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Sökning: onr:"swepub:oai:DiVA.org:mdh-51083" > Understanding Clini...

LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00005396naa a2200505 4500
001oai:DiVA.org:mdh-51083
003SwePub
008201007s2020 | |||||||||||000 ||eng|
0247 a https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-510832 URI
0247 a https://doi.org/10.2196/180722 DOI
040 a (SwePub)mdh
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a for2 swepub-publicationtype
1001 a Jacob, Christineu Anglia Ruskin Univ, East Rd, Cambridge CB1 1PT, England.;Univ Appl Sci Northwestern Switzerland, Brugg, Switzerland.4 aut
2451 0a Understanding Clinicians' Adoption of Mobile Health Tools :b A Qualitative Review of the Most Used Frameworks
264 c 2020-07-06
264 1b JMIR PUBLICATIONS, INC,c 2020
338 a print2 rdacarrier
520 a Background: Although there is a push toward encouraging mobile health (mHealth) adoption to harness its potential, there are many challenges that sometimes go beyond the technology to involve other elements such as social, cultural, and organizational factors. Objective: This review aimed to explore which frameworks are used the most, to understand clinicians' adoption of mHealth as well as to identify potential shortcomings in these frameworks. Highlighting these gaps and the main factors that were not specifically covered in the most frequently used frameworks will assist future researchers to include all relevant key factors. Methods: This review was an in-depth subanalysis of a larger systematic review that included research papers published between 2008 and 2018 and focused on the social, organizational, and technical factors impacting clinicians' adoption of mHealth. The initial systematic review included 171 studies, of which 50 studies used a theoretical framework. These 50 studies are the subject of this qualitative review, reflecting further on the frameworks used and how these can help future researchers design studies that investigate the topic of mHealth adoption more robustly. Results: The most commonly used frameworks were different forms of extensions of the Technology Acceptance Model (TAM; 17/50, 34%), the diffusion of innovation theory (DOI; 8/50, 16%), and different forms of extensions of the unified theory of acceptance and use of technology (6/50, 12%). Some studies used a combination of the TAM and DOI frameworks (3/50, 6%), whereas others used the consolidated framework for implementation research (3/50, 6%) and sociotechnical systems (STS) theory (2/50, 4%). The factors cited by more than 20% of the studies were usefulness, output quality, ease of use, technical support, data privacy, self-efficacy, attitude, organizational inner setting, training, leadership engagement, workload, and workflow fit. Most factors could be linked to one framework or another, but there was no single framework that could adequately cover all relevant and specific factors without some expansion. Conclusions: Health care technologies are generally more complex than tools that address individual user needs as they usually support patients with comorbidities who are typically treated by multidisciplinary teams who might even work in different health care organizations. This special nature of how the health care sector operates and its highly regulated nature, the usual budget deficits, and the interdependence between health care organizations necessitate some crucial expansions to existing theoretical frameworks usually used when studying adoption. We propose a shift toward theoretical frameworks that take into account implementation challenges that factor in the complexity of the sociotechnical structure of health care organizations and the interplay between the technical, social, and organizational aspects. Our consolidated framework offers recommendations on which factors to include when investigating clinicians' adoption of mHealth, taking into account all three aspects.
650 7a SAMHÄLLSVETENSKAPx Annan samhällsvetenskap0 (SwePub)5092 hsv//swe
650 7a SOCIAL SCIENCESx Other Social Sciences0 (SwePub)5092 hsv//eng
653 a telemedicine
653 a smartphone
653 a electronic health record
653 a workflow
653 a workload
653 a workplace
653 a public health practice
653 a technology
653 a perception
653 a health education
653 a mHealth
653 a mobile health
653 a telehealth
653 a eHealth
7001 a Sanchez-Vazquez, Antoniou Anglia Ruskin Univ, Innovat & Management Practice Res Ctr, Cambridge, England.4 aut
7001 a Ivory, Chrisu Anglia Ruskin Univ, Innovat & Management Practice Res Ctr, Cambridge, England.,IPR4 aut0 (Swepub:mdh)ciy01
7102 a Anglia Ruskin Univ, East Rd, Cambridge CB1 1PT, England.;Univ Appl Sci Northwestern Switzerland, Brugg, Switzerland.b Anglia Ruskin Univ, Innovat & Management Practice Res Ctr, Cambridge, England.4 org
7730 t JMIR mhealth and uhealthd : JMIR PUBLICATIONS, INCg 8:7q 8:7x 2291-5222
8564 u https://doi.org/10.2196/18072y Fulltext
8564 u https://jmir.org/api/download?alt_name=mhealth_v8i7e18072_app1.pdf&filename=e208ab3626d26492cfc6593212acac52.pdf
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-51083
8564 8u https://doi.org/10.2196/18072

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