Background Artificial Intelligence (AI) techniques are being applied in nursing and midwifery to improve decision‐making, patient care and service delivery. However, an understanding of the real‐world applications of AI across all domains of both professions is limited. Objectives To synthesise literature on AI in nursing and midwifery. Methods CINAHL, Embase, PubMed and Scopus were searched using relevant terms. Titles, abstracts and full texts were screened against eligibility criteria. Data were extracted, analysed, and findings were presented in a descriptive summary. The PRISMA checklist guided the review conduct and reporting. Results One hundred and forty articles were included. Nurses’ and midwives' involvement in AI varied, with some taking an active role in testing, using or evaluating AI‐based technologies; however, many studies did not include either profession. AI was mainly applied in clinical practice to direct patient care (n = 115, 82.14%), with fewer studies focusing on administration and management (n = 21, 15.00%), or education (n = 4, 2.85%). Benefits reported were primarily potential as most studies trained and tested AI algorithms. Only a handful (n = 8, 7.14%) reported actual benefits when AI techniques were applied in real‐world settings. Risks and limitations included poor quality datasets that could introduce bias, the need for clinical interpretation of AI‐based results, privacy and trust issues, and inadequate AI expertise among the professions. Conclusion Digital health datasets should be put in place to support the testing, use, and evaluation of AI in nursing and midwifery. Curricula need to be developed to educate the professions about AI, so they can lead and participate in these digital initiatives in healthcare. Relevance for clinical practice Adult, paediatric, mental health and learning disability nurses, along with midwives should have a more active role in rigorous, interdisciplinary research evaluating AI‐based technologies in professional practice to determine their clinical efficacy as well as their ethical, legal and social implications in healthcare.

The study provides key insights for health practitioners interested in promoting the use of an alerting device in community-dwelling older people.

The 21st century has seen several infectious disease outbreaks that have turned into epidemics and pandemics including Severe Acute Respiratory Syndrome (SARS) which began in Asia in 2003 (Poon,

PurposeTo explore the needs and preferences of community-dwelling older people, by involving them in the device design and mock-up development stage of a fall detection device, consisting of a body-worn sensor linked to a smartphone application.Patients and methodsA total of 22 community-dwelling persons 75 years of age and older were involved in the development of a fall detection device. Three semistructured focus group interviews were conducted. The interview data were analyzed using qualitative descriptive analysis with deductive coding.ResultsThe mock-up of a waterproof, body-worn, automatic and manual alerting device, which served both as a day-time wearable sensor and a night-time wearable sensor, was welcomed. Changes should be considered regarding shape, color and size along with alternate ways of integrating the sensor with items already in use in daily life, such as jewelry and personal watches. The reliability of the sensor is key for the participants. Issues important to the alerting process were discussed, for instance, who should be contacted and why. Several participants were concerned with the mandatory use of the smartphone and assumed that it would be difficult to use. They criticized the limited distance between the sensor and the smartphone for reliable fall detection, as it might restrict activity and negatively influence their degree of independence in daily life.ConclusionThis study supports that involving end users in the design and mock-up development stage is welcomed by older people and allows their needs and preferences concerning the fall detection device to be explored. Based on these findings, the development of a “need-driven” prototype is possible. As participants are doubtful regarding smartphone usage, careful training and support of community-dwelling older people during real field testing will be crucial.