Integrated Data Collection in Q Methodology: Using ChatGPT From Concourse to Q-sample to Q-sort

Abstract

Data collection in mixed methods research (MMR) can present challenges. To demonstrate the inherently mixed data collection within Q methodology (Q-technique), we start by generating a concourse of subjective statements with ChatGPT. A structured Q-sample is selected from the concourse using Fisher’s Design of Experiments which came from agricultural research and involves small sample theory and variance design. The process of the Q-sort involves each participant placing the Q-sample’s numbered subjective items into a continuum (grid) of Most Like to Most Unlike their view on the topic. Thus, the participants transform the subjective statements into a qualitative–quantitative hybrid representation of their inner subjectivity. The contribution to MMR is continuing the dialogue for integrated data collection via a specific example.