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Personality and gender prototypes for predicting health: a multilevel and cluster analysis.

Sara Esteban-GonzaloJuan Carlos Fernández-GonzaloJuan Luis González-PascualCarmen Bouzas-MosqueraLaura Esteban-Gonzalo
Published in: Archives of women's mental health (2023)
Prior studies have identified that mentally healthy people tend to share common characteristics and common ways of coping with stressful life events; they show similar patterns of behavior and more flexible and adaptive social roles. The objectives of the study are to assess the influence of personality factors on gender roles and mental health, to identify personality patterns along with gender roles, and to assess the influence of the patterns identified on mental health. Data collection from a sample of 795 university students was carried out during 2019. Multilevel analyses tested the associations between gender (BSRI) and personality (TIPI) and between personality and health -mental health (GHQ12) and wellbeing (MHC-SF). Cluster analysis explored tendencies of gender and personality, and each cluster showed different health patterns. Individuals with high scores in extraversion, conscientiousness, emotional stability, openness to experience, and very high agreeableness score, as well as high femininity and masculinity scores, presented a decreased psychological morbidity (β= -3.62, 0.57 (SE), p<0.001) and an increased well-being (β=7.68, 1.15 (SE), p<0.001). The most relevant indicators of mental health were identified in androgynous individuals, those individuals with high scores in masculinity and femininity, as well as high scores in extraversion, openness to experience, emotional stability, agreeableness, and conscientiousness.
Keyphrases
  • mental health
  • mental illness
  • public health
  • social support
  • machine learning
  • depressive symptoms
  • social media
  • health information
  • climate change
  • artificial intelligence
  • big data