Social determinants of health associated with psychological distress stratified by lifetime traumatic brain injury status and sex: Cross-sectional evidence from a population sample of adults in Ontario, Canada
Bibliographic record
Abstract
This study identified the social determinants of health (SDoH) associated with psychological distress in adults with and without a self-reported history of traumatic brain injury (TBI), stratified by sex. Data from the 2014-2017 cycles of the Centre for Addiction and Mental Health Monitor Survey, a representative survey of adults ≥18 years in Ontario, Canada, were analyzed (N = 7,214). The six-item version of the Kessler Psychological Distress Scale was used to determine moderate to severe psychological distress. Self-reported lifetime TBI was defined as a head injury resulting in a loss of consciousness for ≥5 minutes or at least one-night stay in the hospital (16.4%). Among individuals reporting a history of TBI, 30.2% of males and 40.1% of females reported psychological distress (p = 0.0109). Among individuals who did not report a history of TBI, 17.9% of males and 23.5% of females reported psychological distress (p<0.0001). Multivariable logistic regression analyses showed that the SDoH significantly associated with elevated psychological distress were similar between individuals with and without a history of TBI. This included unemployment, student, or 'other' employment status among both males and females; income below the provincial median and age 65+ among males; and rural residence among females. This study highlighted opportunities for targeted population-level interventions, namely accessible and affordable mental health supports for individuals with lower income. Notably, this study presented evidence suggesting adaptations to existing services to accommodate challenges associated with TBI should be explored, given the finite and competing demands for mental health care and resources.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".