29 THE RISK FACTOR ANALYSIS OF COGNITIVE IMPAIRMENT IN PATIENTS WITH FIRST-EPISODE SCHIZOPHRENIA IN VOCATIONAL COLLEGES AND UNIVERSITIES
Bibliographic record
Abstract
Abstract Background Schizophrenia is a complex and severe mental disorder that typically manifests in late adolescence or early adulthood. Its characteristics include abnormalities in thinking, emotions, and behavior, which have long-term adverse effects on the patient’s cognitive and social functioning. Cognitive impairment is one of the important features of schizophrenia, especially in patients with first onset schizophrenia (FES), where this impairment may be more pronounced and directly affect the treatment effectiveness and quality of life of the disease. Vocational college students, as a special group, may experience cognitive impairment due to their educational environment and psychological pressure. Early intervention in FES patients is key to improving long-term prognosis, therefore, in-depth research on the risk factors of cognitive impairment in this population is of great significance for optimizing intervention measures. Methods The study focuses on FES patients in vocational colleges and systematically analyzes the main risk factors for cognitive impairment, providing scientific basis for intervention strategies in this field. The study was designed as a cross-sectional study, recruiting a total of 150 first-episode schizophrenia patients from vocational colleges. Evaluate the overall cognitive function of patients using the Montreal Cognitive Assessment Scale (MoCA), while selecting neuropsychological domains such as memory, executive function, and attention for in-depth analysis. The socio demographic characteristics, disease history, and psychosocial factors of patients were obtained through standardized questionnaires and structured interviews. Using univariate analysis to screen potential variables associated with cognitive impairment, and further determining significant independent risk factors through multivariate logistic regression analysis. Results The analysis of the situation of each patient is shown in Table 1. According to Table 1, among 150 patients, 92 (61.3%) had significant cognitive impairment (MoCA score<26). Multivariate logistic regression analysis showed that the following risk factors were significantly associated with cognitive impairment. Untreated duration of mental illness exceeding 12 months significantly increases the risk of cognitive impairment, and patients with lower levels of education have poorer cognitive function. Patients with higher scores on the Negative Symptom Assessment Scale have a significantly increased risk of cognitive impairment. Discussion The research results indicate that the incidence of cognitive impairment is higher in first-episode schizophrenia patients in vocational colleges, and the main risk factors include longer duration of untreated mental illness, lower education level, and severe negative symptoms. Early intervention should focus on shortening treatment delays, strengthening educational support, and actively treating negative symptoms to alleviate cognitive impairment in patients. Future research can further validate research conclusions through longitudinal studies and explore personalized intervention strategies targeting risk factors to promote patient functional recovery and social integration.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".