Media use, attention, mental health and academic performance among 8 to 12 year old children

The rise in digital media consumption, especially among children, raises the societal question of its impact on cognition, mental health and academic achievement. Here, we review the impact of three different ways of measuring technology use—total hours of media consumed, hours of video game play and number of media used concurrently—in a study surveying 156 eight-to-twelve year-old children. At stake is the question of whether different technology uses may have different effects, which could explain some of the past mixed findings. We collected data over three sessions relating to children’s media uses as well as (i) attentional and behavioral control abilities, (ii) psychological distress, psychosocial functioning, and sleep, and (iii) academic achievement and motivation. While attentional control abilities were assessed using both cognitive tests (D2, SART, BLAST) and questionnaires (mind-wandering; Connors), mental health and sleep were all questionnaire-based (K6, Strength and Difficulties Questionnaire-SDQ, Sleep Quality/Quantity). Finally, academic performance was based on self-reported grades, with motivational variables being measured through the grit and the growth-mindset questionnaires. We present partial correlation analyses and construct a psychological network to assess the structural associations between different forms of media consumption and the three categories of measures. Our results are in line with those observed with adults: children consume large amounts of media and media multitask substantially. Partial correlation analyses show that media multitasking specifically was mostly correlated with negative mental health, while playing video games was associated with faster responding and better mental health. No significant partial correlations were observed for total hours on media. Psychological network analysis complement these first results by indicating that all three ways of consuming technology are only indirectly related to self-reported grades. Thus, technology uses appear to only indirectly relate to academic performance, while more directly affecting mental health. This work emphasizes the need to differentiate among technology uses when considering their impact on human behavior, It also highlights the importance of characterizing the variety of technology uses that need to be considered, if one is to understand how every day digital consumption impacts human behavior

Media use, attention, mental health and academic performance among 8 to 12 year old children

The rise in digital media consumption, especially among children, raises the societal question of its impact on cognition, mental health and academic achievement. Here, we investigate three different ways of measuring technology use-—total hours of media consumed, hours of video game play and number of media used concurrently—-in 118 eight-to-twelve year-old children. At stake is the question of whether different technology uses have different effects, which could explain some of the past mixed findings. We collected data about children’s media uses as well as (i) attentional and behavioral control abilities, (ii) psychological distress, psychosocial functioning, and sleep, and (iii) academic achievement and motivation. While attentional control abilities were assessed using both cognitive tests and questionnaires, mental health and sleep were all questionnaire-based. Finally, academic performance was based on self-reported grades, with motivational variables being measured through the grit and the growth-mindset questionnaires. We present partial correlation analyses and construct a psychological network to assess the structural associations between different forms of media consumption and the three categories of measures. We observe that children consume large amounts of media and media multitask substantially. Partial correlation analyses show that media multitasking specifically was mostly correlated with negative mental health, while playing video games was associated with faster responding and better mental health. No significant partial correlations were observed for total hours on media. Psychological network analysis complement these first results by indicating that all three ways of consuming technology are only indirectly related to self-reported grades. Thus, technology uses appear to only indirectly relate to academic performance, while more directly affecting mental health. This work emphasizes the need to differentiate among technology uses if one is to understand how every day digital consumption impacts human behavior

Phase 3, Multicenter Open‐Label study to investigate the efficacy of elbasvir and grazoprevir fixed‐dose combination for 8 weeks in treatment‐naïve, HCV GT1b‐infected patients, with non‐severe fibrosis

International audienc

An objective score to identify psychogenic seizures based on age of onset and history

OBJECTIVE:Psychogenic nonepileptic seizure (PNES) is a common diagnosis after evaluation of medication resistant or atypical seizures with video-electroencephalographic monitoring (VEM), but usually follows a long delay after the development of seizures, during which patients are treated for epilepsy. Therefore, more readily available diagnostic tools are needed for earlier identification of patients at risk for PNES. A tool based on patient-reported psychosocial history would be especially beneficial because it could be implemented in the outpatient clinic. METHODS:Based on the data from 1375 patients with VEM-confirmed diagnoses, we used logistic regression to compare the frequency of specific patient-reported historical events, demographic information, age of onset, and delay from first seizure until VEM in five mutually exclusive groups of patients: epileptic seizures (ES), PNES, physiologic nonepileptic seizure-like events (PSLE), mixed PNES plus ES, and inconclusive monitoring. To determine the diagnostic utility of this information to differentiate PNES only from ES only, we used multivariate piecewise-linear logistic regression trained using retrospective data from chart review and validated based on data from 246 prospective standardized interviews. RESULTS:The prospective area under the curve of our weighted multivariate piecewise-linear by-sex score was 73%, with the threshold that maximized overall retrospective accuracy resulting in a prospective sensitivity of 74% (95% CI: 70-79%) and prospective specificity of 71% (95% CI: 64-82%). The linear model and piecewise linear without an interaction term for sex had very similar performance statistics. In the multivariate piecewise-linear sex-split predictive model, the significant factors positively associated with ES were history of febrile seizures, current employment or active student status, history of traumatic brain injury (TBI), and longer delay from first seizure until VEM. The significant factors associated with PNES were female sex, older age of onset, mild TBI, and significant stressful events with sexual abuse, in particular, increasing the likelihood of PNES. Delays longer than 20years, age of onset after 31years for men, and age of onset after 40years for women had no additional effect on the likelihood of PNES. DISCUSSION:Our promising results suggest that an objective score has the potential to serve as an early outpatient screening tool to identify patients with greater likelihood of PNES when considered in combination with other factors. In addition, our analysis suggests that sexual abuse, more than other psychological stressors including physical abuse, is more associated with PNES. There was a trend of increasing frequency of PNES for women during childbearing years and plateauing outside those years that was not observed in men