ReviewClinical nursing research2018
Sleep Among Long-Term Care Residents in China: A Narrative Review of Literature.
Review in Clinical nursing research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prevalence of sleep disorders among older adults in Chinese older adults care institutions: a systematic review and meta-analysis.Frontiers in public health · 2025Pooled it
- The relationship between pain, sleep quality, and care dependency in older adults living in a long-term care facility.BMC geriatrics · 2025Article
- The Impact of Social Support on Sleep Quality in Elderly Care Institutions in Northeast China: the Chain-Mediating Effect of Psychological Adjustment and Coping Style.Patient preference and adherence · 2024Article
- Age and objectively measured sleep: investigating associations and interactions by sex and race in middle-aged and older adults.Sleep advances : a journal of the Sleep Research Society · 2024Article
- The sleep patterns and their associations with mental health among nursing home residents: a latent profile approach.BMC geriatrics · 2023Article
- Behavioral and exercise interventions for sleep dysfunction in the elderly: a brief review and future directions.Sleep & breathing = Schlaf & Atmung · 2021Review
- Sleep Disturbance, Sleep Disorders and Co-Morbidities in the Care of the Older Person.Medical sciences (Basel, Switzerland) · 2021Review
- Article
- Insomnia, Benzodiazepine Use, and Falls among Residents in Long-term Care Facilities.International journal of environmental research and public health · 2019Article
- Sleep in Normal Aging.Sleep medicine clinics · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The objective of this study is to synthesize and evaluate the current body of sleep research among long-term care (LTC) residents in China and provide insights for future research. Systematic searches identified 15 studies that examined sleep in LTC residents in China. Sleep disturbances and poor sleep quality were prevalent in Chinese LTC residents. Eight cross-sectional studies reported that demographics, comorbidities, lifestyle, and environment were associated with sleep quality in Chinese LTC residents. Seven intervention studies, including exercise, traditional Chinese medicine, light therapy, and behavioral interventions resulted in improved sleep quality. Only subjective sleep measures were used in all 15 studies. Some methodological issues were identified in studies, especially those conducted in Mainland China. Sleep research in LTC residents in China is still at the beginning stages. Future studies should consider more rigorous designs and objective sleep measures, and develop target interventions based on factors associated with sleep disturbances.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.