Assessment of community integration following traumatic brain injury
Bibliographic record
Abstract
PRIMARY OBJECTIVE: Despite the importance of community integration to individuals with traumatic brain injury, it is assessed relatively infrequently. The present paper provides a review of current approaches to the assessment of community integration, including evaluation of psychometric and administrative properties reported in the literature. MAIN OUTCOME AND RESULTS: Based on results from existing systematic reviews, the Community Integration Questionnaire (CIQ), Craig Handicap Assessment and Reporting Technique (CHART), Reintegration to Normal Living Index (RNLI), Sydney Psychosocial Reintegration Scale (SPRS) and Community Integration Measure (CIM) were included in the present study. Descriptive details are provided along with results of psychometric evaluations and discussion of the strengths and limitations associated with each instrument. CONCLUSIONS: The instruments reviewed all provide assessment of three core elements of community integration: relationships with others, independence in one's own living situation and meaningful activities. Within the context of available information, the CIQ and RNLI appear the most reliable and valid, objective and subjective assessments of community reintegration, respectively. Caution is recommended in use of these tools by proxy raters. Unfortunately, with the exception of the CIQ and RNLI, evaluation of measurement characteristics and clinical usefulness is lacking. To promote an informed process of selection of tools, further evaluation is recommended.
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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 | 0.008 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".