Depressive symptoms mediate the longitudinal relationships between sleep quality and cognitive functions among older adults with mild cognitive impairment: A cross-lagged modeling analysis
Bibliographic record
Abstract
Although it is generally recognized that sleep quality, depressive symptoms, and cognitive functions are related respectively, the main ambiguity comes from difficulties in determining their cause-effect relationships. The present study aimed to explore the longitudinal causation relationships among sleep quality, depressive symptoms, and cognitive functions in older people with mild cognitive impairment (MCI). A total of 134 patients from 24 communities in Ningbo City, Zhejiang Province, China with MCI were interviewed at baseline, while 124 of them were re-interviewed 2 months later, and 122 were re-interviewed 4 months later. The Patient Health Questionnaire-9, the Pittsburgh Sleep Quality Index and the Montreal Cognitive Assessment Scale were assessed in the interview. Cross-lagged models were tested to disentangle the relationships among sleep quality, depressive symptoms, and cognitive functions using structural equation modeling with latent variables on the four-mouth longitudinal data. The correlation coefficients between sleep quality and depressive symptoms were significant showing the stability across time points of assessment, while the correlation coefficient of cognitive function was not significant (r = 0.159, p > 0.05). The results of index of model fit indicated that the cross-lagged model was acceptable (CFI = 0.934, TLI = 0.899, RMSEA = 0.075, χ 2 /df = 1.684). The results of cross-lagged model analysis supported the complete mediating role of depressive symptoms in the association between sleep quality and cognitive functions, where worse sleep quality may lead to more severe depressive symptoms, which in turn leads to more severe cognitive decline. In Conclusion, sleep quality is significantly correlated with cognitive functions in patients with mild cognitive impairment, which association is fully mediated by depressive symptoms. Approaches addressing sleep quality and depressive symptoms are recommended and hold promise for the management of mild cognitive impairment.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".