Hospice Care Knowledge and Death Attitude Profiles Among Healthcare Workers: A Latent Profile Analysis

Hospice Care Knowledge and Death Attitude Profiles Among Healthcare Workers: A Latent Profile Analysis | 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 Hospice Care Knowledge and Death Attitude Profiles Among Healthcare Workers: A Latent Profile Analysis Xiuping Li, Hanxiao Luo, Hangfei Mao, Shina Qiao, Mengjiao Sun, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8438501/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Background Healthcare workers’ attitudes toward death play an important role in the quality of end-of-life care, yet such attitudes are often treated as homogeneous and insufficiently examined in relation to hospice care preparedness. Understanding heterogeneity in death attitudes and their educational correlates is essential for strengthening the palliative care workforce. Methods A cross-sectional survey was conducted among 1,421 healthcare workers from secondary and tertiary hospitals in Zhejiang Province, China. Death attitudes were assessed using the Death Attitude Profile–Revised (DAP-R), and hospice care knowledge was measured using a structured questionnaire. Latent profile analysis was applied to identify distinct death attitude profiles. A multinomial logistic regression model was used to examine associations between hospice care knowledge, demographic characteristics, and profile membership. Results Three distinct death attitude profiles were identified: a moderate profile characterized by balanced acceptance and fear, a more adaptive profile marked by higher acceptance and lower fear, and a less adaptive profile characterized by lower acceptance and higher fear or avoidance. Hospice care knowledge showed a consistent and graded association with profile membership, with higher knowledge levels associated with increased likelihood of belonging to more adaptive profiles. In contrast, demographic and occupational characteristics were not significantly associated with profile membership. Overall, hospice care knowledge levels were relatively low, with most participants scoring in the poor or very poor range. Conclusion Healthcare workers exhibit substantial heterogeneity in attitudes toward death, which is closely associated with hospice care knowledge. These findings highlight the relevance of educational preparedness in shaping engagement with end-of-life care and support the integration of structured hospice and palliative care education into routine professional training to enhance workforce readiness and improve the quality of end-of-life care Palliative care Hospice care knowledge Death attitudes Latent profile analysis Healthcare workforce End-of-life care Figures Figure 1 Figure 2 Introduction The quality of hospice and palliative care depends not only on the availability of services, but also on the preparedness of the healthcare workforce to engage with patients and families at the end of life. As populations age and the burden of life-limiting illness increases worldwide, healthcare professionals are increasingly required to provide care that addresses not only physical symptoms, but also the psychological, social, and existential dimensions of dying[ 1 , 2 ]. In this context, workforce readiness has become a critical determinant of the effectiveness and sustainability of palliative care delivery[ 3 , 4 ]. Among the multiple components of workforce preparedness, healthcare workers’ attitudes toward death play a particularly important role in shaping end-of-life care practices[ 5 ]. Death-related attitudes influence clinicians’ willingness to initiate palliative care discussions, their comfort in communicating about prognosis and dying, and their ability to provide emotionally supportive care to patients and families[ 6 , 7 ]. Previous studies have shown that fear, avoidance, or discomfort with death may hinder timely palliative care engagement, whereas more accepting attitudes are associated with greater confidence and perceived competence in end-of-life care[ 8 – 10 ]. Death attitudes are widely conceptualized as multidimensional constructs encompassing fear, avoidance, and different forms of acceptance. Within palliative care settings, these attitudinal dimensions rarely exist in isolation; instead, they co-occur in complex patterns that may reflect healthcare workers’ overall psychological and professional readiness for end-of-life care. For example, clinicians may simultaneously endorse acceptance of death while still experiencing fear or avoidance in clinical encounters with dying patients[ 7 , 11 , 12 ]. Understanding how these dimensions cluster within individuals is therefore essential for identifying subgroups of the palliative care workforce who may require different forms of educational or organizational support. Most existing studies have examined healthcare workers’ death attitudes using variable-centered approaches, focusing on associations between individual attitude dimensions and demographic or occupational characteristics[ 13 – 15 ]. While informative, such approaches implicitly assume relative homogeneity within the workforce and may obscure meaningful subgroups characterized by distinct configurations of death-related attitudes. Person-centered methods, such as latent profile analysis, allow for the identification of heterogeneous patterns of attitudes within a population and have the potential to inform more tailored approaches to palliative care education and workforce development[ 16 ]. However, the application of these methods among healthcare workers in palliative and hospice care contexts remains limited. Against this background, the present study aimed to identify distinct profiles of death attitudes among healthcare workers using latent profile analysis and to examine how these profiles are associated with hospice care knowledge. By clarifying patterns of death-related attitudes within the palliative care workforce, this study seeks to provide empirical evidence that may inform the design of more targeted and effective educational strategies to strengthen end-of-life care delivery Methods 1.1 Participants and Setting This cross-sectional survey was conducted among healthcare workers from secondary and tertiary hospitals across Zhejiang Province, China. Between September and October 2023, a total of 1,421 valid questionnaires were collected from 31 hospitals located in seven prefecture-level cities, including Hangzhou, Ningbo, Wenzhou, and Jinhua. Zhejiang Province has been one of the national pilot regions for hospice and palliative care, providing a relevant context for investigating healthcare workers' knowledge of hospice care and attitudes toward death. Eligible participants were physicians and nurses working in departments that commonly provide care for patients with life-limiting illnesses, such as oncology, geriatrics, internal medicine, surgery, and critical/emergency care. Inclusion criteria were: (1) age ≥ 18 years; (2) possession of a valid nursing or medical qualification certificate; (3) ≥ 1 year of clinical experience; and (4) voluntary participation with informed consent. Exclusion criteria included: (1) < 1 year of clinical experience; (2) being on leave during the survey period; and (3) temporary or non-registered staff. Data were collected anonymously via the online platform Questionnaire Star. Trained nursing department coordinators assisted with standardized administration. Each IP address could submit only one response, and questionnaires completed in less than 120 seconds or containing logical inconsistencies were excluded. Ultimately, 1,421 valid questionnaires were included in the analysis (effective response rate = 94.7%). The study adopted convenience sampling for feasibility, while the inclusion of multiple hospitals across diverse regions improved the representativeness of the sample. Ethical approval was obtained from the Institutional Review Board of Sir Run Run Shaw Hospital, Zhejiang University School of Medicine (Approval No. 20230149). All participants provided electronic informed consent. 1.2 Measures 1.2.1 General information questionnaire The general information questionnaire was developed by the research team based on relevant literature and study objectives. It collected participants’ demographic and occupational characteristics, including gender, age, educational background, region, occupation, professional title, years of work, department, ethnicity, and religious belief. 1.2.2 Hospice Care Knowledge Questionnaire The Hospice Care Knowledge Questionnaire was designed by the research team to assess medical staff's understanding of hospice care.Item development was informed by hospice and palliative care curricula, relevant clinical guidelines, and two rounds of expert consultation involving senior nursing educators and palliative care physicians, which also served as the basis for defining the correct responses to each item. The final instrument comprises 20 single-choice items addressing basic concepts of hospice care, symptom and pain management, psychological and social aspects of end-of-life care, and common ethical issues encountered in practice. Each item has three response options (“True,” “False,” “Don't know”). Correct answers were scored as 5 and incorrect/“Don't know” as 0, yielding a total score of 0–100. Higher scores indicate greater knowledge. The questionnaire demonstrated strong psychometric performance, with item-level content validity indices of 0.82–1.00, a scale-level CVI of 0.91, internal consistency reliability of 0.846, and a two-week test–retest reliability of 0.852. The English version of the Hospice Care Knowledge Questionnaire is provided as Supplementary File 2. 1.2.3 Death Attitude Profile–Revised(DAP-R) The DAP-R, originally developed by Wong, Reker, and Gesser and later adapted into Chinese by Tang, has demonstrated good reliability and validity among Chinese healthcare professionals[ 17 , 18 ]. The instrument contains 32 items across five dimensions: Fear of Death (FD), Death Avoidance (DA), Neutral Acceptance (NA), Escape Acceptance (EA), and Approach Acceptance (AA). Items are scored on a five-point Likert scale (1 = strongly disagree; 5 = strongly agree), with higher scores indicating stronger endorsement of the corresponding attitude[ 18 ]. In this study, the Chinese version showed good internal consistency (Cronbach’s α = 0.846; subscale α = 0.72–0.83). Both total and subscale scores were used following conventional analytic practice. Statistical Analysis Descriptive statistics were first generated to summarize participants’ demographic characteristics, hospice care knowledge, and DAP-R scores, with continuous variables presented as means and standard deviations and categorical variables as frequencies and percentages. Latent profile analysis (LPA) was then performed in Mplus to identify subgroups of death attitude patterns based on the five DAP-R dimensions. All dimension scores were standardized into z-scores before modeling to ensure comparability across scales[ 19 ]. Competing models with increasing numbers of classes were estimated and evaluated using the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), adjusted BIC (aBIC), entropy, the Lo–Mendell–Rubin adjusted likelihood ratio test (LMR-LRT), and the bootstrap likelihood ratio test (BLRT). Model selection was guided by a combination of statistical fit, classification accuracy, and conceptual interpretability, and class-specific standardized means were visualized to aid interpretation[ 20 ]. To examine factors associated with latent class membership, a multinomial logistic regression model was fitted in SPSS using the three-class solution derived from LPA, with Class 1 specified as the reference category. Gender, age, educational level, profession, professional title, department category, years of working, ethnicity, religious belief, and hospice care knowledge score were entered as independent variables. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated, and only significant findings are reported in the main text, with the full regression model provided in Table S1 , Supplementary File 1. All data were analyzed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA) and Mplus version 8.3 (Muthén & Muthén, Los Angeles, CA, USA). A two-sided p < .05 was considered statistically significant. Result A total of 1,421 healthcare workers were included in the analysis. The distributions of demographic and occupational characteristics across the three latent classes are presented in Table 1 . Overall, most participants were female (93.4%), younger than 40 years (81.3%), and held a bachelor's degree (83.7%). Nurses accounted for 93.8% of the sample. The mean hospice care knowledge score for the total sample was 45.13 ± 11.62 (Table 1 ). Significant between-class differences were observed for educational level and profession, whereas no statistically significant differences were found for gender, age group, professional title, years of working, department category, ethnicity, or religious belief. In contrast, both hospice care knowledge and overall death attitude score differed markedly across the three classes. Table 1 Indicator Differences Across Latent Profiles No.(%) Latent profile Characteristics All (n = 1421) Class 1 (n = 252) Class 2 (n = 1030) Class 3 (n = 139) P value Gender 0.315 Male 94 (6.62) 20 (8.00) 62 (6.01) 12 (8.63) Female 1327 (93.38) 230 (92.00) 970 (93.99) 127 (91.37) Age 0.793 ≤ 30 673 (47.36) 120 (48.00) 489 (47.38) 64 (46.04) 31–40 482 (33.92) 91 (36.40) 345 (33.43) 46 (33.09) 41–50 235 (16.54) 36 (14.40) 173 (16.76) 26 (18.71) ≥ 51 31 (2.18) 3 (1.20) 25 (2.42) 3 (2.16) Educational level 0.034 Associate degree or below 169 (11.89) 25 (10.00) 126 (12.21) 18 (12.95) Bachelor's degree 1189 (83.67) 207 (82.80) 862 (83.53) 120 (86.33) Master's degree or above 63 (4.43) 18 (7.20) 44 (4.26) 1 (0.72) Profession 0.003 Nurse 1333 (93.81) 224 (89.60) 973 (94.28) 136 (97.84) Doctor 88 (6.19) 26 (10.40) 59 (5.72) 3 (2.16) • Professional title 0.663 Junior 829 (58.34) 143 (57.20) 605 (58.62) 81 (58.27) Intermediate 455 (32.02) 80 (32.00) 326 (31.59) 49 (35.25) Senior 137 (9.64) 27 (10.80) 101 (9.79) 9 (6.47) Years of working 0.606 <10 837 (58.90) 151 (60.40) 607 (58.82) 79 (56.83) 11–20 362 (25.48) 68 (27.20) 257 (24.90) 37 (26.62) ≥21 222 (15.62) 31 (12.40) 168 (16.28) 23 (16.55) Department 0.128 Surgical Department 275 (19.35) 49 (19.60) 203 (19.67) 23 (16.55) Internal Medicine Department 607 (42.72) 105 (42.00) 434 (42.05) 68 (48.92) Critical Care System 286 (20.13) 39 (15.60) 219 (21.22) 28 (20.14) Others 253 (17.80) 57 (22.80) 176 (17.05) 20 (14.39) Ethnicity 0.108 Han Chinese 1399 (98.45) 243 (97.20) 1020 (98.84) 136 (97.84) Other Ethnicities 22 (1.55) 7 (2.80) 12 (1.16) 3 (2.16) Religious Belief 0.264 No 1298 (91.34) 231 (92.40) 945 (91.57) 122 (87.77) Yes 123 (8.66) 19 (7.60) 87 (8.43) 17 (12.23) Hospice Care Knowledge, Mean(SD) 45.13(11.62) 29.97(6.26) 45.54(5.74) 69.39(7.98) < .001 Latent profile analysis was conducted using standardized (z-score) scores from the five dimensions of the DAP-R scale. Models with one to four classes were estimated and compared. The three-class solution was selected as the optimal model based on a combination of statistical fit indices and interpretability. Compared with the two-class model, the three-class model showed lower AIC, BIC, and adjusted BIC values, and both the Lo–Mendell–Rubin test and the bootstrap likelihood ratio test indicated a significant improvement in model fit. And the entropy retained high classification quality in three-class model. Detailed model fit indices are presented in Table S1 , Supplementary File 1. Figure 1 displays the standardized mean profiles across the five DAP-R dimensions. Class 1 (n = 250; 17.6%) showed the lowest levels of natural and approach acceptance and the highest levels of fear and avoidance. Class 2 (n = 1,032; 72.6%) exhibited intermediate levels across all dimensions. Class 3 (n = 139; 9.8%) demonstrated the most adaptive pattern, with high acceptance and low fear/avoidance. The three trajectories remained clearly separated on all dimensions, indicating distinct attitudinal patterns rather than subtle variations of a single continuum. Differences in hospice care knowledge across classes are also presented in Table 1 . Knowledge scores increased progressively from Class 1 to Class 3 (29.97 ± 6.26; 45.54 ± 5.74; 69.39 ± 7.98). The violin plot in Fig. 2 further illustrates these differences. Class 1 displayed a narrow concentration of lower scores, whereas Class 2 showed a symmetric distribution centered around the moderate range. Class 3 exhibited the highest mean score and comparatively less variability. The distributional patterns were consistent with the observed mean differences, suggesting a robust association between hospice care knowledge and death attitude profiles. A multinomial logistic regression was conducted to examine factors associated with class membership, using Class 1 as the reference category (Table 2 ). Hospice care knowledge emerged as the only significant correlate. Higher knowledge scores were significantly associated with belonging to Class 2 compared with Class 1 (OR = 2.261, 95% CI: 2.10–3.282) and with belonging to Class 3 compared with Class 1 (OR = 2.26, 95% CI: 1.81–2.83). None of the demographic or occupational variables—including gender, age group, educational level, profession, department type, professional title, years of working, ethnicity, or religious belief—showed statistically significant associations with class membership (all p > 0.05). Full regression results, including all covariates, are provided in Table S2 , Supplementary File 1. Table 2 Multinomial logistic regression of hospice care knowledge score on latent class membership Variable Class Comparison β SE z Wald χ² OR (95% CI) P -value Hospice care knowledge score Class 2 vs Class 1 0.97 0.11 8.48 71.86 2.63 (2.10–3.28) < 0.001 Class 3 vs Class 1 0.82 0.11 7.16 51.27 2.26 (1.81–2.83) < 0.001 Notes : Class 1 served as the reference category. β, regression coefficient; SE, standard error; OR, odds ratio; CI, confidence interval. Only statistically significant variable is shown. Discussion This study identified three distinct death attitude profiles among healthcare workers and demonstrated a consistent association between hospice care knowledge and profile membership. Most participants belonged to a moderate profile characterized by balanced levels of acceptance and fear, whereas smaller subgroups exhibited either more adaptive or less adaptive orientations toward death. When examined alongside demographic and occupational characteristics, hospice care knowledge showed a statistically significant association with latent profile membership, whereas other examined characteristics did not, underscoring its relevance in relation to healthcare workers’ attitudes toward death. In addition, the overall level of hospice care knowledge observed in this study was relatively low, with most participants scoring in the poor or very poor range. This finding is consistent with prior studies conducted in China and other settings, which have reported insufficient palliative care knowledge among nurses and other healthcare professionals, largely attributed to limited formal education and training opportunities in end-of-life care[ 21 – 23 ]. The presence of three differentiated profiles indicates substantial heterogeneity in how healthcare workers perceive and engage with death. Similar variability has been reported in previous studies, in which acceptance and fear often coexist among clinicians and vary according to training experiences, cultural context, and clinical exposure[ 24 – 26 ]. In the present study, the profile characterized by higher acceptance and lower fear may reflect healthcare workers who feel better prepared to manage end-of-life situations, potentially owing to greater familiarity with hospice principles or prior educational exposure. Conversely, the profile marked by lower acceptance and heightened fear or avoidance may represent individuals who experience greater emotional discomfort or uncertainty when confronted with dying patients, possibly in the absence of structured end-of-life care training. These findings support the view that healthcare workers do not constitute a homogeneous group with respect to death attitudes but instead form distinct subgroups with practical implications for care delivery[ 27 ]. This heterogeneity is also reflected in international literature. A mixed-methods systematic review found that nurses’ attitudes toward end-of-life care and death vary substantially across cultural and educational backgrounds, influencing their approaches to care, emotional responses, and communication with dying patients and families[ 28 ]. A key finding of this study is the observed graded association between hospice care knowledge and death attitude profiles. Higher knowledge scores were associated with an increased likelihood of belonging to more adaptive profiles and a reduced likelihood of membership in the least adaptive profile. Although the cross-sectional design precludes causal inference, this pattern is consistent with prior empirical evidence indicating that education and training in hospice or palliative care are associated with more favorable attitudes toward death and dying. For example, Hao et al. demonstrated that a structured palliative care learning intervention significantly improved nurses’ hospice care knowledge and attitudes toward dying patients, although changes in specific death attitude dimensions varied[ 21 ]. Similarly, a recent meta-analysis from Ethiopia reported that nurses who received palliative care training were more than twice as likely to hold favorable attitudes toward palliative care compared with those without training[ 29 ]. Educational exposure may help reduce misconceptions, improve professional confidence, and enhance psychological preparedness, thereby mitigating fear and avoidance[ 30 , 31 ]. In contrast, limited knowledge may reinforce ambiguity and emotional distress when facing end-of-life situations, contributing to less adaptive attitudinal patterns[ 32 ]. It should be noted that hospice care knowledge was assessed using a self-reported instrument, and the observed associations should therefore be interpreted as indicative rather than causal. In contrast to hospice care knowledge, demographic and occupational characteristics—including age, gender, educational level, profession, department type, and years of clinical experience—were not significantly associated with death attitude profile membership. Although some earlier studies have reported associations between death attitudes and variables such as age or professional seniority[ 27 ],[ 33 ], the absence of such relationships in the present analysis may reflect the relative homogeneity of the sample, which consisted predominantly of young, highly educated nurses working in hospital settings. More importantly, this finding suggests that routine clinical exposure alone may not be sufficient to shape healthcare workers’ engagement with death in the absence of structured palliative care education. From a palliative care standpoint, this underscores the importance of formal training and reflective learning opportunities as key components of workforce readiness, potentially exerting a more decisive influence on death attitudes than background characteristics[ 34 , 35 ]. The clear separation of standardized mean trajectories across the five DAP-R dimensions supports the interpretability of the identified profiles. Consistent differences across fear-, avoidance-, and acceptance-related dimensions suggest stable and meaningful attitudinal patterns rather than minor variations along a single continuum. The observed differences in hospice care knowledge across profiles further reinforce the distinctiveness of these groups, lending credibility to the latent structure identified in this study. From a practical perspective, these findings suggest that strengthening hospice and palliative care education may represent a feasible strategy for promoting more adaptive death attitudes among healthcare workers. Educational approaches that integrate theoretical instruction with reflective learning, clinical exposure, and interdisciplinary collaboration have been shown to improve comfort and competence in end-of-life care. Evidence from intervention and implementation studies suggests that blended educational approaches—combining e-learning, reflective discussion, and clinical exposure—can effectively enhance both hospice care knowledge and attitudes toward end-of-life care among nurses[ 21 , 22 ]. Given that demographic and occupational factors did not differentiate profiles, such interventions may be most effective when implemented broadly rather than targeted to specific subgroups, particularly in settings where formal palliative care training remains limited[ 36 ]. Several limitations should be acknowledged. First, the cross-sectional design limits conclusions regarding the directionality of the observed associations between hospice care knowledge and death attitudes. Second, hospice care knowledge was assessed using a self-developed questionnaire, which, despite demonstrating acceptable psychometric properties, has not yet been externally validated across diverse settings. Third, the latent profile solution may be sample-dependent, and replication in independent or longitudinal samples is warranted. Finally, the predominance of nurses and the single-province sampling frame may limit the generalizability of the findings to other professional groups or healthcare systems. Despite these limitations, this study contributes to the palliative care literature by elucidating the heterogeneity of healthcare workers’ death attitudes and highlighting their association with hospice care knowledge. Rather than being uniformly distributed, attitudes toward death appear to cluster into distinct patterns with potential relevance for education and workforce development. These findings support the integration of structured hospice and palliative care education into routine professional training as a means of enhancing workforce preparedness and ultimately improving the quality of end-of-life care. Conclusion This study identified distinct profiles of death attitudes among healthcare workers and found a consistent association between hospice care knowledge and profile membership. The findings highlight the heterogeneity of attitudes toward death within the healthcare workforce and underscore the relevance of educational preparedness in end-of-life care. Strengthening structured hospice and palliative care education may help foster more adaptive attitudes toward death and better equip healthcare workers to meet the complex needs of patients and families at the end of life. Declarations Availability of data and materials The datasets generated and analysed during the current study are not publicly available due to property rights protection, but may be made available upon request, pending application to and approval from the corresponding author Weilan Xiang. Funding This project was funded by the General scientific research of Provincial Education Department of Zhejiang Province (award Nos. Y202249520). Competing Interests The authors have no relevant financial or non-financial interests to disclose. Author information Xiuping Li And Hanxiao Luo contributed equally to this paper and share the first author. Authors and Affiliations Nursing Department, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310016, China Xiuping Li MSN, Hanxiao Luo MSN, Hangfei Mao MS, Shina Qiao MS, Mengjiao Sun, Xiaojie Zhang MS, Fanglei Gu, Weilan Xiang PHD* Author Contributions Xiuping Li and Hanxiao Luo contributed equally to this work and are co-first authors. Xiuping Li and Weilan Xiang conceived and designed the study. Data collection and material preparation were performed by Xiuping Li, Hangfei Mao, Yushu Sun, Mengjiao Sun, Shina Qiao, Xiaojie Zhang, and Fanglei Gu. Hanxiao Luo conducted the statistical analyses and contributed to data interpretation. Xiuping Li and Hanxiao Luo drafted the initial manuscript. All authors critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript. Corresponding Author s Correspondent to Weilan Xiang PHD. Email address: [email protected] Ethics approval and consent to participate All procedures involving human participants were conducted in accordance with the ethical standards of the institutional and national research committees and with the principles of the Declaration of Helsinki. The present study was approved by the institutional review board at of Sir Run Run Shaw Hospital Affiliated to Zhejiang University School of Medicine (No. 20230149). Electronic informed consent to participate was obtained from all participants prior to data collection. Consent for publication Not applicable. Competing interests All co-authors declare no competing interests. References Yoo SH, Lee J, Kang JH, Maeng CH, Kim YJ, Song E-K, et al. Association of illness understanding with advance care planning and end-of-life care preferences for advanced cancer patients and their family members. Support Care Cancer. 2020;28:2959–67. https://doi.org/10.1007/s00520-019-05174-5 . 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Int J Environ Res Public Health. 2022;19:13119. https://doi.org/10.3390/ijerph192013119 . Chen X, Zhang Y, Arber A, Huo X, Liu J, Sun C, et al. The training effects of a continuing education program on nurses’ knowledge and attitudes to palliative care: a cross sectional study. BMC Palliat Care. 2022;21:56. https://doi.org/10.1186/s12904-022-00953-0 . Hamayoshi M, Goto S, Matsuoka C, Kono A, Miwa K, Tanizawa K, et al. Effects of an advance care planning educational programme intervention on the end-of-life care attitudes of multidisciplinary practitioners at an acute hospital: A pre- and post-study. Palliat Med. 2019;33:1158–65. https://doi.org/10.1177/0269216319860707 . Suikkala A, Tohmola A, Rahko EK, Hökkä M. Future palliative competence needs - a qualitative study of physicians’ and registered nurses’ views. BMC Med Educ. 2021;21:585. https://doi.org/10.1186/s12909-021-02949-5 . Additional Declarations No competing interests reported. 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1","display":"","copyAsset":false,"role":"figure","size":124306,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eZ-score profiles of the five dimensions across the three latent classes\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8438501/v1/a00f7bbc8507a914fc218c9b.png"},{"id":101075023,"identity":"415c1c27-748e-47bb-995e-6a24f14fbc11","added_by":"auto","created_at":"2026-01-25 10:24:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":53988,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHospice Care Knowledge Scores Across Latent Classes\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8438501/v1/cf4a13eeac4de13df049a20f.png"},{"id":101207886,"identity":"e34e2e4c-35cb-45bc-846e-05545fcbff36","added_by":"auto","created_at":"2026-01-27 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As populations age and the burden of life-limiting illness increases worldwide, healthcare professionals are increasingly required to provide care that addresses not only physical symptoms, but also the psychological, social, and existential dimensions of dying[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In this context, workforce readiness has become a critical determinant of the effectiveness and sustainability of palliative care delivery[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong the multiple components of workforce preparedness, healthcare workers\u0026rsquo; attitudes toward death play a particularly important role in shaping end-of-life care practices[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Death-related attitudes influence clinicians\u0026rsquo; willingness to initiate palliative care discussions, their comfort in communicating about prognosis and dying, and their ability to provide emotionally supportive care to patients and families[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Previous studies have shown that fear, avoidance, or discomfort with death may hinder timely palliative care engagement, whereas more accepting attitudes are associated with greater confidence and perceived competence in end-of-life care[\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDeath attitudes are widely conceptualized as multidimensional constructs encompassing fear, avoidance, and different forms of acceptance. Within palliative care settings, these attitudinal dimensions rarely exist in isolation; instead, they co-occur in complex patterns that may reflect healthcare workers\u0026rsquo; overall psychological and professional readiness for end-of-life care. For example, clinicians may simultaneously endorse acceptance of death while still experiencing fear or avoidance in clinical encounters with dying patients[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Understanding how these dimensions cluster within individuals is therefore essential for identifying subgroups of the palliative care workforce who may require different forms of educational or organizational support.\u003c/p\u003e \u003cp\u003eMost existing studies have examined healthcare workers\u0026rsquo; death attitudes using variable-centered approaches, focusing on associations between individual attitude dimensions and demographic or occupational characteristics[\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. While informative, such approaches implicitly assume relative homogeneity within the workforce and may obscure meaningful subgroups characterized by distinct configurations of death-related attitudes. Person-centered methods, such as latent profile analysis, allow for the identification of heterogeneous patterns of attitudes within a population and have the potential to inform more tailored approaches to palliative care education and workforce development[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, the application of these methods among healthcare workers in palliative and hospice care contexts remains limited.\u003c/p\u003e \u003cp\u003eAgainst this background, the present study aimed to identify distinct profiles of death attitudes among healthcare workers using latent profile analysis and to examine how these profiles are associated with hospice care knowledge. By clarifying patterns of death-related attitudes within the palliative care workforce, this study seeks to provide empirical evidence that may inform the design of more targeted and effective educational strategies to strengthen end-of-life care delivery\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cb\u003e1.1 Participants and Setting\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis cross-sectional survey was conducted among healthcare workers from secondary and tertiary hospitals across Zhejiang Province, China. Between September and October 2023, a total of 1,421 valid questionnaires were collected from 31 hospitals located in seven prefecture-level cities, including Hangzhou, Ningbo, Wenzhou, and Jinhua. Zhejiang Province has been one of the national pilot regions for hospice and palliative care, providing a relevant context for investigating healthcare workers' knowledge of hospice care and attitudes toward death.\u003c/p\u003e \u003cp\u003eEligible participants were physicians and nurses working in departments that commonly provide care for patients with life-limiting illnesses, such as oncology, geriatrics, internal medicine, surgery, and critical/emergency care. Inclusion criteria were: (1) age\u0026thinsp;\u0026ge;\u0026thinsp;18 years; (2) possession of a valid nursing or medical qualification certificate; (3)\u0026thinsp;\u0026ge;\u0026thinsp;1 year of clinical experience; and (4) voluntary participation with informed consent. Exclusion criteria included: (1)\u0026thinsp;\u0026lt;\u0026thinsp;1 year of clinical experience; (2) being on leave during the survey period; and (3) temporary or non-registered staff.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eData were collected anonymously via the online platform Questionnaire Star. Trained nursing department coordinators assisted with standardized administration. Each IP address could submit only one response, and questionnaires completed in less than 120 seconds or containing logical inconsistencies were excluded. Ultimately, 1,421 valid questionnaires were included in the analysis (effective response rate\u0026thinsp;=\u0026thinsp;94.7%).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe study adopted convenience sampling for feasibility, while the inclusion of multiple hospitals across diverse regions improved the representativeness of the sample. Ethical approval was obtained from the Institutional Review Board of Sir Run Run Shaw Hospital, Zhejiang University School of Medicine (Approval No. 20230149). All participants provided electronic informed consent.\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e1.2 Measures\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e1.2.1 General information questionnaire\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe general information questionnaire was developed by the research team based on relevant literature and study objectives. It collected participants\u0026rsquo; demographic and occupational characteristics, including gender, age, educational background, region, occupation, professional title, years of work, department, ethnicity, and religious belief.\u003c/p\u003e \u003cp\u003e \u003cb\u003e1.2.2 Hospice Care Knowledge Questionnaire\u003c/b\u003e \u003c/p\u003e \u003cp\u003e The Hospice Care Knowledge Questionnaire was designed by the research team to assess medical staff's understanding of hospice care.Item development was informed by hospice and palliative care curricula, relevant clinical guidelines, and two rounds of expert consultation involving senior nursing educators and palliative care physicians, which also served as the basis for defining the correct responses to each item. The final instrument comprises 20 single-choice items addressing basic concepts of hospice care, symptom and pain management, psychological and social aspects of end-of-life care, and common ethical issues encountered in practice. Each item has three response options (\u0026ldquo;True,\u0026rdquo; \u0026ldquo;False,\u0026rdquo; \u0026ldquo;Don't know\u0026rdquo;). Correct answers were scored as 5 and incorrect/\u0026ldquo;Don't know\u0026rdquo; as 0, yielding a total score of 0\u0026ndash;100. Higher scores indicate greater knowledge. The questionnaire demonstrated strong psychometric performance, with item-level content validity indices of 0.82\u0026ndash;1.00, a scale-level CVI of 0.91, internal consistency reliability of 0.846, and a two-week test\u0026ndash;retest reliability of 0.852. The English version of the Hospice Care Knowledge Questionnaire is provided as Supplementary File 2.\u003c/p\u003e \u003cp\u003e \u003cb\u003e1.2.3 Death Attitude Profile\u0026ndash;Revised(DAP-R)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe DAP-R, originally developed by Wong, Reker, and Gesser and later adapted into Chinese by Tang, has demonstrated good reliability and validity among Chinese healthcare professionals[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The instrument contains 32 items across five dimensions: Fear of Death (FD), Death Avoidance (DA), Neutral Acceptance (NA), Escape Acceptance (EA), and Approach Acceptance (AA). Items are scored on a five-point Likert scale (1\u0026thinsp;=\u0026thinsp;strongly disagree; 5\u0026thinsp;=\u0026thinsp;strongly agree), with higher scores indicating stronger endorsement of the corresponding attitude[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In this study, the Chinese version showed good internal consistency (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.846; subscale α\u0026thinsp;=\u0026thinsp;0.72\u0026ndash;0.83). Both total and subscale scores were used following conventional analytic practice.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics were first generated to summarize participants\u0026rsquo; demographic characteristics, hospice care knowledge, and DAP-R scores, with continuous variables presented as means and standard deviations and categorical variables as frequencies and percentages.\u003c/p\u003e \u003cp\u003eLatent profile analysis (LPA) was then performed in Mplus to identify subgroups of death attitude patterns based on the five DAP-R dimensions. All dimension scores were standardized into z-scores before modeling to ensure comparability across scales[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Competing models with increasing numbers of classes were estimated and evaluated using the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), adjusted BIC (aBIC), entropy, the Lo\u0026ndash;Mendell\u0026ndash;Rubin adjusted likelihood ratio test (LMR-LRT), and the bootstrap likelihood ratio test (BLRT). Model selection was guided by a combination of statistical fit, classification accuracy, and conceptual interpretability, and class-specific standardized means were visualized to aid interpretation[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo examine factors associated with latent class membership, a multinomial logistic regression model was fitted in SPSS using the three-class solution derived from LPA, with Class 1 specified as the reference category. Gender, age, educational level, profession, professional title, department category, years of working, ethnicity, religious belief, and hospice care knowledge score were entered as independent variables. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated, and only significant findings are reported in the main text, with the full regression model provided in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, Supplementary File 1. All data were analyzed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA) and Mplus version 8.3 (Muth\u0026eacute;n \u0026amp; Muth\u0026eacute;n, Los Angeles, CA, USA). A two-sided \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cp\u003eA total of 1,421 healthcare workers were included in the analysis. The distributions of demographic and occupational characteristics across the three latent classes are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Overall, most participants were female (93.4%), younger than 40 years (81.3%), and held a bachelor's degree (83.7%). Nurses accounted for 93.8% of the sample. The mean hospice care knowledge score for the total sample was 45.13\u0026thinsp;\u0026plusmn;\u0026thinsp;11.62 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Significant between-class differences were observed for educational level and profession, whereas no statistically significant differences were found for gender, age group, professional title, years of working, department category, ethnicity, or religious belief. In contrast, both hospice care knowledge and overall death attitude score differed markedly across the three classes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIndicator Differences Across Latent Profiles\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eNo.(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eLatent profile\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll (n\u0026thinsp;=\u0026thinsp;1421)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eClass 1 (n\u0026thinsp;=\u0026thinsp;252)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClass 2 (n\u0026thinsp;=\u0026thinsp;1030)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eClass 3 (n\u0026thinsp;=\u0026thinsp;139)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.315\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e94 (6.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20 (8.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62 (6.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12 (8.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1327 (93.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e230 (92.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e970 (93.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e127 (91.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.793\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e673 (47.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120 (48.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e489 (47.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64 (46.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e482 (33.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e91 (36.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e345 (33.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e46 (33.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41\u0026ndash;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e235 (16.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36 (14.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e173 (16.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26 (18.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31 (2.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25 (2.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssociate degree or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e169 (11.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 (10.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e126 (12.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18 (12.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1189 (83.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e207 (82.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e862 (83.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e120 (86.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaster's degree or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63 (4.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (7.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44 (4.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1 (0.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfession\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNurse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1333 (93.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e224 (89.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e973 (94.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e136 (97.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDoctor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88 (6.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26 (10.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59 (5.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026bull; Professional title\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.663\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e829 (58.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e143 (57.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e605 (58.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e81 (58.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e455 (32.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80 (32.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e326 (31.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49 (35.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSenior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e137 (9.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27 (10.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e101 (9.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9 (6.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYears of working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.606\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e837 (58.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e151 (60.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e607 (58.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e79 (56.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e362 (25.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68 (27.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e257 (24.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37 (26.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e222 (15.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31 (12.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e168 (16.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23 (16.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepartment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurgical Department\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e275 (19.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49 (19.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e203 (19.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23 (16.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternal Medicine Department\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e607 (42.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105 (42.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e434 (42.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e68 (48.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCritical Care System\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e286 (20.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39 (15.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e219 (21.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28 (20.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e253 (17.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57 (22.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e176 (17.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20 (14.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHan Chinese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1399 (98.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e243 (97.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1020 (98.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e136 (97.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Ethnicities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22 (1.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (2.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12 (1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReligious Belief\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1298 (91.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e231 (92.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e945 (91.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e122 (87.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e123 (8.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (7.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e87 (8.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17 (12.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospice Care Knowledge, Mean(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45.13(11.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.97(6.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.54(5.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e69.39(7.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eLatent profile analysis was conducted using standardized (z-score) scores from the five dimensions of the DAP-R scale. Models with one to four classes were estimated and compared. The three-class solution was selected as the optimal model based on a combination of statistical fit indices and interpretability. Compared with the two-class model, the three-class model showed lower AIC, BIC, and adjusted BIC values, and both the Lo\u0026ndash;Mendell\u0026ndash;Rubin test and the bootstrap likelihood ratio test indicated a significant improvement in model fit. And the entropy retained high classification quality in three-class model. Detailed model fit indices are presented in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, Supplementary File 1.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e displays the standardized mean profiles across the five DAP-R dimensions. Class 1 (n\u0026thinsp;=\u0026thinsp;250; 17.6%) showed the lowest levels of natural and approach acceptance and the highest levels of fear and avoidance. Class 2 (n\u0026thinsp;=\u0026thinsp;1,032; 72.6%) exhibited intermediate levels across all dimensions. Class 3 (n\u0026thinsp;=\u0026thinsp;139; 9.8%) demonstrated the most adaptive pattern, with high acceptance and low fear/avoidance. The three trajectories remained clearly separated on all dimensions, indicating distinct attitudinal patterns rather than subtle variations of a single continuum.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDifferences in hospice care knowledge across classes are also presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Knowledge scores increased progressively from Class 1 to Class 3 (29.97\u0026thinsp;\u0026plusmn;\u0026thinsp;6.26; 45.54\u0026thinsp;\u0026plusmn;\u0026thinsp;5.74; 69.39\u0026thinsp;\u0026plusmn;\u0026thinsp;7.98). The violin plot in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e further illustrates these differences. Class 1 displayed a narrow concentration of lower scores, whereas Class 2 showed a symmetric distribution centered around the moderate range. Class 3 exhibited the highest mean score and comparatively less variability. The distributional patterns were consistent with the observed mean differences, suggesting a robust association between hospice care knowledge and death attitude profiles.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA multinomial logistic regression was conducted to examine factors associated with class membership, using Class 1 as the reference category (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Hospice care knowledge emerged as the only significant correlate. Higher knowledge scores were significantly associated with belonging to Class 2 compared with Class 1 (OR\u0026thinsp;=\u0026thinsp;2.261, 95% CI: 2.10\u0026ndash;3.282) and with belonging to Class 3 compared with Class 1 (OR\u0026thinsp;=\u0026thinsp;2.26, 95% CI: 1.81\u0026ndash;2.83). None of the demographic or occupational variables\u0026mdash;including gender, age group, educational level, profession, department type, professional title, years of working, ethnicity, or religious belief\u0026mdash;showed statistically significant associations with class membership (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Full regression results, including all covariates, are provided in Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e, Supplementary File 1.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultinomial logistic regression of hospice care knowledge score on latent class membership\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClass Comparison\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ez\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWald χ\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHospice care knowledge score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClass 2 vs Class 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e71.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.63 (2.10\u0026ndash;3.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClass 3 vs Class 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.26 (1.81\u0026ndash;2.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003eNotes\u003c/em\u003e: Class 1 served as the reference category. β, regression coefficient; SE, standard error; OR, odds ratio; CI, confidence interval. Only statistically significant variable is shown.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study identified three distinct death attitude profiles among healthcare workers and demonstrated a consistent association between hospice care knowledge and profile membership. Most participants belonged to a moderate profile characterized by balanced levels of acceptance and fear, whereas smaller subgroups exhibited either more adaptive or less adaptive orientations toward death. When examined alongside demographic and occupational characteristics, hospice care knowledge showed a statistically significant association with latent profile membership, whereas other examined characteristics did not, underscoring its relevance in relation to healthcare workers\u0026rsquo; attitudes toward death. In addition, the overall level of hospice care knowledge observed in this study was relatively low, with most participants scoring in the poor or very poor range. This finding is consistent with prior studies conducted in China and other settings, which have reported insufficient palliative care knowledge among nurses and other healthcare professionals, largely attributed to limited formal education and training opportunities in end-of-life care[\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe presence of three differentiated profiles indicates substantial heterogeneity in how healthcare workers perceive and engage with death. Similar variability has been reported in previous studies, in which acceptance and fear often coexist among clinicians and vary according to training experiences, cultural context, and clinical exposure[\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In the present study, the profile characterized by higher acceptance and lower fear may reflect healthcare workers who feel better prepared to manage end-of-life situations, potentially owing to greater familiarity with hospice principles or prior educational exposure. Conversely, the profile marked by lower acceptance and heightened fear or avoidance may represent individuals who experience greater emotional discomfort or uncertainty when confronted with dying patients, possibly in the absence of structured end-of-life care training. These findings support the view that healthcare workers do not constitute a homogeneous group with respect to death attitudes but instead form distinct subgroups with practical implications for care delivery[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This heterogeneity is also reflected in international literature. A mixed-methods systematic review found that nurses\u0026rsquo; attitudes toward end-of-life care and death vary substantially across cultural and educational backgrounds, influencing their approaches to care, emotional responses, and communication with dying patients and families[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA key finding of this study is the observed graded association between hospice care knowledge and death attitude profiles. Higher knowledge scores were associated with an increased likelihood of belonging to more adaptive profiles and a reduced likelihood of membership in the least adaptive profile. Although the cross-sectional design precludes causal inference, this pattern is consistent with prior empirical evidence indicating that education and training in hospice or palliative care are associated with more favorable attitudes toward death and dying. For example, Hao et al. demonstrated that a structured palliative care learning intervention significantly improved nurses\u0026rsquo; hospice care knowledge and attitudes toward dying patients, although changes in specific death attitude dimensions varied[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Similarly, a recent meta-analysis from Ethiopia reported that nurses who received palliative care training were more than twice as likely to hold favorable attitudes toward palliative care compared with those without training[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Educational exposure may help reduce misconceptions, improve professional confidence, and enhance psychological preparedness, thereby mitigating fear and avoidance[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In contrast, limited knowledge may reinforce ambiguity and emotional distress when facing end-of-life situations, contributing to less adaptive attitudinal patterns[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. It should be noted that hospice care knowledge was assessed using a self-reported instrument, and the observed associations should therefore be interpreted as indicative rather than causal.\u003c/p\u003e \u003cp\u003eIn contrast to hospice care knowledge, demographic and occupational characteristics\u0026mdash;including age, gender, educational level, profession, department type, and years of clinical experience\u0026mdash;were not significantly associated with death attitude profile membership. Although some earlier studies have reported associations between death attitudes and variables such as age or professional seniority[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e],[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], the absence of such relationships in the present analysis may reflect the relative homogeneity of the sample, which consisted predominantly of young, highly educated nurses working in hospital settings. More importantly, this finding suggests that routine clinical exposure alone may not be sufficient to shape healthcare workers\u0026rsquo; engagement with death in the absence of structured palliative care education. From a palliative care standpoint, this underscores the importance of formal training and reflective learning opportunities as key components of workforce readiness, potentially exerting a more decisive influence on death attitudes than background characteristics[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe clear separation of standardized mean trajectories across the five DAP-R dimensions supports the interpretability of the identified profiles. Consistent differences across fear-, avoidance-, and acceptance-related dimensions suggest stable and meaningful attitudinal patterns rather than minor variations along a single continuum. The observed differences in hospice care knowledge across profiles further reinforce the distinctiveness of these groups, lending credibility to the latent structure identified in this study.\u003c/p\u003e \u003cp\u003eFrom a practical perspective, these findings suggest that strengthening hospice and palliative care education may represent a feasible strategy for promoting more adaptive death attitudes among healthcare workers. Educational approaches that integrate theoretical instruction with reflective learning, clinical exposure, and interdisciplinary collaboration have been shown to improve comfort and competence in end-of-life care. Evidence from intervention and implementation studies suggests that blended educational approaches\u0026mdash;combining e-learning, reflective discussion, and clinical exposure\u0026mdash;can effectively enhance both hospice care knowledge and attitudes toward end-of-life care among nurses[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Given that demographic and occupational factors did not differentiate profiles, such interventions may be most effective when implemented broadly rather than targeted to specific subgroups, particularly in settings where formal palliative care training remains limited[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged. First, the cross-sectional design limits conclusions regarding the directionality of the observed associations between hospice care knowledge and death attitudes. Second, hospice care knowledge was assessed using a self-developed questionnaire, which, despite demonstrating acceptable psychometric properties, has not yet been externally validated across diverse settings. Third, the latent profile solution may be sample-dependent, and replication in independent or longitudinal samples is warranted. Finally, the predominance of nurses and the single-province sampling frame may limit the generalizability of the findings to other professional groups or healthcare systems.\u003c/p\u003e \u003cp\u003eDespite these limitations, this study contributes to the palliative care literature by elucidating the heterogeneity of healthcare workers\u0026rsquo; death attitudes and highlighting their association with hospice care knowledge. Rather than being uniformly distributed, attitudes toward death appear to cluster into distinct patterns with potential relevance for education and workforce development. These findings support the integration of structured hospice and palliative care education into routine professional training as a means of enhancing workforce preparedness and ultimately improving the quality of end-of-life care.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study identified distinct profiles of death attitudes among healthcare workers and found a consistent association between hospice care knowledge and profile membership. The findings highlight the heterogeneity of attitudes toward death within the healthcare workforce and underscore the relevance of educational preparedness in end-of-life care. Strengthening structured hospice and palliative care education may help foster more adaptive attitudes toward death and better equip healthcare workers to meet the complex needs of patients and families at the end of life.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analysed during the current study are not publicly available due to property rights protection, but may be made available upon request, pending application to and approval from the corresponding author\u0026nbsp;Weilan Xiang.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was funded by the General scientific research of Provincial Education Department of Zhejiang Province (award Nos.\u0026nbsp;Y202249520).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXiuping Li And Hanxiao Luo contributed equally to this paper and share the first author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNursing Department, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310016, China\u003c/p\u003e\n\u003cp\u003eXiuping Li MSN, Hanxiao Luo MSN, Hangfei Mao MS, Shina Qiao MS, Mengjiao Sun, Xiaojie Zhang MS, Fanglei Gu, Weilan Xiang PHD*\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXiuping Li and Hanxiao Luo contributed equally to this work and are co-first authors. Xiuping Li and Weilan Xiang conceived and designed the study. Data collection and material preparation were performed by Xiuping Li, Hangfei Mao, Yushu Sun, Mengjiao Sun, Shina Qiao, Xiaojie Zhang, and Fanglei Gu. Hanxiao Luo conducted the statistical analyses and contributed to data interpretation. Xiuping Li and Hanxiao Luo drafted the initial manuscript. All authors critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding Author\u003c/strong\u003e\u003cstrong\u003es\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondent to Weilan Xiang PHD.\u003c/p\u003e\n\u003cp\u003eEmail address: [email protected]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures involving human participants were conducted in accordance with the ethical standards of the institutional and national research committees and with the principles of the Declaration of Helsinki. The present study was approved by the institutional review board at of Sir Run Run Shaw Hospital Affiliated to Zhejiang University School of Medicine (No. 20230149). Electronic informed consent to participate was obtained from all participants prior to data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll co-authors declare no competing interests.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYoo SH, Lee J, Kang JH, Maeng CH, Kim YJ, Song E-K, et al. Association of illness understanding with advance care planning and end-of-life care preferences for advanced cancer patients and their family members. 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BMC Med Educ. 2021;21:585. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12909-021-02949-5\u003c/span\u003e\u003cspan address=\"10.1186/s12909-021-02949-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-palliative-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pcar","sideBox":"Learn more about [BMC Palliative Care](http://bmcpalliatcare.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pcar/default.aspx","title":"BMC Palliative Care","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Palliative care, Hospice care knowledge, Death attitudes, Latent profile analysis, Healthcare workforce, End-of-life care","lastPublishedDoi":"10.21203/rs.3.rs-8438501/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8438501/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHealthcare workers\u0026rsquo; attitudes toward death play an important role in the quality of end-of-life care, yet such attitudes are often treated as homogeneous and insufficiently examined in relation to hospice care preparedness. Understanding heterogeneity in death attitudes and their educational correlates is essential for strengthening the palliative care workforce.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional survey was conducted among 1,421 healthcare workers from secondary and tertiary hospitals in Zhejiang Province, China. Death attitudes were assessed using the Death Attitude Profile\u0026ndash;Revised (DAP-R), and hospice care knowledge was measured using a structured questionnaire. Latent profile analysis was applied to identify distinct death attitude profiles. A multinomial logistic regression model was used to examine associations between hospice care knowledge, demographic characteristics, and profile membership.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThree distinct death attitude profiles were identified: a moderate profile characterized by balanced acceptance and fear, a more adaptive profile marked by higher acceptance and lower fear, and a less adaptive profile characterized by lower acceptance and higher fear or avoidance. Hospice care knowledge showed a consistent and graded association with profile membership, with higher knowledge levels associated with increased likelihood of belonging to more adaptive profiles. In contrast, demographic and occupational characteristics were not significantly associated with profile membership. Overall, hospice care knowledge levels were relatively low, with most participants scoring in the poor or very poor range.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eHealthcare workers exhibit substantial heterogeneity in attitudes toward death, which is closely associated with hospice care knowledge. These findings highlight the relevance of educational preparedness in shaping engagement with end-of-life care and support the integration of structured hospice and palliative care education into routine professional training to enhance workforce readiness and improve the quality of end-of-life care\u003c/p\u003e","manuscriptTitle":"Hospice Care Knowledge and Death Attitude Profiles Among Healthcare Workers: A Latent Profile Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-25 10:23:56","doi":"10.21203/rs.3.rs-8438501/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-14T14:56:45+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-26T14:31:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"224457480808000313831856875440674122789","date":"2026-03-13T12:41:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-26T22:06:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"48328826655687236575961954483957832691","date":"2026-02-13T17:12:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-21T15:18:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-04T01:55:55+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-29T09:13:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-28T06:02:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Palliative Care","date":"2025-12-28T05:54:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-palliative-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pcar","sideBox":"Learn more about [BMC Palliative Care](http://bmcpalliatcare.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pcar/default.aspx","title":"BMC Palliative Care","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"78036877-5756-449f-bf0d-e1253de8fccb","owner":[],"postedDate":"January 25th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-14T14:56:45+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T15:09:52+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-25 10:23:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8438501","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8438501","identity":"rs-8438501","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}