Browsing by Author "Goktas, Polat"

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Citation - WoS: 6
Citation - Scopus: 6
Artificial Intelligence in Nursing Practice: A Qualitative Study of Nurses' Perspectives on Opportunities, Challenges, and Ethical Implications
(BMC, 2025) Bodur, Gonul; Cakir, Hanife; Turan, Suzan; Seren, Arzu Kader Harmanci; Goktas, Polat
BackgroundThe study aims to explore nurses' views on the effects of artificial intelligence (AI) in nursing, focusing on their understanding, practical applications, ethical considerations, and perceived opportunities and threats.MethodsThis qualitative study used semi\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:-$$\end{document}structured interviews to gain comprehensive insights from clinical nurses, adhering to the Standards for Reporting Qualitative Research for methodological rigor. After obtaining ethical approval, researchers conducted semi\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:-$$\end{document}structured interviews with 25 clinical nurses. The interviews explored nurses' perceptions of AI, including its basic concepts, applications in nursing practice, ethical and social implications, and potential benefits and drawbacks.ResultsThe analysis identified four overarching themes: (1) Nurses' Conceptualizations of Artificial Intelligence, (2) Opportunities of AI in Nursing Practice, (3) Threats of AI in Nursing Practice, and (4) Ethical and Psychological Concerns in AI-Based Nursing Practice. The findings revealed that nurses had a foundational understanding of AI and its definitions. They acknowledged both the positive and negative impacts of AI technologies on their practice. Nurses expressed that AI could reduce workload, enhance patient care, and improve efficiency. However, they also articulated significant threats, including concerns over professional redundancy, emotional disconnection in caregiving, de-skilling, and the risk of dehumanizing the healthcare environment. Additionally, ethical and psychological concerns emerged, such as ambiguity in accountability, threats to data security and patient safety, unsuitability in psychiatric care contexts, staff surveillance anxiety, and risks of misuse or systemic bias.ConclusionThe study concluded that while nurses possess a basic understanding of AI, the effective and ethical integration of AI technologies in nursing requires targeted training, institutional preparedness, and robust interdisciplinary collaboration. To ensure AI complements rather than compromises nursing values, it is imperative to equip nurses with skills in digital literacy, ethical reasoning, and critical engagement with AI tools. The findings highlight the necessity of structured education programs and policy development that address both the technological and humanistic dimensions of AI use in healthcare. Future research should actively incorporate patient and public voices to ensure that AI-driven transformations in care remain aligned with the principles of patient-centeredness and human dignity.
Mapping the Evolution of Stigmatization in Mental Disorders: A Bibliometric Analysis From 1974 to 2024
(Springer Heidelberg, 2026) Goktas, Polat; Dikec, Gul
BackgroundThis bibliometric study scrutinizes the thematic evolution of research on stigma and discrimination in mental disorders, covering a span of five decades. It reflects on the shifting paradigms within the stigma-focused mental health research community from 1974 to 2024.MethodsA comprehensive bibliometric analysis was employed using the Bibliometrix R package and VOSviewer software, analyzing 1,892 articles from databases like Scopus, Web of Science, PubMed Central, and APA PsycInfo. Adherence to PRIBA guidelines ensured a holistic representation of the evolving research narrative.ResultsThe analysis outlined three distinct periods: the Genesis Period (1974 - 2007), focusing on foundational concepts of mental disorders and stigma; the Growth Period (2008 - 2015), which experienced a broadening into themes of discrimination and diagnostic refinement; and the Rapid Growth Period (2016 - 2024), characterized by a surge in research on child mental disorders and the impacts of posttraumatic stress disorder. Network analyses highlighted significant journals, key authors, and international collaborations that have shaped this field.ConclusionsThe study maps a significant transformation in stigma-focused mental health research themes over fifty years, highlighting the growing complexity and the need for ongoing research into stigma and discrimination. It calls for interdisciplinary approaches to tackle these enduring challenges effectively.