Introduction

In 2014, the Joint United Nations Program on HIV/AIDS called for a rapid scaling-up of essential HIV prevention and treatment approaches to achieve the target of “90-90-90” by the year 2020 [1]. The worldwide “90-90-90” target calls for 90 % of people living with HIV (PLH) to be diagnosed, with 90 % of those receiving combination antiretroviral therapy (ART), and 90 % of PLH on antiretroviral therapy (ART) to sustain virological suppression [1, 2]. Achieving this target by 2020 would consequently, by 2030, decrease the global burden of HIV/AIDS by 90 % from that in 2010 [1]. The target is based on the HIV care continuum model, also known as the HIV treatment cascade. This model outlines the sequential steps or stages of HIV treatment that PLH transition from initial diagnosis to achieving viral suppression, and shows the proportion of PLH who are engaged at each stage. Parallel to the optimistic “90-90-90” target are the discouraging funding cuts to the Global Fund for AIDS, Tuberculosis and Malaria (GFATM) and the United States’ President’s Emergency Plan for AIDS Relief (PEPFAR), which together disproportionately affect practices relating to HIV (prevention and treatment) and addiction (harm reduction) treatment programs [3]. This issue has particular significance for Eastern European (e.g. Ukraine, Russia), Central Asian (e.g. Kazakhstan) and Asian (e.g. Vietnam, Malaysia) countries, where HIV epidemics are largely shaped by people who inject (PWIDs) and who use drugs (PWUDs) [2]. HIV-infected PWUDs and PWIDs are a key population who, in the absence of scaled-up prevention and treatment interventions, would likely experience suboptimal outcomes along the HIV continuum of care. Achieving the 90-90-90 target, particularly for this population would, therefore, require scaling up of integrated and comprehensive interventions, which are not only sustainable but also cost-effective.

A significant body of evidence, from both theoretical and public health perspectives, points to the influence of network-based strategies such as social network analysis (SNA) and social network based interventions (SNIs) on HIV prevention and treatment outcomes for PWIDs and PWUDs. For the purpose of this paper, we define social networks in a SNA as a group of individuals who knew each other prior to an intervention. In comparison, SNI is a ‘peer-driven-intervention’ (PDI) where the peers (either known or unknown a priori) play the role of educators of HIV prevention information, health advocates, or health buddies, supporting each other to improve ART adherence and retention in HIV care.

Prior research suggests drug users in one’s social network act as dysfunctional role models [4, 5], reinforce risky drug use behaviors [6, 7], increase likelihood of engaging in sexual risk behaviors [8–14], and consequently lead to poor HIV treatment outcomes [15]. Conversely, self-reported condom use is strongly associated with positive norms using condoms among social network members [12] and social support increases engagement in needle exchange [16, 17] and addiction treatment programs [18, 19]. In terms of structural characteristics of networks (e.g. size, density), several studies indicate strong association between high-risk sexual behavior [20–22], HIV infection [23], HIV transmission [24–26], and increased drug use. Other structural network characteristics, such as being a bridge population [27], centrality [28], and core-periphery relationships [29], have been identified as contributors to both sexual [27, 30] and drug injection-related HIV transmission [31].

From a broader public health perspective, some SNIs have demonstrated promising potential in their ability to reach a higher proportion of key populations (e.g. PWIDs/PWUDs), that are challenging to engage in communities, and populations that may be unable to travel to health services by themselves. These findings imply that efforts to prevent HIV transmission must incorporate the impact of social networks. Social networks can, therefore, play a dual role in HIV transmission: they serve as both the routes of transmission for the virus and the routes of dissemination for information related to HIV prevention and treatment services [32, 33].

The objective of this systematic scoping review was to identify and synthesize such extensive information on evidence-based network approaches (SNA and SNI) that strategically target HIV prevention and treatment in one or more steps along a HIV care continuum. The following key questions guide the scope of this review:

  1. 1.

    Given the heterogeneity of the usage of social network approaches, what are the different ways SNA and SNI are conducted, analyzed, and reported in the studies?

  2. 2.

    What is the distribution of the approaches identified in #1 in terms of their targeting outcome measures associated with HIV prevention and steps of a HIV care continuum?

  3. 3.

    Given the lack of clarity on recruitment methods and whether the networks are defined post hoc by the researchers, how are the social network members identified and involved in the SNIs?

  4. 4.

    What type of effect did the SNIs have on the intervention outcomes?

Methods

We started this scoping review with a systematic literature search and selection of studies in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [34–36]. Similar to systematic reviews and meta-analysis, scoping reviews also follow rigorous PRISMA guidelines for identifying a comprehensive set of relevant studies [34–36].

Search Strategy

An exhaustive search strategy was developed based on key terms, synonyms, and subject headings related to two groups: (1) social networks strategies and (2) study population of interest. For group one, the search consisted of the main term ‘social network’ and terms related to measuring and analyzing social networks such as ‘social network analysis’, ‘sociometrics’, ‘sociograms’, ‘sociomaps’, ‘egonetworks’, and ‘respondent driven sampling’. Names of software packages commonly used in SNA e.g. ‘UCINET’, ‘NetDraw’, and ‘Pajek’ were also used. The subject headings included were ‘social support’, ‘interpersonal relationships’, ‘cliques’, and ‘community support’.

For group two, the terms, subject headings, or combination of both included were ‘substance use’, ‘substance use disorder‘, ‘drug use’, ‘injecting drug use’, ‘non-injecting drug use’, ‘HIV’, ‘AIDS’, and ‘mental health’. We searched 5 electronic databases (MEDLINE, PubMed, PsycINFO, Social Science Citation Index, and Web of Science) and the website of International Social Network Analysis (www.insna.org). We also manually searched studies published in the journals of Social Networks and Connections, which are the two flagship publications of INSNA, the professional association for researchers interested in SNA. Studies were managed using an electronic bibliography (Endnote version X7).

Selection Criteria

Two primary inclusion criteria were used to select the studies:

  1. (1)

    sociometric analysis, egocentric network analysis, respondent-driven sampling (RDS), or social network-based intervention was part of the methodology of the study;

  2. (2)

    study population included substance users (PWUDs, PWIDs, and people with drinking problems) with or at risk for HIV.

We limited our review to peer-reviewed studies published in English between 1980 through February 2015. While social network approaches have evolved since the 1950s, HIV/AIDS and addiction research began in the 1980s and AIDS was not reported until 1981. Consequently, inclusion of studies was restricted to those published after 1980. Systematic reviews, meta-analysis, and studies that examined tobacco use, criminal justice system, biological studies of HIV/AIDS, and mental health issues not related to HIV/AIDS and substance use disorders as outcome measures were excluded from this review.

We further selected studies for our review using a two-stage process. First, four authors (DG, AK, BG, and SB) scanned titles, abstracts, and keywords identified from the search strategy (k = 6,241) and excluded them as appropriate based on the above-mentioned inclusion and exclusion criteria. To ensure reliability and consistency, the four authors assessed a pilot sample of 200 randomly selected studies independently on the basis of their title, abstract, and keywords. Both the included and excluded groups of studies from all the four authors were compared for consistency. Undecided studies, which needed further clarifications, were discussed collectively and resolved (either included and excluded). We repeated this pilot step in order for all the authors to understand and follow the inclusion and exclusion criteria consistently. These steps demonstrated good reliability (Cohen’s k = 0.74). A significant number of studies (k = 4,795) were excluded. The primary reason for exclusion was that SNA or SNI was not used as one of the analytical approach and social influence or relationships were measured and described by other techniques (Fig. 1).

Fig. 1
figure 1

Flowchart illustrating the selection of studies for the systematic review

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Second, the four authors thoroughly reviewed the methodology section of 1446 studies and further excluded 544 studies, resulting in 902 studies. To clarify, the database of 902 records was for multiple (but related) reviews under preparation by the same authors. This particular review comprised 58 studies where SNA or SNI was part of their methodology and the study population was substance users at-risk for or living with HIV/AIDS (Fig. 1).

Extraction and Charting the Results

Data extraction and charting of results were done at various stages by one author and thoroughly reviewed and audited by another for consistency, quality, and relevance [36]. First, we reviewed the full text of 58 studies and extracted information on the descriptive characteristics: year of publication, number of authors, name of the peer-reviewed journal, study population, study area, sample size, data collection, and types of social networks. Types of social network were further coded into two categories: risk networks (e.g. drug, sexual, and/or alcohol) and support networks (e.g. friends and/or family). We created a map of the different study locations, categorized by the outcome measures (HIV prevention and the steps of HIV care continuum) (Fig. 2).

Fig. 2
figure 2

Map of study locations from 58 included studies

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Second, to systematically identify the different social network strategies included in the methodology (refer to #1 key question), we used a data extraction form to collect and code information on: data collection (categories: whole network, egocentric network, or RDS), types of network measures (categories: size, structural, dyads, relation, and social network member properties), network measures as variables in statistical/mathematical models (categories: univariate, bivariate, multivariate regression, structural equation modeling, repeated measures, projection models, and agent-based models), and network-based intervention protocol.

Third, based on the outcome measures, the studies were grouped into 7 categories: HIV prevention, HIV testing and diagnosis, linkage to care, retention in care, ART prescription, ART adherence, and viral suppression. A cross tabulation was conducted between the types of social network strategies and outcomes measures (Fig. 3). These steps of synthesizing data addressed key question #2.

Fig. 3
figure 3

Cross tabulation of studies categorized by social network approaches and study outcomes representing the stages of HIV care continuum

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Fourth, for studies that conducted SNI, data on study period, location, population, sample size, study design, intervention aim, randomized control trial (RCT), outcome measures, methods of identifying peer participants, methods of identifying social network participants, control group (if any), major findings, and limitations were extracted. Summary tables of key information were then created (Tables 1, 2, and 3) (refer to key questions #3 and #4).

Table 1 Descriptive characteristics of Level III studies (K = 13)
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Table 2 Methodology and intervention design of Level III studies (K = 13)
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Table 3 Summary of outcome measures, major findings, and intervention related limitations of Level III studies (K = 13)
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Results

Descriptive Characteristics

Among the final 58 studies, 11 (19 %) were conducted in the 1990s [24, 37–46], 24 (41 %) from 2000 to 2009 [20, 47–69], and 23 (40 %) studies after 2009 [30, 70–89]. The populations in the studies were divided into two broad groups: (1) PWID/PWUD and HIV-infected and (2) individuals at high-risk for HIV who used or injected drugs. Some specific high-risk groups were homeless men [82, 84], homeless youth [45, 64, 72], black men who have sex with men (MSM) [63], HIV-infected women [61, 74], and female sex workers (FSW) [37, 62, 67]. The sample size of the studies varied significantly with the majority of studies (64 %) sampling 250 to 1000 participants. Two were pilot studies with sample sizes fewer than 25 participants [49, 67] and two were large-scale multi-site studies with sample sizes over 2000 participants [80, 83]. Using World Bank’s designation [90] for country income level, most studies (k = 50, 86 %) were conducted in high-income countries, three studies in upper middle-income countries [62, 65, 68], four studies in lower middle-income [66, 73, 76, 80], and none in low-income countries. Fifty-one studies (88 %) were conducted in the United States, Canada, or Europe, four studies in East and Southeast Asia [68, 76, 77, 85], three in Central America [50, 56, 65], one in South Africa [62], and no studies were conducted in Australia or South America (Fig. 2). The studies that focused on HIV prevention were primarily conducted in the United States or Europe (88 %), with few in South-Southeast Asia, Central America, and Africa. All studies where outcome measures were associated with the various steps of the HIV-care continuum of care, however, were conducted in North America, including studies on: HIV-testing [61, 72] (New York, Iowa, and Nebraska), linkage to care [70] (San Francisco), retention in care [39, 49, 57] (San Francisco, Connecticut, and Maryland), and ART adherence and viral suppression [49, 67] (Connecticut and Vancouver) (Fig. 2). No studies focused on ART prescription.

What are the Different Ways SNA and SNI are Conducted, Analyzed, and Reported in the Studies?

Based on how social network approaches were conducted, we divided the included studies into three categories: Level I, II, and III.

Level I (Social Network Analysis) Studies where (i) social networks, including support and risk networks, were described in terms of their size [38, 40, 42, 74, 86], composition [19, 51, 53, 56, 72, 84], and structure [30, 37, 59, 66], (ii) sociometric and/or egocentric network analyses were conducted to calculate network metrics such as centrality [30], density [38, 40, 42, 63], assortivity, and constraints, (iii) network metrics were used as predictor variables in statistical/mathematical models to identify correlates of substance use and HIV/AIDS were included in this category. There were 37 (64 %) studies in Level I. One consistent trend identified in the majority of these studies (85 %) was that univariate, bivariate, and multivariate statistical analyses were conducted with the calculated network properties or metrics. The most common sequence of analytical steps was to first describe the summary statistics of the network properties; second, conduct a bivariate cross-tabulation or correlation between the outcome variables and the network properties; and third, include the network properties as variables with individual level variables in a multivariate regression analysis. It is important to note here that for these studies, SNA was used to support the preprocessing and creation of new variables to quantify social relationships and was not the primary analytical technique of the methodology.

Level II (Respondent Driven Sampling) This category included studies that exclusively reported using social networks for sampling, such as RDS or contact sampling. Most of the studies focused on the mathematics and statistics of the sampling design and then subsequently conducted a descriptive analysis of the participants and their social networks. There were 8 studies (14 %) in Level II [41, 65, 69, 77, 83, 88, 89].

Level III (Social Network Interventions) Studies that reported the involvement of peers and/or network members and used the results of a typical whole or egocentric network analysis as part of an HIV prevention and treatment intervention were classified as Level III studies. There were 13 studies in Level III [43, 44, 46, 49, 54, 58, 66–68, 73, 78, 80, 87].

What is the Distribution of the Network Approaches in Terms of Their Application in Addressing Outcome Measures Associated with HIV Prevention and Stages of a HIV Care Continuum?

The majority of studies (k = 48, 83 %) focused on HIV prevention, whereas a few (k = 10, 17 %) addressed the different steps in the HIV care continuum. Only four studies included outcome measures associated with HIV diagnosis and testing (7 %) [61, 72, 76, 88], five (9 %) [39, 49, 57, 70, 89] for HIV care linkage and retention, and even fewer for ART adherence (k = 2, 3 %) [49, 67] and viral suppression (k = 1, 2 %) [49]. ART prescription, a crucial step between being eligible for and initiating ART, was not addressed at all (Fig. 4). A cross-tabulation of social network approaches (Level I, II, and III) with outcome measures further provided important results (Fig. 3). In line with Fig. 4, Fig. 3 also showed the considerable concentration of research on HIV prevention across the Level I, II, and III studies (above 80 %). Less than 10 % of the studies were applying the potential of social network approaches to address HIV care and treatment. Among the studies in the Levels I and II, only eight studies (18 %) addressed three components of the HIV care continuum: HIV diagnosis, HIV care linkage, and retention [39, 57, 61, 70, 72, 76, 88, 89]. Additionally, of the thirteen social network intervention (Level III) studies, only one study, which was a pilot intervention (sample size = 20), had a primary biological outcome of viral load and a secondary outcome measure of adherence to ART (pharmacy records and self-reported adherence) [67]. Another pilot intervention (sample size = 14) measured retention in HIV care (percentage of appointments) and ART adherence (pill-counts) as primary outcomes [49].

Fig. 4
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Distribution of selected studies categorized by outcome measures of HIV prevention and care continuum

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How are the Social Network Members Recruited, Identified, and Involved in the SNIs?

All 13 SNIs were based on the conceptual framework of ‘peer-driven-interventions’ (PDI) with minor variations. The basic framework of a typical PDI involves two stages: first, peers, or index participants, are recruited and provided training to understand and perform in a HIV prevention or treatment intervention; second, peers deliver the intervention among family or members from their drug and sexual networks in the community.

In most studies [64, 65, 67, 79, 87, 94, 99] identified in this review, the peers were recruited through street outreach, word of mouth, advertisements, and referrals from community health agencies and former drug users. Latkin et al. [54, 87] and Sherman et al. [68] followed a much more targeted outreach strategy to recruit peers from the cities of Baltimore and Philadelphia (USA) and Chiang Mai (Thailand), respectively. The targeted recruitment procedures included ethnographic observations, focus groups, and stratified sampling based on geographical units (e.g. zip codes or US Census block groups) with higher drug-related arrests or higher prevalence of HIV/AIDS (Table 2). An alternative strategy deployed by Broadhead et al. was that the RDS and PDI were linked. The RDS was used to recruit and identify peers within the network in which the health advocate and peers would work to reduce HIV transmission [91].

The composition of the recruited peers and social network members also varied. For SNIs focused on HIV prevention (k = 11), peer educators or leaders recruited participants from their drug using and/or sexual social networks. Of these eleven, there were six studies (56 %), where the both the peer and their recruited social network members, had equal participation in the study, and everyone received the intervention [43, 44, 46, 58, 78, 80]. In the remaining five studies (44 %), network members did not participate in the intervention directly, but were recipients of diffusion of HIV prevention information from peers and participated in the baseline and/or follow-up assessments [54, 66, 68, 73, 87]. For the SNIs focused on HIV treatment (k = 2), the project personnel identified the health advocates (HAs) and their peers from the enrolled study population [49, 67] (Table 2).

In most of the identified interventions (k = 10/13, 77 %), peers played the role of educators of HIV prevention information. In the remaining three studies [49, 67, 78], peers played the role of health advocates or health buddies supporting each other to improve adherence to ART and retention in HIV care (Table 1). The HIV prevention interventions in these studies included: providing educational information on practicing and promoting safe sexual and drug using behaviors with social network members throughout the study period [43, 44, 46, 58, 80]; distribution of materials such as bleach, condoms, and needles in the community [44, 46, 80]; and hands-on experimental sessions on HIV prevention education of 90–120 min over a period of 2–4 weeks. The experimental sessions included information on communication strategies to conduct peer outreach and how to promote social norms and act as a role model in the community [54, 66, 68, 73, 87]. As part of the intervention, peers also recruited other substance users from their social networks to become peer educators, thereby reaching a larger group in the community. The HIV care and treatment interventions included weekly sessions where peers serving as health advocates encouraged other participants on keeping their clinical appointments, responding to physicians’ referrals, picking up prescriptions on time, and adhering to ART [49, 67]. The theoretical frameworks used in the SNI included behavior change theories, social identity theory, social cognitive theory, diffusion theory, and social support theories.

What Type of Effect did the SNIs have on the Intervention Outcomes?

All the nine HIV prevention studies that included controls showed substantial improvement in more than one HIV-risk reduction behavior (sharing syringes, sharing cookers and filters, frequency of injection, unprotected sex) and HIV education communication among social networks comparing control and intervention conditions [43, 44, 46, 54, 58, 66, 68, 78, 80]. Four studies documented that SNIs, compared to the control conditions, were successful in recruiting a higher proportion of hard to reach at-risk population, which is the first step of any HIV prevention or treatment programs [43, 44, 58, 80] (Table 3). The recruited population had diverse ethnic backgrounds [43], wide geographic distribution [43], low-income [54], women, young-injectors, and people who injected a variety of drugs [80]. HIV prevention outcome measures were assessed in four studies at multiple follow-up periods [54, 58, 68, 78]: HIV education communication among groups (e.g. peers and social network members) was higher at 6 month follow-up [54, 58], more than 90 % of the peers or indexes (e.g. peer health advocates) became active peer interventionists and two-third of study populations had adopted the intervention by the 6 month follow-up [78], reduction in methamphetamine use and increase in condom use were evident at the 12 month follow-up [68], and decrease in drug injection started by the 3 month follow-up [46] (Table 3). One study [73], however, showed that the comparison group (individual intervention) experienced significantly greater reductions in sexual risk behaviors than the SNI group.

Both social network-based HIV treatment interventions were pilot studies and successfully showed the feasibility of HIV infected drug users’ willingness and ability to provide direct social support to their peers [49, 67]. In Broadhead et al. [49], health advocates (HAs) succeeded in keeping 80 % of their peers’ HIV care appointments. Additionally, medication adherence score for all participants (peers and health advocates) was 90 %, and 75 % of participants enrolled in drug treatment by the end of the study. Results from the Deering et al. [67] intervention were supporting, showing that with increasing frequency of intervention meetings, the self-reported rate of ART adherence increased and by the end of the intervention period, overall ART adherence was as high as 92 % among FSWs with HIV and who used drugs. The number of participants achieving viral suppression (HIV-1 RNA <50 copies/mL) increased by 40 % from the pre-intervention period (1 year before enrollment) to the end of the study (duration enrolled) [67]. Although the encouraging results from these two pilot studies do not predict long-term treatment successes, the SNI approach to HIV treatment was a promising strategy for vulnerable population who might otherwise be excluded from the HIV care continuum altogether.

Discussion

This systematic scoping review describes how SNA and SNI was measured, analyzed, and utilized to examine the influence of social networks on HIV prevention, and treatment outcomes for substance-using people with or at-risk for HIV. To the best of our knowledge, this is the first review with a primary focus on evaluating the state of research in SNA and SNI-based studies, which are sustainable and cost-effective strategies to improve behavior change and reach hidden populations [92].

What was striking was that the majority of the studies (Level I and Level II) conducted egocentric SNA as an exploratory tool to sample hidden populations, quantify interpersonal relationships, and describe the structural characteristics of risk and support networks. Here, SNA was not the primary methodology deployed but facilitated in calculating network variables for confirmatory or causal analysis using other mathematical and statistical models. Even when a range of modeling techniques provided convincing evidence that risk behaviors for HIV transmission and loss from HIV care continuum were linked to network factors, few studies (k = 10, 27 %) recommended optimizing the advantages of these approaches for implementing network-based interventions. Of the 58 included studies, only 13 conducted SNIs. This clearly reflects a lack of research involving social networks as part of an intervention and underscores for the imperative for future network interventionists to fill this critical research gap.

Another prominent finding of this systematic scoping review was that social network approaches were utilized predominantly for HIV prevention research (83 %). This trend was true for all three levels of studies. A plausible explanation could be that HIV prevention had been emphasized more by funders or, alternatively, the achievements in HIV prevention were needed to spur innovation for its use in treatment. This is supported by relatively recent findings that HIV treatment is an extremely effective strategy for prevention [93–95]. Few studies from Level I and II had primary or secondary outcomes associated with the first two steps of HIV continuum (diagnosis and linkage to HIV care) and none for the later stages (ART adherence and viral suppression). Interestingly, except for one study conducted in southern India [76], all HIV treatment based studies were located in the United States.

Among the thirteen SNIs studies, only two studies strategically targeted one or more steps along a HIV care continuum [49, 67]. For example, the outcome measures in Broadhead et al. [49], conducted in New Haven, CT in 2002, were retention in care and ART adherence. A biological outcome of viral load was measured in only one study conducted by Deering et al. [67] in Vancouver in 2006. These two HIV treatment studies were conducted at a time (between 2002 and 2006) when HIV prevention research was perhaps the major focus worldwide. Even though the results supported the feasibility of SNI, where drug-using PLH serving as health advocates were capable of providing support to their network members to remain engaged in HIV care and ultimately achieve viral suppression, the two studies were pilot interventions with sample sizes less than 25 participants. It is unclear whether the authors later adapted these pilot studies to large-scale interventions, but findings suggest that larger challenges existed with intervention expansion for HIV treatment [96]. Regardless, these finding undoubtedly show that although there has been considerable progress of social network research in HIV prevention, there still remains a wide gap in utilizing the potential of SNIs in HIV treatment research.

What are some of the advantages and disadvantages of SNIs, which make them a common approach for HIV prevention interventions but not so prevalent in HIV care and treatment research? Social network-based HIV prevention and care interventions have several advantages that were highlighted in the included studies. Eleven of the thirteen studies (Level III) showed substantial reductions in HIV-risk behaviors and increase in HIV prevention communication among social network members. Among these eleven studies, five studies showed sustained positive effects of the interventions beyond the study period indicating that SNIs could be an effective sustainable approach. The remaining two studies showed the feasibility of HIV treatment interventions with drug-using PLH as peer health educators. Most importantly, these SNIs all used social networks that were defined by the study participants themselves. The Community Popular Opinion Leader (CPOL) or the Targeted Outreach Intervention (TOI) models chose leaders from the community with a possibility of missing smaller yet critical social networks that impact one’s daily interactions [92, 97]. In most of the reviewed SNIs, the network members were either directly involved in the intervention or indirectly when receiving information from the peers. This structure has the potential of delivering an intervention to a larger population at a much lesser cost. In addition, the majority of studies had higher retention rates (exceeding 80 %) at the last follow-up visits. This further suggests that groups who are recruited through social network based methods may be better connected and easier to follow and retain compared to non-network recruitment methods. Thus, SNIs may also be valuable for recruiting hard-to-reach populations and giving peers an opportunity to serve a positive role for individuals who are members of disenfranchised and stigmatized groups in the community.

This systematic scoping review also highlighted several limitations of SNIs. First, contamination has been a persistent challenge in these studies, whereby individuals in the experimental intervention group talk to and encourage those in the control group to alter their behaviors. This scenario is more critical for studies that use densely connected social networks. However, while contamination does impact the evaluation of effect sizes by biasing towards the null hypotheses, it does not compromise the end goal of implementing network based HIV prevention and treatment interventions. In a recent study, Simmons et al. [98] evaluated a measure based on recall of intervention terms to assess contamination in a randomized, prospective trial of a social network-based, peer-driven education intervention. Another approach is to consider location and geographic distance between the experiment and the control groups to assess contamination. If experimental and controls are in close proximity for several minutes, that could be a measure of potential contamination.

Second, instability and incidents of rapid network turnover may prohibit sufficient interaction between peers educators, health advocates, or support groups with their respective social network members. Such limited interactions may prohibit effective diffusion of intervention and behavior change. This limitation will disproportionately affect HIV treatment interventions because peers need to encourage and support each other consistently and in a timely manner to stay on HIV care, pick up prescriptions, and adhere to medications. To circumvent this limitation, a plausible solution would be to train a sufficient number of peers to ensure their steady presence. For SNIs to become a widely adopted approach for HIV treatment, however, cutting edge analytical techniques for collecting sociometric data and modeling network change over time must be developed.

Third, for SNIs to perform effectively, the peers should be motivated, willing, and able to recruit network participants as well as deliver accurate information among their social networks. For example, it is possible that peer educators, instructed to deliver specific intervention content among their network members or in the community, might alter the content of the actual intervention. While PDIs are culturally competent because they allow information to be expressed as it would among peers, health educators often need to ensure that accurate intervention content is included. It is also possible that in interventions where peers are trained to be leaders or role models, they refuse to reduce their own high-risk behaviors.

Fourth, for HIV treatment interventions, it is important to assess the disclosure dynamics of an individual’s HIV status to their social network members [96]. This is related to another long lasting issue of what type of information can be ethically collected or shared among the social network members. For interventions focused on measures related to retention in HIV care and ART adherence, a lot of personal health information will be required to be disclosed to peers for them to effectively support each other with their HIV treatment regimen. This will further complicate the protocol of whom and how participants (including peers and social network members) need to be consented during a social network based intervention. Last, another challenge for interventions targeting to increase retention in HIV care is to recruit a control population of PLH with no medical care. This could also raise ethical and moral issues for researchers of not providing medical care to PLH who are in need.

Limitations

While rigorous methods were used to identify studies and extract information to inform collective knowledge on HIV-related SNA and SNIs in substance users, some limitations do exist. The included studies differed substantially in their study design, duration of the intervention, timing of outcome assessment, and outcome measures used. The high degree of heterogeneity in both the studies and the reporting of outcomes precluded a meta-analysis [35, 36, 99, 100]. Studies (with same study population and data) that used both egocentric SNA and SNI but reported findings in different peer- reviewed journal articles were included twice: egocentric analysis study was included in Level I and SNI in the Level II categories. Additionally, the thirteen SNI studies that we reviewed had different recruitment methods and differed slightly in the way in which networks were defined and analyzed. Measurement of study quality was not conducted because currently there is no gold standard for assessing study quality in social network based intervention studies. Finally, although we conducted an extensive search of the literature databases, it is possible that our review missed some studies where SNA and/or SNI were conducted only on PLH but who were not active substance users. Even when peer outreach is central to HIV prevention efforts for PWUDs and/or PWIDs, many studies do not assess network components and social diffusion of information and behavior change. In addition, there may be studies where social-structural settings, such as bars or shooting galleries, are conceptualized as networks settings for diffusion of intervention for behavior change. However, such studies do not directly or indirectly involve existing social network members in the intervention.

Conclusions and Implications for Future Research and Practice

This systematic scoping review began by discussing the presence of large amount of evidence that showed the positive influence of social networks and network-based interventions on HIV prevention and treatment outcomes. Some studies have also reported sustained benefits beyond the study period. Due to the heterogeneity and lack of clarity of network-based approaches and how they strategically targeted one or more steps along a HIV care continuum, this paper systematically identified the dominant patterns of using SNA and SNI methods and showed the pressing need for more SNI research at various care stages, especially those addressing ART prescription. The review also highlighted the potential advantages of SNIs as a sustainable approach and whose effects continue beyond the study period. They are also cost-effective strategies to deliver an intervention to a larger population, recruit from hard to reach populations, and provide an opportunity for members of disenfranchised groups in the community to serve as a positive role for individuals. Based on the limitations of social network approaches identified by the review there are several implications for future research on best theoretical and applied practices: recruiting intervention and control groups, training an effective group of peer educators or care supporters, assessing relationship between treatment regimen and behavior changes over time, and maximum diffusion of intervention in a cost effective way. The goal of the next generation of network interventionists, therefore, is to ensure that research practices are aligned with the complexities of social network dynamics and optimally use the power of social networks to reduce HIV transmission and optimize HIV care.