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

**Authors:** Chi-shan Tsai, HyunHae Lee, Warren Szewczyk, Julia K Palmer, Sophie Putnam, Sean A Munson, Jaimee L Heffner, Alexi Vasbinder, Amandalynne Paullada, Weichao Yuwen, Kerryn W Reding

PMC · DOI: 10.2196/86945 · JMIR Formative Research · 2026-03-06

## TL;DR

This study investigates what health science researchers want in an AI-based virtual study assistant and identifies eight key features and their importance.

## Contribution

The paper introduces a set of prioritized features for virtual study assistants based on direct input from health science researchers.

## Key findings

- Eight potential features for virtual study assistants were identified.
- Researchers provided insights into the relative priorities of these features.

## Abstract

This formative research explored health science researchers’ perspectives on the development of an artificial intelligence–based virtual study assistant and identified 8 potential features and their priorities.

## Full-text entities

- **Diseases:** GenAI (MESH:C538142)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC13005061/full.md

## References

5 references — full list in the complete paper: https://tomesphere.com/paper/PMC13005061/full.md

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Source: https://tomesphere.com/paper/PMC13005061