Schizophrenia and sensory modulation problems: the relationship between severity, depression and sensory responsiveness
Bibliographic record
Abstract
BACKGROUND: Sensory modulation difficulties have been increasingly recognized in schizophrenia, with neurophysiological evidence indicating altered sensory processing. However, how these abnormalities relate to symptomatology and depressive features in daily life remains underexplored. This study aimed to investigate the associations between sensory responsiveness, symptom severity and depressive symptoms in individuals with schizophrenia. METHODS: A cross-sectional study was conducted with 74 outpatients diagnosed with schizophrenia. Participants completed the Sensory Responsiveness Questionnaire (SRQ), and clinicians rated symptom severity using the Positive and Negative Syndrome Scale (PANSS) and Calgary Depression Scale for Schizophrenia (CDSS). The relationship between schizophrenia symptoms, sensory integration and depressive symptoms was evaluated by correlation analysis. RESULTS: The mean age was 41.4 ± 12.5 years, with a mean duration of illness was 13.8 ± 11.1 years. The pleasure subscale of the SRQ was positively correlated with PANSS positive symptoms (r = 0.299, p < 0.001) and general psychopathology (r = 0.342, p < 0.001). Severity of depression was significantly associated with all PANSS subscales. CONCLUSION: These findings indicate altered sensory responses in individuals with schizophrenia, particularly in relation to positive symptoms and general psychopathology. This supports the clinical relevance of incorporating sensory profiling into assessment and therapeutic planning in schizophrenia care.
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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 | 0.002 |
| 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 | 0.001 |
| 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".