Effect of Tai Chi combined with music therapy on the cognitive function in older adult individuals with mild cognitive impairment
Bibliographic record
Abstract
Background With the global aging population increasing, cognitive impairment among the older adult, particularly Mild Cognitive Impairment (MCI), has garnered remarkable attention. MCI, often a precursor to dementia, presents an opportunity for early intervention. This study investigates the effects of Tai Chi combined with music therapy on the cognitive function in older adult individuals with MCI. Methods In this randomized controlled trial, 66 older adult participants with MCI were randomly assigned to one of the following three groups: a Control Group (CG), a Tai Chi Group (TCG), and a Tai Chi Combined with Music Group (TCMG), with 22 participants in each group. Cognitive function was evaluated over a 12-week intervention using the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), and Stroop Color and Word Test. Results Baseline characteristics showed no significant differences among the groups. The TCG and TCMG exhibited significant improvements after 16-week intervention. The participants with TCG group improved in MoCA score (P = 0.005), attention accuracy (P = 0.031), and delayed recall (P = 0.003). The participants with TCMG showed notable enhancements in MoCA (P = 0.000), MMSE (P = 0.001), attention accuracy (P = 0.025), visuospatial and executive functions (P = 0.001), naming (P = 0.014), abstraction (P = 0.020), and delayed recall (P = 0.006). The CG experienced decreased language repetition ability (P = 0.042) and delayed recall (P = 0.030). Conclusion Twelve weeks of Tai Chi combined with music therapy substantially improved cognitive function in older adult individuals with MCI. This combined intervention is more effective than Tai Chi alone, highlighting its potential as a non-pharmacological approach to enhance cognitive health in the aging population.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".