A survey of stakeholders' perceived importance of health indicators and subgroup analyses to inform the Canadian clinical practice guideline for managing paediatric obesity
Bibliographic record
Abstract
OBJECTIVE: To assess stakeholder ratings of health indicators and subgroup analyses in systematic reviews used to update the Canadian Clinical Practice Guideline for Managing Paediatric Obesity. METHODS: Stakeholders (caregivers of children with obesity and Clinical Practice Guideline Steering Committee members) completed an online survey between April 2020 and March 2021. Participants rated importance of health indicators and subgroup analyses for behavioural and psychological, pharmacotherapeutic, and surgical interventions for managing paediatric obesity from not important to critically important using Grading, Recommendations, Assessment, Development and Evaluation criteria. RESULTS: No health indicators or subgroup analyses were rated not important by the 30 caregivers and 17 Steering Committee members. Across intervention types, stakeholders rated anxiety, depression, health-related quality of life, serious adverse events, plus age and weight status subgroups as critically important. CONCLUSION: Stakeholder ratings will inform data reporting and interpretation to update Canada's Clinical Practice Guideline for Managing Paediatric Obesity.
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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 | 0.273 | 0.488 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| 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".