- Title
- Critical measurement issues in the assessment of social media influence on body image
- Creator
- Jarman, Hannah; McLean, Sian; Griffiths, Scott; Teague, Samantha; Rodgers, Rachel; Paxton, Susan; Austen, Emma; Harris, Emily; Steward, Trevor; Shatte, Adrian; Khanh-Dao Le, Long; Anwar, Tarique; Mihalopoulos, Cathrine; Parker, Alexandra; Yager, Zali; Fuller-Tyszkiewicz, Matthew
- Date
- 2022
- Type
- Text; Journal article; Review
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/185216
- Identifier
- vital:16630
- Identifier
-
https://doi.org/10.1016/j.bodyim.2021.12.007
- Identifier
- ISBN:1740-1445 (ISSN)
- Abstract
- Progress towards understanding how social media impacts body image hinges on the use of appropriate measurement tools and methodologies. This review provides an overview of common (qualitative, self-report survey, lab-based experiments) and emerging (momentary assessment, computational) methodological approaches to the exploration of the impact of social media on body image. The potential of these methodologies is detailed, with examples illustrating current use as well as opportunities for expansion. A key theme from our review is that each methodology has provided insights for the body image research field, yet is insufficient in isolation to fully capture the nuance and complexity of social media experiences. Thus, in consideration of gaps in methodology, we emphasise the need for big picture thinking that leverages and combines the strengths of each of these methodologies to yield a more comprehensive, nuanced, and robust picture of the positive and negative impacts of social media. © 2022 Elsevier Ltd
- Publisher
- Elsevier Ltd
- Relation
- Body Image Vol. 40, no. (2022), p. 225-236
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © 2022 Elsevier Ltd
- Subject
- 4206 Public health; 4410 Sociology; 5205 Social and personality psychology; Assessment; Body image; Computational modelling; Experimental; Measurement; Momentary assessment; Qualitative; Social media; Survey; Web scraping
- Reviewed
- Funder
- This work was supported by the Medical Research Future Fund (MRFF; APP1179321
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