Searching for New Model of Digital Informatics for Human–Computer Interaction: Testing the Institution-Based Technology Acceptance Model (ITAM)

Abstract

The fourth industrial revolution has produced new information technology (IT) that is widely used in the healthcare industry. Although the nature of the institution affects IT adoption, the Technology Acceptance Model (TAM), a dominant theory, has dismissed its role and influence. Our research investigates how institutions influence the adoption of new IT by using the Institution-based Technology Acceptance Model (ITAM). We conducted an empirical test by using survey data collected from 300 employees in the public sector. Structural equation modeling was applied to test the proposed hypotheses. The results showed the total effect of institutions on the intention to use new IT is positive and significant. Second, IT adoption is not only affected by external institutions but also by type of institution; the external institution takes a greater role in inducing perceived usefulness, perceived ease of use, and intention to use than does the internal. Third, perceived ease of use and perceived usefulness play mediating roles between institution and IT adoption. Fourth, an alternative expanded model to which more individual and organizational factors were added confirmed the results of the base model. We concluded that institutions have a strong impact on the level of intention for IT use through perceived ease of use and perceived usefulness.

Integrative adoption model for personal health records: A structural equation modeling approach

“…This suggests that it is important for people to perceive positive results during their use of the system in order to communicate to others about the benefits or outcomes of PHR system use. This significant relationship complies with prior studies in complex health-related systems (Brunner et al, 2018;Kang et al, 2021;Okediran et al, 2020). That is, it confirms that when people are able to explain the benefits of using innovation to others, a PHR system is more likely to be adopted.…”

Key drivers involved in the telemonitoring of covid-19 for self-health management: an exploratory factor analysis

“…Perception of technological risk prevents patients from using digital health platforms. For this reason, according to studies investigating the facilitated conditions to use of digital platforms in the healthcare industry [ 28 ], individual's control belief regarding the availability of resources and support structures to facilitate system use can affect the technology acceptance and the use of e-service positively [ 60 , 61 ]. As a result, reduced cognitive effort and perceived risk levels should add to the IT system's instrumental benefits, such as increased performance [ 59 ].…”

“…[ 20 ] “Satisfaction is defined as a global evaluation or feeling state” [ 21 :256] Cooperation—The higher the level of satisfaction the more the patient will follow the treatment and cooperate with the doctors and health workers [ 22 , 23 ] Perceived benefit “Perceived benefit refers to the perceived likelihood that taking a recommended course of action will lead to a positive outcome, such as reduced risk or reduced worry” [ 24 :36] “Benefits refer to the expected or experienced positive consequences of [a given behavior]” [ 25 :50] “Perceived benefits construct is […] defined as an individual’s belief that specific positive outcomes will result from a specific behavior” [ 26 :88] Intention to use—The benefits perceived by the patient are inversely proportional to the difficulty perceived in the use of the technology [ 27 ]. The expected benefits have an effect on the intention to use the digital health platform [ 28 ] Perceived Technological Risk “(…) is commonly thought of as felt uncertainty regarding possible negative consequences of using a product or service” [ 29 :453] “(…) the potential for loss in the pursuit of a desired outcome of using an e-service” [ 29 :454] Reliability of health services—The level of security of the patient’s clinical data and their correct storage on the web increases the level of reliability of the health services provided through the digital health platform [ 30 ] Effort Expectancy “(…) is defined as the degree of ease associated with the use of the system” [ 31 :509] Intention to use—The patient’s effort expectancy affects the intention to use a digital health service [ 28 ] Perceived Usefulness “The prospective user’s subjective probability that using a specific application system will increase his or her job performance within an organizational context’’ [ 32 :985] “(…) the degree to which a person believes that using a particular system would enhance his or her job performance” [ 33 :320] Positive attitude of patients—The perception of usefulness of digital health services favorably predisposes the patients and facilitates the doctor’s decision-making process (medical decision making) [ 34 ] Perceived Ease ...…”

“…Therefore the achievable benefits in terms of performance are negatively offset by the effort made to use it. Many studies have shown that effort expectancy affects the intention to adopt a new technology [ 28 , 46 – 48 ] even if this is more noticeable in the early stages of its use [ 31 ] and dependent on the personal experience of the individual [ 44 ].…”

Evaluation of Student Satisfaction with Ubiquitous-Based Tests in Women’s Health Nursing Course

“…Although research on CBT is increasing, there are limitations in comparison and analysis because research on UBT is limited. According to the technology acceptance model, which is widely used for adaptive decision making on the Internet and in information technology fields, if perceived usefulness and perceived ease of use are high, the technology can be used easily [ 30 , 31 , 32 , 33 ]. Perceived usefulness refers to the belief that a new technology improves performance, while perceived ease of use refers to the degree to which a technology can be easily used.…”