PDA usage in healthcare professionals: testing an extended technology acceptance model
Abstract
Personal Digital Assistants (PDAs) have attracted extensive attention in healthcare organisations because of their potential contribution to enhancing healthcare practice. Successful implantation of PDA is, to a large extent, confined by PDA acceptance by healthcare professionals. This study proposes an extended technology acceptance model (TAM) to predict actual PDA usage. The results support all the hypotheses. Consistent with prior research, perceived usefulness and perceived ease of use are dominant determinants of usage. Personal innovativeness was found to affect usage directly and indirectly through perceived ease of use. Perceived usefulness mediates the effects of job relevance, compatibility, and perceived ease of use on usage. Support also affects usage through perceived ease of use. Overall our proposed model can explain 61.6% of the variance in the healthcare professionals' PDA usage. Implications for IT management in healthcare organisations are discussed.
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Five reviewed studies collected data from a mix of physicians, nurses, pharmacists, and medical technicians.
“Five studies collected data from a mix of physicians, nurses, pharmacists, and medical technicians [106-110].”
From The Technology Acceptance Model: Its past and its future in health care (2010) · cites this paper as [106]
Variables related to compatibility between health IT and clinical work processes were commonly added in the reviewed studies.
“For example, the common addition of variables related to compatibility between the health IT and clinical work processes in the reviewed studies [48, 49, 98, 103, 105, 106, 109] is in line with growing interest in the concept of “fit” as a critical need for successful IT design [131, 132], especially in health care [21, 28, 57, 62, 72, 100, 133-135].”
From The Technology Acceptance Model: Its past and its future in health care (2010) · cites this paper as [106]
Some reviewed studies aggregated data across professions, making comparisons possible but not carried out.
“Although individual or profession-specific differences may not have been possible to study in homogeneous samples, such as those comprised of only young physicians [99, 109], all-females [103], or all-males [96], there were studies in which comparisons were possible but not carried out, such as the study aggregating data from physicians, nurses, and information systems department staff [110], one”
From The Technology Acceptance Model: Its past and its future in health care (2010) · cites this paper as [106]
Some reviewed studies incorporated health care-specific measures of usefulness, such as increased quality of care.
“Thus, some studies incorporate measures of increased quality of care [97, 106] and similar health care-specific measures of usefulness [32, 104].”
From The Technology Acceptance Model: Its past and its future in health care (2010) · cites this paper as [106]
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References 30 · Cited by 98
- Authors
- Liang, H., Xue, Y., & Byrd, T. A.
- Affiliations
- Florida Atlantic University (US)
- Auburn University (US)
- Venue
- International Journal of Mobile Communications
- Publisher
- Inderscience Publishers
- Published
- 2003
- Volume
- 1
- Issue
- 4
- Pages
- 372
- ISSN
- 1470-949X (ISSN-L)
- 1741-5217
- OpenAlex
- W1975069357
- Cited by
- 98
- References
- 30
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2023: 5 · 2022: 3 · 2020: 7 · 2019: 9 · 2018: 2 · 2017: 3 · 2016: 6 · 2015: 10 · 2014: 6 · 2013: 5 · 2012: 5
- FWCI
- 9.17
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Mobile Communications (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- personal digital assistants, technology acceptance model, healthcare workers, perceived usefulness, perceived ease of use, personal innovativeness, job relevance, compatibility, support, technology adoption
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