Table 1.

eHealth adoption models.

Theory	Dependent variable	Findings	Reference
TAMa, motivational model (MM), integrated model (IM)	eHealth behavioral intention	Users’ perceived ease of use (PEOU), users’ perceived technology usefulness (PU), intrinsic motivation (IM), and extrinsic motivation (MM) have a significant positive influence on behavioral Intention. IM does not have a better performance than TAM or MM when predicting behavioral Intention.	[30]
Elaboration likelihood model (ELM), concern for information privacy (CFIP)	EHRb behavioral intention	Positively framed arguments and issue involvement generate more favorable attitudes toward EHR behavioral intention. CFIP is negatively associated with likelihood of adoption.	[2]
TAM (qualitative study)	eHealth services behavioral Intention	PU seemed to be important. PEOU did not seem to be an issue. Although experience is not a TAM construct, it seemed to have influenced behavioral Intention.	[41]
TAM, plus several other constructs	Internet use behavior as a source of information	PU, importance given to written media in searches for health information, concern for personal health, importance given to the opinions of physicians and other health professionals, and the trust placed in the information available are the best predictors to use behavior.	[42]
Personal empowerment	Internet use behavior as a source of information	There are three types of attitudes encouraging Internet use to seek health information: professional, consumer, and community logic.	[16]
Extended TAM in health information technology (HIT)	HIT behavioral intention	PU, PEOU, and perceived threat significantly impacted health consumers’ behavioral intention.	[31]

^aTAM: technology acceptance model.

^bEHR: electronic health record.