An empirical investigation of Technology Readiness among medical staff based in Greek hospitals

Technology readiness (TR) represents an individual’s mental readiness to accept new technologies. Although the TR scale has been used in many studies, its application in the healthcare context is limited. This paper focuses on identifying the TR profiles of medical staff and to model preference TR variations with respect to computer use, computer knowledge and computer feature demands. The study reports results from a nationwide study conducted in Greece, during a three-year period, which sampled responses from 604 physicians and nurses working in 14 Greek hospitals. Exploratory Structural Equation Modelling analysis is used in order to confirm the structure of the Technology Readiness Index. The results confirm the five groups of the TR taxonomy. Statistical differences were found between classes in information and communication technology (ICT) knowledge, ICT feature demands, hours of use per week as well as ICT use performance, but not in the general use of ICT. The results facilitate comprehension of the factors, which influence the use of ICT by medical staff and, in addition, they convey important policy and managerial implications. In conclusion, medical staff should be treated according to its TR taxonomy classes in order to expedite the acceptance and use of an ICT system.

[1]  Jason Bennett Thatcher,et al.  Conceptualizing models using multidimensional constructs: a review and guidelines for their use , 2012, Eur. J. Inf. Syst..

[2]  Pierre Frémont,et al.  Systematic Review of Factors Influencing the Adoption of Information and Communication Technologies by Healthcare Professionals , 2012, Journal of Medical Systems.

[3]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[4]  Anne P. Massey,et al.  Usability of Online Services: The Role of Technology Readiness and Context , 2007, Decis. Sci..

[5]  Nikos Tsikriktsis.  A Technology Readiness-Based Taxonomy of Customers , 2004 .

[6]  P. J. Sher,et al.  Integrating technology readiness into technology acceptance: The TRAM model , 2007 .

[7]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[8]  Ulrich Trautwein,et al.  Please Scroll down for Article Structural Equation Modeling: a Multidisciplinary Journal Exploratory Structural Equation Modeling, Integrating Cfa and Efa: Application to Students' Evaluations of University Teaching , 2022 .

[9]  Dhruv Grewal,et al.  Self-service technology effectiveness: the role of design features and individual traits , 2007 .

[10]  Doreen Neville,et al.  Exploring the technology readiness of nursing and medical students at a Canadian University , 2008, Journal of interprofessional care.

[11]  Anol Bhattacherjee,et al.  Physicians' resistance toward healthcare information technology: a theoretical model and empirical test , 2007, Eur. J. Inf. Syst..

[12]  S. Fournier,et al.  Paradoxes of Technology: Consumer Cognizance, Emotions, and Coping Strategies , 1998 .

[13]  B. Muthén.  Latent Variable Mixture Modeling , 2001 .

[14]  Rolph E. Anderson,et al.  Multivariate Data Analysis with Readings , 1979 .

[15]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[16]  Rohit Verma,et al.  Exploring the Use of the Abbreviated Technology Readiness Index for Hotel Customer Segmentation , 2009 .

[17]  Marjolein van Offenbeek,et al.  Towards integrating acceptance and resistance research: evidence from a telecare case study , 2013, Eur. J. Inf. Syst..

[18]  J. Lin,et al.  The role of technology readiness in customers' perception and adoption of self‐service technologies , 2006 .

[19]  Mun Y. Yi,et al.  Understanding information technology acceptance by individual professionals: Toward an integrative view , 2006, Inf. Manag..

[20]  M. Sobel,et al.  Sociological Methodology - 2001 , 2001 .

[21]  R. Bagozzi,et al.  On the evaluation of structural equation models , 1988 .

[22]  D. Flora,et al.  An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. , 2004, Psychological methods.

[23]  Lukas Furst,et al.  Multivariate Data Analysis With Readings , 2016 .

[24]  Margaret Reid,et al.  Remote working: survey of attitudes to eHealth of doctors and nurses in rural general practices in the United Kingdom. , 2004, Family practice.

[25]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[26]  Rudolf H. Moos,et al.  Differential effects of ward settings on psychiatric patients. A replication and extension. , 1967, The Journal of nervous and mental disease.

[27]  Amy K. Yarbrough,et al.  Technology Acceptance among Physicians , 2007, Medical care research and review : MCRR.

[28]  A. Satorra,et al.  Complex Sample Data in Structural Equation Modeling , 1995 .

[29]  A. Parasuraman,et al.  Technology Readiness Index (Tri) , 2000 .

[30]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[31]  Ryan T. Wright,et al.  Operationalizing Multidimensional Constructs in Structural Equation Modeling: Recommendations for IS Research , 2012, Commun. Assoc. Inf. Syst..

[32]  A. Parasuraman,et al.  The effects of the dimensions of technology readiness on technology acceptance: An empirical analysis , 2008 .

[33]  E. Rogers.  Diffusion of Innovations , 1962 .

[34]  Mary Jo Bitner,et al.  The influence of technology anxiety on consumer use and experiences with self-service technologies , 2003 .

[35]  Ritu Agarwal,et al.  The Digital Transformation of Healthcare: Current Status and the Road Ahead , 2010 .

[36]  R. Hodge,et al.  Introducing telemedicine technology to rural physicians and settings. , 2001, The Journal of family practice.

[37]  B. Muthén,et al.  Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study , 2007 .

[38]  Eric W. Jamoom,et al.  Physicians in nonprimary care and small practices and those age 55 and older lag in adopting electronic health record systems. , 2012, Health affairs.

[39]  Viswanath Venkatesh,et al.  Explaining physicians' use of EMR systems and performance in the shakedown phase , 2011, J. Am. Medical Informatics Assoc..

[40]  I. Ajzen,et al.  Prediction of goal directed behaviour: Attitudes, intentions and perceived behavioural control , 1986 .

[41]  Lillian A. C. Burke,et al.  Information Technology for the Health Professions , 1999 .

[42]  B. Muthén,et al.  Multilevel Covariance Structure Analysis , 1994 .

[43]  Allard C. R. van Riel,et al.  Technology readiness and the evaluation and adoption of self-service technologies , 2006 .

[44]  Leonidas A. Zampetakis,et al.  Fostering corporate entrepreneurship through internal marketing , 2007 .

[45]  D. Blumenthal.  Stimulating the adoption of health information technology. , 2009, The West Virginia medical journal.

[46]  Vassilis Moustakis,et al.  Evaluating the properties of the Evidence-Based Practice Attitude Scale (EBPAS) in health care. , 2012, Psychological assessment.

[47]  Charles P. Friedman,et al.  Development and initial validation of an instrument to measure physicians' use of, knowledge about, and attitudes toward computers. , 1998, Journal of the American Medical Informatics Association : JAMIA.

[48]  A. Parasuraman,et al.  Serving customers and consumers effectively in the twenty-first century: A conceptual framework and overview , 2000 .

[49]  R. Bhagat.  Culture's Consequences: Comparing Values, Behaviors, Institutions, and Organizations Across Nations , 2002 .

[50]  B. Muthén,et al.  Exploratory Structural Equation Modeling , 2009 .

[51]  Kevin Celuch,et al.  Technology Readiness in the E-Insurance Industry: An Exploratory Investigation and Development of an Agent Technology E-Consumption Model , 2002 .

[52]  Albert H. Segars,et al.  Assessing the unidimensionality of measurement : a paradigm and illustration within the context of information systems research , 1997 .

[53]  Ananthanarayanan Parasuraman,et al.  Techno-Ready Marketing: How and Why Your Customers Adopt Technology (Маркетинг технологий: как и почему Ваши потребители принимают технологии) , 2001 .

[54]  Andrew Georgiou,et al.  Health informatics and evidence-based medicine - more than a marriage of convenience? , 2001 .

[55]  Viswanath Venkatesh,et al.  Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology , 2012, MIS Q..

[56]  Zhiping Walter,et al.  Physician acceptance of information technologies: Role of perceived threat to professional autonomy , 2008, Decis. Support Syst..

[57]  Vassilis Moustakis,et al.  Modeling the acceptance of clinical information systems among hospital medical staff: An extended TAM model , 2011, J. Biomed. Informatics.

[58]  Eta S Berner,et al.  Patterns of Use of Handheld Clinical Decision Support Tools in the Clinical Setting , 2007, Medical decision making : an international journal of the Society for Medical Decision Making.

[59]  Scott B. MacKenzie,et al.  Common method biases in behavioral research: a critical review of the literature and recommended remedies. , 2003, The Journal of applied psychology.