Reimagining community mental health nursing: integrating digital health, artificial intelligence, early intervention and recovery-oriented care – a narrative review

Nicholas S.; Raj Kumar D. R.; Haritha M. Nair; Sudha A.; C. S. Sivasakthi; Deeksha Srivastava; Umesh; Thota Malathi

doi:10.18203/2320-6012.ijrms20263577

Authors

Nicholas S. Department of Mental Health Nursing, A. G. Nursing College, Bokaro, Jharkhand, India
Raj Kumar D. R. Department of Mental Health Nursing, Shri Guru Ram Rai College of Nursing, Shri Guru Ram Rai, Kotdwar, Dehradun, Uttarakhand, India
Haritha M. Nair Department of Mental Health Nursing, SCPM College of Nursing, Gonda, Atal Bihari Vajpayee Medical University, Lucknow, Uttar Pradesh, India
Sudha A. Department of Mental Health Nursing, SCPM College of Nursing, Gonda, Atal Bihari Vajpayee Medical University, Lucknow, Uttar Pradesh, India
C. S. Sivasakthi Department of Community Health Nursing, Arcot Sri Mahalakshmi Women's College of Nursing, The Tamil Nadu Dr. M.G.R. Medical University, Villapakkam, Chennai, Tamil Nadu, India
Deeksha Srivastava Department of Mental Health Nursing, SCPM College of Nursing, Gonda, Atal Bihari Vajpayee Medical University, Lucknow, Uttar Pradesh, India
Umesh Department of Mental Health Nursing, SCPM College of Nursing, Gonda, Atal Bihari Vajpayee Medical University, Lucknow, Uttar Pradesh, India
Thota Malathi Department of Medical-Surgical Nursing, GITAM Institute of Nursing, GITAM Deemed to be University, Visakhapatnam, Andhra Pradesh, India

DOI:

https://doi.org/10.18203/2320-6012.ijrms20263577

Keywords:

Community mental health nursing, Digital health, Artificial intelligence, Telepsychiatry, Early intervention, Recovery-oriented care, Predictive analytics, Mental health, Peer support, Community-based care

Abstract

Community mental health nursing is undergoing a substantial transformation driven by digital health, artificial intelligence (AI), early intervention, and recovery-oriented approaches. This narrative review examines how these emerging domains can be integrated to strengthen accessible, proactive, person-centred community mental health services. Literature published primarily between 2020 and 2026 was explored through PubMed/MEDLINE, Scopus, Web of Science, CINAHL, PsycINFO, and the Cochrane Library using MeSH terms and related keywords encompassing community mental health services, psychiatric nursing, telemedicine, digital health, AI, early intervention, recovery, peer support, and primary healthcare. The evidence indicates that telepsychiatry, mobile health applications, digital self-management platforms, and remote monitoring can improve service accessibility, continuity, engagement, and symptom management, although digital exclusion and adherence remain important challenges. AI-based machine learning, predictive analytics, and conversational agents demonstrate potential for early risk identification, personalized intervention, symptom monitoring, and clinical decision support. However, limitations related to external validation, algorithmic bias, transparency, privacy, and limited nursing-specific evidence require careful consideration. Recovery-oriented and peer-supported approaches remain essential for promoting autonomy, empowerment, social functioning, and meaningful participation. The review proposes a human-centred model in which AI and digital technologies augment, rather than replace, therapeutic nursing relationships and professional judgement. Future community mental health services should integrate technological innovation with ethical governance, digital inclusion, early intervention, interdisciplinary collaboration, and recovery-focused nursing practice.

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