JOURNAL ARTICLE
Contact With Older Adults Is Related to Positive Age Stereotypes and Self-Views of Aging: The Older You Are the More You Profit.
Published In: Journals of Gerontology Series B: Psychological Sciences & Social Sciences, 2023, v. 78, n. 8. P. 1330 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Cohn-Schwartz, Ella; Couto, M Clara de Paula; Fung, Helene H; Graf, Sylvie; Hess, Thomas M; Liou, Shyhnan; Nikitin, Jana; Rothermund, Klaus 3 of 3
Abstract
This article investigates how contact with older adults relates to individuals' views of themselves in old age, focusing on both younger adults (intergenerational contact) and older adults (contact with same-age peers) across the domains of family, friends, and leisure. Analyzing data from 2,356 participants aged 39–90 from China, the Czech Republic, Germany, and the United States, the study found that more frequent contact with older adults is associated with more positive self-views in old age, mediated by more positive age stereotypes (AS). These effects were stronger for older adults, particularly in the friendship and leisure domains, while contact within the family domain showed weaker or no mediation effects. The findings suggest that encouraging contact among older adults themselves, especially in voluntary social contexts, may foster more positive aging perceptions, which have implications for health and well-being in later life.
Additional Information
- Source:Journals of Gerontology Series B: Psychological Sciences & Social Sciences. 2023/08, Vol. 78, Issue 8, p1330
- Document Type:Article
- Subject Area:Sociology
- Publication Date:2023
- ISSN:1079-5014
- DOI:10.1093/geronb/gbad038
- Accession Number:169728867
- Copyright Statement:Copyright of Journals of Gerontology Series B: Psychological Sciences & Social Sciences is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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