Self-Advocacy and Influencing Factors in Post-Surgical Breast Cancer Patients: A Latent Profile Analysis

Self-Advocacy and Influencing Factors in Post-Surgical Breast Cancer Patients: A Latent Profile Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Self-Advocacy and Influencing Factors in Post-Surgical Breast Cancer Patients: A Latent Profile Analysis Jing Chen, Shuyi Zhu, Yanxin Xu, Jiawen Huo, Rui Li, Xuan Ren, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6632387/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 This study aimed to identify latent profiles of self-advocacy among post-surgical breast cancer patients and to explore associated influencing factors, thereby providing a basis for targeted interventions. Methods A total of 350 post-surgical breast cancer patients were recruited through convenience sampling at Guangdong Provincial Hospital of Traditional Chinese Medicine between July 2023 and May 2024. Participants completed a demographic questionnaire, the Self-Advocacy Scale for Female Cancer Patients, the Breast Cancer Survivor Self-Efficacy Scale, and the Family Avoidance of Cancer Communication Scale. Latent profile analysis (LPA) was conducted using Mplus 8.3, with 18 items from the self-advocacy scale serving as observed indicators. Multinomial logistic regression was performed to identify factors associated with profile membership. Results Three distinct self-advocacy profiles were identified: Low Advocacy-Self-Reliant Group (39.2%), Moderate Advocacy-Low Support Group (19.7%), and High Advocacy-Balanced Group (41.1%). Multivariate analysis revealed that education level, personality traits, type of medical insurance, family history of breast cancer, and self-efficacy significantly influenced profile membership (all P < 0.05). Conclusion Developing tailored interventions based on patients’ self-advocacy profiles may enhance engagement in treatment decision-making and support improved clinical outcomes. Breast cancer Self-advocacy Postoperative Latent profile analysis Influencing Factors Figures Figure 1 Figure 2 Introduction Breast cancer (BC) remains a major global health concern. In 2022, it accounted for an estimated 2.3 million new diagnoses, making it the most commonly diagnosed cancer worldwide[ 1 ]. BC accounts for approximately 15.5% of global cancer-related deaths, making it one of the leading causes of cancer mortality worldwide. In contrast, the mortality rate in China is reported at 3.9%. These figures highlight the urgent need for context-specific research and targeted interventions to enhance breast cancer care and survivorship. Although advances in early detection, surgical techniques, and adjuvant therapies have significantly improved outcomes, BC remains a major contributor to cancer mortality. Survival rates vary substantially by stage at diagnosis, with five-year survival exceeding 95% for stage I and approximately 85% for stage II disease[ 2 ]. However, many patients continue to face substantial challenges in making informed decisions, largely due to information asymmetry, emotional distress, and limited engagement in shared decision-making. This underscores the critical role of self-advocacy in empowering patients to actively participate in their care decisions and long-term recovery planning. Self-advocacy refers to a patient's ability to actively participate in medical decision-making by articulating their needs, expressing preferences, and seeking appropriate support throughout the cancer care continuum. It fosters patient autonomy and empowerment, enabling individuals to take a more active role in their treatment and overall care experience[ 3 ]. With the growing emphasis on patient-centered care in oncology, active involvement in treatment decision-making has become a critical indicator of care quality. Research indicates that patients with higher levels of self-efficacy are more capable of managing their illness and are more likely to engage in clinical decision-making processes, thereby promoting self-advocacy among individuals with breast cancer[ 4 ]. However, when families avoid discussing cancer-related issues, patients may experience limited understanding of their condition, which can hinder their involvement in treatment planning and decision-making[ 5 ]. These findings underscore the pivotal influence of self-efficacy and family communication dynamics on self-advocacy behaviors in post-surgical breast cancer patients. Gaining a deeper understanding of how these psychosocial factors interact is vital for designing effective support strategies that enhance patient engagement across the cancer care continuum. Existing research on breast cancer self-advocacy primarily relies on quantitative assessments, such as self-advocacy scale scores, to evaluate advocacy levels [ 6 ]. While these studies have yielded valuable insights, they often adopt variable-centered approaches—such as regression analyses—which inherently assume population homogeneity. This assumption may mask important within-group differences and fail to capture the heterogeneity of self-advocacy behaviors among breast cancer patients. Moreover, limited attention has been given to exploring the nuanced, person-centered patterns of advocacy that reflect diverse patient experiences and psychosocial contexts. To address these limitations, the present study introduces a novel application of latent profile analysis (LPA) to the field of self-advocacy research. Specifically, it aims to: (1) identify distinct subgroups of breast cancer patients based on their post-surgical self-advocacy profiles; (2) apply the Social Cognitive Theory framework to explore the psychosocial factors associated with each subgroup. By adopting a person-centered analytical strategy, this study seeks to provide a more comprehensive understanding of self-advocacy heterogeneity. The findings will inform the development of tailored interventions that enhance patient engagement in treatment decision-making and long-term disease self-management. Theoretical framework Social Cognitive Theory (SCT), developed by Bandura, offers a comprehensive framework for understanding the reciprocal interactions among personal, behavioral, and environmental factors in shaping human behavior [ 7 ]. Unlike traditional behaviorist models that focus solely on external reinforcement, SCT emphasizes individual agency, highlighting how personal cognition, emotions, intentions, attitudes, and self-efficacy contribute directly to behavioral choices. Environmental feedback, in turn, plays a critical role in reinforcing or modifying these behaviors over time [ 8 ]. As a result, the concept of triadic reciprocal causation was introduced, highlighting a form of determinism based on the mutual interaction of three core elements [ 9 ]. This study utilizes Social Cognitive Theory (SCT) as a foundational framework to explore the dynamic nature of self-advocacy among post-surgical breast cancer patients. Rather than considering self-advocacy as an inherent trait, it is framed as a flexible behavior that evolves through cognitive beliefs, such as self-efficacy, and interpersonal influences, particularly in healthcare and family contexts. By integrating SCT’s triadic model, this approach provides a deeper insight into how personal beliefs, self-regulation, and family communication collaboratively shape patients' involvement in treatment decisions and long-term care. SCT has long been applied to health behavior research to examine the complex interactions between individual factors, behavior, and environmental contexts. In this study, the focus is placed on three critical factors: self-advocacy, self-efficacy, and family communication patterns concerning cancer. These constructs are measured through validated instruments, while a structured questionnaire also collects sociodemographic and clinical data, enabling a thorough subgroup analysis and contextual understanding of the findings[ 10 ]. The conceptual framework for this study is depicted in Fig. 1 . Methods Study design and participants This study employed a cross-sectional design. A total of 350 breast cancer patients were recruited from the Breast Surgery Department of Guangdong Provincial Hospital of Traditional Chinese Medicine between July 2023 and May 2024 using a convenience sampling approach. Eligible participants were: (1) aged 18 years or older; (2) diagnosed with primary breast cancer; (3) underwent initial surgical treatment at the study site; (4) cognitively intact and able to complete the questionnaire independently; and (5) provided informed consent. Exclusion criteria included severe psychiatric or cognitive disorders and a history of other malignancies. A pilot survey was conducted in July 2023 among 30 patients to assess the clarity and feasibility of the questionnaire and refine the survey process accordingly. Data collection procedures Trained researchers conducted face-to-face recruitment and explained the study objectives, procedures, and confidentiality principles to all participants. After obtaining informed consent, participants completed the paper-based questionnaires independently in a quiet setting. Standardized instructions were provided, and any unclear items were explained upon request. Each questionnaire was reviewed on-site to ensure completeness. Responses with major missing data, logical inconsistencies, or mechanical answering patterns were excluded from the final analysis. All data were double-entered into Excel spreadsheets by two independent researchers and cross-verified for accuracy. The final dataset was analyzed using SPSS version 26.0. Measures Four validated instruments were used in this study to assess demographic and clinical characteristics, self-advocacy, self-efficacy, and family cancer communication. Demographic and clinical characteristics A structured questionnaire was designed based on previous literature and expert consultations. It included two components: (1) demographic variables such as age, education level, marital status, occupation, monthly household income per capita, and personality traits; and (2) clinical variables such as type of surgery, time since surgery, family history of breast cancer, TNM stage, and time spent searching for breast cancer information. Self-advocacy The Female Self-Advocacy in Cancer Survivorship Scale (FSACS), originally developed by Hagan et al. [ 3 ] and adapted into Chinese by Feng Ling et al. [ 11 ], was used to assess self-advocacy. The scale contains 18 items across three subscales: informed decision-making, effective communication, and perceived social support (connected strength). Each item is rated on a 6-point Likert scale (1 = strongly disagree, 6 = strongly agree), yielding a total score ranging from 18 to 108. Higher scores indicate greater self-advocacy. In this study, the Cronbach’s α coefficient for the Chinese version was 0.886. Self-efficacy Self-efficacy was measured using the Chinese version of the Breast Cancer Survivor Self-Efficacy Scale (BCSES), developed by Champion et al. [ 12 ] and translated by Liu Yanjin et al. [ 13 ]. The scale includes 11 items rated on a 5-point Likert scale, with total scores ranging from 11 to 55. Higher scores reflect greater perceived self-efficacy. The Cronbach’s α in this study was 0.844. Family communication about cancer Family communication patterns were assessed using the Family Avoidance of Communication about Cancer Scale (FACCS), developed by Mallinger et al. [ 14 ] and adapted to Chinese by Zhang Xueyun [ 15 ]. The scale includes 5 items rated on a 5-point Likert scale. Raw scores were converted to standardized scores using the formula: (Raw score-1) / 4 × 100. Higher scores represent stronger avoidance of cancer-related communication. Cronbach’s α for this scale was 0.722. Statistical analysis Descriptive statistics were used to summarize sociodemographic and clinical characteristics. Latent profile analysis (LPA) was conducted using Mplus version 8.3 to identify unobserved subgroups of self-advocacy based on participants’ responses to the 18 FSACS items. A series of models with increasing profile numbers were tested, and model fit was evaluated using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), sample-size adjusted BIC (aBIC), entropy, Lo-Mendell-Rubin adjusted likelihood ratio test (LMR-LRT), and Bootstrap Likelihood Ratio Test (BLRT). The optimal model was determined based on statistical indicators and interpretability. Following LPA, a multinomial logistic regression analysis was performed using SPSS 26.0 to examine the sociodemographic and psychosocial factors associated with class membership. Statistical significance was set at P < 0.05. Data analysis Data analysis was conducted using SPSS 26 and Mplus 8.3, with a significance level set at α = 0.05. Descriptive statistics were used to calculate participants' demographic, clinical characteristics and scale scores. Continuous data were presented as means ± SD, and categorical data as frequencies and percentages. Univariate analysis was performed using the chi-square test, Fisher's exact test, analysis of variance test, or the Kruskal-Wallis H test. Mplus 8.3 was used to conduct latent profile analysis to explore the types of self-advocacy in post-operative breast cancer patients. The model fitting process started with one profile and incrementally increased the number of profiles. The goodness-of-fit evaluation indicators included Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), adjusted Bayesian Information Criterion (aBIC), Entropy, Lo-Mendell-Rubin likelihood ratio Test (LMRT) and Bootstrap Likelihood Ratio Test (BLRT). Smaller AIC, BIC, and aBIC values indicated better model fitting [ 16 ]. The Entropy value ranges from 0 to 1, with values closer to 1 indicating more accurate model profile classification. A statistically significant difference in LMRT and BLRT suggested that the model with m profiles is superior to the model with m-1 profiles [ 17 ]. Finally, multinomial logistic regression analysis was performed using SPSS 26.0 to determine the factors influencing the heterogeneous subgroups of self-advocacy levels in post-operative breast cancer patients. Ethical considerations The research has been reviewed and approved by the Ethics Committee of Guangdong Provincial Hospital of Traditional Chinese Medicine (reference number: YE2023-321-01). Prior to the investigation, the researchers contacted the relevant hospital departments and began data collection upon receiving consent. All patients had complete understanding of the study and voluntary participation. Results Participant characteristics Among the 350 post-surgical breast cancer patients, ages ranged from 26 to 77 years, with a mean of 52.98 ± 10.73 years. Surgical procedures included breast-conserving surgery (140 cases, 40.0%), total mastectomy (123 cases, 35.1%), and breast reconstruction after mastectomy (87 cases, 24.9%). Surgery had been performed within the past three months in 290 patients (82.9%) and more than three months ago in 60 patients (17.1%). TNM staging was distributed as follows: Stage I (84 cases, 24.0%), Stage II (187 cases, 53.4%), and Stage III (79 cases, 22.6%). The mean total score of self-advocacy was 67.25 (SD = 17.10). Among the subdimensions, the mean scores were 26.95 (SD = 7.20) for self-decision making, 22.35 (SD = 6.42) for effective communication, and 17.96 (SD = 8.39) for perceived social support. Results of the latent profile analysis Table 1 displays the model indices for the one to five-class models that were analyzed. Latent profile analysis was performed using the 18-item Female Self-Advocacy in Cancer Survivorship Scale to assess self-advocacy in post-surgical breast cancer patients. Among them, the three-profile model had the highest entropy value, with statistically significant P-values for both the Lo-Mendell-Rubin test (LMRT) and the Bootstrapped Likelihood Ratio Test (BLRT), indicating a significantly better fit than the one- and two-profile models. In contrast, the LMRT P-values for the four and five-profile models were not statistically significant, suggesting these models did not provide distinct profiles. Based on a comprehensive evaluation of model fit indices, the final latent profile model for self-advocacy in post-surgical breast cancer patients was determined to consist of three categories. Table 1 Latent profile model fit indicators. Model AIC BIC aBIC LMRT BLRT Entropy 1 23724.37 23863.256 23749.051 - - - 2 22071.072 22283.258 22108.779 0.0021 0.0000 0.928 3 21394.498 21679.985 21445.230 0.0005 0.0000 0.950 4 20898.731 21257.519 20962.490 0.5343 0.0000 0.944 5 20658.027 21090.116 20734.812 0.1829 0.0000 0.934 Latent Profile Analysis and Classification of Self-Advocacy in Post-Surgical Breast Cancer Patients A latent profile distribution diagram was created based on the scores of the three dimensions in the Female Self-Advocacy in Cancer Survivorship Scale to illustrate the characteristics of the three identified profiles (Fig. 2 ). As can be seen from Fig. 2 , the first profile (C1) included 137 patients (39.2%) and was characterized by the lowest scores across all dimensions of self-advocacy, particularly in self-decision-making. This group was therefore classified as "Low Advocacy–Self-Reliant Group". The second profile (C2) comprised 69 patients (19.7%) and showed relatively lower scores in effective communication and social support. Given these characteristics, it was labeled as "Moderate Advocacy–Low Support Group". The third profile (C3) consisted of 144 patients (41.1%) and exhibited the highest scores across all dimensions, with a relatively balanced distribution. As a result, this profile was designated as "High Advocacy–Balanced Group". The detailed distribution of latent profile characteristics is presented in Table 2 . Table 2 Comparison of Self-Advocacy Scores and Dimensions Among Different Latent Profiles of Post-Surgical Breast Cancer Patients (Mean ± SD). Group Sample (n) Self-Advocacy Self-Decision Effective Communication Effective Social Support C1 Group 137 63.69 ± 17.68 25.28 ± 7.18 21.45 ± 6.55 16.97 ± 8.27 C2 Group 69 65.48 ± 14.92 27.83 ± 7.94 20.97 ± 7.23 16.68 ± 8.12 C3 Group 144 71.49 ± 16.70 28.11 ± 6.56 23.23 ± 6.43 20.15 ± 8.12 F 8.063 6.263 3.742 6.814 P < 0.001 0.002 0.025 0.001 Univariate Analysis of Latent Profiles of Self-Advocacy Among Postoperative Breast Cancer Patients Categorical variables across different latent profiles were compared using the chi-square test. The results revealed significant differences ( P < 0.05) in several factors, including living conditions, educational level, medical payment method, number of children, personality traits, family history of breast cancer, time spent per session searching for breast cancer-related information online, self-efficacy, and family avoidance of cancer-related communication (Table 3 ). Table 3 Univariate Analysis of Self-Advocacy Profiles Among Postoperative Breast Cancer Patients with Different Characteristics (n = 350). Variables Sample (n%) C1 Group (n = 137) C2 Group (n = 69) C3 Group (n = 144) χ ² P Residence 10.125 0.038 Living alone 36(10.3) 13(9.5) 15(21.7) 11(7.6) with family 272(77.7) 107(78.1) 46(66.7) 116(80.6) Others 42(12.0) 17(12.4) 8(11.6) 17(11.8) Education Level 11.877 0.018 Junior high or below 126(36.0) 19(13.8) 24(34.8) 53(36.8) High school 107(30.6) 44(32.1) 21(30.4) 42(29.2) College 117(33.4) 44(32.1) 24(34.8) 49(34.0) Payment Method 6.476 0.039 Medical insurance 330(94.3) 131(95.6) 61(88.4) 139(96.5) Others 20(5.7) 6(4.4) 8(11.6) 5(3.5) Number of Children 9.849 0.043 None 43(12.3) 13(9.5) 14(20.3) 11(7.6) ≤ 3个 174(49.7) 76(55.5) 32(43.4) 71(49.3) > 3个 133(38.0) 48(35.0) 23(33.3) 62(43.1) Personality Traits 9.628 0.047 Introverted 149(42.6) 56(40.9) 37(53.6) 56(38.9) Extroverted 92(26.3) 34(24.8) 20(29.0) 33(22.9) Mixed 109(31.1) 47(34.3) 12(17.4) 55(38.2) Family History of Breast Cancer 6.498 0.039 No 317(90.6) 121(88.3) 67(97.1) 123(85.4) Yes 33(9.4) 16(11.7) 2(2.9) 21(14.6) Time Spent Searching for Breast Cancer Information per Session 13.128 0.041 None 56(16.0) 17(12.4) 22(31.9) 25(17.4) 30min 82(23.4) 29(21.1) 14(20.3) 31(21.5) Self-Efficacy 40(34,46) 39(35,46) 39(33,42) 6.180 0.046 Family Avoidance of Cancer Communication 30(20,45) 25(15,40) 33(25,44) 7.694 0.021 Multivariate Logistic Regression Analysis of Latent Profiles of Self-Advocacy in Postoperative Breast Cancer Patients A multivariate logistic regression analysis was performed with the three identified latent profiles as the dependent variable (C1 = 1, C2 = 2, C3 = 3), using the Low Advocacy–Self-Reliant Group (C1) as the reference category. Independent variables included those that were statistically significant in the univariate analysis. The model fit was satisfactory ( P < 0.001), indicating that the regression model was well-fitted. The results showed that, compared to the Low Advocacy–Self-Reliant Group, factors associated with classification into the Moderate Advocacy–Low Support Group included an education level of junior high school or below, introverted personality traits, and the absence of a family history of breast cancer. In contrast, classification into the High Advocacy–Balanced Group was significantly linked to an education level of junior high school or below, medical insurance coverage, and self-efficacy. Detailed results are provided in Table 4 . Table 4 Multiple Logistic regression analysis of the potential profile of self-advocacy in patients after breast cancer surgery (n = 350). Variables Moderate Advocacy–Low Support Group (C2) High Advocacy–Balanced Group (C3) reference object β SE P OR 95% CI β SE P OR 95% CI constant -0.971 1.884 0.606 3.409 1.382 0.014 Education Level (Junior high or below) College 1.013 0.392 0.010 2.754 1.279 ~ 5.934 0.848 0.31 0.006 2.336 1.272 ~ 4.290 Personality Traits (Introverted) Mixed 0.994 0.418 0.017 2.702 1.191 ~ 6.129 -0.22 0.296 0.457 0.803 0.45 ~ 1.433 Family History of Breast Cancer (No) Yes 1.692 0.832 0.042 5.429 1.062 ~ 27.747 -0.414 0.385 0.282 0.661 0.311 ~ 1.433 Payment Method (Medical insurance) Others -0.990 0.771 0.199 0.371 0.082 ~ 1.684 -1.307 0.633 0.039 0.271 0.078 ~ 0.935 Self-Efficacy -0.019 0.022 0.390 0.982 0.941 ~ 1.024 -0.049 0.017 0.005 0.952 0.920 ~ 0.985 Note: The reference group is Low Advocacy–Self-Reliant Group (C1). Discussion Potential categories and characteristics of self-advocacy The overall self-advocacy score for post-surgical breast cancer patients was 67.25 ± 17.10. This score aligns with the self-advocacy levels observed in patients undergoing chemotherapy for breast cancer, indicating a moderate to above-average degree of self-advocacy overall[ 18 ]. Advancements in modern technology have made it easier for breast cancer patients to access up-to-date medical research and treatment options, thereby enhancing their understanding of the disease and available treatments. Additionally, the growing emphasis on patient-centered care in healthcare systems encourages patients to actively participate in the decision-making process. This shift not only fosters a sense of empowerment but also plays a crucial role in improving patients' self-advocacy levels[ 19 ]. A detailed analysis revealed that item 17, "Telling others my story makes me feel good," had the lowest score, followed by item 18, "I am happy to share my cancer experience with others." This may be due to patients feeling that the support and understanding they received after sharing their stories did not meet their expectations. Therefore, healthcare providers should encourage patients to express their feelings and establish breast cancer support groups where patients feel their stories will be respected and understood. Additionally, these groups can help patients recognize the positive impact their experiences can have on others. This study identified three distinct subgroups, each exhibiting unique characteristics. The "High Advocacy-Balanced" group, which accounted for 41.1% of the participants, demonstrated the highest scores across all dimensions of self-advocacy, reflecting a well-rounded profile characterized by effective communication, strong social support, and active decision-making. These patients appear to have a robust set of personal resources that enable them to effectively navigate healthcare challenges and engage actively in their care. The "Low Advocacy-Self-Reliant" group, comprising 39.2% of the sample, showed relatively low overall self-advocacy scores but outperformed the "Moderate Advocacy-Low Support" group in areas such as communication and social support. This suggests that, although these patients tend to rely more on personal judgment and less on external support, they possess certain interpersonal strengths that may still facilitate their engagement with healthcare providers[ 20 ]. In contrast, the "Moderate Advocacy-Low Support" group, accounting for 19.7% of the participants, showed moderate levels of self-advocacy but notably lower scores in the dimension of social support. This suggests that insufficient access to supportive relationships may hinder their ability to express needs and preferences within clinical contexts, potentially limiting their overall advocacy capacity. Analysis of influencing factors for potential categories of self-advocacy Logistic regression analysis revealed that individuals with lower educational attainment, introverted personality traits, and no family history of breast cancer were more likely to be classified into the "Moderate Advocacy–Low Support" group. Specifically, participants whose highest level of education was junior high school or below had a significantly higher likelihood of falling into this subgroup compared to those with a college education or above. This finding suggests that educational background may influence patients' help-seeking behaviors and their ability to access, comprehend, and utilize health-related resources. These results are consistent with previous studies, such as that of Calderon, which emphasized the role of education in shaping self-advocacy and patient engagement[ 21 ]. In terms of personality traits, individuals with introverted personalities were more likely to be classified into the Moderate Advocacy-Low Support group. Introverted individuals tend to favor meaningful one-on-one interactions over participating in large-group social activities. This communication style may limit their ability to establish broad social connections and access support, thereby reducing their level of self-advocacy [ 20 ]. Individuals without a family history of breast cancer were more likely to be classified into the moderate self-advocacy—social support-deficient group. It is consistent with Pegington's research results [ 22 ]. These individuals may be less focused on disease prevention and early intervention, which could result in a lack of sufficient self-advocacy awareness when facing health issues. Additionally, support networks within their social circles are often built around shared health concerns, leading to a weaker social support system. This suggests that healthcare providers should pay closer attention to patients with lower educational levels, introverted personalities, and no family history of breast cancer. For these patients, providing visually enriched health education materials, along with positive feedback and encouragement, can help enhance their confidence and ability to manage their health. The results of the logistic regression analysis indicated that individuals with medical insurance coverage were more likely to be classified into the High Advocacy–Balanced Group. The medical insurance system typically involves clear reimbursement procedures and standardized medical services, which provide transparency, enabling patients to better understand their rights and financial responsibilities in the healthcare process. This clarity allows for more informed decision-making, a finding consistent with the research of Crespo-Gonzalez [ 23 ]. Higher levels of self-efficacy were significantly associated with membership in the High Advocacy–Balanced group. As a foundational construct of Bandura’s Social Cognitive Theory, self-efficacy reflects an individual’s belief in their capacity to exert control over their actions and environment. It is widely recognized as a critical determinant of health behavior change and sustainability. Individuals with strong self-efficacy are more likely to regulate their emotions, adopt and maintain health-promoting behaviors, and navigate health-related challenges effectively, thereby enhancing both disease management and overall quality of life. These findings suggest that healthcare professionals should actively support patients in setting realistic goals, developing action plans, and participating in tailored treatment and rehabilitation strategies. Such efforts may foster a greater sense of agency and motivation, ultimately strengthening self-advocacy behaviors throughout the care continuum[ 10 ]. Study limitations This study has several limitations that warrant consideration. First, the use of a small, single-center sample and convenience sampling restricts the generalizability of the findings, limiting their applicability to broader populations across different regions or healthcare settings. Second, due to the complexity of the relationships among influencing factors, this study was unable to elucidate the pathways or establish causal links between variables. Third, the study did not include post-discharge follow-up, making it difficult to assess how patients' self-advocacy levels may change over time. Future research should adopt a longitudinal design to examine the trajectory of self-advocacy across various stages of recovery and to better understand the dynamic interplay of contributing factors. Clinical implications In our study, we identified three self-advocacy subgroups among postoperative breast cancer patients and examined the factors influencing these groups. Based on these findings, we recommend that healthcare providers focus on patients with lower educational levels, those who opt for out-of-pocket or public health insurance, individuals without a family history of breast cancer, introverted personalities, and low self-efficacy. These patients may have weaker self-advocacy abilities during the diagnostic stage. These findings and recommendations provide a foundation for clinical intervention and healthcare policy improvements, facilitating the development of targeted interventions tailored to the specific needs of different patient groups and ultimately enhancing patients' autonomy in health management and improving their quality of life. Conclusions This study based on latent profile analysis, divides post-surgical self-advocacy in breast cancer patients into three categories. It identifies factors such as education level, healthcare payment methods, family history, personality traits, and self-efficacy as key influences on self-advocacy. Consequently, healthcare providers can offer targeted health education. Our findings advocate for stratified interventions: For the Low Advocacy-Self-Reliant Group, enhancing communication skills through role-playing exercises may be prioritized, whereas the Moderate Advocacy-Low Support Group may benefit from social support networks and health literacy programs. Declarations Acknowledgements The authors would like to thank the Guangdong Pharmaceutical University and Guangdong Provincial Hospital of Traditional Chinese Medicine for their support of the study site, and the patients for their selfless help. Author contribution Jing Chen: Writing-review & editing, Writing-original draft, Formal analysis, Data curation, Conceptualization. Shuyi Zhu: Formal analysis, Data curation, Conceptualization. Yanxin Xu: Investigation, Data curation. Jiawen Huo: Investigation, Data curation. Rui Li: Investigation, Data curation. Xuan Ren: Investigation, Data curation. Shuhua Ye: Investigation, Data curation. Aoxiang Luo: Writing-review & editing, Supervision, Project administration, Funding acquisition, Conceptualization. Funding This work was supported by the Guangzhou Civil Affairs Science and Technology Fund [grant number:2021MZK34], the Guangdong Provincial Continuing Education Quality Improvement Project [grant number: JXJYGC2022GX164], and the Guangdong Provincial Joint Training Graduate Demonstration Base [grant number: Yue JiaoYan Han [2024] 1-57]. Data availability All members of the research team can view and use all data from the study. Data can be provided to the publisher from the corresponding author. Ethical approval The researchers strictly followed the Declaration of Helsinki during the study. The research has been reviewed and approved by the Ethics Committee of Guangdong Provincial Hospital of Traditional Chinese Medicine (reference number: YE2023-321-01). Participants were informed in detail about the purpose of the study, methodology, and content, etc. Participants were also assured that they could withdraw at any time during the study and that there would be no impact on their follow-up care. Participant data remained anonymous, were kept by the researcher, and were not given to others. Consent to participate All of the participants provided Informed consent in this study. Consent for publicatio n All of the authors approved the final paper for publication. Competing interests The authors declare no competing interests. References Bashar, M.D.A., Begam, N. 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(2023) Using multimedia technology to enhance self-advocacy of people with intellectual disabilities: Introducing a theoretical framework for “Multimedia Advocacy”. J. Appl. Res. Intellect. Disabil. JARID 36, 739–749. https://doi.org/10.1111/jar.13107 Hagan, T.L., Cohen, S.M., Rosenzweig, M.Q., Zorn, K., Stone, C.A., Donovan, H.S. (2018) The Female Self-Advocacy in Cancer Survivorship Scale: A validation study. J. Adv. Nurs. 74, 976-987. https://doi.org/10.1111/jan.13498 Bandura, A. (2001) Social cognitive theory: an agentic perspective. Annu. Rev. Psychol. 52, 1–26. https://doi.org/10.1146/annurev.psych.52.1.1 Eriksson, M., Sundberg, L.R., Santosa, A., Lindgren, H., Ng, N., Lindvall, K. (2025) Health behavioural change - the influence of social-ecological factors and health identity. Int. J. Qual. Stud. Health Well-Being 20, 2458309. https://doi.org/10.1080/17482631.2025.2458309 Bandura, A., Adams, N.E., Beyer, J. (1977) Cognitive processes mediating behavioral change. J. Pers. Soc. Psychol. 35, 125–139. https://doi.org/10.1037//0022-3514.35.3.125 Barley, E., Lawson, V. (2016) Using health psychology to help patients: theories of behaviour change. Br. J. Nurs. Mark Allen Publ. 25, 924-927. https://doi.org/10.12968/bjon.2016.25.16.924 Feng Ling et al. (2021) The localization and reliability and validity test of the Self-Advocacy Scale for Female Cancer Survivors. Nurs. Res. 377–381. Champion, V.L., Ziner, K.W., Monahan, P.O., Stump, T.E., Cella, D., Smith, L.G., et al. (2013) Development and psychometric testing of a breast cancer survivor self-efficacy scale. Oncol. Nurs. Forum 40, E403-410. https://doi.org/10.1188/13.ONF.E403-E410 Liu Yanjin et al. (2016) Reliability and validity analysis of the Chinese version of the Self-Efficacy Scale for Breast Cancer Survivors. Gen. Pract. China 3336–3340. Mallinger, J.B., Griggs, J.J., Shields, C.G. (2006) Family communication and mental health after breast cancer. Eur. J. Cancer Care (Engl.) 15, 355–361. https://doi.org/10.1111/j.1365-2354.2006.00666.x Zhang Xueyun (2022) The Relationship between Disease Perception, Mindfulness and Fear of Cancer Recurrence in Breast Cancer Patients and their Spouses: The mediating role of Family avoidance of cancer communication. Shandong Univ. https://doi.org/10.27272/d.cnki.gshdu.2022.003524 Sarah L et al., U. institution-id-type="Ringgold"2954/institution-idinstitution content-type="university"Wayne S.U. (2020) Finding latent groups in observed data: A primer on latent profile analysis in Mplus for applied researchers. Int. J. Behav. Dev. 458-468. Gitta Lubke et al. (2007) Performance of Factor Mixture Models as a Function of Model Size, Covariate Effects, and Class-Specific Parameters. Struct. Equ. Model. 26-47. He Li et al. (2023) Analysis of the Current Situation and influencing Factors of Self-advocacy Ability of Breast Cancer patients undergoing Chemotherapy. Chin. J. Nurs. 788-793. Hagan, T.L., Donovan, H.S. (2013) Self-advocacy and cancer: a concept analysis. J. Adv. Nurs. 69, 2348–2359. https://doi.org/10.1111/jan.12084 Thomas, T.H., Donovan, H.S., Rosenzweig, M.Q., Bender, C.M., Schenker, Y. (2021) A Conceptual Framework of Self-advocacy in Women With Cancer. ANS Adv. Nurs. Sci. 44, E1–E13. https://doi.org/10.1097/ANS.0000000000000342 Calderon, C., Gomez, D., Carmona-Bayonas, A., Hernandez, R., Ghanem, I., Gil Raga, M., et al. (2021) Social support, coping strategies and sociodemographic factors in women with breast cancer. Clin. Transl. Oncol. Off. Publ. Fed. Span. Oncol. Soc. Natl. Cancer Inst. Mex. 23, 1955–1960. https://doi.org/10.1007/s12094-021-02592-y Pegington, M., Davies, A., Mueller, J., Cholerton, R., Howell, A., Evans, D.G., et al. (2022) Evaluating the Acceptance and Usability of an App Promoting Weight Gain Prevention and Healthy Behaviors Among Young Women With a Family History of Breast Cancer: Protocol for an Observational Study. JMIR Res. Protoc. 11, e41246. https://doi.org/10.2196/41246 Crespo-Gonzalez, C., Benrimoj, S.I., Frommer, M., Dineen-Griffin, S. (2024) Navigating online health information: Insights into consumer influence and decision-making strategies-An overview of reviews. Digit. Health 10, 20552076241286815. https://doi.org/10.1177/20552076241286815 Additional Declarations No competing interests reported. Supplementary Files ANRManuscriptChecklist.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6632387","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":475943672,"identity":"f0621c05-1e91-4373-a9e1-7e1e71680aba","order_by":0,"name":"Jing Chen","email":"","orcid":"","institution":"Guangdong Pharmaceutical University","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Chen","suffix":""},{"id":475943673,"identity":"f88f0624-f416-414c-95f2-6b2bef1f2738","order_by":1,"name":"Shuyi Zhu","email":"","orcid":"","institution":"Guangdong Pharmaceutical University","correspondingAuthor":false,"prefix":"","firstName":"Shuyi","middleName":"","lastName":"Zhu","suffix":""},{"id":475943674,"identity":"d37087bd-8f2f-4315-8aa5-a729b178797b","order_by":2,"name":"Yanxin Xu","email":"","orcid":"","institution":"Guangdong Pharmaceutical University","correspondingAuthor":false,"prefix":"","firstName":"Yanxin","middleName":"","lastName":"Xu","suffix":""},{"id":475943675,"identity":"1207f72e-fc99-436f-9856-61f8c8d3a590","order_by":3,"name":"Jiawen Huo","email":"","orcid":"","institution":"Guangdong Pharmaceutical University","correspondingAuthor":false,"prefix":"","firstName":"Jiawen","middleName":"","lastName":"Huo","suffix":""},{"id":475943676,"identity":"25eacb5c-a15d-412e-9e01-9b73a869ea23","order_by":4,"name":"Rui Li","email":"","orcid":"","institution":"Guangdong Pharmaceutical University","correspondingAuthor":false,"prefix":"","firstName":"Rui","middleName":"","lastName":"Li","suffix":""},{"id":475943677,"identity":"de33b05c-e860-426d-bf2e-1c7b82ed47a2","order_by":5,"name":"Xuan Ren","email":"","orcid":"","institution":"Guangdong Pharmaceutical University","correspondingAuthor":false,"prefix":"","firstName":"Xuan","middleName":"","lastName":"Ren","suffix":""},{"id":475943678,"identity":"f0253ce2-5d5e-4d37-ab47-35e3a4a94f1b","order_by":6,"name":"Shuhua Ye","email":"","orcid":"","institution":"Guangdong Provincial Hospital of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Shuhua","middleName":"","lastName":"Ye","suffix":""},{"id":475943679,"identity":"94c24d09-c10f-4987-bbd7-12c900c13425","order_by":7,"name":"Aoxiang Luo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYDACCQjmYWNvbHz4gRQtcnw8h5uNJYjWAgTGchLpbQI8xOiQn9187IFl253ENsmHbUD9dnK6DQS0MM45lm4g2fYssU06se1BAUOysdkBAlqYJXLMJCTbDoO0tBtIMBxI3EZIC5tE/jeIFsmDbRI8xGjhkchhA2kxZpNgJFKLhESamYTEucNybDyJwEA2IMIv8jOSn0lLlB3mkW8//vDhhwo7OYJaQIAZEYMGRCgHAUbi0skoGAWjYBSMWAAA6nQ70QC8ADAAAAAASUVORK5CYII=","orcid":"","institution":"Guangdong Pharmaceutical University","correspondingAuthor":true,"prefix":"","firstName":"Aoxiang","middleName":"","lastName":"Luo","suffix":""}],"badges":[],"createdAt":"2025-05-10 04:38:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6632387/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6632387/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85843832,"identity":"3a69d5d7-58d6-4393-8c04-d8856e89d076","added_by":"auto","created_at":"2025-07-02 09:24:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":28407,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA \u003c/strong\u003econceptual framework of self-advocacy rights after breast cancer surgery based on social cognitive theory\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6632387/v1/bb7afd2412c80497f612eb99.png"},{"id":85843720,"identity":"820418d8-6d97-4c86-b867-503f85b7a2ef","added_by":"auto","created_at":"2025-07-02 09:24:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":57426,"visible":true,"origin":"","legend":"\u003cp\u003eCharacteristic Distribution of Latent Profiles of Self-Advocacy in Post-Surgical Breast Cancer Patients\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6632387/v1/5ba81c3ff6a42d3683790b79.png"},{"id":93815476,"identity":"15aec0a5-7ae8-419c-8e96-2586d9479d99","added_by":"auto","created_at":"2025-10-17 23:31:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1307442,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6632387/v1/76dddc30-2b8c-4d19-abe1-a799ab2de441.pdf"},{"id":85843816,"identity":"894a9dab-a0b8-43bf-a78d-56f5f8ac8558","added_by":"auto","created_at":"2025-07-02 09:24:10","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":46176,"visible":true,"origin":"","legend":"","description":"","filename":"ANRManuscriptChecklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-6632387/v1/c223ccc2f66266786578d6f7.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Self-Advocacy and Influencing Factors in Post-Surgical Breast Cancer Patients: A Latent Profile Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast cancer (BC) remains a major global health concern. In 2022, it accounted for an estimated 2.3\u0026nbsp;million new diagnoses, making it the most commonly diagnosed cancer worldwide[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. BC accounts for approximately 15.5% of global cancer-related deaths, making it one of the leading causes of cancer mortality worldwide. In contrast, the mortality rate in China is reported at 3.9%. These figures highlight the urgent need for context-specific research and targeted interventions to enhance breast cancer care and survivorship. Although advances in early detection, surgical techniques, and adjuvant therapies have significantly improved outcomes, BC remains a major contributor to cancer mortality. Survival rates vary substantially by stage at diagnosis, with five-year survival exceeding 95% for stage I and approximately 85% for stage II disease[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, many patients continue to face substantial challenges in making informed decisions, largely due to information asymmetry, emotional distress, and limited engagement in shared decision-making. This underscores the critical role of self-advocacy in empowering patients to actively participate in their care decisions and long-term recovery planning.\u003c/p\u003e \u003cp\u003eSelf-advocacy refers to a patient's ability to actively participate in medical decision-making by articulating their needs, expressing preferences, and seeking appropriate support throughout the cancer care continuum. It fosters patient autonomy and empowerment, enabling individuals to take a more active role in their treatment and overall care experience[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. With the growing emphasis on patient-centered care in oncology, active involvement in treatment decision-making has become a critical indicator of care quality. Research indicates that patients with higher levels of self-efficacy are more capable of managing their illness and are more likely to engage in clinical decision-making processes, thereby promoting self-advocacy among individuals with breast cancer[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, when families avoid discussing cancer-related issues, patients may experience limited understanding of their condition, which can hinder their involvement in treatment planning and decision-making[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. These findings underscore the pivotal influence of self-efficacy and family communication dynamics on self-advocacy behaviors in post-surgical breast cancer patients. Gaining a deeper understanding of how these psychosocial factors interact is vital for designing effective support strategies that enhance patient engagement across the cancer care continuum.\u003c/p\u003e \u003cp\u003eExisting research on breast cancer self-advocacy primarily relies on quantitative assessments, such as self-advocacy scale scores, to evaluate advocacy levels [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. While these studies have yielded valuable insights, they often adopt variable-centered approaches—such as regression analyses—which inherently assume population homogeneity. This assumption may mask important within-group differences and fail to capture the heterogeneity of self-advocacy behaviors among breast cancer patients. Moreover, limited attention has been given to exploring the nuanced, person-centered patterns of advocacy that reflect diverse patient experiences and psychosocial contexts.\u003c/p\u003e \u003cp\u003eTo address these limitations, the present study introduces a novel application of latent profile analysis (LPA) to the field of self-advocacy research. Specifically, it aims to: (1) identify distinct subgroups of breast cancer patients based on their post-surgical self-advocacy profiles; (2) apply the Social Cognitive Theory framework to explore the psychosocial factors associated with each subgroup. By adopting a person-centered analytical strategy, this study seeks to provide a more comprehensive understanding of self-advocacy heterogeneity. The findings will inform the development of tailored interventions that enhance patient engagement in treatment decision-making and long-term disease self-management.\u003c/p\u003e\n\u003ch3\u003eTheoretical framework\u003c/h3\u003e\n\u003cp\u003eSocial Cognitive Theory (SCT), developed by Bandura, offers a comprehensive framework for understanding the reciprocal interactions among personal, behavioral, and environmental factors in shaping human behavior [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Unlike traditional behaviorist models that focus solely on external reinforcement, SCT emphasizes individual agency, highlighting how personal cognition, emotions, intentions, attitudes, and self-efficacy contribute directly to behavioral choices. Environmental feedback, in turn, plays a critical role in reinforcing or modifying these behaviors over time [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. As a result, the concept of triadic reciprocal causation was introduced, highlighting a form of determinism based on the mutual interaction of three core elements [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study utilizes Social Cognitive Theory (SCT) as a foundational framework to explore the dynamic nature of self-advocacy among post-surgical breast cancer patients. Rather than considering self-advocacy as an inherent trait, it is framed as a flexible behavior that evolves through cognitive beliefs, such as self-efficacy, and interpersonal influences, particularly in healthcare and family contexts. By integrating SCT’s triadic model, this approach provides a deeper insight into how personal beliefs, self-regulation, and family communication collaboratively shape patients' involvement in treatment decisions and long-term care.\u003c/p\u003e \u003cp\u003eSCT has long been applied to health behavior research to examine the complex interactions between individual factors, behavior, and environmental contexts. In this study, the focus is placed on three critical factors: self-advocacy, self-efficacy, and family communication patterns concerning cancer. These constructs are measured through validated instruments, while a structured questionnaire also collects sociodemographic and clinical data, enabling a thorough subgroup analysis and contextual understanding of the findings[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The conceptual framework for this study is depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e\n\n\n\n\n\n \n\n\n\n "},{"header":"Methods","content":"\u003ch2\u003eStudy design and participants\u003c/h2\u003e\u003cp\u003eThis study employed a cross-sectional design. A total of 350 breast cancer patients were recruited from the Breast Surgery Department of Guangdong Provincial Hospital of Traditional Chinese Medicine between July 2023 and May 2024 using a convenience sampling approach. Eligible participants were: (1) aged 18 years or older; (2) diagnosed with primary breast cancer; (3) underwent initial surgical treatment at the study site; (4) cognitively intact and able to complete the questionnaire independently; and (5) provided informed consent. Exclusion criteria included severe psychiatric or cognitive disorders and a history of other malignancies. A pilot survey was conducted in July 2023 among 30 patients to assess the clarity and feasibility of the questionnaire and refine the survey process accordingly.\u003c/p\u003e\u003ch3\u003eData collection procedures\u003c/h3\u003e\u003cp\u003eTrained researchers conducted face-to-face recruitment and explained the study objectives, procedures, and confidentiality principles to all participants. After obtaining informed consent, participants completed the paper-based questionnaires independently in a quiet setting. Standardized instructions were provided, and any unclear items were explained upon request. Each questionnaire was reviewed on-site to ensure completeness. Responses with major missing data, logical inconsistencies, or mechanical answering patterns were excluded from the final analysis. All data were double-entered into Excel spreadsheets by two independent researchers and cross-verified for accuracy. The final dataset was analyzed using SPSS version 26.0.\u003c/p\u003e\u003ch3\u003eMeasures\u003c/h3\u003e\u003cp\u003eFour validated instruments were used in this study to assess demographic and clinical characteristics, self-advocacy, self-efficacy, and family cancer communication.\u003c/p\u003e\u003ch3\u003eDemographic and clinical characteristics\u003c/h3\u003e\u003cp\u003eA structured questionnaire was designed based on previous literature and expert consultations. It included two components: (1) demographic variables such as age, education level, marital status, occupation, monthly household income per capita, and personality traits; and (2) clinical variables such as type of surgery, time since surgery, family history of breast cancer, TNM stage, and time spent searching for breast cancer information.\u003c/p\u003e\u003ch2\u003eSelf-advocacy\u003c/h2\u003e\u003cp\u003eThe Female Self-Advocacy in Cancer Survivorship Scale (FSACS), originally developed by Hagan et al. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] and adapted into Chinese by Feng Ling et al. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], was used to assess self-advocacy. The scale contains 18 items across three subscales: informed decision-making, effective communication, and perceived social support (connected strength). Each item is rated on a 6-point Likert scale (1 = strongly disagree, 6 = strongly agree), yielding a total score ranging from 18 to 108. Higher scores indicate greater self-advocacy. In this study, the Cronbach’s α coefficient for the Chinese version was 0.886.\u003c/p\u003e\u003ch3\u003eSelf-efficacy\u003c/h3\u003e\u003cp\u003eSelf-efficacy was measured using the Chinese version of the Breast Cancer Survivor Self-Efficacy Scale (BCSES), developed by Champion et al. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and translated by Liu Yanjin et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The scale includes 11 items rated on a 5-point Likert scale, with total scores ranging from 11 to 55. Higher scores reflect greater perceived self-efficacy. The Cronbach’s α in this study was 0.844.\u003c/p\u003e\u003ch3\u003eFamily communication about cancer\u003c/h3\u003e\u003cp\u003eFamily communication patterns were assessed using the Family Avoidance of Communication about Cancer Scale (FACCS), developed by Mallinger et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and adapted to Chinese by Zhang Xueyun [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The scale includes 5 items rated on a 5-point Likert scale. Raw scores were converted to standardized scores using the formula: (Raw score-1) / 4 × 100. Higher scores represent stronger avoidance of cancer-related communication. Cronbach’s α for this scale was 0.722.\u003c/p\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistics were used to summarize sociodemographic and clinical characteristics. Latent profile analysis (LPA) was conducted using Mplus version 8.3 to identify unobserved subgroups of self-advocacy based on participants’ responses to the 18 FSACS items. A series of models with increasing profile numbers were tested, and model fit was evaluated using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), sample-size adjusted BIC (aBIC), entropy, Lo-Mendell-Rubin adjusted likelihood ratio test (LMR-LRT), and Bootstrap Likelihood Ratio Test (BLRT). The optimal model was determined based on statistical indicators and interpretability.\u003c/p\u003e\u003cp\u003eFollowing LPA, a multinomial logistic regression analysis was performed using SPSS 26.0 to examine the sociodemographic and psychosocial factors associated with class membership. Statistical significance was set at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eData analysis was conducted using SPSS 26 and Mplus 8.3, with a significance level set at α = 0.05. Descriptive statistics were used to calculate participants' demographic, clinical characteristics and scale scores. Continuous data were presented as means ± SD, and categorical data as frequencies and percentages. Univariate analysis was performed using the chi-square test, Fisher's exact test, analysis of variance test, or the Kruskal-Wallis H test.\u003c/p\u003e\u003cp\u003eMplus 8.3 was used to conduct latent profile analysis to explore the types of self-advocacy in post-operative breast cancer patients. The model fitting process started with one profile and incrementally increased the number of profiles. The goodness-of-fit evaluation indicators included Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), adjusted Bayesian Information Criterion (aBIC), Entropy, Lo-Mendell-Rubin likelihood ratio Test (LMRT) and Bootstrap Likelihood Ratio Test (BLRT). Smaller AIC, BIC, and aBIC values indicated better model fitting [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The Entropy value ranges from 0 to 1, with values closer to 1 indicating more accurate model profile classification. A statistically significant difference in LMRT and BLRT suggested that the model with m profiles is superior to the model with m-1 profiles [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Finally, multinomial logistic regression analysis was performed using SPSS 26.0 to determine the factors influencing the heterogeneous subgroups of self-advocacy levels in post-operative breast cancer patients.\u003c/p\u003e\u003ch2\u003eEthical considerations\u003c/h2\u003e\u003cp\u003eThe research has been reviewed and approved by the Ethics Committee of Guangdong Provincial Hospital of Traditional Chinese Medicine (reference number: YE2023-321-01). Prior to the investigation, the researchers contacted the relevant hospital departments and began data collection upon receiving consent. All patients had complete understanding of the study and voluntary participation.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eParticipant characteristics\u003c/h2\u003e \u003cp\u003eAmong the 350 post-surgical breast cancer patients, ages ranged from 26 to 77 years, with a mean of 52.98\u0026thinsp;\u0026plusmn;\u0026thinsp;10.73 years. Surgical procedures included breast-conserving surgery (140 cases, 40.0%), total mastectomy (123 cases, 35.1%), and breast reconstruction after mastectomy (87 cases, 24.9%). Surgery had been performed within the past three months in 290 patients (82.9%) and more than three months ago in 60 patients (17.1%). TNM staging was distributed as follows: Stage I (84 cases, 24.0%), Stage II (187 cases, 53.4%), and Stage III (79 cases, 22.6%). The mean total score of self-advocacy was 67.25 (SD\u0026thinsp;=\u0026thinsp;17.10). Among the subdimensions, the mean scores were 26.95 (SD\u0026thinsp;=\u0026thinsp;7.20) for self-decision making, 22.35 (SD\u0026thinsp;=\u0026thinsp;6.42) for effective communication, and 17.96 (SD\u0026thinsp;=\u0026thinsp;8.39) for perceived social support.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eResults of the latent profile analysis\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e displays the model indices for the one to five-class models that were analyzed. Latent profile analysis was performed using the 18-item Female Self-Advocacy in Cancer Survivorship Scale to assess self-advocacy in post-surgical breast cancer patients. Among them, the three-profile model had the highest entropy value, with statistically significant P-values for both the Lo-Mendell-Rubin test (LMRT) and the Bootstrapped Likelihood Ratio Test (BLRT), indicating a significantly better fit than the one- and two-profile models. In contrast, the LMRT P-values for the four and five-profile models were not statistically significant, suggesting these models did not provide distinct profiles. Based on a comprehensive evaluation of model fit indices, the final latent profile model for self-advocacy in post-surgical breast cancer patients was determined to consist of three categories.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLatent profile model fit indicators.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eaBIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLMRT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBLRT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEntropy\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23724.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23863.256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23749.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22071.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22283.258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22108.779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.928\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21394.498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21679.985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21445.230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.950\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20898.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21257.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20962.490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.944\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20658.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21090.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20734.812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.934\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eLatent Profile Analysis and Classification of Self-Advocacy in Post-Surgical Breast Cancer Patients\u003c/h2\u003e \u003cp\u003eA latent profile distribution diagram was created based on the scores of the three dimensions in the Female Self-Advocacy in Cancer Survivorship Scale to illustrate the characteristics of the three identified profiles (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs can be seen from Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the first profile (C1) included 137 patients (39.2%) and was characterized by the lowest scores across all dimensions of self-advocacy, particularly in self-decision-making. This group was therefore classified as \"Low Advocacy\u0026ndash;Self-Reliant Group\". The second profile (C2) comprised 69 patients (19.7%) and showed relatively lower scores in effective communication and social support. Given these characteristics, it was labeled as \"Moderate Advocacy\u0026ndash;Low Support Group\". The third profile (C3) consisted of 144 patients (41.1%) and exhibited the highest scores across all dimensions, with a relatively balanced distribution. As a result, this profile was designated as \"High Advocacy\u0026ndash;Balanced Group\". The detailed distribution of latent profile characteristics is presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Self-Advocacy Scores and Dimensions Among Different Latent Profiles of Post-Surgical Breast Cancer Patients (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003cp\u003e(n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSelf-Advocacy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSelf-Decision\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEffective Communication\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEffective Social Support\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC1 Group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.69\u0026thinsp;\u0026plusmn;\u0026thinsp;17.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.28\u0026thinsp;\u0026plusmn;\u0026thinsp;7.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.45\u0026thinsp;\u0026plusmn;\u0026thinsp;6.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.97\u0026thinsp;\u0026plusmn;\u0026thinsp;8.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC2 Group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.48\u0026thinsp;\u0026plusmn;\u0026thinsp;14.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.83\u0026thinsp;\u0026plusmn;\u0026thinsp;7.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.97\u0026thinsp;\u0026plusmn;\u0026thinsp;7.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.68\u0026thinsp;\u0026plusmn;\u0026thinsp;8.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC3 Group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.49\u0026thinsp;\u0026plusmn;\u0026thinsp;16.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.11\u0026thinsp;\u0026plusmn;\u0026thinsp;6.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.23\u0026thinsp;\u0026plusmn;\u0026thinsp;6.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.15\u0026thinsp;\u0026plusmn;\u0026thinsp;8.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.814\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eUnivariate Analysis of Latent Profiles of Self-Advocacy Among Postoperative Breast Cancer Patients\u003c/h2\u003e \u003cp\u003eCategorical variables across different latent profiles were compared using the chi-square test. The results revealed significant differences (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in several factors, including living conditions, educational level, medical payment method, number of children, personality traits, family history of breast cancer, time spent per session searching for breast cancer-related information online, self-efficacy, and family avoidance of cancer-related communication (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate Analysis of Self-Advocacy Profiles Among Postoperative Breast Cancer Patients with Different Characteristics (n\u0026thinsp;=\u0026thinsp;350).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003cp\u003e(n%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC1 Group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;137)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC2 Group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;69)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC3 Group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;144)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eχ\u003csup\u003e\u0026sup2;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36(10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11(7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ewith family\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e272(77.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107(78.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46(66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e116(80.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42(12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17(12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17(11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation Level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunior high or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126(36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19(13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24(34.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53(36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e107(30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44(32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(30.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42(29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117(33.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44(32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24(34.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49(34.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePayment Method\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e330(94.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131(95.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61(88.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e139(96.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20(5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of Children\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43(12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11(7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;3个\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e174(49.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76(55.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32(43.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71(49.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3个\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133(38.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48(35.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23(33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62(43.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePersonality Traits\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntroverted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e149(42.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56(40.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37(53.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56(38.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExtroverted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92(26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34(24.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20(29.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33(22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109(31.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47(34.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55(38.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily History of Breast Cancer\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e317(90.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121(88.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67(97.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e123(85.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33(9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21(14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTime Spent Searching for Breast Cancer Information per Session\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56(16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17(12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22(31.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25(17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;15min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114(32.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52(38.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(23.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46(31.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15-30min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98(28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39(28.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(24.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42(29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82(23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29(21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31(21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSelf-Efficacy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40(34,46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39(35,46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39(33,42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily Avoidance of Cancer Communication\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30(20,45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25(15,40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33(25,44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eMultivariate Logistic Regression Analysis of Latent Profiles of Self-Advocacy in Postoperative Breast Cancer Patients\u003c/h2\u003e \u003cp\u003eA multivariate logistic regression analysis was performed with the three identified latent profiles as the dependent variable (C1\u0026thinsp;=\u0026thinsp;1, C2\u0026thinsp;=\u0026thinsp;2, C3\u0026thinsp;=\u0026thinsp;3), using the Low Advocacy\u0026ndash;Self-Reliant Group (C1) as the reference category. Independent variables included those that were statistically significant in the univariate analysis.\u003c/p\u003e \u003cp\u003eThe model fit was satisfactory (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that the regression model was well-fitted. The results showed that, compared to the Low Advocacy\u0026ndash;Self-Reliant Group, factors associated with classification into the Moderate Advocacy\u0026ndash;Low Support Group included an education level of junior high school or below, introverted personality traits, and the absence of a family history of breast cancer. In contrast, classification into the High Advocacy\u0026ndash;Balanced Group was significantly linked to an education level of junior high school or below, medical insurance coverage, and self-efficacy. Detailed results are provided in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple Logistic regression analysis of the potential profile of self-advocacy in patients after breast cancer surgery (n\u0026thinsp;=\u0026thinsp;350).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eModerate Advocacy\u0026ndash;Low Support Group (C2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e \u003cp\u003eHigh Advocacy\u0026ndash;Balanced Group (C3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference object\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95%\u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e95%\u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003econstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation Level (Junior high or below)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCollege\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.279\u0026thinsp;~\u0026thinsp;5.934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.848\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.272\u0026thinsp;~\u0026thinsp;4.290\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePersonality Traits (Introverted)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.702\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.191\u0026thinsp;~\u0026thinsp;6.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.45\u0026thinsp;~\u0026thinsp;1.433\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily History of Breast Cancer (No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.062\u0026thinsp;~\u0026thinsp;27.747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.311\u0026thinsp;~\u0026thinsp;1.433\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePayment Method (Medical insurance)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.082\u0026thinsp;~\u0026thinsp;1.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.078\u0026thinsp;~\u0026thinsp;0.935\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-Efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.941\u0026thinsp;~\u0026thinsp;1.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.920\u0026thinsp;~\u0026thinsp;0.985\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eNote: The reference group is Low Advocacy\u0026ndash;Self-Reliant Group (C1).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003ePotential categories and characteristics of self-advocacy\u003c/h2\u003e \u003cp\u003eThe overall self-advocacy score for post-surgical breast cancer patients was 67.25\u0026thinsp;\u0026plusmn;\u0026thinsp;17.10. This score aligns with the self-advocacy levels observed in patients undergoing chemotherapy for breast cancer, indicating a moderate to above-average degree of self-advocacy overall[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Advancements in modern technology have made it easier for breast cancer patients to access up-to-date medical research and treatment options, thereby enhancing their understanding of the disease and available treatments. Additionally, the growing emphasis on patient-centered care in healthcare systems encourages patients to actively participate in the decision-making process. This shift not only fosters a sense of empowerment but also plays a crucial role in improving patients' self-advocacy levels[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. A detailed analysis revealed that item 17, \"Telling others my story makes me feel good,\" had the lowest score, followed by item 18, \"I am happy to share my cancer experience with others.\" This may be due to patients feeling that the support and understanding they received after sharing their stories did not meet their expectations. Therefore, healthcare providers should encourage patients to express their feelings and establish breast cancer support groups where patients feel their stories will be respected and understood. Additionally, these groups can help patients recognize the positive impact their experiences can have on others.\u003c/p\u003e \u003cp\u003eThis study identified three distinct subgroups, each exhibiting unique characteristics. The \"High Advocacy-Balanced\" group, which accounted for 41.1% of the participants, demonstrated the highest scores across all dimensions of self-advocacy, reflecting a well-rounded profile characterized by effective communication, strong social support, and active decision-making. These patients appear to have a robust set of personal resources that enable them to effectively navigate healthcare challenges and engage actively in their care.\u003c/p\u003e \u003cp\u003eThe \"Low Advocacy-Self-Reliant\" group, comprising 39.2% of the sample, showed relatively low overall self-advocacy scores but outperformed the \"Moderate Advocacy-Low Support\" group in areas such as communication and social support. This suggests that, although these patients tend to rely more on personal judgment and less on external support, they possess certain interpersonal strengths that may still facilitate their engagement with healthcare providers[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn contrast, the \"Moderate Advocacy-Low Support\" group, accounting for 19.7% of the participants, showed moderate levels of self-advocacy but notably lower scores in the dimension of social support. This suggests that insufficient access to supportive relationships may hinder their ability to express needs and preferences within clinical contexts, potentially limiting their overall advocacy capacity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of influencing factors for potential categories of self-advocacy\u003c/h2\u003e \u003cp\u003eLogistic regression analysis revealed that individuals with lower educational attainment, introverted personality traits, and no family history of breast cancer were more likely to be classified into the \"Moderate Advocacy\u0026ndash;Low Support\" group. Specifically, participants whose highest level of education was junior high school or below had a significantly higher likelihood of falling into this subgroup compared to those with a college education or above. This finding suggests that educational background may influence patients' help-seeking behaviors and their ability to access, comprehend, and utilize health-related resources. These results are consistent with previous studies, such as that of Calderon, which emphasized the role of education in shaping self-advocacy and patient engagement[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn terms of personality traits, individuals with introverted personalities were more likely to be classified into the Moderate Advocacy-Low Support group. Introverted individuals tend to favor meaningful one-on-one interactions over participating in large-group social activities. This communication style may limit their ability to establish broad social connections and access support, thereby reducing their level of self-advocacy [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIndividuals without a family history of breast cancer were more likely to be classified into the moderate self-advocacy\u0026mdash;social support-deficient group. It is consistent with Pegington's research results [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. These individuals may be less focused on disease prevention and early intervention, which could result in a lack of sufficient self-advocacy awareness when facing health issues. Additionally, support networks within their social circles are often built around shared health concerns, leading to a weaker social support system. This suggests that healthcare providers should pay closer attention to patients with lower educational levels, introverted personalities, and no family history of breast cancer. For these patients, providing visually enriched health education materials, along with positive feedback and encouragement, can help enhance their confidence and ability to manage their health.\u003c/p\u003e \u003cp\u003eThe results of the logistic regression analysis indicated that individuals with medical insurance coverage were more likely to be classified into the High Advocacy\u0026ndash;Balanced Group. The medical insurance system typically involves clear reimbursement procedures and standardized medical services, which provide transparency, enabling patients to better understand their rights and financial responsibilities in the healthcare process. This clarity allows for more informed decision-making, a finding consistent with the research of Crespo-Gonzalez [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHigher levels of self-efficacy were significantly associated with membership in the High Advocacy\u0026ndash;Balanced group. As a foundational construct of Bandura\u0026rsquo;s Social Cognitive Theory, self-efficacy reflects an individual\u0026rsquo;s belief in their capacity to exert control over their actions and environment. It is widely recognized as a critical determinant of health behavior change and sustainability. Individuals with strong self-efficacy are more likely to regulate their emotions, adopt and maintain health-promoting behaviors, and navigate health-related challenges effectively, thereby enhancing both disease management and overall quality of life. These findings suggest that healthcare professionals should actively support patients in setting realistic goals, developing action plans, and participating in tailored treatment and rehabilitation strategies. Such efforts may foster a greater sense of agency and motivation, ultimately strengthening self-advocacy behaviors throughout the care continuum[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eStudy limitations\u003c/h2\u003e \u003cp\u003eThis study has several limitations that warrant consideration. First, the use of a small, single-center sample and convenience sampling restricts the generalizability of the findings, limiting their applicability to broader populations across different regions or healthcare settings. Second, due to the complexity of the relationships among influencing factors, this study was unable to elucidate the pathways or establish causal links between variables. Third, the study did not include post-discharge follow-up, making it difficult to assess how patients' self-advocacy levels may change over time. Future research should adopt a longitudinal design to examine the trajectory of self-advocacy across various stages of recovery and to better understand the dynamic interplay of contributing factors.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eClinical implications\u003c/h2\u003e \u003cp\u003eIn our study, we identified three self-advocacy subgroups among postoperative breast cancer patients and examined the factors influencing these groups. Based on these findings, we recommend that healthcare providers focus on patients with lower educational levels, those who opt for out-of-pocket or public health insurance, individuals without a family history of breast cancer, introverted personalities, and low self-efficacy. These patients may have weaker self-advocacy abilities during the diagnostic stage. These findings and recommendations provide a foundation for clinical intervention and healthcare policy improvements, facilitating the development of targeted interventions tailored to the specific needs of different patient groups and ultimately enhancing patients' autonomy in health management and improving their quality of life.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study based on latent profile analysis, divides post-surgical self-advocacy in breast cancer patients into three categories. It identifies factors such as education level, healthcare payment methods, family history, personality traits, and self-efficacy as key influences on self-advocacy. Consequently, healthcare providers can offer targeted health education. Our findings advocate for stratified interventions: For the Low Advocacy-Self-Reliant Group, enhancing communication skills through role-playing exercises may be prioritized, whereas the Moderate Advocacy-Low Support Group may benefit from social support networks and health literacy programs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003eThe authors would like to thank the Guangdong Pharmaceutical University and Guangdong Provincial Hospital of Traditional Chinese Medicine for their support of the study site, and the patients for their selfless help.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u0026nbsp;\u003c/strong\u003eJing Chen: Writing-review \u0026amp; editing, Writing-original draft, Formal analysis, Data curation, Conceptualization. Shuyi Zhu: Formal analysis, Data curation, Conceptualization. Yanxin Xu: Investigation, Data curation. Jiawen Huo: Investigation, Data curation. Rui Li: Investigation, Data curation. Xuan Ren: Investigation, Data curation. Shuhua Ye: Investigation, Data curation. Aoxiang Luo: Writing-review \u0026amp; editing, Supervision, Project administration, Funding acquisition, Conceptualization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis work was supported by the Guangzhou Civil Affairs Science and Technology Fund [grant number:2021MZK34], the Guangdong Provincial Continuing Education Quality Improvement Project [grant number: JXJYGC2022GX164], and the Guangdong Provincial Joint Training Graduate Demonstration Base [grant number: Yue JiaoYan Han [2024] 1-57].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u0026nbsp; All members of the research team can view and use all data from the study. Data can be provided to the publisher from the corresponding author.\u003c/p\u003e\n\u003cp\u003eEthical approval The researchers strictly followed the Declaration of Helsinki during the study. The research has been reviewed and approved by the Ethics Committee of Guangdong Provincial Hospital of Traditional Chinese Medicine (reference number: YE2023-321-01). Participants were informed in detail about the purpose of the study, methodology, and content, etc. Participants were also assured that they could withdraw at any time during the study and that there would be no impact on their follow-up care. Participant data remained anonymous, were kept by the researcher, and were not given to others.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u0026nbsp; All of the participants provided Informed consent in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publicatio\u003c/strong\u003en \u0026nbsp;All of the authors approved the final paper for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u0026nbsp; The authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBashar, M.D.A., Begam, N. (2022) Breast cancer surpasses lung cancer as the most commonly diagnosed cancer worldwide. Indian J. Cancer 59, 438\u0026ndash;439. https://doi.org/10.4103/ijc.IJC-83-21\u003c/li\u003e\n\u003cli\u003eKashyap, D., Pal, D., Sharma, R., Garg, V.K., Goel, N., Koundal, D., et al. 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(2007) Performance of Factor Mixture Models as a Function of Model Size, Covariate Effects, and Class-Specific Parameters. Struct. Equ. Model. 26-47.\u003c/li\u003e\n\u003cli\u003eHe Li et al. (2023) Analysis of the Current Situation and influencing Factors of Self-advocacy Ability of Breast Cancer patients undergoing Chemotherapy. Chin. J. Nurs. 788-793.\u003c/li\u003e\n\u003cli\u003eHagan, T.L., Donovan, H.S. (2013) Self-advocacy and cancer: a concept analysis. J. Adv. Nurs. 69, 2348\u0026ndash;2359. https://doi.org/10.1111/jan.12084\u003c/li\u003e\n\u003cli\u003eThomas, T.H., Donovan, H.S., Rosenzweig, M.Q., Bender, C.M., Schenker, Y. (2021) A Conceptual Framework of Self-advocacy in Women With Cancer. ANS Adv. Nurs. Sci. 44, E1\u0026ndash;E13. https://doi.org/10.1097/ANS.0000000000000342\u003c/li\u003e\n\u003cli\u003eCalderon, C., Gomez, D., Carmona-Bayonas, A., Hernandez, R., Ghanem, I., Gil Raga, M., et al. (2021) Social support, coping strategies and sociodemographic factors in women with breast cancer. Clin. Transl. Oncol. Off. Publ. Fed. Span. Oncol. Soc. Natl. Cancer Inst. Mex. 23, 1955\u0026ndash;1960. https://doi.org/10.1007/s12094-021-02592-y\u003c/li\u003e\n\u003cli\u003ePegington, M., Davies, A., Mueller, J., Cholerton, R., Howell, A., Evans, D.G., et al. (2022) Evaluating the Acceptance and Usability of an App Promoting Weight Gain Prevention and Healthy Behaviors Among Young Women With a Family History of Breast Cancer: Protocol for an Observational Study. JMIR Res. Protoc. 11, e41246. https://doi.org/10.2196/41246\u003c/li\u003e\n\u003cli\u003eCrespo-Gonzalez, C., Benrimoj, S.I., Frommer, M., Dineen-Griffin, S. (2024) Navigating online health information: Insights into consumer influence and decision-making strategies-An overview of reviews. Digit. Health 10, 20552076241286815. https://doi.org/10.1177/20552076241286815\u003c/li\u003e\n\u003c/ol\u003e\n"}],"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":"Breast cancer, Self-advocacy, Postoperative, Latent profile analysis, Influencing Factors","lastPublishedDoi":"10.21203/rs.3.rs-6632387/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6632387/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThis study aimed to identify latent profiles of self-advocacy among post-surgical breast cancer patients and to explore associated influencing factors, thereby providing a basis for targeted interventions.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 350 post-surgical breast cancer patients were recruited through convenience sampling at Guangdong Provincial Hospital of Traditional Chinese Medicine between July 2023 and May 2024. Participants completed a demographic questionnaire, the Self-Advocacy Scale for Female Cancer Patients, the Breast Cancer Survivor Self-Efficacy Scale, and the Family Avoidance of Cancer Communication Scale. Latent profile analysis (LPA) was conducted using Mplus 8.3, with 18 items from the self-advocacy scale serving as observed indicators. Multinomial logistic regression was performed to identify factors associated with profile membership.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThree distinct self-advocacy profiles were identified: Low Advocacy-Self-Reliant Group (39.2%), Moderate Advocacy-Low Support Group (19.7%), and High Advocacy-Balanced Group (41.1%). Multivariate analysis revealed that education level, personality traits, type of medical insurance, family history of breast cancer, and self-efficacy significantly influenced profile membership (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eDeveloping tailored interventions based on patients\u0026rsquo; self-advocacy profiles may enhance engagement in treatment decision-making and support improved clinical outcomes.\u003c/p\u003e","manuscriptTitle":"Self-Advocacy and Influencing Factors in Post-Surgical Breast Cancer Patients: A Latent Profile Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-02 09:23:34","doi":"10.21203/rs.3.rs-6632387/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":"31c8608e-65c6-4d79-aa00-121938300b84","owner":[],"postedDate":"July 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-17T23:23:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-02 09:23:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6632387","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6632387","identity":"rs-6632387","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}