Background Social desirability response bias may lead to inaccurate self-reports and erroneous study conclusions. The present study examined the relationship between social desirability response bias and self-reports of mental health, substance use, and social network factors among a community sample of inner-city substance users. Methods The study was conducted in a sample of 591 opiate and cocaine users in Baltimore, Maryland from 2009–2013. Modified items from the Marlowe-Crowne Social Desirability Scale were included in the survey, which was conducted face-to-face and using Audio Computer Self Administering Interview (ACASI) methods. Results There were highly statistically significant differences in levels of social desirability response bias by levels of depressive symptoms, drug use stigma, physical health status, recent opiate and cocaine use, Alcohol Use Disorders Identification Test (AUDIT) scores, and size of social networks. There were no associations between health service utilization measures and social desirability bias. In multiple logistic regression models, even after including the Center for Epidemiologic Studies Depression Scale (CES-D) as a measure of depressive symptomology, social desirability bias was associated with recent drug use and drug user stigma. Social desirability bias was not associated with enrollment in prior research studies. Conclusions These findings suggest that social desirability bias is associated with key health measures and that the associations are not primarily due to depressive symptoms. Methods are needed to reduce social desirability bias. Such methods may include the wording and prefacing of questions, clearly defining the role of “study participant,” and assessing and addressing motivations for socially desirable responses.

Crime and neighborhood disorder may negatively impact the health of urban residents. Neighborhoods with high levels of violent crime may also increase residents' risk of experiencing violence. Most studies supporting the assertion that neighborhood disorder impacts mental health have used residents' own ratings of their neighborhoods. The present study examines the relationships among block-group level crime, perceived neighborhood disorder, violence experienced in the neighborhood, and depression. The sample was comprised of current and former drug users (n=786) nested in 270 block groups within Baltimore, Maryland, USA. Using path analysis, we tested the hypothesis that neighborhood violent crime has a direct impact on experiences of violence. Also, we hypothesized that neighborhood violence had a direct and indirect impact on depressive symptoms. Results support a model in which violence is associated with psychological distress through perceptions of neighborhood disorder, and through experiences of violence. We conclude that community and structural level interventions are needed to decrease neighborhood crime and improve residents' perception of their neighborhood.

Aims-To assess the effectiveness of a peer-based, personal risk network focused HIV prevention intervention to 1) train IDUs to reduce injection and sex risk behaviors, 2) conduct outreach to behaviorally risky individuals in their personal social networks (called Risk Network Members), and 3) reduce RNM HIV risk behaviors.Design-Randomized controlled trial with prospective data collection at 6, 12, and 18 months. Intervention condition consisted of 5 group-sessions, one individual session and one session with Index and the RNM. Participants-1) Index participants were aged ≥18 years and self-reported injection drug use in the prior 6 months and 2) their RNMs who were aged ≥18 years and drug users or sex partners of Index.Measurements-Outcomes included: 1) injection risk based on sharing needles, cookers and cotton for injection and drug splitting, 2) sex risk based on number of sex partners, condom use and exchanging sex and 3) Index HIV outreach behaviors.Findings-A total of n=227 Index participants recruited n=366 RNMs. Retention of Index at 18-month follow-up exceeded 85%. Findings suggest the experimental condition was efficacious at 18-months in reducing Index participant injection risk (OR=0.38; 95%CI=0.18-0.77), drug splitting risk (OR=0.46; 95%CI=0.25-0.88), and sex risk among Index (OR=0.53; 95%CI=0.34-0.86). Significant intervention effect on increased condom use among female RNM was observed (OR=0.34; 95%CI=0.18-0.62).

Social network structure and norms are linked to HIV risk behavior. However little is known about the gradient of norm of HIV risk that exists among social networks. We examined the association between injection risk network structure and HIV risk norms among 818 injection drug users (IDUs). IDUs were categorized into four distinct groups based on their risk behaviors with their drug networks: no network members with whom they shared cookers or needles, only cooker-sharing member, one needle-sharing member, and multiple needle-sharing members. The riskiest group, networks of multiple needle sharers, was more likely to endorse both risky needle-sharing and sex norms. Networks of only cooker sharers were less likely to endorse high-risk norms, as compared to the networks with no sharing. There were also differences based on gender. Future HIV prevention interventions for IDUs should target both injection and sex risk norms, particularly among IDUs in the multiple needle-sharing networks.

This article reviews current issues and advancements in social network approaches to HIV prevention and care. Social network analysis can provide a method to understand health disparities in HIV rates and treatment access and outcomes. Social network analysis is a value tool to link social structural factors to individual behaviors. Social networks provide an avenue for low cost and sustainable HIV prevention interventions that can be adapted and translated into diverse populations. Social networks can be utilized as a viable approach to recruitment for HIV testing and counseling, HIV prevention interventions, and optimizing HIV medical care and medication adherence. Social network interventions may be face-to-face or through social media. Key issues in designing social network interventions are contamination due to social diffusion, network stability, density, and the choice and training of network members. There are also ethical issues involved in the development and implementation of social network interventions. Social network analyses can also be used to understand HIV transmission dynamics.