This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License. (http://creativecommons.org/licenses/by-nd/4.0)If the original work is properly cited and retained without any modification or reproduction, it can be used and re-distributed in any format and medium. Purpose: The aims of this study were to construct a hypothetical structural model which explains premenstrual coping in university students and to test the fitness with collected data. Methods: Participants were 206 unmarried women university students from 3 universities in A and B cities. Data were collected from March 29 until April 30, 2016 using self-report structured questionnaires and were analyzed using IBM SPSS 23.0 and AMOS 18.0. Results: Physiological factor was identified as a significant predictor of premenstrual syndrome (t=6.45, p<.001). This model explained 22.1% of the variance in premenstrual syndrome. Psychological factors (t=-2.49, p=.013) and premenstrual syndrome (t=8.17, p<.001) were identified as significant predictors of premenstrual coping. Also this model explained 30.9% of the variance in premenstrual coping in university students. A physiological factors directly influenced premenstrual syndrome (b=.41, p=.012). Premenstrual syndrome (b=.55, p=.005) and physiological factor (b=.23, p=.015) had significant total effects on premenstrual coping. Physiological factor did not have a direct influence on premenstrual coping, but indirectly affected it (b=.22, p=.007). Psychological factors did not have an indirect or total effect on premenstrual coping, but directly affected it (b=-.17, p=.036). Conclusion: These findings suggest that strategies to control physiological factors such as menstrual pain should be helpful to improve premenstrual syndrome symptoms. When developing a program to improve premenstrual coping ability and quality of menstrual related health, it is important to consider psychological factors including perceived stress and menstrual attitude and premenstrual syndrome.
The purpose of this study was to identify the influence of physical activity and depression on sleep quality among the young-old and old-old community-dwelling elderly. Methods: Participants were 216 community-dwelling older adults in Korea aged 65 or above. Data were collected using structured questionnaires with face-to-face interviews that included demographic and health-related characteristics, International Physical Activity Questionnaires (IPAQ), the Short Form Geriatric Depression Scale (SGDS) and the Pittsburgh Sleep Quality Index (PSQI). A hierarchical multiple regression was conducted to examine whether physical activity and depression would predict sleep quality under other controlled factors. Results: There were differences in demographic and health-related characteristics, physical activity, and depression by age groups, but not in sleep quality. In the young-old elderly, physical activity (β= -0.22, p= .043) and depression (β= 0.31, p= .002) were significantly associated with sleep quality (F= 4.46, p= .001, Adjusted R 2 = .16). In the old-old elderly, physical activity (β= -0.29, p= .001) and depression (β= 0.41, p< .001) were significantly associated with sleep quality (F= 10.79, p< .001, Adjusted R 2 = .29). Conclusion: These finding highlight physical activity and depression as important contributors to sleep quality in both young-old and old-old elderly.
This study examined the effectiveness of maternity nursing simulations using a high-fidelity simulator for undergraduate nursing students. One-group pretest-posttest design was used. The simulation-based education program consisted of three sessions, including the clinical scenarios about prenatal, childbearing and postpartum care. The program provided for 3 weeks in November 2014. Data was collected before and after the simulation education using self-reported questionnaires, which included simulation effectiveness, problem solving ability, communication skills and self-confidence in maternity nursing. The data of 83 participants were analyzed using the IBM SPSS 20.0 program. After simulation education, the overall score of the simulation effectiveness was 17.4 out of 26.0. Communication skill (t=4.58, p=<.001) and self-confidence in maternity nursing (t=9.70, p=<.001) increased significantly in the posttest. On the other hand, there was no significant change in the problem solving ability. The simulation effectiveness correlated significantly with the problem solving ability (r=.494, p<.001), communication skill (r=.361, p<.001), and self-confidence in maternity nursing (r=.497, p<.001) after simulation-based education. These findings suggest that the high-fidelity simulation in maternity nursing education could be used not only to enhance the nursing competency, but also to deal with the limitations of the clinical practicum in the current situation.
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