Abstract
This study investigates the convergence relationship of factors related to hopelessness among some health college students to identify the advantage of data analysis in the field of health care. The questionnaire was conducted using an unregistered self-administered questionnaire for 214 students from a college located in J area from October 1, 2018 to October 31, 2018. The hierarchical multiple regression analysis shows the following results. The hopelessness of respondents turned out to be significantly higher in following groups: a group in which academic burnout is higher, a group in which anxiety is higher, and a group in which psychosocial stress is higher. The results show explanatory power of 43.3%. And this indicates that the efforts to decrease academic burnout, anxiety, and psychosocial stress are required to decrease hopelessness among health college students. These results can be used to guide college life counseling to lower hopelessness among health college students. It is also expected to be used for efficient data analysis of health problems. Further research requires the development of sophisticated data analysis techniques and procedures that can be used more efficiently in health care.
Highlights
The government and related agencies continue to make efforts to efficiently plan and implement policies to promote the health of local residents
This study analyzed the relationship among the academic burnout, anxiety, psychosocial stress and hopelessness of some college students majoring in health science to identify the advantages of data analysis in health care
The survey was conducted on 214 college students majoring in health science randomly selected from a college in J area from October 1, 2018 to October 31, 2018
Summary
The government and related agencies continue to make efforts to efficiently plan and implement policies to promote the health of local residents. The project’s validity is verified by viewing the program’s output as utility or effect rather than currency, so identifying cause and effect on health problems is an important means to improve the efficiency of health projects. A multidisciplinary cause of health-related problems requires a methodology to analyze data and explore causes through scientific methods. This study identifies analysis in health care by measuring the variables of causes and results of health problems with a certified measure with proven reliability and validity and by utilizing statistical analysis tools such as t-test, ANOVA and hierarchical multiple regression analysis. The causal relationship of hopelessness and these factors was determined by statistical data analysis
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