The Q-sorting technique is a research method used in psychology and social sciences to study the âsubjectivityâ of people, that is, their point of view. The question was developed by psychologist William Stevenson. It was used both in a clinical setting to measure a patientâs progress over time (intragroup comparison) and in a research setting to study how people think about a topic (intergroup comparison).
Etymology
The name "Q" comes from the form of factor analysis, which is used to analyze data. Normal factor analysis, called the âR method,â involves finding correlations between variables (say, height and age) from a sample of subjects. Q, in turn, seeks correlations between subjects in a sample of variables. Analysis of the Q-factor reduces many individual points of view of the subjects to several "factors", which, they say, represent common ways of thinking. It is sometimes said that Q-factor analysis is an R-factor analysis with an inverted data table. Although this explanation is useful as a heuristic for understanding Q, it can be misleading, since most Q methodologists argue that, for mathematical reasons, no data matrix will be suitable for analysis with either Q or R.
How does it work
How to handle Stephenson's Q sorting? Data for Q-factor analysis comes from a series of âQ-varietiesâ performed by one or more subjects. Sorting Q is the ranking of variables, usually represented as operators, printed on small cards in accordance with some kind of âlearning conditionâ. For example, in question Q about people's views on celebrity, the subject may be given statements such as âHe is a deeply religious personâ and âHe is a liar,â and they will be asked to make them out based on their own opinions. Using ranking instead of asking subjects to evaluate their agreement with statements individually is intended to reflect the idea that people think about ideas in relation to other ideas, rather than in isolation. Stephensonâs best Q-sorting test for efficiency is working directly with it!
Distinctive features
One significant difference between Q and other social science research methodologies, such as surveys, is that it typically uses far fewer items. Since Q is sometimes used with one subject, this makes research much cheaper. In such cases, a person evaluates the same set of statements under different learning conditions. For example, someone may be given a series of statements about personal qualities, and then be asked to rate them according to how well they describe themselves, their ideal self, their father, their mother, etc. Working with one person is especially relevant in studying how a personâs rating changes over time. This was the first use of Q-methodology. Because Stephenson's Q-sorting works with a small, non-representative sample, the findings cover only those who participated in the study.
Intelligence research
In intelligence studies, Q-factor analysis can generate consensus estimates (CBA) as a direct measurement. Alternatively, a personâs unit of measurement in this context is his load factor for Q-sorting, which he performs.
Factors are norms in relation to schemes. The person who receives the greatest load on the Operent factor is the one who is able to better understand the norm of the factor. What does the norm mean? This question is always full of speculation and rebuttal. This may indicate the wisest decision or the most responsible, most important or optimized balanced decision. These are all unverified hypotheses that require further study. However, they are already used in Q-sorting tests that work with intelligence.
An alternative method that determines the similarity between subjects that are somewhat similar to the Q methodology, as well as the cultural âtruthâ of the statements used in the test, is the theory of cultural consensus.
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, the consulting firm Davis Brand Capital has created their own online product, nQue, which they use to conduct online sorts that mimic the analog paper-based sorting process.
However, a web application that uses a graphical user interface to assist researchers is not commercially available. UC Riverside Riverside Situational Q-Sorting (RSQ), recently developed by the university, is designed to measure the psychological properties of situations. Their project âInternational situationsâ uses a tool to study the psychologically significant aspects of situations and how these aspects can vary in different cultures using this web application developed by the university. To date, there has been no study of differences in varieties produced using computer and physical sorting.
One Q-sorting by V. Stefanson should produce two data sets. The first is the physical distribution of sorted objects. The second is either a constant âthought out aloudâ story or discussion that immediately follows the sorting exercise. The purpose of these narratives was primarily to identify reasons for specific placements. Although the relevance of this qualitative data is often suppressed in modern applications of Q-methodology, the methods of reasoning about the placement of an item may be more analytically significant than the absolute placement of cards.
Application
Q-methodology has been used as a research tool in a wide range of disciplines, including nursing, veterinary medicine, healthcare, transportation, education, rural sociology, hydrology and mobile communications. The methodology is especially useful when researchers want to understand and describe the diversity of subjective points of view on a problem.
There are many challenges in the design, implementation and evaluation of health policies. One of the challenges is understanding how different stakeholders view a particular policy and how these views can affect implementation. Q-methodology is one approach that can be used to help policy-makers and researchers actively interact with those who play an important role in policy implementation.
Benefits
Q-methodology combines qualitative and quantitative research methods for the systematic study and description of the range of points of view on the topic. Participants should evaluate a set of predefined statements related to the topic in accordance with their own point of view. Then factor analysis methods identify people who adhere to like-minded people in how they see the topic, and clearly identify areas of consensus and divergence of views. Such a reflection of the points of view allows those who work on the implementation of the policy to anticipate possible barriers and levers in implementing the new policy.
Work with people
V. Stefanson's Q-sorting technique (also known as Q-sorting) is a systematic study of participants' perspectives. The Q-methodology is used to study the perspectives of participants who represent different positions on a problem, inviting participants to rank and sort a series of statements.
Participants' responses are analyzed using factor analysis. Unlike the standard use of factor analysis (often called R-methodology), variables are individuals, not attributes. There are five basic steps in setting up this methodology:
- Definition of the subject area of ââdiscourse on a specific issue.
- Development of a set of statements (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.
Principle of operation
This method uses the researcher's qualitative judgments in determining the problem, developing statements to study participants' points of view (some of the statements can be developed after interviewing key informants) and selecting them. Quantitative analysis options are used. This can be very useful for identifying prospects that do not require participants to articulate them clearly. This is a useful addition to a number of other objective measures of assessment. For example, the Q-methodology can be used to study the teacherâs views on teaching as part of a school district assessment. Other evaluation measures may include test results, attendance, and completion.
Innovative approach
The method of Q-sorting is an innovative technique that provides a quantitative structure of the opinions of individuals through factor analysis. The authors present the results of a case study in which the Q methodology was used to study attitudes toward an online wiki. Technology Encyclopedia (TE), among 35 engineers and technical staff of a manufacturing company. Management wanted to understand if employees were ready to use social conversational technology as a way to share knowledge. The purpose of this example is to demonstrate how the Q methodology works in practical terms. Who is the author of the Q-sorting technique? It is known that it was created by a team of American authors, the most significant of which was a man by the name of Stefanson. The authors also study a published journal article to evaluate how the Q methodology can be used to improve accounting research.
The results show that the Q-sorting technique can provide benefits in data collection (less respondent burden), data analysis (deeper understanding of the respondentâs subconscious) and results (better respondent âownershipâ 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 statements.