The Effect of GLP-1 Receptor Agonist Use on Negative Evaluations of Women with Higher and Lower Body Weight
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Background: GLP-1 receptor agonists (GLP-1 RAs) have dramatically altered obesity treatment. Media reports suggest that GLP-1 RAs users often report feeling judged for taking a "shortcut" to lose weight, which may be related to negative stereotypes toward people with larger bodies. Media reports also describe negative attitudes about lean people who take GLP-1 RAs to enhance their appearance. The present research used a 2 × 2 experimental design to test the effects of GLP-1 RA use and body size on attitudes and egocentric impressions.
Subjects/methods: A sample of 357 U.S. adults (M = 37.8, SD = 13) were randomly assigned to read about a woman, who either was lean or had obesity, and who lost 15% of her body weight either with diet/exercise or a GLP-1 RA. Participants answered questions measuring endorsement of negative weight-related stereotypes and egocentric attitudes toward the woman, as well as beliefs that she took a shortcut to lose weight and beliefs that biogenetic factors caused her baseline weight.
Results: Negative evaluations and egocentric impressions were stronger toward a woman who lost weight with a GLP-1 RA compared to diet/exercise. Losing weight with a GLP-1 RA led to stronger negative evaluations through higher weight loss shortcut beliefs irrespective of body size. Losing weight with a GLP-1 RA also led to higher egocentric impressions through higher shortcut beliefs, and this effect was stronger for a lean woman. Finally, losing weight with a GLP-1 RA led to more negative evaluations through stronger endorsement of biogenetic causal beliefs for a lean woman only.
Conclusions: This timely study provides evidence that people with larger and smaller bodies alike are at-risk for being judged for using GLP-1 RAs due to beliefs that these medications are a shortcut. Findings also demonstrate novel reactions related to egotism when weight loss is achieved with pharmacological interventions. PRE-REGISTRATION AND DATA: osf.io/xme4w.
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