PubMed İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14627/8

Browse

Now showing 1 - 4 of 4

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.
'I Feel Like the Burden of the World Is on My Shoulders': A Phenomenological Qualitative Study on the Life Experiences of Adult Children of Parents with Schizophrenia
(BMC, 2025) Pehlivan Saribudak, Tugba; Dag, Zeynep; Ozturk, Ayse; Dikec, Gul
BackgroundStudies investigating the experiences of adult children of parents with schizophrenia (ACPS) are limited, and no qualitative study examining this issue in T & uuml;rkiye has been previously conducted. This study aimed to examine the life experiences of ACPS providing primary care.MethodsThis phenomenological qualitative study was conducted with 14 ACPS in acute clinics of a regional psychiatric hospital in Istanbul between March and August 2024. Data were collected through in-depth interviews and analyzed using Colaizzi's seven-step analysis method.ResultsData analysis revealed five main themes: (1) Difficult beginning of life, (2) Being a caregiver without receiving care, (3) Emotional storm, (4) Disruption of the flow of life, and (5) Coping. The study found that adult children who cared for their parents could not remember their childhood, had to grow up early without parents, and experienced violence. Adult children had difficulty carrying the burden of care, experienced various emotions at the same time, and care disrupted their lives. They were both using adaptive and maladaptive coping methods.ConclusionsThis study determined that ACPS experienced significant childhood stressors and difficulties providing care in adult life that changed the flow of their daily lives while challenging their ability to cope. Psychiatric nurses have essential tasks to support ACPS in coping with difficult life experiences and reducing their care burdens. They should inform ACPS about schizophrenia, regularly monitor their mental health, and implement initiatives that will protect or improve their mental health.Clinical trial registrationNot applicable.
Psychometric Evaluation of the Person-Centred Climate Questionnaire - Staff Version
(BMC, 2025) Arici, Furkan Cihat; Harmanci Seren, Arzu Kader; Edvardsson, David
BackgroundValid and reliable instruments are needed to assess person-centredness that serve as quality care indicators. Person-Centred Climate Questionnaire - staff version is an interculturally used tool to evaluate person-centredness in clinical settings. This study aimed to examine the psychometrics of the tool in the Turkish language.MethodsThis was a methodological study involving a sample of 140 nurses. One of the researchers collected data using the Turkish version of the questionnaire-staff version in a private hospital in Istanbul. After performing the language validity steps, the researchers analysed the content validity ratios of the items and the questionnaire's content validity index, and they performed exploratory and confirmatory factor analysis to validate the construct. The internal consistency of the subdimensions and the questionnaire was determined utilising a Cronbach's Alpha test.ResultsThe content validity ratios of the items ranged from 0.84 to 1, and the correlation coefficients ranged from 0.50 to 0.69. The three-factor structure accounted for 70.40% of the total variance. The items' standardised factor loads were between 0.501 and 1.140. The Cronbach's alpha consistency value was 0.90.ConclusionThe staff version of the questionnaire is an adequately valid and reliable instrument in the Turkish language.
The Relationship Between Nurses Anxiety and Attitudes Towards Artificial Intelligence and Examination of Influencing Factors
(BMC, 2026) Nirgiz, Cansu; Sari, Merve Kiymac; Cayli, Nazan
Aim to explore the relationships between nurses'anxiety and attitudes toward artificial intelligence (AI) and the factors associated with them. Background Although AI technologies are increasingly integrated into healthcare, research exploring nurses ' psychological readiness and emotional responses to AI remains limited. Existing studies have primarily focused on nursing students or general healthcare professionals, leaving a gap in understanding how practicing nurses perceive and emotionally adapt to AI within real clinical environments-particularly in T & uuml;rkiye, where digital transformation in healthcare is accelerating. Addressing this gap is essential, as nurses play a pivotal role in ensuring the safe and ethical implementation of AI-driven tools in patient care. Methods This descriptive and correlational study included 562 nurses from 14 branches of a private hospital chain across seven Turkish cities between November 2024 and January 2025.This sample was selected because it represents nurses actively engaged in clinical decision-making within healthcare systems that are rapidly adopting AI technologies. According to a power analysis performed in G*Power (rho = 0.25, alpha = 0.05, power = 0.95), the required sample size was 202 participants. Data were collected through an online questionnaire comprising a Descriptive Information Form, the AI Anxiety Scale, and the General Attitudes toward AI Scale. Descriptive statistics, independent samples t-tests, ANOVA (F), Tukey post hoc test, Pearson correlation, and multiple regression analyses were conducted. Ethical approval was obtained from the Fenerbah & ccedil;e University Ethics Committee, and informed consent was obtained digitally. Results Nurses reported moderate anxiety levels and generally positive attitudes toward AI. Male nurses showed an association with lower anxiety levels and higher positive attitude scores than female nurses. Single individuals and those with higher levels of education showed higher positive attitudes toward AI. Those with 0-3 years of experience in the profession were associated with lower anxiety and higher positive attitude scores. Nurses who used AI in practice, were knowledgeable about its use, or perceived it as reliable showed a relationship with lower anxiety and more positive attitudes. Regression analysis showed that each one-unit increase in the learning and AI configuration subscales of the AI Anxiety Scale was associated with a 0.740-and 0.716-point lower score in the total attitude score, respectively. Conclusion The findings suggest that lower levels of anxiety related to learning and AI configuration are associated with more positive attitudes toward AI. Addressing these specific anxiety domains may be related to the successful integration of AI technologies into clinical practice and could be linked to the digital transformation in healthcare.

Browse

Browsing PubMed İndeksli Yayınlar Koleksiyonu by Journal "BMC Nursing"