Child Mind Institute - Detect Sleep States
\nProblematic Internet use (PIU), personality profiles and emotion dysregulation in a cohort of young adults: trajectories from risky behaviors to addiction
\nAuthors: Mauro Pettorruso, Stephanie Valle, Elizabeth Cavic, Giovanni Martinotti,Massimo di Giannantonio, Jon E. Grant - https://doi.org/10.1016/j.psychres.2020.113036
\n\"11.2% of a large sample of non-treatment seeking young adults met criteria for problematic Internet use.\"
\n\"Young adults with problematic Internet use exhibited lower novelty seeking, harm avoidance, and reward dependence.\"
\n\"Problematic Internet use was associated with more pronounced motor impulsivity and problems with emotional regulation.\"
\n\"Problematic Internet Use (PIU) encloses excessive online activities (like video gaming, social media use, web-streaming, pornography viewing, buying). Despite its psychological burden, risk factors related to PIU remain still unclear. In the present study the authors explored the role of personality traits and emotion dysregulation as potential vulnerability factors for PIU. In a sample of American young adults with different PIU risk levels (established through the Internet Addiction Diagnostic Questionnaire), we administered the Tridimensional Personality Questionnaire (TPQ), the Difficulties in Emotion Regulation Scale (DERS), the Barratt Impulsiveness Scale, the Hamilton Depression Rating Scale, the Hamilton Anxiety Rating Scale.\"
\n\"PIU participants were more likely to report lower TPQ scores in novelty seeking, harm avoidance and reward dependence. Moreover, DERS total scores significantly differed across PIU-risk groups, along with a progressively higher occurrence of depression, anxiety and impulsivity. These results preliminarily support the hypothesis of PIU as a mainly behavior aimed at ‘escaping’ from negative affects. Besides confirming the role of some personality traits and emotional dysregulation, the authors proposed the concept of risk-trajectories to monitor and prevent the emergence of PIU. Gaining more insight into PIU vulnerability factors may allow us to establish targeted interventions to cope with emotion dysregulation and negative affects.\"
\n\n\"From the use of accelerometers, it's possible to estimate different variables related to sleep, such as duration and efficiency. For this, The authors have used the Heuristic algorithm, looking at Distribution of Change in z-Angle presented by Van Hees (2018). This algorithm identifies the longest period of inactivity within 24 hours, with the least number of interruptions, classifying as a sleep period.\"
\nhttps://eleva.ufsc.br/en/acelerometros/
\nIntensity Thresholds on Raw Acceleration Data: Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) Approaches
\nCitation: Bakrania K, Yates T, Rowlands AV, Esliger DW, Bunnewell S, Sanders J, et al. (2016) Intensity Thresholds on Raw Acceleration Data: Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) Approaches. PLoS ONE 11(10): e0164045. https://doi.org/10.1371/journal.pone.0164045
\n\" To develop and internally-validate Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) thresholds for separating sedentary behaviours from common light-intensity physical activities using raw acceleration data collected from both hip- and wrist-worn tri-axial accelerometers; and to compare and evaluate the performances between the ENMO and MAD metrics.\"
\nChild Mind Institute - Detect Sleep States
\nProblematic Internet use (PIU), personality profiles and emotion dysregulation in a cohort of young adults: trajectories from risky behaviors to addiction
\nAuthors: Mauro Pettorruso, Stephanie Valle, Elizabeth Cavic, Giovanni Martinotti,Massimo di Giannantonio, Jon E. Grant - https://doi.org/10.1016/j.psychres.2020.113036
\n\"11.2% of a large sample of non-treatment seeking young adults met criteria for problematic Internet use.\"
\n\"Young adults with problematic Internet use exhibited lower novelty seeking, harm avoidance, and reward dependence.\"
\n\"Problematic Internet use was associated with more pronounced motor impulsivity and problems with emotional regulation.\"
\n\"Problematic Internet Use (PIU) encloses excessive online activities (like video gaming, social media use, web-streaming, pornography viewing, buying). Despite its psychological burden, risk factors related to PIU remain still unclear. In the present study the authors explored the role of personality traits and emotion dysregulation as potential vulnerability factors for PIU. In a sample of American young adults with different PIU risk levels (established through the Internet Addiction Diagnostic Questionnaire), we administered the Tridimensional Personality Questionnaire (TPQ), the Difficulties in Emotion Regulation Scale (DERS), the Barratt Impulsiveness Scale, the Hamilton Depression Rating Scale, the Hamilton Anxiety Rating Scale.\"
\n\"PIU participants were more likely to report lower TPQ scores in novelty seeking, harm avoidance and reward dependence. Moreover, DERS total scores significantly differed across PIU-risk groups, along with a progressively higher occurrence of depression, anxiety and impulsivity. These results preliminarily support the hypothesis of PIU as a mainly behavior aimed at ‘escaping’ from negative affects. Besides confirming the role of some personality traits and emotional dysregulation, the authors proposed the concept of risk-trajectories to monitor and prevent the emergence of PIU. Gaining more insight into PIU vulnerability factors may allow us to establish targeted interventions to cope with emotion dysregulation and negative affects.\"
\n\n\"From the use of accelerometers, it's possible to estimate different variables related to sleep, such as duration and efficiency. For this, The authors have used the Heuristic algorithm, looking at Distribution of Change in z-Angle presented by Van Hees (2018). This algorithm identifies the longest period of inactivity within 24 hours, with the least number of interruptions, classifying as a sleep period.\"
\nhttps://eleva.ufsc.br/en/acelerometros/
\nIntensity Thresholds on Raw Acceleration Data: Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) Approaches
\nCitation: Bakrania K, Yates T, Rowlands AV, Esliger DW, Bunnewell S, Sanders J, et al. (2016) Intensity Thresholds on Raw Acceleration Data: Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) Approaches. PLoS ONE 11(10): e0164045. https://doi.org/10.1371/journal.pone.0164045
\n\" To develop and internally-validate Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) thresholds for separating sedentary behaviours from common light-intensity physical activities using raw acceleration data collected from both hip- and wrist-worn tri-axial accelerometers; and to compare and evaluate the performances between the ENMO and MAD metrics.\"
\n