ArticleInternational journal of environmental research and public health2022
Effectiveness of a Hybrid Exercise Program on the Physical Abilities of Frail Elderly and Explainable Artificial-Intelligence-Based Clinical Assistance.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 4 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 4 syntheses or guidelines pooled it, 26 citations in OpenAlex.
- Effects of Tai Chi-based combined interventions on muscle function, muscle mass, and physical performance in older adults with sarcopenia, frailty, or risk of functional decline: a systematic review and meta-analysis.Frontiers in public health · 2026Pooled it
- The impact of machine learning on physical activity-related health outcomes: A systematic review and meta-analysis.International nursing review · 2025Pooled it
- Effectiveness of Mind-Body Exercise in Older Adults With Sarcopenia and Frailty: A Systematic Review and Meta-Analysis.Journal of cachexia, sarcopenia and muscle · 2025Pooled it
- Effects of Tai Chi on balance and fall prevention in healthy older adults: a randomized controlled meta-analysis.Frontiers in public health · 2025Pooled it
- Investigating the efficacy of AI-enhanced telerehabilitation in sarcopenic older individuals.European geriatric medicine · 2025Trial
- Quantifying the Enhancement of Sarcopenic Skeletal Muscle Preservation Through a Hybrid Exercise Program: Randomized Controlled Trial.JMIR aging · 2024Trial
- Proposal and validation of a new approach in tele-rehabilitation with 3D human posture estimation: a randomized controlled trial in older individuals with sarcopenia.BMC geriatrics · 2024Trial
- Hybrid Exercise Program for Sarcopenia in Older Adults: The Effectiveness of Explainable Artificial Intelligence-Based Clinical Assistance in Assessing Skeletal Muscle Area.International journal of environmental research and public health · 2022Trial
- Effects of Traditional Chinese Mind-Body Exercise on Physical Function in Older Adults with Sarcopenia and Frailty: A Meta-Analysis of Randomized Controlled Trials.Healthcare (Basel, Switzerland) · 2026Review
- Artificial Intelligence Empowers Physical Therapy for Older Adults: A Perspective.Health science reports · 2026Article
- "Though helpful, still hesitant": a TAM-based qualitative study on older adults' ambivalent acceptance and model extensions in AI fitness coaches.Frontiers in psychology · 2025Article
- A scoping review of methodologies for applying artificial intelligence to physical activity interventions.Journal of sport and health science · 2024Article
- Review
- The Effectiveness of a Hybrid Exercise Program on the Physical Fitness of Frail Elderly.International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Due to the low physical fitness of the frail elderly, current exercise program strategies have a limited impact. Eight-form Tai Chi has a low intensity, but high effectiveness in the elderly. Inspired by it, we designed an exercise program that incorporates eight-form Tai Chi, strength, and endurance exercises, to improve physical fitness and reverse frailty in the elderly. Additionally, for the ease of use in clinical practice, machine learning simulations were used to predict the frailty status after the intervention. Methods: For 24 weeks, 150 frail elderly people completed the experiment, which comprised the eight-form Tai Chi group (TC), the strength and endurance training group (SE), and a comprehensive intervention combining both TC and SE (TCSE). The comparison of the demographic variables used one-way ANOVA for continuous data and the chi-squared test for categorical data. Two-way repeated measures analysis of variance (ANOVA) was performed to determine significant main effects and interaction effects. Eleven machine learning models were used to predict the frailty status of the elderly following the intervention. Results: Two-way repeated measures ANOVA results before the intervention, group effects of ten-meter maximum walking speed (10 m MWS), grip strength (GS), timed up and go test (TUGT), and the six-minute walk test (6 min WT) were not significant. There was a significant interaction effect of group × time in ten-meter maximum walking speed, grip strength, and the six-minute walk test. Post hoc tests showed that after 24 weeks of intervention, subjects in the TCSE group showed the greatest significant improvements in ten-meter maximum walking speed (p < 0.05) and the six-minute walk test (p < 0.05) compared to the TC group and SE group. The improvement in grip strength in the TCSE group (4.29 kg) was slightly less than that in the SE group (5.16 kg). There was neither a significant main effect nor a significant interaction effect for TUGT in subjects. The stacking model outperformed other algorithms. Accuracy and the F1-score were 67.8% and 71.3%, respectively. Conclusion: A hybrid exercise program consisting of eight-form Tai Chi and strength and endurance exercises can more effectively improve physical fitness and reduce frailty among the elderly. It is possible to predict whether an elderly person will reverse frailty following an exercise program based on the stacking model.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.