Brain Health PRO: Evaluating a Web‐Based Multidomain Intervention to Improve Dementia Literacy and Self‐Efficacy
Bibliographic record
Abstract
BACKGROUND: Early interventions addressing lifestyle-related risk factors present a compelling strategy for mitigating cognitive decline. In response to this need, the Canadian Consortium on Neurodegeneration in Aging has developed Brain Health Pro, an innovative remote web-based educational intervention aimed at enhancing dementia literacy and supporting older adults in adopting healthier lifestyles. The program focuses on seven key topics that influence brain health: physical activity, diet, mental stimulation, sleep, social and psychological health, vascular health, and vision and hearing. METHOD: This is a twelve-month prospective multi-center longitudinal study testing the effect of Brain Health PRO. The intervention comprises 181 chapters delivered progressively over 10 months. Each chapter is interactive, focusing on a specific topic, and provides relevant information, practical tips, and guidelines. The content is presented based on priorities tailored to individual risk levels and personal preferences. Participants included older adults with no cognitive impairment or those with mild cognitive impairment and at least one dementia risk factor (first-degree family history of dementia, hypertension, hypercholesterolemia, body mass index >30 or physical inactivity). The primary outcome was dementia literacy, assessed using the Alzheimer's Disease Knowledge Scale at 6 and 12 months. Secondary outcomes included self-efficacy, measured by the General Self-Efficacy Scale, and attitudes toward dementia, assessed using the PRISM-PC questionnaire. RESULT: A covariate-adjusted linear mixed model for the intention-to-treat sample (N = 353; mean age = 69.7) revealed a significant positive change in dementia literacy at 6 months (standardized change = 0.246; p = 0.012) and a significant improvement in self-efficacy at 12 months (standardized change = 0.157; p = 0.008). However, no significant change was observed in attitudes toward dementia. CONCLUSION: Brain Health Pro offers a personalized and accessible approach that can increase individuals' knowledge about dementia risk while enhancing their general self-efficacy. These dimensions are critical determinants of health. Improving them may foster long-lasting lifestyle changes to support sustained cognitive health.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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) | 0.007 | 0.001 |
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".