The Dimensions of Auditory Hallucination in Schizophrenia: Association with Depressive Symptoms and Quality of Life
Bibliographic record
Abstract
Introduction: Auditory hallucination (AH) is often unexplored in depth in clinical practice. This study sought to ascertain the relationship between AH, depressive symptoms and quality of life (QOL) and its association with socio-demographic and clinical variables. Methods: This was a cross sectional study done in a psychiatry unit involving 60 schizophrenic patients between 18 to 60 years old. Psychotic Symptom Rating Scale – Auditory Hallucination subscale (PSYRATS-AH), Calgary Depression Scale for Schizophrenia (CDSS) and World Health Organization Quality of Life-Brief scale (WHOQOL-BREF) were used as instruments. Results: Alcohol intake was found to be significantly associated with the severity of AH. A significant moderate positive correlation was found between AH total score and CDSS (r=0.53, p<0.001) and moderately high correlation between emotional characteristics subscale with CDSS (r=0.651, p<0.005). The PSYRATS-AH dimensions; amount of distress (r=0.721, p<0.001) and intensity of distress (r=0.757, p<0.001) showed significant high correlation with CDSS. As for QOL, frequency of AH (r=-0.419, p<0.01) and CDSS (r=0.435, p<0.01) showed significant moderate negative correlation, while duration, loudness, amount and intensity of distress, disruption to life and controllability of voices had significant fair correlation with QOL. Multiple regression analysis revealed that the frequency of AH (p=0.047), controllability of AH (p=0.027) and depressive symptoms (p=0.001) significantly predict QOL. Conclusion: Our results demonstrated that each dimension of AH had different contributions towards depressive symptoms and the QOL in patients with schizophrenia. Therefore, appropriate treatment focusing on the specific dimension of AH not only may reduce depressive symptoms, but may also improve QOL of these patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".