RESUMO
Background: With the increasing integration of artificial intelligence (AI) technologies into healthcare systems, there is a growing emphasis on privacy and ethical considerations. Nurses, as frontline healthcare professionals, are pivotal in-patient care and offer valuable insights into the ethical implications of AI adoption. Objectives: This study aimed to explore nurses' perspectives on privacy and ethical concerns associated with the implementation of AI in healthcare settings. Methods: We employed Van Manen's hermeneutic phenomenology as the qualitative research approach. Data were collected through purposive sampling from the December 7, 2023 to the January 15, 2024, with interviews conducted in Bengali. Thematic analysis was utilized following member checking and an audit trail. Results: Six themes emerged from the research findings: Ethical dimensions of AI integration, highlighting complexities in incorporating AI ethically; Privacy challenges in healthcare AI, revealing concerns about data security and confidentiality; Balancing innovation and ethical practice, indicating a need to reconcile technological advancements with ethical considerations; Human touch vs. technological progress, underscoring tensions between automation and personalized care; Patient-centered care in the AI era, emphasizing the importance of maintaining focus on patients amidst technological advancements; and Ethical preparedness and education, suggesting a need for enhanced training and education on ethical AI use in healthcare. Conclusions: The findings underscore the importance of addressing privacy and ethical concerns in AI healthcare development. Nurses advocate for patient-centered approaches and collaborate with policymakers and tech developers to ensure responsible AI adoption. Further research is imperative for mitigating ethical challenges and promoting ethical AI in healthcare practice.
RESUMO
Background: With the ever-increasing integration of artificial intelligence (AI) into health care, it becomes imperative to gain an in-depth understanding of how health care professionals, specifically nurse practitioners, perceive and approach this transformative technology. Objectives: This study aimed to gain insights into nurse practitioners' perceptions and attitudes toward AI adoption in health care. Methods: This qualitative research employed a descriptive and phenomenological approach using in-depth interviews. Data were collected through a semi-structured questionnaire with 37 nurse practitioners selected through purposive sampling, specifically Maximum Variation Sampling and Expert Sampling techniques, to ensure diversity in characteristics. Trustworthiness of the research was maintained through member checking and peer debriefing. Thematic analysis was employed to uncover recurring themes and patterns in the data. Results: The thematic analysis revealed nine main themes that encapsulated nurse practitioners' perceptions and attitudes toward AI adoption in health care. These included nurse practitioners' perceptions of AI implementation, attitudes toward AI adoption, patient-centered care and AI, quality of health care delivery and AI, ethical and regulatory aspects of AI, education and training needs, collaboration and interdisciplinary relationships, obstacles in integrating AI, and AI and health care policy. While this study found that nurse practitioners held a wide range of perspectives, with many viewings AI as a tool to enhance patient care. Conclusions: This research provides a valuable contribution to the evolving discourse surrounding AI adoption in health care. The findings underscore the necessity for comprehensive education and training in AI, accompanied by clear and robust ethical and regulatory guidelines to ensure the responsible integration of AI in health care practice. Furthermore, fostering collaboration and interdisciplinary relationships is pivotal for the successful incorporation of AI in health care. Policymakers should also address the challenges and opportunities that AI presents in the health care sector. This study enhances the ongoing conversation on AI adoption in health care by shedding light on the perspectives of nurses, thereby shaping future strategies for AI integration.
RESUMO
Childhood experiences are known to shape individuals' development and can influence various aspects of life later on. Understanding the long-term effects is crucial for informing interventions and policies aimed at promoting healthy aging. This review aimed to explore the long-term effects of childhood experiences on older individuals. This systematic review comprised three distinct phases. Firstly, a systematic review was conducted, exploring databases such as Google Scholar, PubMed, EMBASE, PsycINFO, and the Web of Science. Out of the 2116 studies initially identified, 24 studies were selected based on the inclusion criteria. Secondly, these inclusion criteria were applied to ensure that the chosen studies specifically delved into the connection between childhood experiences and outcomes in older individuals. Finally, data extraction and synthesis techniques were employed to analyze findings, facilitating the drawing of conclusions concerning the enduring impacts of childhood experiences on the well-being of older individuals. The review's findings revealed how negative experiences in childhood continue to affect older individuals in various ways. These early-life events have far-reaching consequences, profoundly impacting their physical health, making them more susceptible to chronic diseases and weakening their immune system. Additionally, they affect mental health, leading to conditions like depression, anxiety, and substance abuse. Cognitive function is also affected, resulting in memory problems and cognitive decline. Furthermore, these experiences impact social relationships, affecting trust, emotional control, and social isolation in later life. This review highlighted the enduring influence of childhood circumstances on the health and well-being of older individuals. Policymakers and health care practitioners should consider these findings when developing strategies to support healthy aging and mitigate the long-term effects of adverse childhood experiences.
RESUMO
Background: The rapid integration of artificial intelligence (AI) into healthcare has raised concerns among healthcare professionals about the potential displacement of human medical professionals by AI technologies. However, the apprehensions and perspectives of healthcare workers regarding the potential substitution of them with AI are unknown. Objective: This qualitative research aimed to investigate healthcare workers' concerns about artificial intelligence replacing medical professionals. Methods: A descriptive and exploratory research design was employed, drawing upon the Technology Acceptance Model (TAM), Technology Threat Avoidance Theory, and Sociotechnical Systems Theory as theoretical frameworks. Participants were purposively sampled from various healthcare settings, representing a diverse range of roles and backgrounds. Data were collected through individual interviews and focus group discussions, followed by thematic analysis. Results: The analysis revealed seven key themes reflecting healthcare workers' concerns, including job security and economic concerns; trust and acceptance of AI; ethical and moral dilemmas; quality of patient care; workforce role redefinition and training; patient-provider relationships; healthcare policy and regulation. Conclusions: This research underscores the multifaceted concerns of healthcare workers regarding the increasing role of AI in healthcare. Addressing job security, fostering trust, addressing ethical dilemmas, and redefining workforce roles are crucial factors to consider in the successful integration of AI into healthcare. Healthcare policy and regulation must be developed to guide this transformation while maintaining the quality of patient care and preserving patient-provider relationships. The study findings offer insights for policymakers and healthcare institutions to navigate the evolving landscape of AI in healthcare while addressing the concerns of healthcare professionals.