Currently, most studies on the factors affecting sleep quality have used logistic regression or multiple linear regression to identify such factors, there are same drawbacks in these methods, the structural equation modeling (SEM) can compensate for these deficiencies. A total of 2341 students from three universities in Hainan, China, participated in the cross-sectional survey. The Pittsburgh sleep quality index (PSQI) was used to evaluate sleep quality. A self-administered questionnaire was provided to collect data for the symptom checklist-90 (SCL-90) and the internet addiction test (IAT), as well as other potential or hidden factors affecting sleep quality. SEM was used to estimate the important factors affecting sleep quality, and to explore the particular contributions of the identified factors. The types of hidden factors affecting sleep quality were, in descending order, psychological (0.308), behavioral (0.289), physiological (0.250), and environmental (0.019) factors. More specifically, higher scores on the SCL-90 (0.780) caused the biggest difference in sleep quality, followed by health status (0.601), the frequency of late sleeping (0.574), internet addiction (0.530), and the dormitory environment (0.470). The results provide reliable means for the improvement of sleep quality among college students. [ABSTRACT FROM AUTHOR]