Integrating social networks and human social motives to achieve social influence at scale

Heterogeneous peer effects of college roommates on academic performance

Understanding how student peers influence learning outcomes is crucial for effective education management in complex social systems. The complexities of peer selection and evolving peer relationships, however, pose challenges for identifying peer effects using static observational data. Here we use both null-model and regression approaches to examine peer effects using longitudinal data from 5,272 undergraduates, where roommate assignments are plausibly random upon enrollment and roommate relationships persist until graduation. Specifically, we construct a roommate null model by randomly shuffling students among dorm rooms and introduce an assimilation metric to quantify similarities in roommate academic performance. We find significantly larger assimilation in actual data than in the roommate null model, suggesting roommate peer effects, whereby roommates have more similar performance than expected by chance alone. Moreover, assimilation exhibits an overall increasing trend over time, suggesting that peer effects become stronger the longer roommates live together. Our regression analysis further reveals the moderating role of peer heterogeneity. In particular, when roommates perform similarly, the positive relationship between a student's future performance and their roommates' average prior performance is more pronounced, and their ordinal rank in the dorm room has an independent effect. Our findings contribute to understanding the role of college roommates in influencing student academic performance.

Trust and trustworthy artificial intelligence: A research agenda for AI in the environmental sciences

Demands to manage the risks of artificial intelligence (AI) are growing. These demands and the government standards arising from them both call for trustworthy AI. In response, we adopt a convergent approach to review, evaluate, and synthesize research on the trust and trustworthiness of AI in the environmental sciences and propose a research agenda. Evidential and conceptual histories of research on trust and trustworthiness reveal persisting ambiguities and measurement shortcomings related to inconsistent attention to the contextual and social dependencies and dynamics of trust. Potentially underappreciated in the development of trustworthy AI for environmental sciences is the importance of engaging AI users and other stakeholders, which human-AI teaming perspectives on AI development similarly underscore. Co-development strategies may also help reconcile efforts to develop performance-based trustworthiness standards with dynamic and contextual notions of trust. We illustrate the importance of these themes with applied examples and show how insights from research on trust and the communication of risk and uncertainty can help advance the understanding of trust and trustworthiness of AI in the environmental sciences.

Effect of social support on illness perception in patients with atrial fibrillation during "Blanking Period": Mediating role of sense of mastery

AIM

To explore whether sense of mastery can mediate the relationship between social support and illness perception in patients with atrial fibrillation (AF) who were at the "Blanking Period."

DESIGN

A cross-sectional design.

METHODS

405 patients with AF who were at the "Blanking Period" in the Affiliated Hospital of Qingdao University were recruited; they completed a set of questionnaires, including the Perceived Social Support Scale, the Personal Mastery Scale and the Brief Illness Perception Questionnaire.

RESULTS

Social support and sense of mastery were both adversely connected to illness perception. The indirect effect of social support on illness perception through sense of mastery was negative, accounting for 86.04% of the total effect.

CONCLUSION

During the "Blanking Period," better social support and sense of mastery contribute to a positive illness perception of AF patients. Social support also can influence patients' illness perception indirectly via the mediator of sense of mastery.

Effects of social networks on interventions to change conservation behavior

Social networks are critical to the success of behavioral interventions in conservation because network processes such as information flows and social influence can enable behavior change to spread beyond a targeted group. We investigated these mechanisms in the context of a social marketing campaign to promote a wildlife poisoning hotline in Cambodia. With questionnaire surveys we measured a social network and knowledge and constructs from the theory of planned behavior at 3 points over 6 months. The intervention initially targeted ∼11% (of 365) of the village, but after 6 months ∼40% of the population was knowledgeable about the campaign. The likelihood of being knowledgeable nearly doubled with each additional knowledgeable household member. In the short term, there was also a modest, but widespread improvement in proconservation behavioral intentions, but this did not persist after 6 months. Estimates from stochastic actor-oriented models suggested that the influences of social peers, rather than knowledge, were driving changes in intention and contributed to the failure to change behavioral intention in the long term, despite lasting changes in attitudes and perceived norms. Our results point to the importance of accounting for the interaction between networks and behavior when designing conservation interventions.

Evidence-based recommendations for communicating the impacts of climate change on health

Climate change poses a multifaceted, complex, and existential threat to human health and well-being, but efforts to communicate these threats to the public lag behind what we know how to do in communication research. Effective communication about climate change's health risks can improve a wide variety of individual and population health-related outcomes by: (1) helping people better make the connection between climate change and health risks and (2) empowering them to act on that newfound knowledge and understanding. The aim of this manuscript is to highlight communication methods that have received empirical support for improving knowledge uptake and/or driving higher-quality decision making and healthier behaviors and to recommend how to apply them at the intersection of climate change and health. This expert consensus about effective communication methods can be used by healthcare professionals, decision makers, governments, the general public, and other stakeholders including sectors outside of health. In particular, we argue for the use of 11 theory-based, evidence-supported communication strategies and practices. These methods range from leveraging social networks to making careful choices about the use of language, narratives, emotions, visual images, and statistics. Message testing with appropriate groups is also key. When implemented properly, these approaches are likely to improve the outcomes of climate change and health communication efforts.

‘Exploring the Influence of Social Media Influencers on Intention to Attend Cervical Screening in the UK: Utilising the Theory of Planned Behaviour’

Objectives

Cervical cancer is 99.8% preventable when detected early; however, uptake of screening in the United Kingdom is at a 20-year low. Recently, a number of social media influencers have video logged about their experiences of cervical screening through narrative communication with their audience. Here we aimed to explore if accessing cervical screening information from a social media influencer can impact the theory of planned behaviour variables and predict intention to attend cervical screening appointments.

Design

Utilising a cross-sectional design a volunteer sample of 102 UK women (mean age = 28; SD = 3.10; range = 25–35) took part in an online questionnaire study.

Results

Hierarchical regression modelling revealed attitude as a significant predictor of intention to attend a cervical screening appointment and that social media influencers affect attitudes of their audience, indirectly influencing intention to attend.

Conclusion

Health messages communicated by social media influencers are effective in promoting positive attitudes but not directly influence intention to attend towards cervical screening. Further research should explore influencer impact on attitudes towards this health behaviour with the ultimate aim of increasing attendance and consequently saving lives.

Determinants of the Land Registration Information System Operational Success: Empirical Evidence from Ethiopia

Ethiopia has embarked on one of the largest digitalization programs for rural land registration in Africa. The program is called the national rural land administration information system (NRLAIS). Over the past couple of years, NRLAIS was rolled-out and made operational in over 180 woredas (districts). There is, however, limited empirical evidence on whether and to what extent NRLAIS has been successful. This study explores the factors that influence the acceptance and actual use of NRLAIS to gauge its operational success in Ethiopia. Data were collected both from primary and secondary sources using surveys, key informant interviews, and a literature review. Survey data were collected from 201 staff of 50 woreda land administration offices in three regional states (Amhara, Oromia, and SNNP) and analyzed using a structural equation model. The results revealed that system quality, information quality, service quality, and perceived usefulness of NRLAIS have positively and significantly influenced the acceptance and actual use of the system. However, perceived ease of use has an insignificant influence. The predictive relevance of the research model is significant and indicates substantial operational success of NRLAIS. The quick acceptance and use of NRLAIS will likely improve service delivery, promote data integration, and strengthen informed decision-making. The study recommends strengthening behavioral changes of the land administration experts through two enhanced service quality measures—technical and operational capacity to a robust and sustainable digitalization. Policymakers could leverage operational success to upgrade the NRLAIS into a unified national land registration information system that bridges the urban–rural land governance divide.

Using Trellis software to enhance high-quality large-scale network data collection in the field

Trellis is a mobile platform created by the Human Nature Lab at the Yale Institute for Network Science to collect high-quality, location-aware, off-line/online, multi-lingual, multi-relational social network and behavior data in hard-to-reach communities. Respondents use Trellis to identify their social contacts by name and photograph, a procedure especially useful in low-literacy populations or in contexts where names may be similar or confusing. We use social network data collected from 1,969 adult respondents in two villages in Kenya to demonstrate Trellis' ability to provide unprecedented metadata to monitor and report on the data collection process including artifactual variability based on surveyors, time of day, or location.

Fundamental insights on when social network data are most critical for conservation planning

As declines in biodiversity accelerate, there is an urgent imperative to ensure that every dollar spent on conservation counts toward species protection. Systematic conservation planning is a widely used approach to achieve this, but there is growing concern that it must better integrate the human social dimensions of conservation to be effective. Yet, fundamental insights about when social data are most critical to inform conservation planning decisions are lacking. To address this problem, we derived novel principles to guide strategic investment in social network information for systematic conservation planning. We considered the common conservation problem of identifying which social actors, in a social network, to engage with to incentivize conservation behavior that maximizes the number of species protected. We used simulations of social networks and species distributed across network nodes to identify the optimal state-dependent strategies and the value of social network information. We did this for a range of motif network structures and species distributions and applied the approach to a small-scale fishery in Kenya. The value of social network information depended strongly on both the distribution of species and social network structure. When species distributions were highly nested (i.e., when species-poor sites are subsets of species-rich sites), the value of social network information was almost always low. This suggests that information on how species are distributed across a network is critical for determining whether to invest in collecting social network data. In contrast, the value of social network information was greatest when social networks were highly centralized. Results for the small-scale fishery were consistent with the simulations. Our results suggest that strategic collection of social network data should be prioritized when species distributions are un-nested and when social networks are likely to be centralized.

The Radiation-Transmission-Reception (RTR) model of propagation: Implications for the effectiveness of network interventions

Propagating phenomena in networks have received significant amount of attention within various domains, ranging from contagion in epidemiology, to diffusion of innovations and social influence on behavior and communication. Often these studies attempt to model propagation processes in networks to create interventions that steer propagation dynamics towards desired or away from undesired outcomes. Traditionally, studies have used relatively simple models of the propagation mechanism. In most propagation models this mechanism is described as a monolithic process and a single parameter for the infection rate. Such a description of the propagation mechanism is a severe simplification of mechanisms described in various theoretical exchange theories and phenomena found in real world settings, and largely fails to capture the nuances present in such descriptions. Recent work has suggested that such a simplification may not be sufficient to explain observed propagation dynamics, as nuances of the mechanism of propagation can have a severe impact on its dynamics. This suggests a better understanding of the role of the propagation mechanism is desired. In this paper we put forward a novel framework and model for propagation, the RTR framework. This framework, based on communication theory, decomposes the propagation mechanism into three sub-processes; Radiation, Transmission and Reception (RTR). We show that the RTR framework provides a more detailed way for specifying and conceptually thinking about the process of propagation, aligns better with existing real world interventions, and allows for gaining new insights into effective intervention strategies. By decomposing the propagation mechanism, we show that the specifications of this mechanism can have significant impact on the effectiveness of network interventions. We show that for the same composite single-parameter specification, different decompositions in Radiation, Transmission and Reception yield very different effectiveness estimates for the same network intervention, from 30% less effective to 70% more effective. We find that the appropriate choice for intervention depends strongly on the decomposition of the propagation mechanism. Our findings highlight that a correct decomposition of the mechanism is a prerequisite for developing effective network intervention strategies, and that the use of monolithic models, which oversimplify the mechanism, can be problematic of supporting decisions related to network interventions. In contrast, by allowing more detailed specification of the propagation mechanism and enabling this mechanism to be linked to existing interventions, the RTR framework provides a valuable tool for those designing interventions and implementing interventions strategies.

"They Destroy the Reproductive System": Exploring the Belief that Modern Contraceptive Use Causes Infertility

A common reason for nonuse of modern contraceptives is concern about side effects and health complications. This article provides a detailed characterization of the belief that modern contraceptives cause infertility, and an examination of how this belief arises and spreads, and why it is so salient. We conducted focus group discussions and key informant interviews in three rural communities along Kenya's eastern coast, and identified the following themes: (1) the belief that using modern contraception at a young age or before childbirth can make women infertile is widespread; (2) according to this belief, the most commonly used methods in the community were linked to infertility; (3) when women observe other women who cannot get pregnant after using modern contraceptives, they attribute the infertility to the use of contraception; (4) within the communities, the primary goal of marriage is childbirth and thus community approval is rigidly tied to childbearing; and, therefore (5) the social consequences of infertility are devastating. These findings may help inform the design of programs to address this belief and reduce unmet need.

Sustainable reduction of antibiotic-induced antimicrobial resistance (ARena) in German ambulatory care: study protocol of a cluster randomised trial

Background

Despite many initiatives to enhance the rational use of antibiotics, there remains substantial room for improvement. The overall aim of this study is to optimise the appropriate use of antibiotics in German ambulatory care in patients with acute non-complicated infections (respiratory tract infections, such as bronchitis, sinusitis, tonsillitis and otitis media), community-acquired pneumonia and non-complicated cystitis, in order to counter the advancing antimicrobial resistance development.

Methods

A three-armed cluster randomised trial will be conducted in 14 practice networks in two German federal states (Bavaria and North Rhine-Westphalia) and an added cohort that reflects standard care. The trial is accompanied by a process evaluation.

Each arm will receive a different set of implementation strategies. Arm A receives a standard set, comprising of e-learning on communication with patients and quality circles with data-based feedback for physicians, information campaigns for the public, patient information material and performance-based additional reimbursement. Arm B receives this standard set plus e-learning on communication with patients and quality circles with data-based feedback tailored for non-physician health professionals of the practice team and information material for tablet computers (culture sensitive). Arm C receives the standard set as well as a computerised decision support system and quality circles in local multidisciplinary groups.

The study aims to recruit 193 practices which will provide data on 23,934 patients each year (47,867 patients in total).

The outcome evaluation is based on claims data and refers to established indicators of the European Surveillance of Antimicrobial Consumption Network (ESAC-Net). Primary and secondary outcomes relate to prescribing of antibiotics, which will be analysed in multivariate regression models. The process evaluation is based on interviews with surveys among physicians, non-physician health professionals of the practice team and stakeholders. A patient survey is conducted in one of the study arms. Interview data will be qualitatively analysed using thematic framework analysis. Survey data of physicians, non-physician health professionals of the practice team and patients will use descriptive and exploratory statistics for analysis.

Discussion

The ARena trial will examine the effectiveness of large scale implementation strategies and explore their delivery in routine practice.

Trial registration

ISRCTN, ISRCTN58150046. Registered 24 August 2017.

Electronic supplementary material

The online version of this article (10.1186/s13012-018-0722-0) contains supplementary material, which is available to authorized users.

Social Mobilization

This article reviews research from several behavioral disciplines to derive strategies for prompting people to perform behaviors that are individually costly and provide negligible individual or social benefits but are meaningful when performed by a large number of individuals. Whereas the term social influence encompasses all the ways in which people influence other people, social mobilization refers specifically to principles that can be used to influence a large number of individuals to participate in such activities. The motivational force of social mobilization is amplified by the fact that others benefit from the encouraged behaviors, and its overall impact is enhanced by the fact that people are embedded within social networks. This article may be useful to those interested in the provision of public goods, collective action, and prosocial behavior, and we give special attention to field experiments on election participation, environmentally sustainable behaviors, and charitable giving.

Nonrandomized Trial of Feasibility and Acceptability of Strategies for Promotion of Soapy Water as a Handwashing Agent in Rural Bangladesh

We conducted a nonrandomized trial of strategies to promote soapy water for handwashing in rural Bangladesh and measured uptake. We enrolled households with children < 3 years for three progressively intensive study arms: promotion of soapy water (N = 120), soapy water promotion plus handwashing stations (N = 103), and soapy water promotion, stations plus detergent refills (N = 90); we also enrolled control households (N = 72). Our handwashing stations included tap-fitted buckets and soapy water bottles. Community promoters visited households and held community meetings to demonstrate soapy water preparation and promote handwashing at key times. Field workers measured uptake 4 months later. In-depth interviews and focus group discussions assessed factors associated with uptake. More households had soapy water at the handwashing place in progressively intensive arms: 18% (promotion), 60% (promotion plus station), and 71% (promotion, station with refills). Compared with the promotion-only arm, more households that received stations had soapy water at the primary handwashing station (44%, P ≤ 0.001; 71%, P < 0.001 with station plus detergent refill). Qualitative findings highlighted several dimensions that affected use: contextual (shared courtyard), psychosocial (perceived value), and technology dimensions (ease of use, convenience). Soapy water may increase habitual handwashing by addressing barriers of cost and availability of handwashing agents near water sources. Further research should inform optimal strategies to scale-up soapy water as a handwashing agent to study health impact.

Diffusion Dynamics of Energy Saving Practices in Large Heterogeneous Online Networks

Online social networks are today's fastest growing communications channel and a popular source of information for many, so understanding their contribution to building awareness and shaping public perceptions of climate change is of utmost importance. Today's online social networks are composed of complex combinations of entities and communication channels and it is not clear which communicators are the most influential, what the patterns of communication flow are, or even whether the widely accepted two-step flow of communication model applies in this new arena. This study examines the diffusion of energy saving practices in a large online social network across organizations, opinion leaders, and the public by tracking 108,771 communications on energy saving practices among 1,084 communicators, then analyzing the flow of information and influence over a 28 day period. Our findings suggest that diffusion networks of messages advocating energy saving practices are predominantly led by the activities of dedicated organizations but their attempts do not result in substantial public awareness, as most of these communications are effectively trapped in organizational loops in which messages are simply shared between organizations. Despite their comparably significant influential values, opinion leaders played a weak role in diffusing energy saving practices to a wider audience. Thus, the two-step flow of communication model does not appear to describe the sharing of energy conservation practices in large online heterogeneous networks. These results shed new light on the underlying mechanisms driving the diffusion of important societal issues such as energy efficiency, particularly in the context of large online social media outlets.

Childhood peer network characteristics: genetic influences and links with early mental health trajectories

BACKGROUND

Peer relationships are important for children's mental health, yet little is known of their etiological underpinnings. Here, we explore the genetic influences on childhood peer network characteristics in three different networks defined by rejection, acceptance, and prosocial behavior. We further examine the impact of early externalizing and internalizing trajectories on these same peer network characteristics.

METHODS

Participants were 1,288 children from the Dutch 'Generation R' birth cohort. At age 7, we mapped out children's classroom peer networks for peer rejection, acceptance, and prosocial behavior using mutual peer nominations. In each network, genetic influences were estimated for children's degree centrality, closeness centrality and link reciprocity from DNA using Genome-wide Complex Trait Analysis. Preschool externalizing and internalizing trajectories were computed using parental ratings at ages 1.5, 3, and 5 years.

RESULTS

Of the three network properties examined, closeness centrality emerged as significantly heritable across all networks. Preschool externalizing problems predicted unfavorable positions within peer rejection networks and having fewer mutual friendships. In contrast, children with preschool-internalizing problems were not actively rejected by their peers, but were less well-connected within their social support network.

CONCLUSIONS

Our finding of significant heritability for closeness centrality should be taken as preliminary evidence that requires replication. Nevertheless, it can orient us to the role of genes in shaping a child's position within peer networks. Additionally, social network perspectives offer rich insights into how early life mental health trajectories impact a child's later functioning within peer networks.

Impact of Economic Constraints on Public Health Delivery Systems Structures

OBJECTIVES

We estimated the effect of economic constraints on public health delivery systems (PHDS) density and centrality during 3 time periods, 1998, 2006, and 2012.

METHODS

We obtained data from the 1998, 2006, and 2012 National Longitudinal Study of Public Health Agencies; the 1993, 1997, 2005, and 2010 National Association for County and City Health Officials Profile Study; and the 1997, 2008, and 2011 Area Resource Files. We used multivariate regression models for panel data to estimate the impact of economic constraints on PHDS density and centrality.

RESULTS

Findings indicate that economic constraints did not have a significant impact on PHDS density and centrality over time but population is a significant predictor of PHDS density, and the presence of a board of health (BOH) is a significant predictor of PHDS density and centrality. Specifically, a 1% increase in population results in a significant 1.71% increase in PHDS density. The presence of a BOH is associated with a 10.2% increase in PHDS centrality, after controlling for other factors.

CONCLUSIONS

These findings suggest that other noneconomic factors influence PHDS density centrality.