Effects of depression and cognitive impairment on quality of life in older adults with schizophrenia spectrum disorder: Results from a multicenter study
Bibliographic record
Abstract
BACKGROUND: Little is known about the respective effects of depression and cognitive impairment on quality of life among older adults with schizophrenia spectrum disorder. METHODS: We used data from the Cohort of individuals with Schizophrenia Aged 55-years or more (CSA) study, a large multicenter sample of older adults with schizophrenia or schizoaffective disorder (N = 353). Quality of life (QoL), depression and cognitive impairment were assessed using the Quality of Life Scale (QLS), the Center of Epidemiologic Studies Depression scale and the Mini-Mental State Examination, respectively. We used structural equation modeling to examine the shared and specific effects of depression and cognitive impairment on QoL, while adjusting for sociodemographic characteristics, general medical conditions, psychotropic medications and the duration of the disorder. RESULTS: Depression and cognitive impairment were positively associated (r = 0.24, p < 0.01) and both independently and negatively impacted on QoL (standardized β = -0.41 and β = -0.32, both p < 0.01) and on each QLS quality-of-life domains, except for depression on instrumental role and cognitive impairment on interpersonal relations in the sensitivity analyses excluding respondents with any missing data. Effects of depression and cognitive impairment on QoL were not due to specific depressive symptoms or specific cognitive domains, but rather mediated through two broad dimensions representing the shared effects across all depressive symptoms and all cognitive deficits, respectively. LIMITATIONS: Because of the cross-sectional design of this study, measures of association do not imply causal associations. CONCLUSIONS: Mechanisms underlying these two broad dimensions should be considered as important potential targets to improve quality of life of this vulnerable population.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".