How to design a Q-sample: A seven-step approach based on interview data

In recent decades, medical education research has increasingly investigated the subjectivity and viewpoints of (pre-service) healthcare professionals. A promising approach for exploring subjectivity is Q-methodology (Q). Q, which combines qualitative and quantitative methods, involves a card-sorting process in which participants are asked to sort statements into a (normal distribution) grid according to their preferences. Similar sorting patterns are then summarized into profiles and described narratively. A central element of this process is the design of the Q-sample - a set of statements representing a wide range of opinions, beliefs, or perspectives on the subject of study. The Q-sample is, therefore, critical for the success of a Q-study and requires precise development steps. Currently, these steps are only preliminarily described in the literature. The present paper addresses this gap by defining a seven-step approach to Q-sample design based on interview data. It offers a systematic and methodological approach that captures the diversity of viewpoints on a particular research topic. Building on a previous qualitative study, it demonstrates how to translate interview data into a Q-sample while ensuring coverage and balance through the use of a mapping technique. The paper also addresses the significance of editing and how to preserve the everyday language of participants when modifying the Q-sample to facilitate self-reference. A comprehensive overview of the criteria for designing a Q-sample is provided. Practical recommendations for selecting a Q-sample and implementing Q-methodology in medical education are offered, and potential challenges are discussed in detail.