From one end of the scale to the other: overweight and obese individuals’ experiences with anorexic attitudes, cognitions, and behaviours
Bibliographic record
Abstract
Abstract The weight-based definition of anorexia nervosa (AN) can result in heavier individuals being excluded from evidence-based interventions and erroneously included in practices with negative physical and psychological consequences. Our purpose was to address the AN weight criteria limitation by expanding upon the components of disordered eating underlying membership in weight categories that are considered unhealthy. In this cross-sectional study, 733 male and female participants completed online questionnaires assessing age, gender, BMI (height and weight), and disordered eating behaviours and attitudes. Participants were grouped according to their weight status (underweight, normal weight, overweight, and obese). Results indicated that BMI was positively associated with many aspects of disordered eating but was inversely associated with restricting eating, excessive exercise, and muscle building in women. Underweight men and women reported similar levels of body dissatisfaction, but compared to men, the effect was much more pronounced in women as weight increased. Taken together, lighter-weight individuals reported higher levels of AN-specific behaviour (restricting eating) compared to heavier-weight participants. In contrast, heavier-weight individuals had higher AN-related attitudes, cognitions, and behaviours, such as body dissatisfaction, cognitive restraint, and binge eating. These results support that AN attitudes, cognitions, and behaviours can be found in individuals regardless of whether they are underweight or obese. Future research is needed to develop interventions addressing anorexic symptoms in people considered overweight or obese to meet their specific needs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".