Journal of Education and Health Promotion

Abstract Background: Although psychological factors are now recognized as playing a significant
and independent role in the development of coronary heart disease (CHD) and its
complications, many of these factors are correlated with each other. The present study is
aimed at examining the association between alexithymia and anxiety depression, stress,
quality of life, and social support in CHD patients. Materials and Methods: In this research
398 patients with coronary heart disease (166 females and 232 males) from the city of
Isfahan were selected using random sampling. The tools used included depression, anxiety,
and stress scale (DASS-21), Health-related to Quality Of Life (HRQOL-26), Multiple Scale
Perceived Social Support (MSPSS-12), and the Toronto Alexithymia Scale (TAS-20). The data
were analyzed using structural equation modeling by using the Statistical Package for Social
Science (SPSS21) (IBM Corp: Armonk, New York.U.S.) and Asset Management Operating
System (AMOS21) SPSS, an IBM Company: Chicago, U.S. Software. Results: Results of
the structural equation model showed an acceptable goodness of fit, for the explanation
alexithymia that was significantly associated with lower HRQOL and social support and
increasing anxiety, depression, and stress. Conclusions: Alexithymia may increase anxiety,
depression, and stress and can be a predisposing factor to poorer HRQOL and social
support.

Abstract Background: Considering the significance of quality of life in chronic diseases and the role of
education in its improvement, this study was performed to investigate the effect of cognitivebehavioral therapy on improving the quality of life of cardiovascular patients in Isfahan city.
Materials and Methods: In this experimental study, 56 patients, who referred to Chamran
Hospital and Isfahan Cardiovascular Research Center, were randomly selected and assigned
to two groups, i.e. experiment and control. The experiment group was trained in eight sessions, each session taking 2 hours. Both groups received MacNew quality of life questionnaire
before and 2 weeks after treatment. Some demographic data were also gathered along with
the questionnaire. Data were analyzed by SPSS software using statistical tests such as independent t-test, Chi-square, and analysis of covariance. Results: Observing the possible effect
of pre-test, cognitive-behavioral therapy had a significant effect on the total score of quality
of life and its three subscales. Conclusion: It seems that along with other medical therapies,
making use of cognitive-behavioral intervention is an appropriate method for improving the
quality of life of cardiovascular patients.