TaiChi-MSS protocol: enhancing cognitive and brain function in MCI patients through Tai Chi exercise combined with multisensory stimulation
Bibliographic record
Abstract
Background: The aging population in China is confronted with considerable challenges, with 14.71% of elderly individuals affected by mild cognitive impairment (MCI). The practice of Tai Chi has been demonstrated to enhance cognitive function, while sensory stimulation has been shown to facilitate neural activity. Nevertheless, the combined impact of Tai Chi and sensory stimulation on cognitive, sensory functions, and brain activation in older adults with MCI remains uncertain. This study aims to ascertain whether the integration of Tai Chi with sensory stimulation can facilitate more efficacious interventions for these outcomes. Methods and analysis: The TaiChi-MSS (Tai Chi and Multisensory Stimulation for Cognitive Function) study is a multi-center, randomized controlled trial (RCT) conducted in Suzhou and Shanghai, enrolling 88 participants aged 60 years or older with MCI. Participants will be randomly assigned to one of four groups: Tai Chi, multisensory stimulation, Tai Chi combined with multisensory stimulation or control. The intervention will last 6 months, with follow-up assessments at 3, 6, and 9 months. Primary outcomes include cognitive and sensory assessments, assessed using the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), domain-specific cognitive tests, Pure Tone Audiometry (PTA), and Sniffin' Sticks Odor Identification Test. Secondary outcomes involve brain activation, measured through functional Magnetic Resonance Imaging (fMRI) scans. fMRI will be used to assess brain structure and connectivity changes, focusing on neuroplasticity. Data will be analyzed using mixed-effects models. The False Discovery Rate (FDR) will be the correction method for multiple comparisons to control for the expected proportion of false positives. Ethics and dissemination: This study was approved by the ethics committee of Shanghai University of Sport (No. 102772023RT200). The results of this study will be disseminated in peer-reviewed journals and presented at academic conferences.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.035 | 0.005 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".