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Medicine (Baltimore)
Medicine (Baltimore)
MD
Medicine
0025-7974
1536-5964
Lippincott Williams & Wilkins Hagerstown, MD

39029078
MD-D-24-05805
00080
10.1097/MD.0000000000038836
3
4600
Research Article
Observational Study
Perceived social support, self-management, perceived stress, and post-traumatic growth in older patients following stroke: Chain mediation analysis
https://orcid.org/0009-0002-5737-7573
Chen Meng BSN a
https://orcid.org/0009-0001-4823-942X
Che Chengcheng BSN a*
a Department of Emergency Medicine, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, China.
* Correspondence: Chengcheng Che, Department of Emergency Medicine, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, 110004 Shenyang, Liaoning Province, China (e-mail address: ccchenshengjh@ldy.edu.rs).
19 7 2024
19 7 2024
103 29 e3883624 5 2024
14 6 2024
14 6 2024
Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.

Stroke is a potentially traumatic event that can lead to both positive changes associated with post-traumatic growth (PTG) and enduring mental distress. This study aimed to investigate the association between perceived stress and PTG among older postsurvivors, as well as to explore the potential mediating role of perceived social support and self-management in this relationship. A cross-sectional study was conducted to recruit 354 older poststroke survivors from 2 tertiary hospitals in Shenyang, China, between January 2022 and October 2023. Various multidimensional scales were utilized to measure perceived stress, perceived social support, self-management, and PTG. Structural equation modeling was employed by Amos 24.0 to analyze the mediating pathways. The average score of PTG was 50.54 ± 22.69 among older poststroke patients. Pearson analysis revealed significant associations between perceived stress, perceived social support, self-management, and PTG (all P < .01). The mediation model showed that perceived stress could both direct influence PTG (Effect = −0.196, 95% CI = [−0.259, −0.129]), and indirectly impact PTG through perceived social support (Effect = −0.096, 95% CI = [−0.157, −0.044]), through self-management (Effect = −0.033, 95% CI = [−0.064, −0.012]), and sequentially through perceived social support and self-management (Effect = −0.007, 95% CI = [−0.017, −0.002]), accounting for 58.9%, 28.8%, 9.9%, and 2.1% of the total effect, respectively. These findings confirmed the mediating roles of perceived social support and self-management between perceived stress and PTG among older poststroke survivors. This provides valuable insights into developing targeted social intervention programs to improve stroke management among older survivors.

mediating effect
older poststroke survivors
perceived social support
perceived stress
post-traumatic growth
self-management
OPEN-ACCESSTRUE
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pmc1. Introduction

Stroke is recognized as the leading cause of death in China, with its incidence showing an increasing trend annually.[1] Recently, it has been estimated that the percentage of the population over 60 in China will increase to 28.0% by 2040, making it the country with the world’s largest older adult population.[2] Consequently, studies have observed that the high prevalence of stroke and recurring rates contribute to an alarming elevation of cognitive impairment and functional disability among adult stroke survivors.[3] Previous research has shown that older individuals are at a higher risk of experiencing a stroke and have a less favorable prognosis compared to their younger counterparts, resulting in prolonged hospital stays, deteriorated walking ability, and worsening neurological function.[4] Furthermore, older poststroke survivors often encounter functional limitations and debilitating mental distress, which can significantly impede their long-term functional recovery and place substantial social and economic burdens on healthcare systems.[5] Thus, understanding the burden of stroke is crucial for the implementation of effective strategies to mitigate stroke risks among poststroke populations, particularly considering the factor of age.

Given the nature of stroke, which shares characteristics with traumatic events such as sudden onset, unpredictability, and potential life-threatening consequences, a growing body of evidence has revealed the coexistence of both positive and negative changes in individuals following a stroke.[6] Post-traumatic growth (PTG) is defined as positive psychological and behavioral changes, enhanced appreciations of life, and a heightened sense of personal strength following exposure to stressful life circumstances.[7] Importantly, PTG has been found to be correlated with various traumatic events, including stroke. For instance, Gangstad et al[8] observed that PTG had a positive correlation with cognitive processing and a negative association with mental distress among 60 stroke survivors. Notably, it has been demonstrated that older adults (>60 years) have exhibited lower levels of PTG compared to their younger counterparts when experiencing traumatic events, indicating the likelihood of an inverse correlation between increasing age and moderate-to-high PTG.[9] Nevertheless, there remains a scarcity of research focusing on the correlation of PTG among older Chinese individuals poststroke.

Stress is a complex psychobiological phenomenon that arises from the perception of danger or threat in one’s environment. Perceived stress is commonly associated with psychological distress following a stroke.[10] Older poststroke patients, in particular, are more susceptible to perceived stress due to their heightened risks of morbidity, disability, recurrence, and mortality.[11] A cross-sectional study revealed that perceived stress indirectly influenced PTG through post-traumatic symptoms among 662 citizens in Italy during the COVID-19 pandemic.[12] Furthermore, research by Arpawong et al[13] identified lower perceived stress as a significant predictor of PTG during the early stages of emerging adulthood among of 564 American youths who experienced frequent stressful life events. Given the escalating levels of perceived stress among older Chinese stroke patients attributed to financial burden, inadequate healthcare, and caregiver fatigue, there is an urgently need for a comprehensive examination of the direct and indirect effects of perceived stress on PTG in this population. This investigation is essential for the development of more effective therapeutic strategies to enhance PTG in older poststroke patients. Thus, we proposed Hypothesis 1 (H1): perceived stress negatively predicts PTG among older poststroke survivors.

Perceived social support refers to the perception of being respected, cared for, and supported by family members, friends, and relatives.[14] Accumulating evidence has highlighted the protective role of perceived social support in reducing stress appraisal responses by offering effective solutions during stressful events. For example, the Stroke Organization in the UK has implemented a nationwide peer support program aimed to providing group-based assistance to stroke survivors, helping them enhance their confidence and resilience when facing challenges.[15] Moreover, perceived social support has been shown to play a significant mediating role in the relationship between perceived stress and well-being among mothers of school-aged children with cerebral palsy.[16] On the other hand, PTG has been widely recognized to be positively influenced by perceived social support, particularly through interactive support groups.[17] For example, one review emphasized the positive association of social support and high PTG levels in later life among older adults engaged in supportive organizations.[9] Despite the increasing attention given to the relationships among perceived stress, perceived social support, and PTG, the underlying mechanisms remain unclear. Thus, we proposed Hypothesis 2 (H2): Perceived social support mediates the relationship between perceived stress and PTG among older poststroke survivors.

The ability and behaviors required for individual to maintain their physical and psychological well-being while minimizing the impact of a disease on their daily functioning are known as self-management. It is noted that self-management is essential for poststroke prognosis.[18] For example, effective health promotion interventions that target enhancing self-management skills, including self-care abilities, self-efficacy, and disease management, have shown to reduce risk factors associated with poststroke complications and improve overall quality of life.[19] With the growing number of older adults experiencing stroke, it is beneficial to provide appropriate self-management supports for older poststroke adults to enhance their physical and mental functioning.[20] Additionally, perceived stress was found to indirectly influence diabetes self-management through self-efficacy among adolescents with type 1 diabetes.[21] Moreover, self-management capabilities have been identified as a protective factor against adverse mental outcomes and linked to fostering PTG among older adults who engaged in self-directed physical exercises during the COVID-19 pandemic.[22] Despite these findings, there is still a gap in understanding of the interplay between perceived stress, self-management, and PTG among older poststroke survivors. Thus, we proposed Hypothesis 3 (H3): Self-management serves as a mediator between perceived stress and PTG among older poststroke survivors.

It is well established that perceived social support significantly impacts an individual’s ability to navigate challenging situation according to the literature.[23] In Uganda, perceived social support has been found to play a pivotal role in improving diabetes self-management behaviors among patients facing challenges such as inadequate healthcare supplies and underdeveloped healthcare systems.[24] Additionally, another Study discovered that patients with type 2 diabetes who received support from their family members were more inclined to engage in self-management activities.[25] A quasi-experimental study conducted in Iran further supported these findings by demonstrating that appropriate social support from their family members could augment self-management practices, expedite rehabilitative progress, and reduce the recurrence rate among heart failure patients by mitigating the negative physiological effects of their conditions.[26] Conversely, inadequate social support has been linked to poorer self-management outcomes.[27] Older poststroke patients experiencing severe mental stress are particularly vulnerable to social isolation and struggle to maintain social relationships due to their physical inactivity and body frailty, which can lead to a lack of social support. This barrier to social support may impede their self-management abilities and hinder the development of PTG. Hence, we proposed Hypothesis 4 (H4): Perceived social support and self-management jointly act as mediators in the relationship between perceived stress and PTG among older poststroke survivors.

While various psychological factors have been shown to impact the prognosis of older poststroke survivors, the specific relationship among the aforementioned 4 variables has not yet been explored in older Chinese poststroke adults. Despite previous literature having provided valuable insights, there is still a significant gap in understanding how changes in perceived stress might be linked to PTG, especially among older Chinese survivors following a stroke. Additionally, the potential contributions of perceived social support and self-management to the relationship between perceived stress and PTG remain unclear. Therefore, this cross-sectional study aimed to fill this gap by investigating the correlation between perceived stress, perceived social support, self-management, and PTG among older Chinese poststroke survivors. Furthermore, we sought to determine whether the relationship between perceived stress and PTG could be partially mediated by perceived social support and self-management. Building on existing evidence, the hypothesized model was depicted in Figure 1.

Figure 1. Hypothesized framework of the chain mediation model. PTG = post-traumatic growth.

2. Methods

2.1. Participants

A cross-sectional study was conducted in 2 regional hospitals in Shenyang City, Liaoning, China, utilizing the convenience sampling method. A total of 354 eligible patients were recruited to participant in this study from January 2022 to October 2023. The inclusion criteria were as follows: a confirmed diagnosis of stroke through computed tomography and brain magnetic resonance imaging; aged 60 years or older; onset of stroke occurring at least 1 month prior to this study; had adequate cognitive and communication abilities to independently respond to questionnaires or with assistance from investigators; voluntarily participated in this research and provided written informed consent. The exclusion criteria included: a history of psychiatric disorders; recent experience of other traumatic events within the last 6 months such as serious injuries resulting from traffic accidents or divorce; transient ischemic attack; accompanying severe life-threatening diseases such as malignant tumors.

2.2. Data collection

All the researchers received uniformed training before the study to ensure that they were sufficiently knowledgeable about the survey process. Eligible participants were convened in a quiet consultation room at the outpatient clinic. At the beginning of the study, our trained researchers briefly explained the purpose, procedure, and significance of the research to in a standardized manner all participants. They were explicitly informed of their right to withdraw from the survey at any point. Upon obtaining written informed consent from each participant, ensuring their voluntary engagement, the survey was initiated. Self-reported measurement instruments were then distributed to each participant, who were requested to independently complete the questionnaires. In cases where participants faced difficulties comprehending the queries or had visual impairments, our trained researchers were responsible for uniformly explaining the items to the participants, without providing any guidance or hints to influencing their self-judgment. The completion of all questionnaires typically spanned 20 to 30 minutes. Any incomplete or erroneous submissions were promptly reviewed by responsible researchers on the spot.

2.3. Ethical consideration

Stringently upholding confidentiality and anonymity, written informed consent was obtained from each participant before the study. This study was approved by the Ethics Committee of Shengjing Hospital of China Medical University (No. EC-2022-HS-021) and in accordance with the Declaration of Helsinki.

2.4. Sample size

The sample size was assessed using the Kendall criterion with 5 to 10 times the number of variables.[28] There were 31 variables (14 variables about demographic and clinical information, 2 subscales in perceived stress scale, 3 domains in perceived social support scale, 7 domains in self-management scale, and 5 domains in PTG scale) included in this study, therefore, the suggested sample size ranged from 155 to 310. Furthermore, considering a 20% rate of sample loss, the required minimum sample size for this study was 194 participants. A total of 354 older poststroke patients were recruited to participate in this study. After excluding 41 cases due to missing data, 313 valid questionnaires were collected for final data analysis, with an efficient response rate of 88.4%.

2.5. Outcome measures

2.5.1. Demographic information

A self-designed survey was distributed to all participants to collect their demographic and clinical information, including age, gender, body mass index (BMI), marital status, primary caregivers, stroke type, stroke duration, family monthly income, medical payment method, stroke recurrence, and common stroke risk factors such as smoking, diabetes, hyperlipidemia, and heart diseases.

2.5.2. Perceived stress scale

Perceived stress was measured using the Chinese version of Perceived stress scale-10 (CPSS-10) scale. This scale gauges an individual’s perception of stress as uncontrollable, unpredictable, and overwhelming over the past month. The CPSS-10 has demonstrated good validity and reliability in prior studies by Chinese researchers.[29] It comprises ten items (e.g., “Felt nervous and stressed?”; “Been able to control irritations in your life?”) and is categorized into 2 dominations: feeling of stress (6 items) and ability to deal with stress (4 items). Each item is rated on a 5-point Likert scale, scoring from 0 (never) to 4 (always). The total score ranges from 0 to 40, with higher scores representing a heightened perception of pressure. In the present study, the Cronbach α for the total CPSS-10 was 0.940, with subscales’ α coefficients of 0.901 and 0.853, respectively, indicating good internal consistency. Confirmatory factor analysis (CFA) confirmed the scale’s validity, with values well within acceptable ranges: maximum likelihood and degrees of freedom (χ2/df) = 2.773 (<3), incremental fit index (IFI) = 0.973 (>0.90), comparative fit index (CFI) = 0.973 (>0.90), Tucker–Lewis index (TLI) = 0.963 (>0.90), standard root mean-square residual (SRMR) = 0.030 (<0.08), root mean-square error of approximation (RMSEA) = 0.075 (<0.08).[30]

2.5.3. Perceived social support scale

The multidimensional Scale of Perceived Social Support (MSPSS), developed by Zimet et al,[31] was employed to assess perceived social support. This scale consists of 12 items (e.g., “My friends really try to help me.”; “My family really tries to help me.”) and is divided into 3 subscales that evaluate support from friends (4 items), family members (4 items), and significant others (4 items). Each item is rated on a 7-point Liker scale, ranging from 1 (totally disagree) to 7 (totally agree). The total score ranges from 12 to 84, the higher the score, the greater the perceived social support. The Cronbach α for the total MSPSS in this study was 0.979 and for the 3 subscales ranged from 0.931 to 0.941, indicative of good internal consistency. CFA analysis reinforced the scale’s validity, with favorable values: χ2/df = 1.210, IFI = 0.998, CFI = 0.998, TLI = 0.997, SRMR = 0.011, RMSEA = 0.026.

2.5.4. Self-management scale

The Stroke self-management scale (SSMS), developed by Chinese scholars Wang et al,[32] was used to assess the self-management ability of stroke patients. This scale, known for its good reliability and validity, consists of 50 items (e.g., “Lipid measurement frequency in the past month?”; “Been in a state of stress for a long time in the past month.”) across 7 domains addressing disease management (11 items), daily life (8 items), medication (5 items), emotion (5 items), diet (8 items), social function and interpersonal relationship (6 items), and rehabilitation exercise (7 items). Each item is rated on a 5-point Likert scale (from 1 = never to 5 = always), except for 1 item of diet management dimension, which is scored 1 to 10 points. The total score, ranging from 51 to 255, reflects the overall self-management ability, with higher scores indicating better management skills. In this study, the Cronbach α for the total SSMS was 0.982 and for the 7 subscales ranged from 0.780 to 0.975, indicating good internal consistency. CFA analysis demonstrated the scale’s validity, with satisfactory values: χ2/df = 2.012, IFI = 0.915, CFI = 0.915, TLI = 0.909, SRMR = 0.037, RMSEA = 0.057.

2.5.5. PTG scale

The Chinese version of Post-Traumatic Growth Inventory (C-PTG1) was employed to evaluate the PTG of stroke survivors. The C-PTG1 had demonstrated satisfactory reliability and validity,[33] which comprises 20 items (e.g., “I know better that I can handle difficulties.”; “I developed new interests.”). It is categorized into 5 dimensions: personal strength (4 items), spiritual changes (3 items), relatedness to others (6 items), new possibilities (3 items), and appreciation for life (four items). Each item is scored on a 5-point Likert scale, ranging from 0 (no change) to 5 (obviously change). The total score ranges from 0 to 100, with higher scores indicating greater levels of PTG. The Cronbach α for the total PTG1 was 0.979 and for the 5 subscales were between 0.893 and 0.963 in this study, indicating good internal consistency. CFA analysis confirmed the scale’s validity, with acceptable values: χ2/df = 1.193, IFI = 0.995, CFI = 0.995, TLI = 0.994, SRMR = 0.016, RMSEA = 0.025.

2.5.6. Control variables

Based on the univariate analysis results, age, gender, stroke duration, stroke recurrence, and heart disease were identified as statistically significant factors influencing PTG among older poststroke survivors. Therefore, these variables were included as control variables to minimize statistical bias in this study.

2.6. Statistical analysis

All statistical data analysis was conducted using IBM SPSS version 25 software. Descriptive statistics for the participant’s characteristics were presented as frequencies (percentages). The average scores of the variables were reported as mean (standard deviation) and calculated by independent t tests or F tests. Pearson correlations were used to explore the relationship between variables. Mediation analysis was performed through structural equation modeling (SEM) using Amos 24.0 software. Model fit was assessed based on various criteria: χ2/df < 3, IFI > 0.90, CFI > 0.90, TLI > 0.90, SRMR < 0.08, RMSEA < 0.08.[30] Total, direct, and indirect effects were considered statistically significant if the 95% bias-corrected confidence internals (CIs) based on 5000 bootstrap samples did not contain zero. A 2-sided P value < .05 was considered statistically significant.

3. Results

3.1. Common method biases

The Harman single-factor test was conducted to evaluate the common method bias resulting from the self-reported questionnaires. The results revealed that 9 common factors displayed eigenvalues greater than 1, Furthermore, the first component explained 36.0% of the total variance, which was less than the threshold value of 40%. This finding suggested that no serious common method deviation existed in the current study.

3.2. Baseline characteristics of the participants

A total of 313 older poststroke patients participated in this study. As presented in Table 1, the average age of older poststroke patients was 69.50 ± 6.32 years, ranging from 60 to 87 years, and the average BMI was 21.98 ± 2.43 kg/m2, with a range of 18.1 to 27.4 kg/m2. Approximately 53.0% of the participants were male, and 54.6% had spouses (Table 1). Moreover, 54.3% received care from their children, 24.0% had a monthly family income more than 6000 Yuan, and 72.2% covered their medical expenses through medical insurance. Furthermore, the majority (80.2%) had experienced ischemic stroke, 33.9% had a stroke history of over 1 year, and 23.6% had experienced stroke recurrence (Table 1). Details of other variables were provided in Table 1. Additionally, the univariate analysis revealed that male stroke survivors (P = .027), those who were relatively younger (P = .047), had a longer duration since their stroke (P = .030), no stroke recurrence (P = .031), and no heart disease (P = .020) reported higher levels of PTG compared to their counterparts (Table 1).

Table 1 Univariate analysis of variables influencing PTG among older stroke patients (N = 313).

Variables	Category	No (%)	PTG scorea	F/t test	P value	
Age (yr)	60 to 69	161 (51.4)	53.60 ± 21.29	3.080	.047*	
70 to 79	128 (40.9)	47.42 ± 23.50	
≥80	24 (7.7)	46.58 ± 25.43	
Gender	Male	166 (53.0)	53.23 ± 21.01	2.245	.027*	
Female	147 (47.0)	47.50 ± 24.16	
BMI (kg/m2)	<18.5	15 (4.8)	55.00 ± 26.57	2.710	.068	
18.5 to 23.9	232 (74.1)	51.84 ± 22.71	
≥24.0	66 (21.1)	44.94 ± 22.69	
Spouse	No	142 (45.4)	48.78 ± 22.28	−1.248	.213	
Yes	171 (54.6)	51.99 ± 22.99	
Primary caregivers	Children	170 (54.3)	50.90 ± 23.13	.170	.843	
Spouse	109 (34.8)	49.58 ± 22.76	
Others	34 (10.9)	51.79 ± 20.65	
Stroke type	Hemorrhagic	62 (19.8)	51.06 ± 24.49	.204	.838	
Ischemic	251 (80.2)	50.41 ± 22.28	
Household monthly income (¥)	<3000	135 (43.1)	48.93 ± 22.40	1.649	.194	
3000 to 6000	103 (32.9)	49.65 ± 22.11	
>6000	75 (24.0)	54.64 ± 23.78	
Medical payment method	Self-paying	87 (27.8)	48.46 ± 25.03	−1.005	.316	
Medical insurance	226 (72.2)	51.34 ± 21.73	
Stroke duration (mo)	2 to 6	72 (23.0)	46.43 ± 26.25	3.558	.030*	
7 to 12	135 (43.1)	49.19 ± 15.03	
>12	106 (33.9)	55.04 ± 27.23	
Stroke recurrence	No	239 (76.4)	51.95 ± 23.45	1.983	.031*	
Yes	74 (23.6)	45.99 ± 19.51	
Current smoke	No	251 (80.2)	51.42 ± 22.52	−1.401	.162	
Yes	62 (19.8)	46.97 ± 23.23	
Diabetes	No	71 (22.7)	51.58 ± 22.44	0.439	.661	
Yes	242 (77.3)	50.23 ± 22.80	
Hypotension	No	198 (63.3)	51.68 ± 23.02	1.167	.244	
Yes	115 (36.7)	48.57 ± 22.07	
Heart disease	No	214 (63.4)	52.57 ± 22.97	2.348	.020*	
Yes	99 (31.6)	46.14 ± 21.54	
BMI = body mass index, PTG = post-traumatic growth.

a The mean and standard deviation were presented.

* P < .05.

3.3. The correlations between variables

As shown in Table 2, older poststroke survivors had an average perceived stress score of 19.02 ± 9.01, a perceived social support score of 46.13 ± 18.26, a self-management score of 145.35 ± 43.29, and a PTG score of 50.54 ± 22.69, respectively. Furthermore, Pearson correlation analysis showed that perceived stress was significantly and negatively associated with perceived social support (r = −0.220, P < .01), self-management (r = −0.234, P < .01), and PTG (r = −0.412, P < .01, Table 2). Additionally, perceived social support was significantly and positively correlated with self-management (r = 0.247, P < .01) and PTG (r = 0.650, P < .01, Table 2). Furthermore, self-management exhibited a significant relationship with PTG (r = 0.406, P < .01, Table 2).

Table 2 Pearson correlation between variables among older stroke patients (N = 313).

Variables	Mean ± SD	1.	2.	3.	4.	5.	6.	7.	8.	9.	10.	11.	
1. Percieved stress	19.02 ± 9.01	1											
2. Feeling of stress	11.46 ± 5.52	0.986**	1										
3. Ability to deal with stress	7.55 ± 3.69	0.968**	0.911**	1									
4. Perceived social support	46.13 ± 18.26	−0.220**	−0.209**	−0.225**	1								
5. Self-management	145.35 ± 43.29	−0.234**	−0.243**	−0.208**	0.247**	1							
6. PTG	50.54 ± 22.69	−0.412**	−0.406**	−0.400**	0.650**	0.406**	1						
7. Personal strength	10.12 ± 4.68	−0.409**	−0.401**	−0.400**	0.620**	0.377**	0.961**	1					
8. Spiritual changes	7.67 ± 3.66	−0.360**	−0.352**	−0.351**	0.617**	0.415**	0.949**	0.898**	1				
9. Relatedness to others	15.25 ± 6.98	−0.413**	−0.411**	−0.393**	0.624**	0.388**	0.975**	0.915**	0.902**	1			
10. New possibilities	7.60 ± 3.56	−0.387**	−0.377**	−0.381**	0.626**	0.361**	0.949**	0.896**	0.879**	0.910**	1		
11. Appreciation for life	9.90 ± 4.71	−0.396**	−0.388**	−0.385**	0.636**	0.411**	0.964**	0.907**	0.903**	0.921**	0.896**	1	
PTG = post-traumatic growth, SD = standard deviation.

** P < .01

3.4. Measurement model test

The reliability and validity of the measurement model were assessed by Amos.24.0 before testing the structural relationships (Table 3). The results showed that the standardized factor loadings of the latent variables ranged from 0.780 to 0.978 (higher than the threshold of 0.7) (Table 3), suggesting the substantial relationships between the observed variables and latent variables in all constructs. In addition, the average variance extracted (AVE) of the 4 scales were between 0.766 and 0.943 (higher than the threshold of 0.5), and the composite reliability (CR) values ranged from 0.954 to 0.980 (higher than the threshold of 0.7) (Table 3), indicating good convergent validity and composite reliability for all constructs. Moreover, the results revealed that the square root of the AVE of each construct was greater than its correlation with other constructs, as detected by Pearson correlation analysis in Table 2, indicating satisfactory level of discriminant validity (Table 3).[34]

Table 3 Measurement model test.

Scale	Indicator	Factor loading	AVE	CR	Divergent validity	
Perceived stress	Feeling of stress	0.973	0.912	0.954	0.955	
Ability to deal with stress	0.936	
Perceived social	Friends	0.978	0.943	0.980	0.971	
Support	Family members	0.969	
Significant others	0.967	
Self-management	Disease management	0.787	0.766	0.958	0.875	
Daily life management	0.780	
Medication management	0.826	
Emotion management	0.956	
Diet management	0.975	
SFIR	0.890	
Rehabilitation exercise	0.893	0.903	0.979	0.950	
PTG	Personal strength	0.951	
Spiritual changes	0.940	
Related to others	0.963	
New possibilities	0.940	
Appreciation for life	0.957	
AVE = average variance extracted, CR = composite reliability, PTG = post-traumatic growth, SFIR = Social function and interpersonal relationship.

3.5. Mediating effect analysis and test

SEM was constructed by Amos 24.0 to examine the hypothesized structural relationship among perceived stress, perceived social support, self-management, and PTG. Prior to the mediation analysis, the goodness-of-fit indices were assessed, with χ2/df = 1.750, CFI = 0.979, IFI = 0.979, TLI = 0.976, SRMR = 0.049, and RMSEA = 0.046, indicated a satisfactory fit for the SEM. After adjusting for control variables, the results presented in Table 4 revealed that perceived stress significantly and negatively predicted PTG (β = −0.244, P < .001). Furthermore, perceived stress had a negative impact on perceived social support (β = −0.218, P < .001), and perceived social support subsequently positively influenced PTG (β = 0.550, P < .001, Table 4). Additionally, perceived stress also negatively affected self-management (β = −0.200, P < .001), and then self-management positively predicted higher PTG (β = 0.203, P < .001, Table 4). Moreover, there was a positive correlation between perceived social support and self-management (β = 0.210, P < .001, Table 4).The final mediation SEM was depicted in Figure 2, illustrating the direct standardized path coefficients between the 4 latent variables.

Table 4 Path coefficients in the mediation analysis (N = 313).

Path	B	SE	β	t value	P value	
Perceived stress → perceived social support	−0.240	0.063	−0.218	−3.788	***	
Perceived social support → self-management	0.225	0.061	0.210	3.681	***	
Perceived stress → self-management	−0.236	0.068	−0.200	−3.456	***	
Perceived stress → PTG	−0.196	0.034	−0.244	−5.797	***	
Perceived social support → PTG	0.401	0.030	0.550	13.22	***	
Self-management → PTG	0.138	0.028	0.203	4.864	***	
B = unstandardized estimates, PTG = post-traumatic growth, SE = standard error, β = standardized estimates.

*** P < .001.

Figure 2. Chain mediating model of perceived stress predicting PTG in the older poststroke survivors. PTG = post-traumatic growth; SFIR = Social function and interpersonal relationship. ***P < .001.

Furthermore, the mediation analysis was tested using the Bias-corrected bootstrapping method. Table 5 showed that the total, direct, and indirect effects of perceived stress on PTG were all statistically significant, as the 95% CIs did not contain zero. The direct effect of perceived stress on PTG was −0.196 (Boot SE = 0.034, 95% CI = [−0.259, −0.129]), accounting for 58.9% of the total effect. The total indirect effect of perceived stress on PTG accounted for 40.8% of the total effect (Effect = −0.136, Boot SE = 0.034, 95% CI = [−0.208, −0.074]). Specifically, the indirect effect of perceived stress on PTG through the mediating roles of perceived social support and self-management were found to be significant, with the effect sizes of −0.096 (Boot SE = 0.029, 95% CI = [−0.157, −0.044]) and −0.033 (Boot SE = 0.013, 95% CI = [−0.064, −0.012]), accounting for 28.8% and 9.9% of the total effect, respectively (Table 5). Furthermore, the chain mediating effect of perceived social support and self-management on the relationship between perceived stress and PTG was also significant, yielding an effect size of −0.007 (Boot SE = 0.004, 95% CI = [−0.017, −0.002]) and explaining 2.1% of the total effect (Table 5). Therefore, these findings verified that perceived social support and self-management play a serial mediating role in the relationship between perceived stress and PTG.

Table 5 Bootstrap test of total, direct, and indirect effects in the mediation model.

Path	Estimated effect	Boot SE	95% CI	Relative effect size	
Lower	Upper	
Total effect: perceived stress → PTG	−0.333	0.047	−0.424	−0.239		
Total direct effect: perceived stress → PTG	−0.196	0.034	−0.259	−0.129	58.9%	
Total indirect effect: perceived stress → PTG	−0.136	0.034	−0.208	−0.074	40.8%	
Perceived stress → perceived social support → PTG	−0.096	0.029	−0.157	−0.044	28.8%	
Perceived stress → self-management → PTG	−0.033	0.013	−0.064	−0.012	9.9%	
Perceived stress → perceived social support → self-management → PTG	−0.007	0.004	−0.017	−0.002	2.1%	
CI = confidence interval, PTG = post-traumatic growth, SE = standard error.

4. Discussion

To the best of our knowledge, this study was the first to explore the relationship among perceived stress, perceived social support, self-management, and PTG among older poststroke survivors, as well as the mediating roles of perceived social support and self-management within this framework. Our findings suggested that perceived stress, perceived social support, and self-management were significant predictors of PTG in older poststroke survivors. Particularly, perceived social support and self-management appeared to serve as independent and serial mediators in the relationship between perceived stress and PTG among these survivors, offering valuable insights for the development of targeted strategies aimed at promoting PTG in this population.

4.1. The relationship between perceived stress and PTG

PTG, recognized as a critical positive psychological construct, can emerge in the early stages poststroke and gradually intensity throughout long-term recovery. In our study, the average score of PTG was 50.54 ± 22.69, relatively lower than the PTG scores (55.40 ± 11.00) reported in a previous Chinese cross-sectional study involving 207 stroke survivors.[35] The differences might be attributed to the advanced age of our sample, aligning with prior literature that demonstrated a negative association between age and PTG among stroke survivors.[36] Notably, our study identified perceived stress as a significant negative predictor of PTG, supporting Hypothesis 1. Increasing evidence has elucidated that increasing age is a crucial risk factor for stroke mortality, especially for the older population, who are more susceptible to physical and emotional challenges.[37] These challenges can trigger heightened perceived stress levels, exacerbating their coping mechanisms following the stroke.[11] In the current study, older poststroke survivors experiencing high levels of perceived stress tended to confront the stroke in a maladaptive manner, showing resistance to accepting their altered reality and exhibiting negative emotional responses like anxiety, fear, and depression.[34] Similarly, a recent randomized controlled trail (RCT) discovered that a nurse-led mindfulness exercise program had a significant effect on reducing perceived stress and fostering PTG among 59 Chinese breast cancer females,[38] emphasizing the critical necessity for effective interventions addressing the relationship between perceived stress and PTG in older poststroke survivors.

4.2. The mediating role of perceived social support

The hypothesis that perceived social support would mediate the relationship between perceived stress and PTG (Hypothesis 1) was supported. Our finding affirmed that perceived stress could hinder PTG development by inhibiting perceived social support among older poststroke patients. It is well-documented that social support obtained from friends, family members, healthcare professionals, and supportive institutions can effectively enhance the psychosocial health and functional outcomes of stroke patients.[39] However, older poststroke adults are considered a particularly vulnerable group, as they are prone to psychological distress, loneliness, and social isolation due to their cognitive impairments, disabilities, and difficulties in establishing new social connections after retiring from work.[40] Consequently, those with lower perceived social support lack the strength and support to navigate challenging circumstances, ultimately leading to impeding PTG in the face of poststroke adversity. Consistent with our findings, Shang et al verified that survivors of natural disasters who received substantial quality and quantity of social support exhibited higher levels of PTG following the disaster.[41] Interestingly, differing from the previous researcher Măirean, who highlighted the positive moderating effect of perceived social support in the relationship between traumatic stress and PTG,[42] our current results strengthened the positive mediating role of perceived social support in buffering the adverse effect of perceived stress on PTG among older poststroke patients. Therefore, we suggested that the associations among variables related to traumatic events might differ across diverse samples based on the unique characteristics of distinct conditions.

4.3. The mediating effect of self-management

The mediating role of self-management in the relationship between perceived stress and PTG among older poststroke survivors (Hypothesis 3) was confirmed in this study. Older poststroke patients experiencing heightened mental stress and pressure were prone to feelings of hopelessness, distress, and powerlessness, which impeded their ability to engage in effective self-management practices.[43] Subsequently, limited self-management knowledge and behaviors further hinder their capacity to enhance PTG following stroke. It has been demonstrated that proficient self-management skills are beneficial for older adults in cultivating personal growth and resilience against adverse mental outcomes following traumatic events.[22] Meanwhile, stress management interventions have been shown to yield significant downstream effects by improving functional recovery and reducing symptoms of depression for stroke survivors.[44] Likewise, the current study also provided a valuable insights into how perceived stress influenced PTG among older poststroke patients, with a particular focus on the mediating role of self-management. Acquiring adequate self-care knowledge and skills could not only help patients efficiently manage their disease, but also diminish the adverse effect of perceived stress on PTG among older poststroke patients. Therefore, to improve functional recovery, psychosocial outcomes, and quality of life for older adults affected by stroke, present research advocates the importance of developing more efficacious self-management interventions based on scientific evidence and validated empirical theories. For instance, patients were encouraged to attend risk biomarker screening programs regularly to monitoring their poststroke outcomes and prevent stroke recurrence effectively.[45,46]

4.4. The chain mediating effect of perceived social support and self-management

In addition, our study further revealed the chain mediating role of perceived social support and self-management in the relationship between perceived stress and PTG among older poststroke patients, thus confirming Hypothesis 4. This study identified a significant correlation between perceived social support and self-management, implying that older poststroke survivors who received adequate support were more likely to access assistance, information, and knowledge from others to effectively navigate practical challenges. These support systems empower them to proactively address the negative impact of perceived stress, enabling them to efficiently manage their daily lives, and subsequently foster personal growth following stroke adversity. Similar results were observed in previous studies focusing on this association among stroke patients in China.[47] Therefore, to enhance the acquisition of appropriate self-management skills among older poststroke patients, it is advisable to consider interventions targeting social support. For example, evidence found that older adults with chronic conditions who received higher levels of informational social support exhibited better medication adherence than those with low levels of support.[48] Moreover, developing self-management strategies tailored specifically to older adults and their social networks might achieve better quality of life poststroke. For instance, education and support provided by healthcare workers could help older patients facilitate a long-lasting behavioral change, such as keep a healthy diet, engaging in regular exercise, and reducing smoking and alcohol consumption after a stroke.[49] It is noted to recognize that the social reintegration and self-management needs of older poststroke individuals differ significantly from those of other age groups.[50] Therefore, it is necessary to explore available self-management support specific to this particular population.

4.5. Practical significance

This study investigated the impact of perceived stress on PTG among older poststroke survivors, contributing to the theoretical foundation for interventions targeting PTG in this population. Healthcare professionals should promptly evaluate older poststroke survivors for signs of stress overload, address their physical, psychological, and social needs, and assist in alleviating emotional distress. Additionally, nursing staff should let them know that it is very common to experience stress, sadness, and loneliness following stroke, offer them appropriate coping strategies and facilitate access to social support. In addition, healthcare practitioners should empower patients with adequate knowledge and skills to modify health behaviors and manage their conditions on their own. For example, as members of patients’ crucial social network, healthcare workers should actively cultivate the relationships with patients to bolster perceived social support, encourage participation in stroke management rehabilitation programs, and raise their awareness of stroke symptoms to facilitate prompt medical intervention in case of stroke recurrence.[51,52] Overall, to effectively address the low levels of PTG observed in the older poststroke population, it is essential to concurrently strengthen perceived social support and self-management capabilities to counteract the adverse effects of perceived stress on PTG.

4.6. Limitations

Several limitations exist in the current study. First, this study was conducted solely in a city in Northeastern China and focused only on older survivors following stroke, potentially leading to sampling bias and affecting the generalizability of the results. Future studies should be encompassing more regions and a broader age range. Second, this study employed a cross-sectional design, limiting the ability to establish causal relationships between variables. It is crucial that future longitudinal research should be conducted to track changes in these variables for each patient over time. Third, this study relied on self-reported measures, which might not objectively reflect participants’ feelings, despite these questionnaires are commonly used in epidemiological research. Future studies should use more effective rating scales to obtain more objective data and reduce method bias.

5. Conclusion

The findings of this study demonstrated that perceived stress exerted a negative impact on PTG among older poststroke survivors. Perceived social support and self-management were identified as chain mediators linking perceived stress to PTG, suggesting their potential practical significance in enhancing PTG among older poststroke survivors. Therefore, it highlighted the necessity of encouraging older poststroke patients to engage in more social activities, such as professional self-management training programs, rehabilitation strategies, and regular conversation with others to enhance their self-management skills, thereby promoting their levels of PTG. These insights provide novel directions for healthcare providers to mitigate perceived stress and engender PTG among older poststroke patients in clinical settings.

Acknowledgments

The authors would like to thank all participants enrolled in the study.

Author contributions

Conceptualization: Meng Chen, Chengcheng Che.

Data curation: Meng Chen, Chengcheng Che.

Investigation: Meng Chen, Chengcheng Che.

Methodology: Meng Chen, Chengcheng Che.

Software: Meng Chen, Chengcheng Che.

Writing – original draft: Meng Chen.

Supervision: Chengcheng Che.

Validation: Chengcheng Che.

Writing – review & editing: Chengcheng Che.

Abbreviations:

AVE average variance extracted

BMI body mass index

CFI comparative fit index

CI confidence interval

CPSS-10 Chinese version of Perceived stress scale-10

C-PTG1 Chinese version of post-traumatic growth inventory

CR composite reliability

IFI incremental fit index

MSPSS multidimensional scale of perceived social support

PTG post-traumatic growth

RMSEA root mean-square error of approximation

SD standard deviation

SEM structural equation modeling

SFIR social function and interpersonal relationship

SRMR standard root mean-square residual

SSMS stroke self-management scale

TLI Tucker–Lewis index

χ2/df maximum likelihood and degrees of freedom

Written informed consent was obtained from each participant before the study. This study was approved by the Ethics Committee of Shengjing Hospital of China Medical University (No. EC-2022-HS-021) and in accordance with the Declaration of Helsinki.

The authors have no funding and conflicts of interest to disclose.

The authors declare that this article represents solely personal viewpoints and does not reflect any institutional or organizaitonal stance. This ariticle is intended soely for academic exchange and does not consititute any medical advice. The author disclaims any responsibliity for consequences arising from the use of the information provided in this article.

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

How to cite this article: Chen M, Che C. Perceived social support, self-management, perceived stress, and post-traumatic growth in older patients following stroke: Chain mediation analysis. Medicine 2024;103:29(e38836).
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