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Record W4409653641 · doi:10.1519/jpt.0000000000000457

A Systematic Review and Meta-Analysis to Examine the Effectiveness of Exercise Training in People With Osteoporosis or Osteopenia Compared to Other Rehabilitation Interventions on Fear of Falling and the Number of Falls

2025· review· en· W4409653641 on OpenAlexaff
Sahar Johari, Joy C. MacDermid, Laura J. Graham, Christina Ziebart, Erfan Shafiee

Bibliographic record

VenueJournal of Geriatric Physical Therapy · 2025
Typereview
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsParkwood InstituteLawson Health Research InstituteQueen's UniversitySt Joseph's Health CentreWestern University
Fundersnot available
KeywordsOsteopeniaMedicineCochrane LibraryFear of fallingPhysical therapyRandomized controlled trialMeta-analysisOsteoporosisPsychological interventionMEDLINEPoison controlGerontologyInjury preventionPsychiatryBone mineralSurgeryEnvironmental healthInternal medicine

Abstract

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BACKGROUND AND PURPOSE: Fear of falling (FoF) and falls are significant concerns for community-dwelling older adults with osteoporosis or osteopenia, leading to decreased mobility and quality of life. Despite evidence suggesting the benefits of exercise training, its specific effects on the FoF and number of falls (NoF) in this population are not well-documented. This study aims to appraise research evidence on the effects of exercise training, including balance, resistance, and aerobic exercises, on the FoF and NoF in community-dwelling older adults with osteoporosis or osteopenia. METHODS: A comprehensive search was conducted on scientific databases, including EMBASE, MEDLINE, PEDRO, the Cochrane Library, Psych INFO, CINHAL, and Google Scholar, to identify relevant articles. Randomized controlled trials written in English and focusing on exercise training in older adults with osteoporosis or osteopenia were considered for inclusion in this study. Two independent authors conducted screening and reviewed articles. They extracted pertinent information, including authors' names, publication year, sample characteristics, intervention and comparison groups details, the FoF and NoF outcomes, intervention duration and dosage, and follow-up periods. We used the Cochrane Risk of Bias tool (RoB2) for the risk of bias assessment and the GRADE approach to evaluate the quality of evidence for each outcome. We calculated standardized mean difference, Incidence Rate Ratio, and 95% confidence intervals for the quantitative synthesis of the FoF and NoF. RESULTS AND DISCUSSION: We included 14 randomized controlled trials (8 for FoF, 5 for the NoF, and 1 with both outcomes) with 2797 participants. All studies but one (with some risk) had a high risk of bias. The primary sources of bias in the included studies were the measurement of outcomes and selective reporting of results. Meta-analyses demonstrated that exercise training including balance, resistance, and aerobic exercises reduced FoF measured using the Fall Efficacy Scale International (overall effect size: -2.15, 95% CI = -3.16 to -1.15, Z = -4.2, P = .001, and I 2 = 0.97) and NoF (IRR = 0.46, 95% CI: 0.14 to 0.78, Z = 2.79, P = .012, and I 2 = 96%) significantly. Exercise training may effectively reduce the FoF and fall incidence in patients with osteoporosis or osteopenia. However, the considerable variability, high risk of bias, and methodological limitations in most studies underscored the critical need for high-quality studies to inform evidence-based guidelines, optimize intervention protocols, and establish these programs' long-term effects and sustainability. CONCLUSION: Our study highlighted that exercise training including balance, resistance, and aerobic exercises can significantly decrease the FoF and NoF in older adults with osteoporosis or osteopenia. This issue supports the inclusion of tailored exercise prescriptions within fall prevention strategies for this group. Future research should aim to standardize these exercise interventions to enhance their effectiveness.

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 imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.029
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.057
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0290.040
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.068
GPT teacher head0.431
Teacher spread0.363 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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