Knowledge, Attitude, and Practice (KAP) Regarding the Use of Artificial Intelligence in Hospital Settings in Mardan, Khyber Pakhtunkhwa, Pakistan DOI Open Access
Faizan Sadiq, Fouzia Sadiq, Rukhsana Gul

et al.

Cureus, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 9, 2024

Background Artificial intelligence (AI) is revolutionizing healthcare globally by enhancing diagnostic accuracy, predicting patient outcomes, and enabling personalized treatment plans. However, in low- middle-income countries (LMICs) like Pakistan, the integration of AI into limited due to challenges such as lack funding, provider resistance, inadequate training. Despite these barriers, there growing interest among providers understanding adopting technologies improve professional efficiency. Objective To determine knowledge, attitude, practice (KAP) regarding use artificial doctors a hospital setting. Method This cross-sectional study was conducted at Mardan Medical Complex, Mardan, from January 2023 March 2023. A total 150 various departments participated completing validated questionnaire designed assess their KAP AI. The questionnaire, consisting nine close-ended questions, specifically distributed participants through social media applications, including WhatsApp (California, USA) email, maximize accessibility. It included structured questions rated on Likert scales quantify levels practice. Participants were also asked about exposure AI-related training or work. Descriptive analysis performed frequency percentage responses. Results mean ± SD age this 36.95 8.58 years. Male 72.66%, while 27.33% females. response showed that majority (66%) knew term AI; however, they unsure its healthcare. (67.33%) had positive thoughts possibility using health management. Importantly, (72.66%) never chance do any work lives. assessment medium level knowledge (36.66%), high attitude (57.55%), low (65.66%) Conclusions These results conclude AI's clinical low; have applying

Language: Английский

Awareness of the role of artificial intelligence in health care among undergraduate nursing students: A descriptive cross-sectional study DOI

Misbah Naureen,

Sana Siddiqui,

Summaira Nasir

et al.

Nurse Education Today, Journal Year: 2025, Volume and Issue: 149, P. 106673 - 106673

Published: March 8, 2025

Language: Английский

Citations

0
A Novel Scale to Measure Nursing Students’ Fear of Artificial Intelligence: Development and Validation DOI Open Access
Zainab Fatehi Albikawi, Mohammad Abuadas

The Open Nursing Journal, Journal Year: 2025, Volume and Issue: 19(1)

Published: Feb. 17, 2025

Background The integration of Artificial Intelligence (AI) in healthcare is revolutionizing patient care and clinical practice, enhancing efficiency, accuracy, accessibility. However, it has also sparked concerns among nursing students about job displacement, reliance on technology, the potential loss human qualities like empathy compassion, to this date, there no established scale measuring level fear, especially students. Aim To develop validate a assess students' fear artificial intelligence. Methods current study employed cross-sectional design, involving total 225 Saudi enrolled college. scale's construct, convergent, discriminant validity were evaluated using exploratory factor analysis (EFA) confirmatory (CFA). Results A comprehensive review literature addressing AI guided development Fear Towards Scale (FtAIS). An initial pool items was subjected content assessment by an expert panel, which refined 10 categorized into two dimensions: issues humanity. two-factor structure responsible for 73.52% variance. items' reliability Cronbach's alpha coefficient, yielding value 0.803. coefficients subscales, issues, humanity, are 0.804 0.801, respectively. model demonstrated good fit. convergent both confirmed. Conclusion FtAIS rigorously developed validated tool fears toward AI. These findings emphasize need targeted educational interventions training programs that could mitigate AI-related prepare its healthcare. offers practical applications educators policymakers fostering confident adoption enhance outcomes.

Language: Английский

Citations

0
The predictive effect of nursing students' attitudes and acceptance towards artificial intelligence on their clinical competencies DOI
Enes Şimşek, Aslı Akdeniz Kudubeş, Remziye Semerci

et al.

Teaching and learning in nursing, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

Citations

0
Hemşirelik Öğrencilerinin Yapay Zekâya Yönelik Tutumları ile Tıbbi Yapay Zekâya Hazır Bulunuşlukları Arasındaki İlişkisinin İncelenmesi; Bir Üniversite Örneği DOI
Erhan Elmaoğlu, Hacı Yusuf GÜLEÇ

Bingöl Üniversitesi Sağlık Dergisi, Journal Year: 2025, Volume and Issue: 6(1), P. 144 - 151

Published: April 23, 2025

Hemşirelik öğrencilerin yapay zekâya yönelik tutumlarının ve tıbbi hazır bulunuşlukları arasındaki ilişkisinin belirlenmesi amacıyla yapılmıştır. Tanımlayıcı kesitsel araştırmadır. Araştırmanın evrenini bir devlet üniversitesinde hemşirelik bölümünde eğitim gören 400 öğrenci, örneklemini ise 318 öğrenci oluşturmaktadır. Çalışmada ‘’Kişisel Bilgi Formu’’, ‘’Yapay Zekâya Yönelik Genel Tutum Ölçeği’’ ‘’Tıbbi Yapay Zekâ Hazır Bulunuşluk kullanılmıştır. Verilerin analizinde tanımlayıcı istatistiklerin yanı sıra iki bağımsız değişkenin karşılaştırılmasında t testi, çoklu karşılaştırmalarda gruplarda One-Way ANOVA, bağımlı örneklemlerde tek faktörlü ANOVA Katılımcıların %39,3’nun 1. Sınıf %48,4’nün ortalamasının 2,5-3,0 puan arasında olduğu belirlendi. Tıbbi Ölçeği toplam 76,72±11.87 hesaplandı. genel pozitif tutumunun, bulunuşlarını yönde ortada düzeyde ilişki

Citations

0
Knowledge, attitudes, practices, and barriers of artificial intelligence as predictors of intent to stay among nurses: A cross-sectional study DOI Creative Commons
Islam Oweidat, Mohammad Alkhatib, Mohammed ALBashtawy

et al.

Digital Health, Journal Year: 2025, Volume and Issue: 11

Published: April 1, 2025

Objective Integrating artificial intelligence (AI) in healthcare presents significant opportunities and challenges for nurses other professionals. AI adoption may influence nurses’ work environment overall healthcare. This study aimed to describe the level of knowledge, attitudes, practices, barriers among Jordan their on intent stay job positions. Methods A descriptive correlational cross-sectional was conducted working governmental hospitals Jordan. Data were collected using two validated instruments analyzed statistics, Pearson correlation, multivariate regression. Results The results showed that mean scores barriers, as follows: 3.91 (0.67), 4.15 (0.51), 3.98 (0.56), 3.93 (0.62), 4.17 (0.49), respectively. While attitudes ( r = .64, β .34, P < .001) practices .58, .29, significantly predicted stay, negatively correlated with it −.42, −.14, .05). Conclusion positive attitude practical engagement Could enhance while undermine retention. Addressing these factors through targeted training policy reforms is crucial nursing workforce stability.

Language: Английский

Citations

0
Artificial Intelligence in Dental Education: A Scoping Review of Opportunities, Challenges, and Ethical Frameworks for Shaping Accreditation Standards and Future Practice DOI
Ayman M. Khalifah,

Rasha S Alafaleg

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: May 5, 2025

Abstract Background: The integration of artificial intelligence (AI) into dental education offers transformative potential for enhancing learning outcomes, clinical training, and institutional efficiency. However, rapid AI adoption introduces ethical, logistical, pedagogical challenges that require systematic exploration. This scoping review maps the current applications, challenges, future directions in education, focusing on its curricula while ensuring equitable, pedagogically sound practices. Methods: Joanna Briggs Institute framework was followed, with reporting per PRISMA-ScR guidelines reviews. A search conducted across PubMed, EMBASE, MEDLINE-Ovid, Google Scholar studies published between January 2018 2025. terms included "artificial intelligence," "dental education," "machine learning," "ChatGPT," "ethical challenges," Medical Subject Headings (MeSH) applied where applicable. After duplicate removal, 624 510 records underwent title/abstract screening, followed by a full-text 57 articles, 43 meeting eligibility criteria. Data extraction focused study design, population, type, key challenges. Results: findings include following: 1. AI-Driven Personalization: Generative (e.g., ChatGPT) reduced grading time 45% improved reflective although 33% reported algorithmic bias due to nonrepresentative training data. 2. In tools achieved 99% accuracy caries detection compared 77–79% students, but models trained homogeneous datasets underperformed diverse cohorts. 3. Institutional Efficiency: Automated scheduling administrative workloads 30%, yet only 18% institutions had updated literacy modules. 4. Ethical Governance: privacy data protection breaches occurred 24% studies, 41% faculty resistance adoption, highlighting need dental-specific guidelines. Conclusion: AI holds significant promise requires addressing Future efforts should focus updating accreditation standards, fostering interdisciplinary collaboration, developing hybrid balance AI-driven efficiency traditional mentorship. Longitudinal are needed evaluate long-term impact competence patient outcomes. Significance: Dental educators clearer guidance integrating curriculum.

Language: Английский

Citations

0
Nursing Students’ Attitudes Toward Artificial Intelligence: Palestinian Perspectives DOI Creative Commons
Basma Salameh, Jamal Qaddumi, Bahaaeddin M. Hammad

et al.

SAGE Open Nursing, Journal Year: 2025, Volume and Issue: 11

Published: Jan. 1, 2025

Artificial intelligence (AI) is significantly transforming the nursing profession, enhancing patient care, and shaping future practice. Understanding students' attitudes toward AI applications crucial for its effective integration into clinical practice education. To evaluate in Palestine. A cross-sectional design was conducted among 325 students. Due to logistical constraints, data were gathered via online surveys using attitude scale. The research between February March 2024 at Arab American University results showed that average scores (M = 61.81; SD 9.74) greater than neutral score (p .001). Nursing students have a positive terms of benefits willingness use it However, practical advantages exhibit negative dangers nursing. Furthermore, gender, academic year, purpose had statistically significant differences .034, .039, 0.042 respectively). Female higher levels usage, while participants with master's degree lowest level AI. Our findings demonstrate healthcare practice, along intentions utilize technology. highlight need AI-focused training within curricula.

Language: Английский

Citations

0
Knowledge, perception, and attitude of Egyptian dental students toward the role of robotics and artificial intelligence in dental practices - a cross-sectional study DOI Creative Commons
Naglaa Ezzeldin, Aya A. Salama,

Karim A. Shehab

et al.

BMC Oral Health, Journal Year: 2025, Volume and Issue: 25(1)

Published: May 21, 2025

Abstract Background Rapid technological progress has made robotics (R) and artificial intelligence (AI) essential components of our everyday existence. In addition, robots designed for dental applications have been created. This study aimed to assess Egyptian students’ Knowledge, perception, attitude toward the role AI in practices. Methods A cross-sectional questionnaire-based was conducted involving 204 students from Faculty Dentistry at October University Modern Sciences Arts. The electronic link questionnaire created using Google Forms distributed via email. included 26 questions that assessed knowledge, R Dentistry. Results total 85.8% were familiar with concepts AI. Among them, 66.2% demonstrated a good understanding dentistry, while 59.3% showed positive towards these technologies. Dental perceived use favorably, particularly implants CAD/CAM technologies, 80.6% 82.3% expressing approval, respectively. However, 66.9% opposed idea replacing dentists Additionally, 75% expressed desire learn more about future. Conclusions possess attitudes diagnosis interpretation. They believe can play an active various aspects practice. they express uncertainty possibility dentists.

Language: Английский

Citations

0
Nursing students' attitudes and literacy toward artificial intelligence: a cross-sectional study DOI
Aylin Akça Sümengen, Damla Özçevik Subaşı, Gökçe Naz Çakır

et al.

Teaching and learning in nursing, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 1, 2024

Language: Английский

Citations

3
From anxiety to action: exploring the impact of artificial intelligence anxiety and artificial intelligence self-efficacy on motivated learning of undergraduate students DOI
Chen Chen, Wei Hu, Xiaomin Wei

et al.

Interactive Learning Environments, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 16

Published: Dec. 17, 2024

The rapid development of artificial intelligence (AI) technology, while empowering higher education, has also introduced anxiety and stress among university students. This study examines the impact AI on motivated learning moderating role self-efficacy. Data were collected from 387 valid questionnaires at a in China, hypotheses analyzed using SPSS 25.0 PROCESS plug-in. results indicate that anxiety, encompassing dimensions learning, configuration, job replacement, sociotechnical blindness, positive self-efficacy positively moderates relationship between learning. Specifically, enhances effect contributes to existing literature offers insights for application education practice.

Language: Английский

Citations

2