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

## TL;DR

This paper introduces a seven-step method for creating a Q-sample, a set of statements used in Q-methodology to explore diverse viewpoints in medical education research.

## Contribution

The novel contribution is a systematic seven-step approach for designing a Q-sample based on interview data, enhancing methodological rigor in Q-methodology.

## Key findings

- A seven-step approach ensures comprehensive and balanced Q-sample design.
- Interview data can be effectively translated into a Q-sample using a mapping technique.
- Editing the Q-sample preserves participants' language while maintaining clarity and self-reference.

## Abstract

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.