Toward Psychoinformatics: Computer Science Meets Psychology

Social media are many things: Addressing the components and patterns of adolescent social media use

Adolescent development is increasingly shaped by social media contexts, with implications for well-being. In this commentary, we discuss and present conceptual and methodological alternatives for two persistent limitations in prior research. First, most prior work measures screen time, implicitly treating social media as a monolith. Emerging research highlights that social media are multifaceted environments where youth encounter diverse experiences. We advocate for more work taking this nuanced approach and for the development of a comprehensive taxonomic framework that categorizes specific online experiences afforded by social media features and content. To support this approach, we call for the development of psychometrically rigorous self-report scales to measure affective and cognitive social media experiences and for innovative behavioral observation techniques. Second, research that considers specific online experiences typically focuses on one in isolation. We argue that a holistic, interactionist approach to understanding human development requires integrating the numerous positive and negative online experiences that co-occur in distinct patterns for diverse adolescents. We discuss the merits of mixture models as one potential analytic solution to address configurations of online experiences and systematically model heterogeneity among youth. These conceptual and methodological shifts can lead to targeted interventions and policies that recognize the interactive effects of digital experiences.

Nomophobia, Psychopathology, and Smartphone-Inferred Behaviors in Youth With Depression: Longitudinal Study

BACKGROUND

Smartphones have become an indispensable part of people's lives, and the fear of being without them, what has been termed "no mobile phone phobia" (nomophobia), is a growing phenomenon. The rise of problematic smartphone use highlights the urgent need to explore the intricate relationship between smartphones and human behavior. However, the connections between nomophobia, mental health indicators, smartphone use patterns, and daily activities remain largely underexplored.

OBJECTIVE

This study aimed to explore the relationship between young adults with depression and smartphones and investigate nomophobia by analyzing data obtained from a pilot study of depression in a youth cohort. Exploring nomophobia can enhance our understanding of the dynamics between young adults and smartphone use, potentially empowering them to manage and regulate their smartphone use more effectively.

METHODS

During an 8-week period, data collected via smartphone sensors, such as locations and screen status, were gathered from a cohort of 41 individuals diagnosed with major depressive disorder. In addition to passive-sensing smartphone data, the study collected ecological momentary assessments and psychometric measures, including the Nomophobia Questionnaire, which formed the basis of our investigation. We explored statistical associations among smartphone-derived behavioral features, psychometric indicators, and nomophobia. In addition, we used behavioral and psychometric data to develop regression models demonstrating the prediction of nomophobia levels.

RESULTS

Our findings revealed that the level of nomophobia was positively associated with depression and negative affect, lower geolocation movements, and higher comfort with smartphone sensing. The exploratory predictive linear regression models demonstrated the feasibility of predicting an individual's Nomophobia Questionnaire score based on their smartphone sensing data. These models effectively used input features derived from both a combination of smartphone sensing data and psychometric measures and from smartphone sensing data alone.

CONCLUSIONS

Our work is the first to explore the relationship between nomophobia and smartphone sensor data. It provides valuable insights into the predictors of nomophobia level, contributing to the understanding of the relationship between smartphones and human behavior and paving the way for future studies.

ChatDashboard: A Framework to collect, link, and process donated WhatsApp Chat Log Data

In this paper, we present ChatDashboard, a framework for collecting, linking, and processing donated WhatsApp chat log data. The framework consists of the WhatsR R package for parsing, anonymizing, and preprocessing donated WhatsApp chat logs, the ChatDashboard R Shiny web app for uploading, reviewing, and securely donating WhatsApp chat logs, and DashboardTester, an automated script for testing the correct setup of the framework by simulating participants. With ChatDashboard, researchers can set up their own data collections to gather transparently donated WhatsApp chat log data from consenting participants and link them to survey responses. It enables researchers to retrospectively collect highly granular data on interpersonal interactions and communication without building their own tools from scratch. We briefly discuss the advantages of donated WhatsApp chat log data for investigating social relationships and provide a detailed explanation of the ChatDashboard framework. Additionally, we provide a step-by-step guideline in the supplementary materials for researchers to set up their own data donation pipelines.

Predicting Big Five personality traits from smartphone data: A meta-analysis on the potential of digital phenotyping

OBJECTIVE

Since the first study linking recorded smartphone variables to self-reported personality in 2011, many additional studies have been published investigating this association. In the present meta-analyses, we aimed to understand how strongly personality can be predicted via smartphone data.

METHOD

Meta-analytical calculations were used to assess the association between smartphone data and Big Five traits. Because of the lack of independence of many included studies, analyses were performed using a multilevel approach.

RESULTS

Based on data collected from 21 distinct studies, extraversion showed the largest association with the digital footprints derived from smartphone data (r = .35), while remaining traits showed smaller associations (ranging from 0.23 to 0.25). For all traits except neuroticism, moderator analyses showed that prediction performance was improved when multiple features were combined together in a single predictive model. Additionally, the strength of the prediction of extraversion was improved when call and text log data were used to perform the prediction, as opposed to other types of smartphone data CONCLUSIONS: Our synthesis reveals small-to-moderate associations between smartphone activity data and Big Five traits. The opportunities, but also dangers of the digital phenotyping of personality traits based on traces of users' activity on a smartphone data are discussed.

Digitale Phänotypisierung in der Psychologie – ein Quantensprung in der psychologischen Forschung?

Zusammenfassung. Digitale Phänotypisierung stellt einen neuen, leistungsstarken Ansatz zur Realisierung psychodiagnostischer Aufgaben in vielen Bereichen der Psychologie und Medizin dar. Die Grundidee besteht aus der Nutzung digitaler Spuren aus dem Alltag, um deren Vorhersagekraft für verschiedenste Anwendungsmöglichkeiten zu überprüfen und zu nutzen. Voraussetzungen für eine erfolgreiche Umsetzung sind elaborierte Smart Sensing Ansätze sowie Big Data-basierte Extraktions- (Data Mining) und Machine Learning-basierte Analyseverfahren. Erste empirische Studien verdeutlichen das hohe Potential, aber auch die forschungsmethodischen sowie ethischen und rechtlichen Herausforderungen, um über korrelative Zufallsbefunde hinaus belastbare Befunde zu gewinnen. Hierbei müssen rechtliche und ethische Richtlinien sicherstellen, dass die Erkenntnisse in einer für Einzelne und die Gesellschaft als Ganzes wünschenswerten Weise genutzt werden. Für die Psychologie als Lehr- und Forschungsdomäne bieten sich durch Digitale Phänotypisierung vielfältige Möglichkeiten, die zum einen eine gelebte Zusammenarbeit verschiedener Fachbereiche und zum anderen auch curriculare Erweiterungen erfordern. Die vorliegende narrative Übersicht bietet eine theoretische, nicht-technische Einführung in das Forschungsfeld der Digitalen Phänotypisierung, mit ersten empirischen Befunden sowie einer Diskussion der Möglichkeiten und Grenzen sowie notwendigen Handlungsfeldern.

Development of Digital Biomarkers of Mental Illness via Mobile Apps for Personalized Treatment and Diagnosis

The development of precision psychiatry is largely based on multi-module measurements from the molecular, cellular, and behavioral levels, which are integrated to assess neurocognitive performances and clinically observed psychopathology. Nevertheless, quantifying mental activities and functions accurately and continuously has been a major difficulty within this field. This article reviews the latest efforts that utilize mobile apps to collect human–smartphone interaction data and contribute towards digital biomarkers of mental illnesses. The fundamental principles underlying a behavioral analysis with mobile apps were introduced, such as ways to monitor smartphone use under different circumstances and construct long-term patterns and trend changes. Examples were also provided to illustrate the potential applications of mobile apps that gain further insights into traditional research topics in occupational health and sleep medicine. We suggest that, with an optimized study design and analytical approach that accounts for technical challenges and ethical considerations, mobile apps will enhance the systemic understanding of mental illnesses.

On Blurry Boundaries When Defining Digital Biomarkers: How Much Biology Needs to Be in a Digital Biomarker?

Recent years have seen a rise in research where so called "digital biomarkers" represent the focal study interest. Many researchers understand that digital biomarkers describe digital footprints providing insights into healthy and pathological human (neuro-)biology. Beyond that the term digital biomarker is also used at times to describe more general concepts such as linking digital footprints to human behavior (which itself can be described as the result of a biological system). Given the lack of consensus on how to define a digital biomarker, the present short mini-review provides i) an overview on various definitions and ii) distinguishes between direct (narrow) or indirect (broad) concepts of digital biomarkers. From our perspective, digital biomarkers meant as a more direct (or narrow) concept describe digital footprints being directly linked to biological variables, such as stemming from molecular genetics, epigenetics, endocrinology, immunology or brain imaging, to name a few. More indirect concepts of digital biomarkers encompass digital footprints being linked to human behavior that may act as latent variables indirectly linked to biological variables.

Intelligent Cognitive Assistants for Attitude and Behavior Change Support in Mental Health: State-of-the-Art Technical Review

Intelligent cognitive assistant (ICA) technology is used in various domains to emulate human behavior expressed through synchronous communication, especially written conversation. Due to their ability to use individually tailored natural language, they present a powerful vessel to support attitude and behavior change. Behavior change support systems are emerging as a crucial tool in digital mental health services, and ICAs exceed in effective support, especially for stress, anxiety and depression (SAD), where ICAs guide people’s thought processes and actions by analyzing their affective and cognitive phenomena. Currently, there is no comprehensive review of such ICAs from a technical standpoint, and existing work is conducted exclusively from a psychological or medical perspective. This technical state-of-the-art review tried to discern and systematize current technological approaches and trends as well as detail the highly interdisciplinary landscape of intersections between ICAs, attitude and behavior change, and mental health, focusing on text-based ICAs for SAD. Ten papers with systems, fitting our criteria, were selected. The systems varied significantly in their approaches, with the most successful opting for comprehensive user models, classification-based assessment, personalized intervention, and dialogue tree conversational models.

Fear of Missing Out (FoMO) and social media's impact on daily-life and productivity at work: Do WhatsApp, Facebook, Instagram, and Snapchat Use Disorders mediate that association?

Fear of Missing Out (FoMO) is the tendency to experience anxiety over missing out on rewarding experiences of others. It has been associated with daily-life disruptions, such as distractions during driving. FoMO has also consistently been a predictor of Internet, smartphone, and social networks use disorders. In the current work, we investigated the association between FoMO and social media use's impact on daily-life and productivity at work. In addition, we aimed to determine whether WhatsApp, Facebook, Instagram, and Snapchat Use Disorders mediate that relationship. The effective sample comprised 748 German-speaking study participants from the general population (age M = 38.63, SD = 12.10; 336 men, 412 women) who took part in an online survey study. Bivariate analyses showed that severity of all social networks use disorders were positively correlated with FoMO and social media's negative impact on daily-life and productivity at work. Furthermore, controlling for age and gender, mediation analyses showed that out of all platforms, only Snapchat Use Disorder did not mediate the association between FoMO and social media's negative impact on daily-life and productivity at work. These results provide further evidence about FoMO's central role in digital technology use-related disorders.

Sedentary Work in Desk-Dominated Environments: A Data-Driven Intervention Using Intervention Mapping

Background

Since desk-dominated work environments facilitate sedentary behavior, office workers sit for 66% of their working days and only 8% succeed in interrupting their prolonged periods of sitting within the first 55 minutes. Yet stretches of long and uninterrupted sitting increase the likelihood of several chronic metabolic and cardiovascular diseases.

Objective

We therefore developed a computer-based app designed to interrupt periods of prolonged sitting among office employees.

Methods

When developing the intervention, we applied the intervention mapping protocol. This approach for the systematic design of theory and evidence-based behavior change programs consists of 6 steps: creation of a logic model of the problem, creation of a logic model of change, program design, program production, design of an implementation plan, and development of an evaluation plan.

Results

Working through all 6 steps has resulted in an individually adaptable intervention to reduce sedentary behavior at work. The intervention, UPcomplish, consists of tailored, half-automatized motivational components delivered by a coach. To register sedentary behavior, the VitaBit (VitaBit Software International BV) toolkit, a wearable accelerometry-based monitoring device, is used. Among others, UPcomplish includes personalized goal setting, tailored suggestions to overcome hurdles, and weekly challenges. The VitaBit toolkit supports the participants to monitor their behavior in relation to self-set goals.

Conclusions

Intervention mapping is a useful protocol not only for the systematic development of a comprehensive intervention to reduce sedentary behavior but also for planning program adherence, program implementation, and program maintenance. It facilitates obtaining the participation of relevant stakeholders at different ecological levels in the development process of the intervention and anticipating facilitators to and barriers of program implementation and maintenance.

Trial Registration

Netherlands Trial Register NL7503; https://www.trialregister.nl/trial/7503

Investigating the Relationship between Personality and Technology Acceptance with a Focus on the Smartphone from a Gender Perspective: Results of an Exploratory Survey Study

Prior research found that user personality significantly affects technology acceptance perceptions and decisions. Yet, evidence on the moderating influence of user gender on the relationship between personality and technology acceptance is barely existent despite theoretical consideration. Considering this research gap, the present study reports the results of a survey in which we examined the relationships between personality and technology acceptance from a gender perspective. This study draws upon a sample of N = 686 participants (n = 209 men, n = 477 women) and applied the HEXACO Personality Inventory—Revised along with established technology acceptance measures. The major result of this study is that we do not find significant influence of user gender on the relationship between personality and technology acceptance, except for one aspect of personality, namely altruism. We found a negative association between altruism and intention to use the smartphone in men, but a positive association in women. Consistent with this finding, we also found the same association pattern for altruism and predicted usage: a negative one in men and a positive one in women. Implications for research and practice are discussed, along with limitations of the present study and possible avenues for future research.

Personality associations with Facebook use and tendencies towards Facebook Use Disorder

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Facebook users reported higher levels of extraversion compared to non-users.

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Facebook users reported lower levels of conscientiousness compared to non-users.

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Tendencies towards Facebook-Use Disorder correlated negatively with conscientiousness.

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Tendencies towards Facebook-Use Disorder correlated positively with neuroticism.

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All results are controlled for potential effects of demographic variables.

Introduction

The present study sought to address core issues in the association between personality and the putative disordered use of Facebook. First, to redress the issue of generalisation from samples solely recruited from Facebook, we sought to explore personality differences between users and non-users of Facebook. Second, we aimed to investigate associations between personality and Facebook Use Disorder. The present study contributes a novel perspective to extant research on this topic by moving beyond the broad Big Five of personality, to explore possible relationships between Facebook use and sub-facets of the Big Five; all analyses were additionally controlled for confounding effects of demographic variables.

Methods

3,835 (n = 2,366 males) participants completed socio-demographic variables, the Big Five Inventory and stated their user status on Facebook (i.e. user versus non-user). Facebook-users also completed a Facebook Use Disorder scale assessing addictive tendencies towards Facebook use.

Results

Facebook users reported higher levels of extraversion and lower levels of conscientiousness compared to non-users. Tendencies towards Facebook Use Disorder correlated negatively with conscientiousness and positively with neuroticism in both males and females.

Conclusions

The present results indicate that research samples drawn from Facebook users may be biased with regard to personality (extraversion, conscientiousness). Moreover, certain personality traits – conscientiousness and neuroticism – which may influence the tendency towards Facebook Use Disorder are discussed.

Age, gender, personality, ideological attitudes and individual differences in a person's news spectrum: how many and who might be prone to "filter bubbles" and "echo chambers" online?

Potential effects of demographics, personality, and ideological attitudes on the number of news sources consumed should be investigated. The number of news sources consumed, in turn, was seen as inverse proxy for the susceptibility to be caught in “filter bubbles” and/or “echo chambers” (online), which are hotly discussed topics also in politics. A sample of 1,681 (n = 557 males) participants provided data on demographics, the Big Five as well as Right-Wing Authoritarianism (RWA) alongside the number of different news sources consumed and current voting preferences. Results showed that age (positively), gender (higher in males), Openness (positively), and RWA (negatively) predicted the number of different news sources consumed. The group of participants consuming news exclusively offline showed highest scores in Conscientiousness and lowest scores in Neuroticism compared to the “news feeds only” and the “news feeds and online” groups. However, less than 5% of the participants exclusively consumed news via news feeds of social networking sites. Participants who stated that they would not vote reported the lowest number of different news sources consumed. These findings reveal first insights into predisposing factors for the susceptibility to be caught in “filter bubbles” and/or “echo chamber” online and how this might be associated with voting preferences.

The Flatland Fallacy: Moving Beyond Low-Dimensional Thinking

Psychology is a complicated science. It has no general axioms or mathematical proofs, is rarely directly observable, and is the only discipline in which the subject matter (i.e., human psychological phenomena) is also the tool of investigation. Like the Flatlanders in Edwin Abbot's famous short story (), we may be led to believe that the parsimony offered by our low-dimensional theories reflects the reality of a much higher-dimensional problem. Here we contend that this "Flatland fallacy" leads us to seek out simplified explanations of complex phenomena, limiting our capacity as scientists to build and communicate useful models of human psychology. We suggest that this fallacy can be overcome through (a) the use of quantitative models, which force researchers to formalize their theories to overcome this fallacy, and (b) improved quantitative training, which can build new norms for conducting psychological research.

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

With the advent of the World Wide Web, the smartphone and the Internet of Things, not only society but also the sciences are rapidly changing. In particular, the social sciences can profit from these digital developments, because now scientists have the power to study real-life human behavior via smartphones and other devices connected to the Internet of Things on a large-scale level. Although this sounds easy, scientists often face the problem that no practicable solution exists to participate in such a new scientific movement, due to a lack of an interdisciplinary network. If so, the development time of a new product, such as a smartphone application to get insights into human behavior takes an enormous amount of time and resources. Given this problem, the present work presents an easy way to use a smartphone application, which can be applied by social scientists to study a large range of scientific questions. The application provides measurements of variables via tracking smartphone–use patterns, such as call behavior, application use (e.g., social media), GPS and many others. In addition, the presented Android-based smartphone application, called Insights, can also be used to administer self-report questionnaires for conducting experience sampling and to search for co-variations between smartphone usage/smartphone data and self-report data. Of importance, the present work gives a detailed overview on how to conduct a study using an application such as Insights, starting from designing the study, installing the application to analyzing the data. In the present work, server requirements and privacy issues are also discussed. Furthermore, first validation data from personality psychology are presented. Such validation data are important in establishing trust in the applied technology to track behavior. In sum, the aim of the present work is (i) to provide interested scientists a short overview on how to conduct a study with smartphone app tracking technology, (ii) to present the features of the designed smartphone application and (iii) to demonstrate its validity with a proof of concept study, hence correlating smartphone usage with personality measures.

Development of a mobile application (App) to delineate "digital chronotype" and the effects of delayed chronotype by bedtime smartphone use

The widespread use and deep reach of smartphones motivate the use of mobile applications to continuously monitor the relationship between circadian system, individual sleep patterns, and environmental effects. We selected 61 adults with 14-day data from the "Know Addiction" database. We developed an algorithm to identify the "sleep time" based on the smartphone behaviors. The total daily smartphone use duration and smartphone use duration prior to sleep onset were identified respectively. We applied mediation analysis to investigate the effects of total daily smartphone use on sleep through pre-sleep use (PS). The results showed participants' averaged pre-sleep episodes within 1 h prior to sleep are 2.58. The duration of three pre-sleep uses (PS_1∼3) maybe a more representative index for smartphone use before sleep. Both total daily duration and the duration of the last three uses prior to sleep of smartphone use significantly delayed sleep onset, midpoint of sleep and reduced total sleep time. One hour of increased smartphone use daily, delays the circadian rhythm by 3.5 min, and reduced 5.5 min of total sleep time (TST). One hour of increased pre-sleep smartphone use delayed circadian rhythm by 1.7 min, and reduced 39 s of TST. The mediation effects of PS_1∼3 significantly impacted on these three sleep indicators. PS_1∼3 accounted for 14.3% of total daily duration, but the proportion mediated of delayed circadian rhythm was 44.0%. We presented "digital chronotype" with an automatic system that can collect high temporal resolution data from naturalistic settings with high ecological validity. Smartphone screen time, mainly mediated by pre-sleep use, delayed the circadian rhythm and reduced the total sleep time.

Using Eye Tracking to Explore Facebook Use and Associations with Facebook Addiction, Mental Well-being, and Personality

Social networking sites (SNSs) have become ubiquitous in our everyday lives, and for all its communicative benefits, excessive SNS use has been associated with a range of negative health implications. In the present study, the authors use eye-tracking methodology to explore the relationship between individual differences in personality, mental well-being, SNS usage, and the focus of Facebook users’ visual attention. Participants (n = 69, mean age = 23.09, SD = 7.54) completed questionnaire measures for personality and to examine changes in depression, anxiety, stress, and self-esteem. They then engaged in a Facebook session while their eye movements and fixations were recorded. These fixations were coded as being directed to social and update areas of interest (AOI) of the Facebook interface. An exploratory analysis of personality factors revealed a negative correlation between openness to experience and inspection times for the updates AOI and an unexpected negative relationship between extraversion and inspection times for social AOI. There were correlations between changes in depression score and inspection of updates AOI, with reduced depression scores associated with increased inspection of updates. Finally, self-reported duration of participants’ typical Facebook sessions did not correlate with eye-tracking measures but were associated with increased Facebook addiction scores and greater increases in depression scores. These initial findings indicate that there are differences in the outcomes of interacting with Facebook which can vary based on Facebook addiction, personality variables, and the Facebook features that individuals interact with.

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

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.

The Multipurpose Application WeChat: A Review on Recent Research

With currently over one billion monthly active users, the Chinese social media and multipurpose application WeChat (, Wēixìn, micro-message) has become one of the world's most popular social media platforms. Despite its enormous number of users in Asia, WeChat is still not well known in Western countries. Against this background, the present review aims to provide the reader with a comprehensive overview on the functionality of this application, comparison with other popular applications such as Facebook/WhatsApp and previous research. Although WeChat has become an integral part of everyday life for many users, research has only recently begun to examine the impact of this development on the societal and individual levels. The present review summarizes the literature on this topic with a focus on the motives to engage in using the app and potential detrimental effects of excessive use. In the context of the growing popularity and increasing usage times of the app - in particular in Asian countries - future research seems warranted to examine systematically how social media platforms such as WeChat will affect interpersonal communication behavior, well-being, and mental health. The direct comparison of WeChat's influence on the mentioned variables compared with its competitors Facebook and WhatsApp often used in Western countries will also be of high importance.

Associations between the dark triad of personality and unspecified/specific forms of Internet-use disorder

BACKGROUND AND AIMS

Despite indications that the dark triad of personality might be associated with Internet-use disorder (IUD), research about these associations is lacking.

METHODS

Two studies were performed to grasp the links between these variables. In the first study, a sample consisting of N = 468 participants (n = 130 males) filled in the Short Dark Triad Questionnaire to assess scores in the dark triad of personality and the short Internet Addiction Test to assess tendencies toward unspecified IUD. In the second study, another independent sample of N = 472 participants (n = 143 males) filled in the same questionnaires plus items about specific forms of IUD.

RESULTS

Traits Machiavellianism and psychopathy were positively linked to tendencies toward unspecified IUD in both samples and males and females. Regarding the associations between tendencies toward specific IUDs and the dark triad of personality, no significant associations were found in males (at least not passing correction procedures for multiple testing). In females, trait Machiavellianism/psychopathy and tendencies toward Internet-shopping disorder, trait psychopathy, and tendencies toward Internet-pornography-use disorder as well as trait Machiavellianism and tendencies toward Internet-communication disorder were significantly positively correlated [at least one of the (sub)scales assessing the respective specific IUD was significantly associated with the respective dark triad trait even after correction procedures for multiple testing]. No robust pattern of associations between trait narcissism and unspecified/specific forms of IUD could be observed across (sub)samples.

DISCUSSION AND CONCLUSIONS

These results indicate positive associations of the traits Machiavellianism and psychopathy (on a subclinical level) with tendencies toward IUD, especially unspecified IUD. The associations with tendencies toward specific forms of IUD seem more complex with differential personality correlates for each specific IUD. These associations need to be replicated.

Orderliness predicts academic performance: behavioural analysis on campus lifestyle

Quantitative understanding of relationships between students' behavioural patterns and academic performances is a significant step towards personalized education. In contrast to previous studies that were mainly based on questionnaire surveys, recent literature suggests that unobtrusive digital data bring us unprecedented opportunities to study students' lifestyles in the campus. In this paper, we collect behavioural records from undergraduate students' (N = 18 960) smart cards and propose two high-level behavioural characters, orderliness and diligence. The former is a novel entropy-based metric that measures the regularity of campus daily life, which is estimated here based on temporal records of taking showers and having meals. Empirical analyses on such large-scale unobtrusive behavioural data demonstrate that academic performance (GPA) is significantly correlated with orderliness. Furthermore, we show that orderliness is an important feature to predict academic performance, which improves the prediction accuracy even in the presence of students' diligence. Based on these analyses, education administrators could quantitatively understand the major factors leading to excellent or poor performance, detect undesirable abnormal behaviours in time and thus implement effective interventions to better guide students' campus lives at an early stage when necessary.

Network Neuroscience and Personality

Personality and individual differences originate from the brain. Despite major advances in the affective and cognitive neurosciences, however, it is still not well understood how personality and single personality traits are represented within the brain. Most research on brain-personality correlates has focused either on morphological aspects of the brain such as increases or decreases in local gray matter volume, or has investigated how personality traits can account for individual differences in activation differences in various tasks. Here, we propose that personality neuroscience can be advanced by adding a network perspective on brain structure and function, an endeavor that we label personality network neuroscience. With the rise of resting-state functional magnetic resonance imaging (MRI), the establishment of connectomics as a theoretical framework for structural and functional connectivity modeling, and recent advancements in the application of mathematical graph theory to brain connectivity data, several new tools and techniques are readily available to be applied in personality neuroscience. The present contribution introduces these concepts, reviews recent progress in their application to the study of individual differences, and explores their potential to advance our understanding of the neural implementation of personality. Trait theorists have long argued that personality traits are biophysical entities that are not mere abstractions of and metaphors for human behavior. Traits are thought to actually exist in the brain, presumably in the form of conceptual nervous systems. A conceptual nervous system refers to the attempt to describe parts of the central nervous system in functional terms with relevance to psychology and behavior. We contend that personality network neuroscience can characterize these conceptual nervous systems on a functional and anatomical level and has the potential do link dispositional neural correlates to actual behavior.

Affective Neuroscience Theory and Personality: An Update

The present work gives a short overview of central aspects of Jaak Panksepp's Affective Neuroscience Theory (AN theory) and its relevance for modern personality neuroscience. In contrast to the widely used Big Five approach to studying and understanding human personality, AN theory provides researchers with a distinct roadmap to the biological basis of personality, including molecular and neuroanatomical candidates, to understand individual differences in human behavior. Such molecular and neuroanatomical brain candidates have been derived by means of electrical brain stimulation and pharmacological challenges, while investigating primary emotional systems anchored in the subcortical mammalian brain. Research results derived from the study of emotions in mammals are also of relevance for humans because ancient layers of our minds-those layers where primary emotions originate-have been homologously conserved across species. From an evolutionary perspective, this makes sense because primal emotions represent "built-in tools for survival" for all mammals. In this context, Montag and Panksepp recently illustrated a potential ancient neurobiological effect by carving out robust associations between individual differences in primary emotions (assessed via self-report) and the Big Five in a cross-cultural study with data from the United States, Germany, and China. These associations together with some ideas derived from MacLean's Triune Brain concept highlighted (a) that primary emotions likely represent the phylogenetically oldest parts of human personality and (b) that primary emotions influence human personality in a bottom-up fashion given their localization in ancient subcortical brain regions. A comment on the work by Montag and Panksepp asked for insights on putative links between primary emotions and facets of the Big Five. Therefore, we provide some first insights into such associations from recent Germany data. In addition, the present work provides a new short version of the Affective Neuroscience Personality Scales to assess individual differences in primary emotions.

Originally Adapted Mobile Application Used for Neuropsychiatric Patients

The potential use of modern mobile devices for medical purposes is huge. Digital mental health tools have mostly tended to use psycho-educational strategies based on treatment orientations developed and validated outside digital health.

The aim of this study was to test the availability of our own original app named “Neuro-game” for evaluation of reaction time in different neuropsychiatric patients. Reaction time is strongly related to the executive brain functions.

The examined sample comprised of 135 neuropsychiatric patients (with epilepsy, depression, general anxiety, psychosis and ADHD) compared with matched 50 healthy persons.

We showed that the average reaction time in neuropsychiatric patients compared with healthy people is not notably different. However, we found significant differences in total hits, total misses and total tries in the performances of ill persons.

The crucial differences in obtained scores are confirmed for age and gender issues.

The most important differences are found in the number of hits, misses and tries in the group of depressed, followed by psychotic and ADHD patients, while anxious ones showed pretty normal parameters.

All tested parameters are remarkably different for the epileptic group vs. healthy people.

The T-test for epileptic vs. healthy people showed noteworthy differences for total tries, total misses, and total hits, but the average time reaction did not differ significantly.

In comparison with other psychometric assessments, this approach by using mobile phones seemed more practical, available anywhere (not only in medical settings), less time consuming and quite interesting for all ages.

The details of past actions on a smartphone touchscreen are reflected by intrinsic sensorimotor dynamics

Unconstrained day-to-day activities are difficult to quantify and how the corresponding movements shape the brain remain unclear. Here, we recorded all touchscreen smartphone interactions at a sub-second precision and show that the unconstrained day-to-day behavior captured on the phone reflects in the simple sensorimotor computations measured in the laboratory. The behavioral diversity on the phone, the speed of interactions, the amount of social & non-social interactions, all uniquely influenced the trial-to-trial motor variability used to measure the amount of intrinsic neuronal noise. Surprisingly, both the motor performance and the early somatosensory cortical signals (assessed using EEG in passive conditions) became noisier with increased social interactions. Inter-individual differences in how people use the smartphone can help thus decompose the structure of low-level sensorimotor computations.

Internet Communication Disorder and the structure of the human brain: initial insights on WeChat addiction

WeChat represents one of the most popular smartphone-based applications for communication. Although the application provides several useful features that simplify daily life, a growing number of users spend excessive amounts of time on the application. This may lead to interferences with everyday life and even to addictive patterns of use. In the context of the ongoing discussion on Internet Communication Disorder (ICD), the present study aimed to better characterize the addictive potential of communication applications, using WeChat as an example, by examining associations between individual variations in tendencies towards WeChat addiction and brain structural variations in fronto-striatal-limbic brain regions. To this end levels of addictive tendencies, frequency of use and structural MRI data were assessed in n = 61 healthy participants. Higher tendencies towards WeChat addiction were associated with smaller gray matter volumes of the subgenual anterior cingulate cortex, a key region for monitoring and regulatory control in neural networks underlying addictive behaviors. Moreover, a higher frequency of the paying function was associated with smaller nucleus accumbens volumes. Findings were robust after controlling for levels of anxiety and depression. The present results are in line with previous findings in substance and behavioral addictions, and suggest a similar neurobiological basis in ICD.

Smartphone addiction, daily interruptions and self-reported productivity

The advent of the smartphone has dramatically altered how we communicate, navigate, work and entertain ourselves. While the advantages of this new technology are clear, constant use may also bring negative consequences, such as a loss of productivity due to interruptions in work life. A link between smartphone overuse and loss of productivity has often been hypothesized, but empirical evidence on this question is scarce. The present study addressed this question by collecting self-report data from N = 262 participants, assessing private and work-related smartphone use, smartphone addiction and self-rated productivity. Our results indicate a moderate relationship between smartphone addiction and a self-reported decrease in productivity due to spending time on the smartphone during work, as well as with the number of work hours lost to smartphone use. Smartphone addiction was also related to a greater amount of leisure time spent on the smartphone and was strongly related to a negative impact of smartphone use on daily non-work related activities. These data support the idea that tendencies towards smartphone addiction and overt checking of the smartphone could result in less productivity both in the workplace and at home. Results are discussed in relation to productivity and technostress.

The Use of Smartphone in Medical Practice

In this review we present some data about the use of mobile phones in medical practice. The results of over hundred studies cited in PubMed during the last few years have been discussed. The article gives background connected with a project in the Macedonian Academy of Sciences and Arts referring to a personal mobile phone application named "Neurogame" which is currently constructed to evaluate motor skills related to attention and concentration in different samples of people.

Commuting, Life-Satisfaction and Internet Addiction

The focus of the present work was on the association between commuting (business and private), life satisfaction, stress, and (over-) use of the Internet. Considering that digital devices are omnipresent in buses and trains, no study has yet investigated if commuting contributes to the development of Internet addiction. Overall, N = 5039 participants (N = 3477 females, age M = 26.79, SD = 10.68) took part in an online survey providing information regarding their commuting behavior, Internet addiction, personality, life satisfaction, and stress perception. Our findings are as follows: Personality seems to be less suitable to differentiate between commuter and non-commuter groups, which is possibly due to commuters often not having a choice but simply must accept offered job opportunities at distant locations. Second, the highest levels of satisfaction were found with income and lodging in the group commuting for business purposes. This might be related to the fact that commuting results in higher salaries (hence also better and more expensive housing style) due to having a job in another city which might exceed job opportunities at one’s own living location. Third, within the business-commuters as well as in the private-commuter groups, females had significantly higher levels of stress than males. This association was not present in the non-commuter group. For females, commuting seems to be a higher burden and more stressful than for males, regardless of whether they commute for business or private reasons. Finally, we observed an association between higher stress perception (more negative attitude towards commuting) and Internet addiction. This finding suggests that some commuters try to compensate their perceived stress with increased Internet use.

Users of the main smartphone operating systems (iOS, Android) differ only little in personality

The increasingly widespread use of mobile phone applications (apps) as research tools and cost-effective means of vast data collection raises new methodological challenges. In recent years, it has become a common practice for scientists to design apps that run only on a single operating system, thereby excluding large numbers of users who use a different operating system. However, empirical evidence investigating any selection biases that might result thereof is scarce. Henceforth, we conducted two studies drawing from a large multi-national (Study 1; N = 1,081) and a German-speaking sample (Study 2; N = 2,438). As such Study 1 compared iOS and Android users across an array of key personality traits (i.e., well-being, self-esteem, willingness to take risks, optimism, pessimism, Dark Triad, and the Big Five). Focusing on Big Five personality traits in a broader scope, in addition to smartphone users, Study 2 also examined users of the main computer operating systems (i.e., Mac OS, Windows). In both studies, very few significant differences were found, all of which were of small or even tiny effect size mostly disappearing after sociodemographics had been controlled for. Taken together, minor differences in personality seem to exist, but they are of small to negligible effect size (ranging from OR = 0.919 to 1.344 (Study 1), η_p² = .005 to .036 (Study 2), respectively) and may reflect differences in sociodemographic composition, rather than operating system of smartphone users.