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. Author manuscript; available in PMC: 2023 Jun 25.
Published in final edited form as: Drug Alcohol Depend. 2020 Oct 2;216:108334. doi: 10.1016/j.drugalcdep.2020.108334

Daily heroin injection and psychiatric disorders: a cross-sectional survey among People Who Inject Drugs (PWID) in Haiphong, Vietnam

Sao Mai Le 1,*, Philippe Trouiller 2, Huong Duong Thi 1, Oanh Khuat Thi Hai 3, Khue Pham Minh 1, Roselyne Vallo 4, Delphine Rapoud 4, Catherine Quillet 4, Thuy Linh Nguyen 1, Quang Duc Nguyen 1, Tuyet Thanh NhamThi 3, Giang Hoang Thi 1, Jonathan Feelemyer 5, Vinh Vu Hai 6, Jean-Pierre Moles 4, Hong Quang Doan 1, Didier Laureillard 4,7, Don C Des Jarlais 5, Nicolas Nagot 4, Laurent Michel 2; DRIVE Study Team
PMCID: PMC10290903  NIHMSID: NIHMS1634767  PMID: 33038638

Abstract

Background:

Psychiatric comorbidities are frequent among people who inject drugs, they are associated with a poorer prognosis and need to be addressed. Their interaction with daily heroin injection requires clarification.

Methods:

A cross-sectional survey was conducted among PWID recruited in the city of Haiphong, Vietnam, by respondent-driven sampling. The inclusion criteria were age 18 or older and current injection drug use, verified by skin marks and positive urine tests for heroin or methamphetamine. Data on socio-demographic characteristics, drug use, sexual behaviour and access to treatment were collected using face-to-face questionnaires by trained interviewers. PWID were screened by trained psychiatrists for depression, psychotic disorder and suicidality, using the MINI questionnaire.

Results:

418 participants were included in the analyses. All were injected heroin users, 21% were diagnosed with a current major depressive disorder, 15% with a current psychotic disorder and 12% presented a suicide risk. In the bivariate analyses, regular meth use, cannabis use and ketamine use were positively associated with presenting at least one psychiatric condition while daily heroin injection and being currently treated with methadone were negatively associated. In the multivariate model, poly-substance use was positively associated with depression (methamphetamine and drinking in addition to heroin) and psychotic disorder (methamphetamine and/or hazardous drinking in addition to heroin) while daily heroin injection and current methadone treatment were negatively and independently associated with depression and psychotic syndrome.

Conclusions:

Our survey confirms the burden of methamphetamine use and the protective effect of methadone but also a possible protective effect of daily heroin injection.

Keywords: Methamphetamine, Heroin, Psychosis, Depression, Dual Disorder

1. Introduction

Psychiatric comorbidities are very common among drug users and are associated with a poor prognosis of both psychiatric and substance-use disorders, with little chance of recovery (Buckley and Brown, 2006; Cuffel, 1996; EMCDDA, 2015; Kessler, 2004; Kessler et al., 1996). This is a key issue for national and international drug policies (EMCDDA, 2015). The most common disorders are mood, anxiety and personality disorders (Compton et al., 2007; Kingston et al., 2017; Regier et al., 1990) but there are considerable variations across study populations, the instruments used and the drugs considered (Kingston et al., 2017; Schuckit, 2006) raising the question of the nature of the links between substance use and psychiatric disorders.

Primary/independent psychiatric disorders can be defined as psychiatric conditions observed in the absence of any other major diagnosis for a given time interval, often preceding the substance use disorder. The mental disorder leads to the onset of substance use disorder possibly through increased exposure to drug use and self-medication. The second possibility is that substance use disorders induce psychiatric disorders through a combination of biological and environmental mechanisms. Common causes (genetic, environmental etc.) can also underpin the two disorders, as is the case for nicotine dependence and depression. The two disorders can be independent (de Graaf et al., 2002; Kessler, 2004; Schuckit, 2006). The prevalence of psychiatric disorders is systematically higher among people who use drugs than in the general population, and a wide range of drugs are involved in the onset of mood disorders. Cannabis and stimulants are specifically associated with drug-induced psychotic disorders (Lev-Ran et al., 2012; Schuckit, 2006). In the last few years, methamphetamine use has dramatically increased in Asia, with major public health consequences, including exposure to HIV risk, social harm and frequent psychiatric complications (Darke et al., 2008; Degenhardt et al., 2010; Marshall and Werb, 2010; McKetin et al., 2019; Salo et al., 2011). The prevalence of current psychosis among methamphetamine users is 11 times higher than in the general population and around 1/4 of regular methamphetamine users experience clinically significant psychotic symptoms (McKetin et al., 2006). A recent meta-analysis confirmed the strong link between methamphetamine use and psychosis, in addition to associations with violence, depression and suicidality (McKetin et al., 2019).

The role of opioid use is more controversial. Opioid use is rarely described as a risk factor for drug-induced psychotic disorder (Arunogiri et al., 2018; Dalmau et al., 1999; Fiorentini et al., 2011). Overall, substance-induced conditions are observed less frequently among opioid-dependent individuals (Schuckit, 2006). They could be related to social impairment, stigma, or comorbidities associated to drug injection (HIV, HCV) more than the biological effects of opioids (Levintow et al., 2019; Li et al., 2013; Nguyen et al., 2019; Tomori et al., 2014). Among opioid-dependent patients, methadone and buprenorphine, which are opioid agonists, are associated with improved quality of life and mental health (Teesson et al., 2006; Tenore, 2008; Ward et al., 1999; Xiao et al., 2010) through biological stabilization, and also a rapid improvement of living conditions.

Suicide and suicide attempts are also strongly associated with substance misuse with a clear overlap between suicide and overdose, reaching up to 50% overdoses among subjects in addiction treatment involving suicidal intent (Bohnert et al., 2010; Gicquelais et al., 2020).

The objective of the present study was to describe the prevalence of depression, psychotic syndrome and suicide risk among people who inject heroin, and the associated factors, in order to design an improved community-based mental health intervention to prevent and treat the psychiatric complications of drug use. The role of daily heroin injection was particularly investigated, as it remains unclear in the literature.

2. Material and methods

2.1. Design and participants

The DRIVE RDS bio-behavioral survey was conducted from October 2019 to January 2020 among PWIDs in Hai Phong. Participants were recruited using a standard RDS strategy (Heckathorn, 1997, 2002) with twenty initial “seeds” who were each given three coupons to distribute to potentially eligible participants (details of the sampling strategy have been previously described (Des Jarlais, D. et al., 2016)). The RDS eligibility criteria were (1) age 18 or older, (2) ability to provide informed consent, and (3) current injection drug use, verified by skin marks and positive urine test for opiates or methamphetamines. Participants previously recruited in any step of the DRIVE project were allowed to participate in the RDS. The target sample size was 1500, but the recruitment of new participants slowed considerably five weeks into the survey. As a result, “snowball” recruiting was initiated (Biernacki P, 1981) where each participant was asked to recruit as many new participants as they could (up to 20). We continued to use the RDS coupon system to track recruitment. The RDS procedure took place in 2 offices of the Community-Based Organisations (CBO) participating in the project in Hai Phong. CBO members contributed to all study procedures, and after specific training, they recruited the seeds, registered participants, presented the study, determined eligibility, collected data (particularly on drug use and sexual behavior), paid honoraria and distributed coupons for further recruitment (Des Jarlais, D. et al., 2016). Participants received 150,000 VND ($7.50 USD) compensation for their participation and ($2.50 USD for each PWID recruited, with a maximum of 3) for recruiting new participants.

2.2. Psychiatric disorder variables

In this paper, psychiatric disorders include current major depressive disorder, current psychotic disorder and suicide risk screened for by trained psychiatrists from Hai Phong University of Medicine and Pharmacy using the Mini International Neuropsychiatric Interview (MINI 5.0.0) (Sheehan et al., 1998) which was translated into Vietnamese following a translation–back translation–pre-test strategy (Brislin, 1986; Flaherty et al., 1988; Ghimire, 2011; Pham Minh et al., 2018). The psychiatrists were present full time in each CBO site for 4 weeks and then half-time in each CBO site. They met all the participants who were also on site during their time of presence. They were trained by the research coordinators (international and national experts from the field of mental health). Participants diagnosed with a mental health disorder were offered a psychiatric follow-up on site.

2.3. Study questionnaire

Data was collected by trained interviewers using a face-to-face questionnaire on socio-demographic characteristics, injecting and sexual behaviors and drug use, and blood samples for HIV and HCV screening were taken. The variable “daily heroin use” referred to the last 30 days. “Regular methamphetamine use” referred to use at least 4 times in the past month. Hazardous and binge drinking in the last six months were assessed using the Audit-C questionnaire (Bush et al., 1998; Dawson et al., 2012). The variable “regular poly-substance use” was defined as the number of substances regularly consumed among the following: alcohol (Audit-C score of 3 or more for women and 4 for men, over the last six months), heroin (injected at least once a day in the past month) and methamphetamines (at least 4 times in the past month).

2.4. Laboratory testing

The blood samples were tested for HIV and HCV. HIV serology followed national guidelines including an initial rapid test using SD BIOLINE HIV 1/2 3.0 (Standard Diagnostic Inc., South Korea), coupled with confirmation using two other rapid tests (Alere Determine HIV 1/2 (Abbott Alere Medical Co., Japan, and VIKIA®HIV1/2, Biomerieux, France). HCV serology was based on a rapid test SD BIOLINE HCV (SD standard Diagnostic Inc, South Korea)).

2.5. Ethical considerations

The study was approved by the Institutional Review Board of the Haiphong University of Medicine and Pharmacy (Vietnam) and the Icahn School of Medicine at Mount Sinai (USA). All PWIDs included in the study signed informed consent.

2.6. Statistical analysis

Participants in RDS who met the eligibility criteria but had already been enrolled in previous steps of the DRIVE project were excluded from our analyses, leaving only the DRIVE-naive subjects who had not experienced any kind of intervention, including the study-related mental health intervention.

After estimating the prevalence of current depression, psychotic disorder and suicidality, a bivariate analysis was conducted to compare the two PWID groups for each variable: those who presented a psychiatric disorder and those who did not (table 2). Then two multivariate models were run to further examine the association between the daily injection of heroin and diagnoses of a current psychotic disorder and major depressive disorder (table 3). In these multivariate models, the independent variables were “daily heroin injection”, “current methadone treatment”, “heroin use duration”, and “regular poly-substance use”. In order to estimate prevalence ratios, a log-binomial regression was used (Petersen and Deddens, 2008). The selection of independent variables included in the model was based on epidemiological relevance and not on a statistical criterion: since we chose to focus on the link between daily heroin use and psychotic disorder or major depressive disorder, factors with a potentially confounding effect on these associations were included (i.e. factors associated with both heroin use and psychiatric disorders) Sensitivity analyses were performed to estimate the robustness of the results; a multivariate model was run including regular methamphetamine use, cannabis use and hazardous drinking (based on the AUDIT-C score) as independent covariates, instead of a synthetic “regular poly-substance use” variable. Because snowball sampling added at the end of the survey violates RDS assumptions, sampling weights were not used in our analyses; nevertheless weighted prevalences for psychiatric disorders are presented in the text for information (using RDS-II weights (Volz E, 2008)). These analyses were performed with R software version 3.5.1 (R Core Team, 2016).

Table 2.

Participant characteristics according to psychiatric disorder (N=418)

Current major depressive episode Current psychotic disorder Suicidality (any level) One or more disorder
No Yes p No Yes p No Yes p No Yes p
N = 329 89 355 63 367 51 281 137
Age (mean (sd)) 39.91 (8.55) 41.57 (9.14) 0.109 40.26 (8.59) 40.29 (9.31) 0.982 40.02 (8.55) 41.98 (9.57) 0.132 39.83 (8.53) 41.16 (8.98) 0.141
Male (%) 315 (95.7) 82 (92.1) 0.267 339 (95.5) 58 (92.1) 0.403 352 (95.9) 45 (88.2) 0.044 270 (96.1) 127 (92.7) 0.212
Living with a partner (%) 134 (40.7) 34 (38.2) 0.757 150 (42.3) 18 (28.6) 0.057 152 (41.4) 16 (31.4) 0.223 120 (42.7) 48 (35.0) 0.163
ID card (%) 245 (74.5) 68 (76.4) 0.813 269 (75.8) 44 (69.8) 0.399 275 (74.9) 38 (74.5) 1 212 (75.4) 101 (73.7) 0.794
Health insurance (%) 140 (42.6) 29 (32.6) 0.114 150 (42.3) 19 (30.2) 0.096 151 (41.1) 18 (35.3) 0.519 125 (44.5) 44 (32.1) 0.021
Sexual partner in the last 6 months (%) 210 (63.8) 43 (48.3) 0.011 216 (60.8) 37 (58.7) 0.86 225 (61.3) 28 (54.9) 0.469 178 (63.3) 75 (54.7) 0.114
Methamphetamine use in the last 6 months (%) 205 (62.3) 63 (70.8) 0.176 224 (63.1) 44 (69.8) 0.376 223 (60.8) 45 (88.2) <0.001 168 (59.8) 100 (73.0) 0.011
Methamphetamine use in the last 30 days (%) 143 (43.5) 41 (46.1) 0.75 149 (42.0) 35 (55.6) 0.062 154 (42.0) 30 (58.8) 0.034 114 (40.6) 70 (51.1) 0.054
Regular methamphetamine use (≥ 4 times in the last 30 days) (%) 67 (20.4) 28 (31.5) 0.038 68 (19.2) 27 (42.9) <0.001 76 (20.7) 19 (37.3) 0.014 52 (18.5) 43 (31.4) 0.005
Positive urine test for methamphetamine (%) 128 (38.9) 35 (39.3) 1 132 (37.2) 31 (49.2) 0.096 135 (36.8) 28 (54.9) 0.02 101 (35.9) 62 (45.3) 0.084
Daily heroin use (in the past month) (%) 230 (69.9) 52 (58.4) 0.054 248 (69.9) 34 (54.0) 0.02 245 (66.8) 37 (72.5) 0.504 199 (70.8) 83 (60.6) 0.047
Duration heroin use (%) 0.106a 0.07a 0.18a 0.01 a
Less than 5 years 56 (17.0) 11 (12.4) 61 (17.2) 6 (9.5) 60 (16.3) 7 (13.7) 51 (18.1) 16 (11.7)
5 to 10 years 95 (28.9) 24 (27.0) 102 (28.7) 17 (27.0) 106 (28.9) 13 (25.5) 82 (29.2) 37 (27.0)
10 to 15 years 80 (24.3) 19 (21.3) 84 (23.7) 15 (23.8) 90 (24.5) 9 (17.6) 70 (24.9) 29 (21.2)
15 years or more 98 (29.8) 35 (39.3) 108 (30.4) 25 (39.7) 111 (30.2) 22 (43.1) 78 (27.8) 55 (40.1)
Cannabis use (%) 31 (9.4) 18 (20.2) 0.009 35 (9.9) 14 (22.2) 0.009 42 (11.4) 7 (13.7) 0.809 23 (8.2) 26 (19.0) 0.002
Ketamine use (%) 15 (4.6) 11 (12.4) 0.014 20 (5.6) 6 (9.5) 0.371 21 (5.7) 5 (9.8) 0.411 10 (3.6) 16 (11.7) 0.003
Street methadone use (%) 85 (25.8) 27 (30.3) 0.474 94 (26.5) 18 (28.6) 0.848 98 (26.7) 14 (27.5) 1 68 (24.2) 44 (32.1) 0.11
Hazardous drinking (Audit-c score ≥ 3 in women and ≥ 4 in men) (%) 84 (25.5) 27 (30.3) 0.438 86 (24.2) 25 (39.7) 0.016 96 (26.2) 15 (29.4) 0.746 68 (24.2) 43 (31.4) 0.149
Lifetime suicide attempt (%) 15 (4.3) 11 (17.5) <0.001 15 (4.3) 11 (17.5) <0.001 0 (0.0) 26 (51.0) <0.001 0 (0.0) 26 (19.0) <0.001
Positive serology for HCV (%) 229 (69.6) 58 (65.2) 0.502 247 (69.6) 40 (63.5) 0.417 257 (70.0) 30 (58.8) 0.146 196 (69.8) 91 (66.4) 0.565
Positive serology for HIV (%) 58 (17.6) 13 (14.6) 0.607 60 (16.9) 11 (17.5) 1 60 (16.3) 11 (21.6) 0.465 48 (17.1) 23 (16.8) 1
Past experience of overdose (%) 7 (2.1) 5 (5.6) 0.164 7 (2.0) 5 (7.9) 0.028 7 (1.9) 5 (9.8) 0.007 5 (1.8) 7 (5.1) 0.109
Currently under methadone treatment (%) 110 (33.4) 22 (24.7) 0.15 116 (32.7) 16 (25.4) 0.318 119 (32.4) 13 (25.5) 0.402 98 (34.9) 34 (24.8) 0.049
Positive urine test for methadone (%) 181 (55.0) 42 (47.2) 0.233 195 (54.9) 28 (44.4) 0.161 199 (54.2) 24 (47.1) 0.417 157 (55.9) 66 (48.2) 0.169
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a

p for trend

Table 3.

Multivariate analysis across all subjects (N = 418): factors associated with major depressive episode and psychotic disorder

Unadjusted prevalence Ratio Prevalence Ratio 95% CI
Major depressive episode
Daily heroin use (in the past month) 0.68 0.52 0.34 – 0.83
Duration heroin use** 1.16 1.15 0.97 – 1.38
Current methadone treatment 0.71 0.64 0.40 – 0.98
Regular poly-substance use (ref = 0)*
One substance 0.91 1.27 0.73 – 2.30
Two substances 0.82 1.23 0.61 – 2.47
Three substances 1.81 2.72 1.09 – 6.23
Current psychotic disorder
Daily heroin use (in the past month) 0.57 0.3 0.18 – 0.52
Duration heroin use** 1.22 1.17 0.95 – 1.47
Current methadone treatment 0.74 0.68 0.39 – 1.11
Regular poly-substance use (ref = 0)*
One substance 0.94 1.82 0.92 – 3.97
Two substances 1.15 2.77 1.21 – 6.50
Three substances 3.45 9.35 3.50 – 24.94
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*

Regular poly-substance use. including daily heroin injection. regular methamphetamine use (≥ 4 times in the last 30 days). and alcohol misuse

**

Levels were set as follows: less than 5 years (ref); 5–10 years; 10–15 years; 15+ years. Coefficient for each level increase

The threshold for statistical significance was set at p <0.05.

3. Results

3.1. Overall population

Overall, 1339 subjects agreed to participate in the DRIVE RDS study and 1268 met the eligibility criteria. Among them, 978 were randomly screened for psychiatric disorders using the MINI questionnaire but 560 had already been enrolled in previous steps of the DRIVE project. Hence, data for 418 PWID was analyzed, representing around 8% of the estimated total population of PWID in the city of Haiphong (Des Jarlais et al., 2018).

3.2. Participant characteristics and prevalence of current psychiatric disorder

The study population characteristics are summarized in Table 1. The mean age in our sample was 40.3 years and 95% of participants were male. All participants were using injected heroin and screened positive for heroin in their urine, 28% reported receiving methadone treatment at the time of the survey, 27% reported the use of street methadone (median [IQR], the number of days of street methadone use during the last 30 days was 2 [2,4]) and 50% screened positive for methadone in their urine. Methamphetamine use in the past month was reported by 44% of the participants and 22.7% reported regular methamphetamine use. Around 25% of the participants reported regular use of two substances and 4% reported 3 substances among the following: daily heroin injection, hazardous drinking and methamphetamine use ≥ 4 times during the last 30 days. 24% of the women and 12% of the men reported a past history of suicide attempt. Regarding the psychiatric assessment, 21.3% (95% CI = [17.6 – 25.5]) of all participants presented a current major depressive episode (weighted estimation using RDS-II weights = 22.4%). A psychotic disorder was identified for 15.1% [11.9 – 18.8] of the participants (weighted % = 15.3), and suicide risk was identified for 12.2% [9.4 – 15.7] (weighted % = 13.5). Finally, 32.8 % [28.4 – 37.4] of all participants presented at least one of the above-mentioned three psychiatric disorders (weighted % = 35.2).

Table 1.

Participant characteristics (n = 418)

Socio-demographics Age (mean (sd)) 40.26 (8.69)
Male (%) 397 (95.0)
Female (%) 21 (5.0)
Living with a partner (%) 168 (40.2)
ID card (%) 313 (74.9)
Health insurance (%) 169 (40.4)
Sexual partner in the last 6 months (%) 253 (60.5)
Psychiatric disorder Current major depressive episode (%) 89 (21.3)
Current suicidality (%)
None 367 (87.8)
Low 31 (7.4)
Moderate 11 (2.6)
High 9 (2.2)
Suicidality (any level) (%) 51 (12.2)
Lifetime suicide attempt (%) 26 (6.2)
Current psychotic disorder (%) 63 (15.1)
One disorder or morea (%) 137 (32.8)
Drug/alcohol use Methamphetamine use in the last 6 months (%) 268 (64.1)
Methamphetamine use in the last 30 days (%) 184 (44.0)
Regular methamphetamine use (≥ 4 times in the last 30 days) (%) 95 (22.7)
Positive urine test for methamphetamine (%) 163 (39.0)
Daily heroin use (in the past month) (%) 282 (67.5)
Duration heroin use (%)
Less than 5 years 67 (16.0)
5 to 10 years 119 (28.5)
10 to 15 years 99 (23.7)
15 years or more 133 (31.8)
Cannabis use (%) 49 (11.7)
Ketamine use (%) 26 (6.2)
Street methadone use (%) 112 (26.8)
Hazardous drinking (Audit-c score ≥ 3 in women and ≥ 4 in men) (%) 111 (26.6)
Regular poly-substance useb (%)
0 66 (15.8)
1 233 (55.7)
2 102 (24.4)
3 17 (4.1)
Health Positive serology for HCV (%) 287 (68.7)
Positive serology for HIV (%) 71 (17.0)
Past experience of overdose (%) 12 (2.9)
Currently under methadone treatment (%) 132 (31.6)
Positive urine test for methadone (%) 223 (53.3)
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*

Percentage (unless otherwise stated) taking into account the RDS sampling with RDS-II weights

a

one disorder or more among the following: major depressive episode, psychotic disorder, suicidality risk score > 0)

b

including daily heroin injection, regular methamphetamine use (≥ 4 times during the last 30 days), and alcohol misuse

Figure 1 shows the distribution of the different psychiatric disorders among those with at least one disorder (N=137).

Fig. 1.

Fig. 1.

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Venn Diagram for Psychiatric Disorders.

Among PWID reporting regular methamphetamine use (≥ 4 times in last 30 days), 28% were diagnosed with a current psychotic disorder (vs. 10% for those using methamphetamine <4 times in the last 30 days), 29% with a major depressive episode (vs. 20%) and 20% with suicide risk (vs. 10%).

Among the PWID reporting daily heroin injection, 12% were diagnosed with a current psychotic disorder (vs. 21% for those injecting heroin less than daily), 18% with a major depressive episode (vs. 27%) and 13% with suicide risk (vs. 10%).

3.3. Bivariate analysis: factors associated with current psychiatric disorder

Participant characteristics in relation to their psychiatric disorder status are described in table 2. Regular methamphetamine use was positively associated with each of the psychiatric disorders we focused on in this study, and especially with a current psychotic disorder (among those who presented this disorder 42.9% reported regular methamphetamine use vs. 19.2% among those who did not, p < 0.001). Cannabis use was associated with both current major depressive episode and psychotic disorder. Alcohol misuse assessed by AUDIT-C was only associated with psychotic disorder (39.7% vs 24.2%, p = 0.016).

Interestingly, the daily use of heroin seemed negatively associated with both current major depressive episode and current psychotic disorder. Indeed, in the group showing depressive symptoms, 58.4 % reported daily use of heroin vs. 69.9% in the other group (p= 0.054). Likewise, among subjects presenting a psychotic disorder 54% reported daily use of heroin vs. 69.9% among those who did not (p = 0.02).

3.4. Multivariate analysis: relationship between regular heroin use and psychotic disorder

Results from the two multivariate models are presented in Table 3. Participants who reported daily use of heroin were less likely to present a major depressive episode (prevalence ratio (PR) : 0.52, p < 0.001) or a current psychotic disorder (prevalence ratio : 0.3, p < 0.001) after controlling for current methadone treatment, heroin use duration, and regular poly-substance use. Finally, the use of two or three substances, including alcohol, heroin or methamphetamine was strongly associated with a current psychotic disorder (prevalence ratio of 2.77 [1.21 – 6.50] and 9.35 [3.50 – 24.94], respectively).

3.5. Sensitivity analyses

Our sensitivity analysis presented in Table 4 showed that the daily use of heroin was still negatively associated with current psychotic disorder (PR : 0.64, p = 0.049) and major depressive disorder (PR: 0.68, p = 0.039) after including regular methamphetamine use, cannabis use and alcohol misuse (based on AUDIT-C score) as control variables, instead of a synthetic “regular poly-substance use” variable.

Table 4.

Sensitivity analysis. Factors associated with major depressive episode and psychotic disorder (multivariate model, N = 418)

Prevalence Ratio 95% CI
Major depressive disorder
Daily heroin use (in the past month) 0.68 0.46 – 0.98
Heroin use duration 1.18 0.99 – 1.40
Current methadone treatment 0.64 0.41 – 1.00
Hazardous drinking (Audit-c score ≥ 3 in women and ≥ 4 in men) (%) 1.02 0.69 – 1.51
Regular methamphetamine use (≥ 4 times in the last 30 days) (%) 1.31 0.88 – 1.93
Cannabis use 1.7 1.11 – 2.62
Psychotic Disorder
Daily heroin use (in the past month) 0.64 0.41 – 0.99
Heroin use duration 1.17 0.95 – 1.45
Current methadone treatment 0.72 0.42 – 1.22
Hazardous drinking (Audit-c score ≥ 3 in women and ≥ 4 in men) (%) 1.52 0.97 – 2.39
Regular methamphetamine use (≥ 4 times in the last 30 days) (%) 2.16 1.37 – 3.41
Cannabis use 1.43 0.85 – 2.39
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4. Discussion

More than one third of the PWID participating in this survey were diagnosed with at least one disorder, around a quarter with a current major depressive episode and more than one sixth with a current psychotic disorder.

The prevalence of major depressive disorder was lower in our population sample than in many other studies conducted among PWID (Colledge et al., 2020; Iskandar et al., 2012) in which the prevalence of anxiety disorders and depression ranged from 4% to 53% and 18% to 72% respectively. However, one third of our subjects had already been treated with methadone, which is associated with lower depression rates (Pani et al., 2010), and two-thirds were injecting heroin every day, which is associated with lower prevalence of depression. Suicide risk was difficult to compare with other studies, as both the populations and the assessment of suicide risk differs considerably from one study to another (Colledge et al., 2020; Iskandar et al., 2012). Indeed, previous studies showed prevalence rates of suicidal ideation and suicide attempts ranging from 50 to 93% and 43 to 87% respectively (Iskandar et al., 2012). The prevalence of psychotic disorder was higher than in other studies, (for example a study by Iskandar et al. showed a prevalence of psychotic disorders of around 12% (Iskandar et al., 2012)), but in line with what is observed among subjects using methamphetamines (Arunogiri et al., 2020), and 69% of the participants reported methamphetamine use in the last 30 days.

In our study, regular heroin injection was negatively and independently associated with being diagnosed with a current psychotic disorder and a major depressive disorder, even after adjustment on the many possible confounding factors. Diacetylmorphine (heroin) is a strong, full opioid agonist that is used in a therapeutic context as maintenance treatment (heroin-assisted treatment) for severely dependent opioid users. Controlled studies have shown that diacetylmorphine or diacetylmorphine plus methadone were superior to methadone alone on different outcomes, including quality of life, psychological health, and psychosocial functioning (Ferri et al., 2011; Haasen et al., 2007; Karow et al., 2010; Oviedo-Joekes et al., 2010; Reimer et al., 2011; Schafer et al., 2010; van den Brink et al., 2003). Shafer et al. concluded that psychiatric comorbidity should be an inclusion criterion for heroin-assisted treatment (Schafer et al., 2010).

Although the context of our study is far removed from a therapeutic context, it can nevertheless be assumed that PWID injecting heroin daily could draw benefit from heroin on their psychiatric symptoms.

The many benefits of methadone initiation among heroin-dependent injection drug users are well documented (Connock et al., 2007; Gowing et al., 2011; MacArthur et al., 2014; Marks et al., 2019; Mattick et al., 2009, 2014; Molero et al., 2018) and one benefit is the improvement in mental health status, particularly for depression, but also for psychosis (Deglon, 2008; Gossop et al., 2006; Maremmani et al., 2011; Ward et al., 1999). Increasing methadone doses for heroin-dependent subjects hospitalized for psychiatric emergencies was found to reduce their needs for anti-manic and antipsychotic drugs (Pacini, 2005). Cases of psychosis related to methadone withdrawal have been described (Cobo et al., 2006). Overall, while psychotic disorders are more frequent among drug users than in the general population (Lev-Ran et al., 2012; Regier et al., 1990), opioids are rarely identified as being responsible for psychotic disorders, unlike stimulants, alcohol or cannabis (Arunogiri et al., 2018; Dalmau et al., 1999; Fiorentini et al., 2011; Schuckit, 2006), thus raising the question of the chronology of the occurrence of psychotic symptoms compared to opioid use initiation. The hypothesis of an antipsychotic or modulatory effect of opioids on dopamine or on the neurotransmitter system that controls mood has been suggested (Deglon, 2008; Maremmani et al., 2014; Schmauss and Emrich, 1985; Tenore, 2008).

In Vietnam, heroin has been the predominant substance of abuse since the early 90s and is mainly injected, but stimulant use and particularly methamphetamine use have increased rapidly since the beginning of the 2000s to become a major public health concern today (Giang et al., 2013). In 2016, up to 50% of the people who inject drugs (PWIDs) in the city of Haiphong were also inhaling methamphetamines (Feelemyer et al., 2018) and methamphetamine use was reported by 77% of the young people (16–24) using drugs in the cities of Haiphong, Ho Chi Minh City and Hanoi (Michel et al., 2020). Methamphetamine use, and particularly regular methamphetamine use, was positively and strongly associated with psychiatric disorders in our study, as in previous studies (McKetin et al., 2019). The proportion of PWID with regular methamphetamine use and with psychotic symptoms observed in our study is alarming, but very similar to proportions found in other studies (approximately 25%) (McKetin et al., 2006). This emphasizes the dramatic public health consequences of methamphetamine use and the need to inform, prevent its trivialization and work on the representations associated with it. Many people who use drugs in Vietnam and elsewhere see methamphetamine as a trendy, fashionable “social” drug, inhaled and not injected, associated with sex and fun, and also as helping to cope with stress; this contrasts with heroin, which is primarily injected, thus exposing PWID to HIV and overdose, and is associated with loneliness and being identified as a “junkie”(Degenhardt et al., 2010; Hobkirk et al., 2016; Liu et al., 2018; Michel et al., 2020; Noroozi et al., 2018).

Regular poly-substance use (i.e. the association of regular methamphetamine use, daily heroin injection and hazardous drinking) is associated with the highest prevalence ratios for all disorders. The association between alcohol use disorder and psychiatric comorbidities has been well established, for major depressive disorder as well as psychotic disorder (Castillo-Carniglia et al., 2019; Dalmau et al., 1999; Hasin et al., 2007; Hjemsaeter et al., 2019). The deleterious cumulate effect of regular methamphetamine use and hazardous drinking is not surprising, as outlined in previously documented studies (Chen et al., 2003; Connor et al., 2014; Dalmau et al., 1999; Wouldes et al., 2013).

These findings have clinical implications. In order to prevent psychiatric complications among PWID, regular methamphetamine use should be targeted first, particularly when it is associated with hazardous drinking. Screening for both substances using self-report questionnaires and rapid psychiatric screening should be routinely implemented, and brief interventions proposed, mainly based on information and harm reduction messages. Access to methadone treatment needs to be facilitated and persistence of heroin injection during methadone treatment should not be sanctioned, but a more comprehensive support and harm reduction approach should be offered. Access to psychiatric interventions also needs to be organized for those exhibiting significant symptoms and could involve peer support in low-middle income countries (Patel et al., 2007; Pham Minh et al., 2018; Sunkel, 2012; WHO, 2013).

Some limitations of this study should be noted. We used a cross-sectional design, which did not allow us to establish temporal relationships across variables. Psychiatric problems can occur before or after the onset of a drug addiction or share the same risk factors; it is likely that the chronology could have consequences for the approach to treatment and for understanding of the relationship between drug use and the incidence of psychiatric disorders. Although RDS sampling remains a method of choice to investigate hidden populations such as PWID, caution is needed when interpreting results based on this method. The weighted proportion we calculated, while it was not perfect for dealing with representativeness bias (McCreesh et al., 2012), suggests that a slight underestimation of the disorders is possible. In addition, our conclusions are limited to the profile of our population sample which included only people who inject heroin. Extending these conclusions to other populations of people who use drugs would need further studies. Finally, we cannot rule out a social desirability bias in self-report of behaviors (the variables explored here were self-reported and could present under-reporting bias, etc.).

5. Conclusions

Our survey confirms the dramatic mental health consequences of methamphetamine use and concern about its association with hazardous drinking, but it also suggests a protective effect of regular heroin injection, particularly when methadone treatment has already been initiated. Taken together, these results pinpoint the importance of routine screening for methamphetamine use and mental health disorders among people who use drugs, with community-based links to care in countries where psychiatric facilities are limited. It also suggests that in places where psychosocial interventions associated with methadone treatment are sparse, daily heroin use could potentiate methadone treatment and should not be sanctioned but rather associated with comprehensive support and harm reduction interventions.

Highlights.

  • Regular heroin injection could be protective for depression and psychotic symptoms.

  • Psychiatric burden of methamphetamine use is high.

  • PWID treated with methadone are less often depressed.

  • Regular polysubstance use is associated with higher rate of psychiatric disorders.

Role of Funding Source:

This work was supported by grants from NIDA (US) (#DA041978) and ANRS (France) (#13353).The funding agencies had no role in designing the research, data analyses and preparation of the report.

Abbreviations

CBO

Community-based organization

HCV

Hepatitis C virus

HIV

Human immunodeficiency virus

MINI

Mini international neuropsychiatric interview

PR

Prevalence ratio

PWID

People who inject drugs

USD

US dollars

VND

Vietnamese dong

Footnotes

Conflict of interest:

No conflict declared.

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References

  1. Arunogiri S, Foulds JA, McKetin R, Lubman DI, 2018. A systematic review of risk factors for methamphetamine-associated psychosis. Aust N Z J Psychiatry 52(6), 514–529. [DOI] [PubMed] [Google Scholar]
  2. Arunogiri S, McKetin R, Verdejo-Garcia A, Lunbman DI, 2020. The Methamphetamine-Associated Psychosis Spectrum: a Clinically Focused Review. Int J Ment Health Addiction 18, 54–65. [Google Scholar]
  3. Bohnert AS, Roeder K, Ilgen MA, 2010. Unintentional overdose and suicide among substance users: a review of overlap and risk factors. Drug Alcohol Depend 110(3), 183–192. [DOI] [PubMed] [Google Scholar]
  4. Brislin RW, 1986. The Wording and Translation of Research Instruments., in: Lonner WJB (Ed.) Field methods in Cross-Cultural research. Sage Publications, Beverly Hills, Calif. [Google Scholar]
  5. Buckley PF, Brown ES, 2006. Prevalence and consequences of dual diagnosis. J Clin Psychiatry 67(7), e01. [DOI] [PubMed] [Google Scholar]
  6. Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA, 1998. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Arch Intern Med 158(16), 1789–1795. [DOI] [PubMed] [Google Scholar]
  7. Castillo-Carniglia A, Keyes KM, Hasin DS, Cerda M, 2019. Psychiatric comorbidities in alcohol use disorder. Lancet Psychiatry 6(12), 1068–1080. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Chen CK, Lin SK, Sham PC, Ball D, Loh EW, Hsiao CC, Chiang YL, Ree SC, Lee CH, Murray RM, 2003. Pre-morbid characteristics and co-morbidity of methamphetamine users with and without psychosis. Psychol Med 33(8), 1407–1414. [DOI] [PubMed] [Google Scholar]
  9. Cobo J, Ramos MM, Pelaez T, Garcia G, Marsal F, 2006. Psychosis related to methadone withdrawal. Acta Neuropsychiatr 18(1), 50–51. [DOI] [PubMed] [Google Scholar]
  10. Colledge S, Larney S, Peacock A, Leung J, Hickman M, Grebely J, Farrell M, Degenhardt L, 2020. Depression, post-traumatic stress disorder, suicidality and self-harm among people who inject drugs: A systematic review and meta-analysis. Drug Alcohol Depend 207, 107793. [DOI] [PubMed] [Google Scholar]
  11. Compton WM, Thomas YF, Stinson FS, Grant BF, 2007. Prevalence, correlates, disability, and comorbidity of DSM-IV drug abuse and dependence in the United States: results from the national epidemiologic survey on alcohol and related conditions. Arch Gen Psychiatry 64(5), 566–576. [DOI] [PubMed] [Google Scholar]
  12. Connock M, Juarez-Garcia A, Jowett s., Frew E, Liu Z, Fry-Smith A, Day E, Lintzeris N, Roberts T, Burls A, Taylor RS, 2007. Methadone and buprenorphine for the management of opioid dependence: a systematic review and economic evaluation. Health Technology Assessment 11(9), 1–190. [DOI] [PubMed] [Google Scholar]
  13. Connor JP, Gullo MJ, White A, Kelly AB, 2014. Polysubstance use: diagnostic challenges, patterns of use and health. Curr Opin Psychiatry 27(4), 269–275. [DOI] [PubMed] [Google Scholar]
  14. Cuffel BJ, 1996. Comorbid substance use disorder: prevalence, patterns of use, and course. New Dir Ment Health Serv(70), 93–105. [DOI] [PubMed] [Google Scholar]
  15. Dalmau A, Bergman B, Brismar B, 1999. Psychotic disorders among inpatients with abuse of cannabis, amphetamine and opiates. Do dopaminergic stimulants facilitate psychiatric illness? Eur Psychiatry 14(7), 366–371. [DOI] [PubMed] [Google Scholar]
  16. Darke S, Kaye S, McKetin R, Duflou J, 2008. Major physical and psychological harms of methamphetamine use. Drug Alcohol Rev 27(3), 253–262. [DOI] [PubMed] [Google Scholar]
  17. Dawson DA, Smith SM, Saha TD, Rubinsky AD, Grant BF, 2012. Comparative performance of the AUDIT-C in screening for DSM-IV and DSM-5 alcohol use disorders. Drug Alcohol Depend 126(3), 384–388. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. de Graaf R, Bijl RV, Smit F, Vollebergh WA, Spijker J, 2002. Risk factors for 12-month comorbidity of mood, anxiety, and substance use disorders: findings from the Netherlands Mental Health Survey and Incidence Study. Am J Psychiatry 159(4), 620–629. [DOI] [PubMed] [Google Scholar]
  19. Degenhardt L, Mathers B, Guarinieri M, Panda S, Phillips B, Strathdee SA, Tyndall M, Wiessing L, Wodak A, Howard J, Reference Group to the United Nations on, H.I.V., injecting drug, u., 2010. Meth/amphetamine use and associated HIV: Implications for global policy and public health. Int J Drug Policy 21(5), 347–358. [DOI] [PubMed] [Google Scholar]
  20. Deglon JW,E, 2008. Methadone: A Fast and Powerful Anti-anxiety, Anti-depressant and Anti-psychotic Treatment. Heroin Addict Relat Clin Probl 10(1), 47–54. [Google Scholar]
  21. Des Jarlais D, Duong HT, Pham Minh K, Khuat OH, Nham TT, Arasteh K, Feelemyer J, Heckathorn DD, Peries M, Moles JP, Laureillard D, Nagot N, 2016. Integrated respondent-driven sampling and peer support for persons who inject drugs in Haiphong, Vietnam: a case study with implications for interventions. AIDS Care 28(10), 1312–1315. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Des Jarlais D, Khue PM, Feelemyer J, Arasteh K, Thi Huong D, Thi Hai Oanh K, Thi Giang H, Thi Tuyet Thanh N, Vinh VH, Heckathorn DD, Moles JP, Vallo R, Quillet C, Rapoud D, Michel L, Laureillard D, Hammett T, Nagot N, 2018. Using dual capture/recapture studies to estimate the population size of persons who inject drugs (PWID) in the city of Hai Phong, Vietnam. Drug Alcohol Depend 185, 106–111. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Des Jarlais DC, Thi Huong D, Thi Hai Oanh K, Khue Pham M, Thi Giang H, Thi Tuyet Thanh N, Arasteh K, Feelemyer J, Hammett T, Peries M, Michel L, Vu Hai V, Roustide MJ, Moles JP, Laureillard D, Nagot N, Team DS, 2016. Prospects for ending the HIV epidemic among persons who inject drugs in Haiphong, Vietnam. Int J Drug Policy 32, 50–56. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. EMCDDA, 2015. Comorbidity of substance use and mental disorders in Europe, Insights. [Google Scholar]
  25. Feelemyer J, Duong Thi H, Khue Pham M, Hoang Thi G, Thi Tuyet Thanh N, Thi Hai Oanh K, Arasteh K, Moles JP, Vu Hai V, Vallo R, Quillet C, Rapoud D, Michel L, Hammett T, Laureillard D, Nagot N, Des Jarlais D, Team DS, 2018. Increased Methamphetamine Use among Persons Who Inject Drugs in Hai Phong, Vietnam, and the Association with Injection and Sexual Risk Behaviors. J Psychoactive Drugs 50(5), 382–389. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Ferri M, Davoli M, Perucci CA, 2011. Heroin maintenance for chronic heroin-dependent individuals. Cochrane Database Syst Rev(12), CD003410. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Fiorentini A, Volonteri LS, Dragogna F, Rovera C, Maffini M, Mauri MC, Altamura CA, 2011. Substance-induced psychoses: a critical review of the literature. Curr Drug Abuse Rev 4(4), 228–240. [DOI] [PubMed] [Google Scholar]
  28. Flaherty JA, Gaviria FM, Pathak D, Mitchell T, Wintrob R, Richman JA, Birz S, 1988. Developing instruments for cross-cultural psychiatric research. J Nerv Ment Dis 176(5), 257–263. [PubMed] [Google Scholar]
  29. Ghimire DC,S; Kessler R; Axinn W; Adhikari B, 2011. Modifying and validating the Composite International Diagnostic Interview (CIDI) for use in Nepal. Population Studies Center, University of Michigan. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Giang LM, Ngoc LB, Hoang VH, Mulvey K, Rawson RA, 2013. Substance use disorders and HIV in Vietnam since Doi Moi (Renovation): an overview. J Food Drug Anal 21(4), S42–S45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Gicquelais RE, Jannausch M, Bohnert ASB, Thomas L, Sen S, Fernandez AC, 2020. Links between suicidal intent, polysubstance use, and medical treatment after non-fatal opioid overdose. Drug Alcohol Depend 212, 108041. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Gossop M, Marsden J, Stewart D, 2006. Remission of psychiatric symptoms among drug misusers after drug dependence treatment. J Nerv Ment Dis 194(11), 826–832. [DOI] [PubMed] [Google Scholar]
  33. Gowing L, Farrell MF, Bornemann R, Sullivan LE, Ali R, 2011. Oral substitution treatment of injecting opioid users for prevention of HIV infection. Cochrane Database Syst Rev(8), CD004145. [DOI] [PubMed] [Google Scholar]
  34. Haasen C, Verthein U, Degkwitz P, Berger J, Krausz M, Naber D, 2007. Heroin-assisted treatment for opioid dependence: randomised controlled trial. Br.J.Psychiatry. 191, 55–62. [DOI] [PubMed] [Google Scholar]
  35. Hasin DS, Stinson FS, Ogburn E, Grant BF, 2007. Prevalence, correlates, disability, and comorbidity of DSM-IV alcohol abuse and dependence in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Arch Gen Psychiatry 64(7), 830–842. [DOI] [PubMed] [Google Scholar]
  36. Hjemsaeter AJ, Bramness JG, Drake R, Skeie I, Monsbakken B, Benth JS, Landheim AS, 2019. Mortality, cause of death and risk factors in patients with alcohol use disorder alone or poly-substance use disorders: a 19-year prospective cohort study. BMC Psychiatry 19(1), 101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Hobkirk AL, Watt MH, Myers B, Skinner D, Meade CS, 2016. A qualitative study of methamphetamine initiation in Cape Town, South Africa. Int J Drug Policy 30, 99–106. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Iskandar S, Kamal R, De Jong CA, 2012. Psychiatric comorbidity in injecting drug users in Asia and Africa. Curr Opin Psychiatry 25(3), 213–218. [DOI] [PubMed] [Google Scholar]
  39. Karow A, Reimer J, Schafer I, Krausz M, Haasen C, Verthein U, 2010. Quality of life under maintenance treatment with heroin versus methadone in patients with opioid dependence. Drug Alcohol Depend 112(3), 209–215. [DOI] [PubMed] [Google Scholar]
  40. Kessler RC, 2004. The epidemiology of dual diagnosis. Biol Psychiatry 56(10), 730–737. [DOI] [PubMed] [Google Scholar]
  41. Kessler RC, Nelson CB, McGonagle KA, Edlund MJ, Frank RG, Leaf PJ, 1996. The epidemiology of co-occurring addictive and mental disorders: implications for prevention and service utilization. American Journal of Orthopsychiatry 66, 17–31. [DOI] [PubMed] [Google Scholar]
  42. Kingston REF, Marel C, Mills KL, 2017. A systematic review of the prevalence of comorbid mental health disorders in people presenting for substance use treatment in Australia. Drug Alcohol Rev 36(4), 527–539. [DOI] [PubMed] [Google Scholar]
  43. Lev-Ran S, Imtiaz S, Le Foll B, 2012. Self-reported psychotic disorders among Individuals with substance use disorders: findings from the National Epidemiologic Survey on Alcohol and Related Conditions. The American journal on addictions / American Academy of Psychiatrists in Alcoholism and Addictions 21(6), 531–535. [DOI] [PubMed] [Google Scholar]
  44. Levintow SN, Pence BW, Ha TV, Le Minh N, Sripaipan T, Latkin CA, Quan VM, Frangakis C, Go VF, 2019. Depressive Symptoms at HIV Testing and Two-Year All-Cause Mortality Among Men Who Inject Drugs in Vietnam. AIDS and Behavior 23(3), 609–616. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Li L, Tuan NA, Liang LJ, Lin C, Farmer SC, Flore M, 2013. Mental health and family relations among people who inject drugs and their family members in Vietnam. Int J Drug Policy 24(6), 545–549. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Liu L, Chui WH, Chai X, 2018. A qualitative study of methamphetamine initiation among Chinese male users: Patterns and policy implications. Int J Drug Policy 62, 37–42. [DOI] [PubMed] [Google Scholar]
  47. MacArthur GJ, van Velzen E, Palmateer N, Kimber J, Pharris A, Hope V, Taylor A, Roy K, Aspinall E, Goldberg D, Rhodes T, Hedrich D, Salminen M, Hickman M, Hutchinson SJ, 2014. Interventions to prevent HIV and Hepatitis C in people who inject drugs: a review of reviews to assess evidence of effectiveness. Int J Drug Policy 25(1), 34–52. [DOI] [PubMed] [Google Scholar]
  48. Maremmani AG, Rovai L, Pani PP, Pacini M, Lamanna F, Rugani F, Schiavi E, Dell’osso L, Maremmani I, 2011. Do methadone and buprenorphine have the same impact on psychopathological symptoms of heroin addicts? Ann Gen Psychiatry 10, 17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Maremmani AG, Rovai L, Rugani F, Bacciardi S, Dell’Osso L, Maremmani I, 2014. Substance abuse and psychosis. The strange case of opioids. Eur Rev Med Pharmacol Sci 18(3), 287–302. [PubMed] [Google Scholar]
  50. Marks C, Borquez A, Jain S, Sun X, Strathdee SA, Garfein RS, Milloy MJ, DeBeck K, Cepeda JA, Werb D, Martin NK, 2019. Opioid agonist treatment scale-up and the initiation of injection drug use: A dynamic modeling analysis. PLoS Med 16(11), e1002973. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Marshall BD, Werb D, 2010. Health outcomes associated with methamphetamine use among young people: a systematic review. Addiction 105(6), 991–1002. [DOI] [PubMed] [Google Scholar]
  52. Mattick RP, Breen C, Kimber J, Davoli M, 2009. Methadone maintenance therapy versus no opioid replacement therapy for opioid dependence. Cochrane Database Syst Rev(3), CD002209. [DOI] [PubMed] [Google Scholar]
  53. Mattick RP, Breen C, Kimber J, Davoli M, 2014. Buprenorphine maintenance versus placebo or methadone maintenance for opioid dependence. Cochrane Database Syst Rev(2), CD002207. [DOI] [PubMed] [Google Scholar]
  54. McCreesh N, Frost SD, Seeley J, Katongole J, Tarsh MN, Ndunguse R, Jichi F, Lunel NL, Maher D, Johnston LG, Sonnenberg P, Copas AJ, Hayes RJ, White RG, 2012. Evaluation of respondent-driven sampling. Epidemiology 23(1), 138–147. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. McKetin R, Leung J, Stockings E, Huo Y, Foulds J, Lappin JM, Cumming C, Arunogiri S, Young JT, Sara G, Farrell M, Degenhardt L, 2019. Mental health outcomes associated with of the use of amphetamines: A systematic review and meta-analysis. EClinicalMedicine 16, 81–97. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. McKetin R, McLaren J, Lubman DI, Hides L, 2006. The prevalence of psychotic symptoms among methamphetamine users. Addiction 101(10), 1473–1478. [DOI] [PubMed] [Google Scholar]
  57. Michel L, Nguyen LT, Nguyen AK, Ekwaru JP, Laureillard D, Nagot N, Phan O, Khuat OTH, 2020. Exposure to HIV risks among young people who use drugs (YPUD) in three cities in Vietnam: time to develop targeted interventions. Harm Reduct J 17(1), 13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Molero Y, Zetterqvist J, Binswanger IA, Hellner C, Larsson H, Fazel S, 2018. Medications for Alcohol and Opioid Use Disorders and Risk of Suicidal Behavior, Accidental Overdoses, and Crime. Am J Psychiatry 175(10), 970–978. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Nguyen MX, Go VF, Bui QX, Gaynes BN, Pence BW, 2019. Perceived need, barriers to and facilitators of mental health care among HIV-infected PWID in Hanoi, Vietnam: a qualitative study. Harm Reduct J 16(1), 74. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Noroozi A, Malekinejad M, Rahimi-Movaghar A, 2018. Factors Influencing Transition to Shisheh (Methamphetamine) among Young People Who Use Drugs in Tehran: A Qualitative Study. J Psychoactive Drugs 50(3), 214–223. [DOI] [PubMed] [Google Scholar]
  61. Oviedo-Joekes E, Guh D, Brissette S, Marchand K, Marsh D, Chettiar J, Nosyk B, Krausz M, Anis A, Schechter MT, 2010. Effectiveness of diacetylmorphine versus methadone for the treatment of opioid dependence in women. Drug Alcohol Depend 111(1–2), 50–57. [DOI] [PubMed] [Google Scholar]
  62. Pacini MM, I., 2005. Methadone reduces the need for antipsychotic and antimanic agents in heroin addicts hospitalized for manic and/or acute psychotic episodes. Heroin Add & Rel Clin Probl 7(4), 43–48. [Google Scholar]
  63. Pani PP, Vacca R, Trogu E, Amato L, Davoli M, 2010. Pharmacological treatment for depression during opioid agonist treatment for opioid dependence. Cochrane Database Syst Rev(9), CD008373. [DOI] [PubMed] [Google Scholar]
  64. Patel V, Araya R, Chatterjee S, Chisholm D, Cohen A, De Silva M, Hosman C, McGuire H, Rojas G, van Ommeren M, 2007. Treatment and prevention of mental disorders in low-income and middle-income countries. Lancet 370(9591), 991–1005. [DOI] [PubMed] [Google Scholar]
  65. Petersen MR, Deddens JA, 2008. A comparison of two methods for estimating prevalence ratios. BMC Med Res Methodol 8, 9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Pham Minh K, Vallo R, Duong Thi H, Khuat Thi Hai O, Jarlais DCD, Peries M, Le SM, Rapoud D, Quillet C, Nham Thi TT, Hoang Thi G, Feelemyer J, Vu Hai V, Moles JP, Pham Thu X, Laureillard D, Nagot N, Michel L, Study Team D, 2018. Psychiatric Comorbidities among People Who Inject Drugs in Hai Phong, Vietnam: The Need for Screening and Innovative Interventions. Biomed Res Int 2018, 8346195. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. R Core Team, 2016. R Foundation for Statistical Computing. Vienna, Austria. [Google Scholar]
  68. Regier DA, Farmer ME, Rae DS, Locke BZ, Keith SJ, Judd LL, Goodwin FK, 1990. Comorbidity of mental disorders with alcohol and other drug abuse. JAMA 264(19), 2511–2518. [PubMed] [Google Scholar]
  69. Reimer J, Verthein U, Karow A, Schafer I, Naber D, Haasen C, 2011. Physical and mental health in severe opioid-dependent patients within a randomized controlled maintenance treatment trial. Addiction 106(9), 1647–1655. [DOI] [PubMed] [Google Scholar]
  70. Salo R, Flower K, Kielstein A, Leamon MH, Nordahl TE, Galloway GP, 2011. Psychiatric comorbidity in methamphetamine dependence. Psychiatry Res 186(2–3), 356–361. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Schafer I, Eiroa-Orosa FJ, Verthein U, Dilg C, Haasen C, Reimer J, 2010. Effects of psychiatric comorbidity on treatment outcome in patients undergoing diamorphine or methadone maintenance treatment. Psychopathology 43(2), 88–95. [DOI] [PubMed] [Google Scholar]
  72. Schmauss C, Emrich HM, 1985. Dopamine and the action of opiates: a reevaluation of the dopamine hypothesis of schizophrenia. With special consideration of the role of endogenous opioids in the pathogenesis of schizophrenia. Biol Psychiatry 20(11), 1211–1231. [DOI] [PubMed] [Google Scholar]
  73. Schuckit MA, 2006. Comorbidity between substance use disorders and psychiatric conditions. Addiction 101 Suppl 1, 76–88. [DOI] [PubMed] [Google Scholar]
  74. Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, Hergueta T, Baker R, Dunbar GC, 1998. 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 59 Suppl 20, 22–33;quiz 34–57. [PubMed] [Google Scholar]
  75. Sunkel C, 2012. Empowerment and partnership in mental health. Lancet 379(9812), 201–202. [DOI] [PubMed] [Google Scholar]
  76. Teesson M, Ross J, Darke S, Lynskey M, Ali R, Ritter A, Cooke R, 2006. One year outcomes for heroin dependence: findings from the Australian Treatment Outcome Study (ATOS). Drug Alcohol Depend 83(2), 174–180. [DOI] [PubMed] [Google Scholar]
  77. Tenore PL, 2008. Psychotherapeutic benefits of opioid agonist therapy. J Addict Dis 27(3), 49–65. [DOI] [PubMed] [Google Scholar]
  78. Tomori C, Go VF, Tuan le N, Huong NM, Binh NT, Zelaya CE, Celentano DD, Dat do T, Quan VM, 2014. “In their perception we are addicts”: social vulnerabilities and sources of support for men released from drug treatment centers in Vietnam. Int J Drug Policy 25(5), 897–904. [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. van den Brink W, Hendriks VM, Blanken P, Koeter MW, van Zwieten BJ, van Ree JM, 2003. Medical prescription of heroin to treatment resistant heroin addicts: two randomised controlled trials. Bmj 327(7410), 310. [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Volz E HD, 2008. Probability based estimation theory for respondent driven sampling. Journal of Official Statistics 24(79). [Google Scholar]
  81. Ward J, Hall W, Mattick RP, 1999. Role of maintenance treatment in opioid dependence. Lancet 353(9148), 221–226. [DOI] [PubMed] [Google Scholar]
  82. WHO, 2013. Mental health action plan 2013–2020. [Google Scholar]
  83. Wouldes TA, LaGasse LL, Derauf C, Newman E, Shah R, Smith LM, Arria AM, Huestis MA, DellaGrotta S, Wilcox T, Neal CR Jr., Lester BM, 2013. Co-morbidity of substance use disorder and psychopathology in women who use methamphetamine during pregnancy in the US and New Zealand. Drug Alcohol Depend 127(1–3), 101–107. [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Xiao L, Wu Z, Luo W, Wei X, 2010. Quality of life of outpatients in methadone maintenance treatment clinics. J Acquir Immune Defic Syndr 53 Suppl 1, S116–120. [DOI] [PMC free article] [PubMed] [Google Scholar]

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