Effectiveness of exercise-referral schemes to promote physical activity in adults: systematic review
Bibliographic record
Abstract
BACKGROUND: Despite the health benefits of physical activity, most adults do not take the recommended amount of exercise. AIM: To assess whether exercise-referral schemes are effective in improving exercise participation in sedentary adults. DESIGN OF STUDY: Systematic review. METHOD: Studies were identified by searching MEDLINE, CINAHL, EMBASE, AMED, PsycINFO, SPORTDiscus, The Cochrane Library and SIGLE until March 2007. Randomised controlled trials (RCTs), observational studies, process evaluations and qualitative studies of exercise-referral schemes, defined as referral by a primary care clinician to a programme that encouraged physical activity or exercise were included. RCT results were combined in a meta-analysis where there was sufficient homogeneity. RESULTS: Eighteen studies were included in the review. These comprised six RCTs, one non-randomised controlled study, four observational studies, six process evaluations and one qualitative study. In addition, two of the RCTs and two of the process evaluations incorporated a qualitative component. Results from five RCTs were combined in a meta-analysis. There was a statistically significant increase in the numbers of participants doing moderate exercise with a combined relative risk of 1.20 (95% confidence intervals = 1.06 to 1.35). This means that 17 sedentary adults would need to be referred for one to become moderately active. This small effect may be at least partly due to poor rates of uptake and adherence to the exercise schemes. CONCLUSION: Exercise-referral schemes have a small effect on increasing physical activity in sedentary people. The key challenge, if future exercise-referral schemes are to be commissioned by the NHS, is to increase uptake and improve adherence by addressing the barriers described in these studies.
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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 | 0.013 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".