Why don’t families initiate treatment? A qualitative multicentre study investigating parents’ reasons for declining paediatric weight management
Bibliographic record
Abstract
BACKGROUND: Many families referred to specialized health services for managing paediatric obesity do not initiate treatment; however, reasons for noninitiation are poorly understood. OBJECTIVE: To understand parents' reasons for declining tertiary-level health services for paediatric weight management. METHOD: Interviews were conducted with 18 parents of children (10 to 17 years of age; body mass index ≥85th percentile) who were referred for weight management, but did not initiate treatment at one of three Canadian multidisciplinary weight management clinics. A semi-structured interview guide was used to elicit parents' responses about reasons for noninitiation. Interviews were audio-recorded and transcribed verbatim. Data were managed using NVivo 9 (QSR International, Australia) and analyzed thematically. RESULTS: Most parents (mean age 44.1 years; range 34 to 55 years) were female (n=16 [89%]), obese (n=12 [66%]) and had a university degree (n=13 [71%]). Parents' reasons for not initiating health services were grouped into five themes: no perceived need for paediatric weight management (eg, perceived children did not have a weight or health problem); no perceived need for further actions (eg, perceived children already had a healthy lifestyle); no intention to initiate recommended care (eg, perceived clinical program was not efficacious); participation barriers (eg, children's lack of motivation); and situational factors (eg, weather). CONCLUSION: Physicians should not only discuss the need for and value of specialized care for managing paediatric obesity, but also explore parents' intention to initiate treatment and address reasons for noninitiation that are within their control.
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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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".