Exploring Feature Priorities and User Needs in Developing Virtual Study Assistants

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.