The Q-sort technique is a research method used in psychology and social sciences to study people's "subjectivity", i.e. their point of view. The question was developed by psychologist William Stevenson. It has been used both in a clinical setting to assess a patient's progress over time (intragroup comparison) and in a research setting to study how people think about a topic (between group comparisons).
Etymology
The name "Q" comes from a form of factor analysis that is used to analyze data. Normal factor analysis, called the "R method", involves looking for correlations between variables (say, height and age) across a sample of subjects. Q, in turn, looks for correlations between subjects in the sample of variables. Q-factor analysis reduces many of the subjects' individual perspectives to a few "factors" that are said to represent general ways of thinking. Sometimes they saythat Q-factor analysis is R-factor analysis with a flipped data table. While this explanation is useful as a heuristic for understanding Q, it can be misleading as most Q methodologists argue that, for mathematical reasons, no data matrix will be suitable for analysis with both Q and R.
How it works
How to handle Stephenson's Q-sort? The data for Q-factor analysis comes from a series of "Q-sorts" performed by one or more subjects. Q sorting is a ranking of variables, usually represented as statements printed on small cards, according to some kind of "learning condition". For example, in a question Q about people's views of a celebrity, the subject might be given statements such as "He is a deeply religious person" and "He is a liar" and asked to parse them based on their own opinions. The use of rankings, rather than asking subjects to rate their agreement with statements individually, is intended to capture the idea that people think about ideas in relation to other ideas, rather than in isolation. The best test of Stephenson's Q-sort for efficiency is to work with it!
Distinguishing Features
One significant difference between Q and other social science research methodologies such as surveys is that it typically uses far fewer subjects. Since Q is sometimes used with a single subject, this makesresearch is much cheaper. In such cases, a person evaluates the same set of statements under different learning conditions. For example, someone might be given a series of personality trait statements and then asked to rate them according to how well they describe themselves, their ideal self, their father, their mother, and so on. Working with one person is especially relevant in studying how a person's rating changes over time. This was the first use of the Q methodology. Because Stephenson's Q-sort works on a small, unrepresentative sample, the findings only cover those who participated in the study.
Intelligence Research
In intelligence research, Q-factor analysis can generate consensus-based scores (CBA) as a direct measure. Alternatively, a person's unit in this context is their load factor for the Q-sort they perform.
Factors are norms in relation to schemes. The person who gets the most load on the Operent factor is the one who is able to better understand the norm of the factor. What does norm mean? This question is always full of conjectures and denials. It may indicate the wisest decision, or the most responsible, most important, or optimized balanced decision. These are all untested hypotheses that require further study. However, they are already being used in tests of Q-sort that work with intelligence.
An alternative method that determines the similarity between items that are somewhat similar toQ's methodology, as well as the cultural "truth" of the statements used in the test, is the cultural consensus theory.
Interpretation
The data collection procedure of the Q sorting technique is traditionally performed using a paper template and sample statements printed on separate cards. However, there are also computer software applications for online sorting. For example, consulting firm Davis Brand Capital has created its own online product, nQue, which they use to run online sorts that mimic the analog paper-based sorting process.
However, the web application that uses a graphical user interface to assist researchers is not commercially available. UC Riverside The Riverside Situational Q-sort (RSQ), recently developed by the university, is designed to measure the psychological properties of situations. Their International Situations project uses a tool to explore the psychologically significant aspects of situations and how those aspects can differ across cultures with this university-developed web application. To date, no study has been conducted on the differences in varieties produced using computer and physical sorting.
One Q-sort by W. Stefanson should produce two sets of data. The first is the physical distribution of the sorted objects. The second is either a constant "thinking out loud" story or a discussion that immediately follows the exercise insorting. The purpose of these narratives was primarily to identify reasons for specific placements. Although the relevance of these qualitative data is often stifled in current applications of Q-methodology, ways of reasoning about item placement can be more analytically meaningful than absolute card placement.
Application
The Q-methodology has been used as a research tool in a wide variety of disciplines, including nursing, veterinary medicine, public he alth, transportation, education, rural sociology, hydrology, and mobile communications. The methodology is especially useful when researchers want to understand and describe a variety of subjective perspectives on a problem.
There are many challenges in developing, implementing and evaluating he alth policy. One of the challenges is understanding how different stakeholders view a particular policy and how those views can affect implementation. The Q-methodology is one approach that can be used to help policy makers and researchers to actively engage with those who play an important role in policy implementation.
Benefits
Q-methodology combines qualitative and quantitative research methods to systematically explore and describe a range of perspectives on a topic. Participants must evaluate a set of predefined statements related to the topic according to their own point of view. Factor analysis methods then identify peoplewhich adhere to like-minded people in how they see the topic and allow for clear identification of areas of consensus and divergence of views. This mapping of viewpoints allows those working on policy implementation to anticipate potential barriers and leverage in implementing a new policy.
Working with people
W. Stefanson's Q-sorting (also known as Q-sorting) is a systematic study of participants' points of view. Q-methodology is used to explore the perspectives of participants who represent different positions on an issue by asking participants to rank and sort a series of statements.
Participant responses are analyzed using factor analysis. Unlike the standard use of factor analysis (often referred to as R-methodology), variables are individuals, not features. There are five main steps in setting up this methodology:
- Defining the subject area of discourse on a specific issue.
- Developing a set of assertions (Q-sort).
- Selection of participants representing different points of view.
- Q sorting by participants, as well as analysis and interpretation.
- Q-sort is a mixed methodology.
Working principle
This method uses the qualitative judgment of the researcher in defining the problem, developing statements to explore participants' perspectives (some of the statements can be developed after interviewing key informants), and selecting them. Quantitative variants of the analysis are used. This can be very useful for identifying perspectives that do not require participants to articulate them clearly. This is a useful addition to a number of other objective evaluation measures. For example, the Q-methodology can be used to examine teacher perspectives on teaching as part of a school district assessment. Other evaluation measures may include test scores, attendance, and completion.
Innovative approach
The Q-sort technique is an innovative technique that provides a quantitative structure to the opinions of individuals through factor analysis. The authors present the results of a case study in which the Q methodology was used to examine attitudes towards online wikis. Encyclopedia of Technology (TE), among 35 engineers and technical staff of a manufacturing company. Management wanted to understand whether employees were ready to use social conversational technologies as a way to share knowledge. The purpose of this example is to demonstrate how the Q methodology works in a practical setting. Who is the author of the Q-sort technique? It is known that it was created by a team of American authors, the most significant of which was a man named Stefanson. The authors are also reviewing a published journal article to evaluate how the Q methodology can be used to improve accounting research.
The results show that the Q-sort technique can provide advantages in data collection (less burden on the respondent), data analysis (greater understanding of the subconsciousrespondent) and outcomes (better respondent “ownership” of organizational problems and solutions). However, it also has disadvantages in terms of managerial application.
When working with an industry partner, researchers may need to consider a more positivist approach and be prepared to explain the context behind the claims.
