Continued attendance for paediatric weight management: A multicentre, qualitative study of parents' reasons and facilitators
Bibliographic record
Abstract
Although prolonged engagement in paediatric weight management (PWM) is associated with positive treatment outcomes, little is currently known about enablers of long-term programme attendance. The purpose of our study was to explore families' reasons for and facilitators of their continued attendance at health services for PWM. Semi-structured, individual interviews were conducted with parents of children (10-17 year old; body mass index ≥85th percentile) who completed the active phase of treatment in one of four Canadian multidisciplinary clinics for PWM. Interview data were recorded digitally, transcribed verbatim and analysed thematically. Parents' (n = 40) reasons for continued clinic attendance included ongoing concerns (eg, parental concern about their child's health), actual and expected benefits from treatment (eg, lifestyle improvements) and perceived quality of care (eg, structured, comprehensive, tailored health services). Several logistical and motivational factors contributed to continued attendance, including flexible work schedules, flexible appointment times, financial resources and children's motivation for treatment. Helping families address treatment barriers and ensuring that weight management services meet families' treatment expectations are promising strategies to enhance retention in PWM to optimize health outcomes.
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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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".