Comparison of Exergames Versus Conventional Exercises on the Health Benefits of Older Adults: Systematic Review With Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND: Conventional exercises (CEs) can provide health benefits for older adults, but the long-term exercise adherence rate is low. As an emerging, stimulating, and self-motivating strategy, exergames (EGs) are defined as combinations of exercises and games that users carry out through physical actions. They can promote exercise, but the health effects of EGs versus CEs on the physical function and mental health (cognitive function, depression, and quality of life) of older adults remain controversial. OBJECTIVE: The aim of the study is to compare the health benefits of EGs versus those of CEs for the physical function and mental health of older adults. METHODS: A comprehensive search was conducted from the earliest available date to February 2023 in the following 6 databases: PubMed, Web of Science, Embase, Cochrane, CINAHL, and PsycINFO. All English-language randomized controlled trials comparing the effects of EGs versus those of CEs on the physical function and mental health of older adults, with nearly same physical activity between the 2 interventions, were included. Risk of bias was independently evaluated by 2 authors using the Cochrane risk of bias in randomized trials tool. Two authors independently extracted data. We followed the Cochrane Handbook of Systematic Reviews of Interventions to process and analyze the data for meta-analysis. Standardized mean differences (SMDs) and 95% CIs were used for continuous data, and random models were used for analyses. RESULTS: =4%; SMD=0.09; 95% CI -0.27 to 0.44) effects. CONCLUSIONS: Our findings indicate no significant difference between EGs and CEs in improving the physical function and cognitive function of older adults. Future studies are required to compare the effects of EGs versus those of CEs on cognitive function according to cognitive status, quantify the "dose-effect" relationship between EGs and health benefits, and evaluate the effects of different types and devices of EGs with regard to the health benefits of older adults. TRIAL REGISTRATION: PROSPERO CRD42022322734; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=322734.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.109 | 0.018 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".