“i want help!”: Psychologists’ and physicians’ competence, barriers, and needs in the management of eating disorders in children and adolescents in Canada.
Bibliographic record
Abstract
Studies show that physicians are dissatisfied with their training in the area of eating disorders in general, and a number of practice barriers and training needs have been identified. There are no known studies examining attitudes and needs of physicians or psychologists with respect to eating disorders in children and adolescents in Canada. This study’s objectives are to examine primary care clinicians’ self-assessed competence, barriers, and needs with respect to the diagnosis and treatment of eating disorders in children and adolescents. A 20-item survey was developed to obtain information from family physicians and psychologists in Ontario, Canada. Findings of this study suggest that, with some exceptions, selfassessments of competence are low, and barriers to practice include lack of skill, case complexity, and lack of resources. Identified training needs suggest that, despite discipline-specific differences, a large proportion of clinicians report an interest in learning more about all areas of the management of pediatric eating disorders, including prevention efforts. In Ontario, primary care clinicians are interested in receiving training and support to better identify and treat children and adolescents with eating disorders. As such, it is worthwhile to increase the number of training opportunities for students and professionals alike.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".