Asia-Pacific Journal of Oncology Nursing最新文献

{"title":"An ideal portrait of the professional competence of clinical research nurses: A qualitative study","authors":"Heng Yang ,&nbsp;Yipei Chen ,&nbsp;Xin Peng","doi":"10.1016/j.apjon.2025.100682","DOIUrl":"10.1016/j.apjon.2025.100682","url":null,"abstract":"<div><h3>Objective</h3><div>This study aims to identify and define the ideal professional competencies of Clinical Research Nurses (CRNs) in China, focusing on the essential knowledge, skills, and personal attributes required for effective practice in clinical trials.</div></div><div><h3>Methods</h3><div>Interviews were conducted with CRNs, Nurse Managers (NMs), Principal Investigators (PIs), Sub-Investigators (SIs), Clinical Research Coordinators (CRCs), Clinical Research Associates (CRAs), and subjects. Thematic analysis was performed using Colaizzi's seven-step method to analyze interview data and identify key competencies.</div></div><div><h3>Results</h3><div>The study identified four primary themes that characterize the ideal CRN profile: (1) theoretical knowledge ability, (2) practical technical ability, (3) professional quality and ability, and (4) personal traits. A total of 21 specific indicators were delineated, reflecting the diverse expectations of various stakeholders in clinical trials.</div></div><div><h3>Conclusions</h3><div>The findings highlight the multifaceted nature of CRN competencies, emphasizing the importance of comprehensive training programs tailored to the needs of CRNs. This study provides a foundational framework for enhancing CRN training and professional development in China.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100682"},"PeriodicalIF":2.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"“Don't need resuscitate” in palliative care: Ethical challenge or obstacle to a good death","authors":"Mohadese Babaie ,&nbsp;Azam Shirinabadi Farahani ,&nbsp;Maryam Rassouli","doi":"10.1016/j.apjon.2025.100681","DOIUrl":"10.1016/j.apjon.2025.100681","url":null,"abstract":"","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100681"},"PeriodicalIF":2.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143619728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Psychometric validation of the Chinese version of the Edmonton-33 scale in patients with head and neck cancer","authors":"Yumin Zhang ,&nbsp;Min Zhou ,&nbsp;Yu Liu ,&nbsp;Li Chen ,&nbsp;Sanlan Guo ,&nbsp;Lin Zhang","doi":"10.1016/j.apjon.2025.100685","DOIUrl":"10.1016/j.apjon.2025.100685","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to translate the Edmonton-33 scale (E−33) into Chinese and evaluate its reliability and validity in patients with head and neck cancer (HNC).</div></div><div><h3>Methods</h3><div>In Phase 1, the E−33 was translated from English to Chinese using the Brislin double-back translation method. Content validity was evaluated by a panel of experts, and a pilot test was conducted with a small sample of HNC patients. In Phase 2, a cohort of 510 patients from Henan and Hubei provinces was recruited. Psychometric properties were assessed through item analysis; and reliability testing (including Cronbach's alpha, test-retest reliability, and split-half reliability), as well as construct validity (using exploratory and confirmatory factor analysis).</div></div><div><h3>Results</h3><div>The item-level content validity index (I–CVI) ranged from 0.833 to 1.000, and the scale-level content validity index (S–CVI/Ave) was 0.965. The Cronbach's alpha, the test-retest reliability coefficient, and the split-half reliability values were 0.922, 0.973, and 0.971, respectively. Four main factors were identified using exploratory factor analysis, explaining 77.07% of the total variance. Confirmatory factor analysis showed good fit indices: χ²/df ​= ​1.626, RMSEA ​= ​0.048, NFI ​= ​0.936, RFI ​= ​0.930, IFI ​= ​0.974, TLI ​= ​0.972, and CFI ​= ​0.974.</div></div><div><h3>Conclusions</h3><div>The Chinese version of the Edmonton-33 scale (CE-33) demonstrated high reliability and validity, suggesting its potential as a valuable self-report tool for assessing functional outcomes in Chinese-speaking HNC patients.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100685"},"PeriodicalIF":2.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143815002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Network analysis of quality of life among young and middle-aged Korean cancer survivors","authors":"Yoonjung Kim ,&nbsp;Dahee Wi ,&nbsp;Eunjin Kim ,&nbsp;Jiae Lee","doi":"10.1016/j.apjon.2025.100684","DOIUrl":"10.1016/j.apjon.2025.100684","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to identify and compare the network structure of quality of life factors among cancer survivors to inform tailored interventions.</div></div><div><h3>Methods</h3><div>A cross-sectional study was conducted using data from 330 cancer survivors aged 18–64 years, drawn from the 2019–2021 Korea National Health and Nutrition Examination Survey (KNHANES). Participants were categorized into two groups: cancer survivors with current cancer and those without. Network analysis using the EBICglasso algorithm was performed to assess eight quality of life (QoL) components measured by the Health-related Quality of Life Instrument with 8 Items (HINT-8) scale: climbing stairs, pain, vitality, work ability, depression, memory, sleep quality, and happiness.</div></div><div><h3>Results</h3><div>The network analysis revealed distinct patterns between the two groups. Among survivors with current cancer, depression, work ability, and vitality were the most central QoL components, suggesting a need for targeted psychological and occupational support. In contrast, survivors without current cancer exhibited a network where work ability, pain, and climbing stairs (physical function) played a dominant role, emphasizing the importance of pain management and functional rehabilitation. Work ability emerged as a critical determinant in both groups, indicating its sustained impact throughout the survivorship continuum. Additionally, the network structure in survivors without current cancer showed greater interconnectedness, reflecting the complex interplay of long-term survivorship challenges.</div></div><div><h3>Conclusions</h3><div>The study highlights the need for personalized, stage-specific interventions in cancer survivorship. Work remained central in both groups, emphasizing its ongoing impact on quality of life throughout the survivorship journey. While psychological support is crucial to cancer survivors with current cancer due to the centrality of depression, long-term pain management becomes increasingly important post-treatment. These findings provide valuable insights for nursing practice, suggesting that tailored interventions addressing work-related challenges, psychological distress, and chronic symptom management could improve quality of life and facilitate survivors' reintegration into daily life.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100684"},"PeriodicalIF":2.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143747855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence-assisted machine learning models for predicting lung cancer survival","authors":"Yue Yuan ,&nbsp;Guolong Zhang ,&nbsp;Yuqi Gu ,&nbsp;Sicheng Hao ,&nbsp;Chen Huang ,&nbsp;Hongxia Xie ,&nbsp;Wei Mi ,&nbsp;Yingchun Zeng","doi":"10.1016/j.apjon.2025.100680","DOIUrl":"10.1016/j.apjon.2025.100680","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to evaluate the feasibility of large language model-Advanced Data Analysis (ADA) in developing and implementing machine learning models to predict survival outcomes for lung cancer patients, with a focus on its implications for nursing practice.</div></div><div><h3>Methods</h3><div>A retrospective study design was employed using a dataset of lung cancer patients. Data included sociodemographic, clinical, treatment-specific, and comorbidity variables. Large language model-ADA was used to build and evaluate three machine learning models. Model performance was validated, and results were presented using calibration plots.</div></div><div><h3>Results</h3><div>Of 737 patients, the survival rate of this cohort was 73.3%, with a mean age of 59.32 years. Calibration plots indicated robust model reliability across all models. The Random Forest model demonstrated the highest predictive accuracy among the models. Most critical features identified were preoperative white blood cells (2.2%), preoperative lung function of Forced Expiratory Volume in one second (2.1%), preoperative arterial oxygen saturation (1.9%), preoperative partial pressure of oxygen (1.7%), preoperative albumin (1.6%), preoperative preparation time (1.5%), age at admission (1.5%), preoperative partial pressure of carbon dioxide (1.5%), preoperative hospital stay days (1.5%), and postoperative total days of thoracic tube drainage (1.4%).</div></div><div><h3>Conclusions</h3><div>Large language model-ADA effectively facilitates the development of machine learning models for lung cancer survival prediction, enabling non-technical health care professionals to harness the power of advanced analytics. The findings underscore the importance of preoperative factors in predicting outcomes, while also highlighting the need for external validation across diverse settings.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100680"},"PeriodicalIF":2.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Home-based symptom management for patients with malignant lymphoma undergoing intermittent chemotherapy: A prospective observational study using network analysis","authors":"Qinglu Li ,&nbsp;Lu Yang ,&nbsp;Nan Wang ,&nbsp;Wenting Shi ,&nbsp;Lei Luo ,&nbsp;Hui Chen ,&nbsp;Guorong Wang","doi":"10.1016/j.apjon.2025.100683","DOIUrl":"10.1016/j.apjon.2025.100683","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to explore the symptom burden of patients with malignant lymphoma at home during the intermittent periods of chemotherapy and identify core symptoms using network analysis.</div></div><div><h3>Methods</h3><div>A prospective observational study was conducted, recruiting 208 patients from December 2019 to December 2020. Symptom burden was assessed using the MD Anderson Symptom Inventory-Chinese version (MDASI-C) at three time points during the first to third chemotherapy cycles (T1–T3). Symptom networks were constructed for each time point, and centrality indices were analyzed to identify core and bridge symptoms. Network comparison tests (NCT) were used to examine changes in symptom interconnectivity over time.</div></div><div><h3>Results</h3><div>A total of 208 participants were included in the data analysis. Fatigue and vomiting were the most prevalent and severe symptoms reported at all time points, respectively. In the presented symptom network, lack of appetite (<em>r</em>_<em>s</em> ​= ​1.13), sadness (<em>r</em>_<em>s</em> ​= ​1.20), and nausea (<em>r</em>_<em>s</em> ​= ​1.13) were the core symptoms of T1, T2, and T3, respectively. Lack of appetite (<em>r</em>_<em>b</em> ​= ​21, <em>r</em>_<em>c</em> ​= ​0.01), distress (<em>r</em>_<em>b</em> ​= ​25, <em>r</em>_<em>c</em> ​= ​0.01), and dry mouth (<em>r</em>_<em>b</em> ​= ​11, <em>r</em>_<em>c</em> ​= ​0.01) were identified as bridge symptoms at T1, T2, and T3, respectively. NCT results indicated no statistical differences in the global symptom network strength and overall edge weight among the three time points, while sadness exhibited higher betweenness and closeness in the network of T2 (T1 vs. T2, <em>P</em>_<em>c</em> ​= ​0.03, <em>P</em>_<em>b</em> ​= ​0.03; T2 vs. T3, <em>P</em>_<em>c</em> ​= ​0.01, <em>P</em>_<em>b</em> ​= ​0.03)</div></div><div><h3>Conclusions</h3><div>The findings highlight lack of appetite, sadness, and nausea as critical targets for symptom management in patients with malignant lymphoma undergoing intermittent chemotherapy. Caregivers and healthcare providers should focus on these symptoms to improve home-based symptom management and enhance patient well-being.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100683"},"PeriodicalIF":2.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143825496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning models to predict 6-month mortality risk in home-based hospice patients with advanced cancer","authors":"Wan Cheng ,&nbsp;Jianwei Zheng ,&nbsp;Yuanfeng Lu ,&nbsp;Guojuan Chen ,&nbsp;Zheng Zhu ,&nbsp;Hong Wu ,&nbsp;Yitao Wei ,&nbsp;Huimin Xiao","doi":"10.1016/j.apjon.2025.100679","DOIUrl":"10.1016/j.apjon.2025.100679","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to construct predictive models using five different machine learning algorithms for predicting 6-month mortality risk among home-based hospice patients with advanced cancer.</div></div><div><h3>Methods</h3><div>This population-based retrospective prognostic study examined data from 7023 patients in a home-based hospice center. Various algorithms including logistic regression, random forest, XGBoost, support vector machine, and neural network were implemented in this study. The model performance and effectiveness were assessed using sensitivity, specificity, accuracy, the area under the curve (AUC), and F1 Score. Additionally, a nomogram was developed to calculate individualized risk probabilities, enhancing clinical utility.</div></div><div><h3>Results</h3><div>Among the five types of predictive models, the logistic regression model achieved an AUC of 0.754 (95% CI: 0.721–0.786) in the test dataset, outperforming other machine learning algorithms. The nomogram developed from the logistic regression model included 10 independent risk factors for 6-month mortality. The Hosmer–Lemeshow test showed no significant difference between the predicted and observed outcomes (training set: 12.646, <em>P</em> ​= ​0.13; testing set: 3.807, <em>P</em> ​= ​0.87). Clinical decision curve analysis indicated that the model provided substantial net benefits across a wide range of thresholds.</div></div><div><h3>Conclusions</h3><div>Our study demonstrated that routinely collected healthcare data on the first home visit have the potential to help screen high-risk patients, which may provide evidence for targeted hospice care.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100679"},"PeriodicalIF":2.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A cross-sectional study on knowledge, attitude and practice of osteoporosis prevention in patients with breast cancer undergoing endocrine therapy: A cross-sectional study","authors":"Yan Ma ,&nbsp;Yun Li ,&nbsp;Weiwu Lu ,&nbsp;Lichen Tang ,&nbsp;Ping Li ,&nbsp;Jiajia Qiu ,&nbsp;Zhenqi Lu","doi":"10.1016/j.apjon.2025.100678","DOIUrl":"10.1016/j.apjon.2025.100678","url":null,"abstract":"<div><h3>Objectives</h3><div>This study aims to understand the current status of knowledge, health beliefs, and behavior related to osteoporosis prevention in patients with breast cancer during endocrine therapy and to analyze its influencing factors.</div></div><div><h3>Methods</h3><div>From December 2022 to June 2023, convenience sampling was used to investigate patients with breast cancer receiving endocrine therapy in a Class III Grade A hospital in Shanghai using the general information questionnaire, Osteoporosis-Related preventive Behavior Questionnaire, Osteoporosis Knowledge Questionnaire (OKT), and Osteoporosis Health Belief Scale (OHBS).</div></div><div><h3>Results</h3><div>Four hundred thirty-five questionnaires were distributed, and 403 valid questionnaires were collected, with an effective recovery rate of 92.6%. OKT failed in 282 cases (70.0%), and the standard score was (52.53 ​± ​12.01). The standard score of OHBS was (72.46 ​± ​5.79). The results of univariate analysis showed that age was negatively correlated with daily sunshine time. It was positively correlated with calcium/vitamin D supplementation and bone mineral density measurement. Multiple linear regression analysis showed that age and education level influenced OKT and OHBS scale scores (<em>P</em> ​&lt; ​0.05). Pearson correlation analysis showed a significant positive correlation between OKT and OHBS (<em>P</em> ​&lt; ​0.05).</div></div><div><h3>Conclusions</h3><div>Patients with breast cancer with endocrine therapy have poor knowledge of osteoporosis and low levels of health belief, and most of them have wrong prevention behaviors.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100678"},"PeriodicalIF":2.4,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143814940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coping strategies and psychological distress in postoperative recovery: A repeated-measures study in women undergoing breast-conserving surgery","authors":"Jennifer R. Majumdar ,&nbsp;Margaret Barton-Burke ,&nbsp;Jaime L. Gilliland ,&nbsp;Nalini N. Jairath","doi":"10.1016/j.apjon.2025.100674","DOIUrl":"10.1016/j.apjon.2025.100674","url":null,"abstract":"<div><h3>Objective</h3><div>Breast-conserving surgery (BCS) is the standard treatment for early-stage breast cancer, yet patients often experience significant psychological distress and physical symptoms during recovery. This study aimed to explore the relationships between antecedents, physical symptoms (pain and nausea), psychological distress, and coping strategies utilized by women recovering from BCS to improve management of postoperative challenges.</div></div><div><h3>Methods</h3><div>This repeated-measures descriptive study involved 75 women who underwent BCS with sentinel lymph node biopsy at a National Cancer Institute-designated center. Participants completed the National Comprehensive Cancer Network (NCCN) Distress Thermometer and Ways of Coping Instrument on Postoperative Day 1 (POD1) and POD14. Bivariate analyses, multiple linear regression, and structural equation modeling were conducted to evaluate associations between antecedents, coping strategies, and distress. Open-ended responses were qualitatively analyzed for thematic content.</div></div><div><h3>Results</h3><div>Seeking social support (POD1 mean ​= ​1.25; POD14 mean ​= ​1.20) and planful problem-solving (POD1 mean ​= ​1.19; POD14 mean ​= ​1.04) were the most frequently used coping strategies, while accepting responsibility and confrontive coping were least utilized. Overall coping strategy use decreased between POD1 and POD14, likely reflecting recovery adaptation. Significant predictors of distress included escape-avoidance coping (β ​= ​0.415, <em>P</em> ​&lt; ​0.001), social support (β ​= ​0.270, <em>P</em> ​= ​0.02), history of nausea (β ​= ​0.517, <em>P</em> ​&lt; ​0.001), and age (β ​= ​0.293, <em>P</em> ​= ​0.007). Coping strategies did not mediate the relationship between antecedents and distress.</div></div><div><h3>Conclusions</h3><div>Adaptive coping strategies such as social support and planful problem-solving play a critical role in mitigating distress during BCS recovery. Interventions should emphasize fostering these strategies and addressing high-risk groups, such as younger patients and those with a history of nausea. Despite limitations, this study underscores the importance of supporting adaptive coping to improve postoperative outcomes and provides a basis for future research.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100674"},"PeriodicalIF":2.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adolescent childhood cancer survivors talking about cancer: A socioecological perspective","authors":"Naoko Honda ,&nbsp;Yasutomo Funakoshi ,&nbsp;Yuki Matuishi ,&nbsp;Kanako Morifuji ,&nbsp;Kazuaki Tanabe","doi":"10.1016/j.apjon.2025.100676","DOIUrl":"10.1016/j.apjon.2025.100676","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed (1) to investigate the communication patterns of adolescent childhood cancer survivors (ACCSs), including their motivations, methods, context, and outcomes and (2) to identify factors influencing their cancer-related communication (cancer communication) at each level of the socioecological model.</div></div><div><h3>Methods</h3><div>A qualitative descriptive research design was adopted to explore ACCSs’ experiences of communicating about cancer and the factors influencing such experiences. Semi-structured interviews were conducted, and the collected data were analyzed using thematic analysis. This study was conducted according to the Standards for Reporting Qualitative Research.</div></div><div><h3>Results</h3><div>The ACCSs were motivated to engage in cancer-related communication by acquiring social support and an altruistic perspective. Although ACCSs rarely initiated cancer-related communication proactively, they communicated with close friends and family members about their cancer experiences. The motivation to communicate with friends shifted from sharing factual information, such as their daily lives in the hospital, to seeking emotional connections shaped by psychosocial development. Dissatisfaction with the limitations of school life and concerns about cancer were primarily discussed with parents. Furthermore, parents' perceptions of cancer and their explanations of the illness to their children appeared to influence the children's perceptions of their cancer experiences and their communication about cancer. Cancer-related communication among ACCSs was influenced by factors at multiple levels. Furthermore, institutional- and community-level factors affected individual and interpersonal factors.</div></div><div><h3>Conclusions</h3><div>A multilayered approach involving ACCSs, parents, educators, school peers, and the broader community is essential for enhancing communication about cancer within this population.</div></div>","PeriodicalId":8569,"journal":{"name":"Asia-Pacific Journal of Oncology Nursing","volume":"12 ","pages":"Article 100676"},"PeriodicalIF":2.4,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}