Effects Of Social Interactions Research Articles

A Coordinated Data Analysis of Four Studies Exploring Age Differences in Social Interactions and Loneliness During a Global Pandemic.

Examining loneliness and social isolation during population-wide historical events may shed light on important theoretical questions about age differences, including whether these differences hold across different regions and the timecourse of the unfolding event. We used a systematic, preregistered approach of coordinated data analysis (CDA) of four studies (total N = 1,307; total observations = 18,492) that varied in design (intensive repeated-measures and cross-sectional), region, timing, and timescale during the first year of the COVID-19 pandemic. We harmonized our datasets to a common period within 2020-2021 and created a common set of variables. We used a combination of ordinary least squares regression and multilevel modeling to address the extent to which there was within- and between-person variation in the associations between social isolation and loneliness, and whether these associations varied as a function of age. Within- and between-person effects of social interactions were negatively associated with loneliness in one study; in follow-up sensitivity analyses, these patterns held across early and later pandemic periods. Across all datasets, there was no evidence of age differences in the within-person or between-person associations of social interactions and loneliness. Applying the CDA methodological framework allowed us to detect common and divergent patterns of social interactions and loneliness across samples, ages, regions, periods, and study designs.

Belief in Religion or Participation in Insurance? The Impact of Religious Beliefs on the Decision to Participate in Social Health Insurance in China

Investigating the factors that influence individual decisions to participate in social health insurance is an essential component of constructing a multi-tiered, comprehensive social health insurance system, and religious beliefs may constitute an important potential factor. Utilising data from the China General Social Survey (CGSS), this study has developed a comprehensive explanatory framework encompassing both macro- and micro-level analyses to ascertain the impact of religious beliefs on individual decisions to participate in social health insurance through quantitative methods. The findings indicate that religious beliefs significantly diminish the likelihood of individuals participating in social health insurance, and the influence varies among different types of religions; endogeneity and robustness tests offer robust support for these conclusions. With respect to heterogeneity, the influence of religious beliefs on the decision to participate in social health insurance exhibits differentiation across dimensions such as educational attainment, social trust levels, income levels, and self-rated health statuses. Furthermore, the social interaction effect and the employment opportunity effect are identified as potential mechanisms driving this influence.

Social interactions generate complex selection patterns in virtual worlds.

Understanding the influence of social interactions on individual fitness is key to improving our predictions of phenotypic evolution. However, we often overlook the different components of selection regimes arising from interactions among organisms, including social, correlational, and indirect selection. This is due to the challenging sampling efforts required in natural populations to measure phenotypes expressed during interactions and individual fitness. Furthermore, behaviours are crucial in mediating social interactions, yet few studies have explicitly quantified these selection components on behavioural traits. In this study, we capitalize on an online multiplayer videogame as a source of extensive data recording direct social interactions among prey, where prey collaborate to escape a predator in realistic ecological settings. We estimate natural and social selection and their contribution to total selection on behavioural traits mediating competition, cooperation, and predator-prey interactions. Behaviours of other prey in a group impact an individual's survival, and thus are under social selection. Depending on whether selection pressures on behaviours are synergistic or conflicting, social interactions enhance or mitigate the strength of natural selection, although natural selection remains the main driving force. Indirect selection through correlations among traits also contributed to the total selection. Thus, failing to account for the effects of social interactions and indirect selection would lead to a misestimation of the total selection acting on traits. Dissecting the contribution of each component to the total selection differential allowed us to investigate the causal mechanisms relating behaviour to fitness and quantify the importance of the behaviours of conspecifics as agents of selection. Our study emphasizes that social interactions generate complex selective regimes even in a relatively simple ecological environment.

Gender and racial disparities in altruism in social networks

This paper studies gender and racial disparities in altruism among social network members who are endogenously linked. We specify group (gender or race) specific altruistic interactions models, as well as intra- and inter-group altruistic interactions models, to capture the heterogeneous patterns of altruism associated with the characteristics of two individuals in pairs. We apply the models to the Add Health data to identify altruism and social interaction effects on academic achievement and smoking behaviors among adolescents. The results indicate that females are generally more altruistic than males, and whites appear to be the most altruistic racial group. We also find that blacks exhibit spiteful effects toward other black students who are considered to “act white.”

Racial/ethnic minority females smoke more cigarettes after social interaction with others who smoke

The present study investigated the effects of social interaction with others who smoke on daily cigarette use among diverse females via ecological momentary assessment methods. Ninety-eight premenopausal females (29.6% White, 70.4% racial/ethnic minority) who smoke daily reported their social interactions and cigarette use over 35-days. Greater than usual levels of social interaction with others who smoke was associated with increased cigarette use that day among racial/ethnic minority females. Future smoking cessation interventions targeting racial/ethnic minority females should consider the impact of social environments on smoking behaviors, such as the frequency of peer interactions with others who smoke.

When does antimicrobial resistance increase bacterial fitness? Effects of dosing, social interactions, and frequency dependence on the benefits of AmpC β-lactamases in broth, biofilms, and a gut infection model

When does antimicrobial resistance increase bacterial fitness? Effects of dosing, social interactions, and frequency dependence on the benefits of AmpC <i>β</i>-lactamases in broth, biofilms, and a gut infection model

The oxytocin receptor is essential for the protective effect of pair housing on post-stroke depression in mice

The beneficial effect of social interaction in mitigating the incidence of post-stroke depression (PSD) and ameliorating depressive symptoms has been consistently demonstrated through preclinical and clinical studies. However, the underlying relationship with oxytocin requires further investigation. In light of this, the present study aimed to explore the protective effect of pair housing on the development of PSD and the potential relationship with oxytocin receptors. The PSD model was induced by middle cerebral artery occlusion (MCAO) for 50 min, followed by 4-week isolated housing and restrained stress. Subsequently, each mouse in the pair-housing group (PH) was pair-housed with an isosexual healthy partner. Another group was continuously administrated fluoxetine (10 mg/Kg, i.p, once a day) for 3 weeks. To elucidate the potential role of oxytocin, we subjected pair-housed PSD mice to treatment with an oxytocin receptor (OXTR) antagonist (L368,889) (5 mg/Kg, i.p, once a day) for 3 weeks. At 31 to 32 days after MCAO, anxiety- and depressive-like behaviors were assessed using sucrose consumption, forced swim test, and tail-suspension test. The results showed that pair housing significantly improved post-stroke depression to an extent comparable to that of fluoxetine treatment. Furthermore, pair housing significantly decreased corticosterone in serum, increasing OXT mRNA expression in the hypothalamus. Treatment with L368,889 essentially reversed the effect of pair housing, with no discernible sex differences apart from changes in body weight. Pair housing increased hippocampal serotonin (5-HT), but treatment with L368,889 had no significant impact. Additionally, pair housing effectively reduced the number of reactive astrocytes and increased Nissl's body in the cortex and hippocampal CA3 regions. Correspondingly, treatment with L368,889 significantly reversed the changes in the Nissl's body and reactive astrocytes. Moreover, pair housing downregulated mRNA levels of TNF-α, IL-1β, and IL-6 in the cortex caused by PSD, which was also reversed by treatment with L368,889. In conclusion, pair housing protects against the development of PSD depending on OXT and OXTR in the brain, with no significant divergence based on sex. These findings provide valuable insights into the potential of social interaction and oxytocin as therapeutic targets for PSD. Further research into the underlying mechanisms of these effects may contribute to the development of novel treatments for PSD.

Effect of Social Interaction on Learning Performance of Handicapped Students

Effect of Social Interaction on Learning Performance of Handicapped Students

The Role of Internet and Social Interactions in Advancing Waste Sorting Behaviors in Rural Communities

Addressing the global challenge of sustainable waste management, this research investigates the influence of social dynamics and digital connectivity on rural residents’ willingness to adopt waste classification practices, essential for sustainable environmental management. Through a comprehensive analysis of 5413 rural participants surveyed in the China Labor-force Dynamic Survey (CLDS), this study employs a novel mixed-methods approach. It integrates quantitative analysis with the Manski social interaction framework and a Recursive Bivariate Probit model to explore the intricate interplay between community interactions, internet access, and environmental behaviors. Our methodology stands out for its unique combination of social theory and econometric modeling to address a pressing environmental issue. Results highlight a significant effect of mobile internet use and social interactions within communities on enhancing willingness towards waste classification. Notably, digital connectivity emerges as a key facilitator of environmental engagement, mediating social influences, and fostering a collective approach to waste management. Considering these insights, we propose targeted policy interventions that blend digital strategies with traditional community engagement efforts. Recommendations include crafting digital literacy programs and leveraging social media to bolster community-centric environmental governance. By harnessing the synergistic potential of digital tools and social dynamics, these strategies aim to elevate the effectiveness of waste classification initiatives in rural China, offering a scalable model for environmental sustainability.

Observer Responses to Others' Charitable Donations: Effects of the Donor Social Class-Donation Type Interaction

Observer Responses to Others' Charitable Donations: Effects of the Donor Social Class-Donation Type Interaction

Automated and repeated aerial observations of GPS‐collared animals using UAVs and open‐source electronics

AbstractTelemetry has enabled ecologists to link animal movement trajectories and environmental features at a fine spatiotemporal resolution; however, the effects of social interactions on individual choice within large mobile groups remain largely unknown. Estimating the effect of social interaction in the wild remains challenging because existing long‐term tracking tools such as GPS collars focus on the movements of a single individual and cannot observe the behavior of other individuals within the group. The progression of socially informed movement models requires measuring simultaneous trajectories of many individuals at once, as well as the instantaneous social cues to which individuals may be responding. The availability of low‐flying unmanned aerial vehicles (UAVs) and low‐cost open‐source electronics presents a promising opportunity to collect fine‐scale data on social interactions in order to advance our understanding of collective behavior. Here, we present a tracking system that enables the repeated localization and observation of a collared individual and its near neighbors using nadir video footage collected from a commercial UAV. We make use of open‐source electronics combined with the UAV's in‐built functionality that allows it to follow a stream of GPS locations to create an automated system that can follow a specific individual without user control. We demonstrate the tracking systems' performance by studying the group movements of a herd of Exmoor ponies (Equus ferus caballus), and as a proof of concept, we examine the position of the focal individual (collared animal) in relation to the center of the video frame. We also collect information about the focal individual's nearest neighbors. The automated animal observation tool is effective at consistently keeping the focal individual close to the center of the video frame, offering a new dimension to existing remote telemetry tools. For instance, the repeated observation of the same individual in different physiological states, seasons, and demographic groups potentially opens new avenues in collective movement ecology research. By making our design, software, and firmware freely available, we aim to encourage continuous improvements to collective behavior research and to facilitate replicable approaches across other species and ecosystems.

The Spillover Effects of the Spouse's Retirement on Depression: Evidence From Chinese Middle-Aged and Older Adult Couples.

The present study expands on previous research by examining whether the spouse's retirement affects individual depression both directly, by the changes in individual health investment, and indirectly, through the social interaction effect of the couples' depression. Using the panel data from the 2010-2018 China Family Panel Studies, we investigate the direct and indirect spillover effects of the spouse's retirement on depression among Chinese urban-worker couples (men aged 50-70, women aged 40-60; n = 10,466). To address the potential endogeneity and reflect the social interaction effect of the couples' depression, we combine the Fuzzy Regression Discontinuity method with simultaneous equations. Overall, a spouse's retirement would improve an individual's depression, with the direct spillover dominating compared to the indirect spillover. Gender heterogeneity indicates that husbands' depression is improved by wives' retirement mainly because husbands might receive more healthcare and companionship provided by their retired wives, while wives' depression is aggravated by husbands' retirement because of the decline in household income and the lesser health investment. This difference is more evident when wives retire earlier and both spouses retire in the same year. With the spouse's retirement years increasing, husbands' depression improves and wives' depression declines each year. Moreover, spouses' depression is significantly interactive, and wives' depression is more vulnerable to husbands' depression. The results highlight that the health spillover effects of the spouse's retirement need greater attention in future research and retirement reform.

The beneficial effects of social support and prosocial behavior on immunity and health: A psychoneuroimmunology perspective

The COVID-19 pandemic emphasized the pivotal role of the social environment, prompting a surge in research on its impact on well-being and health. This article aims to examine the link between the social environment, the immune system, and health outcomes, with a particular focus on positive aspects like social support and prosocial behaviors that are under-explored. Different aspects of the social environment are examined: the negative effects of loneliness and adverse social conditions, contrasted with the benefits of social support and prosocial behaviors. While the mechanisms behind negative effects are partially studied, those driving the positive effects remain elusive. Understanding the mechanisms of lack of social connection and their effects will allow us to explore the benefits of social connections and whether they can reverse the adverse outcomes. Potential psychoneuroimmunology mechanisms are proposed, highlighting the promotion of a ‘safe’ state by the vagus nerve, oxytocin circuits, and the additional contribution of the reward pathways. This article reviews the need to bridge knowledge gaps, urging further research to study the causal effects of positive social interactions on immune response and health outcomes to raise clinical awareness and interventions. Such interventions may include integrating lonely individuals with prosocial activities, thereby improving their physical and mental health. There is growing potential to harness the power of social connections for the betterment of individual health and society as a whole.

Supporting social interactions to improve MOOC participants’ learning outcomes: a literature review

IntroductionThe need for more scalable, accessible and affordable education, coupled with technological advancements in information sharing technology and collaborative platforms has led to the growth of MOOCs (massive open online courses). The growth of MOOCs has resulted in learning becoming increasingly distributed, affordable and flexible compared to traditional classroom education, allowing individuals in disadvantaged groups to access high quality educational materials. However, new challenges emerge, most notably with MOOCs’ low completion rates. Among the reasons for a low completion rate, lack of interaction with peers is cited as a major reason, yet, interventions to promote social interaction has received relatively less attention. From a constructivist perspective, social interactions among peers are essential in helping individuals learn. This systematic literature review aimed to understand social interaction interventions in MOOC settings. This includes constructs measured as learning outcomes and how they were measured.MethodsLiterature articles were sourced from multiple databases and filtered for inclusion using the PRISMA process and its four phases. Twenty articles were included in the final review.ResultsResults of the review showed that social interactions fall into three categories: discussion forums, learning groups and one-to-one interactions with peers. Learning outcomes investigated were grouped into four categories: knowledge, social engagement, learning engagement and learner experience.ConclusionAcross the studies, there were clear positive effects of social interaction on learning outcomes. Intervention strategies include sending prompts for individuals to use discussion boards and also grouping learners by homogeneity based on their learning engagement. However, more experimental studies are necessary to bolster the evidence of a causal impact of social interactions. Also, further research should be done to understand potential mediating factors that contribute to the success of implementing social interactive elements in MOOCs.

Twitter (X) use predicts substantial changes in well-being, polarization, sense of belonging, and outrage

In public debate, Twitter (now X) is often said to cause detrimental effects on users and society. Here we address this research question by querying 252 participants from a representative sample of U.S. Twitter users 5 times per day over 7 days (6,218 observations). Results revealed that Twitter use is related to decreases in well-being, and increases in political polarization, outrage, and sense of belonging over the course of the following 30 minutes. Effect sizes were comparable to the effect of social interactions on well-being. These effects remained consistent even when accounting for demographic and personality traits. Different inferred uses of Twitter were linked to different outcomes: passive usage was associated with lower well-being, social usage with a higher sense of belonging, and information-seeking usage with increased outrage and most effects were driven by within-person changes.

When Persuasion Is Too Persuasive: An Empirical Analysis of Product Returns in Livestream e-Commerce

Livestream e-commerce features live social interactions that enable real-time, face-to-text communications among a streamer and many customers. We posit such live social interactions generate persuasion effect that eventually leads to higher product returns. Using data from a leading livestream e-commerce firm, we compare the product returns between live sessions with rerun sessions where the only difference is the presence of live social interactions in live sessions but not in rerun sessions, and develop econometric models to estimate the effect of live social interaction intensity on product returns. We find that product returns are higher for the live sessions than for the rerun sessions, and that the magnitude of the effect increases with live social interaction intensity, confirming the adverse persuasion effect in livestream e-commerce. We also find that the persuasion effect of live social interactions on product returns is stronger when the streamer has more experience in hosting livestream sessions and the product price is lower. We estimate that one standard deviation increase in live social interaction intensity can increase the product return rates by as much as 11.68 percentage points in terms of absolute product return rates, which is more than 30% of the average product return rates. Robustness checks, theoretical and managerial implications are also discussed.

UNDERSTANDING ROLES OF INSTITUTION BASED TRUST AND SOCIAL INTERACTIONS IN SOCIAL COMMERCE ENVIRONMENT

ABSTRACT User-generated content is a two-edged sword in that it can both build and destroy trust in social commerce Web sites. One of the most important ingredients in the social commerce environment is institutional trust. The purpose of this study was to investigate the relationships among institution-based trust, social interactions (content, positive valence, and negative valence), purchase intentions, purchase, and post-purchase behavior of consumers in a social commerce environment. With the help of 227 responses, the proposed research model was validated using structural equation modeling and binary logistic regression analysis techniques. The study’s findings confirmed significant effects of social interactions (content, positive valence, and negative valence) on consumers’ purchase intentions, increasing the likelihood of actual purchasing and sharing shopping experiences with other customers in a social commerce environment. Furthermore, institutional trust was found to be important in influencing content, positive valence, and negative valence. The academic and managerial implications are extensively discussed.

Positive emotions co-experienced with strangers and acquaintances predict COVID-19 vaccination intentions through prosocial tendencies

BackgroundThe efficacy of vaccination depends on its widespread adoption, making vaccine uptake not just a personal health behavior but also a prosocial one. Previous research has shown that everyday moments of co-experienced positive emotions (positivity resonance) are associated with higher prosocial tendencies, and these moments, in turn, prospectively predict people's pandemic hygiene behaviors. Yet, limited research has explored how moments of positivity resonance may have predicted greater COVID-19 vaccine intentions during the early months of the pandemic. MethodsWe longitudinally surveyed a national U.S. sample across four weeks during the fall of 2020. We tested the hypothesis that positivity resonance with strangers and acquaintances indirectly predicts COVID-19 vaccine intentions, as statistically mediated by prosocial tendencies. We also aimed to replicate the indirect effects of positivity resonance on hygiene behaviors (such as mask wearing and hand washing), effects that have been demonstrated in previous research. ResultsIn a pre-registered structural equation model, we found that perceived positivity resonance experienced with strangers and acquaintances prospectively predicted prosocial tendencies, which in turn amplified people's COVID-19 vaccine intentions (β = 0.053) and hygiene behaviors – i.e., social distancing (β = 0.032), mask wearing (β = 0.027), hand washing (β = 0.049). ConclusionsUnderstanding the effects of high-quality social interactions with strangers and acquaintances on vaccine intentions and hygiene behaviors is critical, particularly given the likelihood of emerging pandemics and novel vaccines. We discuss theoretical and practical implications related to perceived positivity resonance, prosocial tendencies, and vaccination uptake for novel vaccines.

A replication and extension of the prosocial effect of online social interactions among Chinese and American emerging adults

ABSTRACT The recent global crisis has had a profound and widespread impact on humanity, eliciting a heightened appreciation for the importance of prosociality. In response, interdisciplinary scholars have called for further research to investigate strategies for cultivating kindness, generosity, and cooperation. To answer this call, we conducted a study examining the potential prosocial impact of online social interactions (OSIs) in two distinct cultures. Through a survey of 644 emerging adults from China and the United States, we found that OSIs positively led to prosocial tendencies in both samples, with social connectedness and trust serving as significant mediating factors. Nevertheless, among the American sample, trust can serve as the sole mediator linking OSIs and prosocial tendencies. Conversely, among the Chinese sample, the development of prosociality stemming from OSIs requires the intervening facilitation of social connectedness. This divergence may speak to cultural research regarding the essential role of interpersonal relationships in fostering trust and prosociality in collectivist societies. This study contributes to prosociality scholarship by highlighting the role of OSIs as a crucial enhancer across two distinct cultures, clarifying the underlying mechanisms, and identifying cultural differences in the process of prosocial development. The results have implications for both prosocial theory and practice.

Effects of social interactions on the neural representation of emotional words in late bilinguals

ABSTRACT This fMRI study explored the relationship between social interactions and neural representations of emotionality in a foreign language (LX). Forty-five late learners of Japanese performed an auditory Japanese lexical decision task involving positive and negative words. The intensity of their social interactions with native Japanese speakers was measured using the Study Abroad Social Interaction Questionnaire. Activity in the left ventral striatum significantly correlated with social interaction intensity for positive words, while the right amygdala showed a significant correlation for negative words. These results indicate neural representations of LX emotional words link with the intensity of social interactions. Furthermore, LX negative words activated the left inferior frontal gyrus more than positive and neutral words, suggesting greater cognitive effort for processing negative words, aligning with a bias in adult social interactions towards more positively-valenced language. Overall, our findings underscore the importance of social interaction experiences in the processing of LX emotional words.