INTRODUCTION

According to the World Health Organization, cardiovascular diseases (CVDs) remain the leading cause of mortality in Europe, accounting for nearly half of all deaths (42.5%), which corresponds to approximately 10,000 deaths per day [1]. Epidemiological data for Poland indicate that CVDs also constitute the dominant cause of mortality. In 2021, 168,854 deaths due to CVDs were recorded in Poland, and the standardized mortality rate was 218 deaths per 100,000 population [2]. Thus, CVDs represent a major public health challenge throughout Europe, particularly in Central and Eastern Europe, where treatment outcomes remain poorer compared with other regions of the continent [3]. In Poland, the high mortality rate is largely associated with hypertensive heart disease, ischemic heart disease, and other circulatory disorders [4]. Consequently, life expectancy in Poland is shorter by approximately 3 to 7 years compared with that in some European Union member states [5].

Disease acceptance is a psychological process encompassing both cognitive and emotional components. From a psychological perspective, acceptance involves a reduction in resistance to illness and coming to terms with
its presence. Understanding one’s disease is associated with health-related behavior, attitudes, and coping strate­gies [6]. By recognizing illness as part of one’s life, individuals modify their attitudes, perceptions, and responses to their condition. From a medical perspective, disease acceptance may be understood as a gradual adaptation to a chronic health condition, resulting in increased perceived control over one’s health and improved quality of life [7]. Research indicates that accepting illness may lead to positive outcomes, including reduced stress and anxiety associated with health deterioration. As patients gradually change their attitudes and adapt to new challenges related to their condition, they gain a greater sense of control over their lives and mental well-being [7, 8]. Interventions aimed at fostering disease acceptance may improve treatment effectiveness, psychological adjustment, and long-term prognosis [8]. Among cardiology patients, psychological factors play a crucial role in cooperation with healthcare professionals and adherence to therapeutic recommendations. These processes contribute to improved health status and enhanced quality of life [9]. Therefore, acceptance of chronic illness is a key element of effective adaptation to long-term disease and constitutes an important indicator of patients’ psychological adjustment to their health condition [10].

Self-efficacy refers to an individual’s belief in their ability to mobilize the resources necessary to cope effectively with challenging situations and to accomplish intended actions [11]. It represents a subjective evaluation of one’s competencies, influencing motivation, decision-making, and emotional responses. Self-efficacy does not always reflect an individual’s actual skill level but rather their beliefs regarding the effective use of those skills [12]. It is considered an important psychological construct relevant across multiple domains of functioning. Confidence in one’s abilities facilitates the successful achievement of goals. Determination, motivation, and perseverance in difficult situations are essential components of self-efficacy [13]. In the context of health, self-efficacy plays a fundamental role in disease management. In cardiovascular conditions, patients characterized by high self-efficacy, problem-solving orientation, goal achievement, and effective stress management are more likely to experience better quality of life compared with those with low self-efficacy [13, 14]. Individuals with chronic illnesses frequently face numerous challenges affecting daily functioning, decision-making capacity, and overall quality of life. Self-efficacy plays an important role in motivating adherence to medical recommendations and maintaining a positive attitude toward treatment [15]. High levels of self-efficacy among patients with chronic diseases facilitate better symptom management and increase engagement in therapeutic regimens. Moreover, such individuals are more likely to actively participate in the treatment process and undertake health-promoting behaviors aimed at improving their condition [12].

Importantly, assessing disease acceptance and self-efficacy provides clinically relevant information that may serve as a foundation for identifying the needs of specific patient subgroups and tailoring targeted interventions. These constructs can be modified through various appropriately designed interventions. Evidence from recent studies indicates that interventions such as cardiac rehabilitation programs, including blended learning approaches, may improve self-efficacy and treatment adherence among patients undergoing cardiac procedures [16]. Similarly, rehabilitation interventions implemented in primary care settings have been shown to enhance patients’ confidence in managing their condition [17]. In addition, eHealth-based interventions have shown potential to improve both subjective well-being and self-efficacy in patients with CVDs [18]. The key role of psychological support in the process of illness acceptance, and its impact on treatment outcomes, is also emphasized [19].

Improvements in self-efficacy are associated with greater engagement in self-care behaviors, better adhe­rence to therapeutic recommendations, and overall im­proved health outcomes. Therefore, evaluating these indi­cators may represent an important first step in designing personalized, patient-centered interventions aimed at improving both psychological adaptation and clinical outcomes in individuals with CVDs.

MATERIAL AND METHODS

This study was a cross-sectional observational study conducted between November 2024 and February 2025 in a cardiology ward, where patients with chronic CVDs were hospitalized. The study included patients aged 18 years and older with confirmed cardiovascular diagnoses documented in their medical records, including ischemic heart disease, arterial hypertension, cardiac arrhyt­hmias, myocardial infarction, heart failure, valvular heart disease, and stroke. The inclusion criteria were a diagnosis of cardiovascular disease, age over 18 years, and informed consent to participate in the study. The exclusion criteria were the absence of cardiovascular disease, age under 18 years, and refusal to participate.

A total of 181 eligible patients hospitalized in the cardiology ward during the study period were invited to participate in the study. Of these, 157 patients consented to participate and completed the questionnaires. Twenty-four patients declined participation in the study. Data were collected in an inpatient hospital setting under conditions ensuring patients’ psychological and physical comfort. Respondents were asked to complete a paper-based questionnaire independently during periods free from medical procedures and at a time convenient for them. The entire research procedure was designed not to interfere with the therapeutic process. In cases of difficulty understanding the questions or the need for clarification, participants could seek assistance from the researcher. The study was conducted in accordance with ethical principles. Participation was voluntary and anonymous. Participants provided written informed consent for the use of their medical records solely for the purpose of confirming cardiovascular diagnoses. Participants had the right to withdraw at any time without providing a reason. Permission to conduct the study was obtained from the head of the department. The study was approved by the Bioethics Committee at the Medical University of Warsaw (approval no. AKBE/394/2025).

MEASUREMENT TOOLS

One of the research instruments used was the Ac­ceptance of Illness Scale (AIS), developed by Felton, Revenson, and Hinrichsen (1984) and adapted into Polish by Juczyński [20]. The questionnaire consists of eight statements referring to the negative consequences of poor health, disease-related limitations, lack of self-sufficiency, and self-esteem. Responses are provided on a five-point Likert scale, where 1 indicates “strongly agree” and 5 indicates “strongly disagree.” The total score ranges from 8 to 40 points [21]. The overall level of disease acceptance is calculated as the sum of all items. Scores below 20 indicate low acceptance, scores between 20 and 29 indicate moderate acceptance, and scores above 30 indicate high acceptance. Low scores reflect poor adaptation and a strong sense of psychological discomfort, whereas high scores indicate better disease adaptation and acceptance of the health condition [21, 22].

The second research instrument was the Generalized Self-Efficacy Scale (GSES), developed by Schwarzer and Jerusalem and adapted by Juczyński [23, 24]. This scale assesses individuals’ subjective beliefs in their ability to cope with life challenges, including difficulties related to chronic illness. It consists of ten items measuring self-efficacy across various challenging life situations. Each item is rated on a four-point scale ranging from 1 (“no”) to 4 (“yes”), with higher scores indicating greater perceived self-efficacy. Higher GSES scores may be associated with greater confidence in coping with health-related challenges and may contribute to engagement in treatment and rehabilitation processes.

The characteristics of the study group were analyzed based on sociodemographic variables, including sex, age, place of residence, education level, marital status, disease duration, and type of condition. These sociodemographic data were obtained directly from patients during the questionnaire process, whereas medical records were used solely to confirm clinical diagnoses. All data were collected after obtaining written informed consent from the study participants.

STATISTICAL ANALYSIS

Statistical analyses were performed using STATISTICA software version 13.0. Descriptive statistics (mean, standard deviation, median and minimum–maximum) were calculated for quantitative variables. Normality of distributions was assessed using the Shapiro-Wilk test and graphical inspection. Due to deviations from normality, nonparametric methods were applied in comparative analyses: the Mann-Whitney U test for two-group comparisons and the Kruskal-Wallis test for multiple-group comparisons. When the Kruskal-Wallis test was significant, pairwise comparisons were conducted using the two-tailed Mann-Whitney U test with Holm correction for multiple testing.

Relationships between variables were examined using Spearman’s rank correlation coefficient (rho). Ordinal variables were coded in ascending order according to their natural sequence (age, place of residence, education level, disease duration). Nominal variables (sex, marital status) were analyzed using comparative methods (Mann-Whitney U/Kruskal-Wallis tests) and were not included in correlation analyses. The significance level was set at α = 0.05, and all tests were two-tailed. Results were reported as test statistics (Mann-Whitney U/Kruskal-Wallis tests, Spearman rank correlation) and p-values (for very small values reported as p < 0.0001).

Additionally, based on the multiple-choice variable “Type of cardiovascular disease (multiple responses allowed),” a disease burden index was constructed as the number of coexisting cardiovascular diagnoses. This variable was categorized into four groups: 1, 2, 3, and ≥ 4 diagnoses.

To identify independent predictors of low disease acceptance and low self-efficacy, two multivariable logistic regression models were estimated using the enter method, with all sociodemographic and clinical variables entered simultaneously. Logistic regression was selected due to the dichotomous nature of the dependent variables – low AIS (< 20 points) and low GSES (< 20 points) – defined according to cut-off points established in the literature [20]. The enter method ensured that the independent contribution of each predictor was assessed after controlling for all remaining variables, eliminating the risk of selection bias inherent in stepwise approaches.

RESULTS

A total of 157 participants were included in the study. Women constituted 58.0% of the study group, while men accounted for 42.0%. Most respondents (40.1%) were aged over 71 years and predominantly resided in cities with more than 500,000 inhabitants (33.1%). The largest proportion of participants reported having higher education (40.8%). Nearly half of the respondents were married (49.7%). The most numerous group (45.9%) consisted of patients whose disease duration exceeded six years. The majority of participants had two (43.3%) or three (31.2%) coexisting CVDs. Statistically significant differences (p < 0.05) in both GSES and AIS scores were observed with respect to age, education level, marital status, disease duration, and the number of cardiovascular conditions. In contrast, no statistically significant differences in GSES and AIS scores were found according to sex or place of residence in the comparative analysis (p > 0.05). Detailed data are presented in Table 1.

The mean score for disease acceptance (AIS) was 20.89 ± 8.32. Frequency analysis revealed that more than half of the respondents, 80 participants (51.0%), demonstrated a low level of disease acceptance. A total of 45 respondents (28.7%) achieved scores indicating a moderate level of disease acceptance. In contrast, a high level of disease acceptance was observed in 32 participants, representing 20.4% of the total sample.

The mean GSES score was 23.43 ± 7.19. Frequency analysis showed that more than half of the respondents, 87 participants (55.4%), exhibited a low level of self-efficacy, while 44 respondents (28.0%) achieved scores indicating a high level of self-efficacy. The remaining 26 participants (16.6%) demonstrated an average level of self-efficacy. Detailed data are presented in Tables 2 and 3.

The study demonstrated that lower levels of disease acceptance and self-efficacy were associated with older age (rho = −0.455, p < 0.0001; rho = −0.398, p < 0.0001), lower educational attainment (rho = −0.433, p < 0.0001; rho = −0.465, p < 0.0001), longer disease duration (rho = −0.370, p < 0.0001; rho = −0.342, p < 0.0001), and a greater number of comorbid cardiovascular conditions (rho = −0.410, p < 0.001; rho = −0.370, p < 0.001). Furthermore, a significant association was also observed with place of residence (rho = 0.242, p = 0.0022; rho = 0.235, p = 0.0031), which may indicate differences in levels of disease acceptance and self-efficacy depending on the living environment. Detailed data are presented in Table 4.

The model for low AIS was statistically significant (c² = 50.14; p < 0.001; Nagelkerke R² = 0.365), as was the model for low GSES (c² = 47.38; p < 0.001; Nagel­kerke R² = 0.370). Nagelkerke R² is a pseudo-coefficient of determination used as a standard fit index in logistic regression; it is not equivalent to R² in linear regression and does not represent the proportion of explained variance in the classical sense, but indicates meaningfully better model fit compared to the null model.

After controlling for all remaining variables, the independent predictors of low AIS were: age (odds ratio, OR = 2.35; 95% confidence interval, CI: 1.20-4.62; p = 0.013), place of residence (OR = 0.52; 95% CI: 0.33-0.80; p = 0.003),
and number of coexisting cardiovascular diagnoses (OR = 1.77; 95% CI: 1.06–2.95; p = 0.029). Older age and a greater number of diagnoses increased the odds of low disease acceptance, whereas residing in a larger city had a protective effect. Sex, education, marital status, and disease duration showed no independent association with AIS after controlling for the remaining predictors.

The independent predictors of low GSES were: education level (OR = 0.42; 95% CI: 0.23-0.78; p = 0.006) and marital status – widowed versus married (OR = 3.54; 95% CI: 1.27-9.85; p = 0.016). Higher education reduced the odds of low self-efficacy, whereas widowhood more than tripled this risk. Age, place of residence, number of cardiovascular diagnoses, and disease duration showed no independent association with GSES after controlling for the remaining variables. Detailed results are presented in Table 5.

A statistically significant positive correlation was found between the level of disease acceptance and self-efficacy. The correlation coefficient was r = 0.86, with p < 0.001. These results indicate that higher levels of self-efficacy are associated with higher levels of disease acceptance. The relationship is illustrated in a scatter plot (Figure 1).

DISCUSSION

The results of this study contribute to the body of research on disease acceptance and self-efficacy among patients with chronic CVDs. In the present study, a low level of disease acceptance and self-efficacy was observed among patients with chronic CVDs, along with a signi­ficant positive correlation between these variables. These findings suggest that patients with lower levels of disease adaptation may simultaneously exhibit reduced confidence in their ability to effectively cope with their condition. In our study, the mean AIS score was 20.89 ± 8.32, with more than half of the respondents (51%) demonstrating a low level of disease acceptance, 27.8% showing a moderate level, and 20.4% reporting a high level. Similar results were reported by Białek and Sadowski [25], who found a moderate level of disease acceptance (22.88 ± 2.86) among patients hospitalized for cardiovascular conditions. As in our study, disease acceptance was related to age, marital status, and education. Likewise, Obiegło et al. [26] reported a significant association between age and disease acceptance, with acceptance decreasing as age increased. This relationship may result from increasing functional limitations, which reduce adaptive resources over time. Higher mean values than those obtained in our study were reported by Andruszkiewicz et al. [27], with mean AIS scores of 27.26 ± 7.55 among chronically ill patients. Similar to our findings, no significant sex differences were observed in disease acceptance, whereas younger age was associated with higher levels of acceptance. In the present study, women constituted a larger proportion of the sample, which is consistent with our findings and may reflect differences in healthcare utilization patterns, health-related behaviors, or willingness to participate in health research. According to Religioni et al. [28], patients over 65 years of age with heart failure exhibited a moderate level of disease acceptance (median = 25), while in our study, the median score was 19. Patients with a history of myocardial infarction, atrial fibrillation, or stroke showed lower levels of disease acceptance. In our study, participants with a higher number of comorbid conditions also demonstrated lower disease acceptance, likely reflecting a higher overall health burden. In a study by Mruk et al. [29], older patients with cardiovascular conditions showed higher mean disease acceptance (29.33 ± 8.58) compared to our results. Consistent with our findings, longer disease duration was associated with lower acceptance. Education level also significantly influenced disease acceptance in both studies. Differences were observed for marital status and place of residence, which were significantly associated with disease acceptance in our study but not in Mruk et al.’s research [29]. Sex had no significant effect on disease acceptance in either study. Importantly, the sex distribution in Mruk et al.’s study [29] (57% women, 43% men) was comparable to that observed in our sample (58% vs. 42%), which may partially support the comparability of findings. However, it should be noted that this sample structure may limit the generalizability of the findings to the male population. The lack of association between place of residence and disease acceptance was also reported by Uchmanowicz et al. [30], whereas our findings demonstrated a statistically significant relationship. These discrepancies may be due to differences in access to healthcare and therapeutic support depending on the living environment.

In our study, the mean GSES score was 23.43 ± 7.19, with more than half of participants (55.4%) reporting low self-efficacy, which may have important implications for their ability to manage their disease effectively. Andruszkiewicz et al. [27] reported a mean GSES score of 29.04, higher than that observed in our study. Religioni et al. [28] found a median GSES score of 30 among patients with heart failure. Other studies in chronic disease populations also reported higher self-efficacy scores than in our sample: Cybulski et al., nursing home residents (28.18 ± 6.14); Carlstedt et al., post-stroke patients (31.7 ± 6.95); Volz et al., post-stroke patients (31.25 ± 5.98); Liu et al., post-stroke patients (25.6 ± 5.8); Susanto et al., patients with hypertension (27.88 ± 6.59); Fan and Lv, patients with heart failure (26.11 ± 6.46) [31]. Wang et al. [32] reported a mean GSES score of 27.2 ± 8.1, significantly associated with age and education, consistent with our findings, though sex and marital status were not significant predictors in their study. Thomet et al. [33] reported a mean GSES score of 30.1 ± 3.3, with lower scores significantly associated with female sex, which contrasts with our study, where sex had no significant effect.

This study also demonstrated a significant positive correlation between disease acceptance and self-efficacy. Patients with higher disease acceptance exhibited higher self-efficacy. Our findings are consistent with other studies. Religioni et al. [28] reported that among patients with heart failure, higher disease acceptance was associated with higher self-efficacy, both of which were related to better functioning and physical activity. Disease acceptance constitutes an important psychological resource supporting adaptation to illness and effective coping with its consequences. As noted by Affendi et al. [34], higher self-efficacy promotes health-promoting behaviors and adherence to therapeutic recommendations, indirectly influencing disease control. Siennicka et al. [35] also highlighted the role of health control and self-efficacy in shaping patient attitudes toward treatment and engagement in the therapeutic process. The relationships between disease acceptance, self-efficacy, and patient functioning were further confirmed by Sadeghiazar et al. [36], indicating that these variables may be related to quality of life and adherence to treatment recommendations. Similar conclusions were reported by other authors; Yao et al. [37] found that higher self-efficacy strengthens the effect of social support on patient quality of life.

Patients with CVDs constitute a heterogeneous population requiring individualized assessment of both clinical and psychosocial factors [38]. Self-efficacy and illness perception are influenced by both individual and environmental determinants [39]. Therefore, it is recommended that all patients receive personalized support tailored to their individual needs and resources [40]. These findings underscore the need for further research conducted in more representative and diverse patient populations. In the context of cardiology, these issues are particularly important, as cardiovascular diseases often require long-term treatment and sustained lifestyle modification [38]. Further studies should adopt a more comprehensive biopsychosocial framework, incorporating psychological resources, social support, and health behaviors in addition to clinical and demographic variables.

This study has several limitations. The sample size was relatively small and data were collected from a single center. A total of 181 eligible patients were invited to participate, and 157 consented and completed the study, resulting in a response rate of 86.7%. However, no systematic data were collected regarding reasons for non-participation, which limits the ability to fully assess sample representativeness and potential non-response bias. Future studies should include structured documentation of refusal rates and reasons for non-participation to better evaluate the representativeness of study samples. Moreover, sex distribution in the study reflects only consenting participants, and sex data for non-parti­cipants were not available, limiting the assessment of potential selection bias.

Due to the cross-sectional design, causal relationships cannot be inferred. Additionally, the study did not consider other psychological variables, such as coping strategies or social support, which could provide a broader understanding of the relationship between disease acceptance and self-efficacy. Future research should include larger samples and examine additional factors, such as lifestyle, physical activity, and overall stress levels.

Nevertheless, the study provides evidence of the relationship between disease acceptance and self-efficacy in patients with CVDs, highlighting its clinical and public health relevance.

Based on the findings, it is advisable to implement psychological interventions, such as educational programs and cognitive-behavioral therapy, aimed at enhancing patients’ sense of control over their health. Developing social support programs may also facilitate better understanding of the disease, promote more informed health decisions, and support adaptation to chronic illness. Furthermore, creating and expanding support groups for cardiac patients can improve psychological well-being and increase motivation for active disease management. Particular attention should be directed toward the most vulnerable populations, including older adults, widowed individuals, those with multimorbidity, individuals with lower educational attainment, and residents of smaller communities. Long-term interventions should be considered in future studies to monitor changes in disease acceptance and self-efficacy over several years, deepening our understanding of adaptation mechanisms to chronic illness and their psychological consequences.

CONCLUSIONS

In the present study, most patients treated for cardiovascular diseases exhibited low levels of disease acceptance and self-efficacy. The results indicate the potential to identify patient groups more likely to report lower disease acceptance or self-efficacy, particularly those who are older, have lower levels of education, live in rural areas, are widowed, and present with multiple comorbidities. The observed relationship between disease acceptance and self-efficacy highlights the importance of psychological resources in adapting to chronic illness and supports the inclusion of psychosocial interventions in patient care. Social support and psychological interventions may represent valuable components of comprehensive care aimed at supporting illness acceptance, self-efficacy, and disease self-management.

Disclosures

1. Institutional review board statement: The study was approved by the Bioethics Committee at the Medical University of Warsaw (approval no. AKBE/394/2025).

2. Assistance with the article: None.

3. Financial support and sponsorship: No external funding.

4. Conflicts of interest: The authors declare no conflict of interest.

References