Deconstructing the construct: A network perspective on psychological phenomena

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Abstract

In psychological measurement, two interpretations of measurement systems have been developed: the reflective interpretation, in which the measured attribute is conceptualized as the common cause of the observables, and the formative interpretation, in which the measured attribute is seen as the common effect of the observables. We advocate a third interpretation, in which attributes are conceptualized as systems of causally coupled (observable) variables. In such a view, a construct like ’depression’ is not seen as a latent variable that underlies symptoms like ’lack of sleep’ or ’fatigue’, and neither as a composite constructed out of these symptoms, but as a system of causal relations between the symptoms themselves (e.g., lack of sleep → fatigue, etc.). We discuss methodological strategies to investigate such systems as well as theoretical consequences that bear on the question in which sense such a construct could be interpreted as real.

Section snippets

Reflective models

In reflective models, observed indicators (e.g., item or subtest scores) are modeled as a function of a common latent variable (i.e., unobserved) and item-specific error variance. Reflective models are commonly presented as ‘measurement models’ in modern test theory (Mellenbergh, 1994). Examples are the IRT models of Rasch, 1960, Birnbaum, 1968 and Samejima (1969), common factor models (Jöreskog, 1971, Lawley and Maxwell, 1963), latent class models (Lazarsfeld, 1959), and latent profile models (

Problems with the reflective and formative conceptualizations

The status and nature of reflective and formative measurement models have been the source of various discussions (Bagozzi, 2007, Bollen, 2007, Howell et al., 2007a, Howell et al., 2007b; see also a special issue of the Journal of Business Research, vol. 16, issue 12, 2008). These have centered on desirable properties of indicators in formative and reflective models (Bollen, 1984, Jarvis et al., 2003, Wilcox et al., 2008), the status of the error term in formative models (Coltman et al., 2008,

The network perspective: constructs as dynamical systems

We propose that the variables that are typically taken to be indicators of latent variables should be taken to be autonomous causal entities in a network of dynamical systems. Instead of positing a latent variable, one assumes a network of directly related causal entities as a result of which one avoids the three problems discussed above.

First, consider criteria for a major depressive episode (MDE; American Psychiatric Association, 1994). These criteria involve symptoms like “lack of sleep,”

Constructs and their interrelations

The ontological status of psychological constructs as well as the epistemic question of how to measure them has been the topic of considerable controversy in psychology. Borsboom, Mellenbergh, and Van Heerden (2004) have argued that, in order to be plausible candidates for measurement, constructs should in fact refer to structures in reality; structures that play a causal role in determining individual differences in test scores. Maraun and Peters (2005) have suggested that the entire idea of

Conclusion

In this paper, we have presented a network approach in which the constituents of psychological constructs are directly related in a nontrivial and non-spurious manner. The network approach is intuitively attractive and naturally accommodates what we know about the elusive nature of psychological constructs. It also offers an explanation of why our traditional psychometric approaches have met with so little success, that is, of why after all these years we still do not know whether typical

Acknowledgements

This work was supported by NWO innovational research grant no. 451-03-068. The authors wish to thank Conor Dolan and Jelte Wicherts for providing the NEO-PI-R data set.

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