Rating scales measuring the severity of psychotic depression
Bibliographic record
Abstract
OBJECTIVE: Unipolar psychotic depression (PD) is a severe and debilitating syndrome, which requires intensive monitoring. The objective of this study was to provide an overview of the rating scales used to assess illness severity in PD. METHOD: Selective review of publications reporting results on non-self-rated, symptom-based rating scales utilized to measure symptom severity in PD. The clinical and psychometric validity of the identified rating scales was reviewed. RESULTS: A total of 14 rating scales meeting the predefined criteria were included in the review. These scales grouped into the following categories: (i) rating scales predominantly covering depressive symptoms, (ii) rating scales predominantly covering psychotic symptoms, (iii) rating scales covering delusions, and (iv) rating scales covering PD. For the vast majority of the scales, the clinical and psychometric validity had not been tested empirically. The only exception from this general tendency was the 11-item Psychotic Depression Assessment Scale (PDAS), which was developed specifically to assess the severity of PD. CONCLUSION: In PD, the PDAS represents the only empirically derived rating scale for the measurement of overall severity of illness. The PDAS should be considered in future studies of PD and in clinical practice.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".