JMIR Publications

ABSTRACT

Background:

Conversational agents(CAs) have been developed in outpatient departments to improve doctor-patient communication efficiency. As end users, patients’ continuance intention is essential for the sustainable development of the agents.

Objective:

The aim of this study was to identify key factors influencing patients’ continuance intention towards CAs and provide corresponding optimization strategies.

Methods:

This study proposed an extended expectation-confirmation model and empirically tested the model via a cross-sectional field survey at Shanghai eye and ENT hospital outpatient department. Structured interviews were conducted and analyzed through manual deductive coding to better understand the confirmation of patients’ initial expectations. Partial least squares structural equation modelling was applied to assess the model and hypotheses.

Results:

A total of 172 completed questionaries were received (100% response rate). The proposed model explained 75.5% of the variance of continuance intention. Satisfaction (β = .68; P<.001) and perceived usefulness (β = .221; P=.004) were both significant predictors of continuance intention. Patients' extent of confirmation significantly and positively affected both perceived usefulness (β = .817; P<.001) and satisfaction (β = .61; P<.001). Contrary to expectations, perceived ease of use had no significant impact on perceived usefulness (β = .048; P=.367), satisfaction (β =- .004; P=.633) and continuance intention (β = .026; P=.91).74 of 172 patients participated in the structured interviews. The answers were categorized into three aspects, personalized interaction (mentioned 50 times), effective utilization (mentioned 37 times) and publicity on benefits (mentioned 5 times).

Conclusions:

Implementing CA systems is not once and for all. By identifying key factors influencing patients’ continuance intention, this study provides a feedback channel for the administrators to gain insight into patients’ experience and thoughts. To maintain patients’ continuance intention and promote the sustainable development of CAs, efforts should be made towards maximizing patients’ satisfaction and perceived usefulness. Feasible measures include understanding patients’ expectations after their actual use and optimizing CA systems accordingly.