Clinical trial of an AI-augmented intervention for HIV prevention in youth experiencing homelessness

Youth experiencing homelessness (YEH) are subject to substantially greater risk of HIV infection, compounded both by their lack of access to stable housing and the disproportionate representation of youth of marginalized racial, ethnic, and gender identity groups among YEH. A key goal for health equity is to improve adoption of protective behaviors in this population. One promising strategy for intervention is to recruit peer leaders from the population of YEH to promote behaviors such as condom usage and regular HIV testing to their social contacts. This raises a computational question: which youth should be selected as peer leaders to maximize the overall impact of the intervention? We developed an artificial intelligence system to optimize such social network interventions in a community health setting. We conducted a clinical trial enrolling 713 YEH at drop-in centers in a large US city. The clinical trial compared interventions planned with the algorithm to those where the highest-degree nodes in the youths' social network were recruited as peer leaders (the standard method in public health) and to an observation-only control group. Results from the clinical trial show that youth in the AI group experience statistically significant reductions in key risk behaviors for HIV transmission, while those in the other groups do not. This provides, to our knowledge, the first empirical validation of the usage of AI methods to optimize social network interventions for health. We conclude by discussing lessons learned over the course of the project which may inform future attempts to use AI in community-level interventions

Predicting Intimate Partner Violence Perpetration Among Young Adults Experiencing Homelessness in Seven U.S. Cities Using Interpretable Machine Learning.

Young adults experiencing homelessness (YAEH) are at higher risk for intimate partner violence (IPV) victimization than their housed peers. This is often due to their increased vulnerability to abuse and victimization before and during homelessness, which can result in a cycle of violence in which YAEH also perpetrates IPV. Identifying and addressing factors contributing to IPV perpetration at an early stage can reduce the risk of IPV. Yet to date, research examining YAEH's IPV perpetration is scarce and has largely employed conventional statistical approaches that are limited in modeling this complex phenomenon. To address these gaps, this study used an interpretable machine learning approach to answer the research question: What are the most salient predictors of IPV perpetration among a large sample of YAEH in seven U.S. cities? Participants (N = 1,426) on average were 21 years old (SD = 2.09) and were largely cisgender males (59%) and racially/ethnically diverse (81% were from historically excluded racial/ethnic groups; i.e., African American, Latino/a, American Indian, Asian or Pacific Islander, and mixed race/ethnicity). Over one-quarter (26%) reported IPV victimization, and 20% reported IPV perpetration while homeless. Experiencing IPV victimization while homeless was the most important factor in predicting IPV perpetration. An additional 11 predictors (e.g., faced frequent discrimination) were positively associated with IPV perpetration, whereas 8 predictors (e.g., reported higher scores of mindfulness) were negatively associated. These findings underscore the importance of developing and implementing effective interventions with YAEH that can prevent IPV, particularly those that recognize the positive association between victimization and perpetration experiences

Social Network Correlates of Methamphetamine, Heroin, and Cocaine Use in a Sociometric Network of Homeless Youth

Objective: Peer influence is one the most consistent correlates of drug use among youth. However, beyond the dyadic level, there is the possibility that peer influence alsofunctions at a more macro or group level, which calls for a better understanding of how positioning within larger social networks affects youth behaviors. Yet, whereas extant research among homeless youth indicates that having substance-using peers is associated with youth\u27s own substance use, the issue of how peer influence operates in conjunction with network structure and position especially with regards to substance use is relatively unexplored. Method: Using Freeman\u27s Event Based Approach, a sociometric network of 136 homeless youth (39.6% female; 38.1% African American; mean age 20.81 years) were recruited in 2008 at 1 drop-in agency in Los Angeles. Self-administered questionnaires and interviewer-administered social network interviews captured individual and network alters\u27 risk behaviors. Network structure and position was assessed with UCINET and visualized with NetDraw. Logistic regressions assessed associations among substance use, adjacent peer substance use, and network position. Results: Youths\u27 connections to specific substance-using peers and their overall position in the network exposed them to behaviors supportive of specific drugs. These results supported the general proposition that both peer and positional attributes affect substance use among homeless youth. Youth\u27s position in the network exposed them to norms supportive of specific illicit drugs. Conclusions: These results underscore the importance of tailoring interventions to reduce drug use at the network level and of recognizing drug use as not only an individual problem but also a social problem. Limitations of this study include its small sample size, the lack of generalizability, and its focus on a finite set of variables

Social Network Correlates of Methamphetamine, Heroin, and Cocaine Use in a Sociometric Network of Homeless Youth

Objective: Peer influence is one the most consistent correlates of drug use among youth. However, beyond the dyadic level, there is the possibility that peer influence alsofunctions at a more macro or group level, which calls for a better understanding of how positioning within larger social networks affects youth behaviors. Yet, whereas extant research among homeless youth indicates that having substance-using peers is associated with youth\u27s own substance use, the issue of how peer influence operates in conjunction with network structure and position especially with regards to substance use is relatively unexplored. Method: Using Freeman\u27s Event Based Approach, a sociometric network of 136 homeless youth (39.6% female; 38.1% African American; mean age 20.81 years) were recruited in 2008 at 1 drop-in agency in Los Angeles. Self-administered questionnaires and interviewer-administered social network interviews captured individual and network alters\u27 risk behaviors. Network structure and position was assessed with UCINET and visualized with NetDraw. Logistic regressions assessed associations among substance use, adjacent peer substance use, and network position. Results: Youths\u27 connections to specific substance-using peers and their overall position in the network exposed them to behaviors supportive of specific drugs. These results supported the general proposition that both peer and positional attributes affect substance use among homeless youth. Youth\u27s position in the network exposed them to norms supportive of specific illicit drugs. Conclusions: These results underscore the importance of tailoring interventions to reduce drug use at the network level and of recognizing drug use as not only an individual problem but also a social problem. Limitations of this study include its small sample size, the lack of generalizability, and its focus on a finite set of variables

Population-level Network Structure Over Time and Marijuana Use among Homeless Youth

Homeless youth report more marijuana use than stably housed youth; their marijuana use has been linked to the marijuana-using behaviors of their peers. This study was the first to examine the process of network influences in marijuana use with population-level (sociometric) social network data over time. Network data were collected from a population of homeless youth recruited from a drop-in center in Los Angeles every 6 months for 1 year (n = 237, 263, and 312). For each panel, a sociomatrix was generated based on youth nominating other youth in the sample. Degree centrality, betweenness, eigen vector centrality, and number of marijuana-using linkages represented network influence; logistic regression assessed associations with heavy marijuana use. Approximately 60% of the network membership changed between panels. Individuals with more network connections to other heavy marijuana users and youth with more connections to any other youth reported more heavy marijuana use. These results suggest that in transient, high-risk populations, social influence processes largely affect individual substance use patterns. Heavy marijuana use appears to be popular and important to the construction and reconstruction of these networks over time

Social Context of Service Use Among Homeless Youth in Los Angeles, California.

Little is known about rates and correlates of service use or the role that social context plays in service engagement among homeless youth. This study compares two distinct service areas and uses a social network approach to examine how environmental factors (e.g., neighborhood), social factors (e.g., social capital and network engagement) and individual level factors that relate to service use patterns among homeless youth in Los Angeles, California. A sample of 938 youth was recruited from three drop-in centers in two distinct service sites. Individuals were surveyed about their individual and social network attributes. Univariable and multivariable analyses were utilized to understand the influence of social-contextual variables on service use. Service use behaviors varied across site and service type with youth in Hollywood showing greater engagement than youth at the Beach site. Across both sites and several service types, staff emotional support was positively correlated with levels of service use. The site comparisons also point to the fact that even within a single geographic area, like Los Angeles County, client profiles and rates of service use can significantly vary. Future research needs are presented with specific emphasis on understanding the needs of non-service-seeking youth

Homelessness and Sexual Identity Among Middle School Students.

BACKGROUND Lesbian, gay, bisexual, or questioning (LGBQ) high school students experience higher rates of homelessness than their heterosexual peers. Moreover, LGBQ high school students are more likely to stay in riskier locations (eg, with a stranger) and less likely to stay in a shelter. This study tested whether these trends also apply to middle school students. METHODS Using representative data, we examined sexual identity and homelessness among Los Angeles Unified School District middle school students. RESULTS Nearly 10% of middle school students identified as LGBQ and 23.5% experienced at least 1 night of homelessness during the previous year. Contrary to high school data, LGBQ students did not experience higher rates of homelessness overall. However, when limiting the sample to students who had experienced homelessness, LGBQ students were more than 5 times as likely as heterosexual students to have stayed in a public place and 63% as likely to have stayed in a shelter. CONCLUSIONS Lesbian, gay, bisexual, or questioning students are more likely to experience public homelessness. Schools must implement homelessness surveillance systems to assist in identifying early episodes of homelessness, thereby reducing the likelihood of poor physical and mental health outcomes associated with chronic homelessness