Back to search

Article

Generation of Synthetic Data in Health Surveys Using Large Language Models

2026-01-30

Abstract excerpt

<h4>Background</h4> Generating synthetic data using artificial intelligence, such as large language models (LLMs), is a useful strategy in public health because it can reduce time and costs, expand access to data, and facilitate information sharing without compromising confidentiality. <h4>Objective</h4> To evaluate the consistency and psychometric plausibility of synthetic data generated by an LLM to simulate t...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
7a269fa1-7e0e-5e08-8114-ae26b76e36da
DOI
10.64898/2026.01.27.26345015
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Generation of Synthetic Data in Health Surveys Using Large Language ModelsDOI 10.64898/2026.01.27.26345015
Select a neighboring publication to make it the new centre.