Abstract
The rapid advancements in generative artificial intelligence have opened new avenues for enhancing various aspects of research, including the design and evaluation of survey questionnaires. However, the recent pioneering applications have not considered questionnaire pretesting. This article explores the use of GPT models as a useful tool for pretesting survey questionnaires, particularly in the early stages of survey design. Illustrated with two applications, the article suggests incorporating GPT feedback as an additional stage before human pretesting, potentially reducing successive iterations. The article also emphasizes the indispensable role of researchers’ judgment in interpreting and implementing AI-generated feedback.
| Original language | English |
|---|---|
| Pages (from-to) | 277-290 |
| Number of pages | 14 |
| Journal | Field Methods |
| Volume | 37 |
| Issue number | 4 |
| Early online date | 12 Sept 2024 |
| DOIs | |
| Publication status | Published - Nov 2025 |
Bibliographical note
Publisher Copyright:© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.
This idea originated from the Sociological Research Methods course for undergraduate students taught by the corresponding author at Lingnan University. Thanks to the students who were willing to share part of their class assignment for this illustration and Tobias Kamelski for his comments.
Publisher Copyright:
© The Author(s) 2024.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Medical Education
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