Beyond TAM and UTAUT: Future directions for HIT implementation research

Shachak, Aviv; Kuziemsky, Craig; Petersen, Carolyn

doi:10.1016/j.jbi.2019.103315

Cited by 154 publications

(152 citation statements)

References 33 publications

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“…Some of the commonly used frameworks, such as TAM, present an oversimplified group of factors that need to be looked at in much more detail, and with greater specificity, if we are to develop and implement successful mHealth tools. Although it is sometimes claimed that it is simplicity that makes such frameworks useful [ 124 ], even in the health care context [ 91 , 125 , 126 ], our conclusions are aligned with the findings of researchers’ critical frameworks such as TAM and UTAUT for overemphasizing individual user beliefs and perceptions [ 127 ]. Most of these frameworks were not developed within a health care setting and thus overlook its organizational and regulatory complexity [ 91 , 128 , 129 ].…”

Section: Discussionsupporting

confidence: 80%

“…We propose a shift toward extended frameworks that take into account the complexity of health care organizations, their highly regulated nature, their interdependence, and the active role of the user in impacting how technology is being used in the work environment. Other researchers have also cited the technology-centered view of many of the broadly used models that mostly focus on the tool itself [ 128 , 129 , 131 ] and suggested a move to multidimensional theories that go beyond usability and consider the surrounding contexts and implementation issues [ 127 , 128 , 131 - 134 ]. Health care technology cannot be successfully adopted in isolation from the broader organizational context in which it is being used; therefore, we need to adopt theoretical frameworks that consider implementation challenges in light of the complexity of the sociotechnical structure and the interplay between the technical, social, and organizational aspects.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Understanding Clinicians’ Adoption of Mobile Health Tools: A Qualitative Review of the Most Used Frameworks

Jacob¹,

Sánchez-Vázquez²,

Ivory³

2020

JMIR Mhealth Uhealth

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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.

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Section: Discussionsupporting

confidence: 80%

Section: Discussionmentioning

confidence: 99%

Understanding Clinicians’ Adoption of Mobile Health Tools: A Qualitative Review of the Most Used Frameworks

Jacob¹,

Sánchez-Vázquez²,

Ivory³

2020

JMIR Mhealth Uhealth

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“…Since the 1980s, individual behavior and behavioral intention of information technology have become a research hotspot in the field of information systems, and a series of information technology acceptance models have been formed [18][19][20]. Among information technology accptance models, the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) are the most commonly used [21,22]. Meanwhile, the UTAUT model has stronger explanatory power than TAM in terms of explanation [21].…”

Section: Introductionmentioning

confidence: 99%

“…Among information technology accptance models, the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) are the most commonly used [21,22]. Meanwhile, the UTAUT model has stronger explanatory power than TAM in terms of explanation [21]. A number of models have been used to predict factors associated with the behavioral intention of m-Health [23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Determinants of the behavioral intention to use a mobile nursing application by nurses in China

Pan

Gao

2021

BMC Health Serv Res

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Background Although a mobile nursing application has began to adopt in nursing, few studies have focused on nurses’ behavioral intention of it. The objective of this study is to gain insight into the behavioral intention of nurses, i.e. chinese nurses of the future, to use a mobile nursing application. This study adopted an extension of the Unified Theory of Acceptance and Use of Technology to examine Chinese nurses’ acceptance of a mobile nursing application. Methods A total of 1207 nurses participated in the cross-sectional survey. The majority of nurses were female (96.2%). The mean age of the participants was 34.18 (SD 7.39). The hypothesized relationships were tested using AMOS structural equation model. Results All constructs exhibited an acceptable level of reliability and validity with Cα and CR > 0.7 and AVE > 0.5. An extension of the Unified Theory of Acceptance and Use of Technology Model had good explanatory power for nurses’ behavioral intention of a mobile nursing application. Although effort expectancy and perceived risks had a surprisingly insignificant effect on nurses’ behavioral intention to use a mobile nursing application, performance expectancy, social influence, facilitating conditions, self-efficacy, and perceived incentives demonstrated significant influence with β = .259, p < .001, β = .296, p < .001, β = .063, p = .037, β = .344, p < .001, β = .091, p = .001, respectively. Conclusion With 70.2% of the variance in behavioral intention to use a mobile nursing app explained by this model, it could be helpful for potential adopters, and further investigation should test the actual usage behavior for a mobile nursing app and investigate the related factors.

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“…Sehingga layak digunakan dalam skala aplikasi menengah ke bawah. Dalam banyak penelitian, model tersebut direduksi menjadi tiga konstruksi saja: manfaat yang dirasakan, persepsi kemudahan penggunaan, dan perhatian penggunaan (Shachak, Kuziemsky, & Petersen, 2019). Namun dalam evaluasi siistem Dashboard ini telah ditambah komponen yang melibatkan persepsi dalam kemudahan penggunaan, persepsi kebermanfaatan sistem, niat dalam berperilaku, pemakaian aktual.…”

Section: Gambar 16 Data Pengukuran Actual Usageunclassified

Evaluasi Sistem Dashboard Monitoring Presensi Akademik Mahasiswa

Sangkot

2020

jartika

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Abstrak: Teknologi pencatatan elektronik untuk presensi mahasiswa dapat menjadi solusi yang meminimalisir kekeliruan pada proses pencatatan dan rekap kehadiran. Perekapan presensi ini mempermudah proses pencatatan kehadiran mahasiswa secara terkomputerisasi agar data kehadiran langsung masuk ke komputer untuk selanjutnya mudah dilakukan pengolahan data presensi. Tujuan dari penelitian ini adalah untuk mengevaluasi sistem yang digunakan oleh user. Metode yang digunakan dalam penelitian ini adalah study evaluasi dengan menggunakan framework yaitu Technology Acceptance Model (TAM). Terdapat beberapa parameter yang dilakukan evaluasi sistem dengan menggunakan tools ini yaitu terkait dengan Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Behavioral Intention (BI), Actual Usage (AU). Mengenai penerapan sistem Dashboard, mayoritas responden siswa memberikan rata-rata sangat setuju pada komponen Perceived Ease Of Use (PEOU) sebesar 78%, Perceived Usefulness (PU) sebesar 73.8%, Behavioral Intention (BI) sebesar 76.8%, Actual Usage (AU) sebesar 78.87%. Sistem yang digunakan berdampak pada pelaksanaan monitoring kehadiran mahasiswa dalam perkuliahan. Staff administrasi dan akademik beserta mahasiswa bisa dengan cepat mengetahui informasi presensi yang direkap dalam sistem. Selain itu atasan juga dapat mendapatkan data dan informasi dari absen tersebut sebagai dasar kebijakan pengambilan keputusan. Abstract: Electronic recording technology for students' student presence can be a solution that minimizes errors in the process of recording and attendance recap. This presence recording makes it easier to process the computerized attendance of students so that attendance data directly enters the computer so that it is easy to process attendance data. The purpose of this study is to evaluate the system used by the user. The method used in this study is an evaluation study using the framework of the Technology Acceptance Model (TAM). There are several parameters that are evaluated by the system using these tools, which are related to Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Behavioral Intention (BI), Actual Usage (AU). Regarding the application of the Dashboard system, the majority of student respondents gave an average of strongly agree on the Perceived Ease of Use (PEOU) component of 78, Perceived Usefulness (PU) of 73.8, Behavioral Intention (BI) of 76.8, Actual Usage (AU) of 78.87. The system used has an impact on the implementation of monitoring the presence of students in lectures. Administrative and academic staff and students can quickly find out the presence information that is recapitulated in the system. In addition, superiors can also get data and information from these absences as a basis for decision making policies.

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Beyond TAM and UTAUT: Future directions for HIT implementation research

Cited by 154 publications

References 33 publications

Understanding Clinicians’ Adoption of Mobile Health Tools: A Qualitative Review of the Most Used Frameworks

Understanding Clinicians’ Adoption of Mobile Health Tools: A Qualitative Review of the Most Used Frameworks

Determinants of the behavioral intention to use a mobile nursing application by nurses in China

Evaluasi Sistem Dashboard Monitoring Presensi Akademik Mahasiswa

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