Psychiatric and Mental Health Nurses' Experiences and Perceptions of Artificial Intelligence in Clinical Practice: A Qualitative Study

INTRODUCTION: Artificial intelligence is increasingly entering healthcare, yet its role in psychiatric and mental health nursing remains underexplored, particularly from nurses' experiential perspectives. AIM: This study aimed to explore psychiatric and mental health nurses' experiences of using generative AI tools in clinical practice, along with their broader perceptions and expectations of artificial intelligence. METHOD: A qualitative descriptive design was used. Semi-structured interviews were conducted with 23 psychiatric and mental health nurses recruited through purposive sampling. Data were analysed using Braun and Clarke's thematic analysis. RESULTS: Four themes emerged: trust-distrust; ease and speed of accessing medical content; limitations in meeting the individualized and relational demands of psychiatric care; and expectations from artificial intelligence. Nurses used artificial intelligence primarily for pharmacological and clinical information access, while adopting cautious, verification-based approaches due to accuracy concerns. DISCUSSION: Participants perceived limitations in AI's ability to address the individualized and relational dimensions of psychiatric care, while difficulties in prompt formulation emerged as a separate practical challenge. LIMITATIONS: Findings are context-specific and based on self-reported data. Participants shared similar educational backgrounds, which may have limited perspective diversity. IMPLICATIONS: Targeted training is needed to develop nurses' capacity to engage critically and effectively with artificial intelligence in clinical settings. RECOMMENDATIONS: Future integration of artificial intelligence into psychiatric nursing should be supported by structured education and system-level implementation strategies.

Authors

Institutions

Publication Details

Journal
Journal of Psychiatric and Mental Health Nursing
Published
2026-11-06
DOI
https://doi.org/10.1111/jpm.70216
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Psychiatric and Mental Health Nurses' Experiences and Perceptions of Artificial Intelligence in Clinical Practice: A Qualitative Study

E. Mor, Nevra Didem Kılınç, Özge Yaman, Fahriye Oflaz
7 links
Journal of Psychiatric and Mental Health Nursing
Artificial Intelligence in Healthcare and Education
article

Psychiatric and Mental Health Nurses' Experiences and Perceptions of Artificial Intelligence in Clinical Practice: A Qualitative Study

E. Mor, Nevra Didem Kılınç, Özge Yaman, Fahriye Oflaz
article en

Abstract

INTRODUCTION: Artificial intelligence is increasingly entering healthcare, yet its role in psychiatric and mental health nursing remains underexplored, particularly from nurses' experiential perspectives. AIM: This study aimed to explore psychiatric and mental health nurses' experiences of using generative AI tools in clinical practice, along with their broader perceptions and expectations of artificial intelligence. METHOD: A qualitative descriptive design was used. Semi-structured interviews were conducted with 23 psychiatric and mental health nurses recruited through purposive sampling. Data were analysed using Braun and Clarke's thematic analysis. RESULTS: Four themes emerged: trust-distrust; ease and speed of accessing medical content; limitations in meeting the individualized and relational demands of psychiatric care; and expectations from artificial intelligence. Nurses used artificial intelligence primarily for pharmacological and clinical information access, while adopting cautious, verification-based approaches due to accuracy concerns. DISCUSSION: Participants perceived limitations in AI's ability to address the individualized and relational dimensions of psychiatric care, while difficulties in prompt formulation emerged as a separate practical challenge. LIMITATIONS: Findings are context-specific and based on self-reported data. Participants shared similar educational backgrounds, which may have limited perspective diversity. IMPLICATIONS: Targeted training is needed to develop nurses' capacity to engage critically and effectively with artificial intelligence in clinical settings. RECOMMENDATIONS: Future integration of artificial intelligence into psychiatric nursing should be supported by structured education and system-level implementation strategies.

Journal of Psychiatric and Mental Health Nursing
Koç University (TR), Istanbul Arel University (TR), Beykent University (TR)
Good health and well-being
Openalex Percentile: Top 23%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon