How does the Calibre learning program impact attitudes towards caring for patients who have obesity?

Weight bias, defined as negative misconceptions and stereotypes associated with weight, is prevalent in healthcare settings and is a critical barrier to patient-centred obesity care. Several calls to action have indicated the need to educate healthcare professionals on mitigating weight bias in delivery of care. The objective of this study was to evaluate the impact of The Canadian Advanced Learning in Bariatric Care (Calibre), on healthcare providers’ attitudes towards caring for patients who have obesity and strategies to reduce weight bias in their delivery of care. This prospective cohort study uses pre- and post-intervention design to assess Calibre. Calibre was administered online to healthcare professionals of any designation who were actively involved or interested in obesity management. Participants completed the Attitudes Towards Caring for Patients Who Have Obesity and Assumptions Towards Compliance with Weight Management scale before and after Calibre. After completion they were asked if they would commit to any change in their practice, and if yes, with an open-ended response option they indicated their commitment. Pre- and post-surveys were assessed by a paired t-test. A conventional content analysis was performed to summarize commitments. The Calibre was completed by 216 health professionals and attitudes towards patients who have obesity significantly improved post taking the course ( p <0.001). All participants made a commitment which were grouped as: Collaborative goal setting, recognizing obesity complexity, implementing practical strategies to prevent weight bias (e.g., ensuring appropriately sized equipment is available) and use of patient-centred conversation and obesity measurement tools (e.g., 5 A’s). The Calibre may be an effective obesity continuing education resource for current and prospective medical professionals that could contribute to reducing weight bias in healthcare settings. Graphical abstract created using ChatGPT (OpenAI, 2026).