Predictors and Consequences of Longitudinal Recovery Following Moderate to Severe Traumatic Brain Injury
Bibliographic record
Abstract
This dissertation aims to longitudinally examine long-term psychological (anxiety and depression) and functional outcomes (productivity and community integration) and the earliest predictors of those outcomes, following moderate to severe traumatic brain injury (msTBI). Studies from this dissertation were secondary analyses of prospective data from the Toronto TBI Recovery Study database, which collected information at approximately two, five, 12, and 36+ months post-msTBI, with relevant measures including clinical interviews, neuropsychological assessments, and psychosocial measures. Study 1 investigated longitudinal trajectories of self-reported anxiety and depressive symptom scales, predictors of the trajectories, and associations with one-year return to productivity. Latent growth mixture modelling revealed that four-class models of anxiety and depressive symptoms best fit the data. Most individuals had stable minimal or low levels of anxiety and depressive symptoms over time. However, smaller subsets of individuals had anxiety (15%) and/or depressive symptoms (20%) that worsened over time. Predictors of worsening anxiety and depression included younger age, lower education, and male gender. Those with worsening anxiety or depressive symptoms were less likely to return to productivity by one year post-injury. The relationship between psychological symptoms in the first year post-injury and long-term functional outcomes was further elucidated in study 2. Study 2 examined predictors of one- and three-year return to productivity and community integration outcomes, including a partial replication of previous study findings using a non-overlapping sample from the same parent dataset. Examined predictors included pre-injury factors (e.g., age, education, estimated premorbid intelligence quotient), injury severity measures, and post-injury factors (e.g., neuropsychological performance, current psychosocial factors). Injury severity, memory performance, and psychosocial factors were significant, unique predictors of one- and three-year functional outcomes. Different aspects of functioning (e.g., productivity, home, and social integration) were associated with different predictor variables, highlighting the importance of considering functioning across multiple domains to best understand recovery post-msTBI. Overall, the findings of this dissertation further elucidate long-term psychological and functional sequelae after msTBI and reveal early modifiable (post-injury) variables that impact recovery, which can be harnessed to inform rehabilitation planning to optimize functional recovery and improve quality of life.
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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 | 0.002 | 0.009 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".