Situational analysis of prevailing practices in the management of first‐episode psychosis in Chennai, India
Bibliographic record
Abstract
AIM: This paper aims to examine how existing mental health within the city of Chennai, India manages first-episode psychosis, to determine lacunae and barriers in providing effective early intervention and to make appropriate recommendations to improve the care of first-episode psychosis patients. METHODS: Interviews were held with 15 health professionals to capture information on current practices and facilities available for the management of first-episode psychosis. RESULTS: No specialized clinic or services were available for individuals with first-episode psychosis in Chennai, except one. Pharmacotherapy was the main treatment modality with psychological support to patients and families. Most common drugs used were Risperidone, Olanzapine, and Haloperidol in their recommended doses. General practitioners and paediatricians, due to inadequate training in mental health, referred patients with psychosis to mental health professionals. CONCLUSIONS: Equipping the existing mental health services to manage FEP and training all health professionals on psychosis will improve FEP management in Chennai.
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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 | 0.001 | 0.002 |
| 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".