Feasibility of Linking Molecular Genetic Markers to Real-World Social Network Size Tracked on Smartphones

Abstract

The study of individual differences in human social behavior has a long tradition in (personality) psychology focusing on traits such as extraversion linked to vividness and assertiveness. The study of molecular genetic underpinnings of individual differences in social behavior produced many genetic association studies with only few genetic variants, robustly associated with individual differences in personality. One possible reason for non-replication of findings might be the different inventories used to assess human social traits. Moreover, self-report methods to assess personality and social behavior might be problematic due to their susceptibility to different biases such as social desirability or poor abilities in self-reflection. We stress the importance of including recorded behavior to understand the molecular genetic basis of individual differences in personality and linked social traits. We present preliminary data linking oxytocin genetics to individual differences in social network size derived from smartphones. Here, the genetic variation rs2268498, located in the adjacent area of the promoter of the gene coding for the oxytocin receptor (OXTR), was linked to the number of active contacts and incoming calls, tracked on the smartphone for 12 days (note that these results became a bit weaker when age was controlled for). Although the present empirical findings should only be seen as a proof of concept study, this work demonstrates the feasibility to combine molecular genetic variables with real world behavior. If this approach keeps its promises, the field of personality research might experience a boost in psychometric quality in the near future.

Concept, Possibilities and Pilot-Testing of a New Smartphone Application for the Social and Life Sciences to Study Human Behavior Including Validation Data from Personality Psychology

“…Thus, for consistency reasons only Spearman's correlations were conducted and the Bias corrected and accelerated bootstrap CIs are reported. Please note, that we also assessed in the present project self-reports on "smartphone addiction" [48], molecular genetic samples (see a first work published with this data [49]), and tracked other variables such as Facebook or WhatsApp usage on the smartphone. Presenting all these findings would go far beyond the main aim of this research piece and therefore we only present the personality associations in this paper.…”

Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study

“…For example, data on pulse rate, finger taps, or voice features can be tracked using an individual's smartphone and then analyzed to measure behavior, physiological states, and cognitive functioning [6][7][8][9]. As the field of digital phenotyping has evolved, projects increasingly include multiple data streams in the analyses, such as data from electronic health records (EHRs), facial recognition technology, ambient sensors, biological scans, or genomic information [10][11][12][13]. The proper terminology for these techniques is still under debate, with terms such as computational behavioral analysis [14], continuous measurement [15], or personal sensing also being applied to similar research approaches that involve continuous monitoring of behavioral data gathered from sensors or digital sources [16,17].…”

Digital Phenotyping - A Case for Cognitive Functions and Dementia?

“…the study of digital footprints. We partially share this opinion in relation to polygenetically influenced phenotypes in psychology also shaped by the environment , but again see the feasibility study by Sariyska et al (2018). For neurodegenerative disorders, however, the situation may be somewhat different, because here genetic variants exert higher influence compared to the effects of a single genetic variant on a trait such as personality (again being influenced by hundred of genetic variants shaped by the environment).…”

“…Early work demonstrated the feasibility of linking both molecular genetic and MRI data to smartphone use variables. Work by Sariyska et al (2018) demonstrated that a genetic variant of the oxytocin receptor (OXTR) gene might be linked to the size of a person's (active) social network. Note that the sample size of this study was rather small and these findings thus need to be replicated by independent work groups.…”