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Artificial Intelligence (4968) Development and Evaluation of Research Methods, Instruments and Tools (1405) Chatbots and Conversational Agents (1225) Research Methodology - AI (202) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (175)

Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/94809, first published .
Nurse addresses seated audience in outdoor clinic setting with facial recognition overlay.

Efficiency vs Depth in AI-Generated and Human-Synthesized Thematic Analyses of Ugandan Women’s Experiences of Obstetric Fistula: Comparative Qualitative Study

Efficiency vs Depth in AI-Generated and Human-Synthesized Thematic Analyses of Ugandan Women’s Experiences of Obstetric Fistula: Comparative Qualitative Study

Authors of this article:

Madeline Pechilis1 Author Orcid Image ;   Monica Getahun1 Author Orcid Image ;   Hadija Nalubwama2 Author Orcid Image ;   Patrick Eyul3 Author Orcid Image ;   Florence Ebem4 Author Orcid Image ;   Alison M El Ayadi5 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Madeline Pechilis   1 , MSc ;   Monica Getahun   1 , MPH ;   Hadija Nalubwama   2 , MPH ;   Patrick Eyul   3 , MSc ;   Florence Ebem   4 , BSc ;   Alison M El Ayadi   5 , SCD

1 Institute for Global Health Sciences, University of California, San Francisco, San Francisco, CA, United States

2 Department of Obstetrics and Gynecology, College of Health Sciences, Makerere University, Kampala, Central Region, Uganda

3 Infectious Diseases Research Collaboration, Kampala, Central Region, Uganda

4 School of Medicine, University of California, San Francisco, San Francisco, CA, United States

5 Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, San Francisco, CA, United States

Corresponding Author:

  • Alison M El Ayadi, SCD
  • Department of Obstetrics, Gynecology and Reproductive Sciences
  • University of California, San Francisco
  • 550 16th Street
  • San Francisco, CA 94158
  • United States
  • Phone: 1 415 476 5877
  • Email: alison.elayadi@ucsf.edu