|Year : 2019 | Volume
| Issue : 2 | Page : 63-71
Modeling of cardiac function of patients with acute myocardial infarction based on Type-D personality: Mediating role of negative emotions
Marzieh Mohammadi Pashaki, Yarali Dousti, Bahram Mirzaian
Department of Clinical Psychology, Sari Branch, Islamic Azad University, Sari, IranDepartment of Clinical Psychology, Sari Branch, Islamic Azad University, Sari, Iran
|Date of Submission||04-Dec-2018|
|Date of Acceptance||07-Jan-2019|
|Date of Web Publication||31-May-2019|
Dr. Yarali Dousti
Department of Clinical Psychology, Sari Branch, Islamic Azad University, Sari
Source of Support: None, Conflict of Interest: None
Context: Cardiac function of patients with acute myocardial infarction (MI) plays a central role in their prognosis.
Aims: The purpose of this study was to model the cardiac function of these patients based on Type-D personality and the mediating role of negative emotions (anger, depression, and anxiety) in this relationship.
Setting and Design: This correlational study was performed using the structural equation modeling method, and specifically the regression equations (combination of path analysis and second-order factor analysis).
Material and Methods: The study population was the patients with acute ST-segment elevation MI (STEMI) who were hospitalized at Mazandaran Cardiovascular Hospital and underwent under primary percutaneous coronary intervention treatment in 2017 and 2018. Using Mueller's formula modeling formula (1996) based on a sample size-to-free parameter ratio, the sample size was calculated to 220 patients were chosen by the purposive method. Data were collected using Denollet'sType-DScale-14, the Spielberger's state-trait anxiety inventory, short-form of the beck depression inventory-13, and Spielberger's state-trait anger expression inventory-2.
Statistical Analysis Used: Data analysis was performed using SPSS-18 and AMOS 23.
Results: Type-D personality can directly predict of the cardiac function of patients with acute STEMI. This variable also predicts the the cardiac function of these patients via the mediation of negative emotions (anger, depression, and anxiety).
Conclusion: Type-D personality affects the incidence and prognosis of myocardial infarction via negative emotions. It is, therefore, recommended to screen the susceptible populations for this personality type.
Keywords: Heart function test, Myocardial infarction, Negative emotions, Type-D personality
|How to cite this article:|
Mohammadi Pashaki M, Dousti Y, Mirzaian B. Modeling of cardiac function of patients with acute myocardial infarction based on Type-D personality: Mediating role of negative emotions. J Nurs Midwifery Sci 2019;6:63-71
|How to cite this URL:|
Mohammadi Pashaki M, Dousti Y, Mirzaian B. Modeling of cardiac function of patients with acute myocardial infarction based on Type-D personality: Mediating role of negative emotions. J Nurs Midwifery Sci [serial online] 2019 [cited 2020 Jul 8];6:63-71. Available from: http://www.jnmsjournal.org/text.asp?2019/6/2/63/259498
| Introduction|| |
Cardiovascular diseases (CVDs) are the leading cause of death in most countries, including Iran. According to the estimates of the World Health Organization, this group of diseases will be the main cause of mortality worldwide in 2020., Myocardial infarction (MI) is one of the major causes of hospitalization, disability, and death that 17.9 million people die each year from CVD, an estimated 31% of all deaths worldwide. >75% of CVD deaths occur in low-income and middle-income countries. Nearly 85% of all CVD deaths are due to heart attacks and strokes. Furthermore, 50% of all deaths per year and 79% of deaths related to chronic diseases are attributed to CVD., Acute MI is universally considered an emergency condition. An ischemic injury in a significant portion of the myocardium that impairs left ventricular pumping is the single most important predictor of mortality following ST-segment elevation MI (STEMI)., The typical emergency medical procedures for limiting the impacts of MI and preventing damage to the myocardium include thrombolytic treatment and balloon angioplasty and stenting.
The incidence of CVDs cannot be fully explained by known biological factors, as psychological and personality factors also play direct and indirect roles in the development and exacerbation of these diseases.,
Given the possible relationships between personality traits and diseases, the role of personality in health has been the subject of many scientific studies. Some of these studies have managed to identify personality traits that make a person more susceptible to certain diseases. Scientific evidence suggests that in the general population, there is a high correlation between well-being and depression, mental disorders, life stress, and introversion, which make people, especially more susceptible to CVDs.
Personality is a set of relatively stable and unique characteristics that distinguish one person from another. In the late 1950s, some theoreticians (Friedman and Rosen man, 1959) hypothesized the role of Type-A personality in the development of coronary heart disease. But subsequent studies showed that the characteristics of Type A personality cannot successfully predict the incidence of this condition. In the late 1990s and early 2000s, Denollet theorized a new personality type called Type-D personality, which revealed a stronger relationship between heart disease and personality traits. It is reported that people with Type-D personality have four times higher risk of ischemic heart disease and consequent mortality than people with lower levels of negative affectivity and social inhibition and that this is independent of the traditional biomedical risk factors.,,
Type-D personality is defined as the combination and interaction of two broad personality traits: negative affectivity and social inhibition.,, People with negative affectivity and social inhibition often suffer from depression, chronic stress, anger, pessimism, low social support, and generally poor health level.,,,, In general, this discussion is closely related to emotion, which refers to a mental feeling that affects and is affected by our thoughts, behaviors, and physiology. By strengthening negative emotions, Type-D personality leads to elevated stress and cortisol levels, which when combined together, impact the heart negatively. The invoked emotion also increases the activity of the autonomic system and affects the severity of coronary artery stenosis.,
For MI patients, the negative affectivity dimension of Type-D personality predicts disability and low quality of life, the latter of which predicts mortality in these patients. However, since not all studies have found a relationship between the Type-D personality and the risk of CVDs, there is a need for more research in this area. Although many studies in Western countries have confirmed the relationship between Type-D personality and the occurrence of cardiac problems, this relationship must be further examined in other countries.
Anger, anxiety, and depression in MI patients can exacerbate cardiac complications such as heart function impairment, increased blood pressure and heart rate, dysrhythmia, ischemia and heart failure, recurrence of heart attacks, and even high mortality rate.,,,
Anger is associated with more than twice higher rate of acute MI and 1.25 times higher rate of mortality due to this condition, especially in the first 3 years after the incident. Depression and anxiety are generally associated with MI, especially at the ages of over 50, and increased morbidity and mortality resulting from this condition., The prevalence of depression and anxiety among coronary heart disease patients generally ranges from 10% to 50%. In a meta-analysis of 12 studies and 5750 MI patients, it was reported that anxiety was associated with a 36% increase in the risk of CVD and mortality. In another study, Murphy et al. reported that mild depression in the hospital and a moderate to severe 2-month depression predict mortality of patients with acute MI in the next 12 years.
Although the role of psychological factors in coronary heart disease has recently received more attention, the major factors that influence the prognosis of heart disease are still not well known. For example, while some researchers have found that anger increases the risk of coronary heart disease, others have reported that anger is a protective factor., Nevertheless, it is believed that negative emotions (such as anger) are not risk factors by themselves and coping and adaptation strategies are also important in this respect. It should also be noted that the prognosis of MI is also influenced by the extent of heart attack and the number of vessels involved. It can, therefore, be concluded that more research is still needed to ascertain the role of emotions on the cardiac function of patients in the acute MI phase. Although the association of psychological factors and coronary heart disease has been extensively researched using correlational, causality-comparative and other approaches, the present study tried to use the method known as structural equation modeling (SEM) for this purpose. Given its objective, this study falls in the category of fundamental research and may contribute to the formation of a basis for a broader theory regarding the psychological consequences of MI and better prevention and treatment strategies for limiting the health implications of this relationship.
In this fundamental research, data collection was performed by the use of a cross-sectional method and data analysis was carried out using a descriptive method of correlational type based on SEM, and specifically the regression equations (combination of path analysis and second-order factor analysis). The analysis was performed using the covariance-based variant of SEM (CB-SEM) in the software AMOS 23. This method can estimate the path coefficients and factor loadings by minimizing the difference between the sample-based and model-based covariance matrices. Furthermore, Baron and Kenny's method was used to investigate the inter-variable correlations, the effect of exogenous variables on mediating variables, he effect of mediating variables on endogenous variables, and finally, the mediation relationship between exogenous and endogenous variables.
The population of this study was the patients with acute STEMI who were admitted to the emergency department of Sari Fatemeh-Zahra Hospital (Sari, Iran) and Mazandaran Cardiovascular Hospital (Sari, Iran) in 2017–2018 and underwent primary percutaneous coronary intervention (PCI) treatment.
Inclusion criteria were as follows:
- Patients aged 30–65 years who were diagnosed with acute STEMI and had undergone primary PCI. STEMI diagnosis criteria were: high ST-segment elevation, elevated level of cardiac enzymes, and clinical presentation of angina pectoris and angiography determined coronary artery stenosis >50%
- Having at least a minimum level of literacy (reading and writing) to fill out questionnaires.
Exclusion criteria were:
- Failure to complete the questionnaire
- Patient's withdrawal from the research
- Presence of physical disorders
- Presence of psychological and mood disorders.
The sample size was determined using Mueller's modeling equation modeling method (1996) based on a sample size-to-free parameter ratio of 10. In this method, in terms of the number of path coefficients and factor loads, a factor of at least 10 is considered. In this research, taking into account the number of 7 path coefficients, 14-factor factors, 21 parameters were multiplied by 10, and the number of 220 samples was estimated. The ethics committee at Islamic Azad University provided ethics approval for the study with the code IR.IAU.SARI.REC.1397.027.
The study was performed through the following procedure. First, the case files of patients hospitalized in the coronary care unit (CCU) were reviewed to identify patients aged 30–65 years who were diagnosed with STEMI and had undergone primary PCI. Data collection instruments chosen for this study were the Type-DScale-14 (DS14), Spielberger's state-trait anxiety inventory (STAI), short-form beck depression inventory (BDI-13), and Spielberger's state-trait anger expression inventory-2 (STAXI-2). Before administering the questionnaires to the eligible patients, inclusion and exclusion criteria were checked by extracting demographic information from patients' records and also by direct examination. The extent of coronary artery involvement was determined from the angiographic report. The participants were explained how to fill out the questionnaire and asked to respond to all questions. The ejection fraction recorded in the echocardiographic report was considered as the measure of cardiac function. Data analysis was performed in SPSS 18 and AMOS (IBM, california, America).
DS14 is a 14-item scale developed in 2005 by Denollet. This scale consists of two subscales: negative affectivity and social inhibition. This scale enjoys high reliability. Specifically, this scale is shown to have a test re-test reliability of 0.81 and a Cronbach Alpha of 0.86 (in Belgium). In terms of validity, it is reported that the negative affectivity subscale has a 0.75 correlation with neuroticism, the social inhibition subscale has a −0.61 correlation with extraversion, a −0.40 correlation with conscientiousness and a 0.50 correlation with neuroticism, all at 0.001 significance level.
According to the studies conducted in Iran, the internal consistency of the negative affectivity and social inhibition subscales in this country is, respectively, 0.77 and 0.90 and their Cronbach's alpha is, respectively, 0.79 and 0.56. The overall Cronbach's alpha of DS14 in Iran is reported to be 0.83.
This scale has been developed based on a five-point Likert scale with responses: False, Rather False, Neutral, Rather true, and true, which have a score of 0, 1, 2, 3, and 4, respectively. The total score of DS14 ranges from 0 to 56, with scores closer to 56 showing that the respondent as a Type-D personality.
Short-form beck depression inventory-13
The initial BDI was first introduced by Beck et al. in 1961. The short-form BDI-13 consists of 13 self-report statements expressing the specific symptoms of depression that measure the severity of this condition (from no depression to severe depression) in the respondent. In a study conducted by Rajabi in Iran, the Cronbach's alpha and the split-half reliability of this inventory were, respectively, 0.89 and 0.87, and the coefficient of correlation between the short form and the 21-item form of the inventory was 0.67.
In BDI-13, responses are arranged based on a 4-point Liker' scale ranging from zero to 4, and the overall score is the sum of all scores given to every statement. The total score of BDI-13 ranges from 0 to 39 and is interpreted as follows:
- 0– 04 : No depression
- 7– 05 : Mild depression
- 8– 15 : Moderate depression
- 16– 39 : Severe depression.
Spielberger's state-trait anger expression inventory-2
Developed by Spielberger in 1985, STAXI is a 57-item inventory consisting of six scales and five sub-scales with questions organized in three sections. Their liability assessments of STAXI-2 have reported an alpha of over 0.84 for state anger and trait anger scales and subscales and an alpha of over 0.73 for anger-in, anger-out, anger control, and the general anger expression index. The first section of the inventory, titled “how I currently feel,” measures the degree of anger felt by subjects on a four-point scale with responses ranging from “not at all = 1” to “Extremely = 4”. This section contains 15 items and includes the state anger scale (S-Ang) with three sub-scales: 1-Feeling Angry (S-Ang/F), 2-feeling expressing anger verbally (S-Ang/V), and 3-feel like expressing anger physically (S-Ang/P).
The second section, titled “how I generally feel,” has 10 items devoted to measuring anger trait, which are scored as in the first section. The anger trait scale (T-ang) has two sub-scales: 1-angry temperament (T-Ang-T) and 2-angry reaction, (T-Ang-R).
The third section, titled “how I generally behave or react when I am angry” measures the respondent's control over anger and consists of 32 items in four subscales: 1-anger expression-out (AX-O), 2-Anger Expression-in (AX-I), 3-anger control-out (AC-O), and 4-anger control-In (AC-I). The responses of this section are arranged based on a 4-point scale ranging from “almost never = 1” to “almost always = 4.”
Among Iranian researchers, Khodayari Fard et al. have confirmed the validity and reliability of STAXI-2, reporting an internal consistency of 0.60–0.93, a split-half coefficient of 0.57–0.89, and a re-test coefficient of 0.72–0.93 for its scales and sub-scales.
In a study by Navidi, (2006) where they investigated the validity of STAXI-2 and general health and adjustment questionnaire on 170 male high school students, they reported a Cronbach's alpha of 0.88 for state anger and 0.85 for trait anger and average alpha of 0.71 for anger control, anger expression, and general anger expression index. All of these coefficients were statistically significant, demonstrating the satisfactory internal consistency of the scales and subscales in the studied population.
Spielberger's state-trait anxiety inventory
Developed by Spielbergerin 1970, STAI consists of 40 questions, half of which measure state anxiety and the other half measure trait anxiety. For the state anxiety questions, the responses are designed based on a 4-point scale and include: Not at all, somewhat, moderately, and very much so. The responses of the trait anxiety questions, which are also based on a 4-point scale, include: almost never, sometimes, often, and almost always. This inventory provides two scores, each ranging from 20 to 80, which quantify the respondent's condition in terms of state anxiety and trait anxiety.
Spielberger et al. (1970) have reported a Cronbach's alpha of 0.92 and 0.90 and a test–retest reliability of 0.62 and 0.68 for state anxiety and trait anxiety subscales, respectively. In a study on 219 patients with generalized anxiety disorder and major depressive disorder and normal people, Cronbach's alpha of state anxiety and trait anxiety subscales were reported to be 0.92 and 0.90, respectively.
In STAI, all items are scored from 1 to 4, but those items that measure the absence of anxiety are scored inversely. The total score of STAI is interpreted as follows:
- 20– 29 : No or low anxiety
- 30– 49 : Moderate anxiety
- 50– 69 : Relatively high anxiety
- 70– 80 : High anxiety.
| Results|| |
After checking the statistical assumptions using the skewness, kurtosis test, Box, and Kolmogorov–Smirnov tests and removing the outlier data using the Mahalanobis test, 201 samples were cleared for final analysis. After establishing the normality of data, the validity of the measurement model for the research variables was also checked and verified. For all subscales of Type-D personality in negative affectivity (anger, depression, and anxiety), the average variance extracted (AVE) were >0.5, indicating the presence of convergent validity. In the investigation of construct validity, the obtained values were found to be greater than the standard value (0.07), thus confirming the AVE and construct reliability of the questionnaire.
As the results presented in [Table 1] show, a significant positive correlation at (0.01 significance level) was found between Type-D personality, negative affectivity (anger, depression, and anxiety) and cardiac function [Table 1].
|Table 1: Mean, standard deviation, and correlation of Type-D personality, negative affectivity (anger, depression, and anxiety) with cardiac function|
Click here to view
As shown in [Table 2], RMSEA was calculated to 0.048 (<0.1), indicating that the model is acceptably accurate. Furthermore, the ratio of the Chi-square to the degree of freedom was 2.911 (within 1–3 range), and goodness-of-fit index, comparative fit index, and normalized fit index values were almost equal and all >0.9, which signified the fitness of the measurement model for the research variables [Table 2].
According to [Table 3], Type-D personality, negative affectivity (anger, depression, and anxiety) have a direct effect on cardiac function [Table 3].
|Table 3: Estimation of direct effects (paths) using the maximum likelihood method|
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As shown in [Table 4], the standardized β, nonstandardized b, and R2 values obtained for the considered indirect paths using the bootstrap method indicate that Type-D personality has a significant indirect effect on cardiac function via negative affectivity (anger, depression, and anxiety) [Table 4].
|Table 4: Estimation of indirect effects (paths) using the bootstrap method|
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Note: To incorporate the latent variables into the final model, there should be multiple indicators for each variable. It is common to use subscales of the measures as independent indicators of the construct, but in cases where there are no multiple subscales for a particular construct, one can use the item parceling method introduced by Russell, Kahn, Spoth, and Altmaier (1998). In this study, this method was used to analyze the variables of depression, personality type D and cardiac function with respect to single variability in order to improve the overall variance of the model according to the Russell method in the hidden variable [Figure 1].
|Figure 1: The final model of the tested paths and standardized statistics for the prediction of cardiac function by Type-D personality with the mediation of negative affectivity (anger, depression, and anxiety)|
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| Discussion|| |
The purpose of this research was to estimate the SEM of the relationship between Type-D personality and cardiac function of patients with acute MI as mediated by negative affectivity (anger, depression, and anxiety). According to the final model, Type-D personality predicts of changes in the cardiac function of patients with acute MI. After investigating the role of Type-D personality and negative affectivity (anger, depression, and anxiety) in the prediction of cardiac function in the patients, coefficient of determination for their role in the variance of cardiac function was calculated to 0.03, 0.06, 0.09, and 0.17, respectively. For the indirect path of Type-D personality toward cardiac function through negative emotions of anger, depression, and anxiety, the coefficient of determination (R2) was calculated to 0.15, 0.12, and 0.24, showing that cardiac function of the patients is also influenced indirectly via these emotions. These results are consistent with the other findings.,,,,,,,,,
Personality can be considered as distinct patterns of thinking, emotion, and behavior that characterize each individual's interaction with the physical and social environment. There are only a few aspects of human activity that does not reflect personality and everything that a person has or will attain, including its general health, is influenced by his own personality and the personality of others with whom he has interaction. Personality types provide a model for assessing how a person behaves and thinks. Each personality type has certain features and attributes that can help the person overcome problems and cope with the environment. The personality type of interest to this study is Type-D personality, the theoretical basis of which originates from a study of heart patients in Belgium, where the role of personality traits on the outcomes was investigated.
The results of the present study in regard to the effect of Type-D personality on cardiac function can be explained as follows. Regarding the mechanism of the effect of Type-D personality factors (social inhibition and negative affectivity) on cardiac function, it can be argued that the effects of these components on the cardiac system are involved. Experiencing a negative emotion stimulates the sympathetic nervous system, and this state of arousal lingers as long as the emotion is unexpressed, which if persistent can undermine cardiac output and hence cardiac function.,,
Type-D personality is a good predictor of physical-psychological outcomes. This personality type is also known to be associated, via lifestyle, with the biological causes of coronary heart disease (blood pressure, blood lipid level, and tobacco use) and therefore the severity of coronary artery stenosis.,, It is also shown that MI patients who have a Type-D personality have a lower quality of life.,
The results of this study showed that Type-D personality affects cardiac function via the mediation of negative affectivity (anger, anxiety, and depression). In the explanation of this result, it can be argued that emotions can negatively affect the cardiac function by affecting the hypothalamic-pituitary-adrenal axis and increasing catecholamines, heart rate, vasoconstriction, and blood pressure.,,, A study by Faramarzinnia and Beshatat has shown that anxiety and anger have a significant positive relationship with chronic hypertension. In a study by Merswolken et al. on patients with MI, anxiety was reported to be a predictor of cortisol secretion, which is known to damage the vessel wall by activating the immune system and triggering inflammatory responses. Depression is also shown to be a predictor of 12-year mortality in patients with MI. It is believed that negative emotions affect the prognosis of coronary heart disease via psychological factors such as quality of life and coping styles., The study of Merswolken et al. on the effect of anxiety in the elevation of cortisol secretion in patients with MI, the study of Rost et al. (2012) on the effect of anxiety on the mortality of these patients, the study of Murphy et al. on the effect of depression on the mortality in stroke patients, the study of Wrenn et al. (2013) on the effect of anger and anxiety on the mortality and survival rate of patients with acute MI, and the study of Vanbeec et al. (2016) on the effect of anxiety on the prognosis of cardiac arrest, new cardiac events, and mortality due to MI all have confirmed the existence of associations investigated. There are some differences between these studies and the present work. In the study of Murphy et al. for example, only the women with MI who had undergone coronary artery bypass graft surgery were investigated, so there ported mortality figures can be influenced by gender and surgery implications. Furthermore, while the above studies have investigated the simultaneous effect of one or two emotions on the mortality of MI patients, the present study examined the effect of three emotions on cardiac function of patients with acute MI. It is also notable that most of the mentioned studies have used correlational or causal-comparative approach, but the present study used the method known as SEM.
The findings of this study could be of use to general health professionals, health psychologists, cardiologists, and CCU nurses. Identification of factors that influence coronary heart disease and cardiac function can also contribute to the development of interventions for improving the cardiac function in general and the prognosis of patients with acute MI in particular.
The notable limitation of this research was the use of self-report instruments, which were too long and too difficult to complete given the physical condition of our patients. Hence, future studies are suggested to adopt a prospective strategy and approach the patients later during or after the recovery.
| Conclusion|| |
Given the physiological components of emotion and involvement of the sympathetic nervous system in this matter, cardiac function can be affected not only by the pathophysiology of MI but also indirectly by psychological factors. Since the prognosis of MI depends on cardiac function, hospitals are recommended to broaden their approach beyond a narrow focus on purely medical treatment by paying closer attention to the psychological health of the patients suffering from MI.
Conflicts of interest
There are no conflicts of interest.
Marzieh Mohammadi Pashaki Introduction author and Original researcher, Yarali Dousti Methodologist, Bahram Mirzaeiyan Discussion author.
Financial support and sponsorship
We would like to thank the patients and their families, at the heart center Hospital of the Mazandaran University of Medical Sciences, Sari/Iran.
| References|| |
Mousa Farkhani A, Baneshi R, Zolali F. Survival of patients with acute myocardial infarction and its effective factors. Med J Mashhad Univ Med Sci V 1392;57:636-46.
Rahimzadeh M, Kavehei B. Short-term survival rate after myocardial infarction in Iran: Systematic review and meta-analysis. JAMS 2017;20:57-67.
Ebrahimi K, Salarilak S, Khadem Vatan K. Determining the health burden of a cardiac event. TUMJ 1396;3:208-18.
Samawat T, Hojatzadeh A, Shams M. The Ways of Prevention and Control of Cardiovascular Diseases. Specialized Government Employees. Tehran: Javan; 2011.
Bravis V, Kaur A, Walkey HC, Godsland IF, Misra S, Bingley PJ, et al.
Relationship between islet autoantibody status and the clinical characteristics of children and adults with incident type 1 diabetes in a UK cohort. BMJ Open 2018;8:e020904.
Longo D, Fauci A, Kasper D, Hauser S, Jameson J, Loscalzo J. Harrison's Principles of Internal Medicine: Cardiovascular Diseases. 18th
ed. Translated by Ghodarzian HR, Khodaie M, Razaghi S. Tehran: Arjomand Publication; 2012.
Sarafino EP. Health Psychology: Biosychological Introduction. Translated by Ahmadi Abhari SA, Eftekhar Ardebili H, Jazayeri A, Shafiei F, Ghavamian P, Garmaroudi GR. Tehran: Roshd; 2015.
KhademVatani K, Aga Khani N, EsmHosseini Gh.R, Hazrati A, Alinejad V, Nazari H. Relationship between spiritual health and anxiety and depression in patients with myocardial infarction admitted to SeyyedAlshohada Hospital of Urmia University of Medical Sciences. Urmia Med J 2014;25:1092-101.
Kramer GP, Bernestine DE, Perez V. Introduction to Clinical Psychology. 9th
ed. Translated by Firozbakht M. Tehran: Arasbaran; 2009.
Moradi K, Agha Yusefi AR, Alipour A, Bahrami B. Comparing the features of stress, coping strategies, personality traits, and personality traits in patients with multiple sclerosis and normal people. Q J Clin Psych Pers 1395;14:99-109.
Annagur BB, Demir K, Avci A, Uygur OF. Impact of a type D personality on clinical and psychometric properties in a sample of Turkish patients with a fi rst myocardial infarction. J PsychiatrPract 2017;23:3-10.
Schultz DP, Schultz SA. Theories of Personality. Yahya Sayyed Mohammadi Translation. 8th
ed. Tehran: Virayesh; 2015.
Seligman M, Roshanhan D, Walker A. Psychiatric Pathology. Translated by Rostami R, Niloufari A, Ghobadi M. Tehran: Arjomand; 2010.
Adel Nasab L. The Role of Personality Type D and Burnout in the Prediction of non-Occurrence of Heart Disease. Thesis; 2010.
Ogińska-Bulik N. Type D personality and quality of life in subjects after myocardial infarction. Kardiol Pol 2014;72:624-30.
Williams L, O'Connor RC, Grubb NR, O'Carroll RE. Type D personality and three-month psychosocial outcomes among patients post-myocardial infarction. J Psychosom Res 2012;72:422-6.
Grande G, Rampple M, Barth J. Association between type D personality and prognosis in patients with cardiovascular disease: A systematic review and meta- analysis of behavioral medicine. Ann Behav Med 2012;43:299-310.
Denollet J. Biobehavioral research on coronary heart disease: Where is the person? J Behav Med 1993;16:115-41.
Denollet J. DS14: Standard assessment of negative affectivity, social inhibition, and type D personality. Psychosom Med 2005;67:89-97.
Pedersen SS, Denollet J. Type D personality, cardiac events, and impaired quality of life: A review. Eur J Cardiovasc Prev Rehabil 2003;10:241-8.
Denollet J, Gidron Y, Vrints CJ, Conraads VM. Anger, suppressed anger, and risk of adverse events in patients with coronary artery disease. Am J Cardiol 2010;105:1555-60.
Barlow DH, Durand VM. Abnorma; Psychology. Translated by Mehrdad Firoozbakhte. Tehran: Resa. 2015.
Ziqami Mohammadi S, Danesh E, Shakour M, Fahimi F, Mohseni B, FallahTaherpazier A. The correlation between D-type personality and compliance with low-salt diet in patients with systolic heart failure. J Qom Univ Med Sci 2017;12:32-42.
Atkinson RA, Atkinson RC, Smith EE, Bem DJ, Hoeksema SN. Introduction to psychology. 13th
ed. Translated by Mohammad Naghei Barahani, Behrooz Birashch, Mehrdad Beyk, Reza Zamani, Saeed Shamloo, Mehrnaz Shahraari Tehran: Roshd Publication; 2011.
Besharat MA, Darwishi Lord M, Gholamali Lavasani M. Relationship between negative emotion and social inhibition with severity of coronary artery stenosis: The role of mediatory ruminant anger. Pers Individ Dif 2016;4:1-24.
Najafi Z, Tagharobi Z, Taghados M, Sharifi K, Farkhian AR. Effect of aromatherapy and Quranic voice on anxiety in patients with myocardial infarction. Q J Complement Med 2014;1:700-12.
Aga Khani N, Sanaei K, Baqaei R, Khademvatan K. The effect of educational-self-care package on anxiety and depression and stress in patients with myocardial infarction. J. Urmia Nurs Midwifery Fac 2017;16:28-39.
Ahangarzadeh Rezaei S, Olaad Rostam N, Nematolahi A. The effect of positive thinking education on stress, anxiety and depression in coronary heart disease patients. J Urmia Nurs Midwifery Fac 2017;15:339-48.
Wrenn KC, Mostofsky E, Tofler GH, Muller JE, Mittleman MA. Anxiety, anger, and mortality risk among survivors of myocardial infarction. Am J Med 2013;126:1107-13.
de Jager TAJ, Dulfer K, Radhoe S, Bergmann MJ, Daemen J, van Domburg RT, et al.
Predictive value of depression and anxiety for long-term mortality: Differences in outcome between acute coronary syndrome and stable angina pectoris. Int J Cardiol 2018;250:43-8.
Roest AM, Zuidersma M, de Jonge P. Myocardial infarction and generalised anxiety disorder: 10-year follow-up. Br J Psychiatry 2012;200:324-9.
Murphy B, Rogerson M, Worcester M, Elliott P, Higgins R, Le Grande M, et al.
Predicting mortality 12 years after an acute cardiac event: Comparison between inhospital and 2-month assessment of depressive symptoms in women. J Cardiopulm Rehabil Prev 2013;33:160-7.
Chida Y, Steptoe A. The association of anger and hostility with future coronary heart disease: A meta-analytic review of prospective evidence. J Am Coll Cardiol 2009;53:936-46.
Davidson KW, Mostofsky E. Anger expression and risk of coronary heart disease: Evidence from the Nova Scotia health survey. Am Heart J 2010;159:199-206.
Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986;51:1173-82.
Mueller RO. Basic Principles Modeling. New York: Springer; 1996.
Denollet J. Personality and coronary heart disease: The type-D scale-16 (DS16). Ann Behav Med 1998;20:209-15.
Ahmadpour Mobarakeh A, Ahadi H, Mazaheri MM, Nafisi GR. Compilation and scale validation to measure personality type D and its relationship with coronary heart disease. Knowledge and Research in Psychology. Islamic Azad University Khorasgan; 2007. p. 32.
Zolgenahi A, Agilar Vafaiy M. The prevalence of type D personality in the community student and the assessment of the personality biologic-behavioral foundations in being susceptible to coronary heart disease. Second Mental Health Student Seminar. Tarbiat Modares University; 2004.
Fakhari A, Nowroozi S, Medicine MZ. The validity and reliability of the Persian version of the D personality inventory (DS14). In Coronary Heart Diseases. Tabriz Univ Med Sci Health Ser 2014;36:78-85.
Rajabi G. Short-form psychometric properties of Beck Depression Inventory (BDI-13). J Iran Psychol 2005;1:291-9.
Fathi Ashtiani A. Psychological Tests of Personality Detection and Mental Health. Tehran: Besat; 2016.
Khodayari Fard M, Gholamali Lavasani M, Akbari Zardkhane S, Liaghat S. Standardization of type Spielberger's state anger inventory 2 for Iranian students 2010;11:47-56.
Asadi M, Tirgari A, Hasanzadeh H. Comparison of the effect of muscle relaxation training on anger reduction and blood glucose control in type 1 and type 2 diabetic patients. Magazine Med Sch Mashhad Univ Med Sci 2013;56:104-12.
Spielberger CD, Gorsuch RL, Lushene RD. Test Manual for the State-Trait Anxiety Inventory. Palo Alto, California: Consulting Psychologists Press; 1970.
Taqhavi M, Najafi M, Kian Ercy F, Aghyan S. Comparison of mood nougat, defensive styles and state- trait anxiety in patients with generalized anxiety disorder, major depression and normal people. J Clin Psychol 2012;5:67-76.
Merswolken M, Deter HC, Siebenhuener S, Orth-Gomér K, Weber CS. Anxiety as predictor of the cortisol awakening response in patients with coronary heart disease. Int J Behav Med 2013;20:461-7.
Van Beek MH, Zuidersma M, Lappenschaar M, Pop G, Roest AM, Van Balkom AJ, et al.
Prognostic association of cardiac anxiety with new cardiac events and mortality following myocardial infarction. Br J Psychiatry 2016;209:400-6.
Lin IM, Fan SY, Lu YH, Lee CS, Wu KT, Ji HJ, et al.
Exploring the blood volume amplitude and pulse transit time during anger recall in patients with coronary artery disease. J Cardiol 2015;65:50-6.
Nadri S. Review of personality types A, B, C, D of auditors on the content of the audit report. Q J Res 2016;5:71-86.
Saber Moghadam Ranjbar M, Rajabzadeh R, Ghabaee NZ. Relationship between lifestyle and hypertension in employees of government departments in Bojnourd. J North Khorasan Univ Med Sci 2013;5:785-91.
Etemad Z, Ismail Nasab A. Relationship between physical activity level and some coronary risk factors (CHD) in students. SJ Kordestan UMS 2012;17:25-35.
Mohseni Pooya H, Haji Miri K, Ismaili Shahmirzadi S, Golshani S, Hashemi Ameri SH, Saifi Makrani A. The relationship between health promoting behaviors and coronary heart disease severity in patients in the department of angiography in Mazandaran cardiac center. J Mazandaran Univ Med Sci 2015;25:19-29.
Mohammadi Pashaki M, Mahmoodi Mollayi AA, Mirzayian B, Heydari J, Jafari H. The effect of training coping styles to deal with negative emotions on mental health of patients undergoing open heart surgery. J Nurs Midwifery Sci 2016;3:13-9.
James Sadock B, Alcott Sadock V, Ruiz P. Synopsis of Psychiatery: Behavioral Sciences/Clinical Psychiatery. 11th
ed. Translated by Rezaee F. Tehran: Arjmand; 2015.
Faramarzinnia E, Beshatat MA. Relationship between anxiety and anger with chronic blood pressure. J Islamic Azad Univ 2010;20:136-41.
AghYousefi AR, Shahandeh M. Anger and quality of life in coronary artery disease patients. Jundishapur J Health Sci 2013;12:345-54.
[Table 1], [Table 2], [Table 3], [Table 4]