Reimagining community mental health nursing: integrating digital health, artificial intelligence, early intervention and recovery-oriented care – a narrative review
DOI:
https://doi.org/10.18203/2320-6012.ijrms20263577Keywords:
Community mental health nursing, Digital health, Artificial intelligence, Telepsychiatry, Early intervention, Recovery-oriented care, Predictive analytics, Mental health, Peer support, Community-based careAbstract
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.
References
World Health Organization. World mental health report: transforming mental health for all. Geneva: World Health Organization. 2022. Available at: WHO World Mental Health Report. Accessed on 02 August 2026.
Dickens GL, Al Maqbali M, Blay N, Hallett N, Ion R, Lingwood L, et al. Randomized controlled trials of mental health nurse-delivered interventions: a systematic review. J Psychiatr Ment Health Nurs. 2023;30(3):341-60.
World Health Organization. Guidance on community mental health services: promoting person-centred and rights-based approaches. Geneva: World Health Organization. 2021. Available at: WHO community mental health guidance. Accessed on 02 August 2026.
Mousavizadeh SN, Jandaghian Bidgoli MA. Recovery-oriented practices in community-based mental health services: a systematic review. Iran J Psychiatry. 2023;18(3):332-51.
Charoensuk S, Jintana Y, Penpaktr U. Recovery-oriented nursing service for people with schizophrenia in the community: an integrative review. Belitung Nurs J. 2023;9(3):198-208.
Hagi K, Shunya K, Akihiro T, Mayu F, Shotaro K, Mari I, et al. Telepsychiatry versus face-to-face treatment: systematic review and meta-analysis of randomised controlled trials. Br J Psychiatry. 2023;223(3):407-14.
Buechner H, Toparlak SM, Ostinelli EG, Shokraneh F, Nicholls-Mindlin J, Cipriani A, et al. Community interventions for anxiety and depression in adults and young people: a systematic review. Aust N Z J Psychiatry. 2023;57(9):1223-42.
Cruz-Gonzalez P, He AWJ, Lam EP, Ng IMC, Li MW, Hou R, et al. Artificial intelligence in mental health care: a systematic review of diagnosis, monitoring, and intervention applications. Psychol Med. 2025;55:e18.
Abu-Mahfouz MS, AlFehaid S, Burqan HM, El Arab RA. Artificial intelligence in mental health care: a scoping review of reviews. Front Psychiatry. 2026;17:1688043.
O'Connell N, O'Connor K, McGrath D, Vagge L, Mockler D, Jennings R, et al. Early intervention in psychosis services: a systematic review and narrative synthesis of the barriers and facilitators to implementation. Eur Psychiatry. 2021;65(1):e2.
Salazar de Pablo G, Almeida J, Camacho J, Suárez Campayo J, Catalan A, Pop M, et al. Do early intervention services for psychosis maintain their effects after transition to usual/modular care? A systematic review and meta-analysis. World Psychiat. 2026;25(1):95-104.
World Health Organization. Ethics and governance of artificial intelligence for health: WHO guidance. Geneva: World Health Organization; 2021. Available at: WHO AI ethics and governance guidance. Accessed on 02 August 2026.
Dickens GL, Al Maqbali M, Blay N, Hallett N, Ion R, Lingwood L, et al. Randomized controlled trials of mental health nurse-delivered interventions: a systematic review. J Psychiatr Ment Health Nurs. 2023;30(3):341-60.
Jørgensen K, Rasmussen T, Hansen M, Andreasson K. Recovery-oriented intersectoral care between mental health hospitals and community mental health services: an integrative review. Int J Soc Psychiatry. 2021;67(6):788-800.
Lau CKY, Saad A, Camara B, Rahman D, Bolea-Alamanac B. Acceptability of digital mental health interventions for depression and anxiety: systematic review. J Med Internet Res. 2024;26:e52609.
Klos MC, Escoredo M, Joerin A, Lemos VN, Rauws M, Bunge EL. Artificial intelligence-based chatbot for anxiety and depression in university students: pilot randomized controlled trial. JMIR Ment Health. 2021;5(8):e20678.
Morriss R, Kaylor-Hughes C, Rawsthorne M, Coulson N, Simpson S, Guo B, et al. A direct-to-public peer support program (Big White Wall) versus web-based information to aid the self-management of depression and anxiety: results and challenges of an automated randomized controlled trial. J Med Internet Res. 2021;23(4):e23487.
Jacobson NC, Nemesure MD. Using artificial intelligence to predict change in depression and anxiety symptoms in a digital intervention: evidence from a transdiagnostic randomized controlled trial. Psychiatry Res. 2021;295:113618.
Huang S, Wang Y, Li G, Hall BJ, Nyman TJ. Digital mental health interventions for alleviating depression and anxiety during psychotherapy waiting lists: systematic review. JMIR Ment Health. 2024;11:e56650.
Chien WT, Chow KM, Gray RJ, McMaster CW. Effectiveness of a peer-facilitated, recovery-focused self-illness management program for adults with first-episode psychosis: a randomized controlled trial. Eur Psychiatry. 2025;68(1):e131.
Hang Y, Wu W, Feng Y, Yan K, Liu Y, Xiao X, et al. The effectiveness of CBT-based NLP-enabled AI conversational agents for mental health intervention: a systematic review and meta-analysis. NPJ Digit Med. 2026.
World Health Organization. Ethics and governance of artificial intelligence for health: guidance on large multi-modal models. Geneva: World Health Organization. 2025. Available at: WHO guidance on large multimodal AI models. Accessed on 02 August 2026.
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Copyright (c) 2026 Nicholas S., Raj Kumar D. R., Haritha M. Nair, Sudha A., C. S. Sivasakthi, Deeksha Srivastava, Umesh, Thota Malathi, Mohammed Umar

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