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This study examines the relationship between personal networks and polysubstance use among people who use drugs (PWUD) in a medium sized city in the Midwest. A large body of work has demonstrated that personal relationships have an ambivalent association with substance use. On the one hand, a supportive network is associated with safer drug use practices and dramatically improves the outlook for recovery. However, individuals whose personal networks are composed of co-drug use partners are more likely to engage in risky practices. We argue that this notion of “supportive” social contacts and “risky” social contacts is ultimately incomplete: risky behaviors are introduced and further developed in a social context, often with the people who provide emotional support. We argue that personal networks with more multiplex relationships (where co-drug use and confiding fuse) are harmful because they combine norms of trust and reciprocity with drug use. We use data from the Rural Health Cohort (RHC) study to test this idea. The sample consists of 120 adult PWUD in a medium sized city located in southeastern Nebraska who were recruited using respondent-driven sampling. Participants listed up to nine confidants and nine co-drug use partners, indicating any overlap between the two networks. Our results demonstrate that multiplex ties are as strongly associated with polysubstance use as simple co-drug use relationships. As the drug crisis has increasingly shifted to underserved populations outside large urban centers, this paper represents an important advance in our understanding of the current drug crisis.

Isolation and cohesion are two key network features, often used to predict outcomes like mental health and deviance. More cohesive settings tend to have better outcomes, while isolates tend to fare worse than their more integrated peers. A common assumption of past work is that the effect of cohesion is universal, so that all actors get the same benefits of being in a socially cohesive environment. Here, we suggest that the effect of cohesion is universal only for specific types of outcomes. For other outcomes, experiencing the benefits of cohesion depends on an individual’s position in the network, such as whether or not an individual has any social ties. Network processes thus operate at both the individual and contextual level, and we employ hierarchical linear models to analyze these jointly to arrive at a full picture of how networks matter. We explore these ideas using the case of adolescents in schools (using Add Health data), focusing on the effect of isolation and cohesion on two outcomes, school attachment and academic engagement. We find that cohesion has a uniform effect in the case of engagement but not attachment. Only non-isolates experience stronger feelings of attachment as cohesion increases, while all students, both isolates and non-isolates, are more strongly engaged in high cohesion settings. Overall, the results show the importance of taking a systematic, multi-level approach, with important implications for studies of health and deviance.

This study examines the relationship between personal networks and polysubstance use among people who use drugs (PWUD) in a medium sized city in the Midwest. A large body of work has demonstrated that personal relationships have an ambivalent association with substance use. On the one hand, a supportive network is associated with safer drug use practices and dramatically improves the outlook for recovery. However, individuals whose personal networks are composed of co-drug use partners are more likely to engage in risky practices. We argue that this notion of “supportive” social contacts and “risky” social contacts is ultimately incomplete: risky behaviors are introduced and further developed in a social context, often with the people who provide emotional support. We argue that personal networks with more multiplex relationships (where co-drug use and confiding fuse) are harmful because they combine norms of trust and reciprocity with drug use. We use data from the Rural Health Cohort (RHC) study to test this idea. The sample consists of 120 adult PWUD in a medium sized city located in southeastern Nebraska who were recruited using respondent-driven sampling. Participants listed up to nine confidants and nine co-drug use partners, indicating any overlap between the two networks. Our results demonstrate that multiplex ties are as strongly associated with polysubstance use as simple co-drug use relationships. As the drug crisis has increasingly shifted to underserved populations outside large urban centers, this paper represents an important advance in our understanding of the current drug crisis.

Isolation and cohesion are two key network features, often used to predict outcomes like mental health and deviance. More cohesive settings tend to have better outcomes, while isolates tend to fare worse than their more integrated peers. A common assumption of past work is that the effect of cohesion is universal, so that all actors get the same benefits of being in a socially cohesive environment. Here, we suggest that the effect of cohesion is universal only for specific types of outcomes. For other outcomes, experiencing the benefits of cohesion depends on an individual’s position in the network, such as whether or not an individual has any social ties. Network processes thus operate at both the individual and contextual level, and we employ hierarchical linear models to analyze these jointly to arrive at a full picture of how networks matter. We explore these ideas using the case of adolescents in schools (using Add Health data), focusing on the effect of isolation and cohesion on two outcomes, school attachment and academic engagement. We find that cohesion has a uniform effect in the case of engagement but not attachment. Only non-isolates experience stronger feelings of attachment as cohesion increases, while all students, both isolates and non-isolates, are more strongly engaged in high cohesion settings. Overall, the results show the importance of taking a systematic, multi-level approach, with important implications for studies of health and deviance.

Background: Ecological momentary assessment (EMA) is an increasingly popular and feasible form of data collection, but it can be intensive and intrusive. Especially for at-risk, vulnerable populations like people who use drugs (PWUD), poor experiences with EMA may exacerbate existing chronic struggles while decreasing response rates. However, little research queries participants’ experiences with EMA studies. Objectives: We explore participants’ positive and negative experiences with EMA, identifying what they liked about the study, the problems they experienced, and suggested solutions to these problems. Methods: Results come from semi-structured interviews from 26 PWUD (6 women; 20 men) in Nebraska who participated in a two-week EMA pilot study on drug use with a study-provided smartphone. Participant responses were recorded by interviewers into open-text fields in Qualtrics. Data were analyzed with an iterative open coding procedure. Results: We found that many participants enjoyed the study and seamlessly incorporated the phone into their daily lives. There were a number of negative study aspects identified, however, as many participants experienced functional issues (e.g., running out of high-speed data, trouble keeping the phone charged, not able to answer questions within the two-hour timeframe) that detracted from their experience, especially if they were homeless. Conclusion: Our findings provide methodological considerations for studies with EMA components among at-risk, vulnerable populations, like PWUD. These suggestions are targeted toward the continued ethical collection of high-quality data in clinical and non-clinical settings.

Throughout North America, indigenous women experience higher rates of intimate partner violence and sexual violence than any other ethnic group, and so it is of particular importance to understand sources of support for Native American women. In this article, we use social network analysis to study the relationship between social integration and women’s access to domestic violence support by examining the recommendations they would give to another woman in need. We ask two main questions: First, are less integrated women more likely to make no recommendation at all when compared with more socially integrated women? Second, are less integrated women more likely than more integrated women to nominate a formal source of support rather than an informal one? We use network data collected from interviews with 158 Canadian women residing in an indigenous community to measure their access to support. We find that, in general, less integrated women are less likely to make a recommendation than more integrated women. However, when they do make a recommendation, less integrated women are more likely to recommend a formal source of support than women who are more integrated. These results add to our understanding of how access to two types of domestic violence support is embedded in the larger set of social relations of an indigenous community.

Background: Ecological momentary assessment (EMA) is a set of research methods that capture events, feelings, and behaviors as they unfold in their real-world setting. Capturing data in the moment reduces important sources of measurement error but also generates challenges for noncompliance (ie, missing data). To date, EMA research has only examined the overall rates of noncompliance. Objective: In this study, we identify four types of noncompliance among people who use drugs and aim to examine the factors associated with the most common types. Methods: Data were obtained from a recent pilot study of 28 Nebraskan people who use drugs who answered EMA questions for 2 weeks. We examined questions that were not answered because they were skipped, they expired, the phone was switched off, or the phone died after receiving them. Results: We found that the phone being switched off and questions expiring comprised 93.34% (1739/1863 missing question-instances) of our missing data. Generalized structural equation model results show that participant-level factors, including age (relative risk ratio [RRR]=0.93; P=.005), gender (RRR=0.08; P=.006), homelessness (RRR=3.80; P=.04), personal device ownership (RRR=0.14; P=.008), and network size (RRR=0.57; P=.001), are important for predicting off missingness, whereas only question-level factors, including time of day (ie, morning compared with afternoon, RRR=0.55; P<.001) and day of week (ie, Tuesday-Saturday compared with Sunday, RRR=0.70, P=.02; RRR=0.64, P=.005; RRR=0.58, P=.001; RRR=0.55, P<.001; and RRR=0.66, P=.008, respectively) are important for predicting expired missingness. The week of study is important for both (ie, week 2 compared with week 1, RRR=1.21, P=.03, for off missingness and RRR=1.98, P<.001, for expired missingness). Conclusions: We suggest a three-pronged strategy to preempt missing EMA data with high-risk populations: first, provide additional resources for participants likely to experience phone charging

Throughout North America, indigenous women experience higher rates of intimate partner violence and sexual violence than any other ethnic group, and so it is of particular importance to understand sources of support for Native American women. In this article, we use social network analysis to study the relationship between social integration and women’s access to domestic violence support by examining the recommendations they would give to another woman in need. We ask two main questions: First, are less integrated women more likely to make no recommendation at all when compared with more socially integrated women? Second, are less integrated women more likely than more integrated women to nominate a formal source of support rather than an informal one? We use network data collected from interviews with 158 Canadian women residing in an indigenous community to measure their access to support. We find that, in general, less integrated women are less likely to make a recommendation than more integrated women. However, when they do make a recommendation, less integrated women are more likely to recommend a formal source of support than women who are more integrated. These results add to our understanding of how access to two types of domestic violence support is embedded in the larger set of social relations of an indigenous community.

Background: Ecological momentary assessment (EMA) is an increasingly popular and feasible form of data collection, but it can be intensive and intrusive. Especially for at-risk, vulnerable populations like people who use drugs (PWUD), poor experiences with EMA may exacerbate existing chronic struggles while decreasing response rates. However, little research queries participants’ experiences with EMA studies. Objectives: We explore participants’ positive and negative experiences with EMA, identifying what they liked about the study, the problems they experienced, and suggested solutions to these problems. Methods: Results come from semi-structured interviews from 26 PWUD (6 women; 20 men) in Nebraska who participated in a two-week EMA pilot study on drug use with a study-provided smartphone. Participant responses were recorded by interviewers into open-text fields in Qualtrics. Data were analyzed with an iterative open coding procedure. Results: We found that many participants enjoyed the study and seamlessly incorporated the phone into their daily lives. There were a number of negative study aspects identified, however, as many participants experienced functional issues (e.g., running out of high-speed data, trouble keeping the phone charged, not able to answer questions within the two-hour timeframe) that detracted from their experience, especially if they were homeless. Conclusion: Our findings provide methodological considerations for studies with EMA components among at-risk, vulnerable populations, like PWUD. These suggestions are targeted toward the continued ethical collection of high-quality data in clinical and non-clinical settings.

Background: Ecological momentary assessment (EMA) is a set of research methods that capture events, feelings, and behaviors as they unfold in their real-world setting. Capturing data in the moment reduces important sources of measurement error but also generates challenges for noncompliance (ie, missing data). To date, EMA research has only examined the overall rates of noncompliance. Objective: In this study, we identify four types of noncompliance among people who use drugs and aim to examine the factors associated with the most common types. Methods: Data were obtained from a recent pilot study of 28 Nebraskan people who use drugs who answered EMA questions for 2 weeks. We examined questions that were not answered because they were skipped, they expired, the phone was switched off, or the phone died after receiving them. Results: We found that the phone being switched off and questions expiring comprised 93.34% (1739/1863 missing question-instances) of our missing data. Generalized structural equation model results show that participant-level factors, including age (relative risk ratio [RRR]=0.93; P=.005), gender (RRR=0.08; P=.006), homelessness (RRR=3.80; P=.04), personal device ownership (RRR=0.14; P=.008), and network size (RRR=0.57; P=.001), are important for predicting off missingness, whereas only question-level factors, including time of day (ie, morning compared with afternoon, RRR=0.55; P<.001) and day of week (ie, Tuesday-Saturday compared with Sunday, RRR=0.70, P=.02; RRR=0.64, P=.005; RRR=0.58, P=.001; RRR=0.55, P<.001; and RRR=0.66, P=.008, respectively) are important for predicting expired missingness. The week of study is important for both (ie, week 2 compared with week 1, RRR=1.21, P=.03, for off missingness and RRR=1.98, P<.001, for expired missingness). Conclusions: We suggest a three-pronged strategy to preempt missing EMA data with high-risk populations: first, provide additional resources for participants likely to experience phone charging

Network concepts are often used to characterize the features of a social context. For example, past work has asked if individuals in more socially cohesive neighborhoods have better mental health outcomes. Despite the ubiquity of use, it is relatively rare for contextual studies to use the methods of network analysis. This is the case, in part, because network data are difficult to collect, requiring information on all ties between all actors. In this article the authors ask whether it is possible to avoid such heavy data collection while still retaining the best features of a contextual-network study. The basic idea is to apply network sampling to the problem of contextual models, in which one uses sampled ego network data to infer the network features of each context and then uses the inferred network features as second-level predictors in a hierarchical linear model. The authors test the validity of this idea in the case of network cohesion. Using two complete data sets as a test, the authors find that ego network data are sufficient to capture the relationship between cohesion and important outcomes, such as attachment and deviance. The hope, going forward, is that researchers will find it easier to incorporate holistic network measures into traditional regression models.

Objectives: The disruption and contraction of older adults’ social networks are among the less discussed consequences of the COVID-19 pandemic. Our objective was to provide an evidence-based commentary on racial/ethnic disparities in social network resources and draw attention to the ways in which disasters differentially affect social networks, with meaningful insight for the ongoing pandemic. Methods: We draw upon prior research on social networks and past natural disasters to identify major areas of network inequality. Attention is given to how pre-pandemic racial/ethnic network disparities are exacerbated during the current crisis, with implications for physical and mental health outcomes. Results: Evidence from the literature shows a robust association between strong social networks and physical and mental health outcomes. During times of crisis, access to social networks for older adults is disrupted, particularly for marginalized groups. We document pre-pandemic disparities in social networks resources and offer insight for examining the impact of COVID-19 on disrupting social networks among older adults. Discussion: Importantly, racial/ethnic disparities in social networks both prior to and as a result of the pandemic intensify existing inequalities and demonstrate the necessity of better understanding social network inequalities for marginalized older adults, particularly in the context of the COVID-19 health crisis.

Network-based intervention strategies can be effective and cost-efficient approaches to curtailing harmful contagions in myriad settings. As studied, these strategies are often impractical to implement, as they typically assume complete knowledge of the network structure, which is unusual in practice. In this paper, we investigate how different immunization strategies perform under realistic conditions—where the strategies are informed by partially- observed network data. Our results suggest that global immunization strategies, like degree immunization, are optimal in most cases; the exception is at very high levels of missing data, where stochastic strategies, like acquaintance immunization, begin to outstrip them in minimizing outbreaks. Stochastic strategies are more robust in some cases due to the different ways in which they can be affected by missing data. In fact, one of our proposed variants of acquaintance immunization leverages a logistically-realistic ongoing survey-intervention process as a form of targeted data-recovery to improve with increasing levels of missing data. These results support the effectiveness of targeted immunization as a general prac- tice. They also highlight the risks of considering networks as idealized mathematical objects: overestimating the accuracy of network data and foregoing the rewards of additional inquiry.

This study examines the relationship between social support profiles and cognitive functioning by race, ethnicity and nativity in older adults using cross-sectional data drawn from the Health and Retirement Study (2010 and 2012). We employed a hierarchical clustering routine to generate nine support profiles that differentiated three sources of support: children, wider family relationships and friendships. Cognitive functioning was measured as the score on the Telephone Interview for Cognitive Status (TICS-m), a 27 point scale of cognitive function. Our approach explicitly acknowledges the ambivalence and multidimensionality of close relationships and the resources embedded within them. Descriptive analyses revealed significant differences in access to support across demographic groups. White respondents are over-represented in profiles that are characterized by support from friends, and under-represented in family support profiles. The reverse is found among Foreign-born Hispanic respondents who are over-represented in the profiles characterized by high family support and under-represented in those with high friend support. Native-born Hispanic respondents and Black respondents have less clear support patterns, although both are more likely to receive support from family and children compared to friends. Findings from the Poisson regression suggest that the relationship between familial support and cognitive decline is stronger among Hispanic respondents, particularly those who are foreign born. These findings are supported even with the inclusion of other relationship quality indicators including negative support and frequency of contact.

Network-based intervention strategies can be effective and cost-efficient approaches to cur- tailing harmful contagions in myriad settings. As studied, these strategies are often impracti- cal to implement, as they typically assume complete knowledge of the network structure, which is unusual in practice. In this paper, we investigate how different immunization strategies perform under realistic conditions—where the strategies are informed by partially-observed network data. Our results suggest that global immunization strategies, like degree immunization, are optimal in most cases; the exception is at very high levels of missing data, where stochastic strategies, like acquaintance immunization, begin to outstrip them in mini- mizing outbreaks. Stochastic strategies are more robust in some cases due to the different ways in which they can be affected by missing data. In fact, one of our proposed variants of acquaintance immunization leverages a logistically-realistic ongoing survey-intervention process as a form of targeted data-recovery to improve with increasing levels of missing data. These results support the effectiveness of targeted immunization as a general prac- tice. They also highlight the risks of considering networks as idealized mathematical objects: overestimating the accuracy of network data and foregoing the rewards of additional inquiry.

Network-based intervention strategies can be effective and cost-efficient approaches to curtailing harmful contagions in myriad settings. As studied, these strategies are often impractical to implement, as they typically assume complete knowledge of the network structure, which is unusual in practice. In this paper, we investigate how different immunization strategies perform under realistic conditions—where the strategies are informed by partially- observed network data. Our results suggest that global immunization strategies, like degree immunization, are optimal in most cases; the exception is at very high levels of missing data, where stochastic strategies, like acquaintance immunization, begin to outstrip them in minimizing outbreaks. Stochastic strategies are more robust in some cases due to the different ways in which they can be affected by missing data. In fact, one of our proposed variants of acquaintance immunization leverages a logistically-realistic ongoing survey-intervention process as a form of targeted data-recovery to improve with increasing levels of missing data. These results support the effectiveness of targeted immunization as a general prac- tice. They also highlight the risks of considering networks as idealized mathematical objects: overestimating the accuracy of network data and foregoing the rewards of additional inquiry.

Network-based intervention strategies can be effective and cost-efficient approaches to cur- tailing harmful contagions in myriad settings. As studied, these strategies are often impracti- cal to implement, as they typically assume complete knowledge of the network structure, which is unusual in practice. In this paper, we investigate how different immunization strategies perform under realistic conditions—where the strategies are informed by partially-observed network data. Our results suggest that global immunization strategies, like degree immunization, are optimal in most cases; the exception is at very high levels of missing data, where stochastic strategies, like acquaintance immunization, begin to outstrip them in mini- mizing outbreaks. Stochastic strategies are more robust in some cases due to the different ways in which they can be affected by missing data. In fact, one of our proposed variants of acquaintance immunization leverages a logistically-realistic ongoing survey-intervention process as a form of targeted data-recovery to improve with increasing levels of missing data. These results support the effectiveness of targeted immunization as a general prac- tice. They also highlight the risks of considering networks as idealized mathematical objects: overestimating the accuracy of network data and foregoing the rewards of additional inquiry.

Network concepts are often used to characterize the features of a social context. For example, past work has asked if individuals in more socially cohesive neighborhoods have better mental health outcomes. Despite the ubiquity of use, it is relatively rare for contextual studies to use the methods of network analysis. This is the case, in part, because network data are difficult to collect, requiring information on all ties between all actors. In this article the authors ask whether it is possible to avoid such heavy data collection while still retaining the best features of a contextual-network study. The basic idea is to apply network sampling to the problem of contextual models, in which one uses sampled ego network data to infer the network features of each context and then uses the inferred network features as second-level predictors in a hierarchical linear model. The authors test the validity of this idea in the case of network cohesion. Using two complete data sets as a test, the authors find that ego network data are sufficient to capture the relationship between cohesion and important outcomes, such as attachment and deviance. The hope, going forward, is that researchers will find it easier to incorporate holistic network measures into traditional regression models.

This study examines the relationship between social support profiles and cognitive functioning by race, ethnicity and nativity in older adults using cross-sectional data drawn from the Health and Retirement Study (2010 and 2012). We employed a hierarchical clustering routine to generate nine support profiles that differentiated three sources of support: children, wider family relationships and friendships. Cognitive functioning was measured as the score on the Telephone Interview for Cognitive Status (TICS-m), a 27 point scale of cognitive function. Our approach explicitly acknowledges the ambivalence and multidimensionality of close relationships and the resources embedded within them. Descriptive analyses revealed significant differences in access to support across demographic groups. White respondents are over-represented in profiles that are characterized by support from friends, and under-represented in family support profiles. The reverse is found among Foreign-born Hispanic respondents who are over-represented in the profiles characterized by high family support and under-represented in those with high friend support. Native-born Hispanic respondents and Black respondents have less clear support patterns, although both are more likely to receive support from family and children compared to friends. Findings from the Poisson regression suggest that the relationship between familial support and cognitive decline is stronger among Hispanic respondents, particularly those who are foreign born. These findings are supported even with the inclusion of other relationship quality indicators including negative support and frequency of contact.

Objectives: The disruption and contraction of older adults’ social networks are among the less discussed consequences of the COVID-19 pandemic. Our objective was to provide an evidence-based commentary on racial/ethnic disparities in social network resources and draw attention to the ways in which disasters differentially affect social networks, with meaningful insight for the ongoing pandemic. Methods: We draw upon prior research on social networks and past natural disasters to identify major areas of network inequality. Attention is given to how pre-pandemic racial/ethnic network disparities are exacerbated during the current crisis, with implications for physical and mental health outcomes. Results: Evidence from the literature shows a robust association between strong social networks and physical and mental health outcomes. During times of crisis, access to social networks for older adults is disrupted, particularly for marginalized groups. We document pre-pandemic disparities in social networks resources and offer insight for examining the impact of COVID-19 on disrupting social networks among older adults. Discussion: Importantly, racial/ethnic disparities in social networks both prior to and as a result of the pandemic intensify existing inequalities and demonstrate the necessity of better understanding social network inequalities for marginalized older adults, particularly in the context of the COVID-19 health crisis.

Prevention and intervention work done within community settings often face unique analytic challenges for rigorous evaluations. Since community prevention work (often geographically isolated) cannot be controlled in the same way other prevention programs and these communities have an increased level of interpersonal interactions, rigorous evaluations are needed. Even when the `gold standard' randomized control trials are implemented within community intervention work, the threats to internal validity can be called into question given informal social spread of information in closed network settings. A new prevention evaluation method is presented here to disentangle the social influences assumed to influence prevention effects within communities. We formally introduce the method and it's utility for a suicide prevention program implemented in several Alaska Native villages. The results show promise to explore eight sociological measures of intervention effects in the face of social diffusion, social reinforcement, and direct treatment. Policy and research implication are discussed.

Understanding the short- and long-term transmission dynamics of blood-borne illnesses in network contexts represents an important public health priority for people who inject drugs and the general population that surrounds them. The purpose of this article is to compare the risk networks of urban and rural people who inject drugs in Puerto Rico. In the current study, network characteristics are drawn from the sampling “trees” used to recruit participants to the study. We found that injection frequency is the only factor significantly related to clustering behavior among both urban and rural people who inject drugs.

Prevention and intervention work done within community settings often face unique analytic challenges for rigorous evaluations. Since community prevention work (often geographically isolated) cannot be controlled in the same way other prevention programs and these communities have an increased level of interpersonal interactions, rigorous evaluations are needed. Even when the `gold standard' randomized control trials are implemented within community intervention work, the threats to internal validity can be called into question given informal social spread of information in closed network settings. A new prevention evaluation method is presented here to disentangle the social influences assumed to influence prevention effects within communities. We formally introduce the method and it's utility for a suicide prevention program implemented in several Alaska Native villages. The results show promise to explore eight sociological measures of intervention effects in the face of social diffusion, social reinforcement, and direct treatment. Policy and research implication are discussed.

Understanding the short- and long-term transmission dynamics of blood-borne illnesses in network contexts represents an important public health priority for people who inject drugs and the general population that surrounds them. The purpose of this article is to compare the risk networks of urban and rural people who inject drugs in Puerto Rico. In the current study, network characteristics are drawn from the sampling “trees” used to recruit participants to the study. We found that injection frequency is the only factor significantly related to clustering behavior among both urban and rural people who inject drugs.

Objective: This research examined the social network and recruitment patterns of a sample of people who inject drugs (PWIDs) in rural Puerto Rico, in an attempt to uncover systematic clustering and between-group social boundaries that potentially influence disease spread. Methods: Respondent driven sampling was utilized to obtain a sample of PWID in rural Puerto Rico. Through eight initial “seeds”, 317 injection drug users were recruited. Using recruitment patterns of this sample, estimates of homophily and affiliation were calculated using RDSAT. Results: Analyses showed clustering within the social network of PWID in rural Puerto Rico. In particular, females showed a very high tendency to recruit male PWID, which suggests low social cohesion among female PWID. Results for (believed) HCV status at the time of interview indicate that HCV+ individuals were less likely to interact with HCV- individuals or those who were unaware of their status, and may be acting as “gatekeepers” to prevent disease spread. Individuals who participated in a substance use program were more likely to affiliate with one another. The use of speedballs was related to clustering within the network, in which individuals who injected this mixture were more likely to affiliate with other speedball users. Conclusion: Social clustering based on several characteristics and behaviors were found within the IDU population in rural Puerto Rico. RDS was effective in not only garnering a sample of PWID in rural Puerto Rico, but also in uncovering social clustering that can potentially influence disease spread among this population.

In the United States, gender gaps in science interest widen during the middle school years. Recent research on adults shows that gender gaps in some academic fields are associated with mindsets about ability and gender-science biases. In a sample of 529 students in a U.S. middle school, we assess how explicit boy-science bias, science confidence, science possible self (belief in being able to become a scientist), and desire to be a scientist vary by gender. Guided by theories and prior research, we use a series of multivariate logistic regression models to examine the relationships between mindsets about ability and these variables. We control for self-reported science grades, social capital, and race/ethnic minority status. Results show that seeing academic ability as innate (“fixed mindsets”) is associated with boy-science bias, and that younger girls have less boy-science bias than older girls. Fixed mindsets and boy-science bias are both negatively associated with a science possible self; science confidence is positively associated with a science possible self. In the final model, high science confident and having a science possible self are positively associated with a desire to be a scientist. Facilitating growth mindsets and countering boy-science bias in middle school may be fruitful interventions for widening participation in science careers.

In the United States, girls and boys have similar science achievement, yet fewer girls aspire to science careers than boys. This paradox emerges in middle school, when peers begin to play a stronger role in shaping adolescent identities. We use complete network data from a single middle school and theories of gender, identity, and social distance to explore how friendship patterns might influence this gender and science paradox. Three patterns highlight the social dimensions of gendered science persistence: (1) boys and girls do not differ in self-perceived science potential and science career aspirations; (2) consistent with gender-based norms, both middle school boys and girls report that the majority of their female friends are not science kinds of people; and (3) youth with gender-inconsistent science aspirations are more likely to be friends with each other than youth with gender normative science aspirations. Together, this evidence suggests that friendship dynamics contribute to gendered patterns in science career aspirations.

In the United States, girls and boys have similar science achievement, yet fewer girls aspire to science careers than boys. This paradox emerges in middle school, when peers begin to play a stronger role in shaping adolescent identities. We use complete network data from a single middle school and theories of gender, identity, and social distance to explore how friendship patterns might influence this gender and science paradox. Three patterns highlight the social dimensions of gendered science persistence: (1) boys and girls do not differ in self-perceived science potential and science career aspirations; (2) consistent with gender-based norms, both middle school boys and girls report that the majority of their female friends are not science kinds of people; and (3) youth with gender-inconsistent science aspirations are more likely to be friends with each other than youth with gender normative science aspirations. Together, this evidence suggests that friendship dynamics contribute to gendered patterns in science career aspirations.

Objective: This research examined the social network and recruitment patterns of a sample of people who inject drugs (PWIDs) in rural Puerto Rico, in an attempt to uncover systematic clustering and between-group social boundaries that potentially influence disease spread. Methods: Respondent driven sampling was utilized to obtain a sample of PWID in rural Puerto Rico. Through eight initial “seeds”, 317 injection drug users were recruited. Using recruitment patterns of this sample, estimates of homophily and affiliation were calculated using RDSAT. Results: Analyses showed clustering within the social network of PWID in rural Puerto Rico. In particular, females showed a very high tendency to recruit male PWID, which suggests low social cohesion among female PWID. Results for (believed) HCV status at the time of interview indicate that HCV+ individuals were less likely to interact with HCV- individuals or those who were unaware of their status, and may be acting as “gatekeepers” to prevent disease spread. Individuals who participated in a substance use program were more likely to affiliate with one another. The use of speedballs was related to clustering within the network, in which individuals who injected this mixture were more likely to affiliate with other speedball users. Conclusion: Social clustering based on several characteristics and behaviors were found within the IDU population in rural Puerto Rico. RDS was effective in not only garnering a sample of PWID in rural Puerto Rico, but also in uncovering social clustering that can potentially influence disease spread among this population.

In the United States, gender gaps in science interest widen during the middle school years. Recent research on adults shows that gender gaps in some academic fields are associated with mindsets about ability and gender-science biases. In a sample of 529 students in a U.S. middle school, we assess how explicit boy-science bias, science confidence, science possible self (belief in being able to become a scientist), and desire to be a scientist vary by gender. Guided by theories and prior research, we use a series of multivariate logistic regression models to examine the relationships between mindsets about ability and these variables. We control for self-reported science grades, social capital, and race/ethnic minority status. Results show that seeing academic ability as innate (“fixed mindsets”) is associated with boy-science bias, and that younger girls have less boy-science bias than older girls. Fixed mindsets and boy-science bias are both negatively associated with a science possible self; science confidence is positively associated with a science possible self. In the final model, high science confident and having a science possible self are positively associated with a desire to be a scientist. Facilitating growth mindsets and countering boy-science bias in middle school may be fruitful interventions for widening participation in science careers.

The importance of community relocation experiences for aboriginal land claims movements is well documented; the role played by successful land claims in prompting ongoing out-migration is not. Data collected in 2011 on the lives of migrants are used to test three hypotheses: H1, Inuit leaving the land claims area for a nearby nonaboriginal city show markedly different social outcomes based on the length of time since migration; H2, these social outcomes map onto patterns of intergroup boundaries in their new communities; and H3, both of these outcomes are better explained by migration patterns after the land claims than by the ethnic/racial exclusion that has been the focus of past research on inequality in the region. This analysis takes advantage of social network techniques used to study hard-to-reach populations, showing how these methods can be used to address broader questions of community structure and cohesion during rapid social change. Conclusions focus on the experiences of migrants on the margins of sending and receiving communities and what they can tell us about the role played by aboriginal land claims in the culture politics of industrial resource extraction.

The importance of community relocation experiences for aboriginal land claims movements is well documented; the role played by successful land claims in prompting ongoing out-migration is not. Data collected in 2011 on the lives of migrants are used to test three hypotheses: H1, Inuit leaving the land claims area for a nearby nonaboriginal city show markedly different social outcomes based on the length of time since migration; H2, these social outcomes map onto patterns of intergroup boundaries in their new communities; and H3, both of these outcomes are better explained by migration patterns after the land claims than by the ethnic/racial exclusion that has been the focus of past research on inequality in the region. This analysis takes advantage of social network techniques used to study hard-to-reach populations, showing how these methods can be used to address broader questions of community structure and cohesion during rapid social change. Conclusions focus on the experiences of migrants on the margins of sending and receiving communities and what they can tell us about the role played by aboriginal land claims in the culture politics of industrial resource extraction.

A sexual double standard in adolescence has important implications for sexual development and gender inequality. The present study uses longitudinal social network data (N = 914; 11–16 years of age) to test if gender moderates associations between adolescents’ sexual behaviors and peer acceptance. Consistent with a traditional sexual double standard, female adolescents who reported having sex had significant decreases in peer acceptance over time, whereas male adolescents reporting the same behavior had significant increases in peer acceptance. This pattern was observed net of respondents’ own perceived friendships, further suggesting that the social responses to sex vary by gender of the sexual actor. However, findings for “making out” showed a reverse double standard, such that female adolescents reporting this behavior had increases in peer acceptance and male adolescents reporting the same behavior had decreases in peer acceptance over time. Results thus suggest that peers enforce traditional sexual scripts for both “heavy” and “light” sexual behaviors during adolescence. These findings have important implications for sexual health education, encouraging educators to develop curricula that emphasize the gendered social construction of sexuality and to combat inequitable and stigmatizing peer responses to real or perceived deviations from traditional sexual scripts.

The importance of community relocation experiences for aboriginal land claims movements is well documented; the role played by successful land claims in prompting ongoing out-migration is not. Data collected in 2011 on the lives of migrants are used to test three hypotheses: H1, Inuit leaving the land claims area for a nearby nonaboriginal city show markedly different social outcomes based on the length of time since migration; H2, these social outcomes map onto patterns of intergroup boundaries in their new communities; and H3, both of these outcomes are better explained by migration patterns after the land claims than by the ethnic/racial exclusion that has been the focus of past research on inequality in the region. This analysis takes advantage of social network techniques used to study hard-to-reach populations, showing how these methods can be used to address broader questions of community structure and cohesion during rapid social change. Conclusions focus on the experiences of migrants on the margins of sending and receiving communities and what they can tell us about the role played by aboriginal land claims in the culture politics of industrial resource extraction.

The importance of community relocation experiences for aboriginal land claims movements is well documented; the role played by successful land claims in prompting ongoing out-migration is not. Data collected in 2011 on the lives of migrants are used to test three hypotheses: H1, Inuit leaving the land claims area for a nearby nonaboriginal city show markedly different social outcomes based on the length of time since migration; H2, these social outcomes map onto patterns of intergroup boundaries in their new communities; and H3, both of these outcomes are better explained by migration patterns after the land claims than by the ethnic/racial exclusion that has been the focus of past research on inequality in the region. This analysis takes advantage of social network techniques used to study hard-to-reach populations, showing how these methods can be used to address broader questions of community structure and cohesion during rapid social change. Conclusions focus on the experiences of migrants on the margins of sending and receiving communities and what they can tell us about the role played by aboriginal land claims in the culture politics of industrial resource extraction.

A sexual double standard in adolescence has important implications for sexual development and gender inequality. The present study uses longitudinal social network data (N = 914; 11–16 years of age) to test if gender moderates associations between adolescents’ sexual behaviors and peer acceptance. Consistent with a traditional sexual double standard, female adolescents who reported having sex had significant decreases in peer acceptance over time, whereas male adolescents reporting the same behavior had significant increases in peer acceptance. This pattern was observed net of respondents’ own perceived friendships, further suggesting that the social responses to sex vary by gender of the sexual actor. However, findings for “making out” showed a reverse double standard, such that female adolescents reporting this behavior had increases in peer acceptance and male adolescents reporting the same behavior had decreases in peer acceptance over time. Results thus suggest that peers enforce traditional sexual scripts for both “heavy” and “light” sexual behaviors during adolescence. These findings have important implications for sexual health education, encouraging educators to develop curricula that emphasize the gendered social construction of sexuality and to combat inequitable and stigmatizing peer responses to real or perceived deviations from traditional sexual scripts.

In the middle of the paragraph just above Figure 6, there is the following sentence: “The range of the mean of the distribution of the proportion infected generated by the simulations is narrow, between 0.5 % and 0.2 % of all nodes.” This should read “between 0.05 % and 0.2 % of all nodes.”

China’s HIV prevalence is low, mainly concentrated among female sex workers (FSWs), their clients, men who have sex with men, and the stable partners of members of these high-risk groups. We evaluate the contribution to the spread of HIV of China’s regime of heterosexual relations, of the structure of heterosexual networks, and of the attributes of key population groups with simulations driven by data from a cross-sectional survey of egocentric sexual networks of the general population of Shanghai and from a concurrent respondent-driven sample of FSWs. We find that the heterosexual network generated by our empirically calibrated simulations has low levels of partner change, strong constraints on partner selection by age and education, and a very small connected core, mainly comprising FSWs and their clients and characterized by a fragile transmission structure. This network has a small HIV epidemic potential but is compatible with the transmission of bacterial sexually transmitted infections (STIs), such as syphilis, which are less susceptible to structural breaks in transmission of infection. Our results suggest that policies that force commercial sex underground could have an adverse effect on the spread of HIV and other STIs.

China’s HIV prevalence is low, mainly concentrated among female sex workers (FSWs), their clients, men who have sex with men, and the stable partners of members of these high-risk groups. We evaluate the contribution to the spread of HIV of China’s regime of heterosexual relations, of the structure of heterosexual networks, and of the attributes of key population groups with simulations driven by data from a cross-sectional survey of egocentric sexual networks of the general population of Shanghai and from a concurrent respondent-driven sample of FSWs. We find that the heterosexual network generated by our empirically calibrated simulations has low levels of partner change, strong constraints on partner selection by age and education, and a very small connected core, mainly comprising FSWs and their clients and characterized by a fragile transmission structure. This network has a small HIV epidemic potential but is compatible with the transmission of bacterial sexually transmitted infections (STIs), such as syphilis, which are less susceptible to structural breaks in transmission of infection. Our results suggest that policies that force commercial sex underground could have an adverse effect on the spread of HIV and other STIs.

In the middle of the paragraph just above Figure 6, there is the following sentence: “The range of the mean of the distribution of the proportion infected generated by the simulations is narrow, between 0.5 % and 0.2 % of all nodes.” This should read “between 0.05 % and 0.2 % of all nodes.”