Jo, Hwang, and Ryu: Relationship between Uncertainty and Health-related Quality of Life in Patients with Implantable Cardioverter-Defibrillators: Mediating Effect of Self-care Competence
Abstract
Purpose
This descriptive survey examined the mediating effect of self-care competence on the relationship between uncertainty and health-related quality of life (HRQoL) in patients with implantable cardioverter-defibrillators (ICDs).
Methods
Data were collected from 108 patients with ICDs who were receiving outpatient treatment at a tertiary hospital in J, Korea. Data were analyzed using SPSS/WIN 25.0 with descriptive statistics, the independent t-test, one-way analysis of variance, Pearson's correlation coefficient, and Hayes’ PROCESS macro Model 4 with 95% bias-corrected bootstrap confidence intervals.
Results
Uncertainty had a significant negative effect on physical HRQoL (β=-9.74, p=.014), whereas self-care competence had a significant positive effect on physical HRQoL (β =5.46, p=.004); the model explained 46% of the variance. The indirect effect of uncertainty on physical HRQoL through self-care competence was significant (indirect effect=-3.26, 95% bootstrap CI: -8.81 to -0.16). Uncertainty also had a significant negative effect on mental HRQoL (β=-15.17, p<.001), whereas self-care competence had a significant positive effect on mental HRQoL (β=5.80, p=.004); the model explained 39% of the variance. The indirect effect of uncertainty on mental HRQoL through self-care competence was significant (indirect effect=-4.52, 95% bootstrap CI: -10.08 to -0.14).
Conclusion
Nursing interventions that strengthen self-care competence for continuous self-management are needed to reduce uncertainty and improve quality of life in patients with ICDs.
Key words: Defibrillators, Patients, Quality of life, Self-care, Uncertainty
INTRODUCTION
An implantable cardioverter defibrillator (ICD) is a prophylactic treatment for patients with ventricular fibrillation, ventricular tachycardia secondary to structural heart disease, who are at high risk of sudden cardiac death because medication alone is inadequate to prevent it, and for patients who have been resuscitated from or are at high risk of sudden cardiac death (SCD) [ 1].
Sudden cardiac death is when a person who is normally asymptomatic develops symptoms of heart disease and dies suddenly within one hour [ 2]. The most common cause of sudden cardiac death is cardiac arrest, which is 90% due to various arrhythmias, including myocardial infarction, and 10% due to malfunctioning of the heart pump [ 2]. As a treatment to prevent these sudden deaths, implantable cardioverter defibrillator is a non-drug treatment that can save the patient's life by detecting dangerous arrhythmia and delivering an electric shock when it occurs, and patients at high risk of cardiac arrest are targeted for such treatment [ 3].
Health-related quality of life (HRQoL) focuses on aspects directly related to health. The World Health Organization (WHO) defined health as "not merely the absence of disease but a state of complete physical, mental, and social well-being" [ 4]. Health-related quality of life (HRQoL) is a concept that focuses on the impact of health, disease, disability, and impairment on an individual's quality of life and emphasizes the individual's subjective experience [ 5].
Although implantable defibrillators can reduce mortality by preventing sudden cardiac death, they can have physical, psychological, and social impacts on the recipient, as permanent implantation of the device requires adaptation to a new way of life and ongoing care [ 6]. In particular, recipients experience various physical discomforts and negative psychological states such as depression, anxiety, and decreased health-related quality of life [ 7], which can lead to decreased physical functioning, decreased hospital utilization, and increased risk of mortality [ 7].
Defibrillator implantation patients experience discomfort with sleep disturbances, weakness [ 8], fatigue, and dizziness [ 9] and vague symptoms such as pain at the implant site, foreign body sensation, palpitations, and chest discomfort, which negatively impact their activities [ 10]. Similarly, defibrillator implantation patients experience arrhythmia symptoms, pain, complications, electric shocks, fear of death, worry about the defibrillator itself, and vague fears about the future [ 10]. These negative experiences are associated with uncertainty [ 9], and negative psychological states, such as fear of electric shocks and midrange sounds, contribute to a decreased quality of life for AED patients [ 10, 11].
Uncertainty is a variable that affects recovery from illness and refers to a cognitive state in which an individual lacks cues and is unable to assign meaning to or interpret an illness in a way that accurately predicts outcomes, which can negatively impact a patient's HRQoL and recovery from illness [ 12]. In addition, uncertainty can lead to assessments of risk rather than opportunity, resulting in negative emotions such as anxiety, depression, anger, and fear [ 13], which can also negatively impact HRQoL [ 14]. The uncertainty associated with living with an ICD leads to psychosocial adjustment problems [ 15] and reduced HRQoL [ 16].
Psychological distress and decreased HRQoL are associated with adverse outcomes such as increased rates of sustained fatal arrhythmias and increased risk of sudden cardiac death [ 8]. Therefore, ICD implant patients must accept the life change of living with an implanted device for the rest of their lives, and the process of adapting to the device and accepting it as part of their lives is necessary [ 7]. Therefore, based on the uncertainty of the disease, self-care competencies that enable patients with implantable cardioverter-defibrillators to evaluate the uncertainty as an opportunity rather than a crisis, to reduce the uncertainty, to help them adapt to the changed life, and ultimately to improve their HRQoL, with active support from family, friends, and medical staff, are important.
Self-care is the activity and performance of one's life and functioning in a healthy manner, and humans are capable of self-care, and self-care competence is an integral acquired ability of an individual that is developed through a learning process based on intellectual curiosity, education and guidance from others, and experience in performing self-care [ 17]. Therefore, self-care competence to understand and manage one's illness is an important variable to reduce uncertainty about the prognosis of patients with implantable cardioverter-defibrillators. Mishel [ 10] found that the best way to reduce uncertainty is through information provision and that adaptation occurs through self-care such as emotion management, cognitive support, and direct action.
Fillion's [ 18] study found that empowering defibrillator implantation patients with self-management skills through continuity of information, continuity of care, continuity of relationships, and active management can reduce uncertainty and improve HRQoL through the crisis-to-opportunity process [ 12] as a coping mechanism.
Self-care competence is an even more critical issue for chronic disease patients who must live with their illness for life, managing and controlling it. Research targeting chronic disease patients is also being conducted domestically. Between uncertainty and HRQoL, self-care competence was reported as a complete mediating variable, indicating its importance when aiming to improve HRQoL in uncertain situations [ 19]. Studies involving hemodialysis patients [ 20] and stroke patients [ 19] showed that higher self-care competence improved HRQoL within the uncertainty-quality of life relationship. Conversely, both hemodialysis [ 20] and stroke [ 19] patient studies found that higher uncertainty levels correlated with lower HRQoL. The HRQoL measurement tool used in the hemodialysis patient study was the same as the one used in this study. This result indicates that self-care competence, as a mediating variable to reduce uncertainty in chronic disease patients, can influence HRQoL. Significant factors affecting quality of life in patients with ICDs included gender, age, underlying disease, ejection fraction (EF), and whether an electrical shock had been delivered [ 21, 22].
However, no studies have validated the mediating effect of self-care competence on the relationship between uncertainty and HRQoL in patients with ICDs, and only fragmentary causal relationships have been identified, such as factors affecting HRQoL in patients with ICDs [ 23]. Therefore, improving the HRQoL of implantable cardioverter-defibrillator patients can reduce the incidence of ventricular arrhythmias and subsequent mortality [ 24, 25].
Therefore, this study aimed to identify the relationship between uncertainty, self-care competence, and HRQoL, and to identify the mediating effect of self-care competence on the relationship between uncertainty and HRQoL to provide a basis for establishing a systematic support system to promote the HRQoL of implantable cardioverter-defibrillator patients. The purpose of this study is to determine the extent of uncertainty, self-care competence, and HRQoL in patients with implantable cardioverter defibrillators and to examine the mediating effect of self-care competence on the relationship between uncertainty and HRQoL.
METHODS
1. Study Design
This descriptive study investigated the mediating effect of self-care competence on the relationship between uncertainty and HRQoL in patients with ICDs.
2. Sample and Setting
We enrolled individuals who received outpatient treatment after ICD implantation at a hospital in Jeonju. Inclusion criteria were: 1) Participants must be adults aged 19 years or older. 2) Participants must have an implantable cardioverter-defibrillator. 3) Participants must have no history of diagnosis by a psychiatrist for conditions such as anxiety or depression. 4) Participants must understand the purpose of the study and be able to communicate effectively. 5) Participants must have voluntarily agreed to participate in the study. Exclusion criteria were: 1) Individuals with a history of psychiatric disorders were excluded. 2) Individuals taking psychiatric medications such as sleeping pills or anti-anxiety drugs were excluded.
The number of study participants was calculated using the G*Power 3.1 software to determine the sample size required for multiple regression analysis [ 14]. We referred to previous studies on uncertainty and HRQoL among patients with ICDs [ 6, 10, 11, 15, 21, 22, 23]. Using an effect size of .15, a significance level (⍺) of .05, and a power (1-β) of .80, with seven predictor variables, the sample size was calculated to be 103 participants. Considering a dropout rate of 14%, a total of 120 participants were enrolled in the study. Excluding 12 incomplete questionnaires, 108 valid responses were selected as the final study sample.
1) Uncertainty
We used the revised tool by Chung, Kim, Rhee, and Do (2005) [ 24] based on the Mishel Uncertainty in Illness Scale (Mishel, 1988) [ 12]. The tool consists of four subdomains: seven items on inconsistency between diagnosis and disease severity, 13 items on ambiguity about the disease, seven items on complexity regarding the nursing system and treatment, and five items on the unpredictability of disease and prognosis. This tool comprises four sub-di-mensions—ambiguity, complexity, inconsistency, and un-predictability—and is structured on a 5-point scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). The scores for the 12 positive-form items are converted to a reverse scale, resulting in a total score ranging from a minimum of 33 to a maximum of 165 points; a higher score indicates a higher level of uncertainty. The original tool had a reliability Cronbach's ⍺ of .91 to .93; Chung et al.(2005) [ 22] obtained .85, whereas our study obtained .80.
2) Self-care competence
The Self-As-Carer Inventory developed by Geden and Taylor (1988) [ 25] and translated by So (1992) [ 26] was used. This tool comprises 34 items and the subdomains comprise cognitive aspects, physical skills, decision-making and judgment processes, information-seeking behavior, self-regulation awareness, and self-management attention. Each item is rated on a 6-point Likert scale from 1 (not at all) to 6 (strongly agree) points, with a minimum of 34 points and a maximum of 204 points. Geden and Taylor (1988) [ 25] obtained a Cronbach's ⍺ of .96, whereas our study obtained .90.
3) Health-related quality of life (HRQoL)
The Medical Outcomes Study Short Form-12 (MOS SF-12) developed by Ware and Sherbourne (Ware & Sherbourne, 1992) [ 27], validated in Korean form by Quality Metric Incorporated (OPTUM), was used. MOS SF-12 is an abbreviated version of the SF-36, consisting of 12 items across 8 subscales. Among these, the Physical Component Score (PCS) consists of 4 domains and 6 items: Physical Function (PF) with 2 items, Role Physical (RP) with 2 items, Body Pain (BP) with 1 item, and General Health (GH) with 1 item. The Mental Component Score (MCS) consists of 4 domains and 6 items. These are Mental Health (MH) with 2 items, Role Emotional (RE) with 2 items, Social Function (SF) with 1 item, and Vitality (VT) with 1 item. The response scale varies from 3 to 5 items per question, with scores ranging from a minimum of 0 to a maximum of 100 points. A higher total score indicates higher HRQoL. Compared with the long-form SF-36, the SF-12 shows more than 90% concordance. Scores range from 0 to 100, with higher scores indicating better HRQoL. Cronbach's ⍺ was .67 for physical HRQoL and .70 for mental HRQoL for the original tool, and .62 and .65, respectively, in our study.
4) General characteristics
General characteristics of the participants included sex, age, marital status, education level, occupation, diabetes, cerebrovascular disease, electric shock experience, ejection fraction (EF) (%), cause of heart disease, New York Heart Association (NYHA) class, ICD type, and period after insertion of defibrillator (months) [ 23].
3. Data Collection
The study data were collected at the Outpatient Cardiology Department of a University Hospital from November 20, 2021, to April 30, 2022. Data collection was conducted in the outpatient consultation room of the cardiology department; the questionnaires, distributed by the researchers, were filled by the participants individually. Questionnaires were filled approximately within 15 min, and a predetermined small gift was given to the study participants.
4. Ethical Considerations
This study was conducted according to The Code of Ethics of the World Medical Association (Declaration of Helsinki) for experiments involving humans. This study was approved by the Institute for Bioethics Policy (No: CUH 2021-08-017-002). In accordance with ethical requirements, the researcher explained the purpose and methods of the study directly to the participant. The researcher explained to the participants that they can refuse to participate at any time after voluntarily agreeing to participate in the study and that they will not be penalized for refusing. The researcher explained to the participants that the data collected will not be used for any purpose other than the research and that anonymity and confidentiality will be guaranteed. Participants were informed that the research questionnaires will be kept for three years and then destroyed
5. Data Analysis
Data analysis was performed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA). General participant characteristics were analyzed using descriptive statistics. The parameters of uncertainty, self-care competence, and HRQoL were summarized using mean and standard deviation. Differences in uncertainty, self-care competence, and HRQoL according to the general and clinical characteristics of the participants were analyzed using independent samples t-test and one-way analysis of variance (ANOVA) with Scheffé's method for post-hoc analyses. Correlations among uncertainty parameters, self-care competence, and HRQoL were calculated using Pearson's correlation coefficient. To confirm the mediating effect of self-care competence in the relationship between the participant's uncertainty and HRQoL, the SPSS PROCESS macro 3.5 program was used to perform an analysis with a medical history mediation model applying model 4 and identify the statistical significance of the indirect effect. To this end, statistical analysis was performed by bias-adjusted bootstrapping 10,000 times with a 95% confidence interval (CI).
RESULTS
1. General and Clinical Characteristics of the Participants
This study finally included a total of 108 participants, with the proportion of men (n=85, 78.7%) being higher than that of women (n=23, 21.3%). The majority of the participants were in the 40∼59 years age group (n=52, 48.1%). 97 participants (89.8%) were married, whereas 11 (10.2%) were unmarried. In total, 43 participants (39.8%) had a high school diploma and 34 (31.5%) had a college degree or higher. More participants were employed than not 70 (64.8%) vs. 38 (35.2%). Most participants did not have diabetes mellitus (n=91, 84.3%) or cerebrovascular disease (n=97, 89.8%). An equal number of participants (n=54, 50.0%) reported experiencing electric shocks as those who did not. The EF (%) averaged 49. Idiopathic ventricular tachycardia (VT)/ventricular fibrillation (VF) was the most common cardiac cause with 52 (48.1%) diagnoses. 83 patients (76.9%) were categorized as NYHA class 1. Regarding ICD type, single-chamber devices were the most frequently used (61 patients, 56.5%), and the period after defibrillator implantation was ≤60 months in 61 patients (56.5%) ( Table 1).
Table 1.
Demographic and Clinical Characteristics in Relation to Uncertainty, Self-care Competence, and Health-related Quality of Life in Patients with ICD (N=108)
|
Characteristics |
Categories |
n (%) or M±SD |
Uncertainty |
Self-care competence |
HRQoL (PCS) |
HRQoL (MCS) |
|
M± SD |
t or F (p) Scheffe) |
M± SD ́ |
t or F (p) Sc he ffe ́ |
M± SD |
t or F (p) Scheffé |
M± SD |
t or F (p) Scheffé |
|
Gender |
Men |
85 (78.7) |
2.82±0.34 |
-1.43 |
4.34±0.74 |
1.47 |
60.86±15.85 |
1.62 |
57.40±15.97 |
1.05 |
|
Women |
23 (21.3) |
2.92±0.29 |
(.161) |
4.13±0.56 |
(.147) |
55.25±14.00 |
(.114) |
54.35±11.27 |
(.301) |
|
Age (year) |
20∼39 |
9 (8.3) |
2.78±0.35 |
0.60 |
4.31±0.29 |
0.01 |
66.20±12.40 |
1.83 |
54.17±18.87 |
0.52 |
|
40∼59 |
52 (48.1) |
2.82±0.26 |
|
4.29±0.78 |
|
60.96±14.88 |
|
58.25±12.80 |
|
|
≥60 |
47 (43.5) 56.62±12.59 |
2.88±0.40 |
(.552) |
4.29±0.78 |
(.995) |
56.74±16.54 |
(.165) |
55.59±17.32 |
(.593) |
|
Marital status |
Married |
97 (89.8) |
2.82±0.28 |
-1.07 |
4.35±0.65 |
1.91 |
59.45±15.54 |
-0.22 |
57.43±14.21 |
1.01 |
|
Unmarried |
11 (10.2) |
3.02±0.59 |
(.310) |
3.75±1.02 |
(.082) |
60.61±16.70 |
(.830) |
50.76±21.39 |
(.334) |
|
Education |
≤ Elementarya
|
14 (13.0) |
2.88±0.28 |
0.51 |
3.76±0.79 |
4.49 |
54.17±16.91 |
0.67 |
55.66±14.67 |
0.36 |
|
Middle schoolb
|
17 (15.7) |
2.92±0.33 |
(.676) |
4.10±0.57 |
(.005) |
59.31±15.28 |
(.571) |
53.92±17.08 |
(.780) |
|
High schoolc
|
43 (39.8) |
2.83±0.38 |
|
4.46±0.71 |
a< c, d |
60.47±14.90 |
|
56.88±16.29 |
|
|
≥ Colleged
|
34 (31.5) |
2.81±0.29 |
|
4.40±0.63 |
|
60.78±16.26 |
|
58.46±12.95 |
|
|
Occupational status |
Employed |
70 (64.8) |
2.83±0.36 |
-0.70 |
4.44±0.70 |
3.15 |
62.92±13.78 |
2.97 |
59.05±14.79 |
2.18 |
|
Not employed |
38 (35.2) |
2.87±0.28 |
(.484) |
4.02±0.65 |
(.002) |
53.40±16.97 |
(.004) |
53.52±14.93 |
(.033) |
|
Diabetes mellitus |
Yes |
17 (15.7) |
2.98±0.54 |
1.17 |
3.83±1.04 |
-2.08 |
48.77±19.86 |
-2.55 |
50.49±22.86 |
-1.30 |
|
No |
91 (84.3) |
2.82±0.27 |
(.257) |
4.38±0.60 |
(.052) |
61.58±13.87 |
(.020) |
57.92±13.01 |
(.210) |
|
Cerebrovascular disease |
Yes |
11 (10.2) |
2.96±0.39 |
1.10 |
4.02±0.73 |
-1.32 |
43.94±16.50 |
-3.35 |
50.00±17.68 |
-1.36 |
|
No |
97 (89.8) |
2.83±0.32 |
(.294) |
4.32±0.71 |
(.212) |
61.34±14.53 |
(.006) |
57.52±14.69 |
(.200) |
|
Electrical shock experience |
Yes |
54 (50.0) |
2.77±0.30 |
-2.23 |
4.37±0.68 |
1.20 |
61.96±14.77 |
1.61 |
58.72±14.23 |
1.36 |
|
No |
54 (50.0) |
2.91±0.34 |
(.028) |
4.21±0.73 |
(.231) |
57.18±16.14 |
(.111) |
54.78±15.81 |
(.177) |
|
EF (%) |
<40a
|
23 (21.3) |
2.97±0.35 |
|
4.23±0.41 |
1.20 |
52.90±14.57 |
5.16 |
53.51±15.51 |
1.50 |
|
40∼<50b
|
22 (20.4) |
2.94±0.43 |
4.59 |
4.06±0.83 |
(.141) |
55.49±17.89 |
(.007) |
53.60±19.21 |
(.229) |
|
≥50c
|
63 (58.3) |
2.77±0.26 |
(.012) |
4.40±0.65 |
|
63.43±14.07 |
a< c |
58.86±13.12 |
|
|
49±12.26 |
|
|
|
|
|
|
|
|
|
Causes of heart disease |
Idiopathic VT/VF |
52 (48.1) |
2.86±0.39 |
0.98 |
4.28±0.79 |
0.86 |
56.33±16.49 |
1.47 |
54.97±16.40 |
0.63 |
|
Heart Failure |
15 (13.9) |
2.97±0.30 |
(.432) |
4.03±0.61 |
(.510) |
60.28±12.49 |
(.207) |
55.56±15.40 |
(.680) |
|
Long QT syndrome |
14 (13.0) |
2.78±0.34 |
|
4.53±0.66 |
|
67.56±11.58 |
|
59.23±15.78 |
|
|
Brugada syndrome |
9 (8.3) |
2.72±0.14 |
|
4.47±0.38 |
|
65.28±6.59 |
|
63.43±9.94 |
|
|
Post-myocardial infarction ventricular arrhythmia |
12 (11.1) |
2.80±0.17 |
|
4.22±0.76 |
|
59.03±20.63 |
|
58.68±11.85 |
|
|
ARVD |
6 (5.6) |
2.76±0.19 |
|
4.34±0.63 |
|
59.72±16.80 |
|
55.56±14.60 |
|
|
NYHA class |
I |
83 (76.9) |
2.82±0.35 |
-1.35 |
4.40±0.68 |
3.13 |
63.05±13.79 |
4.28 |
58.69±14.68 |
2.46 |
|
II |
25 (23.1) |
2.91±0.26 |
(.183) |
3.92±0.67 |
(.003) |
48.00±15.87 |
(<.001) |
50.33±14.98 |
(.019) |
|
ICD type |
Single-chambera
|
61 (56.5) |
2.86±0.40 |
0.15 |
4.25±0.72 |
1.90 |
57.58±16.29 |
3.83 |
53.76±14.59 |
3.41 |
|
Double-chamberb
|
40 (37.0) |
2.82±0.21 |
(.857) |
4.43±0.61 |
(.155) |
64.27±13.11 |
(.025) |
61.56±14.69 |
(.037) |
|
CRT-Dc
|
7 (6.5) |
2.87±0.30 |
|
3.91±1.02 |
|
50.00±16.32 |
c< b |
55.36±16.96 |
|
|
Period after defibrillator implantation (month) |
≤60a
|
61 (56.5) |
2.90±0.36 |
3.14 |
4.28±0.71 |
0.01 |
59.36±15.92 |
0.32 |
55.67±17.10 |
0.84 |
|
61∼120b
|
32 (29.6) |
2.82±0.29 |
(.047) |
4.30±0.68 |
(.899) |
61.07±12.59 |
(.727) |
59.64±9.73 |
(.435) |
|
≥121c
|
15 (13.9) |
2.67±0.22 |
c< a |
4.32±0.81 |
|
57.22±20.20 |
|
55.00±15.92 |
|
2. Differences in Uncertainty, Self-care Competence, and HRQoL According to General and Clinical Characteristics
Participants’ general and clinical characteristics that showed significant differences with uncertainty were the experience of electric shocks, EF and the period after defibrillator implantation. Shock experience (t=-2.23, p=.028), EF (t=4.59, p=.012) was significantly different in terms of uncertainty. Time since defibrillation (months) showed a significant difference in uncertainty (F=3.14, p=.047), with post-hoc analysis showed a higher uncertainty in patients with a post-implantation period of ≤60 months than in those with ≥121 months. Differences in self-care competence were observed according to education level, occupational status, and NYHA class. The education level (F=4.49, p=.005), occupational status (t=3.15, p=.002) showed a significant difference in self-care competence. The post-hoc analysis demonstrated that self-care competence was higher in high school and university graduates than in elementary school graduates. Patients with NYHA class I had a significantly higher level of self-care competence than did those with NYHA class II (t=3.13, p=.003).
Variables that showed differences with physical HRQoL were occupational status, diabetes mellitus, cerebrovascular disease, EF, NYHA class, and ICD type. Significant differences were found for occupational status (t=2.97, p=.004), diabetes mellitus (t=-2.55, p=.020), cerebrovascular disease (t=-3.35, p=.006), NYHA class (t=4.28, p<.001). EF (F=5.16, p=.007) also showed a significant difference, and according to the post-hoc analysis, the physical HRQoL score was significantly higher in patients with over 50 than below 40. ICD type (F=3.83, p =.025) also showed a significant difference, and according to the post-hoc analysis, the physical HRQoL score was significantly higher in patients with Double-chamber ICD than CRT-D.
Likewise, Variables that showed differences with mental HRQoL were occupational status (t=2.18, p=.033), NYHA class (t=2.46, p=.019), and ICD type (F=3.41, p=.037) showed significant differences in mental HRQoL ( Table 1).
3. Uncertainty, Self-Care Competence, and HRQoL
Among the study participants, the average degree of uncertainty was 2.84±0.33 (out of 5 points), and the degree of self-care competence was 4.29±0.71 (out of 6 points). Furthermore, the average physical and mental HRQoL scores were 59.57±15.58 and 56.75±15.10, respectively (out of 100 points) ( Table 2).
Table 2.
Descriptive Statistics for Uncertainty, Self-care Competence, and Health-related Quality of Life in Patients with ICDs (N=108)
|
Variables |
M±SD |
Minimum |
Maximum |
Range |
|
Uncertainty |
2.84±0.33 |
2.03 |
4.61 |
1∼5 |
|
Self-care competence |
4.29±0.71 |
1.68 |
5.91 |
1∼6 |
|
HRQoL (PCS) |
59.57±15.58 |
16.67 |
83.33 |
0∼100 |
|
HRQoL (MCS) |
56.75±15.10 |
4.17 |
91.67 |
0∼100 |
4. Correlations among Uncertainty, Self-Care Competence, and HRQoL
Based on correlation analyses, uncertainty had a significant negative correlation with self-care competence (r= -.39, p<.001), physical HRQoL (r=-.38, p<.001), and mental HRQoL (r=-.47, p<.001). Contrarily, the correlation of self-care competence with physical HRQoL (r=.50, p<.001) and mental HRQoL (r=.48, p<.001) was significantly positive. Likewise, physical HRQoL and mental HRQoL showed a significant positive correlation (r=.63, p<.001) ( Table 3).
Table 3.
Correlations among Uncertainty, Self-care Competence, and Health-related Quality of Life (N=108)
|
Variables |
Uncertainty |
Self-care competence |
HRQoL (PCS) |
|
r (p) |
r (p) |
r (p) |
|
Uncertainty |
1 |
|
|
|
Self-care competence |
-.39 (<.001) |
1 |
|
|
HRQoL (PCS) |
-.38 (<.001) |
.50 (<.001) |
1 |
|
HRQoL (MCS) |
-.47 (<.001) |
.48 (<.001) |
.63 (<.001) |
5. Mediating Effect of Self-Care Competence on the Relationship between Uncertainty and HRQoL
We examined during the regression analysis conducted to verify the mediating effect of self-care competence on the relationship between patient uncertainty and HRQoL. We were controlling for occupation, diabetes, cerebrovascular disease, NYAH, and ICD type, which were found to have significant effects on physical HRQoL. We were controlling for occupation, NYAH, and ICD type, which were found to have significant effects on mental HRQoL.
As a result of checking multicollinearity, the tolerance limits of physical HRQoL were 0.19∼0.84, and the tolerance limits of mental HRQoL were 0.20∼0.90, all above 0.1, and the variance expansion index of physical HRQoL was 1.18∼5.73, and the variance expansion index of mental HRQoL was 1.12∼5.07, all below 10, so there was no problem of multicollinearity. Normality was checked through the p-p plot, and the points were close to the 45-degree straight line, showing a normal distribution of the error term. The scatterplot of standardized residuals showed that the residuals were irregularly distributed without any trend, tendency, or periodicity around the mean of 0, confirming the homoscedasticity of the residuals. It was confirmed that there is no autocorrelation between residuals ( Table 4).
Table 4.
Mediating Effects of Self-care Competence in the Relationship between Uncertainty and Health-related Quality of Life in ICDs (N=108)
|
Direct effect |
β |
SE |
t |
p
|
95% CI |
|
LLCI |
ULCI |
|
Uncertainty →Self-care competence |
-0.71 |
0.19 |
-3.80 |
<.001 |
-1.08 |
-0.34 |
|
R=.39, R2=.15, F=18.87, p<001 |
|
Uncertainty →HRQoL (PCS) |
-9.74 |
3.87 |
-2.52 |
.014 |
-17.41 |
-2.08 |
|
Self-care competence→HRQoL (PCS) |
5.46 |
1.94 |
2.92 |
.004 |
1.82 |
9.50 |
|
R=.68, R2=.46, F=8.18 p<001 |
|
Uncertainty →Self-care competence |
-0.75 |
0.18 |
-4.08 |
<.001 |
-1.12 |
-0.39 |
|
R=.39, R2=.15 F=18.87 p<001 |
|
Uncertainty →HRQoL (MCS) |
-15.17 |
3.89 |
-3.90 |
<.001 |
-23.89 |
-7.45 |
|
Self-care competence →HRQoL (MCS) |
5.80 |
1.94 |
3.00 |
.004 |
1.95 |
9.64 |
|
R=.62, R2=.39, F=7.77 p<001 |
1) Mediating effect of self-care competence on the relationship between uncertainty and physical HRQoL
To test the mediating effect of self-care competence in the relationship between uncertainty and physical HRQoL in patients with ICDs, an analysis was conducted using a mediation model using PROCESS macro. In the univariate analysis of uncertainty and physical HRQoL, occupation, diabetes, cerebrovascular disease, NYHA class, ICD type, EF and these were adjusted as control factors. Uncertainty was found to have a significant positive effect on self-care competence (β=-.71, p<.001), and the explanatory power was 15%. Uncertainty (β=-9.74, p=.014) and self-care competence (β=5.46, p=.004) showed a direct effect on physical HRQoL, with an explanatory power of 46% ( Table 4, Figure 1). The mediating effect of self-care competence on the relationship between uncertainty and physical HRQoL in patients with ICDs was verified. The results showed that the total effect size between uncertainty and physical HRQoL was -13.68, with a 95% Bootstrap confidence interval (-21.10 to -6.26). The direct effect size was -9.73, with a 95% Bootstrap confidence interval (-17.44 to -2.01). This did not include zero and was statistically significant. The magnitude of the indirect effect on physical HRQoL, mediated by uncertainty and self-care compenece, was -3.26, with a 95% Bootstrap confidence interval of (-8.81 to -0.16). This did not include zero and was statistically significant ( Table 5, Figure 1).
Figure 1.
Mediating effects of self–care competence in the relationship between uncertainty and health-related quality of life.
Table 5.
Verification of Total, Direct, and Individual Indirect Effects Through Bootstrapping (N=108)
|
Variables |
Effect |
SE |
95%CI |
|
Boot LLCI |
Boot ULCI |
|
Total effect |
-13.68 |
3.74 |
-21.10 |
-6.26 |
|
Direct effect: Uncertainty → HRQoL (PCS) |
-9.73 |
3.89 |
-17.44 |
-2.01 |
|
Indirect effect: Uncertainty → Self-care competence→HRQoL (PCS) |
-3.26 |
2.25 |
-8.81 |
-0.16 |
|
Total effect |
-19.76 |
3.79 |
-27.27 |
-12.24 |
|
Direct effect: Uncertainty →HRQoL (MCS) |
-15.24 |
3.96 |
-23.09 |
-7.39 |
|
Indirect effect: Uncertainty →Self-care competence→HRQoL (MCS) |
-4.52 |
2.62 |
-10.08 |
-0.14 |
2) Mediating effect of self-care competence on the relationship between uncertainty and mental HRQoL
To test the mediating effect of self-care competence in the relationship between uncertainty and mental HRQoL in patients with ICDs, an analysis was conducted using a mediation model using PROCESS macro. In the univariate analysis of uncertainty and mental HRQoL, occupation, NYHA class, ICD type and these were adjusted as control factors. The results showed that uncertainty had a significant positive effect on self-care competence (β=-.75, p<.001) with an explanatory power of 15%. Uncertainty (β=-15.17, p<.001) and self-care competence (β=5.80, p= .004) showed a direct effect on mental HRQoL, with an explanatory power of 39% ( Table 4, Figure 1). The mediating effect of self-care competence on the relationship between uncertainty and mental HRQoL in patients with ICDs was verified.
The results showed that the total effect size between uncertainty and mental HRQoL was -19.76, with a 95% Bootstrap confidence interval (-27.27 to -12.24). The direct effect size was -15.24, with a 95% Bootstrap confidence interval (-23.09 to -7.39). This did not include zero and was statistically significant. The magnitude of the indirect effect on mental HRQoL, mediated by uncertainty and self-care competence, was -4.52 with a 95% Bootstrap confidence interval of (-10.08 to -0.14). It did not include zero and was statistically significant ( Table 5, Figure 1).
DISCUSSION
This study was conducted to determine the extent of uncertainty, self-care competence, and HRQoL in patients with ICDs, and to identify the mediating effect of self-care competence on the relationship between uncertainty and HRQoL, and to provide a basis for intervention programs to improve the HRQoL of patients with ICDs.
We found that the mean uncertainty score for ICD patients was 2.84±0.33 out of 5, which is moderate. This is lower than the score of 3.08±0.50 measured with the same tool in the study by Bangchoy (2021) [ 28] for patients with ICDs. This result is likely due to the difference in fear of electric shocks, with 37.4% of the subjects in Bangchoy's study having experienced electric shocks and 50.0% of the subjects in our study having experienced electric shocks. Illness uncertainty is related to ambiguity and unpredictability of disease prognosis, and studies have supported that ICD patients experience illness uncertainty due to the unpredictable nature of symptoms such as arrhythmia symptoms, cardiac arrest experience, and electric shock [ 29]. Therefore, to reduce uncertainty in ICD implant patients, it is necessary to apply nursing interventions in the clinical setting that consider not only physical symptoms but also psychological problems.
The self-care competence scores of ICD patients in this study were 4.29±0.71 out of 6 points, differing from the 3.96±0.07 points reported by Chae et al.[ 20] using the same tool in hemodialysis patients. This difference likely stems from the distinct self-management demands of each condition: hemodialysis patients face complex, ongoing requirements spanning strict dialysis schedules, dietary restrictions, and fluid management across daily life, whereas ICD patients primarily focus on psychological anxiety regarding the risk of electrical shocks, device monitoring, and symptom tracking. Therefore, a simple score comparison is limited due to the differing disease characteristics and may alter the inherent meaning of the self-care competence scores themselves. This difference is thought to arise because the moderating factors influencing self-care competence differ between the two conditions.
The subjects in this study were 43.5% aged 60 or older and 78.7% male, whereas in Chae et al.'s [ 19] study, 52.7% were aged 60 or older and 56.2% were male. This variation is likely due to the diverse moderating factors of self-care competence, such as gender and age [ 18]. Age can significantly influence the performance of self-care competence. Self-care theory posits that self-care competence is closely linked to cognitive capacity, learning ability, and health literacy. Older adults are more likely to experience natural declines in these abilities, which can act as limitations to self-care competence. Furthermore, studies on elderly ICD patient populations have reported anxiety and reduced HRQoL associated with shock events, confirming a correlation between disease understanding and self-care competence [ 30]. Therefore, tailored educational strategies for different age groups are required.
Gender differences are also an important interpretive variable. The high proportion of male participants and high employment rate in this study suggest that differences in self-care attitudes can be interpreted in relation to social role factors. Maintaining employment and a sense of social responsibility can strengthen motivation to engage in self-care competence, which may lead to disease adaptation and health care behaviors. This context should be understood not as a gender generalization but as a variable interacting with social role and economic factors [ 31].
Therefore, it is thought that the self-care competence of ICD patients will be strengthened if the moderating factors to improve self-care competence are identified and customized programs are developed and intervened. According to a study by Grady et al (2014) [ 32], chronic patients such as ICD patients can improve self-care through knowledge of the disease, symptom monitoring, lifestyle changes, medication adherence, and regular hospital visits, so it is necessary to develop intervention programs that take this into account.
In the HRQoL of this study, the physical HRQoL score was 59.57±15.58 and the mental HRQoL score was 56.75 ±15.10. In a previous study of ICD implantation patients (Bang, 2021) [ 28] was physical HRQoL score 58.93±17.0 and the mental HRQoL score of 59.82±18.74. In this study, physical HRQoL scores were higher than mental HRQoL scores, whereas in Bang's (2021) [ 28] study, physical HRQoL was slightly lower than mental HRQoL. This difference may be due to the fact that our study had more NYHA Class I (76.9%) patients than NYHA Class II (23.1%) patients, whereas Bang [ 28] et al. had more Class II (56.4%) patients than NYHA Class I (32.5%) patients.
It is thought that unpredictable electrical shocks and device-related complications (Flemme et al., 2011) [ 33] and negative emotional states (Rosman et al., 2015) [ 34] associated with ICD implantation affect mental HRQoL. Therefore, it is necessary for healthcare providers in clinical settings to improve the quality of life by forming a psychological support system to provide a sense of mental stability in addition to physical symptoms.
The factors that made a significant difference in uncertainty in our study were shock experience and time since defibrillation. This is similar to a previous study [ 11] that found that patients who had never been shocked had higher levels of uncertainty due to the mental challenge of not knowing when they would be shocked. It was suggested that they were expressing uncertainty about death rather than just the event of a shock [ 11]. Therefore, it is thought that ICD patients have high uncertainty because their negative evaluation of their health status leads to anxiety about their prognosis. Therefore, psychological counseling programs that can reduce uncertainty are needed. In addition, in terms of the number of months since ICD implantation that had a significant effect on uncertainty, 60 months or less had significantly higher uncertainty than 121 months. A previous study [ 9] showed that there was no difference between the immediate post-implantation period, 6 months, and 12 months, and Lee [ 35] showed that psychological adjustment was different depending on the order of time at 1 month, 6 months, and 1 year after the procedure, but there is no long-term study after the procedure, so repeated studies are needed to confirm the uncertainty of ICD timing.
The factors that showed significant differences in self-care competence in this study were education, occupational status, and NYAH class. In this study, high school and university graduates had higher self-care competence than elementary school graduates and below. Lee [ 35], who investigated the anxiety and depression levels of patients after implantation of an implantable cardioverter defibrillator (ICD), found that the higher the level of education, the more efficiently they could acquire information about and manage the ICD. In addition, the higher the education level of the subjects, the higher the self-care capability. This suggests that subjects with higher education have a better understanding of the disease, so it is necessary to provide differentiated education programs by education level to improve self-care capabilities.
The finding that those with jobs had higher self-care competence than those without jobs in this study is in the same vein as the finding that those with better economic conditions are better adapted to the treatment process and self-care [ 36], and it is thought that those with jobs make persistent efforts to manage their disease in order to maintain their jobs. NYAH Class I patients had higher self-care competence than NYAH Class II patients. In a study of ICD implantation patients, Yoon [ 37] reported that the higher the NYHA stage, the more severe the experience of symptoms such as severe dizziness, shortness of breath, palpitations, chronic fatigue, and pain. This is likely due to the fact that subjects with NYAH Class 1 did not have severe physical symptoms. Therefore, careful nursing care is needed to identify the NYAH class stage and identify physical symptoms.
In this study, factors showing differences in physical HRQoL were employment status, diabetes, cerebrovascular disease, NYHA class, and ICD type, EF, while factors showing differences in mental HRQoL were employment status, NYHA class, and ICD type. Particularly, having employment was associated with significantly higher physical and mental HRQoL. These results align with previous studies reporting that employed individuals reported higher levels of physical and mental HRQoL [ 6, 37, 38]. However, employment status should be interpreted not merely as an indicator of economic capability, but as a concept encompassing various factors such as maintaining social roles, performing activities of daily living, physical functional level, and social interaction. That is, the very fact of maintaining employment likely reflects a relatively good functional status and level of social participation, and these factors may be associated with improved HRQoL. Meanwhile, ICD recipients require long-term medical management, including device checks, follow-up monitoring, and battery replacement procedures. Some studies report that this ongoing treatment process can act as a psychological burden factor [ 35, 36]. However, since this study did not directly measure economic burden, there are limitations to interpreting the relationship between occupational status and HRQoL as directly linked to medical cost burden. Therefore, future studies need to comprehensively analyze the impact on HRQoL by considering financial factors such as ICD-related medical cost burdens, economic stress, and insurance coverage levels.
In this study, patients with NYHA class I had higher physical and mental HRQoL than patients with class II. In a study by Yoon [ 37] also reported that the lower the NYHA class, the higher the physical and mental HRQoL because of the better daily activity status. These results suggest that the lower the stage of NYAH class, the higher the physical and mental HRQoL because patients experience fewer symptoms and can be more active in daily life. Therefore, it is necessary to repeat the study in a larger group of patients with various NYAH classes in the future.
In the present study, the mean physical HRQoL according to ICD type was statistically significantly higher for Double cavity (64.27 points) than CRT-D (50.00 points). In a study by Yoon [ 37], there was no statistical difference in physical HRQoL scores by ICD type, and in a study of Chinese people [39], the mean physical HRQoL scores by ICD type were 44.72 for single cavity, 42.60 for double cavity, and 42.11 for CRT-D. Therefore, it is necessary to repeat the study to confirm and compare the differences including physical HRQoL scores by ICD type. Based on this study alone, the physical HRQoL score was highest for Double cavity 64.27, but there was no difference in uncertainty and mental HRQoL by ICD type. Therefore, it is necessary to identify the degree and frequency of physical symptoms to improve the physical HRQoL of ICD implantation patients by ICD type and manage symptoms accordingly.
The findings that physical HRQoL was higher in the absence of diabetes and cerebrovascular disease were similar to the findings of Yoon [ 37], who reported higher physical and mental HRQoL in the absence of diseases other than rhythm disorders. It is thought that the absence of underlying medical conditions may have contributed to higher physical and mental HRQoL due to positive effects on self-management in daily life. Based on these results, comprehensive self-management through lifestyle management, psychological support, and information sharing about ICD implantation should be provided after ICD implantation to prevent the development of underlying diseases in ICD implantation patients.
The results of this study showed that the physical and mental HRQoL of the Participants were negatively correlated with uncertainty and positively correlated with self-care competence, and the relationship between uncertainty and self-care competence was negatively correlated, and physical and mental HRQoL were positively correlated. It can be seen that the lower the uncertainty and the higher the self-care competence of ICD implantation patients, the higher the physical and mental HRQoL. This is consistent with the findings of Jo et al. [ 19]. It can be seen that the higher the uncertainty, the lower the HRQoL [ 10, 12], and the higher the self-care competence, the higher the HRQoL [ 23], which is characterized by negative emotions such as arrhythmia symptoms and electric shocks in ICD patients. Therefore, a comprehensive self-management empowerment strategy involving healthcare providers, counselors, and family members is needed to reduce uncertainty and increase self-care competence.
In this study, self-care competence was found to partially mediate the relationship between uncertainty and HRQoL. The study found that uncertainty had a direct negative impact on physical and mental HRQoL, and self-care competence was identified as a key mechanism partially mediating this relationship. This suggests that uncertainty not only directly negatively impacts HRQoL but also indirectly lowers it by diminishing self-care competence. Self-care competence comprises not only knowledge but also complex behavioral elements such as symptom recognition and monitoring ability, decision-making ability, and self-regulation ability. For ICD patients, unpredictable electrical shock experiences and physical changes can be linked to psychological distress, leading to reduced HRQoL. Previous studies have also confirmed that increasing uncertainty leads to a decline in self-care competence [ 30]. This means that uncertainty affects HRQoL through self-care competence, and when uncertainty is low and self-care competence is high, HRQoL is high. This is consistent with the findings of studies that mediated the relationship between uncertainty and HRQoL through self-care competence [ 19, 20]. These results suggest that self-care competence is important for improving HRQoL in uncertain situations such as ICD implant patients’ various symptoms and electric shock experiences.
This suggests that the HRQoL of ICD patients is not solely determined by disease severity or demographic characteristics but can be structurally influenced by cognitive interpretations of the disease situation and self-care competence. Notably, self-care competence demonstrated the potential to function as an adaptive resource capable of buffering the decline in HRQoL during periods of uncertainty. Therefore, nursing care for ICD patients needs to expand beyond a device-management-centered approach to a multidimensional management system integrating uncertainty reduction strategies and interventions to enhance self-care competence. This study is significant in that it simultaneously provides theoretical grounds and practical directions for improving the HRQoL of ICD patients. Therefore, to improve the HRQoL for ICD patients, strategies to enhance self-care using digital tools—such as step-by-step education programs tailored to the disease characteristics, symptom monitoring training, and self-care program should be implemented alongside psychological interventions that simply reduce uncertainty. Such strategies can serve as interventions that strengthen patients’ self-care competence and simultaneously improve both physical and mental HRQoL.
1. Limitation
This study has some limitations with regard to generalizing and interpreting the results. At present, there are no tools specifically developed for populations in special circumstances, such as ICD patients. The MOS SF-12 has been widely used in numerous studies to measure HRQoL; however, previous studies using this tool have reported low reliability. This is likely due to the severity of the condition and the clinical characteristics of ICD patients; therefore, the results of this study should be interpreted with caution. In this cross-sectional study, patients with ICDs from a tertiary medical institution were randomly selected, which may have resulted in bias. Therefore, we propose a study in which research subjects are selected through random sampling from tertiary medical institutions nationwide. As this study examined the uncertainty level, self-care competence, and HRQoL of patients who underwent ICD implantation, it is difficult to compare these variables with their pre-implant levels. This study found no significant difference in HRQoL by age, but since the ages in this study ranged from 20 to 70 years old, and the average age was 56 years old, we recommend future studies to check the HRQoL by age group by dividing them into young, middle, and old age.
2. Application
In the findings of this study, self-care competence is a crucial mediating factor for reducing uncertainty and improving HRQoL for patients living with ICDs. Therefore, it is necessary to identify patients with high levels of uncertainty and apply self-care competence enhancement programs capable of improving their HRQoL. To this end, the development and implementation of self-care competence enhancement programs utilizing non-face-to-face self-management apps, in addition to face-to-face sessions, are required. Furthermore, since patients with ICDs must live their entire lives with psychological anxiety and the uncertainty of facing death if the device ceases to function, it is necessary to develop collaborative self-care competence enhancement programs through the establishment of a psychological support system.
CONCLUSION
The study participants were middle-aged, employed, and had high EF. They were classified as NYHA Class I. While uncertainty, self-care competence, and both physical and mental HRQoL associated with ICD were at moderate levels, mental HRQoL was lower than physical HRQoL. The results of this study showed that self-care competence had a direct effect on both physical and mental HRQoL in the relationship between uncertainty and HRQoL in patients with ICDs. Therefore, self-care competence was identified as a mediating variable that positively influences HRQoL in uncertain situations, indicating that the implementation of self-care competence enhancement programs is crucial for improving participants’ HRQoL. To reduce uncertainty and improve HRQoL, it is necessary to assess the degree of uncertainty and strengthen self-care competence by utilizing self-care competence apps that enable continuous self-care. Additionally, nursing intervention strategies are required to enhance psychological support, including professional counseling to strengthen emotional support systems.
REFERENCES
1. Roh SY, Choi JI, Kim MS, Cho EY, Kim YG, Lee KN, et al. Trends in the use of implantable cardioverter-defibrillators for prevention of sudden cardiac arrest: a South Korean nationwide population-based study. Pacing and Clinical Electrophysiology. 2019;42(8):1086-1094. https://doi.org/10.1111/pace.13741
6. Thylén I. Psychosocial concerns in patients living with an implantable cardioverter defibrillator. In: Dunbar SB, Dougherty CM, Sears SF, editors. Psychological, Emotional, Social and Cognitive Aspects of Implantable Cardiac Devices. Cham: Springer; 2017. p. 47-65.
8. Palese A, Cracina A, Purino M, Urli N, Fabris S, Danielis M. The experiences of patients electrically shocked by an implantable cardioverter defibrillator: findings from a descriptive qualitative study. Nursing in Critical Care. 2020;25(4):229-237. https://doi.org/10.1111/nicc.12424
10. Savastano S, Baldi E, Brondino N. Psychiatric aspects of sudden cardiac arrest and implantable cardioverterdefibrillators. In: Govoni S, Politi P, Vanoli E, editors. Brain and Heart Dynamics. Cham: Springer; 2020. p. 377-385. https://doi.org/10.1007/978-3-319-90305-7_21-1
11. Kamphuis HCM, De Leeuw JRJ, Derksen R, Hauer RNW, Winnubst JAM. Implantable cardioverter defibrillator recipients: quality of life in recipients with and without ICD shock delivery: a prospective study. EP Europace. 2003;5(4):381-389. https://doi.org/10.1016/s1099-5129(03)00078-3
13. In:. In: Smith MJ, Liehr PR, editors. Middle Range Theory for Nursing.. 2nd ed.. New York: Springer Publishing Company; 2008. p. 55-84.
17. Orem DE. Nursing: concepts of practice.. 6th ed.. St. Louis, MO: Mosby; 2001. p. 20-22.
18. Fillion L, Cook S, Veillette AM, Aubin M, de Serres M, Rainville F, et al. Professional navigation framework: elaboration and validation in a Canadian context. Oncology Nursing Forum. 2012;39(1):E58-E69. https://doi.org/10.1188/12.ONF.E58-E69
19. Jo EH, Lee SJ, Jo JH. Mediating effects of self-care competence on the relationship between uncertainty and quality of life in stroke patients. Korean Journal of Adult Nursing. 2021;33(1):56-66. https://doi.org/10.7475/kjan.2021.33.1.56
20. Chae YJ, Ahn JH, Kang KP, Jo E. Mediating Effects of Self-Care Competence on the Relationship between Uncertainty and Quality of Life in Hemodialysis Patients. Korean Journal of Adult Nursing. 2020;32(1):67-77. https://doi.org/10.7475/kjan.2020.32.1.67
21. Hopgood DA, Czosek RJ, Bakas T, Garritano N, Gillespie GL. The Capture Gap: Implantable Cardioverter-Defibrillator Quality of Life. Clinical Nursing Research. 2020;29(2):97-107. https://doi.org/10.1177/1054773818803741
22. Miller JL, Thylén I, Moser DK. Gender disparities in symptoms of anxiety, depression, and quality of life in defibrillator recipients. Pacing and Clinical Electrophysiology. 2016;39(2):149-159. https://doi.org/10.1111/pace.12786
23. Guo X, Tripp C, Huber NL, Hou C, Lv R, Li J, et al. Patient reported outcomes and quality of life in Chinese patients with implantable cardioverter defibrillators. Heart & Lung. 2021;50(1):):153-158. https://doi,org/10.1016/j.hrtlng.2020.05.003
24. Chung CW, Kim MJ, Rhee MH, Do HG. Functional status and psychosocial adjustment in gynecologic cancer patients receiving chemotherapy. Korean Journal of Women Health Nursing. 2005;11(1):58-66. https://doi.org/10.4069/kjwhn.2005.11.1.58
25. Geden E, Taylor S. Self-as-carer: A preliminary evaluation. Paper presented at: Seventh Annual Nursing Research Conference. 1988. Columbia, MO. Columbia, MO: University of Missouri-Columbia School of Nursing; p. 719.
26. So HS. Testing construct validity of self-as-carer inventory and its predictors. The Korean Journal of Adult Nursing. 1992;4(2):147-161.
28. Bang C. The structural model for uncertainty of illness in implantable cardioverter defibrillator patient. [doctoral dissertation]. Seoul: Ewha Womans University; 2021. p. 7-42.
29. Larimer K, Durmus J, Florez E. Experiences of young adults with pacemakers and/or implantable cardioverter defibrillators. Journal of Cardiovascular Nursing. 2016;31(6):517-522. https://doi.org/10.1097/JCN.0000000000000280
30. Jo E, Hwang R, Ryu JL, Yoo C. Developing and evaluating a mobile application self-management program for patients with implantable cardioverter-defibrillators: an experimental study. Computers, Informatics, Nursing. 2026;44(1):e01275.
33. Flemme I, Hallberg U, Johansson I, Strömberg A. Uncertainty is a major concern for patients with implantable cardioverter defibrillators. Heart & Lung. 2011;40(5):420-428. https://doi.org/10.1016/j.hrtlng.2011.02.003
34. Rosman L, Whited A, Lampert R, Mosesso VN, Lawless C, Sears SF. Cardiac anxiety after sudden cardiac arrest: Severity, predictors andclinical implications. International Journal of Cardiology. 2015;181: 73-76. https://doi.org/10.1016/j.ijcard.2014.11.115
35. Lee SM. Adaptation experiences of implantable cardioverter defibrillator (ICD) recipients [master's thesis]. Seoul: Seoul National University; 2015. p. 20-63.
36. Byun JG, Lee JP, Park JY, Kim YM, Lee EH, Chang KH, et al. Factors influencing quality of life of cervical cancer patients in Korea. Obstetrics & Gynecology Science. 2006;49(12):2564-2573.
37. Yoon SY. Symptom experience and quality of life in patients with implantable pacemaker [master's thesis]. Seoul: Yonsei University; 2004. p. 18-39.
38. Malm D, Svensson E, Karlsson JE, Fridlund B. Health-related quality of life in pacemaker patients: a single and multidimensional self-related health comparison study. European Journal of Cardiovascular Nursing. 2003;2(4):291-302. https://doi.org/10.1016/S1474-5151(03)00065-3
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