Rayna Sariyska

Background: Social communication via instant messaging (IM) and social networking (SN) apps makes up a large part of the time that smartphone users spend on their devices. Previous research has indicated that the excessive use of these apps is positively associated with problematic smartphone use behaviors. In particular, image-based SN apps, such as Instagram (Facebook Inc) and Snapchat (Snap Inc), have been shown to exert stronger detrimental effects than those exerted by traditional apps, such as Facebook (Facebook Inc) and Twitter (Twitter Inc). Objective: In this study, we investigated the correlation between individuals’ tendencies toward smartphone use disorder (SmUD) and objective measures of the frequency of smartphone usage. Additionally, we put to test the hypothesis that the pathway linking the frequency of actual smartphone usage to self-reported tendencies toward SmUD was mediated by the increased frequency of IM and SN app usage. Methods: We recruited a sample of 124 adult smartphone users (females: 78/124, 62.9%; age: mean 23.84 years, SD 8.29 years) and collected objective information about the frequency of smartphone and SN app usage over 1 week. Participants also filled in a self-report measure for assessing the multiple components of tendencies toward SmUD. Bivariate associations were investigated by using Spearman correlation analyses. A parallel mediation analysis was conducted via multiple regression analysis. Results: The frequency of smartphone usage, as well as the use of IM apps (Messenger, Telegram, and WhatsApp [Facebook Inc]), Facebook, and image-based apps (Instagram and Snapchat), had significant positive associations with at least 1 component of SmUD, and the cyberspace-oriented relationships factor exhibited the strongest associations overall. We found support for an indirect effect that linked actual smartphone usage to SmUD tendencies via the frequency of the use of image-based SN apps. Conclusions: Our novel results shed light on the factors that promote SmUD tendencies and essentially indicate that image-based SN apps seem to be more strongly associated with problematic smartphone behaviors compared to IM apps and traditional SN apps, such as Facebook.

BACKGROUND Social communication via instant messaging (IM) and social networking (SN) apps makes up a large part of the time that smartphone users spend on their devices. Previous research has indicated that the excessive use of these apps is positively associated with problematic smartphone use behaviors. In particular, image-based SN apps, such as Instagram (Facebook Inc) and Snapchat (Snap Inc), have been shown to exert stronger detrimental effects than those exerted by traditional apps, such as Facebook (Facebook Inc) and Twitter (Twitter Inc). OBJECTIVE In this study, we investigated the correlation between individuals’ tendencies toward smartphone use disorder (SmUD) and objective measures of the frequency of smartphone usage. Additionally, we put to test the hypothesis that the pathway linking the frequency of actual smartphone usage to self-reported tendencies toward SmUD was mediated by the increased frequency of IM and SN app usage. METHODS We recruited a sample of 124 adult smartphone users (females: 78/124, 62.9%; age: mean 23.84 years, SD 8.29 years) and collected objective information about the frequency of smartphone and SN app usage over 1 week. Participants also filled in a self-report measure for assessing the multiple components of tendencies toward SmUD. Bivariate associations were investigated by using Spearman correlation analyses. A parallel mediation analysis was conducted via multiple regression analysis. RESULTS The frequency of smartphone usage, as well as the use of IM apps (Messenger, Telegram, and WhatsApp [Facebook Inc]), Facebook, and image-based apps (Instagram and Snapchat), had significant positive associations with at least 1 component of SmUD, and the cyberspace-oriented relationships factor exhibited the strongest associations overall. We found support for an indirect effect that linked actual smartphone usage to SmUD tendencies via the frequency of the use of image-based SN apps. CONCLUSIONS Our novel results shed light on the factors that promote SmUD tendencies and essentially indicate that image-based SN apps seem to be more strongly associated with problematic smartphone behaviors compared to IM apps and traditional SN apps, such as Facebook.

In the context of (digital) human–machine interaction, people are increasingly dealing with artificial intelligence in everyday life. Through this, we observe humans who embrace technological advances with a positive attitude. Others, however, are particularly sceptical and claim to foresee substantial problems arising from such uses of technology. The aim of the present study was to introduce a short measure to assess the Attitude Towards Artificial Intelligence (ATAI scale) in the German, Chinese, and English languages. Participants from Germany (N = 461; 345 females), China (N = 413; 145 females), and the UK (N = 84; 65 females) completed the ATAI scale, for which the factorial structure was tested and compared between the samples. Participants from Germany and China were additionally asked about their willingness to interact with/use self-driving cars, Siri, Alexa, the social robot Pepper, and the humanoid robot Erica, which are representatives of popular artificial intelligence products. The results showed that the five-item ATAI scale comprises two negatively associated factors assessing (1) acceptance and (2) fear of artificial intelligence. The factor structure was found to be similar across the German, Chinese, and UK samples. Additionally, the ATAI scale was validated, as the items on the willingness to use specific artificial intelligence products were positively associated with the ATAI Acceptance scale and negatively with the ATAI Fear scale, in both the German and Chinese samples. In conclusion we introduce a short, reliable, and valid measure on the attitude towards artificial intelligence in German, Chinese, and English language.

Exaggerated reactivity to drug-cues and emotional dysregulations represent key symptoms of early stages of substance use disorders. The diagnostic criteria for (Internet) Gaming Disorder strongly resemble symptoms for substance-related addictions. However, previous cross-sections studies revealed inconsistent results with respect to neural cue reactivity and emotional dysregulations in these populations. To this end the present fMRI study applied a combined cross-sectional and prospective longitudinal design in excessive online gamers (n=37) and gaming-naïve controls (n=67). To separate gaming-associated changes from predisposing factors, gaming-naive subjects were randomly assigned to 6 weeks of daily Internet gaming or a non-gaming condition. At baseline and after the training subjects underwent an fMRI paradigm presenting gaming-related cues and non-gaming related emotional stimuli. Cross-sectional comparisons revealed gaming-cue specific enhanced valence attribution and neural reactivity in a parietal network, including the posterior cingulate/precuneus in excessive gamers as compared to gaming naïve-controls. Prospective analysis revealed that six weeks of gaming elevated valence ratings as well as neural cue-reactivity in a similar parietal network, specifically the posterior cingulate/precuneus in previously gaming-naïve controls. Together, the prospective longitudinal design did not reveal supporting evidence for altered emotional processing of non-gaming associated stimuli in excessive gamers while convergent evidence for increased emotional and neural reactivity to gaming-associated stimuli was observed. Findings suggest that exaggerated neural reactivity in posterior parietal regions engaged in self-referential processing already occur during early stages of regular gaming probably promoting continued engagement in gaming behavior.

The awareness of the consequences of consuming animal products for the environment and one’s own health has been growing in recent years. The aim of the present research project was to examine the relationship between individual differences in biologically rooted primary emotional systems arising from phylogenetically old brain areas and dietary habits including being a vegan/vegetarian or omnivore (Study 1). Additionally, the link between the Dark Triad personality traits and dietary habits was investigated (also Study 1). In Study 2 it was aimed to replicate the associations between the Dark Triad traits and dietary habits in a new sample. In total 1140 (Study 1) and 444 (Study 2) participants took part in the research project. The Affective Neuroscience Personality Scales (ANPS) were applied to assess individual differences in six primary emotional systems. The Short Dark Triad Scale (SD3) was administered to assess individual differences in Machiavellianism, psychopathy and narcissism. The eating style of participants was measured with the Eating Behavior Questionnaire (EBQ). Results of Study 1 demonstrated higher CARE, SADNESS and spirituality scores, and lower PLAY scores in vegans/vegetarians than in omnivores. However, after the sex of the participants was included in the model, the effect on CARE got weaker. Additionally, omnivores scored higher on Machiavellianism, however, this association disappeared when sex was added to the model. In Study 2, higher scores in Machiavellianism, narcissism and psychopathy were reported for the group of omnivores compared to vegans/vegetarians, however, those effects got weaker or disappeared after the sex of participants was added to the model. The present research project adds to the literature by investigating the ANPS model and the Dark Triad of personality in the context of eating style for the first time. The findings of these two studies might help to better understand how people following different types of diet, might differ in their personalities.

Background: ‘Gaming Disorder’ (GD) has received increased medical attention and official recognition from both the American Psychiatric Association (APA) and the World Health Organization (WHO). Although these two medical organizations have independently developed promising clinical diagnostic frameworks to assess disordered gaming, little is known about how these frameworks compare at different psychometric levels in terms of producing consistent outcomes in the assessment of GD. Methods: A sample of 1429 German gamers (Mean_age = 29.74 years; SD = 12.37 years) completed an online survey including measures on different psychopathological symptoms (depression, loneliness and attention problems), gaming motives and disordered gaming according to the WHO and APA frameworks. Results: The findings suggest the existence of minor discrepancies in the estimation of prevalence rates of GD according among the two frameworks. Nevertheless, both diagnostic frameworks are fairly consistent in the psychometric prediction of GD in relation to gaming motives and psychopathological symptoms. The findings underscore the role of key gaming motives as risk factors and protective factors across both diagnostic frameworks. Finally, the study provides support for the WHO diagnostic framework for GD and its measurement with the German Gaming Disorder Test (GDT). The findings and their implications are further discussed in terms of clinical relevance.

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.

In the present study, we investigated individual differences in the motivation for Facebook use. In total N = 736 participants from Europe and Asia took part in the study. They filled in the Facebook questionnaire (FQ), including the two factors Attitude toward Facebook and Online Sociability, and the Unified Motive Scale (UMS-3), measuring the motives Achievement, Affiliation, Intimacy, Power, and Fear. The results showed that the Attitude toward Facebook was more positive in the subsample from Asia, but no differences could be found between the Asian and European sample with respect to the frequency of use of different activities on Facebook. The motives Fear, Power, Affiliation, and Intimacy significantly predicted the FQ factor Attitudes. Furthermore, the Attitude toward Facebook mediated the associations between the motives Power/Affiliation and Online Sociability. However, these results were only found for the European sample. The associations found suggest the important role of different motives such as Power/Affiliation for the study of Facebook use. The present work shows the possibility of motivational factors for Facebook use to differ depending on the culture. The study adds to the literature by investigating a classic motivation theory in the context of Facebook use.

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.