A Mindfulness-Based Lifestyle Intervention for Dementia Risk Reduction: Protocol for the My Healthy Brain Feasibility Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Lifestyle behavior change and mindfulness have direct and synergistic effects on cognitive functioning and may prevent Alzheimer disease and Alzheimer disease-related dementias (AD/ADRD). We are iteratively developing and testing My Healthy Brain (MHB), the first mindfulness-based lifestyle group program targeting AD/ADRD risk factors in older adults with subjective cognitive decline. Our pilot studies (National Institutes of Health [NIH] stage 1A) have shown that MHB is feasible, acceptable, and associated with improvement in lifestyle behavior and cognitive outcomes. OBJECTIVE: We will compare the feasibility of MHB versus an education control (health enhancement program [HEP]) in 50 older adults (aged ≥60 y) with subjective cognitive decline and AD/ADRD risk factors. In an NIH stage 1B randomized controlled trial (RCT), we will evaluate feasibility benchmarks, improvements in cognitive and lifestyle outcomes, and engagement of hypothesized mechanisms. METHODS: We are recruiting through clinics, flyers, web-based research platforms, and community partnerships. Participants are randomized to MHB or the HEP, both delivered in telehealth groups over 8 weeks. MHB participants learn behavior modification and mindfulness skills to achieve individualized lifestyle goals. HEP participants receive lifestyle education and group support. Assessments are repeated after the intervention and at a 6-month follow-up. Our primary outcomes are feasibility, acceptability, appropriateness, credibility, satisfaction, and fidelity benchmarks. The secondary outcomes are cognitive function and lifestyle (physical activity, sleep, nutrition, alcohol and tobacco use, and mental and social activity) behaviors. Data analyses will include the proportion of MHB and HEP participants who meet each benchmark (primary outcome) and paired samples 2-tailed t tests, Cohen d effect sizes, and the minimal clinically important difference for each measure (secondary outcomes). RESULTS: Recruitment began in January 2024. We received 225 inquiries. Of these 225 individuals, 40 (17.8%) were eligible. Of the 40 eligible participants, 21 (52.5%) were enrolled in 2 group cohorts, 17 (42.5%) were on hold for future group cohorts, and 2 (5%) withdrew before enrollment. All participants have completed before the intervention assessments. All cohort 1 participants (9/21, 43%) have completed either MHB or the HEP (≥6 of 8 sessions) and after the intervention assessments. The intervention for cohort 2 (12/21, 57%) is ongoing. Adherence rates for the Garmin Vivosmart 5 (128/147, 87.1% weeks) and daily surveys (105/122, 86.1% weeks) are high. No enrolled participants have dropped out. Enrollment is projected to be completed by December 2024. CONCLUSIONS: The RCT will inform the development of a larger efficacy RCT (NIH stage 2) of MHB versus the HEP in a more diverse sample of older adults, testing mechanisms of improvements through theoretically driven mediators and moderators. The integration of mindfulness with lifestyle behavior change in MHB has the potential to be an effective and sustainable approach for increasing the uptake of AD/ADRD risk reduction strategies among older adults. TRIAL REGISTRATION: ClinicalTrials.gov NCT05934136; https://www.clinicaltrials.gov/study/NCT05934136. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/64149.
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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 | 0.026 | 0.024 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.009 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.072 | 0.011 |
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".