"It's Just Good Science": A Qualitative Study Exploring Equity, Diversity and Inclusion in Canadian Arthritis Research.

Objective: Despite knowledge that health outcomes vary according to patient characteristics, identity, and geography, including underrepresented populations in arthritis research remains a challenge. We conducted interviews to explore how researchers in arthritis have used equity, diversity, and inclusion (EDI) principles to inform their research.

Methods: Semi-structured interviews were conducted with individuals who 1) have experience conducting arthritis research studies; 2) reside in and/or conduct their research in Canada; and 3) speak English or French.

Mapping Trust in Nurses with Dimensions of Trustworthy Artificial Intelligence: A Scoping Review.

This scoping review examines the concept of trust in nursing and its potential application in developing trustworthy Artificial Intelligence (AI) for healthcare. Recognizing nurses as highly trusted professionals, the study explores how attributes contributing to trust in nursing can inform AI development. Following the Joanna Briggs Institute framework, the review synthesizes literature on patients' perceptions of nurses' trustworthiness and compares these with desired qualities in trustworthy AI.

Fairness in Classifying and Grouping Health Equity Information.

This paper explores the balance between fairness and performance in machine learning classification, predicting the likelihood of a patient receiving anti-microbial treatment using structured data in community nursing wound care electronic health records. The data includes two important predictors (gender and language) of the social determinants of health, which we used to evaluate the fairness of the classifiers. At the same time, the impact of various groupings of language codes on classifiers' performance and fairness is analyzed.

Generating user-driven patient personas to support preventive health care activities of rural-living unattached patients.

Objective: This study created personas using quantitative segmentation and knowledge user enhancement to inform intervention and service design for rural patients to encourage preventive care uptake.

Methods: This study comprised a cross-sectional survey of rural unattached patients and a co-design workshop for persona development. Cross-sectional survey data were analyzed for meaningful subgroups based on quartiles of preventive care completion.

Nursing Informatics' Contribution to One Health.

Objectives: To summarise contemporary knowledge in nursing informatics related to education, practice, governance and research in advancing One Health.

Methods: This descriptive study combined a theoretical and an empirical approach. Published literature on recent advancements and areas of interest in nursing informatics was explored.

Differing Effects of Implementation Leadership Characteristics on Nurses' Use of mHealth Technologies in Clinical Practice: Cross-Sectional Survey Study.

Background: Leadership has been consistently identified as an important factor in shaping the uptake and use of mobile health (mHealth) technologies in nursing; however, the nature and scope of leadership remain poorly delineated. This lack of detail about what leadership entails limits the practical actions that can be taken by leaders to optimize the implementation and use of mHealth technologies among nurses working clinically.

Objective: This study aimed to examine the effects of first-level leaders' implementation leadership characteristics on nurses' intention to use and actual use of mHealth technologies in practice while controlling for nurses' individual characteristics and the voluntariness of use, perceived usefulness, and perceived ease of use of mHealth technologies.

Evaluating the representation of disaster hazards in SNOMED CT: gaps and opportunities.

Objective: Climate change, an underlying risk driver of natural disasters, threatens the environmental sustainability, planetary health, and sustainable development goals. Incorporating disaster-related health impacts into electronic health records helps to comprehend their impact on populations, clinicians, and healthcare systems. This study aims to: (1) map the United Nations Office for Disaster Risk Reduction and International Science Council (UNDRR-ISC) Hazard Information Profiles to SNOMED CT International, a clinical terminology used by clinicians, to manage patients and provide healthcare services; and (2) to determine the extent of clinical terminologies available to capture disaster-related events.

A cross-sectional study of the preventive health care activities of western Canadian rural-living patients unattached to primary care providers.

Prevention services, such as screening tests and vaccination, are underutilized, especially by rural populations and patients without a usual primary care provider. Little is known about the compounding impacts on preventive care of being unattached and living in a rural area and there has been no comprehensive exploration of this highly vulnerable population's prevention activities. The twofold purpose of this research was to examine rural unattached patients' prevention activity self-efficacy and completion and to explore their experiences accessing healthcare, including COVID-19 impacts.

Towards Automated Screening of Literature on Artificial Intelligence in Nursing.

We evaluate the performance of multiple text classification methods used to automate the screening of article abstracts in terms of their relevance to a topic of interest. The aim is to develop a system that can be first trained on a set of manually screened article abstracts before using it to identify additional articles on the same topic. Here the focus is on articles related to the topic "artificial intelligence in nursing".

The Untapped Potential of Nursing and Allied Health Data for Improved Representation of Social Determinants of Health and Intersectionality in Artificial Intelligence Applications: A Rapid Review.

Objectives: The objective of this paper is to draw attention to the currently underused potential of clinical documentation by nursing and allied health professions to improve the representation of social determinants of health (SDoH) and intersectionality data in electronic health records (EHRs), towards the development of equitable artificial intelligence (AI) technologies.

Methods: A rapid review of the literature on the inclusion of nursing and allied health data and the nature of health equity information representation in the development and/or use of artificial intelligence approaches alongside expert perspectives from the International Medical Informatics Association (IMIA) Student and Emerging Professionals Working Group.

Results: Consideration of social determinants of health and intersectionality data are limited in both the medical AI and nursing and allied health AI literature.

Artificial Intelligence -based technologies in nursing: A scoping literature review of the evidence.

Background: Research on technologies based on artificial intelligence in healthcare has increased during the last decade, with applications showing great potential in assisting and improving care. However, introducing these technologies into nursing can raise concerns related to data bias in the context of training algorithms and potential implications for certain populations. Little evidence exists in the extant literature regarding the efficacious application of many artificial intelligence -based health technologies used in healthcare.

Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative.

Aim: To develop a consensus paper on the central points of an international invitational think-tank on nursing and artificial intelligence (AI).

Methods: We established the Nursing and Artificial Intelligence Leadership (NAIL) Collaborative, comprising interdisciplinary experts in AI development, biomedical ethics, AI in primary care, AI legal aspects, philosophy of AI in health, nursing practice, implementation science, leaders in health informatics practice and international health informatics groups, a representative of patients and the public, and the Chair of the ITU/WHO Focus Group on Artificial Intelligence for Health. The NAIL Collaborative convened at a 3-day invitational think tank in autumn 2019.

COVID-19 restrictions: experiences of immigrant parents in Toronto.

Parenting is a demanding undertaking, requiring continuous vigilance to ensure children's emotional, physical, and spiritual well-being. It has become even more challenging in the context of COVID-19 restrictions that have led to drastic changes in family life. Based on the results of a qualitative interpretive descriptive study that aimed to understand the experiences of immigrants living in apartment buildings in the Greater Toronto Area, Ontario, Canada, this paper reports the experiences of 50 immigrant parents.