The Effects of Combined Music Care With Sleep Management Network on Sleep Quality, Sleep Knowledge, and Sleep Hygiene in Nursing Students

Background: Poor sleep quality affect students' learning achievement. Several factors may cause sleep disturbance among nursing students. Sleep and its several influencing factors are both continuous dynamic process. However, changes in students' sleep patterns and related characteristics over time remain unclear. Therefore, understanding the issue and examining an effective program is important to ameliorate sleep and improve learning. Integrated care program has proved to be a nursing students' health promotion intervention. However, research related to sleep and related issue in nursing students in a longitudinal manner is limited worldwide. Thus, the investigators intend to conduct a 3-year research divided into three phases to explore the issue. Objectives: The first phase will adopt longitudinal panel study design. Nursing students from two schools will be invited to participate in the first year study, which will be about 800 people.The data will be obtained from 4 waves (the interval of each wave will be 2 months) of the longitudinal survey of sleep quality of the nursing students and how the students' characteristics influence sleep. Distinct patterns of sleep over time will help to identify what characteristics of students to target for the researchers and to make evidence-based intervention for them. The second phase is to classify music appreciated by the students that may be effective and can be used at the third phase. The third phase is designed to explore the longitudinal effects of a 3-month social network combined with music care program on sleep quality, sleep knowledge, sleep hygiene and daytime sleepiness and fatigue. 100 students will be randomized into 2 groups: intervention and control groups. Participants in the intervention group will receive a 12-week intervention program. The control group will be no intervention. Data will be collected from both groups at pretests, and at different time points depending on variables after intervention completed. Statistical analysis: Growth curve modeling will be employed in this study for longitudinal analyses to identify the trajectory of sleep predicted by the students' characteristics. Descriptive analyses will be conducted using SPSS 18. Anticipated results and implications: This study will enable us to advance knowledge and research about nursing students' longitudinal patterns of sleep and the longitudinal effects of the intervention program on their sleep. If the longitudinal effects of the intervention program on their sleep are confirmed, the findings will provide evidence for educators and policy makers using evidence-based intervention to ameliorate sleep in nursing students.