Artificial Intelligence is being applied in oncology to improve patient and service outcomes. Yet, there is a limited understanding of how these advanced computational techniques are employed in cancer nursing to inform clinical practice. This review aimed to identify and synthesise evidence on artificial intelligence in cancer nursing. CINAHL, MEDLINE, PsycINFO, and PubMed were searched using key terms between January 2010 and December 2022. Titles, abstracts, and then full texts were screened against eligibility criteria, resulting in twenty studies being included. Critical appraisal was undertaken, and relevant data extracted and analysed. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Artificial intelligence was used in numerous areas including breast, colorectal, liver, and ovarian cancer care among others. Algorithms were trained and tested on primary and secondary datasets to build predictive models of health problems related to cancer. Studies reported this led to improvements in the accuracy of predicting health outcomes or identifying variables that improved outcome prediction. While nurses led most studies, few deployed an artificial intelligence based digital tool with cancer nurses in a real-world setting as studies largely focused on developing and validating predictive models. Electronic cancer nursing datasets should be established to enable artificial intelligence techniques to be tested and if effective implemented in digital prediction and other AI-based tools. Cancer nurses need more education on machine learning and natural language processing, so they can lead and contribute to artificial intelligence developments in oncology.

In the wake of the COVID-19 pandemic, the fluctuating nurse resignation rates highlighted an understudied area in healthcare: post-pandemic challenges in clinical settings. This study, conducted from May to November 2023, employed a qualitative inquiry using focus groups to delve into these challenges. Six focus group sessions, involving 33 nurse participants recruited through snowball sampling from various hospital settings were conducted to explore their clinical experiences during and after the pandemic. Thematic analysis revealed two primary themes: the 'Invisibility of Nurses' within the healthcare system and the 'Moral Duty of Nursing Practice'. These findings illuminate a tension between the overlooked role of nurses and their ethical obligations, underscoring a critical need for policy reassessment. The study advocates for systemic changes, particularly in the undervaluation of the nursing profession and the National Health Insurance system, to address the poor working environment and mitigate long-term nursing shortages. This research deepens understanding of post-pandemic nursing workforce challenges in Taiwan, highlighting the need for policy evolution to enhance recognition and support for the nursing industry. It is suggested to provide tangible compensation to acknowledge nurses' daily care and health education for patients. A healthier working environment can be enhanced by collaborative efforts between healthcare institutions and nurses.

Purpose The study aims to investigate long-term psychological distress and its risk factors in the burn survivors. Design A longitudinal study with follow-up interviews was conducted from November 2015–June 2018. A post-burn baseline interview was conducted 6 months after the event, followed by annual surveys for three years. Methods The burn survivors received structured assessment through telephone in the four-wave interviews, including the five-item Brief Symptom Rating Scale (BSRS-5); two-item Patient Health Questionnaire (PHQ-2); four-item Startle, Physiological Arousal, Anger, and Numbness Scale (SPAN-4); and six-item Impact of Event Scale (IES-6) alongside demographic data and other health-related assessment. Findings A total of 180 respondents with the mean age of 23 years old completed the four waves of interview. Using the BSRS-5 as the outcome, each variable had different input in psychological distress during the follow-up years. The main finding was that the SPAN-4 score could predict more than 62% of psychological distress between 6 months and 3 years after the disaster. The generalized estimating equation demonstrated that SPAN-4, IES-6, family functioning impairment, hypnotics use, adaptation to the event, and PHQ-2 could predict psychological distress. However, the variable of follow-up year did not exemplify significant estimation in the model. Conclusions The results indicated that different factors had various influences on psychological distress across the four follow-up stages. PTSD-like symptoms, depression, and anxiety were the most common psychological problems experienced by the young burn cohort in the longitudinal post-traumatic period. Clinical relevance Healthcare providers should be aware of psychological consequences of traumatic events within up to a 3-year post-burn period, particularly post-traumatic stress, depression, and anxiety symptoms.

This study investigated how relocation patterns affect disaster survivors’ psychological stress on the diverse durations and spaces of relocation. It analyzed a 10-year data set of 1,236 families affected by 2009’s Typhoon Morakot in Taiwan, identifying six relocation patterns through dynamic time warping (DTW). A hierarchical linear model was utilized, revealing the discernible impacts of environmental factors, sociocultural factors, and family-level socioeconomic factors on psychological stress. The study revealed that survivors who quickly found stable residences after the disaster initially experienced lower stress levels, but in the long term, their stress increased. Conversely, those with unstable residences experienced higher initial stress but lower long-term stress. Comparing similar patterns, we found that survivors who had more time for preparation and who sought opportunities, coped, or adapted to secondary stressors before long-distance relocation faced lower stress levels. These findings suggest that relocation patterns have a greater impact on the psychosocial stress of disaster survivors than time or relocation distance.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Type 2 diabetes is a chronic disease with significant medical burden. eHealth care integrates medicine and technology to enhance such patient outcomes; however, adequate eHealth literacy (eHL) is necessary for that to happen. Fostering eHL is crucial for diabetes patients to engage with eHealth care and receive quality care and timely support. Experiential learning theory can enhance patients’ eHL and skills to use eHealth care technology in their daily care. Objective: This study explored the effectiveness of an eHealth care experiential learning program in improving eHL, patient health engagement, and eHealth usage status among patients with type 2 diabetes. Methods: In this randomized controlled trial, patients under case management services from various clinics were randomly assigned to either the intervention group receiving the six-section eHealth care experiential learning program or the control group receiving usual care. Data were collected using structured questionnaires at three-time points: pre-test, post-intervention, and three months after the intervention. Descriptive data were presented using frequency distribution, percentage, average, and standard deviation. The outcomes were analyzed using a generalized estimating equation by intention to treat analysis. Results: 92 participants (46 in each group) were recruited in this study. Of these, 86 completed the course and follow-up evaluations, with an average age of 62.38 years (standard deviation [SD] = 12.91). After completing the intervention, the intervention group had significantly higher post-test scores in eHL (β = 19.94, standard error [SE] = 3.52, P < .001), patient health engagement (β = 0.28, SE = 0.13, P = .037), and eHealth usage status (β = 3.96, SE = 0.42, P < .001) than that in the control group. Furthermore, the intervention group maintained these significant improvements in eHL (β = 18.19, SE = 3.82, P < .001) and eHealth usage status (β = 3.87, SE = 0.49, P < .001) after three months. Conclusions: Receiving the eHealth care experiential learning program resulted in significant improvements in eHL, patient health engagement, and eHealth usage among patients with type 2 diabetes. Our interventional program can inform future clinical practice and policies to strengthen self-management skills and facilitate the use of health technology in caring for patients with chronic diseases in future clinical practice and procedures. Clinical Trial: ClinicalTrials.gov NCT05180604 (https://clinicaltrials.gov/ct2/show/NCT05180604)