Application of an egocentric social network approach to examine changes in social connections following treatment for anxiety and depression: A novel measurement tool for clinical trials research?

The epidemic of loneliness and social isolation has been recognized as a public health crisis warranting the same prioritization as other public health issues today, such as obesity, substance use disorders, and tobacco use. Social disconnection is particularly prevalent and disabling among individuals with anxiety and depression, yet it is inadequately evaluated and addressed in most clinical psychology treatment research. Studies generally employ global measures of perceived connectedness, loneliness, or relationship satisfaction, limiting understanding about elements of one's social network that may change with treatment. This study examined changes in the degree (number of people nominated) and quality of one's social network from pre-to post-treatment using an egocentric social network approach in 59 adults (mean age = 30.8 years, range = 18 to 54) with clinically elevated anxiety or depression who were randomized to a cognitive and behavioral positive valence treatment versus waitlist. Participants (egos) named people in their lives (alters) with whom they discussed important issues or spent free time. For each alter, participants rated how close they felt, how close they thought the alter felt to them, and how frequently they communicated. Linear regressions, which included treatment group as a predictor, revealed no group differences in changes in network degree, perceived alter feelings of closeness, or communication frequency, despite prior findings from this sample indicating larger increases in perceived global connectedness in the treatment group. Unexpectedly, the control group reported a greater increase in perceived closeness to alters. Post-hoc analyses revealed this was explained by the treatment group identifying more distal social ties (e.g., extended family, colleagues, roommates) as alters following treatment - an outcome positively associated with global improvements in connectedness. This proof-of-concept study suggests egocentric social network surveys may provide unique information on treatment-related changes in social functioning. Suggestions are provided for adaptations to facilitate application of social network surveys to mental health treatment research.

Amplification of Positivity Treatment for Anxiety and Depression: A Randomized Experimental Therapeutics Trial Targeting Social Reward Sensitivity to Enhance Social Connectedness.

BACKGROUND: Social disconnection is common and causes significant impairment in anxiety and depressive disorders, and it does not respond sufficiently to available treatments. The positive valence system supports social bond formation and maintenance but is often hyporesponsive in people with anxiety or depression. We conducted an experimental therapeutics trial to test the hypothesis that targeting positive valence processes through cognitive and behavioral strategies would enhance responsivity to social rewards, a core mechanism underlying social connectedness. METHODS: Sixty-eight adults who endorsed clinically elevated anxiety and/or depression with social impairment were randomized 1:1:1 to 5 (n = 23) or 10 (n = 22) sessions of amplification of positivity (AMP) treatment or waitlist (n = 23). Pre- to posttreatment change in striatal activity (primary outcome) during social reward anticipation was measured using functional magnetic resonance imaging, and reactivity to a social affiliation task (secondary) and self-reported social connectedness (exploratory) were examined. Primary analyses compared AMP (doses combined) versus waitlist. A second aim was to compare the effects of different doses. RESULTS: AMP engaged the hypothesized treatment target, leading to greater striatal activation during anticipation of social rewards versus waitlist (d = 1.01 [95% CI = 0.42-1.61]; largest striatal volume). AMP yielded larger improvements in positive affect and approach behavior during the affiliation task (but not other outcomes) and social connectedness. Larger striatal and social connectedness increases were observed for 5-session versus 10-session AMP (d range = 0.08-1.03). CONCLUSIONS: Teaching people with anxiety or depression strategies to increase positive thoughts, behaviors, and emotions enhances activity in brain regions that govern social reward processing and promotes social connectedness. Social reward sensitivity may be a transdiagnostic target for remediating social disconnection.

Epidemiology of Mycobacterium bovis infection in free-ranging rhinoceros in Kruger National Park, South Africa.

Mycobacterium bovis infection, which is a prominent cause of bovine tuberculosis, has been confirmed by mycobacterial culture in African rhinoceros species in Kruger National Park (KNP), South Africa. In this population-based study of the epidemiology of M. bovis in 437 African rhinoceros (Diceros bicornis, Ceratotherium simum), we report an estimated prevalence of 15.4% (95% CI: 10.4 to 21.0%), based on results from mycobacterial culture and an antigen-specific interferon gamma release assay from animals sampled between 2016 and 2020. A significant spatial cluster of cases was detected near the southwestern park border, although infection was widely distributed. Multivariable logistic regression models, including demographic and spatiotemporal variables, showed a significant, increasing probability of M. bovis infection in white rhinoceros based on increased numbers of African buffalo (Syncerus caffer) herds in the vicinity of the rhinoceros sampling location. Since African buffaloes are important maintenance hosts for M. bovis in KNP, spillover of infection from these hosts to white rhinoceros sharing the environment is suspected. There was also a significantly higher proportion of M. bovis infection in black rhinoceros in the early years of the study (2016­2018) than in 2019 and 2020, which coincided with periods of intense drought, although other temporal factors could be implicated. Species of rhinoceros, age, and sex were not identified as risk factors for M. bovis infection. These study findings provide a foundation for further epidemiological investigation of M. bovis, a multihost pathogen, in a complex ecosystem that includes susceptible species that are threatened and endangered.

Longitudinal social network analysis of avian mycobacteriosis incidence in a large population of zoo birds.

The goal of this study was to evaluate longitudinal patterns of avian mycobacteriosis spread through a social network. Specifically, we wanted to determine whether the patterns of connectivity over time can predict future infections, and whether this pattern can distinguish between different sources of infection. The study population included 13,409 individuals nested in a larger population of birds that were closely monitored in zoological facilities for over 22 years (1992-2014). A retrospective cohort study design and social network connectivity were used to estimate the association between exposure to an infected bird, and development of mycobacteriosis. Avian mycobacteriosis was diagnosed from histopathology and network connectivity was defined by enclosure histories over discrete time periods. Single-variable and multivariable longitudinal, mixed effects logistic regression models examined whether exposure to infected birds, both directly- and indirectly-connected, was associated with development of mycobacteriosis at the next time step. Our adjusted model showed an increased odds of developing mycobacteriosis (odds ratio = 2.15; 95 % CI: 1.48-3.12; p < 0.001) for birds that were directly exposed (i.e., housed in the same aviary) to another infected bird, compared to those with no exposure. Exposure to a positive, indirectly-connected bird at a previous time step was independently associated with an increased risk of mycobacteriosis (odds ratio = 1.56; 95 % CI: 1.11-2.19). This association persisted in adjusted models even when the indirect contacts were housed in distinctly different aviaries and never had contact with the subject of interest or its environment. Adjusted, risk-stratified models further characterized the type of exposure that increased the risk of avian mycobacteriosis. Birds that were exposed in small aviaries were more likely to develop mycobacteriosis than those exposed in larger aviaries and those with no exposure. The lesion distribution and species of the contact (same species versus different species) were also significant predictors of disease risk. Some findings were sensitive to model variation of time divisions and initiation time. Our study shows avian mycobacteriosis spread through the social network in quantifiable and discernable patterns. We provide empirical evidence that a contagious process drives some of the observed infection, but we also show low transmissibility based on sustained patterns of low incidence over time even when large groups of birds are exposed. Targeted risk mitigation efforts based on the characteristics of the exposure may be effective at reducing risk of avian mycobacteriosis while enhancing population sustainability.

Social network analysis and whole-genome sequencing to evaluate disease transmission in a large, dynamic population: A study of avian mycobacteriosis in zoo birds.

This study combined a social network analysis and whole-genome sequencing (WGS) to test for general patterns of contagious spread of a mycobacterial infection for which pathways of disease acquisition are not well understood. Our population included 275 cases diagnosed with avian mycobacteriosis that were nested in a source population of 16,430 birds at San Diego Zoo Wildlife Alliance facilities from 1992 through mid-2014. Mycobacteria species were determined using conventional methods and whole genome sequencing (WGS). Mycobacterium avium avium (MAA) and Mycobacterium genavense were the most common species of mycobacteria identified and were present in different proportions across bird taxa. A social network for the birds was constructed from the source population to identify directly and indirectly connected cases during time periods relevant to disease transmission. Associations between network connectivity and genetic similarity of mycobacteria (as determined by clusters of genotypes separated by few single nucleotide polymorphisms, or SNPs) were then evaluated in observed and randomly generated network permutations. Findings showed that some genotypes clustered along pathways of bird connectivity, while others were dispersed throughout the network. The proportion of directly connected birds having a similar mycobacterial genotype was 0.36 and significant (p<0.05). This proportion was higher (0.58) and significant for MAA but not for M. genavense. Evaluations of SNP distributions also showed genotypes of MAA were more related in connected birds than expected by chance; however, no significant patterns of genetic relatedness were identified for M. genavense, although data were sparse. Integrating the WGS analysis of mycobacteria with a social network analysis of their host birds revealed significant genetic clustering along pathways of connectivity, namely for MAA. These findings are consistent with a contagious process occurring in some, but not all, case clusters.

Stay-at-home orders associate with subsequent decreases in COVID-19 cases and fatalities in the United States.

Governments issue "stay-at-home" orders to reduce the spread of contagious diseases, but the magnitude of such orders' effectiveness remains uncertain. In the United States these orders were not coordinated at the national level during the coronavirus disease 2019 (COVID-19) pandemic, which creates an opportunity to use spatial and temporal variation to measure the policies' effect. Here, we combine data on the timing of stay-at-home orders with daily confirmed COVID-19 cases and fatalities at the county level during the first seven weeks of the outbreak in the United States. We estimate the association between stay-at-home orders and alterations in COVID-19 cases and fatalities using a difference-in-differences design that accounts for unmeasured local variation in factors like health systems and demographics and for unmeasured temporal variation in factors like national mitigation actions and access to tests. Compared to counties that did not implement stay-at-home orders, the results show that the orders are associated with a 30.2 percent (11.0 to 45.2) average reduction in weekly incident cases after one week, a 40.0 percent (23.4 to 53.0) reduction after two weeks, and a 48.6 percent (31.1 to 61.7) reduction after three weeks. Stay-at-home orders are also associated with a 59.8 percent (18.3 to 80.2) average reduction in weekly fatalities after three weeks. These results suggest that stay-at-home orders might have reduced confirmed cases by 390,000 (170,000 to 680,000) and fatalities by 41,000 (27,000 to 59,000) within the first three weeks in localities that implemented stay-at-home orders.

Political Differences in American Reports of Sexual Harassment and Assault.

Political ideology has been linked to beliefs regarding sexual harassment and assault (SH&A). Using data from the January 2018 Stop Street Sexual Harassment online poll (N = 2,009), this study examined associations of political identity and political ideology with self-reported experiences of being the victim of SH&A. SH&A experiences were coded into four mutually exclusive groups: none, non-physically aggressive harassment, physically aggressive harassment, or sexual assault. Sex-stratified logistic regression models assessed associations of interest, adjusting for participant demographics. Among women, more conservative political ideology was negatively associated with reports of sexual assault, odds ratio (OR) = 0.85, 95% confidence interval (CI) = [0.74, 0.98]. Among males, more conservative political ideology was negatively associated with reports of physically aggressive sexual harassment (OR = 0.85, 95% CI = [0.73, 0.98]), and greater Republican affiliation was negatively associated with reports of sexual assault (OR = 0.82, 95% CI = [0.68, 0.99]). Conservative and Republican women and men are thus less likely to report more severe forms of SH&A, which may explain differences in beliefs on these issues. Research is needed to determine if political differences are due to reporting biases or differential vulnerabilities.

Spatiotemporal network structure among "friends of friends" reveals contagious disease process.

Disease transmission can be identified in a social network from the structural patterns of contact. However, it is difficult to separate contagious processes from those driven by homophily, and multiple pathways of transmission or inexact information on the timing of infection can obscure the detection of true transmission events. Here, we analyze the dynamic social network of a large, and near-complete population of 16,430 zoo birds tracked daily over 22 years to test a novel "friends-of-friends" strategy for detecting contagion in a social network. The results show that cases of avian mycobacteriosis were significantly clustered among pairs of birds that had been in direct contact. However, since these clusters might result due to correlated traits or a shared environment, we also analyzed pairs of birds that had never been in direct contact but were indirectly connected in the network via other birds. The disease was also significantly clustered among these friends of friends and a reverse-time placebo test shows that homophily could not be causing the clustering. These results provide empirical evidence that at least some avian mycobacteriosis infections are transmitted between birds, and provide new methods for detecting contagious processes in large-scale global network structures with indirect contacts, even when transmission pathways, timing of cases, or etiologic agents are unknown.

Using social and behavioural science to support COVID-19 pandemic response.

The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.

Assortative mating at loci under recent natural selection in humans.

Genetic correlation between mates at specific loci can greatly alter the evolutionary trajectory of a species. Genetic assortative mating has been documented in humans, but its existence beyond population stratification (shared ancestry) has been a matter of controversy. Here, we develop a method to measure assortative mating across the genome at 1,044,854 single-nucleotide polymorphisms (SNPs), controlling for population stratification and cohort-specific cryptic relatedness. Using data on 1683 human couples from two data sources, we find evidence for both assortative and disassortative mating at specific, discernible loci throughout the entire genome. Then, using the composite of multiple signals (CMS) score, we also show that the group of SNPs exhibiting the most assortativity has been under stronger recent positive selection. Simulations using realistic inputs confirm that assortative mating might indeed affect changes in allele frequency over time. These results suggest that genetic assortative mating may be speeding up evolution in humans.

The Structure of Negative Social Ties in Rural Village Networks.

Negative (antagonistic) connections have been of longstanding theoretical importance for social structure. In a population of 24,696 adults interacting face to face within 176 isolated villages in western Honduras, we measured all connections that were present, amounting to 105,175 positive and 16,448 negative ties. Here, we show that negative and positive ties exhibit many of the same structural characteristics. We then develop a complete taxonomy of all 138 possible triads of two-type relationships. Consistent with balance theory, we find that antagonists of friends and friends of antagonists tend to be antagonists; but, in an important empirical refutation of balance theory, we find that antagonists of antagonists also tend to be antagonists, not friends. Finally, villages with comparable levels of animosity tend to be geographically proximate. Similar processes, involving social contact, give rise to both positive and negative social ties in rural villages, and negative ties play an important role in social structure.

Weather impacts expressed sentiment.

We conduct the largest ever investigation into the relationship between meteorological conditions and the sentiment of human expressions. To do this, we employ over three and a half billion social media posts from tens of millions of individuals from both Facebook and Twitter between 2009 and 2016. We find that cold temperatures, hot temperatures, precipitation, narrower daily temperature ranges, humidity, and cloud cover are all associated with worsened expressions of sentiment, even when excluding weather-related posts. We compare the magnitude of our estimates with the effect sizes associated with notable historical events occurring within our data.

Weight and weight control behaviors of Latinas and their social ties.

OBJECTIVE: Shared behaviors have been implicated in the clustering of obesity among socially connected people. This study determined how weight and weight control behaviors of participants and their social ties are related and how these factors are associated with weight change in participants. METHOD: Adult Latinas participating in a lifestyle intervention completed an egocentric network measure of weight and weight control behaviors. Participant weight was objectively measured at baseline and 12 months. Multivariable regression models determined the relationship between weight and weight control behaviors of participants and their social ties. RESULTS: Participants and their social ties shared similarities in weight control behaviors and weight change. Participants who reported social ties that had lost weight were more likely to eat small portions and low-fat foods, but those with social ties that had gained weight were more likely to use herbal supplements. Participants who reported more social ties who exercised, drank liquid meal replacements, took herbal supplements, and self-weighed were more likely to lose weight whereas those with fewer social ties that exercised were more likely to gain weight. Weight loss and weight gain by social ties predicted participant weight loss and weight gain, respectively. CONCLUSIONS: Given that weight and weight control behaviors of Latinas reflect that of their social ties, targeting existing social networks for lifestyle interventions may more effectively improve and sustain health-promoting behaviors and outcomes. (PsycINFO Database Record

Familial social structure and socially driven genetic differentiation in Hawaiian short-finned pilot whales.

Social structure can have a significant impact on divergence and evolution within species, especially in the marine environment, which has few environmental boundaries to dispersal. On the other hand, genetic structure can affect social structure in many species, through an individual preference towards associating with relatives. One social species, the short-finned pilot whale (Globicephala macrorhynchus), has been shown to live in stable social groups for periods of at least a decade. Using mitochondrial control sequences from 242 individuals and single nucleotide polymorphisms from 106 individuals, we examine population structure among geographic and social groups of short-finned pilot whales in the Hawaiian Islands, and test for links between social and genetic structure. Our results show that there are at least two geographic populations in the Hawaiian Islands: a Main Hawaiian Islands (MHI) population and a Northwestern Hawaiian Islands/Pelagic population (FST and ΦST p < .001), as well as an eastern MHI community and a western MHI community (FST p = .009). We find genetically driven social structure, or high relatedness among social units and clusters (p < .001), and a positive relationship between relatedness and association between individuals (p < .0001). Further, socially organized clusters are genetically distinct, indicating that social structure drives genetic divergence within the population, likely through restricted mate selection (FST p = .05). This genetic divergence among social groups can make the species less resilient to anthropogenic or ecological disturbance. Conservation of this species therefore depends on understanding links among social structure, genetic structure and ecological variability within the species.

An exploratory comparison of name generator content: Data from rural India.

Since the 1970s sociologists have explored the best means for measuring social networks, although few name generator analyses have used sociocentric data or data from developing countries, partly because sociocentric studies in developing countries have been scant. Here, we analyze 12 different name generators used in a sociocentric network study conducted in 75 villages in rural Karnataka, India. Having unusual sociocentric data from a non-Western context allowed us to extend previous name generator research through the unique analyses of network structural measures, an extensive consideration of homophily, and investigation of status difference between egos and alters. We found that domestic interaction questions generated networks that were highly clustered and highly centralized. Similarity between respondents and their nominated contacts was strongest for gender, caste, and religion. We also found that domestic interaction name generators yielded the most homogeneous ties, while advice questions yielded the most heterogeneous. Participants were generally more likely to nominate those of higher social status, although certain questions, such as who participants talk to uncovered more egalitarian relationships, while other name generators elicited the names of social contacts distinctly higher or lower in status than the respondent. Some questions also seemed to uncover networks that were specific to the cultural context, suggesting that network researchers should balance local relevance with global generalizability when choosing name generators.

Nighttime temperature and human sleep loss in a changing climate.

Human sleep is highly regulated by temperature. Might climate change-through increases in nighttime heat-disrupt sleep in the future? We conduct the inaugural investigation of the relationship between climatic anomalies, reports of insufficient sleep, and projected climate change. Using data from 765,000 U.S. survey respondents from 2002 to 2011, coupled with nighttime temperature data, we show that increases in nighttime temperatures amplify self-reported nights of insufficient sleep. We observe the largest effects during the summer and among both lower-income and elderly respondents. We combine our historical estimates with climate model projections and detail the potential sleep impacts of future climatic changes. Our study represents the largest ever investigation of the relationship between sleep and ambient temperature and provides the first evidence that climate change may disrupt human sleep.

Social influence and political mobilization: Further evidence from a randomized experiment in the 2012 U.S. presidential election.

A large-scale experiment during the 2010 U.S. Congressional Election demonstrated a positive effect of an online get-out-the-vote message on real world voting behavior. Here, we report results from a replication of the experiment conducted during the U.S. Presidential Election in 2012. In spite of the fact that get-out-the-vote messages typically yield smaller effects during high-stakes elections due to saturation of mobilization efforts from many sources, a significant increase in voting was again observed. Voting also increased significantly among the close friends of those who received the message to go to the polls, and the total effect on the friends was likely larger than the direct effect, suggesting that understanding social influence effects is potentially even more important than understanding the direct effects of messaging. These results replicate earlier work and they add to growing evidence that online social networks can be instrumental for spreading offline behaviors.

Exploiting social influence to magnify population-level behaviour change in maternal and child health: study protocol for a randomised controlled trial of network targeting algorithms in rural Honduras.

INTRODUCTION: Despite global progress on many measures of child health, rates of neonatal mortality remain high in the developing world. Evidence suggests that substantial improvements can be achieved with simple, low-cost interventions within family and community settings, particularly those designed to change knowledge and behaviour at the community level. Using social network analysis to identify structurally influential community members and then targeting them for intervention shows promise for the implementation of sustainable community-wide behaviour change. METHODS AND ANALYSIS: We will use a detailed understanding of social network structure and function to identify novel ways of targeting influential individuals to foster cascades of behavioural change at a population level. Our work will involve experimental and observational analyses. We will map face-to-face social networks of 30 000 people in 176 villages in Western Honduras, and then conduct a randomised controlled trial of a friendship-based network-targeting algorithm with a set of well-established care interventions. We will also test whether the proportion of the population targeted affects the degree to which the intervention spreads throughout the network. We will test scalable methods of network targeting that would not, in the future, require the actual mapping of social networks but would still offer the prospect of rapidly identifying influential targets for public health interventions. ETHICS AND DISSEMINATION: The Yale IRB and the Honduran Ministry of Health approved all data collection procedures (Protocol number 1506016012) and all participants will provide informed consent before enrolment. We will publish our findings in peer-reviewed journals as well as engage non-governmental organisations and other actors through venues for exchanging practical methods for behavioural health interventions, such as global health conferences. We will also develop a 'toolkit' for practitioners to use in network-based intervention efforts, including public release of our network mapping software. TRIAL REGISTRATION NUMBER: NCT02694679; Pre-results.

Dueling biological and social contagions.

Numerous models explore how a wide variety of biological and social phenomena spread in social networks. However, these models implicitly assume that the spread of one phenomenon is not affected by the spread of another. Here, we develop a model of "dueling contagions", with a particular illustration of a situation where one is biological (influenza) and the other is social (flu vaccination). We apply the model to unique time series data collected during the 2009 H1N1 epidemic that includes information about vaccination, flu, and face-to-face social networks. The results show that well-connected individuals are more likely to get vaccinated, as are people who are exposed to friends who get vaccinated or are exposed to friends who get the flu. Our dueling contagion model suggests that other epidemiological models may be dramatically underestimating the R0 of contagions. It also suggests that the rate of vaccination contagion may be even more important than the biological contagion in determining the course of the disease. These results suggest that real world and online platforms that make it easier to see when friends have been vaccinated (personalized vaccination campaigns) and when they get the flu (personalized flu warnings) could have a large impact on reducing the severity of epidemics. They also suggest possible benefits from understanding the coevolution of many kinds of dueling contagions.

Face-to-Face and Online Networks: College Students' Experiences in a Weight-Loss Trial.

This study aimed to understand how college students participating in a 2-year randomized controlled trial (Project SMART: Social and Mobile Approach to Reduce Weight; N = 404) engaged their social networks and used social and mobile technologies to try and lose weight. Participants in the present study (n = 20 treatment, n = 18 control) were approached after a measurement visit and administered semi-structured interviews. Interviews were analyzed using principles from grounded theory. Treatment group participants appreciated the timely support provided by the study and the integration of content across multiple technologies. Participants in both groups reported using non-study-designed apps to help them lose weight, and many participants knew one another outside of the study. Individuals talked about weight-loss goals with their friends face to face and felt accountable to follow through with their intentions. Although seeing others' success online motivated many, there was a range of perceived acceptability in talking about personal health-related information on social media. The findings from this qualitative study can inform intervention trials using social and mobile technologies to promote weight loss. For example, weight-loss trials should measure participants' use of direct-to-consumer technologies and interconnectivity so that treatment effects can be isolated and cross-contamination accounted for.