Comparing the Sensitivity of Generic Effectiveness Measures With Symptom Improvement in Persons With Schizophrenia
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to compare the sensitivity of four generic effectiveness measures with clinically meaningful symptom improvement in persons with schizophrenia. METHOD: Baseline and 6-month interviews were conducted with 134 subjects diagnosed with schizophrenia or schizoaffective disorder. The design was observational. The four generic effectiveness measures included the Quality of Well-Being scale (QWB), a quality-adjusted index score based on the SF-36 VAS, Veterans SF-36 mental health component summary score (MCS), and the World Health Organization Disablement Assessment Schedule (WHO-DAS). Symptom measures included the Positive and Negative Syndrome Scale (PANSS) and Calgary Depression Scale (CDS). The side effect measure was the Extrapyramidal Symptom Rating Scale (ESRS). Data analysis included correlations between symptom, side effect, and generic effectiveness change scores; and an effect size calculation to detect a clinically significant improvement in the total PANSS. RESULTS: All four effectiveness measures were correlated with changes in side effects. All but the SG-36 VAS were correlated with changes in depression. Only the QWB was correlated with changes in PANSS scores. The QWB required at least three times fewer subjects (n = 61) to detect a clinically significant improvement in total PANSS compared with the other effectiveness measures (n = 201-324). CONCLUSIONS: It is recommended that clinicians and researchers use the QWB to demonstrate the effectiveness and cost-effectiveness of schizophrenia interventions. The QWB allows for direct comparison of the effectiveness and cost-effectiveness of schizophrenia interventions with other mental and physical health interventions and may contribute to a greater recognition of the value of mental health interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".