Can Patients at Risk for Persistent Negative Symptoms Be Identified During Their First Episode of Psychosis?
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
Patients with schizophrenia who show persistent negative symptoms are an important subgroup, but they are difficult to identify early in the course of illness. The objective of this study was to examine characteristics that discriminate between first-episode psychosis (FEP) patients in whom primary negative symptoms did or did not persist after 1 year of treatment. Patients with a DSM-IV diagnosis of FEP whose primary negative symptoms did (N = 36) or did not (N = 35) persist at 1 year were contrasted on their baseline and 1-year characteristics. Results showed that patients with persistent primary negative symptoms (N = 36) had a significantly longer duration of untreated psychosis (p < .005), worse premorbid adjustment during early (p < .001) and late adolescence (p < .01), and a higher level of affective flattening (p < .01) at initial presentation compared with patients with transitory primary negative symptoms. The former group also showed significantly lower remission rates at 1 year (p < .001). Multiple regression analysis confirmed the independent contribution of duration of untreated psychosis, premorbid adjustment, and affective flattening at baseline to the patients' likelihood of developing persistent negative symptoms. It may therefore be possible to distinguish a subgroup of FEP patients whose primary negative symptoms are likely to persist on the basis of characteristics shown at initial presentation for treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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