Researchers are increasingly using data coded from autobiographical memory narratives as a tool to explore autobiographical memory processes. Evidence of this trend includes recent guides for conducting effective narrative coding (Adler et al., 2017; Syed & Nelson, 2015) as well as recent reviews (Adler, Lodi-Smith, Philippe, & Houle, 2016; Grysman & Mansfield, 2017) and factor analyses (Adler, Waters, Poh, & Seitze, 2018; Graci, Watts, & Fivush, 2018; McLean et al., in press) examining multiple narrative coding systems in single papers. What these papers share in common is an approach toward narrative methodology that considers the aggregate of multiple methods and their implications for theory and future work using them. We encourage readers to view these papers to gain an understanding of process and theory in this domain. We have two central aims in the current chapter, which contribute to the existing literature on narrative methods. Our first aim is to examine a core distinction between two approaches to coding narrative data, as we elaborate below. Our second aim is to outline methodological choices that must be made early in the study conceptualization and coding process, creating a guide for new narrative researchers.

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Grysman, Azriel, and Cade D. Mansfield. Narrative Methods in Autobiographical Memory. In Autobiographical Memory Development: Theoretical and Methodological Approaches, edited by Sami Gülgöz and Basak Sahin-Acar, 67-82. London: Routledge, Taylor & Francis Group, 2020.

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