Characterizing Traumatic Brain Injury and Its Association with Losing Stable Housing in a Community-based Sample
Bibliographic record
Abstract
Objective: Traumatic brain injury (TBI) is increasingly recognized as a common and impactful health determinant in homeless and precariously housed populations. We sought to describe the history of TBI in a precariously housed sample and evaluate how TBI was associated with the initial loss and lifetime duration of homelessness and precarious housing. Method: We characterized the prevalence, mechanisms, and sex difference of lifetime TBI in a precariously housed sample. We also examined the impact of TBI severity and timing on becoming and staying homeless or precariously housed; 285 precariously housed participants completed the Brain Injury Screening Questionnaire in addition to other health assessments. Results: A history of TBI was reported in 82.1% of the sample, with 64.6% reporting > 1 TBI, and 21.4% reporting a moderate or severe TBI. Assault was the most common mechanism of injury overall, and females reported significantly more traumatic brain injuries due to physical abuse than males (adjusted OR = 1.26, 95% CI = 1.14 to 1.39, P < 0.0001). The first moderate or severe TBI was significantly closer to the first experience of homelessness ( b = 2.79, P = 0.003) and precarious housing ( b = 2.69, P < 0.0001) than was the first mild TBI. In participants who received their first TBI prior to becoming homeless or precariously housed, traumatic brain injuries more proximal to the initial loss of stable housing were associated with a longer lifetime duration of homelessness (RR = 1.04, 95% CI = 1.02 to 1.06, P < 0.0001) and precarious housing (RR = 1.03, 95% CI = 1.01 to 1.04, P < 0.0001). Conclusions: These findings demonstrate the high prevalence of TBI in this vulnerable population, and that aspects of TBI severity and timing are associated with the loss and lifetime duration of stable housing.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".