Mapping quality of life in Norway: psychometric evaluation and network analysis of 15,148 responses from a public health study

TL;DR

This study evaluates the psychometric properties and network structure of quality of life and health measures in a large Norwegian population sample to support public health policy.

Contribution

The study introduces a network analysis approach to identify structural relationships among quality of life and health indicators in a large-scale public health survey.

Findings

Measures showed acceptable reliability and validity with minor modifications.

Network analysis revealed a central cluster of psychological health indicators and peripheral physical health variables.

Physical health variables were less connected and positioned at the network periphery.

Abstract

The Norwegian Quality of Life Study (NQoLS) was established to inform public health policy by assessing self-reported health (SRH) and quality of life (QoL) outcomes across the general population, identifying factors that influence these outcomes, and highlighting vulnerable groups. In this study, we assessed the psychometric properties of the NQoLS measures and applied network analysis to explore the structural relationships among outcome variables.

The 2022 NQoLS is a cross-sectional study that included 15,148 adults from the general adult Norwegian population. No exclusion criteria were specified beyond the requirement that participants have a registered address, email, and/or phone number. The study assessed SRH and QoL through single- and multi-item measures across physical, psychological, and social domains. The psychometric evaluation included descriptive statistics, reliability testing, confirmatory factor analysis, and correlation analysis, followed by a network analysis to map how outcomes connect and cluster.

Measures generally demonstrated acceptable reliability and validity. Model fit for multi-item scales was generally adequate following minor modifications. Network analysis identified a central cluster, including the Satisfaction with life scale, Hopkins Symptom Checklist-5, and Satisfaction with psychological health. These indicators were highly connected and structurally central. In contrast, physical health variables, including Satisfaction with physical health, Pain and discomfort, and General health, were more weakly connected and positioned at the network periphery. The sensitivity analysis, stratified by language preference, yielded results consistent with those of the entire sample.

The NQoLS provides a foundation for mapping SRH and QoL. Most measures worked well, though a few could be fine-tuned for a better fit and sensitivity. Based on our assessment and the structure revealed by the network analysis, physical health appears to be relatively underrepresented in the current survey, suggesting a potential area for future enhancement.

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