Logistic regression model and Bayesian network of factors related to drug propensity

Document Type : Original Article

Authors

1 Student of Law, Najafabad Branch, Islamic Azad University, Najafabad, Iran

2 Assistant Professor of Law, Najafabad Branch, Islamic Azad University, Najafabad, Iran

3 Associate Professor, Department of Law, Najafabad Branch, Islamic Azad University, Najafabad, Iran

Abstract

Objective: To compare the chances of drug addiction among members of addiction treatment camps and members of the Association of Anonymous Addicts (NA) using logistic regression model and to identify the Bayesian network model of factors related to drug addiction. Method: The research method is descriptive-correlation with logistic regression model and Bayesian network. The population is people who referred to NA or one of the medium-term accommodation centers in Isfahan province in the second half of 1399. 823 questionnaires were provided to the centers as a sample, and 769 questionnaires were analyzed by removing the distortions. Drug addiction was assessed with Wade and Butcher Addiction Readiness Scale α = 0.9. Conclusion: The logistic model showed that the chances of drug addiction in NAs are lower than others. The accuracy of the Bayesian network model algorithm indicates that it can well predict the tendency to use drugs.The accuracy of the Bayesian network model algorithm indicates that it can well predict the tendency to use drugs.

Keywords

Political Sociology of Iran
Volume 3, Issue 4 - Serial Number 12
February 2021
Pages 2202-2188

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