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Reflective, causal, and composite indicators of quality of life: A conceptual or an empirical distinction?

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Abstract

Items (or indicators) that constitute “quality of life” instruments can be classified as either reflective (manifestations of some underlying construct), causal (the construct is an effect of the indicators), or composite (the construct is an exact linear combination of the indicators). Psychometric methods based on inter-item associations are only appropriate for reflective indicators, whereas other statistical and non-statistical validation methods can be used for composite or causal indicators. Thus, the distinction has important practical, as well as theoretical, implications. Attempts have been made to empirically identify which items of the EORTC QLQ-C30, a cancer-specific instrument, are causal and which are reflective. Such attempts, however, first require commitment to a particular definition of quality of life, of which there are many. Whether an indicator forms a composite, is causal or reflective of quality of life will depend on the definition adopted, and therefore, the reflective–composite–causal distinction is, arguably, best established on conceptual rather empirical grounds, guided by the “mental experiments” suggested by Bollen (Structural equations with latent variables, Wiley, New York, 1989). Conceptual models of health status and quality of life, as well as a cognitive-linguistic approach to quality of life assessment, may make some contribution to this practice. Theoretical consideration of indicator content can guide not only instrument development and validation, but also the selection of an appropriate instrument.

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Notes

  1. Fayers and Hand [4] distinguished between reflective and causal indicators along psychometric–clinimetric lines, where clinimetrics is defined as “the domain concerned with indexes, rating scales, and other expressions that are used to describe or measure symptoms, physical signs, and other distinctly clinical phenomena in clinical medicine” [18] , p 5]. Although tangential to the present discussion, it is worth noting that the psychometric–clinimetric distinction is not straightforward [19–22] so this parallel with the reflective–causal distinction may not be helpful.

  2. Because a composite variable is defined by its indicators rather than conceptually, composite indicators are not considered in this exercise. This is not to say that items on quality of life instruments cannot be composite indicators, just that such indicators may not map to a conceptual definition.

  3. One complication in the Wilson and Cleary model is that the authors equate health-related quality of life with health status. One interpretation of this is that all aspects of the model except overall quality of life are reflective of health-related quality of life and formative for overall quality of life. Another complication is that Wilson and Cleary acknowledge that most of these associations could be bidirectional.

  4. It seems to make little sense to consider including composite indicators alongside either reflective or causal indicators, as the latter require some conceptual definition of the construct that is independent of its measurement, whereas the former does not. A conceptually defined construct would not “require” composite indicators to define it operationally.

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  1. Psycho-oncology Co-operative Research Group (PoCoG), School of Psychology, The University of Sydney, Level 6, Chris O’Brien Lifehouse (C39Z), Sydney, NSW, 2006, Australia

    Daniel S. J. Costa

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Costa, D.S.J. Reflective, causal, and composite indicators of quality of life: A conceptual or an empirical distinction?. Qual Life Res 24, 2057–2065 (2015). https://doi.org/10.1007/s11136-015-0954-2

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