Keywords

type D personality, coronary heart disease, psychological distress, health-promoting behavior, quality of life

 

Authors

  1. CAO, Xi

ABSTRACT

Background: Type D personality, a newly specified personality type defined as the interaction of high levels of negative affectivity and social inhibition, is associated with poor health outcomes. Few interventional studies have been performed to improve health outcomes in this subpopulation.

 

Purpose: This study was developed to examine the effects of an educational intervention on psychological health, health-promoting behaviors, and quality of life in coronary heart disease (CHD) patients with type D personality in China.

 

Methods: A randomized controlled trial was adopted. One hundred twenty-eight patients with CHD and type D personality were randomly assigned. The intervention group received the 12-week educational intervention in addition to usual care, whereas the control group received usual care only. Data on anxiety and depression, health-promoting behaviors, and quality of life were collected at baseline and at 1 and 3 months after enrollment. After controlling for the covariates, the generalized estimating equation model was used to examine the intervention effects.

 

Results: The mean age of the participants was 61.02 years, and more than 70% were male. Results of the generalized estimating equation analysis showed significantly greater improvements in anxiety, depression, and health-promoting behaviors in the intervention group than in the control group. In addition, quality of life, the domains of angina limitation, angina stability, and treatment satisfaction were found to have improved more significantly in the intervention group than the control group, whereas the posttest changes in angina frequency and disease perception were found to be similar in both groups.

 

Conclusions/Implications for Practice: The educational intervention was shown to be effective in improving psychological health, health-promoting behaviors, and certain domains of quality of life in patients with CHD and type D personality. Nurses should identify patients with this personality type and provide tailored care to improve their health outcomes in clinical practice.

 

Article Content

Introduction

Coronary heart disease (CHD) is a leading cause of death worldwide. In the United States, an estimated 20.1 million adults aged 20 years or above have CHD (Virani et al., 2021), and in China, about 11.4 million people aged 15 years or above are diagnosed with CHD (The Writing Committee of the Report on Cardiovascular Health and Diseases in China, 2022). A rapid increase in the prevalence of CHD is expected because of the rising prevalence of cardiac risk factors (e.g., hypertension, diabetes mellitus) and population aging (National Center for Cardiovascular Diseases, 2021). Type D personality, also called distressed personality, is defined as the interaction of high levels of negative affectivity and social inhibition (Denollet et al., 2010). Type D personality has been associated with 19%-51% of patients with CHD (Enatescu et al., 2021; Mesa-Vieira et al., 2021) and is an established psychosocial risk factor affecting CHD prognosis.

 

Empirical evidence indicates that cardiac patients with type D personality face an increased risk of adverse health outcomes (Grassi et al., 2022; Manoj et al., 2020). For example, patients with CHD who have a type D personality face an up to 3 times higher risk of experiencing a cardiovascular event than those with other personality types (Leu et al., 2019). In addition, compared with patients with no type D personality, patients with type D personality who undergo percutaneous coronary intervention face 3.7-fold and 2.7-fold higher risks of depression and anxiety, respectively, during follow-up (AL-Qezweny et al., 2016). Having a type D personality may also worsen the effects of other psychosocial risk factors such as depression, negatively affecting well-being and further impairing quality of life (Jo et al., 2019).

 

Psychophysiological and behavioral pathways have been proposed to elucidate the link between type D personality and adverse health outcomes (Enatescu et al., 2021; Kupper & Denollet, 2018), with the former focused on physiological responses elicited by a range of psychological disorders experienced by individuals with type D personality (Enatescu et al., 2021; Kupper & Denollet, 2018) and the latter focused on the predisposing, negative effects of type D personality on various health-related behaviors such as lifestyle modification and adherence to medication or cardiac rehabilitation that lead to poor cardiac prognoses (Kupper & Denollet, 2018). In addition, patients with type D personalities typically cope less effectively with their illness than their non-type-D counterparts (Grassi et al., 2022). Thus, these two pathways suggest potentially efficacious targets to improve health outcomes in patients with type D personalities.

 

Despite the poor health outcomes associated with type D personality, few interventional studies have been published on this subpopulation. Sogaro et al. (n = 59) investigated the effects of cardiac rehabilitation on health outcomes in cardiac patients with type D personality and found significant improvements in psychological health and quality of life after attending a 4-week intensive cardiac rehabilitation program (Sogaro et al., 2010). However, compared with their non-type-D counterparts, those with type D personality still showed poorer psychological well-being. A systematic review was conducted to synthesize the evidence on interventions for cardiovascular patients with type D personality, providing preliminary but low-quality evidence (e.g., nonrandomized controlled trials, small sample sizes) on the use of cardiac rehabilitation in this subpopulation (Cao et al., 2016). In addition, whether cardiac rehabilitation may be generalized to this population in China requires careful consideration because of the limited cardiac rehabilitation resources available. Therefore, in this study, we aimed to develop an educational intervention to modify the behavioral pathway and to test the effects of this intervention on psychological health, lifestyle behaviors, and quality of life in patients with CHD and type D personality in China using a randomized controlled trial design.

 

Methods

Study Design, Participants, and Settings

A randomized controlled trial with repeated measures was adopted. Patients who were admitted to the cardiac wards of two university-affiliated hospitals in Changsha, China, from October 2015 to August 2016 were approached and screened based on the inclusion and exclusion criteria. The inclusion criteria included (a) age >= 18 years, (b) diagnosis of CHD confirmed by a physician and type D personality as determined using the Type D Scale-14 (Denollet, 2005), (c) being available for telephone follow-up, and (d) being able to provide written consent. Following Huang (2008), patients who scored >= 6 on the Negative Affectivity subscale and >= 9 on the Social Inhibition subscale on the Type D Scale-14 were classified in this study as meeting the criteria for type D personality (Huang, 2008). Patients with physical immobility as indicated by medical records; diagnosed with psychiatric illness, a cognitive disorder such as dementia, or a terminal disease such as cancer; or currently participating in another study were excluded.

 

Randomization

A research assistant who was not involved in any other procedures of the study generated the randomization sequence using an online randomization program (http://www.randomization.com/). The same research assistant prepared opaque and sealed envelopes with a card inside indicating group allocation. These envelopes were sequentially numbered and distributed to participants based on their order of enrollment in this study. Finally, the participants were assigned randomly to either the intervention or control group.

 

Sample Size

Sample size was calculated based on a previous Chinese study on patients with acute myocardial infarction that reported a medium intervention effect (Cohen's effect size of 0.54) on psychological health (Wang et al., 2012). Using G*Power (Version 3.1), a sample of 110 participants was estimated for this study with a power of 80% at a significance level of .05. Considering an attrition rate of 15%, 128 patients with CHD and type D personality (64 per group) was required.

 

Intervention

Social cognitive theory by Bandura (2012) was used to guide this study. According to the social cognitive theory, human behavior is a dynamic process influenced by personal (e.g., beliefs, perceptions, and feelings toward the illness) and environmental (e.g., access to health resources after discharge, support from outside) factors. Previous studies have suggested that cardiac patients with type D personality hold misperceptions toward their illness (e.g., symptoms cannot be effectively controlled), have poor social support, and are less likely to seek professional advice on illness management (Mols et al., 2020; Park et al., 2021). Therefore, in this study, an educational intervention based on the social cognitive theory was developed that focuses on correcting misperceptions and providing support and resources to facilitate and enhance behavioral change in patients with CHD and type D personality.

 

The 12-week educational intervention incorporated two face-to-face, in-hospital education sessions and six telephone follow-ups after hospital discharge. The first face-to-face education session involved (a) assessing the perception of the participants toward their illness to recognize misperceptions, evaluating their psychological distress, and identifying the underlying causes and (b) providing education based on the results of the assessment that addressed CHD information, risk factors, and medical treatment and the influence of lifestyle (e.g., diet, physical activity, stress) on CHD prognosis. In the second session, the participants were trained on skills necessary to cope with their illness and facilitate self-management after discharge. These skills included consuming a healthy diet, exercise, and symptom and stress management. The participants were also instructed to use goal-setting techniques to achieve behavioral change. Each face-to-face session lasted for at least 1 hour. A booklet on CHD management and a logbook were provided to facilitate behavioral change. Telephone follow-ups were initiated during the first week after hospital discharge. During each call, participants were assessed for behavior change progress as well as problems and barriers encountered, with feedback and possible solutions provided based on individual participant need. Each call lasted 15-20 minutes.

 

The usual care received by both groups included routine medical and nursing care provided by the hospitals. Brief information about CHD and treatment as well as general advice on lifestyle change were provided by nurses during the normal course of their duties. The intervention group received the educational intervention in addition to usual care, whereas the control group received usual care only.

 

Measures and Measurements

Demographic and clinical data

Demographic data on age, gender, marital status, educational level, and employment status and clinical characteristics, including New York Heart Association class, history of hypertension and diabetes, cardiac intervention received, blood pressure, and lipid profile, were collected.

 

Anxiety and depression

Anxiety and depression were measured using the Chinese version of the Hospital Anxiety and Depression Scale (Wang et al., 2009). This scale comprises a seven-item depression subscale and a seven-item anxiety subscale, with total scores for each subscale ranging from 0 to 21 and higher scores indicating higher levels of depression and anxiety, respectively. Satisfactory internal consistency of the Chinese version of the Hospital Anxiety and Depression Scale was established on a myocardial infarction sample with Cronbach's alphas of .85, .79, and .79 for the overall scale and anxiety and depression subscales, respectively (Wang et al., 2009).

 

Quality of life

Quality of life was measured using the Chinese version of the Seattle Angina Questionnaire (SAQ). The 19-item SAQ is a disease-specific questionnaire designed to measure quality of life in cardiac patients (S. H. Liu, 2003) that consists of 19 items to assess five dimensions of quality of life, including physical limitation, angina stability, angina frequency, treatment satisfaction, and disease perception. A standard score for each dimension is calculated using the formula: [(sum of item scores - the lowest possible scale score) / the range of the scale] x 100. The validity and reliability of the Chinese version of the SAQ were previously established in a Chinese sample of patients with CHD (S. H. Liu, 2003).

 

Health-promoting behaviors

The Chinese version of the Health-Promoting Lifestyle Profile (Chen, 1999) is a 40-item instrument used to measure six domains of health-promoting behavior. Five of the six domains (excluding the domain of self-actualization) were employed to measure health-promoting behaviors in this study. The total possible score for these five domains ranges from 0 to 96, with higher scores indicating better health-promoting behaviors. The Chinese version of the Health-Promoting Lifestyle Profile has shown good psychometric properties, with Cronbach's alphas of .92 for the entire scale and .69-.84 for the subscales (Chen, 1999).

 

Self-efficacy

Self-efficacy was measured in this study using the Chinese version of the General Self-Efficacy Scale (Zhang & Schwarzer, 1995). The general self-efficacy consists of 10 items used to evaluate beliefs related to effectively dealing with stressful life events. Each item is rated on a 4-point Likert scale. Total possible scores range from 10 to 40, with higher scores indicating higher levels of self-efficacy. The Chinese version of the General Self-Efficacy Scale has shown satisfactory internal consistency (Cronbach's alpha of .91; Zhang & Schwarzer, 1995).

 

Data Collection Procedure

Patients admitted to the cardiac wards were approached and initially screened by a trained nurse based on the inclusion and exclusion criteria. Those who met these criteria were then further screened for type D personality using the Type D Scale-14, with eligible patients then invited to participate. Written informed consent was obtained from those who agreed to participate after the study purpose and procedures, potential benefits and risks, and the right to withdrawal at any time were explained. Next, baseline data (T0) were collected by two trained research assistants. The participants were interviewed and asked to complete the questionnaires independently. Clinical data were abstracted from patients' medical records. Follow-up data were collected at 1 month (T1) and 3 months (T2) after study enrollment by the same research assistants. Regular audit reviews (every 2 weeks) between the researcher and the two research assistants were conducted to ensure interrater reliability.

 

Data Analysis

Data were analyzed using IBM SPSS Statistics Version 25.0 (IBM, Inc., Armonk, NY, USA). Descriptive statistics (e.g., means, standard deviations, frequency, percentage) were used as appropriate. Between-group differences were examined using independent t test, analysis of variance, chi-square test, or nonparametric test as appropriate. Generalized estimating equation (GEE) model was used to examine changes in outcome variables between the two groups. In the GEE analysis, AR(1) was chosen for the working correlation matrix, whereas a linear model was chosen for the link function, as the outcome data in this study were normally distributed. Potential covariates were identified when either (a) variables for which a p < .25 between study groups at baseline was indicated (Bursac et al., 2008) or (b) variables were identified in the literature as having potential intervention effects in patients with type D personality (i.e., educational level, disease severity, baseline self-efficacy, negative affectivity score; Cao et al., 2016; L. Liu et al., 2018). These variables were then treated in GEE analysis as covariates. Both crude (unadjusted) and adjusted models from the GEE analysis were output. Goodness of fit for the adjusted GEE model was examined. Intention-to-treat analysis was adopted. The significance level was set as .05 and two tailed.

 

Ethics Considerations

Ethical approval for this study was obtained from the Joint Chinese University of Hong Kong-New Territories East Cluster Clinical Research Ethics Committee (CREC Ref. No. 2015.352). Written consent was obtained from each participant after explaining to them the study purpose, procedures, benefits, and potential risks. The right to withdraw or discontinue participation at any time without any penalty along with confidentiality and anonymity were assured to participants. This article is reported in accordance with Consolidated Standards of Reporting Trials guidelines.

 

Results

Participant Recruitment

One hundred sixty-six of 1,836 patients were initially screened, with 128 patients finally enrolled as participants and randomized. Six and ten participants dropped out at 1 month (T1) and 3 months (T2), respectively. The main reasons for their withdrawal included lack of interest, time conflicts, and being unable to be reached. The participant recruitment flow is presented in Figure 1.

  
Figure 1 - Click to enlarge in new windowFigure 1. Flow Diagram of Participant Recruitment

Sociodemographic and Clinical Characteristics of Participants

Sociodemographic and clinical characteristics of the participants are presented in Table 1. The mean age was 61.02 (SD = 9.47) years, and over 70% were male. Over half had received a cardiac intervention (percutaneous transluminal coronary angioplasty or percutaneous coronary intervention), and 55.5% had hypertension. In terms of anxiety and depression, 36.7% reported anxiety and 34.4% experienced depression at baseline. With the exception of hypertension status, no significant differences in terms of sociodemographic, clinical, or outcome variables between the two study groups were found (Table 1). More hypertension cases were observed in the intervention group than the control group ([chi]2 = 5.35, p = .021). Hypertension, social inhibition score, and potential confounders (educational level, disease severity, negative affectivity score, and baseline self-efficacy) suggested by the literature were adjusted in the GEE analysis.

  
Table 1-a Sociodemog... - Click to enlarge in new windowTable 1-a Sociodemographic and Clinical Characteristics of Participants and Intergroup Differences

Intervention Effects on Anxiety and Depression

The control group showed a significant decrease in anxiety and depression over time in both the crude and adjusted models (all ps < .05). Compared with the control group, the intervention group showed a greater decrease in anxiety (Group x Time 1: [beta] = -1.20, 95% CI [-2.23, -0.17]; Group x Time 2: [beta] = -1.84, 95% CI [-2.91, -0.77]) and depression (Group x Time 1: [beta] = -1.18, 95% CI [-1.94, -0.42]; Group x Time 2: [beta] = -1.41, 95% CI [-2.27, -0.55]) at both T1 and T2. The GEE results for anxiety and depression are shown in Table 2.

  
Table 2 - Click to enlarge in new windowTable 2 GEE Results of Intervention Effects on Anxiety and Depression

Intervention Effects on Health-Promoting Behaviors

Although the control group showed improvements in health-promoting behaviors, these improvements did not reach significance (Table 3). The intervention group reported more-significant improvements than the control group in overall health-promoting behaviors across the study period (Group x T1: [beta] = 5.70, 95% CI [2.30, 9.10]; Group x T2: [beta] = 11.50, 95% CI [7.77, 15.23]; Table 3). With regard to specific behaviors, health responsibility, exercise, and stress management improved more significantly in the intervention group than the control group at both T1 and T2, whereas significant improvements in nutrition behavior and interpersonal support were observed at T2 only.

  
Table 3 - Click to enlarge in new windowTable 3 GEE Results for Intervention Effects on Health-Promoting Behaviors

Intervention Effects on Quality of Life

Participants in the control group achieved significant improvements in angina stability, angina frequency, treatment satisfaction, and disease perception across the study period (all ps < .05), whereas physical limitation showed significant improvement only at T1 (Table 4). With regard to group differences in terms of quality of life, angina stability improved more significantly in the intervention group at both T1 and T2, whereas physical limitation (Group x T2: [beta] = 5.86, 95% CI [1.21, 10.51]) and treatment satisfaction (Group x T2: [beta] = 6.95, 95% CI [1.40, 12.50]) improved more significantly in the intervention group at T2 only. No significant intergroup difference in terms of angina frequency or disease perception was found.

  
Table 4 - Click to enlarge in new windowTable 4 GEE Results for Intervention Effects on Quality of Life

Intervention Effects on Self-Efficacy

Self-efficacy did not improve significantly in the control group over the study period (all ps > .05). Although the intervention group showed improvements in self-efficacy, these improvements reached significance at T2 only (Group x Time 2: [beta] = 2.08, 95% CI [0.29, 3.88]).

 

Discussion

This randomized controlled trial was designed to examine the effects of an educational intervention on psychological health, health-promoting behaviors, and quality of life in Chinese patients with CHD and type D personality. Overall, the intervention group showed more-significant improvements in anxiety, depression, and health-promoting behaviors than the control group. In addition, the beneficial effects of the intervention on quality of life were observed in certain domains of the SAQ.

 

Despite the poor health outcomes documented in cardiac patients with type D personality, the potential benefits of providing related interventions to patients with type D personality remain unclear (Dornelas, 2012). Some researchers have claimed that patients with this personality type may not benefit from interventions, as personality traits are stable across time and difficult to change. However, others have argued that, rather than changing the personality itself, interventions in the type D context could focus on modifying (e.g., by reducing psychological distress and modifying unhealthy behaviors) the known links between type D personality and adverse health outcomes (Kupper & Denollet, 2018). The findings of this study support the latter position that individuals with type D personality may benefit from interventions that work to modify these potential pathways.

 

In this study, significant reductions in anxiety and depression were found in the control group, which may be explained by the provided medical treatments and time effects (Murphy et al., 2020). However, the intervention group achieved more-significant reductions in these two aspects. The mind-body-heart connectivity favors the co-management of mental and somatic illnesses to promote psychological health in cardiac patients (Levine et al., 2021). In this study, we provided knowledge and skills related to illness, symptoms, and stress management that can enable participants to cope effectively with somatic problems and negative emotions, thus promoting an improved psychological status. Similar results have been reported in studies conducted in Turkey (Bilir Kaya, 2019) and Italy (Sogaro et al., 2010), both of which used cardiac rehabilitation as the intervention and reported significant reductions in anxiety and depression in patients with type D personality at the end of the intervention. However, despite the improvements in psychological health found in these studies, the patients still showed higher scores for anxiety and depression than their non-type-D counterparts (Sogaro et al., 2010). Similarly, in this study, we found a declining trend for both anxiety and depression improvements in the intervention group at 3 months (T2). The nature of this personality type may predispose individuals to experience a wide range of psychological or emotional disorders (e.g., irritability, social phobia; Lambertus et al., 2018) that may arouse anxiety and depression that counteract the intervention effects. Therefore, more efforts are needed to sustain the intervention effects on psychological health in this subpopulation. Furthermore, we found significant improvements in psychological health in the control group, which may be attributable to the normal process of cardiac disease recovery.

 

Consistent with previous studies on general cardiac patients (Basile et al., 2021), the educational intervention in this study enhanced the adoption and efficacy of health-promoting behaviors in the participants. Sogaro et al. (2010) previously reported improved social functioning in cardiac patients with type D personalities after cardiac rehabilitation, and a study in South Korea found significant improvement in social functioning in female cardiac patients with type D personality after a psycho-behavioral intervention (Hur et al., 2014). Despite the differences in interventions, the results of this and previous studies support that patients with type D personality can benefit from interventions designed to improve their lifestyle behaviors. The findings of previous studies also indicate that illness perception and professional support affect the behavioral engagement of individuals with type D personality (Denollet et al., 2021; Park et al., 2021) and that patients with type D personality are likely to hold misperceptions toward their illness (Kwon & Kang, 2018). The social cognitive theory also emphasizes the role of an individual's cognitive perceptions and environmental factors (e.g., social support) in healthy behavior formation (Bandura, 2012). To foster correct illness perceptions among the participants in this study, we first identified the misperceptions they held and then provided correct information to motivate their engagement in health-promoting behaviors. For example, we found that some of the participants refused to do physical activity because of believing physical activity would cause the reoccurrence of chest pains or relocation of their implanted stent. Furthermore, participants were empowered with practical skills for lifestyle management, and the use of goal-setting techniques and follow-up phone calls could further enhance behavioral change. All these factors may help explain the significant improvements in health-promoting behaviors achieved in the intervention group.

 

In this study, in terms of quality of life, favorable intervention effects were observed in the domains of physical limitation, angina stability, and treatment satisfaction, whereas no significant intergroup differences were found in the domains of angina frequency and disease perception. Previous studies, using instruments other than SAQ (e.g., 36-Item Short Form Health Survey), have identified significantly improved quality of life in patients with type D personality after their participation in a cardiac rehabilitation program (Bilir Kaya, 2019; Sogaro et al., 2010). The improved symptoms and health-related behaviors derived from the educational interventions in this and other studies may be attributed to quality of life improvements. In addition, the psychological health improvements achieved may also help explain the observed improvements in quality of life, as psychological status has been reported to relate significantly to quality of life in patients with CHD (Soleimani et al., 2022). Disease perception in SAQ refers to the perceived burden of heart disease. In this study, we found significantly improved disease perception in the control group, which may indicate that the educational intervention was less effective in reducing disease burden in patients with CHD and type D personality in China.

 

Limitations

Despite the strength of this study, several limitations should be acknowledged when interpreting the findings. First, despite the positive findings, the long-term effects of the educational intervention remain unclear, as only the immediate intervention effects were examined. Further study is warranted to explore the longer-term effects of this educational intervention. Second, participants in this study were not blinded and were aware of their group assignment, which may result in Hawthorne effect and, consequently, in the overestimation of the intervention effects. Third, the unexpectedly large value of goodness of fit may indicate that the GEE model was suboptimal in this study, which may undermine the validity of the findings. Thus, additional studies are suggested to further confirm the findings of this study. Finally, because of cultural differences, whether the findings are generalizable to patients with type D personality in other countries is unclear.

 

Conclusions/Implication for Research and Practice

The results of this randomized controlled trial showed the favorable effects of the educational intervention on improving psychological health, health-promoting behaviors, and certain domains of quality of life in patients with CHD and type D personality. The findings of this study provide evidence in support of the effectiveness of theory-based educational interventions in improving the health outcomes of patients with type D personalities.

 

Regarding the implications of this study, future research should explore the longer-term effects of this educational intervention and further confirm the findings in other cardiac patient populations with type D personality. This study included patients with type D personality only and did not employ an additional arm of non-type-D patients, making it unclear whether similar benefits may be generated for non-type-D patients. If so, this may indicate the presence of shared health demands between patients with type D personality and those with non-type-D personality and that, possibly, patients with type D personalities may also benefit from treatments designed for patients with non-type-D personalities. However, this should be further explored using empirical studies. Regarding implications for practice, the positive findings of this study highlight the importance of identifying these high-risk patients in clinical settings and providing guidance to nurses with regard to caring for patients with this personality type. Particularly, nurses should recognize the underlying causes (e.g., behavioral-change-related misperceptions) of maladaptive coping in patients with type D personalities and plan tailored care/education for these patients to enhance their health.

 

Acknowledgment

We thank all participants for their participation in this study.

 

Author Contributions

Study conception and design: SYC, EMLW, XC

 

Data collection: MYT, XC

 

Data analysis and interpretation: EMLW, MYT, XC

 

Drafting of the article: All authors

 

Critical revision of the article: SYC, XC

 

References

 

AL-Qezweny M. N. A., Utens E. M. W. J., Dulfer K., Hazemeijer B. A. F., van Geuns R.-J., Daemen J., van Domburg R. (2016). The association between type D personality, and depression and anxiety ten years after PCI. Netherlands Heart Journal, 24(9), 538-543. [Context Link]

 

Bandura A. (2012). Social cognitive theory. In P. A. M. Van Lange, A. W. Kruglanski, E. T. Higgins (Eds.), Handbook of theories of social psychology (pp. 349-373). Sage Publications. [Context Link]

 

Basile A. J., Renner M. W., Hidaka B. H., Sweazea K. L. (2021). An evolutionary mismatch narrative to improve lifestyle medicine: A patient education hypothesis. Evolution, Medicine and Public Health, 9(1), Article eoab010. [Context Link]

 

Bilir Kaya B. (2019). Does type D personality inhibit benefits of cardiac rehabilitation? Haydarpasa Numune Training and Research Hospital Medical Journal, 59(3), 244-249. [Context Link]

 

Bursac Z., Gauss C. H., Williams D. K., Hosmer D. W. (2008). Purposeful selection of variables in logistic regression. Source Code for Biology and Medicine, 3(1), Article No. 17. [Context Link]

 

Cao X., Wong E. M. L., Chow Choi K., Cheng L., Ying Chair S. (2016). Interventions for cardiovascular patients with type D personality: A systematic review. Worldviews on Evidence-Based Nursing, 13(4), 314-323. [Context Link]

 

Chen M.-Y. (1999). The effectiveness of health promotion counseling to family caregivers. PHN: Public Health Nursing, 16(2), 125-132. [Context Link]

 

Denollet J. (2005). DS14: Standard assessment of negative affectivity, social inhibition, and type D personality. Psychosomatic Medicine, 67(1), 89-97. [Context Link]

 

Denollet J., Schiffer A. A., Spek V. (2010). A general propensity to psychological distress affects cardiovascular outcomes: Evidence from research on the type D (distressed) personality profile. Circulation: Cardiovascular Quality and Outcomes, 3(5), 546-557. [Context Link]

 

Denollet J., Trompetter H. R., Kupper N. (2021). A review and conceptual model of the association of type D personality with suicide risk. Journal of Psychiatric Research, 138, 291-300. [Context Link]

 

Dornelas E. A. (Ed.). (2012). Stress proof the heart: Behavioral interventions for cardiac patients. Springer. [Context Link]

 

Enatescu V. R., Cozma D., Tint D., Enatescu I., Simu M., Giurgi-Oncu C., Lazar M. A., Mornos C. (2021). The relationship between type D personality and the complexity of coronary artery disease. Neuropsychiatric Disease and Treatment, 17, 809-820. [Context Link]

 

Grassi L., Caruso R., Murri M. B., Fielding R., Lam W., Sabato S., De Padova S., Nanni M. G., Bertelli T., Palagini L., Zerbinati L. (2022). Association between type-D personality and affective (anxiety, depression, post-traumatic stress) symptoms and maladaptive coping in breast cancer patients: A longitudinal study. Clinical Practice & Epidemiology in Mental Health, 17(1), 271-279. [Context Link]

 

Huang Y. K. (2008). The application of Chinese version of Type D Personality Scale in Chinese community-dwelling population [Master's thesis, Central South University]. https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CMFD2009&filename=2008164269 (Original work published in Chinese) [Context Link]

 

Hur S., Cho B. J., Kim S. R. (2014). Comparison of the effects of exercise participation on psychosocial risk factors and cardiovascular disease in women. Journal of Physical Therapy Science, 26(11), 1795-1798. [Context Link]

 

Jo E., Kim S. R., Kim H. Y. (2019). Predictive model for quality of life in patients with recurrent coronary artery disease. European Journal of Cardiovascular Nursing, 18(6), 501-511. [Context Link]

 

Kupper N., Denollet J. (2018). Type D personality as a risk factor in coronary heart disease: A review of current evidence. Current Cardiology Reports, 20(11), Article No.104. [Context Link]

 

Kwon M., Kang J. (2018). Mediating effect of illness perception on the relationship between type D personality and health behaviors among coronary artery disease patients. Health Psychology Open, 5(2), Article 2055102918817228. [Context Link]

 

Lambertus F., Herrmann-Lingen C., Fritzsche K., Hamacher S., Hellmich M., Junger J., Ladwig K.-H., Michal M., Ronel J., Schultz J.-H., Vitinius F., Weber C., Albus C. (2018). Prevalence of mental disorders among depressed coronary patients with and without type D personality. Results of the multi-center SPIRR-CAD trial. General Hospital Psychiatry, 50, 69-75. [Context Link]

 

Leu H. B., Yin W. H., Tseng W. K., Wu Y. W., Lin T. H., Yeh H. I., Cheng Chang K., Wang J. H., Wu C. C., Chen J. W. (2019). Impact of type D personality on clinical outcomes in Asian patients with stable coronary artery disease. Journal of the Formosan Medical Association, 118(3), 721-729. [Context Link]

 

Levine G. N., Cohen B. E., Commodore-Mensah Y., Fleury J., Huffman J. C., Khalid U., Labarthe D. R., Lavretsky H., Michos E. D., Spatz E. S., Kubzansky L. D. (2021). Psychological health, well-being, and the mind-heart-body connection: A scientific statement from the American heart association. Circulation, 143, E763-E783. [Context Link]

 

Liu L., Wang X., Cao X., Gu C., Yang C., OuYang Y. (2018). Self-care confidence mediates the relationship between type D personality and self-care adherence in Chinese heart failure patients. Heart & Lung, 47(3), 216-221. [Context Link]

 

Liu S. H. (2003). Psychometric properties of Chinese version of Seattle Angina Questionnaire in patients with CHD. Tian Jin Medical University. https://reurl.cc/dDeGDg[Context Link]

 

Manoj M., Joseph K., Vijayaraghavan G. (2020). Type D personality and myocardial infarction: A case-control study. Indian Journal of Psychological Medicine, 42(6), 555-559. [Context Link]

 

Mesa-Vieira C., Grolimund J., von Kanel R., Franco O. H., Saner H. (2021). Psychosocial risk factors in cardiac rehabilitation: Time to screen beyond anxiety and depression. Global Heart, 16(1), Article 16. [Context Link]

 

Mols F., Thong M., Denollet J., Oranje W. A., Netea-Maier R. T., Smit J. W. A., Husson O. (2020). Are illness perceptions, beliefs about medicines and type D personality associated with medication adherence among thyroid cancer survivors? A study from the population-based PROFILES registry. Psychology and Health, 35(2), 128-143. [Context Link]

 

Murphy B., Le Grande M., Alvarenga M., Worcester M., Jackson A. (2020). Anxiety and depression after a cardiac event: Prevalence and predictors. Frontiers in Psychology, 10, Article 3010. [Context Link]

 

National Center for Cardiovascular Diseases. (2021). Annual report on cardiovascular health and diseases in China (2020). China Science Publishing & Media. (Original work published in Chinese) [Context Link]

 

Park C., Won M. H., Son Y. J. (2021). Mediating effects of social support between type D personality and self-care behaviours among heart failure patients. Journal of Advanced Nursing, 77(3), 1315-1324. [Context Link]

 

Sogaro E., SchininA F., Burgisser C., Orso F., Pallante R., Aloi T., Vanni D., Pazzagli A., Fattirolli F. (2010). Type D personality impairs quality of life, coping and short-term psychological outcome in patients attending an outpatient intensive program of cardiac rehabilitation. Monaldi Archives for Chest Disease, 74(4), 181-191. [Context Link]

 

Soleimani M. A., Zarabadi-Pour S., Huak Chan Y., Allen K. A., Shamsizadeh M. (2022). Factors associated with hope and quality of life in patients with coronary artery disease. The Journal of Nursing Research, 30(2), Article e200. [Context Link]

 

The Writing Committee of the Report on Cardiovascular Health and Diseases in China. (2022). Report on cardiovascular health and diseases in China 2021: An updated summary. Biomedical and Environmental Sciences, 35(7), 573-603. [Context Link]

 

Virani S. S., Alonso A., Aparicio H. J., et alAmerican Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. (2021). Heart disease and stroke statistics-2021 update: A report from the American Heart Association. Circulation, 143(8), e254-e743. [Context Link]

 

Wang W., Chair S. Y., Thompson D. R., Twinn S. F. (2009). A psychometric evaluation of the Chinese version of the Hospital Anxiety and Depression Scale in patients with coronary heart disease. Journal of Clinical Nursing, 18(13), 1908-1915. [Context Link]

 

Wang W., Chair S. Y., Thompson D. R., Twinn S. F. (2012). Effects of home-based rehabilitation on health-related quality of life and psychological status in Chinese patients recovering from acute myocardial infarction. Heart & Lung, 41(1), 15-25. [Context Link]

 

Zhang J. X., Schwarzer R. (1995). Measuring optimistic self-beliefs: A Chinese adaptation of the general self-efficacy scale. Psychologia, 38(3), 174-181. [Context Link]