Cited by 80Obesity and Health PracticesObesity, Physical Activity, DietEating Disorders and Behaviors

Knowledge gaps and weight stigma shape attitudes toward obesity

Open access
O'Keeffe, Majella, Flint, Stuart W, Watts, Krista, Rubino, Francesco·2020·The Lancet Diabetes & Endocrinology

Integrity signals

Registry

Crossref · 10.1016/s2213-8587(20)30073-5

Cites

10 of 10 references verified0 citation errors · 0 not checkable

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  • Individuals with obesity face a pervasive form of social stigma.

    “Individuals with obesity face a pervasive form of social stigma.”

    From Definition and diagnostic criteria of clinical obesity (2025) · cites this paper as [196]

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Authors
O'Keeffe, M., Flint, S. W., Watts, K., & Rubino, F.
Affiliations
  • King's College London (GB)
  • University of Leeds (GB)
  • United States Military Academy (US)
Corresponding author
Rubino, Francesco
Venue
The Lancet Diabetes & Endocrinology
Publisher
Elsevier BV
Published
2020-05
Volume
8
Issue
5
Pages
363-365
ISSN
2213-8587 (ISSN-L)
OpenAlex
W3009294152
Cited by
80
References
10
Citations by year
2026: 8 · 2025: 22 · 2024: 15 · 2023: 5 · 2022: 10 · 2021: 13 · 2020: 7
FWCI
13.60
Type
journal article
Language
en
Open access
Locations
  • The Lancet Diabetes & Endocrinology (publishedVersion)
  • PubMed (publishedVersion)
  • Research Portal (King's College London) (publishedVersion, cc-by-nc-nd)
Funders
  • Medtronic
  • Novo Nordisk
Topics
  • Health Sciences › Health Professions › Pharmacy › Obesity and Health Practices
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
  • Social Sciences › Psychology › Clinical Psychology › Eating Disorders and Behaviors
Keywords
weight stigma, obesity, obesity knowledge, healthcare workers
MeSH terms
Attitude, Body Weight, Female, Humans, Health Knowledge, Attitudes, Practice, Male, Obesity, Social Stigma

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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