Falls Prevention Among Older Adults in Rural Communities: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Falls are a critical source of injury and hospitalization and leave many older adults unable to return home, especially in rural communities with limited access to health care and support services. Studying falls prevention among rural older adults is essential because they may face an increased risk of falls due to unique environmental factors, geography, and outdoor activities. Moreover, rural older adults may have limited awareness regarding fall-related risks and preventive activities. OBJECTIVE: The objective of this scoping review is to explore the literature about falls prevention from the perspectives of older adults living within a rural context. This review protocol aims to identify the search parameters and methodology that will be used in the scoping review. METHODS: This scoping review will be guided by Arksey and O'Malley's 5-step methodological framework. We will search for relevant peer-reviewed English language literature from 5 databases: CINAHL, PubMed, Academic Search Complete, PsycINFO, and Scopus. The reference lists of relevant studies will be hand-searched to identify papers. Inclusion criteria (English language, peer-reviewed journal papers, original research, focusing on rural perspectives to support falls prevention, and published from January 2013 to December 31, 2023) will be used to determine the eligibility of the journal papers. The data from the included papers will be extracted using a standardized table and analyzed using thematic analysis. RESULTS: This protocol was registered with the Open Science Framework on June 26, 2024. The scoping review's data collection and analysis were conducted from September to December 2024. Results from the review will be distributed through publication in a peer-reviewed journal paper, conference presentation, webinar, and a rural community workshop. CONCLUSIONS: Understanding rural older adults' perspectives of falls prevention is critical to supporting independence and healthy aging in rural communities. This review's findings about falls prevention may have important implications for rural community leaders, policy makers, and health practitioners working to support falls prevention in rural communities. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/63716.
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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 | 0.116 | 0.106 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.012 | 0.015 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.085 | 0.017 |
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".