Stress is a nonspecific response of the body to any demand imposed upon it, disrupting the body homoeostasis and manifested with symptoms such as anxiety, depression or even headache. These responses are quite frequent in the present competitive world. The aim of this review is to explore the effect of stress on gut microbiota. First, we summarize evidence of where the microbiota composition has changed as a response to a stressful situation, and thereby the effect of the stress response. Likewise, we review different interventions that can modulate microbiota and could modulate the stress according to the underlying mechanisms whereby the gut–brain axis influences stress. Finally, we review both preclinical and clinical studies that provide evidence of the effect of gut modulation on stress. In conclusion, the influence of stress on gut microbiota and gut microbiota on stress modulation is clear for different stressors, but although the preclinical evidence is so extensive, the clinical evidence is more limited. A better understanding of the mechanism underlying stress modulation through the microbiota may open new avenues for the design of therapeutics that could boost the pursued clinical benefits. These new designs should not only focus on stress but also on stress-related disorders such as anxiety and depression, in both healthy individuals and different populations.

Aim. To synthesise the available evidence on the applicability of artificial intelligence in nursing care. Background. Artificial intelligence involves the replication of human cognitive abilities in machines, allowing to perform tasks that conventionally necessitate human cognition. However, its application in health sciences is a recent one, and its use is currently limited to supporting the diagnosis and prognosis of hospitalised patients, among others. Evaluation. A systematic review was conducted in the PubMed-Medline, Scopus, CINAHL, Web of Science, and Nursing & Allied Health databases until September 2022, following the PRISMA guidelines. Key Issues. A total of 21 articles were selected for the review. The different applications of artificial intelligence in nursing identified comprised (i) advances in early disease detection and clinical decision making; (ii) artificial intelligence-based support systems in nursing for patient monitoring and workflow optimisation; and (iii) artificial intelligence insights for nursing training and education. Conclusion. Artificial intelligence-based systems demonstrated increased autonomy of patients and professionals in care processes such as wound management through guided instructions, improved workflows, and efficiency in terms of time, materials, and human resources. Implications for Nursing Management. Artificial intelligence applied to nursing practice can be a very useful resource for professionals, managers, and supervisors. It has the potential to change current working flow systems and may serve as a down-to-earth resource to support nursing professionals in their decision-making process that ensures high quality and patient safety care.

Purpose: Gamification or learning using game elements is a process that seeks to capture students’ interest. One of the most popular games in recent years is the Escape Room, but the study of its use in education and with health professionals is still limited. The aim of this study was to find out the perceptions and experiences of final year nursing students in an Objective Structured Clinical Examination (OSCE) by means of an Escape Room. Methods: In January 2019, 9 focus groups (FG) were held, with a total of 95 final year nursing students. We applied a qualitative content analysis approach and ATLAS.ti version 8 was used for data analysis. Results: The data revealed 3 main themes and 8 sub-themes. The three main themes, which were mapped to the conceptual framework, were student learning outcomes, emotional impact on students and conclusions on the serious games experience. Both the main themes and the sub-themes were illustrated using representative quotes from the participants. Conclusions: These results can help to apply these methodologies, such as the Escape Room, alongside other pre-existing ones, complementing the way in which students are assessed and the development of important nursing skills, such as teamwork and communication.

Cancer affects more than 19.3 million people and has become the second leading cause of death worldwide. Chemo- and radiotherapy, the most common procedures in these patients, often produce unpleasant treatment-related side effects that have a direct impact on the quality of life of these patients. However, innovative therapeutic strategies such as probiotics are being implemented to manage these complications. Thus, this study aimed to evaluate the efficacy of probiotics supplements as a therapeutic strategy in adult oncology treatment-related side effects. A systematic review of randomized controlled trials was conducted in PubMed, Scielo, ProQuest and OVID databases up to and including January 2021, following the PRISMA guidelines. The quality of the included studies was assessed by the Jadad Scale. Twenty clinical trials published between 1988 and 2020 were included in this review. Seventeen studies (85%) revealed predominantly positive results when using probiotics to reduce the incidence of treatment-related side effects in oncology patients, while three studies (15%) reported no impact in their findings. This study sheds some light on the significance of chemotherapy and radiotherapy in altering the composition of gut microbiota, where probiotic strains may play an important role in preventing or mitigating treatment-related side effects.

The aim of this study is to explore the experiences and perceptions of final‐year nursing students on the acceptability and feasibility of using a chatbot for clinical decision‐making and patient safety. The effective and inclusive use of new technologies such as conversational agents or chatbots could support nurses in increasing evidence‐based care and decreasing low‐quality services. A descriptive qualitative study was used through focus group interviews. The data analysis was conducted using a thematic analysis. This study included 114 participants. After our data analysis, two main themes emerged: (i) experiences in the use of a chatbot service for clinical decision‐making and and (ii) integrating conversational agents into the organizational safety culture. The findings of our study provide preliminary support for the acceptability and feasibility of adopting SafeBot, a chatbot for clinical decision‐making and patient safety. Our results revealed substantial recommendations for refining navigation, layout and content, as well as useful insights to support its acceptance in real nursing practice. Leaders and managers may well see artificial intelligence‐based conversational agents like SafeBot as a potential solution in modern nursing practice for effective problem‐solving resolution, innovative staffing and nursing care delivery models at the bedside and criteria for measuring and ensure quality and patient safety.