The status and determinants of demoralization in stroke patients: a cross-sectional study in China

The status and determinants of demoralization in stroke patients: a cross-sectional study in China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The status and determinants of demoralization in stroke patients: a cross-sectional study in China Hongyan Yang, Ting Yang, Hui Wei, Miaomiao Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7212645/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background: Irreversible neurological trauma, long-term rehabilitation, disability, psychological issues, costly medical and financial burden, and difficulties in reintegration into the community may ultimately lead to demoralization in stroke survivors. However, the status and determinantsof demoralization in stroke patients are still unknown. Aim: To analyze the current status of demoralization in stroke patients, and explore factorsthat influenced demoralization in relation to demographic and stroke characteristics, and self-perceived burden. Methods: A cross-sectional study using the convenient sampling method was conducted to select the research objects of stroke patients who were inpatients in a general public hospital in Hangzhou, Zhejiang Province. The survey period was from January 2025 to May 2025. The Mandarin Version of the Demoralization Scaleand the Self-Perceived Burden Scale were used to assess demoralization and self-perceived burden, respectively. General information, including demographic data and stroke characteristics, was collected. The data was analyzed using SPSS 25.0 software. Results: This study included 376 stroke patients with a mean DS-MV score of 34.32 ± 11.249. Of these, 26 (6.9%) had mild demoralization, 296 (78.7%) had moderate demoralization, and 54 (14.4%) had severe demoralization. Considering a DS-MV score > 30 for detection,51.9% of stroke patientshad demoralization. Education level, comorbidity, number of stroke incidences, activity of daily living, and self-perceived burden level were the important factors associated with the severity of demoralization in stroke patients. Conclusions: Stroke patients exhibit a notable prevalence and severity of demoralization. Healthcare professionals should develop targeted interventions after stroke by considering sociodemographic (education level) and stroke characteristics (comorbidity, number of stroke incidences, and activity of daily living) and reducing self-perceived burden. Furthermore, stroke patients at high risk of demoralization should be promptly monitored. Stroke Demoralization Determinants Status Self-perceived burden Figures Figure 1 Figure 2 1. Introduction Stroke is the second-highest cause of death worldwide and the third-highest cause of disability [1]. In 2021, there were 7.3 million deaths from stroke, and 160.5 million disability-adjusted life-years (DALYs) from stroke, comprising 10.7% of all deaths and 5.6% of all DALYs from all causes [2]. Current estimates on the disease burden of stroke indicate that in China, the incidence rate of stroke increased by 86% from 1990 and there were roughly 3.94 million new stroke cases in 2019, with the largest share in the world [3]. The survival rate of stroke has increased steadily in the past 20 years, however, longer survival is often accompanied by long-term effects of the sequelae [4]. Half of stroke survivors are left disabled, with a third relying on others to assist with activities of daily living [5]. Psychological issues, such as depression and anxiety, may persist even after the physical symptoms have been stabilized. The incidence of depressive symptoms within 2 years after stroke was 11% to 41% [6], and approximately one-third of stroke patients at any time up to five years after stroke are affected by depressive symptoms [7]. Irreversible neurological trauma, long-term rehabilitation, disability, psychological issues, costly medical and financial burden, and difficulties in reintegration into the community may ultimately lead to demoralization in stroke survivors. Demoralization is a psychological distress state caused by a series of life events, which refers to inability to adapt or subjective incompetence when facing pressure, mainly manifested as a sense of powerlessness, loneliness, and despair [8]. The prevalence of demoralization in cancer patients ranges from 13.50% to 49.4% [9]. Demoralization can reduce an individual’s ability to cope with stressful events, which may lead to a series of adverse health outcomes, such as impaired physical symptoms, low adherence to rehabilitation treatment, limited social functioning, and compromised quality of life [10]. However, due to the fact that patients with demoralization often exhibit persistent depression and few symptoms of functioning-related impairment, they may be overlooked and considered a common response to stressful stimuli [11]. Robinson et al. [12] reported that there was a significant correlation between demoralization and the desire to hasten death, with high-demoralization patients having higher levels of suicidal ideation than low-demoralization patients. Vehling et al. [13] found clinically relevant demoralization frequently occurred independently of a mental disorder in patients with cancer and had a unique contribution to suicidal ideation. With the development of social medicine and health, mental health has attracted widespread attention in healthcare discussions. It has become an important indicator of the quality of care. However, there have been extensive studies focused on mental disorders in stroke patients such as depression, anxiety, and apathy [14-15], and less attention to demoralization. In addition, the research on demoralization mainly focuses on cancer [16], terminal illness [17], and Parkinson's disease [18]. We find a lack of studies on demoralization and its determinants in stroke patients. A meta-analysis involving 17,189 stroke survivors showed that, the pooled prevalence of suicidal ideation among stroke survivors was 12.25% [19]. In addition, depression is a particularly common and persistent psychological problem after stroke. Demoralization has been proven to be highly correlated with depression in cancer patients [20]. The Demoralization Hypothesis states that non-delusional awareness of one's social, cognitive, or occupational deterioration elicits depression and hopelessness [21]. Therefore, an urgent need exists to investigate the status and determinants of demoralization in stroke patients, which will help us improve clinical nursing practice in stroke care. Self-perceived burden refers to feelings such as reduced self-worth, shame, and blame, which are caused by the physical and psychological burden on the caregivers due to the limitation of physical activities [22]. The prevalence of self-perceived burden is quite high in stroke survivors, ranging from 65% to 70% [23-24]. SPB has been associated with expressions of a desire for death, self-reported suicidal ideation, and an interest in receiving physician-assisted suicide [25]. We already know that demoralization is related to suicidal ideation, however, it is unknown whether self-perceived burden could reinforce demoralization and lead to suicidal ideation. Therefore, it is necessary to explore the relationship between self-perceived burden and demoralization. Based on these premises, this study aimed to analyze the current status of demoralization in stroke patients and explored determinants that influenced demoralization in relation to demographic and stroke characteristics, and self-perceived burden. Our hypothesis posits that we will observe the demoralization experiences of stroke patients and identify the influencing factors associated with demoralization. 2. Methods 2.1 Design and participants This cross-sectional survey used the convenient sampling method to select the research objects of stroke patients who were inpatients in a general public hospital in Hangzhou, Zhejiang Province, and the survey time was from January 2025 to May 2025. Inclusion criteria: (1) Age ≥ 18 years old; (2) Patients diagnosed with stroke confirmed by imaging; (3) Clear consciousness and able to clearly understand the questionnaire content; (4) Voluntary participation in this study and signing informed consent. Exclusion criteria: (1) Patients with other major diseases, such as advanced cancer or critical diseases of the heart, liver, lungs, and kidneys; (2) suffering from serious mental illness. The sample size was determined using the G-Power 3.1.9.7 linear multiple regression algorithm. With an effect size of 0.15, an α value of 0.05, and an anticipated power (1-β) of 0.95, this study included 19 variables: 11 demographic and disease-related characteristics, and 8 dimensions related to the scale. The minimum required sample size was calculated to be 187 stroke patients, considering a 20% rate of invalid questionnaires, a minimum of 225 stroke patients were needed to meet the minimum sample size requirement. In total, 376 stroke patients completed the survey. 2.2 Measures 2.2.1 General information questionnaire The general information questionnaire collected demographic and stroke characteristics data. It included the following 2 sections: (1) demographic data on age, sex, education level, marital status, place of residence, occupational status, and medical payment method; (2) disease-related characteristics, including type of stroke, comorbidity, number of stroke incidences, and activity of daily living (ADL). 2.2.2 Mandarin Version of the Demoralization Scale (DS-MV) The DS-MV was translated from the Demoralization Scale developed by Kissane et al. [ 26 ], consists of 24 items covering five dimensions: loss of meaning, dysphoria, disheartenment, helplessness, and sense of failure. The DS-MV score uses a five-point Likert scale, from “strong disagreement” to “strong agreement”. The higher the total score of the scale is, the higher the level of demoralization. According to Kissane et al. [ 26 ], a score of 30 was proposed as the demarcation value. Mullane et al. [ 27 ] suggested categorizing the degree of demoralization in patients based on mean ± standard deviation. The DS-MV has acceptable psychometric properties when used in Taiwanese patients with cancer [ 28 ]. In this study, the Cronbach's α coefficient for the DS-MV was 0.748. 2.2.3 Self-Perceived Burden Scale (SPBS) The SPBS, developed by Cousineau et al. [ 29 ], consists of 10 items covering three dimensions: body burden, economic burden, and emotional burden. The SPBS score uses a five-point Likert scale, from “never” (1 point) to “always” (5 points). The total score is the sum of individual items (only the eighth item was reverse-scored; all the others were positive). The SPBS score is classified into the following four groups: <20, not significant; 20–29, mild; 30–39, moderate; and ≥ 40, severe self-perceived burden. The higher the total score, the higher the individual’s self‐perceived burden level. In this study, the Cronbach's α coefficient for the SPBS was 0.782. 2.3 Statistical analysis Data analysis was conducted using SPSS 25.0. Significance was set at p < 0.05, employing two-tailed tests. Demographic/stroke characteristics were presented as frequency/percentage and scale scores were presented as mean ± standard deviation. The t-test or analysis of variance was used to explore the differences of demoralization in different demographic and stroke characteristics. Pearson correlation analysis was used to explore the relationships between variables. Multiple linear regression was used to analyze influencing factors. 2.4 Ethical considerations The study procedures were approved by the Ethics Committee of the corresponding author's hospital (IRB No.20240095). Written consent was obtained from all study participants. The study adhered to the reporting guidelines set forth by the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement [ 30 ]. 3. Results 3.1 Levels of demoralization in stroke patients The average total score of DS-MV was (34.32 ± 11.249). According to demoralization level classification proposed by Kissane et al. [ 26 ], 181 (48.1%) did not have demoralization (DS-MV score ≤ 30), and 195 (51.9%) had significant demoralization (DS-MV score > 30). According to demoralization level classification proposed by Mullane et al. [ 27 ], 26 (6.9%) patients had mild demoralization, 296 (78.7%) had moderate demoralization, and 54 (14.4%) had severe demoralization. The levels of demoralization in stroke patients are presented in Table 1 . Table 1 Levels of demoralization in stroke patients (n = 376). Levels of demoralization Grading Frequency (n) Percentage (%) Mild levels of demoralization 45.569 54 14.4% No apparent demoralization ≤ 30 181 48.1% Significant demoralization >30 195 51.9% Note: The degree of demoralization of stroke patients was categorized into three levels based on the criterion of mean ± standard deviation (SD), mild demoralization 45.569 (mean + SD = 34.32 + 11.249 = 45.569), moderate demoralization as 23.071 ~ 45.569. 3.2 Association of demoralization with demographic and stroke characteristics The DS-MV scores of stroke patients were significantly different in age, education level, marital status, occupational status, medical payment method, comorbidity, number of stroke incidences, ADL (p 0.05). The univariate analysis of demographic and stroke characteristics is presented in Table 2 . Table 2 The univariate analysis of demographic and stroke characteristics (N = 376). Variables N( %) Mean ( SD) t/F P value Age F = 9.278 <0.001 18 ~ 44 53( 14.1) 40.00( 16.44) 45 ~ 59 96( 25.5) 34.76(9.59) ≥ 60 227( 60.4) 32.81( 9.96) Sex t = 0.770 0.442 Male 263( 69.9) 34.61( 11.10) Female 113( 30.1) 33.64(11.61) Education level F = 6.438 <0.001 Primary school or below 131(34.8) 36.69(9.66) Middle school 157( 41.8) 34.18(12.70) High school/technical school 62( 16.5) 32.77(7.64) Bachelor or higher 26(6.9) 26.85(13.05) Marital status t=−2.074 0.042 Married 321(85.4) 33.66(10.20) Single/Divorced/Widowed 55( 14.6) 38.18(15.62) Place of residence t=−0.647 0.518 Urban 196(52.1) 33.96(10.65) Rural 180(47.9) 34.71(11.88) Occupational status F = 9.111 <0.001 Unemployed 58(15.4 ) 39.55(16.02) Employed 126(33.5) 34.63(9.83) Retired 192(51.1) 32.54(9.85) Medical payment method t = 2.969 0.004 Self-pay 53( 14.1) 39.36(13.73) Medical Insurance 323(85.9) 33.49(10.59) Type of stroke F = 0.920 0.399 Ischemic stroke 338( 89.9) 34.22(11.38) Hemorrhagic stroke 32(8.5 ) 34.19(9.81) Mixed stroke 6(1.6 ) 40.50(10.75) Comorbidity t=−2.795 0.005 Yes 273(72.6) 35.31(10.46) No 101(26.9) 31.67(12.92) Number of stroke incidences F = 18.405 <0.001 1 297(79.0 ) 32.89(10.19) 2 61(16.2 ) 37.41(11.90) ≥ 3 18( 4.8) 47.39(15.27) Activity of daily living F = 18.709 <0.001 No dependence 212(56.4) 32.24(11.12) Mild dependence 131(34.8) 36.60(10.14) Moderate dependence 17(4.5) 27.94(2.44) Heavy dependence 16(4.3) 50.00(10.61) Note: SD: standard deviation; t: independent samples t-tests; F: one-way analysis of variance. 3.3 The association between demoralization and self-perceived burden The average total score of DS-MV was (34.32 ± 11.249), and the average total score of SPBS was (23.08 ± 7.547). Pearson rank correlation test showed a positive association between demoralization and self-perceived burden (r = 0.691, p < 0.001). An ANOVA was conducted using demoralization as the categorical variable and self‐perceived burden as the continuous variable, and the results showed that the self‐perceived burden scores increased with the severity of demoralization overall but decreased in moderate demoralization (F = 129.020, p <0.001, Fig. 1 ). An ANOVA was conducted using self‐perceived burden as the categorical variable and demoralization as the continuous variable, and the outcomes showed that demoralization scores increased linearly with the severity of self‐perceived burden (F = 123.054, P <0.001, Fig. 2 ). 3.4 Multivariate analysis of demoralization Five variables were significantly associated with the total DS-MV score, including education level, comorbidity, number of stroke incidences, ADL, and self-perceived burden level. The multiple linear regression model explained 56.0% of the variance in the total DS-MV score (R 2 = 0.571, adjusted R 2 = 0.560). The multiple linear regression of factors of demoralization in stroke is presented in Table 3 . Table 3 Multiple linear regression of factors of demoralization in stroke (N = 376). Variable Unstandardized coefficient Standardized coefficient P value 95% confidence interval B Standard error β t Lower Upper Constant 16.666 3.743 4.453 0 9.305 24.026 Age -0.333 0.859 -0.022 -0.387 0.699 -2.022 1.357 Education level -2.75 0.46 -0.217 -5.975 <0.001 -3.656 -1.845 Marital status 1.119 1.178 0.035 0.949 0.343 -1.199 3.436 Occupational status Unemployed 1.152 1.293 0.037 0.891 0.373 -1.39 3.695 Retired 0.504 1.244 0.022 0.405 0.686 -1.944 2.951 Medical payment method -2.131 1.158 -0.066 -1.841 0.066 -4.408 0.145 Comorbidity 3.647 0.934 0.147 3.907 <0.001 1.811 5.483 Number of stroke incidences 2.755 0.751 0.131 3.666 <0.001 1.277 4.232 Activity of daily living 1.717 0.542 0.118 3.17 0.002 0.652 2.782 Self-perceived burden 7.308 0.457 0.601 16 <0.001 6.41 8.206 Note: R² = 0.571, adjust R² = 0.560, F = 48.662, P <0.001. 4. Discussion 4.1 High prevalence of demoralization in stroke patients As we all know, this was the first report on the status and determinants of demoralization in stroke patients in China. Unexpectedly, the prevalence of demoralization in stroke patients was very high. Considering a DS-MV score > 30 for detection, 51.9% of stroke patients had demoralization, which was much higher than that of Parkinson's patients [ 31 ]. The mean demoralization score of stroke patients was 34.32 ± 11.249, with 78.7% of patients exhibiting moderate demoralization and 14.4% of patients exhibiting severe demoralization. Compared with cancer patients [ 32 ], stroke patients have a higher level of demoralization. Although stroke occurs as an acute event, patients often face long-term and multidimensional rehabilitation, which affects the quality of life of patients and increases the economic burden. In addition, patients often experience movement disorder, speech dysfunction, cognitive dysfunction, and psychological disorders, which greatly affect their social roles and functions. So stroke patients are prone to demoralization. Previous studies [ 33 – 34 ] have shown a positive correlation between demoralization and suicidal ideation. The association between demoralization and suicidal ideation is higher than that between depression and suicidal ideation, and patients with demoralization have stronger suicidal mobility and higher suicide mortality than those with depression. However, in clinical practice, demoralization often manifests as persistent low mood, which is easily masked by other symptoms, leading to diagnostic difficulties. Therefore, medical staff should pay close attention to the psychological state of stroke patients, regularly assess demoralization, identify high-risk patients for demoralization early, and provide targeted intervention measures. Mindfulness-integrated cognitive behavior has been proven to have positive therapeutic effects on demoralization, which includes a set of evidence-based techniques to increase self-awareness, self-control, and self-efficacy in various areas of life [ 35 ]. 4.2 The demoralization level in stroke patients is influenced by multiple factors In our study, education level, comorbidity, number of stroke incidences, ADL, and self-perceived burden level were the important factors associated with the severity of demoralization in stroke patients. Our findings showed that stroke patients with lower education level were more likely to be demoralized, which is consistent with prior studies [ 36 – 37 ]. Usually, patients with higher education level may receive better quality education, including psychological training, which makes it easier to understand the condition and face the disease more rationally. Simultaneously, a low level of education may mean lower income, making it difficult to afford expensive treatment costs, and thus more likely to experience a higher level of demoralization. Results further showed comorbidity was a predictor of demoralization level in stroke patients. The overwhelming majority of stroke patients exhibit comorbidity in China. Zhao et al. [ 38 ] included 2539 acute ischemic stroke patients, with 90% exhibiting multimorbidity (≥ 2 comorbidities). The more comorbidities a patient has, the more complex their condition becomes, requiring more time and effort to balance disease management with daily life and work. Secondly, patients with excessive comorbidities need to participate in multiple treatment trajectories, which can increase their time burden, transportation burden, and economic burden during the treatment process, leading to an increased treatment burden for patients. Furthermore, having a high number of comorbidities may mean that patients need to take multiple medications, leading to an increased drug burden. Additionally, the more frequent the stroke attacks, the higher the demoralization level in stroke patients. The frequency of stroke attacks indicates the severity and control of the disease. Patients with more episodes often have more severe illnesses, which limits their social interactions. As the frequency of attacks increases, the psychological burden on patients increases, and they gradually lose confidence in disease management. Subjectively, they are unwilling to communicate with others, isolate themselves, and their sense of social alienation increases, which are not conducive to the recovery of role functions [ 39 ]. The long-term existence of this situation can increase despair and helplessness, and expensive medical costs can also increase psychological pressure, ultimately leading to the demoralization. The study also demonstrated that ADL was a significant predictor for demoralization. Poor ADL often means that stroke patients cannot fully take care of themselves, and largely depend on their caregivers in daily life, which leads them to feel extremely guilty and perceive burden. Stroke is a leading cause of disability and morbidity associated with increased economic burden due to post-stroke care and rehabilitation. It can be interpreted that patients may worry about their stroke-related disabilities, which may cause them to be abandoned. Furthermore, self-perceived burden has a positive predictive effect on demoralization. Self‐perceived burden is a common psychological characteristic in patients with chronic diseases and is associated with physical conditions and negative psychology, including depression and suicidal ideation [ 40 ]. It has been found that self‐perceived burden may be higher among those with other disabling but nonfatal conditions, such as stroke [ 40 ]. It should be noted that previous studies [ 9 , 17 ] did not find self‐perceived burden to be a significant predictor for demoralization. In addition, we have preliminarily found that low self‐perceived burden may also indicate moderate demoralization. Such evidence suggests that early identification and specific treatment for self‐perceived burden may prevent or reduce the sense of demoralization. Overall, our findings emphasize the need to assess the status and determinants of demoralization in stroke patients, to improve the quality of life of stroke patients. 5. Limitations Some limitations need to be addressed. First, the cross-sectional design was used in this study, the lack of qualitative and mixed methods of research endangers a deeper understanding of the demoralization characteristics. Future qualitative studies are necessary to capture trends, specific experiences, and insights into demoralization. Second, considering that demoralization level is a dynamic indicator, longitudinal studies are also needed. Third, this study selected stroke patients only from one hospital with the convenience sampling method, and the sample may not fully represent the entire stroke population. Multi-center studies are needed to determine a widespread belief in results in the future. Finally, self-report measures may produce response biases. In the future, self-evaluation may be conducted in conjunction with peer evaluation to more accurately portray the characteristics of demoralization. 6. Conclusions Our study provided a reasonably clear picture of the status and determinants of demoralization in stroke patients. The prevalence of demoralization in stroke patients was quite high, influenced by various factors. However, demoralization is often neglected in clinical practice. Healthcare professionals should develop targeted interventions after stroke by considering sociodemographic (education level) and stroke characteristics (comorbidity, number of stroke incidences, and ADL) and reducing self-perceived burden. Furthermore, stroke patients at high risk of demoralization should be promptly monitored. Declarations Author Contributions: Hongyan Yang: Conceptualization, Methodology, Data curation, Software, Validation, Investigation, Formal analysis, Writing-original draft. Ting Yang : Conceptualization, Methodology, Software, Formal analysis. Hui Wei : Data curation, Investigation. Miaomiao Liu : Supervision, Validation, Writing–reviewing and editing. Acknowledgments: We thank the participants for their active cooperation. Declaration of Competing Interest: The authors have no conflict of interest to declare. Funding: This study was funded by the Zhejiang Province Medical Science and Technology Project (2024KY1058). Clinical Trial Number: Not applicable Data Availability Declaration: The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request. Ethics Approval and Consent to Participate: Statement that all methods are performed in accordance with relevant guidelines and requlations. This study received approval from the Human Research and Ethics Committee of The Second Affiliated Hospital of Zhejiang University of Medicine, China (IRB No.20240095). Informed consent was obtained from all individual participants included in the study. Consent for publication: Not applicable References Feigin VL, Brainin M, Norrving B, et al. World Stroke Organization: Global Stroke Fact Sheet 2025. Int J Stroke . 2025;20(2):132-144. doi:10.1177/17474930241308142 GBD 2021 Stroke Risk Factor Collaborators. Global, regional, and national burden of stroke and its risk factors, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet Neurol. 2024 Oct;23(10):973-1003. doi: 10.1016/S1474-4422(24)00369-7 Ma Q, Li R, Wang L, et al. Temporal trend and attributable risk factors of stroke burden in China, 1990-2019: an analysis for the Global Burden of Disease Study 2019. Lancet Public Health. 2021;6(12):e897-e906. doi:10.1016/S2468-2667(21)00228-0 Patel MD, Tilling K, Lawrence E, et al. Relationships between long-term stroke disability, handicap and health-related quality of life. Age Ageing. 2006 May;35(3):273-9. Markus HS. Reducing disability after stroke. Int J Stroke. 2022;17(3):249-250. Guo J, Wang J, Sun W, et al. The advances of post-stroke depression: 2021 update. J Neurol. 2022 Mar;269(3):1236-1249. Kutlubaev MA, Hackett ML. Part II: predictors of depression after stroke and impact of depression on stroke outcome: an updated systematic review of observational studies. Int J Stroke. 2014 Dec;9(8):1026-36. Mehnert A,Vehling S,Höcker A,et al. Demoralization and depression in patients with advanced cancer:validation of the German version of the Demoralization Scale[J]. J Pain Symptom Manage,2011,42(5):768-776. Wang Y, Sun H, Ji Q, Wu Q, Wei J, Zhu P. Prevalence, Associated Factors and Adverse Outcomes of Demoralization in Cancer Patients: A Decade of Systematic Review. Am J Hosp Palliat Care. 2023 Nov;40(11):1216-1230. doi: 10.1177/10499091231154887. Bovero A, Opezzo M, Tesio V. Relationship between demoralization and quality of life in end-of-life cancer patients. Psychooncology. 2023;32(3):429-437. doi:10.1002/pon.6095 Fava GA, Guidi J. Clinical Characterization of Demoralization. Psychother Psychosom. 2023;92(3):139-147. doi: 10.1159/000530760. Robinson S, Kissane DW, Brooker J, Hempton C, Burney S. The Relationship Between Poor Quality of Life and Desire to Hasten Death: A Multiple Mediation Model Examining the Contributions of Depression, Demoralization, Loss of Control, and Low Self-worth. J Pain Symptom Manage. 2017 Feb;53(2):243-249. doi: 10.1016/j.jpainsymman.2016.08.013. Vehling S, Kissane DW, Lo C, Glaesmer H, Hartung TJ, Rodin G, Mehnert A. The association of demoralization with mental disorders and suicidal ideation in patients with cancer. Cancer. 2017 Sep 1;123(17):3394-3401. doi: 10.1002/cncr.30749. Almhdawi KA, Alazrai A, Kanaan S, et al. Post-stroke depression, anxiety, and stress symptoms and their associated factors: A cross-sectional study. Neuropsychol Rehabil. 2021;31(7):1091-1104. doi:10.1080/09602011.2020.1760893 Pallucca C, Lisiecka-Ford DM, Wood L, et al. Apathy After Stroke[J]. Neurology,2024,102(3):e208052. Shao Q, Li Y, Lin L, Boardman M, Hamadi H, Zhao M. Demoralization syndrome and its impact factors among cancer patients in China. J Psychosoc Oncol. 2024;42(3):365-380. doi: 10.1080/07347332.2023.2249895 Chan WCH, Yu CTK, Kwok DKS, Wan JKM. Prevalence and factors associated with demoralization in palliative care patients: A cross-sectional study from Hong Kong. Palliat Support Care. 2024 Aug;22(4):709-717. de Figueiredo JM, Zhu B, Patel AS, Kohn R, Koo BB, Louis ED. Differential impact of resilience on demoralization and depression in Parkinson disease. Front Psychiatry. 2023 Jul 24;14:1207019. doi: 10.3389/fpsyt.2023.1207019. Chen X, Zhang H, Xiao G, Lv C. Prevalence of suicidal ideation among stroke survivors: A systematic review and meta-analysis. Top Stroke Rehabil. 2021 Oct;28(7):545-555. doi: 10.1080/10749357.2020.1846933. Tang PL, Wang HH, Chou FH. A Systematic Review and Meta-Analysis of Demoralization and Depression in Patients With Cancer. Psychosomatics. 2015 Nov-Dec;56(6):634-43. doi: 10.1016/j.psym.2015.06.005. Drake RE, Gates C, Whitaker A, Cotton PG. Suicide among schizophrenics: a review. Compr Psychiatry. 1985 Jan-Feb;26(1):90-100. doi: 10.1016/0010-440x(85)90053-7. Cousineau N, McDowell I, Hotz S, Hébert P. Measuring chronic patients' feelings of being a burden to their caregivers: development and preliminary validation of a scale. Med Care. 2003 Jan;41(1):110-8. doi: 10.1097/00005650-200301000-00013. McPherson CJ, Wilson KG, Chyurlia L, Leclerc C. The balance of give and take in caregiver–partner relationships: an examination of self-perceived burden, relationship equity, and quality of life from the perspective of care recipients following stroke. Rehabil Psychol. 2010;55(2):194–203. doi: 10.1037/a0019359. Ren H, Liu C, Li J, Yang R, Ma F, Zhang M, Wang R, Gan L. Self-perceived Burden in the Young and Middle-aged Inpatients with Stroke: A Cross-sectional Survey. Rehabil Nurs. 2016 Mar-Apr;41(2):101-11. doi: 10.1002/rnj.193. Wilson KG, Dalgleish TL, Chochinov HM, Chary S, Gagnon PR, Macmillan K, De Luca M, O’Shea F, Kuhl D, Fainsinger RL. Mental disorders and the desire for death in patients receiving palliative care for cancer. BMJ Support Palliat Care. 2016;6(2):170–177. doi: 10.1136/bmjspcare-2013-000604 Kissane DW, Wein S, Love A, Lee XQ, Kee PL, Clarke DM. The Demoralization Scale: a report of its development and preliminary validation. J Palliat Care. 2004;20(4):269-276. Mullane M, Dooley B, Tiernan E, Bates U. Validation of the Demoralization Scale in an Irish advanced cancer sample. Palliat Support Care. 2009 Sep;7(3):323-30. Hung HC, Chen HW, Chang YF, Yang YC, Liu CL, Hsieh RK, Leu YS, Chen YJ, Wang TE, Tsai LY, Liu SI, Fang CK. Evaluation of the reliability and validity of the Mandarin Version of Demoralization Scale for cancer patients. J Intern Med Taiwan. 2010;21:427–435. Cousineau N, McDowell I, Hotz S, Hébert P. Measuring chronic patients' feelings of being a burden to their caregivers: development and preliminary validation of a scale. Med Care. 2003 Jan;41(1):110-8. von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. Int J Surg. 2014;12(12):1495-1499. Koo BB, Chow CA, Shah DR, Khan FH, Steinberg B, Derlein D, Nalamada K, Para KS, Kakade VM, Patel AS, de Figueiredo JM, Louis ED. Demoralization in Parkinson disease. Neurology. 2018 May 1;90(18):e1613-e1617. doi: 10.1212/WNL.0000000000005425. Chang TG, Huang PC, Hsu CY, Yen TT. Demoralization in oral cancer inpatients and its association with spiritual needs, quality of life, and suicidal ideation: a cross-sectional study. Health Qual Life Outcomes. 2022 Apr 2;20(1):60. doi: 10.1186/s12955-022-01962-6. Chytas V, Costanza A, Mazzola V, Luthy C, Bondolfi G, Cedraschi C. Demoralization and Suicidal Ideation in Chronic Pain Patients. Psychol Res Behav Manag. 2023 Mar 5;16:611-617. Luo Y, Lai Q, Huang H, Luo J, Miao J, Liao R, Yang Z, Zhang L. Risk factor analysis and nomogram construction for predicting suicidal ideation in patients with cancer. BMC Psychiatry. 2022 May 24;22(1):353. Soleymani Moghadam M, Parvizifard A, Foroughi A, Ahmadi SM, Farshchian N. An investigation of the effect of mindfulness-integrated cognitive behavior therapy on demoralization, body image, and sexual function in Iranian women with breast cancer: a randomized controlled trial. J Cancer Res Clin Oncol. 2024 Mar 14;150(3):128. doi: 10.1007/s00432-024-05655-z. Tang L, Li Z, Pang Y. The differences and the relationship between demoralization and depression in Chinese cancer patients. Psychooncology. 2020 Mar;29(3):532-538. doi: 10.1002/pon.5296. Li YC, Ho CH, Wang HH. Demoralization in Cancer Patients and Related Factors in Taiwan. Cancer Nurs. 2017 Jan/Feb;40(1):E54-E60. doi: 10.1097/NCC.0000000000000352. Zhao H, Qian Y, Zhou Y, Zhang D, Zhao Z, Zhang W, Shan C, Wang Y, Chen Z, Wang J, Pei L, Zhang Q, Zhou Q, Xu Y, Ning M, Buonanno FS, Sun C, Song B. Association of multimorbidity with biological age acceleration in acute ischemic stroke patients: a cross-sectional study. QJM. 2025 Jul 3:hcaf148. doi: 10.1093/qjmed/hcaf148 McCurley JL, Funes CJ, Zale EL, Lin A, Jacobo M, Jacobs JM, Salgueiro D, Tehan T, Rosand J, Vranceanu AM. Preventing Chronic Emotional Distress in Stroke Survivors and Their Informal Caregivers. Neurocrit Care. 2019 Jun;30(3):581-589. doi: 10.1007/s12028-018-0641-6 Kowal J, Wilson KG, McWilliams LA, Péloquin K, Duong D. Self-perceived burden in chronic pain: relevance, prevalence, and predictors. Pain. 2012;153(8):1735-1741. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 28 Nov, 2025 Reviews received at journal 13 Sep, 2025 Reviewers agreed at journal 13 Sep, 2025 Reviews received at journal 13 Sep, 2025 Reviewers agreed at journal 09 Sep, 2025 Reviewers agreed at journal 03 Sep, 2025 Reviewers invited by journal 02 Sep, 2025 Editor assigned by journal 28 Aug, 2025 Editor invited by journal 06 Aug, 2025 Submission checks completed at journal 01 Aug, 2025 First submitted to journal 01 Aug, 2025 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-7212645","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":510979774,"identity":"dc013ccc-bb17-40a7-9228-0110bd1eac06","order_by":0,"name":"Hongyan Yang","email":"","orcid":"","institution":"Second Affiliated Hospital of Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Hongyan","middleName":"","lastName":"Yang","suffix":""},{"id":510979775,"identity":"3bde562c-479d-4c48-b4f6-163a4e10e922","order_by":1,"name":"Ting Yang","email":"","orcid":"","institution":"Second Affiliated Hospital of Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Ting","middleName":"","lastName":"Yang","suffix":""},{"id":510979776,"identity":"c0308257-2145-4bdb-b621-3d95a7c1d7f2","order_by":2,"name":"Hui Wei","email":"","orcid":"","institution":"Second Affiliated Hospital of Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Wei","suffix":""},{"id":510979777,"identity":"2fe1480a-f8f0-419a-ab22-268cc4e3ff93","order_by":3,"name":"Miaomiao Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIie3RMQrCQBBA0QmBtRlJu6LoFTbYCBEsLLxGbEwlWFnPIsQmB4hYeAZvkLCgTbBOYRHwApYpFDRWVnHtBPd3A/OYYgBMph/MachVcS2HXYDkOTIN0opU6G6iWV+fiHxCbWRqSq9Rh0BukUBUwU5mAq5LBc6W6oW1lVTwQTCXlAkrPing56Se2J2UhEBvvoJM2M1QgeB+PWF8StxndsAqctchWJGEjX2siKVDOKahK6OZG8NhkUanAHn+gYyO68vlVg57vVjti3LpdZ34A3m7l7yeibr7zxz6YtlkMpn+qgcDgUbtEeoYagAAAABJRU5ErkJggg==","orcid":"","institution":"Second Affiliated Hospital of Zhejiang University","correspondingAuthor":true,"prefix":"","firstName":"Miaomiao","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-07-25 09:23:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7212645/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7212645/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90905331,"identity":"8a90593c-f681-4711-9f8e-0f34779b179b","added_by":"auto","created_at":"2025-09-09 13:04:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":55981,"visible":true,"origin":"","legend":"\u003cp\u003eThe association between self-perceived burden score and the severity of demoralization\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7212645/v1/9f6c8ca710b7ad51a2b2344d.png"},{"id":90904712,"identity":"3713c962-aea5-49d7-b259-d2dfa68e1249","added_by":"auto","created_at":"2025-09-09 12:56:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":57023,"visible":true,"origin":"","legend":"\u003cp\u003eThe association between demoralization score and the severity of self-perceived burden\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7212645/v1/dd3eee19ba4827555d5cf589.png"},{"id":90907091,"identity":"1647e0e8-1523-4594-9a27-1c582d5b489f","added_by":"auto","created_at":"2025-09-09 13:20:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1277763,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7212645/v1/a182bc9f-79c2-4838-9a9f-462fe2b84dce.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The status and determinants of demoralization in stroke patients: a cross-sectional study in China","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eStroke is the second-highest cause of death worldwide and the third-highest cause of disability [1]. In 2021, there were 7.3 million deaths from stroke, and 160.5 million disability-adjusted life-years (DALYs) from stroke, comprising 10.7% of all deaths and 5.6% of all DALYs from all causes [2]. Current estimates on the disease burden of stroke indicate that in China, the incidence rate of stroke increased by 86% from 1990 and there were roughly 3.94 million new stroke cases in 2019, with the largest share in the world [3].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe survival rate of stroke has increased steadily in the past 20 years, however, longer survival is often accompanied by long-term effects of the sequelae [4].\u0026nbsp;Half of stroke survivors are left disabled, with a third relying on others to assist with activities of daily living\u0026nbsp;[5]. Psychological issues, such as depression and anxiety, may persist even after the physical symptoms have been stabilized. The incidence of depressive symptoms within 2 years after stroke was 11% to 41% [6], and approximately one-third of stroke patients at any time up to five years after stroke are affected by depressive symptoms [7]. Irreversible neurological trauma, long-term rehabilitation, disability, psychological issues, costly medical and financial burden, and difficulties in reintegration into the community may ultimately lead to demoralization in stroke survivors.\u003c/p\u003e\n\u003cp\u003eDemoralization is a psychological distress state caused by a series of life events, which refers to inability to adapt or subjective incompetence when facing pressure, mainly manifested as a sense of powerlessness, loneliness, and despair [8]. The prevalence of demoralization in cancer patients ranges from 13.50% to 49.4% [9]. Demoralization can reduce an individual\u0026rsquo;s ability to cope with stressful events, which may lead to a series of adverse health outcomes, such as impaired physical symptoms, low adherence to rehabilitation treatment, limited social functioning, and compromised quality of life [10]. However, due to the fact that patients with demoralization often exhibit persistent depression and few symptoms of functioning-related impairment, they may be overlooked and considered a common response to stressful stimuli [11]. Robinson\u0026nbsp;et al.\u0026nbsp;[12]\u0026nbsp;reported that there was a significant correlation between demoralization\u0026nbsp;and the\u0026nbsp;desire\u0026nbsp;to hasten death, with high-demoralization\u0026nbsp;patients having higher levels of suicidal ideation than low-demoralization\u0026nbsp;patients. Vehling et\u0026nbsp;al. [13] found clinically relevant demoralization frequently occurred independently of a mental disorder in patients with cancer and had a unique contribution to suicidal ideation.\u003c/p\u003e\n\u003cp\u003eWith the development of social medicine and health, mental health has attracted widespread attention in healthcare discussions. It has become an important indicator of the quality of care. However, there have been extensive studies focused on mental disorders in stroke patients such as depression, anxiety, and\u0026nbsp;apathy\u0026nbsp;[14-15], and less attention to demoralization. In addition, the research on\u0026nbsp;demoralization\u0026nbsp;mainly focuses on cancer [16], terminal illness [17], and Parkinson\u0026apos;s disease [18]. We find a lack of studies on demoralization and its\u0026nbsp;determinants\u0026nbsp;in\u0026nbsp;stroke\u0026nbsp;patients. A meta-analysis\u0026nbsp;involving 17,189 stroke survivors showed that, the pooled prevalence of suicidal ideation among stroke survivors was 12.25%\u0026nbsp;[19]. In addition,\u0026nbsp;depression is a particularly common and persistent psychological problem after stroke. Demoralization\u0026nbsp;has been proven to be highly correlated with depression in cancer patients [20].\u0026nbsp;The Demoralization Hypothesis states that non-delusional awareness of one\u0026apos;s social, cognitive, or occupational deterioration elicits depression and hopelessness [21].\u0026nbsp;Therefore,\u0026nbsp;an urgent need exists to\u0026nbsp;investigate the status and\u0026nbsp;determinants\u0026nbsp;of demoralization in stroke patients, which will help us improve clinical nursing practice in stroke care.\u003c/p\u003e\n\u003cp\u003eSelf-perceived burden refers to feelings such as reduced self-worth, shame, and blame, which are caused by the physical and psychological burden on the caregivers due to the limitation of physical activities [22]. The prevalence of self-perceived burden is quite high in stroke survivors, ranging from 65% to 70% [23-24]. SPB has been associated with expressions of a desire for death, self-reported\u0026nbsp;suicidal ideation,\u0026nbsp;and an interest in receiving physician-assisted suicide [25]. We already know that demoralization is related to\u0026nbsp;suicidal ideation, however, it is unknown whether self-perceived burden could reinforce demoralization and lead to\u0026nbsp;suicidal ideation. Therefore, it is necessary to explore the relationship between self-perceived burden and demoralization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBased on these premises, this study aimed to analyze the current status of demoralization in stroke patients and explored determinants that influenced demoralization in relation to demographic and stroke characteristics, and self-perceived burden. Our hypothesis posits that we will observe the demoralization experiences of stroke patients and identify the influencing factors associated with demoralization.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Design and participants\u003c/h2\u003e\n \u003cp\u003eThis cross-sectional survey used the convenient sampling method to select the research objects of stroke patients who were inpatients in a general public hospital in Hangzhou, Zhejiang Province, and the survey time was from January 2025 to May 2025. Inclusion criteria: (1) Age\u0026thinsp;\u0026ge;\u0026thinsp;18 years old; (2) Patients diagnosed with stroke confirmed by imaging; (3) Clear consciousness and able to clearly understand the questionnaire content; (4) Voluntary participation in this study and signing informed consent. Exclusion criteria: (1) Patients with other major diseases, such as advanced cancer or critical diseases of the heart, liver, lungs, and kidneys; (2) suffering from serious mental illness.\u003c/p\u003e\n \u003cp\u003eThe sample size was determined using the G-Power 3.1.9.7 linear multiple regression algorithm. With an effect size of 0.15, an \u0026alpha; value of 0.05, and an anticipated power (1-\u0026beta;) of 0.95, this study included 19 variables: 11 demographic and disease-related characteristics, and 8 dimensions related to the scale. The minimum required sample size was calculated to be 187 stroke patients, considering a 20% rate of invalid questionnaires, a minimum of 225 stroke patients were needed to meet the minimum sample size requirement. In total, 376 stroke patients completed the survey.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Measures\u003c/h2\u003e\n \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.1 General information questionnaire\u003c/h2\u003e\n \u003cp\u003eThe general information questionnaire collected demographic and stroke characteristics data. It included the following 2 sections: (1) demographic data on age, sex, education level, marital status, place of residence, occupational status, and medical payment method; (2) disease-related characteristics, including type of stroke, comorbidity, number of stroke incidences, and activity of daily living (ADL).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.2 Mandarin Version of the Demoralization Scale (DS-MV)\u003c/h2\u003e\n \u003cp\u003eThe DS-MV was translated from the Demoralization Scale developed by Kissane et al. [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e], consists of 24 items covering five dimensions: loss of meaning, dysphoria, disheartenment, helplessness, and sense of failure. The DS-MV score uses a five-point Likert scale, from \u0026ldquo;strong disagreement\u0026rdquo; to \u0026ldquo;strong agreement\u0026rdquo;. The higher the total score of the scale is, the higher the level of demoralization. According to Kissane et al. [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e], a score of 30 was proposed as the demarcation value. Mullane et al. [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e] suggested categorizing the degree of demoralization in patients based on mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. The DS-MV has acceptable psychometric properties when used in Taiwanese patients with cancer [\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e]. In this study, the Cronbach\u0026apos;s \u0026alpha; coefficient for the DS-MV was 0.748.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.3 Self-Perceived Burden Scale (SPBS)\u003c/h2\u003e\n \u003cp\u003eThe SPBS, developed by Cousineau et al. [\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e], consists of 10 items covering three dimensions: body burden, economic burden, and emotional burden. The SPBS score uses a five-point Likert scale, from \u0026ldquo;never\u0026rdquo; (1 point) to \u0026ldquo;always\u0026rdquo; (5 points). The total score is the sum of individual items (only the eighth item was reverse-scored; all the others were positive). The SPBS score is classified into the following four groups: \u0026lt;20, not significant; 20\u0026ndash;29, mild; 30\u0026ndash;39, moderate; and \u0026ge;\u0026thinsp;40, severe self-perceived burden. The higher the total score, the higher the individual\u0026rsquo;s self‐perceived burden level. In this study, the Cronbach\u0026apos;s \u0026alpha; coefficient for the SPBS was 0.782.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Statistical analysis\u003c/h2\u003e\n \u003cp\u003eData analysis was conducted using SPSS 25.0. Significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, employing two-tailed tests. Demographic/stroke characteristics were presented as frequency/percentage and scale scores were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. The t-test or analysis of variance was used to explore the differences of demoralization in different demographic and stroke characteristics. Pearson correlation analysis was used to explore the relationships between variables. Multiple linear regression was used to analyze influencing factors.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Ethical considerations\u003c/h2\u003e\n \u003cp\u003eThe study procedures were approved by the Ethics Committee of the corresponding author\u0026apos;s hospital (IRB No.20240095). Written consent was obtained from all study participants. The study adhered to the reporting guidelines set forth by the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Levels of demoralization in stroke patients\u003c/h2\u003e\n \u003cp\u003eThe average total score of DS-MV was (34.32\u0026thinsp;\u0026plusmn;\u0026thinsp;11.249). According to demoralization level classification proposed by Kissane et al. [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e], 181 (48.1%) did not have demoralization (DS-MV score\u0026thinsp;\u0026le;\u0026thinsp;30), and 195 (51.9%) had significant demoralization (DS-MV score\u0026thinsp;\u0026gt;\u0026thinsp;30). According to demoralization level classification proposed by Mullane et al. [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e], 26 (6.9%) patients had mild demoralization, 296 (78.7%) had moderate demoralization, and 54 (14.4%) had severe demoralization. The levels of demoralization in stroke patients are presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLevels of demoralization in stroke patients (n\u0026thinsp;=\u0026thinsp;376).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLevels of demoralization\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGrading\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFrequency (n)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMild levels of demoralization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;23.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate levels of demoralization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.071\u0026thinsp;~\u0026thinsp;45.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e78.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh levels of demoralization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;45.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo apparent demoralization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSignificant demoralization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eNote: The degree of demoralization of stroke patients was categorized into three levels based on the criterion of mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), mild demoralization\u0026thinsp;\u0026lt;\u0026thinsp;16.45(mean\u0026ndash; SD\u0026thinsp;=\u0026thinsp;34.32-11.249\u0026thinsp;=\u0026thinsp;23.071), high demoralization\u0026thinsp;\u0026gt;\u0026thinsp;45.569 (mean\u0026thinsp;+\u0026thinsp;SD\u0026thinsp;=\u0026thinsp;34.32\u0026thinsp;+\u0026thinsp;11.249\u0026thinsp;=\u0026thinsp;45.569), moderate demoralization as 23.071\u0026thinsp;~\u0026thinsp;45.569.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Association of demoralization with demographic and stroke characteristics\u003c/h2\u003e\n \u003cp\u003eThe DS-MV scores of stroke patients were significantly different in age, education level, marital status, occupational status, medical payment method, comorbidity, number of stroke incidences, ADL (p\u0026lt;0.05), but there was no significant difference in sex, place of residence, and type of stroke (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The univariate analysis of demographic and stroke characteristics is presented in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe univariate analysis of demographic and stroke characteristics (N\u0026thinsp;=\u0026thinsp;376).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN(\u0026thinsp;%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u0026thinsp;(\u0026thinsp;SD)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003et/F\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u0026thinsp;=\u0026thinsp;9.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026thinsp;~\u0026thinsp;44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53(\u0026thinsp;14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40.00(\u0026thinsp;16.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u0026thinsp;~\u0026thinsp;59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96(\u0026thinsp;25.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34.76(9.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e227(\u0026thinsp;60.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.81(\u0026thinsp;9.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003et\u0026thinsp;=\u0026thinsp;0.770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.442\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e263(\u0026thinsp;69.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34.61(\u0026thinsp;11.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e113(\u0026thinsp;30.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.64(11.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u0026thinsp;=\u0026thinsp;6.438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary school or below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e131(34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36.69(9.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e157(\u0026thinsp;41.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34.18(12.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh school/technical school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e62(\u0026thinsp;16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.77(7.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBachelor or higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26(6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26.85(13.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003et=\u0026minus;2.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.042\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e321(85.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.66(10.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle/Divorced/Widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55(\u0026thinsp;14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38.18(15.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003et=\u0026minus;0.647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e196(52.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.96(10.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e180(47.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34.71(11.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupational status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u0026thinsp;=\u0026thinsp;9.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58(15.4\u0026thinsp;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39.55(16.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e126(33.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34.63(9.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e192(51.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.54(9.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedical payment method\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003et\u0026thinsp;=\u0026thinsp;2.969\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSelf-pay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53(\u0026thinsp;14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39.36(13.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedical Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e323(85.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33.49(10.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of stroke\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u0026thinsp;=\u0026thinsp;0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.399\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIschemic stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e338(\u0026thinsp;89.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34.22(11.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHemorrhagic stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32(8.5\u0026thinsp;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34.19(9.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixed stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(1.6\u0026thinsp;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40.50(10.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003et=\u0026minus;2.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e273(72.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35.31(10.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e101(26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31.67(12.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of stroke incidences\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u0026thinsp;=\u0026thinsp;18.405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e297(79.0\u0026thinsp;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.89(10.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e61(16.2\u0026thinsp;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37.41(11.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(\u0026thinsp;4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47.39(15.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eActivity of daily living\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u0026thinsp;=\u0026thinsp;18.709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e212(56.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.24(11.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMild dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e131(34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36.60(10.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27.94(2.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeavy dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16(4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50.00(10.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eNote: SD: standard deviation; t: independent samples t-tests; F: one-way analysis of variance.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 The association between demoralization and self-perceived burden\u003c/h2\u003e\n \u003cp\u003eThe average total score of DS-MV was (34.32\u0026thinsp;\u0026plusmn;\u0026thinsp;11.249), and the average total score of SPBS was (23.08\u0026thinsp;\u0026plusmn;\u0026thinsp;7.547). Pearson rank correlation test showed a positive association between demoralization and self-perceived burden (r\u0026thinsp;=\u0026thinsp;0.691, p \u0026lt; 0.001). An ANOVA was conducted using demoralization as the categorical variable and self‐perceived burden as the continuous variable, and the results showed that the self‐perceived burden scores increased with the severity of demoralization overall but decreased in moderate demoralization (F\u0026thinsp;=\u0026thinsp;129.020, p \u0026lt;0.001, Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). An ANOVA was conducted using self‐perceived burden as the categorical variable and demoralization as the continuous variable, and the outcomes showed that demoralization scores increased linearly with the severity of self‐perceived burden (F\u0026thinsp;=\u0026thinsp;123.054, P \u0026lt;0.001, Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 Multivariate analysis of demoralization\u003c/h2\u003e\n \u003cp\u003eFive variables were significantly associated with the total DS-MV score, including education level, comorbidity, number of stroke incidences, ADL, and self-perceived burden level. The multiple linear regression model explained 56.0% of the variance in the total DS-MV score (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.571, adjusted R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.560). The multiple linear regression of factors of demoralization in stroke is presented in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultiple linear regression of factors of demoralization in stroke (N\u0026thinsp;=\u0026thinsp;376).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eUnstandardized\u003c/p\u003e\n \u003cp\u003ecoefficient\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStandardized\u003c/p\u003e\n \u003cp\u003ecoefficient\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e95% confidence\u003c/p\u003e\n \u003cp\u003einterval\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStandard\u003c/p\u003e\n \u003cp\u003eerror\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLower\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUpper\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16.666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.699\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.357\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.845\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.436\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupational status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.695\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.951\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedical payment method\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-2.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.841\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-4.408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.934\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.483\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of stroke incidences\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.755\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.232\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eActivity of daily living\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.717\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.782\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelf-perceived burden\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.206\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003eNote: R\u0026sup2; = 0.571, adjust R\u0026sup2; = 0.560, \u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;48.662, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1 High prevalence of demoralization in stroke patients\u003c/h2\u003e\n \u003cp\u003eAs we all know, this was the first report on the status and determinants of demoralization in stroke patients in China. Unexpectedly, the prevalence of demoralization in stroke patients was very high. Considering a DS-MV score\u0026thinsp;\u0026gt;\u0026thinsp;30 for detection, 51.9% of stroke patients had demoralization, which was much higher than that of Parkinson\u0026apos;s patients [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. The mean demoralization score of stroke patients was 34.32\u0026thinsp;\u0026plusmn;\u0026thinsp;11.249, with 78.7% of patients exhibiting moderate demoralization and 14.4% of patients exhibiting severe demoralization. Compared with cancer patients [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e], stroke patients have a higher level of demoralization.\u003c/p\u003e\n \u003cp\u003eAlthough stroke occurs as an acute event, patients often face long-term and multidimensional rehabilitation, which affects the quality of life of patients and increases the economic burden. In addition, patients often experience movement disorder, speech dysfunction, cognitive dysfunction, and psychological disorders, which greatly affect their social roles and functions. So stroke patients are prone to demoralization. Previous studies [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e] have shown a positive correlation between demoralization and suicidal ideation. The association between demoralization and suicidal ideation is higher than that between depression and suicidal ideation, and patients with demoralization have stronger suicidal mobility and higher suicide mortality than those with depression. However, in clinical practice, demoralization often manifests as persistent low mood, which is easily masked by other symptoms, leading to diagnostic difficulties. Therefore, medical staff should pay close attention to the psychological state of stroke patients, regularly assess demoralization, identify high-risk patients for demoralization early, and provide targeted intervention measures. Mindfulness-integrated cognitive behavior has been proven to have positive therapeutic effects on demoralization, which includes a set of evidence-based techniques to increase self-awareness, self-control, and self-efficacy in various areas of life [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003e4.2 The demoralization level in stroke patients is influenced by multiple factors\u003c/h2\u003e\n \u003cp\u003eIn our study, education level, comorbidity, number of stroke incidences, ADL, and self-perceived burden level were the important factors associated with the severity of demoralization in stroke patients.\u003c/p\u003e\n \u003cp\u003eOur findings showed that stroke patients with lower education level were more likely to be demoralized, which is consistent with prior studies [\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e]. Usually, patients with higher education level may receive better quality education, including psychological training, which makes it easier to understand the condition and face the disease more rationally. Simultaneously, a low level of education may mean lower income, making it difficult to afford expensive treatment costs, and thus more likely to experience a higher level of demoralization.\u003c/p\u003e\n \u003cp\u003eResults further showed comorbidity was a predictor of demoralization level in stroke patients. The overwhelming majority of stroke patients exhibit comorbidity in China. Zhao et al. [\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e] included 2539 acute ischemic stroke patients, with 90% exhibiting multimorbidity (\u0026ge;\u0026thinsp;2 comorbidities). The more comorbidities a patient has, the more complex their condition becomes, requiring more time and effort to balance disease management with daily life and work. Secondly, patients with excessive comorbidities need to participate in multiple treatment trajectories, which can increase their time burden, transportation burden, and economic burden during the treatment process, leading to an increased treatment burden for patients. Furthermore, having a high number of comorbidities may mean that patients need to take multiple medications, leading to an increased drug burden.\u003c/p\u003e\n \u003cp\u003eAdditionally, the more frequent the stroke attacks, the higher the demoralization level in stroke patients. The frequency of stroke attacks indicates the severity and control of the disease. Patients with more episodes often have more severe illnesses, which limits their social interactions. As the frequency of attacks increases, the psychological burden on patients increases, and they gradually lose confidence in disease management. Subjectively, they are unwilling to communicate with others, isolate themselves, and their sense of social alienation increases, which are not conducive to the recovery of role functions [\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e]. The long-term existence of this situation can increase despair and helplessness, and expensive medical costs can also increase psychological pressure, ultimately leading to the demoralization.\u003c/p\u003e\n \u003cp\u003eThe study also demonstrated that ADL was a significant predictor for demoralization. Poor ADL often means that stroke patients cannot fully take care of themselves, and largely depend on their caregivers in daily life, which leads them to feel extremely guilty and perceive burden. Stroke is a leading cause of disability and morbidity associated with increased economic burden due to post-stroke care and rehabilitation. It can be interpreted that patients may worry about their stroke-related disabilities, which may cause them to be abandoned.\u003c/p\u003e\n \u003cp\u003eFurthermore, self-perceived burden has a positive predictive effect on demoralization. Self‐perceived burden is a common psychological characteristic in patients with chronic diseases and is associated with physical conditions and negative psychology, including depression and suicidal ideation [\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e]. It has been found that self‐perceived burden may be higher among those with other disabling but nonfatal conditions, such as stroke [\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e]. It should be noted that previous studies [\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e] did not find self‐perceived burden to be a significant predictor for demoralization. In addition, we have preliminarily found that low self‐perceived burden may also indicate moderate demoralization. Such evidence suggests that early identification and specific treatment for self‐perceived burden may prevent or reduce the sense of demoralization. Overall, our findings emphasize the need to assess the status and determinants of demoralization in stroke patients, to improve the quality of life of stroke patients.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5. Limitations","content":"\u003cp\u003eSome limitations need to be addressed. First, the cross-sectional design was used in this study, the lack of qualitative and mixed methods of research endangers a deeper understanding of the demoralization characteristics. Future qualitative studies are necessary to capture trends, specific experiences, and insights into demoralization. Second, considering that demoralization level is a dynamic indicator, longitudinal studies are also needed. Third, this study selected stroke patients only from one hospital with the convenience sampling method, and the sample may not fully represent the entire stroke population. Multi-center studies are needed to determine a widespread belief in results in the future. Finally, self-report measures may produce response biases. In the future, self-evaluation may be conducted in conjunction with peer evaluation to more accurately portray the characteristics of demoralization.\u003c/p\u003e"},{"header":"6. Conclusions","content":"\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eOur study provided a reasonably clear picture of the status and determinants of demoralization in stroke patients. The prevalence of demoralization in stroke patients was quite high, influenced by various factors. However, demoralization is often neglected in clinical practice. Healthcare professionals should develop targeted interventions after stroke by considering sociodemographic (education level) and stroke characteristics (comorbidity, number of stroke incidences, and ADL) and reducing self-perceived burden. Furthermore, stroke patients at high risk of demoralization should be promptly monitored.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHongyan Yang:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Data curation, Software, Validation, Investigation, Formal analysis, Writing-original draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTing Yang\u003c/strong\u003e: Conceptualization, Methodology, Software, Formal analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHui Wei\u003c/strong\u003e: Data curation, Investigation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMiaomiao Liu\u003c/strong\u003e: Supervision, Validation, Writing\u0026ndash;reviewing and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the participants for their active cooperation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflict of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Zhejiang Province Medical Science and Technology Project (2024KY1058).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Declaration:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatement that all methods are performed in accordance with relevant guidelines and requlations. This study received approval from the Human Research and Ethics Committee of The Second Affiliated Hospital of Zhejiang University of Medicine, China (IRB No.20240095). Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eFeigin VL, Brainin M, Norrving B, et al. World Stroke Organization: Global Stroke Fact Sheet 2025. \u003cem\u003eInt J Stroke\u003c/em\u003e. 2025;20(2):132-144. doi:10.1177/17474930241308142\u003c/li\u003e\n \u003cli\u003eGBD 2021 Stroke Risk Factor Collaborators. Global, regional, and national burden of stroke and its risk factors, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet Neurol. 2024 Oct;23(10):973-1003. doi: 10.1016/S1474-4422(24)00369-7\u003c/li\u003e\n \u003cli\u003eMa Q, Li R, Wang L, et al. Temporal trend and attributable risk factors of stroke burden in China, 1990-2019: an analysis for the Global Burden of Disease Study 2019.\u0026nbsp;Lancet Public Health. 2021;6(12):e897-e906. doi:10.1016/S2468-2667(21)00228-0\u003c/li\u003e\n \u003cli\u003ePatel MD, Tilling K, Lawrence E, et al. Relationships between long-term stroke disability, handicap and health-related quality of life. Age Ageing. 2006 May;35(3):273-9.\u003c/li\u003e\n \u003cli\u003eMarkus HS. Reducing disability after stroke.\u0026nbsp;Int J Stroke. 2022;17(3):249-250.\u003c/li\u003e\n \u003cli\u003eGuo J, Wang J, Sun W, et al. The advances of post-stroke depression: 2021 update. J Neurol. 2022 Mar;269(3):1236-1249.\u003c/li\u003e\n \u003cli\u003eKutlubaev MA, Hackett ML. Part II: predictors of depression after stroke and impact of depression on stroke outcome: an updated systematic review of observational studies. Int J Stroke. 2014 Dec;9(8):1026-36.\u003c/li\u003e\n \u003cli\u003eMehnert A,Vehling S,H\u0026ouml;cker A,et al. Demoralization and depression in patients with advanced cancer:validation of the German version of the Demoralization Scale[J]. J Pain Symptom Manage,2011,42(5):768-776.\u003c/li\u003e\n \u003cli\u003eWang Y, Sun H, Ji Q, Wu Q, Wei J, Zhu P. Prevalence, Associated Factors and Adverse Outcomes of Demoralization in Cancer Patients: A Decade of Systematic Review. Am J Hosp Palliat Care. 2023 Nov;40(11):1216-1230. doi: 10.1177/10499091231154887.\u003c/li\u003e\n \u003cli\u003eBovero A, Opezzo M, Tesio V. Relationship between demoralization and quality of life in end-of-life cancer patients.\u0026nbsp;Psychooncology. 2023;32(3):429-437. doi:10.1002/pon.6095\u003c/li\u003e\n \u003cli\u003eFava GA, Guidi J. Clinical Characterization of Demoralization. Psychother Psychosom. 2023;92(3):139-147. doi: 10.1159/000530760.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eRobinson S, Kissane DW, Brooker J, Hempton C, Burney S. The Relationship Between Poor Quality of Life and Desire to Hasten Death: A Multiple Mediation Model Examining the Contributions of Depression, Demoralization, Loss of Control, and Low Self-worth. J Pain Symptom Manage. 2017 Feb;53(2):243-249. doi: 10.1016/j.jpainsymman.2016.08.013.\u003c/li\u003e\n \u003cli\u003eVehling S, Kissane DW, Lo C, Glaesmer H, Hartung TJ, Rodin G, Mehnert A. The association of demoralization with mental disorders and suicidal ideation in patients with cancer. Cancer. 2017 Sep 1;123(17):3394-3401. doi: 10.1002/cncr.30749.\u003c/li\u003e\n \u003cli\u003eAlmhdawi KA, Alazrai A, Kanaan S, et al. Post-stroke depression, anxiety, and stress symptoms and their associated factors: A cross-sectional study.\u0026nbsp;Neuropsychol Rehabil. 2021;31(7):1091-1104. doi:10.1080/09602011.2020.1760893\u003c/li\u003e\n \u003cli\u003ePallucca C, Lisiecka-Ford DM, Wood L, et al. Apathy After Stroke[J]. Neurology,2024,102(3):e208052.\u003c/li\u003e\n \u003cli\u003eShao Q, Li Y, Lin L, Boardman M, Hamadi H, Zhao M. Demoralization syndrome and its impact factors among cancer patients in China. J Psychosoc Oncol. 2024;42(3):365-380. doi: 10.1080/07347332.2023.2249895\u003c/li\u003e\n \u003cli\u003eChan WCH, Yu CTK, Kwok DKS, Wan JKM. Prevalence and factors associated with demoralization in palliative care patients: A cross-sectional study from Hong Kong. Palliat Support Care. 2024 Aug;22(4):709-717.\u003c/li\u003e\n \u003cli\u003ede Figueiredo JM, Zhu B, Patel AS, Kohn R, Koo BB, Louis ED. Differential impact of resilience on demoralization and depression in Parkinson disease. Front Psychiatry. 2023 Jul 24;14:1207019. doi: 10.3389/fpsyt.2023.1207019.\u003c/li\u003e\n \u003cli\u003eChen X, Zhang H, Xiao G, Lv C. Prevalence of suicidal ideation among stroke survivors: A systematic review and meta-analysis. Top Stroke Rehabil. 2021 Oct;28(7):545-555. doi: 10.1080/10749357.2020.1846933.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eTang PL, Wang HH, Chou FH. A Systematic Review and Meta-Analysis of Demoralization and Depression in Patients With Cancer. Psychosomatics. 2015 Nov-Dec;56(6):634-43. doi: 10.1016/j.psym.2015.06.005.\u003c/li\u003e\n \u003cli\u003eDrake RE, Gates C, Whitaker A, Cotton PG. Suicide among schizophrenics: a review. Compr Psychiatry. 1985 Jan-Feb;26(1):90-100. doi: 10.1016/0010-440x(85)90053-7.\u003c/li\u003e\n \u003cli\u003eCousineau N, McDowell I, Hotz S, H\u0026eacute;bert P. Measuring chronic patients\u0026apos; feelings of being a burden to their caregivers: development and preliminary validation of a scale. Med Care. 2003 Jan;41(1):110-8. doi: 10.1097/00005650-200301000-00013.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMcPherson CJ, Wilson KG, Chyurlia L, Leclerc C. The balance of give and take in caregiver\u0026ndash;partner relationships: an examination of self-perceived burden, relationship equity, and quality of life from the perspective of care recipients following stroke. Rehabil Psychol. 2010;55(2):194\u0026ndash;203. doi: 10.1037/a0019359.\u003c/li\u003e\n \u003cli\u003eRen H, Liu C, Li J, Yang R, Ma F, Zhang M, Wang R, Gan L. Self-perceived Burden in the Young and Middle-aged Inpatients with Stroke: A Cross-sectional Survey. Rehabil Nurs. 2016 Mar-Apr;41(2):101-11. doi: 10.1002/rnj.193.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eWilson KG, Dalgleish TL, Chochinov HM, Chary S, Gagnon PR, Macmillan K, De Luca M, O\u0026rsquo;Shea F, Kuhl D, Fainsinger RL. Mental disorders and the desire for death in patients receiving palliative care for cancer. BMJ Support Palliat Care. 2016;6(2):170\u0026ndash;177. doi: 10.1136/bmjspcare-2013-000604\u003c/li\u003e\n \u003cli\u003eKissane DW, Wein S, Love A, Lee XQ, Kee PL, Clarke DM. The Demoralization Scale: a report of its development and preliminary validation.\u0026nbsp;J Palliat Care. 2004;20(4):269-276.\u003c/li\u003e\n \u003cli\u003eMullane M, Dooley B, Tiernan E, Bates U. Validation of the Demoralization Scale in an Irish advanced cancer sample. Palliat Support Care. 2009 Sep;7(3):323-30.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eHung HC, Chen HW, Chang YF, Yang YC, Liu CL, Hsieh RK, Leu YS, Chen YJ, Wang TE, Tsai LY, Liu SI, Fang CK. Evaluation of the reliability and validity of the Mandarin Version of Demoralization Scale for cancer patients. J Intern Med Taiwan. 2010;21:427\u0026ndash;435.\u003c/li\u003e\n \u003cli\u003eCousineau N, McDowell I, Hotz S, H\u0026eacute;bert P. Measuring chronic patients\u0026apos; feelings of being a burden to their caregivers: development and preliminary validation of a scale. Med Care. 2003 Jan;41(1):110-8.\u003c/li\u003e\n \u003cli\u003evon Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. Int J Surg. 2014;12(12):1495-1499.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eKoo BB, Chow CA, Shah DR, Khan FH, Steinberg B, Derlein D, Nalamada K, Para KS, Kakade VM, Patel AS, de Figueiredo JM, Louis ED. Demoralization in Parkinson disease. Neurology. 2018 May 1;90(18):e1613-e1617. doi: 10.1212/WNL.0000000000005425.\u003c/li\u003e\n \u003cli\u003eChang TG, Huang PC, Hsu CY, Yen TT. Demoralization in oral cancer inpatients and its association with spiritual needs, quality of life, and suicidal ideation: a cross-sectional study. Health Qual Life Outcomes. 2022 Apr 2;20(1):60. doi: 10.1186/s12955-022-01962-6.\u003c/li\u003e\n \u003cli\u003eChytas V, Costanza A, Mazzola V, Luthy C, Bondolfi G, Cedraschi C. Demoralization and Suicidal Ideation in Chronic Pain Patients. Psychol Res Behav Manag. 2023 Mar 5;16:611-617.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLuo Y, Lai Q, Huang H, Luo J, Miao J, Liao R, Yang Z, Zhang L. Risk factor analysis and nomogram construction for predicting suicidal ideation in patients with cancer. BMC Psychiatry. 2022 May 24;22(1):353. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSoleymani Moghadam M, Parvizifard A, Foroughi A, Ahmadi SM, Farshchian N. An investigation of the effect of mindfulness-integrated cognitive behavior therapy on demoralization, body image, and sexual function in Iranian women with breast cancer: a randomized controlled trial. J Cancer Res Clin Oncol. 2024 Mar 14;150(3):128. doi: 10.1007/s00432-024-05655-z.\u003c/li\u003e\n \u003cli\u003eTang L, Li Z, Pang Y. The differences and the relationship between demoralization and depression in Chinese cancer patients. Psychooncology. 2020 Mar;29(3):532-538. doi: 10.1002/pon.5296.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLi YC, Ho CH, Wang HH. Demoralization in Cancer Patients and Related Factors in Taiwan. Cancer Nurs. 2017 Jan/Feb;40(1):E54-E60. doi: 10.1097/NCC.0000000000000352.\u003c/li\u003e\n \u003cli\u003eZhao H, Qian Y, Zhou Y, Zhang D, Zhao Z, Zhang W, Shan C, Wang Y, Chen Z, Wang J, Pei L, Zhang Q, Zhou Q, Xu Y, Ning M, Buonanno FS, Sun C, Song B. Association of multimorbidity with biological age acceleration in acute ischemic stroke patients: a cross-sectional study. QJM. 2025 Jul 3:hcaf148. doi: 10.1093/qjmed/hcaf148\u003c/li\u003e\n \u003cli\u003eMcCurley JL, Funes CJ, Zale EL, Lin A, Jacobo M, Jacobs JM, Salgueiro D, Tehan T, Rosand J, Vranceanu AM. Preventing Chronic Emotional Distress in Stroke Survivors and Their Informal Caregivers. Neurocrit Care. 2019 Jun;30(3):581-589. doi: 10.1007/s12028-018-0641-6\u003c/li\u003e\n \u003cli\u003eKowal J, Wilson KG, McWilliams LA, P\u0026eacute;loquin K, Duong D. Self-perceived burden in chronic pain: relevance, prevalence, and predictors. Pain. 2012;153(8):1735-1741.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Stroke, Demoralization, Determinants, Status, Self-perceived burden","lastPublishedDoi":"10.21203/rs.3.rs-7212645/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7212645/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eIrreversible neurological trauma, long-term rehabilitation, disability, psychological issues, costly medical and financial burden, and difficulties in reintegration into the community may ultimately lead to demoralization in stroke survivors. However, the status and determinantsof demoralization in stroke patients are still unknown.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAim: \u003c/strong\u003eTo analyze the current status of demoralization in stroke patients, and explore factorsthat influenced demoralization in relation to demographic and stroke characteristics, and self-perceived burden.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA cross-sectional study using the convenient sampling method was conducted to select the research objects of stroke patients who were inpatients in a general public hospital in Hangzhou, Zhejiang Province. The survey period was from January 2025 to May 2025. The Mandarin Version of the Demoralization Scaleand the Self-Perceived Burden Scale were used to assess demoralization and self-perceived burden, respectively. General information, including demographic data and stroke characteristics, was collected. The data was analyzed using SPSS 25.0 software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThis study included 376 stroke patients with a mean DS-MV score of 34.32 ± 11.249. Of these, 26 (6.9%) had mild demoralization, 296 (78.7%) had moderate demoralization, and 54 (14.4%) had severe demoralization. Considering a DS-MV score \u0026gt; 30 for detection,51.9% of stroke patientshad demoralization. Education level, comorbidity, number of stroke incidences, activity of daily living, and self-perceived burden level were the important factors associated with the severity of demoralization in stroke patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Stroke patients exhibit a notable prevalence and severity of demoralization. Healthcare professionals should develop targeted interventions after stroke by considering sociodemographic (education level) and stroke characteristics (comorbidity, number of stroke incidences, and activity of daily living) and reducing self-perceived burden. Furthermore, stroke patients at high risk of demoralization should be promptly monitored.\u003c/p\u003e","manuscriptTitle":"The status and determinants of demoralization in stroke patients: a cross-sectional study in China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-09 12:55:59","doi":"10.21203/rs.3.rs-7212645/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-28T06:54:41+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-14T02:37:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269483899923971905174374444236559021694","date":"2025-09-14T02:20:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-13T15:20:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"26583470442520591543207063230335559707","date":"2025-09-09T18:40:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"202583521386293589029242369760502872360","date":"2025-09-04T02:51:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-02T15:42:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-28T06:36:50+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-06T07:57:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-02T02:25:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2025-08-02T02:22:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cbf39fbe-3ee5-4f72-80b8-18f79cfb0ac3","owner":[],"postedDate":"September 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-03T17:39:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-09 12:55:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7212645","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7212645","identity":"rs-7212645","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}