Perceived Weight, Weight Stigma, and Disordered Eating Among Students in Health-Related University Programs
Bibliographic record
Abstract
The present study aimed to examine the association between experienced weight stigma (WS) and disordered eating among undergraduate students in health-related programs, and to examine whether perceived weight status explained disordered eating beyond experienced WS. It was hypothesized that (1) experienced WS would positively correlate with disordered eating scores, and (2) perceived weight status could explain disordered eating behaviours over and above the explanation of experienced WS for cognitive and emotional eating, but not for uncontrolled eating. To test these hypotheses, undergraduate students and alumni enrolled in health-related majors (n=187) were recruited from a mid-sized university in Ontario, Canada. All participants reported their perceived weight status, and filled out a demographic information sheet, the Three-Factor Eating Questionnaire-18, and the Stigmatizing Situations Inventory-Brief Form questionnaire. Linear regressions and hierarchical regression models were used to analyze these potential relationships. A significant, positive correlation existed between experienced WS and disordered eating among undergraduate students in health-related programs. Additionally, it was found that perceived weight status explained further variance than experienced WS could for cognitive restraint and emotional eating, but not for uncontrolled eating. The findings suggest that health-related undergraduate students do not significantly differ from other groups; however, further research is supported.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".