The relationship between illness perception and adherence to functional exercise in stroke patients: the chain mediating role of sense of coherence and self-regulatory fatigue

The relationship between illness perception and adherence to functional exercise in stroke patients: the chain mediating role of sense of coherence and self-regulatory fatigue | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The relationship between illness perception and adherence to functional exercise in stroke patients: the chain mediating role of sense of coherence and self-regulatory fatigue Fangli Liu, Yufen Xue, Jiachi Wang, Tengteng Kang, Cunzhe Tong, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9146399/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Motor dysfunction caused by stroke not only directly impairs physiological functions but also exerts a negative impact on psychological well-being. Adherence to functional exercises is critical for improving motor function recovery and enhancing the quality of life of stroke survivors. This study aimed to investigate the current status of illness perception, sense of coherence, self-regulatory fatigue, and functional exercise adherence in stroke patients, and to examine the chain mediating effects of sense of coherence and self-regulatory fatigue between illness perception and functional exercise adherence. Methods A cross-sectional descriptive study design was adopted, and convenience sampling was used to recruit stroke patients who attended follow-up visits at the neurology outpatient departments of two general hospitals in Henan Province. All participants completed a set of standardized questionnaires: including the demographic questionnaire, the Brief Illness Perception Questionnaire, the Sense of Coherence Scale, the Self-Regulatory Fatigue Scale, and the Stroke Patients' Functional Exercise Adherence Questionnaire. Results A total of 427 stroke patients were included. The mean scores of illness perception, sense of coherence, self-regulatory fatigue, and functional exercise adherence was (43.15 ± 9.24), (54.77 ± 10.86), (46.99 ± 8.25), and (34.30 ± 6.18), respectively. Multiple linear regression analysis identified that age, monthly household income per capita, primary caregiver, number of strokes episodes, number of chronic conditions, self-care capacity, illness perception, self-regulatory fatigue, and sense of coherence as significant predictors, collectively accounting for 72.3% of the variance in functional exercise adherence. Mediation effect analysis showed that illness perception not only directly influenced functional exercise adherence but also indirectly affected it through sense of coherence and self-regulatory fatigue. The mediating effects of sense of coherence and self-regulatory fatigue were − 0.101 (19.42% of total effect) and − 0.084 (16.15%), respectively, and their chain mediating effect was − 0.095 (18.27%). Conclusion Stroke patients in this study demonstrated moderate levels of illness perception, sense of coherence, and functional exercise adherence, upper-medium levels of self-regulatory fatigue. Sense of coherence and self-regulatory fatigue exhibiting chain-mediating effects between illness perception and functional exercise adherence. Clinical nursing staff should assist patients in establishing appropriate illness perceptions, enhancing their sense of coherence and reducing self-regulatory fatigue to improve functional exercise. Stroke Illness perception Sense of coherence Self-regulatory fatigue Functional exercise adherence Mediating effect Figures Figure 1 1 Introduction Stroke is an acute neurological deficit syndrome caused by impaired cerebral blood circulation, characterized by high incidence, high disability rate, and significant economic burden [ 1 ]. According to World Health Organization (WHO) statistics, approximately 15 million people worldwide suffer from stroke annually, with nearly 6 million deaths [ 2 , 3 ]. The latest findings from China's Cardiovascular Health and Disease Report indicate that the country currently has 13 million stroke patients, with new stroke cases increasing year by year [ 4 ]. Among stroke survivors, approximately 30% to 70% suffer from varying degrees of limb motor dysfunction, imposing a huge burden on families and society [ 5 ]. Functional exercise refers to a therapeutic method whereby individuals accelerate the recovery of bodily functions through scientific physical training [ 6 , 7 ]. The Global Manual for Prevention and Control of Cardiovascular and Cerebrovascular Diseases clearly points out that insufficient functional exercise is a primary cause of recurrence in stroke patients and delayed recovery of limb function [ 8 ]. Numerous studies have demonstrated a close association between the degree of limb function improvement and adherence to functional exercise[ 9 , 10 ]. According to the WHO definition, adherence refers to the consistency between patients' health behaviors and the diagnosis, treatment, and health management plans formulated by medical staff, which not only includes medication compliance but also behavioral cooperation in rehabilitation training, dietary management and other aspects [ 11 , 12 ]. In this study, functional exercise adherence in stroke patients refers to the degree to which their exercise behaviors align with healthcare professionals' recommended exercise regimens to promote limb function recovery. Research has concluded that patients with high functional exercise adherence exhibit a lower risk of recurrence compared to those with low adherence, along with a significant reduction in readmission rates [ 13 ]. Therefore, focusing on the level of functional exercise adherence in stroke patients and investigating the factors influencing their adherence behavior holds significant importance for promoting limb function recovery and improving the long-term prognosis of stroke patients.. A growing body of evidence indicates thats illness perception is a key psychological factor influencing patient’s health behaviors and treatment adherence [ 14 , 15 ]. Illness perception is defined as an individual's subjective cognition and evaluation of the severity, course, and prognosis of their own disease, which reflects the individual's subjective understanding and emotional response to the disease [ 16 ]. Yin et al.[ 17 ] found that illness perception is an independent influencing factor of rehabilitation exercise adherence in stroke patients with dysphagia. Therefore, patients with a positive illness perceptions generally possess accurate understanding of illness progression and outcomes, which facilitates improved adherence levels. Sense of coherence reflects an individual's overall perception and experience of life, serving as a key predictor of health-promoting behaviors such as treatment and exercise adherence [ 18 ]. study indicates that higher level of sense of coherence correlate with more proactive health-promoting behaviors and better treatment adherence [ 19 ]. However, sense of coherence is influenced by illness perception; patients with negative illness perception tend to have a lower level of sense of coherence [ 20 ]. In clinic practice,due to the lack of a rational understanding of the disease, such patients cannot develop effective coping strategies, leading to heightened uncertainty and anxiety about stoke and consequently lower sense of coherence[ 21 ]. In sum, it is meaningful to detect the effect of Sense of coherence between illness perception and functional exercise adherence. Stroke patients in the rehabilitation stage face heavy rehabilitation training tasks and great psychological pressure making them prone to self-regulatory fatigue. Proposed by Baumeister et al. [ 22 ], self-regulatory fatigue refers to a state of psychological exhaustion caused by the continuous consumption of mental resources due to prolonged self-control behaviors, which leads to the decline of individual cognitive, emotional and behavioral regulatory abilities. In this study, self-regulatory fatigue in stroke patients specifically refers to the psychological exhaustion state caused by the consumption of limited mental resources during the process of adhering to functional exercise, which is manifested as the reduction of self-regulatory ability and willingness to perform exercise. Self-regulatory fatigue can impair individuals' behavioral control abilities and lowers adherence to health behaviors [ 23 ]. Research indicates that positive illness perceptions among patients can mitigate the occurrence of self-regulatory fatigue to a certain extent [ 24 ]. Zhang et al. [ 25 ] surveyed 199 stroke patients in the rehabilitation phase, revealing moderate-to-high levels of self-regulatory fatigue. Similar findings emerged from Shen et al.'s [ 26 ] study of 330 stroke patients. Conversely, Xu et al.'s [ 27 ] investigation among elderly stroke patients indicated elevated levels of self-regulatory fatigue. Liu et al. [ 28 ] studied 254 stroke patients and found their self-regulatory fatigue was moderately high, directly impacting self-management levels. Pan et al. [ 29 ] demonstrated that self-regulatory fatigue is a significant factor affecting patients' quality of life. Additional research indicates a positive correlation between self-regulatory fatigue and functional exercise after stroke[ 30 ]. Adherence to function Exercise plays a crucial role in stroke patients' rehabilitation. Illness perception, sense of coherence, and self-regulatory fatigue are considered key influencing factors of patients' functional exercise adherence behaviors. However, existing studies predominantly examine pairwise relationships, and the interrelationships among these four factors warrant further investigation. Therefore, guided by the Stress and Coping Theory, this study constructs a theoretical model to deeply explore the underlying mechanisms and specific pathways through which illness perception, sense of coherence, and self-regulated fatigue influence functional exercise adherence in stroke patients. The model will be validated, aiming to provide new insights and references for enhancing functional exercise adherence levels and promoting early recovery in stroke patients. 2 Materials and methods 2.1 Research Hypothesis This study proposes the following research hypotheses and constructs a chained mediation theoretical model diagram. • H1: illness perception was an influencing factor for functional exercise adherence among stroke patients. • H2: Sense of coherence exerts a mediating effect between perceived illness and functional exercise adherence. • H3: Self-regulatory fatigue exerts a mediating effect between perceived illness and functional exercise adherence. • H4: Sense of coherence and self-regulatory fatigue exert a chain-mediated effect between perceived illness and functional exercise adherence. 2.2 Study Design A cross-sectional descriptive study design was used in this research. 2.3 Study Participants In this study, from February 2025 to September 2025, stroke patients undergoing follow-up examinations at the neurology outpatient departments of two general hospitals in Henan Province were selected using convenience sampling. Inclusion criteria: (1) All subjects must be ≥18 years of age; (2) Meet the diagnostic criteria for stroke outlined in the 2019 Chinese Diagnostic Guidelines for Major Cerebrovascular Diseases; (3) Confirmed diagnosis of stroke via imaging studies such as cranial computed tomography (CT) or magnetic resonance imaging (MRI); (4) Within 2–4 weeks after discharge from hospital; (5) Residual limb dysfunction with muscle strength ≤ Grade 4 post-stroke; (6) Patients must be conscious with adequate comprehension and communication abilities. Exclusion criteria: (1) Patients with psychiatric disorders or cognitive impairment; (2) Concurrent severe comorbidities such as organ dysfunction, respiratory failure, or malignant tumors. Sample size estimation : Based on sample size estimation methods, a rough calculation is performed using 5 to 10 times the number of dependent variables [31]. This study involved 25 variables: (13 items in the general information questionnaire, 3 dimensions from the illness perception questionnaire, 3 dimensions from the sense of coherence scale, 3 dimensions from the self-regulatory fatigue scale, and 3 dimensions from the stroke patient functional exercise adherence scale). Taking 10 times the number of variables(n=250), and considering a 10%-20% sample attrition rate. The required sample size ranged from 275 to 300, with a total of 427 cases included in the study. stroke patients undergoing follow-up examinations at the neurology outpatient departments of two tertiary-grade hospitals in Henan Province were investigated. 2.4 Research Instruments 2.4.1 Functional Exercise Adherence Scale for Stroke Patients The Functional Exercise adherence Scale for Stroke Patients developed by Lin et al. [32] in 2013 was employed for this survey. The scale includes 3 dimensions with 14 items: Functional Exercise adherence (8 items, Items 1–8), effect monitoring adherence (3 items, Items 9–11), and advice-seeking adherence (items 12–14). All items were scored positively using a 4-point Likert scale, yielding a total score range of 14 to 56 points. The adherence index is calculated as adherence Index = (adherence Score / 56) × 100, The adherence level is divided into three grades: High level( 76–100 points); Moderate level(51–75 points) and Low level: (1–50 points) A Higher adherence index indicates better patient adherence to functional exercise. In this study, the scale demonstrated a Cronbach’s α coefficient of the scale was 0.847, indicating good internal consistency reliability.. 2.4.2 General Information Questionnaire A customized general information questionnaire was developed for this study, comprising two sections: general demographic data and disease-related information. Within the disease-related section, patients' self-care abilities were assessed using the Barthel Index (BI), primarily evaluating two domains: self-care activities and mobility-related activities. This includes 10 items: eating, bathing, bowel and bladder control, transferring between bed and chair, walking on level ground, climbing stairs, dressing, personal hygiene, and using the toilet. The total score is out of 100 points. Based on BI scores, patients were categorized into four dependency levels: Severe dependency (0–40 points); Moderate dependency (41–60 points); Mild dependency (61–99 points) and Independent (100 points). Higher scores indicate greater functional independence [33]. 2.4.3 Brief Illness Perception Questionnaire (B-IPQ) The survey employed the Brief Illness Perception Questionnaire developed by Broadbent et al. [34]. The questionnaire comprises three dimensions: five items measuring illness perception (Items 1- 5), two items assessing emotional state (Items 6, 8), and one item evaluating illness understanding (Item 7), along with an open-ended question (listing in order the three most significant factors contributing to illness). Scoring used a 0–10, 11-point scale. The sum of item scores constituted the patient's total illness perception score. Items 3, 4, and 7 were reverse-scored. The total scale score ranged from 0 to 80, with higher scores indicating greater severity of illness perception. In this study, the Cronbach's α coefficient for the scale was 0.767, indicating acceptable internal consistency reliability. 2.4.4 Sense of Coherence Scale (SOC-13) The Chinese version of the SOC-13, translated by domestic scholars including Bao et al. [35], was employed for this study. The scale comprises 13 items across three dimensions: sense of comprehensibility, sense of manageability, and sense of meaning. The dimensions comprise: Sense of Comprehensibility (5 items, Items 2, 6, 7, 8, 12); manageability (4 items, Items 3, 4, 5, 10), and meaningfulness (4 items, Items 1, 9, 11, 13). All items are scored using a 7-point Likert scale (1 = completely inconsistent, 7 = completely consistent), with Items 1, 2, 3, 8, and 13 being reverse-scored. The total score ranges from 13 to 91 points,, with a higher score indicate greater sense of coherence. In this study, the Cronbach’s α coefficient for the scale was 0.903, , indicating excellent internal consistency reliability.. 2.4.5 Self-regulatory of Fatigue Scale (SRFS) The Chinese version of the SRFS revised by Wang et al. [36] was used to evaluate the level of self-regulatory fatigue in stroke patients. The scale includes 16 items and 3 dimensions: cognitive control fatigue (6 items, Items 1, 2, 3, 5, 11, 13); emotional control fatigue (5 items, Items 7, 9, 12, 14, 15); and behavioral control fatigue (5 items, Items 4, 6, 8, 10, 16). All items are scored using a 5-point Likert scale (1 = completely inconsistent, 5 = completely consistent), with Items 1, 2, 5, 9, and 14 being reverse-scored. The total score ranges from 16 to 80 points, with a higher score indicating a more severe level of self-regulatory fatigue. In this study, the Cronbach's α coefficient of the scale was 0.849, indicating good internal consistency reliability. 2.5 Data Collection Data collection took place from February 2025 to September 2025 All researchers and data collectors received standardized training before the study, including the research purpose, questionnaire instructions, and quality control measures. With the approval of the director of the neurology department and the head nurse of the participating hospitals, the investigators screened eligible stroke patients at the neurology outpatient department. Before the questionnaire survey, the investigators fully explained the research purpose, content, and confidentiality measures to the participants and their families, and obtained written informed consent from the participants who agreed to participate in the study. The questionnaires were distributed on the spot, and . Participants who could complete the questionnaire independently filled it out by themselves, and for those who could not (e.g., due to limb dysfunction), the investigators read the questionnaire items and options aloud and recorded the answers according to the participants' responses. All questionnaires were checked on the spot for completeness and validity. A total of 443 questionnaires were distributed in this study, and 427 valid questionnaires were recovered, with an effective recovery rate of 96.39%. 2.6 Statistical analysis Database construction was performed using Excel spreadsheets. Statistical analysis primarily employed the SPSS 25.0 statistical software package, supplemented by the Process v3.5 plugin for mediation effect analysis. The significance level was set at α=0.05, with P values less than 0.05 considered statistically significant. Descriptive Analysis: Frequency distributions and percentages were used to describe demographic characteristics of the study subjects. Mean ± standard deviation (Mean±SD) was employed to report total scores and dimension-specific scores for variables including illness perception, sense of coherence, self-regulatory fatigue, and functional exercise adherence. Univariate Analysis: Independent samples t-tests or one-way ANOVA were selected based on data characteristics to compare differences in illness perception, sense of coherence, self-regulatory fatigue, and functional exercise adherence among stroke patients across various sociodemographic and disease-related factors. Correlation Analysis: Pearson correlation analysis was used to explore relationships among the four variables, including illness perception. Multivariate Analysis: Multiple linear regression analysis examined the influence of variables with significant P<0.05 in univariate analysis, along with illness perception, self-regulatory fatigue, and sense of coherence, on functional exercise adherence in stroke patients. Mediation Analysis: Based on the research hypothesis, functional exercise adherence in stroke patients was set as the dependent variable (Y). Illness perception served as the independent variable (X), while sense of coherence and self-regulatory fatigue acted as mediating variables (M1, M2). Models 4 and 6 of the Process v3.5 plugin in SPSS 25 software were employed to analyze the mediating effects of sense of coherence and self-regulatory fatigue on the relationship between illness perception and functional exercise adherence (Model 4 analyzed single mediation effects, while Model 6 assessed chained mediation effects). 6 models (Model 4 for single mediation and Model 6 for chain mediation) to analyze the mediating effects and chain mediation effects of sense of coherence and self-regulatory fatigue between illness perception and exercise adherence. Bootstrap tests were employed to validate the mediation effects. 3. Results 3.1 Participants Characteristics 3.1.1 Demographic Data of Stroke Patients This study investigated 427 Stroke patients, including 297 males (69.56%) and 130 females (30.44%). The average age was (63.10 ± 11.36) years old，of which 158 cases (37.00%) were ≤ 60 years old and 269 cases (63.00%) were > 60 years old. The majority had a high school or technical secondary education background, totaling 154 cases (36.07%); Most were retired, totaling 213 cases (49.88%); Monthly income ranged mostly between 1000-3000 yuan, with 207 cases (48.48%), followed by 3,001-5,000 yuan, totaling 116 cases (27.17%); 261 cases (61.12%) resided in urban areas; the primary caregiver was the spouse in 195 cases (45.67%). Detailed sociodemographic characteristics of the study subjects are presented in Table 1. Table 1 General information of stroke patients ( n =427) Variable Classification n Proportion (%) Age ≤60 158 37.00 ＞60 269 63.00 Gender Male 297 69.56 Female 130 30.44 Marital status Married 379 88.76 No spouse (single/divorced/widowed) 48 11.24 Education level Elementary school and below 74 17.33 Junior high school 113 26.46 High school or technical secondary school 154 36.07 College and above 86 20.14 Working condition On duty 46 10.77 Retired 213 49.88 Off duty 168 39.34 Monthly income per capita (yuan) 5000 44 10.30 Place of residence Urban 261 61.12 Rural 166 38.88 Primary caregiver Spouse 195 45.67 Children 116 27.17 Other individuals 116 27.17 Medical payment method Employee Medical Insurance 225 52.69 Resident Medical Insurance 193 45.20 Self-pay 9 2.11 3.1.2 Disease-Related Data for Stroke Patients Data on stroke patients indicate that the predominant stroke type was ischemic, accounting for 301 cases (70.49%); most were first-time strokes, totaling 309 cases (72.37%); 209 patients (48.95%) had one chronic condition, while 44.5% had two or more chronic conditions; Detailed characteristics of the study subjects' disease-related information are presented in Table 2. Table 2 Disease-related data of stroke patients ( n =427) Variable Classification n Proportion (%) Types of stroke Hemorrhagic 126 29.51 Ischemic 301 70.49 Number of strokes First time 309 72.37 Second time 93 21.78 Third time and beyond 25 5.85 Number of chronic conditions 0 28 6.56 1 209 48.95 2 157 36.77 3 33 7.73 Self-care ability (Barthel Index) Mild Dependence 61 14.29 Moderate Dependence 170 39.81 Severe Dependence 196 45.90 3.2 Current Status of Functional Exercise Adherence, Illness perception, Psychological Coherence, and Self-regulatory of Fatigue Among Stroke Patients Using a method based on skewness and kurtosis coefficients for normality testing, the results showed that the skewness coefficients for stroke patients' illness perception, sense of coherence, self-regulatory fatigue, and functional exercise adherence were -0.096, -0.003, 0.307, and -0.158, respectively; The kurtosis coefficients were -0.559, -0.796, -0.420, and -0.396, respectively, all falling within ±1. According to relevant statistical research, skewness and kurtosis coefficients between -1 and +1 indicate acceptable normality [37]. The scores of the four variables and the dimensions of functional exercise adherence are shown in Table 3; the total score of illness perception was moderate level(43.15 ± 9.24); the total score of sense of coherence was moderate level(54.77 ± 10.86); the total score of self-regulatory fatigue was moderate-to-high level (46.99 ± 8.25) . Table 3 The scores of Functional Exercise Adherence and its dimensions in stroke patients (n=427, Mean ± SD) Variable Number of entries Mean±SD Adherence to Functional Exercise 8 21.24±3.83 Adherence to Effect Monitoring 3 6.80±1.47 Adherence to Seeking Advice 3 6.26±1.88 Functional Exercise Adherence(total score) 14 34.30±6.18 3.3 Analysis of differences in functional exercise adherence scores among stroke patients based on general demographic data Using independent samples t-tests or one-way analysis of variance, we investigated differences in functional exercise adherence scores among stroke patients across general demographic characteristics and disease-related information. Results revealed significant differences ( P < 0.05) in functional exercise adherence scores among stroke patients across various demographic categories, including age group, marital status, educational attainment, occupational status, household monthly income level, primary caregiver type, medical payment method, number of stroke episodes, number of comorbid chronic diseases, and level of self-care ability (Table 4). Table 4 Univariate analysis of factors associated with functional exercise adherence in stroke patients (n=427) Variable Classification n Score (Mean±SD) t/F P Age ≤60 158 35.54±6.52 3.220 0.001 ＞60 269 33.57±5.86 Gender Male 297 34.49±6.52 1.057 0.291 Female 130 33.85±5.31 Marital status Married 379 34.58±6.13 2.676 0.008 No spouse 48 32.06±6.15 Education level Elementary school and below 74 32.09±5.34 11.564 ＜0.001 Junior high school 113 32.84±6.20 High school/technical secondary school 154 34.99±5.87 College and above 86 36.85±6.31 Working condition On duty 46 37.07±6.62 13.522 ＜0.001 Retired 213 35.06±6.13 Off duty 168 32.57±5.66 Monthly income per capita 5000 44 39.89±6.71 Place of residence Urban 261 34.64±6.16 1.447 0.149 Rural 166 33.75±6.20 Primary caregiver Spouse 195 35.34±5.92 6.328 0.002 Children 116 34.01±6.24 Other individuals 116 32.83±6.27 Medical payment method Employee Medical Insurance 225 34.97±6.04 2.780 0.085 Resident Medical Insurance 193 33.60±6.01 Self-pay 9 32.22±10.79 Types of stroke Hemorrhagic 126 33.83±5.89 -1.016 0.310 Ischemic 301 34.49±6.30 Number of strokes First time 309 35.38±5.81 19.642 ＜0.001 Second time 93 31.38±5.41 Third time and beyond 25 31.80±8.82 Number of chronic conditions 0 28 36.29±4.75 10.598 ＜0.001 1 209 35.63±5.96 2 157 32.97±5.82 ≥ 3 33 30.42±7.38 Self-care ability Mild Dependence 61 38.48±4.06 74.237 ＜0.001 Moderate Dependence 170 36.51±5.36 Severe Dependence 196 31.07±5.77 3.5 Correlation analysis of illness perception, sense of coherence, self-regulatory of fatigue, and functional exercise adherence in stroke patients The result of Pearson correlation analysis shows that illness perception among stroke patients was negatively correlated with sense of coherence (r = -0.856, P < 0.01), positively correlated with self-regulatory fatigue (r = 0.827, P < 0.01), and negatively correlated with functional exercise adherence (r = -0.778, P < 0.01). Sense of coherence scores were negatively correlated with self-regulatory fatigue (r = -0.845, P < 0.01) and positively correlated with total functional exercise adherence scores (r = 0.758, P < 0.01). Self-regulatory fatigue was negatively correlated with functional exercise adherence (r = -0.770, P < 0.01) (Table 5). Table 5 Pearson correlation coefficients among illness perception, sense of coherence, self-regulatory fatigue and functional exercise adherence (n=427) Variable Illness perception Sense of coherence Self-regulatory fatigue Functional exercise adherence Illness perception 1 Sense of coherence -0.856** 1 Self-regulatory fatigue 0.827** -0.845** 1 Functional exercise adherence -0.778** 0.758** -0.770** 1 Note:** P ＜0.01 3.6 Multiple linear regression analysis of functional exercise adherence in stroke patients Multiple linear regression analysis was further employed to explore predictors of functional exercise adherence among stroke patients. Functional exercise adherence was designated as the dependent variable in the regression model, while the independent variables comprised statistically significant factors identified in the univariate analysis. These included 10 variables from the demographic data—such as age, marital status, and educational attainment—along with illness perception, sense of coherence, and self-regulatory fatigue, which were incorporated into the multiple linear regression analysis. Before conducting multiple linear regression analysis, it is essential to test for multicollinearity among the variables. Statistically, a tolerance (T) below 0.1 and a variance inflation factor (VIF) above 10 are typically regarded as indicators of multicollinearity. In this study, all T values exceeded 0.1 and all VIF values remained below 10. This indicates that no multicollinearity issues exist among the study variables included in the multiple linear regression equation. Subsequently, the independent variables were assigned values according to the requirements of multiple linear regression.The assignment method was as follows. Marital status: married=0, no spouse=1; Education level: elementary school and below=1, Junior high school=2, High school/technical secondary school=3, College and above=4; Working condition: on duty=1, retirement=2, off duty=3; Monthly income per capita: 5000=4; Primary caregiver: spouse=1, children=2, other individuals=3; Medical payment method: employee medical insurance=1, resident medical insurance=2, self-pay=3; Number of strokes:first time=1, second time=2, third time and beyond=3; Number of chronic conditions: 0=1, 1=2, 2=3, 3=4; Self-care ability: mild dependence=1, moderate dependence=2, severe dependence=3; Age, self-care ability, illness perception, sense of coherence, and self-regulatory fatigue scores were all included in the equation with the original values. The regression equation results indicate that monthly income per capita, primary caregiver, number of strokes, number of chronic conditions, self-care ability, self-regulatory fatigue, illness perception, and sense of coherence ultimately entered the regression equation. Together, these factors explain 72.3% of the total variance in functional exercise adherence among stroke patients. The regression model validation yielded an F-value of 82.999 with P < 0.001, confirming the model’s statistical significance. Among these factors, monthly income per capita, self-care ability, and sense of coherence positively predicted exercise adherence, while age, primary caregiver status, number of strokes, number of chronic conditions, self-regulatory fatigue, and illness perception negatively predicted adherence.（Table 6） Table 6 Multiple linear regression analysis of functional exercise adherence in stroke patients Model B S.E. β t P Tolerance VIF Constant 42.520 4.201 10.123 ＜0.001 Age -0.037 0.015 -0.067 -2.379 0.018 0.839 1.192 Monthly income per capita 1.446 0.255 0.197 5.674 ＜0.001 0.554 1.806 Primary caregiver -0.540 0.207 -0.073 -2.614 0.009 0.860 1.162 Number of strokes -0.804 0.289 -0.076 -2.784 0.006 0.902 1.109 Number of chronic conditions -0.472 0.232 -0.056 -2.032 0.043 0.885 1.130 Self-care ability 0.037 0.012 0.100 3.162 0.002 0.664 1.507 Self-Regulatory Fatigue -0.167 0.041 -0.223 -4.072 ＜0.001 0.223 4.481 Illness Perception -0.159 0.038 -0.238 -4.161 ＜0.001 0.206 4.864 Psychological Coherence 0.121 0.033 0.213 3.656 ＜0.001 0.197 5.064 Note： F =82.999, P <0.001; R 2 =0. 723, Adjusted R 2 =0.714 3.7 Chain mediation analysis of sense of coherence and self-regulatory fatigue in the relationship between illness perception and functional exercise adherence among stroke patients Using stroke patients’ illness perception as the independent variable, sense of coherence (M1) and self-regulatory fatigue (M2) as mediating variables, and functional exercise adherence as the dependent variable, mediation analysis was conducted using Model 6 in the Process 3.5 plugin of SPSS 25. Results indicated that illness perception significantly negatively predicted sense of coherence (β = -0.856, P < 0.001); illness perception significantly positively predicted self-regulatory fatigue (β = 0.387, P < 0.001); sense of coherence significantly negatively predicted self-regulatory fatigue (β = -0.513, P < 0.001); Perceived illness significantly negatively predicted adherence to functional exercise (β = -0.358, P < 0.001); sense of coherence significantly positively predicted adherence to functional exercise (β = 0.177, P < 0.01); self-regulatory fatigue significantly negatively predicted adherence to functional exercise (β = -0.324, P < 0.001) . Using Bootstrap resampling with 5,000 iterations, we further examined the chained mediating effects of sense of coherence and self-regulatory fatigue. The results revealed a significant chained mediating effect between sense of coherence and self-regulatory fatigue, with an effect size of -0.095. This chained mediation accounted for 53.85% of the total effect. Specifically, the mediating effect comprised indirect effects generated through three pathways: illness perception→ Sense of coherence → Functional exercise adherence, with an indirect effect value of -0.101. The 95% confidence interval (CI) bounds were (-0.167 to -0.036), excluding zero, confirming the mediating effect of sense of coherence . This path accounted for 19.42% of the total effect. Path ②: Illness perception → Self-Regulatory Fatigue → Functional Exercise Adherence. The indirect effect value was -0.084, with a 95% confidence interval of (-0.121, -0.052), which did not include zero. This indicates that the mediating effect of self-regulatory fatigue was established, accounting for 16.15% of the total effect. Path ③: Illness perception → Sense of coherence → Self-regulatory fatigue → Functional exercise adherence. The indirect effect value was -0.095, with a 95% confidence interval of (-0.136, -0.058), which did not include zero. This indicates that the chained mediating effect of sense of coherence and self-regulatory fatigue is established. The indirect effect of this path accounted for 18.27% of the total effect. This indicates that 18.27% of the total effect of illness perception on functional exercise is mediated through the chained mediating effects of sense of coherence and self-regulatory fatigue. For details, see Tables 7 and 8, and Figure 1. Table 7 Analysis of the mediating effects of sense of coherence and regulatory fatigue on illness perception and exercise adherence Result variable Predictor variable β t Lower limit Upper limit R 2 F Sense of coherence Illness perception -0.856 -34.190*** -1.064 -0.949 0.733 1168.934 Self-regulatory fatigue Illness perception 0.387 8.292*** 0.263 0.427 0.754 648.907 Sense of coherence -0.513 -11.002*** -0.459 -0.320 Functional exercise adherence Illness perception -0.358 -6.079*** -0.317 -0.162 0.663 276.871 Sense of coherence 0.177 2.848** 0.031 0.170 Self-regulatory fatigue -0.324 -5.701*** -0.327 -0.159 Note: ** indicates P < 0.01, ***indicates P < 0.001 Table 8 Testing the Mediating Effects of Psychological Coherence and Regulatory Fatigue on Illness Perception and Exercise Adherence Path Effect value SE Lower limit Upper limit Effect Proportion Total effect -0.520 0.020 -0.560 -0.480 Direct effect -0.240 0.039 -0.317 -0.162 46.15% Indirect effect ① X→M 1 →Y -0.101 0.034 -0.167 -0.036 19.42% Indirect effect ② X→M 2 →Y -0.084 0.018 -0.121 -0.052 16.15% Indirect effect ③ X→M 1 →M 2 →Y -0.095 0.019 -0.136 -0.058 18.27% Total indirect effect -0.280 0.035 -0.347 -0.211 53.85% The model shows the direct and indirect paths: ① Illness perception directly affects functional exercise adherence (β = -0.358 ); ② Illness perception affects functional exercise adherence through sense of coherence (β = -0.101); ③ Illness perception affects functional exercise adherence through self-regulatory fatigue (β = -0.084); ④ Illness perception affects functional exercise adherence through the chain of sense of coherence → self-regulatory fatigue (β = -0.095). All mediating effects were statistically significant (95% CI excluding 0). 4. Discussion This study examined the mechanisms through which illness perception influences adherence to functional exercise in stroke patients with focusing on the potential chain mediating roles of sense of coherence and self-regulatory fatigue. The most significant contribution of this study lies in demonstrating the mediation pathway of sense of coherence and regulatory fatigue on illness perception and exercise adherence. The following sections provide a detailed discussion of the findings. 4.1 the state of the variables The findings of this study indicate that the functional exercise adherence score among stroke patients was a moderate level. This result is consistent with the findings of Wu et al. [ 38 ] and Lan et al. [ 39 ], and slightly higher than the adherence scores reported by Zhou et al. [ 40 ] for elderly stroke patients.. The illness perception score was at the moderate level which was consistent with the results reported by Wu. et al. [ 38 ] in Chinese stroke patients. Among the illness perception subdimensions, the ‘perception’ dimension scored highest, aligning with findings by He et al. [ 41 ]. The sense of coherence scale revealed a mean score among stroke patients, indicating a moderate level. This aligns with previous studies by Li et al. [ 42 ] and Fu et al. [ 43 ] on sense of coherence in stroke patients. This suggested that healthcare providers can enhance patients' sense of coherence by encouraging family and friend accompaniment, establishing supportive medical teams, and improving illness management capabilities, thereby strengthening their psychological adaptability [ 44 , 45 ]. Patients can be encouraged to focus on incremental progress in functional exercises, thereby boosting their rehabilitation hope and finding meaning in overcoming illness [ 46 , 47 ]. Patients' self-regulatory fatigue scores averaged, consistent with studies by Zhang et al. [ 25 ] and Liu et al. [ 48 ], indicating an overall moderately high level. Research indicates [ 49 , 50 ] that self-regulatory fatigue diminishes patients’ motivation for illness management, thereby impacting prognosis and reducing quality of life. Healthcare providers should engage in regular communication with patients to understand their psychological dynamics. Employing cognitive behavioral therapy can help patients develop accurate perceptions of their illness and rehabilitation process, alleviate anxiety and other negative emotions, reduce psychological burden, and lower self-regulatory fatigue levels [ 51 ]. 4.2 the analysis of the relationships among illness perception and adherence to functional exercise of stroke patients Firstly, the results showed that illness perception among stroke patients was negatively correlated with sense of coherence; positively correlated with self-regulatory fatigue and negatively correlated with functional exercise adherence, supporting Hypothesis. This study confirms significant pairwise correlations among the four core variables. First, illness perception and sense of coherence among stroke patients exhibit a significant negative correlation, consistent with previous scholarly findings [ 52 ]. Patients with more negative perceptions of their illness often lack confidence in illness progression and functional rehabilitation, believing they cannot effectively cope with changes brought by the disease, resulting in low sense of coherence. Dou et al. [ 53 ] also noted that patients with negative illness perceptions tend to view the illness as a severe threat to themselves, perceiving life as filled with uncertainty and uncontrollability, leading to decreased sense of coherence. Second, patients' illness perception showed a significant positive correlation with regulatory fatigue, similar to findings by Xiao et al. [ 54 ]. Patients with high illness perception scores often perceive bleak rehabilitation prospects, experience more negative emotions, and are more prone to fatigue. International scholars like De Gucht et al. [ 55 ] also noted that patients with more negative illness perceptions typically exhibit higher fatigue levels. Once self-regulatory fatigue emerges, patients’ self-regulatory abilities diminish, making it difficult to cope with disease-related stress and challenges. This further reinforces negative perceptions of the disease, creating a vicious cycle that continuously strengthens the positive correlation between the two factors. Third, patients' illness perception is negatively correlated with functional exercise adherence, consistent with previous domestic and international research findings [ 56 , 57 ]. Slark et al. [ 58 ] suggest that reasonable illness cognition promotes the adoption of healthy behaviors, whereas excessively negative illness perceptions undermine patients' confidence in treatment and reduce their adherence levels. Patients with negative illness perceptions often view post-stroke limb dysfunction as irreversible, doubt the rationality of functional exercise, and lose intrinsic motivation to participate. Fourth, patients' sense of coherence shows a significant negative correlation with self-regulatory fatigue. Patients with high sense of coherence believe they can cope with stress more effectively and possess stronger self-regulatory abilities, resulting in lower self-regulatory fatigue levels. Moreover, individuals with high sense of coherence typically hold more positive cognitions, believing functional exercises are meaningful for illness recovery, which further reduces self-regulatory fatigue. Furthermore, research by Zhan et al. [ 59 ] indicates that individuals with high sense of coherence are more inclined to adopt proactive and effective coping strategies to resolve problems. This approach helps reduce negative emotions, avoids unnecessary resource depletion, and consequently alleviates self-regulatory fatigue. Fifth, patients' sense of coherence levels showed a significant positive correlation with functional exercise adherence, consistent with findings from domestic scholars Lü et al. [ 60 ]. Zhou et al. [ 19 ] also demonstrated that patients with higher sense of coherence exhibit greater medication adherence. Those possessing higher sense of coherence can more actively comprehend their illness and rehabilitation process, overcome various difficulties in functional exercise, and achieve rehabilitation goals. Sixth, self-regulatory fatigue is negatively correlated with functional exercise adherence, consistent with the findings of Sun et al. [ 61 ] in chronic heart failure patients. Related studies indicate that patients with high self-regulatory fatigue are more prone to procrastination, interruption, or even abandonment when facing tasks [ 60 , 62 ]. In this study, stroke patients require long-term self-regulatory to perform functional exercise tasks, continuously depleting their psychological resources. Once this depletion exceeds their recovery capacity, they enter a state of self-regulatory fatigue, leading to diminished willpower and concentration, and consequently lower functional exercise adherence levels. 4.3 Mediation analysis 4.3.1 Independent mediating effects of sense of coherence and regulatory fatigue The findings of this study indicate that sense of coherence and self-regulatory fatigue partially mediate the relationship between illness perception and adherence to functional exercise. Sense of coherence influences patients' attitudes and beliefs toward functional exercise, playing a significant buffering and moderating role in negative illness perception and health behaviors. Previous research by Li et al. [ 63 ] also demonstrated that individuals with high sense of coherence exhibit more positive attitudes and better health behaviors when coping with stressors such as illness events. Self-regulatory plays a crucial role in illness perception and coping behaviors, consistent with previous scholarly findings [ 54 ]. When patients experience severe negative illness perceptions, they incur greater psychological stress and consume mental resources, leading to self-regulatory fatigue that subsequently impacts their coping strategies. Furthermore, patients with negative illness perceptions often experience heightened negative emotions and psychological burdens. This leads to greater resource depletion during self-regulatory, increasing susceptibility to regulatory fatigue and consequently reducing adherence to functional exercise programs. 4.3.2 Chain Mediating Effect of Psychological Coherence and Self-regulatory Fatigue The findings also reveal a chain mediation effect between sense of coherence and self-regulatory fatigue on illness perception and functional exercise adherence among stroke patients. Stroke patients' illness perception influences their sense of coherence levels, which in turn generates self-regulatory fatigue, ultimately affecting exercise adherence. According to Lazarus's stress and coping theory, individuals facing illness engage in cognitive appraisal to assess their coping capacity, subsequently adopt coping strategies, and ultimately influence health outcomes [ 64 ]. Perception of illness reflects an individual's cognitive understanding of the disease, while sense of coherence reflects their assessment of coping abilities and resources. An individual's cognitive evaluation influences coping behaviors, and the coping process itself involves depletion of personal resources. These factors ultimately affect the level of functional exercise adherence, i.e., health outcomes. In this study, patients with low illness perception scores demonstrated accurate perceptions of illness recovery and prognosis. Conversely, those with high sense of coherence levels more effectively integrated illness information, enabling better adaptation to functional exercise. This adaptation reduced the depletion of self-regulatory resources during exercise, thereby maintaining higher functional exercise adherence. Patients with higher illness perception scores often harbor excessive negative perceptions of their illness, lowering their sense of coherence. Individuals with low sense of coherence perceive illness progression as uncontrollable and functional exercise as meaningless. This leads to insufficient resources for self-regulatory in subsequent self-control behaviors, ultimately resulting in decreased adherence to functional exercise. This suggests clinicians should not only foster positive illness cognition but also prioritize enhancing individual sense of coherence and managing self-regulatory fatigue. Providing personalized illness information and rehabilitation guidance can help patients better understand their condition and recovery process, thereby establishing accurate illness cognition. Additionally, encouraging active patient involvement in rehabilitation decisions enhances their sense of control over the recovery process, improving sense of coherence. Designing phased functional exercise plans for patients can reduce self-regulatory fatigue, ultimately improving exercise adherence and accelerating recovery. 4.4 Limitations There are some limitations in this study. First, the cross-sectional survey design collected static data, failing to capture dynamic changes or reveal causal relationships among variables. Future longitudinal studies are needed to explore these aspects further. Second, this study relied solely on questionnaires to assess post-stroke patients' psychological status and exercise adherence levels. Future research could incorporate smart devices for real-time tracking of patients' psychological states and adherence behaviors, quantifying findings to enhance data objectivity. Third, this study employed convenience sampling, surveying patients from only two hospitals in Henan Province. Generalizing the findings to a broader population may be limited. Subsequent research is recommended to expand in two dimensions: increasing sample size to enhance statistical power; considering a multicenter collaborative approach to conduct large-scale surveys across different regions and healthcare institutions. This would enhance the representativeness and generalizability of findings, enabling more comprehensive validation of current conclusions and providing a stronger empirical foundation for theoretical development. 5. Conclusion This study found that stroke patients have moderate levels of illness perception, sense of coherence and functional exercise adherence, and a moderate-to-high level of self-regulatory fatigue, and there are significant pairwise correlations among the four variables. Functional exercise adherence of stroke patients is affected by multiple factors, including age, monthly household per capita income, primary caregiver, number of stroke episodes, number of chronic comorbidities, self-care ability, illness perception, sense of coherence, and self-regulatory fatigue. Notably, illness perception not only has a direct negative predictive effect on functional exercise adherence, but also exerts an indirect influence through three pathways: single mediation of sense of coherence, single mediation of self-regulatory fatigue, and chain mediation of sense of coherence and self-regulatory fatigue. Clinical nursing staff should focus on the psychological characteristics and exercise adherence status of stroke patients, take targeted intervention measures to help patients establish a rational illness perception, enhance their sense of coherence, alleviate self-regulatory fatigue, and thus improve their adherence to functional exercise, promote limb function recovery, and improve the rehabilitation prognosis of stroke patients. Future research should adopt a longitudinal design and multi-center sampling to further verify the causal relationship and chain mediation mechanism among variables, and provide more comprehensive empirical evidence for the clinical rehabilitation of stroke patients. Declarations Ethics approval and consent to participate: This study protocol received ethical approval from the Ethics Committee of Henan University (Approval No. HUSOM2024-573). We declare that the research was performed in accordance with relevant regulatory and conformed to the provisions of the Declaration of Helsinki. Written informed consent was obtained from all participants prior to their inclusion in the study. Consent for publication: Not applicable. Availability of data and materials The datasets supporting the conclusions of this article are included within the article. Competing interests The authors declare that they have no competing interests. Funding: This research was supported by Henan Provincial Department of Science and Technology Key project (Grant NO. 242102310252, Grant NO. 252102311067), and Henan University Youth Cross Fund General (Grant NO. S23060Y). Authors' contributions FLL: conception, design of the work, method and statistical analysis, drafting the initial manuscript. YFX: data collection, analysis, interpretation of data. JCW: data collection, interpretation of data. TTK and CZT: data collection and revision of the initial manuscript. JL: data collection and revision of the initial manuscript. JXD: design of the work, data analysis, interpretation of data and revision of article. All authors reviewed the manuscript. Acknowledgement We extend our sincere appreciation to all members that contributed to this research. Clinical trial number Not applicable. References Group Report On Stroke Center. Summary of China Stroke Center Report 2022. Chin J Cerebrovasc Dis. 2024;21(8):565-76. Salvalaggio S, Cacciante L, Maistrello L, et al. Clinical predictors for upper limb recovery after stroke rehabilitation: retrospective cohort study[J]. Healthcare (Basel), 2023, 11(3). Lozano R, Naghavi M, Foreman K, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010[J]. Lancet, 2012,380(9859):2095-2128. Ma LY, Wang ZW, Fan J, et al. 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Relationship between illness perception and self-management behavior in breast cancer-related lymphedema patients and its mediating effect [Master's thesis]. Henan University; 2024. Folkman S, Lazarus R S, Gruen R J, et al. Appraisal, coping, health status, and psychological symptoms[J]. J Pers Soc Psychol, 1986,50(3):571-579. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9146399","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":626182238,"identity":"d3c2383e-32f1-4ac4-b2fd-3a497bc1e170","order_by":0,"name":"Fangli Liu","email":"","orcid":"","institution":"Henan University","correspondingAuthor":false,"prefix":"","firstName":"Fangli","middleName":"","lastName":"Liu","suffix":""},{"id":626182239,"identity":"f57812c0-f9b9-422d-8c34-999d64ed09fb","order_by":1,"name":"Yufen Xue","email":"","orcid":"","institution":"Henan University","correspondingAuthor":false,"prefix":"","firstName":"Yufen","middleName":"","lastName":"Xue","suffix":""},{"id":626182241,"identity":"ec73bd6b-b6e1-4119-a688-25ebc0940244","order_by":2,"name":"Jiachi Wang","email":"","orcid":"","institution":"Henan University","correspondingAuthor":false,"prefix":"","firstName":"Jiachi","middleName":"","lastName":"Wang","suffix":""},{"id":626182245,"identity":"c109f2e7-dc0f-42e3-bcf6-44e841820ba8","order_by":3,"name":"Tengteng Kang","email":"","orcid":"","institution":"Universiti Sains Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Tengteng","middleName":"","lastName":"Kang","suffix":""},{"id":626182247,"identity":"bdc3eba3-7a77-467e-a77d-440902b3b7aa","order_by":4,"name":"Cunzhe Tong","email":"","orcid":"","institution":"Henan University","correspondingAuthor":false,"prefix":"","firstName":"Cunzhe","middleName":"","lastName":"Tong","suffix":""},{"id":626182249,"identity":"7cf41a9b-0cb3-4011-9080-7b960a987d88","order_by":5,"name":"Jing Liu","email":"","orcid":"","institution":"Henan University","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Liu","suffix":""},{"id":626182250,"identity":"8a1365f8-b428-412d-aa4b-2e2a652ce2e0","order_by":6,"name":"Jiexin Deng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYDCCA0AsYcDAwMbAfAwqlEC0FrY0ErRAAI8ZcVr4jvcefmFRYJPYJ93z7cHHHYcZ+NlzDBh+7sCtRfLMuTQLCYM0YzaZs9sNZ545zCDZ88aAsfcMbi0GN3LMDCQMDsuxSeRuk+ZtOwwSMWBmbMOj5f4bkJb/PGwSOc+k/wK12BPUcoPH+IGEwQGgLTls0owgWyQIaJE8k2MGDORkYzaJNDPJ3rZ0HokzzwoO9uLRwnf8jPFniT92ifNnJD+T+NlmLcffnrzxwU88WoCATVoCiccDIg7g1cDAwPzxAwEVo2AUjIJRMMIBAD3mTOmB5+WeAAAAAElFTkSuQmCC","orcid":"","institution":"Henan University","correspondingAuthor":true,"prefix":"","firstName":"Jiexin","middleName":"","lastName":"Deng","suffix":""}],"badges":[],"createdAt":"2026-03-17 08:53:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9146399/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9146399/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107520010,"identity":"d1406fbc-457a-40f8-b0b4-2b51dd348f35","added_by":"auto","created_at":"2026-04-22 08:58:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":72799,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of the chain mediation effect of sense of coherence and regulatory fatigue on illness perception and exercise adherence\u003c/p\u003e\n\u003cp\u003eNote: **\u003cem\u003e indicates P \u0026lt; 0.01, ***indicates P \u0026lt; 0.001\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9146399/v1/1b3d5da865bc8ccf65771028.png"},{"id":109430322,"identity":"a15c3e0c-9cb0-4850-9cc8-7c1995f02953","added_by":"auto","created_at":"2026-05-18 04:25:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":555346,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9146399/v1/c624c23c-62df-498f-a2ed-e92ab9857447.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The relationship between illness perception and adherence to functional exercise in stroke patients: the chain mediating role of sense of coherence and self-regulatory fatigue","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eStroke is an acute neurological deficit syndrome caused by impaired cerebral blood circulation, characterized by high incidence, high disability rate, and significant economic burden [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. According to World Health Organization (WHO) statistics, approximately 15\u0026nbsp;million people worldwide suffer from stroke annually, with nearly 6\u0026nbsp;million deaths [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The latest findings from China's Cardiovascular Health and Disease Report indicate that the country currently has 13\u0026nbsp;million stroke patients, with new stroke cases increasing year by year [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Among stroke survivors, approximately 30% to 70% suffer from varying degrees of limb motor dysfunction, imposing a huge burden on families and society [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFunctional exercise refers to a therapeutic method whereby individuals accelerate the recovery of bodily functions through scientific physical training [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. \u003cem\u003eThe Global Manual for Prevention and Control of Cardiovascular and Cerebrovascular Diseases\u003c/em\u003e clearly points out that insufficient functional exercise is a primary cause of recurrence in stroke patients and delayed recovery of limb function [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Numerous studies have demonstrated a close association between the degree of limb function improvement and adherence to functional exercise[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. According to the WHO definition, adherence refers to the consistency between patients' health behaviors and the diagnosis, treatment, and health management plans formulated by medical staff, which not only includes medication compliance but also behavioral cooperation in rehabilitation training, dietary management and other aspects [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In this study, functional exercise adherence in stroke patients refers to the degree to which their exercise behaviors align with healthcare professionals' recommended exercise regimens to promote limb function recovery. Research has concluded that patients with high functional exercise adherence exhibit a lower risk of recurrence compared to those with low adherence, along with a significant reduction in readmission rates [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Therefore, focusing on the level of functional exercise adherence in stroke patients and investigating the factors influencing their adherence behavior holds significant importance for promoting limb function recovery and improving the long-term prognosis of stroke patients..\u003c/p\u003e \u003cp\u003eA growing body of evidence indicates thats illness perception is a key psychological factor influencing patient\u0026rsquo;s health behaviors and treatment adherence [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Illness perception is defined as an individual's subjective cognition and evaluation of the severity, course, and prognosis of their own disease, which reflects the individual's subjective understanding and emotional response to the disease [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Yin et al.[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] found that illness perception is an independent influencing factor of rehabilitation exercise adherence in stroke patients with dysphagia. Therefore, patients with a positive illness perceptions generally possess accurate understanding of illness progression and outcomes, which facilitates improved adherence levels.\u003c/p\u003e \u003cp\u003eSense of coherence reflects an individual's overall perception and experience of life, serving as a key predictor of health-promoting behaviors such as treatment and exercise adherence [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. study indicates that higher level of sense of coherence correlate with more proactive health-promoting behaviors and better treatment adherence [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, sense of coherence is influenced by illness perception; patients with negative illness perception tend to have a lower level of sense of coherence [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In clinic practice,due to the lack of a rational understanding of the disease, such patients cannot develop effective coping strategies, leading to heightened uncertainty and anxiety about stoke and consequently lower sense of coherence[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In sum, it is meaningful to detect the effect of Sense of coherence between illness perception and functional exercise adherence.\u003c/p\u003e \u003cp\u003eStroke patients in the rehabilitation stage face heavy rehabilitation training tasks and great psychological pressure making them prone to self-regulatory fatigue. Proposed by Baumeister et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], self-regulatory fatigue refers to a state of psychological exhaustion caused by the continuous consumption of mental resources due to prolonged self-control behaviors, which leads to the decline of individual cognitive, emotional and behavioral regulatory abilities. In this study, self-regulatory fatigue in stroke patients specifically refers to the psychological exhaustion state caused by the consumption of limited mental resources during the process of adhering to functional exercise, which is manifested as the reduction of self-regulatory ability and willingness to perform exercise. Self-regulatory fatigue can impair individuals' behavioral control abilities and lowers adherence to health behaviors [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Research indicates that positive illness perceptions among patients can mitigate the occurrence of self-regulatory fatigue to a certain extent [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Zhang et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] surveyed 199 stroke patients in the rehabilitation phase, revealing moderate-to-high levels of self-regulatory fatigue. Similar findings emerged from Shen et al.'s [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] study of 330 stroke patients. Conversely, Xu et al.'s [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] investigation among elderly stroke patients indicated elevated levels of self-regulatory fatigue. Liu et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] studied 254 stroke patients and found their self-regulatory fatigue was moderately high, directly impacting self-management levels. Pan et al. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] demonstrated that self-regulatory fatigue is a significant factor affecting patients' quality of life. Additional research indicates a positive correlation between self-regulatory fatigue and functional exercise after stroke[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdherence to function Exercise plays a crucial role in stroke patients' rehabilitation. Illness perception, sense of coherence, and self-regulatory fatigue are considered key influencing factors of patients' functional exercise adherence behaviors. However, existing studies predominantly examine pairwise relationships, and the interrelationships among these four factors warrant further investigation. Therefore, guided by the Stress and Coping Theory, this study constructs a theoretical model to deeply explore the underlying mechanisms and specific pathways through which illness perception, sense of coherence, and self-regulated fatigue influence functional exercise adherence in stroke patients. The model will be validated, aiming to provide new insights and references for enhancing functional exercise adherence levels and promoting early recovery in stroke patients.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Research Hypothesis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study proposes the following research hypotheses and constructs a chained mediation theoretical model diagram.\u003c/p\u003e\n\u003cp\u003e• H1: \u0026nbsp;illness perception was an influencing factor for functional exercise adherence among stroke patients.\u003c/p\u003e\n\u003cp\u003e• H2: Sense of coherence exerts a mediating effect between perceived illness and functional exercise adherence.\u003c/p\u003e\n\u003cp\u003e• H3: Self-regulatory fatigue exerts a mediating effect between perceived illness and functional exercise adherence.\u003c/p\u003e\n\u003cp\u003e• H4: Sense of coherence and self-regulatory fatigue exert a chain-mediated effect between perceived illness and functional exercise adherence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Study Design\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional descriptive study design was used in this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Study Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, from February 2025 to September 2025, stroke patients undergoing follow-up examinations at the neurology outpatient departments of two general hospitals in Henan Province were selected using convenience sampling.\u003c/p\u003e\n\u003cp\u003eInclusion criteria: (1) All subjects must be ≥18 years of age; (2) Meet the diagnostic criteria for stroke outlined in the 2019 Chinese Diagnostic Guidelines for Major Cerebrovascular Diseases; (3) Confirmed diagnosis of stroke via imaging studies such as cranial computed tomography (CT) or magnetic resonance imaging (MRI); (4) Within 2–4 weeks after discharge from hospital; (5) Residual limb dysfunction with muscle strength ≤ Grade 4 post-stroke; (6) Patients must be conscious with adequate comprehension and communication abilities.\u003c/p\u003e\n\u003cp\u003eExclusion criteria: (1) Patients with psychiatric disorders or cognitive impairment; (2) \u0026nbsp;Concurrent severe comorbidities such as organ dysfunction, respiratory failure, or malignant tumors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size estimation\u003c/strong\u003e: Based on sample size estimation methods, a rough calculation is performed using 5 to 10 times the number of dependent variables [31]. This study involved 25 variables: (13 items in the general information questionnaire, 3 dimensions from the illness perception questionnaire, 3 dimensions from the sense of coherence scale, 3 dimensions from the self-regulatory fatigue scale, and 3 dimensions from the stroke patient functional exercise adherence scale). Taking 10 times the number of variables(n=250), and considering a 10%-20% sample attrition rate. The required sample size ranged from 275 to 300, with a total of 427 cases included in the study. stroke patients undergoing follow-up examinations at the neurology outpatient departments of two tertiary-grade hospitals in Henan Province were investigated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Research Instruments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4.1 Functional Exercise Adherence Scale for Stroke Patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Functional Exercise adherence Scale for Stroke Patients developed by Lin et al. [32] in 2013 was employed for this survey. The scale includes 3 dimensions with 14 items: Functional Exercise adherence (8 items, Items 1–8), effect monitoring adherence (3 items, Items 9–11), and advice-seeking adherence (items 12–14). All items were scored positively using a 4-point Likert scale, yielding a total score range of 14 to 56 points. The adherence index is calculated as adherence Index = (adherence Score / 56) × 100, The adherence level is divided into three grades: High level( 76–100 points); Moderate level(51–75 points) and Low level: (1–50 points) \u0026nbsp;A Higher adherence index indicates better patient adherence to functional exercise. In this study, the scale demonstrated a Cronbach’s α coefficient of\u0026nbsp;the scale was\u0026nbsp;0.847,\u0026nbsp;indicating good internal consistency reliability..\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4.2 General Information Questionnaire\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA customized general information questionnaire was developed for this study, comprising two sections: general demographic data and disease-related information. Within the disease-related section, patients' self-care abilities were assessed using the Barthel Index (BI), primarily evaluating two domains: self-care activities and mobility-related activities. This includes 10 items: eating, bathing, bowel and bladder control, transferring between bed and chair, walking on level ground, climbing stairs, dressing, personal hygiene, and using the toilet. The total score is out of 100 points. Based on BI scores, patients were categorized into four dependency levels: Severe dependency (0–40 points); Moderate dependency (41–60 points); Mild dependency (61–99 points) and Independent (100 points). Higher scores indicate greater functional independence [33].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4.3 Brief Illness Perception Questionnaire\u003c/strong\u003e (B-IPQ)\u003c/p\u003e\n\u003cp\u003eThe survey employed the Brief Illness Perception Questionnaire developed by Broadbent et al. [34]. The questionnaire comprises three dimensions: five items measuring illness perception (Items 1- 5), two items assessing emotional state (Items 6, 8), and one item evaluating illness understanding (Item 7), along with an open-ended question (listing in order the three most significant factors contributing to illness). Scoring used a 0–10, 11-point scale. The sum of item scores constituted the patient's total illness perception score. Items 3, 4, and 7 were reverse-scored. The total scale score ranged from 0 to 80, with higher scores indicating greater severity of illness perception. In this study, the Cronbach's α coefficient for the scale was 0.767, indicating acceptable internal consistency reliability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4.4\u0026nbsp;\u003c/strong\u003eSense of Coherence Scale (SOC-13)\u003c/p\u003e\n\u003cp\u003eThe Chinese version of the SOC-13, translated by domestic scholars including Bao et al. [35], was employed for this study. The scale comprises 13 items across three dimensions: sense of comprehensibility, sense of manageability, and sense of meaning. The dimensions comprise: \u0026nbsp; Sense of Comprehensibility (5 items, Items 2, 6, 7, 8, 12); \u0026nbsp;manageability (4 items, Items 3, 4, 5, 10), and meaningfulness (4 items, Items 1, 9, 11, 13). \u0026nbsp;All items are scored using a 7-point Likert scale (1 = completely inconsistent, 7 = completely consistent), with Items 1, 2, 3, 8, and 13 being reverse-scored. The total score ranges from 13 to 91 points,, with a \u0026nbsp;higher score indicate greater sense of coherence. In this study, the Cronbach’s α coefficient for the scale was 0.903, , indicating excellent internal consistency reliability..\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4.5 Self-regulatory of Fatigue Scale\u0026nbsp;\u003c/strong\u003e(SRFS)\u003c/p\u003e\n\u003cp\u003eThe Chinese version of the SRFS revised by Wang et al. [36] was used to evaluate the level of self-regulatory fatigue in stroke patients. The scale includes 16 items and 3 dimensions: cognitive control fatigue (6 items, Items 1, 2, 3, 5, 11, 13); emotional control fatigue (5 items, Items 7, 9, 12, 14, 15); and behavioral control fatigue (5 items, Items 4, 6, 8, 10, 16). All items are scored using a 5-point Likert scale (1 = completely inconsistent, 5 = completely consistent), with Items 1, 2, 5, 9, and 14 being reverse-scored. The total score ranges from 16 to 80 points, with a higher score indicating a more severe level of self-regulatory fatigue. In this study, the Cronbach's α coefficient of the scale was 0.849, indicating good internal consistency reliability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Data Collection\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData collection took place from February 2025 to September 2025 All researchers and data collectors received standardized training before the study, including the research purpose, questionnaire instructions, and quality control measures. With the approval of the director of the neurology department and the head nurse of the participating hospitals, the investigators screened eligible stroke patients at the neurology outpatient department. Before the questionnaire survey, the investigators fully explained the research purpose, content, and confidentiality measures to the participants and their families, and obtained written informed consent from the participants who agreed to participate in the study.\u003c/p\u003e\n\u003cp\u003eThe questionnaires were distributed on the spot, and . Participants who could complete the questionnaire independently filled it out by themselves, and for those who could not (e.g., due to limb dysfunction), the investigators read the questionnaire items and options aloud and recorded the answers according to the participants' responses. All questionnaires were checked on the spot for completeness and validity. A total of 443 questionnaires were distributed in this study, and 427 valid questionnaires were recovered, with an effective recovery rate of 96.39%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDatabase construction was performed using Excel spreadsheets. Statistical analysis primarily employed the SPSS 25.0 statistical software package, supplemented by the Process v3.5 plugin for mediation effect analysis. The significance level was set at α=0.05, with P values less than 0.05 considered statistically significant.\u003c/p\u003e\n\u003cp\u003eDescriptive Analysis: Frequency distributions and percentages were used to describe demographic characteristics of the study subjects. Mean ± standard deviation (Mean±SD) was employed to report total scores and dimension-specific scores for variables including illness perception, sense of coherence, self-regulatory fatigue, and functional exercise adherence.\u003c/p\u003e\n\u003cp\u003eUnivariate Analysis: Independent samples t-tests or one-way ANOVA were selected based on data characteristics to compare differences in illness perception, sense of coherence, self-regulatory fatigue, and functional exercise adherence among stroke patients across various sociodemographic and disease-related factors.\u003c/p\u003e\n\u003cp\u003eCorrelation Analysis: Pearson correlation analysis was used to explore relationships among the four variables, including illness perception.\u003c/p\u003e\n\u003cp\u003eMultivariate Analysis: Multiple linear regression analysis examined the influence of variables with significant P\u0026lt;0.05 in univariate analysis, along with illness perception, self-regulatory fatigue, and sense of coherence, on functional exercise adherence in stroke patients.\u003c/p\u003e\n\u003cp\u003eMediation Analysis: Based on the research hypothesis, functional exercise adherence in stroke patients was set as the dependent variable (Y). Illness perception served as the independent variable (X), while sense of coherence and self-regulatory fatigue acted as mediating variables (M1, M2). Models 4 and 6 of the Process v3.5 plugin in SPSS 25 software were employed to analyze the mediating effects of sense of coherence and self-regulatory fatigue on the relationship between illness perception and functional exercise adherence (Model 4 analyzed single mediation effects, while Model 6 assessed chained mediation effects). 6 models (Model 4 for single mediation and Model 6 for chain mediation) to analyze the mediating effects and chain mediation effects of sense of coherence and self-regulatory fatigue between illness perception and exercise adherence. Bootstrap tests were employed to validate the mediation effects.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Participants Characteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.1 Demographic Data of Stroke Patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study investigated 427 Stroke patients, including 297 males (69.56%) and 130 females (30.44%). The average age was (63.10 \u0026plusmn; 11.36) years old，of which 158 cases (37.00%) were \u0026le; 60 years old and 269 cases (63.00%) were \u0026gt; 60 years old. The majority had a high school or technical secondary education background, totaling 154 cases (36.07%); Most were retired, totaling 213 cases (49.88%); Monthly income ranged mostly between 1000-3000 yuan, with 207 cases (48.48%), followed by 3,001-5,000 yuan, totaling 116 cases (27.17%); 261 cases (61.12%) resided in urban areas; the primary caregiver was the spouse in 195 cases (45.67%). Detailed sociodemographic characteristics of the study subjects are presented in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e General information of stroke patients (\u003cem\u003en\u003c/em\u003e=427)\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"662\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eClassification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eProportion (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u0026le;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e37.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e＞60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e63.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e69.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e30.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e88.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eNo spouse (single/divorced/widowed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e11.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eElementary school and below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e17.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e26.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eHigh school or technical secondary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e36.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eCollege and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e20.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eWorking condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eOn duty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e10.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e49.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eOff duty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e39.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eMonthly income per capita\u003c/p\u003e\n \u003cp\u003e(yuan)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u0026lt;1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e14.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e1000~3000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e48.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e3001~5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e27.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u0026gt;5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e10.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003ePlace of residence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e61.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e38.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003ePrimary caregiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eSpouse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e45.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eChildren\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e27.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eOther individuals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e27.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eMedical payment method\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eEmployee Medical Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e52.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eResident Medical Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e45.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eSelf-pay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.2 Disease-Related Data for Stroke Patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData on stroke patients indicate that the predominant stroke type was ischemic, accounting for 301 cases (70.49%); most were first-time strokes, totaling 309 cases (72.37%); 209 patients (48.95%) had one chronic condition, while 44.5% had two or more chronic conditions; Detailed characteristics of the study subjects\u0026apos; disease-related information are presented in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003eDisease-related data of stroke patients (\u003cem\u003en\u003c/em\u003e=427)\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"662\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 255px;\"\u003e\n \u003cp\u003eClassification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eProportion (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eTypes of stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eHemorrhagic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e29.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eIschemic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e70.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eNumber of strokes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eFirst time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e72.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eSecond time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e21.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eThird time and beyond\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e5.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eNumber of chronic conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e6.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e48.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e36.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e7.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eSelf-care ability (Barthel Index)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eMild Dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e14.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eModerate Dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e39.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eSevere Dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e45.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Current Status of Functional Exercise Adherence, Illness perception, Psychological Coherence, and Self-regulatory of Fatigue Among Stroke Patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing a method based on skewness and kurtosis coefficients for normality testing, the results showed that the skewness coefficients for stroke patients\u0026apos; illness perception, sense of coherence, self-regulatory fatigue, and functional exercise adherence were -0.096, -0.003, 0.307, and -0.158, respectively; The kurtosis coefficients were -0.559, -0.796, -0.420, and -0.396, respectively, all falling within \u0026plusmn;1. According to relevant statistical research, skewness and kurtosis coefficients between -1 and +1 indicate acceptable normality [37].\u003c/p\u003e\n\u003cp\u003eThe scores of the four variables and the dimensions of functional exercise adherence are shown in Table 3; the total score of illness perception was moderate level(43.15 \u0026plusmn; 9.24); the total score of sense of coherence was moderate level(54.77 \u0026plusmn; 10.86); the total score of self-regulatory fatigue was moderate-to-high level (46.99 \u0026plusmn; 8.25) .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e The scores of Functional Exercise Adherence and its dimensions in stroke patients (n=427, Mean \u0026plusmn; SD)\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 409px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eNumber of entries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 127px;\"\u003e\n \u003cp\u003eMean\u0026plusmn;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 409px;\"\u003e\n \u003cp\u003eAdherence to Functional Exercise\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e21.24\u0026plusmn;3.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 409px;\"\u003e\n \u003cp\u003eAdherence to Effect Monitoring\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e6.80\u0026plusmn;1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 409px;\"\u003e\n \u003cp\u003eAdherence to Seeking Advice\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e6.26\u0026plusmn;1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 409px;\"\u003e\n \u003cp\u003eFunctional Exercise Adherence(total score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e34.30\u0026plusmn;6.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Analysis of differences in functional exercise adherence scores among stroke patients based on general demographic data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing independent samples t-tests or one-way analysis of variance, we investigated differences in functional exercise adherence scores among stroke patients across general demographic characteristics and disease-related information. Results revealed significant differences (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) in functional exercise adherence scores among stroke patients across various demographic categories, including age group, marital status, educational attainment, occupational status, household monthly income level, primary caregiver type, medical payment method, number of stroke episodes, number of comorbid chronic diseases, and level of self-care ability (Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e Univariate analysis of factors associated with functional exercise adherence in stroke patients (n=427)\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"643\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 183px;\"\u003e\n \u003cp\u003eClassification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 125px;\"\u003e\n \u003cp\u003eScore (Mean\u0026plusmn;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cem\u003et/F\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e\u0026le;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e35.54\u0026plusmn;6.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e3.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e＞60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e33.57\u0026plusmn;5.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e34.49\u0026plusmn;6.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e33.85\u0026plusmn;5.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e34.58\u0026plusmn;6.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eNo spouse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e32.06\u0026plusmn;6.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"4\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eElementary school and below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e32.09\u0026plusmn;5.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e11.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e32.84\u0026plusmn;6.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eHigh school/technical secondary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e34.99\u0026plusmn;5.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eCollege and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e36.85\u0026plusmn;6.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eWorking condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eOn duty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e37.07\u0026plusmn;6.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e13.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e35.06\u0026plusmn;6.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eOff duty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e32.57\u0026plusmn;5.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"4\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eMonthly income per capita\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e\u0026lt;1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e30.08\u0026plusmn;5.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e49.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e1000~3000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e32.55\u0026plusmn;4.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e3001~5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e37.47\u0026plusmn;5.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e\u0026gt;5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e39.89\u0026plusmn;6.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003ePlace of residence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e34.64\u0026plusmn;6.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e33.75\u0026plusmn;6.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003ePrimary caregiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eSpouse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e35.34\u0026plusmn;5.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e6.328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eChildren\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e34.01\u0026plusmn;6.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eOther individuals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e32.83\u0026plusmn;6.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eMedical payment method\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eEmployee Medical Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e34.97\u0026plusmn;6.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.780\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eResident Medical Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e33.60\u0026plusmn;6.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eSelf-pay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e32.22\u0026plusmn;10.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eTypes of stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eHemorrhagic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e33.83\u0026plusmn;5.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-1.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.310\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eIschemic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e34.49\u0026plusmn;6.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eNumber of strokes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eFirst time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e35.38\u0026plusmn;5.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e19.642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eSecond time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e31.38\u0026plusmn;5.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eThird time and beyond\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e31.80\u0026plusmn;8.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"4\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eNumber of chronic conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e36.29\u0026plusmn;4.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e10.598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e35.63\u0026plusmn;5.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e32.97\u0026plusmn;5.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e\u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e30.42\u0026plusmn;7.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eSelf-care ability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eMild Dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e38.48\u0026plusmn;4.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e74.237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eModerate Dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e36.51\u0026plusmn;5.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003eSevere Dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e31.07\u0026plusmn;5.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 Correlation analysis of illness perception, sense of coherence, self-regulatory of fatigue, and functional exercise adherence in stroke patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe result of Pearson correlation analysis shows that illness perception among stroke patients was negatively correlated with sense of coherence (r = -0.856, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01), positively correlated with self-regulatory fatigue (r = 0.827, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01), and negatively correlated with functional exercise adherence (r = -0.778, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01). Sense of coherence scores were negatively correlated with self-regulatory fatigue (r = -0.845, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01) and positively correlated with total functional exercise adherence scores (r = 0.758, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01). Self-regulatory fatigue was negatively correlated with functional exercise adherence (r = -0.770, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01) (Table 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e Pearson correlation coefficients among illness perception, sense of coherence, self-regulatory fatigue and functional exercise adherence (n=427)\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eIllness perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eSense of coherence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eSelf-regulatory fatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003eFunctional exercise adherence\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eIllness perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eSense of coherence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e-0.856**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eSelf-regulatory fatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.827**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e-0.845**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eFunctional exercise adherence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e-0.778**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e0.758**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e-0.770**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 126px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote:** \u003cem\u003eP\u003c/em\u003e＜0.01\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6 Multiple linear regression analysis of functional exercise adherence in stroke patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultiple linear regression analysis was further employed to explore predictors of functional exercise adherence among stroke patients. Functional exercise adherence was designated as the dependent variable in the regression model, while the independent variables comprised statistically significant factors identified in the univariate analysis. These included 10 variables from the demographic data\u0026mdash;such as age, marital status, and educational attainment\u0026mdash;along with illness perception, sense of coherence, and self-regulatory fatigue, which were incorporated into the multiple linear regression analysis.\u003c/p\u003e\n\u003cp\u003eBefore conducting multiple linear regression analysis, it is essential to test for multicollinearity among the variables. Statistically, a tolerance (T) below 0.1 and a variance inflation factor (VIF) above 10 are typically regarded as indicators of multicollinearity. In this study, all T values exceeded 0.1 and all VIF values remained below 10. This indicates that no multicollinearity issues exist among the study variables included in the multiple linear regression equation. Subsequently, the independent variables were assigned values according to the requirements of multiple linear regression.The assignment method was as follows. Marital status: married=0, no spouse=1; Education level: elementary school and below=1, Junior high school=2, High school/technical secondary school=3, College and above=4; Working condition: on duty=1, retirement=2, off duty=3;\u0026nbsp;Monthly income per capita: \u0026lt;1000=1, 1000~3000=2, 3001~5000=3, \u0026gt;5000=4; Primary caregiver: spouse=1, children=2, other individuals=3; Medical payment method: employee medical insurance=1, resident medical insurance=2, self-pay=3; Number of strokes:first time=1, second time=2, third time and beyond=3; Number of chronic conditions: 0=1, 1=2, 2=3, 3=4; Self-care ability: mild dependence=1, moderate dependence=2, severe dependence=3; Age, self-care ability, illness perception, sense of coherence, and self-regulatory fatigue scores were all included in the equation with the original values.\u003c/p\u003e\n\u003cp\u003eThe regression equation results indicate that monthly income per capita, primary caregiver, number of strokes, number of chronic conditions, self-care ability, self-regulatory fatigue, illness perception, and sense of coherence ultimately entered the regression equation. Together, these factors explain 72.3% of the total variance in functional exercise adherence among stroke patients. The regression model validation yielded an F-value of 82.999 with P \u0026lt; 0.001, confirming the model\u0026rsquo;s statistical significance. Among these factors, monthly income per capita, self-care ability, and sense of coherence positively predicted exercise adherence, while age, primary caregiver status, number of strokes, number of chronic conditions, self-regulatory fatigue, and illness perception negatively predicted adherence.（Table 6）\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6\u003c/strong\u003e Multiple linear regression analysis of functional exercise adherence in stroke patients\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"640\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eS.E.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eTolerance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eVIF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e42.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e4.201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e10.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-2.379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.839\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e1.192\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003eMonthly income per capita\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1.446\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e5.674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e1.806\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003ePrimary caregiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-2.614\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.860\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e1.162\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003eNumber of strokes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.804\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-2.784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.902\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e1.109\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003eNumber of chronic conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.472\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-2.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e1.130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003eSelf-care ability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e3.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.664\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e1.507\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003eSelf-Regulatory Fatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-4.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e4.481\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003eIllness Perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e-0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-0.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-4.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e4.864\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003ePsychological Coherence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e3.656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e5.064\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote：\u003cem\u003eF\u003c/em\u003e =82.999, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001; \u003cem\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e=0. 723, \u003cem\u003eAdjusted R\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e=0.714\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.7 Chain mediation analysis of sense of coherence and self-regulatory fatigue in the relationship between illness perception and functional exercise adherence among stroke patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing stroke patients\u0026rsquo; illness perception as the independent variable, sense of coherence (M1) and self-regulatory fatigue (M2) as mediating variables, and functional exercise adherence as the dependent variable, mediation analysis was conducted using Model 6 in the Process 3.5 plugin of SPSS 25. Results indicated that illness perception significantly negatively predicted sense of coherence (\u0026beta; = -0.856, P \u0026lt; 0.001); illness perception significantly positively predicted self-regulatory fatigue (\u0026beta; = 0.387, P \u0026lt; 0.001); sense of coherence significantly negatively predicted self-regulatory fatigue (\u0026beta; = -0.513, P \u0026lt; 0.001); Perceived illness significantly negatively predicted adherence to functional exercise (\u0026beta; = -0.358, P \u0026lt; 0.001); sense of coherence significantly positively predicted adherence to functional exercise (\u0026beta; = 0.177, P \u0026lt; 0.01); self-regulatory fatigue significantly negatively predicted adherence to functional exercise (\u0026beta; = -0.324, P \u0026lt; 0.001) .\u003c/p\u003e\n\u003cp\u003eUsing Bootstrap resampling with 5,000 iterations, we further examined the chained mediating effects of sense of coherence and self-regulatory fatigue. The results revealed a significant chained mediating effect between sense of coherence and self-regulatory fatigue, with an effect size of -0.095. This chained mediation accounted for 53.85% of the total effect. Specifically, the mediating effect comprised indirect effects generated through three pathways: illness perception\u0026rarr; Sense of coherence \u0026rarr; Functional exercise adherence, with an indirect effect value of -0.101. The 95% confidence interval (CI) bounds were (-0.167 to -0.036), excluding zero, confirming the mediating effect of sense of coherence . This path accounted for 19.42% of the total effect. Path ②: Illness perception \u0026rarr; Self-Regulatory Fatigue \u0026rarr; Functional Exercise Adherence. The indirect effect value was -0.084, with a 95% confidence interval of (-0.121, -0.052), which did not include zero. This indicates that the mediating effect of self-regulatory fatigue was established, accounting for 16.15% of the total effect. Path ③: Illness perception \u0026rarr; Sense of coherence \u0026rarr; Self-regulatory fatigue \u0026rarr; Functional exercise adherence. The indirect effect value was -0.095, with a 95% confidence interval of (-0.136, -0.058), which did not include zero. This indicates that the chained mediating effect of sense of coherence and self-regulatory fatigue is established. The indirect effect of this path accounted for 18.27% of the total effect. This indicates that 18.27% of the total effect of illness perception on functional exercise is mediated through the chained mediating effects of sense of coherence and self-regulatory fatigue. For details, see Tables 7 and 8, and Figure 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7\u0026nbsp;\u003c/strong\u003eAnalysis of the mediating effects of sense of coherence and regulatory fatigue on illness perception and exercise adherence\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eResult variable\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003ePredictor variable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eLower limit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eUpper limit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eSense of coherence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003eIllness perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e-0.856\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e-34.190***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e-1.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-0.949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.733\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e1168.934\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eSelf-regulatory fatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003eIllness perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e8.292***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.427\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e648.907\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003eSense of coherence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e-0.513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e-11.002***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e-0.459\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-0.320\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003eFunctional exercise adherence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003eIllness perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e-0.358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e-6.079***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e-0.317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e276.871\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003eSense of coherence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.848**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.170\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003eSelf-regulatory fatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e-0.324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e-5.701***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e-0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e-0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote: **\u003cem\u003e\u0026nbsp;indicates P \u0026lt; 0.01, ***indicates P \u0026lt; 0.001\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8\u0026nbsp;\u003c/strong\u003eTesting the Mediating Effects of Psychological Coherence and Regulatory Fatigue on Illness Perception and Exercise Adherence\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003ePath\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eEffect value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eLower limit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003eUpper limit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eEffect Proportion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003eTotal effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e-0.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e-0.560\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003eDirect effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e-0.240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e-0.317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e46.15%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003eIndirect effect ①\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eX\u0026rarr;M\u003csub\u003e1\u003c/sub\u003e\u0026rarr;Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e-0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e-0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e19.42%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003eIndirect effect ②\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eX\u0026rarr;M\u003csub\u003e2\u003c/sub\u003e\u0026rarr;Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e-0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e-0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e16.15%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003eIndirect effect ③\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eX\u0026rarr;M\u003csub\u003e1\u003c/sub\u003e\u0026rarr;M\u003csub\u003e2\u003c/sub\u003e\u0026rarr;Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e-0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e-0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e18.27%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003eTotal indirect effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e-0.280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e-0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e-0.211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e53.85%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eThe model shows the direct and indirect paths: ① Illness perception directly affects functional exercise adherence (\u0026beta; = -0.358\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e); ② Illness perception affects functional exercise adherence through sense of coherence (\u0026beta; = -0.101); ③ Illness perception affects functional exercise adherence through self-regulatory fatigue (\u0026beta; = -0.084); ④ Illness perception affects functional exercise adherence through the chain of sense of coherence \u0026rarr; self-regulatory fatigue (\u0026beta; = -0.095). All mediating effects were statistically significant (95% CI excluding 0).\u003c/em\u003e\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study examined the mechanisms through which illness perception influences adherence to functional exercise in stroke patients with focusing on the potential chain mediating roles of sense of coherence and self-regulatory fatigue. The most significant contribution of this study lies in demonstrating the mediation pathway of sense of coherence and regulatory fatigue on illness perception and exercise adherence. The following sections provide a\u003c/p\u003e \u003cp\u003edetailed discussion of the findings.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.1 the state of the variables\u003c/h2\u003e \u003cp\u003eThe findings of this study indicate that the functional exercise adherence score among stroke patients was a moderate level. This result is consistent with the findings of Wu et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] and Lan et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], and slightly higher than the adherence scores reported by Zhou et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] for elderly stroke patients.. The illness perception score was at the moderate level which was consistent with the results reported by Wu. et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] in Chinese stroke patients. Among the illness perception subdimensions, the \u0026lsquo;perception\u0026rsquo; dimension scored highest, aligning with findings by He et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The sense of coherence scale revealed a mean score among stroke patients, indicating a moderate level. This aligns with previous studies by Li et al. [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] and Fu et al. [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] on sense of coherence in stroke patients. This suggested that healthcare providers can enhance patients' sense of coherence by encouraging family and friend accompaniment, establishing supportive medical teams, and improving illness management capabilities, thereby strengthening their psychological adaptability [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Patients can be encouraged to focus on incremental progress in functional exercises, thereby boosting their rehabilitation hope and finding meaning in overcoming illness [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePatients' self-regulatory fatigue scores averaged, consistent with studies by Zhang et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and Liu et al. [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], indicating an overall moderately high level. Research indicates [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] that self-regulatory fatigue diminishes patients\u0026rsquo; motivation for illness management, thereby impacting prognosis and reducing quality of life. Healthcare providers should engage in regular communication with patients to understand their psychological dynamics. Employing cognitive behavioral therapy can help patients develop accurate perceptions of their illness and rehabilitation process, alleviate anxiety and other negative emotions, reduce psychological burden, and lower self-regulatory fatigue levels [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003e4.2 the analysis of the relationships among illness perception and adherence to functional exercise of stroke patients\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFirstly, the results showed that illness perception among stroke patients was negatively correlated with sense of coherence; positively correlated with self-regulatory fatigue and negatively correlated with functional exercise adherence, supporting Hypothesis. This study confirms significant pairwise correlations among the four core variables. First, illness perception and sense of coherence among stroke patients exhibit a significant negative correlation, consistent with previous scholarly findings [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Patients with more negative perceptions of their illness often lack confidence in illness progression and functional rehabilitation, believing they cannot effectively cope with changes brought by the disease, resulting in low sense of coherence. Dou et al. [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] also noted that patients with negative illness perceptions tend to view the illness as a severe threat to themselves, perceiving life as filled with uncertainty and uncontrollability, leading to decreased sense of coherence. Second, patients' illness perception showed a significant positive correlation with regulatory fatigue, similar to findings by Xiao et al. [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Patients with high illness perception scores often perceive bleak rehabilitation prospects, experience more negative emotions, and are more prone to fatigue. International scholars like De Gucht et al. [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] also noted that patients with more negative illness perceptions typically exhibit higher fatigue levels. Once self-regulatory fatigue emerges, patients\u0026rsquo; self-regulatory abilities diminish, making it difficult to cope with disease-related stress and challenges. This further reinforces negative perceptions of the disease, creating a vicious cycle that continuously strengthens the positive correlation between the two factors. Third, patients' illness perception is negatively correlated with functional exercise adherence, consistent with previous domestic and international research findings [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Slark et al. [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] suggest that reasonable illness cognition promotes the adoption of healthy behaviors, whereas excessively negative illness perceptions undermine patients' confidence in treatment and reduce their adherence levels. Patients with negative illness perceptions often view post-stroke limb dysfunction as irreversible, doubt the rationality of functional exercise, and lose intrinsic motivation to participate. Fourth, patients' sense of coherence shows a significant negative correlation with self-regulatory fatigue. Patients with high sense of coherence believe they can cope with stress more effectively and possess stronger self-regulatory abilities, resulting in lower self-regulatory fatigue levels. Moreover, individuals with high sense of coherence typically hold more positive cognitions, believing functional exercises are meaningful for illness recovery, which further reduces self-regulatory fatigue. Furthermore, research by Zhan et al. [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] indicates that individuals with high sense of coherence are more inclined to adopt proactive and effective coping strategies to resolve problems. This approach helps reduce negative emotions, avoids unnecessary resource depletion, and consequently alleviates self-regulatory fatigue. Fifth, patients' sense of coherence levels showed a significant positive correlation with functional exercise adherence, consistent with findings from domestic scholars L\u0026uuml; et al. [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Zhou et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] also demonstrated that patients with higher sense of coherence exhibit greater medication adherence. Those possessing higher sense of coherence can more actively comprehend their illness and rehabilitation process, overcome various difficulties in functional exercise, and achieve rehabilitation goals. Sixth, self-regulatory fatigue is negatively correlated with functional exercise adherence, consistent with the findings of Sun et al. [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] in chronic heart failure patients. Related studies indicate that patients with high self-regulatory fatigue are more prone to procrastination, interruption, or even abandonment when facing tasks [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. In this study, stroke patients require long-term self-regulatory to perform functional exercise tasks, continuously depleting their psychological resources. Once this depletion exceeds their recovery capacity, they enter a state of self-regulatory fatigue, leading to diminished willpower and concentration, and consequently lower functional exercise adherence levels.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Mediation analysis\u003c/h2\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003ch2\u003e4.3.1 Independent mediating effects of sense of coherence and regulatory fatigue\u003c/h2\u003e \u003cp\u003eThe findings of this study indicate that sense of coherence and self-regulatory fatigue partially mediate the relationship between illness perception and adherence to functional exercise. Sense of coherence influences patients' attitudes and beliefs toward functional exercise, playing a significant buffering and moderating role in negative illness perception and health behaviors. Previous research by Li et al. [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] also demonstrated that individuals with high sense of coherence exhibit more positive attitudes and better health behaviors when coping with stressors such as illness events. Self-regulatory plays a crucial role in illness perception and coping behaviors, consistent with previous scholarly findings [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. When patients experience severe negative illness perceptions, they incur greater psychological stress and consume mental resources, leading to self-regulatory fatigue that subsequently impacts their coping strategies. Furthermore, patients with negative illness perceptions often experience heightened negative emotions and psychological burdens. This leads to greater resource depletion during self-regulatory, increasing susceptibility to regulatory fatigue and consequently reducing adherence to functional exercise programs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e4.3.2 Chain Mediating Effect of Psychological Coherence and Self-regulatory Fatigue\u003c/h2\u003e \u003cp\u003eThe findings also reveal a chain mediation effect between sense of coherence and self-regulatory fatigue on illness perception and functional exercise adherence among stroke patients. Stroke patients' illness perception influences their sense of coherence levels, which in turn generates self-regulatory fatigue, ultimately affecting exercise adherence. According to Lazarus's stress and coping theory, individuals facing illness engage in cognitive appraisal to assess their coping capacity, subsequently adopt coping strategies, and ultimately influence health outcomes [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Perception of illness reflects an individual's cognitive understanding of the disease, while sense of coherence reflects their assessment of coping abilities and resources. An individual's cognitive evaluation influences coping behaviors, and the coping process itself involves depletion of personal resources. These factors ultimately affect the level of functional exercise adherence, i.e., health outcomes. In this study, patients with low illness perception scores demonstrated accurate perceptions of illness recovery and prognosis. Conversely, those with high sense of coherence levels more effectively integrated illness information, enabling better adaptation to functional exercise. This adaptation reduced the depletion of self-regulatory resources during exercise, thereby maintaining higher functional exercise adherence. Patients with higher illness perception scores often harbor excessive negative perceptions of their illness, lowering their sense of coherence. Individuals with low sense of coherence perceive illness progression as uncontrollable and functional exercise as meaningless. This leads to insufficient resources for self-regulatory in subsequent self-control behaviors, ultimately resulting in decreased adherence to functional exercise. This suggests clinicians should not only foster positive illness cognition but also prioritize enhancing individual sense of coherence and managing self-regulatory fatigue. Providing personalized illness information and rehabilitation guidance can help patients better understand their condition and recovery process, thereby establishing accurate illness cognition. Additionally, encouraging active patient involvement in rehabilitation decisions enhances their sense of control over the recovery process, improving sense of coherence. Designing phased functional exercise plans for patients can reduce self-regulatory fatigue, ultimately improving exercise adherence and accelerating recovery.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Limitations\u003c/h2\u003e \u003cp\u003eThere are some limitations in this study. First, the cross-sectional survey design collected static data, failing to capture dynamic changes or reveal causal relationships among variables. Future longitudinal studies are needed to explore these aspects further. Second, this study relied solely on questionnaires to assess post-stroke patients' psychological status and exercise adherence levels. Future research could incorporate smart devices for real-time tracking of patients' psychological states and adherence behaviors, quantifying findings to enhance data objectivity. Third, this study employed convenience sampling, surveying patients from only two hospitals in Henan Province. Generalizing the findings to a broader population may be limited. Subsequent research is recommended to expand in two dimensions: increasing sample size to enhance statistical power; considering a multicenter collaborative approach to conduct large-scale surveys across different regions and healthcare institutions. This would enhance the representativeness and generalizability of findings, enabling more comprehensive validation of current conclusions and providing a stronger empirical foundation for theoretical development.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study found that stroke patients have moderate levels of illness perception, sense of coherence and functional exercise adherence, and a moderate-to-high level of self-regulatory fatigue, and there are significant pairwise correlations among the four variables. Functional exercise adherence of stroke patients is affected by multiple factors, including age, monthly household per capita income, primary caregiver, number of stroke episodes, number of chronic comorbidities, self-care ability, illness perception, sense of coherence, and self-regulatory fatigue. Notably, illness perception not only has a direct negative predictive effect on functional exercise adherence, but also exerts an indirect influence through three pathways: single mediation of sense of coherence, single mediation of self-regulatory fatigue, and chain mediation of sense of coherence and self-regulatory fatigue.\u003c/p\u003e \u003cp\u003eClinical nursing staff should focus on the psychological characteristics and exercise adherence status of stroke patients, take targeted intervention measures to help patients establish a rational illness perception, enhance their sense of coherence, alleviate self-regulatory fatigue, and thus improve their adherence to functional exercise, promote limb function recovery, and improve the rehabilitation prognosis of stroke patients. Future research should adopt a longitudinal design and multi-center sampling to further verify the causal relationship and chain mediation mechanism among variables, and provide more comprehensive empirical evidence for the clinical rehabilitation of stroke patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study protocol received ethical approval from the Ethics Committee of Henan University (Approval No. HUSOM2024-573). We declare that the research was performed in accordance with relevant regulatory and conformed to the provisions of the Declaration of Helsinki. Written informed consent was obtained from all participants prior to their inclusion in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets supporting the conclusions of this article are included within the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by Henan Provincial Department of Science and Technology Key project (Grant NO. 242102310252, Grant NO. 252102311067), and Henan University Youth Cross Fund General (Grant NO. S23060Y).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFLL: conception, design of the work, method and statistical analysis, drafting the initial manuscript. YFX: data collection, analysis, interpretation of data. JCW: data collection, interpretation of data. TTK and CZT: data collection and revision of the initial manuscript. JL: data collection and revision of the initial manuscript. JXD: design of the work, data analysis, interpretation of data and revision of article. All authors reviewed the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend our sincere appreciation to all members that contributed to this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eGroup Report On Stroke Center. Summary of China Stroke Center Report 2022. Chin J Cerebrovasc Dis. 2024;21(8):565-76.\u003c/li\u003e\n \u003cli\u003eSalvalaggio S, Cacciante L, Maistrello L, et al. Clinical predictors for upper limb recovery after stroke rehabilitation: retrospective cohort study[J]. Healthcare (Basel), 2023, 11(3).\u003c/li\u003e\n \u003cli\u003eLozano R, Naghavi M, Foreman K, et al. 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J Pers Soc Psychol, 1986,50(3):571-579.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Stroke, Illness perception, Sense of coherence, Self-regulatory fatigue, Functional exercise adherence, Mediating effect","lastPublishedDoi":"10.21203/rs.3.rs-9146399/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9146399/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMotor dysfunction caused by stroke not only directly impairs physiological functions but also exerts a negative impact on psychological well-being. Adherence to functional exercises is critical for improving motor function recovery and enhancing the quality of life of stroke survivors. This study aimed to investigate the current status of illness perception, sense of coherence, self-regulatory fatigue, and functional exercise adherence in stroke patients, and to examine the chain mediating effects of sense of coherence and self-regulatory fatigue between illness perception and functional exercise adherence.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional descriptive study design was adopted, and convenience sampling was used to recruit stroke patients who attended follow-up visits at the neurology outpatient departments of two general hospitals in Henan Province. All participants completed a set of standardized questionnaires: including the demographic questionnaire, the Brief Illness Perception Questionnaire, the Sense of Coherence Scale, the Self-Regulatory Fatigue Scale, and the Stroke Patients' Functional Exercise Adherence Questionnaire.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 427 stroke patients were included. The mean scores of illness perception, sense of coherence, self-regulatory fatigue, and functional exercise adherence was (43.15\u0026thinsp;\u0026plusmn;\u0026thinsp;9.24), (54.77\u0026thinsp;\u0026plusmn;\u0026thinsp;10.86), (46.99\u0026thinsp;\u0026plusmn;\u0026thinsp;8.25), and (34.30\u0026thinsp;\u0026plusmn;\u0026thinsp;6.18), respectively. Multiple linear regression analysis identified that age, monthly household income per capita, primary caregiver, number of strokes episodes, number of chronic conditions, self-care capacity, illness perception, self-regulatory fatigue, and sense of coherence as significant predictors, collectively accounting for 72.3% of the variance in functional exercise adherence. Mediation effect analysis showed that illness perception not only directly influenced functional exercise adherence but also indirectly affected it through sense of coherence and self-regulatory fatigue. The mediating effects of sense of coherence and self-regulatory fatigue were \u0026minus;\u0026thinsp;0.101 (19.42% of total effect) and \u0026minus;\u0026thinsp;0.084 (16.15%), respectively, and their chain mediating effect was \u0026minus;\u0026thinsp;0.095 (18.27%).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eStroke patients in this study demonstrated moderate levels of illness perception, sense of coherence, and functional exercise adherence, upper-medium levels of self-regulatory fatigue. Sense of coherence and self-regulatory fatigue exhibiting chain-mediating effects between illness perception and functional exercise adherence. Clinical nursing staff should assist patients in establishing appropriate illness perceptions, enhancing their sense of coherence and reducing self-regulatory fatigue to improve functional exercise.\u003c/p\u003e","manuscriptTitle":"The relationship between illness perception and adherence to functional exercise in stroke patients: the chain mediating role of sense of coherence and self-regulatory fatigue","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-22 08:56:33","doi":"10.21203/rs.3.rs-9146399/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7b11be25-b38b-4ea4-9e7f-e349a9e08d07","owner":[],"postedDate":"April 22nd, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-18T04:10:10+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-05T20:45:51+00:00","index":72,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-30T17:42:42+00:00","index":71,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-18T04:25:45+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-22 08:56:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9146399","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9146399","identity":"rs-9146399","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}