Taking Stock of the Past: A Psychometric Evaluation of the Autobiographical Interview

Overview

Journal Behav Res Methods

Publisher Springer

Specialty Social Sciences

Date 2023 Mar 22

PMID 36944860

Authors

Amber W Lockrow

Roni Setton

Karen A P Spreng

Signy Sheldon

Gary R Turner

R Nathan Spreng

Affiliations

Soon will be listed here.

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. Psychology and Aging, 17(4), 677-689, 2002) 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.

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