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MEJDS (2020) 10: 245 |
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Tahamtan A, Kalhornia Golkar M, Haji Alizadeh K. Designing a Causal Model of Cognitive Emotion Regulation, Mental Health, and Alexithymia in Patients with Hypertension. MEJDS 2020; 10 :245-245
URL: http://jdisabilstud.org/article-1-2256-en.html
URL: http://jdisabilstud.org/article-1-2256-en.html
1- Department of Psychology, Kish International Branch, Islamic Azad University
2- Department of Psychology, Karaj Branch, Islamic Azad University
3- Department of Psychology, Bandar Abbas Branch, Islamic Azad University
2- Department of Psychology, Karaj Branch, Islamic Azad University
3- Department of Psychology, Bandar Abbas Branch, Islamic Azad University
Abstract: (1255 Views)
Background & Objectives: Physical disabilities may cause psychological problems, leading to exacerbated biological conditions. Stress, conflicts, and generalized anxiety disorder can affect most physical illnesses; some diseases are even further affected by such characteristics than others. Accordingly, hypertension is among the most essential causes of numerous internal diseases. The present study aimed to investigate the fitness of the causal model of Cognitive Emotion Regulation (CER) with mental health and emotional alexithymia in patients with hypertension. This study examined individuals with hypertension, high emotional disabilities, and the inability to control and express their emotions. Thus; they encountered physical injuries, like hypertension. Mental health is among the most crucial and effective factors in improving the condition of these patients. Therefore, identifying characteristics related to mental health and recognizing emotions in subjects with hypertension can help to make a significant contribution to improving their mental health and wellbeing. The present study aimed to model the relationship between CER, mental health, and alexithymia in patients with hypertension.
Methods: This correlational study used structural equation modeling. The statistical population included all patients with hypertension referring to healthcare centers in Shiraz City, Iran, in 2019. Among them, 480 patients were selected by the purposive sampling technique. The inclusion criteria of the study were an age range of 35 to 50 years, systolic blood pressure of ≥140 mmHg and diastolic blood pressure of 90 mmHg, at least one year of presenting hypertension, and literacy. Exclusion criteria were the existence of a serious medical illness, major psychiatric disorders, cognitive impairments, or weaknesses in the patient's cognitive function. The research tools included the General Health Questionnaire–28 (GHQ–28) (Goldberg and Hillier, 1979) and the Toronto Alexithymia Scale (TAS–20) (Bagby et al., 1994). To analyze the obtained data, we used descriptive statists, such as mean and standard deviation. To fit the model, we applied inferential statistics (correlation) and structural equation modeling. Pearson correlation coefficient method and structural equation modeling were employed to analyze the obtained data in SPSS, SmartPLS, and LISREL.
Results: The present research findings supported the research model and indicated that the direct path coefficient between the cognitive regulation of negative emotions and mental health was positive and significant (p<0.001, β=0.531). Besides, there was a negative and significant relationship between the cognitive regulation of positive emotions and mental health (p<0.001, β=–0.650). The direct path coefficient between the cognitive regulation of negative emotion and emotional alexithymia was positive and significant (p<0.001, β=0.672); there was a negative and significant difference between the cognitive regulation of positive emotion and emotional alexithymia (p<0.001, β=–0.430). Furthermore, the direct path coefficient between emotional alexithymia and mental health was positive and significant (p<0.001, β=0.834). The indirect relationship between the three variables (the relationship between the cognitive regulation of emotion & mental health mediated by alexithymia) was significant; the higher limit (0.4289) and the lower limit (0.3232) did not include a zero confidence interval for them. The final model fit indicators were as follows: Goodness of Fit Index (GFI)=0.92, Comparative Fit Index (CFI)=0.93, and Root Mean Square Error of Approximation (RMSEA)=0.079.
Conclusion: The present study results emphasized the need to use adaptive CER strategies to overcome emotional alexithymia and consequently improve mental health in patients with hypertension.
Methods: This correlational study used structural equation modeling. The statistical population included all patients with hypertension referring to healthcare centers in Shiraz City, Iran, in 2019. Among them, 480 patients were selected by the purposive sampling technique. The inclusion criteria of the study were an age range of 35 to 50 years, systolic blood pressure of ≥140 mmHg and diastolic blood pressure of 90 mmHg, at least one year of presenting hypertension, and literacy. Exclusion criteria were the existence of a serious medical illness, major psychiatric disorders, cognitive impairments, or weaknesses in the patient's cognitive function. The research tools included the General Health Questionnaire–28 (GHQ–28) (Goldberg and Hillier, 1979) and the Toronto Alexithymia Scale (TAS–20) (Bagby et al., 1994). To analyze the obtained data, we used descriptive statists, such as mean and standard deviation. To fit the model, we applied inferential statistics (correlation) and structural equation modeling. Pearson correlation coefficient method and structural equation modeling were employed to analyze the obtained data in SPSS, SmartPLS, and LISREL.
Results: The present research findings supported the research model and indicated that the direct path coefficient between the cognitive regulation of negative emotions and mental health was positive and significant (p<0.001, β=0.531). Besides, there was a negative and significant relationship between the cognitive regulation of positive emotions and mental health (p<0.001, β=–0.650). The direct path coefficient between the cognitive regulation of negative emotion and emotional alexithymia was positive and significant (p<0.001, β=0.672); there was a negative and significant difference between the cognitive regulation of positive emotion and emotional alexithymia (p<0.001, β=–0.430). Furthermore, the direct path coefficient between emotional alexithymia and mental health was positive and significant (p<0.001, β=0.834). The indirect relationship between the three variables (the relationship between the cognitive regulation of emotion & mental health mediated by alexithymia) was significant; the higher limit (0.4289) and the lower limit (0.3232) did not include a zero confidence interval for them. The final model fit indicators were as follows: Goodness of Fit Index (GFI)=0.92, Comparative Fit Index (CFI)=0.93, and Root Mean Square Error of Approximation (RMSEA)=0.079.
Conclusion: The present study results emphasized the need to use adaptive CER strategies to overcome emotional alexithymia and consequently improve mental health in patients with hypertension.
Keywords: Mental health, Cognitive emotion regulation, Emotional alexithymia, Patients, Hypertension.
Type of Study: Original Research Article |
Subject:
Psychology
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