A Scoping Review of Interventions Aimed at Reducing Fear of Falling in Older Adults With Orthopedic Conditions
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Fear of falling (FoF) is a persistent anxiety regarding the risk of falling, which can even impact individuals without a history of falls. Fear of falling has been associated with decreased physical functioning and increased risk of falls. Most interventions have focused on reducing FoF in healthy older adults. This study aimed to review the literature's scope, nature, and content related to FoF interventions in older adults with orthopedic conditions. METHODS: A scoping literature review was conducted. The method steps included identifying the research question, identifying relevant studies, selecting the studies, charting the data, and synthesizing, summarizing, and reporting the results. Cochrane Library, Medline, PsycINFO, Embase, ProQuest, and Google Scholar were searched. The search strategy used a set of key concepts, including "Fear of Falling," "Orthopedic conditions," "Interventions," and "Older adults." RESULTS AND DISCUSSION: Out of the 33 articles that fulfilled the inclusion criteria, 21 were randomized control trials (RCTs), 5 were RCT protocols, 3 were quasi-experimental studies, 2 employed pre-post designs, 1 was a prospective cohort study, and 1 was an experimental study. The review revealed 7 distinct categories of interventions: exercise training, cognitive behavioral therapy, enhanced occupational or physical therapy (OT or PT), motivational interviews, interdisciplinary interventions, education, and mind-body intervention. The Falls Efficacy Scale (FES) was the most frequently used outcome measure for assessing FoF. Other measures were the Fear of Falling Questionnaire (FoFQ), the International Physical Activity Questionnaire (IPAQ), and the Perceived Ability to Manage Fall (PAMF). The studies varied in their reasoning, content, and how they reported findings, posing challenges for healthcare professionals in choosing and applying FoF intervention programs specific to various orthopedic conditions. CONCLUSION: This review highlighted the need for adopting more comprehensive approaches for assessing and addressing FoF in older adults with orthopedic conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.021 | 0.019 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".