Unemployment and Personal Income Loss After Traumatic Brain Injury
Bibliographic record
Abstract
Importance: Employment and personal income loss after traumatic brain injury is a major source of postinjury stress and a barrier to societal reintegration. The magnitude of labor market ramifications following traumatic brain injury remains largely unknown. Objectives: To quantify the 3-year postinjury labor market consequences following traumatic brain injury in Canada. To also estimate the incurred national labor market cost over the study period. Design, Setting, and Participants: This retrospective quasi-experimental, pan-Canadian observational cohort study used linked administrative health and federal taxation data obtained between 2007 and 2017. Mixed-effects difference-in-difference regressions were constructed to estimate the annualized magnitude of the personal income and employment loss during each of the 3 years following injury, respectively, relative to preinjury baseline. Participants included tax-filing adult (19 to 61 years old) traumatic brain injury survivors. Exposure: Traumatic brain injury. Main Outcome Measures: Coprimary outcomes were personal income loss and the proportion of newly unemployed individuals per annum. Secondary objectives were to quantify income and employment loss within mild, moderate, and severe traumatic brain injury subgroups. Results: A total of 18 050 patients with traumatic brain injury between 2007 and 2017 were identified (mean age, 38.0 [SD, 12.4] years; 13 360 male [74.0%]), each of whom was followed up with for 3 consecutive fiscal years. Mean income was CAD $42 600 (US $31 083) in the fiscal year prior to injury and 82% were employed at time of injury. The adjusted mean loss of personal income was CAD $7635 (US $5650) in the first year after injury (Y+1) and CAD $5000 (US $3700) in the third year after injury (Y+3) relative to uninjured controls. In each of the 3 postinjury years, 7.8% individuals were newly unemployed compared with the preinjury baseline. The adjusted average personal income loss for mild, moderate, and severe traumatic brain injury subgroups were CAD $3354 (US $2482), CAD $6750 (US $4995), and CAD $17 375 (US $12 859), respectively, at Y+3; the proportion of unemployed individuals increased by 5.8%, 9.2%, and 20% across the same groups at Y+3 after injury relative to preinjury baseline. The estimated total reduction in personal income aggregated over the 3 postinjury years for the affected participants was CAD $588 million (US $435 million). Conclusions and Relevance: This work represents national cohort data quantifying the labor market implications of traumatic brain injury. These results may be used to inform economic evaluations and social service resource allocation.
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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) | 0.002 | 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".