Components of Adolescent Behavioural Interventions With Eating Disorder Outcomes: Systematic Review With Intervention Mapping
Bibliographic record
Abstract
OBJECTIVE: To understand delivery features and intervention strategies of adolescent weight management interventions which may influence eating disorder risk. METHODS: Systematic searches in four databases and two trial registries to identify randomised controlled trials in adolescents with overweight/obesity measuring eating disorder risk pre- and post-intervention. Delivery features and intervention strategies were coded from published descriptions using a project-specific codebook, validated by trial investigators and narratively synthesised. RESULTS: Of 11 860 records screened, 23 trials, with 54 intervention arms, were included in the analysis. Most interventions focused on weight loss and maintenance (54%) and were informed by a cognitive behavioural framework (43%). Interventions commonly targeted an individual with a support person (70%). Median intervention duration was 26 weeks, with weekly (35%) or staged (e.g., weekly, then monthly) visit (41%) frequency. Interventions had a mean (SD) of 30 (16.1) intervention strategies. Most included healthy eating education (89%), physical activity education (89%) and problem-solving barriers to dietary change (80%). Few included mental health strategies (17%). Interventions included 'dietary prescription' (65%), and 78% promoted 'healthful/helpful eating behaviours'. CONCLUSION: Weight management interventions are complex and vary in delivery approach and strategies used to change behaviors. Characterising interventions is a critical first step to understanding how weight management interventions' influence eating disorder risk.
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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 | 0.029 | 0.110 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".