Harnessing Artificial Intelligence: Strategies for Mental Health Nurses in Optimizing Psychiatric Patient Care

Nashwan, Abdulqadir J.; Gharib, Suzan; Alhadidi, Majdi; El-Ashry, Ayman Mohamed; Alamgir, Asma; Al-Hassan, Mohammed; Khedr, Mahmoud Abdelwahab; Dawood, Shaimaa; Abufarsakh, Bassema

doi:10.1080/01612840.2023.2263579

Cited by 14 publications

(3 citation statements)

References 139 publications

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“…The emergence of AI is catalysing a profound paradigm shift in the realm of mental health nursing (Nashwan et al., 2023). This innovative technology augments diagnostic and risk assessment processes by meticulously analysing a vast array of patient data, encompassing medical records, speech patterns, and facial expressions.…”

Section: Ai In the Mental Health Nursingmentioning

confidence: 99%

Critical review of self‐diagnosis of mental health conditions using artificial intelligence

Wimbarti,

Kairupan,

Tallei

2024

Int J Mental Health Nurs

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The advent of artificial intelligence (AI) has revolutionised various aspects of our lives, including mental health nursing. AI‐driven tools and applications have provided a convenient and accessible means for individuals to assess their mental well‐being within the confines of their homes. Nonetheless, the widespread trend of self‐diagnosing mental health conditions through AI poses considerable risks. This review article examines the perils associated with relying on AI for self‐diagnosis in mental health, highlighting the constraints and possible adverse outcomes that can arise from such practices. It delves into the ethical, psychological, and social implications, underscoring the vital role of mental health professionals, including psychologists, psychiatrists, and nursing specialists, in providing professional assistance and guidance. This article aims to highlight the importance of seeking professional assistance and guidance in addressing mental health concerns, especially in the era of AI‐driven self‐diagnosis.

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Section: Ai In the Mental Health Nursingmentioning

confidence: 99%

Critical review of self‐diagnosis of mental health conditions using artificial intelligence

Wimbarti,

Kairupan,

Tallei

2024

Int J Mental Health Nurs

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“…Remarkably, treatment errors do not occur in isolation; according to the Swiss cheese model, multiple systems errors (represented as holes in the cheese) had to align perfectly for the adverse event to happen. Table 1 presents the Emergency Care Research Institute’s primary 10 concerns regarding patient safety in 2023 concerning treatment and diagnosis,[ 19 ] along with the potential of AI to assist in addressing these crucial issues, such as mental health issues,[ 20 ] clinicians operating beyond their expertise,[ 21 ] delayed identification and treatment of sepsis,[ 22 ] inadequate coordination of care for complex conditions,[ 23 ] oversight of medication safety,[ 24 ] medication errors,[ 25 ] unintentional administration of neuromuscular blocking agents,[ 26 ] and preventable injuries due to overlooked care or treatment. [ 27 ]…”

Section: Applications Of Ai In Hospital Based-improvement Levelmentioning

confidence: 99%

Transforming Hospital Quality Improvement Through Harnessing the Power of Artificial Intelligence

Abukhadijah,

Nashwan

2024

Global Journal on Quality and Safety in Healthcare

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This policy analysis focuses on harnessing the power of artificial intelligence (AI) in hospital quality improvement to transform quality and patient safety. It examines the application of AI at the two following fundamental levels: (1) diagnostic and treatment and (2) clinical operations. AI applications in diagnostics directly impact patient care and safety. At the same time, AI indirectly influences patient safety at the clinical operations level by streamlining (1) operational efficiency, (2) risk assessment, (3) predictive analytics, (4) quality indicators reporting, and (5) staff training and education. The challenges and future perspectives of AI application in healthcare, encompassing technological, ethical, and other considerations, are also critically analyzed.

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“…Similar systems are also utilized in hospitals and laboratories for repetitive tasks, administrative procedures [ 12 ], rehabilitation, and physical therapy. Virtual nurse assistants [ 13 ] even leverage voice and AI technologies to conduct wellness checks. All these examples show how AI is playing a transformative role in the field of medicine.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Diagnostic and Immunohistochemical Workup and Literature Review Capabilities of Online Artificial Intelligence Assistance Models in Pathology

Dougan,

Patel,

Bardarov

2024

Cureus

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Artificial intelligence (AI) is a suite of technologies that enables computers to learn and interpret information like human cognition. It has found applications across various fields, including healthcare, agriculture, astronomy, navigation, and robotics. Within healthcare, AI has the potential to enhance diagnostic accuracy, facilitate drug research, and automate patient experiences. This comparative study focuses on the proficiency of AI in generating accurate differential diagnoses in the field of pathology. Six medical vignettes were crafted, and each scenario was then input into three different AI platforms. The pathologist reviewed and determined the most accurate AI model.

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Harnessing Artificial Intelligence: Strategies for Mental Health Nurses in Optimizing Psychiatric Patient Care

Cited by 14 publications

References 139 publications

Critical review of self‐diagnosis of mental health conditions using artificial intelligence

Critical review of self‐diagnosis of mental health conditions using artificial intelligence

Transforming Hospital Quality Improvement Through Harnessing the Power of Artificial Intelligence

A Comparison of Diagnostic and Immunohistochemical Workup and Literature Review Capabilities of Online Artificial Intelligence Assistance Models in Pathology

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