Evaluation of the Scale-up and Implementation of Mind, Exercise, Nutrition…Do It! (MEND) in British Columbia: A Hybrid Trial Type 3 Evaluation
Bibliographic record
Abstract
Abstract Background The Mind, Exercise, Nutrition…Do it! (MEND) childhood obesity intervention was implemented in British Columbia (B.C.), Canada from April 2013 to June 2017. The study objective was: a) to describe and explore program reach, attendance, satisfaction, acceptability, fidelity, and facilitators and challenges to implementation during scale-up and implementation of MEND in B.C. while b) monitoring program effectiveness in improving children’s body mass index (BMI) z-score, waist circumference, dietary and physical activity behaviours, and psychological well-being.Methods This prospective, pragmatic implementation evaluation (Hybrid Type 3 design) recruited families with children aged 7-13 with a BMI ≥ 85th percentile for age and sex. The 10-week MEND B.C. program was delivered in 27 sites, throughout all five B.C. health regions (Northern, Interior, Island, Fraser, and Vancouver Coastal) over four years. A mixed-method approach was used to collect and analyze the data. Evaluation measures included: program reach, attendance, fidelity, acceptability, satisfaction, facilitators and challenges to implementation, and effectiveness (change in children’s BMI z-score, physical activity, screen-time, eating behaviours, self-esteem and emotional distress).Results 136 MEND B.C. programs were delivered over four years. The program reached 987 eligible children. 755 (76.5%) children completed the program. The average program attendance was 81.5%. Parents reported the program content was easy to understand, culturally suitable for their family, respectful of their family's financial situation and provided adequate information to build a healthy lifestyle. Children achieved significant positive changes across all four evaluation years in BMI z-score, nutrition behaviours, physical activity levels, hours of screen time per week and emotional distress (p<0.05). Challenges to continued program implementation included: recruitment, resource requirement for implementation and the need to tailor the program locally to be more flexible and culturally relevant.Conclusions Scaling up efficacious childhood obesity interventions into real-world settings is critical to combat the obesity epidemic. Future family-based childhood obesity management interventions need to explore strategies to enhance program delivery flexibility while optimizing the use of health care resources.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".