Abstract
This study explores the use of mobile health applications (mHealth apps) on smartphones or tablets for health-seeking behavior among US adults. Data was obtained from cycle 4 of the 4th edition of the Health Information National Trends Survey (HINTS 4). Weighted multivariate logistic regression models examined predictors of 1) having mHealth apps, 2) usefulness of mHealth apps in achieving health behavior goals, 3) helpfulness in medical care decision-making, and 4) asking a physician new questions or seeking a second opinion. Using the Andersen Model of health services utilization, independent variables of interest were grouped under predisposing factors (age, gender, race, ethnicity, and marital status), enabling factors (education, employment, income, regular provider, health insurance, and rural/urban location of residence), and need factors (general health, confidence in their ability to take care of health, Body Mass Index, smoking status, and number of comorbidities). In a national sample of adults who had smartphones or tablets, 36 % had mHealth apps on their devices. Among those with apps, 60 % reported the usefulness of mHealth apps in achieving health behavior goals, 35 % reported their helpfulness for medical care decision-making, and 38 % reported their usefulness in asking their physicians new questions or seeking a second opinion. The multivariate models revealed that respondents were more likely to have mHealth apps if they had more education, health insurance, were confident in their ability to take good care of themselves, or had comorbidities, and were less likely to have them if they were older, had higher income, or lived in rural areas. In terms of usefulness of mHealth apps, those who were older and had higher income were less likely to report their usefulness in achieving health behavior goals. Those who were older, African American, and had confidence in their ability to take care of their health were more likely to respond that the mHealth apps were helpful in making a medical care decision and asking their physicians new questions or for a second opinion. Potentially, mHealth apps may reduce the burden on primary care, reduce costs, and improve the quality of care. However, several personal-level factors were associated with having mHealth apps and their perceived helpfulness among their users, indicating a multidimensional digital divide in the population of US adults.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Martínez-Pérez, B., De La Torre-Díez, I., and López-Coronado, M., Privacy and security in mobile health apps: a review and recommendations. J Med Syst 39:1–8, 2015.
Mosa, A. S. M., Yoo, I., and Sheets, L., A systematic review of healthcare applications for smartphones. BMC Med Inform Decis Mak 12:1, 2012.
Zapata, B. C., Fernández-Alemán, J. L., Idri, A., and Toval, A., Empirical studies on usability of mHealth apps: A systematic literature review. J Med Syst 39:1–19, 2015.
Kuersten, R. (2010) 500 Million People Will be Using Mobile Health Applications in 2015. http://www.prnewswire.com/news-releases/500-million-people-will-be-using-mobile-health-applications-in-2015-107160173.html. Accessed Feb 1st 2016.
Bert, F., Giacometti, M., Gualano, M. R., and Siliquini, R., Smartphones and health promotion: a review of the evidence. J Med Syst 38:1–11, 2014.
Alghamdi, M., Gashgari, H., and Househ, M., A Systematic Review of Mobile Health Technology Use in Developing Countries. Stud Health Technol Inform 213:223–226, 2015.
Anglada-Martínez, H., Martin-Conde, M., Rovira-Illamola, M., Sotoca-Momblona, J. M., Sequeira, E., Aragunde, V., Moreno, M. A., Catalan, M., and Codina-Jané, C., Feasibility and Preliminary Outcomes of a Web and Smartphone–Based Medication Self-Management Platform for Chronically Ill Patients. J Med Syst 40:1–14, 2016.
Boulos, M. N. K., Brewer, A. C., Karimkhani, C., Buller, D. B. , Dellavalle, R. P., Mobile medical and health apps: state of the art, concerns, regulatory control and certification. Online J Public Health Inform 5, 2014.
Hamel, M. B., Cortez, N. G., Cohen, I. G., and Kesselheim, A. S., FDA regulation of mobile health technologies. N Engl J Med 371:372–379, 2014.
Pew Research Center (2005) Trends 2005. http://www.pewresearch.org/files/old-assets/trends/trends2005.pdf. Accessed Feb 1st 2016.
Hesse, B. W., Nelson, D. E., Kreps, G. L., Croyle, R. T., Arora, N. K., Rimer, B. K., and Viswanath, K., Trust and sources of health information: the impact of the Internet and its implications for health care providers: findings from the first Health Information National Trends Survey. Arch Intern Med 165:2618–2624, 2005.
Krebs, P., and Duncan, D. T., Health App Use among US Mobile Phone Owners: A National Survey. JMIR Mhealth Uhealth 3:e101, 2015.
Madden M, Rainee L (ed) (2003) America’s Online Pursuits: The changing picture of who’s online and what they do. Pew Internet & American Life Project. http://www.pewinternet.org/files/old-media/Files/Reports/2003/PIP_Online_Pursuits_Final.PDF.PDF. Accessed Feb 2nd 2016.
Andersen, R. M., Revisiting the behavioral model and access to medical care: does it matter?. J Health Soc Behav:1–10, 1995
National Cancer Institute Health Information National Trends Survey 4 (HINTS 4). http://hints.cancer.gov/. Accessed Jan 2nd 2016.
National Cancer Institute (2016) Frequently asked questions about HINTS. http://hints.cancer.gov/faq.aspx. Accessed Jan 10th 2016.
SAS Institute Inc. SAS version 9.4
Witte, J., Kiss, M., and Lyon, R., The Internet and Social Inequalities in the US. In: Ragnedde, M., and Muschert, G. W. (Eds.), The Digital Divide: the internet and social inequality in international perspective. Routledge, London, pp. 67–84, 2010.
Ma, Q., Chan, A. H., and Chen, K., Personal and other factors affecting acceptance of smartphone technology by older Chinese adults. Appl Ergon 54:62–71, 2016.
Aday, L. A., Andersen, R. M., Equity of access to medical care: a conceptual and empirical overview. Med Care:4–27, 1981.
Aday, L. A., and Andersen, R., A framework for the study of access to medical care. Health Serv Res 9:208–220, 1974.
Azar, K. M., Lesser, L. I., Laing, B. Y., Stephens, J., Aurora, M. S., Burke, L. E., and Palaniappan, L. P., Mobile applications for weight management: theory-based content analysis. Am J Prev Med 45:583–589, 2013.
Baskerville, N. B., Struik, L. L., Hammond, D., Guindon, G. E., Norman, C. D., Whittaker, R., Burns, C. M., Grindrod, K. A., and Brown, K. S., Effect of a mobile phone intervention on quitting smoking in a young adult population of smokers: randomized controlled trial study protocol. JMIR Res Protoc 4:e10, 2015.
Conroy, D. E., Yang, C., and Maher, J. P., Behavior change techniques in top-ranked mobile apps for physical activity. Am J Prev Med 46:649–652, 2014.
Du, H., Venkatakrishnan, A., Youngblood, G. M., Ram, A., and Pirolli, P., A Group-Based Mobile Application to Increase Adherence in Exercise and Nutrition Programs: A Factorial Design Feasibility Study. JMIR Mhealth Uhealth 4:e4, 2016.
Schoffman, D. E., Turner-McGrievy, G., Jones, S. J., and Wilcox, S., Mobile apps for pediatric obesity prevention and treatment, healthy eating, and physical activity promotion: just fun and games? Transl Behav Med 3:320–325, 2013.
Siddiqui, M., ul Islam, M. Y., Mufti, B. A. I., Khan, N., Farooq, M. S., Muhammad, M. G., Osama, M., Kherani, D., Kazi, A. N., and Kazi, A. M., Assessing acceptability of hypertensive/diabetic patients towards mobile health based behavioral interventions in Pakistan: A pilot study. Int J Med Inf 84:950–955, 2015.
Author information
Authors and Affiliations
Corresponding author
Additional information
This article is part of the Topical Collection on Mobile Systems
Rights and permissions
About this article
Cite this article
Bhuyan, S.S., Lu, N., Chandak, A. et al. Use of Mobile Health Applications for Health-Seeking Behavior Among US Adults. J Med Syst 40, 153 (2016). https://doi.org/10.1007/s10916-016-0492-7
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10916-016-0492-7