بررسی تصمیمات متخصصی بهداشت و درمان برای پذیرش فناوری پزشکی از راه دور: آزمون تجربی نظریه های رقیب
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|13157||2002||15 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Information & Management, Volume 39, Issue 4, January 2002, Pages 297–311
The proliferation of information technology (IT) in supporting highly specialized tasks and services has made it increasingly important to understand the factors essential to technology acceptance by individuals. In a typical professional setting, the essential characteristics of user, technology, and context may differ considerably from those in ordinary business settings. This study examined physicians’ acceptance of telemedicine technology. Following a theory comparison approach, it evaluated the extent to which prevailing intention-based models, including the technology acceptance model (TAM), the theory of planned behavior (TPB) and an integrated model, could explain individual physicians’ technology acceptance decisions. Based on responses from more than 400 physicians, both models were evaluated in terms of overall fit, explanatory power, and their causal links. Overall, findings suggest that TAM may be more appropriate than TPB for examining technology acceptance by individual professionals and that the integrated model, although more fully depicting physicians’ technology acceptance, may not provide significant additional explanatory power. Also, instruments developed and repeatedly tested in prior studies involving conventional end-users and business managers may not be valid in professional settings. Several interesting implications are also discussed.
Recent information technology (IT) developments have expanded into areas that can be broadly characterized by their technology applications and targeted users. To excel, or even survive, most businesses continue to rely on, and indeed accelerate, heavy investment in IT. Concurrently, various IT applications designed to support highly specialized tasks and services by individual professionals have also proliferated. A case in point is telemedicine technology for healthcare professionals. Understandably, physicians are among the principal users of this technology and have profound influences on its success. Physicians may exhibit interesting or fundamental differences from ordinary business user groups, in part because of their professional training, etc. Most telemedicine research has focused on the technology developments and clinical applications essential to its success. Consequently, there has been limited discussion of managerial issues that are arguably equally important. This study investigated user technology acceptance in healthcare organizations already providing or planning to provide telemedicine-enabled patient care and services. Thus, examining the validity and explanatory (or predictive) utility of prevalent theories or models in a professional setting is particularly interesting and timely. Specifically, this study examined and compared the technology acceptance model (TAM)  and  and the theory of planned behavior (TPB)  and . Both TAM and TPB are leading theoretical models for such research and have accumulated fairly strong empirical support involving various end-users and business managers. We also examined a model integrating elements derived from both TAM and TPB. In a nutshell, theory testing follows replication logic and hence makes theory comparison an attractive approach, i.e. generating support for a theory (or some theories) and, at the same time, singling out the potential limitations of others. Using the responses from a survey study that involved more than 400 physicians, the research effort evaluated and compared the extent to which the respective models could explain individual physicians’ intention to use telemedicine technology. The causal paths specified by each model were also examined.
نتیجه گیری انگلیسی
This study investigated factors essential to acceptance of telemedicine technology by individual healthcare professionals. We took a theory-comparison approach and used behavioral intention as a measure of technology acceptance. Findings of the study suggest several potential areas where healthcare professionals might interestingly or fundamentally differ in technology acceptance decision-making, compared with the user populations commonly examined in prior research. First, when making a decision to accept versus reject a technology, healthcare professionals appear to be fairly pragmatic, concentrating on the technology’s usefulness rather than on its ease of use. Furthermore, these professionals seem to be relatively independent in making technology acceptance decisions, e.g. not attaching much weight to suggestions or opinions from others. The study has the merits of evaluating individual technology acceptance in a real-world professional setting, including principal target users who assess telemedicine technology in light of their routine clinical tasks and services. In addition, this study represents a needed and timely effort for extending technology acceptance research into health care, a service sector that has demonstrated increasing IT investment and penetration . This study has several limitations. First, this study concentrated on a particular technology and involved a specific professional group. Thus, caution needs to be taken when generalizing the findings and discussion to other technologies or professional groups. Second, measurement items for the constructs specified by the investigated models exhibited reasonable but not highly satisfactory reliability. Third, responses on behavioral intention were collected using a self-reporting method, a common data collection technique that has been justified and advocated by some researchers  but questioned for inadequacy or lack of validity by others . Szajna  suggests that alternative behavior-oriented measures (e.g. choice behavior) should be used instead. Similarly, Thompson et al.  suggest the use of both objective and subjective measures that allow desired examinations of the correspondence (or the lack of it) between them, regardless of the dependent variable. Despite its limitations, results from the study have some interesting implications. First, the study generates interesting empirical evidence that highlights plausible limitations of TAM and TPB in explaining or predicting technology acceptance by healthcare and possibly other professionals. Both models were able to account for an acceptable but not a dominant portion of the behavioral intention variances observed. The explanatory utility improvement for behavioral intention resulting from the addition of subjective norms and perceived behavioral control to TAM was limited, if any. The fact that none of the investigated models was able to explain half of the behavioral intention variance may signify the need for a broader exploration of factors beyond TAM and TPB. Responding to calls for additional theory-testing efforts to validate or extend the research results from prior studies, this study empirically investigated telemedicine technology acceptance by physicians. Results from prior research may represent a logical and reasonable point of departure in searching for additional or mediating factors. Candidate factors might include self-efficacy, user participation and involvement, prior usage and experience, and user characteristics. Theory refinement through model decomposition represents a promising approach. Although a decomposed model may provide additional insights to behavioral intention and actual behavior, it does not guarantee significantly improved explanatory or predictive power. Theory expansion through model integration is another interesting approach. Collectively, the approaches and prior research may provide a reasonable starting point for identifying additional or mediating factors or developing theoretical frameworks instrumental to advancing our understanding of technology acceptance by individual professionals. 7.1. Implications for technology management practice From a technology management standpoint, findings of the study reveal the importance of attitude cultivation and management. To foster individual acceptance of a newly adopted or implemented technology, management in a professional organization needs to devise strategies for cultivating positive attitudes toward using the technology. In this connection, favorable perception of the technology’s usefulness is crucial, whereas the technology’s ease of use might not be of equal importance. Upon deciding to adopt telemedicine technology, management should strongly emphasize, demonstrate and communicate the technology’s usefulness to the routine tasks and services of individual physicians. Thus, initial information sessions and training programs should focus on how the technology can improve the efficiency or effectiveness of individual physicians’ patient care and services rather than on familiarization with the detailed procedures for operating the technology. The observed insignificant effects of subjective norms on intention suggests that a physician, when making the technology acceptance decision, might value his or her own assessments more than the opinions and suggestions of others. This finding may have in part resulted from the overall early development of telemedicine in Hong Kong, where the number of telemedicine “guru” or highly experienced physicians is limited. Awareness and understanding of successful telemedicine programs and applications elsewhere may mitigate this constraint. By witnessing and interacting with peers known for telemedicine-enabled services, physicians may be able to assess the technology from a different and perhaps broader perspective. Continued education programs, clinical workshops and international conferences are adequate arrangements for increased awareness and knowledge about telemedicine technology and its applications. The modest significance of perceived behavioral control on intention, though weaker than that of attitude, suggests that perceived behavioral control remains important in shaping individual intention toward technology acceptance. The observed weaker influence, as compared to that of attitude, may have in part attributed to the characteristics of public acute-care tertiary hospitals in Hong Kong. By and large, these organizations have a fairly sophisticated in-house technology base and reasonable access to various resources, including designated space to house telemedicine technology. Thus, convenient technology access and in-house technology training and support are usually available and consequently may not constitute central concerns in physicians’ technology acceptance decisions. When introducing telemedicine technology and promoting its acceptance among physicians, management, nevertheless, needs to evaluate these facilitating conditions, e.g. access and training.