Employment and accommodation needs and the effect of COVID-19 on men and women with traumatic brain injury
Bibliographic record
Abstract
BACKGROUND: Traumatic brain injury (TBI) impacts an individual's workforce involvement post-injury. Support services and workplace accommodations that can help with work re-integration post-TBI may differ based on a person's sex and gender. The added impact of COVID-19 remains under-explored. OBJECTIVE: We aimed to investigate the support services and workplace accommodation needs and the impact of COVID-19 on work and mental health for persons with TBI, considering sex and gender. METHODS: A cross-sectional online survey was distributed. Descriptive and regression analyses were applied to uncover sex and gender differences, along with content analysis for open-ended responses. RESULTS: Thirty-two persons with TBI (62% women, 38% men) participated. Physiotherapy, occupational therapy, and counselling services were indicated as the most needed services by women and men. Modified hours/days and modified/different duties were the most needed workplace accommodations. Mental challenges impacting well-being was a highlighted concern for both men and women. Women scored poorer on the daily activity domain of the Quality of Life after Brain Injury - Overall Scale (p = 0.02). Assistance with daily activities was highlighted by women for a successful transition to work, including housekeeping and caregiving. Men were more likely than women to experience change in employment status because of COVID-19 (p = 0.02). Further, a higher percentage of men expressed concern about the inability to pay for living accommodations, losing their job, and not having future job prospects. CONCLUSION: Findings reveal important differences between men and women when transitioning to work post-TBI and emphasize the need for sex and gender considerations.
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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 | 0.002 | 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".