Recent research has shown that cultural, linguistic, and sociodemographic peculiarities influence the measurement of trait emotional intelligence (trait EI). Assessing trait EI in different populations fosters cross-cultural research and expands the construct's nomological network. In mental health, the trait EI of clinical populations has been scarcely researched. Accordingly, the present study examined the relationship between trait EI and key sociodemographic variables on Trait Emotional Intelligence Questionnaire (TEIQue-SF) datasets with mental healthcare patients from three different Spanish-speaking countries. Collectively, these datasets comprised 528 participants, 23% from Chile (120), 28% from Peru (150), and 49% from Spain (258). The sociodemographic variables we used for trait EI comparisons were gender, age, educational level, civil status, and occupational status. Analyses involved Multigroup Exploratory Structural Equation Modelling (to test measurement invariance) and analysis of covariance (ANCOVA). Our results revealed significant between-country differences in trait EI across the studied sociodemographic variables and interactions between these variables. Measurement invariance across the datasets was attained up to the scalar level regarding gender and education (i.e., strong invariance), although analyses on age, civil status, and occupation displayed non-invariance. The resultant psychometric evidence supports the suitability of the TEIQue-SF for the accurate cross-cultural assessment of trait EI in mental health settings. It also highlights the importance of incorporating trait EI into extant psychotherapeutic frameworks to enhance non-pharmacological treatment efficacy.
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http://dx.doi.org/10.3389/fpsyg.2022.796057 | DOI Listing |
Reprod Health
January 2025
Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium.
Background: Over one-third of the global stillbirth burden occurs in countries affected by conflict or a humanitarian crisis, including Afghanistan. Stillbirth rates in Afghanistan remained high in 2021 at over 26 per 1000 births. Stillbirths have devastating physical, psycho-social and economic impacts on women, families and healthcare providers.
View Article and Find Full Text PDFAn Pediatr (Engl Ed)
January 2025
Stress and Health Research Group, Autonomous University of Barcelona, Barcelona, Spain.
Objective: To describe the perceived wellbeing (pWB) and the psychological characteristics of young people with life-limiting and life-threatening conditions (LLTCs).
Methods: We conducted a cross-sectional study in young people aged 8 years or older with collection of data on demographic and disease-related variables from the health records. In the psychological evaluation, we collected data on emotion regulation, cognitive strategies and risk of depression and anxiety, in addition to the assessment of the pWB through a visual analogue scale.
JMIR Ment Health
December 2024
Department of Psychiatry, Northwell Health, Zucker Hillside Hospital, Glen Oaks, NY, United States.
Background: Digital health technologies are increasingly being integrated into mental health care. However, the adoption of these technologies can be influenced by patients' digital literacy and attitudes, which may vary based on sociodemographic factors. This variability necessitates a better understanding of patient digital literacy and attitudes to prevent a digital divide, which can worsen existing health care disparities.
View Article and Find Full Text PDFJ Psychiatr Res
December 2024
Research Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdom; Anna Freud National Centre for Children and Families, London, United Kingdom.
Background: The present study examines the interplay between epistemic stance, attachment dimensions, and childhood trauma in relation to specific demographic factors and mental health outcomes. This study aims to understand how these factors form distinct profiles among individuals, to identify those at risk of mental health concerns.
Method: Latent Profile Analysis (LPA) was employed on a dataset from the general population (n = 500) to identify subgroups of individuals based on their epistemic stance (mistrust and credulity), attachment dimensions, and childhood trauma.
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