Cognitive health promotion through a low-intensity high-volume webinar intervention for older adults at risk of future dementia
Bibliographic record
Abstract
Introduction Mild cognitive impairment (MCI) affects 1 in 10 older adults and is a significant risk factor for dementia, a condition impacting over 63 million people worldwide. Despite the growing need for dementia prevention care, resources to empower individuals with MCI/cognitive decline and their families remain limited. The Learning the Ropes Foundations© webinar was developed to provide a free, evidence-based, and accessible low-volume, high-intensity intervention to support brain health. Methods Between January and December 2024, 78 participants with cognitive decline (99% >60 years, 58% women) and 30 family members of those with cognitive decline (97% >50 years, 57% women) completed a survey assessing the webinar’s usability, satisfaction, and ability to motivate behavior change. One-month following webinar completion, 19 participants with cognitive decline completed a follow-up survey assessing their implementation of behavior changes. Surveys included Likert-scale and open-ended questions. Data were analyzed using descriptive statistics. Results Among survey respondents, 82% of participants with cognitive decline and 97% of family agreed they could apply the information to their everyday lives, 81% of participants with cognitive decline and 100% of family agreed they would recommend the webinar, and 90% of all participants reported being motivated to adopt at least one behavior change. Of the one-month follow-up participants, 74% reported implementing at least one behavior change. Discussion The Learning the Ropes Foundations© webinar shows strong potential as a user-friendly resource that supports usability, satisfaction, and motivation for behavior change among individuals with MCI/cognitive decline and their families. Future directions include expanding reach and evaluating long-term lifestyle impacts.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".