Predicting Students' Quality of Life based on Self-differentiation, Mindfulness, and Social Intelligence

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Sara Dibazer, Zeinab Sabouri, Javad Nouri Sadegh, Saeed Bakhtiarpour

Abstract

The present study was conducted to predict the quality of life based on self-differentiation, mindfulness, and social intelligence in students of Ahvaz Islamic Azad University. For this study, 198 students were selected as the sample by the available sampling method. In collecting data, the World Health Organization (WHO) quality of life questionnaires - short form, awareness of Brown and Ryan's conscious mind, Tromso's social intelligence, and Scorne self-differentiation were used. Data analysis was performed using correlation methods. The results of the Pearson correlation coefficient showed a significant relationship between the variables of self-differentiation, mindfulness, and social intelligence with quality of life at the level of one percent. Multiple regression results showed that; there are multiple correlations of 0.449 between the predictor variables of self-differentiation, mindfulness, and social intelligence with quality of life. In the meantime, mindfulness, unlike self-differentiation and social intelligence, does not help to predict the quality of life. Also, no significant difference was observed between the predictive power of social intelligence and self-differentiation. In the final analysis, which was performed using MATLAB software and artificial neural network statistical test, the results showed that; The accuracy of quality of life prediction based on these three variables is equal to 0.63. This accuracy of prediction by the artificial neural network in comparison with the prediction made by multiple regressions indicates a more accurate prediction of the artificial neural network.

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