Background

Global mental health

Quality and accessible mental health services, including substance use disorder services, in low-resource settings are increasingly being recognized as issues of global importance [1,2,3]. In 2016, the adoption of the United Nations 2030 Sustainable Development Goals (SDGs) pushed for the prioritization of focused action in the field of mental healthcare and substance abuse treatment and prevention [1, 3]. The inclusion of mental health and well-being in the SDGs was motivated by previous calls for action and research findings urging to increase the level of care for mental and substance use disorders [3,4,5]. Mental health and substance use disorders are the world’s leading cause of years lived with disability (YLDs) and account for 183.9 million disability-adjusted life years (DALYs) [6]. Moreover, substance use disorders can best be understood as primarily mental health conditions; SUDs are often treated by mental health professionals in specialized clinics, hospitals, or out-patient treatment programs.

In low-and middle-income countries (LMICs) the treatment gap for mental disorders is between 76 and 85%, meaning that at least three fourths of people with a mental disorder do not receive treatment [2]. In this context, two key objectives outlined in the WHO Mental Health Action Plan and the UN SDGs are to scale-up community-based mental health services and “strengthen the prevention and treatment of substance abuse” [1, 2].

Low-and-middle income countries (LMICs) are defined as those classified as such by the World Bank [7]. Research has shown that the insufficient quality, availability, and funding for mental and substance use disorder services is a significant barrier for the improvement of mental health systems in LMICs [8, 9]; high-income countries (HICs) spend up to twenty times more than low-income countries on mental health-related prevention, treatment, management, and educational programs [10]. Stakeholders in LMICs believe that four mechanisms are key in order to increase the availability and quality of mental health services: the de-centralization of psychiatric institutions, the implementation of community-based mental health services, the increased availability of adequately trained and supervised mental health staff, and the incorporation of mental health care into primary care settings and general hospitals [11]. Addressing these barriers will be essential in order to narrow the current treatment gap and improve services for mental and substance use disorders in LMICs, and with that reduce the disproportionately high burden of disease due to mental disorders in these settings.

Barriers to the scaling up of substance abuse treatment and prevention efforts in LMICs include a low prioritization of the problem, an inability to detect and treat non-severe substance use disorders at an early stage and in the community, and lower help-seeking by affected populations due to fear of stigma or normative cultural views on substance use [12,13,14,15,16,17]. These persistent political, structural, and sociocultural issues continue to obstruct efforts to provide effective and equitable care services to the mental health populations most in need of them in LMICs [8, 11, 18, 19].

Substance use disorders in low-and-middle income countries

People suffering from psychoactive substance use disorders (SUDs) make up a large portion of the underserved mental health population, accounting for at least 20.5% of the 183.9 million DALYs due to mental disorders [6]. This review defines SUDs according to the ICD-10 classification, that is, “mental and behavioral disorders due to psychoactive substance use” including acute intoxication, harmful use, dependence syndrome, withdrawal state, withdrawal state with delirium, psychotic disorder, amnesic syndrome, and residual late-onset psychotic disorder [20]. Psychoactive substances include alcohol, opioids, cannabinoids, sedatives, cocaine, stimulants, hallucinogens, tobacco and volatile solvents [20].

This review focuses on SUDs related to alcohol, cannabis, cocaine, opioid, and amphetamine-type stimulant use, as these have a greater correlation with treatment entry and with comorbidity with other mental disorders [6, 21]. Treatment gap estimates for substance use disorders in LMICs range from 75–95%, with the gap being greater in rural areas [16, 17, 22, 23]. SUD-affected populations in LMICs are two to ten times less likely to receive minimally adequate treatment (defined as the minimum number of visits to treat a disorder) and those with a SUD in these settings are less able to recognize their need for treatment than their HIC counterparts [12, 21]. Further, although harmful alcohol use contributes to a greater portion of the alcohol-related harm in LMICs than alcohol dependence, many LMICs place a greater focus on detecting and treating alcohol dependence; as a result, harmful/hazardous drinkers are often not identified early on and receive care only when their condition has progressed significantly [24]. Although the same cannot be said with regards to illicit substance use due to a lack of data globally, it has been mentioned that “there is a need to improve our understanding of these basic epidemiological questions about illicit drug use and dependence in order to improve our capacity to respond” [25]. In this context, prioritizing efforts to screen for and treat harmful substance use would present significant benefits to LMICs (i.e. by reducing alcohol-related harm, improving prevention of dependence, and generating previously lacking epidemiological data).

The barriers toward the scale-up of SUD treatment and prevention in LMICs may also be related to how SUDs are formally conceptualized and addressed in these settings. The criminalization of illicit substance use poses unique challenges to the field of public health as it not only limits the range of possible SUD treatment or prevention services in a given setting, but it may also increase the negative health effects and other health risks (e.g. of intimate partner violence, HIV/AIDS, tuberculosis) among drug-using populations [26,27,28,29,30]. Only recently—in 2016, at the United Nations General Assembly Special Session on drugs—have more countries agreed to recognize SUDs as “complex multifactorial health” disorders and begun to shift from a punishment approach towards a public health approach [31]. However, despite this step in the right direction, there remain significant knowledge and implementation gaps in the field of SUD care in LMICs, with actions still largely limited to the dissemination of recommendations and materials [26, 31].

Substance use disorder treatment and prevention

The ecology of SUDs involves “intrapersonal, inter-personal, and broader systems-level processes” which, from a public health perspective, should each be addressed sufficiently [32, 33]. As mentioned previously, SUDs may range from mild (acute intoxication and harmful use) to severe (dependence and withdrawal syndrome), which means that different intervention types, intervention settings, and intervention intensities are necessary to address the care needs of the entire SUD population [32, 34]. Persons with SUDs may receive treatment through specialized treatment settings such as in-patient detoxification and rehabilitation services, through residential treatment and therapeutic communities, through other mental health services, mutual help organizations, or through outpatient hospital and primary care services; however, there is limited information about the arrangement and functioning of such services in LMICs [13, 15].

An ‘indicated prevention’ approach is recommended to prevent the further development of the disorder in cases of harmful substance use [35], that is, a pattern of use not yet characterized as dependence but which causes physical or mental damage to health [20]. Indicated prevention interventions may be defined as brief “client-centered, goal-oriented” psychosocial interventions with educational and motivational components; they have shown positive results in LMICs when delivered by a non-specialized, primary care workforce in rural and community settings [35]. That said, there is currently insufficient evidence about what intervention models and characteristics may be suitable to address the needs of various SUD populations in LMICs.

Substance use disorder interventions may be pharmacological and/or psychosocial in nature. Pharmacological interventions are normally delivered during the early stages of treatment and involve using antagonist and withdrawal-reducing medications to alleviate withdrawal symptoms and facilitate treatment adherence for physically dependent individuals [32, 36, 37]. Psychosocial SUD interventions are usually face-to-face interventions that focus on the psychological and social aspects of a person’s life [38, 39]. Examples of psychosocial SUD interventions include cognitive-behavioral therapy (CBT), brief interventions (including indicated prevention interventions), interpersonal therapy, self-help groups, family therapy, motivational interviewing, and relapse prevention [34, 38]. Lastly, the sociocultural environments in which interventions are delivered may further affect their effectiveness and implementation (e.g. feasibility and acceptability); studies have shown that culturally-adapting psychosocial SUD interventions may result in improved implementation outcomes by addressing context-specific factors such as stigma, ethnicity and cultural beliefs [40,41,42,43,44]. So far, there is limited evidence about the extent to which SUD interventions are culturally adapted in LMICs or about the facilitators, barriers, or common elements involved in this process.

Community-based SUD interventions

Community mental health and SUD interventions present significant advantages for mental health service users and systems in LMICs such as reduced costs, greater reach, decreased stigma, and improved quality of life and community functioning for affected populations [32, 45,46,47]. This review defines community-based mental health interventions as decentralized interventions integrated into primary care settings or general hospitals which are supported by collaborations between a range of stakeholders (formal and informal) and which aim to facilitate independent community functioning and rehabilitation through education, self-care, “goal setting, skills development, and… access to community and environmental resources” [2, 48]. Based on this definition, examples of community-based mental health and SUD interventions may include psychosocial interventions delivered through community facilities, outpatient care settings or mental health centers, “support of people with mental disorders living with their families, supported housing”, assertive community treatment, and pharmacological and harm-reduction interventions [2, 47].

There seems to be a growing number of efforts to implement community-based SUD services in LMICs that are responsive to context-specific needs, possibilities, and barriers [35, 49,50,51]. Although this topic has not has not yet been systematically investigated, previous individual studies from LMICs have demonstrated that various resource, sociocultural and/or political factors may influence the development, implementation and/or outcomes of community-based SUD interventions [35, 49, 50, 52]. Therefore, an initial attempt to systematically identify and describe the relevant contextual factors that may affect community-based SUD interventions in LMICs seems warranted.

In summary, considering the high prevalence of SUDs in LMICs and the discussed barriers to scale-up SUD services in these settings, there has been an increased demand to implement cost-effective community-based SUD interventions in LMICs. However, the translation into practice is still lacking and research on this matter, especially in relation to psychosocial interventions, remains scarce and limited to high-income settings [2, 32, 35].

Aims

This review aimed to identify and describe the different types and characteristics of psychosocial community-based SUD interventions in LMICs, and explore what context-specific factors (i.e. policy, resource, sociocultural) may influence such interventions in their design, implementation, and/or outcomes.

Methods

A narrative literature review was conducted on community-based substance use disorder intervention studies from LMICs. This method was seen as the most suitable research design because such reviews seek to identify and discuss information from various sources about relatively broad topics, topics that have not-yet been sufficiently addressed, and/or topics for which quantitative meta-analysis would not be the suitable [53, 54]. This review followed a systematic data collection process using a defined set of criteria and standardized data extraction tools, which are recommended in order to minimize bias and increase the quality of narrative reviews [54]. For the PRISMA checklist, see Additional file 1: Appendix S4.

The narrative synthesis process for this review was inspired by the Guidance on the Conduct of Narrative Synthesis in Systematic Reviews (CNSSR) [55]. First, a preliminary synthesis of the intervention characteristics was developed and presented through textual descriptions and tabulation. Thereafter, a content and brief thematic analysis was conducted based on the (manually) coded data extracted from the included studies. The data coding process used both deductive and inductive coding techniques [56,57,58].

Eligibility criteria

Tables 1 and 2 outline the inclusion and exclusion criteria for this review based on the PICOS model (participants, interventions, comparisons, outcomes, and study design). Since the aim of this review was to identify and describe the characteristics of community-based SUD interventions, all study designs were included if they contained a description of the intervention and the process of implementation. No limits were placed on study comparisons or reported outcomes to ensure that the greatest variety of interventions were included.

Table 1 Inclusion and exclusion criteria
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Table 2 Exclusion Criteria
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To be included, interventions had to be psychosocial face-to-face interventions delivered in community settings as described in the background section of this manuscript. Interventions had to be targeted at people identified as having a psychoactive substance use disorder due to alcohol, cannabis, cocaine, opiate, or amphetamine-type stimulant use with or without a formal diagnosis; this was to ensure that all interventions for these populations were included regardless of resource limitations or differences in diagnostic materials/standards used [35, 46, 59]. Prevention intervention studies were only included if they fit the criteria for “indicated prevention” according to Kane and Greene, that is, “programs that are targeted towards those who are not only at higher risk for an outcome but who have signs and symptoms… of the outcome itself [i.e. substance use, acute intoxication, harmful use]” [35]. Interventions targeting vulnerable populations, such as HIV-positive populations, were only included if these populations (or a sub-set thereof) also had a SUD and if the interventions also targeted the SUD. As this is an exploratory review, no limits were placed on reported outcomes and no risk of bias assessment was conducted.

Data collection

Articles were obtained via a search for abstracts on the MEDLINE, Academic Search Complete and PsycINFO databases using the EBSCOHOST online repository [60,61,62]. The search terms used were based on this study’s inclusion criteria and the Medical Subject Headings (MeSH) substance-related disorders, community health services, primary health care, psychiatric rehabilitation and community psychiatry. In addition, the search string used for this review was informed by terms used in previous reviews relevant to this research topic [35, 42, 63,64,65,66]. In summary, the search string used in this review covered four key concepts for which related terms were used: (1) psychoactive substance use disorders, (2) psychosocial intervention, (3) community-based, and 4) low-and middle-income country. Additional file 1: Appendix S1 outlines the search string used for this review and special limiters applied.

After duplicates were removed, all abstracts were screened using a screener sheet (Additional file 1: Appendix S2) that was based on this review’s inclusion criteria to determine if articles may be eligible for inclusion. When there were uncertainties about the eligibility of articles, these were discussed with and reviewed by a second reviewer (BJHW, the second author of this manuscript).

Data coding and analysis

A data capture sheet (Additional file 1: Appendix S3) was developed based on the screener sheet and previously developed materials [67,68,69] to further inform inclusion decisions and ensure the systematic collection of relevant data. Thus, the data capture sheet served as the coding framework for this review and facilitated the systematic identification of the main study characteristics.

The pre-defined topics used for deductive coding were those that focused on what/how policy, resource, or sociocultural factors influenced interventions in their design, implementation, and/or outcomes [55, 56]. Context-specific barriers and facilitators were initially defined as the sociocultural, political or resource factors that were reported by the authors to have had an impact on the interventions’ design, implementation and/or outcomes. However, early in the coding process it became apparent that the authors’ discussions of these factors in the context of barriers and/or facilitators were significantly limited across studies. Therefore, to allow for some description and analysis of these contextual factors, the data extraction approach was expanded to include any discussion of political, resource, sociocultural and/or implementation factors that may have played a role, either explicitly or implicitly, in the rationale for, planning, delivery, and/or outcomes of the interventions (see Additional file 1: Appendix S3). Lastly, any additional or emerging themes from the extracted data were identified and discussed [56].

Results

Included articles

Figure 1 shows the article selection process of this review according to PRISMA guidelines. Out of 908 abstracts screened, 24 full-text articles were assessed for eligibility; out of these 24, nine articles were cross-checked for eligibility by a second reviewer and eventually excluded. Finally, a total of 15 articles were included for this review. Ten out of the 15 included studies were published in or after 2015, suggesting that there has been a relatively recent increase in efforts to implement and/or study community-based SUD interventions in LMICs. Table 3 presents the key characteristics of the included studies, and Table 4 a description of the interventions and a summary of their findings. The italicized text in Tables 3, 4, and 5 are direct quotations that have been extracted from the included studies.

Fig. 1
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Screening and selection of eligible studies

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Table 3 Characteristics of included studies
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Table 4 Descriptions of the interventions and main findings
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Table 5 Contextual factors coded data
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Of the 15 included studies, 13 were randomized controlled trials (RCTs), one was a retrospective cross-sectional study, and one was a pre-post study. Of the 13 RCTs, one was an updated RCT protocol of a trial completed in March of 2019 but for which no final results have yet been published; however, the protocol was included as it includes preliminary data relevant to the scope of this review [70]. Several ‘sister articles’ were identified during the screening and study selection process, that is, different publications which discussed the same intervention; in such cases, data was extracted from both publications when relevant (see ‘Reference’ column in Tables 3 and 4). Furthermore, when authors described relevant information related to an included study (such as the detailed methodology) in other articles, data was also extracted from these articles even if they were not identifiable within the initial 908 search results.

Study characteristics

This review’s first aim was to identify and describe the characteristics of the included studies; Table 3 provides an overview of these characteristics (i.e. setting, study design and objectives, target population and condition, and intervention objectives).

Nearly every study was carried out in one LMIC, with the exception of two RCTs which were carried out in four and in three countries. In the RCT carried out in four countries [71], two countries were HICs (Australia and the United States). Overall, intervention settings ranged from 1–40 sites per country (e.g. districts, cities, neighborhoods, primary healthcare centers) and all but two of the interventions were delivered in more than one site per country. The most common intervention delivery settings were primary health care centers (PHCs) (n = 8 interventions), hospital out-patient settings (n = 3 interventions), neighborhoods (n = 3 interventions) and specialized SUD treatment settings (n = 2 interventions). Moreover, other than one Thai study which was conducted in only rural areas [72], two studies included both rural and urban areas, although this data was not uniformly reported across all studies. In total, 18 SUD treatment or indicated prevention interventions were implemented across 12 countries (excluding Australia and the USA, as they are HICs): five countries (10 interventions) in Asia, three countries (six interventions) in Africa, one country (one intervention) in Eastern Europe, and one country (two interventions) in South America. Per country, the most interventions were implemented in South Africa (n = 3), India (n = 3), Thailand (n = 2), China (n = 2) and Brazil (n = 2); all are currently upper-middle income countries except for India, which is lower-middle income. None of the included studies were conducted in a low-income country.

Table 4 provides a summary of the interventions’ characteristics (including the intervention model/s used, intervention objectives, intervention components, the duration of the interventions, the persons delivering the interventions, and the implementation method) and the findings of the included studies. It should be noted that not all of this data was uniformly reported across the included studies.

Eleven studies targeted both men and women (one of which targeted family units which could include children), two studies, which were set in India, targeted only males [41, 73], and two studies targeted only women (one focused on female sex workers and the other on pregnant women) [74, 75]. Of the 11 studies which targeted both men and women, all of them recruited significantly more men than women with a SUD. However, it is worth noting that about 80% of the women recruited in the three-country study came from Ukraine (the other two countries were Vietnam and Indonesia), which the study authors claimed was reflective of differences in local views (e.g. stigma) and help-seeking behaviors across settings [76, 77]. Population sizes across studies ranged from 69 participants in a single-site cross-sectional study to 1196 participants in the Ukraine-Vietnam-Indonesia RCT.

As per this review’s inclusion criteria, all of the interventions were psychosocial in nature and addressed a range of SUDs. Nearly half of the interventions (n = 9) targeted SUDs alongside other priority conditions or objectives according to the setting, such as HIV and/or tuberculosis (TB), substance-use (SU) related and risky sexual behaviors (n = 2), maternal health (n = 1), response after a natural disaster (n = 1), and intimate partner violence (IPV) (n = 1). Furthermore, nine out of the 18 interventions included in this study addressed alcohol use disorders exclusively; five interventions addressed the use of multiple substances; three interventions targeted intravenous drug use; and one intervention targeted opiate dependent participants. The interventions varied considerably in terms of target SUD and the conditions targeted alongside the SUDs.

Regarding the specific intervention types, screening and brief intervention (SBI) interventions were proportionately the most commonly implemented (n = 10 interventions). All of the brief interventions were based on previously developed guides, protocols, or models (for examples, see 78,79,80,81). Although the content, intensities, and lengths of the brief interventions varied, they all shared the core objectives/traits of problem identification through discussion of substance use behaviors, psychoeducation about SU-related risks and consequences, goal-and-motivation-setting to reduce substance use, and feedback and follow-up. The brief interventions could consist of anywhere between 1–6 sessions and the sessions could last anywhere between 8 and 45 min across studies. In addition to the brief interventions, there were: three CBT-based interventions, one long-term social reintegration and housing-support intervention, and four interventions which essentially consisted of peer outreach, provision of information, and practical and psychosocial support.

Context-specific factors in community-based SUD care

The second aim of this review was to identify and discuss what/how context-specific factors influenced interventions in their design, implementation and/or outcomes. For this, article data was initially extracted on the reported barriers and facilitators related to these factors (see Additional file 1: Appendix S3), however, as mentioned earlier, explicit reports and discussions of these factors in the context of barriers and/or facilitators were significantly limited across studies (this is partly reflected by the general lack of data in Table 5). Therefore, to allow for some description and analysis of these contextual factors, the data extraction approach was expanded to include any political, resource, sociocultural and/or implementation factors that may have played a role in the rationale for, planning, delivery, and/or outcomes of the interventions. Accordingly, in this section, we discuss the topics of ‘cultural adaptations made’ and the ‘training and use of non-professionals’, as these topics directly reflect how sociocultural and resource factors influenced the interventions.

Sociocultural and resource factors

The two most discussed contextual factors were resource and sociocultural factors, which generally appeared to be related. Specifically, the training and use of non-professionals to deliver the interventions (in 11 studies) was often described as a strategy to address local resource limitations and, to a somewhat lesser extent, sociocultural perspectives in different settings. Moreover, the trainings for non-professionals generally consisted of understanding the disorder/objective in question, learning patient-centered communication techniques, and practicing acquired skills [50, 73, 82,83,84]. These findings may indicate that training non-professionals to deliver community-based SUD interventions in LMICs may be a strategy to address local resource and/or sociocultural barriers.

Regarding the sociocultural factors considered for the planning and delivery of the interventions, the main topics discussed across the included studies were: societal perspectives about gender differences [83], stigma [43], low literacy rates among target populations [41, 85], specific substance use behaviors [50, 83, 85, 86], specific help-seeking behaviors [82]. These factors were discussed in the context of the adaptations that were made to the interventions in order to improve their acceptability by the target populations. For example, in one study, gender stratification of group sessions was “deemed necessary to avoid reinforcement of the secondary status of women and encourage their open discussion and engagement in treatment” [43], while in other studies images were used to assist less literate participants in understanding certain topics [75] or “engage patients in treatment” in a culturally acceptable way [41, 73]. Lastly, nearly all of the studies reported to have translated screening, training and/or intervention materials into local languages. Despite these findings on the sociocultural factors considered for the planning and tailoring of some interventions, this topic was not addressed in most studies, as is reflected by the general lack of data under the ‘cultural adaptations made’ column in Table 5 .

The sociocultural factors that influenced the execution and results of the studies included: stigma against female substance use behaviors [76, 77], limited education/literacy (leading to limited engagement) [41], particular help-seeking behaviors due to fear of stigma [87], local views on punctuality (leading to limited engagement) [83], and the event of a local holiday (which influenced substance use patterns) [72]. Based on these factors, some studies recommended that future interventions should be adapted to improve acceptability by female populations, enhance help-seeking behaviors, and focus more on specific substance use patterns per setting.

The resource-related factors that affected the interventions’ implementation and/or outcomes included: financial and time limitations by the participants, leading to lower participation [41]; the limited capacity of non-professional “counsellors to achieve the standards of competence to deliver” an intervention [41]; the limited capacity to deliver trainings that were in line with “current international standards” [72]; and constraints which impeded significant changes to be detected and/or measured over time [50, 88]. In addition to the use of non-professionals for intervention delivery, few further resource facilitators were discussed across studies.

According to some authors, the characteristics and outcomes of their interventions demonstrated that it was feasible and acceptable to deliver such interventions in LMICs despite possible financial, demographic, and awareness (both societal and from participants) barriers [41, 50, 73, 76, 86, 89]. The few resource-related facilitators to the interventions that were identified involved reimbursing participants for participation and/or transportation costs [83], and task-sharing by non-professionals to adopt multiple yet simple functions [76]. Furthermore, findings from the Thai brief intervention study showed that delivering the brief intervention (which took about 8 min) was as effective in reducing substance use as simple advice (control condition, which took about 4 min); according to the authors, these findings are relevant for future decision-making in low-resource settings where large populations need to be screened in a short amount of time [86]. These examples may reflect (albeit in a limited sense) how SUD interventions in LMICs may be adapted to increase acceptability and be more responsive to the available resources in a given setting.

Policy-related factors

Only three studies explicitly discussed any influence of policies or governments on the planning, implementation, and/or outcomes of the interventions. In the first study, the Brazilian ‘recovery housing’ intervention was introduced as a government-funded program in response to the “growing public health and social security issue” of substance abuse in the country [87]. Moreover, a policy-related barrier discussed in the ‘recovery housing’ intervention was that most participants were not eligible to receive government benefits because of local law arrangements [87]. Second, during the Thai brief intervention study, “the Thai Government launched a new initiative… [to decrease the number of substance] users by 400,000” in 1 year through a number of strategies, including compulsory treatment [86]; although the authors claim that this initiative likely influenced the study’s favorable outcomes, there was no discussion about the mechanisms by which this could have happened, that is, for example, whether the government initiative was genuinely effective in reducing substance use, or whether it influenced participants’ self-report of substance use to possibly avoid compulsory treatment. Third, authors from the Indonesia-Ukraine-Vietnam study reported that although access to medication assisted treatment (MAT) is still limited in these settings, it has been increasing “due to changes in health policy” in the three countries, therefore, more positive results may be seen in future follow-ups [76]. Lastly, although government funding and/or collaborations were not discussed as facilitators per se, it is worth noting that six studies were at least partly supported by national governmental organizations; the rest received funding from international health/development organizations such as the National Institutes of Health (NIH), the United States Agency for International Development (USAID), the World Health Organization (WHO), and the United States Centers for Disease Control and Prevention (CDC).

Discussion

This review sought to identify and describe the characteristics of psychosocial community-based SUD interventions in LMICs. Furthermore, this review aimed to discuss the relevant context-specific factors in the field based on the information reported within the included studies. The fact that ten of the fifteen studies were published in or after 2015 (all of them after 2010) suggests a recent rise in efforts to study community-based SUD treatment and indicated prevention interventions in LMICs, which is in-line with recent international calls for action [1,2,3]. Moreover, the proportionately high number of interventions delivered by non-professionals in this review is in-line with other recent findings in LMICs, strengthening the perspective that utilizing non-professionals is a good practice and convenient strategy to implement community-based SUD services in settings with limited resources [90, 91]. Although these are positive findings for the field of SUD care in LMICs, the low total number of studies identified and the heterogeneity among them still reflect a significantly limited evidence-base on the topic. The heterogeneity across studies is not surprising given this review’s broad inclusion criteria and considering the complexities involved in implementing and studying community-based SUD interventions in different settings. However, researchers and project leaders in the field can and should reinforce the importance of reporting and examining interventions in terms of the sociocultural, resource, and political context factors discussed in this review; this is especially relevant because of the variable and mature nature of this field. If the burden of SUDs in LMICs is to be reduced and if SUD services are to become more accessible and more responsive to different settings, then efforts to understand and report the influences of context will need to be intensified. With this greater understanding about how contextual factors may influence the utility, acceptability, adoption, feasibility and/or sustainability of SUD interventions in various settings, project leaders will be better able to design and tailor future SUD interventions in the most appropriate manner.

Most of the included studies were carried out in upper-middle-income countries; no studies were from low-income countries. This finding limits our review’s ability to address its research aims with respect to low-and-middle income countries. In addition to the likely greater capacity of upper-middle-income countries to implement community-based SUD interventions, the greater concentration of interventions in these settings could also be due to their seemly greater need for such interventions, as reports have shown that three times more DALYs are lost there due to substance use than in low-income countries [21]. However, low-income countries also more frequently lack adequate “data collection systems on epidemiology and treatment” of SUDs, which limits the credibility of reports on the matter [21]. With that in mind, the absence of studies from low-income countries that met this review’s criteria could also be explained by the likely greater focus on gathering epidemiological data and improving routine data collection systems in low-income countries. Indeed, a number of low-income-country prevalence studies were identified during this review’s article selection process [see 79, 80, 92, 93]. With that in mind, it may be useful to adapt/specify future research questions about SUD interventions or related studies to low-income countries or middle-income countries separately, as it appears to be a premature time to apply this review’s research questions to low-and middle-income countries.

To be included in this review, SUD interventions had to be treatment or indicated prevention interventions. Indicated prevention interventions were included because it has been found that a large proportion of at-risk harmful substance users are not sufficiently identified and/or treated [24, 35]. Most of the brief interventions included in this review could be considered to be indicated prevention interventions because they targeted harmful substance users [35, 94]; however, none of them were described as such by the authors. This may be because the field of mental health prevention is still in need of taxonomical clarifications regarding the different types of SUD prevention interventions [95, 96] and/or because ‘harmful substance use’ is itself classified as a sub-type of psychoactive substance use disorders in the ICD-10, which is incompatible with the concept of ‘prevention’. Despite this finding, the brief intervention/indicated prevention model seems to be the current first choice when it comes to implementing previously-reccommended accessible, low intensity and preventative SUD services in LMICs [14, 34, 35].

Most of the interventions in this review were somehow related to other priority conditions or goals in different settings, such as sexual behaviors, HIV, tuberculosis (TB), pregnancy, and intimate partner violence (IPV). Regarding the SUD-related characteristics of these integrated interventions, cognitive-behavioral techniques, motivational enhancement techniques, and (to a lesser extent) peer outreach were reported as key intervention components. Although unexpected, the proportionately high number of integrated programming interventions identified is not surprising as SUDs have been associated with higher rates of IPV, HIV & TB transmission, and risky sexual behaviors [29, 97, 98]. With that in mind, there are clear public health benefits to be gained from integrated SUD interventions, especially in low and middle income settings with large vulnerable populations [29, 99,100,101,102,103]. Integrated SUD interventions may also be particularly suited for LMICs considering the often-limited resources available to reach and treat large underserved populations in these settings [30, 104]. However, the number of integrated interventions identified in this review were too few and their characteristics too different to be able to highlight any further key characteristics among them. This review highlights an evidence-gap in the literature on the characteristics, development, mechanisms, and effects of multi-component, integrated interventions to address SUDs alongside other conditions, which should be addressed in future (possibly less systematic) reviews and studies.

Due to the high variability in the objectives, methods, and reporting styles of the included studies, little can be said about the context-specific factors that influenced the interventions in their rationale, implementation and/or outcomes. This is an interesting finding as previous calls for action and intervention materials have highlighted the importance of considering sociocultural, resource, and political barriers to the implementation of accessible mental and SUD services in LMICs [2, 32, 105]. Therefore, it was not predicted that these factors would be discussed as infrequently and inconsistently as they were across the included studies. This ‘reporting gap’ may be attributable to the generally lacking resources (financial and otherwise) to incorporate more complex research methods (such as implementation research approaches) to evaluate the role of these factors in LMIC settings. Our limited findings on this important theme should encourage funders, researchers and project leaders to prioritize investigating and reporting on the influence of contextual factors in the planning and delivery of SUD interventions.

A notable finding was that about one third of the interventions were adapted to accommodate local literacy rates, sociocultural beliefs on gender differences, help-seeking behaviors, and locally-bound substance use behaviors. This finding may add to the current literature about how community-based SUD interventions can potentially be adapted depending on the context [32, 40, 42]. Moreover, the translation and adaptation of intervention materials, as well as the use of non-professionals, may be useful strategies to address local resource and sociocultural barriers, although it may be challenging to sufficiently train non-professionals in some settings due to time and/or resource limitations [41, 72].

Limitations

In addition to the limitations that have already been mentioned, some important limitations of this review are that it did not quantitatively analyze the results of the included studies, asses their quality of evidence, or risk of bias. Statistical analyses of results was not within scope of this review, nor would it have been feasible given the heterogeneity of study results. Another limitation may lie in this review’s inclusion/exclusion criteria, as it was often challenging to determine which populations were “at an elevated risk” for SUDs in a way that fit this review’s criteria. Although this limitation was minimized by the assessments of a second, more experienced reviewer, it is still possible that a small number of studies were missed during the article selection process. Finally, as this review looked at only published peer-reviewed articles, publication bias may have affected the number of studies identified.

Conclusion

This review was a necessary first attempt to explore and describe the current evidence base in the field of community-based SUD care in LMICs. The findings of this review present relevant considerations for the future work of researchers, decision-makers and SUD intervention developers with regards to the planning, implementation and adaptation of community-based SUD interventions in LMICs. Future similar reviews may benefit from focusing on discrete (as opposed to multiple) context-specific factors and review literature beyond intervention studies (such as reports, policy papers, and other non-scientific literature). Authors of future community-based SUD intervention studies will need to prioritize discussing what/how contextual factors played a role in their interventions if this field is to develop further in LMICs. Indeed, sharing this knowledge and lessons learned would improve the utility of future similar reviews and it would enhance our global capacity design and implement community-based SUD interventions that are compatible and responsive to different settings.