# Technology Acceptance in Healthcare: A Systematic Review
## 2 Literature Review  
During the last three decades, various theoretical models and their extensions have been designed to understand the acceptance levels and individuals' behaviors toward different technologies in various disciplines [6]. These models introduced different factors to understand their effect on the user's acceptance of technology. Those theories include but are not limited to the theory of reasoned action (TRA) [12], the technology acceptance model (TAM) [13; 14; 15], extensions of TAM [16; 17], the unified theory of acceptance and use of technology (UTAUT) [18], social cognitive theory (SCT) [19; 20], the theory of interpersonal behavior (TIB) [21], the perceived characteristics of innovating theory [22], the theory of planned behavior (TPB) [23], the model of PC utilization [24], the motivational model [25], innovation diffusion theory (IDT) [26], and [PERSON]'s model [27]. Among the aforementioned theories and models, the UTAUT is known as the most relevant [28] and the most actively used model in technology acceptance studies in the healthcare domain [28; 29]. Apart from the healthcare domain, TAM is also recognized as the gold standard model across several technologies [30; 31; 32]. On the other hand, UTAUT has shown 20-30% better explanatory power than TAM, which means 40-50% of the explanatory power regarding the behavioral intention of end-users [18; 31]. Several reviews were conducted to analyze the technology acceptance models and their related constructs/factors in healthcare. It is impossible to ignore those reviews. As seen in Table 1, the review studies have mainly discussed one specific technology acceptance model except for two review studies [33; 34]. Besides, only one study focused on the classification of studies based on the examined technologies, participants, and country of implementation [6]. For instance, telehealth solutions were mainly studied from the perspective of older populations [35], with little attention paid to the developing countries. There is an increasing number of healthcare services, which has resulted from the increment of population ages [36; 37]. To make it distinct, this review provides a broader view for understanding healthcare technologies and identifies the potential gaps in technology acceptance in healthcare. It is beneficial to have a general review exploring multiple technology acceptance models instead of focusing on one acceptance model (e.g., TAM). Additionally, reviewing different information technologies instead of only one technology (e.g., electronic medical records) is essential to recognize a plethora or gap in the research. Therefore, this review study attempts to present a fresh overview of the literature of technology acceptance in the healthcare domain by classifying the collected studies based on the utilized technology acceptance models, the studied information technologies, participants, and countries of implementation. Additionally, this study aims to identify the prevailing acceptance models, the most utilized factors, and the most confirmed relationships to address the literature gaps and assist further research in building integrated models for technology acceptance in the healthcare domain. As an example for the included studies, [PERSON] [38] has studied the acceptance of electronic health records (EHRs) through a self-administered questionnaire filled by 1539 nurses from 15 hospitals in Jordan. The utilized research model was the original TAM. A multiple linear regression analysis was used to explore nurses' perceptions regarding the ease of use and usefulness of the solution. It was found that the intention to use is influenced by the perceived ease of use and perceived usefulness. The study was limited to nurses without including other medical staff, such as physicians, pharmacists, or laboratory staff. [PERSON] et al. [39] have explored 146 general practitioners' (GPs) intention to use the e-learning continuing medical education (e-CME).