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Yonnedi, Effa
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Dentistry Health Professions Nursing Public Health Veterinary

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Quantitative analysis in early detection of drug abuser relapse: effectiveness of data-driven predictive models WD, Marryo Borry; Semiarty, Rima; Tabranny, Hasbullah; Yonnedi, Effa
Science Midwifery Vol 12 No 6 (2025): February: Health Sciences and related fields
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/midwifery.v12i6.1811

Abstract

The purpose of this study is to analyze the description of early detection of relapse in drug abuse and to see the relationship between factors that significantly influence relapse in drug abuse. This study uses a quantitative design to describe the implementation of early detection of relapse prevention in drug abuse in Padang City and determine the determinants that are most related to the occurrence of relapse. The results of the statistical test showed that the variables of age, gender, education level, and marital status had a p > value of 0.05, which means that there was no relationship between these variables and the incidence of relapse in drug abusers. However, the variable of employment status had a p < value of 0.05, indicating a relationship between employment status and the incidence of relapse in drug abusers. Furthermore, the variables of age, education level, and employment status met the assumption test with the condition of p < 0.25 at the next stage. The results of the statistical test showed that there was no relationship between the variables of age, gender, education level, and marital status with the incidence of relapse in drug abusers (p > 0.05). However, there was a relationship between employment status and the incidence of relapse (p < 0.05). In addition, the variables of age, education level, and employment status met the assumption test at the next stage (p < 0.25).
Co-Authors Rima Semiarty Tabranny, Hasbullah WD, Marryo Borry