Understanding workaholics' motivations: a self-determination perspective

In order to explain the diverging well-being outcomes of workaholism, this study aimed to examine the motivational orientations that may fuel the two main components of workaholism (i.e. working excessively and working compulsively). Drawing on Self-Determination Theory, both autonomous and controlled motivation were suggested to drive excessive work, which therefore was expected to relate positively to both well-being (i.e. vigor) and ill-health (i.e. exhaustion). Compulsive work, in contrast, was hypothesized to originate exclusively out of controlled motivation and therefore to only associate positively with ill-being. Structural equation modeling in a heterogeneous sample of Belgian white-collar workers (N=370) confirmed that autonomous motivation associated positively with excessive work, which then related positively to vigor. Controlled motivation correlated positively with compulsive work, which therefore related positively with exhaustion. The hypothesized path from controlled motivation to exhaustion through excessive work was not corroborated. In general, the findings suggest that primarily compulsive work yields associations with ill-being, since it may stem from a qualitatively inferior type of motivation

On the impact of video stalling and video quality in the case of camera switching during adaptive streaming of sports content

The widespread usage of second screens, in combination with mobile video streaming technologies like HTTP Adaptive Streaming (HAS), enable new means for taking end-users' Quality of Experience (QoE) to the next level. For sports events, these technological evolutions can, for example, enhance the overall engagement of remote fans or give them more control over the content. In this paper, we consider the case of adaptively streaming multi-camera sports content to tablet devices, enabling the end-user to dynamically switch cameras. Our goal is to subjectively evaluate the trade-off between video stalling duration (as a result of requesting another camera feed) and initial video quality of the new feed. Our results show that short video stallings do not significantly influence overall quality ratings, that quality perception is highly influenced by the video quality at the moment of camera switching and that large quality fluctuations should be avoided

The presence of extracellular microRNAs in the media of cultured Drosophila cells

While regulatory RNA pathways, such as RNAi, have commonly been described at an intracellular level, studies investigating extracellular RNA species in insects are lacking. In the present study, we demonstrate the presence of extracellular microRNAs (miRNAs) in the cell-free conditioned media of two Drosophila cell lines. More specifically, by means of quantitative real-time PCR (qRT-PCR), we analysed the presence of twelve miRNAs in extracellular vesicles (EVs) and in extracellular Argonaute-1 containing immunoprecipitates, obtained from the cell-free conditioned media of S2 and Cl. 8 cell cultures. Next-generation RNA-sequencing data confirmed our qRT-PCR results and provided evidence for selective miRNA secretion in EVs. To our knowledge, this is the first time that miRNAs have been identified in the extracellular medium of cultured cells derived from insects, the most speciose group of animals

Data mining in the development of mobile health apps : assessing in-app navigation through Markov chain analysis

Background: Mobile apps generate vast amounts of user data. In the mobile health (mHealth) domain, researchers are increasingly discovering the opportunities of log data to assess the usage of their mobile apps. To date, however, the analysis of these data are often limited to descriptive statistics. Using data mining techniques, log data can offer significantly deeper insights. Objective: The purpose of this study was to assess how Markov Chain and sequence clustering analysis can be used to find meaningful usage patterns of mHealth apps. Methods: Using the data of a 25-day field trial (n=22) of the Start2Cycle app, an app developed to encourage recreational cycling in adults, a transition matrix between the different pages of the app was composed. From this matrix, a Markov Chain was constructed, enabling intuitive user behavior analysis. Results: Through visual inspection of the transitions, 3 types of app use could be distinguished (route tracking, gamification, and bug reporting). Markov Chain-based sequence clustering was subsequently used to demonstrate how clusters of session types can otherwise be obtained. Conclusions: Using Markov Chains to assess in-app navigation presents a sound method to evaluate use of mHealth interventions. The insights can be used to evaluate app use and improve user experience

Subjective quality assessment of longer duration video sequences delivered over HTTP adaptive streaming to tablet devices

HTTP adaptive streaming facilitates video streaming to mobile devices connected through heterogeneous networks without the need for a dedicated streaming infrastructure. By splitting different encoded versions of the same video into small segments, clients can continuously decide which segments to download based on available network resources and device characteristics. These encoded versions can, for example, differ in terms of bitrate and spatial or temporal resolution. However, as a result of dynamically selecting video segments, perceived video quality can fluctuate during playback which will impact end-users' quality of experience. Subjective studies have already been conducted to assess the influence of video delivery using HTTP Adaptive Streaming to mobile devices. Nevertheless, existing studies are limited to the evaluation of short video sequences in controlled environments. Research has already shown that video duration and assessment environment influence quality perception. Therefore, in this article, we go beyond the traditional ways for subjective quality evaluation by conducting novel experiments on tablet devices in more ecologically valid testing environments using longer duration video sequences. As such, we want to mimic realistic viewing behavior as much as possible. Our results show that both video content and the range of quality switches significantly influence end-users' rating behavior. In general, quality level switches are only perceived in high motion sequences or in case switching occurs between high and low quality video segments. Moreover, we also found that video stallings should be avoided during playback at all times