Pathways to care in first-episode psychosis in low-resource settings: Implications for policy and practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Developing countries such as India face a major mental health care gap. Delayed or inadequate care can have a profound impact on treatment outcomes. We compared pathways to care in first episode psychosis (FEP) between North and South India to inform solutions to bridge the treatment gap. METHODS: Cross-sectional observation study of 'untreated' FEP patients (n = 177) visiting a psychiatry department in two sites in India (AIIMS, New Delhi and SCARF, Chennai). We compared duration of untreated psychosis (DUP), first service encounters, illness attributions and socio-demographic factors between patients from North and South India. Correlates of DUP were explored using logistic regression analysis (DUP ≥ 6 months) and generalised linear models (DUP in weeks). RESULTS: Patients in North India had experienced longer DUP than patients in South India (β = 17.68, p < 0.05). The most common first encounter in North India was with a faith healer (45.7%), however, this contact was not significantly associated with longer DUP. Visiting a faith healer was the second most common first contact in South India (23.6%) and was significantly associated with longer DUP (Odds Ratio: 6.84; 95% Confidence Interval: 1.77, 26.49). Being in paid employment was significantly associated with shorter DUP across both sites. CONCLUSIONS: Implementing early intervention strategies in a diverse country like India requires careful attention to local population demographics; one size may not fit all. A collaborative relationship between faith healers and mental health professionals could help with educational initiatives and to provide more accessible care.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it