AbstractPurposeThis study explored the influence of family support, self-care performance and symptom cluster on quality of life (QoL) among individuals with Parkinson’s disease (PD).
MethodsA cross-sectional descriptive study was conducted with 132 participants who were over 40 years old and diagnosed with PD from a tertiary hospital in Seoul between September 5 and November 7, 2024. Data were analyzed using descriptive statistics, factor analysis, t-tests, ANOVA, correlation, and hierarchical multiple regression analysis.
ResultsThe explanatory power of the final regression model was 71% (F=17.72, p<.001). The most significant factors affecting QoL were motor symptom clusters (t=4.38, p<.001), emotional/emotion regulation clusters (t=2.90, p=.004), time since diagnosis (t=-3.11, p=.002), having a spouse as the primary caregiver (t=2.55, p=.012), self-care performance in the daily life management domain (t=-2.35, p=.020), and self-care performance in the diet domain (t=-2.01, p=.046).
INTRODUCTION1. BackgroundParkinson’s disease (PD) is the second most prevalent degenerative central nervous system disorder in individuals over 50, following dementia. Its prevalence increases with age; however, recently, early symptoms have been appearing in individuals under 49, indicating a trend toward a gradually decreasing age of onset [1]. The number of individuals diagnosed with PD in South Korea has increased by 70% over a period of 7 years, from approximately 96,600 in 2016 to approximately 130,000 in 2023. Projections indicate that this number will exceed 150,000 by 2025 [2]. Consequently, the health insurance medical expenditures have escalated dramatically, with an observed increase of 191.9% [2]. The quality of life for individuals with PD has been documented as being lower in comparison not only to that of healthy individuals of the same age, but also to that of stroke and diabetes patients [3]. PD is a progressive disorder with no known cure once it develops. Current treatments focus on maintaining daily functioning through dopamine agonists [4].
Self-care performance among individuals with PD exhibits a gradual decline over time, largely attributable to the nature of the condition. The variability in medication effects contributes to the challenge of maintaining self-management of symptoms [5,6]. Consequently, patients require assistance from others in their daily lives and activities, and role of family members, particularly spouses, has been found to be of particular importance. Spouses have been reported to be the primary caregivers for 66.0% of individuals diagnosed with PD [7], underscoring the pivotal role that spouses play in patient management. Family support constitutes a crucial foundation that extends beyond merely meeting the patient’s needs. It has been demonstrated that such support enhances emotional stability and self-efficacy, thereby promoting the patient’s self-care performance and, in turn, improving the patient’s quality of life [8].
Recent studies have emphasized the classification of PD symptoms into symptom clusters to propose more structured and personalized symptom management, thereby gaining prominence [9]. The intricate combination of diverse symptoms in PD suggests that symptom management is difficult and intricate, negatively impacting quality of life [9]. This underscores the necessity for customized nursing interventions tailored to address the distinctive manifestations of each symptom cluster.
Domestically, research tends to focus more on the burden on families and support measures for them rather than on the quality of life if individuals with PD. This study aims to categorize the diverse symptoms of individuals with PD into symptom clusters, thereby proposing a more systematic and personalized approach to symptom management. Furthermore, this study seeks to examine the relationship between symptom clusters, self-care performance, family support, and quality of life, and to provide foundational data for developing a family-centered nursing intervention program based on these findings.
2. PurposeThe purpose of this study is to identify symptom clusters in PD and to examine the relationships among family support, self-care performance, symptom clusters, and quality of life, thereby providing foundational data for developing a family-centered nursing intervention program.
The specific objectives were:
1) to identify the general characteristics, disease-related characteristics, family support, self-care performance, and quality of life;
2) to determine the symptom cluster of each participant;
3) to examines differences in quality of life based on general characteristics, disease-related characteristics, and study variables; and
4) to identify factors affecting the quality of life of individuals with PD.
METHODS
Ethic statement: This study was approved by the Institutional Review Board (IRB) of the Samsung Medical Center (IRB No. SMC 2024-08-032-001). Informed consent was obtained from the participants.
1. Study DesignThis study is a cross-sectional descriptive survey designed to identify the relationships among family support, self-care performance, symptom clusters, and quality of life in individuals with PD, and to analyze their impact on quality of life. This study utilized the Theory of Unpleasant Symptoms proposed by Lenz et al. [10] as a conceptual framework to understand the concept of symptom clusters and their effects. This study was designed to reflect the characteristics of individuals with PD, incorporating cognitive (gender, occupation, marital status, etc.), emotional (family support), behavioral (self-care performance), and outcome factors (quality of life). This study was described in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines (https://www.strobe-statement.org).
2. ParticipantsThe inclusion criteria for participants were adults aged 40 years or older diagnosed with PD, while exclusion criteria were a history of neurological disorders or communication difficulties. Using G*Power 3.1 software, the sample size was calculated based on an effect size of 0.15, a significance level of .05, a power of 0.90, and six independent variables. Considering a 10% dropout rate, 137 participants were recruited. After excluding data from five individuals with incomplete responses, the final analysis included data from 132 participants.
3. Measures2) Self-Care PerformanceThe self-care performance was assessed using a 34-item scale developed by Kim and Min [13] based on research by Song et al. [14]. This instrument, scored on a 5-point Likert scale, comprised six domains: exercise (6 items), diet (7 items), medication (5 items), symptom management (5 items), daily life management (6 items), and environmental management (5 items). A higher measured score indicates a higher level of self-care performance. Given the absence of identified citations subsequent to its development, a Content Validity Index (CVI) was calculated based on a 4-point scale to ascertain content validity prior to conducting the research. In this study, a panel of seven experts was convened for the purpose of validation. The panel consisted of five nurses with over 5 years of experience in neurology wards, one neurologist, and one 4th-year neurology resident. The CVI was confirmed to be 0.78 or higher for all items. The Cronbach’s ⍺ was .80 in this study.
3) SymptomsThe assessment of PD symptoms was conducted using the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) Part 1 (non-motor symptoms, 13 items) and Part 2 (motor symptoms, 13 items) via self-report. Each item is scored on a scale of 0 to 4 points, with a higher score indicating a higher severity of symptoms [15]. In this study, Cronbach’s α for Part 1 and Part 2 was .87 and .93, respectively.
4) Quality of LifeThe quality of life of the participants was assessed using the 8-item Parkinson’s Disease Questionnaire (PDQ-8). Each item was evaluated on a scale of 0 to 4 points, subsequently converted to a 100-point scale for analysis [16].
4. Data CollectionThis study was conducted using convenience sampling of individuals with PD at Samsung Medical Center, a tertiary hospital, from September 5 to November 7, 2024. The investigator elucidated the objective of the study to patients awaiting outpatient care or immediately following admission, obtained their consent to participate, and subsequently requested that they complete the questionnaire. A subsequent analysis of the electronic medical records, accessed with the consent of the hospital department head and the participants, revealed the presence of certain disease-related characteristics. Participants were provided with a token of appreciation.
5. Data AnalysisThe collected data were analyzed using the SPSS 29.0 program (IBM Corp.). The analysis methods are as follows:
1) The general characteristics and disease-related characteristics of the participants, family support, self-care performance, symptoms, and quality of life were analyzed using frequencies, percentages, means, and standard deviations.
2) Principal component analysis with Varimax orthogonal rotation was performed for symptom cluster classification, and the adequacy was verified using the Kaiser-Meyer-Olkin (KMO) method and Bartlett’s test. The derived symptom clusters were described using frequencies, means, and standard deviations.
3) The differences in quality of life based on the general characteristics and disease-related characteristics of the participants were analyzed using t-tests and ANOVA, and post-hoc tests were performed using Scheffé tests.
4) The correlations among the study variables, including family support, self-care performance, symptom clusters, and quality of life, were analyzed using Pearson’s correlation coefficient.
5) The effects of family support, self-care performance, and symptom clusters on quality of life were examined using hierarchical multiple regression analysis.
6. Limitations of the StudyAs this study is a convenience sample study conducted at a single institution in Seoul, it may not reflect the characteristics of patients in the community or those affiliated with other healthcare institutions. In addition, due to the nature of PD, patients often attend outpatient appointments accompanied by caregivers. Therefore, during the course of the study, the influence of caregivers may have affected participants’ responses regarding family support and self-care performance. Since the caregivers were present in the same space as the patients, responses related to family support or self-care practices may not fully reflect the actual patient experience, potentially leading to selective bias.
RESULTS1. Participant Characteristics and Research VariablesThe general characteristics of the participants are shown in Table 1. The mean age of participants was 70.27±8.82 years. The majority of participants were unemployed (51.5%) or had lost their jobs due to PD (31.8%). Regarding the diagnosis of PD, the most common scenario was immediate diagnosis and treatment initiation at the onset of symptoms, accounting for 41.7% (n=55). Delays exceeding 2 years were observed in 30.3% (n=40) of cases. The most common daily levodopa dosage among study participants was found to be between 300 and 600 mg, accounting for 41.7% of the sample (n=55). Meanwhile, 19.7% (n=26) of participants received a daily dosage of 600 mg or more.
The analysis of differences in self-care performance according to general characteristics revealed significant differences in the exercise domain based on education level and number of current illnesses. Self-care performance in the exercise domain showed a significant difference based on education level (F=3.47, p=.034), and post-hoc tests revealed that the group with a college degree or higher scored higher than the group with a middle school education or lower. The difference based on the number of current illnesses was also confirmed (F=5.29, p=.006), with the group without current illnesses showing higher performance than the group with two or more current illnesses. Significant differences were found in the dietary domain based on religion status (t=2.06, p=.042), while the medication domain and daily life management domain showed significant differences based on smoking history (F=4.45, p=.029; F=3.62, p=.030). The self-care performance of the group with no smoking history was higher than that of the group with a smoking history or current smokers. In the symptom management domain, employment status had a significant effect (F=3.80, p=.025), with the group unemployed due to PD demonstrating higher performance than the group unemployed for reasons unrelated to the disease. The self-care performance in the environmental management domain showed a significant difference based on religion status (t=2.19, p=.031). The quality of life exhibited significant differences depending on the participants’ educational background, employment status, and timing of diagnosis. The difference in quality of life according to education level was significant (F=3.71, p=.027), with the group having a middle school education or lower reporting a lower quality of life compared to the group with a college degree or higher. The analysis by employment status also revealed significant differences (F=5.57, p=.005), with the group unemployed due to PD having the lowest quality of life. The analysis by timing of diagnosis indicated that patients diagnosed with a delay of 1 to 2 years experienced significantly lower quality of life compared to those diagnosed within 1 year (F=4.94, p=.009).
With respect to family characteristics, 84.8% (n=112) of participants reported residing with their spouse, and 62.9% (n=83) indicated that their spouse served as their primary caregiver. The investigation of family support levels according to family characteristics indicated that the group residing with a spouse exhibited significantly higher levels of family support compared to the group not residing with a spouse (t=3.07, p=.003).
2. Symptoms and Symptom Clusters1) Symptom ClustersPrincipal component analysis with Varimax rotation applied to 26 symptoms revealed no factors with loadings below 0.4. The KMO sample adequacy index was 0.90, confirming the adequacy of the sample for factor analysis. Bartlett’s test of sphericity yielded a value of 2,189.63 (p<.001, degree of freedom=325), indicating suitability for analysis. The analysis yielded five factors, explaining 64.93% of the total variance (Table 2). Factor 1 was named the “motor symptom cluster” for stiffness, tremor, and pain; Factor 2 was named the “daily activity cluster” for swallowing, personal hygiene, and walking; and Factor 3 was named the “emotional/affective regulation cluster” for anxiety, depression, and dopamine regulation issues. Factor 4 was named the “psychiatric/autonomic nervous system cluster” for hallucinations, constipation, and cognitive impairment, and Factor 5 was named the “communication/sleep cluster” for sleep problems, speech issues, and drooling (Table 2).
2) Distribution by Symptom Cluster ItemThe results of analyzing participants’ symptoms into symptom clusters are shown in Table 3.
In the motor symptom cluster, the “Getting out of bed” symptom was identified in 79.5% of cases, with an average score of 1.44±1.15 points, indicating relatively high frequency and severity. In the daily living cluster, “Walking and balance” was observed in the highest proportion of participants at 86.4%, demonstrating high severity with an average score of 1.75±1.28. “Hobbies and other activities” (72.7%, 1.30±1.19) and “Dressing” (73.5%, 1.12±1.03) also emerged as major symptoms. In the emotional/affective regulation cluster, “Depression mood” had the highest frequency at 74.2%, with an average score of 1.01±0.80. “Anxious mood” also affected a large proportion of participants at 60.6%, with an average score of 0.86±0.90. In the psychiatric/autonomic nervous system cluster, “Constipation” and “Fatigue” showed high frequencies of 72.7% each, with average scores of 1.23±1.07 and 1.05±0.93, respectively. Additionally, the frequency of “Daytime sleepiness” was confirmed at 72.0%, with an average score of 1.30±0.97, and “Urinary problems” also showed a high prevalence at 69.7%, with an average score of 1.35±1.27, indicating frequent occurrence of these symptoms among participants. Finally, within the communication/sleep cluster, “Speech issue” was observed with a high frequency of 65.2%, with an average score of 1.15±1.15. “Sleep problems” also occurred frequently at 56.8%, with an average score of 1.23±1.31. In conclusion, motor symptoms (getting out of bed), daily living activities (walking/balance), emotional/affective regulation (depression, anxiety), psychiatric/autonomic nervous system (constipation, fatigue), and communication/sleep (speech, sleep problems) emerged as the core issues.
The findings of the study indicated that patients diagnosed with PD manifest physical symptoms, including impaired walking and balance, as well as emotional problems, such as depression mood. Additionally, these patients frequently experience autonomic nervous system-related symptoms, such as fatigue, constipation, and sleep problems.
3. Correlation With Family Support, Self-Care Performance, Symptom Clusters, and Quality of LifeThe correlations between quality of life and research variables are described in Table 4. The quality of life exhibited a negative correlation with family support (r=-.23, p=.009) and specific domains of self-care performance (exercise: r=-.35, p<.001; diet: r=-.25, p=.004; daily life management: r=-.43, p<.001).
On the other hand, strong positive correlations were observed with all symptom clusters (motor symptom cluster: r=.72, p<.001; daily activity cluster: r=.67, p<.001; emotional/affective regulation cluster: r=.62, p<.001; mental/autonomic nervous system cluster: r=.62, p<.001; communication/sleep cluster: r=.52, p<.001).
4. Factors Affecting Quality of LifeThe factors affecting the quality of life of individuals with PD were identified using hierarchical regression analysis (Table 5). The analysis results showed that the Durbin-Watson statistic was 2.46 in all models, satisfying the independence of residuals, and no multicollinearity issues were identified as the VIF was below 10. The explanatory power of the final model was found to be 71% (R2=.71, F=17.72, p<.001).
In Regression Model 1, significant differences in quality of life were observed. These differences were attributed to general characteristics and disease-related characteristics. The general characteristics included educational level, employment status, residing with a spouse, having a spouse as the primary caregiver, timing of diagnosis (within 1 year), and family support. Family support was found to have a correlation with quality of life. The disease-related characteristics included general characteristics and disease-related characteristics. This model was statistically significant (F=3.97, p<.001), with a 21% explanatory power (R2=.21). The variables found to significantly impact quality of life were education level of middle school or lower, unemployment, timing of diagnosis (within 1 year), and family support.
In Regression Model 2, the self-care domains (exercise, diet, and daily living management) that showed a correlation with quality of life in Model 1 were additionally included. This model was statistically significant (F=6.18, p<.001), with a slightly increased explanatory power of 36% (R2=.36). The significant variables affecting quality of life were employment status, timing of diagnosis (within 1 year), and self-care performance (management of daily living activities).
Regression Model 3 incorporated the symptom cluster as an additional input into Model 2. This model was statistically significant (F=17.72, p<.001) with a substantial increase in explanatory power to 71% (R2=.71). The variables exerting the most substantial influence on quality of life were identified as symptom clusters, namely the motor symptom cluster (β=0.39, p<.001) and the emotional/affective regulation cluster (β=0.20, p=.004). Furthermore, when the primary caregiver was the spouse (β=0.14, p=.012), self-care performance (diet: β=-0.12, p=.046, daily life management: β=-0.14, p=.020), and the time from symptom onset to diagnosis (within 1 year: β=-0.17, p=.002) in that order. These findings imply that higher self-care performance (diet, daily life management) and early diagnosis improve quality of life, whereas higher severity of specific symptom clusters (exercise, emotional/affective regulation) and having a spouse as the primary caregiver are associated with lower quality of life.
DISCUSSIONThis study identified symptom clusters in individuals with PD and determined key factors influencing the impact of family support, self-care performance, and symptom clusters on quality of life.
The symptoms experienced by individuals with PD have been categorized into five major symptom clusters. The motor symptom cluster consisted of symptoms such as rigidity, tremor, and pain, limiting the physical independence of patients and significantly impacting their daily functioning and quality of life [9]. The daily activity cluster consisted of symptoms related to basic daily living abilities such as swallowing, personal hygiene, and walking. In patients with PD, the decline in activities of daily living worsens with disease progression and is closely linked to reduced independence and quality of life [17]. The emotional/affective regulation cluster encompasses emotional symptoms such as anxiety, depression, and apathy. These emotional issues are profoundly associated with dopamine transmission abnormalities in patients with PD [18]. The psychic/autonomic nervous system cluster consisted of autonomic nervous system and neuropsychiatric symptoms such as hallucinations, constipation, and urinary issues. These symptoms can serve as key indicators for assessing disease progression and treatment responsiveness [19]. The communication/sleep cluster consisted of sleep problems and speech disorders, which were closely linked to neurological and muscular abnormalities in individuals with PD [20].
An investigation into the interplay among symptom clusters, self-care performance, and family support in individuals with PD yielded findings of mutual significance.
First, a positive correlation was substantiated between symptom clusters. This finding suggests that PD symptoms exhibit a complex interrelationship rather than manifesting in isolation. Specifically, the correlation between the motor symptom cluster and the daily living cluster exhibited the most robust positive association. This finding suggests that the progression of motor symptoms has a greater adverse effect on daily living activities, thereby corroborating the conclusions of previous studies [9,20] that the advancement of PD leads to an exacerbation of functional limitations in patients. Therefore, a comprehensive cluster-based approach is more important than evaluating individual symptoms alone in the clinical assessment of individuals with PD. Among the various symptom clusters, the daily activity cluster, the emotional/affective regulation cluster, and the mental/autonomic nervous system cluster exhibited a negative correlation with self-care performance. This finding implies that as PD symptoms progress, patients’ self-care performance declines. This symptom cluster is distinguished by the presence of emotional symptoms, including depression, anxiety, and apathy. These findings align with prior research emphasizing the significance of managing non-motor symptoms in individuals with PD [18]. The daily activity cluster and the emotional/affective regulation cluster demonstrated a negative correlation with family support. This finding indicates that as functional and emotional symptoms intensify, patients may experience a diminution in awareness of family support, or family members may encounter limitations in their ability to provide adequate support due to the demanding nature of caring for patients [21]. Therefore, the establishment of a social infrastructure support system is essential to enhance the capabilities of family caregivers, taking into account the unique characteristics of each patient’s symptoms. A positive correlation was observed between family support and self-care performance. This finding aligns with the observations of prior studies [8,11], demonstrating that family support enhances self-management behaviors among patients. Therefore, educational and nursing interventions that engage family members as caregiving resources may be effective in enhancing self-care performance.
An analysis of the factors influencing quality of life in individuals with PD revealed that the motor symptom cluster, emotional/affective regulation cluster, dietary and daily living management domains within self-care performance, a spouse as the primary caregiver, and the timing of diagnosis emerged as significant factors in the final regression model.
Notably, during the hierarchical regression analysis process, the explanatory power increased approximately two-fold, from 36% to 71%, in the model that incorporated the symptom cluster compared to the model that only included general/disease characteristics, family support, and self-care. This finding underscores the importance of symptom clusters in the quality of life of individuals with PD, suggesting that the motor symptom cluster is directly associated with physical independence and represents a major factor in reduced quality of life. It supports existing literature indicating that motor symptoms are the strongest predictor of quality of life [10,18]. Additionally, the emotional/affective regulation cluster emerged as a second robust predictor, encompassing symptoms such as depression, anxiety, and apathy. This finding aligns with prior research [17] indicating that such emotional difficulties, in conjunction with physical discomfort, contribute to an overall diminished quality of life. It appears that nursing interventions for individuals with PD should take into account both the maintenance of motor function and emotional stability in a holistic manner. It is incumbent upon nurses to provide rehabilitation nursing care to prevent functional decline due to patients’ motor symptoms and to support independent living. Concurrently, nurses must conduct early assessments of emotional symptoms such as depression and anxiety. Interventions such as counseling and resource linkage are recommended to provide emotional support.
This finding corroborates the conclusions of previous studies [13,14], which indicated that structured daily living education effectively improves patients’ quality of life. This improvement is attributed to higher adherence to the diet and daily living management domains of self-care performance, which is linked to an enhanced quality of life. In particular, the daily living management items included in this study (basic activities such as washing one’s face, brushing teeth, eating, regular routine management, and hygiene management) reflect self-care performance abilities appropriate to individual functional levels, which can be interpreted as indicating that enhanced autonomy led to improved quality of life. Moreover, the findings on self-care performance in the dietary domain are consistent with prior research [21], suggesting that effective dietary management exerts an indirect influence on symptom alleviation and functional maintenance in individuals with PD. Dietary interventions are known to indirectly contribute to improved quality of life by enhancing drug absorption rates, improving intestinal function, alleviating constipation, and improving nutritional status [21]. In light of these findings, nurses are encouraged to devise personalized daily living and dietary management educational programs, meticulously customized to align with each patient’s unique symptom profile. Additionally, the implementation of a structured feedback mechanism is recommended to assist patients in enhancing their autonomy in self-care.
The quality of life declined when the primary caregiver was the spouse. The impact of PD is predominantly observed among individuals aged 60 and above [1]. Given that the primary caregiver is frequently the spouse, who is also advanced in age, challenges in providing care may emerge. This can lead to a decline in the quality of life for patients due to the limitations of care provided by elderly caregivers [21]. While this highlights the need for support systems within the community, it also suggests the necessity for different policy approaches to care related to aging. In the United States, the Parkinson’s Foundation offers online and in-person self-help groups and educational seminars for caregivers, with the objective of reducing the burden of caregiving [9]. Moreover, national and state-level caregiver support programs systematically provide short-term care services together, ensuring caregivers receive respite time [22]. However, although PD is designated as a special case of intractable disease in South Korea, providing institutional support such as a 10% reduction in patient copayment rates, costs like nursing care expenses are not covered, resulting in a significant financial burden [22]. While home-visit care services are provided through the Long-Term Care Insurance for the Elderly, access to these services remains insufficient for elderly spouses providing care [23]. Therefore, a comprehensive support system comprising expanded special benefits for the elderly, quantitative and qualitative expansion of home care services, and caregiver education and self-help groups should be established at the national policy level.
It has been known that PD typically takes an average of 2.75 years from the onset of symptoms to diagnosis [24]. While some patients receive a diagnosis within 1 year of symptom onset, others may require over a year. This delay is attributed to the diverse presentation of PD symptoms, complicating early disease recognition [24]. These findings support prior research [18] indicating that timely initiation of dopamine agonist therapy delays symptom progression during long-term management, thereby emphasizing the necessity of screening systems in primary care settings and communities. Currently, there is an absence of an officially administered simplified screening test specifically for PD in South Korea, and no active official campaigns are underway. Therefore, a substantial and diverse approach is essential. First, there is a need to enhance the ability of patients and their families to recognize symptoms through educational and disease awareness campaigns targeting the general public regarding non-motor symptoms and early signs of abnormal movement. Second, as overseas pilot programs utilize self-screening instruments for PD, such as the Baylor Functional Assessment Scale (BFAS) [25] and screening systems employing voice analysis-based mobile applications [26], it is imperative to establish a framework that enables the early detection of suspected symptom groups, primarily through community-based centers like public health centers. Finally, in the long term, the implementation of an integrated management system is imperative, as evidenced by the necessity of a national PD registry [27] to facilitate the early detection, monitoring, and intervention of patient populations.
Considering these findings, the following recommendations are put forward for the enhancement of nursing management and services.
Symptom cluster-based standard nursing assessment-planning-evaluation is required. A combined approach involving the MDS-UPDRS (Parts 1 and 2) and quality-of-life tools during the pre-admission and pre-hospitalization phases facilitates the early identification of high-risk groups (patients with high scores in the exercise, emotional/affective regulation cluster). This approach enables the simultaneous implementation of rehabilitation, fall prevention, pain management, and emotional symptom management [13,14,28]. The implementation of protocols that emphasize self-care, with a focus on dietary and daily management, is crucial. Additionally, the standardization of family-participatory education and coaching is indispensable to enhance the sustainability of self-care [8,11].
Furthermore, the establishment of a multidisciplinary integrated care pathway linking public health centers, long-term care facilities, medical institutions, and specialized nurses is necessary to provide patients with rehabilitation, nutrition, and digital management services, while concurrently supporting caregivers with burnout prevention, emotional support, and respite care [9,29]. At the national level, service accessibility should be improved through the introduction of early diagnosis infrastructure (e.g., BFAS, voice analysis) and the expansion of registration systems [25-27], in conjunction with realistic special billing provisions and adjustments to the coverage scope of long-term care insurance to facilitate caregiving and short-term care [22,23].
CONCLUSIONThis study is a descriptive survey designed to identify symptom clusters in individuals with PD and to analyze the relationships among family support, self-care performance, symptom clusters, and quality of life to determine the key factors affecting quality of life. The findings of this study revealed that self-care performance and symptom clusters significantly impact the quality of life in individuals with PD. Based on these results, it is intended to propose tailored nursing interventions and future research strategies.
First, to standardize symptom cluster-based assessment in clinical nursing practice, the electronic health record for initial nursing assessment should incorporate a symptom cluster-based screening checklist. This enables the provision of tailored nursing care, particularly upon confirmation of increased severity in the exercise domain and the emotional/affective regulation cluster.
Second, community-based assessment programs should be implemented to enhance performance in the diet and daily living management domains of self-care performance. In particular, regular self-care ability assessments coupled with tailored feedback linked to systems such as long-term care insurance can strengthen patients’ self-care abilities, supporting them in setting their own management goals.
Third, the community should support the establishment of networks to provide multi-generational caregiver education, burnout management for elderly caregivers, and tailored disease management education to alleviate the burden on spouses. In conclusion, it is crucial to implement self-screening tools focused on public health centers or digital-based early screening systems to facilitate the early detection of PD. Furthermore, these measures should be accompanied by the intensification of awareness campaigns that emphasize the recognition of early symptoms and the disease itself.
Due to the convenience sampling conducted at a single institution and the self-reported survey methodology, the results of this study had limitations in generalizability. Future studies need to expand these findings through multicenter research involving various healthcare institutions and communities.
NOTESAuthors' contribution
Conceptualization - JP and CC; Data curation - JP; Formal analysis - JP and CC; Writing–original draft - JP and CC; Writing–review & editing - JP and CC
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Table 1.General Characteristics and Differences in QoL in Patients With PD (N=132)
Table 2.Factors Analysis of Symptoms (N=132) Table 3.Symptom Clusters (N=132) Table 4.Correlations Among QoL and Study Variables (N=132)
Table 5.Hierarchical Regression Analysis of Factors Influencing Quality of Life (N=132) |
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