Abstract
Aim
This study aimed to assess the recent prevalence of mobile health (mHealth) applications (apps) use among United States (US) adults and identify the factors associated with the non-use of mHealth apps in order to provide the necessary information to address the disparities associated with mHealth use.
Subject and methods
Data from the Health Information National Trends Survey 6 (HINTS 6), a nationally representative survey by the National Cancer Institute targeting US adults, was used. Sociodemographic and individual characteristics were assessed as predictors of mHealth app non-use. Survey data were analyzed using STATA 17.0 with sampling weights incorporated.
Results
Approximately 92.9% of US adults have a smartphone or tablet computer. About 56.6% of US adults used an mHealth app within the past 12 months. mHealth app non-use was significantly associated with an increase in age (aOR = 1.02, p < 0.001), being male (aOR = 1.51, p = 0.001), having an annual income <35,000 (aOR = 2.23, p < 0.001) or between $35,000 and $74,999 (aOR = 1.59, p = 0.003), being unmarried (aOR = 1.24, p = 0.045), having a high school diploma or less (aOR = 2.50, p < 0.001) or some college (aOR = 1.39, p = 0.012), and never had care with telehealth within the past 12 months (aOR = 2.09, p < 0.001).
Conclusion
This study contributed to the literature by providing up-to-date information on the use of mHealth apps and showed that despite the promising potential mHealth has in addressing health disparities among different US populations, it is paramount to consider and adequately address factors that could contribute to the non-usage of mHealth apps itself.
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The primary dataset analyzed during the current study is publicly available on NCI’s website at https://hints.cancer.gov/data/download-data.aspx.
Code availability
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References
Bhuyan S, Lu N, Chandak A, Kim H, Wyant D, Bhatt J, Kedia S, Chang C (2016) Use of mobile health applications for health-seeking behavior among US adults. J Med Syst 40(6):1–8. https://doi.org/10.1007/S10916-016-0492-7/TABLES/2
Carroll J, Moorhead A, Bond R, LeBlanc W, Petrella R, Fiscella K (2017) Who uses mobile phone health apps and does use matter? A secondary data analytics approach. J Med Internet Res 19(4):E125. https://doi.org/10.2196/JMIR.5604
Divo J, Martinez C, Mannino D (2014) Ageing and the epidemiology of multimorbidity. Eur Respir J 44(4):1055–1068. https://doi.org/10.1183/09031936.00059814
Fortune Business (2021) mHealth apps market size, growth analysis report 2021-2028. Healthcare IT. https://www.fortunebusinessinsights.com/mhealth-apps-market-102020. Accessed 14 June 2023
Gell NM, Rosenberg DE, Demiris G, LaCroix AZ, Patel KV (2015) Patterns of technology use among older adults with and without disabilities. Gerontologist 55(3):412–421. https://doi.org/10.1093/GERONT/GNT166
Haridi HK, Alsaleh S, Alzabin S, Almasabi M, Almakrami A, Al-Swedan A, Aman A (2023) Prevalence and determinants of mobile health applications use among Saudi adults. Lecture Notes Net Systems 464:197–206. https://doi.org/10.1007/978-981-19-2394-4_18/TABLES/3
Jembai JV, Wong YL, Bakhtiar NA, Lazim SN, Ling HS, Kuan PX, Chua PF (2022) Mobile health applications: awareness, attitudes, and practices among medical students in Malaysia. BMC Med Educ 22(1):1–14. https://doi.org/10.1186/S12909-022-03603-4/TABLES/6
Kontos E, Blake KD, Chou WY, Prestin A (2014) Predictors of eHealth usage: insights on the digital divide from the Health Information National Trends Survey 2012. J Med Internet Res 16(7):E172. https://doi.org/10.2196/JMIR.3117
Majumdar A, Kar SS, Ganesh KS, Palanivel C, Misra P (2015) mHealth in the prevention and control of non-communicable diseases in India: current possibilities and the way forward. J Clin Diagnostic Res JCDR 9(2):LE06–LE10. https://doi.org/10.7860/JCDR/2015/11555.5573
Mindsea (2021) How Mobile Health Apps Are Improving Healthcare: Saving Costs, Saving Lives. https://mindsea.com/health-apps/. Accessed 14 June 2023
Nanditha NG, Paiero A, Tafessu HM, St-Jean M, McLinden T, Justice AC, Kopec J, Montaner JS, Hogg RS, Lima VD (2021) Excess burden of age-associated comorbidities among people living with HIV in British Columbia, Canada: a population-based cohort study. BMJ Open 11(1):e041734. https://doi.org/10.1136/BMJOPEN-2020-041734
Netis (2018) Mobile healthcare apps in the UK. https://www.netis.hu/en/mobile-healthcare-apps-in-the-uk/. Accessed 14 June 2023
NIH (2023a) Health Information National Trends Survey (HINTS) 6 Methodology Report. https://hints.cancer.gov/data/Default.aspx. Accessed 14 June 2023
NIH (2023b) HINTS6 - Health Information National Trends Survey (HINTS) 6. https://doi.org/10.1017/9781108954846.013. Accessed 14 June 2023
Otto L, Harst L, Timpel P, Wollschlaeger B, Richter P, Schlieter H (2020) Defining and delimitating telemedicine and related terms - an ontology-based classification. information technology based methods for health behaviours. IOS Press. https://doi.org/10.3233/SHTI200010
Pew Research Center (2021) Demographics of Mobile Device Ownership and Adoption in the United States. Pew Research Center. https://www.pewresearch.org/internet/fact-sheet/mobile/. Accessed 14 June 2023
Qan’ir Y, Khalifeh AH, Eid M, Hammad B, Al-Batran M (2021) Mobile health apps use among Jordanian outpatients: a descriptive study. Health Inform J 27(2):1–14. https://doi.org/10.1177/14604582211017940/ASSET/IMAGES/LARGE/10.1177_14604582211017940-FIG3.JPEG
Rowland SP, Fitzgerald JE, Holme T, Powell J, McGregor A (2020) What is the clinical value of mHealth for patients? Npj Digital Med 3(1):1–6. https://doi.org/10.1038/s41746-019-0206-x
Sajja A, Tundealao T (2023) Disparities and racial barriers among african american women despite breastfeeding workplace policies. Fam Community Health. https://doi.org/10.1097/fch.0000000000000389
Sittig DF, Singh H (2017) Key Advances in Clinical Informatics. Wright
Tundealao S, Titiloye T, Sajja A, Egab I (2023) Suicidal ideation, plan and attempt among adolescents in Houston, Texas: a trend and cross-sectional analysis of the youth risk behavior survey 2011–2019 in the United States. Int J Adolescent Med Health. https://doi.org/10.1515/IJAMH-2022-0115
van Veen T, Binz S, Muminovic M, Chaudhry K, Rose K, Calo S, Rammal JA, France J, Miller JB (2019) Potential of mobile health technology to reduce health disparities in underserved communities. Western J Emerg Med 20(5):799. https://doi.org/10.5811/WESTJEM.2019.6.41911
Vaportzis E, Clausen MG, Gow AJ (2017) Older adults perceptions of technology and barriers to interacting with tablet computers: a focus group study. Front Psychol 8(OCT):1687. https://doi.org/10.3389/FPSYG.2017.01687/BIBTEX
Xie Z, Nacioglu A, Or C (2018) Prevalence, demographic correlates, and perceived impacts of mobile health app use amongst Chinese adults: cross-sectional survey study. JMIR Mhealth Uhealth 6(4):e9002. https://doi.org/10.2196/MHEALTH.9002
Acknowledgment
This study used data from the Health Information National Trends Survey 6 (HINTS 6). The authors would love to thank the National Cancer Institute (NCI) for making this dataset available for secondary use.
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All authors contributed to the study’s conception and design. Data analysis was performed by Samuel Tundealao. The first draft of the manuscript was written by Samuel Tundealao and Tolulope Titiloye, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Although this was a secondary analysis, HINTS surveys were approved by the NCI’s Institutional Review Board. Informed consent was obtained from all individual participants included in the study.
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Although this was a secondary analysis, HINTS surveys were approved by the NCI’s Institutional Review Board.
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Informed consent was obtained from all individual participants included in the study.
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Tundealao, S., Titiloye, T., Sajja, A. et al. Factors associated with the non-use of mobile health applications among adults in the United States. J Public Health (Berl.) 33, 1575–1581 (2025). https://doi.org/10.1007/s10389-023-02132-8
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DOI: https://doi.org/10.1007/s10389-023-02132-8