Age Differences in Mobile Technology Use Behavior and Perception During COVID-19

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Published Dec 24, 2024
DOI: https://doi.org/10.18103/mra.v12i12.6106

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Main Article Content

Yi Lin, PhD
Department of Medicine, Division of Gerontology, Geriatrics, and Palliative Care, University of Alabama at Birmingham, Birmingham, Alabama, USA;  Department of Physiology and Aging, University of Florida, Gainesville, Florida, USA
Arnold J. Stromberg, PhD
Department of Statistics, University of Kentucky, Lexington, Kentucky, USA
Robert T. Mankowski, PhD
Department of Medicine, Division of Gerontology, Geriatrics, and Palliative Care, University of Alabama at Birmingham, Birmingham, Alabama, USA ;  Department of Physiology and Aging, University of Florida, Gainesville, Florida, USA
Emily J. Smail, PhD
Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, Florida, USA
Graham D. Rowles, PhD
Graduate Center for Gerontology, University of Kentucky, Lexington, Kentucky

Abstract

Background and Objectives: COVID-19 led to quarantine and mandatory spatial distancing, making mobile technology critical in receiving information and services. Age differences were discovered in many aspects of mobile technology use; however, we lack knowledge about age differences in mobile technology use under the impact of COVID-19. Thus, this cross-sectional study investigated age differences in mobile technology use behavior and perceptions during COVID-19. 


Research Design and Methods: We distributed a pilot-tested survey online. Participants were ≥35 years old, English speakers, and mobile technology users who lived in the United States. Data analysis involved descriptive statistics, Wilcoxon signed-rank test, and the Kruskal-Wallis test.


Results: Participants were categorized into three age groups, 35-49 (n=391, 45% female), 50-64 (n=435, 62% female), and ≥65 (n=386, 59% female). Each group significantly increased use frequency and perceived necessity to use mobile technology during COVID-19. People aged 35-49 reported using video/music entertainment more commonly than others, and people aged ≥65 reported more commonly using mobile technology for navigation and ordering taxi/car services during COVID-19 than those aged 35-49. We found no significant difference among groups regarding valuing social and emotional benefits and ease of use in deciding to use mobile technology during COVID-19.


Discussion and Implications: COVID-19 impacted mobile technology use in all ages, but age groups were found to use mobile technology for different purposes. Still, people of all ages increased their interest in the benefits of using mobile technology and decreased their focus on ease of use. COVID-19 coincidentally created a suitable environment to introduce mobile technology remote services widely to an aging population.

Keywords: daily use frequency, choice of function, perceived necessity, decision to use

Article Details

How to Cite
LIN, Yi et al. Age Differences in Mobile Technology Use Behavior and Perception During COVID-19. Medical Research Archives, [S.l.], v. 12, n. 12, dec. 2024. ISSN 2375-1924. Available at: <https://esmed.org/MRA/mra/article/view/6106>. Date accessed: 06 jan. 2025. doi: https://doi.org/10.18103/mra.v12i12.6106.
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Issue
Vol 12 No 12 (2024): Vol.12 Issue 12 December 2024
Section
Research Articles

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References

1. Guo Y-R, Cao Q-D, Hong Z-S, et al. The origin, transmission and clinical therapies on coronavirus disease 2019 (COVID-19) outbreak–an update on the status. Military medical research. 2020;7:1-10.
2. Coronavirus Resource Center. Mortality analyses. Johns Hopkins University & Medicine; 2023. Accessed March 16. https://coronavirus.jhu.edu/data/mortality
3. Li X, Li T, Wang H. Treatment and prognosis of COVID‑19: Current scenario and prospects. Experimental and therapeutic medicine. 2021;21(1):1-1.
4. Fang X, Li S, Yu H, et al. Epidemiological, comorbidity factors with severity and prognosis of COVID-19: a systematic review and meta-analysis. Aging (Albany NY). Jul 13 2020;12(13):12493-12503. doi:10.18632/aging.103579
5. Lithander FE, Neumann S, Tenison E, et al. COVID-19 in older people: a rapid clinical review. Age and Ageing. 2020;49(4):501-515. doi:10.1093/ageing/afaa093
6. Lotfi M, Hamblin MR, Rezaei N. COVID-19: Transmission, prevention, and potential therapeutic opportunities. Clinica chimica acta. 2020;508:254-266.
7. Sehgal AR, Himmelstein DU, Woolhandler S. Feasibility of separate rooms for home isolation and quarantine for COVID-19 in the United States. Annals of internal medicine. 2021;174(1):127-129.
8. Whitelaw S, Mamas MA, Topol E, Van Spall HG. Applications of digital technology in COVID-19 pandemic planning and response. The Lancet Digital Health. 2020;2(8):e435-e440.
9. Bhavya R, Sambhav S. Role of mobile communication with emerging technology in Covid-19. International Journal of Advanced Trends in Computer Science and Engineering. 2020;9(3)
10. Kondylakis H, Katehakis DG, Kouroubali A, et al. COVID-19 mobile apps: a systematic review of the literature. Journal of medical Internet research. 2020;22(12):e23170.
11. Urbaczewski A, Lee YJ. Information Technology and the pandemic: a preliminary multinational analysis of the impact of mobile tracking technology on the COVID-19 contagion control. European Journal of Information Systems. 2020;29(4):405-414.
12. Ahmad S, Chitkara P, Khan FN, et al. Mobile technology solution for COVID-19: surveillance and prevention. Computational intelligence methods in COVID-19: Surveillance, prevention, prediction and diagnosis. 2021:79-108.
13. Kuoppamäki S-M, Taipale S, Wilska T-A. The use of mobile technology for online shopping and entertainment among older adults in Finland. telematics and Informatics. 2017;34(4):110-117.
14. Renaud K, Van Biljon J. Predicting technology acceptance and adoption by the elderly: a qualitative study. 2008:210-219.
15. Yang K, Jolly LD. Age cohort analysis in adoption of mobile data services: gen Xers versus baby boomers. Journal of consumer marketing. 2008;25(5):272-280.
16. Fox G, Connolly R. Mobile health technology adoption across generations: Narrowing the digital divide. Information Systems Journal. 2018;28(6):995-1019.
17. Shahid Z, Kalayanamitra R, McClafferty B, et al. COVID‐19 and older adults: what we know. Journal of the American Geriatrics Society. 2020;68(5):926-929.
18. Kang S-J, Jung SI. Age-related morbidity and mortality among patients with COVID-19. Infection & chemotherapy. 2020;52(2):154.
19. Centers For Disease Control And Prevention. Risk for COVID-19 Infection, Hospitalization, and Death By Age Group. 2023. Accessed May 30. https://archive.cdc.gov/#/details?url=https://www.cdc.gov/coronavirus/2019-ncov/covid-data/investigations-discovery/hospitalization-death-by-age.html
20. Purcell K. Half of adult cell phone owners have apps on their phones. Pew Internet & American Life Project Washington, DC; 2011.
21. Lin Y, Rowles GD, Stromberg AJ, Zeidan RS, Mankowski RT. Impact of COVID-19 on Mobile Technology use in adults in the United States. F1000Research. 2023;12:1376.
22. Adeniyi EA, Awotunde JB, Ogundokun RO, Kolawole PO, Abiodun MK, Adeniyi AA. Mobile health application and COVID-19: Opportunities and challenges. Journal of Critical Reviews. 2020;7(15):3481-3488.
23. Drew DA, Nguyen LH, Steves CJ, et al. Rapid implementation of mobile technology for real-time epidemiology of COVID-19. Science. 2020;368(6497):1362-1367.
24. Alanzi T. A review of mobile applications available in the app and google play stores used during the COVID-19 outbreak. Journal of multidisciplinary healthcare. 2021:45-57.
25. Islam MN, Islam I, Munim KM, Islam AN. A review on the mobile applications developed for COVID-19: an exploratory analysis. Ieee Access. 2020;8:145601-145610.
26. Etu E-E, Sureshbabu K, Summerville S, Parmar A, Huang G. What changes the travel pattern: A national survey on the impacts of the COVID-19 pandemic on older adults’ public transportation usage. Journal of Transport & Health. 2023;33:101718.
27. Park B, Cho J. Older adults’ avoidance of public transportation after the outbreak of COVID-19: Korean subway evidence. MDPI; 2021:448.
28. Jahangir S, Bailey A, Mowri S, Hasan MMU, Hossain S. Older adults’ mobility amid COVID-19 pandemic in Bangladesh: safety and perceived risks of using public transport. Handbook on COVID-19 Pandemic and Older Persons: Narratives and Issues from India and Beyond. Springer; 2023:535-553.
29. Lithander FE, Neumann S, Tenison E, et al. COVID-19 in older people: a rapid clinical review. Age and ageing. 2020;49(4):501-515.
30. Olson KE, O’Brien MA, Rogers WA, Charness N. Diffusion of technology: frequency of use for younger and older adults. Ageing international. 2011;36(1):123-145.
31. Tracy KW. Mobile application development experiences on Apple's iOS and Android OS. Ieee Potentials. 2012;31(4):30-34.
32. Zhao Y, Ni Q, Zhou R. What factors influence the mobile health service adoption? A meta-analysis and the moderating role of age. International Journal of Information Management. 2018;43:342-350.
33. Murphy S, Kochanek K, Xu J, Arias E. Mortality in the United States, 2020. Centers for Disease Control and Prevention: National center for health statistics. ; 2021. 2021 December. https://www.cdc.gov/nchs/products/databriefs/db427.htm