Abstract
Background
Glucagon-like-peptide-1 receptor agonists (GLP-1s) are a newer class of obesity medications that have garnered significant attention by the public and media. Media reports suggest that medical interventions such as GLP-1s are often perceived as weight loss “shortcuts.”
Purpose
The present experimental research tested the effect of exposure to medical weight loss interventions on GLP-1 policy support, dependent on body mass index.
Methods
A sample of 440 participants (Mage= 37, SD = 12.6) were randomly assigned to read about a woman who lost 15% of her body weight either with a GLP-1, bariatric surgery, or diet/exercise. Participants reported on beliefs that the woman took a weight loss “shortcut” and support for three policies expanding GLP-1 coverage.
Results
Exposure to a woman who lost weight with GLP-1 or bariatric surgery (vs. diet/exercise) led to higher GLP-1 policy support. However, such exposure was also indirectly associated with lower policy support, partially mediated by weight loss “shortcut” beliefs.
Conclusions
This study provides evidence that exposure to medical weight loss interventions leads to higher GLP-1 policy support. Exposure may also, indirectly, lead to lower policy support due to beliefs that such interventions are shortcuts. Findings have implications for policymakers who are interested in how perceptions of medical weight loss interventions influence support for obesity treatments and related health policies.
Keywords: Weight loss medication, GLP-1 receptor agonists, Obesity policy, Policy attitudes
Exposure to medical weight loss interventions led to higher GLP-1 agonist policy support. However, exposure also indirectly led to lower policy support due to beliefs that such interventions are weight loss “shortcuts.”
Introduction
Glucagon-like-peptide-1 receptor agonists (GLP-1s) are a class of anti-obesity medications that result in an average weight loss of 15%–20% of total body weight after one year [1]. Despite their efficacy, support for public policies expanding coverage of medical interventions, such as GLP-1s and bariatric surgery, varies. For example, out of 15 obesity-related policies, government funding of bariatric surgery was ranked second-to-last in terms of support [2], while other research showed that 81% of study participants reported that bariatric surgery should be covered by private insurance for adolescents with “severe obesity” [3]. Similarly, in an opinion poll, 80% of Americans endorsed health insurers covering the cost of prescription weight loss drugs for people with obesity [4], although support for coverage of specific classes of weight loss medications is unknown. Factors influencing support for policies broadening access to medical obesity interventions warrant further investigation, especially because such policies are currently under consideration by the U.S. government [5].
Media reports and empirical research suggest that attitudes about individuals who use GLP-1s to lose weight are often negative due to perceptions that they are “cheating” or taking a “shortcut” to lose weight [6–8]. These perceptions align with research demonstrating that bariatric surgery is also often viewed as an “easy way out” [9] and related work showing that people with obesity who undergo bariatric surgery (vs. diet/exercise) are perceived negatively [10]. Attitudes that medical weight loss interventions are “shortcuts” that require less personal effort could undermine support for policies expanding coverage of GLP-1s for people with obesity, especially if these attitudes occur alongside beliefs that people with obesity are undeserving of such interventions.
Exposure to examples of GLP-1 use in the media, real-life settings, or otherwise may influence endorsement of GLP-1 policies. There is research showing that exposure to different sociopolitical phenomena impacts support for related policies [11, 12]. Thus, exposure to GLP-1 success stories may also affect policy support and lead to higher support for policies expanding coverage of the medications. However, exposure might also reduce policy support if it simultaneously leads to beliefs that GLP-1s are a weight loss “shortcut.” We posed the following research question: Does exposure to a female target who lost weight with medical means (GLP-1 or bariatric surgery, included as a comparison) versus traditional or nonmedical means (diet/exercise) affect GLP-1 policy support? Is the influence of exposure mediated through weight loss “shortcut” beliefs (RQ1)?
Another factor that may impact GLP-1 policy support is an individual’s own body mass index (BMI). While BMI does not account for several important factors (e.g., body fat percentage and racial differences), guidelines and eligibility for GLP-1 use are primarily based on BMI [1]. People with larger bodies also have different personal experiences with and understanding of obesity, which may affect support for medical weight loss interventions. Because personal relevance predicts motivation to cognitively process and support health messages in multiple domains [13], people with larger bodies might consider the personal benefits of using medical means for weight loss and thus could be more likely to support GLP-1 policies. However, perceptions that GLP-1s are a “shortcut” may reduce support for GLP-1 policies for people with larger bodies due to anticipated negative stereotypes associated with using the medications. These opposing perspectives prompted our second research question: Are the effects of exposure to a female target who lost weight with medical means (vs. diet/exercise) on shortcut beliefs and GLP-1 policy support dependent on participant BMI (RQ2)?
Materials and Methods
Participants
The present study used data from another study [8]. Participants (N = 493) were recruited online from Prolific Academic to complete a Qualtrics survey. A power analysis for a small effect size (f = 0.15) with a power of 0.80 showed that 432 participants were needed; 493 participants were recruited to account for potential data loss. After exclusions, a final N of 440 participants (MBMI= 27.5, SD = 6.82) were analyzed.
Eligible participants were U.S. citizens who were at least 18 years of age. Recruitment was stratified to obtain a balance of males versus females (self-reported biological sex), and individuals who self-identified as “overweight”/“very overweight” versus “neither overweight nor underweight”/“underweight”/“very underweight” (demographics in Table 1). Participants were compensated $5.00, and informed consent was obtained from all study participants. Study procedures were ruled exempt by the National Institutes of Health Institutional Review Board.
Table 1.
Demographics
| Total N = 440 | ||
|---|---|---|
| N | % | |
| Gender | ||
| Man | 213 | 48.40 |
| Woman | 220 | 50 |
| Non-binary | 5 | 1.10 |
| Gender fluid | 2 | 0.50 |
| Sexual identity | ||
| Straight or heterosexual | 347 | 78.90 |
| Lesbian | 7 | 1.60 |
| Gay | 13 | 3.00 |
| Bisexual | 41 | 9.30 |
| Pansexual | 9 | 2.00 |
| Asexual | 3 | 0.70 |
| Queer | 3 | 0.70 |
| Other | 14 | 3.18 |
| Did not specify | 3 | 0.70 |
| Racial group | ||
| Asian | 16 | 3.60 |
| Black or African American | 41 | 9.30 |
| Native American/Alaskan Native | 4 | 0.90 |
| North African or Middle Eastern | 2 | 0.50 |
| White or Caucasian | 336 | 76.40 |
| Multiracial | 31 | 7.00 |
| Other | 9 | 2.00 |
| Did not specify | 1 | 0.20 |
| Hispanic or Latinx/a/o | ||
| Yes | 46 | 10.50 |
| No | 394 | 89.50 |
| Household income | ||
| <$25,000 | 76 | 17.30 |
| $25,000–$50,000 | 106 | 24.10 |
| $50,001–$100,000 | 170 | 38.60 |
| $100,001–$200,000 | 72 | 16.40 |
| >$200,000 | 16 | 3.60 |
| Education | ||
| Some high school | 10 | 2.30 |
| High school diploma/GED | 69 | 15.70 |
| Some college | 89 | 20.20 |
| Associates degree or trade school | 42 | 9.50 |
| Bachelor’s degree | 169 | 38.40 |
| Master’s degree | 51 | 11.60 |
| Doctorate or equivalent | 10 | 2.30 |
| Political beliefs | ||
| Extremely liberal | 85 | 19.30 |
| Liberal | 122 | 27.70 |
| Slightly liberal | 56 | 12.70 |
| Moderate/middle of the road | 86 | 19.50 |
| Slightly conservative | 40 | 9.10 |
| Conservative | 40 | 9.10 |
| Extremely conservative | 11 | 2.50 |
| Ever used a weight loss medication | ||
| No | 371 | 84.30 |
| Yes | 69 | 15.70 |
Design
The present study used a randomized, between-subjects design testing the effects of three weight loss methods on GLP-1 policy support (diet/exercise: n = 176, GLP-1: n = 175, or bariatric surgery for targets of higher body size: n = 89). The original study [8] tested an additional factor (body size of a target woman: lean vs. woman with obesity). Because it is not feasible for a lean person to have bariatric surgery, a lean woman/surgery condition was not tested in the original study, resulting in a smaller n for the present study’s surgery condition. Furthermore, exposure to GLP-1 users who have larger and smaller bodies is widespread [14] and likely affects views toward related policies, even when such policies are specifically for people with obesity. Thus, the present study examined effects regardless of the target’s body size on policy support to increase external validity. Participants were randomly assigned to read about and view a photo of a woman (who either was lean or had obesity, per the original study’s design) named Sarah, in her 30s, who lost 15% of her total body weight after 3 months either with diet/exercise, a GLP-1, or bariatric surgery. Participants were informed that the photo depicted Sarah after weight loss.
Measures
Full measures, code, and data analyzed for the present study can be found online at https://osf.io/xme4w/. We assessed self-reported height and weight (to calculate BMI). Political views, self-categorized body size, racial/ethnic group, gender, sexual identity, highest degree of education, annual household income, and past experiences with over-the-counter and prescription weight loss medications and weight loss surgery were also measured as potential covariates and to characterize the sample.
Weight Loss Shortcut Beliefs
After reading about and viewing a photo of Sarah, participants responded to four items assessing the extent to which they believed that, for example, “Sarah took the easy way out to lose weight” [8]. All questions were scaled 1 (not at all) to 7 (very). A mean of all four questions was computed (α = .89).
GLP-1 Policy Support
After reporting weight loss “shortcut” beliefs, participants read information defining obesity as “having a BMI of 30 or higher” and describing GLP-1s before responding to questions assessing support for three policies related to expanding coverage of GLP-1s for people with obesity, scaled from 1 (strongly oppose) to 5 (strongly support). The three items were strongly correlated (rs = .60–.69) and thus were combined into one “GLP-1 policy support” outcome.
The first policy item measured support for the Treat and Reduce Obesity Act, described as a legislative bill that would expand Medicare to cover medications to treat obesity, such as GLP-1s. The Treat and Reduce Obesity Act is currently under consideration by the U.S. government. The second policy item measured support for a federal policy to require employers to cover the cost of GLP-1s for people with obesity. This item was informed by market research measuring perceptions of prescription weight loss drug coverage [15]. The third item measured support for a federal policy subsidizing GLP-1s for people with obesity with household income of less than $30,000 per year. This item was informed by policies that subsidize health costs for people with lower incomes, such as the Affordable Care Act.
Data Analytic Plan
Analyses were conducted with SPSS (v29). With one exception, one-way analyses of variance (ANOVAs) and chi-square tests for categorical variables revealed no significant demographic differences by condition (ps > .05). Because there was a significant difference in past weight loss medication use by condition (p = .047), analyses controlled for past use. Political beliefs positively correlated with policy support and were also included as a covariate.
Although the present data were from a larger study that tested two factors (weight loss method and target body size [8]), the current study’s goal was to examine the effect of exposure to different weight loss methods on policy support. To ensure that combining conditions across target body size was sound, we tested for interactions between the original two factors on each policy outcome with two-way ANOVAs. There were no marginal or significant main effects of target body size or weight loss method-by-target body size interactions (ps > .05).
Mean comparisons of GLP-1 policy support and shortcut beliefs by condition were examined with a one-way analysis of covariance (ANCOVA). Hayes’ PROCESS macro (5,000 bootstrap samples) [16] tested whether weight loss shortcut beliefs mediated the effect of weight loss method (diet/exercise, GLP-1, or bariatric surgery) on GLP-1 policy support, dependent on participant BMI. The diet/exercise condition was the reference group. We confirmed moderated mediation when the 95% bias-corrected bootstrap confidence interval for the index of moderated mediation did not contain zero.
Results
There were significant differences by condition on GLP-1 policy support. The diet/exercise condition (M = 3.20, SE = .08) had significantly lower policy support relative to the GLP-1 condition (M = 3.45, SE = .08; p = .023), but diet/exercise was not significantly different than bariatric surgery (M = 3.39, SE = .11; p = .17). The GLP-1 and surgery conditions also did not significantly differ (p = .62).
There were also significant differences by condition on weight loss shortcut beliefs. The diet/exercise condition (M = 1.27, SD = .54) had significantly lower shortcut beliefs compared to the GLP-1 (M = 3.76, SD = 1.52; p < .001) and surgery (M = 3.51, SD = 1.35; p < .001) conditions. Shortcut beliefs between the GLP-1 and surgery conditions did not significantly differ (p = .122).
Moderated mediation analyses showed that GLP-1 and bariatric surgery exposure (vs. diet/exercise) predicted higher weight loss shortcut beliefs, and shortcut beliefs were negatively associated with GLP-1 policy support. Importantly, there were significant negative indirect effects on policy support, through shortcut beliefs, for both the GLP-1 and surgery conditions. More conservative political beliefs were associated with higher shortcut beliefs and lower policy support. While past weight loss medication use was negatively associated with shortcut beliefs, it was not associated with policy support. There were significant positive direct effects of GLP-1 and surgery (vs. diet/exercise) on policy support. Finally, there were no interactions with BMI and shortcut beliefs or weight loss method on policy support. The index of moderated mediation was not significant. These results indicate that, while controlling for political views and past weight loss medication use, exposure to GLP-1 and surgery use (vs. diet/exercise) led to higher GLP-1 policy support. Exposure also indirectly led to lower GLP-1 policy support, partially mediated by higher shortcut beliefs. However, participant BMI did not moderate these effects (see Fig. 1).
Fig. 1.
Moderated mediation model: the effects of weight loss method on GLP-1 policy support through weight loss shortcut beliefs, dependent on participant BMI. GLP-1 index of moderated mediation = .024, CI = [−.003, .045]. Bariatric surgery index of moderated mediation = .022, CI = [−.003, .041]. Note. Dashed lines indicate that the confidence interval includes zero. Dotted circles indicate variables entered into the model as covariates. BMI = body mass index; WL = weight loss; political beliefs were coded such that higher numbers indicated more conservative beliefs.
Discussion
The present study examined how exposure to a target woman who successfully lost weight with a medical intervention versus diet/exercise influenced support for policies to expand coverage of GLP-1s for people with obesity. Mean differences based on experimental conditions demonstrated that reading about a target woman who lost weight with a GLP-1 or bariatric survey (vs. diet/exercise) led to higher GLP-1 policy support. However, exposure to weight loss with a GLP-1 simultaneously led to lower GLP-1 policy support by eliciting beliefs that GLP-1s and surgery are “shortcuts,” or strategies to lose weight without hard work. This finding is consistent with research showing that both bariatric surgery [9] and other weight loss medications [17] are judged as “taking the easy way out.” This pattern occurred despite a positive direct effect of GLP-1 and surgery exposure on policy support, suggesting that perceptions that medical obesity treatments are a form of “cheating” may diminish otherwise positive effects of exposure to GLP-1 and surgery use, at least to some extent, and reduce support. Perceptions that GLP-1s are a “shortcut” may be related to Western cultural attitudes, such as pro-effort biases about weight and weight loss [18] and Protestant work ethic beliefs, which attach inherent value to hard work. Additionally, weight and thinness are frequently regarded as symbols of social status and good health, and thus these cultural beliefs may contribute to the disapproval of reaping benefits associated with weight loss without exerting effort. If individuals perceive that medical weight loss interventions require less personal effort and hard work than lifestyle changes, it could cultivate attitudes that their broad accessibility for people with obesity is unwarranted.
Notably, the effect of GLP-1 or bariatric surgery (vs. diet/exercise) exposure on policy support, through higher shortcut beliefs, did not depend on participant BMI. Individuals with higher BMIs may have perceived GLP-1s to be a “shortcut” as much as individuals with lower BMIs, despite medical obesity treatments being more personally relevant to people with higher BMIs. This perception could stem from widely held beliefs among individuals of all body sizes that weight and weight loss are a matter of personal responsibility and willpower [19, 20]. Alternatively, individuals with higher BMIs may be skeptical about the effectiveness of GLP-1s for long-term weight management, perceiving it as a short-term “quick fix” solution, especially if they have tried other methods without long-term success. Because the vast majority of people with obesity regain weight after weight loss [21] and research suggests that most GLP-1 users will need to sustain their use over time to maintain weight loss [22], individuals with higher and lower BMIs may be similarly skeptical that GLP-1s can support long-term weight loss. These perceptions could lead to a lack of support for policies promoting GLP-1 treatments.
Political views also impacted GLP-1 policy support. More conservative views were associated with higher shortcut beliefs and lower GLP-1 policy support. However, the effects of exposure to a target woman who lost weight with GLP-1 or bariatric surgery (vs. diet/exercise) on shortcut beliefs and GLP-1 policy support remained significant when controlling for political views, indicating that these effects are independent of and extend beyond the influence of political views. Yet, understanding the influence of political beliefs on support for expanding coverage of GLP-1s is an important next step as demand for access to the medications through employer- and government-sponsored healthcare plans grows [23]. This surge in demand coincides with widely held negative attitudes toward pharmaceutical companies [24] and prescription drug costs [15], suggesting multiple sociopolitical factors may shape GLP-1 policy support and deserve scientific attention.
Finally, it is notable that exposure to GLP-1 use or bariatric surgery affected GLP-1 policy support. This finding suggests a possible spillover effect whereby exposure to people who lose weight with a medical intervention may influence policy support for other medical weight loss treatments, even if the interventions differ substantially. Policymakers should consider such spillover effects to better understand how perceptions of different medical obesity interventions influence support for a broader spectrum of obesity treatments and related health policies.
Limitations and Future Directions
This study examined the effect of exposure to a white target woman who lost weight with GLP-1s on policy support. Racial, gender, and age-related biases exist in the USA, and thus it is unknown how policy support may differ when viewing diverse targets whose characteristics are different from (or similar to) study participants. Additionally, we examined the combined effect of a lean target woman and a woman with obesity. Although this approach increased the present study’s external validity given that people of varying body sizes use GLP-1s for weight loss, future research should examine the effect of exposure to different target weight statuses on policy support independently. Finally, we did not measure baseline GLP-1 policy support, which could have allowed us to assess change in support after presenting the experimental stimuli.
Conclusion
This study provides evidence that exposure to medical weight loss interventions leads to higher GLP-1 policy support. However, such exposure also indirectly leads to lower support due to beliefs that medical weight loss interventions are “shortcuts.” Findings have implications for policymakers aiming to grasp how public perceptions of different weight loss methods influence support for medical obesity treatments and associated health policies.
Acknowledgments
We would like to thank Crystal Peterson and Kaylee Foor for assistance with data collection preparation and Christopher Fortney for assistance with experimental stimuli preparation.
Contributor Information
Stacy M Post, Department of Psychological and Brain Sciences, The George Washington University, Washington, DC, USA.
Rebecca K Hoffman, Pacific Institute for Research & Evaluation, Beltsville, MD, USA.
Junhan Chen, The University of Hong Kong, Journalism and Media Studies Centre, Hong Kong, China.
Michelle L Stock, Department of Psychological and Brain Sciences, The George Washington University, Washington, DC, USA.
Susan Persky, Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD, USA.
Funding
This study was supported by the Intramural Research Program of the National Human Genome Research Institute.
Compliance with Ethical Standards
Authors’ Statement of Conflict of Interest and Adherence to Ethical Standards Authors Stacy M. Post, Rebecca K. Hoffman, Junhan Chen, Michelle L. Stock, and Susan Persky declare that they have no conflicts of interest.
Authors’ Contributions Stacy M. Post (Conceptualization, Investigation, Formal analysis, Methodology, Project administration, Writing—ordinal draft, Writing—review & editing), Rebecca K. Hoffman (Writing—review & editing), Junhan Chen (Investigation, Writing—review & editing), Michelle L. Stock (Writing—review & editing), Susan Persky (Conceptualization, Investigation, Methodology, Writing—review & editing, Supervision)
Transparency Statements
Study registration This study’s data were part of another study, which was preregistered. Details can be found here: https://osf.io/j2tny.
Analytic plan preregistration The analysis plan for the present study was not formally preregistered. However, the original study’s preregistration states the researchers planned to examine the effects of experimental stimuli on policy support as secondary analyses.
Data availability De-identified data from this study are available in a public archive: https://osf.io/xme4w/
Analytic code availability Analytic code used to conduct the analyses presented in this study is available in a public archive: https://osf.io/xme4w/
Materials availability All materials used to conduct the study are available in a public archive: https://osf.io/xme4w/
References
- 1. Jensterle M, Rizzo M, Haluzík M, Janež A.. Efficacy of GLP-1 RA approved for weight management in patients with or without diabetes: a narrative review. Adv Ther. 2022; 39(6):2452–2467. doi: https://doi.org/ 10.1007/s12325-022-02153-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Gendall P, Hoek J, Taylor R, Mann J, Krebs J, Parry-Strong A.. Should support for obesity interventions or perceptions of their perceived effectiveness shape policy? Aust N Z J Public Health. 2015; 39(2):172–176. doi: https://doi.org/ 10.1111/1753-6405.12319 [DOI] [PubMed] [Google Scholar]
- 3. Woolford SJ, Clark SJ, Butchart A, Geiger JD, Davis MM, Fagerlin A.. To pay or not to pay: public perception regarding insurance coverage of obesity treatment. Obesity. 2013; 21(12):E709–E714. doi: https://doi.org/ 10.1002/oby.20387 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Kaiser Family Foundation. The public’s views of new prescription weight loss drugs and prescription drug costs. August 4, 2023. Available at https://www.kff.org/health-costs/poll-finding/public-opinion-on-prescription-drugs-and-their-prices/. Accessed October 18, 2023. [Google Scholar]
- 5. Congressional Budget Office. A call for new research in the area of obesity. October 5, 2023. Available at https://www.cbo.gov/publication/59590#:~:text=Members%20of%20Congress%20have%20introduced,of%20AOMs%20by%20Medicare%20enrollees. Accessed October 23, 2023. [Google Scholar]
- 6. Bernstein E. On Ozempic, and feeling judged for taking the “easy way out.” The Wall Street Journal. July 26, 2023. Available at https://www.wsj.com/articles/ozempic-weight-loss-drugs-strains-relationships-327ab217. Accessed August 25, 2023. [Google Scholar]
- 7. Thompson D. The weight-loss-drug revolution is a miracle—and a menace. The Atlantic. January 27, 2023. Available at https://www.theatlantic.com/newsletters/archive/2023/01/the-weight-loss-drug-revolution-is-a-miracle-and-a-menace/672861/. Accessibility verified November 8, 2023. [Google Scholar]
- 8. Post SM, Persky S.. The effect of GLP-1 receptor agonist use on negative evaluations of women with higher and lower body weight. Int J Obes. 2024; 48(7):1019–1026. doi: https://doi.org/ 10.1038/s41366-024-01516-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Dolan P, Afaneh C, Symer M, Dakin GF, Pomp A, Yeo H.. Assessment of public attitudes toward weight loss surgery in the United States. JAMA Surg. 2019; 154(3):264. doi: https://doi.org/ 10.1001/jamasurg.2018.4650 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Mattingly BA, Stambush MA, Hill AE.. Shedding the pounds but not the stigma: negative attributions as a function of a target’s method of weight loss: attributions of weight loss. J Appl Biobehav Res. 2009; 14(3):128–144. doi: https://doi.org/ 10.1111/j.1751-9861.2009.00045.x [DOI] [Google Scholar]
- 11. McCall L, Burk D, Laperrière M, Richeson JA.. Exposure to rising inequality shapes Americans’ opportunity beliefs and policy support. Proc Natl Acad Sci USA. 2017; 114(36):9593–9598. doi: https://doi.org/ 10.1073/pnas.1706253114 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Saguy AC, Frederick D, Gruys K.. Reporting risk, producing prejudice: how news reporting on obesity shapes attitudes about health risk, policy, and prejudice. Soc Sci Med. 2014; 111:125–133. doi: https://doi.org/ 10.1016/j.socscimed.2014.03.026 [DOI] [PubMed] [Google Scholar]
- 13. Petty RE, Barden J, Wheeler SC.. The elaboration likelihood model of persuasion: developing health promotions for sustained behavioral change. In: DiClemente RJ, Crosby RA, Kegler MC, eds. Emerging Theories in Health Promotion Practice and Research. San Francisco, CA: Jossey-Bass/Wiley; 2009:185–214. [Google Scholar]
- 14. Pazzanese C. How “Ozempic shaming” illuminates complexities of treating weight problems. Harvard Gazette. February 5, 2024. Available at https://news.harvard.edu/gazette/story/2024/02/how-ozempic-shaming-illuminates-complexities-of-treating-weight-problems/. Accessed August 9, 2023. [Google Scholar]
- 15. Sparks G, Kirzinger A, Montero A, Valdes I, Hamel L.. Public opinion on prescription drugs and their prices. Kaiser Family Foundation. August 29, 2023. Available at https://www.kff.org/health-costs/poll-finding/public-opinion-on-prescription-drugs-and-their-prices/. Accessed September 14, 2023. [Google Scholar]
- 16. Hayes A F. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. New York, NY: Guilford; 2017. [Google Scholar]
- 17. Xing S, Sharp LK, Touchette DR.. Weight loss drugs and lifestyle modification: perceptions among a diverse adult sample. Patient Educ Couns. 2017; 100(3):592–597. doi: https://doi.org/ 10.1016/j.pec.2016.11.004 [DOI] [PubMed] [Google Scholar]
- 18. Beames JR, Black MJ, Vartanian LR.. Prejudice toward individuals with obesity: evidence for a pro-effort bias. J Exp Psychol Appl. 2016; 22(2):184–195. doi: https://doi.org/ 10.1037/xap0000079 [DOI] [PubMed] [Google Scholar]
- 19. Grannell A, Le Roux CW, McGillicuddy D.. “You are always at war with yourself” the perceptions and beliefs of people with obesity regarding obesity as a disease. Qual Health Res. 2021; 31(13):2470–2485. doi: https://doi.org/ 10.1177/10497323211040767 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Pearl RL, Lebowitz MS.. Beyond personal responsibility: effects of causal attributions for overweight and obesity on weight-related beliefs, stigma, and policy support. Psychol Health. 2014; 29(10):1176–1191. doi: https://doi.org/ 10.1080/08870446.2014.916807 [DOI] [PubMed] [Google Scholar]
- 21. Dombrowski SU, Knittle K, Avenell A, Araujo-Soares V, Sniehotta FF.. Long term maintenance of weight loss with non-surgical interventions in obese adults: systematic review and meta-analyses of randomised controlled trials. BMJ. 2014; 348:g2646–g2646. doi: https://doi.org/ 10.1136/bmj.g2646 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Wilding JPH, Batterham RL, Davies M, et al. ; STEP 1 Study Group. Weight regain and cardiometabolic effects after withdrawal of semaglutide: the STEP 1 trial extension. Diabetes Obes Metab. 2022; 24(8):1553–1564. doi: https://doi.org/ 10.1111/dom.14725 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Foxman S, Nahmias L.. Ozempic’s cost: weight loss drugs will be billed to US taxpayers. Bloomberg. January 5, 2024. Available at https://www.bloomberg.com/news/articles/2024-01-05/ozempic-s-cost-weight-loss-drugs-will-be-billed-to-us-taxpayers?embedded-checkout=true. Accessed January 16, 2024. [Google Scholar]
- 24. McCarthy J. Big pharma sinks to the bottom of U.S. industry rankings. Gallup. September 3, 2019. Available at https://news.gallup.com/poll/266060/big-pharma-sinks-bottom-industry-rankings.aspx. Accessed October 17, 2023. [Google Scholar]