The need for future research into the assessment and monitoring of eating disorder risk in the context of obesity treatment
Bibliographic record
Abstract
In adolescents and adults, the co-occurrence of eating disorders and overweight or obesity is continuing to increase, and the prevalence of eating disorders is higher in people with higher weight compared to those with lower weight. People with an eating disorder with higher weight are more likely to present for weight loss than for eating disorder treatment. However, there are no clinical practice guidelines on how to screen, assess, and monitor eating disorder risk in the context of obesity treatment. In this article, we first summarize current challenges and knowledge gaps related to the identification and assessment of eating disorder risk and symptoms in people with higher weight seeking obesity treatment. Specifically, we discuss considerations relating to the validation of current self-report measures, dietary restraint, body dissatisfaction, binge eating, and how change in eating disorder risk can be measured in this setting. Second, we propose avenues for further research to guide the development and implementation of clinical and research protocols for the identification and assessment of eating disorders in people with higher weight in the context of obesity treatment. PUBLIC SIGNIFICANCE: The number of people with both eating disorders and higher weight is increasing. Currently, there is little guidance for clinicians and researchers about how to identify and monitor risk of eating disorders in people with higher weight. We present limitations of current research and suggest future avenues for research to enhance care for people living with higher weight with eating disorders.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".