A Factor Analysis of the Strauss and Carpenter Revised Outcome Criteria Scale: A Validation of the French Translation
Bibliographic record
Abstract
This article seeks to validate the French translation of the Strauss and Carpenter revised outcome criteria scale (SCOCS-R) through the study of its interrater reliability, its convergent validity, and its factor structure. Using a sample of 113 DSM-IV schizophrenic subjects, we assessed the interrater reliability of the SCOCS-R and its convergent validity with an already validated scale (Social and Occupational Functioning Assessment Scale). The factor structure of the SCOCS-R was assessed using a principal components analysis. Interrater reliability was excellent (ri > or = 0.88 for each of the individual items), and the convergent validity with the Social and Occupational Functioning Assessment Scale proved to be highly satisfactory (r = 0.89; p < .0001). Factor analyses yielded two factors corresponding to social functioning and professional functioning. These factors accounted for 78% of the variance of outcome. These results demonstrate the reliability and the validity of the French translation of the SCOCS-R. Moreover, the two dimensions yielded by our factor analysis add to the evidence of the multidimensional structure of outcome. This article supports the relevance of the SCOCS-R to assess the dimensions of outcome in schizophrenic subjects.
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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 | 0.013 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".