Community Health Nurses' Perceptions of Emerging Artificial Intelligence and its Impact on Nursing Practice: An Explanatory Sequential Mixed Methods Study.
Jul 2026· The Canadian journal of nursing research = Revue canadienne de recherche en sciences infirmieres· pp.
8445621261463882
· 0 citations· 49 references
Medicine
TL;DR
Dedicated time for AI education for CHNs is needed to address how recommendations are generated and the significance to give to AI recommendations, clear policies and guidelines need to be established to inform CHNs use of AI.
Abstract
BackgroundArtificial intelligence (AI) continues to emerge into nursing practice with much of the AI research being conducted in the acute care sector. Community health nurses (CHNs) have distinct skills and knowledge focusing on helping clients to live well in the community. Community practice is an essential part of healthcare yet often overlooked, creating a knowledge gap. This research aims to understand CHNs' knowledge and perceptions of AI to inform future practice.MethodAn explanatory sequential mixed methods design was conducted, a cross-sectional survey followed by focus groups to combine both sets of results for a comprehensive perspective.ResultsThere were 228 survey respondents and 27 participants forming 8 focus groups. The survey revealed professional concerns: AI giving a wrong recommendation (77.7%) or if a correct recommendation was dismissed (73.8%) with focus groups explaining they knew their responsibility in decision-making, their concerns focused on accepting AI recommendations blindly or using recommendations to assist with decision-making. Overall CHNs felt AI applications had usefulness (68.8%-88%), the focus groups further explained clinical relevance, user friendly and time efficiency were factors that would determine usefulness.ConclusionsDedicated time for AI education for CHNs is needed to address how recommendations are generated and the significance to give to AI recommendations. Clear policies and guidelines need to be established to inform CHNs use of AI. Success of AI in CHNs practice is dependent on applications that do not add time to their busy schedules.
The weak negative correlation between knowledge and attitudes suggests that greater awareness of AI may be accompanied by increased concerns regarding its use, and further educational initiatives are needed to enhance nurses’ preparedness for AI integration in clinical practice.
R. Elsayed, A. Nagy, Eman Sobhy El-Said Hussein et al.· BMC Nursing· 1 citation
Background: Artificial Intelligence Health Technologies (AIHTs) are rapidly transforming healthcare delivery systems worldwide. Nursing students, as future healthcare professionals, must be prepared to adapt to emerging AI-driven clinical environments. Evaluating their awareness, perceptions, readiness, and expected professional impact is essential for strengthening nursing education and practice. Objectives: This study aimed to evaluate the foresighted effects of Artificial Intelligence Health Technologies on nursing students in terms of knowledge, attitude, readiness, perceived benefits, and anticipated challenges in clinical practice.
Methods: A descriptive cross-sectional study was conducted among undergraduate nursing students using a structured questionnaire. Data were collected regarding demographic variables, awareness of AIHTs, perceived usefulness, expected professional impact, and concerns regarding ethical and technical challenges. Statistical analysis included descriptive and inferential methods.
Results: The study findings revealed that most nursing students demonstrated moderate awareness of AIHTs and expressed positive attitudes toward integrating AI technologies into healthcare settings. Students perceived AI as beneficial for improving patient care accuracy, reducing workload, and supporting clinical decision-making. However, concerns regarding reduced human interaction, ethical issues, and lack of technical training were also reported.
Conclusion: Nursing students showed a favorable perception toward AIHTs but emphasized the need for structured training programs within nursing curricula. Integrating AI education into nursing programs will enhance preparedness for future clinical practice and promote effective utilization of AI-based healthcare systems.
L. G, Rajesh Mishra· International Journal For Mu...· 0 citations
Thematic analysis revealed that various factors underpinning their attitudinal, normative, and control beliefs are critical determinants of nurses' and students' overall experiences with GenAI and their intentions to use GenAI technologies.
Ming Wei Jeffrey Woo, Adrian Heng Tsai Tan· Nursing and Health Sciences· 0 citations
In recent times, nursing students have been utilizing artificial intelligence (AI) technology, as they perceive it boosts learning outcomes and academic performance and transforms several facets of healthcare. This study aimed to explore nursing students' knowledge, attitudes and perceptions concerning the adoption of AI in their academic and clinical areas. It applied an exploratory study design to cover the study population of all undergraduate students, including interns from selected private nursing colleges in Tamil Nadu, India (N = 440). A self-designed online questionnaire was distributed via Google Forms to the target population and 317 responded. The results showed that 81.3% were familiar with the term "AI" (81.3%). 76.3% recognized that AI would revolutionize the nursing field. Most nursing students consented that AI should be included in undergraduate (67.2%) and postgraduate (71.3%) nursing curricula. 77.9% perceived that AI would be helpful for their future career. A significant variation was observed in nursing students' knowledge, attitude and perception scores across age categories, but not for gender and year of study. This study concluded that female nursing students, especially those aged 17-19, demonstrated strong knowledge, an optimistic attitude and had a better perception of AI. The findings suggest that nursing students in India possess adequate knowledge about AI, indicating a positive perception that AI plays a transformative function in nursing education and practice, with a need for more focused training and integration into the curriculum.
Arul Valan, Latha S Kannan, A. Subbarayalu et al.· International Research Journ...· 0 citations
Objectives
This study aimed to understand how AI's perceived role interacts with emerging barriers and facilitators to identify factors influencing its adoption across clinical and educational professions in Singapore.
Methods
This study followed a qualitative approach guided by a medical-pedagogical theoretical framework. Semi-structured interviews were conducted between May and July 2025 and followed an interview guide based on the medical-pedagogical framework. Twenty-four people participated, including eight nurses, six psychiatrists, and 10 allied health professionals. All were clinicians and educators. Data were analysed using thematic analysis, with attention to emergent patterns across patient care and educational contexts.
Results
Participants recognised significant potential for AI in patient care and healthcare professions education, particularly for information access, retrieval, clinical documentation, AI-augmented training methods such as virtual patients and educational content creation. Barriers included fears of professional skill degradation, role confusion, lack of familiarity with capabilities and the need for personal evidence of benefit. Enablers encompassed integrated, context-specific training, clear governance frameworks, and peer networks facilitating experiential learning and responsible use. Participants emphasised maintaining human connection and reflective practice as essential to psychiatric care and education.
Conclusions
Effective AI adoption in psychiatric care and education can be facilitated by clearly delineating tasks, embedding digital literacy into training, communicating robust governance structures, and introducing peer-led communities of practice. Relevant stakeholders should be engaged to align AI deployment with real clinical workflows, optimising both patient care and educational outcomes.
D. Poremski, K. Wei, B. Ng et al.· International Journal of Med...· 0 citations
Profile-tailored strategies may help nursing managers facilitate the effective and sustainable implementation of AI technologies in clinical practice and to explore the factors associated with profile membership with type affiliation.