Predictors of Social Participation Outcome after Traumatic Brain Injury Differ According to Rehabilitation Pathways
Bibliographic record
Abstract
Social participation (SP) is one of many objectives in the rehabilitation of patients with traumatic brain injury (TBI). Studies on predictors of SP specific to post-acute universally accessible specialized rehabilitation pathways following TBI are scarce. Our objectives were to: 1) characterize SP, as well as a set of pre-injury, injury-related, and post-injury variables in individuals participating in inpatient-outpatient or outpatient rehabilitation pathways within a universally accessible and organized trauma continuum of care; and 2) examine the ability of pre-injury, injury-related, and post-injury variables in predicting SP outcome after TBI according to rehabilitation path. Participants ( N = 372) were adults admitted to an inpatient-outpatient rehabilitation pathway or an outpatient rehabilitation pathway after sustaining a TBI between 2016 and 2020, and for whom Mayo-Portland Adaptability Intentory-4 (MPAI-4) outcomes were prospectively obtained at the start and end of rehabilitation. Additional data was collected from medical files. For both rehabilitation pathways, predicted SP outcome was MPAI-4 Participation score at discharge from outpatient rehabilitation. Multiple regression models investigated the predictive value of each variable for SP outcome, separately for each care pathway. Main findings show that for the inpatient-outpatient sample, three variables (education years, MPAI-4 Ability and Adjustment scores at rehabilitation intake) significantly predicted SP outcome, with the regression model accounting for 49% of the variance. For the outpatient sample, five variables (pre-morbid hypertension and mental health diagnosis, total indirect rehabilitation hours received, MPAI-4 Abilities and Adjustment scores at rehabilitation intake) significantly predicted SP outcome, with the regression model accounting for 47% of the variance. In conclusion, different pre-morbid and post-injury variables are involved in predicting SP, depending on the rehabilitation path followed. The predictive value of those variables could help clinicians identify patients more likely of showing poorer SP at discharge and who may require additional or different interventions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".