Asia-Pacific Journal of Oncology Nursing最新文献

Objective: This study aimed to explore how patients with lung cancer perceive and cope with the fatigue-pain-sleep disturbance symptom cluster.

Methods: A descriptive qualitative study was conducted using individual semi-structured interviews with 20 patients with lung cancer recruited from the medical and radiation oncology departments of a tertiary hospital in China in January 2025. Data were analyzed following Braun and Clarke's six-phase thematic analysis approach.

Results: Three overarching themes and ten subthemes were identified. (1) Symptom Awareness and Bodily Perception: individual differences in bodily sensitivity, temporal recognition of symptom progression within the cluster, and distress that cannot be easily articulated. (2) How the Symptom Cluster Disrupts Life: erosion of physical function, heightened emotional volatility, guilt associated with being a burden, and involuntary social withdrawal. (3) Learning to Live with the Cluster: reflective attribution, active adaptation, and passive acceptance.

Conclusions: The fatigue-pain-sleep disturbance symptom cluster presents in varying patterns and exerts profound multidimensional impacts on patients with lung cancer. Patients recognize the cluster by perceiving the sequential and interconnected onset of symptoms. Coping strategies span cognitive reframing, proactive self-management, and passive endurance. Future research should integrate subjective experiences with objective assessments to refine core symptom cluster identification, tailor individualized intervention targets, and develop effective management strategies. Empowerment-based approaches may support patients who engage actively in coping, while knowledge-based guidance and emotional support are essential for those who adopt more passive strategies.

Objective: This study aimed to assess the level of preparedness for natural disasters among clinical practitioners who are members of the Japanese Society of Cancer Nursing and identify essential key elements of oncology nursing associated with disaster preparedness.

Methods: A cross-sectional, web-based survey was conducted via email invitation targeting full members of the Japanese Society of Cancer Nursing between November 22, 2024, and January 10, 2025. Forced-entry multiple linear regression analysis was performed with disaster preparedness as the dependent variable.

Results: Of the 5303 members invited, 149 were included in the analysis. Sufficient preparedness was observed in areas such as awareness of potential disruptions to cancer treatment and nursing care during disasters. Conversely, communication strategies during disasters, stockpiling of essential supplies, and knowledge of governmental support systems were identified as areas of insufficient preparedness. Overall disaster preparedness was significantly influenced by the level of institutional disaster preparedness. Significant regression models were developed for 8 of the 17 preparedness items, with institutional disaster preparedness emerging as the strongest predictor for all 8 items. Additionally, the large-scale earthquakes and the possibility of future earthquakes were also predictive factors.

Conclusions: Oncology nurses recognized the risk of interruptions to treatment and nursing care during disasters; however, their knowledge of disaster preparedness and available support systems was insufficient. Their level of preparedness was associated with their institution's disaster preparedness, prior experience with large-scale earthquakes, and exposure to potential disasters such as earthquakes. To ensure effective preparation for future disasters, oncology nurses must enhance their understanding of disaster risks and strengthen organizational preparedness.

Objective: Breast cancer survivors experience significant physical and psychosocial changes after mastectomy, making them vulnerable to mental health challenges such as depression, anxiety, and social dysfunction. This study identifies factors influencing the mental health of breast cancer survivors using Roy's Adaptation Model (RAM), which provides a framework for understanding adaptation processes and their impact on health outcomes.

Methods: A cross-sectional structural equation modeling (SEM) study was conducted to develop and validate a hypothetical model based on RAM. Data were collected through an online survey administered from February 1 to 28, 2023, to female breast cancer survivors who had undergone mastectomy at least one year but less than five years before the commencement of the study. A total of 346 participants from an online community of patients with breast cancer were included in the final analysis. Statistical analyses were performed using IBM SPSS 26.0 and AMOS 28.0.

Results: The goodness-of-fit indices for the structural model indicated acceptable fit (goodness-of-fit index [GFI] ​= ​0.82; RMR ​= ​0.05; comparative-fit-index [CFI] ​= ​0.85; root mean square error of approximation [RMSEA] ​= ​0.09). Seven of the eight hypothesized paths were significant. Coping and adaptation processes directly influenced symptom experience, body image, role performance, and social support and indirectly affected mental health. Body image, role performance, and social support collectively explained 88% of the variance in mental health outcomes. Multigroup SEM analysis revealed differences in the structural paths based on breast reconstruction status.

Conclusions: Effective mental health assessment and intervention for breast cancer survivors undergoing mastectomy requires an integrated approach that considers coping processes, body image, role performance, and social support. Nurses should focus on strengthening adaptive coping strategies, fostering a positive body image, managing role-related stress, and enhancing social support systems to improve survivors' overall mental well-being.

Objective: This study aimed to clarify the subtypes of electronic health literacy among patients with lung cancer surgery and explore the factors affecting profile membership.

Methods: A cross-sectional study utilizing surveys among patients who underwent lung cancer surgery (n ​= ​354). Patients completed the general demographic questionnaire, eHealth literacy scale, strategies used by people to promote health scale, perceived social support scale, and functional assessment of cancer therapy lung cancer scale. Data analyses involved latent profile analysis, variance analysis, Chi-square tests, and multivariate logistic regression.

Results: A total of 354 valid questionnaires were collected and categorized into three latent classes based on eHealth literacy levels among post-operative patients with lung cancer: "Low eHealth Literacy," "Moderate eHealth Literacy," and "High eHealth Literacy". Each profile exhibited distinct characteristics representative of the different levels of eHealth literacy among these patients. Factors such as age, educational attainment, occupation type, monthly household income, presence of chronic diseases, daily use of smart devices, frequency of health information searches, variety of eHealth information sources, self-management efficacy, and levels of social support were identified as influencing the eHealth literacy of postoperative patients with lung cancer across these categories.

Conclusions: eHealth literacy among postoperative patients with lung cancer exhibits distinct classification characteristics, with over half falling into low or moderate levels. Identifying the sociodemographic factors and influences affecting different patient groups is crucial for developing internet-based continuity of care measures tailored to the specific needs of these patients.