Associations Between Alexithymia, Cognitive Emotion Regulation, and Physical Symptoms in Coronary Heart Disease

Associations Between Alexithymia, Cognitive Emotion Regulation, and Physical Symptoms in Coronary Heart Disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Associations Between Alexithymia, Cognitive Emotion Regulation, and Physical Symptoms in Coronary Heart Disease Jie Yuan, Yannan Ma, Song Lin, Xiujuan Wu, Xiaodong Feng, Yuzhen Sun This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8530045/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective Coronary heart disease (CHD) remains the leading cause of death worldwide, with psychological symptoms being highly prevalent among patients and influencing both disease onset and prognosis. Limited research has explored the role of emotional regulation. This study aims to evaluate alexithymia subscales and cognitive emotion regulation strategies (CERS) in patients with CHD and to examine their associations with physical symptoms (PS) and other clinical variables. Methods The sample consisted of 199 patients with CHD and 116 healthy controls. All participants completed the Toronto Alexithymia Scale (TAS-20), the Cognitive Emotion Regulation Questionnaire (CERQ), and the Physical Symptoms Inventory (PSI). Alexithymia was evaluated dimensionally across three core domains (difficulty identifying feelings, difficulty describing feelings, externally oriented thinking), with participants categorized by established TAS-20 cutoff scores. Results Compared with healthy controls, CHD patients exhibited significantly higher levels of alexithymia, including difficulties identifying feelings (DIF), difficulties describing feelings (DDF), and externally oriented thinking (EOT) ( p < 0.05). CHD patients also reported greater reliance on maladaptive cognitive emotion regulation strategies (CERS), including self-blame, rumination, catastrophizing, and other-blame ( p < 0.01). Within the CHD group, DIF, DDF, EOT and maladaptive CERS were positively correlated with physical symptom (PSI, r = 0.37–0.48, p < 0.01), and regression analyses indicated that DIF, EOT, and maladaptive CERS independently predicted PSI severity, accounting for 35% of the variance after controlling for age and New York Heart Association (NYHA) functional class. Conclusions Patients with CHD show marked deficits in emotion recognition and regulation, with DIF, EOT, and maladaptive CERS emerging as key predictors of physical symptoms. alexithymia cognitive emotion regulation strategies physical symptoms inventory psychology CHD Figures Figure 1 Figure 2 Figure 3 Introduction Coronary heart disease (CHD) is a common, heterogeneous, and distressing condition that ranks among the leading causes of death worldwide, exerting a profound impact on both society and individuals [ 1 ] . Traditional risk factors for CHD include hypertension, hypercholesterolemia, smoking, diabetes, obesity, and genetic predisposition [ 2 ] . Emerging evidence highlights the critical role of psychological factors, particularly difficulties in emotion regulation and alexithymia, alongside biological alterations such as endothelial dysfunction and systemic inflammation, in influencing cardiac dysfunction, prognosis, and quality of life in CHD patients [ 3 – 6 ] . Alexithymia, defined as difficulties in identifying and regulating emotions [ 7 ] , is closely associated with impairments in emotional cognitive processing. Accumulating evidence suggests that alexithymia is linked to a wide range of medical and psychiatric conditions, as well as maladaptive illness-related behaviors [ 8 , 9 ] . and is associated with more severe depressive symptoms, lower life satisfaction, and a greater psychological burden [ 10 , 11 ] . It was found that alexithymia was associated with a previous diagnosis of CHD [ 12 ] . Alexithymia has been reported to show independent associations with hypertension and carotid atherosclerosis in some studies [ 13 ] , is linked to coronary artery spasm, and may contribute to the onset of hypertension and its symptomatic manifestations [ 14 – 16 ] . In addition, alexithymia has been associated with an increased risk of post-traumatic stress disorder following myocardial infarction [ 17 , 18 ] . Despite growing interest in psychological factors in CHD, evidence on the associations between alexithymia and other clinical symptoms remains scarce. Addressing this gap, the present study investigates how alexithymia relates to key psychological factors in patients with CHD. Previous studies have consistently confirmed that there is a close association between alexithymia and difficulties in emotion regulation [ 19 ] . cognitive emotion regulation strategies (CERS) play a crucial role in individuals' responses to stressful events and adaptation to life changes, and are related to psychological and physical reactions [ 20 ] . Emotion regulation strategies are divided into adaptive CERS and maladaptive CERS [ 19 ] . The emotion regulation process seems to be disrupted in acute and chronic diseases, with adaptive approaches replaced by maladaptive CERS [ 21 ] .In the population of patients with coronary heart disease, existing studies have found that compared with healthy individuals, patients with comorbid depressive symptoms use maladaptive CERS more frequently in emotion coping [ 22 ] .These strategies have been proven to potentially increase the risk of adverse cardiovascular outcomes and death indirectly by aggravating psychological stress responses and physiological load [ 23 – 25 ] . Physical symptoms (PS) refer to individuals’subjective perceptions of bodily discomfort or functional abnormalities, including pain, fatigue, palpitations, and dyspnea, and are characterized by persistent physical sensations that may occur irrespective of clearly identifiable pathology [ 26 ] .Their occurrence is shaped by a complex interplay of biological, psychological, and social factors and is commonly observed in both acute and chronic diseases [ 27 ] . Ketterer and Knysz investigated the relative contributions of emotional distress and established cardiac risk factors to cardiac related symptoms (including chest pain, fatigue, palpitations, presyncope, and dyspnea) and found that emotion regulation indicators were more strongly associated with these symptoms than traditional risk factors [ 28 ] . Previous studies have consistently reported a high prevalence of alexithymia and impairments in CERS among patients with CHD [ 19 ] . Alexithymia, reflecting deficits in individuals’ emotional awareness, may lead to difficulties in emotional processing and increase reliance on maladaptive regulation strategies. This, in turn, can heighten sensitivity to bodily sensations and disrupt the cognitive appraisal of symptoms, thereby affecting the perception of physical symptoms. Although previous studies have reported associations between alexithymia, CERS, and physical symptoms, no study to date has systematically examined their independent contributions to physical symptom burden in patients with coronary heart disease while controlling for demographic and clinical covariates [ 19 , 29 ] . Building on this rationale, the present study aimed to systematically investigate the relationships among alexithymia, CERS, and PS in patients with CHD. We formulated three primary hypotheses: first, patients with CHD would differ from healthy controls in levels of alexithymia and patterns of cognitive emotion regulation, reflecting interconnected impairments in emotional awareness and regulation; second, among patients with CHD, higher levels of alexithymia would be associated with greater reliance on maladaptive strategies and reduced use of adaptive strategies, independent of demographic and clinical factors; third, alexithymia and cognitive emotion regulation strategies were expected to show distinct and additive associations with physical symptom, indicating that deficits in emotional awareness and maladaptive CERS may jointly contribute to symptom experience in this population. Methods This study included 199 patients with CHD who were recruited from the cardiology outpatient clinics of Fuwai Central China Cardiovascular Hospital (age range = 40–80 years; mean age = 61.37 years) using a convenience sampling method. The diagnosis of CHD was confirmed by a cardiology subspecialist based on the presence of typical angina symptoms, supported by electrocardiogram (ECG) or stress testing, imaging evidence of ≥ 50% coronary artery stenosis, or a documented history of myocardial infarction or coronary revascularization. A total of 116 healthy controls (63 males, 53 females) were recruited from the community through convenience sampling, including hospital-affiliated wellness programs and online announcements. All participants completed the study questionnaires within 10–20 minutes under researcher supervision, with no prior treatment received and no emotional distress reported during the process. Prior to enrollment in the assessment, each participant provided written informed consent.The study was approved by the institutional ethics committee (approval number: 2025LI016) and registered with the Chinese Clinical Trial Registry (ChiCTR) on February 6, 2025, with the trial number ChiCTR2500096793. The Physical Symptoms Inventory The Physical Symptoms Inventory (PSI) assesses the frequency of common physical symptoms, including headaches, fatigue, palpitations, dizziness, gastrointestinal discomfort, and sleep disturbances [ 30 ] . In this study, the PSI was translated into Chinese for administration. Participants rated each item on a 4-point scale from 0 (“never”) to 3 (“every day”), with higher scores indicating more frequent symptoms. While a formal Chinese validation of the PSI is not available, the measure demonstrated good internal consistency in the present sample (Cronbach’ s α = 0.84), supporting its reliability for assessing physical symptom burden. The Toronto Alexithymia Scale-20 The Toronto Alexithymia Scale-20 (TAS-20) is the most widely used instrument for assessing alexithymia in both research and clinical settings [ 31 ] . The TAS-20 evaluates alexithymia across three subscales: Difficulty Identifying Feelings (DIF), Difficulty Describing Feelings (DDF), and Externally-Oriented Thinking (EOT). Each item is rated on a 5-point Likert scale (1 = “almost never” to 5 = “always”). This study used the Chinese version, which has demonstrated good reliability and structural validity [ 32 ] . Participants were classified according to standard cut-offs: alexithymic (≥ 61), borderline (52–60), and non-alexithymic (≤ 51) [ 33 ] . In the present sample, the TAS-20 demonstrated excellent internal consistency (Cronbach’s α = 0.93; DIF = 0.84, DDF = 0.76, EOT = 0.73). The Cognitive Emotion Regulation Questionnaire The Cognitive Emotion Regulation Questionnaire(CERQ) was developed by Garnefski to assess individuals' cognitive regulation strategies when facing negative events [ 34 ] . Cognitive emotion regulation strategies (CERS) refer to the mental techniques individuals use to manage, modify, or control their emotional responses. The questionnaire typically contains 36 items, with 4 items for each strategy. Including adaptive CERS (i.e., perspective-taking, positive refocusing, positive reappraisal, acceptance, and planning) and maladaptive CERS (i.e., self-blame, other-blame, rumination, and catastrophizing). The rating scale usually ranges from 1 (not applicable at all) to 5 (completely applicable). The Chinese version of the CERQ (CERQ-C) was administered, and its psychometric properties have been supported in Chinese adolescent and clinical samples [ 35 ] . In this sample, the CERQ demonstrated good internal consistency (Cronbach’s α = 0.82). Statistical analyses This study investigated psychological differences between patients with CHD and healthy controls, with a focus on the potential impact of emotion regulation and alexithymia on cardiac functional classification and PSI scores in CHD patients. Descriptive statistics were used to summarize sociodemographic and clinical characteristics, reported as frequencies, percentages, means ± standard deviations, and medians with interquartile ranges, as appropriate. These data provided a basis for subsequent group comparisons and correlation analyses. Comparisons of clinical and demographic variables between CHD patients and healthy controls were conducted using independent samples t-tests and chi-square (χ²) tests. Analysis of variance (ANOVA) and analysis of covariance (ANCOVA) were employed to compare alexithymia subscale scores and cognitive CERS between groups. ANCOVA was also used to assess differences in New York Heart Association (NYHA) functional classification, adaptive and maladaptive CERS, and PSI scores between CHD patients with and without alexithymia, adjusting for covariates including education, age, sex and disease duration. Effect sizes were calculated accordingly. Spearman correlation analysis was conducted to examine associations among sex, age, disease duration, alexithymia subscales, adaptive and maladaptive CERS, PS scores, and NYHA functional classification. Partial correlation analysis was used to assess the relationships between alexithymia subscales, CERS, and PS scores in CHD patients while controlling for NYHA functional classification and age. Finally, multiple linear regression analysis was performed to explore the predictive effects of alexithymia and maladaptive CERS scores on PSI, identifying significant independent contributors. Results Demographic and clinical characteristics Demographic and clinical characteristics are presented in Table 1 . There were no significant differences between the two groups in terms of sex distribution (χ² = 1.91, p = 0.16) or age (CHD: 61.37 ± 9.94 years; controls: 60.63 ± 8.42 years; t = 0.67, p = 0.50). However, a significant difference was observed in education level between the groups (χ² = 8.90, p = 0.01). A higher proportion of CHD patients had an education level of middle school or below (63.8%) compared to controls (47.4%), while a greater proportion of controls had completed high school or college education. The mean disease duration among CHD patients was 15.9 ± 9.8 months. Table 1 Sociodemographic and Clinical Characteristics of Patients with Coronary Heart Disease (CHD) and Healthy Controls Variable CHD Group (n = 199) Normal Controls (n = 116) t / χ² p Sex [n (%)] 1.91 0.16 Male 92 (46.2%) 63 (54.3%) Female 107 (53.8%) 53 (45.7%) Age (years, mean ± SD) 61.37 ± 9.94 60.63 ± 8.42 0.67 0.50 Education Level [n (%)] 8.90 0.01* Middle school or below 127 (63.8%) 55 (47.4%) High school 66 (33.2%) 53 (45.7%) College and above 6 (3.0%) 8 (6.9%) Marital Status [n (%)] 6.84 0.10 Married 171 (85.9%) 99 (85.3%) Divorced 20 (10.1%) 14 (12.1%) Widowed 8 (4.0%) 1 (0.9%) Disease duration (months) 15.9 ± 9.8 – – – NYHA functional classification [n (%)] – – – NYHA I 75 (37.7%) NYHA II 102 (51.3%) NYHA III 22(11.1%) Differences in Alexithymia and Cognitive Emotion Regulation Between CHD Patients and Healthy Controls As shown in Table 2 , Significant differences were observed between CHD patients and healthy controls across several alexithymia subscales and CERS. Compared with controls, CHD patients exhibited significantly higher scores in DIF (F = 8.47, p < 0.01), DDF (F = 46.56, p < 0.01), and EOT (F = 4.91, p < 0.05). Regarding emotion regulation, CHD patients scored markedly lower in adaptive CERS overall (F = 129.58, p < 0.01), including positive refocusing (F = 103.46, p < 0.01), refocusing on planning (F = 147.73, p < 0.01), and positive reappraisal (F = 191.42, p 0.05), while acceptance was significantly lower in CHD patients (F = 37.18, p < 0.01). In contrast, CHD patients demonstrated significantly higher scores in maladaptive CERS (F = 76.86, p < 0.01), including self-blame (F = 90.64, p < 0.01), rumination (F = 13.51, p < 0.01), catastrophizing (F = 20.84, p < 0.01), and other-blame (F = 26.68, p < 0.01). These findings indicate that CHD patients tend to exhibit higher levels of alexithymia and rely more on maladaptive emotion regulation strategies, while showing lower use of adaptive strategies, highlighting the potential targets for psychological interventions in this population. Table 2 Comparison of alexithymia subscales and adaptive and maladaptive CERS in CHD patients and normal controls (mean ± SD) Characteristics CHD Patients (n = 199) Normal Controls (n = 115) F a F b Alexithymia Subscales DIF 17.72 ± 4.42 16.19 ± 3.88 9.65** 8.47** DDF 15.20 ± 4.11 14.16 ± 3.21 49.35** 46.56** EOT 21.79 ± 4.51 20.55 ± 4.34 5.71* 4.91* CERS Adaptive CERS 46.61 ± 8.24 58.74 ± 9.58 140.67** 129.58 ** Positive refocusing 8.02 ± 2.86 11.62 ± 3.11 109.46** 103.46** Refocusing on planning 7.61 ± 2.96 12.16 ± 2.38 159.41** 147.73** Positive reappraisal 7.86 ± 3.13 13.22 ± 3.35 203.87** 191.42** Putting into perspective 10.46 ± 3.34 11.05 ± 2.99 2.50 1.66 Acceptance 10.70 ± 2.90 12.66 ± 2.61 38.29** 37.18** maladaptive CERS 47.17 ± 8.42 38.83 ± 7.16 83.17** 76.86** Self-Blame 14.32 ± 3.39 10.51 ± 3.26 95.27** 90.64** Rumination 11.25 ± 2.61 10.82 ± 2.61 15.17** 13.51** Catastrophising 10.80 ± 3.07 9.11 ± 2.84 23.51** 20.84** Other-Blame 10.79 ± 2.73 9.12 ± 2.48 29.31** 26.68** PSI 29.50 ± 5.96 18.42 ± 5.65 278.50** 266.11** DIF: Difficulty Identifying Feelings DDF: Difficulty Describing Feelings EOT: Externally Oriented Thinking CERS: Cognitive Emotion Regulation Strategies F a : Analysis of variance (ANOVA). F b : Analysis of covariance (ANCOVA) adjusted for education as covariate. p < 0.05 was considered statistically significant. * P <0.05. ** P <0.01. Impact of Alexithymia on Emotion Regulation, Physical Symptoms, and Cardiac Function in CHD As shown in Table 3 , group comparisons revealed significant differences in maladaptive CERS, adaptive CERS, PSI scores, and NYHA functional classification across alexithymia subgroups. As shown in Table 3 , 62 (31.1%) were identified as having alexithymia, 57 (28.3%) were classified as borderline alexithymic, and 80 (46.6%) were considered non-alexithymic. The results indicated that the alexithymia group showed significantly higher scores in maladaptive CERS compared to the non-alexithymia group (F = 30.08, p < 0.01), and the borderline alexithymia group also scored significantly higher than the non-alexithymia group ( p < 0.05). Significant group differences were also observed in PSI (F = 31.63, p < 0.01). scores on adaptive CERS were significantly lower in the alexithymic and borderline alexithymic groups compared to the non-alexithymic group (F = 3.46, p < 0.05). Notably, PSI exhibited the largest effect size among the outcome variables, with a Cohen’s d of 0.35, which corresponds to a moderate-to-large magnitude of effect. Ordinal logistic regression analysis indicated that patients in the alexithymia group had significantly higher odds of being classified into a worse NYHA compared to the non-alexithymia group (OR = 2.47, 95% CI [0.11, 1.69], p = 0.024). Table 3 Comparison of maladaptive and Adaptive Cognitive Emotion Regulation, Physical Symptoms, and Cardiac Function Among Alexithymia Subgroups in CHD Patients by controlling gender, age, education, and disease duration (n = 199) Variable Overall (n = 199) Alexithymic (n = 62) Borderline (n = 57) Non-alexithymic (n = 80) F / χ² (p) η² maladaptive CERS 59.75 ± 8.37 52.69 ± 5.30 48.98 ± 6.63 41.53 ± 7.84 30.08** (P < 0.01) 0.23 Adaptive CERS 33.81 ± 7.53 43.61 ± 6.48 45.64 ± 8.06 48.89 ± 6.58 3.46* (P < 0.05) 0.03 PSI 29.49 ± 5.96 32.80 ± 4.38 32.01 ± 4.78 25.13 ± 5.05 31.63** (P < 0.01) 0.24 NYHA functional class 1.71 ± 0.62 1.93 ± 0.69 1.68 ± 0.60 1.61 ± 0.60 5.09* (P = 0.024) — Note: CERS: cognitive emotion regulation strategies; PS: physical symptoms. Data are expressed as mean ± standard deviation or otherwise specified. ANCOVA and partialη2 were employed for dimensional variables. Correlations Between Alexithymia, Cognitive Emotion Regulation, and Physical Symptoms in CHD Patients As shown in Table 4 and Fig. 2 , spearman correlation analysis revealed that PSI scores were significantly and positively correlated with age (r = 0.37, p < 0.01), NYHA (r = 0.14, p < 0.05), maladaptive CERS (r = 0.40, p < 0.01), and all three subscales of alexithymia: DIF (r = 0.48, p < 0.01), DDF (r = 0.44, p < 0.01), and EOT (r = 0.41, p 0.05). Table 4 Spearman Correlations Between Physical Symptom Scores and Demographic, Clinical, and Psychological Variables Variable Spearman’s r p-value Age 0.37 < 0.01** Educational level −0.09 0.20 Disease duration 0.04 0.58 NYHA functional classification 0.14 0.049* Adaptive CERS −0.09 0.21 Maladaptive CERS 0.40 < 0.01** DIF 0.48 < 0.01** DDF 0.44 < 0.01** EOT 0.41 < 0.01** Note: PSI = Physical Symptom Inventory; CERS = Cognitive Emotion Regulation Strategies; DIF, DDF, EOT = Subscales of the Toronto Alexithymia Scale (TAS-20). Pearson correlation coefficients were used, p < 0.05 was considered statistically significant. As shown in Table 5 and Fig. 3 , when partial correlation was used to control NYHA functional classification and age, the results showed that the subscales of DIF (pr = 0.34, p < 0.01), DDF (pr = 0.29, p < 0.01), and EOT (pr = 0.30, p < 0.01) were still correlated with PS. Also, the significant positive correlation between the maladaptive CERS and PS was found (pr = 0.32, p < 0.01). Table 5 Partial correlations between alexithymia subscales and adaptive and maladaptive CERS with PS in patients with CHD (n = 199) 1 2 3 4 5 6 1-DIF — 2-DDF 0.52** — 3-EOT 0.09 0.09 — 4-Adaptive CERS -0.04 -0.11 -0.20** — 5-Maladaptive CERS 0.33** 0.33** 0.32** 0.04 — 6-PSI 0.34** 0.29** 0.30** -0.01 0.32** — Note: Partial correlations by controlling age and NYHA DDF: difficulty describing feelings; EOT: externally oriented thinking; DIF: difficulty identifying feelings; CERS: cognitive emotion regulation strategies; PS: physical symptoms. * p < 0.05. ** p < 0.01. As shown in Table 6 , regression analyses examined the predictors of PSI in CHD patients. In Model 1, age (B = 0.22, β = 0.38, t = 5.85, p < 0.01) significantly predicted PSI, while NYHA grade showed a non-significant trend (B = 0.99, β = 0.11, t = 1.63, p = 0.10), explaining 17% of the variance. Adding DIF in Model 2 significantly improved the model (ΔR² = 0.09, ΔF = 25.04, p < 0.001), with DIF emerging as a strong predictor (B = 0.46, β = 0.35, t = 5.00, p < 0.001). In Model 3, DDF contributed minimally (B = 0.23, β = 0.16, t = 2.00, p = 0.05), with a small increase in explained variance (ΔR² = 0.02, ΔF = 3.99, p = 0.05). When EOT was included in Model 4, it significantly predicted PSI (B = 0.34, β = 0.26, t = 4.07, p < 0.001), further increasing explained variance (ΔR² = 0.06, ΔF = 16.53, p < 0.001). In the final model (Model 5), maladaptive CERS was also added (B = 0.09, β = 0.13, t = 1.86, p = 0.06), and the full model accounted for 35% of the variance (ΔR² = 0.01, ΔF = 3.46, p = 0.06). These results indicate that DIF, EOT, and maladaptive CERS are key psychological predictors of physical symptom severity in CHD, beyond the effects of age and NYHA functional classification. Table 6 Regression analysis for PS in CHD patients (n = 199) Model Variable B SE β t p R² ΔR² F ΔF p (model) 1 (Constant) 12.87 2.73 — 4.72 .00 0.17 — 13.72 — < 0.001** 1 Gender 0.83 0.78 0.07 1.07 0.29 1 Age 0.22 0.04 0.38 5.85 .00 1 NYHAgrade 0.99 0.60 0.11 1.63 0.10 2 (Constant) 11.03 2.60 — 4.25 .00 0.27 0.09 17.82 25.04 < 0.001** 2 Gender 0.49 0.74 0.04 0.67 0.50 2 Age 0.14 0.04 0.25 3.69 .00 2 NYHAgrade 0.38 0.58 0.04 0.66 0.51 2 DIF 0.46 0.09 0.35 5.00 .00 3 (Constant) 10.80 2.58 — 4.18 .00 0.28 0.02 15.27 3.99 0.05 3 Gender 0.48 0.73 0.04 0.65 0.52 3 Age 0.12 0.04 0.22 3.13 0.00 3 NYHAgrade 0.32 0.58 0.03 0.55 0.58 3 DIF 0.35 0.11 0.26 3.28 0.00 3 DDF 0.23 0.12 0.16 2.00 0.05 4 (Constant) 7.26 2.63 — 2.76 0.01 0.34 0.06 16.51 16.53 < 0.001** 4 Gender 0.41 0.70 0.03 0.58 0.56 4 Age 0.07 0.04 0.13 1.80 0.07 4 NYHAgrade 0.36 0.56 0.04 0.65 0.52 4 DIF 0.33 0.10 0.25 3.22 0.00 4 DDF 0.21 0.11 0.14 1.86 0.06 4 EOT 0.34 0.08 0.26 4.07 .00 5 (Constant) 4.17 3.10 — 1.35 0.18 0.35 0.01 14.83 3.46 0.06 5 Gender 0.45 0.70 0.04 0.64 0.52 5 Age 0.07 0.04 0.13 1.81 0.07 5 NYHAgrade 0.28 0.56 0.03 0.50 0.62 5 DIF 0.30 0.11 0.22 2.82 0.01 5 DDF 0.17 0.11 0.12 1.48 0.14 5 EOT 0.29 0.09 0.22 3.34 0.00 5 maladaptive CERS 0.09 0.05 0.13 1.86 0.06 Note. β = standardized coefficientNYHA: NYHA functional classification; DIF: difficulty identifying feelings; EOT: externally oriented thinking; CERS: cognitive emotion regulation strategies; PS: physical symptoms* p < 0.05** p < 0.01 Discussion In summary, the present study highlights that both alexithymia and maladaptive cognitive emotion regulation strategies are highly prevalent among patients with CHD. Approximately 60% of participants met criteria for borderline or full alexithymia, and those with higher alexithymia scores relied more heavily on maladaptive strategies while using adaptive strategies less frequently, which supports previous research on alexithymia in cardiac populations [ 36 ] . Recent evidence also indicates that emotion regulation tendencies, including maladaptive responses such as expressive suppression or other maladaptive strategies, are significantly related to perceived stress and psychological adjustment in patients with CHD, underscoring the clinical relevance of emotion regulation difficulties in this group [ 36 , 37 ] . Importantly, our analyses indicated that DIF, EOT, and greater reliance on maladaptive cognitive emotion regulation strategies jointly accounted for 35% of the variance in physical symptom burden among CHD patients. This aligns with empirical evidence indicating that maladaptive emotion regulation strategies, such as expressive suppression, moderate the relationship between psychological distress (e.g., depressive symptoms) and physiological indices linked to cardiac health in CHD populations (e.g., expressive suppression moderating depression - vmHRV associations in cardiac patients) [ 37 ] . Furthermore, broader research on emotion regulation and cardiovascular risk suggests that frequent use of maladaptive strategies (e.g., rumination, suppression) is linked with greater psychological stress and adverse health outcomes, consistent with biopsychosocial models of disease [ 38 ] . By highlighting these associations, our results underscore the critical role of emotional awareness deficits and maladaptive regulation in shaping both psychological distress and somatic symptom perception in CHD. Building on these core findings, the present results suggest that impaired emotional awareness (alexithymia) combined with habitual reliance on maladaptive cognitive emotion regulation strategies may represent key psychological factors contributing to increased physical symptom burden in patients with coronary heart disease (CHD). Specifically, individuals who struggle to identify their own emotions tend to perceive emotional arousal as vague, poorly differentiated bodily sensations rather than clearly recognizable emotional experiences [ 39 , 40 ] . When emotional signals cannot be adequately recognized or cognitively processed, they are more likely to be interpreted at a somatic level, amplifying symptom perception and intensifying bodily discomfort [ 41 ] . Externally oriented thinking (EOT) may further reinforce this pattern. A cognitive style characterised by reduced attention to internal emotional states has been linked to limitations in reflective processing and diminished use of adaptive emotion regulation strategies such as cognitive reappraisal, with high levels of alexithymia associated with less frequent use of adaptive regulation and greater reliance on maladaptive strategies [ 42 ] . In this context, maladaptive cognitive emotion regulation strategies—specifically rumination, emotional suppression, and catastrophizing—may serve as compensatory efforts to cope with emotional experiences that are difficult to recognize or fully grasp [ 43 , 44 ] . However, maladaptive CERS such as rumination and expressive suppression often fail to effectively reduce emotional distress; instead, they are associated with persistent emotional arousal and increased somatic symptom reporting. Prior research indicates that dysfunctional emotion regulation profiles characterized by reduced emotional awareness and reliance on maladaptive responses are linked with greater somatic symptom severity in clinical populations and somatic symptom disorders [ 45 , 46 ] . From a biopsychosocial perspective, the psychological processes identified in this study are likely to interact with physiological pathways relevant to cardiovascular functioning. Accumulating evidence indicates that impaired emotion processing and maladaptive emotion regulation are linked to prolonged activation of the hypothalamic-pituitary-adrenal axis [ 47 ] , heightened sympathetic nervous system activity [ 48 ] , and persistent low-grade inflammation [ 49 ] . Together, these alterations may contribute to the maintenance of physical symptoms and increased bodily sensitivity in patients with CHD. Although the present study did not directly assess these mechanisms, the overall pattern of findings is consistent with theoretical models of chronic illness, suggesting that maladaptive emotion regulation increases vulnerability to the amplification of physical symptoms. Building on previous research, this study specifically examined distinct dimensions of alexithymia and emotion regulation. After controlling for relevant covariates, DIF and EOT showed stronger associations with physical symptoms than overall alexithymia scores, highlighting the importance of distinguishing between different facets of emotion processing. Moreover, maladaptive CERS explained additional variance beyond alexithymia, suggesting that impaired emotional awareness and maladaptive regulation, while related, represent partially distinct psychological processes. An increasing body of evidence indicates that interventions such as emotion-focused therapy, mindfulness-based programs, and structured emotion skills training can enhance emotion regulation, reduce alexithymic traits, and decrease reliance on maladaptive strategies like rumination, suppression, and catastrophizing, thereby strengthening the functional link between emotional processing and regulation [ 50 , 51 ] . In patients with CHD, although behavioral health interventions-most notably cognitive-behavioral therapy (CBT)-have been shown to effectively reduce depression and anxiety, relatively few studies have specifically targeted distinct dimensions of alexithymia (such as difficulties in identifying feelings and externally oriented thinking) or patterns of emotion regulation, including both adaptive and maladaptive strategies [ 52 ] . In light of the present findings, which indicate that impaired emotional awareness and maladaptive cognitive emotion regulation strategies exert independent and additive effects on physical symptom burden, further intervention research explicitly focused on emotional processing and emotion regulation is warranted. Strengths and limitations This study had several strengths. First, it is one of the few to examine the links between alexithymia, CERS, and physical symptoms in CHD patients, providing evidence for the role of emotional dysregulation in somatic outcomes. Second, by separating adaptive from maladaptive CERS, it shows how specific strategies (e.g., positive reappraisal vs. self-blame, rumination) relate differently to symptoms, adding clinical value. Third, the use of partial correlations and hierarchical regression, with control for age and NYHA class, strengthens the methodological rigor. Finally, the findings highlight the psychological aspects of CHD and underline the need to assess and manage alexithymia and maladaptive regulation strategies in clinical care. However, this study has certain limitations: its cross-sectional design prevents causal inferences; participants were not stratified by CHD subtype; intervention effects on alexithymia and emotion regulation were not assessed; and the sample was limited to ages 40–80, restricting generalizability. Conclusion In patients with coronary heart disease, levels of alexithymia were elevated, accompanied by greater use of maladaptive emotion regulation strategies and reduced use of adaptive strategies. About 60% of participants met criteria for borderline or clinical alexithymia, which was strongly linked to maladaptive regulation. Difficulty identifying feelings, externally oriented thinking, and maladaptive strategies together explained 35% of the variance in physical symptoms, indicating a significant psychological contribution to patients’ symptom burden. These results highlight the need for routine psychological assessment and interventions targeting emotion regulation in cardiac care. Abbreviations CHD Coronary heart disease CERS Cognitive emotion regulation strategies TAS-20 Toronto Alexithymia Scale PSI Physical Symptoms Inventory DIF difficulties identifying feelings DDF difficulties describing feelings EOT externally oriented thinking NYHA New York Heart Association Declarations Acknowledgements We thank all patients who participated in this study for their time and cooperation. We also acknowledge the clinical staff of Fuwai Central China Cardiovascular Hospital for their assistance with participant recruitment and data collection. Author contributions JY and ZYS supervised the research direction, experimental procedures, and manuscript preparation. JY and NYM contributed to study conceptualization and performed the statistical analyses and data visualization. NYM and JXW were responsible for data collection and assisted with study implementation. DXF and SL critically reviewed and revised the manuscript. All authors read and approved the final manuscript. Funding YJ is supported by an institutional research grant from Fuwai Central China Cardiovascular Hospital(ZCK2023070). Data availability The database supporting the reported results is available only upon request due to confidentiality and ethical restrictions. This can be requested from the author of correspondence. Ethics approval and consent to participate This study was approved by the Ethics Committee of Fuwai Central China Cardiovascular Hospital (approval number: 2025LI016). All procedures were conducted in accordance with the principles of the Declaration of Helsinki. The study was approved by the institutional ethics committee and registered with the Chinese Clinical Trial Registry (ChiCTR), with the trial number ChiCTR2500096793.Written informed consent was obtained from all participants prior to their inclusion in the study. The study was conducted under the project registration number (ZCK2023070). Consent for publication Not applicable. Competing interests The authors declare no competing interests. Funding This study was supported by research project of Fuwai Central China Cardiovascular Hospital. Data availability statement The data supporting the findings of this study are not publicly available due to privacy and ethical restrictions, but they can be requested from the corresponding author, Dr. Feng. References ROTH G A, MENSAH G A, JOHNSON C O, et al. 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The emotion regulation process in somatic symptom disorders and related conditions - A systematic narrative review [J]. Clin Psychol Rev. 2022;97:102196. MOORE S, ZOELLNER L, MOLLENHOLT N. Are expression and cognitive reappraisal associated with stress-related symptoms? [J]. Behav Res Ther. 2008;46:993–1000. SLAVICH GM, Stressnology. The primitive (and problematic) study of life stress exposure and pressing need for better measurement [J]. Brain Behav Immun. 2019;75:3–5. KEMP A H, KOENIG J, THAYER JF. From psychological moments to mortality: A multidisciplinary synthesis on heart rate variability spanning the continuum of time [J]. Neurosci Biobehav Rev. 2017;83:547–67. KIECOLT-GLASER J K, RENNA M E, SHROUT M R, et al. Stress Reactivity: What Pushes Us Higher, Faster, and Longer - and Why It Matters [J]. Curr Dir Psychol Sci. 2020;29(5):492–8. NORMAN H, MARZANO L, COULSON M, et al. Effects of mindfulness-based interventions on alexithymia: a systematic review [J]. Evid Based Ment Health. 2019;22(1):36–43. SILVEIRA S, GODARA M, FASCHINGER A, et al. Reducing alexithymia and increasing interoceptive awareness: A randomized controlled trial comparing mindfulness with dyadic socio-emotional app-based practice [J]. J Affect Disord. 2023;341:162–9. PRUESSNER L, HARTMANN S, EHMANN A L, et al. Digital Emotion Regulation Interventions for Patients With Congenital Heart Disease: A Randomized Clinical Trial [J]. JAMA Netw Open. 2025;8(10):e2538813. Additional Declarations No competing interests reported. Supplementary Files supplementaryinformation.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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1","display":"","copyAsset":false,"role":"figure","size":70636,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of Study Design\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8530045/v1/8ebc569c9bd6e72894852cff.png"},{"id":101206499,"identity":"88241946-e5f5-4189-bc80-2436ccd5204d","added_by":"auto","created_at":"2026-01-27 09:56:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":35825,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation Between PSI and Other Variables\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8530045/v1/44ef33b8da6091eace562209.png"},{"id":101206235,"identity":"de59c819-d46e-4f92-81bc-7747f27c36bf","added_by":"auto","created_at":"2026-01-27 09:55:42","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":40293,"visible":true,"origin":"","legend":"\u003cp\u003ePartial Correlation Heamap (CHD Patients)\u003c/p\u003e\n\u003cp\u003eNote: Partial correlations by controlling age and NYHA\u003c/p\u003e\n\u003cp\u003eDDF: difficulty describing feelings; EOT: externally oriented thinking; DIF: difficulty identifying feelings; CERS: cognitive emotion regulation strategies; PS: physical symptoms.\u003c/p\u003e\n\u003cp\u003e*\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e**\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8530045/v1/b6e2576905d18886ad23a44f.png"},{"id":104834886,"identity":"829fa514-b626-40eb-b92a-7203edd6120b","added_by":"auto","created_at":"2026-03-17 17:34:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1445977,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8530045/v1/b3162830-600a-43dc-9a1e-d1f379b7cbd7.pdf"},{"id":101171250,"identity":"db730a45-93ed-4bc9-8827-73165c97cb06","added_by":"auto","created_at":"2026-01-27 00:08:01","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":31864,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-8530045/v1/5ee060680b7a6690c98a62c1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Associations Between Alexithymia, Cognitive Emotion Regulation, and Physical Symptoms in Coronary Heart Disease","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCoronary heart disease (CHD) is a common, heterogeneous, and distressing condition that ranks among the leading causes of death worldwide, exerting a profound impact on both society and individuals\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Traditional risk factors for CHD include hypertension, hypercholesterolemia, smoking, diabetes, obesity, and genetic predisposition\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Emerging evidence highlights the critical role of psychological factors, particularly difficulties in emotion regulation and alexithymia, alongside biological alterations such as endothelial dysfunction and systemic inflammation, in influencing cardiac dysfunction, prognosis, and quality of life in CHD patients\u003csup\u003e[\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAlexithymia, defined as difficulties in identifying and regulating emotions\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e, is closely associated with impairments in emotional cognitive processing. Accumulating evidence suggests that alexithymia is linked to a wide range of medical and psychiatric conditions, as well as maladaptive illness-related behaviors\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. and is associated with more severe depressive symptoms, lower life satisfaction, and a greater psychological burden\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. It was found that alexithymia was associated with a previous diagnosis of CHD\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Alexithymia has been reported to show independent associations with hypertension and carotid atherosclerosis in some studies\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e, is linked to coronary artery spasm, and may contribute to the onset of hypertension and its symptomatic manifestations\u003csup\u003e[\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. In addition, alexithymia has been associated with an increased risk of post-traumatic stress disorder following myocardial infarction\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Despite growing interest in psychological factors in CHD, evidence on the associations between alexithymia and other clinical symptoms remains scarce. Addressing this gap, the present study investigates how alexithymia relates to key psychological factors in patients with CHD.\u003c/p\u003e \u003cp\u003ePrevious studies have consistently confirmed that there is a close association between alexithymia and difficulties in emotion regulation\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. cognitive emotion regulation strategies (CERS) play a crucial role in individuals' responses to stressful events and adaptation to life changes, and are related to psychological and physical reactions\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Emotion regulation strategies are divided into adaptive CERS and maladaptive CERS\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. The emotion regulation process seems to be disrupted in acute and chronic diseases, with adaptive approaches replaced by maladaptive CERS\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e.In the population of patients with coronary heart disease, existing studies have found that compared with healthy individuals, patients with comorbid depressive symptoms use maladaptive CERS more frequently in emotion coping \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e.These strategies have been proven to potentially increase the risk of adverse cardiovascular outcomes and death indirectly by aggravating psychological stress responses and physiological load\u003csup\u003e[\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePhysical symptoms (PS) refer to individuals\u0026rsquo;subjective perceptions of bodily discomfort or functional abnormalities, including pain, fatigue, palpitations, and dyspnea, and are characterized by persistent physical sensations that may occur irrespective of clearly identifiable pathology\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e.Their occurrence is shaped by a complex interplay of biological, psychological, and social factors and is commonly observed in both acute and chronic diseases\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Ketterer and Knysz investigated the relative contributions of emotional distress and established cardiac risk factors to cardiac related symptoms (including chest pain, fatigue, palpitations, presyncope, and dyspnea) and found that emotion regulation indicators were more strongly associated with these symptoms than traditional risk factors\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePrevious studies have consistently reported a high prevalence of alexithymia and impairments in CERS among patients with CHD\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. Alexithymia, reflecting deficits in individuals\u0026rsquo; emotional awareness, may lead to difficulties in emotional processing and increase reliance on maladaptive regulation strategies. This, in turn, can heighten sensitivity to bodily sensations and disrupt the cognitive appraisal of symptoms, thereby affecting the perception of physical symptoms. Although previous studies have reported associations between alexithymia, CERS, and physical symptoms, no study to date has systematically examined their independent contributions to physical symptom burden in patients with coronary heart disease while controlling for demographic and clinical covariates\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBuilding on this rationale, the present study aimed to systematically investigate the relationships among alexithymia, CERS, and PS in patients with CHD. We formulated three primary hypotheses: first, patients with CHD would differ from healthy controls in levels of alexithymia and patterns of cognitive emotion regulation, reflecting interconnected impairments in emotional awareness and regulation; second, among patients with CHD, higher levels of alexithymia would be associated with greater reliance on maladaptive strategies and reduced use of adaptive strategies, independent of demographic and clinical factors; third, alexithymia and cognitive emotion regulation strategies were expected to show distinct and additive associations with physical symptom, indicating that deficits in emotional awareness and maladaptive CERS may jointly contribute to symptom experience in this population.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis study included 199 patients with CHD who were recruited from the cardiology outpatient clinics of Fuwai Central China Cardiovascular Hospital (age range\u0026thinsp;=\u0026thinsp;40\u0026ndash;80 years; mean age\u0026thinsp;=\u0026thinsp;61.37 years) using a convenience sampling method. The diagnosis of CHD was confirmed by a cardiology subspecialist based on the presence of typical angina symptoms, supported by electrocardiogram (ECG) or stress testing, imaging evidence of \u0026ge;\u0026thinsp;50% coronary artery stenosis, or a documented history of myocardial infarction or coronary revascularization. A total of 116 healthy controls (63 males, 53 females) were recruited from the community through convenience sampling, including hospital-affiliated wellness programs and online announcements. All participants completed the study questionnaires within 10\u0026ndash;20 minutes under researcher supervision, with no prior treatment received and no emotional distress reported during the process. Prior to enrollment in the assessment, each participant provided written informed consent.The study was approved by the institutional ethics committee (approval number: 2025LI016) and registered with the Chinese Clinical Trial Registry (ChiCTR) on February 6, 2025, with the trial number ChiCTR2500096793.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eThe Physical Symptoms Inventory\u003c/h2\u003e \u003cp\u003eThe Physical Symptoms Inventory (PSI) assesses the frequency of common physical symptoms, including headaches, fatigue, palpitations, dizziness, gastrointestinal discomfort, and sleep disturbances\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. In this study, the PSI was translated into Chinese for administration. Participants rated each item on a 4-point scale from 0 (\u0026ldquo;never\u0026rdquo;) to 3 (\u0026ldquo;every day\u0026rdquo;), with higher scores indicating more frequent symptoms. While a formal Chinese validation of the PSI is not available, the measure demonstrated good internal consistency in the present sample (Cronbach\u0026rsquo; s α\u0026thinsp;=\u0026thinsp;0.84), supporting its reliability for assessing physical symptom burden.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe Toronto Alexithymia Scale-20\u003c/h3\u003e\n\u003cp\u003eThe Toronto Alexithymia Scale-20 (TAS-20) is the most widely used instrument for assessing alexithymia in both research and clinical settings \u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. The TAS-20 evaluates alexithymia across three subscales: Difficulty Identifying Feelings (DIF), Difficulty Describing Feelings (DDF), and Externally-Oriented Thinking (EOT). Each item is rated on a 5-point Likert scale (1 = \u0026ldquo;almost never\u0026rdquo; to 5 = \u0026ldquo;always\u0026rdquo;). This study used the Chinese version, which has demonstrated good reliability and structural validity\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Participants were classified according to standard cut-offs: alexithymic (\u0026ge;\u0026thinsp;61), borderline (52\u0026ndash;60), and non-alexithymic (\u0026le;\u0026thinsp;51) \u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. In the present sample, the TAS-20 demonstrated excellent internal consistency (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.93; DIF\u0026thinsp;=\u0026thinsp;0.84, DDF\u0026thinsp;=\u0026thinsp;0.76, EOT\u0026thinsp;=\u0026thinsp;0.73).\u003c/p\u003e\n\u003ch3\u003eThe Cognitive Emotion Regulation Questionnaire\u003c/h3\u003e\n\u003cp\u003eThe Cognitive Emotion Regulation Questionnaire(CERQ) was developed by Garnefski to assess individuals' cognitive regulation strategies when facing negative events\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. Cognitive emotion regulation strategies (CERS) refer to the mental techniques individuals use to manage, modify, or control their emotional responses. The questionnaire typically contains 36 items, with 4 items for each strategy. Including adaptive CERS (i.e., perspective-taking, positive refocusing, positive reappraisal, acceptance, and planning) and maladaptive CERS (i.e., self-blame, other-blame, rumination, and catastrophizing). The rating scale usually ranges from 1 (not applicable at all) to 5 (completely applicable). The Chinese version of the CERQ (CERQ-C) was administered, and its psychometric properties have been supported in Chinese adolescent and clinical samples\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. In this sample, the CERQ demonstrated good internal consistency (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.82).\u003c/p\u003e\n\u003ch3\u003eStatistical analyses\u003c/h3\u003e\n\u003cp\u003eThis study investigated psychological differences between patients with CHD and healthy controls, with a focus on the potential impact of emotion regulation and alexithymia on cardiac functional classification and PSI scores in CHD patients. Descriptive statistics were used to summarize sociodemographic and clinical characteristics, reported as frequencies, percentages, means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations, and medians with interquartile ranges, as appropriate. These data provided a basis for subsequent group comparisons and correlation analyses. Comparisons of clinical and demographic variables between CHD patients and healthy controls were conducted using independent samples t-tests and chi-square (χ\u0026sup2;) tests. Analysis of variance (ANOVA) and analysis of covariance (ANCOVA) were employed to compare alexithymia subscale scores and cognitive CERS between groups. ANCOVA was also used to assess differences in New York Heart Association (NYHA) functional classification, adaptive and maladaptive CERS, and PSI scores between CHD patients with and without alexithymia, adjusting for covariates including education, age, sex and disease duration. Effect sizes were calculated accordingly.\u003c/p\u003e \u003cp\u003eSpearman correlation analysis was conducted to examine associations among sex, age, disease duration, alexithymia subscales, adaptive and maladaptive CERS, PS scores, and NYHA functional classification. Partial correlation analysis was used to assess the relationships between alexithymia subscales, CERS, and PS scores in CHD patients while controlling for NYHA functional classification and age. Finally, multiple linear regression analysis was performed to explore the predictive effects of alexithymia and maladaptive CERS scores on PSI, identifying significant independent contributors.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDemographic and clinical characteristics\u003c/h2\u003e \u003cp\u003eDemographic and clinical characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. There were no significant differences between the two groups in terms of sex distribution (χ\u0026sup2; = 1.91, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.16) or age (CHD: 61.37\u0026thinsp;\u0026plusmn;\u0026thinsp;9.94 years; controls: 60.63\u0026thinsp;\u0026plusmn;\u0026thinsp;8.42 years; t\u0026thinsp;=\u0026thinsp;0.67, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.50). However, a significant difference was observed in education level between the groups (χ\u0026sup2; = 8.90, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01). A higher proportion of CHD patients had an education level of middle school or below (63.8%) compared to controls (47.4%), while a greater proportion of controls had completed high school or college education. The mean disease duration among CHD patients was 15.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8 months.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic and Clinical Characteristics of Patients with Coronary Heart Disease (CHD) and Healthy Controls\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCHD Group (n\u0026thinsp;=\u0026thinsp;199)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal Controls (n\u0026thinsp;=\u0026thinsp;116)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et / χ\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92 (46.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 (54.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e107 (53.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53 (45.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61.37\u0026thinsp;\u0026plusmn;\u0026thinsp;9.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.63\u0026thinsp;\u0026plusmn;\u0026thinsp;8.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation Level [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle school or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e127 (63.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (47.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66 (33.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53 (45.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital Status [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e171 (85.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99 (85.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (12.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNYHA functional classification [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNYHA I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75 (37.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNYHA II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e102 (51.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNYHA III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22(11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDifferences in Alexithymia and Cognitive Emotion Regulation Between CHD Patients and Healthy Controls\u003c/h3\u003e\n\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Significant differences were observed between CHD patients and healthy controls across several alexithymia subscales and CERS. Compared with controls, CHD patients exhibited significantly higher scores in DIF (F\u0026thinsp;=\u0026thinsp;8.47, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), DDF (F\u0026thinsp;=\u0026thinsp;46.56, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and EOT (F\u0026thinsp;=\u0026thinsp;4.91, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Regarding emotion regulation, CHD patients scored markedly lower in adaptive CERS overall (F\u0026thinsp;=\u0026thinsp;129.58, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), including positive refocusing (F\u0026thinsp;=\u0026thinsp;103.46, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), refocusing on planning (F\u0026thinsp;=\u0026thinsp;147.73, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and positive reappraisal (F\u0026thinsp;=\u0026thinsp;191.42, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The difference in putting into perspective was not statistically significant (F\u0026thinsp;=\u0026thinsp;1.66, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), while acceptance was significantly lower in CHD patients (F\u0026thinsp;=\u0026thinsp;37.18, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In contrast, CHD patients demonstrated significantly higher scores in maladaptive CERS (F\u0026thinsp;=\u0026thinsp;76.86, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), including self-blame (F\u0026thinsp;=\u0026thinsp;90.64, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), rumination (F\u0026thinsp;=\u0026thinsp;13.51, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), catastrophizing (F\u0026thinsp;=\u0026thinsp;20.84, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and other-blame (F\u0026thinsp;=\u0026thinsp;26.68, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). These findings indicate that CHD patients tend to exhibit higher levels of alexithymia and rely more on maladaptive emotion regulation strategies, while showing lower use of adaptive strategies, highlighting the potential targets for psychological interventions in this population.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of alexithymia subscales and adaptive and maladaptive CERS in CHD patients and normal controls (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCHD Patients\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;199)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal Controls\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;115)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlexithymia Subscales\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e17.72\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;4.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e16.19\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.65**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.47**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e15.20\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;4.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e14.16\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;3.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.35**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e46.56**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEOT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e21.79\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e20.55\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;4.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.71*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.91*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCERS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdaptive CERS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e46.61\u0026thinsp;\u0026plusmn;\u0026thinsp;8.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e58.74\u0026thinsp;\u0026plusmn;\u0026thinsp;9.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e140.67**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e129.58\u003cb\u003e**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive refocusing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e8.02\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e11.62\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;3.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e109.46**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e103.46**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRefocusing on planning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.61\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;2.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e12.16\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e159.41**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e147.73**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive reappraisal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.86\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;3.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e13.22\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;3.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e203.87**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e191.42**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePutting into perspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e10.46\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;3.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e11.05\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;2.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcceptance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e10.70\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;2.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e12.66\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.29**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37.18**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emaladaptive CERS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e47.17\u0026thinsp;\u0026plusmn;\u0026thinsp;8.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e38.83\u0026thinsp;\u0026plusmn;\u0026thinsp;7.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83.17**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76.86**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-Blame\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e14.32\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;3.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.51\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;3.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e95.27**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.64**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRumination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e11.25\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.82\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.17**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.51**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCatastrophising\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e10.80\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;3.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e9.11\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;2.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.51**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.84**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther-Blame\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e10.79\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e9.12\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.31**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.68**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePSI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e29.50\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;5.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e18.42\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;5.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e278.50**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e266.11**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eDIF: Difficulty Identifying Feelings\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eDDF: Difficulty Describing Feelings\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eEOT: Externally Oriented Thinking\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eCERS: Cognitive Emotion Regulation Strategies\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eF\u003csup\u003ea\u003c/sup\u003e: Analysis of variance (ANOVA).\u003c/p\u003e \u003cp\u003eF\u003csup\u003eb\u003c/sup\u003e: Analysis of covariance (ANCOVA) adjusted for education as covariate.\u003c/p\u003e \u003cp\u003e \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003cp\u003e* \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05.\u003c/p\u003e \u003cp\u003e**\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01.\u003c/p\u003e\n\u003ch3\u003eImpact of Alexithymia on Emotion Regulation, Physical Symptoms, and Cardiac Function in CHD\u003c/h3\u003e\n\u003cp\u003eAs shown in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, group comparisons revealed significant differences in maladaptive CERS, adaptive CERS, PSI scores, and NYHA functional classification across alexithymia subgroups. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, 62 (31.1%) were identified as having alexithymia, 57 (28.3%) were classified as borderline alexithymic, and 80 (46.6%) were considered non-alexithymic. The results indicated that the alexithymia group showed significantly higher scores in maladaptive CERS compared to the non-alexithymia group (F\u0026thinsp;=\u0026thinsp;30.08, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and the borderline alexithymia group also scored significantly higher than the non-alexithymia group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Significant group differences were also observed in PSI (F\u0026thinsp;=\u0026thinsp;31.63, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). scores on adaptive CERS were significantly lower in the alexithymic and borderline alexithymic groups compared to the non-alexithymic group (F\u0026thinsp;=\u0026thinsp;3.46, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Notably, PSI exhibited the largest effect size among the outcome variables, with a Cohen\u0026rsquo;s d of 0.35, which corresponds to a moderate-to-large magnitude of effect. Ordinal logistic regression analysis indicated that patients in the alexithymia group had significantly higher odds of being classified into a worse NYHA compared to the non-alexithymia group (OR\u0026thinsp;=\u0026thinsp;2.47, 95% CI [0.11, 1.69], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of maladaptive and Adaptive Cognitive Emotion Regulation, Physical Symptoms, and Cardiac Function Among Alexithymia Subgroups in CHD Patients by controlling gender, age, education, and disease duration (n\u0026thinsp;=\u0026thinsp;199)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall (n\u0026thinsp;=\u0026thinsp;199)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlexithymic (n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBorderline (n\u0026thinsp;=\u0026thinsp;57)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNon-alexithymic (n\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF / χ\u0026sup2; (p)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eη\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emaladaptive CERS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e59.75\u0026thinsp;\u0026plusmn;\u0026thinsp;8.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e52.69\u0026thinsp;\u0026plusmn;\u0026thinsp;5.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e48.98\u0026thinsp;\u0026plusmn;\u0026thinsp;6.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e41.53\u0026thinsp;\u0026plusmn;\u0026thinsp;7.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.08** (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdaptive CERS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e33.81\u0026thinsp;\u0026plusmn;\u0026thinsp;7.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e43.61\u0026thinsp;\u0026plusmn;\u0026thinsp;6.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e45.64\u0026thinsp;\u0026plusmn;\u0026thinsp;8.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e48.89\u0026thinsp;\u0026plusmn;\u0026thinsp;6.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.46* (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e29.49\u0026thinsp;\u0026plusmn;\u0026thinsp;5.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e32.80\u0026thinsp;\u0026plusmn;\u0026thinsp;4.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e32.01\u0026thinsp;\u0026plusmn;\u0026thinsp;4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e25.13\u0026thinsp;\u0026plusmn;\u0026thinsp;5.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.63** (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNYHA functional class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e1.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.09* (P\u0026thinsp;=\u0026thinsp;0.024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: CERS: cognitive emotion regulation strategies; PS: physical symptoms.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or otherwise specified. ANCOVA and partialη2 were employed for dimensional variables.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCorrelations Between Alexithymia, Cognitive Emotion Regulation, and Physical Symptoms in CHD Patients\u003c/h2\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, spearman correlation analysis revealed that PSI scores were significantly and positively correlated with age (r\u0026thinsp;=\u0026thinsp;0.37, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), NYHA (r\u0026thinsp;=\u0026thinsp;0.14, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), maladaptive CERS (r\u0026thinsp;=\u0026thinsp;0.40, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and all three subscales of alexithymia: DIF (r\u0026thinsp;=\u0026thinsp;0.48, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), DDF (r\u0026thinsp;=\u0026thinsp;0.44, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and EOT (r\u0026thinsp;=\u0026thinsp;0.41, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Additionally, PSI scores were not significantly correlated with adaptive CERS, educational level, or disease duration (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSpearman Correlations Between Physical Symptom Scores and Demographic, Clinical, and Psychological Variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpearman\u0026rsquo;s r\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNYHA functional classification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.049*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdaptive CERS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaladaptive CERS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEOT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: PSI\u0026thinsp;=\u0026thinsp;Physical Symptom Inventory; CERS\u0026thinsp;=\u0026thinsp;Cognitive Emotion Regulation Strategies; DIF, DDF, EOT\u0026thinsp;=\u0026thinsp;Subscales of the Toronto Alexithymia Scale (TAS-20). Pearson correlation coefficients were used, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, when partial correlation was used to control NYHA functional classification and age, the results showed that the subscales of DIF (pr\u0026thinsp;=\u0026thinsp;0.34, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), DDF (pr\u0026thinsp;=\u0026thinsp;0.29, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and EOT (pr\u0026thinsp;=\u0026thinsp;0.30, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were still correlated with PS. Also, the significant positive correlation between the maladaptive CERS and PS was found (pr\u0026thinsp;=\u0026thinsp;0.32, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePartial correlations between alexithymia subscales and adaptive and maladaptive CERS with PS in patients with CHD (n\u0026thinsp;=\u0026thinsp;199)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-DIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2-DDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.52**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-EOT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4-Adaptive CERS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.20**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-Maladaptive CERS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.33**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.33**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.32**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6-PSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.34**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.29**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.30**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.32**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: Partial correlations by controlling age and NYHA\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDDF: difficulty describing feelings; EOT: externally oriented thinking; DIF: difficulty identifying feelings; CERS: cognitive emotion regulation strategies; PS: physical symptoms.\u003c/p\u003e \u003cp\u003e*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e**\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, regression analyses examined the predictors of PSI in CHD patients. In Model 1, age (B\u0026thinsp;=\u0026thinsp;0.22, β\u0026thinsp;=\u0026thinsp;0.38, t\u0026thinsp;=\u0026thinsp;5.85, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) significantly predicted PSI, while NYHA grade showed a non-significant trend (B\u0026thinsp;=\u0026thinsp;0.99, β\u0026thinsp;=\u0026thinsp;0.11, t\u0026thinsp;=\u0026thinsp;1.63, p\u0026thinsp;=\u0026thinsp;0.10), explaining 17% of the variance. Adding DIF in Model 2 significantly improved the model (ΔR\u0026sup2; = 0.09, ΔF\u0026thinsp;=\u0026thinsp;25.04, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with DIF emerging as a strong predictor (B\u0026thinsp;=\u0026thinsp;0.46, β\u0026thinsp;=\u0026thinsp;0.35, t\u0026thinsp;=\u0026thinsp;5.00, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In Model 3, DDF contributed minimally (B\u0026thinsp;=\u0026thinsp;0.23, β\u0026thinsp;=\u0026thinsp;0.16, t\u0026thinsp;=\u0026thinsp;2.00, p\u0026thinsp;=\u0026thinsp;0.05), with a small increase in explained variance (ΔR\u0026sup2; = 0.02, ΔF\u0026thinsp;=\u0026thinsp;3.99, p\u0026thinsp;=\u0026thinsp;0.05). When EOT was included in Model 4, it significantly predicted PSI (B\u0026thinsp;=\u0026thinsp;0.34, β\u0026thinsp;=\u0026thinsp;0.26, t\u0026thinsp;=\u0026thinsp;4.07, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), further increasing explained variance (ΔR\u0026sup2; = 0.06, ΔF\u0026thinsp;=\u0026thinsp;16.53, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the final model (Model 5), maladaptive CERS was also added (B\u0026thinsp;=\u0026thinsp;0.09, β\u0026thinsp;=\u0026thinsp;0.13, t\u0026thinsp;=\u0026thinsp;1.86, p\u0026thinsp;=\u0026thinsp;0.06), and the full model accounted for 35% of the variance (ΔR\u0026sup2; = 0.01, ΔF\u0026thinsp;=\u0026thinsp;3.46, p\u0026thinsp;=\u0026thinsp;0.06). These results indicate that DIF, EOT, and maladaptive CERS are key psychological predictors of physical symptom severity in CHD, beyond the effects of age and NYHA functional classification.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression analysis for PS in CHD patients (n\u0026thinsp;=\u0026thinsp;199)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eR\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eΔR\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eΔF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e (model)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Constant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e13.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNYHAgrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Constant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e17.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e25.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNYHAgrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Constant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e15.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNYHAgrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Constant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e16.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e16.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNYHAgrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEOT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Constant)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e14.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNYHAgrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEOT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emaladaptive CERS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eNote. β\u0026thinsp;=\u0026thinsp;standardized coefficientNYHA: NYHA functional classification; DIF: difficulty identifying feelings; EOT: externally oriented thinking; CERS: cognitive emotion regulation strategies; PS: physical symptoms*\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05**\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn summary, the present study highlights that both alexithymia and maladaptive cognitive emotion regulation strategies are highly prevalent among patients with CHD. Approximately 60% of participants met criteria for borderline or full alexithymia, and those with higher alexithymia scores relied more heavily on maladaptive strategies while using adaptive strategies less frequently, which supports previous research on alexithymia in cardiac populations\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e. Recent evidence also indicates that emotion regulation tendencies, including maladaptive responses such as expressive suppression or other maladaptive strategies, are significantly related to perceived stress and psychological adjustment in patients with CHD, underscoring the clinical relevance of emotion regulation difficulties in this group\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. Importantly, our analyses indicated that DIF, EOT, and greater reliance on maladaptive cognitive emotion regulation strategies jointly accounted for 35% of the variance in physical symptom burden among CHD patients. This aligns with empirical evidence indicating that maladaptive emotion regulation strategies, such as expressive suppression, moderate the relationship between psychological distress (e.g., depressive symptoms) and physiological indices linked to cardiac health in CHD populations (e.g., expressive suppression moderating depression - vmHRV associations in cardiac patients)\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. Furthermore, broader research on emotion regulation and cardiovascular risk suggests that frequent use of maladaptive strategies (e.g., rumination, suppression) is linked with greater psychological stress and adverse health outcomes, consistent with biopsychosocial models of disease\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e. By highlighting these associations, our results underscore the critical role of emotional awareness deficits and maladaptive regulation in shaping both psychological distress and somatic symptom perception in CHD.\u003c/p\u003e \u003cp\u003eBuilding on these core findings, the present results suggest that impaired emotional awareness (alexithymia) combined with habitual reliance on maladaptive cognitive emotion regulation strategies may represent key psychological factors contributing to increased physical symptom burden in patients with coronary heart disease (CHD). Specifically, individuals who struggle to identify their own emotions tend to perceive emotional arousal as vague, poorly differentiated bodily sensations rather than clearly recognizable emotional experiences\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e. When emotional signals cannot be adequately recognized or cognitively processed, they are more likely to be interpreted at a somatic level, amplifying symptom perception and intensifying bodily discomfort\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eExternally oriented thinking (EOT) may further reinforce this pattern. A cognitive style characterised by reduced attention to internal emotional states has been linked to limitations in reflective processing and diminished use of adaptive emotion regulation strategies such as cognitive reappraisal, with high levels of alexithymia associated with less frequent use of adaptive regulation and greater reliance on maladaptive strategies\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e. In this context, maladaptive cognitive emotion regulation strategies\u0026mdash;specifically rumination, emotional suppression, and catastrophizing\u0026mdash;may serve as compensatory efforts to cope with emotional experiences that are difficult to recognize or fully grasp\u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e. However, maladaptive CERS such as rumination and expressive suppression often fail to effectively reduce emotional distress; instead, they are associated with persistent emotional arousal and increased somatic symptom reporting. Prior research indicates that dysfunctional emotion regulation profiles characterized by reduced emotional awareness and reliance on maladaptive responses are linked with greater somatic symptom severity in clinical populations and somatic symptom disorders\u003csup\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFrom a biopsychosocial perspective, the psychological processes identified in this study are likely to interact with physiological pathways relevant to cardiovascular functioning. Accumulating evidence indicates that impaired emotion processing and maladaptive emotion regulation are linked to prolonged activation of the hypothalamic-pituitary-adrenal axis\u003csup\u003e[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/sup\u003e, heightened sympathetic nervous system activity\u003csup\u003e[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/sup\u003e, and persistent low-grade inflammation\u003csup\u003e[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]\u003c/sup\u003e. Together, these alterations may contribute to the maintenance of physical symptoms and increased bodily sensitivity in patients with CHD. Although the present study did not directly assess these mechanisms, the overall pattern of findings is consistent with theoretical models of chronic illness, suggesting that maladaptive emotion regulation increases vulnerability to the amplification of physical symptoms.\u003c/p\u003e \u003cp\u003eBuilding on previous research, this study specifically examined distinct dimensions of alexithymia and emotion regulation. After controlling for relevant covariates, DIF and EOT showed stronger associations with physical symptoms than overall alexithymia scores, highlighting the importance of distinguishing between different facets of emotion processing. Moreover, maladaptive CERS explained additional variance beyond alexithymia, suggesting that impaired emotional awareness and maladaptive regulation, while related, represent partially distinct psychological processes.\u003c/p\u003e \u003cp\u003eAn increasing body of evidence indicates that interventions such as emotion-focused therapy, mindfulness-based programs, and structured emotion skills training can enhance emotion regulation, reduce alexithymic traits, and decrease reliance on maladaptive strategies like rumination, suppression, and catastrophizing, thereby strengthening the functional link between emotional processing and regulation\u003csup\u003e[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]\u003c/sup\u003e. In patients with CHD, although behavioral health interventions-most notably cognitive-behavioral therapy (CBT)-have been shown to effectively reduce depression and anxiety, relatively few studies have specifically targeted distinct dimensions of alexithymia (such as difficulties in identifying feelings and externally oriented thinking) or patterns of emotion regulation, including both adaptive and maladaptive strategies\u003csup\u003e[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]\u003c/sup\u003e. In light of the present findings, which indicate that impaired emotional awareness and maladaptive cognitive emotion regulation strategies exert independent and additive effects on physical symptom burden, further intervention research explicitly focused on emotional processing and emotion regulation is warranted.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThis study had several strengths. First, it is one of the few to examine the links between alexithymia, CERS, and physical symptoms in CHD patients, providing evidence for the role of emotional dysregulation in somatic outcomes. Second, by separating adaptive from maladaptive CERS, it shows how specific strategies (e.g., positive reappraisal vs. self-blame, rumination) relate differently to symptoms, adding clinical value. Third, the use of partial correlations and hierarchical regression, with control for age and NYHA class, strengthens the methodological rigor. Finally, the findings highlight the psychological aspects of CHD and underline the need to assess and manage alexithymia and maladaptive regulation strategies in clinical care. However, this study has certain limitations: its cross-sectional design prevents causal inferences; participants were not stratified by CHD subtype; intervention effects on alexithymia and emotion regulation were not assessed; and the sample was limited to ages 40\u0026ndash;80, restricting generalizability.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn patients with coronary heart disease, levels of alexithymia were elevated, accompanied by greater use of maladaptive emotion regulation strategies and reduced use of adaptive strategies. About 60% of participants met criteria for borderline or clinical alexithymia, which was strongly linked to maladaptive regulation. Difficulty identifying feelings, externally oriented thinking, and maladaptive strategies together explained 35% of the variance in physical symptoms, indicating a significant psychological contribution to patients\u0026rsquo; symptom burden. These results highlight the need for routine psychological assessment and interventions targeting emotion regulation in cardiac care.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCHD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCoronary heart disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCERS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCognitive emotion regulation strategies\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTAS-20\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eToronto Alexithymia Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePhysical Symptoms Inventory\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDIF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edifficulties identifying feelings\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDDF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edifficulties describing feelings\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEOT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eexternally oriented thinking\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNYHA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNew York Heart Association\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all patients who participated in this study for their time and cooperation. We also acknowledge the clinical staff of Fuwai Central China Cardiovascular Hospital for their assistance with participant recruitment and data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJY and ZYS supervised the research direction, experimental procedures, and manuscript preparation. JY and NYM contributed to study conceptualization and performed the statistical analyses and data visualization. NYM and JXW were responsible for data collection and assisted with study implementation. DXF and SL critically reviewed and revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYJ is supported by an institutional research grant from Fuwai Central China Cardiovascular Hospital(ZCK2023070).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe database supporting the reported results is available only upon request due to confidentiality and ethical restrictions. This can be requested from the author of correspondence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Fuwai Central China Cardiovascular Hospital (approval number: 2025LI016). All procedures were conducted in accordance with the principles of the Declaration of Helsinki. The study was approved by the institutional ethics committee and registered with the Chinese Clinical Trial Registry (ChiCTR), with the trial number ChiCTR2500096793.Written informed consent was obtained from all participants prior to their inclusion in the study. The study was conducted under the project registration number (ZCK2023070).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by research project of Fuwai Central China Cardiovascular Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting the findings of this study are not publicly available due to privacy and ethical restrictions, but they can be requested from the corresponding author, Dr. Feng.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eROTH G A, MENSAH G A, JOHNSON C O, et al. 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JAMA Netw Open. 2025;8(10):e2538813.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"alexithymia, cognitive emotion regulation strategies, physical symptoms inventory, psychology, CHD","lastPublishedDoi":"10.21203/rs.3.rs-8530045/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8530045/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eObjective\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCoronary heart disease (CHD) remains the leading cause of death worldwide, with psychological symptoms being highly prevalent among patients and influencing both disease onset and prognosis. Limited research has explored the role of emotional regulation. This study aims to evaluate alexithymia subscales and cognitive emotion regulation strategies (CERS) in patients with CHD and to examine their associations with physical symptoms (PS) and other clinical variables.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe sample consisted of 199 patients with CHD and 116 healthy controls. All participants completed the Toronto Alexithymia Scale (TAS-20), the Cognitive Emotion Regulation Questionnaire (CERQ), and the Physical Symptoms Inventory (PSI). Alexithymia was evaluated dimensionally across three core domains (difficulty identifying feelings, difficulty describing feelings, externally oriented thinking), with participants categorized by established TAS-20 cutoff scores.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCompared with healthy controls, CHD patients exhibited significantly higher levels of alexithymia, including difficulties identifying feelings (DIF), difficulties describing feelings (DDF), and externally oriented thinking (EOT) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). CHD patients also reported greater reliance on maladaptive cognitive emotion regulation strategies (CERS), including self-blame, rumination, catastrophizing, and other-blame (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Within the CHD group, DIF, DDF, EOT and maladaptive CERS were positively correlated with physical symptom (PSI, r\u0026thinsp;=\u0026thinsp;0.37\u0026ndash;0.48, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and regression analyses indicated that DIF, EOT, and maladaptive CERS independently predicted PSI severity, accounting for 35% of the variance after controlling for age and New York Heart Association (NYHA) functional class.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003ePatients with CHD show marked deficits in emotion recognition and regulation, with DIF, EOT, and maladaptive CERS emerging as key predictors of physical symptoms.\u003c/p\u003e","manuscriptTitle":"Associations Between Alexithymia, Cognitive Emotion Regulation, and Physical Symptoms in Coronary Heart Disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-27 00:07:56","doi":"10.21203/rs.3.rs-8530045/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2fa5f9a7-86b1-4ea2-96ee-7d482d134c1c","owner":[],"postedDate":"January 27th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-17T06:40:36+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-27 00:07:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8530045","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8530045","identity":"rs-8530045","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}