Validation of Population Characteristics and Dosage Prescriptions for Cognitive Function Intervention Benefits of Different Doses of Tai Chi in Elderly Patients With Mild Cognitive Impairment: A Real-World Cross-Sectional Study

Real-World External Validation Study on Beneficiary Population Characteristics and Individualized Dose Prescription for Cognitive Improvement of Tai Chi Intervention in Elderly Patients With Mild Cognitive Impairment

This is a companion real-world external validation study of two pre-registered parent randomized controlled trials (RCTs, protocol IDs: FujianUTCM-1 and FujianUTCM-2). We aim to validate the generalizability and clinical applicability of a pre-developed machine learning prediction model (for Tai Chi intervention cognitive benefit population characteristics and individualized dose prescription) in a real-world community-dwelling population.

Study Overview

• Status: Not yet recruiting
• Conditions: Mild Cognitive Impairment (MCI)
• Intervention / Treatment: Behavioral: 24-form Simplified Tai Chi (Observational Behavioral Exposure)

Detailed Description

Mild Cognitive Impairment (MCI) represents a critical early intervention window for delaying the onset and progression of dementia, and early non-pharmacological intervention has become an international consensus in this field. Our research team has completed two multicenter interventional randomized controlled trials (RCTs) pre-registered on ClinicalTrials.gov and their companion multicenter RCTs. Both studies adopted the standardized 24-form simplified Tai Chi as the intervention, with highly unified intervention procedures, movement specifications, and dose settings. These trials confirmed the dose-response relationship of Tai Chi intervention on cognitive improvement in older adults with MCI due to Alzheimer's disease, and preliminarily clarified the intervention effects of different Tai Chi dose combinations on patients' global cognition and cognitive subdomains.

On this basis, we will further identify the core characteristics of the population with significant cognitive benefits from Tai Chi intervention through machine learning algorithms. Based on data mining from 890 RCT participants, we will construct a dual-function machine learning prediction model for "beneficiary population identification + individualized Tai Chi dose prescription formulation". However, the above conclusions are all derived from standardized RCT settings, and their generalizability and clinical applicability in real-world community settings have not yet been validated.

As a sequential validation study, this research will conduct a cross-sectional survey by enrolling 150 older adults with long-term regular Tai Chi practice from communities in Fuzhou, China, to complete two-dimensional external validation of the previous RCT findings: to verify the consistency and feasibility between the beneficiary population characteristics and corresponding Tai Chi dose prescriptions mined from the parent RCTs, and the real Tai Chi dose combinations of the beneficiary population in the real world.

This study will form a closed loop from "causal evidence mining in RCTs" to "clinical application validation in real-world settings", and provide direct, high-level scientific evidence for the clinical promotion and individualized application of Tai Chi intervention in older adults with MCI.

• Study Type: Observational
• Enrollment (Estimated): 150

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

This cross-sectional real-world external validation study will enroll 150 community-dwelling older adults aged 60 years and above, who are diagnosed with Mild Cognitive Impairment (MCI) and have regular practice of standardized 24-form simplified Tai Chi for at least 6 months (consistent with the form used in the parent RCTs). Eligible participants will be recruited from communities in Fuzhou, China, to validate the generalizability and clinical applicability of a pre-developed machine learning prediction model for Tai Chi cognitive benefit population identification.

Description

Inclusion Criteria:

• 1. Presence of mild cognitive impairment, not demented; 2. Age ≥ 60 years old; 3.Regular practice of standardized 24-form simplified Tai Chi for at least 6 months (consistent with the form used in the parent randomized controlled trials [RCTs]) ; 4.Informed consent and voluntary participation.

Exclusion Criteria:

1. Geriatric Depression Scale score ≥ 9 points
2. Cognitive impairment caused by other reasons, taking drugs, poisoning, etc;
3. Suffer from severe musculoskeletal system diseases and other contraindications to exercise and are not suitable for Tai Chi training, such as those who suffer from stroke, Parkinson's disease, and have a history of lower limb arthritis, hip and knee joint replacement, etc;
4. Patients with severe heart, liver, kidney failure, malignant tumors, and other major diseases;
5. Individuals with visual/auditory impairments, writing/reading impairments, illiteracy, etc. that affect training and evaluation;
6. Individuals with uncontrolled hypertension (systolic blood pressure greater than 160mmHg or diastolic blood pressure greater than 100mmHg after medication);
7. Participating in other experiments that influence this study. -

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

Cross-Sectional External Validation Cohort; This is the only study population for this cross-sectional observational real-world external validation study. The cohort consists of community-dwelling older adults aged 60 years and above, who are diagnosed with Mild Cognitive Impairment (MCI) and have long-term regular Tai Chi practice. Participants will be recruited from communities in Fuzhou, China, with a planned sample size of 150 participants. This study will conduct a single time-point cross-sectional survey on this population, with no prospective follow-up. The sole objective is to externally validate the generalizability and clinical applicability of a pre-developed machine learning prediction model (for identifying MCI populations who gain significant cognitive benefits from Tai Chi intervention and formulating individualized Tai Chi dose prescriptions) in a real-world community setting.

Behavioral: 24-form Simplified Tai Chi (Observational Behavioral Exposure); This is the core observational exposure factor of this cross-sectional real-world external validation study, NOT an intervention actively assigned, implemented or manipulated by the investigator. This study only observes and records the existing long-term regular Tai Chi practice behavior (including dose, frequency and duration) of enrolled older adults with Mild Cognitive Impairment (MCI) during a single time-point cross-sectional survey, for the sole purpose of externally validating the generalizability of a pre-developed machine learning prediction model for Tai Chi cognitive benefit population identification and individualized dose prescription. No active behavioral intervention will be administered to any participant in this study.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Montreal Cognitive Assessment	Global cognition	Single cross-sectional assessment at the time of study enrollment (baseline visit)

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Wechsler Memory Scale	Memory function	Single cross-sectional assessment at the time of study enrollment (baseline visit)
Digital Symbol test	Attention	Single cross-sectional assessment at the time of study enrollment (baseline visit)
Trial Making Test part B	Executive function	Single cross-sectional assessment at the time of study enrollment (baseline visit)
Stroop color word test	Processing speed	Single cross-sectional assessment at the time of study enrollment (baseline visit)
Boston naming test	Verbal fluency	Single cross-sectional assessment at the time of study enrollment (baseline visit)
Rey-Osterrieth complex graphics test		Single cross-sectional assessment at the time of study enrollment (baseline visit)
Rey Auditory Verbal Learning Test	Episodic memory	Single cross-sectional assessment at the time of study enrollment (baseline visit)

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Blood glucose metabolism index	fasting blood glucose	Single cross-sectional assessment at the time of study enrollment (baseline visit)
Blood lipid metabolism index	total cholesterol (TC), total triglyceride (TG), low density lipoprotein (LDL), high density lipoprotein (HDL)	Single cross-sectional assessment at the time of study enrollment (baseline visit)
Resting-State Functional Magnetic Resonance Imaging: Default Mode Network Functional Connectivity Structural Magnetic Resonance Imaging: Hippocampal Volume	Resting-State Functional Magnetic Resonance Imaging (rs-fMRI) Measurement of Default Mode Network Functional Connectivity Strength Resting-state fMRI (rs-fMRI) data will be acquired using a 3.0T scanner to evaluate default mode network (DMN) functional connectivity strength, a key correlate of cognitive function. All scanning parameters, preprocessing and analysis methods are identical to our parent randomized controlled trials (FujianUTCM-1/2). Data processing uses SPM12 and CONN toolbox. 3.0T Three-Dimensional T1-Weighted Structural MRI (sMRI) Measurement of Bilateral Hippocampal Total Volume 3D T1-weighted structural MRI (sMRI) data will be acquired using a 3.0T scanner to quantify bilateral hippocampal total volume. All scanning parameters, preprocessing and volumetric analysis methods are consistent with our parent randomized controlled trials (FujianUTCM-1/2). Automated segmentation uses FreeSurfer 7.4.1 with manual visual correction.	Single cross-sectional assessment at the time of study enrollment (baseline visit)
Core Peripheral Blood Biomarkers for Mild Cognitive Impairment (MCI)	Amyloid-beta(Aβ)、phosphorylated tau(p-tau)、Neurofilament light chain(NfL)、Glial fibrillary acidic protein(GFAP)	Single cross-sectional assessment at the time of study enrollment (baseline visit)
Pittsburgh Sleep Quality Index, PSQI	Sleep Quality	Single cross-sectional assessment at the time of study enrollment (baseline visit)
12-Item Short Form Health Survey	General health	Single cross-sectional assessment at the time of study enrollment (baseline visit)

Collaborators and Investigators

• Sponsor: Lidian Chen
• Collaborators: Peking University Third Hospital

Study record dates

Study Major Dates

• Study Start (Estimated): May 15, 2026
• Primary Completion (Estimated): March 31, 2027
• Study Completion (Estimated): March 31, 2027

Study Registration Dates

• First Submitted: March 27, 2026
• First Submitted That Met QC Criteria: May 24, 2026
• First Posted (Actual): May 27, 2026

Study Record Updates

• Last Update Posted (Actual): May 27, 2026
• Last Update Submitted That Met QC Criteria: May 24, 2026
• Last Verified: April 1, 2026

More Information

Terms related to this study

• Keywords: machine learning; mild cognitive impairment; External Validation; Real-World Study; taiji
• Additional Relevant MeSH Terms: Mental Disorders; Neurocognitive Disorders; Cognition Disorders; Cognitive Dysfunction
• Other Study ID Numbers: FujianUTCM-2026-001

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No