A case study of the BalancedView course : addressing weight stigma among health care providers in British Columbia
Bibliographic record
Abstract
Growing evidence shows weight stigma as a problem in health care settings. However, there remains a lack of conceptual clarity – particularly regarding if and how the medicalization of weight is implicated in weight stigma – and a gap in knowledge about how to successfully reduce weight stigma in health care. The research questions that guided this study were thus: • What are the different ways that weight stigma in health care can be conceptualized? • What strategies can be employed to reduce weight stigma among health care providers? These questions were explored through a mixed methods case study of the development and implementation of an online course on weight stigma for health care providers in British Columbia called BalancedView, sponsored by the Provincial Health Services Authority. Using participant observation, document analysis, a focus group and semi-structured interviews, I examined how health care stakeholders who developed the course, and participants who went on to take the course, conceptualized weight stigma. I evaluated the effects of the course on 249 participating health care providers through questionnaires before and after the course. Using interviews with course participants and documentary analysis of qualitative comments made by participants during the course, I also explored what was most helpful about the course and why. Following a thematic analysis, I show how weight stigma was conceptualized as a process involving biased attitudes and beliefs that lead to discriminatory behaviours and adverse outcomes. It was perceived as a causally complex issue, with a relationship to emotions. The extent to which the medicalization of weight was viewed as part of weight stigma was a divisive topic in the development stage of the course. However, many participants who took the course reflected later that after learning about medicalization they saw harms in medicalized approaches to weight in health care. This study contributes to the currently limited literature on weight stigma reduction in health care. I demonstrate how an online course on weight stigma that uses multiple stigma reduction techniques had a positive effect in terms of reducing participants’ weight bias and discuss what essential elements within such interventions should be.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.019 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".