One-year outcomes of traumatic injuries among survivors in Ethiopia: a cross-sectional study on the employment outcomes and functioning state
Bibliographic record
Abstract
Background: Traumatic injury is one of the top public health challenges globally. Injury survivors often experience poor health and functioning and restricted participation in employment. In Ethiopia, there is a paucity of evidence about the long-term consequences of injuries, particularly about their employment outcomes and disability status. This study characterizes injury survivors by their preinjury status, injury characteristics, postinjury employment outcomes and disability status 1 year post injury. Methods: An institution-based cross-sectional study was conducted on injury survivors who received services from a large public hospital in Addis Ababa. Medical records of all emergency room patients who visited the hospital within a 3-month period were reviewed to identify those who were eligible. A structured questionnaire was completed using a telephone interview. Descriptive statistics were used to characterize the outcomes. Results: Of the 254 participants, 78% were men, 48% were young adults (age 25-39 years), 41% were injured by road traffic collision, 52% were admitted to the hospital for up to a week and only 16% received compensation for the injury. Before the injury, 87% were working in manual labor. One-year after the injury, the total return to work (RTW) rate was 59%; 61% of participants experienced some level of disability, 33% had at least one type of chronic illness and 56% reported challenges of physical stressors when attempting to RTW. Among the 150 who returned to work, 46% returned within 12 weeks, 78% to the same employer and most received support from multiple sources, including community-level institutions (88%) and families/friends (67%). Conclusion: Traumatic injury substantially impacted the employment outcomes of survivors and contributed to increased disability in Ethiopia. This study lays a foundation for future research and contributes crucial evidence for advocacy to improve injury prevention and trauma rehabilitation in low and middle-income contexts. Level of evidence: II.
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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) | 0.001 | 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".