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- W4200061693 abstract "Autobiographical memory (AM) involves a rich phenomenological re-experiencing of a spatio-temporal event from the past, which is challenging to objectively quantify. The Autobiographical Interview (AI; Levine et al., 2002, Psychology & Aging) is a manualized performance-based assessment designed to quantify episodic (internal) and semantic (external) features of recalled and verbally conveyed prior experiences. The AI has been widely adopted yet has not undergone a comprehensive psychometric validation. We investigated the reliability, validity, association to individual differences measures, and factor structure in healthy younger and older adults (N=352). Evidence for the AI's reliability was strong: the subjective scoring protocol showed high inter-rater reliability and previously identified age effects were replicated. Internal consistency across timepoints was robust, suggesting stability in recollection. Central to our validation, internal AI scores were positively correlated with standard, performance-based measures of episodic memory, demonstrating convergent validity. The two-factor structure for the AI was not well-supported by confirmatory factor analysis. Adjusting internal and external detail scores for the number of words spoken (detail density) improved trait estimation of AM performance. Overall, the AI demonstrated sound psychometric properties for inquiry into the qualities of autobiographical remembering." @default.
- W4200061693 created "2021-12-31" @default.
- W4200061693 creator A5035373200 @default.
- W4200061693 creator A5037462379 @default.
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- W4200061693 creator A5086105896 @default.
- W4200061693 creator A5086506232 @default.
- W4200061693 date "2021-12-23" @default.
- W4200061693 modified "2023-10-10" @default.
- W4200061693 title "Taking stock of the past: A psychometric evaluation of the Autobiographical Interview" @default.
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