Authors
1
Professor, Department of Clinical Psychology, Faculty of Psychology and Educational Sciences, Kharazmi University, Tehran, Iran.
2
Associate Professor of Clinical Psychology, Department of Psychology, Kharazmi University, Tehran, Iran
3
Assistant Professor of Clinical Psychology, Department of Psychology, Kharazmi University, Tehran, Iran
4
Ph.D. student of Health Psychology, Department of Psychology, Kharazmi University, Tehran, Iran
Abstract
Abstract
Introduction: The purpose of this study was to model the structural relationships between executive functions and psychological flexibility and beliefs of disease in adaptation to disease and psychological health in cardiovascular patients.
Materials & Methods: The design of this study was correlation using structural equation model. The statistical population of the present study was people with cardiovascular disease (coronary artery disease) referred to Shahid Gholipour Hospital in Bukan. The sample size was 300 people selected by purposeful sampling. To collect the data, a defect questionnaire was used in Barclay executive functions, health beliefs questionnaire, acceptance and practice questionnaire, cognitive blend questionnaire, psychological adjustment with sickness scale, and Psychophysical Health Scale. Structural equation modeling was used to analyze the data using the least squares and minor components. The data were analyzed using the second version of SmartPLS software.
Results: The results of the measurement model of each of the variables showed that some of the markers had a weak factor load on their current variables and, therefore, they were discarded from the model and the model was re-tested. In the structural model section, the results also showed that the predicted variables (Executive functions, psychological flexibility, and beliefs of the disease) are able to explain 51% of variance of disease-compatible and 33% mental health; variables that predict functional functions and psychological flexibility can predict 60% of disease beliefs among cardiovascular patients.
Conclusion: Finally, the analysis of structural equations showed that latent variables of prediction (executive functions, psychological flexibility and disease beliefs) are capable of explaining 51% of variance of disease compatibility; in addition, predictive variables (executive functions, psychological flexibility and beliefs of disease ) Has the ability to predict 33% mental health, and the variables predicting functional functions and psychological flexibility can predict 60% of the beliefs of the disease among cardiovascular patients. These findings indicate that the model is capable of explaining a relatively high percentage of variance of intrinsic latent variables.
Keywords
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