and by investigating the role of rumination, cognitive avoidance, executive functioning, and meaning making in that relation in a large-scale community sample. The negative relation between memory coherence and both depression and PTSD could not be replicated, nor could the hypothesized negative relation between memory coherence and both rumination and cognitive avoidance be confirmed. In contrast, results indicated more memory coherence to be related to more rumination. Additional analyses in light of these surprising findings revealed that there was a significant indirect relation between memory coherence and both depression and PTSD-related symptoms through rumination. When the latter was controlled for, memory coherence was predictive of PTSD diagnosis and the hypothesized negative association with cognitive avoidance could be confirmed. In line with predictions, both executive functioning and meaning making were positively related to memory coherence. Theoretical and clinical implications are discussed.

Autobiographical memory forms a network of memories about personal experiences that defines and supports well-being and effective functioning of the self in various ways. During the last three decades, there have been two characteristics of autobiographical memory that have received special interest regarding their role in psychological well-being and psychopathology, namely memory specificity and memory coherence. Memory specificity refers to the extent to which retrieved autobiographical memories are specific (i.e., memories about a particular experience that happened on a particular day). Difficulty retrieving specific memories interferes with effective functioning of the self and is related to depression and post-traumatic stress disorder. Memory coherence refers to the narrative expression of the overall structure of autobiographical memories. It has likewise been related to psychological well-being and the occurrence of psychopathology. Research on memory specificity and memory coherence has developed as two largely independent research domains, even though they show much overlap. This raises some important theoretical questions. How do these two characteristics of autobiographical memory relate to each other, both theoretically and empirically? Additionally, how can the integration of these two facilitate our understanding of the importance of autobiographical memory for the self? In this article, we give a critical overview of memory specificity and memory coherence and their relation to the self. We link both features of autobiographical memory by describing some important similarities and by formulating hypotheses about how they might relate to each other. By situating both memory specificity and memory coherence within Conway and Pleydell-Pearce’s Self-Memory System, we make a first attempt at a theoretical integration. Finally, we suggest some new and exciting research possibilities and explain how both research fields could benefit from integration in future research.

The Autobiographical Memory Test (AMT) has been central in psychopathological studies of memory dysfunctions, as reduced memory specificity or overgeneralised autobiographical memory has been recognised as a hallmark vulnerability for depression. In the AMT, participants are asked to generate specific memories in response to emotional cue words, and their responses are scored by human experts. Because the manual coding takes some time, particularly when analysing a large dataset, recent studies have proposed computerised scoring algorithms. These algorithms have been shown to reliably discriminate between specific and non-specific memories of English-speaking children and Dutch- and Japanese-speaking adults. The key limitation is that the algorithm is not developed for English-speaking adult memories, which may cover a wider range of vocabulary that the existing algorithm for English-speaking child memories cannot process correctly. In the present study, we trained a new support vector machine to score memories of English-speaking adults. In a performance test (predicting memory specificity against human expert coding), the adult-memory algorithm outperformed the child-memory variant. In another independent performance test, the adult-memory algorithm showed robust performances to score memories that were generated in response to a different set of cues. These results suggest that the adult-memory algorithm reliably scores memory specificity.

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