Smartphone sensing of social interactions in people with and without schizophrenia

2020 ◽  
Author(s):  
Daniel Fulford ◽  
Jasmine Mote ◽  
Rachel Gonzalez ◽  
Samuel Abplanalp ◽  
Yuting Zhang ◽  
...  
Keyword(s):  
Social Behavior ◽  
Social Functioning ◽  
Social Activity ◽  
Network Size ◽  
Social Impairment ◽  
Schizophrenia Spectrum Disorders ◽  
Social Network Size ◽  
Digital Phenotyping ◽  
Ecological Momentary

Social impairment is a cardinal feature of schizophrenia spectrum disorders (SZ). Smaller social network size, diminished social skills, and loneliness are highly prevalent. Existing, gold-standard assessments of social impairment in SZ often rely on self-reported information that depends on retrospective recall and detailed accounts of complex social behaviors. This is particularly problematic in people with SZ given characteristic cognitive impairments and reduced insight. Ecological Momentary Assessment (EMA; repeated self-reports completed in the context of daily life) allows for the measurement of social behavior as it occurs in vivo, yet still relies on participant input. Momentary characterization of behavior using smartphone sensors (e.g., GPS, microphone) may also provide ecologically valid indicators of social functioning. In the current study we tested associations between both active (e.g., EMA-reported number of interactions) and passive (GPS-based mobility, conversations captured by microphone) smartphone-based measures of social activity and measures of social functioning and loneliness to examine the promise of such measures for understanding social impairment in SZ. Our results indicate that passive markers of mobility were more consistently associated with EMA measures of social behavior in controls than in people with SZ. Furthermore, dispositional loneliness showed associations with mobility metrics in both groups, while general social functioning was less related to these metrics. Finally, interactions detected in the ambient audio were more tied to social functioning in SZ than in controls. Findings speak to the promise of smartphone-based digital phenotyping as an approach to understanding objective markers of social activity in people with and without schizophrenia.

scholarly journals Germline Nuclear-predominant Pten Murine Model Exhibits Impaired Social and Perseverative Behavior, Microglial Activation, and Increased Oxytocinergic Activity

2020 ◽  
Author(s):  
Nick Sarn ◽  
Stetson Thacker ◽  
Hyunpil Lee ◽  
Charis Eng
Keyword(s):  
Social Behavior ◽  
Microglial Activation ◽  
Suppressor Gene ◽  
Social Impairment ◽  
Social Stimuli ◽  
Animal Modeling ◽  
Therapeutic Modalities ◽  
Downstream Effects

Abstract BackgroundAutism spectrum disorder (ASD) has a strong genetic etiology. Germline mutation in the tumor suppressor gene PTEN is one of the best described monogenic risk cases for ASD. Animal modeling of cell-specific Pten loss or mutation has provided insight into how disruptions to the function of PTEN affect neurodevelopment, neurobiology, and social behavior. As such, there is a growing need to understand more about how various aspects of PTEN activity, cell-compartment-specific functions, contribute to certain neurological or behavior phenotypes.MethodsTo understand more about the relationship between Pten localization and downstream effects on neurophenotypes, we generated the nuclear-predominant PtenY68H/+ mouse. We subjected the PtenY68H/+ mouse to morphological and behavioral phenotyping, including the three-chamber sociability and marble burying tests. We subsequently performed in vivo and in vitro cellular phenotyping and concluded the work with a transcriptomic survey of the PtenY68H/+ cortex, which profiled gene expression.ResultsDespite no significant changes in downstream canonical Pten signaling, we found that the PtenY68H/+ mouse presents with macrocephaly, social impairment (i.e., decreased sociability, decreased preference for novel social stimuli, and increased perseverative activity), with significant microglial activation accompanied by enhanced phagocytosis. Because of lack of canonical signaling alterations, we turned to analyzing the neural transcriptomes, which revealed overexpression of many genes involved in neuroinflammation and neuronal function, including oxytocin. Oxytocin transcript was 5-fold overexpressed (P = 0.0018) and oxytocin protein was strongly overexpressed in the PtenY68H/+ hypothalamus. ConclusionsThe nuclear-predominant PtenY68H/+ model has clarified that Pten dysfunction links to microglial pathology and that timed decreased in Pten levels is the provoking insult. Notably, we demonstrate that Pten dysfunction associates with changes in the oxytocin system, an important connection between a prominent ASD risk gene and a potent neuroendocrine regulator of social behavior. Ultimately, the findings from this work may reveal important biomarkers and/or novel therapeutic modalities that could be explored in individuals with germline mutations in PTEN with ASD.

scholarly journals Late-Life Social Activity and Cognitive Decline in Old Age

2011 ◽  
Vol 17 (6) ◽  
pp. 998-1005 ◽  
Author(s):  
Bryan D. James ◽  
Robert S. Wilson ◽  
Lisa L. Barnes ◽  
David A. Bennett
Keyword(s):  
Cognitive Function ◽  
Cognitive Decline ◽  
Old Age ◽  
Sex Education ◽  
Social Activity ◽  
Cognitive Activity ◽  
Network Size ◽  
Sensitivity Analyses ◽  
Social Network Size ◽  
Rate Of Decline

AbstractWe examined the association of social activity with cognitive decline in 1138 persons without dementia at baseline with a mean age of 79.6 (SD = 7.5) who were followed for up to 12 years (mean = 5.2; SD = 2.8). Using mixed models adjusted for age, sex, education, race, social network size, depression, chronic conditions, disability, neuroticism, extraversion, cognitive activity, and physical activity, more social activity was associated with less cognitive decline during average follow-up of 5.2 years (SD = 2.7). A one point increase in social activity score (range = 1–4.2; mean = 2.6; SD = 0.6) was associated with a 47% decrease in the rate of decline in global cognitive function (p < .001). The rate of global cognitive decline was reduced by an average of 70% in persons who were frequently socially active (score = 3.33, 90th percentile) compared to persons who were infrequently socially active (score = 1.83, 10th percentile). This association was similar across five domains of cognitive function. Sensitivity analyses revealed that individuals with the lowest levels of cognition or with mild cognitive impairment at baseline did not drive this relationship. These results confirm that more socially active older adults experience less cognitive decline in old age. (JINS, 2011, 17, 998–1005)

scholarly journals The Influence of Community-Level Built Environment Factors on Active Social Network Size in Older Adults: Social Activity as a Moderator

2020 ◽  
Vol 41 (1) ◽  
pp. 77-87
Author(s):  
Nestor Asiamah ◽  
Kyriakos Kouveliotis ◽  
Richard Eduafo ◽  
Richard Borkey
Keyword(s):  
Older Adults ◽  
Social Network ◽  
Environmental Factors ◽  
Built Environment ◽  
Social Ties ◽  
Social Activity ◽  
Network Size ◽  
Community Level ◽  
Environment Factors ◽  
Social Network Size

Background This study examined the influence of built environmental factors in the community on active social network size as well as the moderating influence of different dimensions of social activity on this relationship. Methods This study employed the cross-sectional and correlational approaches to construct a scale measuring key community-level built environment factors and test the moderating influence of social activity on the association between these factors and active social network size in older adults. The study population was all 3,211 older adults who were resident in Accra and were part of the database of the Social Security and National Insurance Trust. Participants were 515 older adults in Accra aged 60 years or more who met some inclusion criteria. A self-reported questionnaire, including a new scale measuring the built environment factors, was used to collect data. Principal component analysis with varimax rotation and confirmatory factor analysis were used to validate the measurement scales, whereas Pearson’s correlation test and multiple linear regression analysis were used to test the associations of interest. Results After controlling for relevant demographic variables, built environment factors in the community have no significant influence on active social network size. Volunteering, support for social ties, and group activity positively moderated the influence of built environment factors on active social network size at p < .05 and β ≥ 0.2. Conclusion The study concludes that social activity is essential to the utilization of available built environmental factors by older adults to make active social ties in the community.

scholarly journals Novel Influence Maximization Algorithm for Social Network Behavior Management

2021 ◽  
Vol 3 (1) ◽  
pp. 60-68
Author(s):  
Sivaganesan D
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Behavior ◽  
Social Action ◽  
Behavior Management ◽  
Network Size ◽  
Influence Maximization ◽  
Interactive Behavior ◽  
Social Network Size ◽  
The Social

The users largely contributing towards product adoption or information utilization in social networks are identified by the process of influence maximization. The exponential growth in social networks imposes several challenges in the analyses of these networks. Important has been given to modeling structural properties while the relationship between users and their social behavior has being ignored in the existing literature. With respect to the social behavior, the influence maximization task has been parallelized in this paper. In order to maximize the influence in social networks, an interest based algorithm with parallel social action has been proposed. This is algorithm enables identifying influential users in social network. The interactive behavior of the user is weighted dynamically as social actions along with the interests of the users. These two semantic metrics are used in the proposed algorithm. An optimal influential nodes set is computed by implementing the machines with CPU architecture with perfect parallelism through community structure. This helps in reducing the execution time and overcoming the real-word social network size challenges. When compared to the existing schemes, the proposed algorithm offers improved efficiency in the calculation speed on real world networks.

Extraverts Have Larger Social Network Layers

2011 ◽  
Vol 32 (3) ◽  
pp. 161-169 ◽  
Author(s):  
Thomas V. Pollet ◽  
Sam G. B. Roberts ◽  
Robin I. M. Dunbar
Keyword(s):  
Social Network ◽  
Social Relationships ◽  
Outer Layer ◽  
Network Size ◽  
Emotional Intensity ◽  
Emotional Closeness ◽  
Network Layer ◽  
Network Layers ◽  
Social Network Size

Previous studies showed that extraversion influences social network size. However, it is unclear how extraversion affects the size of different layers of the network, and how extraversion relates to the emotional intensity of social relationships. We examined the relationships between extraversion, network size, and emotional closeness for 117 individuals. The results demonstrated that extraverts had larger networks at every layer (support clique, sympathy group, outer layer). The results were robust and were not attributable to potential confounds such as sex, though they were modest in size (raw correlations between extraversion and size of network layer, .20 < r < .23). However, extraverts were not emotionally closer to individuals in their network, even after controlling for network size. These results highlight the importance of considering not just social network size in relation to personality, but also the quality of relationships with network members.

Imaging the “social brain” in schizophrenia: A systematic review of neuroimaging studies of social reward and punishment

2020 ◽  
Author(s):  
Jessica Mow ◽  
Arti Gandhi ◽  
Daniel Fulford
Keyword(s):  
Brain Activity ◽  
Interaction Network ◽  
Social Motivation ◽  
Social Impairment ◽  
Future Research ◽  
Social Reward ◽  
Schizophrenia Spectrum Disorders ◽  
Social Stimuli ◽  
Schizophrenia Spectrum ◽  
Reward And Punishment

Decreased social functioning and high levels of loneliness and social isolation are common in schizophrenia spectrum disorders (SSD), contributing to reduced quality of life. One key contributor to social impairment is low social motivation, which may stem from aberrant neural processing of socially rewarding or punishing stimuli. To summarize research on the neurobiology of social motivation in SSD, we performed a systematic literature review of neuroimaging studies involving the presentation of social stimuli intended to elicit feelings of reward and/or punishment. Across 11 studies meeting criteria, people with SSD demonstrated weaker modulation of brain activity in regions within a proposed social interaction network, including prefrontal, cingulate, and striatal regions, as well as the amygdala and insula. Firm conclusions regarding neural differences in SSD in these regions, as well as connections within networks, are limited due to conceptual and methodological inconsistencies across the available studies. We conclude by making recommendations for the study of social reward and punishment processing in SSD in future research.

scholarly journals How Narcissism Shapes Responses to Antisocial and Prosocial Behavior: Hypo-Responsiveness or Hyper-Responsiveness?

2021 ◽  
pp. 014616722110072
Author(s):  
Jiafang Chen ◽  
Barbara Nevicka ◽  
Astrid C. Homan ◽  
Gerben A. van Kleef
Keyword(s):  
Social Behavior ◽  
Prosocial Behavior ◽  
Social Functioning ◽  
Social Order ◽  
Social Behaviors ◽  
Moral Character ◽  
Prosocial Behaviors ◽  
Future Research ◽  
Clear Cut ◽  
Reward And Punishment

Narcissists have a relatively higher proclivity for displaying antisocial rather than prosocial behaviors, suggesting a comparatively higher tendency for unfavorably impacting societies. However, maintenance of social order also depends on appropriate responses to others’ social behavior. Once we focus on narcissists as observers rather than actors, their impact on social functioning becomes less clear-cut. Theoretical arguments suggest that narcissists could be either hypo-responsive or hyper-responsive to others’ social behavior. Across four studies, we examined narcissists’ responsiveness to variations in others’ antisocial and prosocial behaviors. Results showed that narcissists differentiated less between others’ antisociality/prosociality, as reflected in their subsequent moral character evaluations (Studies 1–4) and reward and punishment (Studies 3 and 4). These results suggest that narcissists are hypo-responsive to others’ social behaviors. Implications and directions for future research are discussed.

scholarly journals Social Networks and Loneliness During the COVID-19 Pandemic

2021 ◽  
Vol 7 ◽  
pp. 237802312098525
Author(s):  
Balazs Kovacs ◽  
Nicholas Caplan ◽  
Samuel Grob ◽  
Marissa King
Keyword(s):  
Social Network ◽  
Social Isolation ◽  
Close Relationships ◽  
Network Size ◽  
Global Network ◽  
Network Data ◽  
Network Characteristics ◽  
Face To Face ◽  
Social Network Data ◽  
Social Network Size

We utilize longitudinal social network data collected pre–COVID-19 in June 2019 and compare them with data collected in the midst of COVID in June 2020. We find significant decreases in network density and global network size following a period of profound social isolation. While there is an overall increase in loneliness during this era, certain social network characteristics of individuals are associated with smaller increases in loneliness. Specifically, we find that people with fewer than five “very close” relationships report increases in loneliness. We further find that face-to-face interactions, as well as the duration and frequency of interactions with very close ties, are associated with smaller increases in loneliness during the pandemic. We also report on factors that do not moderate the effect of social isolation on perceived loneliness, such as gender, age, or overall social network size.

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