Differences in the content and coherence of autobiographical memories between younger and older adults: Insights from text analysis.

Abstract

Several studies have shown that older adults generate autobiographical memories with fewer specific details than younger adults, a pattern typically attributed to age-relate declines in episodic memory. A relatively unexplored question is how aging affects the content used to represent and recall these memories. We recently proposed that older adults may predominately represent and recall autobiographical memories at the gist level. Emerging from this proposal is the hypothesis that older adults represent memories with a wider array of content topics and recall memories with a distinct narrative style when compared to younger adults. We tested this hypothesis by applying natural language processing approaches to a data set of autobiographical memories described by healthy younger and older adults. We used topic modeling to estimate the distribution (i.e., diversity) of content topics used to represent a memory, and sentence embedding to derive an internal similarity score to estimate the shifts in content when narrating a memory. First, we found that older adults referenced a wider array of content topics (higher content diversity) than younger adults when recalling their autobiographical memories. Second, we found older adults were included more content shifts when narrating their memories than younger adults, suggesting a reduced reliance on choronology to form a coherent memory. Third, we found that the content diversity measures were positively related to specific detail generation for older adults, potentially reflecting age-related compensation for episodic memory difficulties. We discuss how our results shed light on how younger and older adults differ in the way they remember and describe the past.

Evoking episodic and semantic details with instructional manipulation during autobiographical recall.

“…The finding that older adults’ narratives were richer in autobiographical facts compared to those from young adults indicates a preserved recall of abstracted forms of autobiographical memories in aging (Acevedo-Molina et al, 2020; Grilli & Sheldon, 2022) and a prevalence of autobiographical facts not only when describing past unique events (in the AI) but also when relating how past life chapters were for them in the P-SAI. The presence of more off-target content in older adults’ narratives, like episodic details and general knowledge, despite their low numbers, aligns with previous findings of more story-asides and variety in narrative content in aging (e.g., Acevedo-Molina et al, 2020; Bluck et al, 2016; Sheldon et al, 2024).…”

“…Given the commonly observed preservation of semantic memory in aging, the presence of additional content related to nontarget information may reflect a tendency of older adults to enrich the recall of semantic knowledge with subjective elements like opinions and beliefs (Bluck et al, 2016; Sheldon et al, 2024), rather than a compensatory strategy. This presence of subjective content in older adults’ narratives may also be attributed to adopting a different communicative goal than young adults (e.g., James et al, 1998).…”

“…This interpretation suggests a transition from highly specific to more gistlike retrieval in aging (Grilli & Sheldon, 2022). Focusing more on gist and general meaning may become natural in aging and, in turn, may promote the elaboration of narratives with a higher variety of topics in comparison to young adults (Sheldon et al, 2024). Accordingly, connections with other meaningful information may be prioritized over describing additional perceptual and contextual information related to the events.…”

A longitudinal study of conversational remembering in WhatsApp group messages before, during, and after COVID-19 lockdown

“…CRSs come to fill an important methodological gap in the literature on how to detect and analyse instances of conversational remembering in the wild. The advancement of computational approaches (e.g., natural language processing and closed-vocabulary dictionaries software) in autobiographical and collective memory research in the social sciences and the humanities (Rouhani et al 2023;Sheldon et al 2023) can contribute to the development of analytical tools to (semi) automatically detect and examine CRSs in large datasets of naturally occurring conversations taken from text-messaging apps. Our study represents a first step towards the systematic identification of recurrent linguistics (e.g., questions, use of past tense, repetition of specific lexical items, and syntactic structures).…”

“…2023; Sheldon et al . 2023) can contribute to the development of analytical tools to (semi) automatically detect and examine CRSs in large datasets of naturally occurring conversations taken from text-messaging apps. Our study represents a first step towards the systematic identification of recurrent linguistics (e.g., questions, use of past tense, repetition of specific lexical items, and syntactic structures).…”