Jenny S Radesky1, Heidi M Weeks2, Rosa Ball3, Alexandria Schaller3, Samantha Yeo3, Joke Durnez4, Matthew Tamayo-Rios4, Mollie Epstein4, Heather Kirkorian5, Sarah Coyne6, Rachel Barr7. 1. Department of Pediatrics, Medical School and jradesky@med.umich.edu. 2. Department of Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan. 3. Department of Pediatrics, Medical School and. 4. OpenLattice, Inc, Redwood City, California. 5. Department of Human Development and Family Studies, University of Wisconsin-Madison, Madison, Wisconsin. 6. Department of Family Life, Brigham Young University, Provo, Utah; and. 7. Department of Psychology, Georgetown University, Washington, District of Columbia.
Abstract
BACKGROUND AND OBJECTIVES: Child mobile device use is increasingly prevalent, but research is limited by parent-report survey methods that may not capture the complex ways devices are used. We aimed to implement mobile device sampling, a set of novel methods for objectively measuring child mobile device use. METHODS: We recruited 346 English-speaking parents and guardians of children aged 3 to 5 years to take part in a prospective cohort study of child media use. All interactions with participants were through e-mail, online surveys, and mobile device sampling; we used a passive-sensing application (Chronicle) in Android devices and screenshots of the battery feature in iOS devices. Baseline data were analyzed to describe usage behaviors and compare sampling output with parent-reported duration of use. RESULTS: The sample comprised 126 Android users (35 tablets, 91 smartphones) and 220 iOS users (143 tablets, 77 smartphones); 35.0% of children had their own device. The most commonly used applications were YouTube, YouTube Kids, Internet browser, quick search or Siri, and streaming video services. Average daily usage among the 121 children with their own device was 115.3 minutes/day (SD 115.1; range 0.20-632.5) and was similar between Android and iOS devices. Compared with mobile device sampling output, most parents underestimated (35.7%) or overestimated (34.8%) their child's use. CONCLUSIONS: Mobile device sampling is an unobtrusive and accurate method for assessing mobile device use. Parent-reported duration of mobile device use in young children has low accuracy, and use of objective measures is needed in future research.
BACKGROUND AND OBJECTIVES:Child mobile device use is increasingly prevalent, but research is limited by parent-report survey methods that may not capture the complex ways devices are used. We aimed to implement mobile device sampling, a set of novel methods for objectively measuring child mobile device use. METHODS: We recruited 346 English-speaking parents and guardians of children aged 3 to 5 years to take part in a prospective cohort study of child media use. All interactions with participants were through e-mail, online surveys, and mobile device sampling; we used a passive-sensing application (Chronicle) in Android devices and screenshots of the battery feature in iOS devices. Baseline data were analyzed to describe usage behaviors and compare sampling output with parent-reported duration of use. RESULTS: The sample comprised 126 Android users (35 tablets, 91 smartphones) and 220 iOS users (143 tablets, 77 smartphones); 35.0% of children had their own device. The most commonly used applications were YouTube, YouTube Kids, Internet browser, quick search or Siri, and streaming video services. Average daily usage among the 121 children with their own device was 115.3 minutes/day (SD 115.1; range 0.20-632.5) and was similar between Android and iOS devices. Compared with mobile device sampling output, most parents underestimated (35.7%) or overestimated (34.8%) their child's use. CONCLUSIONS: Mobile device sampling is an unobtrusive and accurate method for assessing mobile device use. Parent-reported duration of mobile device use in young children has low accuracy, and use of objective measures is needed in future research.
Authors: Paul A Harris; Robert Taylor; Robert Thielke; Jonathon Payne; Nathaniel Gonzalez; Jose G Conde Journal: J Biomed Inform Date: 2008-09-30 Impact factor: 6.317
Authors: Paul A Harris; Robert Taylor; Brenda L Minor; Veida Elliott; Michelle Fernandez; Lindsay O'Neal; Laura McLeod; Giovanni Delacqua; Francesco Delacqua; Jacqueline Kirby; Stephany N Duda Journal: J Biomed Inform Date: 2019-05-09 Impact factor: 6.317
Authors: Kathy Hirsh-Pasek; Jennifer M Zosh; Roberta Michnick Golinkoff; James H Gray; Michael B Robb; Jordy Kaufman Journal: Psychol Sci Public Interest Date: 2015-05
Authors: Deborah L Linebarger; Rachel Barr; Matthew A Lapierre; Jessica T Piotrowski Journal: J Dev Behav Pediatr Date: 2014 Jul-Aug Impact factor: 2.225
Authors: Hilda K Kabali; Matilde M Irigoyen; Rosemary Nunez-Davis; Jennifer G Budacki; Sweta H Mohanty; Kristin P Leister; Robert L Bonner Journal: Pediatrics Date: 2015-11-02 Impact factor: 7.124
Authors: Nalingna Yuan; Heidi M Weeks; Rosa Ball; Mark W Newman; Yung-Ju Chang; Jenny S Radesky Journal: Pediatr Res Date: 2019-06-13 Impact factor: 3.756
Authors: Ross D Neville; Michele A Nelson; Sheri Madigan; Dillon T Browne; Kimberley D Lakes Journal: Eur J Pediatr Date: 2021-03-08 Impact factor: 3.183
Authors: Marisa Meyer; Jennifer M Zosh; Caroline McLaren; Michael Robb; Harlan McCafferty; Roberta Michnick Golinkoff; Kathy Hirsh-Pasek; Jenny Radesky Journal: J Child Media Date: 2021-02-23
Authors: Dillon Thomas Browne; Shealyn S May; Laura Colucci; Pamela Hurst-Della Pietra; Dimitri Christakis; Tracy Asamoah; Lauren Hale; Katia Delrahim-Howlett; Jennifer A Emond; Alexander G Fiks; Sheri Madigan; Greg Perlman; Hans-Jürgen Rumpf; Darcy Thompson; Stephen Uzzo; Jackie Stapleton; Ross Neville; Heather Prime Journal: BMJ Open Date: 2021-05-19 Impact factor: 2.692
Authors: Hira Abbasi; Muhammad Saqib; Rizwan Jouhar; Abhishek Lal; Naseer Ahmed; Muhammad Adeel Ahmed; Mohammad Khursheed Alam Journal: Biomed Res Int Date: 2021-05-23 Impact factor: 3.411