JMIR Publications

ABSTRACT

Background:

The younger generation has experience utilizing Artificial Intelligence (AI) for learning and working as it progressively permeates society. AI-based medication counseling services may help people take medications more accurately and reduce adverse events. However, it is not known which AI-based medication counseling service will be preferred by young people.

Objective:

This study aims to assess young people's preferences for AI-based medication counseling services.

Methods:

A discrete choice experiment (DCE) approach was the main analysis method applied in this study, involving six attributes: granularity, linguistic comprehensibility, symptom-specific results, access platforms, content model, and costs. A mixed logit model was employed to evaluate participants' preferences for AI-based medication counseling services, the relative importance (RI) of attributes, and their willingness to pay (WTP).

Results:

340 participants were included in the analysis of this study, generating 8160 DCE observations. The results demonstrate that participants exhibited a strong preference for receiving 100% symptom-specific results (β=3.18, 95%CI 2.54-3.81, P<.001). Regarding content modes, video was significantly favored over text (β=0.86, 95%CI 0.51-1.22, P<.001). Participants also showed a clear preference for linguistic comprehensibility that was easy to understand compared to the difficult alternatives (β=0.81, 95%CI 0.46-1.16, P<.001). When considering the granularity, refined content was preferred over the general information (β=0.51 95%CI 0.21-0.8, P<.001). Finally, participants exhibited a notable preference for accessing information through WeChat applets rather than websites (β=0.66, 95%CI 0.27-1.05, P<.001). In terms of RI, symptom-specific results (RI=36.99%) and cost (RI=30.24%) occupied the largest portion. Participants' WTP for AI-based medication counseling services from high to low were 100% of the results for symptom-specific results, easy-to-understand language, video content mode, WeChat applet access platform, and refined medication counseling. In which the WTP of participants for 100% symptomatic was 24.01 CNY (95%CI 20.16-28.77) which occupies the highest value among all levels.

Conclusions:

This study conducted an in-depth investigation of the preference of young people for AI-based medication counseling services. Service providers should pay attention to the symptom-specific results, support more convenient access platforms, and optimize the language description, content models that add multiple digital media interactions, and more refined medication counseling to develop AI-based medication counseling services. Clinical Trial: Ethical approval for this study was obtained from Dongying People's Hospital, Approved No. of Ethics Committee: DYYX-2023-168