Psychometric Properties of Korean Minimal Insomnia Screening Scale

Kim, In-Ja; Kim, Sung-Jae; Kim, Beomjong; Choi, Heejung

doi:10.4040/jkan.2012.42.6.853

Cited by 4 publications

(3 citation statements)

References 23 publications

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“…Participants reported some difficulty answering the visual analog scales used in this questionnaire, which have discrete opposite phrase only at the two ends of the scale. This result is in line with a previous study where participants felt more comfortable answering a graphic rating scale (Kim, Choi, & Kim, 2014; Kim, Kim, Choi, & Kim, 2012).…”

Section: Discussionsupporting

confidence: 93%

Psychometric Properties of the Korean Versions of Three Sleep Evaluation Questionnaires

Choi

Kim

et al. 2014

Clin Nurs Res

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Psychometric properties of the Korean versions of three sleep evaluation questionnaires were described to provide tools for practitioners and researchers interested in transcultural studies in Korea. The Pittsburgh Sleep Quality Index (PSQI), the General Sleep Disturbance Scale (GSDS), and the Leeds Sleep Evaluation Questionnaire (LSEQ) were analyzed using data from 959 community-dwelling adults in Korea. Furthermore, cut-off points and prevalence of sleep disturbance were identified. Reliability and concurrent validity for all measures were acceptable. Optimal cut-off points of PSQI, GSDS, and LSEQ with highest Youden's index were 5, 33, and 66, and prevalence of sleep disturbance was 22.1%, 26.3%, and 25.8%, respectively. The Korean PSQI, GSDS, and LSEQ are all valid and reliable tools for detecting sleep disturbance. We provide suggestions for selecting the right tools according to the purpose, setting, and participants of transcultural studies.

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Section: Discussionsupporting

confidence: 93%

Psychometric Properties of the Korean Versions of Three Sleep Evaluation Questionnaires

Choi

Kim

et al. 2014

Clin Nurs Res

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“…In this study, survey data were collected each morning from test participants on their quality of sleep the night before and also collected each night on behaviors of day-time that are known to affect sleep at night. The morning questionnaire measured the subjectively evaluated quality of sleep using questions obtained from the Pittsburgh Sleep Quality Index (PSQI) [35]. The items of morning sleep questionnaires consist of five: subjective sleep quality, sleep disturbance, dream issues, feeling after sleep, and body condition after sleep.…”

Section: B Sleep Label Design From Sleep Questionnairementioning

confidence: 99%

Assessing Sleep Quality Using Mobile EMAs: Opportunities, Practical Consideration, and Challenges

et al. 2022

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Sleep is one of the most important factors in maintaining both physical and mental health. There are many causes of sleep problems, it is generally necessary to maintain a healthy lifestyle to avoid them. In the medical field, information related to sleep problems including lifestyle information is obtained through interviews, but this approach is limited because it is dependent on the patient's memory. Thus, there are many studies adopting ecological momentary assessments (EMAs) to collect patient's lifestyles. Some of them also use smart devices to collect data effectively. However, these studies focused on specific factors such as smoking, exercising so that they have limits to reflect complex narrative of lifestyle patterns. Therefore, we proposed indicators consist of EMAs data for assessing everyday sleep quality and these indicators contain the complex lifestyle contexts in a quantitative manner. First, we collected real-life data using a smartphone through a 4-week data collection experiment. Second, we develop a method of generating daily indexes reflecting geospatial and social habits, social condition, activity level, and emotional condition using self-report data. Third, we evaluated daily indexes whether could use to supplement indicators comprising features using EMAs from conventional sleep questionnaires. The goal of analysis consists of five metrics of sleep quality that explain perceived sleep quality. The result of analysis indicates that features using both daily indexes and sleep questionnaires lead to better prediction of sleep quality. Additionally, it also shows the potential to generate indicators identifying complex human behaviors with the help of mobile devices and EMAs. Further research on user-friendly data acquisition methods and more diverse lifestyle information should be useful to support behavior decisions for better sleep in wellbeing services and in specialized medical fields.

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“…Quality of sleep was measured using the Minimal Insomnia Screening Scale for Korean adults (KMISS) [20]. The KMISS is a self-report questionnaire consisting of the following three items: difficulty falling asleep at night, restlessness during sleep, and tiredness when waking up in the morning.…”

Section: Sleep Qualitymentioning

confidence: 99%

Factors that Influence Sleep among Residents in Long-Term Care Facilities

Kim

Yoon

2020

IJERPH

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Long-term care residents often experience sleep disturbances as they are vulnerable to a variety of physical, psychosocial, and environmental factors that contribute to sleep disturbances. However, few studies have examined the combined impact of multiple factors on sleep among long-term care residents. This study aimed to identify the factors that influence sleep efficiency and sleep quality based on a modified senescent sleep model. A total of 125 residents were recruited from seven long-term care facilities in South Korea. Sleep patterns and sleep quality were collected using 3-day sleep logs and the Minimal Insomnia Screening Scale for Korean adults (KMISS), respectively. The mean sleep efficiency was 84.6% and the mean score on sleep quality was 15.25. A multiple linear regression analysis showed that greater dependence in activities of daily living (ADL), higher pain, and light at night were related to lower sleep efficiency. Higher pain and fatigue, less activity time, noise and light at night, and lower nighttime staffing levels were related to poorer sleep quality. This study highlights that psychosocial and environmental factors as well as physical factors could influence sleep for long-term care residents. Our findings could be foundational evidence for multi-faceted sleep intervention program development in long-term care settings.

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Psychometric Properties of Korean Minimal Insomnia Screening Scale

Cited by 4 publications

References 23 publications

Psychometric Properties of the Korean Versions of Three Sleep Evaluation Questionnaires

Psychometric Properties of the Korean Versions of Three Sleep Evaluation Questionnaires

Assessing Sleep Quality Using Mobile EMAs: Opportunities, Practical Consideration, and Challenges

Factors that Influence Sleep among Residents in Long-Term Care Facilities

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