JOURNAL ARTICLE

Navigating ambivalence: A qualitative study of young fitness self-trackers' engagement with body ideals through social media.

  • Published In: Health: An Interdisciplinary Journal for the Social Study of Health, Illness & Medicine, 2024, v. 28, n. 4. P. 633 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Stage, Carsten; Bach Nielsen, Stinne 3 of 3

Abstract

This article examines the role of social media in shaping body ideals among young Danish fitness self-trackers aged 15–24, based on 20 qualitative interviews. It finds that social media serve primarily as resources for practical knowledge, motivation, and visual goals rather than for personal sharing or interaction, and are experienced as both indispensable and ambivalent environments that require active content curation to navigate misinformation and demotivating imagery. Participants position themselves as mature, rational users who manage social media's dual potential to inspire and discourage by selectively engaging with content, highlighting that self-tracking involves not only quantitative measurement but also imaginative and affective work within a complex social media ecology. The study contributes to body image and self-tracking research by emphasizing the nuanced, agentic ways young fitness exercisers interact with social media, challenging simplistic causal assumptions about media influence on body ideals.

Additional Information

  • Source:Health: An Interdisciplinary Journal for the Social Study of Health, Illness & Medicine. 2024/07, Vol. 28, Issue 4, p633
  • Document Type:Article
  • Subject Area:Technology
  • Publication Date:2024
  • ISSN:1363-4593
  • DOI:10.1177/13634593231175277
  • Accession Number:177672015
  • Copyright Statement:Copyright of Health: An Interdisciplinary Journal for the Social Study of Health, Illness & Medicine is the property of Sage Publications Inc. 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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