4.3 Review

Weight Bias: A Systematic Review of Characteristics and Psychometric Properties of Self-Report Questionnaires

Journal

OBESITY FACTS
Volume 10, Issue 3, Pages 223-237

Publisher

KARGER
DOI: 10.1159/000475716

Keywords

Weight bias; Obesity; Stigma; Systematic review; Assessment

Funding

  1. Fonds de recherche du Quebec Sante (FRQS) Master's Training Award
  2. Banting Canadian Institutes of Health Research (
  3. Applied Public Health Chair award - CIHR (Institute of Population and Public Health and Institute of Musculoskeletal Health and Arthritis)
  4. Public Health Agency of Canada
  5. Alberta Innovates Health Solutions
  6. Campus Alberta Health Outcomes Public Health
  7. Alberta Innovates [201400593] Funding Source: researchfish

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Background: People 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. Methods: We searched five electronic databases to identify Englishlanguage 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. Results: Our 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. Conclusions: We 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. (C) 2017 The Author(s) Published by S. Karger GmbH, Freiburg

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