The relationship between sleep disturbance and cognitive impairment in mood disorders: A systematic review
Bibliographic record
Abstract
Abstract Background Cognitive impairment experienced by people with bipolar disorders (BD) or major depressive disorder (MDD) is associated with impaired psychosocial function and poorer quality of life. Sleep disturbance is another core symptom of mood disorders which may be associated with, and perhaps worsen, cognitive impairments. The aim of this systematic review was to critically assess the relationship between sleep disturbance and cognitive impairment in mood disorders. Methods In this systematic review, relevant studies were identified using electronic database searches of PsychINFO, MEDLINE, Embase and Web of Science. Findings Fourteen studies were included; eight investigated people with BD, five investigated people with MDD, and one included both people with MDD and people with BD. One study was an intervention for sleep disturbance and the remaining thirteen studies used either a longitudinal or cross-sectional observational design. Ten studies reported a significant association between subjectively measured sleep disturbance and cognitive impairment in people with MDD or BD after adjusting for demographic and clinical covariates, whereas no such association was found in healthy participants. Two studies reported a significant association between objectively measured sleep abnormalities and cognitive impairment in mood disorders. One study of cognitive behavioural therapy for insomnia modified for BD (CBTI-BD) found an association between improvements in sleep and cognitive performance in BD. Interpretation There is preliminary evidence to suggest a significant association between sleep disturbance and cognitive impairment in mood disorders. These findings suggest that identifying and treating sleep disturbance may be important when addressing cognitive impairment in mood disorders.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".