A Systematic Review of the Technology Acceptance Model in … · Appl Clin Inform 2018;9:604–634....

A Systematic Review of the TechnologyAcceptance Model in Health InformaticsBahlol Rahimi1 Hamed Nadri1,2 Hadi Lotfnezhad Afshar1 Toomas Timpka3,4

1Department of Health Information Technology, School of AlliedMedical Sciences, Urmia University of Medical Sciences, Urmia, Iran

2Student Research Committee, Urmia University of Medical Sciences,Urmia, Iran

3Department of Computer and Information Sciences, LinköpingUniversity, Linköping, Sweden

4Department of Medical and Health Sciences, Linköping University,Linköping, Sweden

Appl Clin Inform 2018;9:604–634.

Address for correspondence Hamed Nadri, MSc, Department ofHealth Information Technology, School of Allied Medical Sciences,Urmia University of Medical Sciences, Nazloo Campus, Sero Road,Urmia, Iran (e-mail: [email protected]).

Keywords

► technologyacceptance model

► literature review► health information

technology► technology

acceptance► theoretical models► health informatics

Abstract Background One common model utilized to understand clinical staff and patients’technology adoption is the technology acceptance model (TAM).Objective This article reviews published research on TAM use in health informationsystems development and implementation with regard to application areas and modelextensions after its initial introduction.Method An electronic literature search supplemented by citation searching was con-ducted on February 2017 of theWeb of Science, PubMed, and Scopus databases, yielding atotal of 492 references. Upon eliminating duplicates and applying inclusion and exclusioncriteria, 134 articles were retained. These articles were appraised and divided into threecategories according to research topic: studies using the original TAM, studies using anextended TAM, and acceptance model comparisons including the TAM.Results The review identified three main information and communication technology(ICT) application areas for the TAM in health services: telemedicine, electronic healthrecords, andmobile applications. The original TAMwas found to have been extended to fitdynamic health service environments by integration of components from theoreticalframeworks such as the theory of planned behavior and unified theory of acceptance anduse of technology, as well as by adding variables in specific contextual settings. Thesevariables frequently reflected the concepts subjective norm and self-efficacy, but alsocompatibility, experience, training, anxiety, habit, and facilitators were considered.Conclusion Telemedicine applications were between 1999 and 2017, the ICT appli-cation area most frequently studied using the TAM, implying that acceptance of thistechnology was a major challenge when exploiting ICT to develop health serviceorganizations during this period. A majority of the reviewed articles reported exten-sions of the original TAM, suggesting that no optimal TAM version for use in healthservices has been established. Although the review results indicate a continuousprogress, there are still areas that can be expanded and improved to increase thepredictive performance of the TAM.

receivedFebruary 5, 2018accepted after revisionJune 24, 2018

© 2018 Georg Thieme Verlag KGStuttgart · New York

DOI https://doi.org/10.1055/s-0038-1668091.ISSN 1869-0327.

Review Article604

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mailto:[email protected]

https://doi.org/10.1055/s-0038-1668091

https://doi.org/10.1055/s-0038-1668091

Background and Significance

New technologies are continuously being adopted in healthservices.1,2 Modern information and communication tech-nology (ICT) has been understood to improve service qualityin the health service sector in general and in clinical med-icine and at hospitals in particular, enhancing patient safety,staff efficiency and effectiveness, and reducing organiza-tional expenses.3–6 Meanwhile, progress in the life scienceshas led to higher medical specialization and needs toexchange health information across institutional borders.7,8

Despite these needs, health information systems develop-ment methods and research have focused on the technicalaspects of the system design.9–13 If the latter efforts areinsufficient to meet the needs of progressive health serviceorganizations and individual users, ICT investments will bespent ineffectively, and, potentially, patients put at risk.14

Therefore, the impact on ICT adoption of different nontech-nical and individual-level factors need to be established.15 Inthis regard, it is positive that technology acceptance studiesat the present are considered to stand as a mature field ininformation systems research.16

During the past 30 years, several theoretical models havebeen proposed to assess and explain acceptance and beha-viors in association with ICT introduction. Robust measureshave been developed of how well a technology “fits” withuser tasks and have validated these task–technology fitinstruments.17 The best known of these is the technologyacceptance model (TAM), which was presented in 1989,18

and has during this period been applied and empiricallytested in a wide spectrum of ICT application areas.19,20 Also,the TAM is one of the most popular research models topredict use, person’s intention to perform a particular beha-vior, and acceptance of information systems and technologyby individual users.21,22 Originally, the TAM was derivedfrom the social psychological theories of reasonable action(TRA) and planned behavior (TPB),23 these three modelsfocus on a person’s intention to perform the behavior,24

but the constructs of these three models are different andnot exactly the same. The TAM has become the dominantmodel for investigating factors affecting users’ acceptance ofnovel technical systems.25 The basic model presumes amediating role of perceived ease of use and usefulness inassociation between system characteristics (external vari-ables) and system usage (as shown in ►Fig. 1).26 Severalreviews of TAM use encompassing the ICT field in total have

been issued. Accounts of the first decade of TAM-relatedresearch and suggestions of future directions were offered in2003 by Lee et al27 and Legris et al.25 The directions includeda need for incorporating more variables related to humanand social change processes and exploring boundary condi-tions. At that time, the original TAM had already beenmodified in the TAM2 version28 by removal of the “Attitudes”concept and differentiating the “External variables” conceptinto social influence (subjective norm, voluntariness, andimage), cognitive instrumental processes (job relevance,output quality, and result demonstrability), and experience.A few years later, Sharp continued to discuss the relativestrengths of perceived usefulness (PU) and perceived easeand the role of attitudes in user acceptance, but also broughtto the fore differences between volitional andmandatory useenvironments.29 Venkatesh et al proposed a unified model—the unified theory of acceptance and use of technology(UTAUT)—based on studies of eight prominent models (inparticular the TAM). The UTAUT is formulatedwith four coredeterminants of intentions and usage: performance expec-tancy, effort expectancy, social influence, and facilitatingconditions, together with four moderators of key relation-ships: gender, age, experience, and voluntariness of use.16

The same year, King and Jun conducted a statistical meta-analysis of TAM applications in various fields, reporting theTAM to be a valid and robust model that has been widelyused.30 In 2008, the TAM2 was extended with regard todeterminants of perceived ease of use (PEOU) (TAM3).31 TheTAM3 is composed of four constructs: PEOU, PU, behaviorintention, and use behavior.

Turning the attention from theory building to use envir-onments, Turner et al concluded that care should be takenwhen using a particular version of the TAM outside thecontext in which the version originally was validated.32

Proceeding with the analyses of model validity across useenvironments, Hsiao and Yang used cocitation analyses toidentify three main application contexts for TAM use: (1)task-related systems, (2) e-commerce systems, and (3)“experiential” (or “hedonic”) systems.33

Task-related systems are designed to improve task per-formance and efficiency. These systems can be categorized asautomation software, office systems, software development,and communication systems such as electronic health record(EHR). Clinical practice guidelines, linked educational con-tent, and patient handouts can be part of the EHR. This maypermit finding the answer to a medical question while the

Fig. 1 The basic technology acceptance model.18

Applied Clinical Informatics Vol. 9 No. 3/2018

A Systematic Review of the Technology Acceptance Model Rahimi et al. 605

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patient is still in the examination room.34 e-Commerce is theactivity of buying or selling of products on online services orover the Internet.35 The “hedonic” information systems areusually connected to home and leisure activities, focusing onthe fun or novel aspect of information systems includesonline gaming, online surfing, online shopping, and evenonline learning while perusing enjoyment at the sametime.33

In 2010, Gagnon et al conducted a systematic review toinvestigate factors influencing the adoption of ICT by healthcare professionals. In this review, including all ICT accep-tance models in health services, it was concluded that PU ofsystem and PEOU were the two most influential factors.36

These two factors are the main components of the originalTAM.22 Regarding applications in specific health servicesareas, Strudwick concluded from a review of TAM applica-tions among nursing practitioners that a modified TAMwithvariables detailing the health service context and usergroups added could provide a better explanation of nurses’acceptance of health care technology.37 Further, Ahlan andIsma’eel reported from an overview of patient acceptance ofICT that the TAM is one of the most useful models forstudying patients’ perceptions and behaviors.38 Also, Gara-vand et al concluded from their general review of the mostwidely used acceptance models in health services that theTAM is themost importantmodel used to identify the factorsinfluencing the adoption of information technologies in thehealth system.39

Objective

The objective of this systematic review was to compilepublished research on TAM use in health information sys-tems development and implementationwith regard to appli-cation areas and model modifications after its initialintroduction, and also to gain understanding of the existingresearch and debates relevant to a particular topic or area ofstudy. In the present setting, the development of healthservices requires parallel adjustments of ICT support, andaccordingly, of TAMs.

Method

We used systematic search processes to identify all pub-lished original articles related to TAM applications in healthservices from 1989, the year when the TAM was introduced,to February 2017. The PubMed, Scopus, and Web of Sciencedatabases were searched and English-only publicationsselected. The broad keywords used for the initial searchare displayed in ►Table 1. The authors, title, journal, yearof publication, and abstract for each article were collected inan Excel spreadsheet. First, the publication’s titles, andabstracts, were assessed together by two of the four authors,after reviewing all abstracts and eliminating those categor-ized with exclusion criteria or lacking inclusion criteria; thefull texts of the relevant articles were then reviewed by threeauthors together. The full texts of the remaining articleswereread for eligibility, and the qualified publications were

retained in a list. A search of the recent reviews and hand-searching references from articles were made to get relatedarticles. The TAM has been used in many technological andgeographical contexts. Several major technologies likemobile and telemedicine have variety of applications.40,41

In a separate phase, the technologies and applications as asubset of major technological contexts and characteristics ofeach tested model for user groups were identified by threeauthors together. Finally, the publications in the list wereclassified into three categories according to their aim andcontent:

• Original TAM: Applications of the original TAM. In thiscategory, the relationship between themain constructs ofthe original TAM is examined. These relationships includethe relationship between PU and perceived ease to usewith intention to use and also the relationship betweenperceived ease to use and PU.

• Development and Extension of TAM: Reports of newinsights related to the core elements of TAM and/ordevelopment of new TAM versions by integrating newfactors and other acceptance theory variables with theoriginal TAM. These factors incorporate into the con-structs of the original TAM as predictive and moderatingvariables.

• Comparisons of the TAM with other technology accep-tance models: The TAM and other theoretical models arecompared by examining factors associatedwith the adop-tion of a particular technology.

Results

A total of 492 document references were retrieved from thedatabase searches. After removal of 44 duplicates, 448 pub-lications were entered into the selection process. Results ofthe screening process in the analysis are noted in the flowdiagram in ►Fig. 2. First, 448 publications’ titles andabstracts were assessed together by two of the four authors.At this stage, 120 articles unrelated to the topic wereexcluded from the review. The full texts of the relevant

Table 1 Terms used in search

Keyword Boolean Additional keywords

Technologyacceptance model(TAM)

AND Healthcare

Technologyacceptance model,TAM, hospitalinformation system(HIS), extendedtechnologyacceptance model,TAM2, TAM3

AND Healthcare, medicine,health informationsystem (HIS),telemedicine,telehealth, electronichealth record (EHR),computerizedphysician medicationorder entry (CPOE),medication system,bar code medicationadministration(BCMA)


A Systematic Review of the Technology Acceptance Model Rahimi et al.606

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articles were then reviewed by three authors together. Thetitles and abstracts of the relevant articles were thenreviewed by three authors. When the title or abstract wasdeemed significant for inclusion in the review, the full textwas scanned to ensure that the content was relevant. At thisstage, 209 articles that were unrelated to acceptance oftechnology in health care, TAM constructs, or only addressedseparate components of the TAM and other acceptancemodels were excluded. When there was disagreement, theauthors evaluated their assessment until consensus wasreached. A search of the recent reviews and hand-searchingreferences from articles yielded an additional 15 papers. Thesystematic search of the literature identified 134 articles thatreported original empirical research on the use of the TAMwithin health services.

Publications dealing with the original TAM had peaked(n ¼ 3, 2.2% of all articles) in 2013 and 2015, publications ondevelopment and extension of TAM peaked (n ¼ 16, 11.9%)in 2013, while publications reporting comparisons of TAMshad peaked (n ¼ 2, 1.5%) in years 2010 and 2013 (►Fig. 3). Ageneral increase in reports of TAM use suggests a persistinginterest in understanding technology acceptance in healthservices. Also, therewas a noteworthy leap in reports of TAMextensions in 2012 (►Fig. 3), which implies a recent high-lighting of the influence from external factors on technologyacceptance. The 134 articles reporting on TAM use had been

published in 72 scientific journals, and originated from 30countries; 29 (21.6%) studies from the United States, 28(20.9%) from Taiwan, 14 (10.4%) from Spain, while theremaining articles originated from countries in Europe,Asia, and Africa. The journals with the highest numbers ofarticles were International Journal of Medical Informaticswith 11 studies (8.14%), Telemedicine and e-Health with 10studies (7.4%), and BMC Medical Informatics and DecisionMaking, with 8 studies (5.9%).

The first study of a TAM use in health services wasreported in 1999,42 analyzing physicians’ intentions asso-ciated with the adoption of the telemedicine technology in aHongKonghospital setting. The ICT application area inwhichthe TAMwasfirstmore frequently appliedwas EHR forwhicha peak in publications was observed in 2009. Publicationsreporting the TAM applications in telemedicine reached itspeak in 2014, while the use of the TAM for analyses ofmobileapplications did peak in 2015. The first integration of severalacceptance models with the TAM in health services wasreported from Finland for examining acceptance of mobilesystems among physicians.43 In this study, the TAM wascombined with the UTAUT and Personal Innovativeness inthe Domain of Information Technology (PIIT) models.

Three main technological contexts were identified forapplications of the TAM (►Table 2): (1) Telemedicine with25 studies (18.6%), (2) EHR with 21 studies (15.7%), and (3)

Fig. 2 Flow diagram of the study.



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mobile applications with 15 studies (11.2%). Researchers indifferent countries have focused on different specific tech-nologies: researchers in Taiwan on telemedicine (8 articles),mobile applications (n ¼ 5), and hospital information sys-tems (HIS) (n ¼ 4); in the United States on EHRs (n ¼ 8),computers, handheld (personal digital assistants [PDAs])(n ¼ 4), telemedicine, and personal health records(n ¼ 2); and in Spain on telemedicine (n ¼ 6), whileresearchers from Iran have focused on EHR (n ¼ 3) technol-ogy (►Fig. 4).

Telemedicine, the area where the TAM has been mostwidely applied, is also the first technology that was studiedusing the TAM (►Fig. 5). TAM application on mobile tech-nologies was initiated in 200643 and these studies peaked in2015. As shown in ►Table 3, most studies have emphasizedthe acceptance of physicians (n ¼ 43, 32%) and nurses(n ¼ 34, 25.3%). Other users of technology acceptanceinclude patients and clients of health services, pharmacists,and other medical professionals.

Applications of the Original TAMAs shown in ►Table 4, 23 (17.1%) of the identified articlesreported application of the original TAM. In most studiesusing the original TAM to assess technology acceptance, themain constructs (i.e., PU and perceived ease to use) of TAMwere supported. The most frequent ICT application areaswere telemedicine, n ¼ 6 (26%) and PDA, n ¼ 2 (8.6%). Thestudy participants ranged from 10 to 1,942, with an averageof 184. The user category involved in the most studies wasnurses (n ¼ 4, 17%) followed by physicians and patients(both n ¼ 3, 13%).

Development and ExtensionOf all studies, 102 (76.1%) studies reported development orextension of the TAM. In these studies, different factors andtheories were incorporated to the original TAM (►Table 5).The factors investigated in the most commonly used tech-nological contexts such as health information technologysystems in general, telemedicine, EHR, mobile apps, HIS, E-prescription, PDAs, and personal health record are brieflyprovided. According to the results in various technologicalcontexts, it is possible to draw basic factors that incorporatewith the original TAM for each technological context. Themost common factors added to the TAM in almost alltechnological contexts were, in order of importance andfrequency of repetition, compatibility, subjective norm,self-efficacy, experience, training, anxiety, habit, and facil-itators. These factors can be a basic model for most techno-logical contexts with the incorporation of the original TAMand separate variables regarding a context.

Adding separate variables to develop contextualized TAMversions allows optimizing specific dimensions of the TAM inparticular settings and thereby improving predictions inthese contexts. A full summary of the additions to theoriginal TAM displayed by technology application area inhealth services, theories integrated, and new factors andvariables inserted is shown in►Table 6. Themost commonlyintegrated theories were classic acceptance models such asUTAUT, TRA, Diffusion of Innovation theory, and the TPB. Inaddition to the theories, the conditions and technologiesforming the particular context in specific settings have beenused to add further concepts and variables, i.e., some factorswere not derived fromany technology acceptance theory andwere instead specific to a certain technology (such as

Fig. 3 Frequency of articles reporting technology acceptance model use according to the three study categories displayed by year.



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technology features, environmental conditions, user types,etc.). Among the 102 articles, only two studies were con-ducted on the TAM3.

Comparison of Other Technology Acceptance Modelswith TAMNine (6.7%) studies compared TAM with other TAMs. Themost common ICT application area for these comparisonswas mobile technology, n ¼ 3 (33.3%). Typically, Hsiao andTang44 used different variables to investigate the introduc-tion of mobile technologies from the perspective of theelderly people in Taiwan. Their results supported the validityof the TAM variables, and also the inclusion of novel factorssuch as perceived ubiquity, personal health knowledge, andperceived need for health care. Day et al45 conducted a studyto evaluate hospice providers’ attitudes and perceptionsregarding videophone technology in settings where the

technology was introduced but underutilized. Findings indi-cate that the TAM provides a good framework for an under-standing of telehealth underutilization.

In two studies on telemedicine acceptance among physi-cians in China and the United States, respectively, the TAMand the TPB model were compared. Interestingly, the find-ings from China suggested that the TAMwasmore valid thanthe TPB, while the TPB was more valid than the TAM in theUnited States.46,47Another study comparing the TAMand theUTAUT among physicians concluded that the usage inten-tions were strongly associated with the performance expec-tancy on attitude and attitude concepts.48 Manimaran andLakshmi49 formulated an integrated TAM forHealthManage-ment Information System and concluded that health work-ers’ innovativeness and voluntariness had a direct andpositive influence on these intentions. Similarly, Smith andMotley50 found that e-prescribing acceptance was predictedby the technological sophistication, operational factors, andmaturity factors constructs, i.e., ease-of-use variablesderived from the TAM. Liang et al51 examined whetherTAM can be applied to explain physician acceptance ofcomputerized physician order entry (CPOE), and foundthat data analysis provided support for all relationshipspredicted by TAM but failed to support the relationshipbetween ease of use and attitude. A follow-up analysisshowed that this relationship is moderated by CPOE experi-ence (more details of the nine studies are shown in►Table 7).

Discussion

The review showed that the TAM initially was applied totask-related ICT systems such as EHRs. These were oftenconnected to educational processes leading to that system’simpacts on learning and competence were natural criticalinfluences on use intentions. Since the purpose of task-related systems is to enhance the users’ task performanceand improve efficiency, educational concepts can beexpected to continue to play a dominant role within TAMin this domain. In other words, for the task-related systemssuch as EHRs, PU and self-efficacy related to learning can beexpected to have stronger effects on usage than PEOU,33 i.e.,clinical users are likely to accept a new technology mainly ifthey recognize that it can help them to improve their workperformance and build efficacy.52 In addition to PU and self-efficacy, system quality, information quality, physicians’autonomy, security and privacy concerns, and cultural andorganizational characteristicswere found to be important foradoption of task-related technologies, such as EHRs andHISs.

The second aggregation of TAM research was focused oncommunication systems and telemedicine. The rapid devel-opment of worldwide Internet infrastructures has facilitateddevelopment of systems in this domain. Telemedicine appli-cations have in particular allowed to introduce new organi-zational structures in health services40 and consequently ledto an interest in the use of the TAM to facilitate the organiza-tional adaptation. Health care policy makers are still debat-ing why institutionalizing telemedicine applications on alarge scale has been so difficult,53 and why health care

Table 2 Numbers of articles analyzing ICT adoption using TAM(main topics according to the MeSH thesaurus)

Main topic (MeSH) Number Directions ofcountry based ontechnology

Telehealth 25 Taiwan (8), Spain (6),United States (2)

Electronic health record 21 United States (8),Iran (3)

Mobile applications 15 Taiwan (5)

HIT systems in general 8 �Computers, handheld 7 United States (4)

Hospital informationsystems

6 Taiwan (4)

Decision supportsystems, clinical

5 �

Electronic prescribing 4 �Health records, personal 4 United States (2)

Automatic dataprocessing (bar code)

3 �

Radiology informationsystems

2 �

Medical order entrysystems

2 �

Management informationsystems

2 �

Clinical informationsystem

2 �

Enterprise resourcesplanning

2 �

The remaining of the studies dealt with one technology each

Abbreviations: CPOE, computerized physician order entry; HIT, healthinformation technology; ICT, information and communication tech-nology; MeSH, Medical Subject Headings; PACS, picture archiving andcommunication system; PDA, personal digital assistant; TAM, technol-ogy acceptance model.Note: The parenthesized value is number of studies.



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professionals are often averse or indifferent to telemedicineapplications.40,54 We believe that user rejection is one of theimportant factors in institutionalizing various types of tele-medicine applications. Therefore, it is important to examinethe effective factors in accepting telemedicine applicationsby health care professionals. Consequently, when using theTAMon this category of systems, the validity of analyseswithregard to the organizational fit of the novel ICT application is

central.55,56 Other factors commonly associated with tech-nology adoption in this context include subjective norm,security and confidentiality, facilitators, accessibility, andself-efficacy.

Finally, the most recent trend in TAM use—on mobiletechnologies—is characterized by involving also patients asusers. In this setting, the notion of “hedonic” system aspects,denoting factors associated with pleasure or happiness is of

Fig. 4 Technological contexts in using the technology acceptance model between geographical contexts. The parenthesized value is number ofstudies.

Fig. 5 Distribution of three main technological contexts in using the technology acceptance model by year.



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importance.57 Different from the task-related systems, theconcept of hedonic systems focuses on the enjoyable aspectof ICT use and consequently requires other types of factorsand variables for analyses of use intentions. Intrinsic motiva-tional factors such as usability and perceived liveliness are inthis setting as influential as the PU. The progress from EHRsto mobile technologies in ICT applications has required alsothe TAM to be dynamically adapted. Based on this, progressof technology introduction in health services cannot be seento decrease, and a need to modify the TAM to keep up withthe new application areas can be also foreseen in the future.Common factors for hedonic such as mobile apps includeusability, user satisfaction, reliability, privacy, compatibility,innovativeness, subjective norm, self-efficacy, technical sup-port and training, anxiety, and communication. Also, atheory that integrates with the original TAM to examinethe hedonic systems is the self-determination theory (SDT).SDT is a theory ofmotivation that is concernedwith support-ing our natural or intrinsic tendencies to behave in effectiveand healthy ways.58

In the extensions of the TAMobserved in the review, awiderange of technological context factors and circumstanceswere

Table3 Study user group definitions and the number of studiesfor each user group

User groups Number of studies,percentage (%)

Physicians 43 (31.8)

Nurses 34 (25.1)

Patients 17 (13)

Health care professionals 15 (11.1)

Health service staff 13 (9.6)

General population 9 (6.6)

Technology users 8 (5.9)

Managers and providers 4 (2.9)

Students 3 (2.2)

Pharmacists 2 (1.4)

Physiotherapists and midwiveseach

1 (0.7)

Table 4 Publications addressing the original TAM

Author(s) Technologystudied/Platform

Objective Year Samplepopulationand approvedfactors

Setting Country

Hu et al42 Telemedicine The applicability of theTAM in explainingphysicians’ decisions toaccept telemedicinetechnology in the healthcare context

1999 PhysiciansN ¼ 421/perceived easeof use notapproved

Hospital Hong Kong

Barker et al61 Spoken dialoguesystem (SDS)

The application of TAM, touse spoken dialoguetechnology for recordingclinical observationsduring an endoscopicexamination

2003 Clinicians(N ¼ 12)

Endoscopycenter

United Kingd-om

Chang et al62 Triage-basedemergencymedical service(EMS) personaldigital assistant(PDA) supportsystems

Developing triage-basedEMS (PDA) supportsystems among nursesand physicians by TAM

2004 Physicians,nurses(N ¼ 29)

Emergencymedicalcenter

Taiwan

Chang et al63 Emergencymedical servicePDA supportsystems

Extending well-developed, triage-based,EMS (PDA) supportsystems to coverprehospital emergencymedical services


Hospital Taiwan

Chen et al64 Web-basedlearning system

Understanding PHNs’ BItoward Web-basedlearning based on thetechnology acceptancemodel (TAM)

2008 Nurses(N ¼ 202)

Healthcenters

Taiwan

(Continued)



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Table 4 (Continued)



Setting Country

Wilkins65 Electronic healthrecords (EHR)

Examining factors thatmay influence theadoption of electronichealth records by TAM

2009 Healthinformationmanagers(N ¼ 94)

Hospital United States

Marini et al66 BCMA system Using the TAM todetermine the level ofnurses’ readiness to use ITfor medicationadministration

2009 Nurses(N ¼ 276)

Hospital Lebanon

Van Schaiket al67

Portable systemfor posturalassessment

Assessing the TAM for thenew system

2002 Physiothera-pists(N ¼ 49)

Spinal unit United Kingd-om

Huser et al68 A prototype of aflowchart-basedanalyticalframework(RetroGuide)

Exploring acceptance ofquery systems calledRetroGuide for retrievalEHR data

2010 Humansubjects(N ¼ 18)

Laboratory United States

Cranen et al69 Web-basedtelemedicineservice

The patients’ perceptionsregarding a Web-basedtelemedicine service withTAM among patient

2011 Patients(N ¼ 30)

Homecare TheNetherlands

Hung andJen70

Mobile healthmanagementservices (MHMS)

This study introducesMHMS and employs theTAM to explore theintention of students inExecutive Master ofBusiness Managementprograms to adoptmobilehealth managementtechnology

2012 Students(N ¼ 170)

University Taiwan

Aldosari71 Picture archivingandcommunicationsystem (PACS)

The TAM was used toassess the level ofacceptance of the hostPACS by staff in theradiology department

2012 Staffs(N ¼ 89)

Radiologydepartment

Saudi Arabia

Noblin et al72 Personal healthrecord

The TAM was used toevaluate to adoptpersonal health record



Martínez-García et al73

Social networkcomponent

Assessing acceptance anduse of the social networkcomponent (web 2.0) toenable the adoption ofshared decisions amonghealth professionals (thisis highly relevant formultimorbidity patientscare) using TAM

2013 Health careprofessionals(N ¼ 10)

Health carecenter

Spain

Monthuy-Blanc et al74

Telementalhealth(psychotherapydelivered viavideoconferen-cing)

Understanding the role ofmental health serviceproviders’ attitudes andperceptions ofpsychotherapy deliveredvia videoconferencing ontheir intention to use thistechnology with theirpatients

2013 Providers ofhealth care(N ¼ 205)

Center ofTelemental

Canada



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introduced. Examples of such factors include physicians’autonomy, doctor–patient relationship, project team compe-tency, clinical safely, job fit, and optimism, as well as patientuser group,59 voluntariness of the ICTuse, andwhether the ICTsystems were prototypes, trial systems, to-be-implementedsystems, or implementedsystems.Other revisionshadmoreto

do with explicitly stating contextual circumstances, ratherthan extensions per se. For instance, over the life course ofan ICT application, the relationships in the TAM may change,e.g., usability may initially be critical but less important lateron. Two methods to add novel concepts and variables to theTAM were highlighted in this review. The first, theory-based

Table 4 (Continued)



Setting Country

Abdekhodaet al75

Healthinformationmanagementsystem

The acceptance ofinformation technology inthe context of healthinformation management(HIM) by utilizing TAM

2014 Worker ofmedical record(N ¼ 187)

Hospital Iran

Cilliers andStephen76

Telemedicine Using of the TAM toidentify the factors thatinfluence the useracceptance oftelemedicine amonghealth care workers

2014 Health careworkers(n ¼ 75)

Hospital andclinic

South Africa

Ologeanu-Taddei et al77

Hospitalinformationsystem (HIS)

Examining key factors of aHIS acceptance for thecare staff, based on themain concepts of TAM

2015 Staffs(N ¼ 1,942)

Hospital France

Money et al78 Computerized 3Dinterior designapplications(CIDAs)

Exploring the perceptionsof community dwellingolder adults with regardsto adopting and usingCIDAs with TAM

2015 Older adult(N ¼ 10)

Homecare United Kingd-om

Faruqueet al79

Geoinformaticstechnology indisaster diseasesurveillance

Assessing the feasibility ofusing geoinformaticstechnology in disasterdisease surveillance usesby self-administrationbased on the technologyacceptance model (TAM)

2015 Personnel(N ¼ 50)

Healthcenters

Iran

Kivekäset al80

Electronicprescription(e-prescription)system

Assessing generalpractitioners’ (GP)experience of anelectronic prescription (e-prescription) system andthe use of a nationalprescription center

2016 Generalpractitioners(N ¼ 269)

Hospital Finland

Abdullahet al81

Telemonitoringof home bloodpressure (BP)

Exploring patients’acceptance of a BPtelemonitoring servicedelivered in primary carebased on the technologyacceptance model (TAM)


Homecare Malaysia

Hanaueret al82

Computer-basedqueryrecommendationalgorithm

Assessing computer-based queryrecommendationalgorithm as part of asearch engine thatfacilitates retrieval ofinformation from EHRsusing TAM

2017 Clinicians,staffs(N ¼ 33)


Abbreviations: BCMA, bar codemedication administration; BI, business intelligence; EHR, electronic health record; IT, information technology; PHN,public health nurse; TAM, technology acceptance model.



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Table 5 Publications addressing extension and development of TAM

Author(s) Technologystudied

Main topic Years Sample Setting/Incorporatedtheories and variablewith the TAM

Country

Rawstorneet al83

Patient careinformationsystem

Identifying the relevantissues necessary forapplying thetechnology acceptancemodel and the theoryof planned behavior tothe prediction andexplanation ofmandatedIS usage

2000 Nurses(N ¼ 61)

Hospital/theory ofplanned behavior (TPB)

Australia

Handyet al84

Electronicmedicalrecords (EMR)

Studying primary carepractitioners’ views ofan electronic medicalrecords (EMR) systemfor maternity patients

2001 Physiciansandmidwives(N ¼ 167)

Hospital/Systemacceptability, systemcharacteristics,organizationalcharacteristics,individual characteristics

NewZealand

ChismarandSonja85

Internet andInternet-basedhealthapplications

Testing the extensionto a widely used modelin the informationsystems especiallyInternet in pediatrics

2002 Pediatri-cians(N ¼ 89)

Hospital/the TAM2theory

UnitedStates

Lianget al86

Personal digitalassistants(PDAs)

Predicting TAM toactual PDA usage

2003 Health careprofession-als(N ¼ 173)

–/compatibility, support,personal innovativeness,job relevance

UnitedStates

Liu andMa87

Service-orientedmedicalrecords

Extending TAM byembedding perceivedservice level (PSL) as acausal antecedent forhealth care workers’willingness to useapplication service-oriented medicalrecords

2005 Health careworker(N ¼ 79)

Hospital/Perceivedservice level

UnitedStates

Han et al43 Mobile system Examining acceptanceof mobile systemamong physicians withthe aid from mainlyTAM, UTAUT andPersonalInnovativeness in theDomain of InformationTechnology (PIIT)models

2006 Physicians(N ¼ 151)

Health care sector/gender, experience, age,personal innovativeness,compatibility, socialinfluence

Finland

Liu andMa88

Electronicmedicalrecords (EMR)

Introducing the notionof perceivedsystem performance(PSP) to extend theTAM

2006 Medicalprofession-als(N ¼ 77)

Hospital/Perceivedsystem performance

UnitedStates

Palm et al89 Clinicalinformationsystem (CIS)

Designing an electronicsurvey instrument fromtwo theoretical models(Delone and McLean,and TAM) to assess theacceptability of anintegrated CIS

2006 Physicians,nurses,andsecretaries(N ¼ 324)

Hospital/Building on theTAM and the DeLone andMcLean ISS models

France

Kim andChang90

Identifying the corefunctional factors in

2007 Users(N ¼ 228)

Home/Informationsearch, usage support,

SouthKorea



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Table 5 (Continued)



Country

HealthinformationWeb sites

designing andoperating healthinformation Web sites

customization,purchase, and security

Wu et al91 Mobile healthcare systems

Examining determinesmobile health caresystems (MHS)acceptance by healthcare professionalsbased on revised TAM

2007 Physicians,nurses, andmedicaltechnicians(N ¼ 137)

Hospital/MHS self-efficacy, technicalsupport and training,compatibility

Taiwan

Tung et al92 Electroniclogisticsinformationsystem

Nurses’ acceptance ofthe electronic logisticsinformation systemwith new hybrid TAM

2008 Nurses(N ¼ 258)

Hospital/Perceivedfinancial cost,compatibility, trust

Taiwan

Lai et al93 TailoredInterventionsformanagementof DEpressiveSymptoms(TIDES)

Designing TailoredInterventions formanagement ofDEpressive Symptoms(TIDES) program basedon an extension of theTAM


Clinics/framework basedon TAM2 (subjectivenorm, job relevance,experience) and modifiedTAM (socio-demo,adjustment, jobrelevance)

UnitedStates

Wu et al94 Adverse eventreportingsystem

Investigatingdetermines acceptanceof adverse eventreporting systems byhealth careprofessionals withextending TAM thatintegrates variablesconnoting trust andmanagement supportinto the model


Hospital/trust,management support,subjective norm

Taiwan

Yu et al95 Healthinformationtechnologyapplications

Applying a modifiedversion of the TAM2 toexamine the factorsdetermining theacceptance of health ITapplications

2009 Staffmembersfrom long-term carefacilities(N ¼ 134)

Long-term care/age,subjective norm, image,job level, workexperience, computerskills, voluntariness

Australia

Dasguptaet al96

Personal digitalassistants(PDAs)

Evaluatingpharmacists’behavioral intention touse PDAs with TAM2

2009 Pharma-cists(N ¼ 295)

Hospital andcommunitypharmacies/The TAM2theory

UnitedStates

Ilie et al97 Electronicmedical record(EMR)

Examining physicians’responses to uses ofEMR bases on TAM


Hospital/Systemaccessibility

UnitedStates

Trimmeret al98

Electronicmedicalrecords (EMRs)

Application modelsTAM, UTAUT, andorganizational culturein several differentphase for acceptanceEMR

2009 Physicians(N ¼ –)

Residency in familymedicine/Derived fromTAM, UTAUT, andorganizational culture

UnitedStates

Lin andYang99

Asthma caremobile service(ACMS) ¼mobile phone

Integrating TAM and“subjective norm” and“innovativeness” inacceptance ACMS


Remote areas/person-centered,communication

China

Aggelidisand


Examining HISacceptance by hospital

2009 Hospitalpersonnel(N ¼ 283)

Hospital/Derived basedon UTAUT and TAM(Compatibility, training,

Greece

(Continued)



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Table 5 (Continued)



Country

Chatzo-glou100

personnel bases onTAM

social influence,facilitating condition,self-efficiency, anxiety)

Hyunet al101

Structurednarrativeelectronichealth record(EHR) model(electronicnursingdocumenta-tion system)

Applying theory-based(combined technologyacceptance model andtask-technology fitmodel) and user-centered methods toexplore nurses’perceptions offunctionalrequirements for anelectronic nursingdocumentation system

2009 Nurses(N ¼ 17)

Hospital/Combined TAMand task-technology fit(TTF) model

UnitedStates

Vishwa-nathet al102

Personal digitalassistant (PDA)

Exploring thedeterminants ofpersonal digitalassistant (PDA)adoption in health carewith TAM


Hospital/age, position inhospital, clusterownership, specialty

UnitedStates

MortonandSusan103

Electronichealth record(EHR)

Adopting of aninteroperable EHR inambulatory card usesinnovation diffusiontheory and the TAM


University/Combininginnovation diffusiontheory (IDT) and the TAM

UnitedStates

Zhanget al104

Mobilehomecarenursing

Applying TAM2 inmobile homecarenursing

2010 Nurses(N ¼ 91)

Home/The TAM2 theory Canada

Stocker105 Electronicmedicalrecords (EMRs)

Evaluating the TAMrelevance of theintention of nurses touse electronic medicalrecords in acute healthcare settings

2010 Nurses(N ¼ 97)

Hospital/Environment orcontext, nursecharacteristics, EHRcharacteristic

UnitedStates

Lim et al106 Mobile phones Women’s acceptanceof using mobile phonesto seek healthinformation basis onTAM

2011 Women(N ¼ 175)

Home care/Self-efficacy,anxiety, prior experience

Singapore

Schnall andBakken107

Continuity ofcare record(CCR)

Assessing theapplicability of TAMconstructs in explainingHIV case managers’behavioral intention touse a CCR

2011 Managers(N ¼ 94)

Center of HIV care/Perceived barriers to use

UnitedStates

Kowitlawa-kul108

Telemedicine/electronic orremotetechnology(eICU)

Determining factorsand predictors thatinfluence nurses’intention to use theeICU technology baseson TAM

2011 Nurses(N ¼ 117)

Hospital/Support fromphysicians, yearsworking in the hospital,support fromadministrator

UnitedStates

Egea andGonzá-lez109

Electronichealth carerecords (EHCR)

Explaining physicians’acceptance forelectronic health carerecords (EHCR systems)


Hospital/Perceptions ofinstitutional trust,perceived risk,information integrity

Spain



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Table 5 (Continued)



Country

Hsiaoet al110

Hospitalinformationsystems (HIS)

The application of TAMfor evaluate HIS inamong nursingpersonnel

2011 Nurses(N ¼ 501)

Hospital/system quality,information quality, userself-efficacy,compatibility, topmanagement support,and project teamcompetency

Taiwan

Orruñoet al111

Teledermatol-ogy

Examining intention ofphysicians to useteledermatology usinga modified TAM


Home/Subjective norm,facilitator, habit,compatibility

Spain

Melaset al112

Clinicalinformationsystems

Explaining intention touse clinical informationsystems based on TAM

2011 Medicalstaff (total[N ¼ 604],physicians-¼ 534)

Hospital/Physicianspecialty, ICT knowledge,ICT feature demand

Greece

Pai andKai113

Health careinformationsystems

Adopting the systemand services based onModel proposed byDeLone and Mclean andTAM

2011 Nurses,headdirectors,and otherrelatedpersonnel(N ¼ 366)

Hospital/Modelproposed by DeLoneand Mclean and TAM

Taiwan

Jimohet al114

Informationandcommunica-tiontechnology(ICT)

Using modified TAM inamong maternal andchild health workers

2012 Healthworkers(N ¼ 200)

Rural regions/knowledge, endemicbarriers (knowledge aseparate factor fromattitude)

Nigeria

Lu et al115 Hospitalinformationsystem (HIS)

Exploring factorsinfluencing theacceptance of HISs bynurses with derivedmodel from TAM

2012 Nurses(N ¼ 277)

Hospital/Informationsystem success model

Taiwan

LakshmiandRajaram116

Informationtechnology (IT)applicationsandinnovativeness

Analyzing the influenceof IT applications andinnovativeness on theacceptance of ruralhealth care servicesuses by TAM

2012 Healthpersonnel(N ¼ 465)

Rural centers/Information technologyexposure,innovativeness, onlineinformation dependence

India

Jian et al117 USB-basedpersonalhealth records(PHRs)

Factors that influencingconsumer adoption ofUSB-based personalhealth records by TAM

2012 Patients(N ¼-1,465)

Hospital/Subjectivenorm

Taiwan

Escobar-Rodríguezet al118

e-Prescriptionsand automatedmedicationmanagementsystems

Investigating healthcare personnel to use e-prescriptions andautomated medicationmanagement systemswith extensive TAM


Hospital/perceivedcompatibility, perceivedusefulness to enhancecontrol systems,training, perceived risks

Spain

Ketikidiset al119

HIT systems Applying modified TAMin acceptance of HITsystems in health carepersonnel

2012 Healthprofession-als (nursesandmedicaldoctors)(N ¼ 133)

Hospital/Computeranxiety, relevance, self-efficacy, subjective anddescriptive norms,familiarity/ use ofcomputers

Greece

(Continued)



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Table 5 (Continued)



Country

Chen andHsiao120


Examining acceptanceof hospital informationsystems (HIS) byphysicians


Hospital/System quality,information quality,service quality

Taiwan

Kim andPark121

Healthinformationtechnology(HIT)

Developing and verifythe extendedtechnology acceptancemodel (TAM) in healthcare

2012 Healthconsumers(n ¼ 728)

Home/Incorporating theHealth Belief Model(HBM) and theory ofplanned behavior (TPB),along with the TAM

SouthKorea

Parraet al122

Care service forthe treatmentof acute strokepatients basedontelemedicine(TeleStroke)

Development,implementation, andevaluation of a careservice for thetreatment of acutestroke patients basedon telemedicine(TeleStroke) using aTAM

2012 Medicalprofession-als(N ¼ 34)

Hospital/Subjectivenorm, facilitatingconditions

Spain

Gagnonet al123

Telemonitoringsystem

Using a modified TAMto evaluate health careprofessionals’ adoptionof a newtelemonitoring system


Hospital/habit,compatibility,facilitators, subjectivenorm

Spain

Wangia124 Immunizationregistry

Extending withcontextual factors(contextualized TAM)to test hypothesesabout immunizationregistry usage

2012 Immuniza-tionregistryend-users(n ¼ 100)

Unit of immunizationregistry/job-taskchange, commitment tochange, system interfacecharacteristic, subjectivenorm, computer self-efficacy

UnitedStates

Wonget al125

IntelligentComprehen-sive InteractiveCare (ICIC)system(Telemedical)

Evaluating the users’intention using amodified technologicalacceptance model(TAM)

2012 Elderlypeople(N ¼ 121)

Elderly care/The TAM2theory and enjoymentfactor

Taiwan

Holdenet al126

Bar-codedmedicationadministration(BCMA)

Identifying predictorsof nurses’ acceptanceof bar-codedmedicationadministration (BCMA)

2012 Nurses(N ¼ 83)

Hospital/Socialinfluence, training,technical support, age,experience, satisfaction

UnitedStates

Dünnebeilet al127

Electronichealth (e-health) inambulatorycare(Telemedicine)

Extending technologyacceptance models(TAMs) for electronichealth (e-health) inambulatory caresettings by physicians


Ambulatory care/building based on TAMand UTAUT (processorientation, importanceof standardization, e-health knowledge,importance ofdocumentation,importance of datasecurity, intensity of ITutilization)

Germany

Asuaet al128

Telemonitor-ing

Examining thepsychosocial factorsrelated totelemonitoringacceptance among

2012 Nurses,generalpractition-ers, and

Homecare/Habit,compatibility, facilitator,subjective norm

Spain



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Table 5 (Continued)



Country

health care based onTAM2

pediatri-cians(N ¼ 268)

Kummeret al129

Sensor-basedmedicationadministrationsystems

Usage of professionalward nurses towardsensor-basedmedication systemsbased on an TAM2

2013 Nurses(N ¼ 579)

Health associations/Qualitative overload,quantitative overload,personal innovativeness

Australia

Sedlmayret al130

Clinicaldecisionsupportsystems formedication

Testing acceptance ofsystem by EDphysicians with TAM2


Hospital/Resistance tochange(RTC),compatibility (COM)

Germany

Abu-Dalbouh131

Mobile healthapplications

Using TAM to evaluatethe system mobiletracking model

2013 Health careprofession-als(N ¼ –)

–/User satisfaction,attribute of usability

SaudiArabia

Tavakoliet al132

Electronicmedical record(EMR)

Investigating the TAMusing EMR

2013 Users ofEMR(n ¼ cen-sus)

Central Polyclinic OilIndustry/data quality,user interface

Iran

Buenes-tadoet al133

Clinicaldecisionsupportsystems(CDSS) basedoncomputerizedclinicalguidelines andprotocols(CCGP)

Determiningacceptance of initialdisposition ofphysicians toward theuse of CDSS based on(CCGP)


Hospital/ compatibility,habits, facilitators,subjective norm

Spain

Escobar-RodriguezandBartual-Sopena134

Enterpriseresourcesplanning (ERP)systems

Analyzing the attitudeof health carepersonnel toward theuse of an ERP system inpublic hospital

2013 Health carepersonnel(n ¼ 59)

Hospital/Experiencewith IT, training,support, age

Spain

Su et al135 Telecaresystems

Integrating patienttrust with the TAM toexplore the usageintention model ofTelecare systems


Hospital/Patient trust(including Social Trust,Institutional Trust)

Taiwan

Alali andJuhana136

Virtualcommunities ofpractice (VCoPs)

Exploring VCoPssatisfaction based onthe technologyacceptance model(TAM) and DeLone andMcLean IS successmodel

2013 Practition-ers(N ¼ 112)

Hospital/Developingfrom TAM and DeLoneand McLean IS successmodels (knowledgequality [KQ], systemquality [SyQ], servicequality [SeQ],satisfaction [SAT])

Malaysia

Wanget al137

Telecare system Using telecare systemto constructmedication safetymechanisms for remotearea elderly uses TAM

2013 Elderlypatients(N ¼ 271)

Remote areas/Person-centered caring,communication

Taiwan

Chenet al138

Understanding theinfluence on

2013 Citizens(N ¼ 334)

Home/Relationshipquality (including trust,

Taiwan

(Continued)



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Table 5 (Continued)



Country

Hospital e-appointmentsystem

continuance intentionin the hospitale-appointment systembased on extendedTAM

satisfaction),continuance intention

Sicotteet al139

Electronicprescribing

Identifying the factorsthat can predictphysicians’ use ofelectronic prescribingbases on expansion ofthe technologyacceptance model(TAM)


City region/Socialinfluence, practicecharacteristics,physician characteristics

Canada

Liu et al140 Web-basedpersonalhealth recordsystem

Extending TAM thatintegrates thephysician–patientrelationship (PPR)construct into TAM’soriginal constructs foracceptance of Web-based personal healthrecord system


Medical center/Physician–patientrelationship (PPR)

Taiwan

Ma et al141 Blendede-learningsystems(BELS)

Integrating task-technology fit (TTF),computer self-efficacy,the technologyacceptance model anduser satisfaction tohypothesize atheoretical model, toexplain and predictuser’s behavioralintention to use a BELS

2013 Nurses(N ¼ 650)

Hospitals and medicalcenters/Integrating theTAM and task-technologyfit (TTF)

Taiwan

Escobar-RodríguezandRomero-Alonso142

Automatedunit-basedmedicationstorage anddistributionsystems

Identifying attitude ofnurses toward the useof automated unit-based medicationstorage anddistribution systemsand influencing factorsbases on TAM

2013 Nurses(N ¼ 118)

Hospital/Training,perceived risk, experiencelevel

Spain

Huang 143 Telecare Exploring people’sintention to usetelecare with aid fromstructural equationmodeling (SEM)technique that is amodification of TAM

2013 People(N ¼ 369)

City region/Innovativeness,subjective norm

Taiwan

Portelaet al144

PervasiveIntelligentDecisionSupportSystem (PIDSS)

Adopting of INTCaresystem making use ofTAM3 in the ICU

2013 Nurses(N ¼ 14)

ICU/The TAM3 theory Portugal

Johnsonet al145

Evidence-adaptiveclinicaldecision

Acceptance ofevidence-adaptiveclinical decisionsupport systemassociated with an

2014 Internalmedicineresidents(N ¼ 44)

Hospital/Usersatisfaction, computerknowledge, generaloptimism, self-reportedusage, usage trajectory

UnitedStates



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Table 5 (Continued)



Country

supportsystem

electronic healthrecord system usingTAM

group, institutionalizeduse

Zhanget al146

Mobile health Assessment andacceptance betweenprivacy and usingmobile health with aidfrom TAM


Hospital/Personalization, privacy

China

Andrewset al147

Personallycontrolledelectronichealth record(PCEHR)

Examining howindividuals in thegeneral populationperceive the promotedidea of having a PCEHR


Homecare/Social norm,privacy concern, trust,perceived risk,controllability, Webself-efficacy,compatibility,perceived value

Australia

Gagnonet al148


Identifying the maindeterminants ofphysician acceptance ofEHR in a sample ofgeneral practitionersand specialists


Hospital/Integratingoriginal TAM, extendedTAM, psychosocial model

Canada

Hwanget al149

Prehospitaltelemetry

Factors influencing theacceptance oftelemetry byemergency medicaltechnicians inambulances uses byextended TAM

2014 Emergencymedicaltechnicians(n ¼ 136)

Hospital/Job fit, loyalty,organizationalfacilitation, subjectivenorm, expectationconfirmation, clinicalfactors, nonclinicalfactors

SouthKorea

Tsai150 Telehealthsystem

Integrating extendedTAM and health beliefmodel (HBM) for toidentify factors thatinfluence patients’adoption to usetelehealth


Home/Integratingextended technologyacceptance model(extended TAM) andhealth belief model(HBM)

Taiwan

Rho et al151 Telemedicine Developingtelemedicine serviceacceptance modelbased on the TAM withthe inclusion of threepredictive constructsfrom the previouslypublished telemedicineliterature: (1)accessibility of medicalrecords and of patientsas clinical factors, (2)self-efficacy as anindividual factor, and(3) perceived incentivesas regulatory factors


Medical centers andhospitals/Self-efficacy,accessibility, perceivedincentives

SouthKorea

Tsai152 Telehealth Developing acomprehensivebehavioral model foranalyzing therelationships amongsocial capital factors(social capital theory),technological factors

2014 End usersof atelehealthsystem(N ¼ 365)

City region/Integratingsocial capital theory(social trust,institutional trust, socialparticipation), socialcognitive theory (systemself-efficacy) and TAM

Taiwan

(Continued)



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Table 5 (Continued)



Country

(TAM), and system self-efficacy (socialcognitive theory) intelehealth

Horanet al153

Onlinedisabilityevaluationsystem

Developing aconceptual model forphysician acceptancebased on the TAM


Hospital/Organizationalreadiness, technicalreadiness, perceivedreadiness, work practicecompatibility, socialdemographics

UnitedStates

Saigí-Rubióet al154

Telemedicine Analyzing thedeterminants oftelemedicine use in thethree countries withTAM


Hospital, health carecenters of the urbanand rural/Optimism,propensity to innovate,level of ICT use

Spain,Colombia,and Bolivia

SteiningerandBarbara155


Examining andextending factorsinfluence acceptancelevels amongphysicians, uses amodified (TAM)


Hospital/Social impact,HIT experience, privacyconcerns

Austria

Basaket al156

Personal digitalassistant (PDA)

Using an extended TAMfor exploring intentionto use personal digitalassistant (PDA)technology amongphysicians


Hospital/Integrating theTAM and DeLone andMcLean IS successmodels (knowledgequality, system quality,service quality and usersatisfaction)

Turkey

Al-AdwanandHilary157


Applying a modifiedversion of the revisedTAM to examine EHRacceptance andutilization by physicians


Hospital/Compatibility,habit, subjective norm,facilitators

Jordan

Kowitlawa-kul et al158

Electronichealth recordfor nursingeducation(EHRNE)

Investigating thefactors influencingnursing students’acceptance of the EHRsin nursing educationusing the extendedTAM with self-efficacyas a conceptualframework

2015 Students(N ¼ 212)

Clinics/Self-efficacy Singapore

Michel-Verkerkeet al.59

Patient recorddevelopment(EPR)

Developing a modelderived from the DOIand TAM theory forpredicting EPR

2015 Patients(N ¼ –)

–/Derived from DOI andTAM theory

TheNether-lands

Lin160 Hospitalinformationsystem (HIS)

Using the perspectiveof TAM; nationalcultural differences interms of masculinity/femininity,individualism/collectivism, powerdistance, anduncertainty avoidanceare incorporated intothe TAM as moderators

2015 Nurses(N ¼ 261)

Hospital/Powerdistance, uncertainlyavoidance, masculinityor femininity,individualism orcollectivism, timeorientation

Taiwan



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Table 5 (Continued)



Country

Abdekhodaet al59


Assessing physicians’attitudes toward EMRs’adoption by aconceptual path modelof TAM andorganizational contextvariables


Hospital/Managementsupport, training,physicians’ involvement,physicians’ autonomy,doctor–patientrelationship

Iran

Gartrellet al161

Electronicpersonalhealth records(ePHRs)

Using a modifiedtechnology acceptancemodel on nurses’personal use of ePHRs

2015 Nurses(N ¼ 847)

Hospital/Perceived dataprivacy and securityprotection, perceivedhealth-promoting rolemodel

UnitedStates

Carrera andLam-booij162

Out-of-officeblood pressuremonitoring

Developing ananalytical frameworkbased on the TAM, thetheory of plannedbehavior, and themodel of personalcomputing utilizationto guide theimplementation of out-of-office BP monitoringmethods

2015 Patients,physicians(N ¼ 6)

–/Framework based onthe TAM, the TPB(including self-efficiency,social norm), and themodel of personalcomputing utilization(including enablingconditions)

TheNether-lands

Sieverdeset al163

Mobiletechnology

Investigating kidneytransplant patientsattitudes andperceptions towardmobile technology withaid from thetechnology acceptancemodel and self-determination theory


Medical center/Frameworks from theTAM and self-determination theory(SDT)

UnitedStates

Songet al164

Bar codemedicationadministrationtechnology

Using bar codemedicationadministrationtechnology amongnurses in hospitals withTAM

2015 Nurses(N ¼ 163)

Hospital/Feedback andcommunication abouterrors, age, teamworkwithin hospital units,hospital managementsupport for patientsafety, nursing shift,education, computerskills, technology lengthof use

UnitedStates

Jeon andPark165

Mobile obesity-managementapplications(apps)

The acceptance ofmobile obesity-managementapplications (apps) bythe public wereanalyzed using amobilehealth care system(MHS) (TAM)

2015 Public(healthconsumer)(N ¼ 94)

Homecare/Compatibility, self-efficacy, technicalsupport and training

SouthKorea

Alrawab-deh et al166


The revealing factorsthat affect the adoptionof EHR

2015 Final users(N ¼ 6)

Health sector of NHS/Clinical safety, security,integration, andinformation sharing

United Kin-gdom

Escobar-RodríguezandLourdes 167

Enterpriseresourcesplanning (ERP)

Impact of culturalfactors on userattitudes toward ERPuse in public hospitalsand identifying

2015 Users(N ¼ 59)

Hospital/Resistance tobe controlled, perceivedrisks, resistance tochange

Spain

(Continued)



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Table 5 (Continued)



Country

influencing factors usesby TAM

Briz-Ponceand García-Peñalvo168

Mobiletechnologyand “apps”

Measurement andexplain the acceptanceof mobile technologyand “apps” in medicaleducation

2015 Students,medicalprofession-als(N ¼ 124)

University/Reliability,social influence,facilitating conditions,self-efficacy, anxiety,recommendation

Spain

Lai et al169 Mobile hospitalregistrationsystem

The use of the mobilehospital registrationsystem


Hospital/Informationtechnology experience(ITE)

Taiwan

Al-Nassaret al170

Computerizedphysician orderentry (CPOE)

Behavior of CPOEamong physicians inhospitals based on thetechnology acceptancemodel (TAM)

2016 physicians(N ¼ –)

Hospital/Instability ofnew software providers,software quality

Jordan

Lin et al171 Devices formonitoringelderlypeople’spostures andactivities

Designing anddevelopment of anovel, textile-based,intelligent wearablevest for real-timeposture monitoring andemergency warnings


Homecare/Technologyanxiety

Taiwan

Sureshet al172

Healthinformationtechnology(HIT)

Analyzing theapplication of thetechnology acceptancemodel (TAM) byoutpatients


Hospital/Customizedinformation,trustworthiness

India

Ifinedo173 Informationsystems (ISs)

The moderating effectsof demographic andindividualcharacteristics onnurses’ acceptance ofinformation systems(IS)

2016 Nurses(N ¼ 197)

Hospital/Education,computer knowledge

Canada

Goodarziet al174

Picturearchiving andcommunica-tion system(PACS)

The TAM has been usedto measure theacceptance level ofPACS in the emergencydepartment

2016 Users(N ¼ cen-sus)

Hospital/Change Iran

Abdekhodaet al175


Integrating a model toexplore physicians’attitudes toward usingand accepting EMR inhealth care


Hospital/Integrated TAMand diffusion ofinnovation theory (DOI)model

Iran

Strudwicket al176


Developing integratedTAM using theory ofreasoned action, theoryof planned behavior,and the TAM to explainbehavior among nurses

2016 Nurses(N ¼ –)

–/Combining threedifferent models theoryof reasoned action(TRA), theory of plannedbehavior (TPB), and TAM

Canada

Hsiao andChen177

Computerizedclinicalpracticeguidelines

Investigating criticalfactors influencingphysicians’ intentionthrough an integrativemodel of activitytheory, and the


Hospital/ incorporatingactivity theory (threedimensions of factors)with TAM concepts(intention as dependentvariable)

Taiwan



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additions can be expected to allow comparisons between ICTapplicationareas andharmonizationbetween ICTapplicationsand different organizational processes.

However, it has been suggested that a main reason forinconsistent predictive performance of the TAM in healthservices is the poor match between construct operationali-zation and the context inwhich the construct is measured,29

The second method to expand the TAM is to add contextua-lized TAM concepts that increase predictive power. Onemethod to derive such contextualized concepts is beliefelicitation60 which was also the process used to fit generalbehavioral theory to the ICT context when developing theTAM.20 However, this step-wise method is less suitable forcomparisons between application areas and analyses of theorganizational fit of new ICT applications from a generalhealth service perspective. The results of this review suggestthat consensus is needed upon how the TAM extensionprocesses should be designed for uses in health services.

The primary threats to the validity of this review areconcerned with the search strategy employed. First, it maybe possible that we have not identified all relevant pub-lications. The completeness of the search is dependentupon the search criteria used and the scope of the search,and is also influenced by the limitations of the searchengines used. Publication bias is possibly a further threatto validity, in that we were primarily searching for litera-ture available in the major computing digital libraries. It ispossible that, as a result, we included more studies report-ing positive results of the TAM as those publicationsreporting negative results are less likely to be published.Since we have been unable to undertake a formal meta-analysis, we are equally unable to undertake a funnelanalysis—using a series of events that lead toward a definedgoal—to investigate the possible extent of publication bias.Finally, it must be remembered that the TAM does notmeasure the benefit of ICT use,57 implying that measures of

Table 5 (Continued)



Country

technology acceptancemodel

Saigi-Rubióet al178

Telemedicine Investigatingdeterminants oftelemedicine use inclinical practice amongmedical professionalsusing the TAM2 andmicrodata


Health care institution/Security andconfidentiality,subjective norm,physician’s relationshipwith ICTs

Spain

Lin et al179 Nursinginformationsystem (NIS)

Developing aconceptual frameworkthat is based on thetechnology acceptancemodel 3 (TAM3) andbehavior theory

2016 Nurses(N ¼ 245)

Hospital/Frameworkthat is based on theTAM3 and behaviortheory (prior experience)

Taiwan

Ducey andCoovert180

Tabletcomputer

Evaluating practicingpediatricians to use oftablet based onextended technologyacceptance model

2016 Pediatri-cians(physi-cians)(N ¼ 261)

Hospital/Subjectivenorm, compatibility,reliability

UnitedStates

Holdenet al181

Novel health IT,the largecustomizableinteractivemonitor

Examining pediatricintensive care unitnurses’ perceptions,acceptance, and use ofa novel health IT, thelarge customizableinteractive monitorbases on TAM2

2016 Nurses(N ¼ 167)

Hospital/Socialinfluence, perceivedtraining on system,satisfaction with system,complete use of system

UnitedStates

Omaret al182

Prescribingdecisionsupportsystems(EPDSS)

Investigatingperception and use ofEPDSS at a tertiary careusing TAM2

2017 Physicians(pediatri-cians)(N ¼ –)

Hospital/The TAM2theory

Sweden

Abbreviations: DOI, diffusion of innovation; HIV, human immunodeficiency virus; ICT, information and communication technology; ICU, intensivecare unit; IS, information system; IT, information technology; NHS, National Health Service; USB, Universal Serial Bus; UTAUT, unified theory ofacceptance and use of technology.



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Table 6 The factors, variables, and theories used in common technological contexts in studies (respectively, repetition andimportance)

Technology area Factors (variables) and intention-based theories incorporated to original TAM based on different usergroups and technological contexts

User groups Factors and variables Intention-basedtheories

Extended TAMversion used

HIT systems ingeneral

Health careprofessionals

Knowledge, endemic barriers, anxiety,relevance, self-efficacy, subjective anddescriptive norms, age, image, job level, workexperience, computer skills, voluntariness,information technology exposure,innovativeness, online informationdependence

DeLone andMcLean ISsuccess model

–

Nurses Social influence, perceived training on system,satisfaction with system, complete use ofsystem

– –

Patients Customized information, trustworthiness. Health beliefmodel (HBM),TPB

–


Physicians System quality, information quality, servicequality

– TAM3


Compatibility, training, social influence,facilitating condition, self-efficiency, anxiety

UTAUT –

Nurses Power distance, uncertainly avoidance,masculinity or femininity, individualism orcollectivism, time orientation, priorexperience, system quality, informationquality, self-efficacy, compatibility, topmanagement support, project teamcompetency

Informationsystem successmodel

TAM3

Electronic healthrecord (EHR)

Physicians System acceptability, system characteristics,organizational characteristics, individualcharacteristics, system accessibility,organizational cultural, perceptions ofinstitutional trust, perceived risk, informationintegrity, social impact, HIT experience,privacy concerns, compatibility, habit,subjective norm, facilitators, managementsupport, training, physicians’ involvement,physicians’ autonomy, doctor–patientrelationship

DOI, IDT, UTAUT TAM2


Perceived service level, perceived systemperformance, data quality, user interface, self-efficacy, clinical safety, security, integrationand information sharing

– –

Nurses Environment or context, nurse characteristics,EHR characteristic

TRA, TPB, TTF

e-Prescriptionsystems

Physicians Social influence, practice characteristics,physician characteristics, perceivedcompatibility, perceived usefulness toenhance control systems, training, perceivedrisks

– –

Nurses Perceived compatibility, perceived usefulnessto enhance control systems, training,perceived risks

– –

Computers,handheld (PDAs)

Physicians Subjective norm, compatibility, reliability,knowledge quality, system quality, servicequality, user satisfaction, age, position inhospital, cluster ownership, specialty

DeLone andMcLean ISsuccess model

–



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Table 6 (Continued)

Technology area Factors (variables) and intention-based theories incorporated to original TAM based on different usergroups and technological contexts

User groups Factors and variables Intention-basedtheories

Extended TAMversion used


Compatibility, support, personalinnovativeness, job relevance

– –

Nurses � – –

Pharmacists Subjective norm, image, output quality, resultdemonstrability, job relevance, experience,voluntariness

– TAM2

Telemedicine Physicians Security and confidentiality, relationship withICTs, subjective norm, facilitators, habit,compatibility, self-efficacy, accessibility,perceived incentives, process orientation,importance of standardization, e-healthknowledge, importance of documentation,importance of data, propensity to innovate,organizational readiness, technical readiness,social demographics, optimism, propensity toinnovate, enabling conditions

UTAUT, TPB,personalcomputingutilization

TAM2


Subjective norm, job fit, loyalty, expectationconfirmation, clinical factors, nonclinicalfactors, habit, compatibility, facilitators

– –

Patients Patient trust, person-centered caring,communication, enjoyment factor, social andinstitutional trust, social participation, self-efficacy, innovativeness, subjective norm,social norm, enabling conditions, technologyanxiety

HBM, socialcapital theory,social cognitivetheory, TPB,personalcomputingutilization

TAM2

Nurses Support from physicians, experience, supportfrom administrator.

– –

Mobileapplications

Physicians Gender, experience, age, personalinnovativeness, compatibility, social influence

– –


Reliability, social Influence, facilitatingconditions, self-efficacy, anxiety,recommendation, user satisfaction, attributeof usability, technical support and training,compatibility

– –

Nurses Subjective norm, image, output quality, resultdemonstrability, job relevance, experience,voluntariness

– TAM2

Patients Information technology experience (ITE),compatibility, self-efficacy, technical supportand training, personalization, privacy, anxiety,prior experience, person-centered,communication

Self-determinationtheory (SDT)

–

Personal healthrecord (PHR)

Patients Subjective norm, physician–patientrelationship (PPR), social norm, privacyconcern, trust, perceived risk, controllability,self-efficacy, compatibility, perceived value

DOI –

Abbreviations: DOI, diffusion of innovation; HIT, health information technology; ICT, information and communication technology; IDT, innovationdiffusion theory; IS, information system; PDA, personal digital assistant; TAM, technology acceptance model; TPB, theory of planned behavior; TRA,theories of reasonable action; TTF, task-technology fit; UTAUT, unified theory of acceptance and use of technology.



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technology acceptance and use intentions should not bemistaken for measures of technology value. Separatestudies using measures of effectiveness or productivityare needed to assess the organizational value of the newtechnology.

The review was limited to those articles describing onlythe TAM and its application in health care service. Byrestricting our review to a narrow segment of this literature,we may have inadvertently eliminated meaningful detailsfrom other acceptance models and factors in health tech-nologies acceptance. Also, there are books and book chaptersthat deal with the TAM in health care. These types ofpublications are not included in our review, but may containinformation relevant to this review. Finally, our reviewincludes only articles in English language and languagesother than English might have information about the TAMin health care.

Conclusion

The result showed that telemedicine applications peakedbetween 1999 and 2017 and is the ICT application area mostfrequently studied using the TAM, implying that acceptanceof telemedicine applications during this period was a majorchallenge when exploiting ICT to develop health serviceorganizations. A majority of the reviewed articles reportedextensions of the original TAM, suggesting that no optimalTAM version for use in health services has been established.Although the review results indicate a continuous progress,there are still areas that can be expanded and improved toincrease the predictive performance of the TAM. Finally, it issuggested that the common investigated factors in the pre-vious studies (►Table 6), for each technological contexts anduser groups, should tested empirically in real settings. Ifthese factors confirmed, it is recommended that they will be

Table 7 Other models’ comparison with TAM and confirmation of suitability of the TAM factors


Main topic Years Sample Setting Country

Chau andJen-Hwa46

Telemedicine Comparing different models, includingTAM, the theory of planned behavior(TPB), and an integrated model foracceptance telmedicine

2002 Physicians(N > 400)

Hospital China

Lianget al51

Computerizedphysician orderentry (CPOE)

Examining whether the TAM can beapplied to explain physicianacceptance of CPOE


Hospital China

Day et al45 Videophonetechnology

Evaluating hospice providers3attitudes and perceptions regardingvideophone technology in the hospicesetting in the context of the TAM

2007 Providers(N ¼ 17)

Hospice Colombia

Smith andMotley50

Electronicprescribing

The degree of e-prescribingacceptance is highly predictable byfactors that are very stable ease-of-usevariables derived from the TAM

2010 Pharma-cists(N ¼ 50)

Pharma-ceuticalcompany’ssupply

UnitedStates

Kim et al47 Telehomecare(telemedicine)

Comparing two theories of technologyadoption, the technology acceptancemodel and the theory of plannedbehavior, to explain and predictphysicians’ acceptance and use of thetelehomecare technology


Homecare UnitedStates

Kuo et al183 Mobileelectronicmedical record(MEMR)systems

Confirming relationships between theTAM components, and behavioralintention in the technology acceptancemodel toward MEMR usage

2013 Nurses(N ¼ 665)

Hospital Taiwan

ManimaranandLakshmi49

Healthmanagementinformationsystem (HMIS)

Formulating a model of technologyacceptance of health managementinformation system (HMIS) thatfeatures the TAM was confirmed

2013 Healthworkers(N ¼ 960)

Ruralhealth care

India

Hsiao andTang44

Mobile healthcare devices

The use intention of mobile health caredevices from the perspectives ofelderly people


– Taiwan

Kim et al48 Mobileelectronichealth records(EMR) system

Confirming the factors that influenceusers’ intentions to utilize a mobileelectronic health records (EMR) systemwith TAM


Hospital SouthKorea

Abbreviation: TAM, technology acceptance model.



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applied as a basic model for each technological contexts anduser groups.

Clinical Relevance statement

This systematic review showed that between 1999 and 2016,telemedicine applicationswere the ICT application areamostfrequently studied using the TAM, implying that acceptanceof the telemedicine technology during this period was amajor challenge for health service organizations. The con-struct validity of the model is showcased by its broadapplicability to various technologies in health care. Withthe increasing number of technologies in the health careenvironment, the use of technology acceptance models isneeded to guide implementation processes across healthservice contexts and user groups. This review has indicatedcontinuous progress in revealing new aspects critical for ICTimplementation having significant influence on health ser-vice processes and outcomes.

Multiple Choice Questions

1. Which of the following options are three main technolo-gical contexts using the TAM in health care ICTs?a. (1) Hospital information system (HIS), (2)mobile appli-

cations, and (3) electronic health record (EHR).b. (1) Telemedicine, (2) hospital information system

(HIS), and (3) computers, handheld (PDAs).c. (1) Telemedicine, (2) electronic health record (EHR),

and (3) mobile applications.d. (1) Electronic health record (EHR), (2) e-prescription

systems, and (3) hospital information system (HIS).

Correct Answer: The correct answer is option c. The studyidentified three main technological contexts for usingTAM in health care: (1) Telemedicine, (2) electronic healthrecords (EHR), and (3) mobile applications. The geogra-phical contexts of using TAMbetween different countries:Taiwan (telemedicine and mobile applications), U.S. andIran (EHR), and Spain (telemedicine).

2. What variables can be added to the original TAM as a basisformodel application in avarietyof technological contexts?a. Subjective norm, self-efficacy, compatibility, experi-

ence, training, anxiety, habit, and facilitators.b. Job relevance, age, communication, image, information

quality, and uncertainty avoidance.c. Power distance, time orientation, project team compe-

tency, acceptability, and organizational characteristics.d. Training, management support, user interface, auton-

omy, cluster ownership, personal innovativeness, andloyalty.

Correct Answer: The correct answer is option a. The mostcommon factors added to the original TAM in almost alltechnological contexts were, in order of importance andfrequencyof repetition, compatibility, subjectivenorm, self-efficacy, experience, training, anxiety, habit, and facilitators.

Protection of Human and Animal SubjectsNot applicable.

FundingNone.

Conflict of InterestNone.

AcknowledgmentsThis article was developed as a part of the research studycode: 1395–01–52–2759 and by the supports of UrmiaUniversity of Medical Sciences. Also, we are very thankfulto the editorial board of Applied Clinical Informaticsjournal for their valuable and constructive commentsthat made us very encouraged to reread and integrateall the comments.

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A Systematic Review of the Technology Acceptance Model in … · Appl Clin Inform 2018;9:604–634....

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