A systematic review to determine the effect of strategies to sustain chronic disease prevention interventions in clinical and community settings
Bibliographic record
Abstract
This review assessed the effect of strategies designed to sustain the delivery of evidenced based interventions (EBIs) which target behavioural risk factors linked to leading causes of chronic disease in clinical and community settings. Seven electronic databases were searched for randomised controlled studies published from earliest record to November 2022. Studies were included if they tested a strategy to sustain the delivery of an EBI within clinical or community settings. Results were synthesised using vote counting based on direction of effect, and reported in accordance with non-meta-analytic review standards following the Synthesis Without Meta-analysis (SWiM) guidelines. Three studies met the study inclusion criteria. Two studies were community-based, with one conducted in Australian community sports clubs and the second in afterschool clubs in the United States. The single clinical-based study was conducted in community health care centres in the United States. Across the three studies, 25 strategies were employed and only two strategies were common across all studies. Synthesis using vote counting based on direction of effect indicated that two of three studies favoured the intervention as positively impacting sustainment of EBIs. Few studies have been conducted to assess the effect of strategies designed to support sustainment of EBIs for chronic disease prevention in clinical and community settings. As such, it is difficult to determine the effect of strategies designed to support sustainment. Further research with comprehensive reporting of the selection, use and testing of sustainment strategies is needed to advance understanding of how to sustain EBIs in clinical and community settings.
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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 | 0.047 | 0.190 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.015 |
| Bibliometrics | 0.018 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".