Sustainability of fall prevention exercise programmes for community-dwelling older adults: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Falls have financial, emotional and physical implications for ageing individuals and the healthcare system. Evidence-based exercise programmes have been one of the most effective ways of preventing falls in community dwellings for older adults. However, more research is needed to understand how to sustain these programmes. This scoping review protocol describes our plan to investigate the factors influencing the sustainability of community-based fall prevention exercise programmes. METHODS AND ANALYSIS: Our scoping review will use the Joanna Briggs Institute methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews framework. The studies will have no restrictions, including publication date, language or geographic location. Key search terms concerning programme sustainability and exercise falls prevention will be conducted in Medline, EMBASE, Cumulative Index to Nursing and Allied Health Literature, Academic Search Premier, APA PsycINFO and SPORTDiscus in consultation with an experienced librarian. Once duplicates have been removed, two independent reviewers will conduct title and abstract screening, full-text screening and data extraction. Data from eligible articles will be collated and charted to summarise data into three categories: (1) study description, including publication date, author(s), study location, paper's aim/purpose, study participants, study design and conclusion; (2) data regarding the type of exercise programme will be used using the 16-point checklist Consensus on Exercise Reporting Template; and (3) data regarding sustainability will be organised using domains from the Program Sustainability Assessment Tool. Our results will be charted through the use of Covidence to identify patterns across the studies. Additionally, narrative synthesis will be employed to articulate the study findings. ETHICS AND DISSEMINATION: As this is a scoping review, we do not require ethics approval. We intend to share our report findings with scientists, healthcare professionals and decision-makers. We will publish our results in reputable scientific journals and present them at relevant conferences.
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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 | 0.120 | 0.096 |
| Meta-epidemiology (narrow) | 0.005 | 0.007 |
| Meta-epidemiology (broad) | 0.009 | 0.013 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.086 | 0.021 |
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".