Quality Screen TimeQuality Screen Time

PsycCRITIQUES ◽  
2007 ◽  
Vol 5252 (4141) ◽  
Author(s):  
Fran C. Blumberg ◽  
Daniel P. Auld
Keyword(s):  
Screen Time

Reduced Screen Time Leads to Reduced BMI

2008 ◽  
Vol 42 (4) ◽  
pp. 37
Author(s):  
MARY ANN MOON
Keyword(s):  
Screen Time

Screen-Time Behavior As a Predictor of Depressive Symptoms in Overweight and Obese Adolescents

2013 ◽  
Author(s):  
Marisa A. Murray ◽  
Ronald J. Sigal ◽  
Glen P. Kenny ◽  
Stasia Hadjiyannakis ◽  
Angela S. Alberga ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Screen Time ◽  
Time Behavior ◽  
Obese Adolescents

Sleep and Screen Time Questionnaire

2020 ◽  
Author(s):  
Claire Smith ◽  
Tanja de Wilde ◽  
Rachael W. Taylor ◽  
Barbara C. Galland
Keyword(s):  
Screen Time

Children's Screen Time at 12 Months and Pediatrics Developmental Screening Score

PEDIATRICS ◽  
2016 ◽  
Vol 137 (Supplement 3) ◽  
pp. 19A-19A ◽  
Author(s):  
Sahel Hazrati ◽  
Kathi C. Huddleston ◽  
Kathleen Donnelly ◽  
David Ascher ◽  
John E. Niederhuber
Keyword(s):  
Screen Time ◽  
Developmental Screening

Assessment Of Dry Eye Symptoms And Quality Of Sleep In Engineering Students During The Covid-19 Pandemic

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 1202-1207
Author(s):  
Pavithra S ◽  
Dheepak Sundar M
Keyword(s):  
Sleep Quality ◽  
Dry Eye ◽  
Screen Time ◽  
Engineering Students ◽  
Statistical Tests ◽  
Quality Of Sleep ◽  
Cross Sectional ◽  
Eye Symptoms ◽  
Dry Eye Symptoms

To assess dry eye symptoms (DES) and quality of sleep in engineering students during the Covid19 pandemic lockdown and also to assess the association between DES and sleep quality. A cross-sectional questionnaire-based study was carried out among 396 engineering students studying in Saveetha engineering college. The study tool used was a semi-structured google form questionnaire designed for assessing digital device usage, symptoms of dry eye disease and sleep pattern. Responses were analyzed using appropriate statistical tests. Overall 64.1% attained a score of more than 10, indicating the presence of DES. 70.2% of the study population used digital screens for more than 13 hours. A statistically significant association was found between increased screen time and presence of DES(p<0.05). 64.9% had a score of >18 indicating reduced sleep quality. About 77.1% of the students with DES had reduced sleep quality, and a significant association (p<0.01) was observed between the two. During the Covid19 pandemic lockdown, there appears to be rising prevalence of DES in student population, one of the reasons being increased screen time. The sleep quality was also found to be reduced, and a significant association was found between DES and sleep quality.

Examining the accuracy of estimated smartphone use: How well-being and usage level predict discrepancies between estimated and actual use

2019 ◽  
Author(s):  
Craig Sewall ◽  
Daniel Rosen ◽  
Todd M. Bear
Keyword(s):  
Public Health ◽  
Social Media ◽  
Life Satisfaction ◽  
Mobile Device ◽  
Screen Time ◽  
Well Being ◽  
Actual Use ◽  
Smartphone Use ◽  
Usage Level

The increasing ubiquity of mobile device and social media (SM) use has generated a substantial amount of research examining how these phenomena may impact public health. Prior studies have found that mobile device and SM use are associated with various aspects of well-being. However, a large portion of these studies relied upon self-reported estimates to measure amount of use, which can be inaccurate. Utilizing Apple’s “Screen Time” application to obtain actual iPhone and SM use data, the current study examined the accuracy of self-reported estimates, how inaccuracies bias relationships between use and well-being (depression, loneliness, and life satisfaction), and the degree to which inaccuracies were predicted by levels of well-being. Among a sample of 393 iPhone users, we found that: a.) participants misestimated their weekly overall iPhone and SM use by 22.1 and 16.6 hours, respectively; b.) the correlations between estimated use and well-being variables were consistently stronger than the correlations between actual use and well-being variables; and c.) the amount of inaccuracy in estimated use is associated with levels of participant well-being as well as amount of use. These findings suggest that estimates of device/SM use may be biased by factors that are fundamental to the relationships being investigated. **This manuscript is currently under review**

Physical activity, screen time, and nutritional status in adolescents in Banyumas

2019 ◽  
Vol 22 (11) ◽  
pp. 109-114
Author(s):  
IzkaSofiyya Wahyurin ◽  
Saryono Saryono ◽  
Atikah Proverawati
Keyword(s):  
Physical Activity ◽  
Nutritional Status ◽  
Screen Time
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