Preprint

Buffering the Threat: Memory Self-Efficacy and Positive Stereotypes in Reducing Age-Related Stereotype Threat on Working Memory

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Abstract

Age-related declines in working memory are well-documented, but growing evidence suggests that psychosocial and contextual factors also play a critical role in shaping cognitive outcomes in older adulthood. One such factor is stereotype threat, the fear of confirming negative stereotypes about aging, which has been shown to impair working memory by heightening anxiety and reducing cognitive resources. As older adults increasingly engage in online contexts, their exposure to age-related stereotypes also rises. Memory self-efficacy, or belief in one’s memory abilities, may represent an individual difference that influence responses to such threats, potentially increasing vulnerability to declines in working memory performance. In the present study, I will use an online recruitment method to examine how variations in memory self-efficacy affect the impact of stereotype threat on working memory in later life. Further I will investigate whether the introduction of a positive stereotype buffer following exposure to a negative stereotype can attenuate the impact of threat on working memory. Older adults will be randomly assigned to one of three conditions (control, negative stereotype threat, or negative stereotype threat followed by a positive stereotype buffer) and will subsequently complete the Operation Span task. I hypothesize that older adults with lower memory self-efficacy will show greater working memory declines under negative stereotype threat, but these declines may be reduced when a positive buffer is introduced after the threat. Regression analyses will be used to examine how perceptions of aging and memory self-efficacy shape working memory performance under varying conditions. Together, these findings will potentially inform strategies for supporting cognitive functioning and resilience in older adults navigating online environments.

The paper

Preprint, 1 Jan 2026, CC0, Preprint, not peer-reviewed

doi.org/10.17605/osf.io/eb8u2