An Exploratory Study of the Factors Affecting Sleep Quality Levels among a Sample of University Students Using a Multinomial Logistic Regression Model
DOI:
https://doi.org/10.31272/jae.i151.1476Keywords:
Multinomial Logistic Regression, Sleep Quality, Pseudo R-squared, ROC CurveAbstract
The research aims to examine a problem that has recently emerged in society: healthy sleep, as most people, especially university students, experience irregular sleep for several reasons. The researcher used multiple logistic regression to identify factors affecting the quality of sleep among university students, given the categorical nature of the dependent variable (good, average, bad). Data were collected over thirty days using an electronic questionnaire distributed to more than 50 male and female students. Each respondent completed the questionnaire daily, based on their daily reports of sleep quality and psychological stress; monthly averages of these variables were then computed. The data were entered and coded in SPSS, and the analysis results demonstrated the model’s predictive efficiency, as evaluated by the -2 Log Likelihood test, the classification table, the pseudo R-squared statistic, and the ROC curve. The findings indicated that the variables use of a mobile phone before sleep, psychological stress, and caffeine intake were statistically significant predictors of sleep quality. In contrast, other variables — age, gender, sleep duration, physical activity, and sleep environment — were not statistically significant.
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