A Comparison Between a Researcher-Rated and a Self-Report Method of Insight Assessment in Chronic Schizophrenia Revisited
Bibliographic record
Abstract
Previous research in schizophrenia has not consistently found concurrent validity between researcher-rated and self-report scales of insight. Differences in the correlations between the two types of scales have been found when order of administration is varied. The current study sought to replicate this earlier study in a sample of 21 patients with chronic schizophrenia who were given the same researcher-rated scale (Scale to Assess Unawareness of Mental Disorder; SUMD) and a different self-report measure (Self-Appraisal of Illness Questionnaire; SAIQ). A counterbalanced research design was employed. Significant correlations (p < 0.05) were found between the SUMD and SAIQ subscales in the SAIQ first group but not in the SUMD first group. The present study replicated earlier findings and provides further support for the importance of order of administration effects when evaluating concurrent validity between different types of insight scales. The reliability of insight scales may be substantially improved if a self-report insight scale is administered prior to a researcher-rated scale.
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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 | 0.027 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".