A study protocol for implementing Canadian Practice Guidelines for Treating Children and Adolescents with Eating Disorders
Bibliographic record
Abstract
BACKGROUND: Eating disorders have one of the highest mortality rates among psychiatric illnesses. Timely intervention is crucial for effective treatment, as eating disorders tend to be chronic and difficult to manage if left untreated. Clinical practice guidelines play a vital role in improving healthcare delivery, aiming to minimize variations in care and bridge the gap between research and practice. However, research indicates an active guideline implementation approach is crucial to effective uptake. METHODS: Mixed methods will be used to inform and evaluate our guideline implementation approach. Semi-structured focus groups will be conducted in each of the eight provinces in Canada. Each focus group will comprise 8-10 key stakeholders, including clinicians, program administrators, and individuals with lived experience or caregivers. Qualitative data will be analyzed using conventional content analysis and the constant comparison technique and the results will be used to inform our implementation strategy. The study will then evaluate the effectiveness of our implementation approach through pre- and post-surveys, comparing changes in awareness, use, and impact of the guidelines in various stakeholder groups. DISCUSSION: Through a multifaceted implementation strategy, involving the co-creation of educational materials, tailored training, and context-specific strategies, this study intends to enhance guideline uptake and promote adherence to evidence-based practices. Our study will also contribute valuable information on the impact of our implementation strategies.
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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 | 0.093 | 0.074 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.088 | 0.014 |
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".