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TRUVACE RECORD VERSION
record: TRV-2026-1248
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-10-02T06:56:17.980055Z
status: published
lens: trace
sector: health
headline: Artificial Intelligence in Mental Health Care: Implications for Psychiatric Mental Health Nursing-A Scoping Review
dek: AI is increasingly being integrated into mental health support, with applications spanning chatbots, large language models, digital therapeutics and clinical decision-support systems. Although these technologies have demonstrated potential to improve access to care and support clinical practice, their implications for psychiatric mental health nursing (PMHN) remain insufficiently synthesized. This scoping review aimed to examine how AI is being applied in mental health care and to synthesize its implications for…
gain_title: AI-based tools including chatbots and clinical decision-support systems were associated with improved accessibility of mental health support and more efficient risk assessment in psychiatric mental health nursing contexts.
problem_title: Integration of AI into mental health care raised consistent concerns about privacy, algorithmic bias, lack of transparency, and erosion of therapeutic relationships in psychiatric nursing.
trace_subject: AI applications in mental health care and their implications for psychiatric mental health nursing practice
gain_reading: AI-based tools including chatbots and clinical decision-support systems were associated with improved accessibility of mental health support and more efficient risk assessment in psychiatric mental health nursing contexts.
gain_evidence: AI applications were associated with improved accessibility of mental health support, enhanced symptom management and more efficient risk assessment.
problem_reading: Integration of AI into mental health care raised consistent concerns about privacy, algorithmic bias, lack of transparency, and erosion of therapeutic relationships in psychiatric nursing.
problem_evidence: concerns regarding privacy, algorithmic bias, transparency and the preservation of therapeutic relationships were consistently reported.
quick_read: This October 2026 scoping review examined how AI tools such as chatbots, large language models, digital therapeutics and clinical decision-support systems are being applied in mental health care, synthesizing 42 sources from January 2022 to May 2026 to assess implications for psychiatric mental health nursing.

It matters because it documents both observed benefits for access and risk assessment and persistent unresolved concerns about privacy, bias, transparency and therapeutic relationships, leaving uncertainty about how to safely integrate AI without displacing human-centred nursing care.
limitation: Review is limited to a scoping synthesis of 42 sources from a defined window and notes that implications for psychiatric mental health nursing remain insufficiently synthesized, indicating incomplete evidence base.
tag: Dual reading
key_points: Scoping review of 42 sources from January 2022 to May 2026 examined AI applications spanning chatbots, large language models, digital therapeutics and clinical decision-support systems. | Five themes identified: AI-based psychosocial interventions and care delivery, suicide prevention and risk management, therapeutic relationships and human-centred care, ethics safety and governance, and nursing readiness and education. | Authors conclude AI should be viewed as a complementary tool that supports rather than replaces psychiatric mental health nursing practice and call for stronger AI literacy and digital ethics training.
rundown: The review searched four databases for studies published between January 2022 and May 2026 and synthesized 42 sources following PRISMA-ScR methodology.

Findings were organized into five overarching themes covering psychosocial interventions, suicide prevention and risk management, therapeutic relationships, ethics and governance, and nursing readiness and professional transformation.

While benefits for accessibility and efficiency were noted, the authors emphasized AI as complementary to nursing and highlighted needs for education in AI literacy, digital ethics and critical appraisal.
sources:
- peer_reviewed | International Journal of Mental Health Nursing | https://doi.org/10.1111/inm.70361 | 2026-10-01
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