SynthesisObesity facts2017
Weight Bias: A Systematic Review of Characteristics and Psychometric Properties of Self-Report Questionnaires.
Synthesis in Obesity facts, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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.
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.
Who cites it
29 citing papers in PubMed.
- The Effect of an Education Module to Reduce Weight Bias among Medical Centers Employees: A Randomized Controlled Trial.Obesity facts · 2022Trial
- Internalized weight stigma and obesity-related quality of life in adults with obesity or overweight: a cross-sectional study across clinical and community settings.Eating and weight disorders : EWD · 2026Article
- Weight Bias Interventions for Healthcare Professionals: An Integrative Review.Journal of advanced nursing · 2026Review
- Results of the 2024 International Weight Bias Summit: Establishing future research directions in the field.International journal of obesity (2005) · 2026Article
- Associations between weight bias internalization, weight status, and health among a diverse cohort of freshman college students.Journal of American college health : J of ACH · 2025Article
- Mediating Factors and Demographic Disparities Associated With Disordered Eating in University Students During the Era of COVID-19.European eating disorders review : the journal of the Eating Disorders Association · 2025Article
- Assessing exposure to weight stigma: development and initial validation of the Weight Stigma Exposure Inventory (WeSEI).Journal of eating disorders · 2025Article
- Race/Ethnicity as a Moderator of the Association Between Weight-Related Abuse and Disordered Eating.Journal of racial and ethnic health disparities · 2024Article
- Clinical observations of weight stigma among nursing students: A descriptive approach.Obesity science & practice · 2024Article
- Hindi Translation, Cultural Adaptation, and Validation of Modified Weight Bias Internalization Scale (WBIS-M): A Cross-Sectional Study from the Metabolic Surgery Clinic in North India.Indian journal of psychological medicine · 2024Article
- Current trends and future directions in internalized weight stigma research: a scoping review and synthesis of the literature.Journal of eating disorders · 2024Article
- Reducing anti-fat bias toward the self and others: a randomized controlled trial.Journal of eating disorders · 2024Article
- The Impact of Weight Bias and Stigma on the 24 h Dietary Recall Process in Adults with Overweight and Obesity: A Pilot Study.Nutrients · 2024Article
- Improving Weight Bias Awareness Among Providers in the Sexual and Reproductive Health care Setting.Health equity · 2024Article
- Body image is associated with persistence. A study of the role of weight-related stigma.Frontiers in psychiatry · 2024Article
- Weight bias internalization and beliefs about the causes of obesity among the Canadian public.BMC public health · 2023Article
- Developing and validating a Japanese version of the Weight Self-Stigma Questionnaire.Eating and weight disorders : EWD · 2023Article
- Implicit Perception of Differences between NLP-Produced and Human-Produced Language in the Mentalizing Network.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Anti-fat attitudes among Spanish general population: Psychometric properties of the anti-fat attitudes scale.Clinical obesity · 2022Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundPeople living with overweight and obesity often experience weight-based stigmatization. Investigations of the prevalence and correlates of weight bias and evaluation of weight bias reduction interventions depend upon psychometrically-sound measurement. Our paper is the first to comprehensively evaluate the psychometric properties, use of people-first language within items, and suitability for use with various populations of available self-report measures of weight bias.
methodsWe searched five electronic databases to identify English-language self-report questionnaires of weight bias. We rated each questionnaire's psychometric properties based on initial validation reports and subsequent use, and examined item language.
resultsOur systematic review identified 40 original self-report questionnaires. Most questionnaires were brief, demonstrated adequate internal consistency, and tapped key cognitive and affective dimensions of weight bias such as stereotypes and blaming. Current psychometric evidence is incomplete for many questionnaires, particularly with regard to the properties of test-retest reliability, sensitivity to change as well as discriminant and structural validity. Most questionnaires were developed prior to debate surrounding terminology preferences, and do not employ people-first language in the items administered to participants.
conclusionsWe provide information and recommendations for clinicians and researchers in selecting psychometrically sound measures of weight bias for various purposes and populations, and discuss future directions to improve measurement of this construct.
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What OpenQuestion holds
Registered trials
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.