Evaluation of the Effects of an Intervention Intended to Optimize the Sleep Environment Among the Elderly: An Exploratory Study

Sleep state of the elderly population in Korea: Nationwide cross-sectional population-based study

Objective

Interest in sleep disorders among the elderly, especially those in Korea, has increased. We aimed to describe the overall sleep status of the elderly population in Korea using survey data and to determine the risk factors concerning different aspects of sleep status.

Methods

We conducted a cross-sectional survey on 271 respondents aged 65-86 years old. We performed multistage clustered random sampling according to the population and socioeconomic distribution of all Korean territories. The survey questionnaire was used to perform a structural assessment of sociodemographic characteristics; medical comorbidities; psychiatric comorbidities; and sleep status, including sleep duration, sleep quality, presence of insomnia, excessive daytime sleepiness, sleep apnea, and restless legs syndrome.

Results

Approximately 12.5, 22.%, and 51.3% of the elderly population had poor sleep quality, excessive daytime sleepiness, and insomnia, respectively. Hypertension, dyslipidemia, insomnia, anxiety, and depression predicted poor sleep quality. Female sex, insomnia, and sleep apnea predicted excessive daytime sleepiness. Poor sleep quality and depression predicted insomnia.

Conclusion

A substantial proportion of the elderly Korean population have sleep problems, including poor sleep quality, excessive daytime sleepiness, and insomnia. Sleep status is influenced by various factors, including age, sex, and metabolic and psychiatric comorbidities.

Effectiveness of cognitive behaviour therapy (CBT) to improve the sleep quality of the elderly in hospital

Background Quality of sleep is very important for everyone both healthy and sick, Efforts to provide sleeping pills have also not been effective because of the elderly do not want to report or treat sleep problems experienced so that the quality of sleep becomes poor. One of the therapies that can be done to improve the quality of sleep in the elderly, using Cognitive Behaviour Theraphy (CBT) therapy. Method research design is quasi experimental design pre and post test design with Control group and interventions in the form of CBT therapy to elderly clients. The study was conducted using two groups, the intervention group was given CBT therapeutic interventions and the control group was only given general care. The study subjects got CBT therapy for 2 days (dose 2 X 1 day @ 20-30 minutes). Measurement of sleep quality was carried out 2 times for 4 days in the study subjects using the Indonesian version of the ISI instrument.

A Feasibility Study on Smart Mattresses to Improve Sleep Quality

Good sleep quality is essential, especially for clinical users. Sleep disorders not only impair the success rate of treatment but also delay recovery. They can seriously interfere with treatment outcomes and even endanger a user's life. In this study, we created a smart mattress containing 10 × 18 air packs and control units. Each air pack contains a set of pressure and height sensors and two air valves. Each row control unit can detect and adjust the pressure and height of each air bag in the row. When the bed body is turned on, it automatically initializes, adjusts the state of each air bag to the same height and pressure, and enters a slow scanning state. When perceived objects or people are lying on the bed, the bed automatically perceives the human body structure and body pressure matrix, increases the scanning speed for more timely and accurate measurements of the digital matrix and forming pressure by matrix-normalized processing, and then uses local pressure variance detection to automatically adjust to the sleeping position of the human body and thus achieve a uniform force distribution and a comfortable state. Finally, pressure matrix binarization was used to match sleeping position templates to identify the best template for automatic recognition of the sleeping position. The experimental results show that the sleeping position recognition method has high accuracy, recall, and precision. Our mattress is designed with interfaces for external devices. In future research, the smart mattress can connect to an auxiliary part of a smart ecosystem consisting of a smart pill box, a smart lighting system, and a microclimate system, which is expected to yield a more comprehensive intelligent ward to explore the possibility of improving sleep quality.