Positive and Negative Association Rules Mining for Mental Health Analysis of College Students
Long Zhao 1  
,  
Feng Hao 1
,  
Tiantian Xu 1  
,  
 
 
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Qilu University of Technology, Jinan, China
CORRESPONDING AUTHOR
Long Zhao   

Lecturer, School of information, Qilu University of Technology, Jinan, China. Address to No. 3501, University Road, Changqing District, Jinan, China Tel: +86-531-89631258
Tiantian Xu   

Lecturer, School of information, Qilu University of Technology, Jinan, China. Address to No. 3501, University Road, Changqing District, Jinan, China Tel: +86-531-89631251
Online publish date: 2017-08-22
Publish date: 2017-08-22
 
EURASIA J. Math., Sci Tech. Ed 2017;13(8):5577–5587
KEYWORDS
ABSTRACT
The psychological problems of college students have aroused general concerns. A lot of college students are plagued by all kinds of psychological health problems. Psychological health problems brought a lot of negative effects to them. The psychological assessment data and the basic information collected from 6500 freshmen are used to analyze association rules and characteristics of college students’ psychological factors in this paper. The symptom self-rating scale (SCL-90) was compiled by L. R. Derogatis in 1975, which contains 90 items. The SCL-90 has been used in a wide range of psychiatric symptoms. The SCL-90 includes ten factors, such as somatization, obsessive-compulsive symptoms, interpersonal sensitivity, depression, anxiety, hostility, terror, paranoia, psychosis and other factors. The PNARC model is introduced in this paper to mine the positive and negative association rules from real SCL-90 data set of one Chinese college. The support-confidence framework and the correlation test method are obtained to delete the contradict association rules and get the positive and negative association rules for correctly analyzing the potential relationship of SCL-90 factors. Mined positive and negative association rules are also helpful to analyze and coach the mental health of college students.
 
REFERENCES (13)
1.
Burlaka, V., Churakova, I., Aavik, O. A., Staller, K. M., & Delva, J. (2014). Attitudes toward health-seeking behaviors of college students in ukraine. International Journal of Mental Health & Addiction, 12(5), 549-560. DOI:10.1007/s11469-014-9483-4.
 
2.
Cheng, C. W., Martin, G. S., Wu, P. Y., & Wang, M. D. (2014). PHARM - Association Rule Mining for Predictive Health. The International Conference on Health Informatics. Springer International Publishing. DOI:10.1007/978-3-319-03005-0_29.
 
3.
Dong, X., Niu, Z., Shi, X., Zhang, X., & Zhu, D. (2007). Mining Both Positive and Negative Association Rules from Frequent and Infrequent Item sets. International Conference on Advanced Data Mining and Applications, 4632, 122-133. Springer-Verlag. DOI:10.1007/978-3-540-73871-8_13.
 
4.
Han, J. (2010). Fast mining of frequent item sets based on fp-tree. Computer Applications & Software.
 
5.
Han, J., Pei, J., & Yin, Y. (2000). Mining frequent patterns without candidate generation. Acm Sigmod Record, 29(2), 1-12. DOI:10.1145/342009.335372.
 
6.
Herawan, T., Vitasari, P., & Abdullah, Z. (2012). Mining interesting association rules of students suffering study anxieties using slp-growth algorithm. International Journal of Knowledge & Systems Science, 3(2), 24-41. DOI:10.4018/jkss.2012040102.
 
7.
Hodgins, D. C., Ranson, K. M. V., & Montpetit, C. R. (2015). Problem drinking, gambling and eating among undergraduate university students. What are the links? International Journal of Mental Health & Addiction, 1-19. DOI:10.1007/s11469-015-9598-2.
 
8.
Jena, S., & Tiwari, H. (2015). Stress and mental health problems in 1st year medical students: a survey of two medical colleges in Kanpur, India. New England Journal of Medicine, 359(15), 228-232. DOI:10.5455/2320-6012.ijrms20150122.
 
9.
Nembhard, D. A., Yip, K. K., & Stifter, C. A. (2012). Association rule mining in developmental psychology. Data Mining Concepts Methodologies Tools & Applications, 1(1), 23-37. DOI:10.4018/ijaie.2012010103.
 
10.
Özyürek, P., & İbrahim Kılıç. (2015). The investigation of mental health problems and social phobia status of college students. Journal of the Canadian Dental Association, 79, d147-d147. DOI:10.15345/iojes.2015.04.016.
 
11.
Qi, W., Yan, J., Huang, S., Guo, L., & Lu, R. (2013). The application of association rule mining in college students′mental health assessment system. Journal of Hunan University of Technology.
 
12.
Wang, D., & Psychology, S. O. (2015). Application of multidimensional association rules method in psychological measurement. Intelligent Computer & Applications.
 
13.
Zheng, G., Lan, X., Li, M., Ling, K., Lin, H., & Chen, L., Tao, J., Li, J., Zheng, X., Chen, B., & Fang, Q. (2014). The effectiveness of tai chi on the physical and psychological well-being of college students: a study protocol for a randomized controlled trial. Trials, 15(1), 1-9. DOI:10.1186/1745-6215-15-129.
 
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