Talking About Weight With Families—Helping Health Care Professionals Start the Conversation: A Nonrandomized Controlled Trial
Bibliographic record
Abstract
Health care professionals (HCPs) and trainees feel ill-equipped to discuss weight-related issues with children and their families. A whiteboard video for HCPs and trainees outlining strategies to communicate about weight was developed and evaluated. Seventy HCPs, including 15 trainees, participated in the baseline assessment and 39 repeated measures 4 to 6 months later. HCP self-efficacy for initiating conversations with overweight and underweight patients, measured immediately following the video, significantly improved from pre-video values ( Z = −5.6, P ≤ .001, and Z= −3.3, P = .001, respectively). Although improvements were not sustained 4 to 6 months later (overweight: P = .143, and underweight: P = .846), no significant decline was observed, suggesting retention of the skill. A majority of HCP respondents would recommend the video to a colleague and feel it will affect their practice. Thus, the present study suggests educational videos may be an effective tool for facilitating healthy weight-related conversations between HCPs and their pediatric patients.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".