Cognitive complaints in schizophrenia are associated with clinical symptoms and global functioning but not actual cognitive performance
Bibliographic record
Abstract
Introduction Although it is well established that patients with schizophrenia demonstrate cognitive impairments, little is known about their complaints concerning their cognition. We investigate the association of these complaints with clinical symptoms, global functioning and cognitive performance. Method 93 patients with chronic schizophrenia (mean age = 42,59 years, SD = 9,83; mean illness duration = 18,43 years, SD = 11,84) were recruited from one psychiatric department. Their cognitive complaints (Subjective Scale to Investigate Cognition in Schizophrenia-SSTICS), clinical symptoms (Calgary depression scale-CDS, PANSS, GAF), and neuropsychological performance (7 non-verbal CANTAB tests involving psychomotor speed, attention, memory, and executive function and WAIS-III) were assessed at a time that they were able to cooperate with neuropsychological testing. Correlation analyses were performed between SSTICS scores and measures of symptoms, functioning or cognition, using the SPSS. Results SSTICS total score positively correlated with CDS total score (Spearman's rho = 0.311, p = 0.03). Positive correlations were also found between the SSTICS items and CDS total score. Similarly, SSTICS total score positively correlated with PANSS total score (Pearson r = 0,294, p = 0.04). PANSS negative and general psychopathology scores (r = 0,219, p = 0.035 and r = 0.333, p = 0.01, respectively), but not PANSS positive scores accounted for this relationship. SSTICS total score negatively correlated with GAF (rho = −0.251, p = 0.017). No significant associations were revealed between SSTICS total scores and PANSS insight item, PANSS cognitive score, CANTAB or WAIS scores. Conclusions The complaints of patients with schizophrenia about their cognitive impairments are mostly related to their depressive, negative, general psychopathological symptoms and global functioning, rather than their actual cognitive deficits.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".