Navigating life Post-Cancer Diagnosis in women: Symptom Clusters and Influencing Factors

Navigating life Post-Cancer Diagnosis in women: Symptom Clusters and Influencing Factors | 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 Navigating life Post-Cancer Diagnosis in women: Symptom Clusters and Influencing Factors Huyen Thi Hoa Nguyen, Duc Trung Duong, Tran Ngoc Tran, Anh Chau Nguyen, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4817858/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 Aims : 1) To identify symptom clusters in Vietnamese women with cancer and 2) to examine the factors influencing those identified clusters. Method : This cross-sectional study was conducted in 5 hospitals across Vietnam from September to December 2023. A total of 217 valid data sets from women with cancer were included. The symptom clusters were identified by exploratory factor analyses. Results : Fatigue and appetite loss were recognized as the most common symptoms. The exploratory factor analysis showed two distinct groups of factors, occupying 54.66% of total variance: fatigue, appetite loss, pain, sleep issues, hair loss, nausea, and sexual issues (Factor 1 – physical cluster) and mood issues, personal stress, depression, and anxiety (Factor 2 – psychological cluster). In terms of factors influencing two clusters, smoking demonstrated a marginally non-significant negative association with Factor 1 - physical health (R 2 =1.44%), while physical activity illustrated a significant negative association with Factor 2 - mental health (R 2 = 7.25%). Conclusions : The physical and psychological symptom clusters underlay symptom experiences complexity. Tailored interventions from healthcare providers are required to enhance patients’ outcomes and quality of life. symptom clusters influencing factors cancer women Vietnam I. INTRODUCTION Cancer in worldwide and Vietnam Cancer continues to be a global health challenge, with its incidence rate surpassing 19.9 million cases by 2022 (Ferlay et al., 2024). This escalating worldwide burden is influenced by population growth, aging, lifestyle changes, disparities in access to healthcare, and other factors (The American Cancer Society, 2019). While cancer impacts are across diverse populations, women bear a disproportionate burden of the disease in prevention, diagnosis, and supportive care services. In Southeast Asia, the 2022 diagnosis of over 1 million cancer cases underscores the severity; notably in Vietnam, with breast, lung, and colorectal cancers being predominant among Vietnamese women (Ferlay et al., 2024). Socioeconomic elements, cultural beliefs, and geographic barriers may contribute to delayed care-seeking in cancer outcomes among women in this country (Petersen et al., 2022). Cancer treatment disrupts lifestyle and mental health, with cultural beliefs and social support guiding coping (Nguyen et al., 2024), family duties and relationships shaping caregivers' strategies (Xuan Long et al., 2020), and religious values influencing how women communicate pain and coping methods (Nguyen, 2018). This underscores the importance of gender-specific cancer research and interventions for this particular population, emphasizing the need for increased attention to women's groups to ensure gender equality in cancer care provision. Symptom clusters in cancer Symptom clusters are the co-occurrence of two or more interrelated symptoms that may share common mechanisms (Fan et al., 2007; Kim et al., 2005; Kirkova et al., 2011), with a sentinel symptom playing a key role in predicting related symptoms (Rha et al., 2019), and the cluster's stability defined by its enduring nature and symptom consistency (Nguyen & Nguyen, 2022). For instance, heightened fatigue levels may exacerbate pain, sleep disturbances, and emotional distress within a cluster (Rha et al., 2019). Exploring these "symptom clusters" provides insights for unified interventions, conserving resources, and mitigating healthcare costs while elevating the overall quality of care and life for affected individuals (Nguyen & Nguyen, 2022). Given that symptoms of cancer are experienced differently by males and females (Chueng, 2011; Oertelt-Prigione, 2021), it is essential to examine symptom clusters through a gender-specific lens. The variability of measurement tools for assessing symptom clusters has introduced inconsistencies across studies, emphasizing the need for further research to facilitate a systematic review and the development of a unified symptom cluster framework. In Vietnam, the escalating cancer incidence witnessed a threefold increase over the past 30 years, which accentuates the urgency to explore symptom clusters comprehensively (Pham et al., 2019). In 2018, breast and cervical cancers, specifically affecting women, accounted for a total of 11.7% of cancer cases while the total cancer incidence was 164,671 in Vietnam (WHO, 2020). Despite the pervasive nature of interconnected symptoms or symptom clusters in cancer patients, Vietnam's symptom research has predominantly prioritized evaluating and mitigating individual symptoms (Nguyen et al., 2021; Pham et al., 2019). Moreover, there is a shortage of studies addressing symptom clusters among Vietnamese women with cancer. Our study thus assumes a pivotal role in bridging this knowledge gap, aiming to contribute meaningful insights to the existing body of research and data pool. Our primary objectives are to: 1. Identify symptom clusters in women with cancer in Vietnam; and 2. Analyze the factors influencing identified symptom clusters. This research not only sheds light on the specific challenges faced by Vietnamese women with cancer-related symptoms but also lays the groundwork for targeted interventions. By doing so, our findings aim to inform tailored interventions, ultimately easing the overall quality of life and treatment outcomes for women dealing with cancer in Vietnam's unique context. II. METHOD Sample and Setting A cross-sectional study was conducted with a convenience sample of women living and beyond cancer in 5 hospitals across Vietnam from September to December 2023. The inclusion criteria for women included (1) Vietnamese women who able to speak and write in Vietnamese and living in Vietnam at the time participating in the project (2) >18 years-old (3) be diagnosed with at least one type of cancer or have been finished cancer treatment (4) willingness to participate in this study. The study excluded those who are diagnosed with mental illness. The sample size will be calculated (just used for target population) which is based the formula N ≥104 + m (m: number of independent variables). There are 10 independent variables; therefore, the minimum required sample size is 114 (Kupper & Hafner, 1989). In total, we collected 318 cancer women who was eligible and participated in the study. After data cleaning with removing incomplete questionnaires, inconsistent provided information, and duplicate entries, we obtained a total of 217 participants. Measures Demographic characteristics Demographic information included age, gender, living area, religion, level of education, employment, personal income per month, and family member support. Clinical information including medical and family history related to cancer were collected. In addition, some behavioral and lifestyle characteristics were also asked such as smoking, type of exercise, sleeping disturbances, and strategies used to monitor and manage symptoms. Assessing symptoms The number of physical and psychological symptoms were collected including pain, fatigue, insomnia, nausea/vomiting, appetite loss, hair loss, sexual issue, mood issues. Symptoms are reflected with the frequency from “never” to “always”. The score of each statement is evaluated on a 5-level Likert scale, with 0-never, 1-rarely, 2-occasionally, 3-sometimes, 4-usually, 5-always. Visualized Pain Scale (VPS) Participants' pain levels were evaluated using the Visualized Pain Scale, a popular pain rating scale that available in 13 different languages, including Vietnamese (The British Pain Society, 2014). The VPS has a 10-point scale ranging from 0 to 10, with higher scores indicating higher pain levels. Karnofsky Performance Status Scale The Karnofsky Performance Status Scale was used widely to measure the level of functional capacity in patients living with cancer. The KPS has been used in Vietnamese clinical settings for oncology patients (Pham et al., 2017; Thi et al., 2024). This scale rates the level of functional capacity on a scale from 20% to 100%, with higher percentages indicating better functional performance status. Mental Health (PHQ-9 and GAD-7) Patient Health Questionnaire (PHQ-9) Patient Health Questionnaire (PHQ-9) was used to screen for depression in cancer women (Kroenke et al., 2001; Spitzer et al., 1999). This instrument can assess depressive symptoms and suggest grade depressive symptom severity and has been indicated a Cronbach's alpha of 0.7 to 0.8 (Mughal et al., 2021; Phi et al., 2023). Levels of depression severity will be rated according to PHQ-9 score with minimal level (grade from 0 to 4), Mild level (from 5 to 9), Moderate level (from 10-14), Moderately severe (from 15 to 19), and severe level of depression (from 20 to 27). General Anxiety Disorder (GAD-7) General Anxiety Disorder (GAD-7) was used to assess the anxiety (Spitzer et al., 2006). The GAD-7 has been validated in Vietnam with Cronbach alpha of 0.91 (Mughal et al., 2021). Seven items in GAD-7 designed to self-report the anxiety of an individual during the previous 2 weeks will be rated from 0 to 3, corresponding to “not at all,” “several days,” “more than half the day,” and “nearly every day,” respectively. The total score will be summed and range from 0 to 21. The cut-off points for mild, moderate, and severe anxiety are represented as 5, 10, and 15, respectively. Perceived stress scale (PSS-10) The Vietnamese version of the Perceived Stress Scale (PSS-10) was used to assess the self-reported stress among participants (Cronbach’s alpha of 0.80) (Dao-Tran et al., 2017). Participants were asked how often they experience thoughts and feelings during the last months through 10 items. Each item is responded from 0 (never) to 4 (very often). The scores will be aggregated, and the possible total score ranges from 0 to 40. Higher total scores show a higher likelihood that environmental demands exceed the ability to cope with individuals. Procedures The study was approved by the Scientific Council, Ethics Council in Biomedical Research, Vinmec international general hospital (No.75/2022/QD-VMEC dated July 26, 2022). The researchers obtained a list of women with cancer who had received treatment at the selected hospitals, along with their contact information (usually phone numbers). Eligible participants were invited to participate in the study through phone calls or in-person invitations at the hospital. Participants who agreed to participate and met the inclusion criteria were provided with an information sheet about the study and a consent form. After obtaining written consent, participants completed the survey questionnaire in the presence of the investigator. The data collection process took approximately 15 minutes per participant. If doubts arose regarding the interpretation of the instructions, the investigator would assist them. After the questionnaire was completed, it was immediately collected by the administering investigator. Statistical Analysis Data analyses were conducted using IBM SPSS version 26.0. Demographic information, clinical characteristics, and symptom incidence and severity were analyzed using descriptive statistical methods. Exploratory factor analysis was used to extract symptom clusters, and univariate analyses and multiple linear regression analyses were performed to explore factors affecting symptom clusters. Structural equation modeling (SEM) using AMOS version 20, with maximum likelihood estimation, was used to test the hypothesized model. The criteria used to appraise the structural model were model fit indices, as well as the magnitude and direction of path estimates (Hair et al. 1998). The fit indices that were used to evaluate the proposed model were normed Chi-square (χ2/df), Goodness-of-Fit Index (GFI), Adjusted Goodness-of-Fit Index (AGFI), Comparative Fit Index (CFI), Tucker Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA) and Root Mean Square Residual (RMR) (Byrne 2013; Hair et al. 2014; Kline 2011). Following the recommendation by Byrne (2013) and Kline (2011), the model was considered to have an adequate fit when the χ2/df ratio was 0.90 and both RMSEA and RMR values were < 0.08. III. RESULTS Characteristics of the study’s participants Table1. Demographic and clinical characteristics Variables Categories n % Age (Mean±SD) 55.01±12.45 Place of residence Urban 110 50.69 Rural/Mountainous 107 49.31 Religion No 181 83.41 Buddhism 23 10.6 Catholic 13 5.99 Education level Elementary 14 6.45 Middle School 46 21.2 High School 52 23.96 College 105 48.39 Occupation Not employed 42 19.35 Blue collar (farmers, vendors, construction workers, laborers, etc.) 86 39.63 White collar (teachers, healthcare professionals, office workers, military personnel, etc.) 89 41.01 Marital status Single 11 5.07 Divorced/Widowed 19 8.76 Married/Living as married 187 86.18 Yes 205 94.47 Chronic diseases (e.g., hypertension, diabetes, liver disease, kidney disease) No 157 72.35 Yes 60 27.65 Smoking No 213 98.16 Yes 4 1.84 Physical activities No 55 25.35 Yes 162 74.65 Family history of cancer No 158 72.81 Yes 59 27.19 Current treatment therapy Surgery 76 35.02 Chemotherapy 126 58.06 Radiotherapy 41 18.89 Immunotherapy 5 2.3 Hormone therapy 30 13.82 Others 49 22.58 Methods used to monitor and manage symptoms of the disease No 17 7.83 Regular health check-ups 192 88.48 Technological devices (smartphones, smartwatches, etc.) 8 3.69 Online support (online forums, Facebook groups, etc.) 6 2.76 Total 217 100 A total of 217 cancer patients were included in the study. The mean age of the participants was 55.01 ± 12.45 years. The majority were residents of urban areas (50.69%). In terms of religion, 83.41% reported no religion, while 10.6% identified as Buddhist and 4.15% as Catholic. Regarding education level, 48.39% had a college education, followed by 23.96% with a high school education. Occupationally, 41.01% were engaged in intellectual labor, while 39.63% were involved in manual labor. Marital status indicated that 86.18% were married or living as married. A significant portion of participants (72.35%) reported no chronic diseases. The majority were non-smokers (98.16%) and non-drinkers (98.62%). Regarding physical activity, 74.65% engaged in such activities. Additionally, 27.19% reported a family history of cancer. In terms of treatment, the majority underwent chemotherapy (58.06%), followed by surgery (35.02%). The most common method used to monitor and manage symptoms was regular health check-ups (88.48%). More details are displayed in Table 1. Understanding the demographic characteristics establishes a foundation for examining the prevalence of symptoms among participants and their impact on mental health. Prevalence of Symptoms among the study ’s participants Table 2. Prevalence of Symptoms N % Never Rarely (1 time/week) Sometimes (1-2 times/week) Often (3-4 times/week) Usually (5-6 times/week) Always Total Fatigue 49 47 54 38 17 12 217 22.58 21.66 24.88 17.51 7.83 5.53 100 Appetite loss 80 41 46 30 9 11 217 36.87 18.89 21.2 13.82 4.15 5.07 100 Pain 76 58 35 27 11 10 217 35.02 26.73 16.13 12.44 5.07 4.61 100 Sleep disturbances 57 42 46 33 23 16 217 26.27 19.35 21.2 15.21 10.6 7.37 100 Hair loss 77 31 32 18 19 40 217 35.48 14.29 14.75 8.29 8.76 18.43 100 Nausea 113 46 30 14 5 9 217 52.07 21.2 13.82 6.45 2.3 4.15 100 Sexual issue 130 42 24 6 4 11 217 59.91 19.35 11.06 2.76 1.84 5.07 100 Mood issue 110 42 26 16 16 7 217 50.69 19.35 11.98 7.37 7.37 3.23 100 Table 2 illustrates the prevalence of symptoms, anxiety levels, depression levels, and personal stress among the participants. Fatigue and sleep disturbances were reported most frequently, with fatigue being the most prevalent symptom, affecting 77% and 73% participants, respectively. Other common reported symptoms including pain (65%) and appetite loss (63%). Understanding which symptoms are most common lays the groundwork for examining how these symptoms intersect with participants' mental health challenges. Frequency of Mental Health issues among the study participants Table 3. Frequency of Mental Health issues N (n=217) Percentage Anxiety (GAD-7) None or minimal anxiety 181 83.41 Mild anxiety 25 11.52 Moderate anxiety 8 3.69 Severe anxiety 3 1.38 Depression (PHQ-9) None or minimal depression 162 74.65 Mild depression 39 17.97 Moderate depression 10 4.61 Moderately severe depression 4 1.84 Severe depression 2 0.92 Personal stress (PSS) Low stress 75 34.56 Moderate stress 142 65.44 High perceived stress 0 0 Regarding mental health, the majority of participants experienced none or minimal anxiety (83.41%) and none or minimal depression (74.65%). However, mild anxiety (11.52%) and mild depression (17.97%) were also prevalent. A smaller percentage reported moderate to severe levels of anxiety and depression. Additionally, in terms of personal stress, the majority of participants reported moderate stress (65.44%), while a notable portion reported low stress (34.56%), as presented in Table 3. These mental health findings highlight the need to explore how various symptoms interact and cluster, further influencing patients' psychological well-being. Identifying symptom clusters Table 4. Factor analysis of symptom clusters Symptom Factor 1 Factor 2 Fatigue 0.7993 Appetite loss 0.8139 Pain 0.6747 Sleep issue 0.6318 Hair loss 0.6884 Nausea 0.7570 Sexual issue 0.5062 Mood issue 0.5231 Personal stress 0.5696 Depress 0.7610 Anxiety 0.8331 Varian contribution rate, % 35.66 19.00 Cronbach’s Alpha 0.8345 0.6102 Factor loading >0.5 To extract symptom clusters, we utilized Exploratory Factor Analysis (EFA) with principal components and maximum variance rotation method. A total of 11 items were included in the EFA, with an occurrence rate of ≥25%. Tests for the suitability of structure detection showed a Kaiser-Meyer-Olkin value of 0.822 and a Bartlett test with P < 0.001, indicating the data were suitable for EFA. Cronbach’s α was calculated for each factor to evaluate the internal consistency of the symptom clusters. A Cronbach’s α of 0.7 or higher represents good consistency validity. In this study, variables with factor loadings less than 0.5 were excluded, as statistically, a correlation lower than that would produce too many factors in factor analysis. A common practice in factor analysis is to retain only those factors with eigenvalues greater than one (Kaiser, 1960; Costello & Osborne, 2005). This criterion suggests that a factor must explain more variance than a single observed variable would on its own. Essentially, an eigenvalue greater than one indicates that the factor accounts for a significant portion of the total variance in the data, justifying its inclusion in the final model. In this study’s analysis, two distinct factors with eigenvalues greater than 1.00 were retained, accounting for 54.66% of the total variance. Factor loadings represent the correlation between observed variables and their underlying factors; thus, higher loadings indicate a stronger relationship. The 0.5 factor loading threshold was selected to ensure that each item contributes meaningfully to its respective factor, enhances the clarity and reliability of the identified symptom clusters, and minimize cross-loadings (Hair et al., 1998; MacCallum et al., 1999; Stevens, 1992). Factor 1 included fatigue, appetite loss, pain, sleep issues, hair loss, nausea, and sexual issues, with a variance contribution rate of 35.66% and a Cronbach’s α of 0.8345, indicating high internal consistency. Factor 2 comprised mood issues, personal stress, depression, and anxiety, with a variance contribution rate of 19.00% and a Cronbach’s α of 0.6102, reflecting moderate reliability. These findings delineate two main symptom clusters: the physical cluster (Factor 1) and the psychological cluster (Factor 2). This distinction aids in comprehending the different dimensions of symptom experiences and can inform targeted approaches for treatment or intervention. With these clusters identified, it is essential to explore the factors influencing their formation and severity. Factors influencing symptom clusters Table 5. Bivariate Analysis of the Factors on Symptom Clusters Factor 1 (χ 2 ) Factor 2 (χ 2 ) Age -0.0233** 0.0960** Place of residence 3,953 4,046 Religion 2,146 6,513 Education level 7,793 5,519 Occupation 2,618 7,066 Marital status 8,822 9,097 Chronic diseases (e.g., hypertension, diabetes, liver disease, kidney disease) 4,082 6,690 Smoking 9,922* 1,428 Physical activities 4,961 16,404* Family history of cancer 2,171 6,077 *p<0.05 ** Spearman’s rank test A spearman's rank test was employed to analyze the two clusters concerning age. The Kruskal-Wallis H rank sum test was utilized to assess whether other demographic characteristics (such as place of residence, religion, education level, occupation, and marital status) and past medical, social, and family history (including chronic diseases, smoking, physical activities, and family history of cancer) were correlated with the symptom clusters (Table 5). Factor 1, the physical symptom cluster, showed a significant negative association with age (χ2 = -0.0233, p < 0.01) and a significant positive association with smoking (χ2 = 9.922, p < 0.05). Physical activity also had a significant impact on Factor 1 (χ2 = 4.961, p < 0.05). In contrast, Factor 2, the psychological symptom cluster, was significantly influenced by age (χ2 = 0.0960, p < 0.01) and physical activity (χ2 = 16.404, p < 0.05). Other factors such as place of residence, religion, education level, occupation, marital status, chronic diseases, and family history of cancer were analyzed, but only those with significant associations are highlighted here. These findings highlight the complex interplay of demographic, lifestyle, and clinical factors in shaping symptom experiences, paving the way for personalized approaches to symptom management. Table 6. Multiple Linear Regression Analysis of the Factors on Symptom Clusters Factor 1 Factor 2 Variable B (SE) β t p Tolerance VIF B (SE) β t p Tolerance VIF (Constant) 0.425 (1.040) — 0.409 0.683 — — 1.257 (1.015) — 1.238 0.217 — — Age 0.00005 (0.007) 0.001 0.008 0.994 0.63 1.587 0.013 (0.007) 0.156 1.898 0.059 0.63 1.587 Place of residence 0.318 (0.156) 0.159 2.037 0.043 0.734 1.363 -0.155 (0.152) -0.078 -1.021 0.309 0.734 1.363 Religion 0.054 (0.115) 0.033 0.466 0.642 0.893 1.12 0.031 (0.112) 0.019 0.277 0.782 0.893 1.12 Education level -0.038 (0.094) -0.037 -0.404 0.687 0.543 1.842 -0.032 (0.092) -0.031 -0.35 0.727 0.543 1.842 Occupation 0.263 (0.112) 0.197 2.349 0.02 0.639 1.566 -0.007 (0.109) -0.005 -0.067 0.947 0.639 1.566 Marital status -0.245 (0.136) -0.124 -1.797 0.074 0.945 1.058 0.154 (0.133) 0.078 1.158 0.248 0.945 1.058 Chronic diseases -0.051 (0.160) -0.023 -0.321 0.749 0.866 1.154 -0.328 (0.157) -0.147 -2.094 0.037 0.866 1.154 Smoking -1.203 (0.613) -0.162 -1.962 0.051 0.655 1.527 -0.121 (0.599) -0.016 -0.202 0.84 0.655 1.527 Alcohol consumption 0.526 (0.708) 0.062 0.744 0.458 0.652 1.533 -0.476 (0.691) -0.056 -0.689 0.492 0.652 1.533 Physical activities 0.007 (0.158) 0.003 0.043 0.966 0.945 1.059 -0.599 (0.154) -0.261 -3.887 <0.001 0.945 1.059 R-square = 0.077 R-square = 0.120 The multivariate regression analysis revealed that Factor 1 was significantly influenced by place of residence (B = 0.318, p = 0.043) and occupation (B = 0.263, p = 0.020), with marital status (B = -0.245, p = 0.074) showing a marginal effect. Smoking was also approaching significance (B = -1.203, p = 0.051). The R-squared for Factor 1 was 0.077, indicating that the model explains 7.7% of the variance in Factor 1. For Factor 2, physical activity (B = -0.599, p < 0.001) and chronic diseases (B = -0.328, p = 0.037) were significant predictors, while age (B = 0.013, p = 0.059) showed a marginally significant effect. The R-squared for Factor 2 was 0.120, indicating that the model accounts for 12% of the variance in Factor 2. Other variables such as education, alcohol consumption, and smoking did not significantly impact either factor (p > 0.05). All VIF values are below the threshold of 5, and Tolerance values are above 0.2, indicating that the predictor variables are not excessively correlated with one another. Table 7. Structural Equation Modeling (SEM) for Factor Structure of Symptom Clusters χ2 df p χ2/df GFI AGFI CFI TLI RMSEA RMR Model 149.641 43 .000 3.480 .896 .840 .884 .852 .107 .169 The model shows a reasonable fit with a χ²/df of 3.480, which is acceptable, but could be improved. The GFI (0.896), AGFI (0.840), CFI (0.884), and TLI (0.852) are slightly below the ideal 0.90 threshold, indicating a suboptimal fit. The RMSEA value of 0.107 suggests a mediocre fit, and the RMR value of 0.169 indicates moderate residuals. Overall, while the model is acceptable, there is room for improvement in the fit indices. IV. DISCUSSION This study revealed that fatigue, appetite loss, and pain were among the most prevalent symptoms experienced by the participants. Fatigue was reported by the majority, with varying degrees of frequency, followed closely by appetite loss and pain. These findings are consistent with existing literature, underscoring the pervasive nature of these symptoms in cancer patients (Chueng, 2011; Oertelt-Prigione, 2021). The prevalence of symptoms identified in our study aligns with findings from several other studies in the oncology field. Specifically, the high prevalence of fatigue, reported by the majority of our participants, is consistent with results from a systematic review, the findings of which revealed fatigue-sleep disturbance to be a predominant symptom among breast cancer patients across various treatment stages (So et al., 2021). This underscores the pervasive nature of fatigue as a significant burden for cancer patients, necessitating focused interventions. Similarly, our findings regarding appetite loss and pain are in line with previous research. For example, Coleman et al. (2022) identified pain interference as a key component of the SPADE (sleep disturbance, pain interference, anxiety, depression, and energy/fatigue) symptom cluster among cervical cancer survivors (Coleman et al., 2022). Appetite loss, although not as frequently highlighted as fatigue or pain in some studies, was nonetheless significant in our cohort, reflecting the complex interplay of treatment side effects and overall health status in cancer patients. In the multivariate regression analysis, the findings show that place of residence and occupation significantly influenced physical symptoms, with urban living and white-collar occupations associated with fewer physical symptoms. Symptom clusters varied with work status including environmental and occupational contexts, highlighting the impact of daily routines and stressors on physical health (Browall et al., 2017). For psychological symptoms, physical activity and chronic diseases were significant predictors, with active individuals and those without chronic conditions reporting fewer psychological symptoms. This supports Liska (2020) and Luo et al. (2023), who found a relationship between physical activity and emotional well-being in breast cancer patients and advocates for physical activity as a beneficial intervention for enhancing mental health among cancer survivors. Interestingly, while age showed a marginally significant effect on both factors, it did not reach statistical significance in this analysis. This finding diverges from studies that have consistently reported age as a significant factor affecting symptom burden in cancer populations (Oertelt-Prigione et al., 2021). The R-squared values indicate that while these models explain a modest portion of the variance in symptom clusters—7.7% for Factor 1 and 12% for Factor 2—the results still emphasize the complexity of symptom experiences and suggest that additional unmeasured factors may also play a role. Moreover, the absence of significant associations for variables such as education and smoking contrasts with some prior studies that highlighted their relevance in determining symptom severity (Nguyen & Nguyen, 2022; Pham et al., 2019). This discrepancy may reflect cultural differences or variations in how these factors interact within different populations. Through exploratory factor analysis, our study identified two main symptom clusters: physical and psychological. The physical symptom cluster included fatigue, appetite loss, pain, sleep issues, hair loss, nausea, and sexual issues, indicating a high internal consistency. The psychological symptom cluster comprised mood issues, personal stress, depression, and anxiety, reflecting moderate reliability. Our study's identification of distinct physical and psychological clusters aligns well with the broader literature, which frequently highlights the necessity of addressing both domains for effective symptom management. Luo et al. (2023) further elucidated the multidimensional nature of symptom clusters in their prospective study, identifying GI symptoms, emotional & psychological symptoms, neurological symptoms, menopausal symptoms, and self-image disorder among breast cancer patients (Luo et al., 2023). Our study's clustering of physical symptoms similarly reflects this multidimensionality, albeit focusing on different specific symptoms. The distress caused by the emotional symptom cluster, characterized by worry, difficulty concentrating, and sadness, which aligns closely with our psychological cluster findings (Browall et al., 2017). However, our findings differ slightly in that we separated physical and psychological symptoms into distinct clusters, whereas some studies have identified more mixed clusters. For instance, Zhou et al. (2023) identified multiple symptom clusters in cervical cancer patients' post-radiotherapy/chemotherapy, including combinations of psycho-emotion-related and pain-disturbed sleep-related clusters (Zhou et al., 2023). This suggests an understanding of symptom interrelationships, which can vary depending on the patient population and cancer type. Interestingly, our study did not find a significant association between religion and mental health, which contrasts with previous research indicating that religion can positively affect mental health (Salsman, 2015; Kelly, 2022; AI Eid, 2020). This discrepancy may be due to cultural differences, the specific measures of religiosity used, or the unique stressors faced by our study population. Similarly, chronic diseases did not show a significant impact on physical health in our findings. This could be due to the potential for well-managed chronic conditions in our sample, or the overshadowing impact of cancer itself on physical health. The most notable finding from our study was the strong association between physical activity and the psychological symptom cluster. Our results show that the more physical activities there are, the fewer psychological issues are reported. This highlights the potential of physical activity as a critical intervention for improving mental health among women with cancer. Physical activity is known to enhance mood through various mechanisms, such as endorphin release, stress reduction, improved sleep quality, and increased social interaction. Therefore, intervention programs need to focus on incorporating physical activities to improve mental health outcomes for cancer patients (Liska, 2020). Tailored exercise programs; for example, the Women Wellness Program, Survivorship Wellness Group Program and other interventional programs with regular monitoring and support from healthcare providers are essential for maximizing the mental health benefits of physical activity (Anderson et al., 2017; Siwik et al., 2023). In contrast, our study did not find a significant influence of physical activity on the physical health factor. This might be due to the complexity of physical symptoms, which could be influenced by a myriad of factors beyond physical activity alone, such as the severity of the disease, treatment side effects, and other lifestyle factors. Although smoking and physical activity show statistically significant influences on symptom clusters in this study, the analysis indicates that these factors only explain a small proportion of the variance in symptom clusters. One of the reasons might be the questionnaire has not used a standard tool to assess these variables; therefore, the result should be considered and confirmed by future research. Lastly, previous studies have shown that a family history of cancer can affect mental health; however, this study did not find a significant association. Possible explanations could include differences in study populations, the specific types of family history considered, or other mitigating factors such as social support systems. This study has several strengths, including the comprehensive sample characteristics and the use of robust statistical methods such as Exploratory Factor Analysis (EFA) and multiple linear regression analysis. These methodologies provided reliable insights into the patterns and determinants of symptom experiences among a diverse sample of women living with and beyond cancer in Vietnam, enhancing the generalizability of the findings. However, the cross-sectional nature of the study limits the ability to infer causality and track symptom changes over time, highlighting the need for longitudinal studies. Potential biases, such as recall bias from self-reported data due to the absence of a validated questionnaire specifically designed for Vietnamese women with cancer, and the limitations of convenience sampling, may also affect the representativeness of the findings. The sample included participants with a range of cancers, allowing to capture a diverse range of symptom experiences. While this may cause heterogeneity in cancer population, this diversity is crucial as it can identify symptom clusters that are common across various cancer types, providing valuable insights into the general patterns of symptom co-occurrence in women with cancer, and be a reference for tailored interventions that consider the unique symptom profiles associated with each cancer type. With significant symptom clusters and influencing factors were identified, further longitudinal research is needed to confirm these findings, explore temporal relationships and examining how symptom clusters may vary across different cancer diagnoses and stages. Future research should focus on conducting longitudinal studies to monitor symptom progression and clustering over different stages of cancer treatment and survivorship. This will provide deeper insights into the persistence and evolution of symptoms, facilitating more effective and timely interventions. Additionally, exploring a broader range of demographic and clinical factors, such as genetic predispositions and specific cancer types, can help identify high-risk groups and tailor interventions more precisely. Interventional studies targeting the identified symptom clusters, such as randomized controlled trials (RCTs), could evaluate the efficacy of integrative care models combining pharmacological treatments, lifestyle modifications, and psychosocial support. Complementing quantitative findings with qualitative research, such as in-depth interviews and focus groups, can provide rich, contextual insights into the lived experiences of cancer patients, offering a more holistic understanding of symptom management needs and preferences. Addressing these research directions will advance the understanding of symptom experiences and enhance the quality of care for cancer patients, leading to better health outcomes and improved quality of life. V. CONCLUSION This study reveals the pervasive prevalence of fatigue, appetite loss, and pain among women living with and beyond cancer in Vietnam, aligning with similar findings in oncology literature. The primary objectives of this research were to identify distinct physical and psychological symptom clusters and to understand their implications for patient care. Recognizing these symptom clusters underscores the complexity of cancer-related experiences, illustrating the urgent need for tailored interventions that address both physical and psychological dimensions of care. Healthcare providers play a crucial role in developing personalized treatment plans based on these clusters, by integrating pharmacological, nutritional, and psychosocial interventions. Regular screening for symptoms using standardized tools facilitates early detection and intervention, improving patient outcomes and quality of life. Declarations Ethics approval and consent to participate : This study was conducted in accordance with the Declaration of Helsinki. Ethical approval was granted by the Institutional Ethical Review Board of Vinmec International General Hospital JSC – VinUniversity (No. 75/2022/QD-VMEC, dated 26 July 2022). All participants in the study have given informed consent to be involved in the study voluntarily and have the right to participate or not. Consent for publication : Not applicable Availability of data and materials : The datasets generated and/or analysed during the current study are not publicly available due to privacy and ethical restrictions but are available from the corresponding author on reasonable request. Competing interests : The authors declare that they have no competing interests. Funding : Not applicable Authors' contributions : H.T.H.N., T.N.T., A.C.N., M.H.H., Q.T.D., collectively contributed to the conceptualization and design of the study. H.T.H.N., T.N.T., A.C.N, M.H.H., Q.T.D., and T.H.T. were involved in the recruitment of participants and data collection. D.T.D. did the data analysis and result interpretations. D.Q.T. and H.T.X.H. provided oversight and critical feedback throughout the research process. H.T.H.N. led the drafting of the manuscript. All authors critically reviewed and revised the manuscript for important intellectual content. H.T.H.N. supervised the entire study. All authors approved the final version of the manuscript for submission. Acknowledgements : Not applicable References Al Eid, N. A., Alqahtani, M. M., Marwa, K., Arnout, B. A., Alswailem, H. S., & Al Toaimi, A. A. (2020). Religiosity, psychological resilience, and mental health among breast cancer patients in the Kingdom of Saudi Arabia. Breast cancer: basic and clinical research, 14, 1178223420903054. Anderson, D., Seib, C., Tjondronegoro, D., Turner, J., Monterosso, L., McGuire, A., Porter-Steele, J., Song, W., Yates, P., King, N., Young, L., White, K., Lee, K., Hall, S., Krishnasamy, M., Wells, K., Balaam, S., & McCarthy, A. L. (2017). 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J., Jhaveri, K., Jamie Alexis Cohen, Barulich, M., Chang, A., Levin, A. O., Goyal, N. G., Melisko, M., Chesney, M. A., & Shumay, D. (2023). Survivorship wellness: a multidisciplinary group program for cancer survivors. Supportive Care in Cancer, 31(11). https://doi.org/10.1007/s00520-023-08117-3 So, W. K., Law, B. M., Ng, M. S., He, X., Chan, D. N., Chan, C. W., & McCarthy, A. L. (2021). Symptom clusters experienced by breast cancer patients at various treatment stages: A systematic review. Cancer Medicine , 10 (8), 2531-2565. Stevens, J. P. (1992). Applied Multivariate Statistics for the Social Sciences (2nd ed.). Hillsdale, NJ: Erlbaum. The American Cancer Society. (2019). The Burden of Cancer. The Cancer Atlas. https://canceratlas.cancer.org/the-burden/the-burden-of-cancer/ The British Pain Society. (2014). Pain scales in multiple languages | British Pain Society . Britishpainsociety.org. https://www.britishpainsociety.org/british-pain-society-publications/pain-scales-in-multiple-languages/ Thi, T., Trinh, O. T., Do, D. V., Lin, C.-P., & Harding, R. (2024). Characteristics and health problems of cancer patients admitted to palliative care service at the Oncology Hospital in Ho Chi Minh City, Vietnam: a cross-sectional study. Y HOC TP HO CHI MINH , 8 (2), 90–103. https://doi.org/10.32895/ump.mpr.8.2.10 World Health Organization (WHO). (2020). Cancer Viet Nam 2020 country profile . https://www.who.int/publications/m/item/cancer-vnm-2020 Zhou, K.-n., Wang, Y., Xie, Y., Yang, S.-h., Liu, S.-y., Fang, Y.-h., & Zhang, Y. (2023). Symptom burden survey and symptom clusters in patients with cervical cancer: a cross-sectional survey. Supportive Care in Cancer , 31 (6), 338 Xuan Long, N., Bao Ngoc, N., Thi Phung, T., Thi Dieu Linh, D., Nhat Anh, T., Viet Hung, N., Thi Thang, N., Thi Mai Lan, N., Thu Trang, V., Hiep Thuong, N., Van Hieu, N., & Van Minh, H.. (2021). Coping strategies and social support among caregivers of patients with cancer: a cross-sectional study in Vietnam. AIMS Public Health , 8 (1), 1–14. https://doi.org/10.3934/publichealth.2021001 Nguyen, T. H. H.. (2018). Exploring the Association between Religious Values and Communication about Pain Coping Strategies: A Case Study with Vietnamese Female Cancer Patients. Theory and Practice in Language Studies , 8 (9), 1131. https://doi.org/10.17507/tpls.0809.04 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-4817858","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"","associatedPublications":[],"authors":[{"id":409664309,"identity":"b0a29c44-36a9-4fd6-a68b-830ed7f99ec7","order_by":0,"name":"Huyen Thi Hoa Nguyen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIie3RMQrCMBSA4SeCdXjimqLgFSJCq5NXKQhOGRRBnEQQegbFS+jiXHlQl+JcsYMgdOogdHSxShFFG3FzyD8kIeEjgQCoVH8Yfyy0CTjJjM+bUsI4Oj8TZr1f/TGTifqpB8HY1KM69e2gCtp0zXJ2kElaM9FozCBkrYXgNLdDBHSHCQmzH+YLo4JAjB+6FpVsQmDCYOCRjJiXO9m7KalFX4mRvxM/76S3YEJGEuKFgwpy0pdexyHcERawO2haMrLtrGIcUZlvN9MYh9Qua7TyzzybABT560cUboMlAQDaUXqsUqlUKrgCfrpQTy3aRX0AAAAASUVORK5CYII=","orcid":"","institution":"College of Health Sciences, VinUniversity, Hanoi, Vietnam","correspondingAuthor":true,"prefix":"","firstName":"Huyen","middleName":"Thi Hoa","lastName":"Nguyen","suffix":""},{"id":409665223,"identity":"378a8baa-ba7e-4676-aa6e-9ed0c440b34e","order_by":1,"name":"Duc Trung Duong","email":"","orcid":"","institution":"College of Health Sciences, VinUniversity, Hanoi, Vietnam","correspondingAuthor":false,"prefix":"","firstName":"Duc","middleName":"Trung","lastName":"Duong","suffix":""},{"id":409665754,"identity":"31569cea-05ad-4d70-960f-ce0c30b1e999","order_by":2,"name":"Tran Ngoc Tran","email":"","orcid":"","institution":"College of Health Sciences, VinUniversity, Hanoi, Vietnam","correspondingAuthor":false,"prefix":"","firstName":"Tran","middleName":"Ngoc","lastName":"Tran","suffix":""},{"id":409665755,"identity":"9aeb2719-0ebb-4211-9117-3f2c2d955bfb","order_by":3,"name":"Anh Chau Nguyen","email":"","orcid":"","institution":"College of Health Sciences, VinUniversity, Hanoi, Vietnam","correspondingAuthor":false,"prefix":"","firstName":"Anh","middleName":"Chau","lastName":"Nguyen","suffix":""},{"id":409665756,"identity":"16f68391-0fbe-4095-9092-727f77d8c9c1","order_by":4,"name":"My Huyen Hac","email":"","orcid":"","institution":"College of Health Sciences, VinUniversity, Hanoi, Vietnam","correspondingAuthor":false,"prefix":"","firstName":"My","middleName":"Huyen","lastName":"Hac","suffix":""},{"id":409665757,"identity":"e2ea0781-1096-474e-9fa5-4870be1b88bf","order_by":5,"name":"Quyen Thu Do","email":"","orcid":"","institution":"College of Health Sciences, VinUniversity, Hanoi, Vietnam","correspondingAuthor":false,"prefix":"","firstName":"Quyen","middleName":"Thu","lastName":"Do","suffix":""},{"id":409666031,"identity":"e9bdc072-ee60-49eb-b7a9-1b4a7687d502","order_by":6,"name":"Thanh Hai Tran","email":"","orcid":"","institution":"College of Health Sciences, VinUniversity, Hanoi, Vietnam","correspondingAuthor":false,"prefix":"","firstName":"Thanh","middleName":"Hai","lastName":"Tran","suffix":""},{"id":409666032,"identity":"9af7efb5-80ff-4601-a033-f893affa4332","order_by":7,"name":"Duc Quang Tran","email":"","orcid":"","institution":"Faculty of Health Sciences, Dong Nai Technology University, Bien Hoa, Vietnam","correspondingAuthor":false,"prefix":"","firstName":"Duc","middleName":"Quang","lastName":"Tran","suffix":""},{"id":409666268,"identity":"65c191f1-933e-4112-92ea-198b1fed9d07","order_by":8,"name":"Huong Thi Xuan Hoang","email":"","orcid":"","institution":"Faculty of Nursing, Phenikaa University, Hanoi, Vietnam","correspondingAuthor":false,"prefix":"","firstName":"Huong","middleName":"Thi Xuan","lastName":"Hoang","suffix":""}],"badges":[],"createdAt":"2024-07-28 18:29:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4817858/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4817858/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":75186044,"identity":"2ac37824-3738-4b89-8959-3486a3d53c41","added_by":"auto","created_at":"2025-01-31 17:24:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1355126,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4817858/v1/db32b352-6437-40db-bd77-d29f42c70872.pdf"}],"financialInterests":"","formattedTitle":"Navigating life Post-Cancer Diagnosis in women: Symptom Clusters and Influencing Factors","fulltext":[{"header":"I. INTRODUCTION","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCancer in worldwide and Vietnam\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCancer continues to be a global health challenge, with its incidence rate surpassing 19.9 million cases by 2022 (Ferlay et al., 2024). This escalating worldwide burden is influenced by population growth, aging, lifestyle changes, disparities in access to healthcare, and other factors (The American Cancer Society, 2019). While cancer impacts are across diverse populations, women bear a disproportionate burden of the disease in prevention, diagnosis, and supportive care services.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn Southeast Asia, the 2022 diagnosis of over 1 million cancer cases underscores the severity; notably in Vietnam, with breast, lung, and colorectal cancers being predominant among Vietnamese women (Ferlay et al., 2024). Socioeconomic elements, cultural beliefs, and geographic barriers may contribute to delayed care-seeking in cancer outcomes among women in this country (Petersen et al., 2022). Cancer treatment disrupts lifestyle and mental health, with cultural beliefs and social support guiding coping (Nguyen et al., 2024), family duties and relationships shaping caregivers' strategies (Xuan Long et al., 2020), and religious values influencing how women communicate pain and coping methods (Nguyen, 2018). This underscores the importance of gender-specific cancer research and interventions for this particular population, emphasizing the need for increased attention to women's groups to ensure gender equality in cancer care provision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSymptom clusters in cancer\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSymptom clusters are the co-occurrence of two or more interrelated symptoms that may share common mechanisms\u0026nbsp;(Fan et al., 2007; Kim et al., 2005; Kirkova et al., 2011), with a sentinel symptom playing a key role in predicting related symptoms (Rha et al., 2019), and the cluster's stability defined by its enduring nature and symptom consistency (Nguyen \u0026amp; Nguyen, 2022). For instance, heightened fatigue levels may exacerbate pain, sleep disturbances, and emotional distress within a cluster (Rha et al., 2019). Exploring these \"symptom clusters\" provides insights for unified interventions, conserving resources, and mitigating healthcare costs while elevating the overall quality of care and life for affected individuals (Nguyen \u0026amp; Nguyen, 2022). Given that symptoms of cancer are experienced differently by males and females (Chueng, 2011; Oertelt-Prigione, 2021), it is essential to examine symptom clusters through a gender-specific lens. The variability of measurement tools for assessing symptom clusters has introduced inconsistencies across studies, emphasizing the need for further research to facilitate a systematic review and the development of a unified symptom cluster framework.\u003c/p\u003e\n\u003cp\u003eIn Vietnam, the escalating cancer incidence witnessed a threefold increase over the past 30 years, which accentuates the urgency to explore symptom clusters comprehensively (Pham et al., 2019). In 2018, breast and cervical cancers, specifically affecting women, accounted for a total of 11.7% of cancer cases while the total cancer incidence was 164,671 in Vietnam (WHO, 2020). Despite the pervasive nature of interconnected symptoms or symptom clusters in cancer patients, Vietnam's symptom research has predominantly prioritized evaluating and mitigating individual symptoms (Nguyen et al., 2021; Pham et al., 2019). \u0026nbsp;Moreover, there is a shortage of studies addressing symptom clusters among Vietnamese women with cancer. Our study thus assumes a pivotal role in bridging this knowledge gap, aiming to contribute meaningful insights to the existing body of research and data pool. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur primary objectives are to: \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1. Identify symptom clusters in women with cancer in Vietnam; and \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2. Analyze the factors influencing identified symptom clusters. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research not only sheds light on the specific challenges faced by Vietnamese women with cancer-related symptoms but also lays the groundwork for targeted interventions. By doing so, our findings aim to inform tailored interventions, ultimately easing the overall quality of life and treatment outcomes for women dealing with cancer in Vietnam's unique context. \u0026nbsp;\u003c/p\u003e"},{"header":"II.\tMETHOD","content":"\u003cp\u003e\u003cstrong\u003eSample and Setting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional study was conducted with a convenience sample of women living and beyond cancer in 5 hospitals across Vietnam from September to December 2023. The inclusion criteria for women included (1) Vietnamese women who able to speak and write in Vietnamese and living in Vietnam at the time participating in the project (2)\u0026nbsp;\u0026gt;18 years-old (3) be diagnosed with at least one type of cancer or have been finished cancer treatment (4) willingness to participate in this study. The study excluded those who are diagnosed with mental illness. The sample size will be calculated (just used for target population) which is based the formula N ≥104 + m (m: number of independent variables). There are 10 independent variables; therefore, the minimum required sample size is 114 (Kupper \u0026amp; Hafner, 1989). In total, we collected 318 cancer women who was eligible and participated in the study. After data cleaning with removing incomplete questionnaires, inconsistent provided information, and duplicate entries, we obtained a total of 217 participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDemographic characteristics\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDemographic information included age, gender, living area, religion, level of education, employment, personal income per month, and family member support. Clinical information including medical and family history related to cancer were collected. In addition, some behavioral and lifestyle characteristics were also asked such as smoking, type of exercise, sleeping disturbances, and strategies used to monitor and manage symptoms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAssessing symptoms\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe number of physical and psychological symptoms were collected including pain, fatigue, insomnia, nausea/vomiting, appetite loss, hair loss, sexual issue, mood issues. Symptoms are reflected with the frequency from “never” to “always”. The score of each statement is evaluated on a 5-level Likert scale, with 0-never, 1-rarely, 2-occasionally, 3-sometimes, 4-usually, 5-always.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eVisualized Pain Scale (VPS)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants' pain levels were evaluated using the Visualized Pain Scale, a popular pain rating scale that available in 13 different languages, including Vietnamese (The British Pain Society, 2014). The VPS has a 10-point scale ranging from 0 to 10, with higher scores indicating higher pain levels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eKarnofsky Performance Status Scale\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Karnofsky Performance Status Scale was used widely to measure the level of functional capacity in patients living with cancer. The KPS has been used in Vietnamese clinical settings for oncology patients (Pham et al., 2017; Thi et al., 2024). This scale rates the level of functional capacity on a scale from 20% to 100%, with higher percentages indicating better functional performance status.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMental Health (PHQ-9 and GAD-7)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePatient Health Questionnaire (PHQ-9)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePatient Health Questionnaire (PHQ-9) was used to screen for depression in cancer women (Kroenke et al., 2001; Spitzer et al., 1999). This instrument can assess depressive symptoms and suggest grade depressive symptom severity and has been indicated a Cronbach's alpha of 0.7 to 0.8 (Mughal et al., 2021; Phi et al., 2023). Levels of depression severity will be rated according to PHQ-9 score with minimal level (grade from 0 to 4), Mild level (from 5 to 9), Moderate level (from 10-14), Moderately severe (from 15 to 19), and severe level of depression (from 20 to 27).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGeneral Anxiety Disorder (GAD-7)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGeneral Anxiety Disorder (GAD-7) was used to assess the anxiety (Spitzer et al., 2006). The GAD-7 has been validated in Vietnam with Cronbach alpha of 0.91 (Mughal et al., 2021). Seven items in GAD-7 designed to self-report the anxiety of an individual during the previous 2 weeks will be rated from 0 to 3, corresponding to “not at all,” “several days,” “more than half the day,” and “nearly every day,” respectively. The total score will be summed and range from 0 to 21. The cut-off points for mild, moderate, and severe anxiety are represented as 5, 10, and 15, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePerceived stress scale (PSS-10)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Vietnamese version of the Perceived Stress Scale (PSS-10) was used to assess the self-reported stress among participants (Cronbach’s alpha of 0.80) (Dao-Tran et al., 2017). Participants were asked how often they experience thoughts and feelings during the last months through 10 items. Each item is responded from 0 (never) to 4 (very often). The scores will be aggregated, and the possible total score ranges from 0 to 40. Higher total scores show a higher likelihood that environmental demands exceed the ability to cope with individuals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Scientific Council, Ethics Council in Biomedical Research, Vinmec international general hospital (No.75/2022/QD-VMEC dated July 26, 2022). The researchers obtained a list of women with cancer who had received treatment at the selected hospitals, along with their contact information (usually phone numbers). Eligible participants were invited to participate in the study through phone calls or in-person invitations at the hospital. Participants who agreed to participate and met the inclusion criteria were provided with an information sheet about the study and a consent form. After obtaining written consent, participants completed the survey questionnaire in the presence of the investigator. The data collection process took approximately 15 minutes per participant. If doubts arose regarding the interpretation of the instructions, the investigator would assist them. After the questionnaire was completed, it was immediately collected by the administering investigator.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData analyses were conducted using IBM SPSS version 26.0. Demographic information, clinical characteristics, and symptom incidence and severity were analyzed using descriptive statistical methods. Exploratory factor analysis was used to extract symptom clusters, and univariate analyses and multiple linear regression analyses were performed to explore factors affecting symptom clusters.\u003c/p\u003e\n\u003cp\u003eStructural equation modeling (SEM) using AMOS version 20, with maximum likelihood estimation, was used to test the hypothesized model. The criteria used to appraise the structural model were model fit indices, as well as the magnitude and direction of path estimates (Hair et al. 1998). The fit indices that were used to evaluate the proposed model were normed Chi-square (χ2/df), Goodness-of-Fit Index (GFI), Adjusted Goodness-of-Fit Index (AGFI), Comparative Fit Index (CFI), Tucker Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA) and Root Mean Square Residual (RMR) (Byrne 2013; Hair et al. 2014; Kline 2011). Following the recommendation by Byrne (2013) and Kline (2011), the model was considered to have an adequate fit when the χ2/df ratio was \u0026lt;5, the value of both absolute fit indices (GFI and AGFI) and the comparative fit indices (CFI and TLI) were \u0026gt;0.90 and both RMSEA and RMR values were \u0026lt; 0.08.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"III. RESULTS","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCharacteristics\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eof the study\u0026rsquo;s participants\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable1. Demographic and clinical characteristics\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"590\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategories\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eAge (Mean\u0026plusmn;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 214px;\"\u003e\n \u003cp\u003e55.01\u0026plusmn;12.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003ePlace of residence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e50.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eRural/Mountainous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e49.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eReligion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e83.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eBuddhism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eCatholic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e5.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eElementary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e6.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eMiddle School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e21.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eHigh School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e23.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eCollege\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e48.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eOccupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eNot employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e19.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eBlue collar (farmers, vendors, construction workers, laborers, etc.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e39.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eWhite collar (teachers, healthcare professionals, office workers, military personnel, etc.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e41.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e5.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eDivorced/Widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e8.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eMarried/Living as married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e86.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e94.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eChronic diseases (e.g., hypertension, diabetes, liver disease, kidney disease)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e72.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e27.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e98.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003ePhysical activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e25.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e74.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eFamily history of cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e72.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e27.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eCurrent treatment therapy\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eSurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e35.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eChemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e58.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eRadiotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e18.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eImmunotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eHormone therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e13.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e22.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eMethods used to monitor and manage symptoms of the disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e7.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eRegular health check-ups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e88.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eTechnological devices (smartphones, smartwatches, etc.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e3.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eOnline support (online forums, Facebook groups, etc.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e217\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e100\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eA total of 217 cancer patients were included in the study. The mean age of the participants was 55.01 \u0026plusmn; 12.45 years. The majority were residents of urban areas (50.69%). In terms of religion, 83.41% reported no religion, while 10.6% identified as Buddhist and 4.15% as Catholic. Regarding education level, 48.39% had a college education, followed by 23.96% with a high school education. Occupationally, 41.01% were engaged in intellectual labor, while 39.63% were involved in manual labor. Marital status indicated that 86.18% were married or living as married. A significant portion of participants (72.35%) reported no chronic diseases. The majority were non-smokers (98.16%) and non-drinkers (98.62%). Regarding physical activity, 74.65% engaged in such activities. Additionally, 27.19% reported a family history of cancer. In terms of treatment, the majority underwent chemotherapy (58.06%), followed by surgery (35.02%). The most common method used to monitor and manage symptoms was regular health check-ups (88.48%). More details are displayed in Table 1. Understanding the demographic characteristics establishes a foundation for examining the prevalence of symptoms among participants and their impact on mental health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePrevalence of Symptoms among the study\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026rsquo;s participants\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 2. Prevalence of Symptoms\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"588\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNever\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRarely (1 time/week)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSometimes (1-2 times/week)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOften (3-4 times/week)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUsually (5-6 times/week)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlways\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eFatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e22.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e21.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e24.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e7.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e5.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eAppetite loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e36.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e18.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e21.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e13.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e4.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e5.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003ePain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e35.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e26.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e16.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e12.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e5.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e4.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eSleep disturbances\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e26.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e19.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e21.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e15.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e7.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eHair loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e35.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e14.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e14.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e8.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e8.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e18.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eNausea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e52.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e21.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e13.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e6.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e4.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eSexual issue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e59.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e19.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e11.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e5.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eMood issue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e50.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e19.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e11.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e7.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e7.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e3.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2 illustrates the prevalence of symptoms, anxiety levels, depression levels, and personal stress among the participants. Fatigue and sleep disturbances were reported most frequently, with fatigue being the most prevalent symptom, affecting 77% and 73% participants, respectively. Other common reported symptoms including pain (65%) and appetite loss (63%). Understanding which symptoms are most common lays the groundwork for examining how these symptoms intersect with participants\u0026apos; mental health challenges.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFrequency of Mental Health issues among the study participants\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 3. Frequency of Mental Health issues\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"590\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN (n=217)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnxiety (GAD-7)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003eNone or minimal anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e83.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003eMild anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e11.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003eModerate anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e3.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003eSevere anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDepression (PHQ-9)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003eNone or minimal depression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e74.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003eMild depression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e17.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003eModerate depression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e4.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003eModerately severe depression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003eSevere depression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePersonal stress (PSS)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003eLow stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e34.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003eModerate stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e65.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 202px;\"\u003e\n \u003cp\u003eHigh perceived stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eRegarding mental health, the majority of participants experienced none or minimal anxiety (83.41%) and none or minimal depression (74.65%). However, mild anxiety (11.52%) and mild depression (17.97%) were also prevalent. A smaller percentage reported moderate to severe levels of anxiety and depression. Additionally, in terms of personal stress, the majority of participants reported moderate stress (65.44%), while a notable portion reported low stress (34.56%), as presented in Table 3. These mental health findings highlight the need to explore how various symptoms interact and cluster, further influencing patients\u0026apos; psychological well-being.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIdentifying symptom clusters\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Factor analysis of symptom clusters\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"591\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptom\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactor 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactor 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eFatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e0.7993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eAppetite loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e0.8139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003ePain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e0.6747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eSleep issue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e0.6318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eHair loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e0.6884\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eNausea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e0.7570\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eSexual issue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e0.5062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eMood issue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 213px;\"\u003e\n \u003cp\u003e0.5231\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003ePersonal stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 213px;\"\u003e\n \u003cp\u003e0.5696\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eDepress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 213px;\"\u003e\n \u003cp\u003e0.7610\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 213px;\"\u003e\n \u003cp\u003e0.8331\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eVarian contribution rate, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e35.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 213px;\"\u003e\n \u003cp\u003e19.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 190px;\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s Alpha\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e0.8345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 213px;\"\u003e\n \u003cp\u003e0.6102\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eFactor loading \u0026gt;0.5\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo extract symptom clusters, we utilized Exploratory Factor Analysis (EFA) with principal components and maximum variance rotation method. A total of 11 items were included in the EFA, with an occurrence rate of \u0026ge;25%. Tests for the suitability of structure detection showed a Kaiser-Meyer-Olkin value of 0.822 and a Bartlett test with P \u0026lt; 0.001, indicating the data were suitable for EFA. Cronbach\u0026rsquo;s \u0026alpha; was calculated for each factor to evaluate the internal consistency of the symptom clusters. A Cronbach\u0026rsquo;s \u0026alpha; of 0.7 or higher represents good consistency validity. In this study, variables with factor loadings less than 0.5 were excluded, as statistically, a correlation lower than that would produce too many factors in factor analysis.\u003c/p\u003e\n\u003cp\u003eA common practice in factor analysis is to retain only those factors with eigenvalues greater than one (Kaiser, 1960; Costello \u0026amp; Osborne, 2005). This criterion suggests that a factor must explain more variance than a single observed variable would on its own. Essentially, an eigenvalue greater than one indicates that the factor accounts for a significant portion of the total variance in the data, justifying its inclusion in the final model. In this study\u0026rsquo;s analysis, two distinct factors with eigenvalues greater than 1.00 were retained, accounting for 54.66% of the total variance. Factor loadings represent the correlation between observed variables and their underlying factors; thus, higher loadings indicate a stronger relationship. The 0.5 factor loading threshold was selected to ensure that each item contributes meaningfully to its respective factor, enhances the clarity and reliability of the identified symptom clusters, and minimize cross-loadings (Hair et al., 1998; MacCallum et al., 1999; Stevens, 1992). Factor 1 included fatigue, appetite loss, pain, sleep issues, hair loss, nausea, and sexual issues, with a variance contribution rate of 35.66% and a Cronbach\u0026rsquo;s \u0026alpha; of 0.8345, indicating high internal consistency. Factor 2 comprised mood issues, personal stress, depression, and anxiety, with a variance contribution rate of 19.00% and a Cronbach\u0026rsquo;s \u0026alpha; of 0.6102, reflecting moderate reliability.\u003c/p\u003e\n\u003cp\u003eThese findings delineate two main symptom clusters: the \u003cstrong\u003e\u003cem\u003ephysical cluster\u003c/em\u003e\u003c/strong\u003e (Factor 1) and the \u003cstrong\u003e\u003cem\u003epsychological cluster\u003c/em\u003e\u003c/strong\u003e (Factor 2). This distinction aids in comprehending the different dimensions of symptom experiences and can inform targeted approaches for treatment or intervention. With these clusters identified, it is essential to explore the factors influencing their formation and severity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFactors influencing symptom clusters\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5. Bivariate Analysis of the Factors on Symptom Clusters\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"591\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactor 1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u0026chi;\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactor 2\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u0026chi;\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e-0.0233**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e0.0960**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003ePlace of residence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e3,953\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e4,046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eReligion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e2,146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e6,513\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e7,793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e5,519\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eOccupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e2,618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e7,066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e8,822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e9,097\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eChronic diseases (e.g., hypertension, diabetes, liver disease, kidney disease)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e4,082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e6,690\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e9,922*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e1,428\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003ePhysical activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e4,961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e16,404*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003eFamily history of cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e2,171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e6,077\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 261px;\"\u003e\n \u003cp\u003e*p\u0026lt;0.05 ** Spearman\u0026rsquo;s rank test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eA spearman\u0026apos;s rank test was employed to analyze the two clusters concerning age. The Kruskal-Wallis H rank sum test was utilized to assess whether other demographic characteristics (such as place of residence, religion, education level, occupation, and marital status) and past medical, social, and family history (including chronic diseases, smoking, physical activities, and family history of cancer) were correlated with the symptom clusters (Table 5). Factor 1, the physical symptom cluster, showed a significant negative association with age (\u0026chi;2 = -0.0233, p \u0026lt; 0.01) and a significant positive association with smoking (\u0026chi;2 = 9.922, p \u0026lt; 0.05). Physical activity also had a significant impact on Factor 1 (\u0026chi;2 = 4.961, p \u0026lt; 0.05). In contrast, Factor 2, the psychological symptom cluster, was significantly influenced by age (\u0026chi;2 = 0.0960, p \u0026lt; 0.01) and physical activity (\u0026chi;2 = 16.404, p \u0026lt; 0.05). Other factors such as place of residence, religion, education level, occupation, marital status, chronic diseases, and family history of cancer were analyzed, but only those with significant associations are highlighted here. These findings highlight the complex interplay of demographic, lifestyle, and clinical factors in shaping symptom experiences, paving the way for personalized approaches to symptom management.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6. Multiple Linear Regression Analysis of the Factors on Symptom Clusters\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" style=\"width: 43px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactor 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactor 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eB (SE)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eTolerance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eVIF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003eB (SE)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eTolerance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eVIF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e(Constant)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.425 (1.040)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.409\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.257 (1.015)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.00005 (0.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.587\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.013 (0.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.587\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.318 (0.156)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e2.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.043\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e-0.155 (0.152)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-1.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.363\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReligion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.054 (0.115)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.466\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.031 (0.112)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e-0.038 (0.094)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.687\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.842\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e-0.032 (0.092)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.842\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.263 (0.112)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e2.349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.566\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e-0.007 (0.109)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.566\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e-0.245 (0.136)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-1.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.154 (0.133)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic diseases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e-0.051 (0.160)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e-0.328 (0.157)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-2.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.037\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e-1.203 (0.613)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-1.962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.051\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.527\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e-0.121 (0.599)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.527\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol consumption\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.526 (0.708)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e-0.476 (0.691)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.689\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.533\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhysical activities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.007 (0.158)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e-0.599 (0.154)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-3.887\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" style=\"width: 43px;\"\u003e\n \u003cp\u003eR-square = 0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" style=\"width: 44px;\"\u003e\n \u003cp\u003eR-square = 0.120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe multivariate regression analysis revealed that Factor 1 was significantly influenced by place of residence (B = 0.318, p = 0.043) and occupation (B = 0.263, p = 0.020), with marital status (B = -0.245, p = 0.074) showing a marginal effect. Smoking was also approaching significance (B = -1.203, p = 0.051). The R-squared for Factor 1 was 0.077, indicating that the model explains 7.7% of the variance in Factor 1. For Factor 2, physical activity (B = -0.599, p \u0026lt; 0.001) and chronic diseases (B = -0.328, p = 0.037) were significant predictors, while age (B = 0.013, p = 0.059) showed a marginally significant effect. The R-squared for Factor 2 was 0.120, indicating that the model accounts for 12% of the variance in Factor 2. Other variables such as education, alcohol consumption, and smoking did not significantly impact either factor (p \u0026gt; 0.05). All VIF values are below the threshold of 5, and Tolerance values are above 0.2, indicating that the predictor variables are not excessively correlated with one another.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Structural Equation Modeling (SEM) for Factor Structure of Symptom Clusters\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"104%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003edf\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;2/df\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAGFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTLI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSEA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e149.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e3.480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e.884\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e.169\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe model shows a reasonable fit with a \u0026chi;\u0026sup2;/df of 3.480, which is acceptable, but could be improved. The GFI (0.896), AGFI (0.840), CFI (0.884), and TLI (0.852) are slightly below the ideal 0.90 threshold, indicating a suboptimal fit. The RMSEA value of 0.107 suggests a mediocre fit, and the RMR value of 0.169 indicates moderate residuals. Overall, while the model is acceptable, there is room for improvement in the fit indices.\u003c/p\u003e"},{"header":"IV. DISCUSSION ","content":"\u003cp\u003eThis study revealed that fatigue, appetite loss, and pain were among the most prevalent symptoms experienced by the participants. Fatigue was reported by the majority, with varying degrees of frequency, followed closely by appetite loss and pain. These findings are consistent with existing literature, underscoring the pervasive nature of these symptoms in cancer patients (Chueng, 2011; Oertelt-Prigione, 2021).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe prevalence of symptoms identified in our study aligns with findings from several other studies in the oncology field. Specifically, the high prevalence of fatigue, reported by the majority of our participants, is consistent with results from a systematic review, the findings of which revealed fatigue-sleep disturbance to be a predominant symptom among breast cancer patients across various treatment stages (So et al., 2021). This underscores the pervasive nature of fatigue as a significant burden for cancer patients, necessitating focused interventions. Similarly, our findings regarding appetite loss and pain are in line with previous research. For example, Coleman et al. (2022) identified pain interference as a key component of the SPADE (sleep disturbance, pain interference, anxiety, depression, and energy/fatigue) symptom cluster among cervical cancer survivors (Coleman et al., 2022). Appetite loss, although not as frequently highlighted as fatigue or pain in some studies, was nonetheless significant in our cohort, reflecting the complex interplay of treatment side effects and overall health status in cancer patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the multivariate regression analysis, the findings show that place of residence and occupation significantly influenced physical symptoms, with urban living and white-collar occupations associated with fewer physical symptoms. Symptom clusters varied with work status including environmental and occupational contexts, highlighting the impact of daily routines and stressors on physical health (Browall et al., 2017). For psychological symptoms, physical activity and chronic diseases were significant predictors, with active individuals and those without chronic conditions reporting fewer psychological symptoms. \u0026nbsp;This supports Liska (2020) and Luo et al. (2023), who found a relationship between physical activity and emotional well-being in breast cancer patients and advocates for physical activity as a beneficial intervention for enhancing mental health among cancer survivors. Interestingly, while age showed a marginally significant effect on both factors, it did not reach statistical significance in this analysis. This finding diverges from studies that have consistently reported age as a significant factor affecting symptom burden in cancer populations (Oertelt-Prigione et al., 2021). The R-squared values indicate that while these models explain a modest portion of the variance in symptom clusters\u0026mdash;7.7% for Factor 1 and 12% for Factor 2\u0026mdash;the results still emphasize the complexity of symptom experiences and suggest that additional unmeasured factors may also play a role. Moreover, the absence of significant associations for variables such as education and smoking contrasts with some prior studies that highlighted their relevance in determining symptom severity (Nguyen \u0026amp; Nguyen, 2022; Pham et al., 2019). This discrepancy may reflect cultural differences or variations in how these factors interact within different populations.\u003c/p\u003e\n\u003cp\u003eThrough exploratory factor analysis, our study identified two main symptom clusters: physical and psychological. The physical symptom cluster included fatigue, appetite loss, pain, sleep issues, hair loss, nausea, and sexual issues, indicating a high internal consistency. The psychological symptom cluster comprised mood issues, personal stress, depression, and anxiety, reflecting moderate reliability. Our study\u0026apos;s identification of distinct physical and psychological clusters aligns well with the broader literature, which frequently highlights the necessity of addressing both domains for effective symptom management. Luo et al. (2023) further elucidated the multidimensional nature of symptom clusters in their prospective study, identifying GI symptoms, emotional \u0026amp; psychological symptoms, neurological symptoms, menopausal symptoms, and self-image disorder among breast cancer patients (Luo et al., 2023). Our study\u0026apos;s clustering of physical symptoms similarly reflects this multidimensionality, albeit focusing on different specific symptoms. The distress caused by the emotional symptom cluster, characterized by worry, difficulty concentrating, and sadness, which aligns closely with our psychological cluster findings (Browall et al., 2017). However, our findings differ slightly in that we separated physical and psychological symptoms into distinct clusters, whereas some studies have identified more mixed clusters. For instance, Zhou et al. (2023) identified multiple symptom clusters in cervical cancer patients\u0026apos; post-radiotherapy/chemotherapy, including combinations of psycho-emotion-related and pain-disturbed sleep-related clusters (Zhou et al., 2023). This suggests an understanding of symptom interrelationships, which can vary depending on the patient population and cancer type.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInterestingly, our study did not find a significant association between religion and mental health, which contrasts with previous research indicating that religion can positively affect mental health (Salsman, 2015; Kelly, 2022; AI Eid, 2020). This discrepancy may be due to cultural differences, the specific measures of religiosity used, or the unique stressors faced by our study population. Similarly, chronic diseases did not show a significant impact on physical health in our findings. This could be due to the potential for well-managed chronic conditions in our sample, or the overshadowing impact of cancer itself on physical health. The most notable finding from our study was the strong association between physical activity and the psychological symptom cluster. Our results show that the more physical activities there are, the fewer psychological issues are reported. This highlights the potential of physical activity as a critical intervention for improving mental health among women with cancer. Physical activity is known to enhance mood through various mechanisms, such as endorphin release, stress reduction, improved sleep quality, and increased social interaction. Therefore, intervention programs need to focus on incorporating physical activities to improve mental health outcomes for cancer patients (Liska, 2020). Tailored exercise programs; for example, the Women Wellness Program, Survivorship Wellness Group Program and other interventional programs with regular monitoring and support from healthcare providers are essential for maximizing the mental health benefits of physical activity (Anderson et al., 2017; Siwik et al., 2023). In contrast, our study did not find a significant influence of physical activity on the physical health factor. This might be due to the complexity of physical symptoms, which could be influenced by a myriad of factors beyond physical activity alone, such as the severity of the disease, treatment side effects, and other lifestyle factors. Although smoking and physical activity show statistically significant influences on symptom clusters in this study, the analysis indicates that these factors only explain a small proportion of the variance in symptom clusters. One of the reasons might be the questionnaire has not used a standard tool to assess these variables; therefore, the result should be considered and confirmed by future research. Lastly, previous studies have shown that a family history of cancer can affect mental health; however, this study did not find a significant association. Possible explanations could include differences in study populations, the specific types of family history considered, or other mitigating factors such as social support systems.\u003c/p\u003e\n\u003cp\u003eThis study has several strengths, including the comprehensive sample characteristics and the use of robust statistical methods such as Exploratory Factor Analysis (EFA) and multiple linear regression analysis. These methodologies provided reliable insights into the patterns and determinants of symptom experiences among a diverse sample of women living with and beyond cancer in Vietnam, enhancing the generalizability of the findings. However, the cross-sectional nature of the study limits the ability to infer causality and track symptom changes over time, highlighting the need for longitudinal studies. Potential biases, such as recall bias from self-reported data due to the absence of a validated questionnaire specifically designed for Vietnamese women with cancer, and the limitations of convenience sampling, may also affect the representativeness of the findings. The sample included participants with a range of cancers, allowing to capture a diverse range of symptom experiences. While this may cause heterogeneity in cancer population, this diversity is crucial as it can identify symptom clusters that are common across various cancer types, providing valuable insights into the general patterns of symptom co-occurrence in women with cancer, and be a reference for tailored interventions that consider the unique symptom profiles associated with each cancer type. With significant symptom clusters and influencing factors were identified, further longitudinal research is needed to confirm these findings, explore temporal relationships and examining how symptom clusters may vary across different cancer diagnoses and stages.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFuture research should focus on conducting longitudinal studies to monitor symptom progression and clustering over different stages of cancer treatment and survivorship. This will provide deeper insights into the persistence and evolution of symptoms, facilitating more effective and timely interventions. Additionally, exploring a broader range of demographic and clinical factors, such as genetic predispositions and specific cancer types, can help identify high-risk groups and tailor interventions more precisely. Interventional studies targeting the identified symptom clusters, such as randomized controlled trials (RCTs), could evaluate the efficacy of integrative care models combining pharmacological treatments, lifestyle modifications, and psychosocial support. Complementing quantitative findings with qualitative research, such as in-depth interviews and focus groups, can provide rich, contextual insights into the lived experiences of cancer patients, offering a more holistic understanding of symptom management needs and preferences. Addressing these research directions will advance the understanding of symptom experiences and enhance the quality of care for cancer patients, leading to better health outcomes and improved quality of life.\u0026nbsp;\u003c/p\u003e"},{"header":"V.\tCONCLUSION","content":"\u003cp\u003eThis study reveals the pervasive prevalence of fatigue, appetite loss, and pain among women living with and beyond cancer in Vietnam, aligning with similar findings in oncology literature. The primary objectives of this research were to identify distinct physical and psychological symptom clusters and to understand their implications for patient care. Recognizing these symptom clusters underscores the complexity of cancer-related experiences, illustrating the urgent need for tailored interventions that address both physical and psychological dimensions of care. Healthcare providers play a crucial role in developing personalized treatment plans based on these clusters, by integrating pharmacological, nutritional, and psychosocial interventions. Regular screening for symptoms using standardized tools facilitates early detection and intervention, improving patient outcomes and quality of life.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThis study was conducted in accordance with the Declaration of Helsinki. Ethical approval was granted by the Institutional Ethical Review Board of Vinmec International General Hospital JSC – VinUniversity (No. 75/2022/QD-VMEC, dated 26 July 2022). All participants in the study have given informed consent to be involved in the study voluntarily and have the right to participate or not.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThe datasets generated and/or analysed during the current study are not publicly available due to privacy and ethical restrictions but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e:\u0026nbsp;\u003c/em\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors' contributions\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e: H.T.H.N., T.N.T., A.C.N., M.H.H., Q.T.D., collectively contributed to the conceptualization and design of the study. H.T.H.N., T.N.T., A.C.N, M.H.H., Q.T.D., and T.H.T. were involved in the recruitment of participants and data collection. D.T.D. did the data analysis and result interpretations. D.Q.T. and H.T.X.H. provided oversight and critical feedback throughout the research process. H.T.H.N. led the drafting of the manuscript. All authors critically reviewed and revised the manuscript for important intellectual content. H.T.H.N. supervised the entire study. All authors approved the final version of the manuscript for submission.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAl Eid, N. A., Alqahtani, M. M., Marwa, K., Arnout, B. A., Alswailem, H. S., \u0026amp; Al Toaimi, A. A. (2020). 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Exploring the Association between Religious Values and Communication about Pain Coping Strategies: A Case Study with Vietnamese Female Cancer Patients. \u003cem\u003eTheory and Practice in Language Studies\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(9), 1131. https://doi.org/10.17507/tpls.0809.04\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"symptom clusters, influencing factors, cancer, women, Vietnam","lastPublishedDoi":"10.21203/rs.3.rs-4817858/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4817858/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAims\u003c/strong\u003e: 1) To identify symptom clusters in Vietnamese women with cancer and 2) to examine the factors influencing those identified clusters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e: This cross-sectional study was conducted in 5 hospitals across Vietnam from September to December 2023. A total of 217 valid data sets from women with cancer were included. The symptom clusters were identified by exploratory factor analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Fatigue and appetite loss were recognized as the most common symptoms. The exploratory factor analysis showed two distinct groups of factors, occupying 54.66% of total variance: fatigue, appetite loss, pain, sleep issues, hair loss, nausea, and sexual issues (Factor 1 – physical cluster) and mood issues, personal stress, depression, and anxiety (Factor 2 – psychological cluster). In terms of factors influencing two clusters, smoking demonstrated a marginally non-significant negative association with Factor 1 - physical health (R\u003csup\u003e2\u003c/sup\u003e=1.44%), while physical activity illustrated a significant negative association with Factor 2 - mental health (R\u003csup\u003e2\u003c/sup\u003e= 7.25%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: The physical and psychological symptom clusters underlay symptom experiences complexity. Tailored interventions from healthcare providers are required to enhance patients’ outcomes and quality of life.\u003c/p\u003e","manuscriptTitle":"Navigating life Post-Cancer Diagnosis in women: Symptom Clusters and Influencing Factors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-24 10:18:21","doi":"10.21203/rs.3.rs-4817858/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":"99456b8f-bcb8-458e-bb1d-8eecf52d1527","owner":[],"postedDate":"January 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-10T15:08:33+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-24 10:18:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4817858","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4817858","identity":"rs-4817858","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}