GET THE APP
Received February 14, 2012; Accepted March 16, 2012; Published March 20, 2012
Citation: Mohammadpoorasl A, Fakhari A, Akbari H, Karimi F, Arshadi Bostanabad M, et al.(2012) Addiction Relapse and Its Predictors: A Prospective Study. J Addict Res Ther 3:122. doi:10.4172/2155-6105.1000122
Copyright: © 2012 Mohammadpoorasl A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Visit for more related articles at Journal of Addiction Research & Therapy
Drug addiction has been recognized as a chronic, relapsing illness for several years. This study aims to estimate relapse rate and determine its predictors in Iran. In this prospective study, we studied 436 patients referring voluntarily to an addiction treatment center in Maragheh, Iran. We completed two questionnaires at the beginning of study and six months after cessation by conducting interviews with patients by trained interviewers. Logistic regression model was used in order to identify the predictors of relapse in our sample. After six months follow-up, we found that the relapse rate was 64.0% (CI 95%: 59.3-68.4). The results of logistic model indicate that smoking (OR=12.15), having a drug user in the family (OR=2.54), having lower hope to quit (OR=2.61), unemployment (OR=2.78) and stay connected with drug user friends after quitting (OR=46.7) were factors associated with relapse. This study similar to other studies showed a high relapse rate and determined some of its risk factors among addicts.
Addiction; Relapse; Longitudinal study; Substance abuse; Iran
Substance abuse is a chronic, relapsing illness. A large proportion of individuals who have been treated for addiction tend to re-use drug shortly after treatment [1,2]. Factors such as stress, depression, anxiety, positive mood, social pressure, adverse life events, work stress, marital conflict, family dysfunction, and a lower level of social support have been reported as relapse reasons [3-5].
Despite the use of any type of opiate drugs is illegal in Iran, drug addiction is one of the main social disorders in this country. This is due to the fact that Iran lies on a major drug route between Afghanistan -- the world’s biggest producer of opium—and opiate consumers in Europe. Consequently, this increases the availability of the opium and heroin in Iran. It is estimated that more than 2 million Iranian are addicted to opium and/or heroin and the number is rising . Therefore, it is necessary to develop efficient interventions, such as relapse prevention programs. In order to have effective program one need to determine predictors of relapse. This study aims to provide some information on the relapse rate and to determine its predictors in individuals who addicted to opium and opiate drugs.
In this prospective study, 436 patients were studied. The sample was drawn from patients referring voluntarily to an addiction treatment center in Maragheh, a city in northwest of Iran. We entered all referred patients to the center into the study from September 2008 until our target sample size met. Patients who did not become abstinent or relapsed within the treatment period were excluded from study.
A questionnaire that included questions about demographic, personal, and environmental characteristics was completed by conducting an interview with patients by trained interviewers. Patients were followed up for 6 months after cessation for assessing of relapse and patient’s condition in that period. In this study, “relapse” was defined as: “re-use of drugs during the 6 months after quit date”. Our method to characterize relapse was as follow: If a patient himself has announced that he consumed any type of opiate drugs during the 6-month follow-up period, we considered him patient as relapse. Otherwise, we asked from one of his family members (who live with patient in a house) whether or not the patient used drug within the past 6 months. If the answer is positive, we considered the patient as relapse. Ethical Committee of Tabriz University of Medical Sciences has approved this study and all patients signed an informed consent.
The logistic regression model was used to determine the predictors of relapse. Thechi-square test and independent t-test were used to evaluate the statistical significance of each predictor. We performed our analysis using Stata-10 and SPSS-16 statistical package programs.
The descriptive statistics showed that our sample consists of relatively young individual people with an average age of 31.38 (SD, 7.61) years (ranges 18 to 55 years), and only 1.4 percent of subjects were female. Seven percent of individuals in our sample had university degree and 50.2 percent were unemployed.
Six out of 436 subjects in the study had unknown status because of loss to follow-up, 155 (36.0%, CI 95%: 31.6-40.7) subjects were successful quitters (abstinent), and 275 (64.0%, CI 95%: 59.3-68.4) subjects relapsed after quitting. The average age of abstinent and relapsed individuals were 31.7 (SD, 6.9) and 31.2 (SD, 8.0), respectively (P-value=0.459). The mean age of drug abuse unset of the abstinent and relapsed subjects were 20.3 (SD, 3.0) and 20.0 (SD, 2.8), respectively (P-value=0.401). Table 1 reports association of demographic and key characteristics of subjects with quitting status (abstinent or relapse). As shown in this table, all variables have significant association with quit status, with the exception of educational level and marital status.
|Unemployed & housewife||53(25.5)||155(74.5)|
|Governmental employee & retired||7(36.8)||12(63.2)|
|Type of consumed drug|
|More than one drug||45(49.5)||46(50.5)|
|First consumed drug (other than cigarettes and alcohol)|
|Have drug user in the family|
|Having a family disputes|
|Very high or high||4(10.0)||36(90.0)||P<0.001|
|Hoping to quit|
|Somewhat or low||3(8.6)||32(91.4)|
|Employment status after quitting|
|Stay connected with drug-user friends after quitting|
Table 1: Percentage of demographic and key characteristics of subjects by quit status (abstinentor relapse).
We employed a logistic model in order to evaluate the relationship between significant variables in univariate analysis and relapse. The results of this analysis presented in Table 2. The results indicate that smoking (OR=12.15), having drug user in the family (OR=2.54), having lower hope to quit (OR=2.61), unemployment (OR=2.78) and stay connected with drug user friends after quitting (OR=46.7) were factors associated with relapse.
Results of several studies have suggested that relapse is common after treatment for drug addiction. In a ten-year prospective followup study, Xie et al.  have showed that approximately one-third of clients who were in full remission relapsed in the first year, and twothirds relapsed over the full follow-up period. Moore et al.  have reported that 71% who achieved 2 weeks of continuous abstinence during outpatient treatment for marijuana dependence relapsed to marijuana use within 6 months. Furthermore, Smyth et al.  have reported 91% relapse rate. Our study also confirms that drug relapse is a common phenomenon among patients. However, we found relatively a high rate of relapse (64.0%) in our 6 months follow-up study. These findings support Rounsaville’s claim that relapse and relapse prevention represent the major challenges faced by clinicians who work with addicts .
This study also determined the association between relapse and some of individual and socio-environmental variables. Although numerous studies demonstrated that younger age is related to relapse to addiction [8,10], results of our study showed no difference in the average age of relapsed and non-relapsed patients. In contrast with some studies that found that low literacy is associated with relapse to addiction [2,11], our results showed that the relapse rates are similar at different levels of educational. Moreover, unlike the results of a study by Walton et al. , this study did not show that being single is associate with relapse.
The results of logistic regression indicated that having drug user in the family (OR=2.61), being unemployed (OR=2.78), and stay connected with drug user friends after quitting (OR=46.7) were main factors associated with relapse. These results are consistent with some of the previous studies [5,10-12]. Results also showed that smoking (OR=12.15) and having lower hope to quit (OR=2.61) were two other factors that determined relapse.
We acknowledge that, there are several aspects in this study that limit the applicability of these findings. First limitation of the study relates to the duration of time between patient discharges from addiction treatment center and interview (6 months) for assessing relapse and events happening at this time. This may contribute to retrospective recall bias by patients. If recall bias were present it would have reduced our ability to detect significant associations between relapse and the factors which predict it. A second limitation relates to the fact that relapse is increasingly recognized as a complex product of a dynamic interaction of many more distal, intermediate, proximal and transitional factors than those relatively few factors considered by this study. The third limitation of the study is related to generalizability of findings. This can be due to the reason that demographic and socioeconomic characteristics of patients attending drug treatment centers might be different from those who do not refer to these centers for quitting. Thus, we cannot generalize our findings to those who attempt to quit drug without attending treatment centers. In conclusion, this study similar to other studies has shown high relapse rate and determined some of its risk factors among addicts.
|Variable||Odds Ratio||CI (95%)||P-value|
|First consumed drug
(other than cigarettes and alcohol)
|Have drug user in the family||2.54||1.05-7.65||0.026|
|Having lower hope to quit||2.61||1.05-5.48||0.036|
|Unemployed after quitting||2.78||1.17- 7.41||0.032|
|Stayed connected with drug user friends after quitting||46.7||12.7-80.9||P<0.001|
Table 2: Logistic regression analysis of the relationship between “relapse” and “risk variables”.
This work was supported by research grant from Research Deputy of Tabriz University of Medical Sciences. Thereby their support is being greatly appreciated.
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals