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ÜNİVERSİTE ÖĞRENCİLERİNİN KÖTÜ ALIŞKANLIKLARININ BAYESCİ AĞ YÖNTEMİ İLE BELİRLENMESİ

Year 2017, Volume: 26 Issue: 3, 230 - 240, 21.10.2017

Abstract

Son yıllarda,
gençler arasında giderek artan sigara, içki, kumar ve madde bağımlılığı gibi
kötü alışkanlıkların
öncelikle
bireylerin kendilerine ve sonrasında içinde bulundukları topluma geniş ölçüde
zararları dokunmaktadır. Eğitim seviyesinin
artması bu kötü alışkanlıkların önüne geçememektedir. Bu çalışmada
Samsun
Ondokuzmayıs üniversitesinde eğitim alan 1200
öğrencinin (%49,6 erkek;


=21,43, SD=2,17)
sigara, alkol,  madde kullanımı ve kumar
oynama gibi kötü alışkanlıklarının Bayesci ağ yöntemi ile modellenmesi
yapılmıştır. Ayrıca öğrencilerin günlük kitap okuma, internet kullanım alanları
gibi sosyal hayatlarını etkileyen faktörler ile kötü alışkanlıkları arasında
bir ilişki olup olmadığı lojistik regresyon analizi ile ortaya konulmuştur.
Cinsiyet, öğrencilerin nerede kaldıkları ve yaş faktörlerinin kötü
alışkanlıklar üzerinde doğrudan ilişkilerinin olduğu görülmektedir. Öğrencilerde
yaş ortalamasının artması ile birlikte kötü alışkanlıkların azaldığı ve erkek
öğrencilerin kız öğrencilere göre kötü alışkanlıklarının üç kat daha fazla
olduğu ortaya konulmuştur. 

References

  • Anthony, J. C., ve Echeagaray-Wagner, F., (2000). Epidemiologic analysis of alcohol and tobacco use. Alcohol Research and Health, 24(4), 201-208. Bujarski, S., ve Ray, L. A., (2014). Negative affect is associated with alcohol, but not cigarette use in heavy drinking smokers. Addictive behaviors, 39(12), 1723-1729. Cohn, A., Villanti, A., Richardson, A., Rath, J. M., Williams, V., Stanton, C., & Mermelstein, R. (2015). The association between alcohol, marijuana use, and new and emerging tobacco products in a young adult population. Addictive behaviors, 48, 79-88. Constantinou, A. C., Fenton, N. E., & Neil, M. (2012). pi-football: A Bayesian network model for forecasting Association Football match outcomes. Knowledge-Based Systems, 36, 322-339. Ediş, S., & Ulaş, E. (2017). Çankırı Acıçay-Tatlıçay Havzalarında arazi kullanım türlerinin Bayes Ağları yöntemiyle tahmin edilmesi. Turkish Journal of Forestry, 18(3), 212-218. Ehlke, S. J., ve Cohn, A. M., (2016). Was it the drink? The conditioned association of alcohol and desire to quit smoking on the dual use of little cigars/cigarillos and cigarettes among men and women. Addictive Behaviors,59, 48-51. Friedman,N.,Geiger,D.,& Goldszmidt,M. (1997).Bayesian network classiers. MachineLearning,29,131,163. Friedman, N., Nachman, I., Peéer D., 1999. Learning Bayesian Network Structure fromMassive Datasets: The “Sparse Candidate” Algorithm. Proc. Fifteenth Conf. on Uncertainty in Artificial Intelligence (UAI). Hershberger, A. R., Karyadi, K. A., VanderVeen, J. D. ve Cyders, M. A., (2016). Combined expectancies of alcohol and e-cigarette use relate to higher alcohol use. Addictive behaviors, 52, 13-21. Jackson, N., Denny, S., Sheridan, J., Fleming, T., Clark, T., Teevale, T., ve Ameratunga, S., (2014). Predictors of drinking patterns in adolescence: a latent class analysis. Drug and Alcohol Dependence, 135, 133-139. Kjærulff, T. M., Rivera, F., Jiménez-Iglesias, A., ve Moreno, C., (2014). Perceived quality of social relations and frequent drunkenness: a cross-sectional study of Spanish adolescents. Alcohol and Alcoholism, 49(4), 466-471. Mittal A. ve Kassim A. A., 2007 Bayesian Network Technologies: Applications and Graphical Models. Margaritis, D., (2003). Learning Bayesian Network Model Structure from Data. PhD thesis, School of Computer Science, Carnegie-Mellon University, Pittsburgh, PA. CMU-CS-03-153. Morean, M. E., Kong, G., Camenga, D. R., Cavallo, D. A., Simon, P., ve Krishnan-Sarin, S., (2016). Latent class analysis of current e-cigarette and other substance use in high school students. Drug and alcohol dependence, 161, 292-297. Neapolitan R. E., (2003). Learning Bayesian Networks, Prentice Hall Series in Artificial Intelligence. Özdamar, K., (1999). Paket programlar ile istatistiksel veri analizi. Kaan Kitabevi, Eskişehir, 2(s 257). Padmanaban, H., (2014). Comparative Analysis of Naive Bayes and Tree Augmented Naïve Bayes Models. Pearl, J., (1995). Causal diagrams for empirical research. Biometrika, 82(4), 669-688. Pilav, A., Rudić, A., Branković, S., ve Djido, V., (2015). Perception of health risks among adolescents due to consumption of cigarettes, alcohol and psychoactive substances in the Federation of Bosnia and Herzegovina. Public health, 129(7), 963-969. Tomczyk, S., Hanewinkel, R., ve Isensee, B., (2015). Multiple substance use patterns in adolescents—A multilevel latent class analysis. Drug and alcohol dependence, 155, 208-214. Turhan, E., Inandi, T., Özer, C., ve Akoglu, S., (2011). Üniversite ögrencilerinde madde kullanimi, siddet ve bazi psikolojik özellikler. Turkish Journal of Public Health, 9(1), 33. Unger, J. B., Soto, D. W., ve Leventhal, A., (2016). E-cigarette use and subsequent cigarette and marijuana use among Hispanic young adults. Drug and Alcohol Dependence. Xu, W. H., Zhang, X. L., Gao, Y. T., Xiang, Y. B., Gao, L. F., Zheng, W., ve Shu, X. O., (2007). Joint effect of cigarette smoking and alcohol consumption on mortality. Preventive medicine, 45(4), 313-319. Wenzel, S. L., Tucker, J. S., Golinelli, D., Green, H. D., ve Zhou, A., (2010). Personal network correlates of alcohol, cigarette, and marijuana use among homeless youth. Drug and alcohol dependence, 112(1), 140-149.
Year 2017, Volume: 26 Issue: 3, 230 - 240, 21.10.2017

Abstract

References

  • Anthony, J. C., ve Echeagaray-Wagner, F., (2000). Epidemiologic analysis of alcohol and tobacco use. Alcohol Research and Health, 24(4), 201-208. Bujarski, S., ve Ray, L. A., (2014). Negative affect is associated with alcohol, but not cigarette use in heavy drinking smokers. Addictive behaviors, 39(12), 1723-1729. Cohn, A., Villanti, A., Richardson, A., Rath, J. M., Williams, V., Stanton, C., & Mermelstein, R. (2015). The association between alcohol, marijuana use, and new and emerging tobacco products in a young adult population. Addictive behaviors, 48, 79-88. Constantinou, A. C., Fenton, N. E., & Neil, M. (2012). pi-football: A Bayesian network model for forecasting Association Football match outcomes. Knowledge-Based Systems, 36, 322-339. Ediş, S., & Ulaş, E. (2017). Çankırı Acıçay-Tatlıçay Havzalarında arazi kullanım türlerinin Bayes Ağları yöntemiyle tahmin edilmesi. Turkish Journal of Forestry, 18(3), 212-218. Ehlke, S. J., ve Cohn, A. M., (2016). Was it the drink? The conditioned association of alcohol and desire to quit smoking on the dual use of little cigars/cigarillos and cigarettes among men and women. Addictive Behaviors,59, 48-51. Friedman,N.,Geiger,D.,& Goldszmidt,M. (1997).Bayesian network classiers. MachineLearning,29,131,163. Friedman, N., Nachman, I., Peéer D., 1999. Learning Bayesian Network Structure fromMassive Datasets: The “Sparse Candidate” Algorithm. Proc. Fifteenth Conf. on Uncertainty in Artificial Intelligence (UAI). Hershberger, A. R., Karyadi, K. A., VanderVeen, J. D. ve Cyders, M. A., (2016). Combined expectancies of alcohol and e-cigarette use relate to higher alcohol use. Addictive behaviors, 52, 13-21. Jackson, N., Denny, S., Sheridan, J., Fleming, T., Clark, T., Teevale, T., ve Ameratunga, S., (2014). Predictors of drinking patterns in adolescence: a latent class analysis. Drug and Alcohol Dependence, 135, 133-139. Kjærulff, T. M., Rivera, F., Jiménez-Iglesias, A., ve Moreno, C., (2014). Perceived quality of social relations and frequent drunkenness: a cross-sectional study of Spanish adolescents. Alcohol and Alcoholism, 49(4), 466-471. Mittal A. ve Kassim A. A., 2007 Bayesian Network Technologies: Applications and Graphical Models. Margaritis, D., (2003). Learning Bayesian Network Model Structure from Data. PhD thesis, School of Computer Science, Carnegie-Mellon University, Pittsburgh, PA. CMU-CS-03-153. Morean, M. E., Kong, G., Camenga, D. R., Cavallo, D. A., Simon, P., ve Krishnan-Sarin, S., (2016). Latent class analysis of current e-cigarette and other substance use in high school students. Drug and alcohol dependence, 161, 292-297. Neapolitan R. E., (2003). Learning Bayesian Networks, Prentice Hall Series in Artificial Intelligence. Özdamar, K., (1999). Paket programlar ile istatistiksel veri analizi. Kaan Kitabevi, Eskişehir, 2(s 257). Padmanaban, H., (2014). Comparative Analysis of Naive Bayes and Tree Augmented Naïve Bayes Models. Pearl, J., (1995). Causal diagrams for empirical research. Biometrika, 82(4), 669-688. Pilav, A., Rudić, A., Branković, S., ve Djido, V., (2015). Perception of health risks among adolescents due to consumption of cigarettes, alcohol and psychoactive substances in the Federation of Bosnia and Herzegovina. Public health, 129(7), 963-969. Tomczyk, S., Hanewinkel, R., ve Isensee, B., (2015). Multiple substance use patterns in adolescents—A multilevel latent class analysis. Drug and alcohol dependence, 155, 208-214. Turhan, E., Inandi, T., Özer, C., ve Akoglu, S., (2011). Üniversite ögrencilerinde madde kullanimi, siddet ve bazi psikolojik özellikler. Turkish Journal of Public Health, 9(1), 33. Unger, J. B., Soto, D. W., ve Leventhal, A., (2016). E-cigarette use and subsequent cigarette and marijuana use among Hispanic young adults. Drug and Alcohol Dependence. Xu, W. H., Zhang, X. L., Gao, Y. T., Xiang, Y. B., Gao, L. F., Zheng, W., ve Shu, X. O., (2007). Joint effect of cigarette smoking and alcohol consumption on mortality. Preventive medicine, 45(4), 313-319. Wenzel, S. L., Tucker, J. S., Golinelli, D., Green, H. D., ve Zhou, A., (2010). Personal network correlates of alcohol, cigarette, and marijuana use among homeless youth. Drug and alcohol dependence, 112(1), 140-149.
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Details

Journal Section Makaleler
Authors

Tuba Koç

Haydar Koç This is me

Efehan Ulaş

Publication Date October 21, 2017
Submission Date July 13, 2017
Published in Issue Year 2017 Volume: 26 Issue: 3

Cite

APA Koç, T., Koç, H., & Ulaş, E. (2017). ÜNİVERSİTE ÖĞRENCİLERİNİN KÖTÜ ALIŞKANLIKLARININ BAYESCİ AĞ YÖNTEMİ İLE BELİRLENMESİ. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 26(3), 230-240.