Evidence map›Paper›PMID 40764653›Full record

ArticleInternational journal of obesity (2005)2025

Implicit and explicit weight bias among healthcare professionals.

Jane W Liang, Christie Buonpane, Shengxuan Wang, Arghavan Salles

Abstract read
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In one paragraph

Article in International journal of obesity (2005), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Jane W LiangDivision of Research, Kaiser Permanente Northern California, Pleasanton, CA, USA. jane.w.liang@kp.org.ORCID http://orcid.org/0000-0002-2302-3809
Christie BuonpaneDepartment of Surgery, University of Louisville, Louisville, KY, USA.
Shengxuan WangDepartment of Population Health Sciences, Geisinger Medical Center, Danville, PA, USA.
Arghavan SallesDepartment of Medicine, Stanford University School of Medicine, Palo Alto, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patients with overweight and obesity are negatively impacted by weight bias in healthcare, leading to poor quality of care and poor health outcomes. Implicit bias can be estimated from reaction times during Implicit Association Tests (IATs), and explicit bias can be self-reported. Data from over one million online survey responses collected by Project Implicit between 2006-2022 suggest that implicit and explicit weight bias persist among diagnosing and treating practitioners, other healthcare workers, and non-healthcare workers. Moreover, our findings indicate that diagnosing and treating workers could express more explicit bias than others. Across all three occupation groups examined, it appears that men have more explicit negative attitudes toward people with obesity, and explicit weight bias appears to be decreasing over time. Given the powerful impact healthcare workers have on the experiences of patients, more efforts should be made to educate them on how to recognize their weight biases, the negative impact of those biases, and how to take appropriate action.

Indexed as

Attitude of Health PersonnelHealth PersonnelObesityWeight PrejudiceAdultFemaleHumansMaleMiddle AgedSurveys and Questionnaires

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.