Q-Methodology in Healthcare: A Scoping Review

This post introduces the article ‘A scoping review of Q-methodology in healthcare research’ by Churruca, Ludlow, Wu, Gibbons, Nguyen, Ellis, and Braithwaite, published in BMC Medical Research Methodology in 2021. This publication provides a comprehensive overview of Q-methodology, an approach specifically designed for studying complex issues of human ‘subjectivity’. Though developed in the early twentieth century, its value in healthcare research has only been recognized relatively recently.

The primary aim of this scoping review was to systematically examine the empirical healthcare literature to understand the extent to which Q-methodology has been utilized over time, how it has been applied, and for what purposes. The authors conducted a rigorous search across three major electronic databases—Scopus, EBSCO-CINAHL Complete, and Medline—without date restrictions. Their review included English-language, peer-reviewed journal articles that rigorously applied both Q-sorting and inverted factor analysis within healthcare settings. From an initial 2,302 identified articles, 289 studies met the inclusion criteria for detailed analysis and synthesis.

The findings of this review indicate a notable increase in the adoption of Q-methodology in healthcare, particularly within the last five years. However, the research remains diffuse, spread across a large number of journals and diverse topic areas, suggesting that Q-methodology is still perceived as relatively novel in the field. The review highlights Q-methodology’s considerable value in addressing complex, divisive, and ethically fraught issues prevalent in healthcare, as it effectively simplifies complexity by reducing numerous viewpoints into a smaller set of common perspectives while preserving the nuances of individual experiences. It is particularly suited for exploring topics that evoke strong opinions or involve diverse stakeholder groups, including those often marginalized.

Common reasons identified for using Q-methodology included its capacity for exploring complex issues, its holistic and person-centred approach, the utility of its results for identifying distinct attitudes and preferences, its methodological rigour (combining qualitative richness with statistical analysis), and practical benefits such as requiring smaller participant samples for minority groups. The review also revealed key insights into the operational aspects of Q-studies in healthcare, such as the frequent use of literature reviews for Q-set development and face-to-face administration of Q-sorting tasks, often supplemented by post-sorting interviews to capture additional context.

Crucially, the authors identified limitations in the reporting of methods in a number of studies, particularly regarding the derivation of Q-sets, types of analyses performed, and explained variance. To address this and facilitate the future publication and increased adoption of Q-methodological studies, the paper presents a comprehensive checklist of essential details that should be included in reporting. This scoping review therefore not only maps the landscape of Q-methodology in healthcare but also provides valuable guidance for its effective and transparent application moving forward.”

A closer look at the scoping review

Churruca and colleagues followed PRISMA-ScR and searched Scopus, CINAHL Complete and Medline in January 2020 with no date limit. They included English-language, peer-reviewed healthcare studies that used both Q-sorting and inverted factor analysis. Of 2,302 records, 1,350 were screened after removing duplicates and 289 studies were included. Agreement between reviewers on a double-screened sample was high (Cohen’s kappa 0.82).

What the 289 studies show

Q-methodology studies appeared between 1966 and 2019 in 188 journals, with a clear rise in the last five years. Most came from the United Kingdom (85), the United States (46) and South Korea (40). The most common topics were health professional education (17.3%), nursing practice (13.5%) and mental healthcare (12.8%). Health providers took part in about two thirds of studies and consumers in a similar share. Q-sets ranged from 16 to 275 statements, with a median of 42, and the most common sorting grid ran from -4 to +4. Four-factor solutions and varimax rotation were the most frequent analytic choices.

Researchers chose Q-methodology because it handles complex or contested topics, captures viewpoints holistically, combines qualitative and quantitative logic, and works with small or hard-to-reach groups. Typical studies used about 40 to 60 participants.

Gaps and recommendations

The authors found that many studies reported their methods incompletely, for example how the Q-set was developed or why a factor solution was chosen. They propose a reporting checklist covering Q-set development, the ranking scale, analysis choices and factor decisions. They also describe a follow-up design in which a Q-study is followed by a survey, so that researchers can estimate how widely each viewpoint is held in a larger population. The review did not formally assess study quality and may have missed studies that used less specific wording.

Relevance for health management

For managers and policy researchers, Q-methodology offers a structured way to map stakeholder viewpoints before implementing a new policy or service, which is exactly where contested opinions matter most.

APA Reference: Churruca, K., Ludlow, K., Wu, W., Gibbons, K., Nguyen, H. M., Ellis, L. A., & Braithwaite, J. (2021). A scoping review of Q-methodology in healthcare research. BMC Medical Research Methodology, 21(1), 125. https://doi.org/10.1186/s12874-021-01309-7