Status of Patients With First-Episode Psychosis After One Year of Phase-Specific Community-Oriented Treatment
Bibliographic record
Abstract
OBJECTIVE: A phase-specific intervention provided soon after the onset of a first episode of psychosis is likely to engender a more hopeful outlook. This article describes a community-oriented treatment program of phase-specific medical and psychosocial treatments integrated within an intensive case management model for patients with first-episode psychosis in a geographically defined population. One-year status is reported for a consecutive sample of patients with nonaffective mostly schizophrenic first-episode psychosis who were receiving treatment in this program. METHODS: Patients were assessed at baseline and at one year with a modified version of the Interview for Retrospective Assessment of Onset of Schizophrenia, the Structured Clinical Assessment for DSM-IV, the Scale for Assessment of Positive Symptoms, and the Scale for Assessment of Negative Symptoms to ascertain baseline patient characteristics, remission rates, hospital readmission rates, and change in the severity of symptoms. RESULTS: Data at 13 months for 53 patients indicated a complete remission rate of 70 percent, a hospital readmission rate of 20 percent, a highly significant improvement in all dimensions of psychopathology, higher rates of remission among patients who entered treatment within six months of the onset of psychosis (82 percent compared with 60 percent), and a longer median duration of untreated psychosis among patients who did not experience complete remission (10.5 compared with 6.5 months). Nearly half the patients received initial treatment as outpatients without adverse consequences for their subsequent use of hospitalization. CONCLUSIONS: An epidemiologically representative sample of patients experiencing a first episode of psychosis, when treated optimally with low dosages of novel antipsychotics and phase-specific psychological interventions, showed a high rate of clinical recovery and were able to remain in the community most of the time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".