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

Abstract

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.

Keywords: Cancer; Health-Related Quality of Life; Network analysis; Psychometrics; SF-36; Short Form Health Survey.

Fig. 1

Examples of an FM (a), RMM (b) and an NM (c) that can be applied to HRQoL. FM formative model; RMM reflective measurement model; NM network model; MH mental health; NP item 9b of the 36-item Short Form Health Survey (SF-36): “how much of the time during the past 4 weeks have you been a very nervous person”; DC item 9c of the SF-36: “how much of the time during the past 4 weeks have you felt so down in the dumps that nothing could cheer you up”; CP item 9d of the SF-36: “how much of the time during the past 4 weeks have you felt calm and peaceful”; DB item 9f of the SF-36: “how much of the time during the past 4 weeks have you felt downhearted and blue”; HP item 9h of the SF-36: “how much of the time during the past 4 weeks have you been a happy person”. Presumed causal relations between variables are displayed by arrows. Labels on covariances among observed variables and on variances between latent and observed variables are omitted for clarity of presentation

Fig. 2

Network of Health-Related Quality of Life (HRQoL) as measured by the 36-item Short Form Health Survey in a cancer patient sample (a), a national sample (b) a pooled sample of the former two (c). The size of the absolute polychoric partial correlation between two nodes is represented using the color and thickness of an edge [37]. Node colors correspond to the eight domains: RED general health (GH), YELLOW physical functioning (PF), ORANGE mental health (MH), BLUE role limitations–physical (RP), GREEN role limitations–emotional (RE), PURPLE bodily pain (BP), GREY social functioning (SF), PINK vitality (VT), BROWN items not belonging to a domain

Fig. 3

Network of Health-Related Quality of Life (HRQoL) as measured by the domains of the 36-item Short Form Health Survey in a cancer patient sample (a), a national sample (b) a pooled sample of the former two (c). The size of the absolute partial correlation between two nodes is represented using the color and thickness of an edge [37]. Node colors correspond to the eight domains: RED general health (GH), YELLOW physical functioning (PF), ORANGE mental health (MF), BLUE role limitations–physical (RP), GREEN role limitations–emotional (RE), PURPLE bodily pain (BP), GREY social functioning (SF), PINK vitality (VT), BROWN diagnostic status (DS)

Fig. 4

Visual representation of the predictive quality of individual Health-Related Quality of Life characteristics of the 36-item Short Form Health Survey in the network structures using the closeness centrality measure. DS diagnostic status

Fig. 5

Visual representation of the predictive quality of domains of the 36-item Short Form Health Survey in the network structures using the closeness centrality measures. BP bodily pain, GH general health, MH mental health, PF physical functioning, RE role limitations–emotional, RP role limitations–physical, SF social functioning, VT vitality, DS diagnostic status