TECHNOLOGY ACCEPTANCE MODELS IN E-HEALTH
In the health care sector, new technologies are widely adopted [5],
among which modern ICT has been understood to improve the quality of
health care services. TAM is the common model used to understand
technology adoption by clinical staff and patients, and it has been
extended and applied to the development and implementation of health
information systems [43]. TAM is concluded to be one of the most
useful models for studying patients’ perceptions and behaviours towards
e-health [2], it’s used to identify the factors influencing the
adoption of information technologies in the e-health system [20].
However, in terms of the number of studies for each user group, doctors
and nurses are the two main research targets (32% and 25%), and
patients represent only 13% of studies [43].
In the context of e-health, some scholars have expressed concern that
TAM may not capture the unique contextual features of e-health, as TAM
is not a model developed specifically in or for the healthcare context
[22]. The original TAM only considers two variables in determining
behavioural intention [12], the basic constructs of TAM may not
fully account for the context of e-health use [38], so it’s
necessary to extend and incorporate TAM with other constructs to improve
its explanation and prediction of adoption behaviour [22]. To
understand how e-health characteristics influence user satisfaction, a
consistent set of beliefs and attitudes should be measured and
appropriate mediating factors related to the behavioural beliefs and
attitudes specified in TAM should be examined [53]. Lai et al
[33] developed a new framework based on the modified TAM2 to
investigate the acceptability of the Tailored Interventions for the
management of Depressive Symptoms (TIDES) programme. Liu et al [37]
focus on the acceptability of a web-based personal health record system
and integrate the construct of the physician-patient relationship (PPR)
into the TAM. Despite the extensions, perceived usefulness and perceived
ease of use of TAM were the two most influential factors in e-health
adoption [19].
Adoption of e-health in Bangladesh shows that perceived ease of use is
critical to e-health adoption [24]. A study of the acceptance of
diabetes monitoring technology also found that perceived ease of use was
a significant factor in technology acceptance [6]. Adoption of
health applications in developing countries concluded that perceived
usefulness significantly influenced an individual’s acceptance and use
of the technology [18].
Reviewing the theoretical background on e-health and TAM, scholars
propose new constructs according to the specific context, thus different
extended TAM models have been applied to explore the acceptance of
e-health.