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Factors associated with anxiety among the Lebanese population: the role of alexithymia, self-esteem, alcohol use disorders, emotional intelligence and stress and burnout.

Sahar ObeidNathalie LahoudChadia HaddadHala SacreKassandra FaresMarwan AkelPascale R SalamehSouheil Allit
Published in: International journal of psychiatry in clinical practice (2020)
Objective: To assess factors associated with anxiety among a sample of the Lebanese population.Methods: A cross-sectional, conducted between November 2017 and March 2018, enrolled 789 participants. Anxiety was measured using the Hamilton Anxiety Scale. A cluster analysis was then performed with the identified factor scores to identify the different profiles of the participants.Results: A cluster analysis based on the three factors derived three mutually exclusive clusters, which form 29.62%, 34.54%, and 35.84% of all participants, respectively. The first cluster represented people in distress (low emotional intelligence, high depersonalisation, alcohol use disorder, burnout, stress, alexithymia and low self-esteem); the second one represented people with wellbeing (High emotional intelligence, low depersonalisation, low alcohol use disorder, low burnout, low stress, low alexithymia and high self-esteem), whereas cluster 3 represented people in between. Higher age (Beta  =  0.065) was significantly associated with higher anxiety, whereas being in cluster 2 (people with wellbeing) (Beta = -12.37) and cluster 3 (people in between) (Beta = -5.426) were significantly associated with lower anxiety compared to being in cluster 1 (people in distress).Conclusions: The findings of this study are overall consistent with those of epidemiologic community-based surveys and may help inform structural models of classification and prediction of anxiety disorders (ADs).
Keyphrases
  • sleep quality
  • alcohol use disorder
  • machine learning
  • deep learning
  • physical activity
  • data analysis