Improving Collaborative Care in Managing Eating Disorders: A Pilot Study
Bibliographic record
Abstract
INTRODUCTION: The purpose of this pilot study was to evaluate the impact of a continuing interprofessional educational workshop focused on eating disorders in a rural area in Newfoundland and Labrador (NL), Canada. The pilot study helped determine if the eating disorder workshop was feasible for implementation to a broader audience. A conceptual model developed by our eating disorder team and described in the article guided this innovative program. METHODS: The intensive 2-day workshop was piloted in one community with 41 health and education professionals in attendance. A key element was the focus on creating and sustaining collaborative care for eating disorders. Participants completed pre-post workshop measures of interprofessional attitudes and skills, self-reported knowledge, confidence, and intention to change practice (post questionnaire only). A 6-month follow-up survey measured self-reported practice change. RESULTS: There were significant positive changes in interprofessional attitudes and skills as well as knowledge and confidence in collaborative management of eating disorders. Post-workshop, 69% (n = 24/35) of participants indicated intention to change practice, and on follow-up, 7 of 10 respondents reported implementing changes in practice as a result of the workshop. Low response rate at follow-up was a limitation. DISCUSSION: Results support the impact of the workshop in improving knowledge, confidence, and attitudes toward collaboration and changing practice and the value of implementing the program province-wide.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".