Publications & Reports

"Fitspiration" on Social Media: A Content Analysis of Gendered Images.

Carrotte ER, Prichard I, Lim MS

Abstract

BACKGROUND:

“Fitspiration” (also known as “fitspo”) aims to inspire individuals to exercise and be healthy, but emerging research indicates exposure can negatively impact female body image. Fitspiration is frequently accessed on social media; however, it is currently unclear the degree to which messages about body image and exercise differ by gender of the subject.

OBJECTIVE:

The aim of our study was to conduct a content analysis to identify the characteristics of fitspiration content posted across social media and whether this differs according to subject gender.

METHODS:

Content tagged with #fitspo across Instagram, Facebook, Twitter, and Tumblr was extracted over a composite 30-minute period. All posts were analyzed by 2 independent coders according to a codebook. RESULTS: Of the 415/476 (87.2%) relevant posts extracted, most posts were on Instagram (360/415, 86.8%). Most posts (308/415, 74.2%) related thematically to exercise, and 81/415 (19.6%) related thematically to food. In total, 151 (36.4%) posts depicted only female subjects and 114/415 (27.5%) depicted only male subjects. Female subjects were typically thin but toned; male subjects were often muscular or hypermuscular. Within the images, female subjects were significantly more likely to be aged under 25 years (P<.001) than the male subjects, to have their full body visible (P=.001), and to have their buttocks emphasized (P<.001). Male subjects were more likely to have their face visible in the post (P=.005) than the female subjects. Female subjects were more likely to be sexualized than the male subjects (P=.002).

CONCLUSIONS:

Female #fitspo subjects typically adhered to the thin or athletic ideal, and male subjects typically adhered to the muscular ideal. Future research and interventional efforts should consider the potential objectifying messages in fitspiration, as it relates to both female and male body image.

Link to publisher’s web site

We gratefully thank Paige Kernebone and Michelle Motteram for their contribution to coding the content, and Alyce Vella and Cassandra Wright for assisting with the development of the codebook. The authors also acknowledge the contribution to this work of the Victorian Operational Infrastructure Support Program received by the Burnet Institute. ML is supported by the Jim and Margaret Beever Fellowship from the Burnet Institute.

Project

Publication

  • Journal: Journal of Medical Internet Research
  • Published: 29/03/2017
  • Volume: 19
  • Issue: 3
  • Pagination: e95

Author

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