Introduction

Unruptured intracranial aneurysms (UIAs) are commonly acquired vascular lesions that form an outpouching of the arterial wall owing to wall thinning1. The prevalence of UIAs in the global population is 3.2%1,2. Recent advancements in imaging technology and widespread health checks have led to early diagnoses, leading to an increased number of patients diagnosed with UIAs1. The primary concern with UIAs is the risk of rupture, triggering subarachnoid hemorrhage. Subarachnoid hemorrhage bears significant mortality risk, with 50–60% of patients succumbing to death from bleeding and complications. Even among survivors, over 30% live with permanent disabilities3,4.

The risk factors for intracranial aneurysm rupture are categorized into unmodifiable and modifiable types. Unmodifiable risk factors include characteristics of aneurysms (e.g., location, size, number, so on), and patient age, gender, and family history. Modifiable risk factors encompass those that can be altered or controlled to reduce the risk of certain diseases. These may include chronic conditions such as hypertension, diabetes, and high cholesterol1, and non-disease risk factors associated with health habits and stress factors, such as lifestyle (e.g., smoking and drinking) and sleep3,4, which can be improved through self-care performance.

Patients with UIAs need rigorous self-care to prevent rupture while monitoring the progress of conservative treatment or considering surgery3,5. The management of UIAs includes three primary options: conservative treatment (monitoring and controlling risk factors), clipping, and coiling1. Clipping is an open surgical procedure that involves a craniotomy to access the aneurysm. During the procedure, a clip is placed across the neck of the aneurysm to obstruct blood flow and prevent future rupture. Coiling, by contrast, is a minimally invasive approach. A microcatheter is guided through the vascular system to deploy platinum coils into the aneurysm, promoting thrombosis and isolating the aneurysm from the circulatory system1. Although both interventions are effective, patients must engage in ongoing self-care to prevent recurrence and ensure long-term health outcomes3.

Self-care is not limited to surgical recovery; it plays a critical role throughout the management of chronic conditions5, including UIAs. Therefore, understanding the factors that influence self-care performance among these patients is essential for developing targeted nursing strategies and interventions. Broadly, self-care is a dynamic and interactive daily process by which individuals manage their chronic conditions; specifically, it encompasses the ability to manage and treat symptoms and the physical and psychosocial consequences of illness in collaboration with family, community, and healthcare professionals, including by making lifestyle modifications6. Therefore, optimal self-care requires self-regulation, comprising an individual’s deliberate effort to monitor their disease and control their thoughts, emotions, and behaviors5,6.

In a meta-synthesis, Schulman-Green et al.7 suggested that the self-care process could be divided into three components: “focusing on the disease needs” (learning about the skills needed to manage the body and specific illness and engaging in health practices), “utilizing resources” (building relationships with family and healthcare professionals and utilizing social support, personal, spiritual, and psychological resources), and “living with a chronic illness” (dealing with emotions and adjusting to and integrating changes in one’s self and life). This categorization highlights that effective self-care transcends mere behavioral changes to include managing psychological aspects, such as problem-solving, decision-making, resource use, and emotional regulation, to proactively cope with chronic conditions.

Lifestyle improvements play a significant role in reducing the risk of cerebrovascular disease recurrence8. Even after surgery, ongoing self-care is crucial to prevent the recurrence and rupture of any remaining aneurysms. However, the typically asymptomatic nature of UIAs means that they are often discovered incidentally. When symptoms do occur, they rarely cause significant daily disruptions. This poses a challenge for disease recognition and an increased risk of neglect in post-diagnosis management1. Therefore, it is essential to identify predictors of self-care performance and develop effective interventions.

Factors influencing self-care performance among UIA patients have been reported to include sociodemographic and clinical factors, as well as psychosocial factors, such as illness perception and social support. Among these factors, illness perception is defined as the organized cognitive representation or belief an individual holds regarding their illness9. In the context of chronic diseases, illness perception has been identified as a critical behavioral determinant that influences outcomes such as treatment adherence and functional recovery, as well as adaptation to the disease10,11,12. The characteristics of illness perception significantly influence the coping strategies used to manage the illness, thereby affecting both physical and psychological health11. Research on patients who experienced stroke, which falls under the category of cerebrovascular diseases, has shown a substantial connection between illness perception and health-related behaviors10,12. Therefore, illness perception emerges as a pivotal concept as far as it underscores that the extent of self-care performance behaviors is determined through the individual’s unique cognitive representation or belief about their illness.

Social support has also demonstrated a positive correlation with self-care performance among patients with UIAs. Support from family members and medical personnel who can provide accurate knowledge, and an efficient practice system is essential to reinforce the patient’s motivation and maintenance of self-care performance13,14. Post-discharge self-care performance mostly occurs in family or community settings; thus, social support plays a significant role in self-care performance as part of disease management15,16. Studies5,17 has demonstrated a direct link between social support and self-care performance: individuals who enjoy more social support are better equipped to cope with stressful situations by improving psychological factors, such as anxiety and depression. This can positively reinforce health-promoting behaviors and coping strategies.

Most of the previous studies on aneurysm patients have focused on medical aspects, such as diagnosis, complications, and treatment methods2,4,8. Other studies have assessed quality of life18,19, or psychological symptoms, such as anxiety and depression3,15,20. While most studies were conducted on patients with ruptured intracranial aneurysms, studies on patients with UIAs remain limited. Additionally, a study focusing on patients with ruptured intracranial aneurysms identified factors affecting self-care performance in these patients21. However, patients with ruptured aneurysms and those with UIAs—typically asymptomatic and discovered incidentally—exhibit substantially different characteristics, making it difficult to generalize findings across these groups. To address this research gap, the present study aims to evaluate the contributions of sociodemographic and clinical characteristics, illness perception, and social support as predictors of self-care performance in patients with UIAs. Using hierarchical regression analysis, the study assesses how these variables interact and contribute both independently and incrementally to self-care performance. The findings will offer a foundation for developing targeted interventions to improve self-care by addressing behavioral, social, and cognitive factors.

Methods

Study design and participants

We conducted a cross-sectional correlation study to determine the effects of illness perception and social support on self-care performance in UIAs patients. The participants were recruited from among UIAs outpatients who had regular follow-ups at the Department of Neurosurgery at a university hospital in Gyeonggi-do, South Korea. The inclusion criteria for study were as follows: (1) diagnosed with UIAs at least a month before recruitment, (2) undergoing outpatient observation without surgical treatment, (3) visiting the outpatient department for follow-ups after clipping or coiling, (4) no physical functional limitations, and (5) able to communicate in a clear and conscious manner. Patients who had been diagnosed with and treated for ischemic or hemorrhagic stroke, diagnosed with cancer and treated with adjuvant therapy or undergoing adjuvant therapy, and with a history of psychiatric problems or an inability to engage in self-care were excluded.

In this study, the sample size for regression analysis was determined using a priori power analysis to ensure adequate statistical power. The analysis was conducted with G*Power 3.1.9.4 software following Cohen’s guidelines for effect size estimation. The parameters used were as follows: a median effect size (f²) of 0.15, a significance level (α) of 0.05, a statistical power (1-β) of 0.80, and 13 independent variables included in the model. The analysis indicated that a minimum sample size of 131 participants was required to detect a statistically significant effect. To account for potential attrition and incomplete responses, we increased the target sample size by 20%, collecting data from 163 individuals. After excluding 13 incomplete responses, the final sample included 150 participants (response rate 92.0%). This sample exceeded the minimum sample size required by the power analysis, ensuring that the study was adequately powered to detect meaningful effects and support the robustness of the study’s conclusions.

Measures

Illness perception

The Brief Illness Perception Questionnaire (B-IPQ)9,22, was used in the study. The B-IPQ consists of nine items, including consequences, timeline, personal control, treatment control, identity, concern, understanding, emotional response, and a descriptive question about the cause of the illness. Except for the descriptive question, each of the other eight items is rated on a 0 to 10 scale. The total score ranges between 0 and 80 points, with a higher score indicating a higher level of illness perception. The reliability of the internal consistency (Cronbach’s α) in the previous study22 was 0.77. In this study, Cronbach’s α was 0.54.

Social support

The Multidimensional Scale of Perceived Social Support (MSPSS)23,24 was used to measure participants’ perceived level of social support. This tool assesses support from three sources: family, friends, and significant others (represented by medical personnel in this study). Each item is rated on a 5-point Likert scale (1 = very strongly disagree, 5 = very strongly agree), with total scores ranging from 12 to 60. Higher scores indicate greater perceived social support. The internal consistency of the MSPSS in previous studies was Cronbach’s α = 0.8924, and in this study, Cronbach’s α = 0.87.

Self-care performance

Self-care performance was measured using a tool originally developed for patients with acute ischemic stroke25. As no validated tools specific to UIA patients are currently available, we employed this stroke-specific tool, given that both conditions are cerebrovascular diseases with overlapping self-care needs. Each item is rated on a 5-point Likert scale (1 = not being able to do it at all, 5 = doing it very well), with total scores ranging from 15 to 60. Higher scores indicate better self-care performance. The internal consistency of the tool was Cronbach’s α = 0.87 in a previous study25. In this study, Cronbach’s α = 0.74, indicating acceptable reliability to use with UIA patients.

Sociodemographic and clinical characteristics

Sociodemographic and clinical characteristics were investigated using a structured questionnaire and electronic medical records. We investigated the participants’ family histories of intracranial aneurysms, diagnosis period of UIAs, and number of intracranial aneurysms. If the individual had undergone a clipping or coiling procedure at least once for an existing UIA, then they were classified as having completed a clipping or coiling procedure (i.e., they answered “Yes” to having undergone such a procedure). Residual UIAs referred to the presence of UIAs without clipping or coiling.

Data collection

Data were collected from November 2022 to January 2023. Participants were recruited from the outpatients who visited the Department of Neurosurgery at the study site based on the recommendations of the neurologist in charge, per the inclusion criteria. A list of patients who visited the outpatient clinic was obtained from a clinical nurse in advance, and convenience sampling was conducted to select patients with UIAs according to the selection criteria. The questionnaire survey was conducted after the researcher explained the purpose of the study to individual potential participants and obtained written informed consent from them. For individuals who needed assistance in reading or completing the questionnaire, each question was read out by the researcher and the participants provided an immediate response. The time required for completing the questionnaire was approximately 15 min. Among the measurement variables, some of the clinical characteristics were examined through a review of electronic medical records after obtaining consent from each patient.

Ethical consideration

This study meets the ethical standards outlined in the Declaration of Helsinki, and ethics approval was obtained from the institutional review board of University Hospital (IRB no. AJOUIRB-SB-2022-376). Participants were provided with a written explanation of the research through a participant information sheet including purpose, anticipated duration, confidentiality of content, management of personal information, and contact of the researchers. Participants were informed about their right to withdraw from the study at any time. All data were coded and stored in a personal information storage device. The data files were password-protected to ensure that the research data were inaccessible to anyone other than the researcher.

Data analysis

The collected data were analyzed using the SPSS WIN 29.0 program. Participants’ sociodemographic and clinical characteristics were summarized through descriptive statistics. Differences in self-care performance across participant characteristics were examined using independent t-tests and one-way ANOVA, with Scheffé’s test employed for post-hoc comparisons. The relationship among illness perception, social support, and self-care performance were analyzed using Pearson’s correlation coefficient.

Hierarchical regression analysis was conducted to evaluate the predictors of self-care performance and control for potential confounding variables. This method was chosen based on its ability to assess the incremental contribution of predictors26 and its usefulness in controlling for confounding variables26. To identify predictors of self-care performance, hierarchical multiple regression analysis was performed, incorporating variables that were statistically significant in the univariate analysis as independent variables. In the first step, variables such as gender, marital status, current smoking status, and current drinking status were entered to control for potential confounding effects. In the second step, illness perception and social support were added to assess their additional contribution to the explained variance in self-care performance. In the hierarchical regression analysis, the significance and contribution of variables added at each step were evaluated through the significance test of the incremental change in the adjusted R² (Δ Adj. R²).

Results

Participants’ sociodemographic and clinical characteristics

The mean age of the participants was 58.1 ± 10.4 years, with 66.0% being female and 77.3% married. Among the 150 participants, 30.7% reported current smoking, 52.7% consumed alcohol, and 15.3% had a family history of intracranial aneurysms. The average duration since diagnosis was 35.37 ± 40.14 months, the mean aneurysm size was 4.90 ± 5.06 mm, and the average number of aneurysms per participant was 1.55 ± 0.85. A total of 70.7% of participants had undergone clipping or coiling procedures, while 50.0%had residual intracranial aneurysms without having received clipping or coiling (Table 1).

Table 1 Differences in self-care performance according to participants’ sociodemographic and clinical characteristics (N = 150).
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Descriptive statistics of the measurements

The mean of illness perception scores among the participants was 43.70 ± 11.58 points. Among the subdomains, the mean of treatment control was the highest at 7.91 ± 2.36 points, and the mean of symptom identify was the lowest at 3.39 ± 3.28 points. The mean of social support was 43.22 ± 8.87. Among the subdomains, the mean of social support from the family was the highest at 17.26 ± 3.37 points, followed by social support from friends (14.44 ± 3.90) and social support from medical personnel (11.52 ± 4.93). The mean self-care performance score was 57.37 ± 7.73 points (Table 2).

Table 2 Results for illness perception, social support and self-care performance (N = 150).
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Self-care performance according to the participants’ sociodemographic and clinical characteristics

Statistically significant differences in the self-care performance scores were found based on participants’ sociodemographic and clinical characteristics. These differences were observed for the variables of gender (t=-2.70, p = 0.009), marital status (t = 2.64, p = 0.009), current smoking status (t=-4.94, p < 0.001), and current drinking status (t=-3.96, p < 0.001; Table 1).

Relationships between the illness perception, social support, and self-care performance

The self-care performance score was positively correlated with illness perception (r = 0.21, p = 0.009) (Table 3). Meanwhile, self-care performance showed a significant positive correlation with both medical expenses support (r = 0.30, p < 0.001) and family support (r = 0.32, p < 0.001) (Table 3).

Table 3 Correlations among illness perception, social support and self-care performance (N = 150).
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Predictors that affect the participants’ self-care performance

A two-step hierarchical regression analysis was conducted to identify the factors influencing participants’ self-care performance scores. Before testing the regression model, the underlying assumptions for performing multiple regression analysis were tested, and all assumptions were satisfied.

In Step 1, sociodemographic and clinical variables (gender, marital status, current smoking status, and current drinking status) were entered, explaining 20.2% of the variance in self-care performance scores. Among these variables, being married (B = 3.21, p = 0.021), being a non-smoker (B = 5.58, p = 0.001), and being a non-drinker (B = 2.89, p = 0.025) were significantly associated with higher self-care performance. In Step 2, the subdomains of illness perception and social support were added, and the significance and contribution of the added variables were evaluated by testing the incremental change in the adjusted R² (Δ Adj. R²). The explanatory power increased by 12.2%, bringing the total explained variance to 31.4% (F = 10.73, p < 0.001). In the final model, significant predictors included being a non-smoker (B = 4.73, p = 0.003), being a non-drinker (B = 2.56, p = 0.035), receiving social support from family (B = 0.51, p = 0.002) and health care providers (B = 0.28, p = 0.011), and having a strong perception of illness (B = 0.10, p = 0.029). Marital status was no longer significant (p = 0.066) in the final model, and gender remained non-significant (p = 0.778) (Table 4).

Table 4 Impact of illness perception and social support on self-care performance (N = 150).
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Discussion

This study investigated the levels of illness perception, social support, and self-care performance among patients with UIAs and identified the factors associated with their self-care performance. We expected to provide information that could serve as a foundation for developing effective nursing intervention programs for preventing the occurrence and recurrence of aneurysm ruptures.

In our study, the average self-care performance score among participants with UIAs was 57.37 points out of a total of 75, which was slightly lower than the 60.45 points reported in a previous study18 that similarly examined the self-care performance of patients with UIAs. This disparity may be attributed to the higher percentages of current smokers and drinkers in our sample.

In this study, a certain trend was observed when classifying individual self-management scores by item: high compliance with treatment directives, such as attending regular hospital visits and adhering to medication, contrasted with lower compliance in lifestyle changes, such as maintaining diet habits, monitoring blood pressure, recognizing disease risks, and avoiding sudden temperature fluctuations. This pattern aligns with that in a previous study on patients with UIAs18, which reported below-average scores in areas such as diet, exercise, routine precautions, and blood pressure self-monitoring. Effective management of medical risk factors for UIAs, such as hypertension, diabetes, and dyslipidemia, requires constant blood pressure monitoring and diligent dietary control27,28.

In our study, however, these aspects showed the lowest score, aligning with previous findings29 on Koreans’ sodium intake, which pointed to the discrepancy between awareness of the risks associated with excessive sodium intake and actual dietary compliance. Shimizu et al.30 reported that a high-fat diet, resulting in increased serum cholesterol, can accelerate the progression of brain aneurysms owing to cellular changes. This underscores the importance of incorporating dietary improvement strategies in educational materials designed to enhance self-care among patients with UIAs.

We also observed a notably low score in terms of self-monitoring of blood pressure, ranking just after dietary behavior. Among the participants, 68% had comorbidities, with the main disease being hypertension (41%). Zhong et al.28 found that patients who neglect regular blood pressure monitoring face a statistically higher risk of aneurysm rupture compared with those who practice regular monitoring, underscoring the crucial need for consistent blood pressure monitoring and control. Moreover, a growing body of research emphasizes the significance of self-monitoring blood pressure to reduce hypertension and enhance blood pressure management27,28.

For patients with UIAs, avoiding sudden temperature changes is as important as adhering to treatment directives, but scores were relatively low in this study. Hr et al.31 reported that the rupture rate of brain aneurysms increases in low temperatures or with significant temperature fluctuations. Lee and Guth32 also reported that during hot summer periods, prolonged exposure to heat owing to temperature rise increases the risk of rupture of brain aneurysms. Hence, patients with UIAs must be educated to avoid prolonged exposure to extreme temperatures during summer and winter, and to avoid sudden temperature fluctuations, as experienced in saunas and hot baths.

In our sample, the average score for illness perception was 43.7 out of 80. This is significantly higher than the baseline scores reported by patients with UIAs in a study that provided a cognitive-behavioral therapy intervention—27.63 and 31.25 in the experimental and control groups, respectively33. The variation in illness perception scores for the same disease may be influenced by individual circumstances and cultural factors34, and could be attributed to demographic elements, such as ethnicity, education level, and economic status.

Our participants also exhibited a medium level of illness perception related to the chronicity of their conditions, suggesting that UIAs may not generally be perceived as a chronic condition. In contrast, Lemos et al.33 reported that patients with UIAs tend to perceive their condition as chronic. In terms of symptom experience, our participants scored low, similar to the results in Lemos et al.33, supporting the earlier finding that UIAs are often asymptomatic when discovered. This suggests the potential risk of insufficient self-care, highlighting the importance of developing targeted education programs. Considering the crucial role of regular imaging follow-ups and self-care, such as smoking cessation and blood pressure monitoring18,27,28, health authorities need to foster an understanding of UIAs as chronic conditions and enhance disease awareness among patients.

In this study, the illness perception tool demonstrated lower internal consistency (Cronbach’s α = 0.54) compared to previous studies (Cronbach’s α = 0.77)22. The lower reliability might have reflected the unique characteristics of UIA patients, such as their asymptomatic presentation, which could have reduced their engagement with illness-related items. Patients without overt symptoms might have interpreted or responded to questions inconsistently, leading to variability in responses35.

Regarding social support, our participants scored an average of 43.22 out of 60. According to the subscale, family support scored higher than support from medical personnel or friends. This trend may be attributed to Korea’s family-centered lifestyle, where family members are often the primary caregivers. Additionally, the nature of UIAs, typically characterized by infrequent hospital visits and shorter hospital stays for treatment, likely results in more frequent interactions with family members than with medical personnel. The lack of previous research assessing social support among patients with UIAs made it difficult to compare our results. One study by Kang and Lee36 that assessed social support in patients who experienced stroke using the same tool (i.e., the MPSS) reported a similar average score—3.65 out of 5 (43.8 out of 60 when converted). The above-average level of social support observed in our study may be attributed to the nature of cerebrovascular diseases, which often necessitate family engagement and medical care throughout the course of the illness36.

To determine the predictors of self-care performance among patients with UIAs, we conducted the hierarchical multiple regression analysis. Among the participants’ general characteristics, four control variables that exhibited statistically significant differences in self-care performance—gender, marital status, current smoking status, and current drinking status—were entered in the first step to assess their impact on self-care performance. In the second step, we further incorporated illness perception, support from medical personnel, and family support. In Model 1, marital status (married), current smoking status (no), and current drinking status (no) showed a significantly positive impact on self-care performance. In Model 2, the variables that significantly positively impacted self-care performance were family support, support from medical personnel, illness perception, current smoking status (no), and current drinking status (no), accounting for 34.6% of the variance.

The Model 1 regression analysis identified current smoking and drinking as significant determinants of self-care performance. These behaviors are known to cluster together with other self-care practices, including physical activity, nutrition, and diet, indicating that they are not independently found but interdependent and co-occurring37. Tanji et al.38 reported that among patients with intracranial aneurysm, 17.9% are current smokers and 25.5% are former smokers. Current smokers are more likely to be overweight or obese, drink alcohol daily, and have elevated cholesterol levels. Smoking also correlates with decreased appetite and taste sensitivity, which can lead to irregular eating habits and preferences for caffeine, high-fat foods, fast food, instant meals, processed foods, and spicy and salty foods, ultimately contributing to increased sodium intake29.

Research on smoking cessation following a cerebrovascular disease diagnosis indicates that cessation rates vary between 15% and 46%39. This suggests that, despite a significant reduction in the proportion of smokers, a substantial number continues to smoke. Given that smoking is a leading risk factor for intracranial aneurysms, cessation is imperative for patients with UIAs. As factors tend to cluster and influence one another, health care teams must actively promote smoking cessation among patients with UIAs post-diagnosis, educate them on the importance of quitting smoking, and provide adjunct methods to facilitate quitting, including educational materials and intervention programs.

Additionally, family support and support from medical personnel were identified as key factors positively influencing self-care performance among patients with UIAs. The absence of prior studies specifically addressing self-care performance in patients with UIAs precluded a direct comparative analysis. Nonetheless, our results are in line with previous research36,40,41, in which social support is reported as a significant determinant of self-care in patients with cerebrovascular disease.

Family members, as primary caregivers, play a crucial role in assisting patients to cope with their challenges, reorganize their lives, and maintain a normal life as far as possible, including managing self-care15. Family support is known to positively impact self-care performance, as families often share dietary habits, daily routines, and assist in medication adherence, dietary planning, compliance, and illness monitoring42. Studies14,41 on patients who experienced stroke have reported that higher levels of family support correlate with improved self-care performance and sustained adherence. However, family support that is misaligned or offers advice in conflict with self-care recommendations can inadvertently promote unhealthy behaviors, adversely affecting self-care40. Therefore, actively involving families in the treatment process, enhancing their understanding of the disease, and providing them with education and intervention programs are crucial to enhancing patients’ self-care through appropriated family support.

Support from medical personnel, which includes active listening, emotional backing, and the provision of health management education43, has been shown to positively impact self-care. A study14 on patients who experienced stroke demonstrated that enhanced support from medical personnel leads to better self-care and prolonged adherence. Azami et al.44 emphasized the critical role of nurses’ social support in boosting self-care, given nurses’ ideal position to monitor essential aspects of self-care, provide customized feedback, and impart education. Moreover, nurses should also extend their support to families, not only by offering self-care programs to patients but also by encouraging family involvement and support45. As such, effective self-care hinges on both maintaining emotional stability through family support and gaining access to well-informed and systematic assistance from medical personnel for less common diseases and treatment processes46. Nevertheless, given the current scarcity of research on social support among patients with UIAs, further studies must be conducted, along with the development of intervention programs encompassing education, counseling, and support activities.

Lastly, we identified illness perception as a significant factor influencing self-care. Although a direct comparison with previous studies on self-care in patients with UIAs is difficult owing to their absence, our findings are consistent with previous studies on patients with cerebrovascular diseases, which revealed that illness perception impacts self-care10,12. Illness perception consists of cognitive and emotional dimensions. The former encompasses the perceived impact of the disease on life according to its severity and expected duration, as well as personal and treatment control, symptom recognition, and understanding of the disease. The emotional dimension involves the emotional impact and worries associated with the disease12. Cognitive and emotional illness perceptions can improve disease understanding, thereby enhancing participation in health-promoting behaviors10. Consequently, higher levels of illness perception are likely to positively affect self-care activities, including medication adherence and the upkeep of healthy lifestyle choices.

Considering the observed differences in self-care depending on illness perception, medical personnel should assess the illness perception of patients with UIAs with respect to managing risk factors and adapting to living with the disease. Patients with lower levels of illness perception are more likely to believe that they cannot alter their pathological conditions, leading to difficulties in maintaining health-promoting behaviors10. Therefore, nursing interventions intended to enhance self-care must be tailored to the levels of illness perception of individual patients with UIAs. In this context, given that illness perception is modifiable, upward modification of illness perception can improve self-care11,12. Health care teams should determine the factors influencing self-care in each dimension of illness perception in patients with UIAs such that healthy levels are maintained. Despite the lower reliability, the tool provided valuable insights into illness perception in this study. Future research should explore ways to adapt or refine the tool by focusing on domains that are more relevant to asymptomatic conditions like UIAs. Additionally, incorporating qualitative methods, such as patient interviews, could provide deeper insights into the illness perceptions of UIA patients, which are not fully captured by the existing tool.

In interpreting the results of our study, the following limitations need to be considered. First, all participants were recruited from a single tertiary hospital via convenience sampling, and their medical support was provided by staff from the same institution. This recruitment strategy limits the generalizability of the findings to other healthcare institutions or broader populations. The uniformity of care within a single institution may not reflect the diversity of medical support systems available elsewhere. Future research should recruit participants from multiple institutions to better capture variability in medical care and social support, thereby enhancing the external validity of the findings and providing more robust insights into the role of medical support in self-care performance among UIA patients.

Second, self-care performance was assessed solely through self-reported questionnaires, which introduces the possibility of response bias or inaccuracies, particularly for sensitive aspects of self-care. Future studies should complement self-reported data with objective measures, such as hematological parameters or electronic health records, to ensure more accurate and reliable assessments. In addition, the self-care performance tool used in this study was originally developed for stroke patients. Although it was applicable to this study, it may not fully capture the unique self-care needs of patients with UIAs. Future research should modify and enhance this tool to include items that are specifically relevant to UIA patients, thereby improving its applicability and accuracy.

Lastly the illness perception tool used in this study exhibited low internal consistency. Although this tool has demonstrated reliability in previous studies, the differences in illness experiences between stroke and UIA patients may have affected its internal consistency in this study. The asymptomatic nature of UIAs might have led to variability in responses, reducing the tool’s reliability. Future research should focus on adapting or developing new tools tailored specifically to UIA patients to improve reliability. Additionally, cross-cultural validation would enhance the tool’s applicability in diverse patient populations.

Conclusion

Our study demonstrated the correlations between self-care performance and factors such as illness perception and social support in patients with UIAs. It identified the following key predictors of self-care performance: current smoking status, current drinking status, social support (from family and medical personnel), and illness perception. Our findings underscore the importance of considering these factors when developing education and intervention programs aimed at enhancing self-care performance among patients with UIAs.