Table 1.

Theoretical acceptance and adoption models.

Model	Developer	Year	Theoretical basis	Central constructs	Points of critique	Extended models
TAMa	Davis [9,11,12]	1985	Cognitive psychology [13]	Describes elements to predict the degree to which a person plans to perform specific future behavior. It suggests that perceived usefulness, perceived ease of use, and attitude (ie, intention to use) can explain user motivation [12]. It is a way to predict the intended use of a technology.	Mainly conceptualized for the acceptance of individuals and is not useful for explaining acceptance of electronic health (eHealth) technologies by organizations [11,14].	TAM2 (by Venkatesh and Davis) and TAM3 (by Venkatesh and Bala) [9,12]
DOIb	Rogers [9]	1995	Diffusion research [18]	Explains the characteristics of innovation. Observability, trialability, complexity, relative advantage, and compatibility are the primary determinants of innovation diffusion, which help explain the different rates of adoption [9,15]. Diffusion starts with recognizing the user’s need. It spreads by knowledge acquisition, persuasion, decision (ie, adopt or reject), implementation (ie, routine use, reinvention, and conformation), promotion, and evaluation [15].	There is little focus on the organizational context [14,16,17].	The unifying theoretical model of Greenhalgh et al [16] and the Consolidated Framework for Implementation Research (CFIR) of Damschroder et al [17,18]
UTAUTc	Venkatesh et al [9,19]	2003	Cognitive psychology [13]	Builds on TAM and focuses on perceptions and assumptions of people, resulting in the intention to use technology. States that constructs like performance expectancy, effort expectancy, social influence, and facilitating conditions influence intention and ultimately behavior [19]. These four constructs are moderated by gender, age, experience, and voluntariness of use [19].	Does not deal with hindrances to actual use [13]. Excludes users’ cognitive, affective, and physical ability to use technology [20] and ignores technological factors that might influence the decision to use an application [20].	UTAUT2 by Venkatesh et al developed in 2012 [9]
NASSSd framework	Greenhalgh et al [21,22]	2017	Complexity theory [21,22]	Points to aspects explaining the complexity of technological innovations in health care, which according to all the described models influence the adoption. Includes the value proposition (ie, supply-side and demand-side values) as an important factor, in contrast to many implementation theories that do not [14,21].	Not found yet	Not found yet

^aTAM: Technology Acceptance Model.

^bDOI: diffusion of innovations.

^cUTAUT: Unified Theory of Acceptance and Use of Technology.

^dNASSS: nonadoption, abandonment, scale-up, spread, and sustainability.