Multiple mediators of anxiety and depression between living space and cognitive function among elderly patients with ischemic stroke
Bibliographic record
Abstract
Objective To explore the relationship between living space, cognitive function, anxiety, and depression in ischemic stroke patients, specifically examining the mediating roles of anxiety and depression. Methods A cross-sectional study included 445 ischemic stroke patients treated in the neurology department of a top-tier hospital in Zhejiang Province and discharged between January 2024 and January 2025 were selected. Participants completed General information questionnaires, the Montreal Cognitive Assessment (MoCA), Living Space Scale, and Hospital Anxiety and Depression Scale (HADS). Data were analyzed using R4.4.2 and MPLUS 8.7 software. Results Among 445 participants, correlation analysis showed that cognitive function was positively correlated with living space ( r = 0.37, P < 0.05) and negatively correlated with anxiety symptoms and depression symptoms ( r = -0.53, r = -0.64, all P < 0.05). Anxiety and depression were mediating variables between living space and cognitive function ( 95%CI : 0.018~0.117, 0.017~0.095), with effect sizes of 0.072 and 0.057, respectively. Additionally, anxiety and depression played a serial mediating role between living space and cognitive function ( 95%CI : 0.082~0.172), with an effect sizes of 0.122. Conclusion Living space level directly affect the cognitive function in ischemic stroke patients and indirectly affects cognition through its impact on psychological health, mediated independently and serially by anxiety and depression.
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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) | 0.001 | 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 | 0.000 |
| 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".