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Record W4410981458 · doi:10.2196/67250

Technology-Assisted Motor-Cognitive Training Among Older Adults: Rapid Systematic Review of Randomized Controlled Trials

2025· review· en· W4410981458 on OpenAlexvenueno aff
Yaqin Li, Yaqian Liu, Angela Yee Man Leung, Jed Montayre

Bibliographic record

VenueJMIR Serious Games · 2025
Typereview
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialPhysical medicine and rehabilitationCognitionCognitive trainingPhysical therapyPsychologySystematic reviewMedicineGerontologyMEDLINEPsychiatryPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Age-related physiological changes in older adults involve a rapid decline in motor exercise ability; some older adults may also experience difficulties in maintaining focus, memory loss, and a decline in reaction time, which consequently impair their ability to perform dual tasks. Motor-cognitive training (MCT) refers to a blend of motor activity and cognitive training that occurs simultaneously and can assist older adults in enhancing their physical function, cognitive abilities, and dual-task performance. In recent years, the use of technology for delivering MCT has become increasingly popular in research. This has been achieved through various technologies that simplify MCT for older adults. OBJECTIVE: This study aimed to systematically examine the feasibility and effectiveness studies on technology-assisted MCT among older adults. METHODS: This rapid review was conducted following the updated PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 standards, and the Synthesis Without Meta-analysis (SWiM) in systematic reviews reporting guideline. Four databases were searched, including CINAHL, Embase, PubMed, and Scopus, from January 2013 to March 2025. Search strategies were constructed based on three main topics: (1) older adults, (2) MCT, and (3) technology. Inclusion criteria followed the population, intervention, comparator, outcome, and study design framework as follows: older adults (population); technology-assisted MCT (intervention); standard treatment control, active control, partial intervention control, placebo control, and dose-response control (comparator); various measures of physical, cognitive, and dual-task performance (outcome); and randomized controlled trials (RCTs) and pilot RCTs (study design). The Cochrane Risk of Bias Tool was applied for quality appraisal of the included studies. The feasibility of the included studies was assessed using completion rates and attrition rates. Descriptive statistics were used to describe the demographic and clinical characteristics of the groups, while narrative methods were used to categorize and synthesize their effectiveness. RESULTS: In total, 20 studies were included, comprising 16 RCTs and 4 pilot RCTs, most of which were conducted within a 6-week period. Each session typically lasted between 10 and 30 minutes and was held 2 to 3 times per week. Feasibility analysis showed that technology-assisted MCT was generally feasible. While the workload was high, the perceived usability was also high, with a considerable amount of positive feedback and very few reported adverse events. The types of MCT varied in terms of components, duration, and frequency. The majority of studies (18/20, 90%) demonstrated statistically significant improvements in physical, cognitive, and dual-task performance because of technology-assisted MCT. CONCLUSIONS: The feasibility of technology-assisted MCT among older adults was high regardless of the perceived high workload, and most studies showed statistical effectiveness in improving physical, cognitive, and dual-task performance. TRIAL REGISTRATION: Open Science Foundation (OSF) Registries 10.17605/OSF.IO/5SRCQ; https://osf.io/5srcq.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.096
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMeta-epidemiology (broad)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.286
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.096
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0600.012
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.350
Teacher spread0.327 · 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; both teacher heads agree on what is shown here.

Study designSystematic review
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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