Designing Guiding Principles for NLP for Healthcare: A Case Study of Maternal Health

Overview

This repository contains the survey responses for our study on NLP for healthcare.

We include responses for three cohorts: birthing people (recruited via Prolific), healthcare workers (recruited via Prolific), and workshop participants (opted into a workshop on "maternal health equity").

All participants consented to participation in this research study and to having their responses recorded and shared publicly. Our study was approved by the IRB at the Allen Institute for AI.

Data Description

The data files include:

• survey_results_bp_PUBLIC.csv The responses from 30 birthing people.
• survey_results_hcw_PUBLIC.csv The responses from 30 healthcare workers.
• survey_results_wp_PUBLIC.csv The responses from 39 workshop participants.

Because the workshop participants interacted with one another during a live session and could potentially identify each other's responses, we omit their demographic information from this public repository.

More Information

For more information, you can read the full paper describing this study. This work is a public preprint and currently under review.

Designing Guiding Principles for NLP for Healthcare: A Case Study of Maternal Health
Maria Antoniak, Aakanksha Naik, Carla S. Alvarado, Lucy Lu Wang, Irene Y. Chen
2023

If you have questions about this data or research study, please contact Maria Antoniak.