Excessive use of mobile devices and children's physical health

Domoff, Sarah E.; Borgen, Aubrey L.; Foley, Ryan P.; Maffett, Anissa

doi:10.1002/hbe2.145

Cited by 71 publications

(54 citation statements)

References 69 publications

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“…Traditional screen time (i.e., time spent watching TV) has long been associated with physical health outcomes, such as obesity and poorer sleep, in children and adolescents [10]. A recent review on the literature on physical health correlates of mobile devices noted major gaps in our understanding of the impact of excessive smart phone use on the physical health of youth [11]. Although research has most consistently linked smartphone use with disrupted sleep and shorter sleep duration [12], we are unaware of research examining addictive phone use with other health concerns, such as problematic eating behaviors, food addiction, and adiposity.…”

Section: Introductionmentioning

confidence: 99%

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Adolescents’ Addictive Phone Use: Associations with Eating Behaviors and Adiposity

Domoff

Sutherland

Yokum

et al. 2020

IJERPH

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Concerns have been raised about excessive or “addictive” phone use among adolescents, and the impact that addictive phone use (APU) can have on adolescent development and health. Most research on the physical health correlates of smartphone use has been limited to sleep health, whereas other outcomes, such as eating behaviors and obesity risk have not received as much attention. To address this gap in the literature, we examined the association between APU and emotion regulation difficulties, impulsivity, maladaptive eating behaviors, and adiposity in a sample of 111 adolescents. We found that APU is associated with greater emotion regulation difficulties, dysregulated eating, restrained eating, food addiction, and higher percent body fat. Further, we found that emotion regulation difficulties mediated the association between APU and dysregulated eating, restrained eating, and food addiction. Findings suggest that addictive phone use may confer increased risk for obesogenic eating behaviors and food addiction via challenges in regulating emotions.

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Section: Introductionmentioning

confidence: 99%

“…In summary, smartphone addiction and its impact on adolescent health is largely understudied [11]. This is a significant area of research as a vast majority of US teens have their own smartphones, and nearly half of US parents are concerned about their adolescents' addiction to mobile devices [3].…”

Section: Introductionmentioning

confidence: 99%

Adolescents’ Addictive Phone Use: Associations with Eating Behaviors and Adiposity

Domoff

Sutherland

Yokum

et al. 2020

IJERPH

Self Cite

View full text Add to dashboard Cite

show abstract

“…Smartphones, tablets and portable computing devices have a link to health of children in many ways: The common, prevailing perception about the impact of these devices is that frequent consumption and excessive use of such devices impact the quality of life and health of children in several, adverse ways. These tend to affect sleep quality, propensity for obesity, overall fitness, "musculoskeletal pain, ocular health, and migraine/headaches" (Domoff et al 2019). (Liu et al 2017) analyzed the impact of mobile devices and negative emotions among Chinese adolescents by extending current research asserting links between mobile use and negativity of emotions.…”

Section: Background: Data Gathering and Mining Inmentioning

confidence: 99%

Predicting Autism Spectrum Disorder using Machine Learning Technique

Alwidian¹,

Elhassan²,

Ghnemat³

2020

IJRTE

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Autism Spectrum Disorder (ASD) is a psychiatric disorder that puts constraints on the ability to use of cognitive, linguistic, communicative, and social skills. Recently, many data mining techniques employed to serve this domain by determining the main features of the condition and the correlation between them. In this article, we investigate the Association Classification (AC) technique as a data mining technique in predicting whether an individual has autism or not. Accordingly, seven well-known algorithms are selected to conduct analysis and evaluation of the performance of the AC technique in term of identifying correlations between the features to help decide early on whether an individual has autism; this is particularly significant for children. The evaluation for the behavior and the performance in the prediction tasks for the AC algorithms was conducted for the common metrics of including Precision, Accuracy F-Measure as well as Recall. Finally, a comparative performance analysis among the algorithms was used as final result for the study. The results show better performance for the WCBA algorithm in most test scenarios with accuracy of 97 % although, the majority of algorithms exhibited excellent accuracy when applied in this domain.

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“…First, screen time has had meteoric growth. Second, evidence ties high use to major public health issues (Bushman & Huesmann, 2006; Domoff, Borgen, Foley, & Maffett, 2019).…”

Section: Growing Concern Over Excessive Recreational Screen Timementioning

confidence: 99%

A Goal‐Theoretic Framework for Parental Screen‐Time Monitoring Behavior

Owenz

Fowers

2020

J of Family Theo & Revie

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Children's screen time (i.e., time spent using computers, televisions, mobile devices) has rapidly increased with the development of mobile technology, and this increase has become a matter of serious concern for teachers, parents, family life educators, psychologists, and other health professionals. High usage rates (more than 2 hours per day) have been associated with low-quality sleep, language acquisition difficulties, and attentional problems in young children. Results of experimental trials to limit screen time have been mixed. Interventions may be improved with guidance from a systematic theoretical framework focused directly on children's well-being. This article proposes a multifaceted goal-theoretic approach to reducing screen time through involvement in alternative activities. It is proposed that a focus on approach goals involving shared activities that are constitutive of children's well-being can naturally displace excessive screen time, enhance child development, reduce parental stress, and improve familial well-being. Parents, family life educators, psychologists, pediatricians, teachers, and policy makers are increasingly concerned about children's recreational screen time, a term that refers to time spent with digital devices (e.g., televisions,

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Excessive use of mobile devices and children's physical health

Cited by 71 publications

References 69 publications

Adolescents’ Addictive Phone Use: Associations with Eating Behaviors and Adiposity

Adolescents’ Addictive Phone Use: Associations with Eating Behaviors and Adiposity

Predicting Autism Spectrum Disorder using Machine Learning Technique

A Goal‐Theoretic Framework for Parental Screen‐Time Monitoring Behavior

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