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

Basak, Ecem; Gumussoy, Cigdem Altin; Calisir, Fethi

doi:https://doi.org/10.1260/2040-2295.6.3.399

Journal of Healthcare Engineering

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Research Article | Open Access

Volume 6 | Article ID 582071 | https://doi.org/10.1260/2040-2295.6.3.399

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

Ecem Basak,¹Cigdem Altin Gumussoy,¹and Fethi Calisir¹

Received01 Oct 2014

Accepted01 May 2015

Abstract

This study aims at identifying the factors affecting the intention to use personal digital assistant (PDA) technology among physicians in Turkey using an extended Technology Acceptance Model (TAM). A structural equation-modeling approach was used to identify the variables that significantly affect the intention to use PDA technology. The data were collected from 339 physicians in Turkey. Results indicated that 71% of the physicians’ intention to use PDA technology is explained by perceived usefulness and perceived ease of use. On comparing both, the perceived ease of use has the strongest effect, whereas the effect of perceived enjoyment on behavioral intention to use is found to be insignificant. This study concludes with the recommendations for managers and possible future research.

References

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.
View at: Google Scholar
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
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
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
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
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
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
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
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
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
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
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
I. Ajzen and M. Fishbein, Understanding attitudes and predicting social behavior, Prentice-Hall, Englewood Cliffs, NJ, 1980.
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
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
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
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
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
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.
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
B. I. Fox, Explaining pharmacists’intention to use personal digital assistants as clinical resources during patient care interventions [Ph.D. thesis], Aurburn University, 2005.
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
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
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
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
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
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
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
A. Joseph, Comparing the usability of Apple and Plam handheld computing devices among physicians: A randomized crossover study [M.S. thesis], Duke University, 2009.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
E. Rogers, Diffusion of innovations, Free Press, New York, 4th edition, 1995.
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
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
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
A. Bandura and D. C. McClelland, “Social learning theory,” Prentice Hall, pp. 305–316, 1977.
View at: Google Scholar
A. Bandura, Social foundations of thought and action: a social cognitive theory, Prentice-Hall, Englewood Cliffs, New Jersey, 1986.
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
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
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
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
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
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
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
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
K. Jöreskog and D. Sörbom, LISREL software, v8. 80, Scientific Software International, Chicago, 2006.
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.
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
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
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
A. Diamantopoulos and J. A. Siguaw, Introducing LISREL: A guide for the uninitiated, SAGE Publications, 2000.
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
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
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
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
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

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