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Record W4410178655 · doi:10.2196/preprints.77014

A randomized controlled trial: Effects of Tai Chi on Cognitive Function among older T2DM with wearable devices in a mHealth model (Preprint)

2025· preprint· en· W4410178655 on OpenAlexaboutno aff
Xi-Shuang Chen, Huizhen Liu, Jingxian Fang, Suijun Wang, Yue-Xia Han, Jian Meng, Yu Han, Hui-Ming Zou, Qing Gu, Xue Feng Hu, Qian-Wen Ma, Fang Huang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintmHealthWearable computerWearable technologyCognitionRandomized controlled trialPsychologyComputer scienceMedicineEmbedded systemPsychological interventionWorld Wide WebPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND Telemedicine is an effective and promising strategy, especially for the initial stages of a home-based therapeutic exercise program. We designed a randomized controlled trial (RCT) to investigate the effects of Tai Chi and walking on cognitive function in older adults with Type 2 Diabetes Mellitus (T2DM) using wearable devices in a mobile healthcare model. OBJECTIVE We designed a randomized controlled trial (RCT) to investigate the effects of Tai Chi and walking on cognitive function in older adults with Type 2 Diabetes Mellitus (T2DM) using wearable devices in a mobile healthcare model. METHODS The study was a randomized controlled trial in which participants were randomized (1:1:1) to receive usual care, fitness walking, or Tai Chi exercise. All indicators were assessed at baseline and 12-week follow-up. The usual care includes traditional diabetes education. Participants in the fitness walking group performed walking exercises on a treadmill under the supervision of a researcher three times a week for 12 weeks. Participants in the Tai Chi group practiced 24-style Simplified Tai Chi through live video streaming under the guidance of professors and professionals. In this 12-week program, participants underwent continuous glucose monitoring (CGM) using Guardian Sensors 3, CGM sensors attached to the upper arm. All participants will carry bracelets to record their heart rate, sleep parameters, and steps. The primary outcome was the Montreal Cognitive Assessment (MoCA) at 12 weeks. Secondary outcomes included other cognitive subdomain tests, and blood metabolic indices. RESULTS After 12 weeks of intervention, the Tai Chi exercise group showed a significant improvement in MoCA scores from baseline (23.83 [17.79, 25.66] vs. 21.42 [17.11, 24.74], P=0.027). The fitness walking exercise group showed an improvement in MoCA scores (22.94 [18.05, 23.98] vs. 21.58 [17.35, 24.12], P=0.083), but did not reach statistical significance. CONCLUSIONS In summary, this study showed that web-based exercise therapy for patients may help improve exercise therapy's effectiveness in cognitive function among older T2DM. Tai Chi has significant advantages in improving cognitive function and sleep quality, while fitness walking, although also beneficial, is relatively weak in these areas. CLINICALTRIAL All participants signed an informed consent form, and the Institutional Review Boards of all participating institutions approved the study (2024-013-01). The study was registered on the Chinese Clinical Trial Register, ChiCTR2200057863(19/03/2022).

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)0.012
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 score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0140.001

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 head0.011
GPT teacher head0.296
Teacher spread0.285 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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