• Korean Journal of Adult Nursing
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• v.14 no.3
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• pp.378-389
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• 2002

Purpose: The purpose of this study was to identify the relationship of fatigue and quality of sleep in patients with cancer. Method: The data was collected from January to February 2001. Study objects were recruited K university hospital in Busan, Korea. Their fatigue was measured using the Revised Piper Fatigue Scale developed by Piper et. al(1998), and quality of sleep was measured using Quality of Sleep Questionare by Oh et. al(1998). Result: 1) The fatigue score was mean $114.80{\pm}34.88$(range: 22-220). The sub dimension that showed behavior/severity score at $33.70{\pm}13.89$, affective score at $24.23{\pm}3.33$, sensory score at $27.74{\pm}12.51$, and cognitive/mood score at $29.11{\pm}3.71$. And sleep quality score was mean $37.32{\pm}8.18$. 2) There was a significant difference in religion(F=4.157, P= .008), present therapy(F=2.536, P= .043), past therapy(F=6.625, P= .000), major caregiver(F=3.133, P= .028), and change of weight(F=7.965, P=.006), according to general characteristics in the fatigue in patients with cancer. 3) There was a significant difference in present pain(t=-2.103, P= .037) and change of weight(F=5.484, P=.005), according to general characteristics in the sleep quality in patients with cancer. 4) There was a significant negative correlation between fatigue and quality of sleep(r=- .340, P= .000). Conclusion: Patients with cancer experience in fatigue. Increase in fatigue are associated with decreases in quality of sleep. Nurses must provide patients with nursing care about the occurrence of fatigue and interventions to deal with sleep disturbance.

• Journal of the Korean Society of Physical Medicine
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• v.15 no.3
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• pp.43-50
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• 2020

PURPOSE: To investigate the correlation between sleep quality, neck and shoulder pain, neck and shoulder disability, headache, and smartphone addiction in adults, as well as factors affecting sleep disorders in adults. METHODS: A total of 112 adults in their 20s were recruited for participation in this study. This study measured Pearson's correlation of sleep quality, neck and shoulder pain, neck and shoulder disability, headache and smartphone addiction. Logistic regression analysis (sleep disorder, without sleep disorder adults), was performed to analyze factors affecting sleep disorders. RESULTS: Sleep quality index was positively correlated with shoulder pain and disability index(SPADI)-pain score, SPADI-global score and smartphone addiction score. There was a significant difference in SPADI-pain score between the group with sleep disorders and the group without sleep disorders. Shoulder pain and disability were identified as factors affecting sleep disorders. The group with sleep disorders showed 1.088 times more shoulder pain than the group without sleep disorders, and the group with sleep disorders showed 1.006 times higher frequency of shoulder disorders than the group without sleep disorders. CONCLUSION: The results of the present study indicate that as sleep quality worsens, shoulder pain, disability, and smartphone addiction get worse. The group with sleep disorders had significantly increased shoulder pain compared to the group without sleep disorders. We also found that shoulder pain and disability were factors affecting sleep quality. Comparison between intervention method is warranted to better understand adults with sleep disorders.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.640-647
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• 2022

The purpose of this study was to investigate the factors influencing sleep quality of nursing students, focusing on depression, smartphone usage before sleep, and academic score. Among nursing students in the 3rd and 4th grades of two universities, 196 subjects were randomly selected. Data were collected from April to July 2021 using tool of sleep quality(PSQI-K), depression(Korean BDI-II), and smartphone usage before sleep, and the effect on sleep quality was analyzed through Stepwise Multiple Regression Analysis. As a result of the study, two factors, depression and smartphone usage before sleep, had 39.0% explanatory power for the sleep quality of nursing students, and were statistically significant. That is, the higher the depression level and the more frequent smartphone usage before sleep, the worse the sleep quality level. However, academic score was not a significant variable. In conclusion, in order to improve the sleep quality of nursing students, it is necessary to reduce the pattern of sleep disorders related to depression and to correct the lifestyle by reducing smartphone usage before sleep.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.5
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• pp.2909-2913
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• 2013

Background: The aim of this study was to determine factors affecting sleep quality of 100 patients with advanced stage lung cancer. Methods and Results: it was a descriptive study. A variety of assessment tools were used to provide sleep scores to examine the relation between adverse effects caused by the treatment (nausea, vomiting, fatigue) and sleep quality. As a result, no statistically significant relation between coughing and respiratory problems of patients, or existing depression, and average sleep quality score was found (KW:0.872, p=0.646, KW: 3.174, p=0.205, u: 441.000 p=0.916). It was revealed that nausea and loss of appetite experienced also did not affect the sleep quality score (p>0.05), whereas problems such as vomiting and fatigue did exert effects (p<0.01). Conclusions: Patients with advanced stage lung cancer suffer from sleep problems and cancer related symptoms also affect their sleep quality negatively. Nurses should plan interventions that can control symptoms such as pain, vomiting and fatigue, which affect the sleep of patients.

• Journal of Korean Clinical Health Science
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• v.2 no.3
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• pp.176-187
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• 2014

Purpose. The purpose of this study was to identify the factors affecting quality of sleep and sleep disturbance among inpatient. Methods. A descriptive correlational study was conducted Participants were 200 inpatient in a hospital located in B city. A structured questionnaire was used for data collection. Collected data were analyzed using descriptive statistics, t-test, one-way ANOVA, Pearson's correlation, and stepwise multiple regression. Result. Hospitalized patient's score of sleeping quality was 38.26 on an overall scale of 60, indicating it to be higher than 'Medium (30 points). Almost hospitalized patient in this study suffer from sleep disturbances. As results of univariate analyses, Educational level, Departments, Why hospitalized, Insomnia / depression, Chronic Disease, Scale of pain, physical symptoms, environmental factors, emotional factors, and sleep promoting behavior, disturbed sleep among hospitalized. However, the result of stepwise multiple regression analysis identified that physical symptoms, environmental factors, emotional factors, sleep promoting behavior, and Why hospitalized disturbed sleep and were significant score of sleeping quality for hospitalized and these sleep disturbance factors accounted 46.8% of variance of sleeping quality among hospitalized. Conclusion. These findings suggest that hospitalized patients with poor sleep quality should have their health carefully screened for physical symptoms, environmental factors, emotional factors, sleep promoting behavior, and why hospitalized. In addition, we recommend the development of a nursing program for improving sleep quality.

• Journal of Korean Public Health Nursing
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• v.27 no.1
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• pp.76-88
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• 2013

Purpose: The purpose of this study was to identify the degree of sleep quality and its associated factors in adults. Methods: The data was collected from 986 adults aged 19 to 64 by convenience sampling. Subjects completed a questionnaire composed of Pittsburgh Sleep Quality Index (PSQI), Beck Depression Inventory, and other questions that self-rated health and sociodemographic variables. Statistical methods used included descriptive statistics, simple logistic regression, and multiple logistic regression analyses. Results: The global PSQI score was 5.7. About 45% of the subjects were poor sleepers (global PSQI score >5). Multiple logistic regression analyses showed that factors significantly associated with sleep quality were depression and poor self-rated health in young and middle-aged adults. Depression was the most significant associated factor. The presence of a spouse was also associated with sleep quality in young adults. Conclusion: These findings suggest that people with poor sleep quality should have their health carefully screened for depression. In addition, we recommend the development of a nursing program for improving sleep quality.

• Safety and Health at Work
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• v.10 no.1
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• pp.30-38
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• 2019

Background: Police officers' stress perception, frequency of stressful events (stressors), and police work characteristics may contribute to poor sleep quality through different mechanisms. Methods: We investigated associations of stress severity (measured by stress rating score) and frequency of stressors with sleep quality and examined the influence of police work characteristics including workload, police rank, prior military experience, and shift work on the associations. Participants were 356 police officers (256 men and 100 women) enrolled in the Buffalo Cardio-Metabolic Occupational Police Stress Study from 2004 to 2009. A mean stress rating score and mean frequency of stressors occurring in the past month were computed for each participant from the Spielberger Police Stress Survey data. Sleep quality was assessed using the global score derived from the Pittsburgh Sleep Quality Index survey. Linear associations of the stress rating score and frequency of stressors with sleep quality (Pittsburgh Sleep Quality Index global score) were tested. Age, sex, race/ethnicity, and smoking status were selected as potential confounders. Results: The stress rating score was positively and independently associated with poor sleep quality (${\beta}=0.17$, p = 0.002). Only workload significantly modified this association (${\beta}=0.23$, p = 0.001 for high workload group; p-interaction = 0.109). The frequency of stressors was positively and independently associated with poor sleep quality (${\beta}=0.13$, p = 0.025). Only police rank significantly modified the association (${\beta}=0.007$, p = 0.004 for detectives/other executives; p-interaction = 0.076). Conclusion: Both police officers' perception of stress severity and the frequency of stressors are associated with poor sleep quality. Stress coping or sleep promotion regimens may be more beneficial among police officers reporting high workloads.

• Journal of Sasang Constitutional Medicine
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• v.33 no.1
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• pp.102-108
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• 2021

Objectives The purpose of this study was to identify differences in sleep by Sasang constitutional type using Pittsburgh Sleep Quality Index(PSQI). Methods The subjects of this study were 3,578 people who had information on Sasang constitutional type and PSQI among the data established at the Korean Medicine Data Center. We compared each item score in PSQI (subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, use of sleep medication, daytime dysfunction) and PSQI global scores by Sasang constitutional type using analysis of variance. Logistic regression was conducted to calculate the odds ratio of poor sleep by Sasang constitutional type. Results & Conclusions The SE type showed statistically significantly higher scores than the TE type and SY type in subjective sleep quality, sleep latency, habitual sleep efficiency, sleep disturbance, and PSQI global score, indicating poor sleep compared to other constitutional types. The odds ratio for poor sleep also shows that even after adjusting sex, age, height, and weight, the SE type was significantly higher than other constitutional types, indicating that the SE type could be a risk factor for poor sleep.

• Journal of Korean Academy of Nursing
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• v.50 no.4
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• pp.631-640
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• 2020

Purpose: This study aimed to examine premenstrual symptoms (PMS) of shift nurses and identify the association between PMS, sleep, and occupational stress. Methods: This study was conducted with a secondary data analysis that used data from the Shift Work Nurse's Health and Turnover study. The participants were 258 nurses who were working in shifts including night shifts. PMS, sleep patterns (sleep time and sleep time variability), sleep quality, and the occupational stress of each participant were measured using the Moos Menstrual Distress Questionnaire, a sleep diary, an actigraph, the Insomnia Severity Index, and the Korean Occupational Stress Scale, respectively. Data were analyzed using SPSS 23 and STATA 15.1 to obtain descriptive statistics, Pearson's correlation coefficients, multiple linear regression with generalized estimating equations (GEE) and Baron and Kenny's mediating analysis. Results: The average PMS score, average sleep time, average sleep time variability, average sleep quality score, and average occupational stress score of the participants was 53.95 ± 40.45, 7.52 ± 0.89 hours, 32.84 ± 8.43%, 12.34 ± 5.95, and 49.89 ± 8.98, respectively. A multiple linear regression analysis with GEE indicated that sleep time variability (B = 0.86, p = .001), and sleep quality (B = 2.36, p < .001) had negative effects on nurses' PMS. We also found that sleep quality had a complete mediating effect in the relationship between occupational stress and PMS. Conclusion: These findings indicate that both sleep time variability and sleep quality are important factors associated with PMS among shift work nurses. To improve shift nurses' PMS status, strategies are urgently needed to decrease sleep time variability and increase sleep quality.

• Korean Journal of Community Nutrition
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• v.24 no.5
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• pp.395-407
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• 2019

Objectives: This study examined the association of the sleep quality and patterns with the dietary behavior, including snack and beverage consumption, taste preferences, as well as lifestyle of university students. Methods: The subjects were 406 university students in Cheongju, Korea, and the data were collected using a self-administered questionnaire. They were divided into two groups according to the Pittsburgh Sleep Quality Index (PSQI): good-quality sleepers (PSQI score ≤ 5) and poor-quality sleepers (PSQI score > 5). The data were analyzed using a χ²-test, independent t-test, and analysis of covariance using the SPSS 25.0 program. Results: Fifty-two percent of university students were categorized as poor-quality sleepers by the PSQI. Students classified as poor-quality sleepers had delayed bedtimes, and a shorter duration in bed and total sleep hours than the good-quality sleepers did. Poor-quality sleepers were more prevalent among those who were female, having irregular mealtimes, or frequent late night meals. They also consumed fast food frequently, such as fried chicken and hamburgers, and noodles when adjusted for gender. In addition, drinks with caffeine over milk were dominant among poor-quality sleepers. Furthermore, the preferences for spicy and salty tastes and longer smartphone usage were more prevalent in those with poor-sleep quality. Conclusions: These results showed that more than 50% of university students reported disturbed sleep and poor quality sleep was associated with less desirable snack consumption and taste preference, more smartphone usage, and others. Therefore, nutrition education program along with lifestyle changes promoting sufficient sleep are encouraged to provide for university students, particularly those who have poor sleep quality.