Q methodology is a well-established, scientifically based approach to study opinions, attitudes, discourses and beliefs. Operationally, Q technique presents participants with a series of statements, opinions, or other stimuli, which they rank on a positive-to-negative scale. Sophisticated factor analysis of the correlated rankings from all participants then reveals and quantifies underlying viewpoints held by the subjects. This section describes more about Q methodology’s concepts, how the Q technique works, and how Q Methodology is currently used.
Q-Assessor provides many features and capabilities, yet it is actually quite straightforward to use. This section outlines the ten simple steps involved in using Q-Assessor.
The best way to get a direct sense of how Q-Assessor works is to try out it out yourself. Here are several ways that you can do just that.
A Study is the fundamental organizing unit within the Q-Assessor system. It encompasses and manages all the components of a Q Methodology project — the statement samples, the “bins” into which they are sorted, data management, and all the participant-related features (enrollment, reminders, etc). This section provides an outline of how these pieces go together as well as details about how to create and manage the study itself.
Statements are the basic phenomena Q Methodology studies investigate. These are usually texts (opinions, terms, views, or sentences), but they can also be non-verbal elements (audio clips or images). These are the elements that Q study participants evaluate and sort. Q-Assessor provides easy-to-use tools to manage all aspects of handling statement concourses. This section provides detailed descriptions about how to create and edit statements, manage user- and group-scoped libraries, and use them in studies.
Sort Bins in Q-Assessor define the ranked groupings into which participants sort Statements. Each Bin can contain a certain number of Statements, has a certain numerical value used to calculate the Study factors, and has a descriptive label that informs the participant what the Bin means. This section provides a detailed explanation of how to add and adjust Sort Bins to a Study in Q-Assessor.
Each Q-Assessor Study can present participants with one or more additional questions that function as “exit interviews” commonly used by Q investigators. Q-Assessor provides easy-to-use tools to create these questions and maintain them in user- and group-scoped libraries. This section is a description of these tools and how you use them to augment your study’s findings.
Q-Assessor provides powerful tools to make recruiting and interacting with participants easy. Q-Assessor handles email invitations, reminders, and thank-you messages and archives all emails sent for easy review. This section provides detailed descriptions of all these features.
Once you’ve configured and released a Q-Assessor Study, participants perform the online Q-sorts and reply to any ancillary questions. This section describes and illustrates how this all works.
Q-Assessor stores all of a Study’s collected data in its industrial-grade database. As the data arrive, they are easily browsed so investigators can monitor the progress of their study. They can also download their raw data to their own computes at any time. This section describes in detail how Q-Assessor handles these data management features.
Processing Q-sort data into interpretable factors has always been a major rate-limiting step for Q-Methodology. Standard statistical packages do not handle Q’s peculiarities well, and the primary Q-specific tool now in use (PQMethod) is a quirky command-line tool written in FORTRAN back in the early 1990s.
Q-Assessor has reimplemented in a modern language (Ruby) the algorithms of PQMethod to produce identical numeric results. More importantly, Q-Assessor has integrated these numeric processes into a web-based user interface that produces results much faster and more clearly — particularly the interactive “rotation” steps. This section explains how we do this.
Q Methodology originated and has largely been championed in the English-speaking world. Interest in Q is now widespread across the globe, and systems for Q need to support this multilingual context.
Q-Assessor always allowed investigators to author statement concourses and interview questions in any language they liked, but all the operational texts remained in English. Now Q-Assessor lets investigators configure their studies to run entirely in any of the supported languages.
Q-Assessor is available on a monthly subscription basis. One month is the proper length of time needed to deploy and complete a complex Q study. Once one is familiar with Q-Assessor’s features, though, it is possible to deploy several studies within that time.
Once you’ve tried out Q-Assessor by deploying a small test study, you can easily request a subscription from your personal workspace. We will enable you to develop and run full-sized Q studies once payment comes through.
We have several ideas for further enhancements for Q-Assessor. We describe them here and solicit your input as to how important these ideas may be.
Here is the fine-print about using the Q-Assessor site.
Here are answers to frequently-asked questions about procedural details: signing-up, logging-in, managing passwords and email addresses, etc.
While Q-Assessor is still in beta release, subscriptions will remain fairly loosely-defined and generously-granted phenomena. At some point once Q-Assessor has proven its worth and Q-Assessor becomes a truly subscription-based service, we’ll provide details about how to manage your account here as well.