Motivational Cognitive Behavioral Therapy for Dementia Prevention: A Pilot Study to Protect the Brain and Memory
Bibliographic record
Abstract
This study sought to explore the efficacy of a manualized group therapy protocol developed for this project combining empirically-supported Cognitive Behavioral Therapy (CBT) and Motivational Interviewing (MI), which we coined as Motivational CBT (MI-CBT), adapted for individuals at a heightened risk of cognitive decline in later adulthood. Specifically, this study investigated changes in cognition, adaptive sleep behavior, diet, exercise, depression, anxiety, and dementia knowledge as well as modifiable lifestyle factors such as Body Mass Index (BMI), hypertension, cholesterol, cigarette smoking, and medical adherence. A group of twenty-five participants (N = 25) were recruited in a large Northeastern city from a university-based family medicine practice, psychoeducation group, social media postings, and research recruitment website. A pretest-posttest experimental design was utilized. Individuals were assessed using measures to acquire baseline and outcomes on cognition (Montreal Cognitive Assessment), sleep (Sleep Disorders Symptom Checlist-25), depression (Patient Health Questionnaire-9), anxiety (Penn State Worry Questionnaire), diet (Lent-Hope Diet Questionnaire), exercise (Step-Up mobile application), and dementia knowledge (Dementia Awareness Questionnaire) as well as a medical adherence questionnaire. Fifteen of the original twenty five participants completed posttest measures immediately following the MI-CBT group treatment and the same fifteen of the original twenty five were assessed at three-month follow-up. Statistical analysis using a one-way repeated measures Analysis of Variance (ANOVA) revealed significant improvements in insomnia sleep pathology, diet adherence, dementia knowledge, and BMI. This study provides preliminary evidence for a brief group intervention for medically at-risk individuals for dementia and offers practical suggestions on how to overcome obstacles to effective treatment.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".