Bibliographic record
Abstract
Abstract There has been a dramatic increase in recent years in the literature available on community integration among people with acquired brain injuries. At the same time, however, clinicians are calling for information that has utility in the complex environment of community practice. The study was a scoping review to address the question:What is known from the existing literature regarding the best ways to promote community integration in the postacute phase of brain injury recovery?From a preliminary pool of 925 studies identified by electronic searching of 5 databases in a 15-year time window, a final set of 30 was selected for further review, referring to 25 distinct programs. This scoping review has shown that there are 5 types of programs typically offered to survivors of brain injuries to assist with community integration: supported employment, traditional rehabilitation, environmental adaptation, support development and transitional living. These 5 approaches were primarily used to address 2 aspects of community integration: traditional rehabilitation was most commonly used to promote independent living, and supported employment was the most common approach used to promote productive occupation. Themes that emerged from the review were the need for highly individualised programming, in vivo approaches, tailored supports, early intervention and a focus on participation. Methodologically, the study represents an important acknowledgment of the valuable information that is available in the literature in descriptive and small sample 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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.017 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".