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A recent study has implicated the nucleus accumbens of the ventral striatum in explaining why online-users spend time on the social network platform Facebook. Here, higher activity of the nucleus accumbens was associated with gaining reputation on social media. In the present study, we touched a related research field. We recorded the actual Facebook usage of N = 62 participants on their smartphones over the course of five weeks and correlated summary measures of Facebook use with gray matter volume of the nucleus accumbens. It appeared, that in particular higher daily frequency of checking Facebook on the smartphone was robustly linked with smaller gray matter volumes of the nucleus accumbens. The present study gives additional support for the rewarding aspects of Facebook usage. Moreover, it shows the feasibility to include real life behavior variables in human neuroscientific research. [ABSTRACT FROM AUTHOR]

Relational Keyword Search (R-KWS) provides an intuitive way to query relational data without requiring SQL, or knowledge of the underlying schema. In this article we describe a comprehensive framework for R-KWS covering snapshot queries on conventional tables and continuous queries on relational streams. Our contributions are summarized as follows: (i) We provide formal semantics, addressing the temporal validity and order of results, spanning uniformly over tables and streams; (ii) we investigate two general methodologies for query processing, graph based and operator based, that resolve several problems of previous approaches; and (iii) we develop a range of algorithms and optimizations covering both methodologies. We demonstrate the effectiveness of R-KWS, as well as the significant performance benefits of the proposed techniques, through extensive experiments with static and streaming datasets. [ABSTRACT FROM AUTHOR]

Computing temporal aggregates is an important but costly operation for applications that maintain time-evolving data (data warehouses, temporal databases, etc.) Due to the large volume of such data, performance improvements for temporal aggregate queries are critical. Previous approaches have aggregate predicates that involve only the time dimension. In this article we examine techniques to compute temporal aggregates that include key-range predicates as well (range-temporal aggregates). In particular we concentrate on the SUM aggregate, while COUNT is a special case. To handle arbitrary key ranges, previous methods would need to keep a separate index for every possible key range. We propose an approach based on a new index structure called the Multiversion SB-Tree, which incorporates features from both the SB-Tree and the Multiversion B+-tree, to handle arbitrary key-range temporal aggregate queries. We analyze the performance of our approach and present experimental results that show its efficiency. Furthermore, we address a novel and practical variation called functional range-temporal aggregates. Here, the value of any record is a function over time. The meaning of aggregates is altered such that the contribution of a record to the aggregate result is proportional to the size of the intersection between the record's time interval and the query time interval. Both analytical and experimental results show the efficiency of our result. [ABSTRACT FROM AUTHOR]

The present paper provides insight into an emerging research discipline called Psychoinformatics. In the context of Psychoinformatics, we emphasize the cooperation between the disciplines of psychology and computer science in handling large data sets derived from heavily used devices, such as smartphones or online social network sites, in order to shed light on a large number of psychological traits, including personality and mood. New challenges await psychologists in light of the resulting “Big Data” sets, because classic psychological methods will only in part be able to analyze this data derived from ubiquitous mobile devices, as well as other everyday technologies. As a consequence, psychologists must enrich their scientific methods through the inclusion of methods from informatics. The paper provides a brief review of one area of this research field, dealing mainly with social networks and smartphones. Moreover, we highlight how data derived from Psychoinformatics can be combined in a meaningful way with data from human neuroscience. We close the paper with some observations of areas for future research and problems that require consideration within this new discipline. [ABSTRACT FROM AUTHOR]

Virtually everybody would agree that life satisfaction is of immense importance in everyday life. Thus, it is not surprising that a considerable amount of research using many different methodological approaches has investigated what the best predictors of life satisfaction are. In the present study, we have focused on several key potential influences on life satisfaction including bottom-up and top-down models, cross-cultural effects, and demographic variables. In four independent (large scale) surveys with sample sizes ranging from N = 488 to 40,297, we examined the associations between life satisfaction and various related variables. Our findings demonstrate that prediction of overall life satisfaction works best when including information about specific life satisfaction variables. From this perspective, satisfaction with leisure showed the highest impact on overall life satisfaction in our European samples. Personality was also robustly associated with life satisfaction, but only when life satisfaction variables were not included in the regression model. These findings could be replicated in all four independent samples, but it was also demonstrated that the relevance of life satisfaction variables changed under the influence of cross-cultural effects. [ABSTRACT FROM AUTHOR]

Recommendations of the Expert Group on the Prevention of Internet-related Disorders Abstract. Background: Research on Internet-related Disorders is still in its infancies. This is especially true for preventive efforts and early intervention. Method: Initiated by the German Drug Commissioner, Mrs. Marlene Mortler, a group of experts developed recommendations on the prevention of Internet-related Disorders on behalf of the Council of Drugs and Addiction of the German federal government. The recommendations were consented within the group of experts. Results: Currently, the prevention of Internet-related Disorders is not sufficiently based on scientific evidence. Therefore, the efficacy of existing programs is not proven. In addition, most programs focus on behavior-oriented primary prevention and rarely on early interventions. The potential of structural prevention is rarely exploited yet. From concepts of preventive efforts in other areas and in general health promotion some potentially efficacious measures can be derived. These often relate to concepts on the prevention of addiction. It is urgently demanded that efficacious concepts are considered when planning prevention and early intervention of Internet-related Disorders. Currently, the supply of preventive measures in this area can be regarded as deficient. Among others, the expert group gives the following recommendations: 1) Preventive measures should be as close as possible geared to scientific evidence. Only efficacious programs should be implemented nationwide. 2) Efficacious measures on early intervention that can reach a large part of the target group should be promoted. 3) The potential of intensifying structural prevention efforts with regard to ways of protecting minors, restrictions of media use, product design, advertising restrictions, and conditions of the environment should be considered. 4) Research in the areas of mechanisms and prevention of Internet-related disorders has to be promoted urgently. 5) It is recommended to establish a center or network of competence and an expert-commission that can serve as first-choice main-contact by stakeholders (federal states, municipalities, institutions) for investigating measures or giving recommendations in the areas of prevention and early interventions. 6) Regional coordinating centers responsible for providing preventive programs as well as concepts of advanced training and networking are of importance and should be aimed for. These coordinating centers should cooperate with the center/network of competence and the expert-commission. 7) An early warning system to promptly identify new games and apps with high addiction potential should be established. [ABSTRACT FROM AUTHOR]

Psychologists and psychiatrists commonly rely on self-reports or interviews to diagnose or treat behavioral addictions. The present study introduces a novel source of data: recordings of the actual problem behavior under investigation. A total of N = 58 participants were asked to fill in a questionnaire measuring problematic mobile phone behavior featuring several questions on weekly phone usage. After filling in the questionnaire, all participants received an application to be installed on their smartphones, which recorded their phone usage for five weeks. The analyses revealed that weekly phone usage in hours was overestimated; in contrast, numbers of call and text message related variables were underestimated. Importantly, several associations between actual usage and being addicted to mobile phones could be derived exclusively from the recorded behavior, but not from self-report variables. The study demonstrates the potential benefit to include methods of psychoinformatics in the diagnosis and treatment of problematic mobile phone use. [ABSTRACT FROM AUTHOR]

Background: Mounting evidence shows that smartphone usage heavily disrupts our work life and social activities. Moreover, it is possible that overuse could resemble addictive tendencies. A key contributing factor to smartphone overuse seems to be usage of the messaging application WhatsApp. Although WhatsApp is one of the most commonly used communication applications on smartphones, research in this area is scarce. Given the huge societal debate on the impact of smartphone usage on our daily lives, the present study undertook a large-scale investigation in order to provide numbers on smartphone usage generally--and use of WhatsApp in particular, with the aim of providing a basis for a scientific debate. Methods: In a large sample of N = 2,418 users, we recorded WhatsApp behaviour over a 4 week period. Results: Our data show that use of WhatsApp accounted for 19.83% (= 32.11 min) of all smartphone behaviour (compare: Facebook only 9.38% = 15.19 min). The mean of general daily smartphone usage was 161.95 min. Females used WhatsApp for significantly longer periods of time than males and younger age was associated with longer duration of WhatsApp use. While the personality trait Extraversion was positively associated with daily WhatsApp use, Conscientiousness showed an inverse correlation with the length of daily WhatsApp use. Conclusions: The numbers on smartphone usage in the present study show that the smartphone dominates our daily life. In particular WhatsApp is a driving force, here. Given the length of daily smartphone and WhatsApp usage, more studies need to be conducted to better understand smartphone usage. [ABSTRACT FROM AUTHOR]

Background: Mounting evidence shows that smartphone usage heavily disrupts our work life and social activities. Moreover, it is possible that overuse could resemble addictive tendencies. A key contributing factor to smartphone overuse seems to be usage of the messaging application WhatsApp. Although WhatsApp is one of the most commonly used communication applications on smartphones, research in this area is scarce. Given the huge societal debate on the impact of smartphone usage on our daily lives, the present study undertook a large-scale investigation in order to provide numbers on smartphone usage generally--and use of WhatsApp in particular, with the aim of providing a basis for a scientific debate. Methods: In a large sample of N = 2,418 users, we recorded WhatsApp behaviour over a 4 week period. Results: Our data show that use of WhatsApp accounted for 19.83% (= 32.11 min) of all smartphone behaviour (compare: Facebook only 9.38% = 15.19 min). The mean of general daily smartphone usage was 161.95 min. Females used WhatsApp for significantly longer periods of time than males and younger age was associated with longer duration of WhatsApp use. While the personality trait Extraversion was positively associated with daily WhatsApp use, Conscientiousness showed an inverse correlation with the length of daily WhatsApp use. Conclusions: The numbers on smartphone usage in the present study show that the smartphone dominates our daily life. In particular WhatsApp is a driving force, here. Given the length of daily smartphone and WhatsApp usage, more studies need to be conducted to better understand smartphone usage. [ABSTRACT FROM AUTHOR]