Effects of socio‐demographic characteristics, premorbid functioning, and insight on duration of untreated psychosis in first‐episode schizophrenia or schizophreniform disorder in Northern Malawi
Bibliographic record
Abstract
AIM: Long duration of untreated psychosis (DUP) is prevalent and has been shown to be associated with poorer prognosis. Thus, knowledge of its determinants may help to target early interventions to reduce DUP on the needed population. Previous studies seeking to understand determinants of DUP have been inconclusive. Therefore, this study aimed to investigate the effects of socio-demographic characteristics, premorbid functioning, and insight on DUP in patients with first-episode schizophrenia or schizophreniform disorder. METHODS: This cross-sectional study recruited 110 subjects (aged 18-65) during a pilot early intervention service for psychosis in Northern Malawi, between June 2009 and September 2012. Short DUP was defined as ≤6 months, whereas long DUP was defined as >6 months. Unadjusted and adjusted analyses were performed to identify determinants of DUP. RESULTS: Of the 110 subjects, 99 (90%) had schizophrenia. Median DUP was 27.5 months, while mean (SD) DUP was 71.24 (92.32) months. In addition, at least 75% had long DUP, which was associated with lower level of education, poor insight, younger age at onset, and at least one parent deceased. CONCLUSIONS: Long DUP is prevalent in Northern Malawi. Thus, early interventions to reduce DUP are warranted in this population. Although having at least one parent deceased predicted long DUP in this study, this remains speculative because factors, such as timing of parents' death and grief reactions of the patients were not assessed. Therefore, further investigations incorporating these factors are needed to ascertain this result.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".