Physical activity is good for older adults—but is programme implementation being overlooked? A systematic review of intervention studies that reported frameworks or measures of implementation
Bibliographic record
Abstract
OBJECTIVE: To examine older adult physical activity (PA) intervention studies that evaluated implementation and/or scale-up. Research question 1: What implementation and/or scale-up indicators (specific, observable and measurable characteristics that show the progress of implementation) were reported? Research question 2: What implementation and/or scale-up frameworks were reported? Research question 3: Did studies evaluate the relationship between implementation or scale-up of the intervention and individual level health/behaviour outcomes? If yes, how? DESIGN: Systematic review. DATA SOURCES: Publications from electronic databases and hand searches (2000 to December 2019). ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Any PA intervention studies with community-dwelling older adult participants (mean age ≥60 years). Required indicators: (a) Must report amount of PA as an outcome, with validated self-report or objective measures, and (b) Must have reported at least one implementation or scale-up framework and/or one implementation or scale-up indicator. RESULTS: 137 studies were included for research question 1, 11 for question 2 and 22 for question 3. 137 studies reported an implementation indicator: 14 unique indicators. None were specified as indicators for scale-up evaluation. 11 studies were guided by an implementation or scale-up framework. 22 studies described a relationship between an implementation indicator and an individual-level health outcome. CONCLUSION: There is need for implementation research that extends beyond analysis at the individual level, includes clearly defined indicators and provides a guiding framework to support PA initiatives in older adults. Such implementation studies should evaluate factors in the broader context (eg,political, environmental) that influence scale-up. PROSPERO REGISTRATION: CRD42018091839.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".