Table of Contents Author Guidelines Submit a Manuscript
Journal of Healthcare Engineering
Volume 6, Issue 3, Pages 399-418
http://dx.doi.org/10.1260/2040-2295.6.3.399
Research Article

Examining the Factors Affecting PDA Acceptance among Physicians: An Extended Technology Acceptance Model

Ecem Basak, Cigdem Altin Gumussoy, and Fethi Calisir

Industrial Engineering Department, Management Faculty, Istanbul Technical University, 34367, Istanbul, Turkey

Received 1 October 2014; Accepted 1 May 2015

Copyright © 2015 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. A. E. Carroll and D. A. Christakis, “Pediatricians and personal digital assistants: What type are they using?” in Conf Proc AMIA Symposium, pp. 130–134, 2003.
  2. M. J. Tooey and A. Mayo, “Handheld technologies in a clinical setting: state of the technology and resources,” AACN Clin. Issues, vol. 14, no. 3, p. 342, 2003. View at Google Scholar
  3. R. Guerrieri and M. Kokinova, “Does instruction in the use of personal digital assistants increase medical students’comfort and skill level?” Medical Reference Services Quarterly, vol. 28, no. 1, pp. 33–43, 2009. View at Google Scholar
  4. R. Luanrattana, K. T. Win, J. Fulcher, and D. Iverson, “Mobile technology use in medical education,” Journal of Medical Systems, vol. 36, no. 1, pp. 113–122, 2012. View at Google Scholar
  5. D. C. Malone and K. R. Saverno, “Evaluation of a wireless handheld medication management device in the prevention of drug-drug interactions in a medicaid population,” Journal of Managed Care Pharmacy, vol. 18, no. 1, pp. 33–45, 2012. View at Google Scholar
  6. R. Kitchiner, “The role of the personal digital assistant (PDA) in chiropractic practice,” Clinical Chiropractic, vol. 9, no. 3, pp. 119–128, 2006. View at Google Scholar
  7. J. Phua and T. K. Lim, “How residents and interns utilise and perceive the personal digital assistant and UpToDate,” BMC Medical Education, vol. 8, no. 39, 2008. View at Google Scholar
  8. P. Johansson, G. Petersson, and G. Nilsson, “Experience of using a personal digital assistant in nursing practice - a single case study,” Journal of Nursing Management, vol. 19, no. 7, pp. 855–862, 2011. View at Google Scholar
  9. B. S. Davies, J. Rafique, T. R. Vincent et al., “Mobile Medical Education (MoMEd) - How mobile information resources contribute to learning for undergraduate clinical students - a mixed methods study,” BMC Medical Education, vol. 12, no. 1, pp. 1–11, 2012. View at Google Scholar
  10. J.-H. Wu, S.-C. Wang, and L.-M. Lin, “Mobile computing acceptance factors in the healthcare industry: a structural equation model,” International Journal of Medical Informatics, vol. 76, no. 1, pp. 66–77, 2007. View at Google Scholar
  11. C. E. Kuziemsky, F. Laul, and R. C. Leung, “A Review on Diffusion of Personal Digital Assistants in Healthcare,” Journal of Medical Systems, vol. 29, no. 4, pp. 335–342, 2005. View at Google Scholar
  12. V. Venkatesh, M. G. Morris, F. D. Davis, and G. B. Davis, “User acceptance of information tehcnology: Toward a unified view,” MIS Quarterly, vol. 27, no. 3, pp. 425–478, 2003. View at Google Scholar
  13. I. Ajzen and M. Fishbein, Understanding attitudes and predicting social behavior, Prentice-Hall, Englewood Cliffs, NJ, 1980.
  14. F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, “User acceptance of computer technology?: A comparison of two theoretical models,” Management Science, vol. 35, no. 8, pp. 982–1003, 1989. View at Google Scholar
  15. R. Agarwal and J. Prasad, “Are individual differences germane to the acceptance of new information technologies?” Decision Sciences, vol. 30, no. 2, 1999. View at Google Scholar
  16. F. D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Quarterly, vol. 13, no. 3, pp. 319–340, 1989. View at Google Scholar
  17. P. Legris, J. Ingham, and P. Collerette, “Why do people use information technology? A critical review of the technology acceptance model,” Information & Management, vol. 40, no. 3, pp. 191–204, 2003. View at Google Scholar
  18. J.-H. Wu and S.-C. Wang, “What drives mobile commerce?” Information & Management, vol. 42, no. 5, pp. 719–729, 2005. View at Google Scholar
  19. M. A. Morrisey, Healthcare. 2008. Library of Economics and Liberty. Retrieved April 17, 2015 from the World Wide Web http://www.econlib.org/library/Enc/HealthCare.html.
  20. A. Dasgupta, S. S. Sansgiry, J. T. Sherer, D. Wallace, and S. Sikri, “Application of the extended technology acceptance model in predicting pharmacists’ intention to use personal digital assistants,” Journal of the American Pharmacists Association, vol. 49, no. 6, pp. 792–796, 2009. View at Google Scholar
  21. B. I. Fox, Explaining pharmacists’intention to use personal digital assistants as clinical resources during patient care interventions [Ph.D. thesis], Aurburn University, 2005.
  22. R. Kuiper, “Metacognitive factors that impact student nurse use of point of care technology in clinical settings,” International Journal of Nursing Education Scholarship, vol. 7, no. 1, 2010. View at Google Scholar
  23. M. V. Siracuse and J. G. Sowell, “Doctor of pharmacy students' use of personal digital assistants,” American Journal of Pharmaceutical Education, vol. 72, no. 1, p. 7, 2008. View at Google Scholar
  24. M. Y. Yi, J. D. Jackson, J. S. Park, and J. C. Probst, “Understanding information technology acceptance by individual professionals: Toward an integrative view,” Information & Management, vol. 43, no. 3, pp. 350–363, 2006. View at Google Scholar
  25. V. Venkatesh, “Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model,” Information Systems Research, vol. 1997, no. 4, pp. 342–365, 2000. View at Google Scholar
  26. V. Venkatesh and F. Davis, “A theoretical extension of the technology acceptance model: Four longitudinal field studies,” Management Science, vol. 46, no. 2, pp. 186–204, 2000. View at Google Scholar
  27. J. Moon and Y. Kim, “Extending the TAM for a World-Wide-Web context,” Information & Management, vol. 38, no. 4, pp. 217–230, 2001. View at Google Scholar
  28. H. Van der Heijden, “Factors influencing the usage of websites: the case of a generic portal in The Netherlands,” Information & Management, vol. 40, no. 6, pp. 541–549, 2003. View at Google Scholar
  29. A. Joseph, Comparing the usability of Apple and Plam handheld computing devices among physicians: A randomized crossover study [M.S. thesis], Duke University, 2009.
  30. A. Vishwanath, L. Brodsky, and S. Shaha, “Physician adoption of personal digital assistants (PDA): testing its determinants within a structural equation model,” Journal of Health Communication, vol. 14, no. 1, pp. 77–95, 2009. View at Google Scholar
  31. I. Ajzen, “The theory of planned behavior,” Organizational Behavior and Human Decision Processes, vol. 50, no. 2, pp. 179–211, 1991. View at Google Scholar
  32. K. Mathieson, “Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior,” Information Systems Research, vol. 2, no. 3, pp. 173–191, 1991. View at Google Scholar
  33. I. Ajzen and T. J. Madden, “Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control,” Journal of Experimental Social Psychology, vol. 22, no. 5, pp. 453–474, 1986. View at Google Scholar
  34. S. J. Barnes and R. Vidgen, “User acceptance and corporate intranet quality: An evaluation with iQual,” Information & Management, vol. 49, no. 3-4, pp. 164–170, 2012. View at Google Scholar
  35. R. Cheung and D. Vogel, “Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning,” Computer & Education, vol. 63, pp. 160–175, 2013. View at Google Scholar
  36. H. Motaghian, A. Hassanzadeh, and D. K. Moghadam, “Factors affecting university instructors’ adoption of web-based learning systems: Case study of Iran,” Computer & Education, vol. 61, pp. 158–167, 2013. View at Google Scholar
  37. J. C. Dale and J. LeFlore, “Personal digital assistants: making the most use of them in clinical practice,” Journal of Pediatric Healthcare, vol. 21, no. 5, pp. 339–342, 2007. View at Google Scholar
  38. T. Adigüzel, R. M. Capraro, and V. L. Willson, “An examination of handheld computers,” International Journal of Special Education, vol. 26, no. 3, pp. 12–27, 2011. View at Google Scholar
  39. I.-L Wu, J.-Y. Li, and C.-Y. Fu, “The adoption of mobile healthcare by hospital’s professionals: An integrative perspective,” Decision Support Systems, vol. 51, no. 3, pp. 587–596, 2011. View at Google Scholar
  40. M. T. Braun, “Obstacles to social networking website use among older adults,” Computers in Human Behavior, vol. 29, no. 3, pp. 673–680, 2013. View at Google Scholar
  41. F. De grove, J. Bourgonjon, and J. Van Looy, “Digital games in the classroom? A contextual approach to teachers’adoption intention of digital games in formal education,” Computers in Human Behavior, vol. 28, no. 6, pp. 2023–2033, 2012. View at Google Scholar
  42. F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, “Extrinsic and intrinsic motivation to use computers in the workplace,” Journal of Applied Social Psychology, vol. 22, no. 14, pp. 1111–1132, 1992. View at Google Scholar
  43. M. K. O. Lee, C. M. K. Cheung, and Z. Chen, “Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation,” Information & Management, vol. 42, no. 8, pp. 1095–1104, 2005. View at Google Scholar
  44. L. Zhang, J. Zhu, and Q. Liu, “A meta-analysis of mobile commerce adoption and the moderating effect of culture,” Computers in Human Behavior, vol. 28, no. 5, pp. 1902–1911, 2012. View at Google Scholar
  45. T. Domina, S. E. Lee, and M. MacGillivray, “Understanding factors affecting consumer intention to shop in a virtual world,” Journal of Retailing and Consumer Services, vol. 19, no. 6, pp. 613–620, 2012. View at Google Scholar
  46. M. Mäntymäki and J. Salo, “Teenagers in social virtual worlds: Continuous use and purchasing behavior in Habbo Hotel,” Computers in Human Behavior, vol. 27, no. 6, pp. 2088–2097, 2011. View at Google Scholar
  47. F. D. Davis, “User acceptance of information technology: system characteristics, user perceptions and behavioral impacts,” International Journal of Man-Machine Studies, vol. 38, no. 3, pp. 475–478, 1993. View at Google Scholar
  48. G. Hackbarth, V. Grover, and M. Y. Yi, “Computer playfulness and anxiety: positive and negative mediators of the system experience effect on perceived ease of use,” Information & Management, vol. 40, no. 3, pp. 221–232, 2003. View at Google Scholar
  49. G. C. Bruner and A. Kumar, “Explaining consumer acceptance of handheld Internet devices,” Journal of Business Research, vol. 58, no. 5, pp. 553–558, 2005. View at Google Scholar
  50. I. Ha, Y. Yoon, and M. Choi, “Determinants of adoption of mobile games under mobile broadband wireless access environment,” Information & Management, vol. 44, no. 3, pp. 276–286, 2007. View at Google Scholar
  51. T. Bhatti, “Exploring factors influencing the adoption of mobile commerce,” Journal of Internet Banking and Commerce, vol. 12, no. 3, 2007. View at Google Scholar
  52. H. Kim, T. Kim, and S. W. Shin, “Modeling roles of subjective norms and e-trust in customers' acceptance of airline B2C e-vommerce websites,” Tourism Management, vol. 30, no. 2, pp. 266–277, 2009. View at Google Scholar
  53. D. M. Lambert and T. C. Harrington, “Measuring nonresponse bias in customer service mail surveys,” Journal of Business Logistics, vol. 11, no. 2, pp. 5–25, 1990. View at Google Scholar
  54. E. Rogers, Diffusion of innovations, Free Press, New York, 4th edition, 1995.
  55. R. Agarwal and J. Prasad, “The antecedents and consequents of user perceptions in information technology adoption,” Decision Support Systems, vol. 22, no. 1, pp. 15–29, 1998. View at Google Scholar
  56. J. Lu, J. E. Yao, and C.-S. Yu, “Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology,” The Journal of Strategic Information Systems, vol. 14, no. 3, pp. 245–268, 2005. View at Google Scholar
  57. W. Lewis, R. Agarwal, and V. Sambamurthy, “Sources of influence on beliefs about information technology use: An empiric study,” MIS Quarterly, vol. 27, no. 4, pp. 657–678, 2003. View at Google Scholar
  58. A. Bandura and D. C. McClelland, “Social learning theory,” Prentice Hall, pp. 305–316, 1977. View at Google Scholar
  59. A. Bandura, Social foundations of thought and action: a social cognitive theory, Prentice-Hall, Englewood Cliffs, New Jersey, 1986.
  60. D. R. Compeau and C. A. Higgins, “Computer self-efficacy: Development of a measure and initial test,” MIS Quarterly, vol. 19, no. 2, p. 189, 1995. View at Google Scholar
  61. V. Venkatesh and F. D. Davis, “A model of the antecedents of perceived ease of use: Development and test,” Decision Sciences, vol. 27, no. 3, pp. 451–481, 1996. View at Google Scholar
  62. R. Agarwal, V. Sambamurthy, and R. M. Stair, “Research report?: The evolving relationship between general and specific computer self-efficacy - An emprical assesment,” Information Systems Research, vol. 11, no. 4, pp. 418–430, 2000. View at Google Scholar
  63. R. Thompson, D. Compeau, and W. Ontario, “Intentions to use information technologies?: An Integrative Model,” Journal of Organizational and End User Computing, vol. 18, no. 3, p. 22, 2006. View at Google Scholar
  64. J.-C. Gu, S.-C. Lee, and Y.-H. Suh, “Determinants of behavioral intention to mobile banking,” Expert Systems with Applications, vol. 36, no. 9, pp. 11605–11616, 2009. View at Google Scholar
  65. S. Taylor and P. Todd, “Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions,” International Journal of Research in Marketing, vol. 12, no. 2, pp. 137–155, 1995. View at Google Scholar
  66. J. S. Armstrong and T. S. Overton, “Estimating nonresponse bias in mail surveys,” Journal of Marketing Research, vol. 14, no. 3, pp. 396–402, 1977. View at Google Scholar
  67. J. C. Anderson and D. W. Gerbing, “Structural equation modeling in practice: A review and recommended twostep approach,” Psychological Bulletin, vol. 103, no. 3, pp. 411–423, 1988. View at Google Scholar
  68. K. Jöreskog and D. Sörbom, LISREL software, v8. 80, Scientific Software International, Chicago, 2006.
  69. J. F. Hair, R. E. Anderson, R. L. Tatham, and W. C. Black, Multivariate data analysis, Prentice Hall, Englewood cliffs, New Jersey, 5th edition, 1998.
  70. R. P. Bagozzi, Y. Yi, and L. W. Phillips, “Assessing construct validity in organizational research,” Administrative Science Quarterly, vol. 36, no. 3, p. 421, 1991. View at Google Scholar
  71. C. Fornell and D. Larcker, “Evaluating structural equation models with unobservable variables and measurement error,” Journal of Marketing Research, vol. 18, no. 1, pp. 39–50, 1981. View at Google Scholar
  72. L. Chen, M. L. Gillenson, and D. L. Sherrell, “Consumer acceptance of virtual stores: A theoretical model and critical success factors for virtual stores,” ACM SIGMIS Database, vol. 35, no. 2, 2004. View at Google Scholar
  73. A. Diamantopoulos and J. A. Siguaw, Introducing LISREL: A guide for the uninitiated, SAGE Publications, 2000.
  74. J. C. Roca, C.-M. Chiu, and F. J. Martínez, “Understanding e-learning continuance intention: An extension of the technology acceptance model,” International Journal of Human-Computer Studies, vol. 64, no. 8, pp. 683–696, 2006. View at Google Scholar
  75. J. Chen, Y. Park, and G. Putzer, “An examination of the components that increase acceptance of smartphones among healthcare professionals,” Electronic Journal of Health Informatics, vol. 5, no. 2, pp. 1–12, 2010. View at Google Scholar
  76. J. C. Roca and M. Gagné, “Understanding e-learning continuance intention in the workplace: A self-determination theory perspective,” Computers in Human Behavior, vol. 24, no. 4, pp. 1585–1604, 2008. View at Google Scholar
  77. H. Son, Y. Park, C. Kim, and J.-S. Chou, “Toward an understanding of construction professionals’ acceptance of mobile computing devices in South Korea: An extension of the technology acceptance model,” Automation in Construction, vol. 28, pp. 82–90, 2012. View at Google Scholar
  78. A. U. Jan and V. Contreras, “Technology acceptance model for the use of information technology in universities,” Computers in Human Behavior, vol. 27, no. 2, pp. 845–851, 2011. View at Google Scholar