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Qualitative analysis of repertory grids: Interpretive clustering DISCUSSION PAPER QUALITATIVE ANALYSIS OF REPERTORY GRIDS: INTERPRETIVE CLUSTERING Viv Burr and Nigel King Department of Psychology, University of Huddersfield, UK In this discussion paper, we present a new form of qualitative analysis of repertory grid data that we have called ‘Interpretive Clustering’. Although numerous existing publications report having performed qualitative analyses of repertory grid data, upon inspection this is usually a content analysis of constructs. In our research, used as an illustrative example here, we explored people’s constructions of nature through images of outdoor spaces using repertory grids. Through visual in- spection we used patterns of responses across constructs in each participant’s grid to identify con- struct ‘clusters’; these clusters are therefore constituted by constructs that hold implications for each other and are examples of ‘constellatory construing’. We would like to invite comments from academics and practitioners on both the process and potential usefulness of Interpretive Clustering. Key words: repertory grid, clustering, qualitative analysis, interpretive analysis. At the EPCA (European Personal Construct As- describes a process for performing such a con- sociation) conference in Edinburgh, 2018, we tent analysis and this has been adopted in previ- presented material from our ongoing research ous research reporting qualitative analyses of project using Repertory Grid interviews to ex- repertory grids; for example, Kreber & Klampf- plore peoples’ construal of outdoor spaces. In leitner (2013) used this method to derive themes analysing our data, we have been developing a in constructs elicited in relation to teacher effec- method for qualitatively analysing Grids. Grids tiveness as perceived by lecturers and students, are predominantly analysed quantitatively, using and Home, Bauer & Hunziker (2007) used it to computer software, but in this paper we will analyse constructs around urban green spaces. introduce a method for analysing grid data quali- We believe that Interpretive Clustering offers tatively that we have called ‘Interpretive Cluster- a truly qualitative analysis of grid data and there- ing’, which is an extension of the method of fore constitutes a useful addition to research ‘Visual Processing’ described by Stewart & methods for both PCP researchers and practitio- Stewart (1981. We present Interpretive Cluster- ners and for qualitative research more generally. ing here to invite comments from academics and Additionally, when compared to other qualitative practitioners on both the process and potential methods of analysis, such as thematic analysis usefulness of this form of analysis (please find (for example, Braun & Clarke, 2006), Interpre- our contact details at the end of this paper). We tive Clustering arguably represents a more par- are primarily interested in receiving comments ticipant-led approach, rendering the analysis on this method of analysis, rather than in sug- more faithful to the participant’s own meanings. gested revisions to the paper itself. Constructs are thought to be related in a lar- Researchers frequently claim to have used ger system of meaning-making; they are often Repertory Grids qualitatively but in actuality this related to each other so that if the person con- often means a content analysis of elicited con- strues a situation as ‘challenging’ they may also structs, perhaps followed by a quantitative be highly likely to see it as ‘anxiety-provoking’ analysis of the grid data itself. Jankowicz (2004) and ‘threatening’ too. This is what we under- 1 Personal Construct Theory & Practice, 16, 2019 Viv Burr and Nigel King stand as ‘constellatory construing’, if the person it is also valuable for the qualitative researcher, sees something in terms of one construct they are as it enriches and extends our understanding of also likely to see it in terms of other, related the person’s experience. constructs. This relationship between constructs has been very valuable in clinical practice. For example, a Repertory Grids and construct clusters person may see others in terms of constructs such as ‘helps others – selfish’ and ‘taken advan- Repertory Grids enable the researcher to examine tage of by others – assertive’, but if these con- what constructs the participant applies to a particu- structs are related in their system it may mean lar realm of experience and how these constructs that they can have difficulty in becoming more are related to each other. A simple example of a assertive because for them this also implies be- grid can be seen in Tab. 1. coming more ‘selfish’. This relatedness of con- structs has been helpful in clinical practice, and Tab. 1: A simple repertory grid using chocolate bars as elements Preferred Mars Kit Snickers Milky Lion Bounty My ideal Non-preferred pole Kat Way Bar bar pole 5 1 not too 2 4 5 1 4 4 5 too sweet sweet has bits 1 3 5 1 4 3 5 smooth hard 2 3 4 1 4 3 5 soft satisfying 5 4 5 1 4 4 5 still hungry chewy 4 3 5 1 4 3 5 not chewy solid 4 3 5 1 4 4 5 insubstantial Here, chocolate bars have been used as the ele- simply visually inspecting the grid in Tab. 1 it ments and a 5-point rating scale chosen as the can be seen that two elements, the Snickers and scoring method. In the case of each construct, a the Lion Bar, are most closely related to the per- score of 5 represents the left hand, preferred pole son’s ‘ideal bar’ and the Milky Way least like it. and a score of 1 represents the right hand, non- Also, the patterns of scores for the last three preferred pole; the preferred pole is the pole of constructs are very similar, so for this participant the construct that the participant says they would the constructs ‘satisfying – still hungry’, ‘chewy usually choose. The participant was asked to – not chewy’ and ‘solid – insubstantial’ are re- consider each construct in turn and to apply it to lated to each other and form a construct cluster each element, choosing a number between 1 and or constellation. 5 in each case to represent how far towards one However, sometimes it isn’t feasible or desir- pole of the construct or the other they felt that able to use statistical analyses in order to exam- element sits. ine construct clusters. They become less reliable Grids have principally been analysed in order when relatively few elements (fewer than 12) are to examine how constructs are related or ‘clus- used to elicit the constructs, but a researcher tered’ together. Constructs are related to each might choose to use a smaller number of ele- other to the extent that they show similar pat- ments where they want to explore the partici- terns of ratings across the elements, i.e. they are pant’s construing in depth as part of a qualitative applied to the elements in similar ways. Some interview. They are also less reliable where dif- form of factor analysis is typically used to ex- ferent elements are used with different partici- plore how the constructs cluster together. Just by pants, as we did in our research; again this is 2 Personal Construct Theory & Practice, 16, 2019 Qualitative analysis of repertory grids: Interpretive clustering something a qualitative researcher may wish to other. In the case of our research, we had 7 ele- do because they want the participant to select ments in our grids and initially decided that two which elements to rate their constructs against. constructs must show identical responses on 5 There is also some debate about whether the out of the 7 constructs. We felt that accepting various programmes for analysing grids produce fewer than 5 ‘matches’ would render the com- psychologically meaningful or trustworthy out- parison too near to chance levels, but insisting puts (Bell, 2018). The Interpretive Clustering on 6 or 7 matches might be so stringent as to method described below allows the researcher to eliminate potentially important relationships. We consider a number of possible construct clusters experimented with using both criteria in our for a participant and to interpret these using the research; accepting 5+ matches sometimes re- interview material gathered during the construct sulted in a great number of clusters for some elicitation process. We will now illustrate the participants, which were difficult to interpret. On method using data from our research on the the other hand, using only 6+ matches meant meaning of outdoor spaces. that, for some participants, no clusters were identified. There may be an argument for vary- ing the criterion slightly between participants in Using Interpretive Clustering to explore the order to simplify the clusters for participants meaning of outdoor spaces where there is a great deal of interrelatedness in their grid and to make sure this is captured for Thirteen participants were interviewed using participants where it is much less pronounced Repertory Grids. The elements were images of a but still evident. The analysis in the remainder of range of outdoor spaces (some urban, some rural the steps below is based on a criterion of 6 or 7 or wilderness, and some mixed) and constructs matches. We decided on this criterion as several were elicited using the triadic method. In the of our participants demonstrated a considerable case of each construct, the participant’s preferred amount of interconnectedness in their grids and pole was identified and a simple binary scoring using 5+ matches which led to a very complex system (ticks and crosses) was used to complete picture that was hard to interpret. the grids. Elements that were ‘out of range of convenience’ of a construct were scored with a Step 3 0. For each grid, we produced a matrix showing the Below is a detailed account of how we did the number of matches that each construct had with analysis, using examples from this research.

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