Diego Díaz Milanés
Lecturer
Research Interests
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About
Diego Díaz Milanés is a Lecturer at Universidad Loyola Andalucía in Spain. His research areas focus on mental health, wellbeing for veterans and first responders, and psychometric evaluations. Recent publications include evaluations of coercion in psychiatry, the integration of community-based mental health systems, and the impact of interventions on mental health services across various countries. His work employs network analysis and assesses care model implementations in both local and international contexts.
Articles (10)
Year:
2025
Year:
2025
Year:
2025
Year:
2025
Year:
2025
Introduction: The psychometric properties of the Satisfaction With Life Scale (SWLS) have been evaluated across numerous languages and population groups, primarily from a factor analysis perspective. In some studies, inconsistencies in structural invariance have been identified. Objective: This study aims to analyze the properties and gender invariance of the SWLS from a network analysis perspective. Method: A total of 857 Spanish university students were obtained through a stratified random cluster sampling method in a cross-sectional survey design study. Descriptive analysis of the items, partial-correlation network, Bayesian network model estimation, and invariance analysis by gender were conducted. Results: The instrument did not exhibit any floor or ceiling effects. Each item can be considered univariately normally distributed, and all items clustered in a single and stable community. The partial-correlation network model and centrality measures were stable in the full sample and invariant across genders. Item 3 emerged as the most central node in the network with the highest predictability. The Bayesian network indicated that items 2 and 4 initiate the process, while item 5 acts as the sink, and items 1 and 3 act as mediators. Conclusions: The SWLS can be used as a unidimensional measure, and the total score and relationships among items are stable and reliable. Any potential differences among genders cannot be associated with the functioning of the instrument. The predictability of every item was high, and the Bayesian network clearly identified different roles among the items.
Year:
2024
Year:
2024
Year:
2024
Year:
2024
Year:
2023
Collaborators (6)
Nerea Almeda
PhD, Assistant Professor
Universidad Loyola Andalucía
Luis Salvador-Carulla
University of Canberra
Montserrat Andrés Villas
Profesor Contratado Doctor
Universidad de Huelva
Santin Vilariño
Profesora Titular
Universidad de Huelva
Sue Lukersmith
University of Canberra
Pedro Juan Pérez-Moreno
Universidad de Huelva
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