A Scoping Review of Strategies and Outcomes of Sleep Education Interventions for Older Adults
Bibliographic record
Abstract
Abstract As sleep disturbances are prevalent among older adults, it is well-established that sleep health issues are negatively impacting their physical, cognitive, and emotional well-being. Although sleep health interventions have been developed and tested as a key non-pharmacological strategy to improve sleep quality in older adults, the scope of their educational components and their effectiveness across different delivery modalities remain unclear. We conducted a scoping review to assess the impact of sleep education interventions on older adults’ health and well-being. A search of databases was conducted in September 2024, yielding 1,452 studies published in the past 30 years. After conducting title/abstract and full-text review, 33 studies met our inclusion criteria. The inclusion criteria for included studies were: (1) targeting adults age 60+; (2) including sleep education interventions; and (3) in English; Studies including non-educational or self-guided interventions were excluded. Interventions spanned various countries, with the U.S. (n = 14), followed by Iran, Canada, Japan, and Brazil. Randomized Controlled Trials (RCTs) were the most common (n = 21), followed by quasi-experimental, and pilot studies. Sleep education modalities mostly utilized Cognitive Behavioral Therapy for Insomnia (CBT-I), sleep hygiene education, and relaxation training. CBT-I, interventions that also included physical activity, music, and light therapy showed the greatest improvements in sleep quality and reductions in insomnia severity. Additional benefits from sleep education delivered virtually were also highlighted. Our research highlights that sleep education can be a feasible and effective modality to improve sleep in older adults. Future research should explore tailored interventions for marginalized subgroups of aging populations.
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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 | 0.022 | 0.074 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".