Subjective and Objective Measures of Quality of Life Have Different Predictors for People with Schizophrenia
Bibliographic record
Abstract
This study investigated the relationship between subjective and objective quality of life and assessed predictors in people with schizophrenia. The study population consisted of 99 stabilized outpatients with schizophrenia (DSM-IV) who had been regularly receiving outpatient treatment at the Department of Psychiatry, The Tokushima University Hospital. Subjective and objective quality of life were estimated using the Schizophrenia Quality of Life Scale and the Quality of Life Scale, respectively. Psychiatric symptoms were also measured with the Brief Psychiatric Rating Scale and the Calgary Depression Scale for Schizophrenia. Scores on the Schizophrenia Quality of Life Scale Motivation and Energy scales significantly correlated with the Quality of Life Scale total scores -.40 (p <.001), and with the scores on Interpersonal Relations subscale -.42 (p <.001), Instrumental Role subscale -.28 (p = .005), Intrapsychic Foundations subscale -.39 (p<.001), and Common Objects and Activities subscale -.25 (p =.014). The Schizophrenia Quality of Life Scale Psychosocial scale significantly correlated with only the Quality of Life Scale total score -.20 (p =.05), and there was no significant correlation between the scores on the Schizophrenia Quality of Life Scale Symptoms and Side-effects scales and the Quality of Life Scale. Stepwise regression analyses showed that the Calgary Depression Scale for Schizophrenia score was the most important predictor of each scale of the Schizophrenia Quality of Life Scale, and the Brief Psychiatric Rating Scale Negative Symptoms score was the most important predictor of the Quality of Life Scale total score and each subscale. These results suggest that subjective and objective quality of life have different predictors and should be considered as separate and complementary outcome variables.
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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 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".