Exercise Interventions Improve Frailty in Patients Living in Long-Term Care: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVES: The objectives of this study were to examine the impact of exercise training interventions on frailty levels in people who live in long-term care and explore the implementation science outcomes for these interventions. DESIGN: Systematic review and meta-analysis of controlled trials (pre-registered: CRD42024542751). SETTING AND PARTICIPANTS: Adults residing in long-term care settings who are enrolled in exercise training interventions. METHODS: Sources (Scopus, EMBASE, MEDLINE, CINAHL, Academic Search Premier) were searched in May 2024. Studies were included if they conducted an exercise intervention and assessed frailty via a validated frailty assessment tool. The between-group effect size of change in frailty (intervention vs control) was calculated as the standardized mean difference (SMD) using a random effects model. RESULTS: Six studies conducted in nursing homes (n = 1), residential care (n = 1), and long-term care (n = 4) included 191 intervention [age: 81.9 (range: 73.3-86.7) years; n = 115 reported women] and 205 control [age: 81.3 (range: 77.8-86.4) years; n = 106 reported women] participants. Studies included the frailty phenotype (n = five-sixths) or the Study of Osteoporotic Fractures Index (n = one-sixth). The types of training were heterogeneous, but interventions were 3.2 ± 1.1 (range: 2-5) times/week for 44 ± 8.9 (40-60) minutes/session for 23.6 ± 17.7 (6-52) weeks. Most interventions improved frailty compared with controls (n = five-sixths), with the one study observing no change in the intervention, but the control group worsened. A large effect size of the intervention relative to controls was observed (SMD: 1.83; 95% confidence intervals: 0.66-2.99). Implementation outcomes were scarcely reported, but were generally positive when reported (high adherence, high retention rate, low adverse events, strong feasibility). CONCLUSIONS AND IMPLICATIONS: This review and meta-analysis support that exercise training is an effective model of improving frailty levels among older adults in long-term care. Strategies to address the practical aspects of these programs are needed, but this study emphasizes that structured exercise should be a crucial aspect of long-term care.
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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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.035 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".