Transfer and Adoption of Advanced Information Technology Solutions ...

ORIGINAL RESEARCH

Transfer and Adoption of Advanced Information Technology Solutions in Resource-Poor Environments: The Case of Telemedicine Systems Adoption in Ethiopia Mengistu Kifle, Ph.D.,1 Fay Cobb Payton, Ph.D.,2 Victor Mbarika, Ph.D.,3 and Peter Meso, Ph.D.4 1

ICITD, Baton Rouge, Louisiana. College of Management, North Carolina State University, Raleigh, North Carolina. 3 Southern University, Baton Rouge, Louisiana. 4 Georgia Gwinnet College, SST, Lawrenceville, Georgia. 2

Abstract The study of the adoption of information technology (IT) by individuals has taken two approaches, one emphasizing rationalistic goal-oriented behavior and the other focusing on poignant forces that influence an individual’s reaction to a new IT. These approaches are not necessarily mutually exclusive. Individuals’ acceptance and subsequent usage of a new IT is predicated on both. Additionally, the tendency in past studies has been to examine either the rational or the poignant factors in the context of a ‘‘resource-rich’’ environment—one in which there is an abundance of IT, adequate infrastructure, and a high level of acculturation to technology solutions. Consequently, there is a clear need for the examination of these factors in resource-poor environments, where assumptions on technology abundance and technology culturation do not hold. We empirically test a model that explains the intention of physicians in a resource-poor environment (epitomized by rural Ethiopia) to adopt telemedicine systems. This model integrates the rational factors

DOI: 10.1089=tmj.2009.0008

driving goal-oriented behavior with the poignant=emotive factors that are an innate part of each adopter’s reaction to the new technology. We use the model to expose salient contextual factors that explain the acceptance behavior of individuals toward complex information and communications technology (ICT) solutions and implications of these on the management of technology transfer initiatives in a resource-poor environment. The model is parsimonious, yet explains 28% of the variance in the intention to adopt telemedicine systems and 58% in perceived ease of use. The theoretical and practical implications of this model are discussed. Namely, Sub-Saharan African, in general, and Ethiopian culture, in particular, plays an integral role in the adoption of ICT solutions. Organizational positions and roles among physicians, clinical professionals, and superiors stand to impact the adoption of telemedicine and other healthcare applications. Last, the degree to which users perceive that ICT is easy to use (i.e., ease of use) can be a function of technology experience and can influence perceived usefulness on behalf of users and healthcare organizations. Key words: telemedicine, healthcare, technology acceptance, information technology (IT) adoption, sub-Saharan Africa (SSA), Ethiopia

Introduction

T

he health sector is facing the need to provide equitable access to healthcare services while reducing escalating costs and managing chronic illness. In developing countries, there is a growing demand for additional technology-based

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services because of the changing epidemiological landscape, user awareness, and adoption trends. Developing countries, including Ethiopia, are also facing the ever present brain drain of doctors and healthcare workers to the developed world and shifting of clinical professions, for example, to Masters in Public Health training programs. To meet this challenge, healthcare providers are looking to use telemedicine as alternative solution. Telemedicine is most commonly defined as the use of information and communications technology (ICT) to deliver healthcare services at distance. It has been suggested that telemedicine is particularly compelling for service delivery in areas characterized by gross inadequacies in medical personnel, medical centers and institutions, medical equipment, and even medications—in other words, in environments that are classified as resource poor with respect to medical and healthcare service infrastructure. For example, telemedicine systems have been fundamental in allowing the flow of expert medical knowledge from medical referral, research, and teaching institutions to distant remote locations where that knowledge is needed but lacking owing to the absence of requisite medical experts in those remote locations. Telemedicine has also been credited with extending coverage of medical and healthcare services to primary, secondary, and tertiary levels of resources that would otherwise not receive these services.29 The vast majority of least-developed nations are located in subSaharan Africa (SSA), and these countries clearly represent resourcepoor environments. Ethiopia, the second most populated country in SSA with a population of over 75 million people, is a case in point. The country is among the poorest in the world. It has an annual per capita income of less than $100, and an average life expectancy of just 40 years. The ICT indicators for Ethiopia reveal around 1 main telephone line, 0.31 personal computers, 0.05 Internet users, per 100 inhabitants at the very end of the ranking for connectivity access. If we consider radiology, a discipline of medicine that is dependent on technology and tends to be technology intensive, Ethiopia has only 56 radiologists serving its population of 75 million citizens. This shortage of radiologists is further complicated by the fact that 50 of the 56 radiologists are located in the capital city, Addis Ababa. This is a major problem given that 85% of Ethiopia’s population lives in rural areas outside of Addis Ababa.25 The situation in Ethiopia is reflected in most of the other countries in SSA. On average, there are fewer than 10 doctors per 100,000 people in SSA. Fourteen countries within the region do not have a single radiologist.11 Therefore, in resource-poor environments, such as those epitomized by the least-developed countries, including

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Ethiopia, telemedicine solutions become viewed as effective conduits for leveraging the scarce medical resources and infrastructures available to achieve the greatest possible quantity of medical and healthcare service delivery.17,21,46 Although it has been suggested that telemedicine is particularly compelling for service delivery in resource-poor environments, the adoption of the technology in the less-developed nations has been rather slow compared with the adoption of the same technology within the advanced economies. Much of the research on the introduction of telemedicine technologies in the less-developed economies has used theories of technology transfer, where the introduction of the new technology is viewed as an organization-to-organization project. The supplying entity is usually an organization in an advanced country, whereas the receiving entity is an organization in a less-developed nation, and the project is usually turn-key in orientation.29 This stream of research perceives the key factors impacting the transfer of technology and=or its associated knowledge as occurring at the organizational level. Therefore, research in this stream tends to focus on organizational level decision-making behavior, which impacts the transfer of technology. However, although organizational level technology transfer factors are important, subsequent acceptance of a new technology is dependent on the behaviors of the prospective individual users of the new technology solution.23 Bashshur et al.4 determined that physicians’ rejection of novel technology is one of the reasons that telemedicine implementations have failed. Perednia and Allen35 suggested that the success of telemedicine should account for technological advancements as well as user technology acceptance. Additionally, although there is much published research on telemedicine, the majority of attention, however, is focused on the evaluation of the technological aspect of telemedicine, where the experiences from previous projects show failures of adoption due to improper, or lack of consideration of physicians’ needs when introducing new telemedicine technologies into existing medical practices.34 Therefore, an examination of individual decision-making behavior with respect to the acceptance of information technology (IT), in general, and telemedicine, in particular, and how this behavior influences the successful transfer of IT into organizations located within resource-poor environments is both relevant and important. This is because it contributes to the establishment of a deeper understanding of how to best manage successful introduction of novel and useful technology solutions into resource-poor environments. Within the realm of telemedicine transfer, such a study also provides the additional empirical benefit of providing clarity to the factors that mitigate the speedier diffusion of telemedicine technology to

PHYSICIAN ADOPTION OF TELEMEDICINE IN ETHIOPIA

resource-poor countries, especially given the theorization that telemedicine technology is best suited for such environments. In this article, we depart from the common practice of studying technology transfer at the national or organizational level and, instead, seek to examine individuals’ behavior toward the adoption of telemedicine with a view to expose salient factors that may have an influence on and=or explain telemedicine transfer outcomes within a resource-poor environment. Specifically, we empirically analyze the intention of physicians in rural Ethiopia to adopt telemedicine systems, and the relative effect of their behavior intention on the eventual success of telemedicine transfer initiative to this region. This research makes important theoretical and practical contributions. On the theoretical side, impacts of individual action on the eventual success of technology transfer into a resource-poor environment are empirically tested. Empirical evidence of how these factors interplay to influence intention to accept telemedicine technology in resource-poor environments is provided and salient factors that may contribute toward the observed behavior are explained. On the practitioner side, the study identifies a number of key significant factors that should be carefully considered when introducing a new complex interactive IT solution into resource-poor environments. We provide a brief review of telemedicine, followed by the research model and a set of research hypotheses. We discuss the research methods used to test the proposed model and then present the analysis of the study’s results. Finally, we conclude by discussing implications of this study for researchers and healthcare technology management professionals, limitations, and future research directions.

Telemedicine Telemedicine involves the use of ICTs to examine patients in remote areas and to transmit medical data, video images, and audio among physicians and other healthcare providers to treat the sick, thus managing chronic illness, promoting healthcare service, and preventing diseases. These technologies include teleimaging diagnostics (teleradiology, teledermatology, and telepathology), telesurgery, telecardiology, and teleconferencing. In general, improved access to health services, improved quality of healthcare, effective use of scarce medical human resources, and cost control were the motives to telemedicine technology implementations in the 1970s.19 Thus, healthcare providers, patients, and the society at large have been keen on utilizing telemedicine as a technological innovation. Craig and Patterson8 noted that developing countries implement telemedicine because either (1) there are no alternatives (i.e., problems related to accessing healthcare services and telemedicine’s po-

tential role in the delivery of medical care to patients, as well as healthcare provider perspectives), or (2) telemedicine has geographic advantages over traditional medicine (i.e., increasing access and cost benefits of telemedicine compared with traditional alternatives). Moreover, the implementation of telemedicine in developing countries is considered a major innovation at both the technology and social levels of the healthcare system.3 In general, a main objective of telemedicine transfer to developing countries is to facilitate cost-effective delivery of medical services to the majority of the population in rural and urban areas.13,14,35,38 Other reasons for the growing recognition of telemedicine as an alternative solution to reduce the existing healthcare problems in developing countries include financial benefit, access to experts, affordability of visual-based telemedicine applications, recent technology advancements, and rising costs of accessing traditional healthcare services. For these reasons, among others, telemedicine has been identified as one of several possible solutions to serious medical problems evident in most developing countries, especially the SSAs.20,24,25,28,29 The Ethiopian telemedicine system was initially conceptualized and introduced in 2001. Since this time, concerted efforts and collaboration among varied stakeholders has seen the system expand to its present coverage of four teaching hospitals and six district hospitals, which are giving services for more than 29 clinics or health centers. Some experiences of telemedicine practices and uses in Ethiopia include the following26,27: . Teleradiology is used for the purpose of securing second opinions from a specialist, and so better use of clinical competences available at the hospitals and optimization of time and costs for patients and providers are achieved. . Teledermatology centers are equipped with a complete but lowcost system with an ordinary digital camera to provide diagnostic, referral, follow-up, and technical supports. . Teleophthalmology centers establish a network to maintain the software and provide technical support at national level. ORBIS has provided the hardware and software facility for teleophthalmology, as well as teleconsultation with national and international links. . Telepathology hubs are used to connect Black Lion Hospital in Addis Ababa to the iPath server at the University of Basel, Switzerland, for second opinions in the central referral hospital using the iPath Web-based platform. As the expansion and scale-up of the system is still ongoing, a key concern of the implementation team’s efforts was that physicians’ reactions to the telemedicine system would impact implementation


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success. For that reason, we selected to perform a formal empirical assessment of the physician’s intentions to adopt the technology with a view to unearth the salient factors that shape physicians’ acceptance of the new technology and eventually the overall success of this technology transfer initiative.

Research Model and Hypotheses

nology. The most prevalent theories have been the theory of reasoned action, the theory of planned behavior, the technology acceptance model, and the more recent unified technology acceptance and usage of technology model.2,9,10,30,37,44,45 Research on IT use has also indicated that the personal traits of an individual exert an influence on the decision to adopt a new technology. The degree of IT competence that an individual possesses, for example, the image ascribed to the individual by society, and the anxiety owing to pressures of performance excellence expected of the individual, among others, have been shown to impact the individual’s reaction to a new technology.1,2,41,43,45 We refer to these as poignant factors because they do not emanate from an individual’s rational decision-making traits. Rather, they are more emotive in orientation. Hence, information system (IS) research focusing on technological acceptance, widely studied in other contexts and domains of IS utilization,1,5–7,19,22,23,41,44,45 can prove critical in healthcare implementations. Our proposed model (Fig. 1) combines well-validated constructs used in previous studies that focused on telemedicine adoption1,2,9,10,19,30,36,37,41,42 to examine the reactions of Ethiopian physicians. The telemedicine solution, herein, is being diffused to link Ethiopia’s rural areas to centers of expertise at the teaching universities in Addis Ababa. We seek to empirically assess the acceptance of the new telemedicine solution by the physicians. In our study, technology acceptance is defined as a physician’s psychological state with respect to her=his intention to adopt telemedicine. Because telemedicine in Ethiopia is still in the early

With the advent of the Internet and the growth of the telecommunication infrastructures in most of the less-developed nations, there is an increasing interest in the potential impacts of ICT on organizational, institutional, and societal transformations. Much research has been published on both the diffusion of ICT into these nations and the adoption of ICT solutions organizations in these countries. In the context of technology diffusion into these resourcepoor environments, this adoption has largely been studied from the lens of technology exchanges, usually unidirectional transfer, between two partnering organizations. These technology exchanges may take the form of turn-key arrangements,29 knowledge networks,18 or distributed collaboration,42 just to name a few. As Khalifa and Davison pointed out, ‘‘while individuals are clearly involved in organizational adoption decisions, the issues that influence their decision making are quite different from those that would be salient when they are acting as individuals. . . .’’ Therefore, although organizational factors are important and crucial determinants of successful introduction of a new technology into an organization, individual factors play a pivotal role as well. This is particularly the case where the technology being introduced is to be used extensively for knowledge-intensive tasks performed by individual professionals. In this regard, past studies34,19 noted the importance of examining individuals’ reactions to a new technology and how these reactions influence the success or failure of the technology’s implementation. To this end, physicians have been shown to play a critical role in the implementation of healthcare applications and networks.34 An individual’s rational goals influence the adoption behavior exhibited by the individual toward a new technology. Much of the published research on technology adoption has employed theories that capture individual decision-making behavior to model individuals’ affinity toward accepting and using a new tech- Fig. 1. Hypothesis model path coefficients and significance (n ¼ 144).



adoption stage, we targeted both image-based telemedicine practices (i.e., radiology) and patient contact-based telemedicine practices (i.e., internal medicine). Therefore, in keeping with published studies on the acceptance of new IT, and based on our research model, we hypothesized that conventional technology acceptance antecedents, namely perceived ease of use, usefulness, facilitating conditions, voluntariness of use, and social influence, will impact physicians’ intention to adopt telemedicine technology. We also hypothesized that compatibility of the system to the physician’s work practices would also influence the physician’s behavior toward the new technology because it would directly impact the physician’s effectiveness. In addition to the conventional technology acceptance antecedents, we hypothesized that a number of poignant factors, determined

by the resource-poor nature of environment in which the physicians are operating, would also influence the adoption behavior of the physicians. First, the image enjoyed by the physician in the community by virtue of his=her having access to telemedicine systems, given that many other physicians do not enjoy such access, provides status recognition and would thus be a determinant of that physician’s reaction to telemedicine. Second, a physician’s computer selfefficacy, being a measure of how comfortable a physician would be with using IT, in general, would also be a significant determinant of the physician’s telemedicine adoption behavior. Likewise, anxiety, the degree to which a physician is afraid that something may go wrong while using the new technology to perform requisite professional tasks would also impact the physician’s telemedicine adoption behavior. Table 1 presents a summary of the hypotheses.

Table 1. Hypotheses, Relationship, and Results VARIABLE INDEPENDENT

DEPENDENT

SPECIFIC HYPOTHESIS

RESULT

H1

Computer self-efficacy

Perceived ease of use

Computer self-efficacy is positively related to their perception of ease of Supported use of telemedicine

H2

Facilitating conditions


Facilitating conditions are positively related to their behavioral intention Not supported to adopt telemedicine

H3

Perceived compatibility

Usefulness

Perceived compatibility is positively related to their perception of the ease of use of telemedicine

Supported

H4


Usefulness

Perceived ease of use of telemedicine is positively related to their perception of its usefulness

Supported

H5

Image

Behavioral intention to adopt

Image is positively related to their behavioral intention to adopt telemedicine

Not supported

H6

Perceived voluntariness


Voluntary use of telemedicine is positively related to their behavioral intention to adopt

Negative support

H7

Social influences


Social influences are positively related to their behavioral intention to adopt telemedicine

Supported

H8

Anxiety


Anxiety in the use of telemedicine is positively related to their behavioral Supported intention to adopt

H9



Perceived ease of use of telemedicine is positively related to their behavioral intention to adopt it

Not supported

H10

Usefulness


Usefulness of telemedicine is positively related to their behavioral intention to adopt

Supported

Note: ‘‘Supported’’ is strictly path coefficients greater than þ0.20 and P (t) < 0.05. ‘‘Not supported’’ means p-values > 0.05, no matter the value of path coefficient.


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Methodology Our study used well-validated instruments from three previous studies9,19,36 to develop our survey instrument, using a seven-point Likert item scale with values ranging from 1 (strongly disagree) to 7 (strongly agree). The previously validated instruments were adapted to the Ethiopian (sub-Saharan African) context of telemedicine technology. Our instrument included the constructs of ease of use (four items), usefulness (six items), compatibility (three items), image (two items), self-efficiency (eight items), voluntariness of use (two items), and behavioral intention to adopt (four items). These constructs were adapted from Raestone et al.36 as well as Croteau and Vieru.9 The anxiety (five items), social influences (four items), and facilitating conditions (four items) constructs were based on the study by Hu et al.19 Table 2 offers these details. Before our pilot test, the questionnaire was revisited to fit the Ethiopian context and ensure that physicians understood the questions. Hence, a review panel that consisted of three Ethiopian physicians from different specialties was established to assess the validity of the instrument. The review panel also examined the formatted survey instrument to ensure that its layout and word choices were appropriate. Proposed revisions from the review panel, as well as those from the pilot test, were integrated into the survey instrument. We also provided a definition of telemedicine within the questionnaire to ensure that respondents had a common understanding of the concept. These, together with the definition of telemedicine in the instrument and the recalibration of each item on the instrument to ensure that it was adequately understood by respondents, contributed in enhancing both the content validity and the appropriateness of our instrument. Additionally, one of the authors has considerable personal experiences working with telemedicine projects in Ethiopia and is a member of Ethiopia’s National Telemedicine Committee since 2001. Our survey was administrated at several hospitals that were scheduled to implement telemedicine applications in the near future (6–9 months). We selected institutions from each of the following targeted populations (public sector, private sector, and nongovernmental organizations). In total, 13 health institutions were surveyed, including four teaching hospitals, five nonteaching hospitals, one military hospital, and three health clinics. Also, several medical specialty areas were included, such as image-based specialty areas (radiology, pathology, dermatology, ophthalmology, orthopedics, and cardiology) and patient contact-based areas (internal medicine, pediatrics, gynecology, and psychiatry). Some of these physicians had taken a course in telemedicine.


To ensure a better response rate and cooperation from potential respondents, more than five personal visits were made to each of the 13 institutions included in this study. Before distributing the questionnaires, each organization’s directors were informed. Although we had strong endorsement from the Ethiopian National Telemedicine Committee and from healthcare administrators in the country, responses to our survey were absolutely voluntary. It is important to note here that all of the contacted hospitals agreed to participate in the study. The survey was administrated through departmental=administrative level contacts (typically the head of the department or healthcare administrator). The administrator distributed the questionnaires to physicians working within the given healthcare unit. This was followed by telephone calls to the participating institutions that delegated focal persons to collect the surveys from the participants. The physicians were asked to respond within five working days of being contacted. We administered the surveys to 260 physicians. Although this number may arguably seem low by some accounts, it is important to note that there is a major limitation on the total number (1,806) of physicians in Ethiopia. Further, the number of physicians in the country working in health centers or institutions that use or plan to use telemedicine is limited. Out of the 260 surveys distributed, 144 were returned with complete responses. This accounts for a 55.3% response rate. This high response rate can be attributed to our on-site visits as well as strong government support, an indispensable necessity to gain and sustain research progress in most African countries. Of the 144 completed responses, 69 were physicians in residence at the teaching hospitals, and 75 were physicians based at health facilities mentioned earlier.

Analysis and Results The data were analyzed using SPSS version 15.0 statistical software and the partial least squares (PLS) statistical analysis method as supported by the PLS software (MFG).

DESCRIPTIVE STATISTICS OF RESPONDENTS Most of the respondents were between 30 and 40 years in age and had 5–10 years of medical experience. Among the respondents, the male-to-female ratio was approximately 5:1 for physicians in residents and 4:1 for secondary=health centers. Note that there are notable disparities between the number of male and female physicians with most of the female physicians working at the secondary health facilities. Approximately, 60% of the respondents from both groups worked in highly image-based specializations, such as radiology and pathology. Of the healthcare institutions surveyed, 59.4% of the


Table 2. Constructs, Definitions, and Scales CONSTRUCT (SOURCE) [DEFINITION] 10

47

Perceived ease of use (Davis ; Davis et al. ) TAM [The degree to which a person believes that using a particular system would be free of effort]

MEASUREMENT ITEMS (1) Learning to operate the computer to use telemedicine would be easy for me (2) If I were to adopt telemedicine it would be easier for me to access images using this technology rather than regular films (3) If I were to adopt telemedicine it would be easy to use (4) Learning to operate telemedicine would be easy for me

(1) Usefulness (Davis10; Davis et al.47) TAM [The degree to which a person believes that using a particular system would enhance his (2) or her job performance] (3) (4)

Using telemedicine could improve the care I gave my patients If I were to adopt telemedicine I could see more patients out of the hospital Using telemedicine would increase my efficiency as a physician Telemedicine would be an improvement in the area where I see most of my patients (e.g., ICU etc.) (5) Using telemedicine will make it easier to do my job (6) If I were to adopt telemedicine, I would find it useful in my job

Compatibility (Moore and Benbasat30) IDT [The degree to which an innovation is perceived as being consistent with the existing values, needs, and past experiences of potential adopters]

(1) If I were to adopt telemedicine, it would be compatible with most aspects of my work (2) If I were to adopt telemedicine, it would fit my work style (3) If I were to adopt telemedicine, it would fit well with the way I work

Image (Moore and Benbasat30) IDT [The degree to which use of an innovation is perceived to enhance one’s image or status in one’s social system]

(1) If I were to adopt telemedicine I would gain more prestige amongst my peers (2) Using telemedicine will be a status symbol in my department

Self-efficacy (Compeau and Higgins48) IDT [Judgment of one’s ability I could use telemedicine technology . . . to use a technology to accomplish a particular job or task] (1) If I had prior usage of similar technologies (2) Even if I had never used a technology like it before (3) If I only had the built-in ‘‘help’’ function for assistance (4) Even if there was no one around to tell me what to do as I go (5) Even if I only had the software manuals as reference (6) If I had seen someone else using it before typing it myself (7) If I could call the help desk if I got stuck (8) If someone showed me how to use the system beforehand Voluntariness of use (Moore and Benbasat30) IDT [The degree to which use of the innovation is perceived as being voluntary, or of free will]

(1) The department head does not require me to adopt telemedicine (2) Although it might be helpful, adopting telemedicine is certainly not compulsory in my job

Behavioral intention to adopt (Fishbein and Ajzen49) TPB [An individual’s positive or negative feelings (evaluative effect) about performing the target behavior]

(1) If I were to adopt telemedicine, I would use it to perform different task, clinical and non–clinical (education) (2) I intend to adopt telemedicine technology when it becomes available in my department (3) Over the ensuring months (if possible) I plan on experimenting with telemedicine (4) Over the ensuring months (if possible) I plan to regularly use telemedicine

Anxiety (Compeau and Higgins48) IDT [Evoking anxious or emotional (1) I am concerned about possible liability issues associated with the use of telemedicine reactions when it comes to performing a behavior] (2) I do not like the loss of personal contact associated with telemedicine (3) More research is needed on the effectiveness of telemedicine before I would refer patients for teleconsultation (4) If additional credentialing and licensure procedures were required that would discourage me from using telemedicine. (5) I do not think an adequate physical exam can be conducted without the patient being present physically continued "


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Table 2. Constructs, Definitions, and Scales continued CONSTRUCT (SOURCE) [DEFINITION] 49

Social influences (Fishbein and Ajzen ) TPB [The person perception that most people who are important to him thinks he should or should not perform the behavior in question]

MEASUREMENT ITEMS (1) People who influence my behavior think that I should use telemedicine technologies (2) People who are important to me think that I should use telemedicine technologies (3) The senior management of my organization has been helpful in the use of telemedicine (4) In general, my organization has supported the use of the system

Facilitating conditions (Thompson et al.50) TPB [Objective factors in the environment (1) I have the resources necessary to use telemedicine technologies that observers agree make an act easy to accomplish. For example, provision of (2) I have the knowledge necessary to use telemedicine technologies support for users of personal computers] (3) Telemedicine technologies are not compatible with other systems I use (4) A specific person (or group) is available for assistance with system difficulties TAM, technology acceptance model, IDT, innovation diffusion theory; TPB, theory of planned behavior.

resident physicians and 73.3% of the secondary=health center physicians indicated using computers for e-mail, Internet access, and administrative activities. Fifty-seven percent of resident and 36.0% of secondary=health center-affiliated physicians reported using computers at home (Table 3).

of telemedicine also placed a high premium on the impact of perceived ease of use as a factor that influences their acceptance of telemedicine, whereas those with telemedicine knowledge did not. These results are consistent with our expectations. We will return to them in the discussion section.

ASSESSMENT OF THE RESEARCH MODEL

Assessment of the measurement model. We assessed the measurement model’s reliability, convergent validity, and discriminant validity. Reliability was tested using the Cronbach’s alpha values and was found to be satisfactory as all of the Cronbach’s alpha values (except for ‘‘image’’) were above 0.70 (Table 5).32 Confirmatory factor analysis was carried out to assess item loadings. Of the 42 original items listed in Table 2, 36 items loaded adequately.12 Six items (IMAG1, CSE3, CSE7, CSE8, ANX1, and ANX2) did not load adequately (i.e.,