Evidence map›Paper›PMID 37723555›Full record

ArticleJournal of eating disorders2023

Discrepancies between media portrayals and actual demographics of eating disorders in TV and film: implications of representation.

Lucy Bassett, Maya Ewart

Abstract readLetter
In one paragraph

Article in Journal of eating disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Lucy BassettBatten School of Leadership and Public Policy, University of Virginia, Charlottesville, VA, USA. lucybassett@virginia.edu.
Maya EwartNew York City Human Resources Administration, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMedia has a reputation for painting a narrow, simplistic, sensationalized portrait of eating disorders. There is little analysis of how film and TV portray eating disorders nor the implications of this representation. This study fills that gap by comparing demographics of US film and TV characters since the 1980s to actual population demographics of people with eating disorders.

methodsWe compiled a dataset of TV and movie characters with eating disorders and categorized characters' gender, age, race/ethnicity, and sexual orientation. We narrowed the dataset to include only US media depictions to facilitate comparisons with empirical prevalence, resulting in a total of 66 characters over the period 1981 to 2022. We then compared the demographic characteristics of our sample to national statistics on eating disorder prevalence.

resultsUS media depictions of eating disorders overrepresented characters who were heterosexual (75.56%), White (84.85%), women (89.39%), and under age 30 (84.85%). This does not accurately reflect the populations experiencing eating disorders in the US.

conclusionsEating disorders have an image problem. TV and movies inaccurately portray them as primarily affecting heterosexual, White, women under age 30. Misrepresentation could fuel existing stigmas that inhibit individuals with eating disorders from seeking and receiving treatment. It could also perpetuate stereotypes that fuel misperceptions of the disease by medical providers, families, and policymakers. We recommend more accurate representation in the media to better reflect current demographics and increase awareness of the range of people who can experience eating disorders.

Indexed as

AgeAnorexia nervosaBulimia nervosaEating disorderFilmGenderLGBTQ+MediaMoviesTV

Identifiers

PMID37723555
PMCPMC10506274

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.