Island Study Linking Aging and Neurodegenerative Disease (ISLAND) Targeting Dementia Risk Reduction: Protocol for a Prospective Web-Based Cohort Study
Bibliographic record
Abstract
BACKGROUND: Up to 40% of incident dementia is considered attributable to behavioral and lifestyle factors. Given the current lack of medical treatments and the projected increase in dementia prevalence, a focus on prevention through risk reduction is needed. OBJECTIVE: We aim to increase dementia risk knowledge and promote changes in dementia risk behaviors at individual and population levels. METHODS: The Island Study Linking Aging and Neurodegenerative Disease (ISLAND) is a long-term prospective, web-based cohort study with nested interventions that will be conducted over a 10-year period. Target participants (n=10,000) reside in Tasmania and are aged 50 years or over. Survey data on knowledge, attitudes, and behaviors related to modifiable dementia risk factors will be collected annually. After each survey wave, participants will be provided with a personalized dementia risk profile containing guidelines for reducing risk across 9 behavioral and lifestyle domains and with opportunities to engage in educational and behavioral interventions targeting risk reduction. Survey data will be modeled longitudinally with intervention engagement indices, cognitive function indices, and blood-based biomarkers, to measure change in risk over time. RESULTS: In the initial 12 months (October 2019 to October 2020), 6410 participants have provided baseline data. The study is ongoing. CONCLUSIONS: Recruitment targets are feasible and efforts are ongoing to achieve a representative sample. Findings will inform future public health dementia risk reduction initiatives by showing whether, when, and how dementia risk can be lowered through educational and behavioral interventions, delivered in an uncontrolled real-world context. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/34688.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".