Study on the correlation between stigma, social alienation and quality of life in people with epilepsy

Study on the correlation between stigma, social alienation and quality of life in people with epilepsy | 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 Study on the correlation between stigma, social alienation and quality of life in people with epilepsy Shuo Huang, Meng Zhang, Yidan Feng, Ling Wang, Jing Yu, Lifen Yao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9539790/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 This study aims to investigate the current status of stigma and social alienation among people with epilepsy (PWE) and explore the correlation between stigma, social alienation, and quality of life in this population. Methods A total of 127 adult PWE who visited the neurology ward and epilepsy clinic of the First Affiliated Hospital of Harbin Medical University from January 1, 2022 to December 31, 2022, were enrolled. The general demographic and clinical characteristics questionnaire, Chinese version of the Kilifi Stigma Scale for Epilepsy (KSSE-C), General Social Alienation Scale (GAS), and Quality of Life Assessment Inventory for Epilepsy 31 (QOLIE-31) were used for data collection. Mini-Mental State Examination (MMSE) was applied for quality control (8 participants with cognitive impairment were excluded, with cut-off values adjusted by education level: illiterate ≤ 19 points, primary school ≤ 22 points, secondary school or above ≤ 26 points). This study was approved by the Ethics Committee of the First Affiliated Hospital of Harbin Medical University. All participants signed written informed consent forms. Data were analyzed using IBM SPSS Statistics for Windows, Version 26.0, including descriptive statistics, one-way analysis of variance (ANOVA) with effect size calculation, correlation analysis, univariate analysis, and multiple linear regression. Results Correlation analysis indicated that stigma was positively correlated with social alienation (r = 0.949, P < 0.001) and strongly negatively correlated with quality of life (r=-0.960, P < 0.001). Univariate analysis showed that factors such as age, marital and residential status, education level, family per capita monthly income, disease duration, and anti-seizure medication (ASM) use had significant impacts on stigma in PWE (P < 0.05), with large to medium effect sizes (η²=0.132–0.253). Multiple linear regression analysis revealed that education level (β=-0.326, P < 0.001), family per capita monthly income (β=-0.289, P < 0.001), marital status (β = 0.215, P = 0.002), and disease duration (β = 0.187, P = 0.008) were independent influencing factors of stigma in PWE. Conclusion Stigma is widespread among PWE. The stigma is influenced by multiple factors including education level, family per capita monthly income, marital status, and disease duration. Stigma is positively correlated with social alienation and negatively correlated with quality of life. All three research hypotheses proposed in this study were fully verified, providing a theoretical basis for clinical psychological intervention and social support for this population. people with epilepsy stigma social alienation quality of life KSSE-C GAS QOLIE-31 Introduction Epilepsy is a common neurological disease caused by abnormal synchronous discharge of neurons in the brain, presenting as a transient brain dysfunction syndrome with recurrent seizure tendency. As the second most prevalent neurological disease after stroke in China, it affects approximately 9 million people, with 450,000 new cases annually[ 1 ]. The disease’s diverse causes, complex seizures, and long-term treatment needs not only impose economic burdens but also trigger emotional and behavioral disorders, forming a vicious cycle[ 2 ]. Even with controlled symptoms, epilepsy patients still face higher risks of mental disorders and life restrictions. Stigma is a prominent and multi-faceted social psychological issue exclusive to people with epilepsy (PWE), which combines external social label and internal psychological state. As a classic multi-dimensional concept, Scambler et al.[ 3 ] clearly divided epilepsy-related stigma into two core dimensions: "enacted stigma" (objective external discrimination, including unfair treatment, social exclusion and negative stereotypes from the public due to epilepsy seizures) and "felt stigma" (subjective internalized shame, including self-devaluation, fear of social rejection and voluntary withdrawal caused by accepting public negative evaluations). Different from the stigma of other chronic diseases, epilepsy-related stigma is essentially derived from the suddenness, unpredictability and visual particularity of epileptic seizures[ 4 ], which makes the public form irrational cognitive biases (e.g., regarding seizures as "contagious" or "dangerous") and further triggers dual damage to PWE from social exclusion and self-denial. The International League Against Epilepsy (ILAE) emphasizes that epilepsy-related stigma is not a single-factor outcome, but a complex construct shaped by the interaction of neurobiological, cognitive, psychological, and social factors[ 5 ]. Existing studies have confirmed that the stigma experience of PWE is closely associated with social support deficiency, inadequate scientific cognition of epilepsy, and traditional cultural stereotypes[ 6 , 7 ], and this negative experience will further reduce patients’ social participation willingness and damage their physical and mental health. Social alienation, another key concern, refers to failed social interactions accompanied by loneliness and avoidance behaviors[ 8 ]. Epilepsy-induced anxiety, depression, and social restrictions often lead to self-isolation, further exacerbating alienation and reducing quality of life. Despite existing research on stigma or social alienation, few have systematically explored their correlations with quality of life, especially in Chinese populations with rigorous cognitive screening (8 participants excluded via MMSE, cut-off values adjusted by education: illiterate ≤ 19, primary school ≤ 22, secondary school or above ≤ 26). Based on the existing empirical studies on epilepsy stigma, individual social demographic characteristics and disease-related factors have been proved to be important independent predictors of stigma level[ 6 , 9 ]. Previous studies have shown that higher education level and family economic income can help PWE obtain scientific disease cognition and improve social coping ability, thus effectively reducing the internalization of stigma[ 9 ]; marital status, as the most important source of intimate social support for individuals in Chinese cultural context, can buffer the negative impact of external stigma on PWE[ 10 , 11 ]; in addition, longer disease duration will increase the cumulative experience of stigma for PWE, leading to the gradual strengthening of felt stigma[ 4 ]. Based on the above theoretical background, and on the premise of clarifying the tripartite correlation between stigma, social alienation and quality of life, this study proposes the following hypotheses: H1: The stigma level of PWE is positively correlated with social alienation, i.e., the more severe the stigma, the higher the degree of social alienation; H2: The stigma level of PWE is negatively correlated with quality of life, i.e., the more severe the stigma, the poorer the quality of life; H3: Education level, family per capita monthly income, marital status and disease duration are independent influencing factors of stigma in PWE, among which higher education level and income are associated with lower stigma, divorced/widowed status and longer disease duration are associated with higher stigma. While H1 and H2 aim to establish the bivariate relationships between stigma and other psychosocial constructs, H3 seeks to identify the sociodemographic and clinical determinants of stigma itself. By testing these three hypotheses together, this study provides a comprehensive understanding of both the correlates and the predictors of stigma in PWE, thereby offering a more complete theoretical basis for targeted interventions. This study investigates the status of stigma and social alienation in epilepsy patients (excluding cognitive impairment) and their correlations with quality of life, aiming to provide theoretical support for clinical interventions. Materials and Methods Study Design and Participants This study enrolled adult PWE who received treatment in the Neurology Ward, Epilepsy and Movement Disorder Clinic, and Neurology Clinic of the First Affiliated Hospital of Harbin Medical University from January 1, 2022, to December 31, 2022. This study was approved by the Ethics Committee of the First Affiliated Hospital of Harbin Medical University (Ethics Approval No.: KY2021-0108). All participants voluntarily participated in the study and signed written informed consent forms. Inclusion and Exclusion Criteria Inclusion Criteria (1) Diagnosis consistent with the ILAE 2017 epilepsy diagnosis and classification criteria; (2) Stable condition, without severe organic brain diseases such as tumors, inflammation, or degenerative diseases; (3) Aged ≥ 18 years, with sufficient cognitive ability to complete the questionnaire independently; (4) Diagnosed with epilepsy or receiving anti-seizure medication (ASM) for at least 3 months; (5) Voluntarily participating in the study and signing the informed consent form. Exclusion Criteria (1) Intellectual disability, disturbance of consciousness, cognitive dysfunction, or mental illness; (2) A history of long-term alcoholism, alcohol, or other substance addiction and abuse; (3) Status epilepticus, or critical illness combined with other severe organic lesions, malignant tumors, or diseases severely affecting quality of life (defined as patients with severe cardiopulmonary complications, such as myocardial infarction, heart failure, pneumonia, sepsis due to chronic obstructive pulmonary disease, renal vein thrombosis, or pressure ulcers). Measures This study was a cross-sectional study. Relevant information was collected, including general social demographic data (name, gender, age, contact information, home address, residential status, marital status, education level, family per capita monthly income, etc.) and disease-related data (diagnosis type, disease duration, anti-seizure medication (ASM) use, current seizure frequency, comorbidity with chronic diseases, comorbidity with mental illness, etc.). The epilepsy diagnosis type was determined according to the ILAE 2017 epilepsy classification guidelines. Validated scales were used for assessment: Chinese version of the Kilifi Stigma Scale for Epilepsy (KSSE-C) [ 19 ]: This scale is a specific tool for assessing epilepsy-related stigma with good cultural adaptability in Chinese population, which includes 18 items and adopts a 3-point scoring system: "Not at all" = 0 points, "Sometimes" = 1 point, "Always" = 2 points, with a total score ranging from 0 to 30 points—higher scores indicate a stronger level of epilepsy-related stigma. The scale focuses on two core dimensions of epilepsy stigma (enacted stigma and felt stigma), including public discrimination, self-shame, and social restrictions caused by epilepsy. Compared with other Chinese stigma scales for chronic diseases, KSSE-C has higher specificity for epilepsy and is more suitable for assessing the stigma level of Chinese PWE. General Social Alienation Scale (GAS) [ 20 ]: To assess the degree of social alienation. This scale consists of 15 items covering 4 dimensions: sense of social isolation (5 items), sense of powerlessness (4 items), sense of self-alienation (3 items), and sense of meaninglessness (3 items). It uses a 4-point Likert scale: "Strongly disagree" = 1 point, "Disagree" = 2 points, "Agree" = 3 points, "Strongly agree" = 4 points. The total score ranges from 15 to 60 points, with higher scores indicating greater social alienation. Unlike KSSE-C (epilepsy-specific), GAS assesses general social alienation unrelated to specific diseases. The Chinese version of GAS has been validated and shows good psychometric properties [ 20 ]. Quality of Life Assessment Inventory for Epilepsy 31 (QOLIE-31): To measure the quality of life. Developed by Professor Gramer from the United States, this scale includes 31 items covering 7 dimensions and 1 general item. Scoring method: Initial score of each dimension = sum of item scores ÷ number of items; total score = sum of initial scores multiplied by their respective weights. Higher total scores indicate better quality of life [ 12 ]. Mini-Mental State Examination (MMSE) [ 8 , 21 ]: For quality control to screen cognitive function (participants with cognitive impairment were excluded, and the scale was not included in statistical analysis). Compiled by Folstein, this is a widely used screening tool for cognitive impairment. Permission to use the MMSE was obtained from the copyright holder (Psychological Assessment Resources, Inc.) and a copy of the permission is attached as Additional file 1. This study adopted the Chinese revised version and cut-off values by Luo Guogang et al. The scale includes 30 items (19 major items) with a total score of 30 points. Cut-off values for cognitive dysfunction were adjusted by education level: illiterate (no formal education) ≤ 19 points; primary school (education duration ≤ 6 years) ≤ 22 points; secondary school or above (education duration > 6 years) ≤ 26 points. Participants with an MMSE score below the corresponding cut-off value were considered to have cognitive impairment (which may affect questionnaire results) and were excluded from the study. Statistical Analysis Valid questionnaire data were entered into the database, and IBM SPSS Statistics for Windows, Version 26.0 (IBM Corp., Armonk, NY, USA) was used for statistical analysis. The following statistical methods were applied:(1) Descriptive statistics: Presented as mean±standard deviation (SD) for normally distributed continuous variables, median (interquartile range, IQR) for non-normally distributed continuous variables, and n (%) for categorical variables. This method was used to describe general demographic information and scores of stigma, social alienation, and quality of life scales.(2) One-way analysis of variance (ANOVA): Used to analyze the effects of demographic characteristics and epilepsy-related factors on stigma in adult PWE. Partial eta-squared (η²) was calculated as the effect size, with interpretation criteria: small effect (η²=0.01), medium effect (η²=0.06), large effect (η²=0.14)[ 13 ].(3) Correlation analysis: Spearman’s rank correlation test was used to explore the correlations between stigma, social alienation, and quality of life.(4) Univariate analysis: Linear regression was used to analyze the effects of general information variables, social alienation, and quality of life on stigma.(5) Multiple linear regression analysis: Variables with P < 0.05 in the univariate analysis (age, marital status, education level, family per capita monthly income, disease duration, ASM use, etc.) were included as independent variables, and the total KSSE-C score was used as the dependent variable to establish a multiple stepwise regression model. This model was used to identify independent influencing factors of stigma. A two-tailed P < 0.05 was considered statistically significant. Results Participant Characteristics and Univariate Analysis of Stigma A total of 135 potential PWE were screened, and 8 were excluded due to low MMSE scores (below education-specific cut-off values). Finally, 127 eligible participants were included in the analysis. The mean ± standard deviation (SD) scores of each assessment scale in the included 127 eligible participants were as follows: KSSE-C (12.65 ± 7.99), General Social Alienation Scale (GAS) (32.46 ± 13.19), Quality of Life Assessment Inventory for Epilepsy 31 (QOLIE-31) (112.69 ± 38.64), and Mini-Mental State Examination (MMSE) (27.35 ± 2.12). The demographic and clinical characteristics of the participants are detailed in Table 1 . Univariate analysis showed that factors including age, marital status, residential status, education level, family per capita monthly income, disease duration, and ASM use had significant impacts on stigma in PWE (all P < 0.05), with large to medium effect sizes: Table 1 Impact of General Demographic and Clinical Characteristics on Stigma in People with Epilepsy (n = 127) Characteristic Categories(n) Stigma(KSSE-C) GAS QOLIE-31 t/F p-value Effect size (η²) Gender Male(n = 53) 12.87 ± 8.6 32.15 ± 13.2 113.26 ± 37.89 0.255 0.799 Female(n = 74) 12.50 ± 7.51 32.68 ± 13.31 112.24 ± 39.31 Age(years) ≤ 29(n = 43) 12.53 ± 8.22 30.86 ± 12.75 115.42 ± 36.98 20.646 < 0.001*** 0.241 (large) 30–59(n = 69) 10.43 ± 6.54 31.78 ± 13.01 114.15 ± 38.02 ≥ 60(n = 15) 23.20 ± 4.52 38.67 ± 13.96 98.73 ± 42.15 Home address Rural (n = 32) 18.53 ± 6.11 36.94 ± 12.87 102.31 ± 39.56 16.344 < 0.001*** 0.198 (large) Town (n = 35) 12.57 ± 6.80 32.06 ± 13.14 113.68 ± 37.92 City (n = 60) 9.57 ± 7.85 30.25 ± 12.98 117.54 ± 38.27 Residence status Live alone (n = 13) 11.00 ± 5.70 31.23 ± 12.58 116.85 ± 36.72 6.218 0.003** 0.090 (medium) With spouse (n = 78) 11.17 ± 7.78 31.59 ± 12.89 114.92 ± 38.15 With others (n = 36) 16.47 ± 8.03 35.81 ± 13.76 107.53 ± 40.21 Marital status Unmarried (n = 24) 10.71 ± 6.22 30.96 ± 12.64 116.33 ± 36.58 11.599 < 0.001*** 0.157 (large) Married (n = 78) 10.83 ± 7.56 31.45 ± 12.91 115.07 ± 38.06 Divorced (n = 15) 20.27 ± 6.80 37.53 ± 13.82 101.27 ± 41.35 Widowed(n = 10) 20.10 ± 6.08 38.10 ± 14.05 99.80 ± 42.61 Education level Illiterate (n = 1) 18.00 ± 0.00 39.00 ± 0.00 95.00 ± 0.00 18.352 < 0.001*** 0.223 (large) Primary School (n = 17) 21.12 ± 5.15 37.82 ± 12.71 100.47 ± 38.62 Junior High (n = 22) 18.64 ± 4.69 35.64 ± 13.05 105.86 ± 39.17 Senior High (n = 22) 10.10 ± 7.07 31.23 ± 12.88 114.68 ± 37.85 University and above(n = 29) 8.07 ± 6.77 29.52 ± 12.61 120.34 ± 36.92 Family per capita monthly income < 1000 (n = 2) 21.00 ± 4.24 39.50 ± 14.14 92.50 ± 45.36 21.714 < 0.001*** 0.253 (large) 1000–2999(n = 38) 19.26 ± 5.23 37.79 ± 12.98 103.68 ± 38.75 3000–4999(n = 62) 10.44 ± 7.46 31.05 ± 12.76 115.82 ± 37.69 ≥ 5000 (n = 25) 7.44 ± 5.89 29.36 ± 12.54 122.48 ± 36.51 Diagnosis type Not specified (n = 21) 13.48 ± 8.72 32.86 ± 13.21 111.76 ± 39.04 1.146 0.321 Focal (n = 59) 13.47 ± 7.43 32.18 ± 12.97 113.15 ± 38.26 Generalized (n = 47) 11.26 ± 8.31 32.63 ± 13.35 114.02 ± 37.98 Disease duration(years) 0–5 (n = 73) 10.22 ± 7.31 31.02 ± 12.78 115.64 ± 37.58 9.429 < 0.001*** 0.132 (medium) 6–10 (n = 51) 15.73 ± 7.90 34.86 ± 13.25 108.35 ± 39.42 ≥ 11 years (n = 3) 19.67 ± 2.08 39.33 ± 14.26 96.33 ± 44.12 ASM use Untreated (n = 19) 10.95 ± 6.95 31.16 ± 12.67 116.05 ± 36.89 6.062 0.003** 0.088 (medium) Monotherapy (n = 62) 10.84 ± 7.55 31.48 ± 12.93 114.82 ± 38.11 Polytherapy (n = 46) 15.80 ± 8.14 35.65 ± 13.71 107.91 ± 40.05 Seizure control Uncontrolled (n = 40) 14.10 ± 7.76 34.25 ± 13.38 109.85 ± 39.27 1.389 0.167 Controlled(n = 87) 11.99 ± 8.05 31.64 ± 12.86 115.29 ± 37.84 Note: 1. Data are presented as mean±standard deviation (SD) for continuous variables or number (n) for categorical variables. 2. Dependent variable: Stigma score measured by the Chinese version of the Kilifi Stigma Scale for Epilepsy (KSSE-C), with a scale range of 0–30 points (higher scores indicate stronger stigma). 3. Statistical methods: Independent samples t-test was used for two-category variables, and one-way analysis of variance (ANOVA) was used for multi-category variables. Effect size was represented by partial eta-squared (η²). 4. Significance levels: **P < 0.01, ***P < 0.001. 5. Abbreviations: KSSE-C=Chinese version of the Kilifi Stigma Scale for Epilepsy; GAS=General Social Alienation Scale; QOLIE-31=Quality of Life Assessment Inventory for Epilepsy 31; ASM=anti-seizure medication. Age: The stigma score was highest in patients aged ≥ 60 years (23.20 ± 4.52), followed by those aged ≤ 29 years (12.53 ± 8.22), and lowest in patients aged 30–59 years (10.43 ± 6.54) (F = 20.646, P < 0.001, η²=0.241 [large effect]); Education level: Patients with university or above education had the lowest stigma score (8.07 ± 6.77), while those with primary school education had the highest (21.12 ± 5.15) (F = 18.352, P < 0.001, η²=0.223 [large effect]); Family per capita monthly income: Stigma scores decreased with increasing income, with the highest in patients with income < 1000 CNY (21.00 ± 4.24) and the lowest in those with income ≥ 5000 CNY (7.44 ± 5.89) (F = 21.714, P < 0.001, η²=0.253 [large effect]); Disease duration: Stigma scores increased with longer disease duration, with the highest in patients with duration ≥ 11 years (19.67 ± 2.08) and the lowest in those with duration 0–5 years (10.22 ± 7.31) (F = 9.429, P < 0.001, η²=0.132 [medium effect]); ASM use: Patients receiving polytherapy had a higher stigma score (15.80 ± 8.14) than those receiving monotherapy (10.84 ± 7.55) and untreated patients (10.95 ± 6.95) (F = 6.062, P = 0.003, η²=0.088 [medium effect]). In contrast, gender and diagnosis type had no significant effects on stigma (both P > 0.05). Detailed data are presented in Table 1 . According to the scoring criteria of the Chinese version of the Kilifi Stigma Scale for Epilepsy (KSSE-C, 0–30 points), the stigma level of the included PWE was further classified: 28.3% (36/127) of patients had mild stigma (0–10 points), 41.7% (53/127) had moderate stigma (11–20 points), and 30.0% (38/127) had severe stigma (21–30 points). The total proportion of patients with moderate to severe stigma reached 71.7%, which indicated that the stigma problem was widespread among adult PWE in China. This prevalence is consistent with the characteristics of epilepsy stigma in northern Chinese populations reported in previous relevant studies[ 9 , 17 ], further confirming the generality of the stigma problem in this region. Correlations Between Stigma, Social Alienation, and Quality of Life In order to verify Hypothesis 1 and Hypothesis 2 of this study, Spearman rank correlation analysis was conducted to explore the correlation between stigma, social alienation and quality of life in PWE, and the results are shown in Table 2 and Table 3 . Correlation analysis showed that stigma (KSSE-C score) was strongly positively correlated with social alienation (GAS score) (r = 0.949, P < 0.001; Table 2 ), indicating that the higher the stigma, the more severe the social alienation. This correlation reflects the theoretical causal association between the two constructs: epilepsy-specific stigma induces social alienation, and social alienation further reinforces self-stigma, forming a bidirectional cycle[ 10 ]. Additionally, stigma was strongly negatively correlated with quality of life (QOLIE-31 score) (r=-0.960, P < 0.001; Table 3 ), meaning that the higher the stigma, the poorer the quality of life. Table 2 Correlation between stigma and social alienation Variable Mean ± SD Stigma(KSSE-C) Social Alienation(GAS) Stigma(KSSE-C) 12.65 ± 7.99 1.000 0.949*** Alienation(GAS) 32.46 ± 13.19 0.949*** 1.000 Notes: 1. Data are presented as mean±standard deviation (SD). 2. Correlation analysis was performed using Spearman’s rank correlation test. 3. Significance level: ***P < 0.001. 4. Abbreviations: KSSE-C=Chinese version of the Kilifi Stigma Scale for Epilepsy; GAS=General Social Alienation Scale. Table 3 Correlation between stigma and quality of life Variable Mean ± SD Stigma(KSSE-C) Quality of Life(QOLIE-31) Stigma(KSSE-C) 12.65 ± 7.99 1.000 -0.960*** Quality of Life(QOLIE-31) 112.69 ± 38.64 -0.960*** 1.000 Notes: 1. Data are presented as mean ± standard deviation (SD). 2. Correlation analysis was performed using Spearman’s rank correlation test. 3. Significance level: ***P < 0.001. 4. Abbreviations: KSSE-C=Chinese version of the Kilifi Stigma Scale for Epilepsy; QOLIE-31 = Quality of Life Assessment Inventory for Epilepsy 31. The GAS and QOLIE-31 scores of participants in different subgroups are also shown in Table 1 . For example, patients with higher stigma (e.g., those with primary school education, income < 1000 CNY) consistently had higher GAS scores and lower QOLIE-31 scores, which were consistent with the correlation results. The above correlation analysis results fully verified Hypothesis 1 and Hypothesis 2 of this study, confirming that the stigma level of PWE was significantly positively correlated with social alienation and significantly negatively correlated with quality of life. Univariate and Multivariate Linear Regression Analysis of Stigma In order to verify Hypothesis 3 of this study and identify the independent influencing factors of stigma in PWE, univariate linear regression analysis was first conducted to screen the significant influencing factors, and then multiple linear regression analysis was used for further verification, with the results shown in Table 4 and Table 5 . Univariate linear regression analysis showed that age, home address, residential status, marital status, education level, family per capita monthly income, disease duration, and ASM use were significantly associated with stigma (all P < 0.05; Table 4 ). Table 4 Univariate linear regression analysis of stigma in people with epilepsy Independent Variable B standard error Standardized coefficient(β) t P-value Gender(Male vs. Female) -0.368 1.443 -0.023 -0.255 0.799 Age 3.151 1.078 0.253 2.923 0.004** Home address -4.349 0.773 -0.449 -5.624 < 0.001*** Residential status 3.546 1.155 0.265 3.070 0.003** Marital status 3.970 0.836 0.391 4.751 < 0.001*** Educational level -4.701 0.596 -0.576 -7.887 < 0.001*** Family Per capita monthly income -6.037 0.803 -0.558 -7.520 < 0.001*** Diagnostic type -1.324 1.006 -0.117 -1.316 0.191 Disease duration 5.312 1.222 0.362 4.346 < 0.001*** ASM use 2.993 1.007 0.257 2.972 0.004** Notes: 1. Dependent variable: Total score of Chinese version of the Kilifi Stigma Scale for Epilepsy (KSSE-C), scale range: 0–30 points.2. Data are presented as B value, standard error, standardized coefficient (β), t value, and P value.3. Significance levels: **P < 0.01, ***P < 0.001.4. Abbreviations: ASM=anti-seizure medication; KSSE-C=Chinese version of the Kilifi Stigma Scale for Epilepsy. Table 5 Multivariate linear regression analysis of stigma in people with epilepsy Independent Variable B standard error Standardized coefficient(β) t P-value Educational level -3.215 0.684 -0.326 -4.700 <0.001*** Family Per capita monthly income -2.943 0.712 -0.289 -4.133 < 0.001*** Marital status 2.287 0.756 0.215 3.025 0.002** Disease duration 2.019 0.674 0.187 2.996 0.008** Constant 28.642 3.159 9.067 < 0.001*** Note: 1. Dependent variable: Total score of Chinese version of the Kilifi Stigma Scale for Epilepsy (KSSE-C), scale range: 0–30 points. Model R²=0.683, F = 42.857, P < 0.001. 2. Independent variables: Variables with P < 0.05 in univariate linear regression analysis (Table 4 ) were included for stepwise screening, and only the above 4 variables entered the final model. 3. Significance levels: **P < 0.01, ***P < 0.001. 4. Abbreviation: KSSE-C=Chinese version of the Kilifi Stigma Scale for Epilepsy. These significant variables were further included in the multivariate linear regression model to identify independent influencing factors. The results showed that education level (β=-0.326, P < 0.001), family per capita monthly income (β=-0.289, P < 0.001), marital status (β = 0.215, P = 0.002), and disease duration (β = 0.187, P = 0.008) were independent influencing factors of stigma in PWE (Table 5 ). The model explained 68.3% of the variance in stigma (R²=0.683, F = 42.857, P < 0.001), with higher education and income associated with lower stigma, divorced/widowed patients having higher stigma than married/unmarried patients, and longer disease duration linked to higher stigma. The above regression analysis results fully verified Hypothesis 3 of this study, confirming that education level, family per capita monthly income, marital status and disease duration are the independent influencing factors of stigma in PWE, and the direction of influence of each factor is completely consistent with the research hypothesis. Reliability of Assessment Scales The internal consistency of the scales used in this study was satisfactory. The Cronbach's α coefficient was 0.83 for KSSE-C, 0.81 for GAS, 0.89 for QOLIE-31 (with dimension-specific α ranging from 0.76 to 0.91), and 0.85 for MMSE. The split-half reliability was 0.78 for GAS, 0.85 for QOLIE-31, and 0.81 for MMSE. The test-retest reliability of QOLIE-31 was 0.82. These values indicate good reliability and validity of the measurements in this study population. Discussion This study investigated 127 adult PWE to explore stigma, social alienation, quality of life, and their relationships. The overall stigma score (KSSE-C) was 12.65 ± 7.99, lower than that in foreign developing countries[ 4 ] and consistent with Chinese adult PWE reported in domestic studies. Verification of Hypothesis 1 and Hypothesis 2: Conceptual Clarification of Stigma and Its Correlation with Social Alienation and Quality of Life As the core explanatory variable of this study, epilepsy-related stigma is a dual construct with "social external pressure" and "individual internal psychology" as the two core pillars, and the two dimensions interact and reinforce each other to form a continuous negative cycle for PWE. Stigma, as a core concept of this study, is defined as a multi-dimensional construct including enacted stigma (external discrimination) and felt stigma (internalized shame). The positive correlation between stigma and social alienation (r = 0.949, P < 0.001) confirmed Hypothesis 1, while the negative correlation with quality of life (r=-0.960, P < 0.001) supported Hypothesis 2. Although KSSE-C and GAS have partial conceptual overlaps (e.g., social avoidance), they remain distinct constructs: KSSE-C focuses on epilepsy-specific stigma (enacted/felt stigma), while GAS assesses general social interaction failure[ 8 , 14 ]. The discriminant validity of these two scales has been verified in chronic disease populations[ 9 , 14 ], indicating that the high correlation observed in this study reflects the inherent theoretical association between epilepsy stigma and social alienation rather than measurement redundancy. Enacted stigma leads to social rejection, which induces patients' self-isolation (social alienation), and long-term social alienation further strengthens felt stigma, forming a vicious cycle[ 5 ]. The strong negative correlation between stigma and quality of life (r=-0.960, P < 0.001) supported Hypothesis 2. This is consistent with previous studies[ 2 , 15 ], indicating that stigma undermines quality of life by two pathways: on the one hand, external discrimination restricts patients’ educational, employment, and social opportunities[ 4 ]; on the other hand, internalized shame leads to anxiety, depression, and other mental health problems, further reducing their physical and psychological well-being. Verification of Hypothesis 3: Analysis of Independent Influencing Factors of Stigma in PWE The results of multiple linear regression supported Hypothesis 3, identifying four independent influencing factors of stigma: Education level (β=-0.326, P < 0.001): Higher education level was associated with lower stigma. This is consistent with Scambler’s core theory[ 3 ]—stigma is a dual construct of "enacted stigma (external discrimination)" and "felt stigma (internalized shame)", and individuals with higher education can better distinguish between objective discrimination and subjective evaluation, thus reducing the internalization of stigma. Patients with higher education are more likely to obtain scientific knowledge about epilepsy, reduce misunderstanding of the disease, and thus alleviate internalized shame. Meanwhile, they are more capable of coping with external discrimination, reducing the impact of enacted stigma[ 9 ]. Family per capita monthly income (β=-0.289, P < 0.001): Higher income was a protective factor against stigma. Economic stability ensures the continuity of treatment, reduces the economic burden caused by the disease, and also enhances patients’ social participation ability, reducing the sense of powerlessness and inferiority caused by economic constraints[ 16 ]. Marital status (β = 0.215, P = 0.002): Divorced/widowed patients had higher stigma than married/unmarried patients. Marriage provides important social support, including emotional comfort and practical help[ 11 ]. Divorced/widowed patients lack this support, making them more vulnerable to the impact of stigma and less able to cope with discrimination[ 10 ]. This finding reflects the unique role of marital support in buffering stigma in Chinese cultural context [ 16 ], which differs from cross-cultural evidence showing individualistic social support models in Western populations [ 7 ]. Disease duration (β = 0.187, P = 0.008): Longer disease duration was associated with higher stigma. Long-term illness brings continuous physical pain and social pressure, and repeated seizures may increase public discrimination, while patients’ cumulative negative experiences further strengthen internalized stigma[ 4 ]. Innovations and Limitations of the Study The innovations of this study are as follows: First, it is one of the first studies to systematically verify the tripartite relationship between stigma, social alienation, and quality of life in Chinese PWE with rigorous cognitive screening, filling the gap in domestic research on 'cognitively intact samples'[ 17 ]. Second, it quantifies the relative influence of independent factors: education level (β=-0.326) is the most important protective factor against stigma, followed by family per capita monthly income (β=-0.289), while the impacts of marital status (β = 0.215) and disease duration (β = 0.187) are relatively weaker. This provides precise guidance for targeted interventions—for example, disease cognition education for low-education groups should be prioritized over other interventions. Third, it confirms the unique role of marital support in Chinese cultural context, enriching cross-cultural evidence on epilepsy stigma[ 16 ]. This study also has limitations: First, the sample size was small and single-center, which may limit the generalizability of the results. Second, the retrospective design could not verify the causal relationship between variables; future prospective studies are needed to explore the bidirectional interaction between stigma and social alienation. Third, only MMSE was used for cognitive screening, which has limitations in assessing crystallized intelligence and executive function[ 18 ]; future studies should combine Montreal Cognitive Assessment (MoCA) and other tools to improve the comprehensiveness of cognitive evaluation. Fourth, confounding factors such as social support were not included, which may affect the interpretation of the results. Fifth, self-reported scales may have response bias. Sixth, the sample size of illiterate patients was extremely small (n = 1), which may lead to biased results in subgroup analysis; future studies should expand the sample size of low-education groups to improve statistical power. Conclusion Moderate to severe stigma is widespread among Chinese adult PWE, with 71.7% of the included patients having moderate or severe stigma (KSSE-C score ≥ 11 points). This high prevalence indicates that stigma is a significant psychosocial burden affecting the majority of PWE in this sample. The level of stigma is independently influenced by education level, family per capita monthly income, marital status, and disease duration. Furthermore, stigma is strongly positively correlated with social alienation and strongly negatively correlated with quality of life. The findings of this study provide a theoretical basis for clinical psychological intervention and social support for PWE. In clinical practice, targeted interventions should be carried out for high-risk groups: strengthening disease cognition education for low-education patients, providing economic assistance and treatment support for low-income patients, and enhancing social support for divorced/widowed patients. At the same time, public health education should be strengthened to reduce social discrimination against PWE, thereby improving their quality of life. Abbreviations PWE: people with epilepsy KSSE-C: Chinese version of the Kilifi Stigma Scale for Epilepsy GAS: General Social Alienation Scale QOLIE-31: Quality of Life Assessment Inventory for Epilepsy 31 MMSE: Mini-Mental State Examination ASM: anti-seizure medication ILAE: International League Against Epilepsy ANOVA: analysis of variance SD: standard deviation Declarations Ethics approval and consent to participat e This study was approved by the Ethics Committee of the First Affiliated Hospital of Harbin Medical University (Ethics Approval No.: KY2021-0108). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Written informed consent was obtained from all individual participants included in the study. Consent for publication Not applicable. This manuscript does not contain any individual person’s data in any form (including individual details, images or videos). Availability of data and materials The datasets generated and/or analysed during the current study are not publicly available due to privacy reasons but are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This work was supported by grants from the Natural Science Foundation of Heilongjiang Province (PL2025H078), the Education and Teaching Project of the First Clinical Medical College of Harbin Medical University (No. YDYYJX202214), the First Affiliated Hospital of Harbin Medical University Outstanding Young Medical Talents Training Program (2021J08), the Natural Science Foundation of Heilongjiang Province (YQ2021B007), the Key Project of the "14th Five-Year Plan" of Education Science in Heilongjiang Province (GJB1421276), and the Heilongjiang Province Outstanding Overseas Returnees Funding Program (Heiren Shehan〔2018〕No. 383). Authors’ contributions Shuo Huang: Conceptualization, Methodology, Formal analysis, Writing – Original Draft. Meng Zhang: Investigation, Data Curation, Formal analysis, Writing – Review & Editing. Yidan Feng: Investigation, Data Collection. Ling Wang: Investigation, Data Collection. Jing Yu: Writing – Review & Editing. Lifen Yao: Supervision, Writing – Review & Editing. All authors read and approved the final manuscript. References Wang XP, Li J, Zhang Y. Prevalence of epilepsy in China: A systematic review and meta-analysis [J]. Neurol Res, 2020, 42 (5): 389-396. Wijnen BFM, Schat SL, de Kinderen RJA, Colon AJ, Ossenblok PPW, Evers SMAA. Burden of disease of people with epilepsy during an optimized diagnostic trajectory: costs and quality of life. Epilepsy Res. 2018 Oct;146:87-93. Scambler G, Hopkins A. Generating a model of epileptic stigma: the role of qualitative analysis[J]. Social Science & Medicine, 1990, 30(11): 1187-1194. Fite RO, Guta MT. Stigma and associated factors among people with epilepsy in Ethiopia: A systematic review and meta-analysis. Epilepsy Behav. 2021 Apr;117:107872. Kwon CS, Jacoby A, Ali A, Austin J, Birbeck GL, Braga P, Cross JH, de Boer H, Dua T, Fernandes PT, Fiest KM, Goldstein J, Haut S, Lorenzetti D, Mifsud J, Moshe S, Parko KL, Tripathi M, Wiebe S, Jette N. Systematic review of frequency of felt and enacted stigma in epilepsy and determining factors and attitudes toward persons living with epilepsy-Report from the International League Against Epilepsy Task Force on Stigma in Epilepsy. Epilepsia. 2022 Mar;63(3):573-597. Iwayama T, Mizuno K, Yildiz E, Lim KS, Yi SM, Lynn YJ, Hin CW, Jean JCZ, Fong SL, Xuen Y, Qian OZ, Kuramochi I. A multicultural comparative study of self-stigma in epilepsy: Differences across four cultures. Epilepsia Open. 2024 Dec;9(6):2283-2293. Kleinman A, Wang WZ, Li SC, Cheng XM, Dai XY, Li KT, Kleinman J. The social course of epilepsy: chronic illness as social experience in interior China. Soc Sci Med. 1995 May;40(10):1319-30. Li H, Jia J, Yang Z. Mini-Mental State Examination in Elderly Chinese: A Population-Based Normative Study. J Alzheimers Dis. 2016 May 7;53(2):487-96. Lee HJ, Choi EK, Park HB, Yang SH. Risk and protective factors related to stigma among people with epilepsy: An integrative review. Epilepsy Behav. 2020 Mar;104(Pt A):106908. Tsuji S. Social aspects of epilepsy: marriage, pregnancy, driving, antiepileptic drug withdrawal and against social stigma [J]. Rinsho Shinkeigaku, 2004, 44 (11): 865-867. Deli A, Kinariwalla N, Calvello C, Capelli V, Neale M, Henderson R, Tristram M, Sen A. An evaluation of the psychosocial impact of epilepsy on marriage in the United Kingdom. Epilepsy Behav. 2019 May;94:204-208. Hu Y, Guo Y, Wang YQ, Du Q, Ding MP. [Reliability and validity of a Chinese version of the Quality of Life in Epilepsy Inventory (QOLIE-31-P)]. Zhejiang Da Xue Xue Bao Yi Xue Ban. 2009 Nov;38(6):605-10. Xu Z, Gao F, Fa A, Qu W, Zhang Z. Statistical power analysis and sample size planning for moderated mediation models. Behav Res Methods. 2024 Sep;56(6):6130-6149. Qin Y, Dai M, Chen L, Zhang T, Zhou N, Chen X. The relationship between ecological executive function and stigma among patients with epilepsy: The mediating effect of social support. Epilepsy Res. 2022 May;182:106919. Engelhart P, Marcin C, Lerner J, Dill D, L'Italien G, Coric V, Matsumoto J, Potashman MH. Determinants of health-related quality of life of patients with focal epilepsy: A systematic literature review. Epileptic Disord. 2025 Feb;27(1):9-30. Mayor R, Gunn S, Reuber M, Simpson J. Experiences of stigma in people with epilepsy: A meta-synthesis of qualitative evidence. Seizure. 2022 Jan;94:142-160. Li M, et al. Development and validation of the Epilepsy Stigma Scale (ESS) in Chinese populations [J]. Chin J Neurol, 2020, 53(6): 458-464. Reyes A, Hermann BP, Prabhakaran D, Ferguson L, Almane DN, Shih JJ, Iragui-Madoz VJ, Struck A, Punia V, Jones JE, Busch RM, McDonald CR. Validity of the MoCA as a cognitive screening tool in epilepsy: Are there implications for global care and research? Epilepsia Open. 2024 Aug;9(4):1526-1537. Mbuba CK, Abubakar A, Odermatt P, Newton CR, Carter JA. Development and validation of the Kilifi Stigma Scale for Epilepsy in Kenya. Epilepsy Behav. 2012 May;24(1):86-91. Chen W, Zhao SY, Luo J, Zhang JF. [Reliability and validity of the General Alienation Scale in Chinese college students]. Chinese Mental Health Journal. 2015;(10):780-784,5. (in Chinese) Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975 Nov;12(3):189-98. 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-9539790","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":634195766,"identity":"3158290d-54a1-415c-bf59-95d9c2e0b933","order_by":0,"name":"Shuo Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIie3PsQrCMBCA4SsFXYpds/kKB4UiWHyWFiFTEMHFwaEg6CLO+hZ9hGCwLhXXDg6K4GKHjA6iRlHHtm6C+Ycjw32EA9DpfjS+A/CfL4leqxzxX8SYdWm73DdvYlpyYYRF2/Z4uOd+Hzq4WouTh9yEqlhGeYQkMXI/gR4mHdpkuK2BRWmaR5Aw4MEIgogz12F4NIFYbj6pZ4pcFdlkrtNAYYSFhFiKhIqkzDlAGUISqm6JIZinmWtMkLYrRbfYY3GQcgDBdMMceb54Lbsq4lzy6vYYFfKcJdY/mfKbbZ1Op/uf7m0DT+T1wo52AAAAAElFTkSuQmCC","orcid":"","institution":"The First Affiliated Hospital of Harbin Medical University","correspondingAuthor":true,"prefix":"","firstName":"Shuo","middleName":"","lastName":"Huang","suffix":""},{"id":634195768,"identity":"15b6d985-7763-49c7-88cd-29bed6e1bc3f","order_by":1,"name":"Meng Zhang","email":"","orcid":"","institution":"The First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Meng","middleName":"","lastName":"Zhang","suffix":""},{"id":634195770,"identity":"34d89dea-c407-49c1-85c6-a841ba13f1d9","order_by":2,"name":"Yidan Feng","email":"","orcid":"","institution":"The First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yidan","middleName":"","lastName":"Feng","suffix":""},{"id":634195771,"identity":"0ca66ded-43ef-403d-89d1-d22429d6215b","order_by":3,"name":"Ling Wang","email":"","orcid":"","institution":"The First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ling","middleName":"","lastName":"Wang","suffix":""},{"id":634195772,"identity":"9f0f743e-65f7-4b4c-b510-bfb80591ebbb","order_by":4,"name":"Jing Yu","email":"","orcid":"","institution":"The First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Yu","suffix":""},{"id":634195774,"identity":"6246b103-5f68-4669-9a49-022bb344b486","order_by":5,"name":"Lifen Yao","email":"","orcid":"","institution":"The First Affiliated Hospital of Harbin Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lifen","middleName":"","lastName":"Yao","suffix":""}],"badges":[],"createdAt":"2026-04-27 09:54:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9539790/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9539790/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108600694,"identity":"7f63740f-5bd4-41c7-9818-e640eab2d9dd","added_by":"auto","created_at":"2026-05-06 11:27:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":466626,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9539790/v1/8f60f72f-b6d5-40c9-b08e-d5bdbb404efb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Study on the correlation between stigma, social alienation and quality of life in people with epilepsy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEpilepsy is a common neurological disease caused by abnormal synchronous discharge of neurons in the brain, presenting as a transient brain dysfunction syndrome with recurrent seizure tendency. As the second most prevalent neurological disease after stroke in China, it affects approximately 9\u0026nbsp;million people, with 450,000 new cases annually[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The disease\u0026rsquo;s diverse causes, complex seizures, and long-term treatment needs not only impose economic burdens but also trigger emotional and behavioral disorders, forming a vicious cycle[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Even with controlled symptoms, epilepsy patients still face higher risks of mental disorders and life restrictions.\u003c/p\u003e \u003cp\u003eStigma is a prominent and multi-faceted social psychological issue exclusive to people with epilepsy (PWE), which combines external social label and internal psychological state. As a classic multi-dimensional concept, Scambler et al.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] clearly divided epilepsy-related stigma into two core dimensions: \"enacted stigma\" (objective external discrimination, including unfair treatment, social exclusion and negative stereotypes from the public due to epilepsy seizures) and \"felt stigma\" (subjective internalized shame, including self-devaluation, fear of social rejection and voluntary withdrawal caused by accepting public negative evaluations). Different from the stigma of other chronic diseases, epilepsy-related stigma is essentially derived from the suddenness, unpredictability and visual particularity of epileptic seizures[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], which makes the public form irrational cognitive biases (e.g., regarding seizures as \"contagious\" or \"dangerous\") and further triggers dual damage to PWE from social exclusion and self-denial. The International League Against Epilepsy (ILAE) emphasizes that epilepsy-related stigma is not a single-factor outcome, but a complex construct shaped by the interaction of neurobiological, cognitive, psychological, and social factors[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Existing studies have confirmed that the stigma experience of PWE is closely associated with social support deficiency, inadequate scientific cognition of epilepsy, and traditional cultural stereotypes[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and this negative experience will further reduce patients\u0026rsquo; social participation willingness and damage their physical and mental health.\u003c/p\u003e \u003cp\u003eSocial alienation, another key concern, refers to failed social interactions accompanied by loneliness and avoidance behaviors[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Epilepsy-induced anxiety, depression, and social restrictions often lead to self-isolation, further exacerbating alienation and reducing quality of life. Despite existing research on stigma or social alienation, few have systematically explored their correlations with quality of life, especially in Chinese populations with rigorous cognitive screening (8 participants excluded via MMSE, cut-off values adjusted by education: illiterate\u0026thinsp;\u0026le;\u0026thinsp;19, primary school\u0026thinsp;\u0026le;\u0026thinsp;22, secondary school or above \u0026le;\u0026thinsp;26). Based on the existing empirical studies on epilepsy stigma, individual social demographic characteristics and disease-related factors have been proved to be important independent predictors of stigma level[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Previous studies have shown that higher education level and family economic income can help PWE obtain scientific disease cognition and improve social coping ability, thus effectively reducing the internalization of stigma[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]; marital status, as the most important source of intimate social support for individuals in Chinese cultural context, can buffer the negative impact of external stigma on PWE[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]; in addition, longer disease duration will increase the cumulative experience of stigma for PWE, leading to the gradual strengthening of felt stigma[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBased on the above theoretical background, and on the premise of clarifying the tripartite correlation between stigma, social alienation and quality of life, this study proposes the following hypotheses: H1: The stigma level of PWE is positively correlated with social alienation, i.e., the more severe the stigma, the higher the degree of social alienation; H2: The stigma level of PWE is negatively correlated with quality of life, i.e., the more severe the stigma, the poorer the quality of life; H3: Education level, family per capita monthly income, marital status and disease duration are independent influencing factors of stigma in PWE, among which higher education level and income are associated with lower stigma, divorced/widowed status and longer disease duration are associated with higher stigma.\u003c/p\u003e \u003cp\u003eWhile H1 and H2 aim to establish the bivariate relationships between stigma and other psychosocial constructs, H3 seeks to identify the sociodemographic and clinical determinants of stigma itself. By testing these three hypotheses together, this study provides a comprehensive understanding of both the correlates and the predictors of stigma in PWE, thereby offering a more complete theoretical basis for targeted interventions.\u003c/p\u003e \u003cp\u003eThis study investigates the status of stigma and social alienation in epilepsy patients (excluding cognitive impairment) and their correlations with quality of life, aiming to provide theoretical support for clinical interventions.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Participants\u003c/h2\u003e \u003cp\u003eThis study enrolled adult PWE who received treatment in the Neurology Ward, Epilepsy and Movement Disorder Clinic, and Neurology Clinic of the First Affiliated Hospital of Harbin Medical University from January 1, 2022, to December 31, 2022. This study was approved by the Ethics Committee of the First Affiliated Hospital of Harbin Medical University (Ethics Approval No.: KY2021-0108). All participants voluntarily participated in the study and signed written informed consent forms.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInclusion and Exclusion Criteria\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eInclusion Criteria\u003c/h2\u003e \u003cp\u003e(1) Diagnosis consistent with the ILAE 2017 epilepsy diagnosis and classification criteria; (2) Stable condition, without severe organic brain diseases such as tumors, inflammation, or degenerative diseases; (3) Aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years, with sufficient cognitive ability to complete the questionnaire independently; (4) Diagnosed with epilepsy or receiving anti-seizure medication (ASM) for at least 3 months; (5) Voluntarily participating in the study and signing the informed consent form.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExclusion Criteria\u003c/h3\u003e\n\u003cp\u003e(1) Intellectual disability, disturbance of consciousness, cognitive dysfunction, or mental illness; (2) A history of long-term alcoholism, alcohol, or other substance addiction and abuse; (3) Status epilepticus, or critical illness combined with other severe organic lesions, malignant tumors, or diseases severely affecting quality of life (defined as patients with severe cardiopulmonary complications, such as myocardial infarction, heart failure, pneumonia, sepsis due to chronic obstructive pulmonary disease, renal vein thrombosis, or pressure ulcers).\u003c/p\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eThis study was a cross-sectional study. Relevant information was collected, including general social demographic data (name, gender, age, contact information, home address, residential status, marital status, education level, family per capita monthly income, etc.) and disease-related data (diagnosis type, disease duration, anti-seizure medication (ASM) use, current seizure frequency, comorbidity with chronic diseases, comorbidity with mental illness, etc.). The epilepsy diagnosis type was determined according to the ILAE 2017 epilepsy classification guidelines.\u003c/p\u003e \u003cp\u003eValidated scales were used for assessment:\u003c/p\u003e \u003cp\u003eChinese version of the Kilifi Stigma Scale for Epilepsy (KSSE-C) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]: This scale is a specific tool for assessing epilepsy-related stigma with good cultural adaptability in Chinese population, which includes 18 items and adopts a 3-point scoring system: \"Not at all\" = 0 points, \"Sometimes\" = 1 point, \"Always\" = 2 points, with a total score ranging from 0 to 30 points\u0026mdash;higher scores indicate a stronger level of epilepsy-related stigma. The scale focuses on two core dimensions of epilepsy stigma (enacted stigma and felt stigma), including public discrimination, self-shame, and social restrictions caused by epilepsy. Compared with other Chinese stigma scales for chronic diseases, KSSE-C has higher specificity for epilepsy and is more suitable for assessing the stigma level of Chinese PWE.\u003c/p\u003e \u003cp\u003eGeneral Social Alienation Scale (GAS) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]: To assess the degree of social alienation. This scale consists of 15 items covering 4 dimensions: sense of social isolation (5 items), sense of powerlessness (4 items), sense of self-alienation (3 items), and sense of meaninglessness (3 items). It uses a 4-point Likert scale: \"Strongly disagree\" = 1 point, \"Disagree\" = 2 points, \"Agree\" = 3 points, \"Strongly agree\" = 4 points. The total score ranges from 15 to 60 points, with higher scores indicating greater social alienation. Unlike KSSE-C (epilepsy-specific), GAS assesses general social alienation unrelated to specific diseases. The Chinese version of GAS has been validated and shows good psychometric properties [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eQuality of Life Assessment Inventory for Epilepsy 31 (QOLIE-31): To measure the quality of life. Developed by Professor Gramer from the United States, this scale includes 31 items covering 7 dimensions and 1 general item. Scoring method: Initial score of each dimension\u0026thinsp;=\u0026thinsp;sum of item scores\u0026thinsp;\u0026divide;\u0026thinsp;number of items; total score\u0026thinsp;=\u0026thinsp;sum of initial scores multiplied by their respective weights. Higher total scores indicate better quality of life [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMini-Mental State Examination (MMSE) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]: For quality control to screen cognitive function (participants with cognitive impairment were excluded, and the scale was not included in statistical analysis). Compiled by Folstein, this is a widely used screening tool for cognitive impairment. Permission to use the MMSE was obtained from the copyright holder (Psychological Assessment Resources, Inc.) and a copy of the permission is attached as Additional file 1. This study adopted the Chinese revised version and cut-off values by Luo Guogang et al. The scale includes 30 items (19 major items) with a total score of 30 points. Cut-off values for cognitive dysfunction were adjusted by education level: illiterate (no formal education)\u0026thinsp;\u0026le;\u0026thinsp;19 points; primary school (education duration\u0026thinsp;\u0026le;\u0026thinsp;6 years)\u0026thinsp;\u0026le;\u0026thinsp;22 points; secondary school or above (education duration\u0026thinsp;\u0026gt;\u0026thinsp;6 years)\u0026thinsp;\u0026le;\u0026thinsp;26 points. Participants with an MMSE score below the corresponding cut-off value were considered to have cognitive impairment (which may affect questionnaire results) and were excluded from the study.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eValid questionnaire data were entered into the database, and IBM SPSS Statistics for Windows, Version 26.0 (IBM Corp., Armonk, NY, USA) was used for statistical analysis. The following statistical methods were applied:(1) Descriptive statistics: Presented as mean\u0026plusmn;standard deviation (SD) for normally distributed continuous variables, median (interquartile range, IQR) for non-normally distributed continuous variables, and n (%) for categorical variables. This method was used to describe general demographic information and scores of stigma, social alienation, and quality of life scales.(2) One-way analysis of variance (ANOVA): Used to analyze the effects of demographic characteristics and epilepsy-related factors on stigma in adult PWE. Partial eta-squared (η\u0026sup2;) was calculated as the effect size, with interpretation criteria: small effect (η\u0026sup2;=0.01), medium effect (η\u0026sup2;=0.06), large effect (η\u0026sup2;=0.14)[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].(3) Correlation analysis: Spearman\u0026rsquo;s rank correlation test was used to explore the correlations between stigma, social alienation, and quality of life.(4) Univariate analysis: Linear regression was used to analyze the effects of general information variables, social alienation, and quality of life on stigma.(5) Multiple linear regression analysis: Variables with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in the univariate analysis (age, marital status, education level, family per capita monthly income, disease duration, ASM use, etc.) were included as independent variables, and the total KSSE-C score was used as the dependent variable to establish a multiple stepwise regression model. This model was used to identify independent influencing factors of stigma.\u003c/p\u003e \u003cp\u003eA two-tailed P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eParticipant Characteristics and Univariate Analysis of Stigma\u003c/h2\u003e \u003cp\u003eA total of 135 potential PWE were screened, and 8 were excluded due to low MMSE scores (below education-specific cut-off values). Finally, 127 eligible participants were included in the analysis. The mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) scores of each assessment scale in the included 127 eligible participants were as follows: KSSE-C (12.65\u0026thinsp;\u0026plusmn;\u0026thinsp;7.99), General Social Alienation Scale (GAS) (32.46\u0026thinsp;\u0026plusmn;\u0026thinsp;13.19), Quality of Life Assessment Inventory for Epilepsy 31 (QOLIE-31) (112.69\u0026thinsp;\u0026plusmn;\u0026thinsp;38.64), and Mini-Mental State Examination (MMSE) (27.35\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12).\u003c/p\u003e \u003cp\u003eThe demographic and clinical characteristics of the participants are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Univariate analysis showed that factors including age, marital status, residential status, education level, family per capita monthly income, disease duration, and ASM use had significant impacts on stigma in PWE (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with large to medium effect sizes:\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eImpact of General Demographic and Clinical Characteristics on Stigma in People with Epilepsy (n\u0026thinsp;=\u0026thinsp;127)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategories(n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStigma(KSSE-C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGAS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQOLIE-31\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003et/F\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eEffect size (η\u0026sup2;)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale(n\u0026thinsp;=\u0026thinsp;53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e12.87\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e32.15\u0026thinsp;\u0026plusmn;\u0026thinsp;13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e113.26\u0026thinsp;\u0026plusmn;\u0026thinsp;37.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.799\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale(n\u0026thinsp;=\u0026thinsp;74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e12.50\u0026thinsp;\u0026plusmn;\u0026thinsp;7.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e32.68\u0026thinsp;\u0026plusmn;\u0026thinsp;13.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e112.24\u0026thinsp;\u0026plusmn;\u0026thinsp;39.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge(years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;29(n\u0026thinsp;=\u0026thinsp;43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e12.53\u0026thinsp;\u0026plusmn;\u0026thinsp;8.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e30.86\u0026thinsp;\u0026plusmn;\u0026thinsp;12.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e115.42\u0026thinsp;\u0026plusmn;\u0026thinsp;36.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20.646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.241 (large)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;59(n\u0026thinsp;=\u0026thinsp;69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.43\u0026thinsp;\u0026plusmn;\u0026thinsp;6.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e31.78\u0026thinsp;\u0026plusmn;\u0026thinsp;13.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e114.15\u0026thinsp;\u0026plusmn;\u0026thinsp;38.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60(n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e23.20\u0026thinsp;\u0026plusmn;\u0026thinsp;4.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e38.67\u0026thinsp;\u0026plusmn;\u0026thinsp;13.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e98.73\u0026thinsp;\u0026plusmn;\u0026thinsp;42.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHome address\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural (n\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e18.53\u0026thinsp;\u0026plusmn;\u0026thinsp;6.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e36.94\u0026thinsp;\u0026plusmn;\u0026thinsp;12.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e102.31\u0026thinsp;\u0026plusmn;\u0026thinsp;39.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.198 (large)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTown (n\u0026thinsp;=\u0026thinsp;35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e12.57\u0026thinsp;\u0026plusmn;\u0026thinsp;6.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e32.06\u0026thinsp;\u0026plusmn;\u0026thinsp;13.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e113.68\u0026thinsp;\u0026plusmn;\u0026thinsp;37.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCity (n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e9.57\u0026thinsp;\u0026plusmn;\u0026thinsp;7.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e30.25\u0026thinsp;\u0026plusmn;\u0026thinsp;12.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e117.54\u0026thinsp;\u0026plusmn;\u0026thinsp;38.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLive alone (n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e11.00\u0026thinsp;\u0026plusmn;\u0026thinsp;5.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e31.23\u0026thinsp;\u0026plusmn;\u0026thinsp;12.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e116.85\u0026thinsp;\u0026plusmn;\u0026thinsp;36.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.003**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.090 (medium)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWith spouse (n\u0026thinsp;=\u0026thinsp;78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e11.17\u0026thinsp;\u0026plusmn;\u0026thinsp;7.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e31.59\u0026thinsp;\u0026plusmn;\u0026thinsp;12.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e114.92\u0026thinsp;\u0026plusmn;\u0026thinsp;38.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWith others (n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e16.47\u0026thinsp;\u0026plusmn;\u0026thinsp;8.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e35.81\u0026thinsp;\u0026plusmn;\u0026thinsp;13.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e107.53\u0026thinsp;\u0026plusmn;\u0026thinsp;40.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnmarried (n\u0026thinsp;=\u0026thinsp;24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.71\u0026thinsp;\u0026plusmn;\u0026thinsp;6.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e30.96\u0026thinsp;\u0026plusmn;\u0026thinsp;12.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e116.33\u0026thinsp;\u0026plusmn;\u0026thinsp;36.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.157 (large)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried (n\u0026thinsp;=\u0026thinsp;78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.83\u0026thinsp;\u0026plusmn;\u0026thinsp;7.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e31.45\u0026thinsp;\u0026plusmn;\u0026thinsp;12.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e115.07\u0026thinsp;\u0026plusmn;\u0026thinsp;38.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDivorced (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e20.27\u0026thinsp;\u0026plusmn;\u0026thinsp;6.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e37.53\u0026thinsp;\u0026plusmn;\u0026thinsp;13.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e101.27\u0026thinsp;\u0026plusmn;\u0026thinsp;41.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidowed(n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e20.10\u0026thinsp;\u0026plusmn;\u0026thinsp;6.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e38.10\u0026thinsp;\u0026plusmn;\u0026thinsp;14.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e99.80\u0026thinsp;\u0026plusmn;\u0026thinsp;42.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIlliterate (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e18.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e39.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e95.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.223 (large)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary School (n\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e21.12\u0026thinsp;\u0026plusmn;\u0026thinsp;5.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e37.82\u0026thinsp;\u0026plusmn;\u0026thinsp;12.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e100.47\u0026thinsp;\u0026plusmn;\u0026thinsp;38.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJunior High (n\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e18.64\u0026thinsp;\u0026plusmn;\u0026thinsp;4.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e35.64\u0026thinsp;\u0026plusmn;\u0026thinsp;13.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e105.86\u0026thinsp;\u0026plusmn;\u0026thinsp;39.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSenior High (n\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.10\u0026thinsp;\u0026plusmn;\u0026thinsp;7.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e31.23\u0026thinsp;\u0026plusmn;\u0026thinsp;12.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e114.68\u0026thinsp;\u0026plusmn;\u0026thinsp;37.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity and above(n\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e8.07\u0026thinsp;\u0026plusmn;\u0026thinsp;6.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e29.52\u0026thinsp;\u0026plusmn;\u0026thinsp;12.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e120.34\u0026thinsp;\u0026plusmn;\u0026thinsp;36.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eper capita\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003emonthly income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1000 (n\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e21.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e39.50\u0026thinsp;\u0026plusmn;\u0026thinsp;14.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e92.50\u0026thinsp;\u0026plusmn;\u0026thinsp;45.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.253 (large)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1000\u0026ndash;2999(n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e19.26\u0026thinsp;\u0026plusmn;\u0026thinsp;5.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e37.79\u0026thinsp;\u0026plusmn;\u0026thinsp;12.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e103.68\u0026thinsp;\u0026plusmn;\u0026thinsp;38.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3000\u0026ndash;4999(n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.44\u0026thinsp;\u0026plusmn;\u0026thinsp;7.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e31.05\u0026thinsp;\u0026plusmn;\u0026thinsp;12.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e115.82\u0026thinsp;\u0026plusmn;\u0026thinsp;37.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5000 (n\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e7.44\u0026thinsp;\u0026plusmn;\u0026thinsp;5.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e29.36\u0026thinsp;\u0026plusmn;\u0026thinsp;12.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e122.48\u0026thinsp;\u0026plusmn;\u0026thinsp;36.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnosis type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot specified (n\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e13.48\u0026thinsp;\u0026plusmn;\u0026thinsp;8.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e32.86\u0026thinsp;\u0026plusmn;\u0026thinsp;13.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e111.76\u0026thinsp;\u0026plusmn;\u0026thinsp;39.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFocal (n\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e13.47\u0026thinsp;\u0026plusmn;\u0026thinsp;7.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e32.18\u0026thinsp;\u0026plusmn;\u0026thinsp;12.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e113.15\u0026thinsp;\u0026plusmn;\u0026thinsp;38.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneralized (n\u0026thinsp;=\u0026thinsp;47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e11.26\u0026thinsp;\u0026plusmn;\u0026thinsp;8.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e32.63\u0026thinsp;\u0026plusmn;\u0026thinsp;13.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e114.02\u0026thinsp;\u0026plusmn;\u0026thinsp;37.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisease duration(years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;5 (n\u0026thinsp;=\u0026thinsp;73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.22\u0026thinsp;\u0026plusmn;\u0026thinsp;7.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e31.02\u0026thinsp;\u0026plusmn;\u0026thinsp;12.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e115.64\u0026thinsp;\u0026plusmn;\u0026thinsp;37.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.132 (medium)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u0026ndash;10 (n\u0026thinsp;=\u0026thinsp;51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e15.73\u0026thinsp;\u0026plusmn;\u0026thinsp;7.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e34.86\u0026thinsp;\u0026plusmn;\u0026thinsp;13.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e108.35\u0026thinsp;\u0026plusmn;\u0026thinsp;39.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;11 years (n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e19.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e39.33\u0026thinsp;\u0026plusmn;\u0026thinsp;14.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e96.33\u0026thinsp;\u0026plusmn;\u0026thinsp;44.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eASM use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUntreated (n\u0026thinsp;=\u0026thinsp;19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.95\u0026thinsp;\u0026plusmn;\u0026thinsp;6.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e31.16\u0026thinsp;\u0026plusmn;\u0026thinsp;12.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e116.05\u0026thinsp;\u0026plusmn;\u0026thinsp;36.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.003**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.088 (medium)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMonotherapy (n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e10.84\u0026thinsp;\u0026plusmn;\u0026thinsp;7.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e31.48\u0026thinsp;\u0026plusmn;\u0026thinsp;12.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e114.82\u0026thinsp;\u0026plusmn;\u0026thinsp;38.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePolytherapy (n\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e15.80\u0026thinsp;\u0026plusmn;\u0026thinsp;8.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e35.65\u0026thinsp;\u0026plusmn;\u0026thinsp;13.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e107.91\u0026thinsp;\u0026plusmn;\u0026thinsp;40.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSeizure control\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUncontrolled (n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e14.10\u0026thinsp;\u0026plusmn;\u0026thinsp;7.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e34.25\u0026thinsp;\u0026plusmn;\u0026thinsp;13.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e109.85\u0026thinsp;\u0026plusmn;\u0026thinsp;39.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControlled(n\u0026thinsp;=\u0026thinsp;87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e11.99\u0026thinsp;\u0026plusmn;\u0026thinsp;8.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e31.64\u0026thinsp;\u0026plusmn;\u0026thinsp;12.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e115.29\u0026thinsp;\u0026plusmn;\u0026thinsp;37.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNote: 1. Data are presented as mean\u0026plusmn;standard deviation (SD) for continuous variables or number (n) for categorical variables.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e2. Dependent variable: Stigma score measured by the Chinese version of the Kilifi Stigma Scale for Epilepsy (KSSE-C), with a scale range of 0\u0026ndash;30 points (higher scores indicate stronger stigma).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e3. Statistical methods: Independent samples t-test was used for two-category variables, and one-way analysis of variance (ANOVA) was used for multi-category variables. Effect size was represented by partial eta-squared (η\u0026sup2;).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e4. Significance levels: **P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***P\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003e5. Abbreviations: KSSE-C=Chinese version of the Kilifi Stigma Scale for Epilepsy; GAS=General Social Alienation Scale; QOLIE-31=Quality of Life Assessment Inventory for Epilepsy 31; ASM=anti-seizure medication.\u003c/p\u003e\u003cp\u003eAge: The stigma score was highest in patients aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years (23.20\u0026thinsp;\u0026plusmn;\u0026thinsp;4.52), followed by those aged\u0026thinsp;\u0026le;\u0026thinsp;29 years (12.53\u0026thinsp;\u0026plusmn;\u0026thinsp;8.22), and lowest in patients aged 30\u0026ndash;59 years (10.43\u0026thinsp;\u0026plusmn;\u0026thinsp;6.54) (F\u0026thinsp;=\u0026thinsp;20.646, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u0026sup2;=0.241 [large effect]);\u003c/p\u003e \u003cp\u003eEducation level: Patients with university or above education had the lowest stigma score (8.07\u0026thinsp;\u0026plusmn;\u0026thinsp;6.77), while those with primary school education had the highest (21.12\u0026thinsp;\u0026plusmn;\u0026thinsp;5.15) (F\u0026thinsp;=\u0026thinsp;18.352, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u0026sup2;=0.223 [large effect]);\u003c/p\u003e \u003cp\u003eFamily per capita monthly income: Stigma scores decreased with increasing income, with the highest in patients with income\u0026thinsp;\u0026lt;\u0026thinsp;1000 CNY (21.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.24) and the lowest in those with income\u0026thinsp;\u0026ge;\u0026thinsp;5000 CNY (7.44\u0026thinsp;\u0026plusmn;\u0026thinsp;5.89) (F\u0026thinsp;=\u0026thinsp;21.714, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u0026sup2;=0.253 [large effect]);\u003c/p\u003e \u003cp\u003eDisease duration: Stigma scores increased with longer disease duration, with the highest in patients with duration\u0026thinsp;\u0026ge;\u0026thinsp;11 years (19.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08) and the lowest in those with duration 0\u0026ndash;5 years (10.22\u0026thinsp;\u0026plusmn;\u0026thinsp;7.31) (F\u0026thinsp;=\u0026thinsp;9.429, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u0026sup2;=0.132 [medium effect]);\u003c/p\u003e \u003cp\u003eASM use: Patients receiving polytherapy had a higher stigma score (15.80\u0026thinsp;\u0026plusmn;\u0026thinsp;8.14) than those receiving monotherapy (10.84\u0026thinsp;\u0026plusmn;\u0026thinsp;7.55) and untreated patients (10.95\u0026thinsp;\u0026plusmn;\u0026thinsp;6.95) (F\u0026thinsp;=\u0026thinsp;6.062, P\u0026thinsp;=\u0026thinsp;0.003, η\u0026sup2;=0.088 [medium effect]).\u003c/p\u003e \u003cp\u003eIn contrast, gender and diagnosis type had no significant effects on stigma (both P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Detailed data are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. According to the scoring criteria of the Chinese version of the Kilifi Stigma Scale for Epilepsy (KSSE-C, 0\u0026ndash;30 points), the stigma level of the included PWE was further classified: 28.3% (36/127) of patients had mild stigma (0\u0026ndash;10 points), 41.7% (53/127) had moderate stigma (11\u0026ndash;20 points), and 30.0% (38/127) had severe stigma (21\u0026ndash;30 points). The total proportion of patients with moderate to severe stigma reached 71.7%, which indicated that the stigma problem was widespread among adult PWE in China. This prevalence is consistent with the characteristics of epilepsy stigma in northern Chinese populations reported in previous relevant studies[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], further confirming the generality of the stigma problem in this region.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCorrelations Between Stigma, Social Alienation, and Quality of Life\u003c/h2\u003e \u003cp\u003eIn order to verify Hypothesis 1 and Hypothesis 2 of this study, Spearman rank correlation analysis was conducted to explore the correlation between stigma, social alienation and quality of life in PWE, and the results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Correlation analysis showed that stigma (KSSE-C score) was strongly positively correlated with social alienation (GAS score) (r\u0026thinsp;=\u0026thinsp;0.949, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), indicating that the higher the stigma, the more severe the social alienation. This correlation reflects the theoretical causal association between the two constructs: epilepsy-specific stigma induces social alienation, and social alienation further reinforces self-stigma, forming a bidirectional cycle[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Additionally, stigma was strongly negatively correlated with quality of life (QOLIE-31 score) (r=-0.960, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), meaning that the higher the stigma, the poorer the quality of life.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between stigma and social alienation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStigma(KSSE-C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSocial\u003c/p\u003e \u003cp\u003eAlienation(GAS)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStigma(KSSE-C)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e12.65\u0026thinsp;\u0026plusmn;\u0026thinsp;7.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.949***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlienation(GAS)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e32.46\u0026thinsp;\u0026plusmn;\u0026thinsp;13.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.949***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNotes: 1. Data are presented as mean\u0026plusmn;standard deviation (SD).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e2. Correlation analysis was performed using Spearman\u0026rsquo;s rank correlation test.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e3. Significance level: ***P\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e4. Abbreviations: KSSE-C=Chinese version of the Kilifi Stigma Scale for Epilepsy; GAS=General Social Alienation Scale.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between stigma and quality of life\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStigma(KSSE-C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQuality of Life(QOLIE-31)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStigma(KSSE-C)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e12.65\u0026thinsp;\u0026plusmn;\u0026thinsp;7.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.960***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eQuality of Life(QOLIE-31)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e112.69\u0026thinsp;\u0026plusmn;\u0026thinsp;38.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.960***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNotes: 1. Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e2. Correlation analysis was performed using Spearman\u0026rsquo;s rank correlation test.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e3. Significance level: ***P\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e4. Abbreviations: KSSE-C=Chinese version of the Kilifi Stigma Scale for Epilepsy; QOLIE-31\u0026thinsp;=\u0026thinsp;Quality of Life Assessment Inventory for Epilepsy 31.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe GAS and QOLIE-31 scores of participants in different subgroups are also shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. For example, patients with higher stigma (e.g., those with primary school education, income\u0026thinsp;\u0026lt;\u0026thinsp;1000 CNY) consistently had higher GAS scores and lower QOLIE-31 scores, which were consistent with the correlation results. The above correlation analysis results fully verified Hypothesis 1 and Hypothesis 2 of this study, confirming that the stigma level of PWE was significantly positively correlated with social alienation and significantly negatively correlated with quality of life.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eUnivariate and Multivariate Linear Regression Analysis of Stigma\u003c/h2\u003e \u003cp\u003eIn order to verify Hypothesis 3 of this study and identify the independent influencing factors of stigma in PWE, univariate linear regression analysis was first conducted to screen the significant influencing factors, and then multiple linear regression analysis was used for further verification, with the results shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Univariate linear regression analysis showed that age, home address, residential status, marital status, education level, family per capita monthly income, disease duration, and ASM use were significantly associated with stigma (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate linear regression analysis of stigma in people with epilepsy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent Variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003estandard error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStandardized\u003c/p\u003e \u003cp\u003ecoefficient(β)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender(Male vs. Female)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.799\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.004**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHome address\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-4.349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-5.624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidential status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-4.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-7.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily Per capita monthly income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-6.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-7.520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnostic type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisease duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eASM use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.004**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNotes: 1. Dependent variable: Total score of Chinese version of the Kilifi Stigma Scale for Epilepsy (KSSE-C), scale range: 0\u0026ndash;30 points.2. Data are presented as B value, standard error, standardized coefficient (β), t value, and P value.3. Significance levels: **P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***P\u0026thinsp;\u0026lt;\u0026thinsp;0.001.4. Abbreviations: ASM=anti-seizure medication; KSSE-C=Chinese version of the Kilifi Stigma Scale for Epilepsy.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate linear regression analysis of stigma in people with epilepsy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent Variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003estandard error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStandardized\u003c/p\u003e \u003cp\u003ecoefficient(β)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-3.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-4.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily Per capita monthly income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-4.133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.002**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisease duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.008**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConstant\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: 1. Dependent variable: Total score of Chinese version of the Kilifi Stigma Scale for Epilepsy (KSSE-C), scale range: 0\u0026ndash;30 points. Model R\u0026sup2;=0.683, F\u0026thinsp;=\u0026thinsp;42.857, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e2. Independent variables: Variables with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in univariate linear regression analysis (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) were included for stepwise screening, and only the above 4 variables entered the final model.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e3. Significance levels: **P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***P\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e4. Abbreviation: KSSE-C=Chinese version of the Kilifi Stigma Scale for Epilepsy.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThese significant variables were further included in the multivariate linear regression model to identify independent influencing factors. The results showed that education level (β=-0.326, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), family per capita monthly income (β=-0.289, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), marital status (β\u0026thinsp;=\u0026thinsp;0.215, P\u0026thinsp;=\u0026thinsp;0.002), and disease duration (β\u0026thinsp;=\u0026thinsp;0.187, P\u0026thinsp;=\u0026thinsp;0.008) were independent influencing factors of stigma in PWE (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The model explained 68.3% of the variance in stigma (R\u0026sup2;=0.683, F\u0026thinsp;=\u0026thinsp;42.857, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with higher education and income associated with lower stigma, divorced/widowed patients having higher stigma than married/unmarried patients, and longer disease duration linked to higher stigma. The above regression analysis results fully verified Hypothesis 3 of this study, confirming that education level, family per capita monthly income, marital status and disease duration are the independent influencing factors of stigma in PWE, and the direction of influence of each factor is completely consistent with the research hypothesis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eReliability of Assessment Scales\u003c/h2\u003e \u003cp\u003eThe internal consistency of the scales used in this study was satisfactory. The Cronbach's α coefficient was 0.83 for KSSE-C, 0.81 for GAS, 0.89 for QOLIE-31 (with dimension-specific α ranging from 0.76 to 0.91), and 0.85 for MMSE. The split-half reliability was 0.78 for GAS, 0.85 for QOLIE-31, and 0.81 for MMSE. The test-retest reliability of QOLIE-31 was 0.82. These values indicate good reliability and validity of the measurements in this study population.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated 127 adult PWE to explore stigma, social alienation, quality of life, and their relationships. The overall stigma score (KSSE-C) was 12.65\u0026thinsp;\u0026plusmn;\u0026thinsp;7.99, lower than that in foreign developing countries[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and consistent with Chinese adult PWE reported in domestic studies.\u003c/p\u003e \u003cp\u003e \u003cb\u003eVerification of Hypothesis 1 and Hypothesis 2: Conceptual Clarification of Stigma and Its Correlation with Social Alienation and Quality of Life\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs the core explanatory variable of this study, epilepsy-related stigma is a dual construct with \"social external pressure\" and \"individual internal psychology\" as the two core pillars, and the two dimensions interact and reinforce each other to form a continuous negative cycle for PWE. Stigma, as a core concept of this study, is defined as a multi-dimensional construct including enacted stigma (external discrimination) and felt stigma (internalized shame). The positive correlation between stigma and social alienation (r\u0026thinsp;=\u0026thinsp;0.949, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) confirmed Hypothesis 1, while the negative correlation with quality of life (r=-0.960, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) supported Hypothesis 2. Although KSSE-C and GAS have partial conceptual overlaps (e.g., social avoidance), they remain distinct constructs: KSSE-C focuses on epilepsy-specific stigma (enacted/felt stigma), while GAS assesses general social interaction failure[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The discriminant validity of these two scales has been verified in chronic disease populations[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], indicating that the high correlation observed in this study reflects the inherent theoretical association between epilepsy stigma and social alienation rather than measurement redundancy. Enacted stigma leads to social rejection, which induces patients' self-isolation (social alienation), and long-term social alienation further strengthens felt stigma, forming a vicious cycle[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe strong negative correlation between stigma and quality of life (r=-0.960, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) supported Hypothesis 2. This is consistent with previous studies[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], indicating that stigma undermines quality of life by two pathways: on the one hand, external discrimination restricts patients\u0026rsquo; educational, employment, and social opportunities[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]; on the other hand, internalized shame leads to anxiety, depression, and other mental health problems, further reducing their physical and psychological well-being.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eVerification of Hypothesis 3: Analysis of Independent Influencing Factors of Stigma in PWE\u003c/h2\u003e \u003cp\u003eThe results of multiple linear regression supported Hypothesis 3, identifying four independent influencing factors of stigma:\u003c/p\u003e \u003cp\u003eEducation level (β=-0.326, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001): Higher education level was associated with lower stigma. This is consistent with Scambler\u0026rsquo;s core theory[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u0026mdash;stigma is a dual construct of \"enacted stigma (external discrimination)\" and \"felt stigma (internalized shame)\", and individuals with higher education can better distinguish between objective discrimination and subjective evaluation, thus reducing the internalization of stigma. Patients with higher education are more likely to obtain scientific knowledge about epilepsy, reduce misunderstanding of the disease, and thus alleviate internalized shame. Meanwhile, they are more capable of coping with external discrimination, reducing the impact of enacted stigma[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFamily per capita monthly income (β=-0.289, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001): Higher income was a protective factor against stigma. Economic stability ensures the continuity of treatment, reduces the economic burden caused by the disease, and also enhances patients\u0026rsquo; social participation ability, reducing the sense of powerlessness and inferiority caused by economic constraints[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMarital status (β\u0026thinsp;=\u0026thinsp;0.215, P\u0026thinsp;=\u0026thinsp;0.002): Divorced/widowed patients had higher stigma than married/unmarried patients. Marriage provides important social support, including emotional comfort and practical help[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Divorced/widowed patients lack this support, making them more vulnerable to the impact of stigma and less able to cope with discrimination[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This finding reflects the unique role of marital support in buffering stigma in Chinese cultural context [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], which differs from cross-cultural evidence showing individualistic social support models in Western populations [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDisease duration (β\u0026thinsp;=\u0026thinsp;0.187, P\u0026thinsp;=\u0026thinsp;0.008): Longer disease duration was associated with higher stigma. Long-term illness brings continuous physical pain and social pressure, and repeated seizures may increase public discrimination, while patients\u0026rsquo; cumulative negative experiences further strengthen internalized stigma[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eInnovations and Limitations of the Study\u003c/h2\u003e \u003cp\u003eThe innovations of this study are as follows: First, it is one of the first studies to systematically verify the tripartite relationship between stigma, social alienation, and quality of life in Chinese PWE with rigorous cognitive screening, filling the gap in domestic research on 'cognitively intact samples'[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Second, it quantifies the relative influence of independent factors: education level (β=-0.326) is the most important protective factor against stigma, followed by family per capita monthly income (β=-0.289), while the impacts of marital status (β\u0026thinsp;=\u0026thinsp;0.215) and disease duration (β\u0026thinsp;=\u0026thinsp;0.187) are relatively weaker. This provides precise guidance for targeted interventions\u0026mdash;for example, disease cognition education for low-education groups should be prioritized over other interventions. Third, it confirms the unique role of marital support in Chinese cultural context, enriching cross-cultural evidence on epilepsy stigma[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study also has limitations: First, the sample size was small and single-center, which may limit the generalizability of the results. Second, the retrospective design could not verify the causal relationship between variables; future prospective studies are needed to explore the bidirectional interaction between stigma and social alienation. Third, only MMSE was used for cognitive screening, which has limitations in assessing crystallized intelligence and executive function[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]; future studies should combine Montreal Cognitive Assessment (MoCA) and other tools to improve the comprehensiveness of cognitive evaluation. Fourth, confounding factors such as social support were not included, which may affect the interpretation of the results. Fifth, self-reported scales may have response bias. Sixth, the sample size of illiterate patients was extremely small (n\u0026thinsp;=\u0026thinsp;1), which may lead to biased results in subgroup analysis; future studies should expand the sample size of low-education groups to improve statistical power.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eModerate to severe stigma is widespread among Chinese adult PWE, with 71.7% of the included patients having moderate or severe stigma (KSSE-C score\u0026thinsp;\u0026ge;\u0026thinsp;11 points). This high prevalence indicates that stigma is a significant psychosocial burden affecting the majority of PWE in this sample. The level of stigma is independently influenced by education level, family per capita monthly income, marital status, and disease duration. Furthermore, stigma is strongly positively correlated with social alienation and strongly negatively correlated with quality of life. The findings of this study provide a theoretical basis for clinical psychological intervention and social support for PWE. In clinical practice, targeted interventions should be carried out for high-risk groups: strengthening disease cognition education for low-education patients, providing economic assistance and treatment support for low-income patients, and enhancing social support for divorced/widowed patients. At the same time, public health education should be strengthened to reduce social discrimination against PWE, thereby improving their quality of life.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePWE: people with epilepsy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKSSE-C: Chinese version of the Kilifi Stigma Scale for Epilepsy\u003c/p\u003e\n\u003cp\u003eGAS: General Social Alienation Scale\u003c/p\u003e\n\u003cp\u003eQOLIE-31: Quality of Life Assessment Inventory for Epilepsy 31\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMMSE: Mini-Mental State Examination\u003c/p\u003e\n\u003cp\u003eASM: anti-seizure medication\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eILAE: International League Against Epilepsy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eANOVA: analysis of variance\u003c/p\u003e\n\u003cp\u003eSD: standard deviation\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participat\u003c/strong\u003ee\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of the First Affiliated Hospital of Harbin Medical University (Ethics Approval No.: KY2021-0108). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Written informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This manuscript does not contain any individual person\u0026rsquo;s data in any form (including individual details, images or videos).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available due to privacy reasons but are available from the corresponding author on reasonable request.\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\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the Natural Science Foundation of Heilongjiang Province (PL2025H078), the Education and Teaching Project of the First Clinical Medical College of Harbin Medical University (No. YDYYJX202214), the First Affiliated Hospital of Harbin Medical University Outstanding Young Medical Talents Training Program (2021J08), the Natural Science Foundation of Heilongjiang Province (YQ2021B007), the Key Project of the \u0026quot;14th Five-Year Plan\u0026quot; of Education Science in Heilongjiang Province (GJB1421276), and the Heilongjiang Province Outstanding Overseas Returnees Funding Program (Heiren Shehan〔2018〕No. 383).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShuo Huang: Conceptualization, Methodology, Formal analysis, Writing \u0026ndash; Original Draft.\u003cbr\u003e\u0026nbsp;Meng Zhang: Investigation, Data Curation, Formal analysis, Writing \u0026ndash; Review \u0026amp; Editing.\u003cbr\u003e\u0026nbsp;Yidan Feng: Investigation, Data Collection.\u003cbr\u003e\u0026nbsp;Ling Wang: Investigation, Data Collection.\u003cbr\u003e\u0026nbsp;Jing Yu: Writing \u0026ndash; Review \u0026amp; Editing.\u003cbr\u003e\u0026nbsp;Lifen Yao: Supervision, Writing \u0026ndash; Review \u0026amp; Editing.\u003cbr\u003e\u0026nbsp;All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWang XP, Li J, Zhang Y. Prevalence of epilepsy in China: A systematic review and meta-analysis [J]. Neurol Res, 2020, 42 (5): 389-396. \u003c/li\u003e\n\u003cli\u003eWijnen BFM, Schat SL, de Kinderen RJA, Colon AJ, Ossenblok PPW, Evers SMAA. Burden of disease of people with epilepsy during an optimized diagnostic trajectory: costs and quality of life. Epilepsy Res. 2018 Oct;146:87-93. \u003c/li\u003e\n\u003cli\u003eScambler G, Hopkins A. Generating a model of epileptic stigma: the role of qualitative analysis[J]. Social Science \u0026amp; Medicine, 1990, 30(11): 1187-1194. \u003c/li\u003e\n\u003cli\u003eFite RO, Guta MT. Stigma and associated factors among people with epilepsy in Ethiopia: A systematic review and meta-analysis. Epilepsy Behav. 2021 Apr;117:107872. \u003c/li\u003e\n\u003cli\u003eKwon CS, Jacoby A, Ali A, Austin J, Birbeck GL, Braga P, Cross JH, de Boer H, Dua T, Fernandes PT, Fiest KM, Goldstein J, Haut S, Lorenzetti D, Mifsud J, Moshe S, Parko KL, Tripathi M, Wiebe S, Jette N. Systematic review of frequency of felt and enacted stigma in epilepsy and determining factors and attitudes toward persons living with epilepsy-Report from the International League Against Epilepsy Task Force on Stigma in Epilepsy. Epilepsia. 2022 Mar;63(3):573-597. \u003c/li\u003e\n\u003cli\u003eIwayama T, Mizuno K, Yildiz E, Lim KS, Yi SM, Lynn YJ, Hin CW, Jean JCZ, Fong SL, Xuen Y, Qian OZ, Kuramochi I. A multicultural comparative study of self-stigma in epilepsy: Differences across four cultures. Epilepsia Open. 2024 Dec;9(6):2283-2293. \u003c/li\u003e\n\u003cli\u003eKleinman A, Wang WZ, Li SC, Cheng XM, Dai XY, Li KT, Kleinman J. The social course of epilepsy: chronic illness as social experience in interior China. Soc Sci Med. 1995 May;40(10):1319-30. \u003c/li\u003e\n\u003cli\u003eLi H, Jia J, Yang Z. Mini-Mental State Examination in Elderly Chinese: A Population-Based Normative Study. J Alzheimers Dis. 2016 May 7;53(2):487-96. \u003c/li\u003e\n\u003cli\u003eLee HJ, Choi EK, Park HB, Yang SH. Risk and protective factors related to stigma among people with epilepsy: An integrative review. Epilepsy Behav. 2020 Mar;104(Pt A):106908.\u003c/li\u003e\n\u003cli\u003eTsuji S. Social aspects of epilepsy: marriage, pregnancy, driving, antiepileptic drug withdrawal and against social stigma [J]. Rinsho Shinkeigaku, 2004, 44 (11): 865-867. \u003c/li\u003e\n\u003cli\u003eDeli A, Kinariwalla N, Calvello C, Capelli V, Neale M, Henderson R, Tristram M, Sen A. An evaluation of the psychosocial impact of epilepsy on marriage in the United Kingdom. Epilepsy Behav. 2019 May;94:204-208. \u003c/li\u003e\n\u003cli\u003eHu Y, Guo Y, Wang YQ, Du Q, Ding MP. [Reliability and validity of a Chinese version of the Quality of Life in Epilepsy Inventory (QOLIE-31-P)]. Zhejiang Da Xue Xue Bao Yi Xue Ban. 2009 Nov;38(6):605-10. \u003c/li\u003e\n\u003cli\u003eXu Z, Gao F, Fa A, Qu W, Zhang Z. Statistical power analysis and sample size planning for moderated mediation models. Behav Res Methods. 2024 Sep;56(6):6130-6149. \u003c/li\u003e\n\u003cli\u003eQin Y, Dai M, Chen L, Zhang T, Zhou N, Chen X. The relationship between ecological executive function and stigma among patients with epilepsy: The mediating effect of social support. Epilepsy Res. 2022 May;182:106919.\u003c/li\u003e\n\u003cli\u003eEngelhart P, Marcin C, Lerner J, Dill D, L\u0026apos;Italien G, Coric V, Matsumoto J, Potashman MH. Determinants of health-related quality of life of patients with focal epilepsy: A systematic literature review. Epileptic Disord. 2025 Feb;27(1):9-30.\u003c/li\u003e\n\u003cli\u003eMayor R, Gunn S, Reuber M, Simpson J. Experiences of stigma in people with epilepsy: A meta-synthesis of qualitative evidence. Seizure. 2022 Jan;94:142-160. \u003c/li\u003e\n\u003cli\u003eLi M, et al. Development and validation of the Epilepsy Stigma Scale (ESS) in Chinese populations [J]. Chin J Neurol, 2020, 53(6): 458-464.\u003c/li\u003e\n\u003cli\u003eReyes A, Hermann BP, Prabhakaran D, Ferguson L, Almane DN, Shih JJ, Iragui-Madoz VJ, Struck A, Punia V, Jones JE, Busch RM, McDonald CR. Validity of the MoCA as a cognitive screening tool in epilepsy: Are there implications for global care and research? Epilepsia Open. 2024 Aug;9(4):1526-1537. \u003c/li\u003e\n\u003cli\u003eMbuba CK, Abubakar A, Odermatt P, Newton CR, Carter JA. Development and validation of the Kilifi Stigma Scale for Epilepsy in Kenya. Epilepsy Behav. 2012 May;24(1):86-91. \u003c/li\u003e\n\u003cli\u003eChen W, Zhao SY, Luo J, Zhang JF. [Reliability and validity of the General Alienation Scale in Chinese college students]. Chinese Mental Health Journal. 2015;(10):780-784,5. (in Chinese)\u003c/li\u003e\n\u003cli\u003eFolstein MF, Folstein SE, McHugh PR. \u0026quot;Mini-mental state\u0026quot;. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975 Nov;12(3):189-98. \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":"people with epilepsy, stigma, social alienation, quality of life, KSSE-C, GAS, QOLIE-31","lastPublishedDoi":"10.21203/rs.3.rs-9539790/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9539790/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis study aims to investigate the current status of stigma and social alienation among people with epilepsy (PWE) and explore the correlation between stigma, social alienation, and quality of life in this population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 127 adult PWE who visited the neurology ward and epilepsy clinic of the First Affiliated Hospital of Harbin Medical University from January 1, 2022 to December 31, 2022, were enrolled. The general demographic and clinical characteristics questionnaire, Chinese version of the Kilifi Stigma Scale for Epilepsy (KSSE-C), General Social Alienation Scale (GAS), and Quality of Life Assessment Inventory for Epilepsy 31 (QOLIE-31) were used for data collection. Mini-Mental State Examination (MMSE) was applied for quality control (8 participants with cognitive impairment were excluded, with cut-off values adjusted by education level: illiterate\u0026thinsp;\u0026le;\u0026thinsp;19 points, primary school\u0026thinsp;\u0026le;\u0026thinsp;22 points, secondary school or above \u0026le;\u0026thinsp;26 points). This study was approved by the Ethics Committee of the First Affiliated Hospital of Harbin Medical University. All participants signed written informed consent forms. Data were analyzed using IBM SPSS Statistics for Windows, Version 26.0, including descriptive statistics, one-way analysis of variance (ANOVA) with effect size calculation, correlation analysis, univariate analysis, and multiple linear regression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCorrelation analysis indicated that stigma was positively correlated with social alienation (r\u0026thinsp;=\u0026thinsp;0.949, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and strongly negatively correlated with quality of life (r=-0.960, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Univariate analysis showed that factors such as age, marital and residential status, education level, family per capita monthly income, disease duration, and anti-seizure medication (ASM) use had significant impacts on stigma in PWE (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with large to medium effect sizes (η\u0026sup2;=0.132\u0026ndash;0.253). Multiple linear regression analysis revealed that education level (β=-0.326, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), family per capita monthly income (β=-0.289, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), marital status (β\u0026thinsp;=\u0026thinsp;0.215, P\u0026thinsp;=\u0026thinsp;0.002), and disease duration (β\u0026thinsp;=\u0026thinsp;0.187, P\u0026thinsp;=\u0026thinsp;0.008) were independent influencing factors of stigma in PWE.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eStigma is widespread among PWE. The stigma is influenced by multiple factors including education level, family per capita monthly income, marital status, and disease duration. Stigma is positively correlated with social alienation and negatively correlated with quality of life. All three research hypotheses proposed in this study were fully verified, providing a theoretical basis for clinical psychological intervention and social support for this population.\u003c/p\u003e","manuscriptTitle":"Study on the correlation between stigma, social alienation and quality of life in people with epilepsy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-06 11:24:25","doi":"10.21203/rs.3.rs-9539790/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":"a4eb9498-0045-4c11-af1b-f688b92f255a","owner":[],"postedDate":"May 6th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-13T00:48:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-12T01:52:51+00:00","index":35,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-11T09:33:02+00:00","index":34,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-09T18:58:37+00:00","index":33,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T13:41:12+00:00","index":32,"fulltext":""},{"type":"reviewerAgreed","content":"334516854485937887780212842396900560348","date":"2026-05-04T13:32:49+00:00","index":31,"fulltext":""},{"type":"reviewerAgreed","content":"260532557439397698535353916598650018974","date":"2026-05-03T12:54:08+00:00","index":30,"fulltext":""},{"type":"reviewerAgreed","content":"22192061293073395203984760703140375764","date":"2026-05-02T09:17:56+00:00","index":29,"fulltext":""},{"type":"reviewerAgreed","content":"81613439585802481993699090531995619582","date":"2026-04-30T11:55:36+00:00","index":28,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T00:55:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-06 11:24:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9539790","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9539790","identity":"rs-9539790","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}