Relapse Cases Among Drug Addicts Using Logistic Regression Modeling

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


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.


Drug factor relapse Logistic regression analysis 


  1. 1.
    Karofi, U.A.: Drug abuse and criminal behaviour in Penang, Malaysia: a multivariate analysis. Bangladesh e-Journal Sociol. 2(2), 90–116 (2005)Google Scholar
  2. 2.
    Nokman, F.S.: More than 130,000 drug addicts in Malaysia to date, figures show. New Straits Times. Retrieved from, 19 April 2016
  3. 3.
    Amiri, M., Taheri, Z., Hosseini, M., Mohsenpour, M., Davidson, P.M.: Factors affecting tendency for drug abuse in people attending addiction treatment centres: a quatitative content analysis. J. Addict. Res. Ther. 7(2), 1–4 (2016)Google Scholar
  4. 4.
    Tam, C.L., Foo, Y.C.: A qualitative study on drug abuse relapse in Malaysia: contributory factors and treatment effectiveness. Int. J. Collab. Res. Intern. Med. Public Health 5(4), 217–232 (2013)Google Scholar
  5. 5.
    Foo, Y.C., Tam, C.L., Lee. H. L.: Family factors and peer influence in drug abuse: a study in rehabilitation centre. Int. J. Collab. Res. Intern. Med. Public Health 4(3), 190–201(2012)Google Scholar
  6. 6.
    Mohamed, M.N.: Peranan & Penglibatan Keluarga dan Masyarakat Dalam Pencegahan Penagihan Berulang. Jurnal PERKAMA. Bil. 6. ISSN 0127/6301. Terbitan Persatuan Kaunseling Malaysia (1996)Google Scholar
  7. 7.
    Ibrahim, F., Kumar, N.: Factors effecting drug relapse in Malaysia: an empirical evidence. J. Asian Soc. Sci. 5(12), 37–44 (2009)Google Scholar
  8. 8.
    Ibrahim, F., Kumar, N.: The influence of community on relapse addiction to drug use: evidence from Malaysia. Eur. J. Soc. Sci. 11(3), 471–476 (2009)Google Scholar
  9. 9.
    Chie, Q.T., Tam, C.L., Gregory, B., Hoang, M.D., Khairuddin, R.: Substance abuse, relapse, and treatment program evaluation in Malaysia: perspective of rehab patients and staff using the mixed method approach. Front. Psychiatry 7(90), 1–13 (2016)Google Scholar
  10. 10.
    Ismail, M.T., Alias, S.N.S.: Binary logistic regression modelling: measuring the probability of relapse cases among drug addict. In: Proceedings of the 21st National Symposium of Mathematical Sciences (SKSM21). AIP Conference Proceeding, vol. 1605, pp. 792–797 (2014)Google Scholar
  11. 11.
    Hair, J.F., Black, B., Babin, B., Anderson, R.E., Tatham, R.L.: Multivariate Data Analysis, vol. 6. Prentice-Hall, Upper Saddle River, NJ (2006)Google Scholar
  12. 12.
    Wegman, M.P., Altice, F.L., Kaur, S., Rajandaran, V., Osornprasop, S., Wilson, D., Wilson, D.P., Kamarulzaman, A.: Relapse to opioid use in opioid-dependent individuals released from compulsory drug detention centres compared with those from voluntary methadone treatment centres in Malaysia: a two-arm, prospective observational study. Lancet Glob. Health 5, e198–207 (2017)Google Scholar

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

Personalised recommendations