Comparing the Overall Health, Stress, and Characteristics of Canadians with Early-Onset and Late-Onset Dementia
Bibliographic record
Abstract
OBJECTIVE: Dementia is increasingly recognized as a public health priority, but little is known about persons with early-onset dementia (EOD). The objectives of this article are (a) to compare the socio-demographic and health characteristics of people with EOD and late-onset dementia (LOD) and (b) to examine the relationships between EOD and overall health and life stress. METHOD: Data were from the Survey on Living With Neurological Conditions in Canada (SLNCC). Logistic regression models were used to identify the characteristics associated with EOD and LOD, and to assess the impact of EOD on overall health and life stress. RESULTS: Compared with LOD, individuals with EOD were more likely to be male, to have a mood disorder, and to have a longer illness duration. EOD was associated with high life stress, but not with negative overall health. DISCUSSION: This study identified attributes associated with EOD that have important implications for service planning.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".