Traumatic Cervical Spinal Cord Injury and Income and Employment Status
Bibliographic record
Abstract
Importance: Spinal cord injury (SCI) causes drastic changes to an individual's physical health that may be associated with the ability to work. Objective: To estimate the association of SCI with individual earnings and employment status using national administrative health databases linked to income tax data. Design, Setting, and Participants: This was a retrospective, national, population-based cohort study of adults who were hospitalized with cervical SCI in Canada between January 2005 and December 2017. All acute care hospitalizations for SCI of adults ages 18 to 64 years were included. A comparison group was constructed by sampling from individuals in the injured cohort. Fiscal information from their preinjury years was used for comparison. The injured cohort was matched with the comparison group based on age, sex, marital status, province of residence, self-employment status, earnings, and employment status in the year prior to injury. Data were analyzed from August 2022 to January 2023. Main outcomes and Measures: The first outcome was the change in individual annual earnings up to 5 years after injury. The change in mean yearly earnings was assessed using a linear mixed-effects differences-in-differences regression. Income values are reported in 2022 Canadian dollars (CAD $1.00 = US $0.73). The second outcome was the change in employment status up to 5 years after injury. A multivariable probit regression model was used to compare proportions of individuals employed among those who had experienced SCI and the paired comparison group of participants. Results: A total of 1630 patients with SCI (mean [SD] age, 47 [13] years; 1304 male [80.0%]) were matched to patients in a preinjury comparison group (resampled from the same 1630 patients in the SCI group). The mean (SD) of preinjury wage earnings was CAD $46 000 ($48 252). The annual decline in individual earnings was CAD $20 275 (95% CI, -$24 455 to -$16 095) in the first year after injury and CAD $20 348 (95% CI, -$24 710 to -$15 985) in the fifth year after injury. At 5 years after injury, 52% of individuals who had an injury were working compared with 79% individuals in the preinjury comparison group. SCI survivors had a decrease in employment of 17.1 percentage points (95% CI, 14.5 to 19.7 percentage points) in the first year after injury and 17.8 percentage points (14.5 to 21.1 percentage points) in the fifth year after injury. Conclusions and Relevance: In this study, SCI was associated with a decline in earnings and employment up to 5 years after injury for adults aged 18 to 64 years in Canada.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".