Multidisciplinary assessment measure for individuals with disorders of consciousness
Bibliographic record
Abstract
OBJECTIVE: This study introduces the Comprehensive Assessment Measure for the Minimally Responsive Individual (CAMMRI) and reports on its development, inter-rater reliability, construct validity and clinical value. METHODS: A multidisciplinary team of therapists developed this measure, which comprises 12 sub-tests that examine three main areas: Response to the Environment, Motor Control and Communication and Swallowing. The sub-tests are scored using a 7-point scale; sub-tests can also be administered individually. The measure was administered during a pilot project and then 1 year later to 12 adult clients with severe acquired brain injury at a long-term rehabilitation programme. The age range of the participants was 18-65 years; individuals were 1.5-10 years post-injury. RESULTS: Comparison measures included the Western Neuro Sensory Stimulation Profile (WNSSP), the Coma Recovery Scale-Revised (CRS-R) and the Chedoke McMaster Impairment Inventory (CMII). Inter-rater reliability of each sub-test ranged from 0.87-1.0, with an average of 0.90 in the first year of the assessments. CONCLUSION: Validity data supported the use of the CAMMRI for minimally conscious adults with ABI to measure behavioural changes and plan treatment for this population. Future research should focus on using this measure with other neurological populations.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".