Year : 2021  |  Volume : 63  |  Issue : 4  |  Page : 355--365

Predictors of retention in the treatment for opioid dependence: A prospective, observational study from India

Anish Shouan, Abhishek Ghosh, Shubh Mohan Singh, Debasish Basu, Surendra Kumar Mattoo 
 Department of Psychiatry, Post Graduate Institute of Medical Education and Research, Chandigarh, India

Correspondence Address:
Surendra Kumar Mattoo
Department of Psychiatry, Post Graduate Institute of Medical Education and Research, Chandigarh - 160 012


Background: Literature on a longitudinal study of the determinants of treatment retention for patients with opioid dependence is limited. Aim: To find out patient- and treatment-related (buprenorphine-naloxone-assisted treatment [BNX treatment] versus naltrexone treatment) predictors for retention in maintenance treatment. Materials and Methods: A total of 100 participants with opioid dependence were recruited by convenience sampling. The primary outcome was treatment retention – 3 months and 6 months postentry into maintenance treatment. Multiple assessments were done for the severity of opioid dependence and withdrawal, high-risk behavior, quality of life, and recovery capital – baseline and 3 and 6 months. The secondary outcome was to assess the change observed in the above-listed variables. Results and Conclusions: Bivariate analysis across retained and the dropout groups brought out significant differences for some (type of opioids and route of administration) but not for other (age, employment, and education) patient-related factors. Multivariate analysis, adjusting for the type of maintenance treatment, rendered these associations statistically insignificant. BNX-based treatment (compared to naltrexone maintenance) was the most significant predictor of treatment retention both at the end of 3 months and 6 months. Even after controlling for the severity of opioid dependence and withdrawal, type and route of opioid use, and high-risk behavior, patients on BNX were eleven times (14 times at the end of 6 months) more likely to be retained in the treatment. BNX group had significant improvements in the domains of recovery capital, quality of life, addiction severity, and severity of opioid dependence. There is a need to scale up the BNX-assisted treatment program in India and elsewhere.

How to cite this article:
Shouan A, Ghosh A, Singh SM, Basu D, Mattoo SK. Predictors of retention in the treatment for opioid dependence: A prospective, observational study from India.Indian J Psychiatry 2021;63:355-365

How to cite this URL:
Shouan A, Ghosh A, Singh SM, Basu D, Mattoo SK. Predictors of retention in the treatment for opioid dependence: A prospective, observational study from India. Indian J Psychiatry [serial online] 2021 [cited 2021 Oct 17 ];63:355-365
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Full Text


Globally, opioid-dependent people are estimated to number 40.5 million and to suffer the largest proportion of mortality and disability due to drug use disorders.[1],[2] The Magnitude of Substance Use survey estimated 7.7 million people with opioid use disorders in India.[3] In India, agonist-based treatment is primarily done using buprenorphine (and buprenorphine-naloxone [BNX] fixed-dose combination).[4],[5] However, the availability of BNX-assisted treatment is limited, and a large majority of patients would receive antagonist (naltrexone)-based treatment.

Studies have used treatment retention both as a process and an outcome variable.[6] Treatment retention was associated with lower crime rates, decreased risk of relapse, and higher employment.[7] Dropout from treatment, on the other hand, had unfavorable outcomes – higher risk of relapse, legal and financial problems, readmission, and poorer health.[8],[9],[10] Systematic reviews on the predictors of dropout from treatment had identified patient-related demographic (ethnic background, socioeconomic status, and age) and clinical (number of days of use, type of substance) factors.[11],[12] Nevertheless, the authors noted significant inconsistency in the literature. The treatment-related factors as predictors of retention (or dropout) were less studied.[11] In addition, retention was seldom studied in a group with a specific substance use disorder. It is important to note that the type of substance use predicts treatment retention.[12] Both of these might explain the inconsistency. There were a couple of published studies from India with the objective to determine the risk factors for dropout from treatment. All these studies were retrospective.[13],[14],[15] Two of these studies were on patients with opioid dependence. The study by Bandawar et al. reported that patients on buprenorphine were four times more likely to be retained in the treatment than those on naltrexone maintenance.[15] However, this study did not look into the other potential predictors and did not control for the same. The second study, done on emerging adults on buprenorphine maintenance, hence, lacked a group on naltrexone.[13] Therefore, despite the magnitude of the problem in India, there is limited research on the predictors of treatment retention in patients with opioid dependence. There is a need for a prospective study to determine the potential patient- and treatment-related predictors (with patients on BNX treatment or naltrexone treatment) of retention.

 Materials and Methods

Study settings

Subjects were recruited from a tertiary care addiction treatment center in Northern India. At this center, the largest section of patients come from the state of Punjab, one of the northern states with the highest prevalence of opioid dependence in the country.[3],[16] This center provides opioid withdrawal management as well as maintenance treatment services on an inpatient and outpatient basis. For maintenance treatment, both the BNX treatment and antagonist (naltrexone)-based treatments are available. The decision of maintenance treatment is taken through shared decision-making between the treating psychiatrist, patient, and family members. Therefore, the investigator did not influence the treatment decision in any way. All patients started on maintenance with BNX are required to visit the clinic once a week for the first 6 months. This group of patients also receives weekly group counseling with the goal of management of craving, developing, and improving social relationships, and management of anger and stress. A monthly urine chromatographic immunoassay is also done routinely. The BNX treatment broadly follows a recovery-oriented approach with personal recovery as the final goal (reintegration of the person with opioid dependence into the family and society and ensuring functional independence). Objective goals are decided by the persons themselves. Recovery goals are evaluated periodically to see the progress made, facilitate to attain the goals, or recalibrate the previous goals based on the present performance. BNX treatment is neither time limited nor time unlimited, but “goal directed.” Patients are offered to discontinue BNX treatment after the predetermined goals (recovery) are achieved, and the decision to come off the treatment is always by mutual agreement. There is a tentative time target of 1–2 years in which the person is expected to reach the goal of recovery; however, the duration of treatment changes according to the recovery status.[17]

The group on naltrexone maintenance receives routine outpatient based care, at an average frequency of once in a fortnight for the initial month and monthly thereafter.

Study design and sample recruitment

A total of 100 participants were recruited using a convenience sampling method. All subjects were recruited over 12 months (from July 2015 to June 2016). and the data analysis was completed by the end of December 2016. The total number of patients registered during this 1 year was 2800. The largest proportion (around 50%) of patients had opioid dependence. A substantially larger proportion of patients were started on naltrexone (~90%–95% of all patients on maintenance medication) in our clinic. Therefore, to attain balanced recruitment from groups receiving BNX and naltrexone maintenance, convenience sampling was done. Fifty participants were recruited from each group, if they fulfilled the inclusion criteria, i.e. diagnosed with opioid dependence syndrome as per ICD-10 (World Health Organization, 1992), aged 18–60 years, and were taking recovery-oriented BNX treatment or naltrexone maintenance treatment. Most of the participants were outpatients (n = 84). Participants were excluded from the study if they were unwilling or unable to give consent, having dual diagnosis (opioid dependence with severe mental illness, viz., schizophrenia, bipolar disorder, and depressive disorders assessed and excluded by Mini International Neuropsychiatric Interveiw [MINI]),[18] concomitantly using high-dose alcohol or benzodiazepines, and were hypersensitive to buprenorphine. A total of 100 participants were approached, and all of them were included after written informed consent. Clearance was taken from the institutional ethics committee before recruiting the cases.

Study variables

The participants were assessed on a sociodemographic sheet and a clinical profile sheet designed specifically for this patient population. Other variables such as the severity of opioid dependence, high-risk behavior, quality of life, the severity of opioid addiction, and recovery capital were assessed at baseline using appropriate scales:

Mini-International Neuropsychiatric Interview

It is a brief structured interview for the diagnosis of psychiatric disorders. It is administered in 15–20 min, and it is divided into modules corresponding to diagnostic categories. It elicits all the symptoms listed in the symptom criteria for DSM-IV and ICD 10 for major Axis I diagnostic categories, one Axis II disorder, and for suicidality. Its reliability for various psychiatric disorders ranges from good to excellent (kappa = 0.51–0.90).[18]

Severity of Opioid Dependence Questionnaire

It is a 4-point scale (0–3), with 20 items and a maximum score of 60. It measures quantity and pattern, physical withdrawal, withdrawal relief drug usage, rapidity of reinstatement, history of opiate use, narrowing of drug repertoire, tolerance, and subjective sense of habit severity. Its correlation with severity of opiate use and with subjective feelings of dependence is >0.95.[19]

Risk Behavior Inventory

This scale assesses high-risk behaviors through information on demographics, sexual practices, substance abuse, and risk behaviors involving the use of needles and prostitutionism.[20] It is a self-administered scale and has 13 items and takes 5 min to complete.

Clinical Opiate Withdrawal Severity Scale

It is a clinician-administered scale with 11 items, which assesses the level of physical dependence on opioids in terms of mild (5–12), moderate (13–24), moderately to severe (25–36), or severe withdrawal (>36) symptom categories.[21]

Assessment of Recovery Capital

Assessment of Recovery Capital (ARC) is a small and easy-to-administer tool that measures recovery capital.[22] With good psychometric properties, it is useful for deficit-based assessment and outcome monitoring for substance-dependent individuals. It assesses the social, physical, human, and cultural capital in an individual. It tells about the areas in which the patient is lacking and improving. It quantifies each situation statement from 5 to 1.

WHOQuality of Life-BREF (Hindi version)

The scale has 26 items scored from 1 to 5 with a total score range of 26–130. The 26 items are clubbed into four domains of QOL, namely physical health, psychological health, social relationship, and environment; there is an additional measure for general well-being.[23] The psychometric properties of the BREF version are comparable to those of the full version. It has good discriminant validity, concurrent validity, internal consistency, and test–retest reliability.

Addiction Severity Index

Addiction Severity Index (ASI) is a reliable and valid instrument that evaluates substance-abusing patients' functioning in the following seven domains: medical conditions, employment/support, use of alcohol and drugs, legal issues, family history, family/social relationship, and psychiatric disorders.[24] ASI (5.0) screens for problems and impairments accompanying drug abuse, i.e., interpersonal, medical conditions such as hepatitis B and C, HIV/AIDS, alcoholic liver disease, acute MI, and metabolic complications.[25] It covers the preceding 30 days with score ratings ranging 0–4.

Outcome measures

Our primary objective was to determine the patient- and treatment-related predictors of retention at 3 and 6 months postentry into maintenance treatment. The secondary objective was to observe the changes in other outcome variables (e.g. recovery capital, ASI, quality of life, and high-risk behavior) in participants on BNX or naltrexone treatment at 3 and 6 months.

Study procedure

Patients attending the outpatient or admitted to the inpatient were approached and explained about the study. Those who gave the informed consent were assessed on MINI to rule out any severe mental illness. Those fulfilling the diagnosis were further assessed on inclusion and exclusion criteria. All the included subjects in the study were assessed at baseline within 2 weeks of starting BNX or naltrexone maintenance treatment. The participants were observed prospectively and the re-assessments were done at 3 months (±2 weeks) and 6 months (±2 weeks) follow-up period. Information regarding the identity of patients who were started on maintenance treatment was taken from a detailed log kept regarding these patients in our outpatient clinic or liaison with the prescribing psychiatrist.

Statistical analysis

Data were analyzed using IBM SPSS Statistics for Windows, version 21.0 (IBM Corp., Armonk, NY, USA). Descriptive analysis in terms of frequency and percentages was used for categorical sociodemographic variables – gender, religion, marital status, locality, and clinical variables, and mean and standard deviation with range for continuous sociodemographic variables – age, education, clinical variables, etc. The subjects were divided into two groups based on the treatment retention at 3 months and 6 months. We used independent sample t-tests (i.e., age, years of education, age of first use of opioids, SODQ, ARC, WHOQOL, and ASI scores), Mann–Whitney U-tests (i.e., duration of opioid use, RBI and COWS scores), and Chi-square tests (i.e., occupation, religion, family, locality, types of opioids, routes of administration, and maintenance treatment) to compare the demographic and clinical characteristics of the groups retained and dropped out at 3 months. Similar comparison was also done for 6 months. Variables that showed significant difference (i.e., type of opioids, routes of administration, maintenance treatment, SODQ, RBI, and COWS scores) between the two groups were entered in a step-wise logistic regression model. We analyzed the change in the RBI, SODQ, COWS, WHOQOL, ASI, and ARC scores in the BNX treatment group by one-way repeated-measures analysis of variance. We have done a per-protocol analysis and an intention-to-treat analysis (by replacing missing values by carrying forward the last observations in the respective scales). We could not perform similar analysis for the NTX group because of the very high attrition rate (88% and 96% at 3 and 6 months, respectively).


A total of 100 participants were recruited for the study. The participants were followed up for 6 months. Assessments were done thrice – baseline and at 3 and 6 months.

Sociodemography and clinical variables

The average age of the participants was 30.82 (±10.27) years. The mean years of education of the group was 11.63 (±2.56) years. Around half of the participants were from rural areas (55%) and a nonnuclear family setup (54%). Most of the participants were gainfully employed (58%) and of non-Hindu religions (59%) such as Sikhism, Islam, and Christianity.

The mean age of initiation of opioid use was 24.49 (±8.26) years, and the mean duration of opioid use was 6.45 (±6.51) years. For 52% of the participants, the primary opioid was heroin, whereas 51% of heroin users were intravenous users. By design, half of the participants were each on BNX treatment and oral naltrexone maintenance treatment. Participants taking naltrexone were on a standard 50-mg dose taken orally once a day; the mean dose of BNX treatment was 4.90 (3.38) mg/day sublingually.

Average baseline scores for measures of severity of opioid dependence, high-risk behavior, severity of opioid withdrawal, recovery capital, quality of life, and addiction severity using various rating scales are reported in [Table 1].{Table 1}

Treatment retention

Of the 100 participants, 37% and 21%, respectively, were followed up at 3-month and 6-month follow-up period.

Comparison of groups dropped out and retained at 3 months

The baseline sociodemographic and clinical characteristics were compared between the groups who dropped out and retained in the treatment at 3 months.

Group of participants who dropped out of treatment at 3 months were those who were started on naltrexone maintenance treatment (P < 0.001***); had heroin as a primary opioid of choice (P = 0.048*); had nonintravenous route of administration of the opioid (P = 0.003**); and had lower baseline SODQ (P = 0.001***), RBI (P = 0.006**), and COWS scores (P = 0.026*), as shown in [Table 2].{Table 2}

Comparison of groups dropped out and retained at 6 months

The comparison of the baseline sociodemographic and clinical characteristics was also done (between the groups dropped out and retained in the treatment) at 6 months. No significant difference was observed in any of the demographic and clinical profiles except the choice of maintenance treatment. Participants on naltrexone maintenance were significantly more likely to drop out (P < 0.001) from the treatment (than those on buprenorphine-based maintenance).

The results are enumerated in [Table 3].{Table 3}

Predictors of treatment retention at 3 months

A binary logistic regression was run to find out the independent predictors of treatment retention at 3 months of treatment. Clinical and demographic variables observed to be significant in the bivariate analysis were entered in the logistic regression model. Interestingly, the type and route of opioid use and SODQ and RBI scores did not predict the treatment retention at 3 months. However, the choice of maintenance treatment and the severity of clinical withdrawal at the baseline predicted dropout at 3 months. Even after controlling for the other factors (type of opioid use, route of opioid use, baseline SODQ score, baseline RBI score, and baseline COWS score), the odds of treatment retention was 11 times (P < 0.001***; R: 11.431; 95% confidence interval [CI]: 3.19–41) higher in the BNX maintenance group, as compared to that of the naltrexone group. Participants with lower severity of opioid withdrawal at the baseline were more likely to drop out from treatment as well. Nevertheless, the odds were smaller (P = 0.044*; odds ratio [OR]: 1.192; 95% CI: 1.005–1.415) than the choice of maintenance medication. The variance (Nagelkerke R2) explained by the model was 40.8%.

Predictors of treatment retention at 6 months

Similar binary logistic regression was also done to examine the predictors of treatment retention at 6 months. We had tested two models of logistic regression – one with only the choice of the maintenance medication entered in the equation and the one with other clinical variables (type and route of opioid use and COWS, RBI, and SODQ scores) entered alongside.

In both the regression models (with or without controlling for the “other” clinical variables), the choice of maintenance treatment was observed to be a significant predictor even at 6-month follow-up. In the first model, BNX maintenance treatment increased the odds of treatment retention at 6 months by 14 times (P = 0.001***; OR: 14.7; 95% CI: 3.200–67.620). In the second model, controlling for other clinical variables, the odds of treatment retention in participants on BNX increased further (P < 0.001; OR: 33.3; 95% CI 5.1–216.8).

The variances (Nagelkerke R2) explained by the first and second models were 27.7% and 32.6%, respectively.

The results of the first and the second model are displayed in [Table 4].{Table 4}

Change in the other outcome variables among participants on buprenorphine-naloxone treatment over 6 months

Of the participants taking BNX treatment over 6 months, 19 (38%) participants were retained. On analyzing the change in other outcome variables, i.e., high-risk behaviour (RBI), quality of life (all physical, psychological, social relationship, and environmental), severity of opioid dependence (SODQ), and recovery capital (ARC), significant improvement was observed between the baseline and the 3 months and 6 months (but there were no significant changes between 3 and 6 months). Similar results were observed when the last observations were carried forward and an intention-to-treat analysis was done by including all the fifty participants. [Table 5] shows the per-protocol and the intention-to-treat analyses.,{Table 5}


To the best of our knowledge, this is the first prospective study from India exploring the predictors of treatment retention over 6 months in patients with opioid dependence. In addition to the usual sociodemographic (e.g., age, employment, years of education, and family type) and clinical (type, duration, and route of opioid use) variables, this study had looked into the roles of the recovery capital, addiction severity, severity of opioid withdrawal, quality of life, and high-risk behaviors as predictors. Most importantly, treatment-related factors (BNX vs. naltrexone treatment) were studied as well. Follow-up assessments were done twice; hence, it was possible to determine the clinical course.

BNX-based treatment (compared to naltrexone maintenance) came out to be the most significant predictor of treatment retention both at the end of 3 months and 6 months. Even after controlling for the severity of opioid dependence and withdrawal, type and route of opioid use, and high-risk behavior, patients on BNX treatment were eleven times (14 times at the end of 6 months) more likely to be retained in the treatment. Comparison of the BNX and NTX groups showed, except for the place of residence (BNX group had larger representation from the urban areas), type of opioid use (higher proportion of heroin users in the BNX group), and route of administration (higher proportion of injection drug use in BNX group), these two groups did not differ in other demographic and clinical characteristics [Supplementary Table 1]. The differences in these clinical profiles could be understood by our clinic's selection criteria followed for the BNX treatment. Nevertheless, higher odds of treatment retention despite these seemingly unfavorable clinical characteristics indicates the superiority of BNX treatment over naltrexone. The result was similar to a previous study from India, in which the odds of treatment retention was 4.5 times more than that of the naltrexone treatment;[15] however, this was a retrospective study and did not control for other potential confounding variables. Another prospective study from India comparing treatment retention rates between BNX and naltrexone treatment over 1 year reported rates of 68% and 42%, respectively.[26] Both these studies were from the same center in Southern India, where pharmaceutical opioids were the predominant opioid misused. Our study was based at a center in Northern India that caters largely to a catchment area with the highest prevalence of opioid use disorders in the country[3],[16] and heroin as the most commonly abused opioid. Therefore, we believe the present study added to the existing literature by collecting evidence from a different part of the country with a different profile of opioid users and an improved methodology. Studies from elsewhere have reported 6-month retention rates lower for naltrexone-based treatment (10%–60%)[27] and higher for buprenorphine-based treatment (41%–74%).[28] Nonetheless, only a few head-to-head trials were comparing the retention rates between the agonist and antagonist-based treatment. One such study from Malaysia showed retention was two times higher in the buprenorphine group.[29] However, these results were from randomized clinical trials, which would use measures (e.g., patients' contact, patients' convenience, and monitoring) to encourage treatment retention.[30] The present study being controlled and observational, the retention rates were lower (62% and 12% at the end of 3 months and 32% and 4% at the end of 6 months, for BNX and naltrexone, respectively) for both the treatment groups. Nonetheless, the rate was comparable to another retrospective study from North India, done on emerging adults on buprenorphine-based maintenance treatment.[13] Existing literature on the predictors of treatment retention identified the roles of age, type, and routes of substance use; employment; socioeconomic status; and cognitive status.[11],[12],[13] In our study, some of these factors (e.g., type of opioids and route of administration) but not others (age, employment, and education) were observed to be significantly different between the retained and the dropout groups in the bivariate analysis. However, the associations were rendered statistically insignificant following the multivariate analysis, adjusting for the type of maintenance treatment.[INLINE:1]

The next question was, whether the higher treatment retention in the BNX-based treatment group was associated with improved outcome in terms of other clinical parameters. Significant improvements were observed in the domains of recovery capital, quality of life (all four domains), addiction severity, and severity of opioid dependence between the baseline and 3 months (and 6 months). Improvement in the recovery capital was in line with the recovery-oriented BNX treatment, practiced in the clinic.[31] Recovery-oriented BNX treatment goes beyond abstinence and focuses on three major domains – agency (a sense of control over one's life), opportunity (being part of family and larger society), and hope.[32] The recovery capital prospectively predicted a better outcome in a study among patients with heroin and cocaine dependence.[33] Therefore, in the present study, improvement of the recovery capital with BNX treatment would suggest a journey toward recovery. A systematic review of 13 opioid agonist treatment programs from low- and middle-income countries reported that agonist management was associated with a significant decrease in the addiction severity and improvements in all the domains of quality of life.[34] Similar results were seen from a multicentric Indian study of patients on BNX-based treatment.[35] Thus, the results of the present study were in line with the existing evidence. Opioid agonist treatment has also been shown to reduce injection-related (frequency of injection, sharing injection equipment) and possibly high-risk sexual behavior. However, most of the studies included in this Cochrane review were on methadone maintenance.[36] A multi-site cohort study from India among patients on BNX treatment showed a reduction in risk behaviors (both injection and sexual) following 6 months and 9 months of treatment.[37] The present study too had similar results.

Overall, the present study suggested BNX treatment for opioid dependence not only increased the odds of treatment retention but also resulted in significant improvement in the quality of life, promoted recovery, reduced addiction severity, and high-risk behaviors. We would like to bring home a few points here. Firstly, there is a need to scale up the BNX treatment program in India and elsewhere. The estimated number of recipients of BNX treatment in India was 25,000–30,000, which would constitute not more than 5% of patients with opioid dependence in the country.[4] In a high treatment coverage area, 40% of the population with opioid dependence should receive BNX treatment.[2] The glaring gap in the treatment coverage calls for a rapid scaleup of BNX treatment. Secondly, our study suggested that a recovery-oriented BNX treatment helps to improve the recovery capital and perhaps facilitates the journey toward recovery.[17] Nonetheless, we agree that neither the methodology nor the duration of the present study is optimal to examine the effectiveness of recovery-oriented BNX treatment. Thirdly, prescription of naltrexone maintenance with routine clinical care is not enough. Perhaps, there is a need to add behavioral intervention (e.g., contingency management) to naltrexone maintenance.[38]

The present study has the following limitations: the sample size was 100 and no a priori power calculation was done because it was an exploratory and observational study; hence we were not sure about the number of predictors that actually might have to be tested in the regression analysis. However, in the end, we had to enter six potential predictors in the regression model. We did a post hoc power calculation. For the 3-month and 6-month predictors of treatment retention models, the statistical power was 0.99 and 0.95, respectively.[39] The wide 95% CI of the odds ratios would suggest imprecision. but the lower range of the CIs for the odds of treatment retention with BNX based treatment was three. Thus, a higher odds of treatment retention of patients on BNX treatment was unequivocal. All the participants in the present study were men. Previous two studies from our center collating data of more than 30 years reported that 99.5% treatment-seeking patients were men.[14],[40] Therefore, “all-male participants” in our study was reflective of the general treatment-seeking pattern in the region. The study results were based on a single center, which likely caters to severe opioid use disorders. Therefore, these results should not be generalized to other population contexts. Finally, the higher odds of treatment retention in the BNX group should be interpreted in light of the following: BNX-based treatment was accompanied by weekly group counseling sessions and consultation with a psychiatrist every week. On the other hand, patients on naltrexone had received routine medical and psycho-social care every fortnightly or monthly. Therefore, the higher odds of treatment retention in the BNX treatment group could be attributed to both the medication (i.e., BNX) and group counseling.

In sum, BNX treatment, even after controlling for the severity, type, and route of administration, predicted higher retention of patients with opioid dependence. BNX treatment facilitated recovery, improved quality of life, anf reduced the severity of addiction and frequency of high-risk behavior.


AS was responsible for data collection, data analysis, manuscript writing, manuscript editing, and manuscript approval. AG was involved in conceptualization, manuscript writing, manuscript editing, and manuscript approval. SMS, DB, and SKM were involved in conceptualization, manuscript editing, and manuscript approval.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.


1GBD 2016 Alcohol and Drug Use Collaborators. The global burden of disease attributable to alcohol and drug use in 195 countries and territories, 1990-2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet Psychiatry 2018;5:987-1012.
2Degenhardt L, Grebely J, Stone J, Hickman M, Vickerman P, Marshall BD, et al. Global patterns of opioid use and dependence: Harms to populations, interventions, and future action. Lancet 2019;394:1560-79.
3Ambekar A, Agrawal A, Rao R, Mishra A, Khandelwal S, Chadda R. Magnitude of Substance Use in India. New Delhi: Press Information Bureau, Ministry of Social Justice & Empowerment, Government of India; 2019. Available from: 8&fbclid=IwAR1RxwrAqyF440zHF0XxvJ4Jc6TW5Un539iB4NDMIBha4pQF4RQHbuRydPw. [Last accessed on 2020 Apr 22].
4Rao R. The journey of opioid substitution therapy in India: Achievements and challenges. Indian J Psychiatry 2017;59:39-45.
5Ghosh A, Basu D, Avasthi A. Buprenorphine-based opioid substitution therapy in India: A few observations, thoughts, and opinions. Indian J Psychiatry 2018;60:361-6.
6Chou CP, Hser YI, Anglin MD. Interaction effects of client and treatment program characteristics on retention: An exploratory analysis using hierarchical linear models. Subst Use Misuse 1998;33:2281-301.
7Stark MJ. Dropping out of substance abuse treatment: A clinically oriented review. Clin Psychol Rev 1992;12:93-116.
8Alterman AI, McKay JR, Mulvaney FD, McLellan AT. Prediction of attrition from day hospital treatment in lower socioeconomic cocaine-dependent men. Drug Alcohol Depend 1996;40:227-33.
9Brewer DD, Catalano RF, Haggerty K, Gainey RR, Fleming CB. A meta-analysis of predictors of continued drug use during and after treatment for opiate addiction. Addiction 1998;93:73-92.
10Moos RH, Pettit B, Gruber VA. Characteristics and outcomes of three models of community residential care for abuse patients. J Subst Abuse 1995;7:99-116.
11Brorson HH, Ajo Arnevik E, Rand-Hendriksen K, Duckert F. Drop-out from addiction treatment: A systematic review of risk factors. Clin Psychol Rev 2013;33:1010-24.
12Lappan SN, Brown AW, Hendricks PS. Dropout rates of in-person psychosocial substance use disorder treatments: A systematic review and meta-analysis. Addiction 2020;115:201-17.
13Dayal P, Balhara YP. A naturalistic study of predictors of retention in treatment among emerging adults entering first buprenorphine maintenance treatment for opioid use disorders. J Subst Abuse Treat 2017;80:1-5.
14Basu D, Ghosh A, Sarkar S, Patra BN, Subodh BN, Mattoo SK. Initial treatment dropout in patients with substance use disorders attending a tertiary care de-addiction centre in north India. Indian J Med Res 2017;146:S77-84.
15Bandawar M, Kandasamy A, Chand P, Murthy P, Benegal V. Adherence to buprenorphine maintenance treatment in opioid dependence syndrome: A case control study. Indian J Psychol Med 2015;37:330-2.
16Avasthi A, Basu D, Subodh BN, Gupta PK, Goyal BL, Sidhu BS, et al. Epidemiology of dependence on illicit substances, with a special focus on opioid dependence, in the State of Punjab, India: Results from two different yet complementary survey methods. Asian J Psychiatr 2019;39:70-9.
17Das S, Das B, Hazarika M. Global psychiatry: A LAMIC perspective. Open J Psychiatry Allied Sci 2017;8:105-6.
18Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry 1998;59 Suppl 20:22-33.
19Sutherland G, Edwards G, Taylor C, Phillips G, Gossop M, Brady R. The measurement of opiate dependence. Br J Addict 1986;81:485-94.
20Ottomanelli G, Kramer TH, Bihari B, Fine J, Heller S, Mosely JA. AIDS-related risk behaviors among substance abusers. Int J Addict 1990;25:291-9.
21Wesson DR, Ling W. The Clinical Opiate Withdrawal Scale (COWS). J Psychoactive Drugs 2003;35:253-9.
22Groshkova T, Best D, White W. The Assessment of Recovery Capital: Properties and psychometrics of a measure of addiction recovery strengths. Drug Alcohol Rev 2013;32:187-94.
23Saxena S, Chandiramani K, Bhargava R. WHOQOL-Hindi: A questionnaire for assessing quality of life in health care settings in India. World Health Organization Quality of Life. Natl Med J India 1998;11:160-5.
24McLellan AT, Kushner H, Metzger D, Peters R, Smith I, Grissom G, et al. The Fifth Edition of the Addiction Severity Index. J Subst Abuse Treat 1992;9:199-213.
25Leonhard C, Mulvey K, Gastfriend DR, Shwartz M. The Addiction Severity Index: A field study of internal consistency and validity. J Subst Abuse Treat 2000;18:129-35.
26Chand P, Murthy P. Short-term outcome of take-home prescriptions for opioid dependence: A clinic-based study. J Subst Use 2013;18:108-18.
27Johansson BA, Berglund M, Lindgren A. Efficacy of maintenance treatment with naltrexone for opioid dependence: A meta-analytical review. Addiction 2006;101:491-503.
28Timko C, Schultz NR, Cucciare MA, Vittorio L, Garrison-Diehn C. Retention in medication-assisted treatment for opiate dependence: A systematic review. J Addict Dis 2016;35:22-35.
29Ruger JP, Chawarski M, Mazlan M, Ng N, Schottenfeld R. Cost-effectiveness of buprenorphine and naltrexone treatments for heroin dependence in Malaysia. PLoS One 2012;7:e50673.
30Bower P, Brueton V, Gamble C, Treweek S, Smith CT, Young B, et al. Interventions to improve recruitment and retention in clinical trials: A survey and workshop to assess current practice and future priorities. Trials 2014;15:399.
31Moos RH. Addictive disorders in context: Principles and puzzles of effective treatment and recovery. Psychol Addict Behav 2003;17:3-12.
32Humphreys K, Lembke A. Recovery-oriented policy and care systems in the UK and USA. Drug Alcohol Rev 2014;33:13-8.
33Laudet AB, White WL. Recovery capital as prospective predictor of sustained recovery, life satisfaction, and stress among former poly-substance users. Subst Use Misuse 2008;43:27-54.
34Feelemyer JP, Jarlais DC, Arasteh K, Phillips BW, Hagan H. Changes in quality of life (WHOQOL-BREF) and addiction severity index (ASI) among participants in opioid substitution treatment (OST) in low and middle income countries: An international systematic review. Drug Alcohol Depend 2014;134:251-8.
35Dhawan A, Chopra A. Does buprenorphine maintenance improve the quality of life of opioid users? Indian J Med Res 2013;137:130-5.
36Gowing L, Farrell M, Bornemann R, Sullivan L, Ali R. Oral substitution treatment of injecting opioid users for prevention of HIV infection. Cochrane Database Syst Rev [Internet]. 2011;8:CD004145. Available from: [Last accessed on 2021 Feb 11].
37Dhawan A, Jain R, Chopra A. Opioid Substitution-Buprenorphine in India. New Delhi: UNODC, Regional Office for South Asia; 2010.
38Carroll KM, Ball SA, Nich C, O'Connor PG, Eagan DA, Frankforter TL, et al. Targeting behavioral therapies to enhance naltrexone treatment of opioid dependence: Efficacy of contingency management and significant other involvement. Arch Gen Psychiatry 2001;58:755-61.
39Soper DS. Post hoc Statistical Power Calculator for Multiple Regression [Software]; 2021. Available from: [Last accessed on 2020 Apr 22].
40Basu D, Aggarwal M, Das PP, Mattoo SK, Kulhara P, Varma VK. Changing pattern of substance abuse in patients attending a de-addiction centre in north India (1978-2008). Indian J Med Res 2012;135:830-6.