Weight bias internalization and beliefs about the causes of obesity among the Canadian public
Bibliographic record
Abstract
Abstract Background Explicit weight bias is known as negative attitudes and beliefs toward individuals due to their weight status and can be perpetuated through misconceptions about the causes of obesity. Individuals may also experience weight bias internalization (WBI) when they internalize negative weight-related attitudes and self-stigmatize. There is a paucity of research on the beliefs about the causes of obesity and the prevalence of WBI among public Canadian samples. The aim of this study was to describe these attitudes and beliefs about obesity among a large Canadian sample across the weight spectrum. Methods A Canadian sample of adults (N = 942; 51% Women; mean age group = 45–54 years; mean body mass index [BMI] = 27.3 ± 6.7 kg/m2) completed an online questionnaire. Participants completed the Modified Weight Bias Internalization Scale, the Anti-Fat Attitudes Questionnaire, and the Causes of Obesity Questionnaire. Results Mean WBI score within the entire sample was 3.38 ± 1.58, and females had higher mean scores as compared to males (p < 0.001). Mean scores were also higher among individuals with a BMI of > 30 kg/m2 (4.16 ± 1.52), as compared to individuals with a BMI of 25–30 kg/m2 (3.40 ± 1.50), and those with a BMI of 20–25 kg/m2 or below 18.5 kg/m2 (2.81 ± 1.44) (p < 0.001 for all). Forty four percent of Canadians believed behavioural causes are very or extremely important in causing obesity, 38% for environmental causes, 28% for physiological and 27% for psychosocial causes. Stronger beliefs in behavioural causes were associated with higher levels of explicit weight bias. No BMI differences were reported on the four different subscales of the Causes of Obesity Questionnaire. Conclusions Weight bias internalization is prevalent among Canadians across all body weight statuses, and the public endorses behavioural causes of obesity, namely physical inactivity and overeating, more than its other causes. Findings warrant the reinforcement of efforts aimed at mitigating weight bias by educating the public about the complexity of obesity and by highlighting weight bias as a systemic issue that affects all Canadians living in diverse body weight statuses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".