Health care providers’ weight management practices for adolescent obesity and alignment with clinical practice guidelines: a multi-centre, qualitative study
Bibliographic record
Abstract
BACKGROUND: Clinical practice guidelines (CPGs) include evidence-based recommendations for managing obesity in adolescents. However, information on how health care providers (HCPs) implement these recommendations in day-to-day practice is limited. Our objectives were to explore how HCPs deliver weight management health services to adolescents with obesity and describe the extent to which their reported practices align with recent CPGs for managing pediatric obesity. METHODS: From July 2017 to January 2018, we conducted a qualitative study that used purposeful sampling to recruit HCPs with experience in adolescent weight management from multidisciplinary, pediatric weight management clinics in Edmonton and Ottawa, Canada. Data were collected using audio-recorded focus groups (4-6 participants/group; 60-90 min in length). We applied inductive, semantic thematic analysis and the congruent methodological approach to analyze our data, which included transcripts, field notes, and memos. Qualitative data were compared to recent CPGs for pediatric obesity that were published by the Endocrine Society in 2017. Of the 12 obesity 'treatment-related' recommendations, four were directly relevant to the current study. RESULTS: Data were collected through three focus groups with 16 HCPs (n = 10 Edmonton; n = 6 Ottawa; 94% female; 100% Caucasian), including dietitians, exercise specialists, nurses, pediatricians, psychologists, and social workers. We identified three main themes that we later compared with CPG recommendations, including: (i) discuss realistic expectations regarding weight management (e.g., shift focus from weight to health; explore family cohesiveness; foster delayed vs instant gratification), (ii) personalize weight management (e.g., address personal barriers to change; consider developmental readiness), and (iii) exhibit non-biased attitudes and practices (e.g., de-emphasize individual causes of obesity; avoid making assumptions about lifestyle behaviors based on weight). Based on these qualitative findings, HCPs applied all four CPG recommendations in their practices. CONCLUSIONS: HCPs provided practical insights into what and how they delivered weight management for adolescents, which included operationalizing relevant CPG recommendations in their practices.
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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 | 0.022 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 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".