ethique_IA

Ethical, data security, and resource allocation considerations in AI integration for healthcare during Hajj: task force insights and future directions.

Thu, 01 Jan 2026 05:00:00 +0000

International Journal of Medical Informatics; 01/01/2026
(AN 188685751); ISSN: 13865056
CINAHL Complete

Ethics in Danish healthcare AI policy: A document analysis.

Mon, 01 Dec 2025 05:00:00 +0000

International Journal of Medical Informatics; 12/01/2025
(AN 187749857); ISSN: 13865056
CINAHL Complete

Patient perspectives on artificial intelligence in healthcare: A global scoping review of benefits, ethical concerns, and implementation strategies.

Sat, 01 Nov 2025 04:00:00 +0000

International Journal of Medical Informatics; 11/01/2025
(AN 187069175); ISSN: 13865056
CINAHL Complete

Psychometric properties of an Iranian instrument for assessing adherence to ethical principles in the use of artificial intelligence among healthcare providers.

Sat, 01 Nov 2025 04:00:00 +0000

International Journal of Medical Informatics; 11/01/2025
(AN 187069187); ISSN: 13865056
CINAHL Complete

Ethical challenges of using artificial intelligence in healthcare delivery: a thematic analysis of a systematic review of reviews.

Sat, 01 Nov 2025 04:00:00 +0000

Journal of Public Health: From Theory to Practice (2198-1833); 11/01/2025
Aim: The COVID-19 pandemic boosted the digitalization and virtualization of health and social services, leading to an era of AI and AI digital platforms for healthcare. However, various studies have addressed the ethical challenges and issues of AI in healthcare. This study aimed to investigate and accumulate the ethical challenges and issues regarding using artificial intelligence in healthcare service delivery. Subject and methods: We performed a systematic review of the existing reviews published between 2000 and 2023 on multiple databases, such as PubMed, Scopus, ProQuest, and Cochrane database of systematic reviews. After completing the screening, quality and risk of bias assessment of the articles using the CASP checklist, we selected and included the final articles. In the subsequent step, we conducted a thematic analysis of the data extracted from the final articles. Results: Out of 1808 records that were identified, six papers met the eligibility criteria and were included in the analysis. The findings consisted of two major themes and seven sub-themes: the major themes were ethical challenges in the design and development of AI and ethical challenges of AI implementation and impact; the sub-themes were bias, transparency, privacy, accountability, equity, trust, and replacement. Conclusion: Also, the findings implied that ethical principles and values may be context-dependent and dynamic. Hence, it is essential to adopt a multidisciplinary and participatory approach to address the ethical issues of AI in healthcare and to align AI technologies with the goals and values of healthcare.
(AN 188799634); ISSN: 21981833
CINAHL Complete

Guest editorial: Ethics for artificial intelligence: A game based- framework for physiotherapists

Sat, 25 Oct 2025 08:19:50 +0000

Author Names: Laurijssen S.,Six-Dijkstra M.,van den Berg G.,Hanskamp M.,Rijken N.

Database Source: Embase Daily Updates

Journal Title: Journal of Back and Musculoskeletal Rehabilitation

Article Title: Guest editorial: Ethics for artificial intelligence: A game based- framework for physiotherapists

Year: 2025

Issue: 2

Volume: 38

Abstract:

Strengthening ethics review of the development of artificial intelligence (AI) systems in health research: a guide for research ethics committees in Uganda

Sat, 25 Oct 2025 08:19:50 +0000

Author Names: Nabukenya S.,Wasswa W.,Twimukye A.,Mwaka E.S.

Database Source: Embase Daily Updates

Journal Title: BMC medical ethics

Article Title: Strengthening ethics review of the development of artificial intelligence (AI) systems in health research: a guide for research ethics committees in Uganda

Year: 2025

Issue: 1

Volume: 26

Abstract: INTRODUCTION: The ability of artificial intelligence (AI) to analyze data in real-time and improve patients' diagnosis has led to a rapid growth of AI- health research in Uganda. Yet, there are no national guidelines on how to conduct AI-research in an ethical manner. Recent studies have reported that ethics committees lack resources, expertise and training to appropriately address the risks that may arise from AI health research. This study aimed to develop a guide for ethical review of the development of AI systems in health research in Uganda. METHOD(S): This study employed an exploratory qualitative approach between March - October 2024, involving 35 stakeholders in two public universities in Uganda. In-depth interviews were conducted with twelve members of ethics committees who had ever reviewed AI- protocols, six bioethicists, eight health researchers and nine members of AI-development teams. A thematic approach was used to interpret the results. RESULT(S): Six themes emerged from this data including promoting social value and equity; ensuring participants and end-user autonomy and safety; addressing data acquisition, access and sharing gaps; ensuring responsible data use and data minimization; promoting responsible AI and fostering collaborative partnerships. Respondents opined that AI holds promise for improving health research. However, its successful implementation demands ethical considerations to minimize harm to participants and end-users. CONCLUSION(S): Overall, respondents felt that developing a guide for ethics review of AI-research may minimize potential harms that could arise from using AI tools in research. We recommend training of ethics committees on key ethical considerations for development of responsible AI tools. Copyright © 2025. The Author(s).

Applications of Artificial Intelligence in Dermatology: Ethical Considerations

Sat, 25 Oct 2025 08:19:50 +0000

Author Names: Arza A.,Lebhar J.,Lipoff J.B.

Database Source: Embase Weekly Updates

Journal Title: Dermatologic Clinics

Article Title: Applications of Artificial Intelligence in Dermatology: Ethical Considerations

Year: 2025

Issue: 4

Volume: 43

Abstract:

Current applications of artificial intelligence in dermatology offices and potential ethical landmines

Sat, 25 Oct 2025 08:19:50 +0000

Author Names: MacKenzie J.,Coric C.,Kim Y.W.,Lee C.,Grant-Kels J.M.

Database Source: Embase Weekly Updates

Journal Title: Clinics in Dermatology

Article Title: Current applications of artificial intelligence in dermatology offices and potential ethical landmines

Year: 2025

Issue: 5

Volume: 43

Abstract: We review the ethical issues surrounding the use of artificial intelligence (AI) in medical offices, focusing on dermatology. Although previously reviewed, there have been significant advances in the employment of AI in various office tasks over the last year, accompanied by increased acceptance among dermatologists. There is now a plethora of applications for AI in our practices to enhance efficiency, streamline administrative tasks, and reduce physician burnout. Physicians should consider several ethical issues before employing AI, including informed consent, accuracy, privacy, trust/truthfulness, beneficence, nonmaleficence, staff displacement with the associated loss of human contact, bias, and justice or equity. In scenarios where AI proves to be inaccurate, we also need to resolve liability or accountability. We review the various applications of AI in our clinical practice and outline its benefits, including the ethical considerations necessary to use this technology to enhance our practices. Copyright © 2025 Elsevier Inc.

Unlocking the potential: multimodal AI in biotechnology and digital medicine—economic impact and ethical challenges.

Mon, 20 Oct 2025 04:00:00 +0000

NPJ Digital Medicine; 10/20/2025
(AN 188776821); ISSN: 23986352
CINAHL Complete

Strengthening ethics review of the development of artificial intelligence (AI) systems in health research: a guide for research ethics committees in Uganda.

Wed, 15 Oct 2025 04:00:00 +0000

BMC Medical Ethics; 10/15/2025
(AN 188682911); ISSN: 14726939
CINAHL Complete

The ethics of simplification: balancing patient autonomy, comprehension, and accuracy in AI-generated radiology reports.

Wed, 15 Oct 2025 04:00:00 +0000

BMC Medical Ethics; 10/15/2025
(AN 188682910); ISSN: 14726939
CINAHL Complete

Artificial intelligence in nursing practice: a qualitative study of nurses' perspectives on opportunities, challenges, and ethical implications.

Tue, 14 Oct 2025 04:00:00 +0000

BMC Nursing; 10/14/2025
Background: The 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. Methods: This qualitative study used semi 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 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. Results: The 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. Conclusion: The 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. #Artificial Intelligence in Nursing Practice: A Qualitative Study of Nurses' Perspectives on Opportunities, Challenges, and #Ethical Implications.
(AN 188650814); ISSN: 14726955
CINAHL Complete

Current status and solutions for AI ethics in ophthalmology: a bibliometric analysis.

Thu, 02 Oct 2025 04:00:00 +0000

NPJ Digital Medicine; 10/02/2025
(AN 188452612); ISSN: 23986352
CINAHL Complete

Ethical Implications of Artificial Intelligence in Anesthesiology: A Scoping Review.

Thu, 02 Oct 2025 04:00:00 +0000

Archives of Anesthesiology & Critical Care; 10/02/2025
(AN 188769144); ISSN: 24235849
CINAHL Complete

Editorial to the special issue on morality and AI.

Wed, 01 Oct 2025 04:00:00 +0000

Cognition; 10/01/2025
(AN 186591826); ISSN: 00100277
CINAHL Complete

Estimating divergent moral and diversity preferences between AI builders and AI users.

Wed, 01 Oct 2025 04:00:00 +0000

Cognition; 10/01/2025
(AN 186591810); ISSN: 00100277
CINAHL Complete

Does AI and human advice mitigate punishment for selfish behavior? An experiment on AI ethics from a psychological perspective.

Wed, 01 Oct 2025 04:00:00 +0000

Computers in Human Behavior; 10/01/2025
People increasingly rely on AI-advice when making decisions. At times, such advice can promote selfish behavior. When individuals abide by selfishness-promoting AI advice, how are they perceived and punished? To study this question, we build on theories from social psychology and combine machine-behavior and behavioral economic approaches. In a pre-registered, financially-incentivized experiment, evaluators could punish real decision-makers who (i) received AI, human, or no advice. The advice (ii) encouraged selfish or prosocial behavior, and decision-makers (iii) behaved selfishly or, in a control condition, behaved prosocially. Evaluators further assigned responsibility to decision-makers and their advisors. Results revealed that (i) prosocial behavior was punished very little, whereas selfish behavior was punished much more. Focusing on selfish behavior, (ii) compared to receiving no advice, selfish behavior was penalized more harshly after prosocial advice and more leniently after selfish advice. Lastly, (iii) whereas selfish decision-makers were seen as more responsible when they followed AI compared to human advice, punishment between the two advice sources did not vary. Overall, behavior and advice content shapes punishment, whereas the advice source does not. • AI can give harmful advice that people adopt when it fits their selfish interests. • A financially incentivized study tests punishment of selfishness after AI advice. • Responsibility is perceived higher when selfishness followed AI (vs. human) advice. • Costly punishment, however, is not affected by the (AI vs. human) advice source. • Costly punishment is only shaped by behavior and advice content.
(AN 185807591); ISSN: 07475632
CINAHL Complete

Editorial: AI-assisted Letters to the Editor—Scope of a Growing Ethical and Practical Concern, and CORR 's Approach to Managing It.

Wed, 01 Oct 2025 04:00:00 +0000

Clinical Orthopaedics & Related Research®; 10/01/2025
(AN 188283977); ISSN: 0009921X
CINAHL Complete

Artificial Intelligence in Critical Care Nursing: Benefits, Risks, and Ethical Considerations.

Wed, 01 Oct 2025 04:00:00 +0000

Critical Care Nurse; 10/01/2025
Background: The rapid evolution of artificial intelligence technologies, particularly in critical care nursing, presents opportunities and ethical challenges. Artificial intelligence has potential to enhance patient care and clinical decision-making, yet concerns regarding privacy, consent, bias, discrimination, and the dehumanization of care persist. Objective: To explore the intersection of artificial intelligence and ethics in nursing, with a focus on ethical implications for patient care and clinical decision-making. Methods: A comprehensive literature search was done for this narrative review to synthesize knowledge on artificial intelligence in nursing, incorporating insights from nursing, information technology, legal studies, and medicine. Results and Discussion: Artificial intelligence technologies are reshaping nursing workflows and can improve health care outcomes. However, these technologies introduce complex ethical concerns, including the risk for bias, data privacy issues, and the potential for reduced human interaction in patient care. Critical care nurses are uniquely positioned to leverage artificial intelligence effectively while identifying and mitigating risks related to its use. The involvement of critical care nurses in the development and application of artificial intelligence technologies is essential to ensure the accuracy, safety, and fairness of these tools. Conclusion: Critical care nurses must advocate for the ethical integration of artificial intelligence in health care, ensuring alignment with core nursing values such as autonomy, beneficence, nonmaleficence, justice, and veracity. By actively participating in discussions, monitoring artificial intelligence tools, and providing feedback, nurses can help to ensure that artificial intelligence technologies enhance patient care while upholding the ethical principles fundamental to nursing practice.
(AN 188360496); ISSN: 02795442
CINAHL Complete

Preserving medical ethics in the era of artificial intelligence: Challenges and opportunities in neonatology.

Wed, 01 Oct 2025 04:00:00 +0000

Seminars in Perinatology; 10/01/2025
The integration of artificial intelligence (AI) into neonatology offers improved patient care while raising ethical challenges across four principles: beneficence, non-maleficence, justice, and autonomy. AI enhances prediction and early detection capabilities, but introduces concerns including the "black box" nature of many algorithms, which compromises transparency and may propagate existing biases. Justice considerations arise from potential inequities in AI development and deployment. Autonomy is challenged when clinicians cannot fully explain algorithmic decision-making, affecting shared decision-making with families. These ethical tensions are particularly acute in neonatology, where decisions impact vulnerable patients who cannot advocate for themselves. Mitigating these challenges requires developing transparent AI systems, ensuring diverse training data, maintaining human oversight of clinical decisions, and conducting rigorous validation across diverse healthcare settings. Responsible implementation requires balancing technological benefits with ethical principles.
(AN 187866437); ISSN: 01460005
CINAHL Complete

Nursing students' AI literacy and ethical understanding of AI in nursing education.

Wed, 01 Oct 2025 04:00:00 +0000

Teaching & Learning in Nursing; 10/01/2025
• GAI supports student learning but may hinder critical thinking and ethical judgment. • Gaps identified in nursing students' ability to define ethical vs. unethical GAI use. • There is a need for AI ethics and literacy training in nursing education. Generative artificial intelligence (GAI) offers opportunities to enhance learning in nursing education yet raises concerns about academic integrity and critical thinking. Limited research exists on nursing students' ethical understanding and prior GAI exposure. To explore freshman nursing students' understanding of ethical versus unethical uses of GAI, their foundational AI literacy, and prior exposure to AI training. A cross-sectional descriptive study was conducted using a researcher-developed survey administered to 119 freshman BSN students at a large Midwestern university. The survey assessed knowledge of GAI ethics, GAI use, and perceptions of university-led GAI training. Students demonstrated a strong ability to differentiate between ethical and unethical uses of GAI (93 % accuracy). However, gaps were noted in understanding when AI-generated content crosses into academic dishonesty. Many students reported limited AI training and expressed strong interest in AI learning modules. Freshman nursing students are eager to use GAI responsibly but lack foundational training. AI literacy education is essential to support ethical decision-making, preserve academic integrity, and prepare students for responsible AI use in nursing practice.
(AN 187941187); ISSN: 15573087
CINAHL Complete

Use of generative AI in research: ethical considerations and emotional experiences.

Wed, 01 Oct 2025 04:00:00 +0000

Ethics & Behavior; 10/01/2025
This study examines researchers' ethical concerns toward the deployment of GenAI in research and their emotional responses. To acquire an in-depth understanding, we used narrative frames and follow-up interviews to collect data from 22 researchers who reported extensive experience with GenAI. An inductive thematic analysis revealed three themes capturing ethical concerns that invoked three types of emotional reactions. From an ethical perspective, our participants were concerned with "human ethical agency in AI research practices," "cognitive impacts of overreliance on GenAI in research," and "ethical issues of access, accuracy, and privacy." From an emotional perspective, they showed "mixed emotions," "positive emotions," and "negative emotions" when dealing with GenAI tools. There were close connections between the ethical implications of GenAI and the emotional reactions to them. In this light, we conclude that emotional reactions to GenAI, which are determinants of future use, should be taken more seriously in further research.
(AN 188424359); ISSN: 10508422
CINAHL Complete

Transforming Speech-Language Pathology with AI: Opportunities, Challenges, and Ethical Guidelines.

Wed, 01 Oct 2025 04:00:00 +0000

Healthcare (2227-9032); 10/01/2025
(AN 188681502); ISSN: 22279032
CINAHL Complete

Integrating AI in health and risk communication: opportunities, challenges, and ethical considerations.

Wed, 01 Oct 2025 04:00:00 +0000

Journal of Communication in Healthcare; 10/01/2025
(AN 188670803); ISSN: 17538068
CINAHL Complete

Exploring the ethical dimensions of AI integration in nursing practice: A systematic review.

Wed, 01 Oct 2025 04:00:00 +0000

Journal of Nursing Regulation; 10/01/2025
Artificial intelligence (AI) is being increasingly integrated into nursing practice, offering tools such as clinical decision support systems, predictive analytics, and robotic aids. While these technologies promise greater efficiency and precision, they also raise complex ethical challenges specific to the relational, advocacy-driven nature of nursing. To systematically review and synthesize the ethical implications of AI integration in nursing practice, focusing on five key domains: patient autonomy, privacy, accountability, equity and algorithmic bias, and nurse–patient relationships. Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses 2020 guidelines, a systematic review was conducted using PubMed, CINAHL, IEEE Xplore, and Google Scholar. Studies published between 2018 and 2025 that addressed AI ethics within nursing were included. Data were extracted from included studies and analyzed through thematic synthesis. Thirty-three articles met the inclusion criteria. Patient autonomy (67%), privacy (61%), and accountability (49%) were the most frequently discussed ethical concerns. AI's opacity often hindered informed consent and shared decision-making. Privacy risks included secondary data use and insufficient data governance. Accountability remained diffuse in cases of AI error, with nurses caught between professional duty and opaque algorithmic suggestions. Equity and algorithmic bias issues emerged in 42% of studies, especially when AI was trained on nondiverse datasets. Finally, nurse–patient relationships were strained in settings where AI mediated or replaced human contact, particularly in elder care. Ethical integration of AI in nursing requires nurse-centered system design, transparent governance protocols, and ethical education. Future efforts must emphasize equitable data practices, clarify liability, and preserve the relational foundation of nursing.
(AN 188598353); ISSN: 21558256
CINAHL Complete

Artificial intelligence in psychological practice: Applications, ethical considerations, and recommendations.

Wed, 01 Oct 2025 04:00:00 +0000

Professional Psychology: Research & Practice; 10/01/2025
Artificial intelligence (AI) systems are increasingly relied upon in the delivery of health care services traditionally provided solely by humans, and the widespread use of AI in the routine practice of professional psychology is on the horizon. It is incumbent on practicing psychologists to be prepared to effectively implement AI technologies and engage in thoughtful discourse regarding the ethical and responsible development, implementation, and regulation of these technologies. This article provides a brief overview of what AI is and how it works, a description of its current and potential future applications in professional practice, and a discussion of the ethical implications of using AI systems in the delivery of psychological services. Applications of AI technologies in key areas of clinical practice are addressed, including assessment and intervention. Using the Ethical Principles of Psychologists and Code of Conduct (American Psychological Association, 2017) as a framework, anticipated ethical challenges across five domains--harm and nonmaleficence, autonomy and informed consent, fidelity and responsibility, privacy and confidentiality, and bias, respect, and justice--are discussed. Based on these challenges, provisional recommendations for psychologists are provided.
(AN 188791198); ISSN: 07357028
CINAHL Complete

Ethical, Regulatory, and Practical Challenges in Artificial Intelligence-Driven Chest Imaging.

Wed, 01 Oct 2025 04:00:00 +0000

Seminars in Roentgenology; 10/01/2025
Artificial intelligence (AI) enhances the practice of chest imaging by improving diagnostic accuracy, streamlining workflows, and facilitating personalized patient care. As a powerful tool, AI augments the expertise of radiologists, enabling more precise evaluations and quicker decision-making. This article examines the barriers to AI adoption in chest imaging, focusing on challenges related to bias, transparency, accountability, and data privacy. We discuss the ethical implications of AI-driven decision-making, particularly concerning fairness, and propose strategies to address these concerns. Additionally, we explore regulatory obstacles, including the approval pathways for AI algorithms and the need for continuous learning and adaptability in clinical settings. We also address practical considerations, such as the integration of AI tools into existing workflows, model generalizability, and economic factors. The article concludes with recommendations for responsible AI adoption, emphasizing the importance of interdisciplinary collaboration, robust validation frameworks, and continuous education for radiologists. By navigating these challenges, the radiology community can effectively leverage AI's potential, ultimately leading to enhanced patient outcomes and improved diagnostic processes.
(AN 188750844); ISSN: 0037198X
CINAHL Complete

Ethics of AI in healthcare: a scoping review demonstrating applicability of a foundational framework.

Wed, 24 Sep 2025 04:00:00 +0000

Frontiers in Digital Health; 09/24/2025
(AN 188172385); ISSN: 2673253X
CINAHL Complete

Moral values for implementation of AI and machine learning in healthcare.

Mon, 15 Sep 2025 04:00:00 +0000

American Journal of Health-System Pharmacy; 09/15/2025
(AN 187861657); ISSN: 10792082
CINAHL Complete

How Could Artificial Intelligence Change the Doctor–Patient Relationship? A Medical Ethics Perspective.

Mon, 15 Sep 2025 04:00:00 +0000

Healthcare (2227-9032); 09/15/2025
(AN 188326063); ISSN: 22279032
CINAHL Complete

A roadmap of artificial intelligence applications in pediatric surgery: a comprehensive review of applications, challenges, and ethical considerations.

Sat, 06 Sep 2025 04:00:00 +0000

Pediatric Surgery International; 09/06/2025
(AN 187782796); ISSN: 01790358
CINAHL Complete

Designing for dignity: ethics of AI surveillance in older adult care.

Fri, 05 Sep 2025 04:00:00 +0000

Frontiers in Digital Health; 09/05/2025
(AN 187795202); ISSN: 2673253X
CINAHL Complete

Biases in AI: acknowledging and addressing the inevitable ethical issues.

Wed, 03 Sep 2025 04:00:00 +0000

Frontiers in Digital Health; 09/03/2025
(AN 187724481); ISSN: 2673253X
CINAHL Complete

Legalities, Ethics and Frameworks for Healthcare AI in India.

Tue, 02 Sep 2025 04:00:00 +0000

Academic Radiology; 09/02/2025
(AN 188128349); ISSN: 10766332
CINAHL Complete

Ethical Obligations to Inform Patients About Use of AI Tools.

Tue, 02 Sep 2025 04:00:00 +0000

JAMA: Journal of the American Medical Association; 09/02/2025
(AN 187783643); ISSN: 00987484
CINAHL Complete

Moral psychological exploration of the asymmetry effect in AI-assisted euthanasia decisions.