Prediction of Subjective Well-Being based on Mindfulness and Cognitive Flexibility in Nurses of Psychiatric Wards Using an Artificial Neural Network

نویسندگان

1 Department of Psychology, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran

2 Department of Psychology, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran

doi
10.22037/anm.v31i4.40094
چکیده

AbstractIntroduction: The mental health of the nurses is of utmost importance to accomplish the ideal goals of communities in terms of reducing financial and spiritual costs. The present study aimed to investigate the relationship between subjective well-being with mindfulness and cognitive flexibility in nurses of psychiatric wards of hospitals in Ahvaz city using an artificial neural network (ANN).Methods: This was a descriptive and correlational study. The statistical population of this study comprises all nurses of the psychiatric ward of hospitals in Ahvaz city, Iran, in 2022. Accordingly, 200 nurses were selected through convenience sampling. The research instruments included the Kentucky Inventory of Mindfulness Skills, the Subjective Well-being Scale, and the Cognitive Flexibility Inventory. The data were analyzed using descriptive and inferential statistics, Pearson correlation coefficient and simultaneous regression, and ANN.Results: The results suggested a positive and significant relationship between mindfulness and subjective well-being, and between cognitive flexibility and subjective well-being (P<0.001). Furthermore, the subjective well-being of nurses had multiple relationships with mindfulness and cognitive flexibility (P<0.001). Following the results of the ANN, cognitive flexibility demonstrated the highest estimation in predicting subjective well-being.Conclusions: Mindfulness and cognitive flexibility of nurses had a significant relationship with their subjective well-being. The results suggested the necessity to emphasize the appropriate methods of mindfulness and cognitive flexibility, which can be obtained by holding proper workshops and training programs.