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Comparing AI-Assisted Coding and Traditional Qualitative Analysis: a Study Examining Differences in Methods and Results of AI-Assisted Coding and Traditional Content Coding Using Community Engagement Data Collected During the Development of a Municipal Food Plan

Crossref DOI link: https://doi.org/10.1007/s11121-026-01904-4

Published Online: 2026-03-26

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Poulos, Natalie https://orcid.org/0000-0002-3543-0786
Price, Hannah

Bell, Lauren

Byrd-Williams, Courtney

Torres-Peralta, Sergio

Marty, Edwin
Funding

Funding for this research was provided by:

City of Austin, Master Interlocal Agreement (UTA19-000382)
License Information

Text and Data Mining valid from 2026-03-26

Version of Record valid from 2026-03-26
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Article History

Received: 12 March 2025

Accepted: 17 March 2026

First Online: 26 March 2026

Declarations

:

: This study was reviewed by The University of Texas at Austin Institutional Review Board and determined to not be human research, as all data was collected voluntarily and anonymously during public engagement for local government (STUDY00005681). Authors further certify that the study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

: Verbal consent was obtained prior to participation in community engagement.

: Dr. Natalie Poulos serves on the Austin & Travis County Food Policy Board in a volunteer position. Edwin Marty serves as the staff liaison to the Austin & Travis County Food Policy Board.

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