Using Non-linear Models for a Complexity Approach to Psychological Well-being

Using Non-linear Models for a Complexity Approach to Psychological Well-being Psychological well-being in adolescence is an increasing field of study. The literature identifies a large number of dimensions of psychological well-being. However, even when considering all these dimensions, the explanatory power of most models is rather low. Complexity theories can be a productive alternative, at the theoretical but especially the methodological level, to the limitations more traditional approaches to psychological well-being have. In this paper, we suggest a structural equation modelling approach to complexity that focuses on the non-linearity property. Given the large number of dimensions, the model is estimated in two steps as described by Jöreskog [(2000) Latent Variable Scores and Their Uses. Lincolnwood IL: Scientific Software International] First, a confirmatory factor analysis is fitted and Anderson and Rubin’s factor scores are saved. Then all possible products and squared terms of the factor scores are computed and are used as predictors of the dependent variable using an ordered logit model. The results from a sample of 968 Catalan adolescents show that a non-linear model including interaction effects among the eight dimensions, age and gender, has a higher explanatory power to predict satisfaction with life as a whole, compared to a linear model. Important consequences for the study of psychological well-being in adolescence emerge from the methodological procedure we have followed, which can be used to study any type of complex psychological and psychosocial phenomenon. Quality & Quantity Springer Journals

Using Non-linear Models for a Complexity Approach to Psychological Well-being

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Springer Netherlands
Copyright © 2006 by Springer Science + Business Media B.V.
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
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