Protocol for a scoping review on rehabilitation among individuals with traumatic brain injury who intersect with the criminal justice system
Bibliographic record
Abstract
Traumatic brain injury (TBI), a leading cause of both death and disability worldwide, is highly prevalent among individuals who intersect with the criminal justice system. TBI is associated with increased behavioural, psychological, or negative outcomes, such as higher rates of mental health problems, aggression, and violent offending that may lead to negative interactions with the criminal justice system, reincarceration, and recidivism. Although rehabilitation is often recommended and holds promise in addressing TBI-related impairments, there is currently a paucity of reviews on rehabilitation for individuals with TBI who intersect with the criminal justice system (CJS). Concurrently, to the best of our knowledge, there is currently no review that considers rehabilitation among individuals with TBI who intersect with all parts of the CJS (i.e., policing, courts, corrections, and parole). This protocol is for a scoping review to address the above gaps, specifically, to identify the types of rehabilitation interventions and/or programs available to, or used by, individuals with TBI who intersect with all parts of the CJS. Primary research articles that meet pre-defined inclusion criteria will be identified from electronic databases (MEDLINE® ALL, Embase and Embase Classic, Cochrane CENTRAL Register of Clinical Trials, CINAHL, APA PsycINFO, Applied Social Sciences Index and Abstracts, Criminal Justice Abstracts, Nursing and Allied Health, and Dissertation and These Global), reference lists of included articles, and scoping or systematic reviews. Grey literature will also be searched to identify non-peer-reviewed reports. Retrieved articles will be screened by two reviewers and any disagreements will be resolved by a third reviewer. Data will be summarized quantitatively and analyzed using content analytic techniques. Intersecting identities will be charted and considered in the analysis. Stakeholders will be engaged to obtain feedback on preliminary results and the implications of findings. The scoping review will summarize the current state of rehabilitation available to, or used by, individuals with TBI who intersect with all parts of the CJS to (a) inform opportunities to integrate rehabilitation in the criminal justice system for diverse individuals and (b) identify opportunities for future research.
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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 | 0.075 | 0.114 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.017 | 0.016 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.207 | 0.036 |
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".