General life satisfaction predicts dementia in community living older adults: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Low life satisfaction predicts adverse outcomes, and may predict dementia. The objectives were: (1) to determine if life satisfaction predicts dementia over a five year period in those with normal cognition at baseline; and (2) to determine if different aspects of life satisfaction differentially predict dementia. METHODS: Secondary analysis of an existing population-based cohort study with initial assessment in 1991 and follow-up five years later. Initially, 1,751 adults age 65+ living in the community were sampled from a representative sampling frame. Of these, 1,024 were alive and had complete data at time 2, of whom 96 were diagnosed with dementia. Life satisfaction was measured using the Terrible-Delightful scale, which measures overall life satisfaction on a 7-point scale, as well as various aspects of life satisfaction (e.g. friendships, finances, etc.) Dementia was diagnosed by clinical examination using DSM-IIIR criteria. Logistic regression models were constructed for the outcome of dementia at time 2, and adjusted for age, gender, education, and comorbidities. RESULTS: Overall life satisfaction predicted dementia five years later, at time 2. The unadjusted Odds Ratio (OR; 95% confidence interval) for dementia at time 2 was 0.72 (0.55, 0.95) per point. The adjusted OR for dementia was 0.70 (0.51, 0.96). No individual item on the life satisfaction scale predicted dementia. However, the competing risk of mortality was very high for some items. CONCLUSION: A global single-item measure of life satisfaction predicts dementia over a five year period in older adults without cognitive impairment.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".