Facilitators of and Barriers to mHealth Adoption in Older Adults With Heart Failure

Abstract

The purpose of this descriptive, exploratory study was to assess the perceptions of older adults with heart failure regarding the use of mobile technology and to identify potential facilitators of and barriers to mHealth adoption. Semistructured interviews were used to collect data. Transcripts were analyzed using qualitative content analysis. The findings indicated that older adults do not base their intention to use mHealth solely on perceived ease of use and perceived usefulness, as outlined in the Technology Acceptance Model. The following themes emerged from the content analysis: facilitators included previous experience with mobile technology, willingness to learn mHealth, ease of use, presence of useful features, adequate training, free equipment, and doctor's recommendation; barriers included lack of knowledge regarding how to use mHealth, decreased sensory perception, lack of need for technology, poorly designed interface, cost of technology, and limited/fixed income. Overall, the findings suggest that older adults are willing to use mobile health technology, albeit with reservations. Future researchers who seek to implement mHealth-based interventions should address person-related, technology-related, and contextual barriers, and simultaneously capitalize on the influence of potential facilitators, such as a physician's recommendation, to promote mHealth adoption.

Telemedicine Healthcare Service Adoption Barriers in Rural Bangladesh

“…No conceptual or theoretical frameworks concerning the relationships between telemedicine barriers and adoption were found. Robust prior studies in telemedicine, e-Health, telehealth, and m-Health (Alaboudi et al, 2016;Bigna, Noubiap, Plottel, Kouanfack, & Koulla-Shiro, 2014;Boonstra & Broekhuis, 2010;Bullock et al, 2017;Cajita, Hodgson, Lam, Yoo, & Han, 2018;De Bustos, Moulin, & Audebert, 2009;Faber, van Geenhuizen, & de Reuver, 2017;Freed et al, 2018;Gravel, Légaré, & Graham, 2006;Jang-Jaccard et al, 2014;Johnson, 2001;Leaming, 2007;LeRouge & Garfield, 2013;Lin, Lin, & Roan, 2012;Lohmann, Muula, Houlfort, & De Allegri, 2018;Modi, Portney, Hollenbeck, & Ellimoottil, 2018;Moffatt & Eley, 2011;Ramtohul, 2015;Rogove, McArthur, Demaerschalk, & Vespa, 2012;Scott Kruse et al, 2018;Scott & Mars, 2013;Van Dyk, 2014;Whitten, Holtz, Meyer, & Nazione, 2009) were used to develop and test the hypotheses regarded as mutually exclusive and exhaustive when considered from a model parsimony perspective. These seven broad categories of barriers are encapsulated in the study's conceptual model (see Figure 1).…”

The difference in knowledge and attitudes of using mobile health applications between actual user and non-user among adults aged 50 and older

“…We developed a questionnaire based on a literature review, qualitative interviews, and expert opinion. First, we reviewed previous studies that examined factors associated with mHA adoption and developed a conceptual framework using the Health Belief Model [ 20 , 24 , 26 , 33 – 35 ]. We also reviewed previous national surveys that examined similar behaviors [ 40 ].…”

“…Moreover, as aging decreases visual and cognitive function, older adults would have more difficulties using mHAs on the small screen of a smartphone [ 24 ]. Furthermore, previous studies found that old adults experienced low self-efficacy in using mHAs due to lack of technical proficiency, and they had low intention to use the technology [ 19 , 24 , 33 ]. Nevertheless, many within these same age groups have expressed a strong interest in using mobile solutions to manage their conditions; they have simply reported obstacles and barriers in usage.…”

Mobile health and cardiac rehabilitation in older adults

“…While literature supports that older adults may accept new technologies, they often do so with less confidence than younger adults . In a qualitative study on the use of mHealth in older patients with heart failure, lack of knowledge, and even “fear” of misusing the technology, were the most commonly cited barriers to mHealth adoption …”

“…65 In a qualitative study on the use of mHealth in older patients with heart failure, lack of knowledge, and even "fear" of misusing the technology, were the most commonly cited barriers to mHealth adoption. 66 In addition to implementation barriers, there are other potential barriers to success: most notably, current mHealth-CR platforms generally lack the socialization with other patients (peer support) inherent to facility-based CR. This socialization, while difficult to quantify, may help to address the loneliness commonly experienced by older patients with CVD.…”