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Record W4410424686 · doi:10.2196/67267

Online Group–Based Dual-Task Training to Improve Cognitive Function of Community-Dwelling Older Adults: Randomized Controlled Feasibility Study

2025· article· en· W4410424686 on OpenAlexvenueaboutno aff
Pui Hing Chau, Denise Shuk Ting Cheung, Jojo Yan Yan Kwok, Wai Chi Chan, Doris Sau Fung Yu

Bibliographic record

VenueJMIR Aging · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionRandomized controlled trialCognitive trainingAttendanceVerbal fluency testMedicineThematic analysisPhysical therapyPsychologyPhysical medicine and rehabilitationNeuropsychologyQualitative researchPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Cognitive training for older adults is crucial before cognitive impairment emerges. During periods of social distancing like the COVID-19 pandemic, cognitive stimuli are lacking. Online dual-task training is proposed as a solution to address these needs. OBJECTIVE: We aimed to explore the feasibility, acceptance, and potential effects of online group-based dual-task training as an intervention for enhancing cognitive function among community-dwelling older adults. METHODS: A randomized controlled feasibility study was conducted with 76 participants in Hong Kong, randomly assigned to the intervention and attention control groups in a ratio of 2:1 (n=50, 66% and n=26, 34%, respectively). The intervention group underwent 60-minute online dual-task training sessions twice a week for 12 weeks, incorporating cognitive components (upper limb and finger movement, arithmetic operation, and verbal fluency) and physical components (chair-based exercises) developed through a co-design approach. The attention control group received online health talks. Outcomes related to feasibility and acceptance included class attendance and self-reported satisfaction. Main outcomes related to potential effects included the Memory Inventory in Chinese and the Montreal Cognitive Assessment 5 Minutes (Hong Kong Version) at baseline, 6 weeks (midintervention), 12 weeks (postintervention) and 18 weeks (follow-up). Descriptive statistics and linear mixed effects models were used. Effect size was described with Cohen d. Qualitative feedback was collected from 12 informants and analyzed by thematic analysis. RESULTS: About 72% (36/50) of the participants in the intervention group and 62% (16/26) in the control group attended over 75% of the classes. In total, 44 (88%) participants from the intervention group provided acceptance feedback; 82% (36/44) were satisfied and 84% (37/44) would recommend the training to others. Improvement in the Memory Inventory in Chinese score in the intervention group was observed at midintervention, postintervention, and follow-up, with a medium-to-large effect size (d=0.65, 0.43 and 0.85, respectively). Adjusting for baseline values, the between-group differences in the Montreal Cognitive Assessment 5 Minutes (Hong Kong Version) score attained a small-to-medium effect size at midintervention (d=0.34) and postintervention (d=0.23). Qualitative feedback highlighted the timesaving and convenient aspects of online dual-task training, with participants finding the sessions challenging and enjoyable, and reporting benefits across cognitive, physical, and psychosocial domains. However, a preference for traditional in-person training was noted among the older adults despite the advantages of online training. CONCLUSIONS: Online dual-task training is a feasible intervention accepted by the older adults, with potential benefits in cognitive abilities. Online training may complement in-person sessions. Further investigation in a full-scale randomized controlled trial is warranted to comprehensively explore its effects and address areas for improvement. TRIAL REGISTRATION: ClinicalTrials.gov NCT05573646; https://clinicaltrials.gov/study/NCT05573646.

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)0.007
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.025
GPT teacher head0.360
Teacher spread0.335 · 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 designRandomized trial
Domainnot available
GenreEmpirical

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

Citations3
Published2025
Admission routes2
Has abstractyes

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