scholarly journals Mothers' perceptions on their toddlers' smart device use: Focusing on smartphone and tablet PC

2014 ◽  
Vol 9 (1) ◽  
pp. 213-242
Author(s):  
aa
Keyword(s):  
2021 ◽  
Vol 30 ◽  
pp. 72-85
Author(s):  
Supaporn Kumruangrit ◽  
◽  
Raweewan Tansuwat ◽  
Sasithorn Marat ◽  
Laddawan Phothiwichit ◽  
...  

This research investigated smart device use among young Thai children. The study likewise explored the relationship between smart device screen time, family roles in smart device use, and effects of smart device use. In 2020, primary data were collected through questionnaires from 1,100 primary parents of 2-5-year-old children in five provinces in Health Region 3. A Mann-Whitney U Test and Median Test were used in data analyses of the associations. The results revealed that 2-5-year-old children had an average screen time per day of 1 hour and 33 minutes, with 54.3% spending more than 1 hour on smart devices daily. In addition, 21.5% reported owning a smartphone, of which 55.2% accessed YouTube to watch cartoons and movies. In terms of screen time, 21.7% of the children reported unrestricted use. In terms of effects from smart device use, children being easily irritated and moody was noted by most parents (61.5%). In addition, variables under family roles and effects of smart device use showed a statistically significant correlation with smart device screen time. However, median screen time varied by each variable under family roles and effects of smart device use. The findings are essential for future policy planning, which will enable families with young children to become aware of appropriate smartphone or tablet usage by their children.


2020 ◽  
Vol 79 ◽  
pp. 263-273 ◽  
Author(s):  
Min-Seok Lee ◽  
Jee-Hoon Han ◽  
Chul Won Lee
Keyword(s):  

2016 ◽  
Vol 29 (3) ◽  
pp. 363-370
Author(s):  
Sun-Hee Lim ◽  
Mi-Hyun Kim ◽  
Mi-Kyeong Choi

Author(s):  
Jonathan Bishop

This chapter carries out two investigations into digital addiction using the brain productivity measure of knol. It is asserted that digital addiction is caused by two medical conditions linked to the well-known concept of flow and lesser known concept of involvement. These conditions are serotonergic-dopaminergic asynchronicity (SDA) and glutamine inhibition and glutamate acceleration (GIGA). In online environments SDA affects befriending, defriending and kudos and GIGA affects workfulness and smart-device overuse to produce increased wakefulness, causing conditions like Circadian rhythm sleep disorder. In other words, if a person is over-stimulated or under-stimulated, their use of digital technologies, such as at night, will increase. The results show improved sleep and reduced device use during the night when the L-Glutamine is consumed, but effects the following day were not always positive. L-5-Hydroxytryptophan had some effect in reducing ‘mental gaze' caused by glutamate and dopamine, but could not be seen as effective as an SSRI.


Author(s):  
Alexander Burnap ◽  
Panos Y. Papalambros

Design preference models are used widely in product planning and design development. Their prediction accuracy requires large amounts of personal user data including purchase and other personal choice records. With increased Internet and smart device use, sources of personal data are becoming more varied and their capture more ubiquitous. This situation leads to questioning whether there is a trade off between improving products and compromising individual user privacy. To advance this conversation, we analyze how privacy safeguards may affect design preference modeling. We conduct an experiment using real user data to study the performance of design preference models under different levels of privacy. Results indicate there is a tradeoff between accuracy and privacy. However, with enough data, models with privacy safeguards can still be sufficiently accurate to answer population-level design questions.


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