Social networks and smoking: exploring the effects of peer influence and smoker popularity through simulations

Simulating social network-based interventions for adolescent cigarette smoking

Social network-based adolescent substance use interventions have demonstrated potential for reducing adolescent cigarette smoking. This approach is premised upon leveraging youths' social networks for the diffusion of peer influence. Determining which adolescents to select in network interventions for reducing smoking is a major consideration. We utilize a simulation approach that first estimates Stochastic Actor-Oriented models (SAOM) of adolescent smoking using data from two of the largest schools from the longitudinal saturation sample of the National Study of Adolescent to Adult Health (Add Health) (n = 3,154). We then conduct Agent-Based Simulation models which mimic the consequences of intervention strategies selecting adolescents in network positions and structures that are salient for smoking and the diffusion of peer influence within school-based networks, and we select adolescents smoking at different levels. Our findings indicate that selecting adolescents occupying central network positions yielded the greatest reductions in the number of smokers in a school, one year post intervention. Moreover, our findings indicate that in the school with the higher smoking prevalence, there was a beneficial network multiplier effect one year later, which resulted in more non-smokers than those smokers initially intervened upon. When examining the effects of varying the magnitude of peer influence, we find that targeting central positions in networks led to even greater decreases in smoking in schools with higher levels of peer influence. Our findings highlight interdependence and sensitivity of peer influence to network position and have implications for informing school-based network interventions for adolescent smoking.

The Impact of Social Norms on Diffusion Dynamics: A Simulation of E-Cigarette Use Behavior

Diffusion of innovations theory can be used to understand how to prevent or slow the spread of harmful behaviors, such as e-cigarette use in adolescent social networks. This study explores how different network intervention strategies could impact diffusion dynamics through network simulations based on observed social norms and e-cigarette use data. Simulations were initialized with baseline network data collected from 10 schools in a prospective cohort study of adolescent social networks and health behaviors in Southern California. Diffusion conditions varied by changes in social norms for intervention nodes (pro-e-cigarette, anti-e-cigarette, or neutral norms) and intervention strategy, where greater pro- and anti-tobacco norms were assigned to 15% of the network based on four intervention seeding conditions: opinion leadership, betweenness centrality, segmentation, and random selection. For each network, simulations were run using the netdiffuseR package in R and multivariate generalized linear models were estimated to examine changes in diffusion dynamics. Diffusion prevalence and rate were greater in denser networks and networks with more initial e-cigarette users. Anti-e-cigarette norms significantly decreased average prevalence across all intervention conditions. Strategically selecting high betweenness centrality nodes and opinion leader nodes significantly decreased the average prevalence of e-cigarette use. The results of this study show that achieving a change in norms for 15% of a network can substantially impact e-cigarette use prevalence. Furthermore, this study enhances our knowledge of how personal and network factors affect diffusion dynamics and demonstrates that targeting social norms through network-based interventions is one avenue for slowing the spread of harmful behaviors.

Social network characteristics of COVID-19 vaccination and preventive health behaviors: Cross-sectional findings from the US northeast during the early COVID-19 pandemic

Background

The link between individuals' vaccine attitudes and their social networks has been widely studied, but less is known about how these networks impact broader health behaviors like precautionary measures during the COVID-19 pandemic.

Methods

Egocentric social network data were collected from June 7-21, 2021, via an online survey by researchers based at the Brown University School of Public Health. The sample (n = 173) was recruited through Amazon's Mechanical Turk in Connecticut, Massachusetts, New Jersey, New York, and Rhode Island. Participants reported their COVID-19 precautionary behaviors and those of up to 5 of their closest social network contacts (SNCs, n = 851). The primary outcome was the mean of 13 CDC-recommended precautionary behaviors (PBS). Covariates included SNCs' COVID-19 testing, hospitalization, vaccination, disease experiences, social distancing adherence, and encouragement of participants' testing and vaccination. Associations between PBS and SNC attributes were assessed using chi-square tests, t-tests, and Generalized Estimating Equations (GEE).

Results

Eighty percent of participants had received at least one vaccine dose. The PBS ranged from 0.38 to 3.00 (M = 2.3) and was positively associated with SNCs' adherence to social distancing guidelines (0.33, p < 0.001), encouragement of social distancing (0.33, p < 0.001), encouragement of vaccination (0.25, p = 0.001), mask-wearing behavior (0.20, p = 0.008), receiving the vaccine (0.20, p = 0.01), and encouragement of testing (0.17, p < 0.05).

Discussion

The clustering of precautionary behaviors in social networks highlights the potential of leveraging these networks to promote public health interventions. The identification of clusters of unprotected communities at risk underscores the need to address disparities and integrate interpersonal factors into future pandemic responses.

Effects of Online Friendships on Safer Sex Communication and Behavior among Black Sexual Minority Men: A Study of Network Exposure

This study draws on social normative and social learning theories to examine the masspersonal safer sex communication (i.e., Facebook posts about safer sex) and safer sex behavior (i.e., condom use) in a cohort of Black sexual minority men (BSMM) (N = 340), with an eye toward understanding their relationship with the safer sex communication and behaviors of their BSMM Facebook friends. Using linear network autocorrelation regression models, results showed that BSMM's safer sex communication and condom use behavior were each associated with the communication and behavior of their online peers. Specifically, BSMM's condom use was positively associated with their friends' condom use and friends' safer sex communication, and BSMMs' safer sex communication was positively associated with friends' safer sex communication. Moreover, contrary to prior research, BSSM's safer sex communication and condom use were not related to one another, suggesting that talking about safer sex on social media should not be interpreted to be an indication of engageDment in safer sex behavior. These findings underscore an opportunity to leverage peer influence in social media networks, particularly in the form of masspersonal communication, to encourage cascades of safer sex messaging among peers and adoption of safer sex behavior.

Association Between Social Media Use and Substance Use Among Middle and High School-Aged Youth

Purpose: The purpose of our study was to identify whether different aspects of social media use were associated with substance use among middle- and high school-aged youth. Methods: Participants were recruited from four Northeast U.S. middle schools and invited to complete an online survey in Fall 2019 and Fall 2020. We conducted separate adjusted logistic mixed effects models the substance use outcomes: ever use of alcohol, cannabis, e-cigarettes, tobacco cigarettes, prescription drugs, and multiple substances. Our sample included N = 586 participants (52.7% female, 58% White). Results: Seeing a social media post about drugs/alcohol in the past-12-months was significantly associated with higher odds of ever using alcohol, cannabis, e-cigarettes, and multiple substance use. Total number of social media sites ever used was significantly associated with higher odds of ever using cannabis, cigarettes, e-cigarettes, and multiple substances. Checking social media every hour or more was significantly associated with higher odds of ever using alcohol. Higher problematic internet use score was significantly associated with higher odds of ever using cannabis, e-cigarettes, and multiple substances. Online social support seeking score was not associated substance use. Conclusions: Our findings support the need for substance use prevention and social media literacy education and screening to begin early, ideally in elementary school before youth are using social media and substances.

Using systems science to advance health equity in tobacco control: a causal loop diagram of smoking

OBJECTIVES

Develop and use a causal loop diagram (CLD) of smoking among racial/ethnic minority and lower-income groups to anticipate the intended and unintended effects of tobacco control policies.

METHODS

We developed a CLD to elucidate connections between individual, environmental and structural causes of racial/ethnic and socioeconomic disparities in smoking. The CLD was informed by a review of conceptual and empirical models of smoking, fundamental cause and social stress theories and 19 qualitative interviews with tobacco control stakeholders. The CLD was then used to examine the potential impacts of three tobacco control policies.

RESULTS

The CLD includes 24 constructs encompassing individual (eg, risk perceptions), environmental (eg, marketing) and structural (eg, systemic racism) factors associated with smoking. Evaluations of tobacco control policies using the CLD identified potential unintended consequences that may maintain smoking disparities. For example, the intent of a smoke-free policy for public housing is to reduce smoking among residents. Our CLD suggests that the policy may reduce smoking among residents by reducing smoking among family/friends, which subsequently reduces pro-smoking norms and perceptions of tobacco use as low risk. On the other hand, some residents who smoke may violate the policy. Policy violations may result in financial strain and/or housing instability, which increases stress and reduces feelings of control, thus having the unintended consequence of increasing smoking.

CONCLUSIONS

The CLD may be used to support stakeholder engagement in action planning and to identify non-traditional partners and approaches for tobacco control.

Association between Social Participation and Remaining Teeth and Urban-Rural Difference among Older Adults in China

Oral health is an important part of older adults' general health. The study examined the association between social participation (formal and informal) and remaining teeth and the urban-rural difference based on a national survey of older adults in China. The data of older adults were extracted from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and analyzed. A total of 11,948 respondents were ultimately involved, including 6836 urban respondents and 5112 rural respondents. Informal social participation and formal social participation were used to assess social participation. The number of remaining natural teeth was measured. Social participation was significantly associated with remaining teeth among older adults, after adjusting for confounders, a one-level increase in the informal social participation was associated with a decrease in natural teeth by 0.152 (95% CI = -0.274; -0.030) and a one-level increase in the formal social participation was associated with a decrease in natural teeth by 0.370 (95% CI = -0.585; -0.156). In addition, the association between social participation (formal and informal) and remaining teeth was observed among urban older adults, but not rural older adults. A high level of social participation may effectively decrease the risk of oral-health problems for the Chinese older adults. The findings suggest recommendations for an older adults-targeted policy and the practice of oral-health promotion. However, the urban-rural difference should be taken into full consideration in social-participation-driven oral-health promotion interventions.

Multilevel network interventions: Goals, actions, and outcomes

COVID-19 has resulted in dramatic and widespread social network interventions across the globe, with public health measures such as distancing and isolation key epidemiological responses to minimize transmission. Because these measures affect social interactions between people, the networked structure of daily lives is changed. Such largescale changes to social structures, present simultaneously across many different societies and touching many different people, give renewed significance to the conceptualization of social network interventions. As social network researchers, we need a framework for understanding and describing network interventions consistent with the COVID-19 experience, one that builds on past work but able to cast interventions across a broad societal framework. In this theoretical paper, we extend the conceptualization of social network interventions in these directions. We follow Valente (2012) with a tripartite categorization of interventions but add a multilevel dimension to capture hierarchical aspects that are a key feature of any society and implicit in any network. This multilevel dimension distinguishes goals, actions, and outcomes at different levels, from individuals to the whole of the society. We illustrate this extended taxonomy with a range of COVID-19 public health measures of different types and at multiple levels, and then show how past network intervention research in other domains can also be framed in this way. We discuss what counts as an effective network, an effective intervention, plausible causality, and careful selection and evaluation, as central to a full theory of network interventions.

Social Network Ties and Responses to COVID-19 Among E-Cigarette Users

Social networks can enhance behavioral changes or entrench existing patterns of behavior. We aimed to identify how network ties to other e-cigarette users shaped responses to the pandemic and e-cigarette considerations. A national U.S. survey of 562 e-cigarette users was conducted during April 2020. Participants self-reported network ties to other e-cigarette users and pandemic outcomes: receiving expressions of concern about vaping, risk for a bad COVID outcome, changes in e-cigarette risk perceptions, and considerations of quitting. Each additional e-cigarette user tie was associated with a 0.014 unit increase in expressions of concern (p < 0.001), a 0.034 unit increase in perceived risk of a bad outcome (p < 0.05), and 3.9% higher odds of quit considerations (OR = 1.039; p < 0.01). Family ties to e-cigarette users were particularly important. Additional e-cigarette users within a network shaped risk perceptions in response to COVID-19. Network ties to other e-cigarette users have implications for cessation or reduction of e-cigarette use.

Understanding factors associated with firearm possession: Examining differences between male and female adolescents and emerging adults seeking emergency department care

Firearm possession increases the likelihood of hospital visits among adolescents and emerging adults for both males and females. To better inform prevention practices, we examine data among adolescents and emerging adults (A/EAs; ages 16 to 29) presenting to an urban emergency department for any reason to understand the differences in firearm possession between males and females (N = 1312; 29.6% male; 50.5% Black). Regression identified firearm possession correlates, such as male sex (AOR = 2.26), firearm attitudes (AOR = 1.23), peer firearm possession (AOR = 9.84), and community violence exposure (AOR = 1.02). When stratified by sex (e.g., male vs female), regression results yielded differences in correlates for firearm possession: in males, peer firearm possession (AOR = 8.96) were significant, and in females, firearm attitudes (AOR = 1.33) and peer firearm possession (AOR = 11.24) were significant. An interaction between sex and firearm attitudes demonstrated that firearm attitudes were differentially associated with firearm possession between female and male A/EAs (AOR = 1.28). Overall, we found that females are more likely to endorse retaliatory firearm attitudes, and both males and females are highly influenced by their perception of peer firearm possession. These results help inform prevention strategies across multiple settings, especially for hospital-based violence interventions, and suggest that tailored approaches addressing differences between male and female A/EAs are appropriate when addressing firearm violence and injury risk among A/EAs.

The Role of Social Position Within Peer Groups in Distress-Motivated Smoking Among Adolescents

OBJECTIVE

The relationship between smoking and adolescents' peer relationships is complex, with studies showing increased risk of smoking for adolescents of both very high and very low social position. A key question is whether the impact of social position on smoking depends on an adolescent's level of coping motives (i.e., their desire to use smoking to mitigate negative affect).

METHOD

We assessed how social position predicts nicotine dependence in a longitudinal sample (N = 3,717; 44.8% male; mean age = 13.41 years) of adolescent lifetime smokers measured between 6th and 12th grades. Using both social network analysis and multilevel modeling, we assessed this question at the between-person and within-person level, hypothesizing that within-person decreases in social position would lead to increased risk of nicotine dependence among those with high levels of coping motives.

RESULTS

In contrast to our hypotheses, only interactions with the between-person measures of social position were found, with a slight negative relationship at low levels of coping motives. In addition, the main effect of coping motives was considerably stronger than that of social position at the between-person level, and social position had no significant within-person main effect on nicotine dependence risk.

CONCLUSIONS

These results suggest that adolescents with higher overall levels of social position among their peers may have slightly decreased risk for nicotine dependence, but only when coping motives are low. Counter to expectations, higher levels of nicotine dependence risk were not linked to fluctuations in social position.

The Moderating Role of Context: Relationships between Individual Behaviors and Social Networks

A social context can be viewed as an entity or unit around which a group of individuals organize their activities and interactions. Social contexts take such diverse forms as families, dwelling places, neighborhoods, classrooms, schools, workplaces, voluntary organizations, and sociocultural events or milieus. Understanding social contexts is essential for the study of individual behaviors, social networks, and the relationships between the two. Contexts shape individual behaviors by providing an avenue for non-dyadic conformity and socialization processes. The co-participation within a context affects personal relationships by acting as a focus for tie formation. Where participation in particular contexts confers status, this effect may also lead to differences in popularity within interpersonal networks. Social contexts may further play a moderating role in within-network influence and selection processes, providing circumstances that either amplify or suppress these effects. In this paper we investigate the joint role of co-participation via social contexts and dyadic interaction in shaping and being shaped by individual behaviors with the context of a U.S. high school. Implications for future study of social contexts are suggested.

Do high school friends still matter for health behavior in adulthood? Variations in smoking trajectories by adolescent peer smoking networks, race/ethnicity, and gender

Peers play an influential role in the initiation of smoking during adolescence. However, there has been limited literature examining whether adolescent peers are associated with longer-term patterns of smoking. This study uses data from the National Longitudinal Study of Adolescent to Adult Health to examine whether age-based trajectories of smoking likelihood from adolescence to adulthood are associated with the number of adolescent friends who smoked and how this association differs by race/ethnicity and gender. Findings using multilevel growth curve models indicate that individuals who have more adolescent friends who smoked have higher probabilities of smoking during adolescence than those with no adolescent smoking friends. As individuals age into adulthood, the association between adolescent friends' smoking behavior and individual-level smoking begin to dissipate but does not completely disappear. Further analyses show that there are no differences in this association by gender, but there are differences by race/ethnicity. These findings suggest that high school friends continue to be associated with trajectories of smoking even twenty years after high school. These results indicate that anti-smoking campaigns should take a network approach to preventing smoking in adolescence as well as recognize that the same campaign strategy may not work for all groups.

Situating agent-based modelling in population health research

Today's most troublesome population health challenges are often driven by social and environmental determinants, which are difficult to model using traditional epidemiological methods. We agree with those who have argued for the wider adoption of agent-based modelling (ABM) in taking on these challenges. However, while ABM has been used occasionally in population health, we argue that for ABM to be most effective in the field it should be used as a means for answering questions normally inaccessible to the traditional epidemiological toolkit. In an effort to clearly illustrate the utility of ABM for population health research, and to clear up persistent misunderstandings regarding the method's conceptual underpinnings, we offer a detailed presentation of the core concepts of complex systems theory, and summarise why simulations are essential to the study of complex systems. We then examine the current state of the art in ABM for population health, and propose they are well-suited for the study of the 'wicked' problems in population health, and could make significant contributions to theory and intervention development in these areas.

Comparing targeting strategies for network-based adolescent drinking interventions: A simulation approach

Public health researchers and social scientists highlight the promise of network-based strategies to inform and enhance interventions that curb risky adolescent health behaviors. However, we currently lack an understanding of how different variants of network-based interventions shape the distribution of targeted behaviors. The current project considers the effectiveness of five targeting strategies that are designed to have differential impacts on the health of program participants versus non-participants. Using simulations that are empirically-grounded in 28 observed school-based networks from the PROSPER study, we evaluate how these approaches shape long-term alcohol use for intervention participants and non-participants, separately, and consider whether contextual factors moderate their success. Findings suggest that enrolling well-connected adolescents results in the lowest drinking levels for non-participants, while strategies that target groups of friends excel at protecting participants from harmful influences. These trends become increasingly pronounced in contexts characterized by higher levels of peer influence.

Insight into Selecting Adolescents for Drinking Intervention Programs: a Simulation Based on Stochastic Actor-Oriented Models

Adolescent drinking remains a prominent public health and socioeconomic issue in the USA with costly consequences. While numerous drinking intervention programs have been developed, there is little guidance whether certain strategies of participant recruitment are more effective than others. The current study aims at addressing this gap in the literature using a computer simulation approach, a more cost-effective method than employing actual interventions. We first estimate stochastic actor-oriented models for two schools from the National Longitudinal Study of Adolescent to Adult Health (Add Health). We then employ different strategies for selecting adolescents for the intervention (either based on their drinking levels or their positions in the school network) and simulate the estimated model forward in time to assess the aggregated level of drinking in the school at a later time point. The results suggest that selecting moderate or heavy drinkers for the intervention produces better results compared to selecting casual or light drinkers. The intervention results are improved further if network position information is taken into account, as selecting drinking adolescents with higher in-degree or higher eigenvector centrality values for intervention yields the best results. Results from this study help elucidate participant selection criteria and targeted network intervention strategies for drinking intervention programs in the USA.

Agent-Based Modeling for Implementation Research: An Application to Tobacco Smoking Cessation for Persons with Serious Mental Illness

Background

Implementation researchers have sought ways to use simulations to support the core components of implementation, which typically include assessing the need for change, designing implementation strategies, executing the strategies, and evaluating outcomes. The goal of this paper is to explain how agent-based modeling could fulfill this role.

Methods

We describe agent-based modeling with respect to other simulation methods that have been used in implementation science, using non-technical language that is broadly accessible. We then provide a stepwise procedure for developing agent-based models of implementation processes. We use, as a case study to illustrate the procedure, the implementation of evidence-based smoking cessation practices for persons with serious mental illness (SMI) in community mental health clinics.

Results

For our case study, we present descriptions of the motivating research questions, specific models used to answer these questions, and a summary of the insights that can be obtained from the models. In the first example, we use a simple form of agent-based modeling to simulate the observed smoking behaviors of persons with SMI in a recently completed trial (IDEAL, Comprehensive Cardiovascular Risk Reduction Trial in Persons with SMI). In the second example, we illustrate how a more complex agent-based approach that includes interactions between patients, providers and site administrators can be used to provide guidance for an implementation intervention that includes training and organizational strategies. This example is based in part on an ongoing project focused on scaling up evidence-based tobacco smoking cessation practices in community mental health clinics in Maryland.

Conclusion

In this paper we explain how agent-based models can be used to address implementation science research questions and provide a procedure for setting up simulation models. Through our examples, we show how what-if scenarios can be examined in the implementation process, which are particularly useful in implementation frameworks with adaptive components.

COVID-19 information on social media and preventive behaviors: Managing the pandemic through personal responsibility

In the face of a pandemic, social media have found to be vital information channels that might exert a positive influence on people's preventive behaviors. However, little is known about the underlying processes that may mediate or moderate the relationship. The present study examined the relation between novel coronavirus disease (COVID-19) information consumption on social media and preventive behaviors, as well as the mediation role of personal responsibility and moderation role of health orientation. A sample of 511 online participants (mean age = 32.47 years) responded to anonymous questionnaires regarding COVID-19 information consumption on social media, health orientation, personal responsibility, and preventive behaviors. Bias-corrected bootstrap method was used to test the moderated mediation model. Results indicated that after controlling for participants' age, gender, education, income, and insurance, personal responsibility mediated the relationship between COVID-19 information consumption on social media and preventive behaviors. Meanwhile, the direct relation between COVID-19 information consumption on social media and preventive behaviors, and the mediation effect of personal responsibility were moderated by health orientation. The present study can extend our knowledge about how risk information consumption on social media is related to one's behavioral outcomes. Implications and limitations about the present study are also discussed.

Predictors of Cigarette Smoking Cessation in Adolescents: A Systematic Review

PURPOSE

To update a systematic review published in 2012 that identified predictors of cigarette smoking cessation among adolescents.

METHODS

The PubMed and Web of Science databases were searched for relevant articles published between September 2010 and January 2018, using the following keywords: smoking OR tobacco OR cessation; quit OR stop; longitudinal OR prospective OR cohort. Our search identified 3,399 articles. Inclusion criteria included longitudinal studies (intervention and cohort studies) evaluating cigarette smoking cessation in young people (aged 10-24 years). After screening, in total, 34 articles were included in the review.

RESULTS

In total, 63 predictors of smoking cessation among adolescents were identified, with 36 new predictors that were not identified in the previous review: nine sociodemographic factors, 13 psychosocial factors, five behavioral factors, 19 social influences factors, eight smoking related variables, six environmental factors, 2 health related variables, and one genetic factor.

CONCLUSIONS

To increase the probability of successful smoking cessation, strategies targeting young smokers should consider both individual and environmental predictors of cessation.

Social Network Mediation Analysis: A Latent Space Approach

A social network comprises both actors and the social connections among them. Such connections reflect the dependence among social actors, which is essential for individuals' mental health and social development. In this article, we propose a mediation model with a social network as a mediator to investigate the potential mediation role of a social network. In the model, the dependence among actors is accounted for by a few mutually orthogonal latent dimensions which form a social space. The individuals' positions in such a latent social space are directly involved in the mediation process between an independent and dependent variable. After showing that all the latent dimensions are equivalent in terms of their relationship to the social network and the meaning of each dimension is arbitrary, we propose to measure the whole mediation effect of a network. Although individuals' positions in the latent space are not unique, we rigorously articulate that the proposed network mediation effect is still well defined. We use a Bayesian estimation method to estimate the model and evaluate its performance through an extensive simulation study under representative conditions. The usefulness of the network mediation model is demonstrated through an application to a college friendship network.

Inside the adolescent voice: A qualitative analysis of the appeal of different tobacco products

INTRODUCTION

While cigarette use has decreased, adolescents’ overall use of tobacco (e.g. e-cigarettes, cigars, and hookah) has increased. The purpose of this qualitative study is to highlight the decision-making process of adolescents to use certain products over others and why certain tobacco products appeal to them.

METHODS

Twenty-five participants were recruited from a larger study surveying adolescents’ perceptions and tobacco use (772 high school students). The participants were involved in one-on-one semi-structured phone interviews on the appeal of different tobacco products. Interviews were recorded, transcribed verbatim, and analyzed by identifying relevant codes and themes.

RESULTS

Participants for this study had a mean age of 16.4 (SD=1.2) years; over half (14/25) were female. Three major themes emerged from the interviews: 1) social context and circumstances to use, including using and sharing with peers, and reducing boredom; 2) importance of flavors, smell, taste, smoke tricks, and accessibility of products; and 3) misperceptions and misinformation of product risks.

CONCLUSIONS

The findings that emerged showed why participants favored certain tobacco products, especially e-cigarettes, over others. The results support areas for future research and practice, and inform how interventions can better address the appeal of different tobacco products to ultimately prevent adolescent use.

Using Longitudinal Social Network Analysis to Evaluate a Community-Wide Parenting Intervention

Harsh parenting attitudes and behaviors negatively impact children's behavior and development, and are linked to heightened levels of violence in children. Parent training programs are effective preventive interventions, but only reach caregivers who attend them. In this study, programs were implemented alongside a community mobilization process, intended to use caregivers' social networks to disseminate new parenting skills community wide. We used social network analysis to explore whether this intervention, first, increased positive parenting, second, changed social networks of female caregivers (selection), and, third, influenced parenting behavior via connections (socialization), while controlling for psychiatric morbidity, parenting stress, alcohol misuse, and child's age. "Colored" Afrikaans-speaking female caregivers (N = 235; mean age 35.92 years) in a rural community in South Africa, with children between 1½ and 18 years old, were included in the study; two waves of data were collected (January-April 2016 and June-October 2017). We detected community-wide increases in positive parenting behavior (involvement, supervision, consistent discipline, and reduced corporal punishment). Attending at least one session of a parenting skills training program (n = 51; 21.7%) significantly predicted increases in network centrality (i.e., outdegree and indegree). Caregivers appeared to use similar parenting behavior to other caregivers they were connected to within the network, especially when those others attended a parenting skills training program. Overall, the results suggest that the information in the intervention was spread throughout the community through social interactions with program attendees and the community mobilization process. The results also illustrate the value of social network analysis for ascertaining the processes by which the intervention achieved its impact.

A Breath of Knowledge: Overview of Current Adolescent E-cigarette Prevention and Cessation Programs

PURPOSE

Adolescent use of electronic cigarettes (e-cigarettes) has risen rapidly, which is concerning given the health effects of e-cigarettes and youth susceptibility to nicotine addiction. It is critical that efforts to educate, prevent, and reduce adolescent use of e-cigarettes are developed and evaluated. The purpose of this paper is to review available current prevention and cessation programs.

FINDINGS

A web-based search of currently available e-cigarette prevention and cessation/treatment programs was conducted using Google in May of 2020. Programs were then reviewed on whether they included theory- and evidence-based practices of effective adolescent prevention and cessation programs. Eight prevention programs, seven cessation programs, and one program that addressed both prevention and cessation were identified and included in this review. Most prevention programs included the importance of understanding flavored e-cigarette products, addressed industry-targeted marketing, included social learning activities to develop refusal skills, delivered free-of-cost, available online, and explicitly stated their incorporation of theory. Five prevention programs and two cessation programs had empirically evaluated their e-cigarette-related components.

CONCLUSIONS

Although the programs reviewed largely incorporated theory and included key components known to be effective, there are some gaps in the programs' overall ability to prevent and stop adolescents from using e-cigarettes, such as lack of dedicated e-cigarette materials. More evidence-based tools, resources, and evaluations are needed to best inform adolescent e-cigarette cessation. Addressing the gaps that existing prevention and cessation programs present requires intervening at multiple systematic levels, conducting more rigorous program evaluations, and bolstering the availability of cessation programs.

The responsiveness of criminal networks to intentional attacks: Disrupting darknet drug trade

Physical, technological, and social networks are often at risk of intentional attack. Despite the wide-spanning importance of network vulnerability, very little is known about how criminal networks respond to attacks or whether intentional attacks affect criminal activity in the long-run. To assess criminal network responsiveness, we designed an empirically-grounded agent-based simulation using population-level network data on 16,847 illicit drug exchanges between 7,295 users of an active darknet drug market and statistical methods for simulation analysis. We consider three attack strategies: targeted attacks that delete structurally integral vertices, weak link attacks that delete large numbers of weakly connected vertices, and signal attacks that saturate the network with noisy signals. Results reveal that, while targeted attacks are effective when conducted at a large-scale, weak link and signal attacks deter more potential drug transactions and buyers when only a small portion of the network is attacked. We also find that intentional attacks affect network behavior. When networks are attacked, actors grow more cautious about forging ties, connecting less frequently and only to trustworthy alters. Operating in tandem, these two processes undermine long-term network robustness and increase network vulnerability to future attacks.

Agent-based Modeling in Tobacco Regulatory Science: Exploring 'What if' in Waterpipe Smoking

Objectives

Waterpipe tobacco smoking (WTS) is an emerging public health crisis, particularly among youth and young adults. Different from the use of other tobacco products and e-cigarettes, WTS tends to be a social activity occurring among friends or persons associated with social networks. In this paper, we review a potential strategy for WTS-related research.

Methods

As a bottom-up computational model, agent-based modeling (ABM) can simulate the actions and interactions of agents, as well as the dynamic interactions between agents and their environments, to gain an understanding of the functioning of a system. ABM is particularly useful for incorporating the influence of social networks in WTS, and capturing people's space-time activity and the spatial distribution of WTS venues.

Results

Comprehensive knowledge of WTS-related behaviors at the individual level is needed to take advantage of ABM and use it to examine policies such as the interaction between WTS and cigarette smoking and the effect of flavors used in waterpipe tobacco. Longitudinal and WTS-specific surveys and laboratory experiments are particularly helpful to understand WTS basic mechanisms and elicit individual preferences, respectively.

Conclusions

We argue that the uniqueness of WTS makes ABM a promising tool to be used in WTS-related research, as well as understanding use of other tobacco products.

Peer social network processes and adolescent health behaviors: A systematic review

Research has highlighted the importance of peers for determining health behaviors in adolescents, yet these behaviors have typically been investigated in isolation. We need to understand common network processes operating across health behaviors collectively, in order to discern how social network processes impact health behaviors. Thus, this systematic review of studies investigated adolescent peer social networks and health behaviors. A search of six databases (CINAHL, Education Resources Information Centre, Embase, International Bibliography of the Social Sciences, Medline and PsycINFO) identified 55 eligible studies. The mean age of the participants was 15.1 years (range 13-18; 51.1% female). Study samples ranged from 143 to 20,745 participants. Studies investigated drinking (31%), smoking (22%), both drinking and smoking (13%) substance use (18%), physical activity (9%) and diet or weight management (7%). Study design was largely longitudinal (n = 41, 73%) and cross-sectional (n = 14, 25%). All studies were set in school and all but one study focused on school-based friendship networks. The Newcastle-Ottawa Scale was used to assess risk of bias: studies were assessed as good (51%), fair (16%) or poor (33%). The synthesis of results revolved around two network behavior patterns: 1) health behavior similarity within a social network, driven by homophilic social selection and/or social influence, and 2) popularity: health behavior engagement in relation to changes in social status; or network popularity predicting health behaviors. Adolescents in denser networks had statistically significant lower levels of harmful behavior (n = 2/2, 100%). Findings suggest that social network processes are important factors in adolescent health behaviors.

A narrative review of the use of agent-based modeling in health behavior and behavior intervention

Studies of health behaviors and behavior intervention have begun to explore the potential of agent-based modeling (ABM). A review of how ABMs have been used in health behavior, behavior intervention, and corresponding insights is warranted. The goal of this study was to provide a narrative review of the applications of ABMs in health behavior change and intervention. I will focus on two perspectives: (a) the mechanism of behavior and behavior change and (b) ABMs' use for behavior intervention. I identified and reviewed 17 ABMs applied to behaviors including physical activity, diet, alcoholic drinking, smoking, and drug use. Among these ABMs, I grouped their mechanisms of behavior change into four categories and evaluated the advantages and disadvantages of each mechanism. For behavior intervention, I evaluated the use of ABMs on levels of individual, interpersonal, and neighborhood environment. Various behavior change mechanisms and simplifications existed because of our limited knowledge of behaviors at the individual level. Utility maximization was the most frequently used mechanism. ABMs offered insights for behavior intervention including the benefits of upstream interventions and multilevel intervention, as well as balances among various factors, outcomes, and populations. ABMs have been used to model a diversity of behaviors, populations, and interventions. The use of ABMs in health behavior is at an early stage, and a major challenge is our limited knowledge of behaviors at the individual level.

Smoking Diffusion through Networks of Diverse, Urban American Adolescents over the High School Period

This study uses recent data to investigate if smoking initiation diffuses through friendship networks over the high school period and explores if diffusion processes differ across schools. One thousand four hundred and twenty-five racially and ethnically diverse youth from four high schools in Los Angeles were surveyed four times over the high school period from 2010 to 2013. Probit regression models and stochastic actor-based models for network dynamics tested for peer effects on smoking initiation. Friend smoking was found to predict adolescent smoking, and smoking initiation diffused through friendship networks in some but not all of the schools. School differences in smoking rates and the popularity of smokers may be linked to differences in the diffusion of smoking through peer networks. We conclude that there are differences in peer effects on smoking initiation across schools that will be important to account for in network-based smoking interventions.

Social influence of e-cigarette smoking prevalence on smoking behaviours among high-school teenagers: Microsimulation experiments

The prevalence of electronic cigarette (e-cigarette) use has rapidly increased among young people, while conventional cigarette use has decreased in this age group. However, some evidence suggests that e-cigarette use is likely to induce conventional cigarette smoking. The present study explored the social influence of the prevalence of e-cigarette use in the peer network and in the general population as a potential mechanism by which e-cigarette use affects adolescents’ overall smoking behaviours. For this purpose, we developed an agent-based model in which young agents repeatedly choose to smoke conventional cigarettes and/or e-cigarettes, or to remain non-smokers. The choice is based on the agent’s evaluation of the utility derived from smoking and attitude towards smoking (‘openness’), which is influenced by smoking prevalence in the agent’s peer network and in the broader society. We also assumed a ‘crossover’ effect between the different types of smoking. The model was calibrated with United States National Youth Tobacco Survey data to reflect real-world numbers. We further simulated the prevalence of different types of smoking under counterfactual scenarios with different levels of openness and crossover effects. The models developed successfully reproduced actual prevalence trends in different types of smoking from 2011 to 2014. Openness to smoking is associated with a dramatic increase in e-cigarette smoking and especially in dual smoking, which cancels out the decline in sole conventional smoking. Larger crossover effects are associated with a higher prevalence of conventional smoking. The simulation results indicate that the social influence of the prevalence of e-cigarette use may influence young people to initiate or continue conventional cigarette smoking. Assessing the impact of e-cigarettes in the general population as a ‘healthier’ alternative to conventional smoking may require carefully monitoring trends in young people’s smoking behaviours.

Exploring the Social Structure of a Health-Related Online Community for Tobacco Cessation: A Two-Mode Network Approach

Unhealthy behaviors, such as tobacco use, increase individual health risk while also creating a global economic burden on the healthcare system. Social ties have been seen as an important, yet complex factor, to sustain abstinence from these modifiable risk behaviors. However, the underlying social mechanisms are still opaque and poorly understood. Digital health communities provide opportunities to understand social dependencies of behavior change because peer interactions in these platforms are digitized. In this paper, we present a novel approach that integrates theories of behavior change and Exponential Random Graph Models (ERGMs) to understand structural dependencies between users of an online community and the behavior change techniques that are manifested in their communication using an affiliation network. Results indicate population specific traits in terms of individuals' engagement in peer communication embed behavior change techniques in online social settings. Implications for personalized health promotion technologies are discussed.

A multivalued agent-based model for the study of noncommunicable diseases

This paper aims to test and illustrate the utility and extensibility of an existing model, SimNCD (Simulation of NonCommunicable Diseases). It also proposes a way to include questionnaires - widely used in epidemiology - in the individual's reasoning mechanism in order to identify his/her attitude and personal choices. SimNCD is a formal agent-based model. It helps researchers and health practitioners study and simulate the complex dynamics of noncommunicable diseases. It models individuals that evolve within a social network, and behave while engaging in activities offered by their physical environment. The literature strongly supports the influence of the individual's behavioral choices on their health, particularly, the acquirement and maintainability of noncommunicable diseases. Therefore, we propose to extend SimNCD in order to acquire the agents with a reasoning process that allows them to choose the activities to practice. Thus, we model their attitude via preferences that are modeled based on the available literature and expressed with the linguistic 2-tuple method. Our solution also employs a multi-attribute decision-making method. We specify the proposed solution in the study of childhood obesity and use it to predict children's corpulence variations in different scenarios.

Gender differences in cigarette smoking and alcohol drinking among adolescents and young adults in Hanoi, Shanghai, and Taipei

Objective

This study aimed to examine gender differences in smoking and alcohol drinking behaviors in three Asian cities of Hanoi, Shanghai, and Taipei, and to assess the magnitude of gender differences across the three cities.

Methods

A total of 17,016 adolescents (age: 15–19 years) and young adults (age: 20–24 years) were selected using multi-stage sampling methods and surveyed in face-to-face interviews. A total of 16,554 unmarried respondents were included in this analysis.

Results

Gender differences were significant for smoking only, drinking only, and both behaviors in each city. Male respondents were 30.66 times more likely to report smoking only than female respondents in Hanoi, followed by Shanghai and Taipei. This pattern was similar for drinking only and both smoking and drinking behaviors.

Conclusions

The magnitude of gender differences in smoking only, drinking only, and both behaviors widely varies across the three cities. Further research can examine how these differences may be used to prevent and reduce smoking and drinking in the adolescent and young adult population.

Structural Equation Modeling of Social Networks: Specification, Estimation, and Application

Psychologists are interested in whether friends and couples share similar personalities or not. However, no statistical models are readily available to test the association between personalities and social relations in the literature. In this study, we develop a statistical model for analyzing social network data with the latent personality traits as covariates. Because the model contains a measurement model for the latent traits and a structural model for the relationship between the network and latent traits, we discuss it under the general framework of structural equation modeling (SEM). In our model, the structural relation between the latent variable(s) and the outcome variable is no longer linear or generalized linear. To obtain model parameter estimates, we propose to use a two-stage maximum likelihood (ML) procedure. This modeling framework is evaluated through a simulation study under representative conditions that would be found in social network data. Its usefulness is then demonstrated through an empirical application to a college friendship network.

Feedback Between Behavioral Adaptations and Disease Dynamics

We study the feedback processes between individual behavior, disease prevalence, interventions and social networks during an influenza pandemic when a limited stockpile of antivirals is shared between the private and the public sectors. An economic model that uses prevalence-elastic demand for interventions is combined with a detailed social network and a disease propagation model to understand the feedback mechanism between epidemic dynamics, market behavior, individual perceptions, and the social network. An urban and a rural region are simulated to assess the robustness of results. Results show that an optimal split between the private and public sectors can be reached to contain the disease but the accessibility of antivirals from the private sector is skewed towards the richest income quartile. Also, larger allocations to the private sector result in wastage where individuals who do not need it are able to purchase it but who need it cannot afford it. Disease prevalence increases with household size and total contact time but not by degree in the social network, whereas wastage of antivirals decreases with degree and contact time. The best utilization of drugs is achieved when individuals with high contact time use them, who tend to be the school-aged children of large families.

Peer Smoking and Smoking-related Beliefs Among College Students in Bangladesh

Objectives

Smoking is a significant public health issue in Bangladesh. The purpose of this study was to examine peer smoking and smoking-related beliefs among college students in Bangladesh.

Methods

College students at two universities in Dhaka, Bangladesh participated in a self-administered survey in May and June 2017.

Results

First, being a current or former smoker is associated with lower levels of beliefs among respondents that they would not smoke even with smoker friends or nervousness, and lower levels of intentions that they would not smoke, while current smokers and former smokers have different smoking-related beliefs. Second, having smoker friends is associated with lower levels of intentions that they would not smoke. Third, higher levels of normative beliefs that it is important not to smoke are associated with higher levels of beliefs that they would not smoke even with smoker friends or nervousness, higher levels of intentions that they would not smoke, and higher levels of avoidance of smoking.

Conclusions

Smoking-related beliefs and perceived norms in individuals’ social networks are important components in promoting tobacco cessation in Bangladesh. But it is challenging to prevent or intervene in smoking because of the high rates of smoking in this country and the high prevalence of smokers in individuals’ social networks. Future studies should examine the most effective interventions to combat smoking in high-smoking social networks, such as using mobile apps or social media, and evaluate the effectiveness of such interventions.

The interdependence of cigarette, alcohol, and marijuana use in the context of school-based social networks

The concurrent or sequential usage of multiple substances during adolescence is a serious public health problem. Given the importance of understanding interdependence in substance use during adolescence, the purpose of this study is to examine the co-evolution of cigarette smoking, alcohol, and marijuana use within the ever-changing landscape of adolescent friendship networks, which are a primary socialization context for adolescent substance use. Utilizing Stochastic Actor-Based models, we examine how multiple simultaneous social processes co-evolve with adolescent smoking, drinking, and marijuana use within adolescent friendship networks using two school samples from early waves of the National Longitudinal Study of Adolescent to Adult Health (Add Health). We also estimate two separate models examining the effects from using one substance to the initiation and cessation of other substances for each sample. Based on the initial model results, we simulate the model forward in time by turning off one key effect in the estimated model at a time, and observe how the distribution of use of each substance changes. We find evidence of a unilateral causal relationship from marijuana use to subsequent smoking and drinking behaviors, resulting in the initiation of drinking behavior. Marijuana use is also associated with smoking initiation in a school with a low substance use level, and smoking cessation in a school with a high substance use level. In addition, in a simulation model excluding the effect from marijuana use to smoking and drinking behavior, the number of smokers and drinkers decreases precipitously. Overall, our findings indicate some evidence of sequential drug use, as marijuana use increased subsequent smoking and drinking behavior and indicate that an adolescent's level of marijuana use affects the initiation and continuation of smoking and drinking.

Agent-Based Modeling in Public Health: Current Applications and Future Directions

Agent-based modeling is a computational approach in which agents with a specified set of characteristics interact with each other and with their environment according to predefined rules. We review key areas in public health where agent-based modeling has been adopted, including both communicable and noncommunicable disease, health behaviors, and social epidemiology. We also describe the main strengths and limitations of this approach for questions with public health relevance. Finally, we describe both methodologic and substantive future directions that we believe will enhance the value of agent-based modeling for public health. In particular, advances in model validation, comparisons with other causal modeling procedures, and the expansion of the models to consider comorbidity and joint influences more systematically will improve the utility of this approach to inform public health research, practice, and policy.

The influence of peer behavior as a function of social and cultural closeness: A meta-analysis of normative influence on adolescent smoking initiation and continuation

Although the influence of peers on adolescent smoking should vary depending on social dynamics, there is a lack of understanding of which elements are most crucial and how this dynamic unfolds for smoking initiation and continuation across areas of the world. The present meta-analysis included 75 studies yielding 237 effect sizes that examined associations between peers' smoking and adolescents' smoking initiation and continuation with longitudinal designs across 16 countries. Mixed-effects models with robust variance estimates were used to calculate weighted-mean Odds ratios. This work showed that having peers who smoke is associated with about twice the odds of adolescents beginning (OR ¯ = 1.96, 95% confidence interval [CI] [1.76, 2.19]) and continuing to smoke (OR ¯ = 1.78, 95% CI [1.55, 2.05]). Moderator analyses revealed that (a) smoking initiation was more positively correlated with peers' smoking when the interpersonal closeness between adolescents and their peers was higher (vs. lower); and (b) both smoking initiation and continuation were more positively correlated with peers' smoking when samples were from collectivistic (vs. individualistic) cultures. Thus, both individual as well as population level dynamics play a critical role in the strength of peer influence. Accounting for cultural variables may be especially important given effects on both initiation and continuation. Implications for theory, research, and antismoking intervention strategies are discussed. (PsycINFO Database Record

Simulating drinking in social networks to inform alcohol prevention and treatment efforts

Adolescent drinking influences, and is influenced by, peer alcohol use. Several efficacious adolescent alcohol interventions include elements aimed at reducing susceptibility to peer influence. Modeling these interventions within dynamically changing social networks may improve our understanding of how such interventions work and for whom they work best. We used stochastic actor-based models to simulate longitudinal drinking and friendship formation within social networks using parameters obtained from a meta-analysis of real-world 10th grade adolescent social networks. Levels of social influence (i.e., friends affecting changes in one's drinking) and social selection (i.e., drinking affecting changes in one's friendships) were manipulated at several levels, which directly impacted the degree of clustering in friendships based on similarity in drinking behavior. Midway through each simulation, one randomly selected heavy-drinking actor from each network received an "intervention" that either (a) reduced their susceptibility to social influence, (b) reduced their susceptibility to social selection, (c) eliminated a friendship with a heavy drinker, or (d) initiated a friendship with a nondrinker. Only the intervention that eliminated targeted actors' susceptibility to social influence consistently reduced that actor's drinking. Moreover, this was only effective in networks with social influence and social selection that were at higher levels than what was found in the real-world reference study. Social influence and social selection are dynamic processes that can lead to complex systems that may moderate the effectiveness of network-based interventions. Interventions that reduce susceptibility to social influence may be most effective among adolescents with high susceptibility to social influence and heavier-drinking friends. (PsycINFO Database Record

Peer Influence, Peer Selection and Adolescent Alcohol Use: a Simulation Study Using a Dynamic Network Model of Friendship Ties and Alcohol Use

While studies suggest that peer influence can in some cases encourage adolescent substance use, recent work demonstrates that peer influence may be on average protective for cigarette smoking, raising questions about whether this effect occurs for other substance use behaviors. Herein, we focus on adolescent drinking, which may follow different social dynamics than smoking. We use a data-calibrated Stochastic Actor-Based (SAB) Model of adolescent friendship tie choice and drinking behavior to explore the impact of manipulating the size of peer influence and selection effects on drinking in two school-based networks. We first fit a SAB Model to data on friendship tie choice and adolescent drinking behavior within two large schools (n = 2178 and n = 976) over three time points using data from the National Longitudinal Study of Adolescent to Adult Health. We then alter the size of the peer influence and selection parameters with all other effects fixed at their estimated values and simulate the social systems forward 1000 times under varying conditions. Whereas peer selection appears to contribute to drinking behavior similarity among adolescents, there is no evidence that it leads to higher levels of drinking at the school level. A stronger peer influence effect lowers the overall level of drinking in both schools. There are many similarities in the patterning of findings between this study of drinking and previous work on smoking, suggesting that peer influence and selection may function similarly with respect to these substances.

Adolescents’ Perceptions Regarding Effective Tobacco Use Prevention Strategies for their Younger Counterparts: A Qualitative Study in Malaysia

Purpose:The present qualitative study explored adolescents’ perceptions regarding effective strategies to prevent adolescents from using tobacco products (TP). Apart from the commercial TPs, there has been emerging use of alternatives such as vapes, e-cigarettes and shisha. This unfortunate phenomenon continues despite the currently available preventive strategies. Thus, understanding of the perceptions of the current generation would be valuable to provide new insights. Methods: Purposive sampling was utilized to recruit 40 adolescents between the age of 15 and 16 years old attending public daily secondary schools. Eight focus group discussions were conducted among the TP users, ex-users and non-users. Data were analyzed using a thematic content analysis procedure with NVivo. Results: Among barriers with the currently available strategies were having teachers who smoke tobacco, addiction to nicotine and self-perceptions of being healthy. The content of any program should include knowledge on negative outcomes of using tobacco products and awareness of the legislation together with ways to overcome peer and family influence including improving self-efficacy and refusal skills. Strategies were suggested to be delivered using information technology which provides interactive learning and visual effects. Conclusions: Adolescents agreed that the content and delivery of tobacco use prevention strategies need to be revised to suit the current generation to ensure sustainability.

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions.

Optimisation of complex health interventions prior to a randomised controlled trial: a scoping review of strategies used

BACKGROUND

Many complex intervention trials fail to show an intervention effect. Although this may be due to genuine ineffectiveness, it may also be the result of sub-optimal intervention design, implementation failure or a combination of these. Given current financial constraints and the pressure to reduce waste and increase value in health services research, pre-trial strategies are needed to reduce the likelihood of design or implementation failure and to maximise the intervention's potential for effectiveness. In this scoping review, we aimed to identify and synthesise the available evidence relating to the strategies and methods used to 'optimise' complex interventions at the pre-trial stage.

METHODS

We searched MEDLINE, CINAHL, AMED, PsycINFO and ProQuest Nursing & Allied Health Source for papers published between January 2000 and March 2015. We included intervention development and optimisation studies that explored potential intervention weaknesses and limitations before moving to a definitive randomised controlled trial (RCT). Two reviewers independently applied selection criteria and systematically extracted information relating to the following: study characteristics; intervention under development; framework used to guide the development process; areas of focus of the optimisation process, methods used and outcomes of the optimisation process. Data were tabulated and summarised in a narrative format.

RESULTS

We screened 3968 titles and 231 abstracts for eligibility. Eighty-nine full-text papers were retrieved; 27 studies met our selection criteria. Optimisation strategies were used for a range of reasons: to explore the feasibility and acceptability of the intervention to patients and healthcare professionals; to estimate the effectiveness and cost-effectiveness of different combinations of intervention components; and to identify potential barriers to implementation. Methods varied widely across studies, from interviews and focus groups to economic modelling and probability analysis.

CONCLUSIONS

The review identifies a range of optimisation strategies currently used. Although a preliminary classification of these strategies can be proposed, a series of questions remain as to which methods to use for different interventions and how to determine when the intervention is ready or 'optimised enough' to be tested in a RCT. Future research should explore potential answers to the questions raised, to guide researchers in the development and evaluation of more effective interventions.

How Initial Prevalence Moderates Network-based Smoking Change: Estimating Contextual Effects with Stochastic Actor-based Models

We use an empirically grounded simulation model to examine how initial smoking prevalence moderates the effectiveness of potential interventions designed to change adolescent smoking behavior. Our model investigates the differences that result when manipulating peer influence and smoker popularity as intervention levers. We demonstrate how a simulation-based approach allows us to estimate outcomes that arise (1) when intervention effects could plausibly alter peer influence and/or smoker popularity effects and (2) across a sample of schools that match the range of initial conditions of smoking prevalence in U.S. schools. We show how these different initial conditions combined with the exact same intervention effects can produce substantially different outcomes-for example, effects that produce smoking declines in some settings can actually increase smoking in others. We explore the form and magnitude of these differences. Our model also provides a template to evaluate the potential effects of alternative intervention scenarios.

Systems science and systems thinking for public health: a systematic review of the field

OBJECTIVES

This paper reports on findings from a systematic review designed to investigate the state of systems science research in public health. The objectives were to: (1) explore how systems methodologies are being applied within public health and (2) identify fruitful areas of activity.

DESIGN

A systematic review was conducted from existing literature that draws on or uses systems science (in its various forms) and relates to key public health areas of action and concern, including tobacco, alcohol, obesity and the social determinants of health.

DATA ANALYSIS

117 articles were included in the review. An inductive qualitative content analysis was used for data extraction. The following were systematically extracted from the articles: approach, methodology, transparency, strengths and weaknesses. These were then organised according to theme (ie, commonalities between studies within each category), in order to provide an overview of the state of the field as a whole. The assessment of data quality was intrinsic to the goals of the review itself, and therefore, was carried out as part of the analysis.

RESULTS

4 categories of research were identified from the review, ranging from editorial and commentary pieces to complex system dynamic modelling. Our analysis of each of these categories of research highlighted areas of potential for systems science to strengthen public health efforts, while also revealing a number of limitations in the dynamic systems modelling being carried out in public health.

CONCLUSIONS

There is a great deal of interest in how the application of systems concepts and approach might aid public health. Our analysis suggests that soft systems modelling techniques are likely to be the most useful addition to public health, and align well with current debate around knowledge transfer and policy. However, the full range of systems methodologies is yet to be engaged with by public health researchers.

Simulating Dynamic Network Models and Adolescent Smoking: The Impact of Varying Peer Influence and Peer Selection

We used a stochastic actor-based approach to examine the effect of peer influence and peer selection--the propensity to choose friends who are similar--on smoking among adolescents. Data were collected from 1994 to 1996 from 2 schools involved in the National Longitudinal Study of Adolescent to Adult Health, with respectively 2178 and 976 students, and different levels of smoking. Our experimental manipulations of the peer influence and selection parameters in a simulation strategy indicated that stronger peer influence decreased school-level smoking. In contrast to the assumption that a smoker may induce a nonsmoker to begin smoking, adherence to antismoking norms may result in an adolescent nonsmoker inducing a smoker to stop smoking and reduce school-level smoking.

Social Capital and Oral Health Among Adults 50 Years and Older: Results From the English Longitudinal Study of Ageing

OBJECTIVES

This study examines the differential associations of structural and functional social capital with objective and subjective measures of oral health, and the interactions between social capital and other sociodemographic and health factors.

METHODS

Secondary analysis of data on 8552 adults 50 years and older from the third wave (2006-2007) of the English Longitudinal Study of Ageing was conducted. Oral health outcomes were self-rated oral health, edentulousness (having no natural teeth), and Oral Impacts on Daily Performances. Structural social capital was measured by membership of social organizations and volunteering. Functional social capital was measured by the number of close ties and perceived emotional social support. Logistic regression models were sequentially adjusted for demographic, socioeconomic, health-related factors, and smoking status.

RESULTS

Structural social capital was primarily associated with edentulousness. Not being a member of any organization was associated with higher odds of being edentate (odds ratio [OR] = 1.77, 95% confidence interval [CI] = 1.43-2.16). Functional social capital was associated with self-rated oral health and oral impacts. Low social support was associated with poor self-rated oral health (OR = 1.41, 95% CI = 1.16-1.72) and Oral Impacts on Daily Performances (OR = 1.69, 95% CI = 1.27-2.24).

CONCLUSIONS

The association of structural social capital with edentulousness may reflect health selection effects. The availability of a supportive social network seems to be the aspect of social capital most strongly associated with oral health.

The Challenge of Cardiovascular Diseases and Diabetes to Public Health: A Study Based on Qualitative Systemic Approach

The most common modeling approaches to understanding incidence, prevalence and control of chronic diseases in populations, such as statistical regression models, are limited when it comes to dealing with the complexity of those problems. Those complex adaptive systems have characteristics such as emerging properties, self-organization and feedbacks, which structure the system stability and resistance to changes. Recently, system science approaches have been proposed to deal with the range, complexity, and multifactor nature of those public health problems. In this paper we applied a multilevel systemic approach to create an integrated, coherent, and increasingly precise conceptual framework, capable of aggregating different partial or specialized studies, based on the challenges of the Longitudinal Study of Adult Health - ELSA-Brasil. The failure to control blood pressure found in several of the study's subjects was discussed, based on the proposed model, analyzing different loops, time lags, and feedback that influence this outcome in a population with high educational level, with reasonably good health services access. We were able to identify the internal circularities and cycles that generate the system's resistance to change. We believe that this study can contribute to propose some new possibilities of the research agenda and to the discussion of integrated actions in the field of public health.

Research Note: The consequences of different methods for handling missing network data in Stochastic Actor Based Models

Although stochastic actor based models (e.g., as implemented in the SIENA software program) are growing in popularity as a technique for estimating longitudinal network data, a relatively understudied issue is the consequence of missing network data for longitudinal analysis. We explore this issue in our research note by utilizing data from four schools in an existing dataset (the AddHealth dataset) over three time points, assessing the substantive consequences of using four different strategies for addressing missing network data. The results indicate that whereas some measures in such models are estimated relatively robustly regardless of the strategy chosen for addressing missing network data, some of the substantive conclusions will differ based on the missing data strategy chosen. These results have important implications for this burgeoning applied research area, implying that researchers should more carefully consider how they address missing data when estimating such models.