Perceptions of a family-based lifestyle intervention for children with overweight and obesity: a qualitative study on sustainability, self-regulation, and program optimization
Bibliographic record
Abstract
BACKGROUND: Family-based lifestyle interventions (FBLIs) are an important method for treating childhood weight problems. Despite being recognized as an effective intervention method, the optimal structure of these interventions for children's overweight and obesity has yet to be determined. Our aim was to better understand participants' (a) implementation of behaviour strategies and long-term outcomes, (b) perceptions regarding the optimal structure of FBLIs, and (c) insights into psychological concepts that may explain the success of these programs. METHODS: Purposive sampling was used to recruit participants. We conducted focus groups as well as one-to-one interviews with parents (n = 53) and children (n = 50; aged 7-13, M = 9.4 yr, SD = 3.1) three months following their involvement in a 10-week, multi-component, FBLI involving education and activities relating to healthy nutrition, physical activity, and behavior modification. Using an interpretivist approach, a qualitative study design was employed to examine participant experiences. RESULTS: We identified three higher-order categories: (a) participants' program experiences and perceptions (b) lifestyle changes post-program, and (c) recommendations for optimizing family-based programs. Themes identified within these categories included (a) support and structure & content, (b) diet and physical activity, and (c) in-program recommendations and post-program recommendations. CONCLUSIONS: We identified several challenges that can impair lasting behavior change (e.g., physical activity participation) following involvement in a FBLI. On optimizing these programs, participants emphasized fun, interactive content, interpersonal support, appropriate educational content, and behavior change techniques. Concepts rooted in motivational theory could help address calls for greater theoretical and mechanistic insight in FBLIs. Findings may support research advancement and assist health professionals to more consistently realize the potential of these interventions.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".