Abstract
Background
People with obesity (PWO) often experience weight bias, resulting in weight bias internalization (WBI) which may impact their preferences for healthcare engagement. We explored sex differences in self-reported WBI and its influence on telehealth utilization preferences among racially/ethnically diverse PWO who have completed metabolic and bariatric surgery (MBS).
Methods
A qualitative approach was used. The impact of WBI on telehealth utilization preferences was assessed through in-depth interviews. Interviews were thematically analyzed to explore sex differences in preferences between telehealth and in-person visits.
Results
Qualitative analysis (n = 24, 54% female) identified themes such as quality of care, convenience, discrimination in healthcare settings, and shame. WBI was not a primary determinant of how to receive care for both men and women. Their perception of the quality of care they would receive from either telehealth, or in-person visits was the main consideration.
Conclusion
This qualitative research suggests WBI may be common among men and women who have completed MBS, but WBI was not the main factor considered when PWO made decisions about using telehealth or in-person care. Future studies should further explore how WBI impacts healthcare engagement and preferences among PWO who have completed MBS across diverse settings.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to the full article PDF.
USD 39.95
Prices may be subject to local taxes which are calculated during checkout


Similar content being viewed by others
Data availability
The data generated and analyzed for this study, which are primarily qualitative interview transcripts, are not publicly available due to ethical restrictions concerning participant anonymity and confidentiality. However, the study's interview guides and supporting materials are provided in the Supplementary Information files. De-identified excerpts of the data are included in the published article to support the findings.
References
Pearl RL, Puhl RM, Lessard LM, Himmelstein MS, Foster GD. Prevalence and correlates of weight bias internalization in weight management: a multinational study. SSM Popul Health. 2021;13:100755.
Himmelstein MS, Puhl RM, Quinn DM. Intersectionality: an understudied framework for addressing weight stigma. Am J Prev Med. 2017;53:421–31.
Puhl RM, Brownell KD. Psychosocial origins of obesity stigma: toward changing a powerful and pervasive bias. Obes Rev. 2003;4:213–27.
Olaniran MO, Kapti EG, Mathew MS, Schellinger, JN, Allicock, MA, Messiah, SE, et al. Sex differences in perceived discrimination among patients with obesity. Clin Obes. Published online October 17, 2024. https://doi.org/10.1111/cob.12711
Alberga AS, Russell-Mayhew S, von Ranson KM, McLaren L. Weight bias: a call to action. J Eat Disord. 2016;4:34.
Ofori A, Keeton J, Booker Q, Schneider B, McAdams C, Messiah SE. Socioecological factors associated with ethnic disparities in metabolic and bariatric surgery utilization: a qualitative study. Surg Obes Relat Dis. 2020;16:786–95.
Kumar RB, Srivastava G, Reid TJ, Aronne LJ. Understanding the pathophysiologic pathways that underlie obesity and options for treatment. Expert Rev Endocrinol Metab. 2021;16:321–38.
Messiah SE, Xie L, de la Cruz-Muñoz N, Lipshultz SE. Use of metabolic and bariatric surgery among US youth. JAMA Pediatr. 2023;177:856.
English WJ, DeMaria EJ, Hutter MM, Kothari S, Mattar S, Brethauer S, et al. American Society for Metabolic and Bariatric Surgery 2018 estimate of metabolic and bariatric procedures performed in the United States. Surg Obes Relat Dis. 2020;16:457–63.
De Luca M, Shikora S, Eisenberg D, Angrisani L, Parmar C, Alqahtani A, et al. Scientific evidence for the updated guidelines on indications for metabolic and bariatric surgery (IFSO/ASMBS). Obes Surg. Published online September 25, 2024. https://doi.org/10.1007/s11695-024-07370-7
Flum DR, Khan TV, Dellinger EP. Toward the rational and equitable use of bariatric surgery. JAMA. 2007;298:1442.
Halperin F. The Future of Telehealth in Obesity Care. Obesity Action Coalition. Published Winter 2022. https://www.obesityaction.org/resources/the-future-of-telehealth-in-obesity-care/. Accessed November 9, 2024.
Richardson WS, Plaisance AM, Periou L, Buquoi J, Tillery D. Long-term management of patients after weight loss surgery. Ochsner J. 2009;9:154–9.
Messiah SE, Xie L, Mathew MS, Marroquín EM, Almandoz JP, Qureshi FG, et al. Impact of the COVID-19 pandemic on metabolic and bariatric surgery utilization and safety in the United States. Obes Surg. 2022;32:2289–98. https://doi.org/10.1007/s11695-022-06077-x.
Almandoz JP, Xie L, Schellinger JN, Mathew MS, Bismar N, Ofori A, et al. (2021) Substance use, mental health and weight- related behaviours during the COVID-19 pandemic in people with obesity. Clin Obes 11. https://doi.org/10.1111/cob.12440
Almandoz JP, Xie L, Schellinger JN, Mathew MS, Marroquín EM, Murvelashvilli N, et al. Changes in body weight, health behaviors, and mental health in adults with. Obes COVID-19 Pandemic Obes. 2022;30:1875–86. https://doi.org/10.1002/oby.23501.
Rutledge CM, O’Rourke J, Mason AM, Chike-Harris K, Behnke L, Melhado L, et al. Telehealth competencies for nursing education and practice. Nurse Educ. 2021;46:300–5. https://doi.org/10.1097/NNE.0000000000000988.
Gajarawala SN, Pelkowski JN. Telehealth benefits and barriers. J Nurse Practitioners. 2021;17:218–21. https://doi.org/10.1016/j.nurpra.2020.09.013.
Diedrichs P, PR. Weight bias: prejudice and discrimination toward overweight and obese people. Cambridge University Press.
Olaniran MO, Francis J, Neti S, Polavarapu D, Kapti EG, Mathew MS, et al. Mixed methods to assess sex differences in weight bias internalization among patients with obesity. Obes Sci Pract. 2025;11:e70084 https://doi.org/10.1002/osp4.70084.
National Institutes of Health (NIH). Consideration of Sex as a Biological Variable in NIH-funded Research. https://grants.nih.gov/grants/guide/notice-files/NOT-OD-15-102.html.
Szadvári I, Ostatníková D, Babková Durdiaková J. Sex differences matter: males and females are equal but not the same. Physiol Behav. 2023;259:114038 https://doi.org/10.1016/j.physbeh.2022.114038.
Legato MJ, Johnson PA, Manson JE. Consideration of sex differences in medicine to improve health care and patient outcomes. JAMA. 2016;316:1865 https://doi.org/10.1001/jama.2016.13995.
O’Brien BC, Harris IB, Beckman TJ, Reed DA, Cook DA. Standards for reporting qualitative research. Acad Med. 2014;89:1245–51. https://doi.org/10.1097/ACM.0000000000000388.
Tenny S, Brannan J, Brannan G. Qualitative Study. StatPearls Publishing; 2024.
Pavlovic N, Brady B, Boland R, et al. A mixed methods approach to investigating physical activity in people with obesity participating in a chronic care programme awaiting total knee or hip arthroplasty. Musculoskelet Care. 2023;21:1447–62. https://doi.org/10.1002/msc.1825.
Martínez-Mesa J, González-Chica DA, Duquia RP, Bonamigo RR, Bastos JL. Sampling: how to select participants in my research study. Bras Dermatol. 2016;91:326–30. https://doi.org/10.1590/abd1806-4841.20165254.
Craig HC, Alsaeed D, Norris S, Holian J, Kennedy C, Feldman A, et al. Patient perspectives about treatment preferences for obesity with complications. Obes Sci Pract. 2024;10. https://doi.org/10.1002/osp4.720
Onwuegbuzie A, Collins K. A typology of mixed methods sampling designs in social science research. Qualit Rep Published online. 2015. https://doi.org/10.46743/2160-3715/2007.1638. January 15.
Anekwe CV, Jarrell AR, Townsend MJ, Gaudier GI, Hiserodt JM, Stanford FC. Socioeconomics of obesity. Curr Obes Rep. 2020;9:272–9. https://doi.org/10.1007/s13679-020-00398-7.
Butt M, Harvey A, Khesroh E, Rigby A, Paul IM. Assessment and impact of paediatric internalized weight bias: a systematic review. Pediatr Obes. 2023;18. https://doi.org/10.1111/ijpo.13040
Proudfoot K. Inductive/deductive hybrid thematic analysis in mixed methods research. J Mix Methods Res. 2023;17:308–26. https://doi.org/10.1177/15586898221126816
Olson A, Lyons K, Watowicz R, Loria M, Meluban L, Lampkin S, et al. Obesity preclinical elective: a qualitative thematic analysis of student feedback. Int J Obes. 2024;48:78–82. https://doi.org/10.1038/s41366-023-01387-1.
Ryan L, Quigley F, Birney S, Crotty M, Conlan O, Walsh JC. ‘Beyond the scale’: a qualitative exploration of the impact of weight stigma experienced by patients with obesity in general practice. Health Expectations. 2024;27. https://doi.org/10.1111/hex.14098
Saunders JF, Nutter S, Russell-Mayhew S. Examining the conceptual and measurement overlap of body dissatisfaction and internalized weight stigma in predominantly female samples: a meta-analysis and measurement refinement study. Front Glob Womens Health. 2022;3. https://doi.org/10.3389/fgwh.2022.877554
Doyle L, McCabe C, Keogh B, Brady A, McCann M. An overview of the qualitative descriptive design within nursing research. J Res Nurs. 2020;25:443–55. https://doi.org/10.1177/1744987119880234.
Sundler AJ, Lindberg E, Nilsson C, Palmér L. Qualitative thematic analysis based on descriptive phenomenology. Nurs Open. 2019;6:733–9. https://doi.org/10.1002/nop2.275.
Archibald MM. Investigator triangulation. J Mix Methods Res. 2016;10:228–50. https://doi.org/10.1177/1558689815570092.
Lumivero. NVivo (Version 14). www.lumivero.com. Published online 2023.
Diedrichs PC, Puhl R. Weight bias: prejudice and discrimination toward overweight and obese people. In: The Cambridge Handbook of the Psychology of Prejudice. Cambridge University Press; 2016. p. 392–412 https://doi.org/10.1017/9781316161579.017
Tchang BG, Morrison C, Kim JT, Ahmed F, Chan KM, Alonso LC, et al. Weight loss outcomes with telemedicine during COVID-19. Front Endocrinol (Lausanne). 2022;13. https://doi.org/10.3389/fendo.2022.793290
Stewart SJF, Ogden J. The role of social exposure in predicting weight bias and weight bias internalisation: an international study. Int J Obes. 2021;45:1259–70. https://doi.org/10.1038/s41366-021-00791-9.
Predmore ZS, Roth E, Breslau J, Fischer SH, Uscher-Pines L. Assessment of patient preferences for telehealth in post–COVID-19 pandemic health care. JAMA Netw Open. 2021;4:e2136405 https://doi.org/10.1001/jamanetworkopen.2021.36405.
Watson S. Telehealth: the advantages and disadvantages. Harvard Health Publishing. Published online November 2020.
Chen K, Zhang C, Gurley A, Akkem S, Jackson H. Primary care utilization among telehealth users and non-users at a large urban public healthcare system. PLoS One. 2022;17. https://doi.org/10.1371/journal.pone.0272605
Lee J, Chun E, Chang C, Liu T, Dunn RL, McCullough JS, et al. Telehealth and outpatient utilization: trends in evaluation and management visits among Medicare fee-for-service beneficiaries, 2019–2024. MedRxiv. 2025. https://doi.org/10.1101/2025.03.05.25323449
Saharkhiz M, Rao T, Parker-Lue S, Borelli S, Johnson K, Cataife G. Telehealth expansion and medicare beneficiaries’ care quality and access. JAMA Netw Open. 2024;7:e2411006 https://doi.org/10.1001/jamanetworkopen.2024.11006.
Shah VV, Villaflores CW, Chuong LH, Leuchter RK, Kilaru AS, Vangala S, et al. Association between in-person vs telehealth follow-up and rates of repeated hospital visits among patients seen in the emergency department. JAMA Netw Open. Published online 2022:E2237783. https://doi.org/10.1001/jamanetworkopen.2022.37783
Baughman DJ, Jabbarpour Y, Westfall JM, Jetty A, Zain A, Baughman K, et al. Comparison of quality performance measures for patients receiving in-person vs telemedicine primary care in a large integrated health system. JAMA Netw Open. 2022;5:e2233267 https://doi.org/10.1001/jamanetworkopen.2022.33267.
Tierney AA, Payán DD, Brown TT, Aguilera A, Shortell SM, Rodriguez HPTelehealthUse. Care continuity, and quality. Med Care. 2023;61:S62–9. https://doi.org/10.1097/MLR.0000000000001811.
Kahan S, Look M, Fitch A. The benefit of telemedicine in obesity care. Obesity. 2022;30:577–86. https://doi.org/10.1002/oby.23382.
Moulaei K, Sheikhtaheri A, Fatehi F, Shanbehzadeh M, Bahaadinbeigy K. Patients’ perspectives and preferences toward telemedicine versus in-person visits: a mixed-methods study on 1226 patients. BMC Med Inf Decis Mak. 2023;23:261. https://doi.org/10.1186/s12911-023-02348-4.
Luna P, Lee M, Vergara Greeno R, DeLucia N, London Y, Hoffman P, et al. Telehealth care before and during COVID-19: trends and quality in a large health system. JAMIA Open. 2022;5. https://doi.org/10.1093/jamiaopen/ooac079
Binsaeed B, Aljohani FG, Alsobiai FF, Alraddadi M, Alrehaili A, Alnahdi B, et al. Barriers and motivators to weight loss in people with obesity. Cureus. Published online November 19, 2023. https://doi.org/10.7759/cureus.49040
Haleem A, Javaid M, Singh RP, Suman R. Telemedicine for healthcare: capabilities, features, barriers, and applications. Sens Int. 2021;2:100117 https://doi.org/10.1016/j.sintl.2021.100117.
Hinchliffe N, Capehorn MS, Bewick M, Feenie J. The potential role of digital health in obesity care. Adv Ther. 2022;39:4397–412. https://doi.org/10.1007/s12325-022-02265-4.
Hlavin C, Ingraham P, Byrd T, Hyre N, Gabriel L, Agrawal N, et al. Clinical outcomes and hospital utilization among patients undergoing bariatric surgery with telemedicine preoperative Care. JAMA Netw Open. 2023;6:e2255994 https://doi.org/10.1001/jamanetworkopen.2022.55994.
Athanasiadis DI, Carr RA, Smith C, Dirks R, Hilgendorf W, Stefanidou MN, et al. Social support provided to bariatric surgery patients through a Facebook group may improve weight loss outcomes. Surg Endosc. 2022;36:7652–5. https://doi.org/10.1007/s00464-022-09067-3.
Berry CA, Kwok L, Massar R, Change JE, Lindenfeld Z, Shelley D, et al. Patients’ perspectives on the shift to telemedicine in primary and behavioral health care during the COVID-19 pandemic. J Gen Intern Med. 2022;37:4248–56. https://doi.org/10.1007/s11606-022-07827-4.
Aaron DG, Stanford FC. Is obesity a manifestation of systemic racism? A ten-point strategy for study and intervention. J Intern Med. 2021;290:416–20. https://doi.org/10.1111/joim.13270.
Fernbach RA, Papapetros J. Increased access to telehealth as a means of reducing stigma. Behavioral Health News. Published July 14, 2022. https://behavioralhealthnews.org/increased-access-to-telehealth-as-a-means-of-reducing-stigma/. Accessed October 9, 2024.
Acknowledgements
We are grateful to the staff at UTSW Weight Wellness Clinic for their support at the study site, and we are thankful to the patients for their participation in this study.
Funding
This study is funded by a grant from the National Institutes of Minority Health and Health Disparities (3R01MD011686-05S2).
Author information
Authors and Affiliations
Contributions
MO conducted the qualitative data collection and analyses, and was involved with project administration, and writing—original draft, review and editing. SN, DP, AA, and JF assisted with all qualitative analyses, and writing. MM AND JS were involved in recruitment strategies and writing. MA was involved in supervision, and writing—review and editing. SM obtained funding for the research including study design, analysis of data, interpretation of results, and writing of the report, and she was involved in conceptualization, methodology, supervision, project administration, and review and editing of the manuscript. JA obtained funding for the research and led the study design, analysis of data, interpretation of results, and writing of the report. He was involved in conceptualization, methodology, supervision, project administration, and review and editing of the manuscript. All co-authors contributed substantially to the manuscript and approved the final submission.
Corresponding author
Ethics declarations
Competing interests
This study was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. However, JPA has received advisory or consulting fees and/or other support from AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Nestlé, Novo Nordisk A/S and Wave Life Sciences.
Ethics approval and consent to participate
All methods were performed in accordance with the relevant guidelines and regulations. This qualitative study adhered to the Standards for Reporting Qualitative Research (SRQR) guidelines for reporting qualitative research. All study procedures were approved by the Institutional Review Board (IRB) of the Committee for the Protection of Human Subjects (CPHS) at The University of Texas Health Science Center at Houston on November 5, 2018. The approval reference number is IRB NUMBER: HSC-SPH-18-0850.
Informed consent
Participants were recruited following procedures approved by the IRB. Digital informed consent was obtained from all participants by clicking the embedded link within the initial communication, which directed them to a researcher-designed questionnaire where they provided consent and demographic information.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Olaniran, M.O., Neti, S., Polavarapu, D. et al. Sex differences in the influence of weight bias internalization on preferences for telehealth utilization among people with obesity. Int J Obes (2025). https://doi.org/10.1038/s41366-025-01977-1
Received:
Revised:
Accepted:
Published:
Version of record:
DOI: https://doi.org/10.1038/s41366-025-01977-1

