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

• Main Authors: Emilie Lacroix, Angela Alberga, Shelly Russell-Mathew, Lindsay McLaren, Kristin von Ranson
• Format: Article
• Language: English
• Published: Karger Publishers 2017-06-01
• Series: Obesity Facts
• Subjects: Weight bias; Obesity; Stigma; Systematic review; Assessment
• Online Access: http://prod.karger.com/Article/FullText/475716

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 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. 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.