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.