The Association between Depression, Suicidal Ideation, and Stroke in a Population-Based Sample
Bibliographic record
Abstract
BACKGROUND: Stroke survivors often experience poststroke depression and suicidal ideation. PURPOSE: to determine the frequency and odds ratio of depression and suicidal ideation among stroke survivors, in comparison to those without stroke, and to identify demographic factors associated with elevated odds of depression and suicidal ideation among stroke survivors. METHODS: Secondary analysis of the Canadian Community Health Survey, a population-based sample. Logistic regressions of depression and suicidal ideation were conducted. RESULTS: Among those with stroke, 7·4% were depressed, in comparison to 5·2% of those without stroke (P = 0·01). The cumulative lifetime frequency of suicidal ideation was 15·2% among stroke survivors in comparison to 9·4% of those without stroke (P < 0·001). After adjusting for sociodemographic factors, stroke survivors had twice the odds of depression and suicidal ideation in comparison to those without stroke (odds ratio = 2·21; 95% confidence interval = 1·61, 3·04 and odds ratio = 2·07; 95% confidence interval = 1·68, 2·55, respectively). When functional limitations and activities of daily living limitations were added to the analyses, there was a substantial decrease in the associations between stroke and depression (odds ratio = 1·29; confidence interval = 0·93, 1·80) and between stroke and suicidal ideation (odds ratio = 1·37; 95% confidence interval = 1·10, 1·69). Caucasians and younger individuals had higher odds of poststroke depression and suicidal ideation. Stroke survivors with functional limitations had much higher odds of suicidal ideation than those without such limitations. CONCLUSIONS: Regular screening for depression and suicidal ideation is important for stroke survivors, particularly those with substantial physical limitations.
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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 | 0.002 |
| 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".