Subjective sleep quality in non-demented older adults with and without cognitive impairment
Bibliographic record
Abstract
OBJECTIVE: Sleep problems are prevalent among older adults who are at risk of developing dementia. Until now, there have been relatively few studies investigating subjective sleep quality in these individuals. The first objective of this study was to compare seniors with cognitive impairment no dementia (CIND) and older adults without cognitive impairment (non-CIND) on several subjective sleep measures. The second objective was to verify whether sleep parameters associated with CIND differ between men and women. METHODS: The population sample consisted of 2287 French-speaking older adults from Québec (Canada) aged between 65 and 96 years. Participants were classified as CIND or non-CIND on the basis of their mini mental state examination score using sex, age, and education-stratified normative data. All participants completed the Pittsburgh Sleep Quality Index, and responses of CIND and non-CIND individuals were compared. A series of confounding variables (age, education, chronic diseases, mood disorders, anxiety disorders, and use of psychotropic drugs) were statistically controlled for. Student's t-tests were performed to compare characteristics of CIND and non-CIND individuals; data from male and female participants were analyzed separately. Moreover, the association between each sleep variable and CIND was measured by odds ratios based on logistic regression. RESULTS: On the whole, analyses revealed no significant association between subjective sleep parameters and CIND. Moreover, no difference was observed between men and women regarding subjective sleep quality. CONCLUSIONS: Overall, these results suggest that subjective measures of sleep do not allow differentiating cognitively impaired older individuals from those with normal cognition.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".