Abstract
-
Purpose
The aim of this study was to identify the effects of stigma, social support, and resilience on post-traumatic growth in patients with stroke and to provide foundational data for developing nursing interventions that can effectively promote post-traumatic growth in this population.
-
Methods
This cross-sectional study employed a questionnaire-based survey. The participants were 150 patients who attended the neurology outpatient clinic three months after a stroke diagnosis. Data were collected between February and April 2024 using a structured self-report questionnaire. Analyses included descriptive statistics, reliability analysis, inferential statistics(independent t-test, one-way ANOVA, and Scheffé's test), and hierarchical multiple regression using SPSS/WIN 27.0.
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Results
The mean post-traumatic growth score was 2.52±1.05 out of 5. Significant factors affecting post-traumatic growth were age, education, religion, the presence of a housemate, income, time since stroke onset, stroke type, and stroke recurrence. Post-traumatic growth was positively correlated with social support (r=.44, p<.001) and resilience (r=.53, p<.001), but not significantly correlated with stigma. Regression analysis identified resilience (β=.37, p<.001), religion (β=.29, p<.001), and stroke type (β=.23, p=.033) as significant predictors, explaining 44.2% of the variance in post-traumatic growth (F=9.45, p<.001).
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Conclusion
Developing and implementing nursing interventions to increase resilience may be crucial for promoting post-traumatic growth in patients with stroke. Further research is needed to design and evaluate these interventions.
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Key Words: Posttraumatic; Resilience; Social stigma; Social support; Stroke
INTRODUCTION
Statistics indicate that in 2022, stroke accounted for 6.8% of deaths in Korea and ranked fifth after cancer, heart disease, Corona Virus Disease-2019 (COVID-19), and pneumonia [
1]. Furthermore, by 2021 the stroke prevalence rate had increased by 0.8% compared to the previous year [
2], and stroke treatment and management have expanded from an individual focus to a societal concern. Stroke, which contributes significantly to mortality in Korea, is often accompanied by sequelae-such as cognitive impairment, movement disorders, dysphagia, and speech disorders-even in survivors. This underscores the importance of the adaptation process following a stroke diagnosis.
Neurological disorders in stroke patients are recognized as risk factors for negative outcomes [
3] and may sometimes lead to post-traumatic stress disorder [
4]. Conversely, some studies have identified a phenomenon known as post-traumatic growth (PTG), in which individuals experience significant personal development through overcoming traumatic experiences, such as stroke [
5]. Prior research has demonstrated that patients who experience PTG tend to maintain a healthy lifestyle, seek meaning in their existence, persevere through challenging treatment processes, and sustain resilience [
6].
Stroke patients often encounter various forms of stigma, which can significantly affect their psychological well-being and recovery. Stigma refers to the negative social perceptions and attitudes that individuals with stroke may face, leading to feelings of social rejection, criticism, or devaluation [
7]. Three main types of stigma have been identified among stroke patients: social stigma, internalized stigma, and enacted stigma [
7]. Social stigma involves negative stereotypes and discrimination based on visible disabilities or perceived cognitive impairments. Internalized stigma occurs when stroke survivors adopt these negative societal views, resulting in feelings of shame and low self-esteem. Enacted stigma refers to direct experiences of discrimination or exclusion in social or healthcare settings. Although previous research has examined the contribution of social and internalized stigma to negative psychological outcomes in stroke patients [
3], less attention has been given to their potential influence on positive psychological changes, particularly PTG. While higher levels of stigma correlate with increased post-traumatic stress in stroke patients [
3], the relationship between stigma and PTG remains unclear. Understanding this relationship is especially important in the Korean healthcare context, where stroke rehabilitation often involves prolonged engagement with healthcare systems and strong family support networks. Such insights could inform the development of interventions that not only address the negative impacts of stigma but also harness its challenging aspects as a catalyst for psychological growth and adaptation.
Social support, which can facilitate PTG while counteracting factors that hinder it, refers to the exchange of assistance among significant individuals within a society. It encompasses various forms of aid provided by family, friends, medical personnel, and other members of one's social network [
8]. Emotional support from specific individuals is associated with improved functional recovery after stroke [
9]. This study aimed to examine the impact of social support on PTG in stroke patients, as it may contribute to a positive prognosis.
Resilience, another key psychological factor promoting PTG, refers to an individual's capacity to overcome adversity and effectively recover and adapt to stressful situations [
10]. Previous studies have identified resilience as a crucial component in the adaptation process following a stroke [
11]. However, research specifically examining the relationship between resilience and PTG in stroke patients is limited, particularly within the Korean context. This gap in the literature underscores the need for further investigation into how resilience may influence PTG in stroke survivors.
The interrelationships among stigma, social support, and resilience are particularly relevant to understanding stroke recovery. Previous research indicates that stigma can erode social support networks [
8,
12], as stroke survivors experiencing stigma may withdraw from social interactions or suffer from strained relationships due to others' negative perceptions. In turn, social support plays a crucial role in building resilience [
10] by providing the resources and encouragement needed for stroke survivors to adapt to challenges. Conversely, resilience may buffer against the negative effects of stigma [
3], enabling individuals to maintain social connections despite experiencing stigmatization. These complex interactions among PTG, stigma, social support, and resilience in stroke patients warrant further investigation, particularly since research examining their combined effects on PTG in this population remains limited. Consequently, this study aimed to provide foundational data for the development of nursing interventions that effectively facilitate adaptation to the physical and psychological changes following a stroke diagnosis. This was accomplished by investigating the effects of stigma (based on disease characteristics), social support (as a social factor), and resilience (as an individual psychological factor) on PTG.
This study aimed to assess the levels of stigma, social support, and resilience in stroke patients, determine the relationships among these variables, and examine whether stigma, social support, and resilience influence PTG.
METHODS
1. Study Design
We used a cross-sectional study design to evaluate PTG levels in patients with stroke and to examine the influence of stigma, social support, and resilience on PTG.
2. Participants
The study participants were patients diagnosed with stroke who visited the neurology outpatient clinic at Gyeongsang National University Hospital in Jinju, South Korea. We employed convenience sampling to select participants who met the following criteria: 1) age ≥19 years and capable of reading, comprehending, and communicating; 2) diagnosed with either hemorrhagic or ischemic stroke; 3) more than 3 months post-stroke diagnosis, in accordance with previous studies indicating that PTG occurs after this period [
13]; and 4) provided written informed consent after understanding the purpose and methods of the study. Exclusion criteria included patients receiving acute post-stroke treatment, those with significant cognitive impairment impeding communication, and individuals diagnosed with depression.
The sample size was initially determined using G* Power 3.1.9.7 with a significance level (⍺) of .05, an effect size of 0.15, a power (1-β) of .90, and an estimation of 10 independent variables, yielding a minimum sample size of 147 participants. However, as shown in
Table 5, 14 variables were included in the final regression analysis. A post hoc power calculation using the actual sample size of 150 participants and 14 variables confirmed a power (1-β) of .93, which exceeds the recommended threshold of .80 for social science research [
14]. In total, 164 questionnaires were distributed, 153 were returned, and 150 were deemed valid for the final analysis after excluding incomplete responses.
1) General and disease-related characteristics
General characteristics-including age, sex, education level, religious affiliation, marital status, living arrangement, employment status, and monthly income-and disease-related characteristics-including time since stroke onset, stroke type, presence of paralysis, and stroke recurrence-were assessed using 12 items derived from previous studies [
15,
16].
2) PTG
PTG refers to positive psychological changes experienced after traumatic events, signifying a transformation from recovery to enhanced maturity and health [
6]. This study used the Korean version of the Post-traumatic Growth Inventory (K-PTGI), translated and validated by Song et al. [
17] from Tedeschi and Calhoun's original PTGI [
6]. The K-PTGI comprises 16 items across four subdomains: increased interpersonal depth (five items), increased spiritual/religious interest (two items), discovering new possibilities (three items), and changes in self-perception (six items). Responses were scored on a 6-point Likert scale ranging from 0 ("I did not experience this change") to 5 ("I experienced this change to a very high degree"), with higher scores indicating greater PTG. Cronbach's ⍺ for the overall instrument was .90 during its development, .94 in Song et al. [
17], and .92 in this study. For the subdomains in this study, the Cronbach's ⍺ values were as follows: increased interpersonal depth (.87), increased spiritual/religious interest (.83), discovering new possibilities (.76), and changes in self-perception (.82).
3) Stigma
Stigma, defined as the personal experience of social rejection or negative evaluation based on an anticipated negative societal judgment [
12], was measured using the Korean version of the Stigma Scale for Chronic Illnesses 8-Item (K-SSCI-8). This version was validated by Yoo et al. [
18] using the original scale by Molina et al. [
19]. The scale comprises eight items divided into two subdomains: social stigma (four items) and internalized stigma (four items). Responses were evaluated on a 5-point Likert scale ranging from 1 ("not at all") to 5 ("always"), with higher scores indicating greater perceived stigma. Cronbach's ⍺ was .96 in the original form [
20], .90 in the study by Yoo et al. [
18], and .93 in this study.
4) Social support
Social support, referring to the exchange of assistance from significant others such as family members, friends, and healthcare providers [
12], was assessed using the Multidimensional Scale of Perceived Social Support (MSPSS). Developed by Zimet et al. [
21] and translated into Korean by Shin and Lee [
20], the MSPSS comprises 12 items divided into three subdomains: support from family (four items), friends (four items), and healthcare providers (four items). Responses were rated on a 5-point Likert scale ranging from 1 ("strongly disagree") to 5 ("strongly agree"), with higher scores indicating greater perceived social support. The Cronbach's ⍺ was .85 during development [
22], .89 in the study by Shin and Lee [
20], and .91 in this study.
5) Resilience
Resilience is defined as an individual's capacity to cope with and overcome adversities or persistent stress and to successfully recover from such situations [
10]. This study employed the Korean version of the Connor-Davidson Resilience Scale (K-CD-RISC), which was translated and validated by Baek et al. [
22] from the original instrument developed by Connor and Davidson [
23]. The scale comprises 25 items divided into five subdomains: persistence/durability (eight items), robustness (nine items), optimism (four items), support (two items), and spirituality (two items). Responses were evaluated on a 5-point Likert scale ranging from 0 ("not true at all") to 4 ("true nearly all the time"), with higher scores indicating greater resilience. Cronbach's ⍺ was .93 in the original version [
24], as reported by Baek et al. [
22], and .96 in this study.
Data were collected using self-reported questionnaires between February and April 2024. After receiving approval from the department heads and nurses at Gyeongsang National University Hospital, the purpose and methods of the study were explained to the patients, and written informed consent was obtained. A total of 164 questionnaires were distributed, 153 were returned, and three were excluded due to incomplete responses, leaving 150 valid datasets for the final analysis. Completion of the 73-item questionnaire required approximately 20 minutes per participant.
Several measures were implemented to minimize potential sources of bias. To avoid sampling bias, all patients visiting the neurology outpatient clinic were invited to participate, and only those who provided written informed consent were included. This approach may have introduced selection bias, as patients willing to participate might differ from those who declined. Recall bias was reduced by using validated questionnaires and including only patients diagnosed with stroke at least 3 months prior. To address potential measurement bias, data collection was conducted solely by the first author, who was trained in standardized data collection procedures. Although this ensured consistency, we acknowledge that having a single data collector may introduce its own bias.
5. Ethical Considerations
This study was approved by the Institutional Review Board (IRB) of Gyeongsang National University Hospital (Approval No: GNUH 2023-11-026-002). The purpose, procedures, the voluntary nature of participation, and the confidentiality of participants' information were clearly explained. Only participants who provided written informed consent were included in the study. All data were anonymized and securely stored for three years before disposal.
6. Data Analysis
Data were analyzed using SPSS/WIN 27.0 software. Descriptive statistics (frequency, percentage, mean, and standard deviation) were used to describe the general and disease-related characteristics of the participants. Differences in PTG, stigma, social support, and resilience across these characteristics were examined using independent t-tests and one-way ANOVA, with post-hoc analyses performed using Scheffé test. Pearson's correlation was used to assess the relationships among PTG, stigma, social support, and resilience. Hierarchical regression analysis was conducted to identify the factors influencing PTG. The reliability of the measurement tools was evaluated using Cronbach's ⍺.
RESULTS
1. General and Disease-Related Characteristics of Participants
Analysis of the general and disease-related characteristics of the 150 participants revealed that 70.7% (n=106) were male, with the remaining participants being female. The mean age was 64.87±10.20 years, and 34.0% (n=51) were between 55 and 64 years old. Overall, 39.3% (n=59) of the participants had an education level of high school or higher, and 53.3% (n=80) reported having a religious affiliation. Most participants were married (85.3%, n=128), and 75.3% (n=113) lived with at least one other person. Among those with housemates, 89.4% (n=101) lived with their spouses. Unemployed participants accounted for 60.7% (n=91), and 40.0% (n=60) had a monthly income between 1 and 3 million Korean won (KRW). The mean time since stroke onset was 5.21±5.53 years, with 33.3% (n=50) diagnosed 2~5 years prior to the study and 20.7% (n=31) diagnosed 5~10 years prior. Most participants (77.3%, n=116) experienced an ischemic stroke; 64.0% (n=96) had no paralysis, while the remaining participants experienced paralysis. Additionally, 84.0% (n=126) reported no recurrence of stroke (
Table 1).
The mean PTG score was 2.52±1.05 out of 5. The subcategory scores were as follows: changes in self-perception (2.73±1.20), increased interpersonal depth (2.64±1.22), discovering new possibilities (2.47±1.21), and increased spiritual/religious interest (1.69±1.62). The mean stigma score was 1.68±0.87 out of 5, with internalized stigma at 1.89±1.00 and social stigma at 1.47±0.81. Social support had a mean score of 3.11±0.86 out of 5, with family support scoring highest (3.88±0.93), followed by friend support (3.05±1.12) and perceived support from medical staff (2.42±1.11). Resilience had a mean score of 2.35±0.75 out of 4, with subcategory scores as follows: support (2.66±0.93), optimism (2.44±0.86), perseverance (2.39±0.86), robustness (2.30±0.83), and spirituality (1.88±1.02) (
Table 2).
PTG varied significantly according to participants' demographic characteristics. Participants aged ≤54 years exhibited higher PTG than those aged 65~74 and ≥75 years (F=2.91,
p=.037). Participants with university-level education or higher demonstrated significantly greater PTG than those with primary or middle school education (F=4.26,
p=.006). Those with religious affiliations showed higher growth than those without (t=-5.02,
p<.001), and participants with housemates showed higher growth than those living alone (t=-2.01,
p=.046). Income also played a role; those earning 1-3 million KRW or more per month exhibited greater PTG than those earning <1 million KRW (F=10.65,
p<.001). Participants diagnosed with stroke <2 years ago and those diagnosed between 5~10 years ago had significantly higher PTG than those diagnosed >10 years ago (F=2.81,
p=.042). Additionally, those with hemorrhagic stroke showed significantly higher PTG than those with mixed-type strokes (F=3.28,
p=.040) (
Table 3).
Correlation analysis revealed significant relationships among the main variables and among PTG subdomains. PTG showed significant positive correlations with social support (r=.44,
p<.001) and resilience (r=.53,
p<.001). Among the PTG subdomains, changes in self-perception demonstrated the strongest correlation with resilience (r=.60,
p<.001), followed by social support (r=.45,
p<.001), suggesting that these factors exert a particularly strong influence on how stroke survivors reconstruct their self-concept. Changes in self-perception showed the strongest correlation with overall PTG (r=.92,
p<.001), followed by increased interpersonal depth (r=.87,
p<.001). The strong correlation between these two subdomains (r=.71,
p<.001) indicates that personal growth and interpersonal development may reinforce each other during post-stroke recovery. Notably, while increased spiritual/religious interest showed significant correlations with all other subdomains (r=.40~.47,
p<.001), these correlations were relatively modest compared to the relationships between other subdomains. Stigma was not significantly correlated with overall PTG or its subdomains; however, it demonstrated weak negative correlations with social support (r=-.22,
p=.006) and resilience (r=-.23,
p=.003) (
Table 4).
To identify the factors affecting PTG, eight variables that demonstrated significant differences based on general characteristics were incorporated into Model 1. These variables included age (in years), educational level (with elementary school or below as the reference), religious affiliation (with "no" as the reference), presence of a housemate (with "none" as the reference), monthly income (with <1 million KRW as the reference), time since stroke onset (in years), stroke type (with mixed type as the reference), and stroke recurrence (with "no recurrence" as the reference). Model 2 included social support and resilience, which had shown significant correlations with PTG.
The regression results indicated that the Durbin-Watson statistic was 1.826, which is approximately 2.0, suggesting the absence of autocorrelation and independence of errors. The fit of the regression model was deemed satisfactory (F=5.51, p<.001), and the variance inflation factor was less than 10, indicating the absence of multicollinearity issues. In Model 1, the regression yielded statistically significant results (F=5.51, p<.001). Among the variables entered in the first stage, having a religious affiliation (β=.33, p<.001) and monthly income exceeding 3 million KRW (β=.23, p=.033) were identified as significant factors influencing PTG. The explanatory power of the model was 26.6% (F=5.51, p<.001).
In Model 2, the regression model remained statistically significant (F=9.45,
p<.001), with an increased explanatory power of 44.2%, representing a 17.6% improvement over Model 1. The final factors influencing PTG were identified as resilience (β=.37,
p<.001), having a religious affiliation (β=.29,
p<.001), and stroke type, specifically hemorrhagic stroke (β=.23,
p=.033), with an overall explanatory power of 44.2% (F=9.45,
p<.001) (
Table 5).
In summary, resilience, religious affiliation, and stroke type emerged as significant predictors of PTG. Specifically, having a religious affiliation was associated with higher PTG, and individuals with hemorrhagic strokes exhibited higher PTG than those with ischemic or mixed-type strokes.
DISCUSSION
This study examined the effects of stigma, social support, and resilience on PTG in stroke patients with the objective of providing foundational data for developing nursing interventions to effectively promote PTG.
The mean PTG score for stroke patients in this study was 2.52 out of 5, which is moderate but slightly lower than the scores reported by Park and Kim (2.97) [
25] and Jeong and Kim (2.82) [
24]. This discrepancy may be attributed to differences in the study populations; Park and Kim included 74.6% of patients undergoing acute-phase inpatient treatment, whereas this study focused exclusively on outpatients with longer times since stroke diagnosis. Moreover, the mean time since stroke onset in this study (5.21±5.53 years) was considerably longer than that reported by Jeong and Kim (1.95±1.31 years) [
24]. Previous research indicates that PTG tends to peak within six months following a stroke diagnosis [
13,
24], suggesting that patients with shorter diagnosis periods may experience greater PTG. Consequently, longitudinal studies are needed to track changes in PTG over time.
Analysis of the PTG subdomains revealed that "changes in self-perception" had the highest mean score (2.73±1.20), followed by "increased interpersonal depth" (2.64±1.22), while "increased spiritual/religious interest" had the lowest score (1.69±1.62). These findings align with those of Jeong and Kim [
24], in which stroke survivors also scored highest in self-perception changes (2.98±1.15) and lowest in spiritual/religious interest (2.24±1.44). The consistently higher scores in self-perception changes suggest that the disruption of identity caused by stroke prompts a critical reconstructive process in which survivors redefine their self-concept [
24,
26]. Charmaz's work on chronic illness and identity reconstruction [
26] supports the idea that this process can lead to enhanced psychological growth as individuals integrate their post-stroke abilities into a transformed sense of self. The lower scores in spiritual/religious interest-despite religion being a significant predictor of PTG (β=.29,
p<.001)-reveal a notable paradox. Although religious beliefs appear to facilitate PTG, physical limitations and existential challenges following a stroke may impede active spiritual engagement [
27,
28]. This finding is consistent with Giaquinto et al.'s [
28] observation that stroke survivors often struggle to maintain religious practices despite drawing strength from their faith, suggesting that healthcare providers should consider targeted interventions to bridge the gap between spiritual resources and practical engagement during rehabilitation.
In this study, PTG varied significantly according to factors such as age, education level, religious affiliation, living situation, monthly income, time since stroke onset, stroke type, and stroke recurrence. These findings are consistent with those of Park and Kim [
25], who reported that having housemates, a religious affiliation, and higher monthly income significantly influenced PTG. Jeong and Kim [
24] also identified age, education, religion, living situation, and time since stroke onset as important factors. However, unlike Jeong and Kim [
24], our study found a significant relationship between stroke recurrence and PTG, warranting further research on this aspect. Although studies on the relationship between stroke type and PTG are limited, Kang et al. [
29] reported that hemorrhagic stroke had a significantly lower recurrence rate than ischemic stroke in a 10-year follow-up study. Additionally, Lee and Park [
15] found that disease recurrence can prolong treatment and increase patient stress, thereby reducing the likelihood of PTG. Although their research focused on a different patient population, the relationship between recurrence and reduced PTG may also apply to stroke survivors, indicating a need for more stroke-specific studies.
Correlation analysis revealed notable patterns in the relationships between PTG and the key variables. Resilience had its strongest correlation with changes in self-perception (r=.60,
p<.001), suggesting that psychological hardiness is particularly important for reconstructing self-identity after a stroke. This finding is consistent with Lee and Yoon's [
16] work, which demonstrated that resilience helps patients acknowledge and adapt to their altered circumstances. Social support also showed moderate positive correlations across all PTG domains, with the strongest association observed for changes in self-perception (r=.45,
p<.001), supporting previous research on the role of social resources in identity reconstruction after stroke [
8,
9]. Interestingly, while stigma did not show a significant correlation with overall PTG, it had a marginally positive correlation with increased spiritual/religious interest (r=.16,
p=.051). This unexpected trend may indicate that some stroke survivors turn to spiritual resources when facing social challenges, though further research is needed to explore this relationship.
The hierarchical regression analysis identified resilience, religious affiliation, and stroke type as significant predictors of PTG, collectively explaining 44.2% of its variance. In our regression models, PTG was treated as a unified construct rather than being separated into subdomains, consistent with Tedeschi and Calhoun's theoretical framework, which views PTG as an integrated transformation process rather than a set of distinct growth areas [
30].
Resilience emerged as the most influential factor affecting PTG. This finding aligns with previous research [
16] suggesting that patients with higher resilience are better able to acknowledge their illness and adapt successfully. Park et al. [
31] argued that resilience is shaped by both psychological and environmental factors and can be strengthened by external resources such as social support. Sadler et al. [
32] reported that a 6-week resilience enhancement program, which included group discussions and reflection activities with role models, significantly improved resilience in stroke patients 6 to 24 months post-diagnosis. These findings underscore the importance of developing interventions aimed at enhancing resilience in stroke survivors.
Religious affiliation was also found to significantly influence PTG, consistent with previous studies. Jeong and Kim [
24] reported similar findings, suggesting that religious spirituality can help alleviate the emotional shock of a stroke and facilitate social support through religious communities, ultimately leading to greater gratitude and personal growth. Oshvandi et al. [
27] demonstrated that a spiritual support program significantly increased hope in stroke patients, and that this hope was closely linked to PTG. Therefore, the presence of religious beliefs may help mitigate the emotional impact of a stroke and provide additional social support, potentially promoting greater PTG.
Regarding stroke type, our analysis revealed that patients who experienced hemorrhagic stroke demonstrated higher levels of PTG compared to those with ischemic or mixed-type strokes. Although direct comparisons in previous literature are limited, this finding may be related to the often more complete functional recovery and fewer long-term disabilities observed in hemorrhagic stroke survivors. It is important to interpret this result as a comparative observation rather than as evidence that hemorrhagic stroke independently predicts higher PTG. This observation aligns with Calhoun and Tedeschi's theory [
30], which posits that repeated, deliberate rumination in response to extreme stress can facilitate PTG.
In contrast to other factors, stigma did not significantly affect PTG in this study. Our participants reported relatively low levels of stigma compared to previous studies using the SSCI-8 [
12]. This may be due to the characteristics of our sample, as Li et al. [
33] found that younger stroke survivors tend to experience higher stigma due to challenges in maintaining social roles and employment, while nearly half of our participants were aged 65 or older. Additionally, the majority of our participants had no paralysis, which may have reduced the visibility of stroke-related disabilities.
The SSCI-8, although validated for neurological disorders generally, might not fully capture stroke-specific stigma. Kariasa et al. [
34] identified several factors influencing internal stigma among stroke survivors-including self-acceptance, self-awareness, self-efficacy, family support, and age-highlighting the complex, multifaceted nature of stroke-related stigma. Similarly, Chen et al. [
35] demonstrated that cultural context significantly influences responses to mental health issues, with Chinese individuals showing a greater reluctance to seek professional help compared to Australians. This cultural variation in stigma and help-seeking behaviors may extend to stroke survivors, affecting their rehabilitation experiences. Future research should aim to develop a stroke-specific stigma measurement tool that incorporates these cultural and age-related variations to more accurately assess its relationship with PTG.
With advancements in medical technology, the number of stroke survivors is steadily increasing, as is the number of patients living with the physical and psychological sequelae of stroke. Given that stroke necessitates ongoing rehabilitation and lifestyle management, effective adaptation to post-stroke life is crucial. To facilitate this process and promote PTG, it is essential to address the psychosocial factors affecting stroke patients. This study, which identified resilience as the most significant predictor of PTG, can serve as a foundation for developing targeted psychosocial nursing interventions. In addition, our findings regarding the positive influence of religious affiliation and the potential impact of stroke type-specifically hemorrhagic stroke-on PTG provide valuable insights for creating comprehensive programs aimed at fostering PTG among stroke survivors. These results highlight the importance of enhancing resilience, incorporating spiritual aspects of care, and tailoring interventions based on stroke characteristics to promote positive psychological adaptation.
This study has several limitations. First, the use of convenience sampling may limit the generalizability of our findings. Although we took measures to mitigate selection bias, recall bias, and measurement bias as described in the data collection section, these efforts may not have eliminated all sources of bias. Second, the wide variability in time since diagnosis and stroke severity among participants may have influenced the results. Third, as a cross-sectional study, we were unable to observe changes in PTG over time following stroke diagnosis. Despite these limitations, we employed validated questionnaires, included only patients diagnosed at least 3 months prior, and used a single trained researcher for data collection to ensure consistency. Rigorous statistical analyses, including hierarchical regression, were also used to identify significant predictors of PTG while controlling for various factors.
CONCLUSION
This study provides valuable preliminary data on the factors influencing PTG in stroke survivors, despite its limitations. Specifically, our findings suggest that resilience, religion, and stroke type (specifically, hemorrhagic stroke) are significant predictors of PTG in stroke survivors. These insights can inform future research and clinical interventions aimed at promoting PTG in this population.
Future studies should address the limitations of this research by employing more rigorous sampling techniques and focusing on more specific subgroups of stroke survivors. Longitudinal studies with larger, more representative samples could offer more robust insights into the dynamics of PTG among stroke survivors. Additionally, developing and implementing nursing intervention programs to increase resilience may be crucial for promoting PTG in patients with stroke. Further research is needed to design and evaluate the effectiveness of such interventions.
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CONFLICTS OF INTEREST
The authors declared no conflict of interest.
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AUTHORSHIP
Study conception and/or design acquisition - PGE and CH; Analysis - PGE; Interpretation of the data - PGE and CH; Drafting or critical revision of the manuscript for important intellectual content - PGE and CH.
-
ACKNOWLEDGEMENT
This article is a condensed form of the first author's master's thesis dissertation from Gyeongsang National University.
Table 1.General and Disease-Related Characteristics (N=150)
|
Variables |
Categories |
n (%) or M±SD |
|
Gender |
Men |
106 (70.7) |
|
Women |
44 (29.3) |
|
Age (year) |
≤54 |
27 (18.0) |
|
55~64 |
51 (34.0) |
|
65~74 |
41 (27.3) |
|
≥75 |
31 (20.7) |
|
64.87±10.20 |
|
Educational level |
≤Elementary school |
31 (20.7) |
|
Middle school |
29 (19.3) |
|
High school |
59 (39.3) |
|
≥College |
31 (20.7) |
|
Religious affiliation |
No |
70 (46.7) |
|
Yes |
80 (53.3) |
|
Marital status |
Single |
22 (14.7) |
|
Married |
128 (85.3) |
|
Presence of a housemate |
None |
37 (24.7) |
|
Yes |
113 (75.3) |
|
Living arrangement† (n=113) |
Spouse |
101 (89.4) |
|
Children |
49 (43.4) |
|
Parents |
3 (2.7) |
|
Others |
5 (4.5) |
|
Job status |
No |
91 (60.7) |
|
Yes |
59 (39.3) |
|
Monthly income (million KRW) |
＜1 |
48 (32.0) |
|
1~3 |
60 (40.0) |
|
≥3 |
42 (28.0) |
|
Time since stroke onset (year) |
＜2 |
48 (32.0) |
|
2~4 |
50 (33.3) |
|
5~9 |
31 (20.7) |
|
≥10 |
21 (14.0) |
|
5.21±5.53 |
|
Stroke type |
Infarction |
116 (77.3) |
|
Hemorrhage |
24 (16.0) |
|
Mixed |
10 (6.7) |
|
Presence of paralysis |
No |
96 (64.0) |
|
Yes |
54 (36.0) |
|
Stroke recurrence |
No |
126 (84.0) |
|
Yes |
24 (16.0) |
Table 2.The Level of Stigma, Social Support, Resilience, and Post-traumatic Growth (N=150)
|
Variables |
Categories |
Number of items |
Range |
Minimum |
Maximum |
M±SD |
|
Stigma |
Total |
8 |
8~40 |
8 |
36 |
13.43±6.93 |
|
Self-stigma |
4 |
4~20 |
4 |
20 |
7.55±4.01 |
|
Social stigma |
4 |
4~20 |
4 |
19 |
5.89±3.26 |
|
Social support |
Total |
12 |
12~60 |
15 |
56 |
37.36±10.26 |
|
Family support |
4 |
4~20 |
6 |
20 |
15.50±3.71 |
|
Friends support |
4 |
4~20 |
4 |
20 |
12.19±4.50 |
|
Medical staff support |
4 |
4~20 |
4 |
20 |
9.67±4.42 |
|
Resilience |
Total |
25 |
0~100 |
18 |
95 |
58.64±18.66 |
|
Hardiness |
9 |
0~36 |
3 |
36 |
20.72±7.44 |
|
Persistence |
8 |
0~32 |
4 |
32 |
19.11±6.85 |
|
Optimism |
4 |
0~16 |
2 |
16 |
9.74±3.46 |
|
Support |
2 |
0~8 |
0 |
8 |
5.32±1.85 |
|
Spiritual in nature |
2 |
0~8 |
0 |
8 |
3.75±2.05 |
|
Post-traumatic growth |
Total |
16 |
0~80 |
0 |
72 |
40.35±16.83 |
|
Relating to others |
5 |
0~25 |
0 |
25 |
13.21±6.12 |
|
Spiritual change |
2 |
0~10 |
0 |
10 |
3.38±3.24 |
|
New possibilities |
3 |
0~15 |
0 |
15 |
7.40±3.64 |
|
Changed perception of self |
6 |
0~30 |
0 |
30 |
16.37±7.19 |
Table 3.Differences in Post-traumatic Growth According to Participants' Characteristics (N=150)
|
Variables |
Categories |
M±SD |
t or F |
p (Scheffé) |
|
Gender |
Men |
2.53±0.99 |
0.05 |
.962 |
|
Women |
2.52±1.08 |
|
|
|
Age (year) |
≤54a
|
2.80±1.03 |
2.91 |
.037 |
|
55~64b
|
2.74±1.11 |
|
(a＞c, d) |
|
65~74c
|
2.25±1.03 |
|
|
|
≥75d
|
2.28±0.91 |
|
|
|
Education level |
≤Elementary schoola
|
2.28±0.95 |
4.26 |
.006 |
|
Middle schoolb
|
2.27±1.12 |
|
(d＞a, b) |
|
High schoolc
|
2.48±0.97 |
|
|
|
≥Colleged
|
3.08±1.08 |
|
|
|
Religious affiliation |
No |
2.09±1.04 |
-5.02 |
＜.001 |
|
Yes |
2.90±0.92 |
|
|
|
Marital status |
Single |
2.21±0.90 |
-1.53 |
.129 |
|
Married |
2.58±1.07 |
|
|
|
Presence of housemate |
No |
2.22±0.91 |
-2.01 |
.046 |
|
Yes |
2.62±1.08 |
|
|
|
Job status |
No |
2.43±0.99 |
-1.30 |
.197 |
|
Yes |
2.66±1.14 |
|
|
|
Monthly income (million KRW) |
＜1a
|
2.03±0.97 |
10.65 |
＜.001 |
|
1~3b
|
2.59±0.91 |
|
(b, c＞a) |
|
≥3c
|
2.99±1.11 |
|
|
|
Time since stroke onset (year) |
＜2a
|
2.68±0.96 |
2.81 |
.042 |
|
2~4b
|
2.51±1.04 |
|
(a, c＞d) |
|
5~9c
|
2.70±1.04 |
|
|
|
≥10d
|
1.95±1.17 |
|
|
|
Stroke type |
Ischemica
|
2.43±1.07 |
3.28 |
.040 |
|
Hemorrhagicb
|
3.02±0.83 |
|
(b＞c) |
|
Mixedc
|
2.39±1.08 |
|
|
|
Presence of paralysis |
No |
2.57±1.08 |
0.82 |
.414 |
|
Yes |
2.43±1.01 |
|
|
|
Stroke recurrence |
No |
2.60±1.06 |
1.98 |
.049 |
|
Yes |
2.14±0.95 |
|
|
Table 4.Relationships Between Stigma, Social Support, Resilience, and Post-traumatic Growth (N=150)
|
Variables |
Stigma |
Social support |
Resilience |
Post-traumatic growth |
|
|
|
Total |
(1) |
(2) |
(3) |
(4) |
|
|
|
r (p) |
|
|
|
|
|
Stigma |
1 |
|
|
|
|
|
|
|
|
Social support |
-.22 (.006) |
1 |
|
|
|
|
|
|
|
Resilience |
-.23 (.003) |
.65 (＜.001) |
1 |
|
|
|
|
|
|
Post-traumatic growth |
.01 (.957) |
.44 (＜.001) |
.53 (＜.001) |
1 |
|
|
|
|
|
(1) Changes in self-perception |
-.11 (.187) |
.45 (＜.001) |
.60 (＜.001) |
.92 (＜.001) |
1 |
|
|
|
|
(2) Increased interpersonal depth |
.00 (.241) |
.40 (＜.001) |
.36 (＜.001) |
.87 (＜.001) |
.71 (＜.001) |
1 |
|
|
|
(3) Discovering new possibilities |
-.07 (.398) |
.31 (＜.001) |
.45 (＜.001) |
.77 (＜.001) |
.69 (＜.001) |
.52 (＜.001) |
1 |
|
|
(4) Increased spiritual/religious interest |
.16 (.051) |
.20 (.015) |
.25 (.002) |
.65 (＜.001) |
.46 (＜.001) |
.47 (＜.001) |
.40 (＜.001) |
1 |
Table 5.Factors Influencing Post-traumatic Growth (N=150)
|
Variables |
Categories |
Model 1 |
Model 2 |
|
B |
SE |
β |
t |
p
|
B |
SE |
β |
t |
p
|
|
(Constant) |
|
1.87 |
0.83 |
|
2.25 |
.026 |
0.33 |
0.76 |
|
0.44 |
.664 |
|
Age (year) |
|
-0.01 |
0.01 |
-.08 |
-0.86 |
.393 |
-0.01 |
0.01 |
-.11 |
-1.48 |
.142 |
|
Education level |
≤Elementary school (ref.) |
|
|
|
|
|
|
|
|
|
|
|
Middle school |
-0.16 |
0.25 |
-.06 |
-0.63 |
.531 |
-0.04 |
0.23 |
-.02 |
-0.18 |
.854 |
|
High school |
-0.19 |
0.24 |
-.09 |
-0.79 |
.431 |
-0.12 |
0.21 |
-.06 |
-0.57 |
.568 |
|
≥College |
0.21 |
0.31 |
.08 |
0.68 |
.495 |
0.20 |
0.27 |
.08 |
0.76 |
.451 |
|
Religious affiliation |
No (ref.) |
|
|
|
|
|
|
|
|
|
|
|
Yes |
0.70 |
0.16 |
.33 |
4.48 |
＜.001 |
0.61 |
0.14 |
.29 |
4.41 |
＜.001 |
|
Living arrangement |
None (ref.) |
|
|
|
|
|
|
|
|
|
|
|
With family |
0.13 |
0.19 |
.05 |
0.69 |
.493 |
-0.04 |
0.17 |
-.02 |
-0.25 |
.806 |
|
Monthly income (million KRW) |
1 (ref.) |
|
|
|
|
|
|
|
|
|
|
|
1~3 |
0.30 |
0.20 |
.14 |
1.50 |
.137 |
0.25 |
0.17 |
.12 |
1.43 |
.156 |
|
≥3 |
0.53 |
0.24 |
.23 |
2.17 |
.032 |
0.17 |
0.22 |
.07 |
0.79 |
.429 |
|
Time since stroke onset (year) |
|
-0.02 |
0.01 |
-.10 |
-1.27 |
.207 |
-0.02 |
0.01 |
-.13 |
-1.90 |
.060 |
|
Stroke type |
Infarction+Hemorrhage (ref.) |
|
|
|
|
|
|
|
|
|
|
|
Infarction |
0.02 |
0.31 |
.01 |
0.06 |
.952 |
0.30 |
0.27 |
.12 |
1.10 |
.271 |
|
Hemorrhage |
0.52 |
0.35 |
.18 |
1.50 |
.135 |
0.65 |
0.30 |
.23 |
2.15 |
.033 |
|
Stroke recurrence |
No (ref.) |
|
|
|
|
|
|
|
|
|
|
|
Yes |
-0.31 |
0.22 |
-.11 |
-1.41 |
.161 |
-0.01 |
0.20 |
.0 |
-0.07 |
.946 |
|
Social support |
|
|
|
|
|
|
0.17 |
0.11 |
.14 |
1.63 |
.105 |
|
Resilience |
|
|
|
|
|
|
0.52 |
0.12 |
.37 |
4.31 |
＜.001 |
|
Adj. R2
|
|
.266 |
.442 |
|
R2
|
|
.326 |
.495 |
|
Δ Adj. R2
|
|
|
.176 |
|
Δ R2
|
|
- |
.169 |
|
F (p) |
|
5.51 (＜.001) |
9.45 (＜.001) |
|
Durbin-Watson |
|
1.826 |
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