The application of a network approach to Health-Related Quality of Life (HRQoL): introducing a new method for assessing HRQoL in healthy adults and cancer patients

Quality of Life Research, Sep 2015

Purpose Health-Related Quality of Life (HRQoL) research has typically adopted either a formative approach, in which HRQoL is the common effect of its observables, or a reflective approach—defining HRQoL as a latent variable that determines observable characteristics of HRQoL. Both approaches, however, do not take into account the complex organization of these characteristics. The objective of this study was to introduce a new approach for analyzing HRQoL data, namely a network model (NM). An NM, as opposed to traditional research strategies, accounts for interactions among observables and offers a complementary analytic approach. Methods We applied the NM to samples of Dutch cancer patients (N = 485) and Dutch healthy adults (N = 1742) who completed the 36-item Short Form Health Survey (SF-36). Networks were constructed for both samples separately and for a combined sample with diagnostic status added as an extra variable. We assessed the network structures and compared the structures of the two separate samples on the item and domain levels. The relative importance of individual items in the network structures was determined using centrality analyses. Results We found that the global structure of the SF-36 is dominant in all networks, supporting the validity of questionnaire’s subscales. Furthermore, results suggest that the network structure of both samples was highly similar. Centrality analyses revealed that maintaining a daily routine despite one’s physical health predicts HRQoL levels best. Conclusions We concluded that the NM provides a fruitful alternative to classical approaches used in the psychometric analysis of HRQoL data.

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The application of a network approach to Health-Related Quality of Life (HRQoL): introducing a new method for assessing HRQoL in healthy adults and cancer patients

Qual Life Res The application of a network approach to Health-Related Quality of Life (HRQoL): introducing a new method for assessing HRQoL in healthy adults and cancer patients Jolanda J. Kossakowski 0 1 2 Sacha Epskamp 0 1 2 Jacobien M. Kieffer 0 1 2 Claudia D. van Borkulo 0 1 2 Mijke Rhemtulla 0 1 2 Denny Borsboom 0 1 2 0 Interdisciplinary Center Psychopathology and Emotion Regulation, University Medical Center Groningen, University of Groningen , Hanzeplein 1, 9700 RB Groningen , The Netherlands 1 Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute , Plesmanlaan 121, 1066 CX Amsterdam , The Netherlands 2 & Jolanda J. Kossakowski Purpose Health-Related Quality of Life (HRQoL) research has typically adopted either a formative approach, in which HRQoL is the common effect of its observables, or a reflective approach-defining HRQoL as a latent variable that determines observable characteristics of HRQoL. Both approaches, however, do not take into account the complex organization of these characteristics. The objective of this study was to introduce a new approach for analyzing HRQoL data, namely a network model (NM). An NM, as opposed to traditional research strategies, accounts for interactions among observables and offers a complementary analytic approach. Methods We applied the NM to samples of Dutch cancer patients (N = 485) and Dutch healthy adults (N = 1742) who completed the 36-item Short Form Health Survey (SF36). Networks were constructed for both samples separately and for a combined sample with diagnostic status added as an extra variable. We assessed the network structures and compared the structures of the two separate samples on the item and domain levels. The relative importance of individual items in the network structures was determined using centrality analyses. Health-Related Quality of Life; Cancer; Network analysis; Psychometrics; Short Form Health; Survey; SF-36 - Department of Psychology, University of Amsterdam, Weesperplein 4, 1018 WZ Amsterdam, The Netherlands Introduction The question of how theoretical constructs like HealthRelated Quality of Life (HRQoL) should be related to observables reflects one of the fundamental scientific issues facing any field: how should we think about the relation between constructs and observables? Two dominant approaches to this question are known as formative and reflective modeling [ 1, 2 ]. In formative models (FMs), items are viewed as causes of the theoretical construct under consideration, whereas in reflective measurement models (RMMs), items are seen as effects of that construct. In the present paper, we argue that neither of these approaches suits HRQoL, and present an alternative approach based on a network model (NM). Some of the analyses performed in HRQoL research have been based on the application of FMs using principal components analysis (PCA), creating weighted composites of observables to achieve data reduction [ 3 ]. The 36-item Short Form Health Survey (SF-36), a commonly used instrument across different disease conditions and patient groups [ 4 ], has been developed on the basis of PCA. In an FM, HRQoL is the common effect of items (or simply a composite score formed out of them, like in PCA [ 5 ]). The idea behind the FM is that observed variables contribute to HRQoL: if the observables change, HRQoL changes as a result. A simplified example of the FM is represented in Fig. 1a where the observables are represented as forming a ‘‘mental health’’ (MH) component, one of the domains of the SF-36. An advantage of the FM is that it allows people with similar levels of HRQoL to have different item responses. For example, John may have a poor HRQoL because he is a very nervous person, whereas Jane may have a poor HRQoL because she feels downhearted and blue. Furthermore, the FM is appropriate when one would like to calculate a single score to represent someone’s HRQoL, which can be used as an index of general functioning. However, the FM also has some downsides. First, the FM is unidentified unless external outcome variables are added to identify its parameters [ 6 ]. Since different external variables yield different modeling solutions, the definition of a formative construct cannot be assumed stable across applications (i.e., interpretational confounding; [ 7 ]). Second, since the FM does not have implications for the correlation structure between item responses, it cannot evaluate important relations between items that make up HRQoL, nor the processes that give rise to the correlation structure that characterizes it [ 1 ]: relations between items are modeled as nuisance, even when they may harbor important information. An alternative to the FM [e.g., 8, 9] is the RMM. In an RMM, HRQoL is defined as the common determinant of item responses. For example, Fig. 1b shows that the items NP, DC, CP, DP and HP have a common determinant, namely MH. When using an RMM, one has to satisf (...truncated)


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Jolanda J. Kossakowski, Sacha Epskamp, Jacobien M. Kieffer, Claudia D. van Borkulo, Mijke Rhemtulla, Denny Borsboom. The application of a network approach to Health-Related Quality of Life (HRQoL): introducing a new method for assessing HRQoL in healthy adults and cancer patients, Quality of Life Research, 2016, pp. 781-792, Volume 25, Issue 4, DOI: 10.1007/s11136-015-1127-z