Artificial intelligence across community, mental and child health nursing: a future-ready framework for precision, preventive and person centered care

Joy Priscilla; K. Rakhee Sarkar; Akanksha Anjali; Sivakumar Anusha; Gomathi Munusamy; Pradeep Kumar; Ghanshyam Singh; Gomathi; Balamurugan E.; Virat Shankar Gore; Trilok Chand Sharma; Mohammed Umar

doi:10.18203/2394-6040.ijcmph20264136

Authors

Joy Priscilla Department of Child Health Nursing, Bengaluru, Karnataka, India
K. Rakhee Sarkar Department of Community Health Nursing, Navodaya College of Nursing, Rajiv Gandhi University of Health Sciences (RGUHS), Raichur/ Bengaluru, Karnataka, India
Akanksha Anjali Department of Child Health Nursing, MGM College of Nursing and Paramedical, Patna, Bihar, India
Sivakumar Anusha Department of Psychiatry Nursing, Sri Devi College of Nursing, The Tamil Nadu Dr. M. G. R. Medical University, Chennai, Tamil Nadu, India
Gomathi Munusamy Department of Community Health Nursing, Indira Gandhi School and College of Nursing, Atal Bihari Vajpayee Medical University, Amethi, Uttar Pradesh, India
Pradeep Kumar Department of Community Health Nursing, Saraswathi College of Nursing, Atal Bihari Vajpayee Medical University, Hapur, Uttar Pradesh, India
Ghanshyam Singh Department of Community Health Nursing, Saraswathi College of Nursing, Atal Bihari Vajpayee Medical University, Hapur, Uttar Pradesh, India
Gomathi Department of Medical-Surgical Nursing, Sakthi College and School of Nursing, The Tamil Nadu Dr. M. G. R. Medical University, Karur, Tamil Nadu, India
Balamurugan E. Department of Nursing, Indira Gandhi Government General Hospital and Post Graduate Institute, Puducherry, India
Virat Shankar Gore Department of Mental Health Nursing, Pharate Patil B.Sc. Nursing College, Maharashtra University of Health Sciences (MUHS), Shirur, Pune, Maharashtra, India
Trilok Chand Sharma Department of Psychiatry, King George's Medical University (KGMU), King George's Medical University (KGMU), Lucknow, Uttar Pradesh, India
Mohammed Umar Department of Nursing, Uttar Pradesh University of Medical Sciences (UPUMS), Uttar Pradesh University of Medical Sciences (UPUMS), Saifai, Etawah, Uttar Pradesh, India https://orcid.org/0000-0001-8249-3803

DOI:

https://doi.org/10.18203/2394-6040.ijcmph20264136

Keywords:

Artificial intelligence, Community health nursing, Mental health nursing, Child health nursing, Precision nursing, Preventive healthcare, Person-centered care, Machine learning, Digital health, Predictive analytics

Abstract

Artificial intelligence (AI) is transforming healthcare by enabling precision, predictive, and person-centered approaches that enhance the quality, accessibility, and efficiency of nursing care. Community, mental, and child health nursing are increasingly benefiting from AI-driven innovations, including machine learning, deep learning, natural language processing, predictive analytics, clinical decision support systems, wearable technologies, conversational AI, and telehealth platforms. These technologies facilitate early disease detection, population health surveillance, risk prediction, personalized interventions, remote patient monitoring, developmental screening, mental health assessment, and evidence-based clinical decision-making. This narrative review synthesizes contemporary evidence on the integration of AI across community, mental, and child health nursing and explores its implications for preventive healthcare, health promotion, and holistic patient management. Relevant literature published between 2018 and 2026 was identified through major electronic databases, including PubMed, Scopus, Web of Science, CINAHL, Embase, PsycINFO, IEEE Xplore, and Google Scholar. The reviewed evidence demonstrates that AI improves healthcare accessibility, strengthens continuity of care, enhances diagnostic accuracy, supports personalized nursing interventions, and optimizes resource utilization. However, successful implementation requires addressing challenges related to ethical governance, algorithmic bias, data privacy, cybersecurity, interoperability, digital infrastructure, and AI competency among nurses. The review concludes that AI should function as a clinical decision-support tool that complements, rather than replaces, professional nursing judgment. Strategic investment in digital health education, interdisciplinary collaboration, and responsible AI governance will be essential for developing future-ready nurses capable of delivering equitable, evidence-based, and compassionate healthcare across diverse populations.

References

Topol EJ. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. New York: Basic Books; 2019. Available at: https://www.basicbooks.com/titles/eric-topol/deep-medicine/9781541644632. Accessed on 23 September 2026.

World Health Organization. Ethics and Governance of Artificial Intelligence for Health: WHO Guidance. Geneva: World Health Organization; 2021. Available at: https://www.who.int/publications/i/item/9789240029200. Accessed on 23 September 2026.

World Health Organization. Global Strategy on Digital Health 2020–2025. Geneva: World Health Organization; 2021. Available at: https://www.who.int/publications/i/item/9789240020924. Accessed on 23 September 2026.

Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019;25(1):44-56.

Jiang F, Jiang Y, Zhi H, Dong Y, Li H, Ma S, et al. Artificial intelligence in healthcare: past, present and future. Stroke Vasc Neurol. 2017;2(4):230-43.

Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J. 2019;6(2):94-8.

Esteva A, Robicquet A, Ramsundar B, Kuleshov V, DePristo M, Chou K, et al. A guide to deep learning in healthcare. Nat Med. 2019;25(1):24-9.

Rajkomar A, Dean J, Kohane I. Machine learning in medicine. N Engl J Med. 2019;380(14):1347-58.

Yu KH, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat Biomed Eng. 2018;2(10):719-31.

Briganti G, Le Moine O. Artificial intelligence in medicine: today and tomorrow. Front Med. 2020;7:27.

Wahl B, Cossy-Gantner A, Germann S, Schwalbe NR. Artificial intelligence (AI) and global health: how can AI contribute to health in resource-poor settings? BMJ Glob Health. 2018;3:e000798.

Morley J, Machado CCV, Burr C, Cowls J, Joshi I, Taddeo M, et al. The ethics of AI in health care: a mapping review. Soc Sci Med. 2020;260:113172.

Secinaro S, Calandra D, Secinaro A, Muthurangu V, Biancone P. The role of artificial intelligence in healthcare: a structured literature review. BMC Med Inform Decis Mak. 2021;21:125.

Bohr A, Memarzadeh K, editors. Artificial Intelligence in Healthcare. London: Academic Press; 2020.

Coiera E. Guide to Health Informatics. 4th ed. Boca Raton: CRC Press. 2024.

Lee EE, Torous J, De Choudhury M, Depp CA, Graham SA, Kim HC, et al. Artificial intelligence for mental health care: clinical applications, barriers, facilitators, and artificial wisdom. Biol Psychiatry Cogn Neurosci Neuroimaging. 2021;6(9):856-64.

Vaidyam AN, Wisniewski H, Halamka JD, Kashavan MS, Torous J. Chatbots and conversational agents in mental health: a review of the psychiatric landscape. Can J Psychiatry. 2019;64(7):456-64.

Fitzpatrick KK, Darcy A, Vierhile M. Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): a randomized controlled trial. JMIR Ment Health. 2017;4(2):e19.

Topaz M, Pruinelli L. Big data and artificial intelligence in nursing: implications for the future of nursing practice. Nurs Outlook. 2017;65(5):587-9.

Ronquillo CE, Peltonen LM, Pruinelli L, Chu CH, Bakken S, Beduschi A, et al. Artificial intelligence in nursing: priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative. J Adv Nurs. 2021;77(9):3707-17.

Topaz M, Murga L, Gaddis KM, McDonald MV, Bar-Bachar O, Goldberg Y, et al. Mining fall-related information in clinical notes using natural language processing. J Biomed Inform. 2019;98:103270.

Ronquillo CE, Peltonen LM, Pruinelli L, Chu CH, Bakken S, Beduschi A, et al. Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative. J Adv Nurs. 2021;77(9):3707-17.

Buchanan C, Howitt ML, Wilson R, Booth RG, Risling T, Bamford M. Predicted influences of artificial intelligence on the domains of nursing: Scoping review. JMIR Nurs. 2020;3(1):e23939.

Seibert K, Domhoff D, Bruch D, Schulte-Althoff M, Fürstenau D, Biessmann F, et al. Application scenarios for artificial intelligence in nursing care: Rapid review. J Med Internet Res. 2021;23(11):e26522.

Booth RG, Strudwick G, McBride S, O'Connor S, López ALS. How the nursing profession should adapt for a digital future. BMJ. 2021;373:n1190.

O'Connor S, Yan Y, Thilo FJS, Felzmann H, Dowding D, Lee JJ. Artificial intelligence in nursing and midwifery: A systematic review. J Clin Nurs. 2023;32(15-16):2951-68.

Lee P, Bubeck S, Petro J. Benefits, limits, and risks of GPT-4 as an AI chatbot for medicine. N Engl J Med. 2023;388(13):1233-9.

Keesara S, Jonas A, Schulman K. COVID-19 and health care's digital revolution. N Engl J Med. 2020;382(23):e82.

Mesko B, Görög M. A short guide for medical professionals in the era of artificial intelligence. NPJ Digit Med. 2020;3:126.

Longoni C, Bonezzi A, Morewedge CK. Resistance to medical artificial intelligence. J Consum Res. 2019;46(4):629-50.

Lee EE, Torous J, De Choudhury M, Depp CA, Graham SA, Kim HC, et al. Artificial intelligence for mental health care: Clinical applications, barriers, facilitators, and artificial wisdom. Biol Psychiatry Cogn Neurosci Neuroimaging. 2021;6(9):856-64.

Wilson RL. Artificial intelligence: An eye cast towards the mental health of nurses. Int J Ment Health Nurs. 2023;32(5):1255-63.

Vaidyam AN, Wisniewski H, Halamka JD, Kashavan MS, Torous J. Chatbots and conversational agents in mental health: A review of the psychiatric landscape. Can J Psychiatry. 2019;64(7):456-64.

Oh WO. Digital healthcare for child health nursing. Child Health Nurs Res. 2023;29(4):209-14.

Hilty DM, Sunderji N, Suo S, Chan S, McCarron RM. Telepsychiatry and other technologies for integrated care: Evidence base, best practice models and competencies. Int Rev Psychiatry. 2018;30(6):292-309.

Morley J, Machado CCV, Burr C, Cowls J, Joshi I, Taddeo M, et al. The ethics of AI in health care: A mapping review. Soc Sci Med. 2020;260:113172.

Topol EJ. High-performance medicine: The convergence of human and artificial intelligence. Nat Med. 2019;25(1):44-56.

Rajkomar A, Dean J, Kohane I. Machine learning in medicine. N Engl J Med. 2019;380(14):1347-58.

Yu KH, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat Biomed Eng. 2018;2(10):719-31.

Dailah HG. Artificial intelligence in nursing: Technological benefits to healthcare, nursing practice, and patient outcomes. Healthcare (Basel). 2024;12(13):2418.

Ruksakulpiwat S, Liu Z, Yue S, Fan Y. A systematic review of the application of artificial intelligence in nursing care. BMC Nurs. 2024;23:174.

El Arab RA, Alowais SA, Alghamdi SS. The role of AI in nursing education and practice: Umbrella review. J Med Internet Res. 2025;27:e69881.

Al Khatib I, Alshurideh M. Examining the role of AI in changing the role of nurses in patient care: A review. JMIR Nurs. 2025;8:e63335.

Topaz M, Bowles KH. Electronic health records, artificial intelligence and the future of nursing documentation. Nurs Outlook. 2020;68(6):726-28.

Risling T, Low C. Advocating for safe, quality and just care: What nursing leaders need to know about artificial intelligence. Nurs Leadersh (Tor Ont). 2019;32(2):31-45.

Wahl B, Cossy-Gantner A, Germann S, Schwalbe NR. Artificial intelligence and global health: How can AI contribute to health in resource-poor settings? BMJ Glob Health. 2018;3:e000798.