Clinical factors affecting functioning in patients with schizophrenia or schizoaffective disorder
Bibliographic record
Abstract
Introduction Schizophrenia is often associated with impaired functioning abilities due to its disabling symptoms. Objectives to determine the clinical factors that impact the functioning in stabilized patients withschizophrenia and schizoaffective disorder. Methods We conducted a cross-sectional, descriptive and analytical study. It was carried out on an outpatient population with schizophrenia or schizoaffective disorder diagnosis. We used the Functional Assessment Staging Scale (FAST) to measure the functional capacity, the PANSS to assess psychosis symptom severity and the Calgary scale to screen for comorbid depression. Results Seventy-five patients were included with 61 males (81.3%).The mean age was 39.81 ± 9.96 years. The mean sore of the Fast scale was 33 ± 14.95. 90% of our patients scored higher than 11 on the FAST scale revealing a functioning deficiency. 18.7% scored higher than 6 on the Calgary scale revealing a comorbid depression .No significant correlations were found between the FAST score and the age of patient, the gender,the age of onset of psychosis, the duration of untreated psychosis and the number of life-time episodes. Scores of PANSS were significantly higher among patients with a functioning deficiency (p<0.00).No significant correlation was found between the FAST score and the Calgary score. Conclusions Our study suggests that the severity of residual positive and negative symptoms affects negatively the functioning of patients with schizophrenia or schizoaffective disorder. Thus, targeting those symptoms in the treatment may have significant functional benefits. Disclosure No significant relationships.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".