Q Method (also known as Q Methodology) is used to study subjective perspectives. It is useful when you wish to characterise how different groups of people think about a particular issue in a systemic way. It can be used to explore perspectives on any issue area where there is subjective disagreement, making it particularly useful for studying controversial subjects. Q does not look to link perspectives with objective and external variables such as age, job or income, but instead it looks to understand the subject’s own internal frame of reference (Cairns 2012).
Q method is most often used on participant sample sizes of between 12-40 people (Webler, Danielson et al. 2009; Cairns 2012). The participants in a Q study are purposively sampled (ie. they are not randomly selected), and will be determined by the question of interest. They might include for example policy makers, specialists in a particular field or people living in a certain area, or affected by a particular issue. Respondents should be selected to represent the breadth of opinion around the topic of interest, rather than being somehow representative of the population as a whole.
A set of opinion statements is developed to create the Q set or sample. This is done by reviewing the ‘volume of discussion’ on the topic of interest (Brown 1986: 58) and should cover several discourses or ‘ways of seeing’. Depending on the issue of interest, opinion statements can be gathered from any primary or secondary sources where that issue is being discussed. Sources might include interviews or discussions with stakeholders, text from academic papers, grey literature, websites and other media. Opinion statements are gathered from these sources, until it appears that ‘saturation point’ has been reached and the addition of new statements does not add any diversity to the existing set of statements.
This results in large set of opinion statements about the topic of interest (‘the concourse’), which then needs to be reduced down to a manageable number (usually between 20-60 statements, the ‘Q sample’) which will then be sorted by participants. The generation of opinion statements can help in the design of purposive sampling of participants.
Each participant is presented with the sample of opinion statements about the topic of interest and asked to sort them according to a particular sorting instruction (e.g. ‘please sort these statements from those which are most like, to those which are least like your point of view’. This process is known as carrying out a Q sort. The statements are sorted into a normal distribution shape, such as the one below (although see Webler 2009 for some discussion about whether this should be enforced or not). During a Q-sort you can encourage your respondents to think aloud and record their reasoning. Alternatively once completed, you can ask the respondent more questions about their sort.
A final stage of Q method is the factor analysis of the sort results. Free software for analysing Q method sorts is available from Peter Schmolck’s website. Factor analysis is used to analyse the data to find groups or clusters of similarly performed Q sorts. When these are found, this suggests the existence of a shared view among a group of people. The software illustrates these shared views in the form of idealized sorting patterns of the Q statements, and shows which participant’s sorts were clustered together, and correlated with these idealized views. This helps us to describe a number of ‘perspectives’ towards the issue in question.
The software output file provides useful information to help researchers interpret the perspectives that emerge from a study, listing, for example the statements that were placed significantly differently in each of the idealized sorts. The idealized sorts, combined with the interviews carried out during or after the sorting exercise, allows the researcher to write narratives that describes the nature of the perspectives distilled from the exercise. Much more detail on the process of analysis can be found in Webler (2009) amongst others.
Once the narratives have been written it is a good idea to send copies of your perspective write up to those who aligned closely with this ‘idealised’ version for feedback.
Broadening Out and Opening Up?
Q method helps to open up an issue and draw out the different ways that people are thinking about it. By taking a detailed ‘snap shot’ of the diversity of subjective perspectives around a given topic, it can reveal subjectivity within topics which might (on the surface) appear as purely technical debates. It is also great for revealing diversity within debates that might appear at first sight as homogenous (e.g. for looking at the detailed differences within particular views that could all be characterised as ‘environmentalist’). It also helps to move beyond the simplistic linking of views to jobs, demographic characteristics or any other external indicators..
By trying to comprehensively cover the breadth of views on a topic, Q method also gives form and shape to a range of perspectives without prioritisation. With appropriate research design, this can mean that more ‘marginal’ views can be given the same treatment as ‘mainstream’ views, and as such, this method can help to broaden out the ways an issue is characterised. However, much depends on how the topic of interest is bounded, and the ability of the researcher to ensure that a suitably diverse set of opinion statements is included in the Q sample, and a suitably diverse set of participants takes part in the exercise.
Fits and Limits
By looking across your perspective groups and Q sorts, you can also determine areas of agreement and disagreement across groups. This can be helpful in moving a debate forward, or when you wish to more thoroughly understand the nature of a controversy.
There are also situations when the method may not be appropriate. For example, given that the exercise requires participants to read detailed opinion statements and to engage with the researcher for an interview of up to an hour or more, this method may not be the most suitable approach for working with illiterate or hard-to-reach populations. Similarly, it may not be the best means of exploring how views change over time.
Finally, in order to work well, there needs to be a variety of well-formed views about the topic in question. So in cases where such views are yet to form, this may present a problem to the researcher (who may struggle to build a concourse of statements and to find participants who feel strongly about them).
Resources and References
Brown, S. R. (1986). Q technique and method: Principles and procedures. New tools for social scientists: Advances and applications in research methods. W. Berry and M. S. Lewis-Beck. Beverly Hills, CA, Sage.
Cairns, R. C. (2012). “Understanding Science in Conservation: A Q Method Approach on the Galápagos Islands.” Conservation and Society 10(3): 217-231.
Van Exel (2005) Q methodology: A sneak preview (PDF)
Webler, T., S. Danielson, et al. (2009). Using Q method to reveal social perspectives in environmental research. Greenfield MA, Social and Environmental Research Institute. Download this paper (PDF)
O’Donovan, C. and Smith, A. (2020) Technology and Human Capabilities in UK Makerspaces. Journal of Human Development and Capabilities 21(1) (paper describing a study which used Q method to appraise how capabilities are commonly experienced by technology users)
Material for this vignette was contributed by Dr Becky White.