Usability of a Novel Mobile Health iPad App by Vulnerable Populations

David P Miller Jr, Kathryn E Weaver, L Doug Case, Donald Babcock, Donna Lawler, Nancy Denizard-Thompson, Michael P Pignone, John G Spangler, David P Miller Jr, Kathryn E Weaver, L Doug Case, Donald Babcock, Donna Lawler, Nancy Denizard-Thompson, Michael P Pignone, John G Spangler

Abstract

Background: Recent advances in mobile technologies have created new opportunities to reach broadly into populations that are vulnerable to health disparities. However, mobile health (mHealth) strategies could paradoxically increase health disparities, if low socioeconomic status individuals lack the technical or literacy skills needed to navigate mHealth programs.

Objective: The aim of this study was to determine whether patients from vulnerable populations could successfully navigate and complete an mHealth patient decision aid.

Methods: We analyzed usability data from a randomized controlled trial of an iPad program designed to promote colorectal cancer (CRC) screening. The trial was conducted in six primary care practices and enrolled 450 patients, aged 50-74 years, who were due for CRC screening. The iPad program included a self-survey and randomly displayed either a screening decision aid or a video about diet and exercise. We measured participant ability to complete the program without assistance and participant-rated program usability.

Results: Two-thirds of the participants (305/450) were members of a vulnerable population (limited health literacy, annual income < US $20,000, or black race). Over 92% (417/450) of the participants rated the program highly on all three usability items (90.8% for vulnerable participants vs 96.6% for nonvulnerable participants, P=.006). Only 6.9% (31/450) of the participants needed some assistance to complete the program. In multivariable logistic regression, being a member of a vulnerable population was not associated with needing assistance. Only older age, less use of text messaging (short message service, SMS), and lack of Internet use predicted needing assistance.

Conclusions: Individuals who are vulnerable to health disparities can successfully use well-designed mHealth programs. Future research should investigate whether mHealth interventions can reduce health disparities.

Keywords: decision support techniques; health literacy; primary care; technology assessment; vulnerable populations.

Conflict of interest statement

Conflicts of Interest: None declared.

©David P Miller Jr, Kathryn E Weaver, L Doug Case, Donald Babcock, Donna Lawler, Nancy Denizard-Thompson, Michael P Pignone, John G Spangler. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 11.04.2017.

Figures

Figure 1
Figure 1
Sample screenshots from mobile Patient Technology for Health (mPATH) iPad program.

References

    1. Braveman P, Egerter S, Williams D. The social determinants of health: coming of age. Annu Rev Public Health. 2011;32:381–98. doi: 10.1146/annurev-publhealth-031210-101218.
    1. Marmot M. Social determinants of health inequalities. The Lancet. 2005 Mar;365(9464):1099–1104.
    1. Braveman P, Cubbin C, Egerter S, Williams D, Pamuk E. Socioeconomic disparities in health in the United States: what the patterns tell us. Am J Public Health. 2010 Apr 01;100(Suppl 1):S186–96. doi: 10.2105/AJPH.2009.166082.
    1. Ward E, Jemal A, Cokkinides V, Singh GK, Cardinez C, Ghafoor A, Thun M. Cancer disparities by race/ethnicity and socioeconomic status. CA Cancer J Clin. 2004;54(2):78–93.
    1. Nutbeam D. The evolving concept of health literacy. Soc Sci Med. 2008 Dec;67(12):2072–2078.
    1. von Wagner C, Semmler C, Good A, Wardle J. Health literacy and self-efficacy for participating in colorectal cancer screening: the role of information processing. Patient Educ Couns. 2009 Jun;75(3):352–357.
    1. Anderson M. Pew Research Center. 2015. Oct, [2017-01-04]. Technology Device Ownership .
    1. Ventola C. Mobile devices and apps for health care professionals: uses and benefits. Pharm Ther. 2014 May;39(5):356–64.
    1. Mickan S, Tilson J, Atherton H, Roberts N, Heneghan C. Evidence of effectiveness of health care professionals using handheld computers: a scoping review of systematic reviews. J Med Internet Res. 2013 Oct 28;15(10):e212. doi: 10.2196/jmir.2530.
    1. Fiordelli M, Diviani N, Schulz P. Mapping mHealth research: a decade of evolution. J Med Internet Res. 2013 May 21;15(5):e95. doi: 10.2196/jmir.2430.
    1. Free C, Phillips G, Galli L, Watson L, Felix L, Edwards P, Patel V, Haines A. The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: a systematic review. PLoS Med. 2013;10(1):e1001362. doi: 10.1371/journal.pmed.1001362.
    1. Gibbons MC. A historical overview of health disparities and the potential of eHealth solutions. J Med Internet Res. 2005 Oct 04;7(5):e50. doi: 10.2196/jmir.7.5.e50.
    1. American Cancer Society . Colorectal Cancer Facts & Figures 2014-2016. Atlanta: American Cancer Society; 2014.
    1. Siegel R, DeSantis C, Jemal A. Colorectal cancer statistics, 2014. CA Cancer J Clin. 2014 Mar 1;64(2):104–117.
    1. Joseph D, Redwood D, DeGroff A, Butler E. Use of evidence-based interventions to address disparities in colorectal cancer screening. MMWR Suppl. 2016 Feb 12;65(1):21–28.
    1. Sarkar U, Gourley G, Lyles C, Tieu L, Clarity C, Newmark L, Singh K, Bates DW. Usability of commercially available mobile applications for diverse patients. J Gen Intern Med. 2016 Dec;31(12):1417–1426. doi: 10.1007/s11606-016-3771-6.
    1. Czaja S, Zarcadoolas C, Vaughon W, Lee C, Rockoff M, Levy J. The usability of electronic personal health record systems for an underserved adult population. Hum Factors J Hum Factors Ergon Soc. 2015 May 01;57(3):491–506.
    1. Kutner M, Greenberg E, Jin Y, Boyle B, Hsu Y, Dunleavy E. Literacy in Everyday Life: Results from the 2003 National Assessment of Adult Literacy (NCES 2007-490) Washington, DC: National Center for Education Statistics; 2007.
    1. Caprani N, O'Connor N, Gurrin C. InTechopen. 2012. [2017-03-07]. Touch screens for the older user .
    1. Findlater L, Froehlich J, Fattal K, Wobbrock J, Dastyar T. Age-related differences in performance with touchscreens compared to traditional mouse input. Proc SIGCHI Conf Hum Factors Comput Syst; SIGCHI Conference on Human Factors in Computing Systems; 2013; Paris. New York: ACM; 2013. pp. 343–346.
    1. Orphanides AK, Nam CS. Touchscreen interfaces in context: a systematic review of research into touchscreens across settings, populations, and implementations. Appl Ergon. 2017 May;61:116–143.
    1. Motti L, Vigouroux N, Gorce P. Ease-of-Use of Tactile Interaction for Novice Older Adults. In: Zhou J, Salvendy G, editors. Human Aspects of IT for the Aged Population. Design for Aging. Cham: Springer International Publishing; 2015. pp. 463–474.
    1. Piper A, Campbell R, Hollan J. Exploring the accessibility and appeal of surface computing for older adult health care support. Proc SIGCHI Conf Hum Factors Comput Syst; ACM Conference on Human Factors in Computing Systems; 2010; Atlanta. New York: ACM; 2010. pp. 907–916.
    1. Centers for Disease Control and Prevention CDC. 2009. [2017-03-07]. Simply put: a guide for creating easy-to-understand materials .
    1. Lee S, Zhai S. The performance of touch screen soft buttons. Proc SIGCHI Conf Hum Factors Comput Syst; CHI Conference on Human Factors in Computing Systems; 2009; Boston. New York: ACM; 2009. pp. 309–318.
    1. Safeer R, Keenan J. Health literacy: the gap between physicians and patients. Am Fam Physician. 2005;72(3):463–468.
    1. Miller DP, Spangler JG, Case LD, Goff DC, Singh S, Pignone MP. Effectiveness of a web-based colorectal cancer screening patient decision aid. Am J Prev Med. 2011 Jun 1;40(6):608–615.
    1. CDC. 2013. [2017-01-04]. CDC-TV Video: Finding Balance Internet .
    1. Bangor A, Kortum P, Miller J. An Empirical Evaluation of the System Usability Scale. Int J Hum-Comput Interact. 2008;24(6):574–594. doi: 10.1080/10447310802205776.
    1. Chew L, Griffin J, Partin M, Noorbaloochi S, Grill J, Snyder A, Bradley KA, Nugent SM, Baines AD, Vanryn M. Validation of screening questions for limited health literacy in a large VA outpatient population. J Gen Intern Med. 2008 May;23(5):561–6. doi: 10.1007/s11606-008-0520-5.
    1. Bravo C, O'Donoghue C, Kaplan C, Luce J, Ozanne E. Can mHealth improve risk assessment in underserved populations? Acceptability of a breast health questionnaire app in ethnically diverse, older, low-income women. J Health Dispar Res Pract. 2014;7(4)
    1. Hess R, Santucci A, McTigue K, Fischer G, Kapoor W. Patient Difficulty Using Tablet Computers to Screen in Primary Care. J Gen Intern Med. 2008 Apr;23(4):476–80.
    1. Taha J, Sharit J, Czaja S. The impact of numeracy ability and technology skills on older adults' performance of health management tasks using a patient portal. J Appl Gerontol. 2014 Jun 1;33(4):416–36. doi: 10.1177/0733464812447283.
    1. Lyles C, Sarkar U. Health literacy, vulnerable patients, and health information technology use: where do we go from here? J Gen Intern Med. 2015 Jan 15;30(3):271–2.
    1. Georgsson M, Staggers N. Quantifying usability: an evaluation of a diabetes mHealth system on effectiveness, efficiency, and satisfaction metrics with associated user characteristics. J Am Med Inform Assoc. 2016 Jan 1;23(1):5–11.
    1. Kim E-H, Stolyar A, Lober W, Herbaugh A, Shinstrom S, Zierler B, Soh C, Kim Y. Challenges to using an electronic personal health record by a low-income elderly population. J Med Internet Res. 2009 Oct 27;11(4)
    1. Levy H, Janke A, Langa K. Health literacy and the digital divide among older Americans. J Gen Intern Med. 2014 Nov 12;30(3):284–9.
    1. Jensen J, King A, Davis L, Guntzviller L. Utilization of internet technology by low-income adults: the role of health literacy, health numeracy, and computer assistance. J Aging Health. 2010 Sep 1;22(6):804–26.
    1. Choi NG, Dinitto DM. The digital divide among low-income homebound older adults: internet use patterns, eHealth literacy, and attitudes toward computer/Internet use. J Med Internet Res. 2013 May 02;15(5):e93. doi: 10.2196/jmir.2645.
    1. Lober W, Zierler B, Herbaugh A, Shinstrom S, Stolyar A, Kim E, Kim Y. Barriers to the use of a Personal Health Record by an Elderly Population. AMIA Annual Symposium; 2006; Washington, DC. 2006. pp. 514–518.
    1. Venkatesh V, Bala H. Technology acceptance model 3 and a research agenda on interventions. Decis Sci. 2008 May 1;39(2):273–315. doi: 10.1111/j.1540-5915.2008.00192.x.
    1. Gordon N, Hornbrook M. Differences in access to and preferences for using patient portals and other eHealth technologies based on race, ethnicity, and age: a database and survey study of seniors in a large health plan. J Med Internet Res. 2016 Mar 4;18(3):e50.
    1. Lyles C, Schillinger D, Sarkar U. Connecting the dots: health information technology expansion and health disparities. PLoS Med. 2015 Jul;12(7):e1001852. doi: 10.1371/journal.pmed.1001852.
    1. Roundtable on the Promotion of Health Equity and the Elimination of Health Disparities. Board on Population Health and Public Health Practice. Health and Medicine Division. National Academies of Sciences, Engineering, and Medicine . In: The Promises and Perils of Digital Strategies in Achieving Health Equity: Workshop Summary. Anderson KM, Olson S, editors. Washington, DC: National Academies Press; 2016.
    1. Mackert M, Mabry-Flynn A, Champlin S, Donovan EE, Pounders K. Health literacy and health information technology adoption: the potential for a new digital divide. J Med Internet Res. 2016 Oct 04;18(10):e264. doi: 10.2196/jmir.6349.
    1. Horrigan J, Duggan M. Pew Research Center. 2015. [2017-01-04]. Home Broadband 2015 Internet

Source: PubMed

Szponzorok és közreműködők

Egészségi állapot

Kábítószer-beavatkozások

3
Iratkozz fel