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Relapse Cases Among Drug Addicts Using Logistic Regression Modeling

  • Siti Fairus MokhtarEmail author
  • Fazillah Bosli
  • Norashikin Nasarudin
  • Fathiyah Ahmad@Ahmad Jali
Conference paper

Abstract

The objective of this study is to use this statistical method to determine the factors which are considered to be significant contributors for relapse to happen. Logistic regression analysis is an important tool used in the analysis of the relationship between various explanatory variables and nominal response variables. There are eight predictors in this study. The predictors involved are gender, race, religious, age, level of education, type of drug, reason to drug, and technique to drug. The dependent variable is the status of the drug addict either relapses or not. Four hundred samples were randomly selected from National Anti-Drug Agency (NADA) in Kedah. The finding of the study revealed age and type of drug (Opiat) is highly significant. The coefficient of age and type of drug (Opiat) is 0.114 and 2.360. The older age increase the probability of drug addict to repeat. Type of drug indicates that drug addicts who use Opiat increase the probability to repeat compared to drug addict who use ATS (Amphetamine Type Stimulant (ATS). The findings are beneficial to reduce number of drug addict.

Keywords

Drug factor relapse Logistic regression analysis 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Siti Fairus Mokhtar
    • 1
    Email author
  • Fazillah Bosli
    • 1
  • Norashikin Nasarudin
    • 1
  • Fathiyah Ahmad@Ahmad Jali
    • 1
  1. 1.Universiti Teknologi MARAShah AlamMalaysia

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