Systematic Integration of Quantitative Measures into the Qualitative Content Analysis of Constructs

Abstract

Content analysis is a frequently applied technique used to pool the constructs obtained from a set of repertory grid interviews by creating categories containing constructs with similar meanings. In the standard procedure, the constructs are categorized by analyzing only the semantic information given in the construct poles. In a few cases in the literature, the analysis is additionally backed up using the results from isolated similarity scores, cluster analysis, or principal component analysis. This study provides a novel method to systematically integrate numeric measures of construct similarity into the process of content analysis. By mapping the construct similarity information into a color space, each construct receives a specific color value. Numerically similar constructs will have similar colors. By doing so, an additional and intuitive heuristic to match similar constructs is provided. This approach proves to be especially useful when construct descriptions are short or ambiguous and a large number of constructs have been elicited. The application of the method is demonstrated using a set of n = 63 repertory grid interviews containing a total number of k = 627 constructs.