This article introduces Q methodology, an idea-sorting activity that can help Extension improve outreach and education on new and contentious issues. Q methodology is a helpful tool when Extension professionals are confronted with controversial or complex resource management challenges. Through the analysis of a simple card-sorting exercise, researchers can determine quantitatively and qualitatively how different issues combine to result in (a) an individual\u27s viewpoint on an issue and (b) groupings of different viewpoints within a community. We describe the basic approach to implementing Q methodology and suggest circumstances in which it can help facilitate Extension outreach and education

Lien, Aaron M.

López-Hoffman, Laura

Ruyle, George

English

Clemson University: TigerPrints

Journal of Extension Volume 56 Number 2 Article 18 4-1-2018 Q Methodology: A Method for Understanding Complex Viewpoints in Communities Served by Extension Aaron M. Lien University of Arizona George Ruyle University of Arizona Laura López-Hoffman University of Arizona Recommended Citation Lien, A. M., Ruyle, G., & López-Hoffman, L. (2018). Q Methodology: A Method for Understanding Complex Viewpoints in Communities Served by Extension. Journal of Extension, 56(2). Retrieved from https://tigerprints.clemson.edu/joe/vol56/iss2/18 This Ideas at Work is brought to you for free and open access by TigerPrints. It has been accepted for inclusion in Journal of Extension by an authorized editor of TigerPrints. For more information, please contact kokeefe@clemson.edu. April 2018Volume 56Number 2Article # 2IAW4Ideas at WorkQ Methodology: A Method for Understanding Complex Viewpointsin Communities Served by ExtensionAbstractThis article introduces Q methodology, an idea-sorting activity that can help Extension improve outreach andeducation on new and contentious issues. Q methodology is a helpful tool when Extension professionals areconfronted with controversial or complex resource management challenges. Through the analysis of a simple card-sorting exercise, researchers can determine quantitatively and qualitatively how different issues combine to result in(a) an individual's viewpoint on an issue and (b) groupings of different viewpoints within a community. We describethe basic approach to implementing Q methodology and suggest circumstances in which it can help facilitateExtension outreach and education.Keywords: Q methodology, attitudes, Extension outreach and education, survey methods, conflict resolution   IntroductionExtension professionals are often called on to assist communities with controversial natural resourcemanagement issues. For example, species listed under the Endangered Species Act are to be protected, new cropvarieties are introduced, and federal land management priorities change. In other cases, Extension agents aretasked with facilitating the adoption of new technologies. In both types of situations, understanding constituents'attitudes and preferences and identifying common ground is often central to the Extension agent's role ofmediating conflict and helping find solutions to resource management challenges. Here, we present Qmethodology, an approach that can be used by Extension agents to gain new knowledge about the viewpoints oftheir constituents and improve the delivery of Extension programming, especially around controversial issues. Qmethodology is unique because it (a) allows for identification of a range of viewpoints on a single issue throughthe use of an easy-to-implement technique and (b) provides both quantitative and qualitative data on individualand group viewpoints.Q Methodology ExplainedQ methodology is not new, but it has seldom been applied in Extension (only two articles in the Journal ofAaron M. LienAssistant ResearchScientistSchool of NaturalResources and theEnvironmentalien@email.arizona.eduGeorge RuyleProfessor andExtension SpecialistSchool of NaturalResources and theEnvironmentgruyle@cals.arizona.eduLaura López-HoffmanAssociate ProfessorSchool of NaturalResources and theEnvironment and UdallCenter for Studies inPublic Policylauralh@email.arizona.eduUniversity of ArizonaTucson, ArizonaExtension mention Q methodology: Boyd, 2004, and Reisbeck, 1980). The method was developed by WilliamStephenson as a tool for psychologists to use to understand an individual's subjective viewpoints (Stephenson,1935a; Stephenson, 1935b). The difference between Q methodology and survey, interview, or focus groupapproaches is that the response variable in Q methodology is the participant in the study, not the participants'answers to a series of questions (Brown, 1980; McKeown & Thomas, 2013; Watts & Stenner, 2012). Thisdifference is what makes Q methodology a powerful tool for Extension. Surveys provide a snapshot of whatrespondents think about questions that probe different aspects of an issue, but they are poorly suited toproviding understanding of how respondents think about the questions. Interviews and focus group researchallow for a better understanding of how respondents think about an issue but provide only qualitative data,making comparison of viewpoints challenging. Q methodology provides both quantitative and qualitative data.Q methodology is implemented through an idea-sorting exercise. All participants are presented with the same setof materials: a single question, a stack of note cards with printed statements, and a poster with a fixeddistribution for sorting the cards. Figure 1 shows an example of a typical distribution for a Q methodology study.There is one empty rectangle for each note card (e.g., 40 statements, 40 rectangles). The rectangles at thebottom labeled "Less like how I think," "Neutral/No opinion," and "More like how I think" help participants withthe initial sorting of statements. A normal distribution is used to force participants into decisions about whatstatements best represent the way they do or do not think about an issue. Without this distribution, manyparticipants would place a large number of cards at the extreme ends of the distribution, making interpretationdifficult.Figure 1.Example Q Sort WorksheetEach sort in its entirety is a single data point in the study. The way a participant sorts the statements representsthe participant's working understanding of the issue. Analysis of each participant's sort is conducted usingcorrelation and factor analysis and is followed by qualitative analysis of the statements that load on each factor.Qualitative analysis allows the researcher to understand the meaning of factor groupings and the perspectivesIdeas at Work Q Methodology: A Method for Understanding Complex Viewpoints in Communities Served by Extension JOE 56(2)©2018 Extension Journal Inc 1they represent. Table 1 summarizes the steps in developing and implementing a Q methodology study. Tables 2shows partial quantitative results from a Q methodology study conducted in Arizona.Table 1.Summary of Q Methodology ProceduresStep Description1. Selection oftopic andstatementsAppropriate topics for Q methodology studies are issues about whichthere is a range of opinions. The research question should beformulated as a subjective judgment, not a yes-or-no question.Statements should be drawn from prior knowledge of working with thecommunity and are best if they are stated in the language participantswould use.2. Selection ofparticipantsQ methodology can be applied in groups of various sizes, using censusor sampling approaches. For issues relevant to only a small number ofstakeholders, it is possible to use a census approach. In situationswhere the number of stakeholders exceeds 30 or so, a censusbecomes impractical, and a sampling strategy is needed.3. StudyimplementationParticipants are provided with the set of statements and thedistribution poster, and then they independently sort the statementsaccording to how they think about the issue. After completing thesort, participants fill out an evaluation describing their thinking aboutthe statements placed at the polar ends of the distribution and,optionally, demographic information.4. Quantitativeand qualitativeanalysesFactor analysis is used for developing groupings of similar sorts basedon correlations between sorts. Factor analysis provides idealized sortsrepresenting each factor group. Qualitative interpretation of theranking of statements by each factor group is used for understandingdifferences across groups.Table 2.Partial Quantitative Results of a Q Methodology StudyFactor1 2 3Statement Score Rank Score Rank Score Rank1. I support habitat health for allspecies. It is a pyramid in which eachthing depends on the other.0.36 0 1.29 3 −0.79 −12. I use a planned grazing system toimprove grasslands.1.09 3 0.61 1 0.95 2Ideas at Work Q Methodology: A Method for Understanding Complex Viewpoints in Communities Served by Extension JOE 56(2)©2018 Extension Journal Inc 23. I work to make a healthy,functioning landscape.1.35 3 1.28 3 −0.04 04. Ranching provides water and othernatural things that would normally bethere.1.41 4 0.67 1 1.61 35. The benefit of restoration projectsmust offset the cost.−0.30 0 0.18 0 −0.29 −16. I view myself as a temporarysteward to improve the land for thenext generation.0.64 1 1.44 3 0.17 0Note. Abbreviated example of the quantitative output from the factor analysis ofindividual Q sorts. Results are from our study in southern Arizona. We found threeunique factor groups. Statements shown are the first six statements included in ourstudy. Score is the index score indicating how strongly a statement loads on a givenfactor. Rank is the position of each statement in an idealized sort based on the score.Idealized sorts are then interpreted qualitatively for the purpose of understanding theviewpoints represented by each factor group.Q methodology helps identify complex viewpoints. For example, two groups of participants may both think thatclimate change is real, but one group may trust scientists while the other distrusts scientists but believes in whatthey see happening on their farms. Understanding this difference could have implications for how to approachExtension programs and education.Example: Rangeland ConservationWe used Q methodology in Arizona to understand the views of the ranching community toward conservation andrange management. A detailed description of our study is available in Lien, Svancara, Vanasco, Ruyle, and López-Hoffman (2017). Our goal was to improve our understanding of ranchers' views on range management so that wecould develop more effective approaches to mitigating conflict around endangered species conservation. Therewere 40 statements used in the sort. The statements addressed the environment, economics, culture, and therole of government. Each of these four issues contributes to ranchers' approaches to range management.Analysis showed three groupings of ranchers; the groups had similar views on conservation but differed from oneanother in their attitudes toward economic goals and the role of government. We used these findings to informrecommendations relating to the development of economic incentives for habitat conservation.ConclusionThe strength of Q methodology is that it provides an in-depth understanding of a single issue. People do notdevelop opinions about issues in isolation. Rather, viewpoints are the result of how our thoughts on a range ofissues come together to form an opinion about a specific issue. Whereas a survey may reveal groupings ofrespondents who generally agree on an issue, Q methodology helps researchers understand how respondentsarrive at their viewpoints—differences in the range of factors that inform their thinking about the issue.Understanding individual viewpoints can highlight common ground between groups we may otherwise mistake asIdeas at Work Q Methodology: A Method for Understanding Complex Viewpoints in Communities Served by Extension JOE 56(2)©2018 Extension Journal Inc 3being in total disagreement with one another. Q methodology is well suited to complex situations whereidentifying shared values between participants is difficult—a common situation in natural resources management.It is a useful tool for Extension professionals working to mediate or overcome conflict on resource managementchallenges.Recommendations for Further ReadingFor more information, consult the following resources.Guides for implementing Q methodology:Brown S. R. (1980). Political subjectivity: Applications of Q methodology in political science. New Haven, CT:Yale University Press. Provides a detailed explanation of the statistical and methodological theory behind Qmethodology.McKeown, B., & Thomas, D. B. (2013). Q methodology. Los Angeles, CA: Sage Publications. Short guide thatintroduces basic concepts.Watts, S., & Stenner, P. (2012). Doing Q methodological research: Theory, method and interpretation. LosAngeles, CA: Sage Publications. User-friendly implementation guide with examples and straightforwardexplanations.Examples of implementation of Q methodology in a natural resources context:Chamberlain, E. C., Rutherford, M. B., & Gibeau, M. L. (2012). Human perspectives and conservation of grizzlybears in Banff National Park, Canada. Conservation Biology, 26, 420–431. doi:10.1111/j.1523-1739.2012.01856.xLien, A. M., Svancara, C., Vanasco, W., Ruyle, G. B., & López-Hoffman, L. (2017). The land ethic of ranchers: Acore value despite divergent views of government. Rangeland Ecology and Management, 70(6), 787–793.Sandbrook, C., Scales, I. R., Vira, B., & Adams, W. M. (2010). Value plurality among conservationprofessionals: Value plurality in conservation. Conservation Biology, 25, 285–294. doi:10.1111/j.1523-1739.2010.01592.xReferencesBoyd, B. L. (2004). Extension agents as administrators of volunteers: Competencies needed for the future.Journal of Extension, 42(2), Article 2FEA4. Available at: https://www.joe.org/joe/2004april/a4.phpBrown S. R. (1980). Political subjectivity: Applications of Q methodology in political science. New Haven, CT: YaleUniversity Press.Lien, A. M., Svancara, C., Vanasco, W., Ruyle, G. B., & López-Hoffman, L. (2017). The land ethic of ranchers: Acore value despite divergent views of government. Rangeland Ecology and Management, 70(6), 787–793.McKeown, B., & Thomas, D. B. (2013). Q methodology. Los Angeles, CA: Sage Publications.Reisbeck, R. F. (1980). Toward more effective newsletters. Journal of Extension, 18(4). Available at:Ideas at Work Q Methodology: A Method for Understanding Complex Viewpoints in Communities Served by Extension JOE 56(2)©2018 Extension Journal Inc 4https://www.joe.org/joe/1980july/80-4-a2.pdfStephenson, W. (1935a). Correlating persons instead of tests. Journal of Personality, 4(1), 17–24.Stephenson, W. (1935b). Technique of factor analysis. Nature, 136, 297.Watts, S., & Stenner, P. (2012). Doing Q methodological research: Theory, method and interpretation. LosAngeles, CA: Sage Publications.Copyright © by Extension Journal, Inc. ISSN 1077-5315. Articles appearing in the Journal become the property ofthe Journal. Single copies of articles may be reproduced in electronic or print form for use in educational ortraining activities. Inclusion of articles in other publications, electronic sources, or systematic large-scaledistribution may be done only with prior electronic or written permission of the Journal Editorial Office, joe-ed@joe.org.If you have difficulties viewing or printing this page, please contact JOE Technical SupportIdeas at Work Q Methodology: A Method for Understanding Complex Viewpoints in Communities Served by Extension JOE 56(2)©2018 Extension Journal Inc 5

Q Methodology: A Method for Understanding Complex Viewpoints in Communities Served by Extension

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Q Methodology: A Method for Understanding Complex Viewpoints in Communities Served by Extension

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