Do We Need to Review Outcome Measures in Schizophrenia to Capture ‘Real-life’ Situation? [P03-197]
Bibliographic record
Abstract
Introduction: Outcome measures in schizophrenia are defining aspects for deciding the status of recovery based upon which people’ scientific body forms opinions. It is also important in dealing with stigma related to schizophrenia. Recently the concept of ‘recovery’ and ’ outcome’ has come under scientific scrutiny. Literature does not show a consistent pattern in outcome. both short term and long-term outcome show variability, which is often, explained by cultural factors. It has been generally considered that devolved countries have poor outcome than developing, non-industrialized countries. This view has also been challenged recently. the paper draws from the conceptual aspects if our outcome measure are capturing ‘real-life’ situation. We conducted two studies in Mumbai, India: 1. Study of stigma & discrimination, which brought out the facts of families’ expectation and disappointments with level of recovery. 2. A 10 years long term study, to determine recovery status of recovered patients. 80% patients and families felt that recovery is inadequate and short of social integration despite continued treatment in stigma study. in outcome study, 60% patients showed good recovery as per CGIS. These patients were reassessed on 13 outcome criteria's of Meltzer. It is observed tat half of the patients who recovered continue to live with symptoms, a quarter with varying suicidality and side effects, most of the patients were not socially integrated, majority have not returned to productivity, employment and education It is concluded that outcome criteria's need a thoughtful revision and a new perspective to capture ground reality.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.007 |
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".