In recent years, the use of mobile health applications (mHealth apps) to deliver care for patients with breast cancer has increased exponentially. This study aimed to summarize the available evidence on developing mHealth apps to care for patients with breast cancer and identify the need for systematic efforts. A scoping review was performed according to Arksey and O’Malley’s framework, aiming to identify eligible research studies in PubMed, CINAHL, and Web of Science between January 2010 and December 2020. All identified studies were screened, extracted, and analyzed independently by two reviewers. A total of 676 studies were retrieved, and eight eligible studies were finally included. Four themes emerged: the involvement of patients and health professionals in the phases of design and development, patients’ preferences, the characteristics of patients, and the motivators to use mHealth apps. The results indicated promising prospects for using mHealth apps to care for patients with breast cancer and identified the need for systematic efforts to develop and validate relevant apps. The attributes of patient characteristics, needs, and patient-reported outcomes data are vital components for developing mHealth apps for patients with breast cancer. Additionally, collaborative efforts, including patients, nurses, and other significant health professionals, should develop mHealth apps for breast cancer care. Additional research focusing on the design and development of mHealth apps for patients with breast cancer is warranted.

Background: As artificial intelligence (AI) continues to advance in healthcare, limited research has explored how nursing professionals perceive its integration into clinical practice and education—particularly among those directly involved in AI-driven initiatives. This qualitative study aimed to investigate the perceptions, experiences, and expectations of nursing educators and clinical practitioners regarding the application of AI in nursing and to provide insights for the advancement of AI-driven nursing science. Methods: A descriptive qualitative design was employed. Between September and December 2024, semi-structured interviews were conducted with 12 nursing professionals from universities and hospitals in Shanghai, Suzhou, and Chengdu, China. Participants were selected using maximum variation sampling, and data were analyzed using content analysis. Results: Three major themes and eleven sub-themes were identified: (1) The potential of multi-perspective development of AI-driven nursing science and practice, including aiding in decision-making, assisting with writing nursing documents, helping in care practices with high exposure risks and heavy physical exertion, and supporting the development of nursing activities. (2) A multi-dimensional response to the wave of intelligent nursing research and practice: education and scientific research come first, then we fully explore the application scenarios, and then conduct deep interdisciplinary integration. (3) Obstacles for intelligent nursing research and practice: interaction factors of “human–technology–machine” for application, transformation, and promotion; financial support and continuous investment; the controversy behind the intelligent maturity level; and application risk and fault tolerance. Conclusions: Participants emphasized the importance of evidence-based, cautious, and context-sensitive application of AI technologies to ensure that intelligent nursing evolves in alignment with clinical realities. The findings suggest a need for strengthened policy, education, and resource allocation to support the sustainable integration of AI in nursing.

Background: The PROMIS-57 is a commonly used self-reported instrument to solve the lack of generalizable and universal measures required to evaluate common symptoms and functions from patients’ perspectives. This study aimed to translate the PROMIS-57 into Chinese and psychometrically test the translated instrument on patients with breast cancer. Methods: Translation, cross‑cultural adaptation, and psychometric evaluation of the instrument were performed from June 2020 to June 2021. Eligible patients were recruited and completed the PROMIS-57, Functional Assessment of Cancer Therapy-Breast (FACT-B), and a sociodemographic questionnaire. Results: Data from 602 patients with a mean age of 48.83 years were analyzed. Most domains in the PROMIS-57 showed an absence of floor and ceiling effects. Multi-trait scaling analysis demonstrated acceptable convergent and discriminant validity. The correlations between the PROMIS-57 scores and the selected FACT-B scores supported the criterion validity via the Pearson correlation test. Measurement invariance was supported by the absence of differential item functioning for most items. Cronbach’s α of the domains ranged from 0.85–0.95. The unidimensional factor structure of all domains was supported using confirmatory factor analyses. Additionally, most items showed acceptable item information curves and item characteristics curve matrices. Conclusion: The Chinese version of the PROMIS-57 was found to be a reliable and valid tool for assessing common symptoms and functions among patients with breast cancer.

This study aimed to synthesize the available knowledge of symptom trajectories in patients with breast cancer and identify predictors associated with these trajectories. Whittemore and Knafl’s integrative review method was employed to guide a systematic search for literature in four databases (PubMed, Embase, Web of Science, and CINAHL). The retrieved articles’ publication time was limited to 2010 to 2020, and only peer-reviewed English articles were included. Twenty-seven articles were included. The findings of the relevant studies were analyzed using thematic analysis. They were grouped into two themes: symptom trajectories of patients with breast cancer (symptom trajectories in patients with breast cancer, in patients who underwent surgery, and in patients who received cancer-related treatment) and associated factors (socioeconomic factors, health characteristics, cancer-related treatment characteristics). Newly diagnosed patients tended to report high trajectories of depression and persistent sleep disturbance. Most patients who underwent surgery reported significant sleep disturbance and anxiety shortly after surgery. For patients who received cancer-related treatment, only a small proportion had a high level of physical activity after cancer-related therapy over time. A high body mass index, a low relationship quality, parental responsibilities, insufficient social support, a low educational background, and an unhealthy lifestyle may increase the risk of negative symptom trajectories in patients with breast cancer. Additionally, old patients were more likely to report cognitive impairment after chemotherapy, while young patients tended to report trajectories of persistent sexual dysfunction. Concurring symptoms and poor health status also contributed to adverse symptom trajectories. The findings of this review add to the body of knowledge of the interindividual variability of symptom trajectories in patients with breast cancer. Despite the overall similarity in appraisal at baseline, the patients reported varied symptom trajectories over time. It is recommended that nurses consider sociodemographic, clinical and cancer-related treatment characteristics and perform targeted early preventive interventions for patients with breast cancer.

Fatigue is the most frequent and distressing symptom affecting the physical, cognitive, and affective domains of breast cancer patients. The Functional Assessment of Chronic Illness Therapy–Fatigue (FACIT–F) has been widely used in patients with chronic diseases and has shown satisfactory reliability and validity. This study aimed to examine the psychometric properties of the FACIT–F among Chinese patients with breast cancer. Using a convenience sampling method, a cross–sectional survey (January 2020 and September 2022) was used with patients recruited from two tertiary hospitals in Shanghai, Mainland China, and a total of 597 patients completed a demographic information questionnaire, the FACIT–F and the Functional Assessment of Cancer Therapy for Breast Cancer (FACT–B). Convergent validity was estimated by calculating the Pearson correlation coefficient of the FACIT–F with the FACT–B. Measurement invariance across age was performed by examining differential item functioning (DIF) across age groups (≤ 60 and > 60 years). The internal consistency and split–half reliability were performed for reliability analysis. Unidimensionality of the scale was evaluated by the principal component analysis by Rasch analysis. Additionally, Rasch analysis was performed for item difficulty levels, and an item–person map was used. No floor/ceiling effects were observed for the FACIT–F. Moderate correlations were found between FACIT–F and FACT–B (r = − 0.342, p < 0.01). Most items showed an absence of DIF regarding age, except for one item. In addition, the FACIT–F showed acceptable internal consistency. Principal component analysis of Rasch residuals showed that the proportion of variance explained by the FACIT–F was 53.3%, and the outfit mean square statistics for the items ranged from 0.68 to 1.90 and the infit MNSQ from 0.63 to 1.73. Additionally, an acceptable response between items and persons was found. The findings indicate that the Chinese version of the FACIT–F is a valid tool for the measurement of fatigue in breast cancer patients.