Influencing Factors of Lung Cancer Patients' Participation in Shared Decision-making: a Cross-sectional Study

Influencing Factors of Lung Cancer Patients' Participation in Shared Decision-making: a Cross-sectional Study | 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 Influencing Factors of Lung Cancer Patients' Participation in Shared Decision-making: a Cross-sectional Study Ying Wang, Jinna Zhang, Bo Hu, Jizhe Wang, Laixiang Zhang, Xiaohua Li, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1006105/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: The purpose of this study was to investigate and analyze the level of actual participation and perceived importance of shared decision-making on treatment and care of lung cancer patients, to compare their differences and to explore factors that influence them. Methods: A total of 290 lung cancer patients were collected from the department of oncology and thoracic surgery of a comprehensive medical center in Qingdao from October 2018 to December 2019. Participants completed a cross-sectional questionnaire to assess their actual participation and perceived importance in shared decision-making on treatment and care. Descriptive analysis and non-parametric tests were carried out to assess the status quo of patients' shared decision-making on treatment and care. Binary logistic regression analysis with a stepwise back-wards was applied to predict the factors that affected patients' participation in shared decision-making. Results: The results showed that patients with lung cancer had a low degree of participation in shared decision-making. There were significant differences between actual participation and perceived importance of shared decision-making on treatment and care. Education level, younger, gender, income, marital status, personality, the course of the disease (>6 months), and the Pathological TNM staging (Ⅲ) affected the patient's level of participation in shared decision-making. Conclusion: Actual participation in shared decision-making for the treatment and care of lung cancer patients was low and considered unimportant. We could train oncology nurses to use patient decision aids to help patients and families participate in shared decision-making based patients’ value, preferences and needs. Cancer Biology Lung cancer Patient decision aids Shared decision-making Nursing Introduction World Health Organization reported that the number of new cases and deaths of lung cancer ranked first in 2018 [1]. The common treatment methods including surgery, chemotherapy, immunotherapy, and targeted therapy have been selected to prolong lifespan [2], which increases the risks of distant metastasis, chemotherapy reaction and so on. During the terminal phase of lung cancer patients may also choose palliative care (nutritional support, psychological care), which focuses more on improving patient's quality of life. Consequently, patients need to weigh the uncertain risks and benefits between supportive treatments focusing on prolonging survival and quality of life [3]. In this sense, a rational, scientific decision-making process is needed to ensure patients select treatments and care methods that are consistent with their concerns, goals, values, preference, and circumstances. With the transformation of medical models, "shared decision-making" has become the best way to exchange information between clinicians, nurses and patients. As a scientific decision-making process, SDM is a more inclusive and participative approach involving the exchange of information between professionals and patients [4-5]. During the dialogue, both healthcare practitioners and patients think about how to address patient's co-occurring condition based on the relevant evidence and the patients’ values, preference, needs [6]. Elwyn et al. (2017) proposed and revised the three-talk model to guide SDM [7]. The SDM process is divided into 3 stages: 1) team talk: patients, family, and physician form a team to understand patient's goals, describe options and offer support; 2) option talk: various options are discussed using risk communication principles; and 3) decision talk: informed preferences are obtained and informed choices are made. The three-talk model is more concise to help clinicians better understand the core of SDM and implement these processes. SDM is a disruptive idea and cornerstone of patient-centered care [8]. Compared with informed consent, it pays more attention to the needs, expectations and moral values orientation of patients and is representative of the type of clinical interactive decision-making. Friesen-Storms et al. (2015) have agreed that SDM is the best process whereby health care providers and their patients make information exchange and treatment decisions jointly [8]. Nakayama et al. (2020) find that more prostate cancer patients were willing to actively participate in SDM, with only a minority preferring paternalistic decision-making [9]. Similarly, most breast cancer patients report wanting to be involved in SDM because they have not acquired adequate knowledge concerning risks factors for breast cancer treatment and care [10]. SDM primarily focuses on lung cancer screening when it is applied to lung cancer field [11-12]. Lung cancer screening is very important for high-risk groups (smoking, patients with chronic lung disease), and it is convenient for early treatment of patients [13]. Similarly, SDM in the field of lung cancer treatment and care is also involved. There is evidence that some lung cancer patients prefer treatment and care options that improve quality of life the pros and cons of different approaches are not explain in detail when they make decisions [14]. Patient decision aids are tools that help them understand options, consider possible hazards and benefits, and encourage patients to make the best choices for specific problems prudently and wisely [15]. The International Patient Decision Aid Standards (IPDAS) [16] and The Ottawa Decision Support Framework（ODSF) [17] are two criteria for evaluating the development process and quality of patient decision assistance tools. IPDAS has developed a checklist to help researchers develop patient decision aids (http://ipdas.ohri.ca/using.html). ODSF can guide the development of patient decision aids from three aspects: decisional needs, decision support and decisional outcome (https://decisionaid.ohri.ca/odsf.html). While many clinicians believe they implement SDM, they actually do not [10]. Lack of time, skills, and resources are all factors that affect clinicians' implementation of SDM [18]. These factors influence the level and attitude of lung cancer patients to participate in SDM. Some studies have also explored the subjective factors that influence cancer patients' participation in SDM, such as education level [19]. However, there is a gap in research exploring the factors that influence Chinese lung cancer patients' participation in SDM. To make a thorough inquiry of the actual participation and perceived importance of lung cancer patients’ involvement in SDM in terms of treatment and care, we have conducted this cross-sectional survey. The purposes of the current study are to: (1) assess the current status of lung cancer patients’ attitudes and actual participation in SDM on treatment and care; (2) explore whether there is a statistical difference between the actual participation and perceived importance of lung cancer patients in SDM on treatment and care; and (3) predict factors affecting lung cancer patients’ participation in SDM on treatment and care. Methods Design, p articipants and recruitment This study adopted a cross-sectional study design. We collected lung cancer patients in the thoracic surgery and oncology department of a comprehensive medical center in Qingdao, China from October 2018 to December 2019. Participants were eligible for inclusion if they: (1) were 18 years older; (2) met the diagnostic criteria for lung cancer and were aware of the condition [20]; and (3) were informed consent and voluntary to participate in this research. Exclusion criteria included: patients suffered: (1) severe damage to other organs (such as heart, brain, liver, kidney, etc.) or other severe malignant tumors; (2) cognitive impairment or mental illness; and (3) disputes between themselves or their family and the medical institutions. This study used the cross-sectional study calculation formula N = 4(μαS/δ) 2 , where α was 0.05, δ = 0.5S, and the sample size least was 62 cases. We assumed a 20% loss of follow-up rate, about 75 patients were required. To avoid the bias of results caused by a small sample size. A total of 300 patients with lung cancer were enrolled, eventually. Among them, seven patients gave up answering, and three patients stopped answering because of unstable condition. Finally, a total of 290 lung cancer patients participated in this research (response rate = 96.7%). The data were collected by the researchers on-spot at the bedside of the patient. Before collecting the data, the researchers explained the purpose and significance of the study in order to gain the trust of the patients. Data about the study participants was collected by a paper questionnaire. The researchers were presented to explain the queries to the patients without using eliciting language. If patients were encountered to be agitated or unstable during the study, responses were terminated and reassurance was provided. After the subjects finished their answers, the researchers retrieved the questionnaire and checked for any omissions. If any, they were made up on the spot. Measures Sociodemographic and clinical variables The module on patient characteristics included gender, age, marital status, comorbidities, medical insurance, education level, number of children, income, personality, course of disease and pathological TNM stage. Based on Jung’s theory of psychological types, we divided personality into introverted and extroverted types [21]. Patients who claimed themselves as quiet, eccentric, and preferring solitude to contact with others were considered introverted. Patients who self-reported being enthusiastic, lively, sociable and adaptable to their environment were considered extroverted. Questionnaire of Cancer patients’ decision-making regarding treatment and care Lung cancer patient’s SDM on treatment and care was assessed using the questionnaire compiled by Sainio and Lauri (2003) [22]. The questionnaire consists of four dimensions (actual participation of SDM on treatment and care, perceived importance of SDM on treatment and care) that are rated on a Likert scale from 1 to 3. Finally, we calculated the average value of each part of the scale to evaluate the actual participation degree and perceived importance of people with lung cancer in SDM (≤ 1.5 means high degree of actual participation and perceived importance, > 1.5 means low degree of actual participation and perceived importance). The Chinese version of the questionnaire has been revised and developed by Ma (2004), in which the first item "Amount of intravenous fluids" and the seventh item "Investigation scheduling" were deleted [23] After measuring the reliability and validity of the Chinese version of the scale, it exhibited an acceptable content validity index (CVI = 0.89) and internal consistency (Cronbach's α 0.851 in the perceived importance subscale, Cronbach's α 0.838 in the actual participation subscale). Data analysis The survey data were analyzed using the statistical package IBM SPSS v25.0 (IBM. Corp, New York). Descriptive analyses were applied to analyze socio-demographic variables and disease-related data. We used the Wilcoxon Matched-pairs Signed-rank test to analyze the difference between actual participation and perceived importance. Binary logistic regression analysis with a stepwise back-wards was used to predict the factors that affected actual participation and perceived importance of SDM on treatment and care. A variance inflation factor (VIF) was used to test for multicollinearity, and studies with a VIF of less than 10 were generally considered less likely to have multicollinearity. Because the scales were reversely scored. Thus, in the dummy variable setting of the binary logistic regression model, actual participation in SDM on treatment and care as the dependent variable was 0 for high and 1 for low. Similarly, for perceived importance, importance was 0 and insignificance was 1. The Hosmer-Lemeshow test was used to assess the goodness-of-fit of the model. Statistical significance was set at P < 0.05. Ethical considerations We strictly followed the Helsinki Declaration of the World Medical Congress to conduct this research. The study was approved by the ethics committee of the university to which the investigators belonged. Written informed consent was obtained from all patients and their legal representatives. Results Sample characteristics and situation analysis Of 290 lung cancer patients completed the study, ageing from 29 to 70 years (56.37±9.05), and almost half of whom were female (47.9%, n = 139). Nearly 72.1% of the 290 patients had a junior high school education or higher, the vast majority had an income above 3000 RMB (96.9%, n = 281), most were diagnosed with stage Ⅱ or Ⅲ (70.7%, n = 205), and more than one-third of patients had a disease course of 3 – 6 months. Specific information is presented in Table 1. Only 11% of the 290 participants' actual participation in care SDM was higher, as well as 18.3% of the patients felt that care SDM was important. However, 26.9% of patients actually engaged in treatment SDM higher. SDM for treatment was considered more important by 61% compared to SDM in terms of care (Supplementary file 1). Comparison of the actual participation and perceived importance of SDM on treatment and care To better understand the differences between patients' actual participation and perceived importance in SDM on treatment and care, we performed Wilcoxon Matched-pairs signed-rank test (Supplementary file 2 and 3). The results showed that both the actual participation and perceived importance of SDM on treatment and care of lung cancer patients were statistically significant ( P <0.01). Prediction of factors affecting actual participation and perceived importance of SDM on treatment The VIF test results of this study was less than 5, so the likelihood of multicollinearity was minimal. The results of binary logistic regression with a stepwise backward showed that actual participation in SDM was higher among lung cancer patients who were male, younger, had disease course more than 6 months, TNM stage IV, higher education and income (Table 2). However, actual participation was lower among lung cancer patients with a disease course of 3-6 months. We also found higher awareness of the importance of SDM on treatment among patients with other marital status (e.g., divorced, widowed), higher literacy and income (Table 3). However, patients with stage Ⅲ TNM and disease course of 3 – 6 months had lower perceived importance of SDM on treatment (Table 3). Prediction of factors affecting actual participation and perceived importance of SDM on care We found that patients with lung cancer were more willing to participate in care decisions when they possessed higher education, higher income levels, more children, an outgoing personality, and a disease course of more than 6 months (Table 4). We also found that patients with lung cancer perceived higher importance when they possessed higher education, income level, were male, other marital status (e.g., divorced, widowed), had a disease course of more than 6 months, and had TNM stage Ⅳ (Table 5). Among disease-related factors, lung cancer patients with a course of 3 – 6 months considered it unimportant to participate in SDM on care (Table 5). Discussions SDM is important because it ensures that patients’ values, preferences, beliefs and their contextual factors guide all clinical decisions in an evidence-based context [24]. The results of this study indicated that actual participation and perceived importance of SDM on treatment and care among lung cancer patients was low. Furthermore, the actual participation of lung cancer patients in SDM on treatment and care was lower than their perceived importance. This suggested that although participants perceived that participation in SDM on treatment and care was important, their actual participation was not high. The results of this study suggested that patients with higher education actually participated to a greater extent and perceived importance of SDM on treatment and care [19]. Patients with low education level had difficulty in understanding the complexities of medical science or even communicating with healthcare professionals, making it difficult for them to make the best choices. Patients with a high level of education were more likely to receive disease-related information. Studies demonstrated that lung cancer patients would be very interested in the treatment and care process if they had access to sufficient information (19,25-26). Although Chinese existing health insurance policy has wide coverage, not all anticancer drugs mainly used by cancer patients are included in the healthcare system. It is still a heavy burden especially for low-income cancer patients in rural China [27]. We speculated that this group of patients develop thoughts of abandoning treatment due to the high cost of treatment and care, and had difficulty actively participating in SDM. However, it does not preclude the possibility that some of these patients may be more active in discussing cost-efficient treatment options with clinicians and have a higher level of SDM. Therefore, the impact of income level on lung cancer patients' participation in SDM needs to be further explored. Divorced and widowed patients considered it was important to participate in SDM on treatment and care. Some studies had shown that family involvement in SDM for cancer patients was associated with a better understanding of cancer-related information [28]. In the absence of family support, divorced and widowed patients would engage in the three-talk model on their own and make informed decisions with clinicians. In this context, medical staff should provide adequate decision support to patients, and information about patient's concerns (treatment modalities, side effects, prognosis). Men and younger patients were actually more participate in SDM on treatment. Male patients generally took on more responsibility in the family and could analyze treatment more rationally. Younger patients are more receptive to the disease and more knowledgeable about relevant information than the elderly. As a result, male and younger patients more actively participated in SDM on treatment. We also found that patients who were extroverted and had more children actually had higher levels of SDM involvement in care. We speculated that extroverted patients were willing to participate in care decision and chose more appropriate care for themselves. Patients with more children had stronger family support systems. For complex methods of care, the children of this group of patients would help them understand, which would help increase the patient's motivation to participate in care decisions. Patients diagnosed with cancer less than 3 months may be in a fear psychological stage [29]. They fear and refuse to acknowledge that they have been confirmed to have lung cancer. Lung cancer patients diagnosed within 3–6 months underwent chemotherapy and experienced intolerable adverse effects that make them resist treatment and care options. As a result, patients at this stage have a low level of actual participation of SDM on their treatment and perceive SDM as unimportant in treatment and care. Lung cancer patients with a course of more than 6 months may be in the adaptation period, accept their own diagnostic facts, actively participate in the treatment and care of SDM and discuss more useful programs. TNM stage is an important determinant of survival in lung cancer patients [30]. For patients with stage III lung cancer, the five-year survival rate is much lower than for stages I and II, and most patients receive chemotherapy and radiotherapy with enduring adverse reactions [30]. Therefore, we speculated that patients with stage III lung cancer were not better off after receiving treatment and did not consider decision on treatment approach to be important. We found that stage IV patients considered SDM on care to be more important. The five-year survival rate for patients with stage IV lung cancer pathology was estimated to be 13%, compared to 2% for clinical stage IV patients [30]. Patients with stage IV lung cancer present with symptoms such as cough, dyspnea, hemoptysis and chest pain. For these reasons, we speculate that patients prefer care methods that promote a better quality of life rather than pursuing a longer survival rate. Therefore, they focus more on the care approach. Healthcare professionals can use patient decision aids to help patients understand the treatment process and encourage them to express their wishes. The patient decision aids website, established by the Ottawa Hospital Research Association, is a platform that provides decision support [31]. We can directly download and use the patient decision aids list for lung cancer screening patients on this platform. A patient decision aid for treatment selection for lung cancer patients had been developed in the Netherlands (http://www.keuzehulp-longkanker.nl/). Patients can comprehensively consider the pros and cons of surgery and targeted radiotherapy based on the information on this website and decide together with their clinician. Decision coaching is another form of patient decision aids, which is developed in accordance with IPADS [32]. Rahn et al. (2018) conducted a preliminary randomized controlled study in which a decision aid implemented by a nurse-led decision coach facilitated patient participation in SDM [33]. Also, there was evidence that decision coaching could avoid decision-making entanglement and improve the quality of communication with patients and facilitate their learning [34]. The MAGIC program, proposed by the British Health Foundation, has developed option grids to help patients engage with SDM [35]. Currently, treatment option grids are used in a wide range of diseases, such as breast cancer, knee joint arthritis, prostate cancer [36-38]. Study confirmed that the application of option grids in lung cancer screening could lead to better SDM experience and advanced knowledge of lung cancer screening [39]. With advances in medicine and the popularity of SDM, it is imperative to encourage lung cancer patients to participate in SDM. Healthcare professionals can use patient decision aids to help patients choose decisions that match their values, preferences, and personal goals. Clinical implications In the Chinese cultural context and healthcare system, clinicians lack sufficient time to explain the pros and cons of different treatments to patients. As close partners of clinicians, nurses have more contact with patients than clinicians and are more likely to provide health education and understand patients’ wishes regarding treatment and care options. Transitional care is critical for chronic diseases such as cancer, and community health workers are the primary providers of transition care services in the community. Within certain limits of authority, we can train oncology nurse specialists in SDM to join medical staff-patient-family and hospital-home-communities to provide SDM for patients. We should use SDM to maximize patient autonomy and use patient decision aids to help them make decisions. Limitation However, this study has the following limitations. First, this study was conducted in only one comprehensive medical center with limited sample selection. Second, shared decision-making involved not only patients but also their family members. In this study, we didn’t collect the opinions from family members. Third, it is best to analyze the study results through questionnaires and interviews. Therefore, we will conduct interviews with lung cancer patients to obtain more detailed information and include patients' family members in future studies. The results of this study could inform the development of the intervention and will include additional factors as well as future family involvement. Conclusions Actual participation and perceived importance in SDM on treatment and care among lung cancer patients were low and there was variation between them. Lung cancer patients' actual participation in SDM on treatment and care was affected by background factors (education level, household income) and health care provider factors (lack of time, attitude towards SDM). Therefore, SDM orientation sessions should be designed accordingly to the social background of lung cancer patients to help them actively participate. Due to the limited time available to clinicians, nurses are better suited to act as a liaison between patients and physicians to provide SDM support. Thus, SDM knowledge training for oncology nurses is beneficial in facilitating SDM. Declarations Funding: The study was funded by Project of Research Planning Foundation on Humanities and Social Sciences of the Ministry of Education (NO. 20YJAZH144). Conflicts of interest/Competing interests: No conflict of financial or other interest has been declared by the authors. Availability of data and material: All authors declared that all data and materials as well as software application or custom code support their published claims and comply with field standards. Code availability: Not applicable. Authors' contributions: All authors contributed to the study conception and design. Study design and material preparation were performed by Ying Wang, Bo Hu, and Jinna Zhang. Data collection and analysis were performed by Ying Wang, Jinna Zhang, Bo Hu, Jizhe Wang, Laixiang Zhang, Xiaohua Li, and Xiuli Zhu. The first draft of the manuscript was written by Ying Wang, Jinna Zhang, and Bo Hu and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Ethics approval : This study was conducted according to the Declaration of Helsinki and were supported by the ethical committee of the university which the researchers affiliated. Consent to participate: Before distributing the questionnaires, all the patients signed the informed consents. That indicated that they understood the nature and purpose of the study and they knew that their personal information would not be divulged. Consent for publication: Not applicable. Because this is not a case study, but cross-sectional study. We collect data anonymously. We present the results by analysing a large number of quantitative data and there will be no information leakage of any participants. References World Health Organization. (2021). Cancer. Retrieved 05-01, 2021, from https://www.who.int/news-room/fact-sheets/detail/cancer. Duma, N., Santana-Davila, R., & Molina, J. R. (2019). Non-Small Cell Lung Cancer: Epidemiology, Screening, Diagnosis, and Treatment. Mayo Clin Proc, 94 (8), 1623-1640. doi: 10.1016/j.mayocp.2019.01.013. Schmidt, K., Damm, K., Prenzler, A., Golpon, H., & Welte, T. (2016). Preferences of lung cancer patients for treatment and decision-making: a systematic literature review. European journal of cancer care, 25 (4), 580–591. doi: 10.1111/ecc.12425. Kunneman, M., Montori, V. M., Castaneda-Guarderas, A., & Hess, E. P. (2016). What Is Shared Decision Making? (and What It Is Not). Acad Emerg Med, 23 (12), 1320–1324. doi:10.1111/acem.13065. Montori, V. M., Kunneman, M., & Brito, J. P. (2017). Shared Decision Making and Improving Health Care: The Answer Is Not In. JAMA, 318 (7), 617–618. doi: 0.1001/jama.2017.10168. Fulford K., & Handa A. (2021). New resources for understanding patients' values in the context of shared clinical decision-making. World Psychiatry, 20 (3), 446-447. doi:10.1002/wps.20902. Elwyn, G., Durand, M. A., Song, J., Aarts, J., Barr, P. J., Berger, Z., . . . Van der Weijden, T. (2017). A three-talk model for shared decision making: multistage consultation process. Bmj, 359 , j4891. doi: 10.1136/bmj. j4891. Friesen-Storms, J. H., Bours, G. J., van der Weijden, T., & Beurskens, A. J. (2015). Shared decision making in chronic care in the context of evidence based practice in nursing. Int J Nurs Stud, 52 (1), 393-402. doi: 10.1016/j.ijnurstu.2014.06.012. Nakayama, K., Osaka, W., Matsubara, N., Takeuchi, T., Toyoda, M., Ohtake, N., & Uemura, H. (2020). Shared decision making, physicians' explanations, and treatment satisfaction: a cross-sectional survey of prostate cancer patients. BMC Med Inform Decis Mak, 20 (1), 334. doi: 10.1186/s12911-020-01355-z. Berger-Höger, B., Liethmann, K., Mühlhauser, I., Haastert, B., & Steckelberg, A. (2019). Nurse-led coaching of shared decision-making for women with ductal carcinoma in situ in breast care centers: A cluster randomized controlled trial. Int J Nurs Stud, 93 , 141-152. doi: 10.1016/j.ijnurstu.2019.01.013. Brenner, A. T., Malo, T. L., Margolis, M., Elston Lafata, J., James, S., Vu, M. B., & Reuland, D. S. (2018). Evaluating Shared Decision Making for Lung Cancer Screening. JAMA Intern Med, 178 (10), 1311-1316. doi: 10.1001/jamainternmed.2018.3054. Lowenstein, M., Vijayaraghavan, M., Burke, N. J., Karliner, L., Wang, S., Peters, M., . . . Kaplan, C. P. (2019). Real-world lung cancer screening decision-making: Barriers and facilitators. Lung Cancer, 133 , 32-37. doi: 10.1016/j.lungcan.2019.04.026. Hall, H., Tocock, A., Burdett, S., Fisher, D., Ricketts, W. M., Robson, J., et al. (2021). Association between time-to-treatment and outcomes in non-small cell lung cancer: a systematic review. Thorax , thoraxjnl-2021-216865. doi: 10.1136/thoraxjnl-2021-216865. Sullivan, D. R., Eden, K. B., Dieckmann, N. F., Golden, S. E., Vranas, K. C., Nugent, S. M., & Slatore, C. G. (2019). Understanding patients' values and preferences regarding early stage lung cancer treatment decision making. Lung Cancer, 131 , 47-57. doi: 10.1016/j.lungcan.2019.03.009. O'Connor, A. M., Stacey, D., Entwistle, V., Llewellyn-Thomas, H., Rovner, D., Holmes-Rovner, M., Tait, V., Tetroe, J., Fiset, V., Barry, M., & Jones, J. (2003). Decision aids for people facing health treatment or screening decisions . The Cochrane database of systematic reviews, (2), CD001431. doi: 10.1002/14651858.CD001431. Elwyn, G., O'Connor, A., Stacey, D., Volk, R., Edwards, A., Coulter, A., et al., … International Patient Decision Aids Standards (IPDAS) Collaboration (2006). Developing a quality criteria framework for patient decision aids: online international Delphi consensus process. BMJ (Clinical research ed.), 333(7565), 417. doi: 10.1136/bmj.38926.629329.AE. Hoefel, L., & Lewis, K. B. (2020). 20th Anniversary Update of the Ottawa Decision Support Framework: Part 2 Subanalysis of a Systematic Review of Patient Decision Aids. Med Decis Making, 40 (4), 522-539. doi: 10.1177/0272989x20924645. Coulter A. (2017). Shared decision making: everyone wants it, so why isn't it happening? World psychiatry, 16 (2), 117–118. doi: 10.1002/wps.20407. Loh, K., Tsang, M., LeBlanc, T., Back, A., Duberstein, P., Mohile, S., . . . Lee, S. (2020). Decisional involvement and information preferences of patients with hematologic malignancies. Blood Advances, 4 (21), 5492-5500. doi: 10.1182/bloodadvances.2020003044. Detterbeck, F. C., Boffa, D. J., Kim, A. W., & Tanoue, L. T. (2017). The Eighth Edition Lung Cancer Stage Classification. Chest, 151 (1), 193-203. doi: 10.1016/j.chest.2016.10.010. John Beebe, C. J. (2016). Psychological Types . London; New York: Routledge. Sainio, C., & Lauri, S. (2003). Cancer patients' decision-making regarding treatment and nursing care. J Adv Nurs, 41 (3), 250-260. doi: 10.1046/j.1365-2648.2003.02525. x. Ma, L. (2004). Research on the status quo and influencing factors of cancer patients' participation in treatment and nursing decisions. (Master), Peking Union Medical College, Beijing. Rabi, D. M., Kunneman, M., & Montori, V. M. (2020). When Guidelines Recommend Shared Decision-making. JAMA, 323 (14), 1345–1346. doi: 10.1001/jama.2020.1525. Hull, O., Niranjan, S. J., Wallace, A. S., Williams, B. R., Turkman, Y. E., Ingram, S. A., . . . Rocque, G. B. (2020). Should we be talking about guidelines with patients? A qualitative analysis in metastatic breast cancer. Breast Cancer Res Treat, 184 (1), 115-121. doi: 10.1007/s10549-020-05832-x. Passalacqua, R., Caminiti, C., Salvagni, S., Barni, S., Beretta, G. D., Carlini, P., . . . Campione, F. (2004). Effects of media information on cancer patients' opinions, feelings, decision-making process and physician-patient communication. Cancer, 100 (5), 1077-1084. doi: 10.1002/cncr.20050. Leng, A., Jing, J., Nicholas, S., & Wang, J. (2019). Geographical disparities in treatment and health care costs for end-of-life cancer patients in China: a retrospective study. BMC Cancer, 19 (1), 39. doi: 10.1186/s12885-018-5237-1. Hobbs GS, Landrum MB, Arora NK, et al. (2015). The role of families in decisions regarding cancer treatments. Cancer, 121 (7):1079-1087. doi: 10.1002/cncr.29064. Chen, Y. C., Huang, H. M., Kao, C. C., Sun, C. K., Chiang, C. Y., & Sun, F. K. (2016). The Psychological Process of Breast Cancer Patients Receiving Initial Chemotherapy: Rising From the Ashes. Cancer Nurs, 39 (6), E36-e44. doi: 10.1097/ncc.0000000000000331. Woodard, G. A., Jones, K. D., & Jablons, D. M. (2016). Lung Cancer Staging and Prognosis. Cancer Treat Res, 170 , 47-75. doi: 10.1007/978-3-319-40389-2_3. Patient Decision Aids. (2020). Patient Decision Aids. Retrieved 02-20, 2021, from https://decisionaid.ohri.ca/index.html. Rahn, A. C., Jull, J., Boland, L., Finderup, J., Loiselle, M. C., Smith, M., Köpke, S., & Stacey, D. (2021). Guidance and/or Decision Coaching with Patient Decision Aids: Scoping Reviews to Inform the International Patient Decision Aid Standards (IPDAS). Medical decision making, 41 (7), 938–953. doi: 10.1177/0272989X21997330. Rahn, A. C., Köpke, S., Backhus, I., Kasper, J., Anger, K., Untiedt, B., . . . Heesen, C. (2018). Nurse-led immunotreatment DEcision Coaching In people with Multiple Sclerosis (DECIMS) - Feasibility testing, pilot randomised controlled trial and mixed methods process evaluation. Int J Nurs Stud, 78 , 26-36. doi: 10.1016/j.ijnurstu.2017.08.011. Stacey, D., & Légaré, F. (2020). 20th Anniversary Ottawa Decision Support Framework: Part 3 Overview of Systematic Reviews and Updated Framework. Med Decis Making, 40 (3), 379-398. doi: 10.1177/0272989x20911870. The Health Foundation. (2012). A simple tool to facilitate shared decisions. Retrieved June 15, 2021, from http://www.health.org.uk/newsletter-feature/a-simple-tool-to-facilitate -shared-decisions. Durand, M. A., Yen, R. W., O'Malley, A. J., Schubbe, D., Politi, M. C., Saunders, C. H., . . . Elwyn, G. (2020). What matters most: Randomized controlled trial of breast cancer surgery conversation aids across socioeconomic strata. Cancer. 127 (3), 422–436. doi: 10.1002/cncr.33248. Kinsey, K., Firth, J., Elwyn, G., Edwards, A., Brain, K., Marrin, K., . . . Wood, F. (2017). Patients' views on the use of an Option Grid for knee osteoarthritis in physiotherapy clinical encounters: An interview study. Health Expect, 20 (6), 1302-1310. doi: 10.1111/hex.12570. Scalia, P., Durand, M. A., Faber, M., Kremer, J. A., Song, J., & Elwyn, G. (2019). User-testing an interactive option grid decision aid for prostate cancer screening: lessons to improve usability. Bmj Open, 9 (5), e026748. doi: 10.1136/bmjopen-2018-026748. Sferra, S. R., Cheng, J. S., Boynton, Z., DiSesa, V., Kaiser, L. R., Ma, G. X., & Erkmen, C. P. (2020). Aiding shared decision making in lung cancer screening: two decision tools. J Public Health (Oxf), fdaa063. doi: 10.1093/pubmed/fdaa063. tables Table 1 Descriptive analysis of sociodemographic data and disease-related data ( N =290) Variables N (%) N / % SDM on treatment SDM on care Actual participation Perceived importance Actual participation Perceived importance High Low Importance Unimportance High Low Importance Unimportance Gender Male 151 (52.1) 49 (16.9) 102 (35.2) 96 (33.1) 55 (19.0) 23(7.9) 128 (44.1) 36 (12.3) 115 (39.7) Female 139 (47.9) 29 (10.0) 110 (37.9) 81 (27.9) 58 (20.0) 9 (3.1) 130 (44.8) 17 (5.9) 122 (42.1) Age ≤ 40 21 (7.2) 9 (3.1) 12 (4.1) 16 (5.5) 5 (1.7) 2 (0.7) 19 (6.6) 6 (2.1) 15 (5.2) 41 – 50 40 (13.8) 17 (5.9) 23 (7.9) 26 (9.0) 14 (4.8) 7 (2.4) 33 (11.4) 8 (2.8) 32 (11.0) 51 – 60 120 (41.4) 36 (12.4) 84 (29.0) 78 (26.9) 42 (14.5) 15 (5.2) 105 (36.2) 24 (8.3) 96 (33.1) > 60 109 (37.6) 16 (5.5) 93 (32.1) 57 (19.7) 52 (17.9) 8 (2.8) 101 (34.8) 15 (5.2) 94 (32.4) Marital status Married 267 (92.1) 71 (24.5) 196 (67.6) 160 (55.2) 107 (36.9) 27 (9.3) 240 (82.8) 46 (15.9) 221 (76.2) Other 23 (8.9) 7 (2.4) 16 (5.5) 17 (5.9) 6 (2.1) 5 (1.7) 18 (6.2) 7 (2.4) 16 (5.5) Comorbidities No 215 (74.1) 60 (20.7) 155 (53.4) 130 (44.8) 85 (29.3) 21 (7.2) 194 (66.9) 34 (11.7) 181 (62.4) Yes 75 (25.9) 18 (6.2) 57 (19.7) 47 (16.2) 28 (9.7) 11 (3.8) 64 (22.1) 19 (6.6) 56 (19.3) Medical insurance Employee health insurance 141 (48.6) 40 (13.8) 101 (34.8) 92 (31.7) 49 (16.9) 19 (6.5) 122 (42.1) 31 (10.7) 110 (37.9) Resident health insurance 125 (43.1) 31 (10.7) 94 (32.4) 72 (24.8) 53 (18.3) 11 (3.8) 114 (39.3) 20 (6.9) 105 (36.2) Own expense 24 (8.3) 7 (2.4) 17 (5.9) 13 (4.5) 11 (3.8) 2 (0.7) 22 (7.6) 2 (0.7) 22 (7.6) Education level Illiteracy / Primary school 81 (27.9) 8 (2.8) 73 (25.2) 39 (13.4) 42 (14.5) 3 (1.0) 78 (26.9) 9 (3.1) 72 (24.8) Junior high school 111 (38.3) 32 (11.0) 79 (27.2) 66 (22.8) 45 (15.5) 11 (3.8) 100 (34.5) 14 (4.8) 97 (33.4) High school 49 (16.9) 14 (4.8) 35 (12.1) 37 (12.8) 12 (4.1) 6 (2.1) 43 (14.8) 12 (4.1) 37 (12.8) Junior college 20 (6.9) 9 (3.1) 11 (3.8) 13 (4.5) 7 (2.4) 3 (1.0) 17 (5.9) 7 (2.4) 13 (4.5) Bachelor degree and above 29 (10.0) 15 (5.2) 14 (4.8) 22 (7.6) 7 (2.4) 9 (3.1) 20 (6.9) 11 (3.8) 18 (6.2) Number of children ≤ 1 129 (44.5) 38 (13.1) 91 (31.4) 94 (32.4) 35 (12.1) 12 (4.1) 117 (40.3) 27 (9.3) 102 (35.2) 2 129 (44.5) 30 (10.3) 99 (34.1) 65 (22.4) 64 (22.1) 13 (4.5) 116 (40.0) 17 (5.9) 112 (38.6) ≥ 3 32 (11.0) 10 (3.4) 22 (7.6) 19 (6.3) 14 (4.7) 7 (2.4) 25 (8.6) 9 (3.1) 23 (7.9) Income (RMB) < 3000 9 (3.1) 0 (0.0) 9 (3.1) 2 (0.7) 7 (2.4) 0 (0.0) 9 (3.1) 2 (0.7) 7 (2.4) 3000 – 5000 76 (26.2) 11 (3.8) 65 (22.4) 31 (10.7) 45 (15.5) 3 (1.0) 73 (25.2) 5 (1.7) 71 (24.5) 5001 – 10000 175 (60.3) 54 (18.6) 121 (41.7) 118 (40.7) 57 (19.7) 22 (7.6) 153 (52.8) 34 (11.7) 141 (48.6) > 10000 30 (10.3) 13 (4.5) 17 (5.9) 26 (9.0) 4 (1.4) 7 (2.4) 23 (7.9) 12 (4.1) 18 (6.2) Personality Introvert 200 (69.0) 52 (17.9) 148 (51.0) 127 (43.8) 73 (25.2) 14 (4.8) 186 (64.1) 32 (11.1) 168 (57.9) Extrovert 90 (31.0) 26 (9.0) 64 (22.1) 50 (17.2) 40 (13.8) 18 (6.2) 72 (24.8) 21 (7.2) 69 (23.8) Course of disease < 3 months 120 (41.4) 30 (10.3) 90 (31.0) 87 (30.0) 33 (11.4) 6 (2.1) 114 (39.3) 20 (6.9) 100 (34.5) 3 – 6 months 108 (37.2) 6 (2.1) 102 (35.2) 40 (13.8) 68 (23.4) 4 (1.3) 104 (35.9) 7 (2.4) 101 (34.8) > 6 months 62 (21.4) 42 (14.5) 20 (6.9) 50 (17.3) 12 (4.1) 22 (7.6) 40 (13.8) 26 (9.0) 36 (12.4) Pathological typing Ⅰ 48 (16.6) 11 (3.8) 37 (12.8) 34 (11.7) 14 (4.9) 5 (1.8) 43 (14.8) 9 (3.2) 39 (13.4) Ⅱ 122 (42.1) 32 (11.0) 90 (32.1) 80 (27.6) 42 (14.5) 9 (3.1) 113 (39.0) 17 (5.9) 105 (36.2) Ⅲ 83 (28.6) 14 (4.8) 69 (23.8) 36 (12.4) 47 (16.2) 4 (1.4) 79 (27.2) 8 (2.7) 75 (25.9) Ⅳ 37 (12.8) 21 (7.2) 16 (5.6) 27 (9.3) 10 (3.5) 14 (4.9) 23 (7.9) 19 (6.6) 18 (6.2) Note: SDM: shared decision-making Table 2 Multi-factor prediction of actual participation in SDM on treatment. Characteristics OR 95% CI P Demographic characteristics Gender 1.994 1.108 – 3.587 0.021 * Age 1.040 1.006 – 1.075 0.019 * Marital status 0.564 0.184 – 1.616 0.274 Medical insurance Employee health insurance Reference 0.279 Resident health insurance 0.638 0.335 – 1.215 0.171 Own expense 0.497 0.161 – 1.529 0.223 Education level 0.656 0.508 – 0.846 0.001 ** Income (￥) 0.458 0.281 – 0.747 0.002 ** Disease-related factors Course of disease < 3 months Reference <0.01 ** 3 – 6 months 5.845 2.252 – 15.167 6 months 0.162 0.077 – 0.337 <0.01 ** Pathological typing Ⅰ Reference 0.008 ** Ⅱ 0.673 0.281 – 1.609 0.373 Ⅲ 1.521 0.543 – 4.259 0.424 Ⅳ 0.244 0.079 – 0.753 0.014 * Note: OR: odds ratio; CI: Confidence intervals. ** Indicates statistical significance at p≤0.01. * Indicates statistical significance at P ≤ 0.05. Demographic characteristics: Omnbius Tests of model Coefficients: P ≤ 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: χ 2 = 8.764， P = 0.363; Disease-related factors: Omnbius Tests of model Coefficients: P ≤ 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: χ 2 = 6.879, P = 0.332. SDM: Shared decision-making. Table 3 Multi-factor prediction of perceived importance of SDM on treatment. Characteristics OR 95% CI P Demographic characteristics Marital status 0.253 0.085 – 0.754 0.014 * Education level 0.763 0.606 – 0.961 0.021 * Number of children 1.499 0.999 – 2.249 0.051 Income 0.356 0.229 – 0.553 <0.01 ** Disease-related factors Course of disease < 3 months Reference <0.01 ** 3 – 6 months 3.944 2.207 – 7.049 6 months 0.562 0.256 – 1.233 0.151 Pathological typing Ⅰ Reference 0.020 * Ⅱ 1.015 0.469 – 2.199 0.969 Ⅲ 2.463 1.080 – 5.618 0.032 * Ⅳ 0.883 0.311 – 2.511 0.816 Note: OR: odds ratio; CI: Confidence intervals. ** Indicates statistical significance at P ≤ 0.01. * Indicates statistical significance at P ≤ 0.05. Demographic characteristics: Omnbius Tests of model Coefficients: P ≤ 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: χ 2 = 2.852, P=0.898; Disease-related factors: Omnbius Tests of model Coefficients: P ≤ 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: χ 2 = 2.388, P = 0.935. SDM: Shared decision-making. Table 4 Multi-factor prediction of actual participation in SDM on care. Characteristics OR 95% CI P Demographic characteristics Education level 0.575 0.425 – 0.778 <0.01 ** Number of children 0.361 0.184 – 0.706 0.003 ** Income (￥) 0.347 0.180 – 0.670 0.002 ** Personality 0.244 0.106 – 0.558 0.001 ** Disease-related factors Course of disease < 3 months Reference 6 months 0.104 0.037 – 0.295 <0.01 ** Pathological typing Ⅰ Reference 0.002 ** Ⅱ 1.571 0.454 – 5.441 0.476 Ⅲ 3.325 0.754 – 14.660 0.113 Ⅳ 0.328 0.090 – 1.195 0.328 Note: OR: odds ratio; CI: Confidence intervals. ** Indicates statistical significance at p ≤ 0.01. * Indicates statistical significance at P ≤ 0.05; Demographic characteristics: Omnbius Tests of model Coefficients: P ≤ 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: χ 2 = 13.090, P = 0.109; Disease-related factors: Omnbius Tests of model Coefficients: P ≤ 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: χ 2 = 4.738, P = 0.692. SDM : Shared decision-making. Table 5 Multi-factor prediction of perceived importance of SDM on care. Characteristics OR 95% CI P Demographic characteristics Gender 2.302 1.175 – 4.513 0.015 * Marital status 0.320 0.109 – 0.936 0.037 * Education level 0.625 0.487 – 0.801 <0.01 ** Income 0.500 0.301 – 0.830 0.007 ** Disease-related factors Course of disease < 3 months Reference 6 months 0.329 0.153 – 0.708 0.004 ** Pathological typing Ⅰ Reference 0.001 ** Ⅱ 1.311 0.520 – 3.303 0.566 Ⅲ 2.110 0.703 – 6.330 0.183 Ⅳ 0.251 0.086 – 0.727 0.011 * Note: OR: odds ratio; CI: Confidence intervals. ** Indicates statistical significance at P ≤ 0.01. * Indicates statistical significance at P ≤ 0.05. Demographic characteristics: Omnbius Tests of model Coefficients: P ≤ 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: χ 2 = 10.207, P = 0.177; Disease-related factors: Omnbius Tests of model Coefficients: P ≤ 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: χ 2 = 1.617, P = 0.951. SDM: Shared decision-making. 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16:31:42","extension":"doc","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":69057,"visible":true,"origin":"","legend":"","description":"","filename":"STROBEchecklistcrosssectional.doc","url":"https://assets-eu.researchsquare.com/files/rs-1006105/v1/1f9175ec845ef380946e4cac.doc"},{"id":15973623,"identity":"aa18c643-c3a8-4388-ac9f-46f81f1c2b64","added_by":"auto","created_at":"2021-11-29 16:31:42","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":19215,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-1006105/v1/f73cf445a8d7468c1c830092.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eInfluencing Factors of Lung Cancer Patients' Participation in Shared Decision-making: a Cross-sectional Study\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWorld Health Organization reported that the number of new cases and deaths of lung cancer ranked first in 2018 [1]. The common treatment methods including surgery, chemotherapy, immunotherapy, and targeted therapy have been selected to prolong lifespan [2], which increases the risks of distant metastasis, chemotherapy reaction and so on. During the terminal phase of lung cancer patients may also choose palliative care (nutritional support, psychological care), which focuses more on improving patient\u0026apos;s quality of life. Consequently, patients need to weigh the uncertain risks and benefits between supportive treatments focusing on prolonging survival and quality of life [3]. In this sense, a rational, scientific decision-making process is needed to ensure patients select treatments and care methods that are consistent with their concerns, goals, values, preference, and circumstances.\u003c/p\u003e\n\u003cp\u003eWith the transformation of medical models, \u0026quot;shared decision-making\u0026quot; has become the best way to exchange information between clinicians, nurses and patients. As a scientific decision-making process, SDM is a more inclusive and participative approach involving the exchange of information between professionals and patients [4-5]. During the dialogue, both healthcare practitioners and patients think about how to address patient\u0026apos;s co-occurring condition based on the relevant evidence and the patients\u0026rsquo; values, preference, needs [6]. Elwyn et al. (2017) proposed and revised the three-talk model to guide SDM [7]. The SDM process is divided into 3 stages: 1) team talk: patients, family, and physician form a team to understand patient\u0026apos;s goals, describe options and offer support; 2) option talk: various options are discussed using risk communication principles; and 3) decision talk: informed preferences are obtained and informed choices are made. The three-talk model is more concise to help clinicians better understand the core of SDM and implement these processes.\u003c/p\u003e\n\u003cp\u003eSDM is a disruptive idea and cornerstone of patient-centered care [8]. Compared with informed consent, it pays more attention to the needs, expectations and moral values orientation of patients and is representative of the type of clinical interactive decision-making. Friesen-Storms et al. (2015) have agreed that SDM is the best process whereby health care providers and their patients make information exchange and treatment decisions jointly [8]. Nakayama et al. (2020) find that more prostate cancer patients were willing to actively participate in SDM, with only a minority preferring paternalistic decision-making [9]. Similarly, most breast cancer patients report wanting to be involved in SDM because they have not acquired adequate knowledge concerning risks factors for breast cancer treatment and care [10]. SDM primarily focuses on lung cancer screening when it is applied to lung cancer field [11-12]. Lung cancer screening is very important for high-risk groups (smoking, patients with chronic lung disease), and it is convenient for early treatment of patients [13]. Similarly, SDM in the field of lung cancer treatment and care is also involved. There is evidence that some lung cancer patients prefer treatment and care options that improve quality of life the pros and cons of different approaches are not explain in detail when they make decisions [14].\u003c/p\u003e\n\u003cp\u003ePatient decision aids are tools that help them understand options, consider possible hazards and benefits, and encourage patients to make the best choices for specific problems prudently and wisely [15]. The International Patient Decision Aid Standards (IPDAS) [16] and The Ottawa Decision Support Framework（ODSF) [17] are two criteria for evaluating the development process and quality of patient decision assistance tools. IPDAS has developed a checklist to help researchers develop patient decision aids (http://ipdas.ohri.ca/using.html). ODSF can guide the development of patient decision aids from three aspects: decisional needs, decision support and decisional outcome (https://decisionaid.ohri.ca/odsf.html).\u003c/p\u003e\n\u003cp\u003eWhile many clinicians believe they implement SDM, they actually do not [10]. Lack of time, skills, and resources are all factors that affect clinicians\u0026apos; implementation of SDM [18]. These factors influence the level and attitude of lung cancer patients to participate in SDM. Some studies have also explored the subjective factors that influence cancer patients\u0026apos; participation in SDM, such as education level [19]. However, there is a gap in research exploring the factors that influence Chinese lung cancer patients\u0026apos; participation in SDM.\u003c/p\u003e\n\u003cp\u003eTo make a thorough inquiry of the actual participation and perceived importance of lung cancer patients\u0026rsquo; involvement in SDM in terms of treatment and care, we have conducted this cross-sectional survey. The purposes of the current study are to: (1) assess the current status of lung cancer patients\u0026rsquo; attitudes and actual participation in SDM on treatment and care; (2) explore whether there is a statistical difference between the actual participation and perceived importance of lung cancer patients in SDM on treatment and care; and (3) predict factors affecting lung cancer patients\u0026rsquo; participation in SDM on treatment and care.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eDesign, p\u003c/strong\u003e\u003cstrong\u003earticipants\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and recruitment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study adopted a cross-sectional study design. We collected lung cancer patients in the thoracic surgery and oncology department of a comprehensive medical center in Qingdao, China from October 2018 to December 2019. Participants were eligible for inclusion if they: (1) were 18 years older; (2) met the diagnostic criteria for lung cancer and were aware of the condition [20]; and (3) were informed consent and voluntary to participate in this research. Exclusion criteria included: patients suffered: (1) severe damage to other organs (such as heart, brain, liver, kidney, etc.) or other severe malignant tumors; (2) cognitive impairment or mental illness; and (3) disputes between themselves or their family and the medical institutions.\u003c/p\u003e\n\u003cp\u003eThis study used the cross-sectional study calculation formula N = 4(\u0026mu;\u0026alpha;S/\u0026delta;)\u003csup\u003e2\u003c/sup\u003e, where \u0026alpha; was 0.05, \u0026delta; = 0.5S, and the sample size least was 62 cases. We assumed a 20% loss of follow-up rate, about 75 patients were required. To avoid the bias of results caused by a small sample size. A total of 300 patients with lung cancer were enrolled, eventually. Among them, seven patients gave up answering, and three patients stopped answering because of unstable condition. Finally, a total of 290 lung cancer patients participated in this research (response rate = 96.7%).\u003c/p\u003e\n\u003cp\u003eThe data were collected by the researchers on-spot at the bedside of the patient. Before collecting the data, the researchers explained the purpose and significance of the study in order to gain the trust of the patients. Data about the study participants was collected by a paper questionnaire. The researchers were presented to explain the queries to the patients without using eliciting language. If patients were encountered to be agitated or unstable during the study, responses were terminated and reassurance was provided. After the subjects finished their answers, the researchers retrieved the questionnaire and checked for any omissions. If any, they were made up on the spot.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSociodemographic and clinical variables\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe module on patient characteristics included gender, age, marital status, comorbidities, medical insurance, education level, number of children, income, personality, course of disease and pathological TNM stage. Based on Jung\u0026rsquo;s theory of psychological types, we divided personality into introverted and extroverted types [21]. Patients who claimed themselves as quiet, eccentric, and preferring solitude to contact with others were considered introverted. Patients who self-reported being enthusiastic, lively, sociable and adaptable to their environment were considered extroverted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eQuestionnaire of Cancer patients\u0026rsquo; decision-making regarding treatment and care\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLung cancer patient\u0026rsquo;s SDM on treatment and care was assessed using the questionnaire compiled by Sainio and Lauri (2003) [22]. The questionnaire consists of four dimensions (actual participation of SDM on treatment and care, perceived importance of SDM on treatment and care) that are rated on a Likert scale from 1 to 3. Finally, we calculated the average value of each part of the scale to evaluate the actual participation degree and perceived importance of people with lung cancer in SDM (\u0026le; 1.5 means high degree of actual participation and perceived importance, \u0026gt; 1.5 means low degree of actual participation and perceived importance).\u003c/p\u003e\n\u003cp\u003eThe Chinese version of the questionnaire has been revised and developed by Ma (2004), in which the first item \u0026quot;Amount of intravenous fluids\u0026quot; and the seventh item \u0026quot;Investigation scheduling\u0026quot; were deleted [23] After measuring the reliability and validity of the Chinese version of the scale, it exhibited an acceptable content validity index (CVI = 0.89) and internal consistency (Cronbach\u0026apos;s \u0026alpha; 0.851 in the perceived importance subscale, Cronbach\u0026apos;s \u0026alpha; 0.838 in the actual participation subscale).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe survey data were analyzed using the statistical package IBM SPSS v25.0 (IBM. Corp, New York). Descriptive analyses were applied to analyze socio-demographic variables and disease-related data. We used the Wilcoxon Matched-pairs Signed-rank test to analyze the difference between actual participation and perceived importance. Binary logistic regression analysis with a stepwise back-wards was used to predict the factors that affected actual participation and perceived importance of SDM on treatment and care. A variance inflation factor (VIF) was used to test for multicollinearity, and studies with a VIF of less than 10 were generally considered less likely to have multicollinearity. Because the scales were reversely scored. Thus, in the dummy variable setting of the binary logistic regression model, actual participation in SDM on treatment and care as the dependent variable was 0 for high and 1 for low. Similarly, for perceived importance, importance was 0 and insignificance was 1. The Hosmer-Lemeshow test was used to assess the goodness-of-fit of the model. Statistical significance was set at P \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe strictly followed the Helsinki Declaration of the World Medical Congress to conduct this research. The study was approved by the ethics committee of the university to which the investigators belonged. Written informed consent was obtained from all patients and their legal representatives.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSample characteristics and situation analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf 290 lung cancer patients completed the study, ageing from 29 to 70 years (56.37\u0026plusmn;9.05), and almost half of whom were female (47.9%, n = 139). Nearly 72.1% of the 290 patients had a junior high school education or higher, the vast majority had an income above 3000 RMB (96.9%, n = 281), most were diagnosed with stage Ⅱ or Ⅲ (70.7%, n = 205), and more than one-third of patients had a disease course of 3 \u0026ndash; 6 months. Specific information is presented in Table 1.\u003c/p\u003e\n\u003cp\u003eOnly 11% of the 290 participants\u0026apos; actual participation in care SDM was higher, as well as 18.3% of the patients felt that care SDM was important. However, 26.9% of patients actually engaged in treatment SDM higher. SDM for treatment was considered more important by 61% compared to SDM in terms of care (Supplementary file 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of the actual participation and perceived importance of SDM on treatment and care\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo better understand the differences between patients\u0026apos; actual participation and perceived importance in SDM on treatment and care, we performed Wilcoxon Matched-pairs signed-rank test (Supplementary file 2 and 3). The results showed that both the actual participation and perceived importance of SDM on treatment and care\u0026nbsp;of lung cancer patients were statistically significant (\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrediction of factors affecting actual participation and perceived importance of SDM on treatment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe VIF test results of this study was less than 5, so the likelihood of multicollinearity was minimal. The results of binary logistic regression with a stepwise backward showed that actual participation in SDM was higher among lung cancer patients who were male, younger, had disease course more than 6 months, TNM stage IV, higher education and income (Table 2). However, actual participation was lower among lung cancer patients with a disease course of 3-6 months.\u003c/p\u003e\n\u003cp\u003eWe also found higher awareness of the importance of SDM on treatment among patients with other marital status (e.g., divorced, widowed), higher literacy and income (Table 3). However, patients with stage Ⅲ TNM and disease course of 3 \u0026ndash; 6 months had lower perceived importance of SDM on treatment (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrediction of factors affecting actual participation and perceived importance of SDM on care\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe found that patients with lung cancer were more willing to participate in care decisions when they possessed higher education, higher income levels, more children, an outgoing personality, and a disease course of more than 6 months (Table 4).\u003c/p\u003e\n\u003cp\u003eWe also found that patients with lung cancer perceived higher importance when they possessed higher education, income level, were male, other marital status (e.g., divorced, widowed), had a disease course of more than 6 months, and had TNM stage Ⅳ (Table 5). Among disease-related factors, lung cancer patients with a course of 3 \u0026ndash; 6 months considered it unimportant to participate in SDM on care (Table 5).\u003c/p\u003e"},{"header":"Discussions","content":"\u003cp\u003eSDM is important because it ensures that patients\u0026rsquo; values, preferences, beliefs and their contextual factors guide all clinical decisions in an evidence-based context [24]. The results of this study indicated that actual participation and perceived importance of SDM on treatment and care among lung cancer patients was low. Furthermore, the actual participation of lung cancer patients in SDM on treatment and care was lower than their perceived importance. This suggested that although participants perceived that participation in SDM on treatment and care was important, their actual participation was not high.\u003c/p\u003e\n\u003cp\u003eThe results of this study suggested that patients with higher education actually participated to a greater extent and perceived importance of SDM on treatment and care [19]. Patients with low education level had difficulty in understanding the complexities of medical science or even communicating with healthcare professionals, making it difficult for them to make the best choices. Patients with a high level of education were more likely to receive disease-related information. Studies demonstrated that lung cancer patients would be very interested in the treatment and care process if they had access to sufficient information (19,25-26).\u003c/p\u003e\n\u003cp\u003eAlthough Chinese existing health insurance policy has wide coverage, not all anticancer drugs mainly used by cancer patients are included in the healthcare system. It is still a heavy burden especially for low-income cancer patients in rural China [27]. We speculated that this group of patients develop thoughts of abandoning treatment due to the high cost of treatment and care, and had difficulty actively participating in SDM. However, it does not preclude the possibility that some of these patients may be more active in discussing cost-efficient treatment options with clinicians and have a higher level of SDM. Therefore, the impact of income level on lung cancer patients\u0026apos; participation in SDM needs to be further explored.\u003c/p\u003e\n\u003cp\u003eDivorced and widowed patients considered it was important to participate in SDM on treatment and care. Some studies had shown that family involvement in SDM for cancer patients was associated with a better understanding of cancer-related information [28]. In the absence of family support, divorced and widowed patients would engage in the three-talk model on their own and make informed decisions with clinicians. In this context, medical staff should provide adequate decision support to patients, and information about patient\u0026apos;s concerns (treatment modalities, side effects, prognosis).\u003c/p\u003e\n\u003cp\u003eMen and younger patients were actually more participate in SDM on treatment. Male patients generally took on more responsibility in the family and could analyze treatment more rationally. Younger patients are more receptive to the disease and more knowledgeable about relevant information than the elderly. As a result, male and younger patients more actively participated in SDM on treatment.\u003c/p\u003e\n\u003cp\u003eWe also found that patients who were extroverted and had more children actually had higher levels of SDM involvement in care. We speculated that extroverted patients were willing to participate in care decision and chose more appropriate care for themselves. Patients with more children had stronger family support systems. For complex methods of care, the children of this group of patients would help them understand, which would help increase the patient\u0026apos;s motivation to participate in care decisions.\u003c/p\u003e\n\u003cp\u003ePatients diagnosed with cancer less than 3 months may be in a fear psychological stage [29]. They fear and refuse to acknowledge that they have been confirmed to have lung cancer. Lung cancer patients diagnosed within 3\u0026ndash;6 months underwent chemotherapy and experienced intolerable adverse effects that make them resist treatment and care options. As a result, patients at this stage have a low level of actual participation of SDM on their treatment and perceive SDM as unimportant in treatment and care. Lung cancer patients with a course of more than 6 months may be in the adaptation period, accept their own diagnostic facts, actively participate in the treatment and care of SDM and discuss more useful programs.\u003c/p\u003e\n\u003cp\u003eTNM stage is an important determinant of survival in lung cancer patients [30]. For patients with stage III lung cancer, the five-year survival rate is much lower than for stages I and II, and most patients receive chemotherapy and radiotherapy with enduring adverse reactions [30]. Therefore, we speculated that patients with stage III lung cancer were not better off after receiving treatment and did not consider decision on treatment approach to be important. We found that stage IV patients considered SDM on care to be more important. The five-year survival rate for patients with stage IV lung cancer pathology was estimated to be 13%, compared to 2% for clinical stage IV patients [30]. Patients with stage IV lung cancer present with symptoms such as cough, dyspnea, hemoptysis and chest pain. For these reasons, we speculate that patients prefer care methods that promote a better quality of life rather than pursuing a longer survival rate. Therefore, they focus more on the care approach.\u003c/p\u003e\n\u003cp\u003eHealthcare professionals can use patient decision aids to help patients understand the treatment process and encourage them to express their wishes. The patient decision aids website, established by the Ottawa Hospital Research Association, is a platform that provides decision support [31]. We can directly download and use the patient decision aids list for lung cancer screening patients on this platform. A patient decision aid for treatment selection for lung cancer patients had been developed in the Netherlands (http://www.keuzehulp-longkanker.nl/). Patients can comprehensively consider the pros and cons of surgery and targeted radiotherapy based on the information on this website and decide together with their clinician.\u003c/p\u003e\n\u003cp\u003eDecision coaching is another form of patient decision aids, which is developed in accordance with IPADS [32]. Rahn et al. (2018) conducted a preliminary randomized controlled study in which a decision aid implemented by a nurse-led decision coach facilitated patient participation in SDM [33]. Also, there was evidence that decision coaching could avoid decision-making entanglement and improve the quality of communication with patients and facilitate their learning [34].\u003c/p\u003e\n\u003cp\u003eThe MAGIC program, proposed by the British Health Foundation, has developed option grids to help patients engage with SDM [35]. Currently, treatment option grids are used in a wide range of diseases, such as breast cancer, knee joint arthritis, prostate cancer [36-38]. Study confirmed that the application of option grids in lung cancer screening could lead to better SDM experience and advanced knowledge of lung cancer screening [39]. With advances in medicine and the popularity of SDM, it is imperative to encourage lung cancer patients to participate in SDM. Healthcare professionals can use patient decision aids to help patients choose decisions that match their values, preferences, and personal goals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical implications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the Chinese cultural context and healthcare system, clinicians lack sufficient time to explain the pros and cons of different treatments to patients. As close partners of clinicians, nurses have more contact with patients than clinicians and are more likely to provide health education and understand patients\u0026rsquo; wishes regarding treatment and care options. Transitional care is critical for chronic diseases such as cancer, and community health workers are the primary providers of transition care services in the community. Within certain limits of authority, we can train oncology nurse specialists in SDM to join medical staff-patient-family and hospital-home-communities to provide SDM for patients. We should use SDM to maximize patient autonomy and use patient decision aids to help them make decisions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHowever, this study has the following limitations. First, this study was conducted in only one comprehensive medical center with limited sample selection. Second, shared decision-making involved not only patients but also their family members. In this study, we didn\u0026rsquo;t collect the opinions from family members. Third, it is best to analyze the study results through questionnaires and interviews. Therefore, we will conduct interviews with lung cancer patients to obtain more detailed information and include patients\u0026apos; family members in future studies. The results of this study could inform the development of the intervention and will include additional factors as well as future family involvement.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eActual participation and perceived importance in SDM on treatment and care among lung cancer patients were low and there was variation between them. Lung cancer patients\u0026apos; actual participation in SDM on treatment and care was affected by background factors (education level, household income) and health care provider factors (lack of time, attitude towards SDM). Therefore, SDM orientation sessions should be designed accordingly to the social background of lung cancer patients to help them actively participate. Due to the limited time available to clinicians, nurses are better suited to act as a liaison between patients and physicians to provide SDM support. Thus, SDM knowledge training for oncology nurses is beneficial in facilitating SDM.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was funded by Project of Research Planning Foundation on Humanities and Social Sciences of the Ministry of Education (NO. 20YJAZH144).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest/Competing interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo conflict of financial or other interest has been declared by the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declared that all data and materials as well as software application or custom code support their published claims and comply with field standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Study design and material preparation were performed by Ying Wang, Bo Hu, and Jinna Zhang. Data collection and analysis were performed by Ying Wang, Jinna Zhang, Bo Hu, Jizhe Wang, Laixiang Zhang, Xiaohua Li, and Xiuli Zhu. The first draft of the manuscript was written by Ying Wang, Jinna Zhang, and Bo Hu and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted according to the Declaration of Helsinki and were supported by the ethical committee of the university which the researchers affiliated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBefore distributing the questionnaires, all the patients signed the informed consents. That indicated that they understood the nature and purpose of the study and they knew that their personal information would not be divulged.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. Because this is not a case study, but cross-sectional study. We collect data anonymously. We present the results by analysing a large number of quantitative data and there will be no information leakage of any participants.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWorld Health Organization. (2021). \u003cem\u003eCancer.\u003c/em\u003e\u0026nbsp; Retrieved 05-01, 2021, from https://www.who.int/news-room/fact-sheets/detail/cancer.\u003c/li\u003e\n \u003cli\u003eDuma, N., Santana-Davila, R., \u0026amp; Molina, J. R. (2019). Non-Small Cell Lung Cancer: Epidemiology, Screening, Diagnosis, and Treatment. \u003cem\u003eMayo Clin Proc, 94\u003c/em\u003e(8), 1623-1640. doi: 10.1016/j.mayocp.2019.01.013.\u003c/li\u003e\n \u003cli\u003eSchmidt, K., Damm, K., Prenzler, A., Golpon, H., \u0026amp; Welte, T. (2016). Preferences of lung cancer patients for treatment and decision-making: a systematic literature review. \u003cem\u003eEuropean journal of cancer care, 25\u003c/em\u003e(4), 580\u0026ndash;591. doi: 10.1111/ecc.12425.\u003c/li\u003e\n \u003cli\u003eKunneman, M., Montori, V. M., Castaneda-Guarderas, A., \u0026amp; Hess, E. P. (2016). What Is Shared Decision Making? (and What It Is Not). \u003cem\u003eAcad Emerg Med, 23\u003c/em\u003e(12), 1320\u0026ndash;1324. doi:10.1111/acem.13065.\u003c/li\u003e\n \u003cli\u003eMontori, V. M., Kunneman, M., \u0026amp; Brito, J. P. (2017). Shared Decision Making and Improving Health Care: The Answer Is Not In.\u003cem\u003e\u0026nbsp;JAMA, 318\u003c/em\u003e(7), 617\u0026ndash;618. doi: 0.1001/jama.2017.10168.\u003c/li\u003e\n \u003cli\u003eFulford K., \u0026amp; Handa A. (2021). New resources for understanding patients\u0026apos; values in the context of shared clinical decision-making. \u003cem\u003eWorld Psychiatry, 20\u003c/em\u003e(3), 446-447. doi:10.1002/wps.20902.\u003c/li\u003e\n \u003cli\u003eElwyn, G., Durand, M. A., Song, J., Aarts, J., Barr, P. J., Berger, Z., . . . Van der Weijden, T. (2017). A three-talk model for shared decision making: multistage consultation process. \u003cem\u003eBmj, 359\u003c/em\u003e, j4891. doi: 10.1136/bmj. j4891.\u003c/li\u003e\n \u003cli\u003eFriesen-Storms, J. H., Bours, G. J., van der Weijden, T., \u0026amp; Beurskens, A. J. (2015). Shared decision making in chronic care in the context of evidence based practice in nursing. \u003cem\u003eInt J Nurs Stud, 52\u003c/em\u003e(1), 393-402. doi: 10.1016/j.ijnurstu.2014.06.012.\u003c/li\u003e\n \u003cli\u003eNakayama, K., Osaka, W., Matsubara, N., Takeuchi, T., Toyoda, M., Ohtake, N., \u0026amp; Uemura, H. (2020). Shared decision making, physicians\u0026apos; explanations, and treatment satisfaction: a cross-sectional survey of prostate cancer patients. \u003cem\u003eBMC Med Inform Decis Mak, 20\u003c/em\u003e(1), 334. doi: 10.1186/s12911-020-01355-z.\u003c/li\u003e\n \u003cli\u003eBerger-H\u0026ouml;ger, B., Liethmann, K., M\u0026uuml;hlhauser, I., Haastert, B., \u0026amp; Steckelberg, A. (2019). Nurse-led coaching of shared decision-making for women with ductal carcinoma in situ in breast care centers: A cluster randomized controlled trial. \u003cem\u003eInt J Nurs Stud, 93\u003c/em\u003e, 141-152. doi: 10.1016/j.ijnurstu.2019.01.013.\u003c/li\u003e\n \u003cli\u003eBrenner, A. T., Malo, T. L., Margolis, M., Elston Lafata, J., James, S., Vu, M. B., \u0026amp; Reuland, D. S. (2018). Evaluating Shared Decision Making for Lung Cancer Screening. \u003cem\u003eJAMA Intern Med, 178\u003c/em\u003e(10), 1311-1316. doi: 10.1001/jamainternmed.2018.3054.\u003c/li\u003e\n \u003cli\u003eLowenstein, M., Vijayaraghavan, M., Burke, N. J., Karliner, L., Wang, S., Peters, M., . . . Kaplan, C. P. (2019). Real-world lung cancer screening decision-making: Barriers and facilitators. \u003cem\u003eLung Cancer, 133\u003c/em\u003e, 32-37. doi: 10.1016/j.lungcan.2019.04.026.\u003c/li\u003e\n \u003cli\u003eHall, H., Tocock, A., Burdett, S., Fisher, D., Ricketts, W. M., Robson, J., et al. (2021). Association between time-to-treatment and outcomes in non-small cell lung cancer: a systematic review. \u003cem\u003eThorax\u003c/em\u003e, thoraxjnl-2021-216865. doi: 10.1136/thoraxjnl-2021-216865.\u003c/li\u003e\n \u003cli\u003eSullivan, D. R., Eden, K. B., Dieckmann, N. F., Golden, S. E., Vranas, K. C., Nugent, S. M., \u0026amp; Slatore, C. G. (2019). Understanding patients\u0026apos; values and preferences regarding early stage lung cancer treatment decision making. \u003cem\u003eLung Cancer, 131\u003c/em\u003e, 47-57. doi: 10.1016/j.lungcan.2019.03.009.\u003c/li\u003e\n \u003cli\u003eO\u0026apos;Connor, A. M., Stacey, D., Entwistle, V., Llewellyn-Thomas, H., Rovner, D., Holmes-Rovner, M., Tait, V., Tetroe, J., Fiset, V., Barry, M., \u0026amp; Jones, J. (2003). Decision aids for people facing health treatment or screening decisions\u003cem\u003e.\u0026nbsp;The Cochrane database of systematic reviews,\u003c/em\u003e (2), CD001431.\u0026nbsp;\u003ca href=\"https://doi:\"\u003edoi:\u003c/a\u003e 10.1002/14651858.CD001431.\u003c/li\u003e\n \u003cli\u003eElwyn, G., O\u0026apos;Connor, A., Stacey, D., Volk, R., Edwards, A., Coulter, A., et al., \u0026hellip; International Patient Decision Aids Standards (IPDAS) Collaboration (2006). Developing a quality criteria framework for patient decision aids: online international Delphi consensus process.\u0026nbsp;BMJ (Clinical research ed.),\u0026nbsp;333(7565), 417. doi: 10.1136/bmj.38926.629329.AE.\u003c/li\u003e\n \u003cli\u003eHoefel, L., \u0026amp; Lewis, K. B. (2020). 20th Anniversary Update of the Ottawa Decision Support Framework: Part 2 Subanalysis of a Systematic Review of Patient Decision Aids.\u003cem\u003e\u0026nbsp;Med Decis Making, 40\u003c/em\u003e(4), 522-539. doi: 10.1177/0272989x20924645.\u003c/li\u003e\n \u003cli\u003eCoulter A. (2017). Shared decision making: everyone wants it, so why isn\u0026apos;t it happening?\u003cem\u003e\u0026nbsp;World psychiatry, 16\u003c/em\u003e(2), 117\u0026ndash;118. doi: 10.1002/wps.20407.\u003c/li\u003e\n \u003cli\u003eLoh, K., Tsang, M., LeBlanc, T., Back, A., Duberstein, P., Mohile, S., . . . Lee, S. (2020). Decisional involvement and information preferences of patients with hematologic malignancies. \u003cem\u003eBlood Advances, 4\u003c/em\u003e(21), 5492-5500. doi: 10.1182/bloodadvances.2020003044.\u003c/li\u003e\n \u003cli\u003eDetterbeck, F. C., Boffa, D. J., Kim, A. W., \u0026amp; Tanoue, L. T. (2017). The Eighth Edition Lung Cancer Stage Classification. \u003cem\u003eChest, 151\u003c/em\u003e(1), 193-203. doi: 10.1016/j.chest.2016.10.010.\u003c/li\u003e\n \u003cli\u003eJohn Beebe, C. J. (2016). \u003cem\u003ePsychological Types\u003c/em\u003e. London; New York: Routledge.\u003c/li\u003e\n \u003cli\u003eSainio, C., \u0026amp; Lauri, S. (2003). Cancer patients\u0026apos; decision-making regarding treatment and nursing care. \u003cem\u003eJ Adv Nurs, 41\u003c/em\u003e(3), 250-260. doi: 10.1046/j.1365-2648.2003.02525. x.\u003c/li\u003e\n \u003cli\u003eMa, L. (2004). Research on the status quo and influencing factors of cancer patients\u0026apos; participation in treatment and nursing decisions. (Master), Peking Union Medical College, Beijing.\u003c/li\u003e\n \u003cli\u003eRabi, D. M., Kunneman, M., \u0026amp; Montori, V. M. (2020). When Guidelines Recommend Shared Decision-making. \u003cem\u003eJAMA, 323\u003c/em\u003e(14), 1345\u0026ndash;1346. doi: 10.1001/jama.2020.1525.\u003c/li\u003e\n \u003cli\u003eHull, O., Niranjan, S. J., Wallace, A. S., Williams, B. R., Turkman, Y. E., Ingram, S. A., . . . Rocque, G. B. (2020). Should we be talking about guidelines with patients? A qualitative analysis in metastatic breast cancer. \u003cem\u003eBreast Cancer Res Treat, 184\u003c/em\u003e(1), 115-121. doi: 10.1007/s10549-020-05832-x.\u003c/li\u003e\n \u003cli\u003ePassalacqua, R., Caminiti, C., Salvagni, S., Barni, S., Beretta, G. D., Carlini, P., . . . Campione, F. (2004). Effects of media information on cancer patients\u0026apos; opinions, feelings, decision-making process and physician-patient communication. \u003cem\u003eCancer, 100\u003c/em\u003e(5), 1077-1084. doi: 10.1002/cncr.20050.\u003c/li\u003e\n \u003cli\u003eLeng, A., Jing, J., Nicholas, S., \u0026amp; Wang, J. (2019). Geographical disparities in treatment and health care costs for end-of-life cancer patients in China: a retrospective study.\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eBMC Cancer, 19\u003c/em\u003e(1), 39. doi: 10.1186/s12885-018-5237-1.\u003c/li\u003e\n \u003cli\u003eHobbs GS, Landrum MB, Arora NK, et al. (2015). The role of families in decisions regarding cancer treatments. \u003cem\u003eCancer, 121\u003c/em\u003e(7):1079-1087. doi: 10.1002/cncr.29064.\u003c/li\u003e\n \u003cli\u003eChen, Y. C., Huang, H. M., Kao, C. C., Sun, C. K., Chiang, C. Y., \u0026amp; Sun, F. K. (2016). The Psychological Process of Breast Cancer Patients Receiving Initial Chemotherapy: Rising From the Ashes. \u003cem\u003eCancer Nurs, 39\u003c/em\u003e(6), E36-e44. doi: 10.1097/ncc.0000000000000331.\u003c/li\u003e\n \u003cli\u003eWoodard, G. A., Jones, K. D., \u0026amp; Jablons, D. M. (2016). Lung Cancer Staging and Prognosis. \u003cem\u003eCancer Treat Res, 170\u003c/em\u003e, 47-75. doi: 10.1007/978-3-319-40389-2_3.\u003c/li\u003e\n \u003cli\u003ePatient Decision Aids. (2020). \u003cem\u003ePatient Decision Aids.\u003c/em\u003e Retrieved 02-20, 2021, from https://decisionaid.ohri.ca/index.html.\u003c/li\u003e\n \u003cli\u003eRahn, A. C., Jull, J., Boland, L., Finderup, J., Loiselle, M. C., Smith, M., K\u0026ouml;pke, S., \u0026amp; Stacey, D. (2021). Guidance and/or Decision Coaching with Patient Decision Aids: Scoping Reviews to Inform the International Patient Decision Aid Standards (IPDAS). \u003cem\u003eMedical decision making, 41\u003c/em\u003e(7), 938\u0026ndash;953. doi: 10.1177/0272989X21997330.\u003c/li\u003e\n \u003cli\u003eRahn, A. C., K\u0026ouml;pke, S., Backhus, I., Kasper, J., Anger, K., Untiedt, B., . . . Heesen, C. (2018). Nurse-led immunotreatment DEcision Coaching In people with Multiple Sclerosis (DECIMS) - Feasibility testing, pilot randomised controlled trial and mixed methods process evaluation. \u003cem\u003eInt J Nurs Stud, 78\u003c/em\u003e, 26-36. doi: 10.1016/j.ijnurstu.2017.08.011.\u003c/li\u003e\n \u003cli\u003eStacey, D., \u0026amp; L\u0026eacute;gar\u0026eacute;, F. (2020). 20th Anniversary Ottawa Decision Support Framework: Part 3 Overview of Systematic Reviews and Updated Framework.\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eMed Decis Making, 40\u003c/em\u003e(3), 379-398. doi: 10.1177/0272989x20911870.\u003c/li\u003e\n \u003cli\u003eThe Health Foundation. (2012). \u003cem\u003eA simple tool to facilitate shared decisions.\u003c/em\u003e Retrieved June 15, 2021, from\u0026nbsp;\u003ca href=\"http://www.health.org.uk/newsletter-feature/a-simple-tool-to-facilitate\"\u003ehttp://www.health.org.uk/newsletter-feature/a-simple-tool-to-facilitate\u003c/a\u003e -shared-decisions.\u003c/li\u003e\n \u003cli\u003eDurand, M. A., Yen, R. W., O\u0026apos;Malley, A. J., Schubbe, D., Politi, M. C., Saunders, C. H., . . . Elwyn, G. (2020). What matters most: Randomized controlled trial of breast cancer surgery conversation aids across socioeconomic strata. \u003cem\u003eCancer. 127\u003c/em\u003e(3), 422\u0026ndash;436. doi: 10.1002/cncr.33248.\u003c/li\u003e\n \u003cli\u003eKinsey, K., Firth, J., Elwyn, G., Edwards, A., Brain, K., Marrin, K., . . . Wood, F. (2017). Patients\u0026apos; views on the use of an Option Grid for knee osteoarthritis in physiotherapy clinical encounters: An interview study.\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eHealth Expect, 20\u003c/em\u003e(6), 1302-1310. doi: 10.1111/hex.12570.\u003c/li\u003e\n \u003cli\u003eScalia, P., Durand, M. A., Faber, M., Kremer, J. A., Song, J., \u0026amp; Elwyn, G. (2019). User-testing an interactive option grid decision aid for prostate cancer screening: lessons to improve usability. \u003cem\u003eBmj Open, 9\u003c/em\u003e(5), e026748. doi: 10.1136/bmjopen-2018-026748.\u003c/li\u003e\n \u003cli\u003eSferra, S. R., Cheng, J. S., Boynton, Z., DiSesa, V., Kaiser, L. R., Ma, G. X., \u0026amp; Erkmen, C. P. (2020). Aiding shared decision making in lung cancer screening: two decision tools. \u003cem\u003eJ Public Health (Oxf),\u003c/em\u003e fdaa063. doi: 10.1093/pubmed/fdaa063.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Descriptive analysis of sociodemographic data and disease-related data (\u003cem\u003eN\u003c/em\u003e=290)\u003c/p\u003e\n\u003ctable border=\"1\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"4\" width=\"86\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"4\" width=\"50\"\u003e\n \u003cp\u003e\u003cem\u003eN\u003c/em\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"8\" width=\"572\"\u003e\n \u003cp\u003e\u003cem\u003eN\u003c/em\u003e / %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"281\"\u003e\n \u003cp\u003eSDM on treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" width=\"291\"\u003e\n \u003cp\u003eSDM on care\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" width=\"102\"\u003e\n \u003cp\u003eActual participation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"180\"\u003e\n \u003cp\u003ePerceived importance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"111\"\u003e\n \u003cp\u003eActual participation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"180\"\u003e\n \u003cp\u003ePerceived importance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003eImportance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003eUnimportance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003eImportance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003eUnimportance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" width=\"708\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e151 (52.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e49 (16.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e102 (35.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e96 (33.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e55 (19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e23(7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e128 (44.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e36 (12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e115 (39.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e139 (47.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e29 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e110 (37.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e81 (27.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e58 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e9 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e130 (44.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e17 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e122 (42.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" width=\"708\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003e\u0026le; 40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e21 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e9 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e12 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e16 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e5 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e19 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e6 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e15 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003e41 \u0026ndash; 50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e40 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e17 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e23 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e26 (9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e14 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e7 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e33 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e8 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e32 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003e51 \u0026ndash; 60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e120 (41.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e36 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e84 (29.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e78 (26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e42 (14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e15 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e105 (36.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e24 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e96 (33.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003e\u0026gt; 60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e109 (37.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e16 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e93 (32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e57 (19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e52 (17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e8 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e101 (34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e15 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e94 (32.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" width=\"708\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e267 (92.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e71 (24.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e196 (67.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e160 (55.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e107 (36.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e27 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e240 (82.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e46 (15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e221 (76.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e23 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e7 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e16 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e17 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e6 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e5 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e18 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e7 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e16 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" width=\"708\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e215 (74.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e60 (20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e155 (53.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e130 (44.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e85 (29.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e21 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e194 (66.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e34 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e181 (62.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e75 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e18 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e57 (19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e47 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e28 (9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e11 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e64 (22.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e19 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e56 (19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" width=\"708\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedical insurance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eEmployee health insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e141 (48.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e40 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e101 (34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e92 (31.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e49 (16.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e19 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e122 (42.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e31 (10.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e110 (37.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eResident health insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e125 (43.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e31 (10.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e94 (32.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e72 (24.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e53 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e11 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e114 (39.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e20 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e105 (36.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eOwn expense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e24 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e7 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e17 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e13 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e11 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e22 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e22 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" width=\"708\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eIlliteracy / Primary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e81 (27.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e8 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e73 (25.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e39 (13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e42 (14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e78 (26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e9 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e72 (24.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e111 (38.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e32 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e79 (27.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e66 (22.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e45 (15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e11 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52\"\u003e\n \u003cp\u003e100 (34.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81\"\u003e\n \u003cp\u003e14 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e97 (33.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eHigh school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e49 (16.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e14 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35 (12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e12 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e6 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e43 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eJunior college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e20 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e9 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e7 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eBachelor degree and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e29 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e15 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e7 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e9 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" width=\"708\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of children\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003e\u0026le; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e129 (44.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e38 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e91 (31.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e94 (32.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e35 (12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e12 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e117 (40.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e102 (35.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e129 (44.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e30 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e99 (34.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e65 (22.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e64 (22.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e13 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e116 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e112 (38.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003e\u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e32 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e10 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e14 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e7 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25 (8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" width=\"708\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome (RMB)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003e\u0026lt; 3000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e9 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e7 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003e3000 \u0026ndash; 5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e76 (26.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e11 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e65 (22.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31 (10.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e45 (15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e73 (25.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e71 (24.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003e\u0026nbsp;5001 \u0026ndash; 10000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e175 (60.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e54 (18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e121 (41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e118 (40.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e57 (19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e22 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e153 (52.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e141 (48.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003e\u0026gt; 10000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e30 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e13 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26 (9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e4 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e7 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" width=\"708\"\u003e\n \u003cp\u003e\u003cstrong\u003ePersonality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eIntrovert\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e200 (69.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e52 (17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e148 (51.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e127 (43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e73 (25.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e14 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e186 (64.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e168 (57.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eExtrovert\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e90 (31.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e26 (9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e64 (22.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50 (17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e40 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e18 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e72 (24.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e69 (23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" width=\"708\"\u003e\n \u003cp\u003e\u003cstrong\u003eCourse of disease\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003e\u0026lt; 3 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e120 (41.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e30 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90 (31.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e87 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e33 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e6 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e114 (39.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e100 (34.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003e3 \u0026ndash; 6 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e108 (37.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e6 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e102 (35.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e68 (23.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e4 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e104 (35.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e101 (34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003e\u0026gt; 6 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e62 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e42 (14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50 (17.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e12 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e22 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26 (9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e36 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" width=\"708\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathological typing\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eⅠ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e48 (16.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e11 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e14 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e5 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e43 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39 (13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eⅡ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e122 (42.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e32 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90 (32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e80 (27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e42 (14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e9 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e113 (39.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e105 (36.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e83 (28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e14 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e69 (23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e36 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e47 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e4 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e79 (27.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"82\"\u003e\n \u003cp\u003eⅣ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e37 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52\"\u003e\n \u003cp\u003e21 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"98\"\u003e\n \u003cp\u003e10 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59\"\u003e\n \u003cp\u003e14 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: SDM: shared decision-making\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 \u003c/strong\u003eMulti-factor prediction of actual participation in SDM on treatment.\u003c/p\u003e\n\u003ctable border=\"1\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"568\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e1.994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e1.108 \u0026ndash; 3.587\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e0.021\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e1.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e1.006 \u0026ndash; 1.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e0.019\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e0.184 \u0026ndash; 1.616\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eMedical insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eEmployee health insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e0.279\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eResident health insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e0.638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e0.335 \u0026ndash; 1.215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eOwn expense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e0.497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e0.161 \u0026ndash; 1.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e0.656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e0.508 \u0026ndash; 0.846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eIncome (￥)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e0.281 \u0026ndash; 0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e0.002\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"568\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease-related factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eCourse of disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003e\u0026lt; 3 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003e3 \u0026ndash; 6 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e5.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e2.252 \u0026ndash; 15.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003e\u0026gt; 6 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e0.077 \u0026ndash; 0.337\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003ePathological typing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eⅠ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e0.008\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eⅡ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e0.673\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e0.281 \u0026ndash; 1.609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e0.373\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e1.521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e0.543 \u0026ndash; 4.259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e0.424\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"237\"\u003e\n \u003cp\u003eⅣ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"84\"\u003e\n \u003cp\u003e0.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"139\"\u003e\n \u003cp\u003e0.079 \u0026ndash; 0.753\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"108\"\u003e\n \u003cp\u003e0.014\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: OR: odds ratio; CI: Confidence intervals.\u003csup\u003e\u0026nbsp;**\u003c/sup\u003e Indicates statistical significance at p\u0026le;0.01. \u003csup\u003e*\u003c/sup\u003e Indicates statistical significance at \u003cem\u003eP\u003c/em\u003e \u0026le; 0.05. Demographic characteristics: Omnbius Tests of model Coefficients: \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026le; 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: \u0026chi;\u003csup\u003e2\u003c/sup\u003e = 8.764，\u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.363; Disease-related factors: Omnbius Tests of model Coefficients: \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026le; 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: \u0026chi;\u003csup\u003e2\u003c/sup\u003e = 6.879, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.332. SDM: Shared decision-making.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Multi-factor prediction of perceived importance of SDM on treatment.\u003c/p\u003e\n\u003ctable border=\"1\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"198\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"119\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"153\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"99\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"568\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"198\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"119\"\u003e\n \u003cp\u003e0.253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"153\"\u003e\n \u003cp\u003e0.085 \u0026ndash; 0.754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"99\"\u003e\n \u003cp\u003e0.014\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"198\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"119\"\u003e\n \u003cp\u003e0.763\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"153\"\u003e\n \u003cp\u003e0.606 \u0026ndash; 0.961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"99\"\u003e\n \u003cp\u003e0.021\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"198\"\u003e\n \u003cp\u003eNumber of children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"119\"\u003e\n \u003cp\u003e1.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"153\"\u003e\n \u003cp\u003e0.999 \u0026ndash; 2.249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"99\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"198\"\u003e\n \u003cp\u003eIncome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"119\"\u003e\n \u003cp\u003e0.356\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"153\"\u003e\n \u003cp\u003e0.229 \u0026ndash; 0.553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"99\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"568\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease-related factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"568\"\u003e\n \u003cp\u003eCourse of disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"198\"\u003e\n \u003cp\u003e\u0026lt; 3 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"119\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"153\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"99\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"198\"\u003e\n \u003cp\u003e3 \u0026ndash; 6 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"119\"\u003e\n \u003cp\u003e3.944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"153\"\u003e\n \u003cp\u003e2.207 \u0026ndash; 7.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"99\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"198\"\u003e\n \u003cp\u003e\u0026gt; 6 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"119\"\u003e\n \u003cp\u003e0.562\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"153\"\u003e\n \u003cp\u003e0.256 \u0026ndash; 1.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"99\"\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"568\"\u003e\n \u003cp\u003ePathological typing\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"198\"\u003e\n \u003cp\u003eⅠ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"119\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"153\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"99\"\u003e\n \u003cp\u003e0.020\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"198\"\u003e\n \u003cp\u003eⅡ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"119\"\u003e\n \u003cp\u003e1.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"153\"\u003e\n \u003cp\u003e0.469 \u0026ndash; 2.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"99\"\u003e\n \u003cp\u003e0.969\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"198\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"119\"\u003e\n \u003cp\u003e2.463\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"153\"\u003e\n \u003cp\u003e1.080 \u0026ndash; 5.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"99\"\u003e\n \u003cp\u003e0.032\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"198\"\u003e\n \u003cp\u003eⅣ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"119\"\u003e\n \u003cp\u003e0.883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"153\"\u003e\n \u003cp\u003e0.311 \u0026ndash; 2.511\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"99\"\u003e\n \u003cp\u003e0.816\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: OR: odds ratio; CI: Confidence intervals.\u003csup\u003e\u0026nbsp;**\u003c/sup\u003e Indicates statistical significance at \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026le; 0.01.\u003csup\u003e\u0026nbsp;*\u003c/sup\u003e Indicates statistical significance at \u003cem\u003eP\u003c/em\u003e \u0026le; 0.05. Demographic characteristics: Omnbius Tests of model Coefficients: \u003cem\u003eP\u003c/em\u003e \u0026le; 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: \u0026chi;\u003csup\u003e2\u003c/sup\u003e = 2.852, P=0.898; Disease-related factors: Omnbius Tests of model Coefficients: \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026le; 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: \u0026chi;\u003csup\u003e2\u003c/sup\u003e = 2.388, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.935. SDM: Shared decision-making.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4 \u003c/strong\u003eMulti-factor prediction of actual participation in SDM on care.\u003c/p\u003e\n\u003ctable border=\"1\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"212\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"96\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"158\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"568\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"212\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"96\"\u003e\n \u003cp\u003e0.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"158\"\u003e\n \u003cp\u003e0.425 \u0026ndash; 0.778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"212\"\u003e\n \u003cp\u003eNumber of children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"96\"\u003e\n \u003cp\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"158\"\u003e\n \u003cp\u003e0.184 \u0026ndash; 0.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e0.003\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"212\"\u003e\n \u003cp\u003eIncome (￥)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"96\"\u003e\n \u003cp\u003e0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"158\"\u003e\n \u003cp\u003e0.180 \u0026ndash; 0.670\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e0.002\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"212\"\u003e\n \u003cp\u003ePersonality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"96\"\u003e\n \u003cp\u003e0.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"158\"\u003e\n \u003cp\u003e0.106 \u0026ndash; 0.558\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"568\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease-related factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"568\"\u003e\n \u003cp\u003eCourse of disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"212\"\u003e\n \u003cp\u003e\u0026lt; 3 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"96\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"158\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"212\"\u003e\n \u003cp\u003e3 \u0026ndash; 6 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"96\"\u003e\n \u003cp\u003e1.255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"158\"\u003e\n \u003cp\u003e0.330 \u0026ndash; 4.769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e0.739\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"212\"\u003e\n \u003cp\u003e\u0026gt; 6 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"96\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"158\"\u003e\n \u003cp\u003e0.037 \u0026ndash; 0.295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"568\"\u003e\n \u003cp\u003ePathological typing\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"212\"\u003e\n \u003cp\u003eⅠ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"96\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"158\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e0.002\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"212\"\u003e\n \u003cp\u003eⅡ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"96\"\u003e\n \u003cp\u003e1.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"158\"\u003e\n \u003cp\u003e0.454 \u0026ndash; 5.441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e0.476\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"212\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"96\"\u003e\n \u003cp\u003e3.325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"158\"\u003e\n \u003cp\u003e0.754 \u0026ndash; 14.660\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"212\"\u003e\n \u003cp\u003eⅣ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"96\"\u003e\n \u003cp\u003e0.328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"158\"\u003e\n \u003cp\u003e0.090 \u0026ndash; 1.195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e0.328\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: OR: odds ratio; CI: Confidence intervals. \u003csup\u003e**\u003c/sup\u003e Indicates statistical significance at p \u0026le; 0.01. \u003csup\u003e*\u003c/sup\u003e Indicates statistical significance at \u003cem\u003eP\u003c/em\u003e \u0026le; 0.05; Demographic characteristics: Omnbius Tests of model Coefficients: \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026le; 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: \u0026chi;\u003csup\u003e2\u003c/sup\u003e = 13.090, \u003cem\u003eP\u003c/em\u003e = 0.109; Disease-related factors: Omnbius Tests of model Coefficients: \u003cem\u003eP\u003c/em\u003e \u0026le; 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: \u0026chi;\u003csup\u003e2\u003c/sup\u003e = 4.738, \u003cem\u003eP\u003c/em\u003e = 0.692. SDM : Shared decision-making.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5 \u003c/strong\u003eMulti-factor prediction of perceived importance of SDM on care.\u003c/p\u003e\n\u003ctable border=\"1\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"221\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"94\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"121\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"132\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"568\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"221\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"94\"\u003e\n \u003cp\u003e2.302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"121\"\u003e\n \u003cp\u003e1.175 \u0026ndash; 4.513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"132\"\u003e\n \u003cp\u003e0.015\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"221\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"94\"\u003e\n \u003cp\u003e0.320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"121\"\u003e\n \u003cp\u003e0.109 \u0026ndash; 0.936\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"132\"\u003e\n \u003cp\u003e0.037\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"221\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"94\"\u003e\n \u003cp\u003e0.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"121\"\u003e\n \u003cp\u003e0.487 \u0026ndash; 0.801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"132\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"221\"\u003e\n \u003cp\u003eIncome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"94\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"121\"\u003e\n \u003cp\u003e0.301 \u0026ndash; 0.830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"132\"\u003e\n \u003cp\u003e0.007\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"568\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease-related factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"568\"\u003e\n \u003cp\u003eCourse of disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"221\"\u003e\n \u003cp\u003e\u0026lt; 3 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"94\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"121\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"132\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"221\"\u003e\n \u003cp\u003e3 \u0026ndash; 6 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"94\"\u003e\n \u003cp\u003e2.945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"121\"\u003e\n \u003cp\u003e1.135 \u0026ndash; 7.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"132\"\u003e\n \u003cp\u003e0.026\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"221\"\u003e\n \u003cp\u003e\u0026gt; 6 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"94\"\u003e\n \u003cp\u003e0.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"121\"\u003e\n \u003cp\u003e0.153 \u0026ndash; 0.708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"132\"\u003e\n \u003cp\u003e0.004\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"568\"\u003e\n \u003cp\u003ePathological typing\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"221\"\u003e\n \u003cp\u003eⅠ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"94\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"121\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"132\"\u003e\n \u003cp\u003e0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"221\"\u003e\n \u003cp\u003eⅡ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"94\"\u003e\n \u003cp\u003e1.311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"121\"\u003e\n \u003cp\u003e0.520 \u0026ndash; 3.303\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"132\"\u003e\n \u003cp\u003e0.566\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"221\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"94\"\u003e\n \u003cp\u003e2.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"121\"\u003e\n \u003cp\u003e0.703 \u0026ndash; 6.330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"132\"\u003e\n \u003cp\u003e0.183\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"221\"\u003e\n \u003cp\u003eⅣ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"94\"\u003e\n \u003cp\u003e0.251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"121\"\u003e\n \u003cp\u003e0.086 \u0026ndash; 0.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"132\"\u003e\n \u003cp\u003e0.011\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: OR: odds ratio; CI: Confidence intervals.\u003csup\u003e\u0026nbsp;**\u003c/sup\u003e Indicates statistical significance at \u003cem\u003eP\u003c/em\u003e \u0026le; 0.01. \u003csup\u003e*\u003c/sup\u003e Indicates statistical significance at \u003cem\u003eP\u003c/em\u003e \u0026le; 0.05. Demographic characteristics: Omnbius Tests of model Coefficients: \u003cem\u003eP\u003c/em\u003e \u0026le; 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: \u0026chi;\u003csup\u003e2\u003c/sup\u003e = 10.207, \u003cem\u003eP\u003c/em\u003e = 0.177; Disease-related factors: Omnbius Tests of model Coefficients: \u003cem\u003eP\u003c/em\u003e \u0026le; 0.01; The Hosmer-Lemeshow Goodness-of-Fit Test: \u0026chi;\u003csup\u003e2\u003c/sup\u003e = 1.617, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.951. SDM: Shared decision-making.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Lung cancer, Patient decision aids, Shared decision-making, Nursing","lastPublishedDoi":"10.21203/rs.3.rs-1006105/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1006105/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003eThe purpose of this study was to investigate and analyze the level of actual participation and perceived importance of shared decision-making on treatment and care of lung cancer patients, to compare their differences and to explore factors that influence them.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A total of 290 lung cancer patients were collected from the department of oncology and thoracic surgery of a comprehensive medical center in Qingdao from October 2018 to December 2019. Participants completed a cross-sectional questionnaire to assess their actual participation and perceived importance in shared decision-making on treatment and care. Descriptive analysis and non-parametric tests were carried out to assess the status quo of patients' shared decision-making on treatment and care. Binary logistic regression analysis with a stepwise back-wards was applied to predict the factors that affected patients' participation in shared decision-making.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The results showed that patients with lung cancer had a low degree of participation in shared decision-making. There were significant differences between actual participation and perceived importance of shared decision-making on treatment and care. Education level, younger, gender, income, marital status, personality, the course of the disease (\u0026gt;6 months), and the Pathological TNM staging (Ⅲ) affected the patient's level of participation in shared decision-making.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Actual participation in shared decision-making for the treatment and care of lung cancer patients was low and considered unimportant. We could train oncology nurses to use patient decision aids to help patients and families participate in shared decision-making based patients’ value, preferences and needs.\u003c/p\u003e","manuscriptTitle":"Influencing Factors of Lung Cancer Patients' Participation in Shared Decision-making: a Cross-sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-11-29 16:31:40","doi":"10.21203/rs.3.rs-1006105/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"26a516f3-f2d2-4a9c-82da-a23375482b3a","owner":[],"postedDate":"November 29th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":8812583,"name":"Cancer Biology"}],"tags":[],"updatedAt":"2022-01-04T03:56:41+00:00","versionOfRecord":[],"versionCreatedAt":"2021-11-29 16:31:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1006105","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1006105","identity":"rs-1006105","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}