#EARLY BIRD VS NIGHT OWL MEME ANDROID#
#EARLY BIRD VS NIGHT OWL MEME SOFTWARE#

#EARLY BIRD VS NIGHT OWL MEME ANDROID#

Smartphone screen time was assessed by the free Android application Quality Time. Problematic smartphone use was measured by the short version of the Smartphone Addiction Scale. The participants were students of medicine of both sexes. The aim of our study was to measure the level of problematic smartphone use in a student population through the assessment of the smartphone screen time and the determination of the student chronotype, as well as through the correlation between these variables. The global trend of an increase in the frequency of usage of smartphones, that is, prolonged screen time, is closely related to problematic smartphone use. This study describes a proof-of-concept approach for forensic automation on online social networks.īesides numerous advantages and commodities offered by smartphones, there are obvious unhealthy effects. These operators are implemented using Twitter ontology and tested through a case study.

#EARLY BIRD VS NIGHT OWL MEME SOFTWARE#

These operators can be embedded in software tools to help the investigators draw realistic conclusions. Finally, we propose a set of analysis operators based on domain correlations. Here, we introduce a multi-layer automation approach that addresses the automation issues from collection to evidence analysis in online social network forensics. Automating digital forensics is not exclusively a technical problem the technical issues are always coupled with privacy and legal matters. Therefore, it is critical to develop solutions and tools that can assist investigators in their work and decision making. However, accessing this publicly available information for legal use is technically challenging and legally intricate due to heterogeneous and unstructured data and privacy laws, thus generating massive workloads of cognitively demanding cases for investigators. These conclusions may contribute to improving sleep intervention in this population.Ĭurrently, law enforcement and legal consultants are heavily utilizing social media platforms to easily access data associated with the preparators of illegitimate events. A possible explanation for these findings is that nighttime social media might be used as a strategy to cope with aversive cognitive states.

These results suggest that worry and FoMO may potentially affect sleep quality by increasing cognitive pre-sleep arousal and nighttime social media. Nighttime social media use independently predicted poor sleep quality (H4). Both FoMO and worry predicted higher levels of cognitive pre-sleep arousal (H2) and nighttime social media use (H3). Nighttime social media and FoMO were associated with rumination, worry (H1) and cognitive pre-sleep arousal. Multiple linear regression analyses were performed. Measures of sleep quality, morningness/eveningness, cognitive pre-sleep arousal, worry, rumination, FoMO, nighttime screen, and social media use were collected online or in pencil-paper format. Participants were 525 university students, ranging in age from 18 to 64 (M = 22.39, SD = 5.62). The present correlational study followed a cross-sectional design. This study explored the relationships between nighttime social media, sleep quality, FoMO, cognitive pre-sleep arousal, and maladaptive cognitive emotion regulation (i.e., worry/rumination). The use of nighttime social media to cope with other aversive cognitive states (i.e., worry/rumination), their relationship with FoMO, and these variables' association with sleep are not fully understood. Research shows that nighttime social media is negatively associated with sleep quality and that it might be utilized to cope with aversive psychological states related to cognitive pre-sleep arousal (i.e., transdiagnostic psychopathology variables, referring to maladaptive repetitive thought), namely Fear of Missing Out (FoMO).

Early bird vs night owl meme