Sleep Environment and Insomnia in Elderly Persons Living at Home
Bibliographic record
Abstract
The aim of this study was to draw a portrait of the sleep environment of elderly persons living in private households and to determine its relationship with the presence of insomnia. A sample of 599 individuals aged 70 years and older responded to questions about the comfort of their pillow and mattress and the noise level and brightness of their bedroom at night and in the morning. They were also asked whether or not they shared their bed or bedroom with a sleep partner. The Insomnia Severity Index was used to assess insomnia severity. Over 40% of the study participants were using a pillow that was not very comfortable, and almost 30% said that their bedroom was not completely quiet. Binomial logistic regression results revealed that two variables were significantly associated with insomnia symptoms: a pillow rated as moderately comfortable to very uncomfortable and a bedroom that was not completely quiet. No other sleep environment characteristics considered in this study were associated with the risk of insomnia. These results indicate that a nonnegligible proportion of the elderly population endures a suboptimal sleep environment. Although it is difficult to predict the real impact of changes to the sleep environment, this study supports the proposal that simple, minor changes to the bedroom can promote sleep in the elderly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".