Kinds versus continua: a review of psychometric approaches to uncover the structure of psychiatric constructs. Issue 8 (21st March 2016)

• Record Type: Journal Article
• Authors: Borsboom, D.; Rhemtulla, M.; Cramer, A. O. J.; van der Maas, H. L. J.; Scheffer, M.; Dolan, C. V.
• Is Part Of: Psychological medicine. Volume 46:Issue 8(2016)
• Page Start: 1567
• Page End: 1579
• Publication Date: 2016-03-21
• Subjects: Dynamical systems, -- latent variable models, -- network models, -- psychometrics, -- taximetrics; Psychiatry -- Periodicals; Medicine and psychology -- Periodicals; Clinical psychology -- Periodicals; 616.89
• DOI: 10.1017/S0033291715001944
• Languages: English
• ISSNs: 0033-2917

Abstract

Abstract : The question of whether psychopathology constructs are discrete kinds or continuous dimensions represents an important issue in clinical psychology and psychiatry. The present paper reviews psychometric modelling approaches that can be used to investigate this question through the application of statistical models. The relation between constructs and indicator variables in models with categorical and continuous latent variables is discussed, as are techniques specifically designed to address the distinction between latent categories as opposed to continua (taxometrics). In addition, we examine latent variable models that allow latent structures to have both continuous and categorical characteristics, such as factor mixture models and grade-of-membership models. Finally, we discuss recent alternative approaches based on network analysis and dynamical systems theory, which entail that the structure of constructs may be continuous for some individuals but categorical for others. Our evaluation of the psychometric literature shows that the kinds–continua distinction is considerably more subtle than is often presupposed in research; in particular, the hypotheses of kinds and continua are not mutually exclusive or exhaustive. We discuss opportunities to go beyond current research on the issue by using dynamical systems models, intra-individual time series and experimental manipulations.