Negative symptoms in first episode non‐affective psychosis
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence of negative symptoms and to examine secondary sources of influence on negative symptoms and the role of specific negative symptoms in delay associated with seeking treatment in first episode non-affective psychosis. METHOD: One hundred and ten patients who met Diagnostic Statistical Manual-IV (DSM-IV) criteria for a first episode of schizophrenia spectrum psychoses were rated for assessment of negative, positive, depressive and extrapyramidal symptoms, the premorbid adjustment scale and assessment of demographic and clinical characteristics including duration of untreated psychosis (DUP). RESULTS: Alogia/flat affect and avolition/anhedonia were strongly influenced by parkinsonian and depressive symptoms, respectively. A substantial proportion (26.8%) of patients showed at a least moderate level of negative symptoms not confounded by depression and Parkinsonism. DUP was related only to avolition/anhedonia while flat affect/alogia was related to male gender, diagnosis of schizophrenia, age of onset and the length of the prodrome. CONCLUSION: Negative symptoms that are independent of the influence of positive symptoms, depression and extra pyramidal symptoms (EPS) are present in a substantial proportion of first episode psychosis patients and delay in seeking treatment is associated mainly with avolition and anhedonia.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".