Validity Evidence and Reliability of a Subjective Well-Being Scale: A Psychometric Network Analysis

8Citations
Citations of this article
36Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

The objective of the present research was to analyze the psychometric properties of a short scale of subjective well-being based on the metrics corresponding to the network models. A total of 3196 young people and adults between 18 and 56 years of age (mean = 25.88; SD = 8.81) from three cities in Peru were selected by non-probabilistic purposive sampling and divided into two phases: exploratory (n = 642) and confirmatory (n = 2527). The methodology used was network analysis to determine internal structure and reliability. Evidence in relation to another variable was explored by latent network modeling using Patient Health Questionnaire (PHQ-2) and Generalized Anxiety Disorder Scale (GAD-2) as convergence measures. The results reveal that the SWB is a unidimensional measure both in its exploratory phase by Exploratory Graphical Analysis (EGA) and confirmatory (CFI = 1.00; RMSEA = 0.00). The reliability obtained through structural consistency identified that 100% of the time only one dimension was obtained; in addition, the items were stable because they replicated within the empirical dimension in all cases. The relationship with the PHQ-2 (r = −.44) and GAD-2 (r = −.34) maintained the expected direction and strength. The current data lays the groundwork for future research on subjective well-being in Peru, particularly because we now have a quick, valid, and reliable measure that can contribute to the scientific literature on subjective well-being, which is an intriguing construct to investigate due to its association with basic human needs and the prevention of mental health problems in a community.

Cite

CITATION STYLE

APA

Ventura-León, J., Sánchez-Villena, A. R., & Caycho-Rodríguez, T. (2023). Validity Evidence and Reliability of a Subjective Well-Being Scale: A Psychometric Network Analysis. Trends in Psychology. https://doi.org/10.1007/s43076-022-00251-x

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free