Four scales measuring mental wellbeing in the Nordic countries : do they tell the same story? - Aarø, Leif Edvard; Smith, Otto Robert; Damsgaard, Mogens Trab; Fismen, Anne-Siri; Knapstad, Marit; Lyyra, Nelli; Samdal, Oddrun; Thorsteinsson, Einar Baldvin; Eriksson, Charli (BioMed Central, 2025)
Background Mental wellbeing is an important focus in surveys among adolescents. Several relevant instruments are available. In the Nordic part of the Health Behaviour in School-aged Children (HBSC) study 2022, four different scales for the measurement of wellbeing, were employed: Cantril’s Ladder, the WHO-5 Wellbeing Index, the seven-item Short Warwick-Edinburgh Mental Wellbeing Scale (SWEMWBS), and the HBSC Health Complaints Scale. This study aims to examine statistically to what extent these scales overlap or measure distinctly different aspects of mental wellbeing. Methods Data stem from the Nordic part of the HBSC 2022 study (n = 28 189). In all statistical analyses, data are weighted to ensure equal representation of genders, age groups (ages 11, 13, and 15 years), and countries (Denmark, Finland, Iceland, Norway, Sweden). Adjustments were made for cluster effects (school classes). The statistical analyses included factor analysis, general linear modeling, variants of latent variable analysis, and structural equation modeling including bifactor modeling. Results Exploratory factor analysis produced three factors corresponding well to the three multi-item instruments, with the single item Cantril’s ladder loading on the factor defined by the WHO-5 Wellbeing Index. Confirmatory factor analysis produced good fit for a model with one factor consisting of the three positively worded scales and a separate factor for health complaints, but with a high negative correlation between the two factors. Analyses of each of the four scales against gender, age, and 16 other covariates, showed strikingly similar patterns of associations. In an analysis based on a hierarchical model, adjustments for the general mental wellbeing (second-order) factor reduced associations between the first-order factors (one for each scale) and covariates substantially. Latent variable and bifactor modeling confirmed that most of the covariance among all items from all scales combined was captured by one general dimension. Information curve ...