Validation of the Clinical Global Impression—Corrections Scale (CGI-C) by Equipercentile Linking to the BPRS-E
Bibliographic record
Abstract
Background The Clinical Global Impression – Corrections (CGI-C) is an adaptation of the severity scale of the Clinical Global Impression for use in correctional facilities. Although it has been shown to have good inter-rater reliability, there have been no validation studies of this instrument. Method We analysed data from 726 initial assessments of persons detained in two correctional facilities and compared clinicians ratings for the CGI-C and Brief Psychiatric Rating Scale-Expanded (BPRS-E). We used equipercentile linkage and Spearman correlations to investigate concordance in the total sample, by diagnostic groups, and by gender. Results We found that the CGI-C scores and BPRS-E scores among persons in remand settings were significantly correlated (ρ =0.51, p<0.001) and that correlations were the same for men and women. We found that points of equivalence can be reliably found between the two scales using equipercentile linkage, and that those with psychotic disorders had lower BPRS-E scores than those with mood/anxiety/situational stress for equivalent CGI-C scores. Conclusion Overall, CGI-C ratings correspond well to BPRS-E ratings for both men and women remand prisoners across diagnoses, and the CGI-C appears to be a valid tool for the assessment of severity of symptoms in this setting.
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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 | 0.011 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".