Athletic Training and Sports Health Care

Sports Medicine Digest 

Facilitators and Barriers to Mobile Health (mHealth) Application Adoption

Shelby J. Doades, ATC; Zachary Kyle Winkelmann, MS, LAT, ATC

Abstract

Gagnon MP, Ngangue P, Payne-Gagnon J, Desmartis M. m-Health adoption by healthcare professionals: a systematic review. J Am Med Inform Assoc. 2016;23:212–220.

Clinical Question: In the past decade, there has been an exponential growth of individuals who own a mobile phone or other portable electronic communication device.1 Modern technological advances have enabled mobile communication devices to perform functions related to mobile health (mHealth) that previously were impossible. Many definitions for mHealth have been proposed, but they are all based on the idea of mobile technology as a tool to enhance health services for both the health care practitioner and patient.2 The mHealth interventions are designed to improve health care by using mobile devices and smartphones to target communication between health care services and consumers, while also providing support between health care providers.3 The mHealth application is mainly consumer driven and is considered to be an affordable option to increase health promotion, disease prevention, clinician-patient communication, and interprofessional communication.3 The potential benefits of mHealth may never come to fruition for clinical practice if mHealth is not adopted and encouraged in daily clinical practice. Therefore, what are the factors influencing heath care professionals' adoption of mHealth applications?

Data Sources: We identified a systematic review from 2016 that charted the facilitators and barriers to mHealth adoption. The systematic review included literature from four electronic databases (PubMed, EMBASE, CINAHL, and PsychoInfo) between 2000 and 2014. In reference to mHealth, articles included the term mHealth or included both the term health and one of the following terms or their variants: handheld computer, mobile phone, smartphone, mobile application, mobile app, cellular phone, mobile device, mobile technology, SMS, or text message. Finally, the following terms were used to search adoption: acceptance, acceptability, utilization, or attitude.

Study Selection: Studies were included if they mentioned health care professionals' perceptions regarding barriers and facilitators to mHealth utilization, had abstracts written in English, Spanish, or French, and were presented in an empirical study design, which included qualitative, quantitative, or mixed methods. The search strategy led to 4,223 potentially relevant studies, and 33 met the inclusion criteria.

Data Extraction: One reviewer initially screened all of the titles and abstracts from articles based on the study selection and data collection strategies. Another reviewer analyzed the titles and abstracts retained. Then, two reviewers independently read the full text of the preselected articles and collaborated on their final selections. Two distinct groups composed of two authors each independently performed data extraction using a validated data extraction grid, developed through previous research related to the data included in this systematic review. From the included papers, 179 elements were identified as barriers and facilitators regarding the difficulties and opportunities for mHealth adoption.

Main Results: The results from the systematic review identified 81 (45.3%) barriers and 98 (54.7%) facilitators for mHealth adoption.2 The perceived adoption factors of mHealth categorized at the individual, organizational, and contextual levels were perceived usefulness and ease of use, design and technical concerns, cost, time, privacy and security issues, familiarity with the technology, risk-benefit assessment, and interaction with others (colleagues, patients, and management).2 The individual level included the most facilitators for mHealth adoption, with risk-benefit assessment being the most prominent. The organizational level was distributed evenly between 20 barriers and 18 facilitators. The contextual level demonstrated more barriers, focusing more on patient-professional relationships and patient and professional attitudes about mHealth.2Table 1 summarizes the barriers and facilitators per category identified in the systematic review.…

Gagnon MP, Ngangue P, Payne-Gagnon J, Desmartis M. m-Health adoption by healthcare professionals: a systematic review. J Am Med Inform Assoc. 2016;23:212–220.

Clinical Question: In the past decade, there has been an exponential growth of individuals who own a mobile phone or other portable electronic communication device.1 Modern technological advances have enabled mobile communication devices to perform functions related to mobile health (mHealth) that previously were impossible. Many definitions for mHealth have been proposed, but they are all based on the idea of mobile technology as a tool to enhance health services for both the health care practitioner and patient.2 The mHealth interventions are designed to improve health care by using mobile devices and smartphones to target communication between health care services and consumers, while also providing support between health care providers.3 The mHealth application is mainly consumer driven and is considered to be an affordable option to increase health promotion, disease prevention, clinician-patient communication, and interprofessional communication.3 The potential benefits of mHealth may never come to fruition for clinical practice if mHealth is not adopted and encouraged in daily clinical practice. Therefore, what are the factors influencing heath care professionals' adoption of mHealth applications?

Data Sources: We identified a systematic review from 2016 that charted the facilitators and barriers to mHealth adoption. The systematic review included literature from four electronic databases (PubMed, EMBASE, CINAHL, and PsychoInfo) between 2000 and 2014. In reference to mHealth, articles included the term mHealth or included both the term health and one of the following terms or their variants: handheld computer, mobile phone, smartphone, mobile application, mobile app, cellular phone, mobile device, mobile technology, SMS, or text message. Finally, the following terms were used to search adoption: acceptance, acceptability, utilization, or attitude.

Study Selection: Studies were included if they mentioned health care professionals' perceptions regarding barriers and facilitators to mHealth utilization, had abstracts written in English, Spanish, or French, and were presented in an empirical study design, which included qualitative, quantitative, or mixed methods. The search strategy led to 4,223 potentially relevant studies, and 33 met the inclusion criteria.

Data Extraction: One reviewer initially screened all of the titles and abstracts from articles based on the study selection and data collection strategies. Another reviewer analyzed the titles and abstracts retained. Then, two reviewers independently read the full text of the preselected articles and collaborated on their final selections. Two distinct groups composed of two authors each independently performed data extraction using a validated data extraction grid, developed through previous research related to the data included in this systematic review. From the included papers, 179 elements were identified as barriers and facilitators regarding the difficulties and opportunities for mHealth adoption.

Main Results: The results from the systematic review identified 81 (45.3%) barriers and 98 (54.7%) facilitators for mHealth adoption.2 The perceived adoption factors of mHealth categorized at the individual, organizational, and contextual levels were perceived usefulness and ease of use, design and technical concerns, cost, time, privacy and security issues, familiarity with the technology, risk-benefit assessment, and interaction with others (colleagues, patients, and management).2 The individual level included the most facilitators for mHealth adoption, with risk-benefit assessment being the most prominent. The organizational level was distributed evenly between 20 barriers and 18 facilitators. The contextual level demonstrated more barriers, focusing more on patient-professional relationships and patient and professional attitudes about mHealth.2Table 1 summarizes the barriers and facilitators per category identified in the systematic review.

Facilitators and Barriers to Mobile Health (mHealth) Adoption

Table 1:

Facilitators and Barriers to Mobile Health (mHealth) Adoption

Conclusions: The two most important factors that emerged from the review regarding the adoption of mHealth were perceived usefulness and ease of use of the technology. These factors were important for the health care practitioner and patient, and were listed as facilitators and barriers to adoption.2 The usefulness and ease of use pertain to the individual factor that learning and using the technology will be effortless, while also providing improvements over their current clinical practice. Clinicians' behavioral intentions rely on these two factors when considering adoption. It is vital that athletic trainers approach mHealth options with an open mind about how the device may benefit their own and their patients' care. As athletic trainers, we must understand the changing landscape of communication across the population with respect to digital and social media. The current generation (born between 1995 and 2012) has grown up with instant access to technology. It is important to understand that it is likely our current and future patients from this generation will use mHealth due to their familiarity with technology and mobile communication.

Summary: The mHealth application empowers patients because it increases their knowledge of their health and enhances the positive patient-clinician relationship, which facilitates the idea of mHealth being a patient-centered and consumer-driven approach to health care.1 The mHealth application can initiate interactions and provide a singular database of specific information regarding an injury, illness, or condition.4 Individuals in developed countries are also growing up with instant access to information, options, and answers at their fingertips. The systematic review identified that instant access to information is a facilitator for mHealth adoption. However, patients having the independence to search for their symptoms is also a barrier to the adoption of mHealth applications because patients may self-diagnose and not seek the proper health care.2 This has led to the increase of conditions, such as Munchausen syndrome, in which patients self-diagnose using online resources or begin to take on the signs and symptoms they are finding on mHealth applications.5 Patient access to health care resources can also be a barrier that results in patients presenting false information or phony diagnostic imaging to health care professionals and decreasing the clinician's effectiveness in treating their condition.

The mHealth applications can also increase the cooperativity of patients with differing pathologies or illnesses, including orthopedic injuries,4 by providing reminder notifications for home exercise programs, medicine intake, or appointments. This is of interest in athletic training to improve the compliance of therapeutic interventions and promotion of health behaviors as a means of prevention. Examples of general mHealth applications that may be beneficial to populations served by athletic trainers include nutritional and dietary applications to assist patients with calorie counting and locating healthy restaurants, monitoring sleep habits, and mental health applications to treat and reduce the patient's stress and anxiety. Athletic trainers predominately diagnose and manage musculoskeletal conditions, and there are several mHealth applications designed for therapeutic exercise and objective balance testing. Finally, health care administration mHealth applications can provide opportunities for patient scheduling and medical documentation.

This systematic review concluded that most of the literature identified positive indications versus negative outcomes for the implementation of mHealth interventions. The secondary school athletic training setting has a large patient load with limited time per patient interaction. Secondary school athletic trainers should consider using mHealth applications to provide home exercise programs, objective testing, and health behavior reminders to maximize the desired outcomes following the school day. Athletic trainers must be aware that mHealth has barriers to its implementation, which include initial cost, training and continuing education on the platforms, and unforeseen technological issues. However, mHealth is a promising tool to support health care and a unique way to provide information and resources to patients to better understand their conditions, while also giving health care professionals a useful tool to provide information effectively to their patients.

References:

  1. Putzer GJ, Park Y. The effects of innovation factors on smartphone adoption among nurses in community hospitals. Perspect Health Inf Manag. 2010;7:1b.
  2. Gagnon MP, Ngangue P, Payne-Gagnon J, Desmartis M. m-Health adoption by healthcare professionals: a systematic review. J Am Med Inform Assoc. 2016;23:212–220. doi:10.1093/jamia/ocv052 [CrossRef]
  3. Free C, Phillips G, Watson L, et al. The effectiveness of mobile-health technologies to improve health care service delivery processes: a systematic review and meta-analysis. PLoS Med. 2013;10:e1001363. doi:10.1371/journal.pmed.1001363 [CrossRef]
  4. Chen C, Haddad D, Selsky J, et al. Making sense of mobile health data: an open architecture to improve individual- and population-level health. J Med Internet Res. 2012;14:e112. doi:10.2196/jmir.2152 [CrossRef]
  5. Griffiths EJ, Kampa R, Pearce C, Sakellariou A, Solan MC. Munchausen's syndrome by Google. Ann R Coll Surg Engl. 2009;91:159–160. doi:10.1308/003588409X391938 [CrossRef]

Facilitators and Barriers to Mobile Health (mHealth) Adoption

IndividualOrganizationalContextual
TimelinessHealth care system and management supportPatient-professional interactions
Familiarity and ability with technologyImposition of devices on professionalsPatients' attitude toward mHealth
Agreement with the technologyPoor management of informationColleague attitudes toward mHealth
Risk-benefitAvailabilityMiscommunications
Improve patient careAccess to material
Professional experienceHuman resources
Professional autonomyCosts
Clinical uncertaintyUsefulness
Outcome expectancyAdditional tasks
Self-efficacyTraining
Professional securityChoice of system
Awareness of mHealthWorkplace readiness
Familiarity and ability with technology
Voluntary ownership of mHealth
Disrupted work flow
Authors

From the Neuromechanics, Interventions, and Continuing Education Research (NICER) Laboratory, Department of Applied Medicine and Rehabilitation, Indiana State University, Terre Haute, Indiana.

The authors have no financial or proprietary interest in the materials presented herein.

Correspondence: Zachary Kyle Winkelmann, MS, LAT, ATC, Neuromechanics, Interventions, and Continuing Education Research (NICER) Laboratory, Department of Applied Medicine and Rehabilitation, Indiana State University, 567 N. 5th Street, Terre Haute, IN 47809. E-mail: zwinkelmann@sycamores.indstate.edu

10.3928/19425864-20181101-02

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