Due to their potentially lifelong familiarity with digital media, many young adults aged ∼18–30 years are highly experienced with the internet as a source of information and spend more time using the internet than any other age group ( Percheski & Hargittai, 2011 ; SEMRush, 2019 ; Vaterlaus
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Dalia Mickeviciene, Renata Rutkauskaite, Dovile Valanciene, Diana Karanauskiene, Marius Brazaitis, and Albertas Skurvydas
al., 2011 ; Wolpert & Flanagan, 2016 ), it remains to be determined whether the time course of fast learning differs between children, young adults, and the older adults. It is well known that compared with young adults, children have lower and more variable motor and cognitive performance capacities
Lisa Kakinami, Erin K. O’Loughlin, Erika N. Dugas, Catherine M. Sabiston, Gilles Paradis, and Jennifer O’Loughlin
Background:
Compared with traditional nonactive video games, exergaming contributes significantly to overall daily physical activity (PA) in experimental studies, but the association in observational studies is not clear.
Methods:
Data were available in the 2011 to 2012 wave of the Nicotine Dependence in Teens (NDIT) study (N = 829). Multivariable sex-stratified models assessed the association between exergaming (1–3 times per month in the past year) and minutes of moderate and vigorous physical activity in the previous week, and the association between exergaming and meeting PA recommendations.
Results:
Compared with male exergamers, female exergamers were more likely to believe exergames were a good way to integrate PA into their lives (89% vs 62%, P = .0001). After we adjusted for covariates, male exergamers were not significantly different from male nonexergamers in minutes of PA. Female exergamers reported 47 more minutes of moderate PA in the previous week compared with female nonexergamers (P = .03). There was no association between exergaming and meeting PA recommendations.
Conclusion:
Exergaming contributes to moderate minutes of PA among women but not among men. Differences in attitudes toward exergaming should be further explored.
Phillip D. Tomporowski and Daniel M. Pendleton
activity on motor learning may depend on the temporal relation between the exercise bout and task training. Roig et al. ( 2012 ) observed that young adults who performed an intense 20-min cycling bout either prior to or following acquisition of a tracking task demonstrated better retention performance than
Emily A. Roper and José A. Santiago
critical understanding of the power relations involved in the representation of athletic women and girls ( Thorpe et al., 2018 ). Young Adult Sport Literature Sport literature is an important medium that includes biographies, fiction, and nonfiction. The Young Adult Library Services Association of the
Barbara E. Ainsworth and Cheryl Der Ananian
There is a growing recognition of the need for the primary prevention of chronic illnesses across the lifespan. In recent years, diseases that were formerly associated with adulthood such as diabetes are being diagnosed in adolescents and young adults. While there have been many prevention efforts focusing on health in children and adolescents, there is a limited body of research examining prevention in young adults. This article examines the concept of wellness in the Millennial generation and describes how their life course experiences impact seven domains of wellness. Specifically, this article describes the period and cohort effects that influence the domains of wellness and how the Millennial generation differs from other generations in these aspects of wellness. Finally, this paper provides an overview of the technological and cultural influences on wellness in the Millennial generation.
Emma L. J. Eyre, Jason Tallis, Susie Wilson, Lee Wilde, Liam Akhurst, Rildo Wanderleys, and Michael J. Duncan
. For these reasons, recent focus has been placed on the validity of estimating activity intensities in children ( Chinapaw et al., 2010 ; De Vries et al., 2009 ; Lubans et al., 2011 ), older adults ( Garatachea et al., 2010 ), and, to a lesser extent, young adults ( Watson et al., 2014 ). Young
Janet Robertson, Eric Emerson, Susannah Baines, and Chris Hatton
reported low levels of physical activity in adolescents and young adults with mild to moderate intellectual disability, especially women 20 and children and young people with intellectual disability. 21 – 23 A large-scale study in Taiwan found that less than one-third of adolescents with intellectual
Melanna F. Cox, Greg J. Petrucci Jr., Robert T. Marcotte, Brittany R. Masteller, John Staudenmayer, Patty S. Freedson, and John R. Sirard
for video coders. Based on these initial agreement analyses and identification of problematic issues, the DO system was refined (Figure 1 , Phase II). In phase III, the final agreement analyses were conducted with data from the MOCA Study’s young adult subsample (Figure 1 , Phase III). Figure 1
Babatunde O.A. Adegoke and Adewale L. Oyeyemi
Background:
This study assessed the prevalence of physical inactivity and the influence of sociodemographic variables on physical activity categories, highlighting the correlates of physical inactivity in Nigerian young adults.
Methods:
A representative sample of young adults age 16 to 39 years (n = 1006) from a Nigerian University were categorized using the International Physical Activity Questionnaire as physically inactive, moderately active, and highly active. Prevalence rates were computed for the activity categories and the independent associations of sociodemographic correlates on each category were determined using the multinomial logistic regression.
Results:
Physical inactivity prevalence was 41%. More likely to be inactive were females (OR = 1.93; CI: 1.49−2.49), those of Hausa ethnicity (OR = 2.29; CI: 1.08−5.84), having BMI > 30 kg/m2 (OR = 2.88; CI: 1.16−7.17), and those whose parents’ annual income was < 180,000 NAIRA (OR = 1.69; CI: 1.04−2.95). Less likely to be moderately active were females (OR = 0.71; CI: 0.61−0.95), those with BMI between 25.0 to 29.9 kg/m2 (OR = 0.46; CI: 0.23−0.92), and those of Hausa ethnicity (OR = 0.17; CI: 0.04−0.74).
Conclusion:
Important sociodemographic variables that can contribute to the preliminary analysis of correlates of physical inactivity among Nigerian young adults were identified.
