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Identifying and predicting of civil and educational factors associated with suicides in Sri Lanka

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dc.contributor.author Lakmali, S. M. M.
dc.contributor.author Nawarathna, L. S.
dc.date.accessioned 2019-01-29T04:30:59Z
dc.date.available 2019-01-29T04:30:59Z
dc.date.issued 2018
dc.identifier.citation Lakmali, S. M. M. and Nawarathna, L. S. (2018). Identifying and predicting of civil and educational factors associated with suicides in Sri Lanka. Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka. p125. en_US
dc.identifier.uri http://repository.kln.ac.lk/handle/123456789/19750
dc.description.abstract Nowadays, suicides are one of the main social problems experienced by Sri Lanka and almost 4,000 people die by suicide in Sri Lanka every year. It became a significant factor that engaged with education, social status, age, gender and many other factors. Hence, the importance of identifying factors related to suicide and the prediction of future suicides has been emphasized. Therefore, the main objective of this study is to investigate civil and education factors affecting suicidal attempts in Sri Lanka and propose a model to predict the future suicides. For this study, two categories of data were analyzed namely ‘civil status data’ which contain the variables age, gender, civil status and number of suicides, and the ‘educational data’ which contains the variables age, gender, levels of education and number of suicides. The data were collected from the Sri Lanka Police. We modeled the data from 2006 to 2011 and the data from 2014 to 2016 were used for model validation purposes. Quasi Poisson and negative binomial regression models were fitted to identify the major factors affecting suicide in both categories. Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values were used to select the best model. Further, the Mean Absolute Percentage Deviation (MAPD) and Symmetric Mean Absolute Percent Error (SMAPE) were calculated to find the prediction accuracy of the proposed models. The variables age, gender and level of education are significant for the models fitted for educational data, and civil status and gender are significant in the civil status dataset. The highest suicides were recorded for the age groups 21 - 30 and over 61 males, minimallyeducated and married people. Prediction accuracy of both Quasi Poisson models and negative binomial models were above 99% when considering MAPD values. The negative binomial model was considered as the best model, due to its slightly higher accuracy compared to the Quasi Poisson model. A considerable reduction in suicides was obtained in 2010, due to the peaceful situation in Sri Lanka after the civil war. Further, this study indicated that special attention should be given to the teenagers, old-aged and married people to reduce the number of suicides. en_US
dc.language.iso en en_US
dc.publisher Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka en_US
dc.subject Mean absolute percentage deviation en_US
dc.subject negative binomial en_US
dc.subject Quasi Poisson en_US
dc.subject suicides en_US
dc.subject symmetric mean absolute percent error en_US
dc.title Identifying and predicting of civil and educational factors associated with suicides in Sri Lanka en_US
dc.type Article en_US


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