Putting positive weight‐related conversations into practice: The pilot implementation of a Knowledge Translation Casebook
Bibliographic record
Abstract
BACKGROUND: Healthcare professionals (HCPs) play an important role in discussing weight with children and their parents but report barriers such as lack of training and supports. These barriers are especially prevalent within specialized populations such as children with autism spectrum disorder (ASD). To address this, a Knowledge Translation Casebook on positive weight-related conversations was developed by a research team at a Canadian paediatric hospital. The purpose of the current pre-implementation pilot study was to explore initial acceptability and adoption of the Casebook into clinical settings. METHODS: An interactive, multimodal education workshop was created to provide HCPs with knowledge and training on how to have positive weight-related conversations with children and parents. Two workshops were conducted using the same curriculum but delivered either in-person or online. Participants were drawn from a team of clinicians at a teaching hospital whose care focuses on medication management for clients with ASD and clinicians participating in a distance learning programme on best practice care for clients with ASD. Participants completed a demographic questionnaire, workshop evaluation, and a pre-workshop and post-workshop questionnaire. Descriptive statistics were used to summarize demographic, questionnaire, and survey data. Answers to open-ended questions were analysed using content analysis. RESULTS: Participants agreed that the workshop gave them a clear understanding of the Casebook's content and helped them easily navigate the Casebook. Based on raw scores, self-efficacy in having weight-related conversations seemed to increase from pre-to post-workshop, but reported weight-management clinical practice scores did not change over time. However, the small sample precluded in-depth statistical analysis. CONCLUSIONS: The Casebook was acceptable and appeared to increase self-efficacy about having weight-related conversations with children with ASD and parents. More robust implementation strategies are needed to foster the uptake of best practices in weight-related conversations into clinical practice.
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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 | 0.026 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".