A Systematic Review of Factors Associated to M-Health Adoption by Health Care Professionals
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Abstract
Background: As the number of people in the world owning a mobile phone or other portable electronic communication device has grown exponentially during the last decade, m-health (standing for mobile health) is gaining increasing attention. M-health presents a unique tool to provide information, education and resources to both health care providers and patients. However, even with the increased presence of m-health in our everyday life, its use by health care professionals to provide information and care has received limited attention.
Objective: This systematic literature review aims to synthesize current knowledge of the factors influencing health care professional adoption of mobile health (m-health) applications.
Methods: Covering a period from 2000 to 2013, we conducted a systematic literature search on four electronic databases (PubMed, EMBASE, CINAHL, PsychInfo). We also consulted references from included studies. Studies were included if they reported health care professionals’ perceptions regarding barriers and facilitators to m-health utilization. We also included studies published in English, Spanish or French, that presented an empirical study design (either qualitative, quantitative, or mixed-methods). Two authors independently assessed study inclusion and performed content analysis using a validated extraction grid with pre-established categorization of barriers and facilitators
Results: The search strategy led to a total of 4096 potentially relevant papers, of which 27 met the inclusion criteria. Studies were conducted in various settings, including high-, middle- and low-income countries. We synthesized main findings related to perceived factors associated to m-health adoption at the technological, individual, group and organizational levels. In total, we identified 150 elements that emerged as barriers or facilitators to m-health adoption by health care providers. Technology-related factors were the most frequent, with a total of 58 elements, followed by individual factors with 40 elements. Organizational and group factors represented 35 and 17 elements, respectively.
Under the technology-related factors, perceived usefulness and ease of use were the most recurrent factors (19 and 6 elements, respectively), underscoring their importance for m-health adoption by health care professionals. At the individual level, most factors were seen as facilitators. Among those identified, time saving (9 elements), improvement of patient care (7 elements) and agreement with the technology (6 elements) were seen as important factors. Under the group and organizational factors, the impact of m-health on interpersonal relations and communication was highlighted. Indeed, patient and health professional interaction (7 elements) and relation among colleagues (6 elements) were identified as important factors that influence m-health adoption. Only a few studies explicitly used a theoretical framework, so future research on m-health adoption should be based on theories such as the Technology Acceptance Model or the Task-Technology Fit Theory.
Conclusions: Several factors are associated with m-health adoption at the individual, organizational and contextual levels. This systematic review provides a set of key elements to understand the challenges and opportunities for m-health adoption by health care professionals.
Objective: This systematic literature review aims to synthesize current knowledge of the factors influencing health care professional adoption of mobile health (m-health) applications.
Methods: Covering a period from 2000 to 2013, we conducted a systematic literature search on four electronic databases (PubMed, EMBASE, CINAHL, PsychInfo). We also consulted references from included studies. Studies were included if they reported health care professionals’ perceptions regarding barriers and facilitators to m-health utilization. We also included studies published in English, Spanish or French, that presented an empirical study design (either qualitative, quantitative, or mixed-methods). Two authors independently assessed study inclusion and performed content analysis using a validated extraction grid with pre-established categorization of barriers and facilitators
Results: The search strategy led to a total of 4096 potentially relevant papers, of which 27 met the inclusion criteria. Studies were conducted in various settings, including high-, middle- and low-income countries. We synthesized main findings related to perceived factors associated to m-health adoption at the technological, individual, group and organizational levels. In total, we identified 150 elements that emerged as barriers or facilitators to m-health adoption by health care providers. Technology-related factors were the most frequent, with a total of 58 elements, followed by individual factors with 40 elements. Organizational and group factors represented 35 and 17 elements, respectively.
Under the technology-related factors, perceived usefulness and ease of use were the most recurrent factors (19 and 6 elements, respectively), underscoring their importance for m-health adoption by health care professionals. At the individual level, most factors were seen as facilitators. Among those identified, time saving (9 elements), improvement of patient care (7 elements) and agreement with the technology (6 elements) were seen as important factors. Under the group and organizational factors, the impact of m-health on interpersonal relations and communication was highlighted. Indeed, patient and health professional interaction (7 elements) and relation among colleagues (6 elements) were identified as important factors that influence m-health adoption. Only a few studies explicitly used a theoretical framework, so future research on m-health adoption should be based on theories such as the Technology Acceptance Model or the Task-Technology Fit Theory.
Conclusions: Several factors are associated with m-health adoption at the individual, organizational and contextual levels. This systematic review provides a set of key elements to understand the challenges and opportunities for m-health adoption by health care professionals.
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