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Exploring Feature Priorities and User Needs in Developing Virtual Study Assistants.

Chi-Shan Tsai¹, HyunHae Lee¹, Warren Szewczyk¹

¹School of Nursing, University of Washington, Seattle, WA, United States.

JMIR Formative Research

|March 6, 2026

Summary

This summary is machine-generated.

This research explored health science researchers' views on an AI virtual study assistant. Eight features were identified and prioritized to aid study development.

Keywords:

generative artificial intelligence user need user preference user-centered design virtual study assistant

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Area of Science:

Health Informatics
Artificial Intelligence in Healthcare
Research Methodology

Background:

The integration of artificial intelligence (AI) into healthcare research tools is rapidly evolving.
Virtual study assistants offer potential to streamline research processes.
Understanding researcher needs is crucial for effective tool development.

Purpose of the Study:

To explore health science researchers' perspectives on developing an AI-based virtual study assistant.
To identify and prioritize potential features for such an assistant.

Main Methods:

Formative research methodology was employed.
Qualitative data were collected from health science researchers.
Analysis focused on identifying key requirements and feature preferences.

Main Results:

Researchers expressed interest in an AI virtual study assistant.
Eight potential features were identified, with varying priority levels.
Key desired functionalities included data management and analysis support.

Conclusions:

The development of an AI virtual study assistant is supported by health science researchers.
Prioritized features can guide the design and implementation of effective tools.
Future AI tools should focus on enhancing research efficiency and data handling.