Public perceptions of artificial intelligence in healthcare: ethical concerns and opportunities for patient-centered care.

BACKGROUND: In an effort to improve the quality of medical care, the philosophy of patient-centered care has become integrated into almost every aspect of the medical community. Despite its widespread acceptance, among patients and practitioners, there are concerns that rapid advancements in artificial intelligence may threaten elements of patient-centered care, such as personal relationships with care providers and patient-driven choices. This study explores the extent to which patients are confident in and comfortable with the use of these technologies when it comes to their own individual care and identifies areas that may align with or threaten elements of patient-centered care. METHODS: An exploratory, mixed-method approach was used to analyze survey data from 600 US-based adults in the State of Florida. The survey was administered through a leading market research provider (August 10-21, 2023), and responses were collected to be representative of the state's population based on age, gender, race/ethnicity, and political affiliation. RESULTS: Respondents were more comfortable with the use of AI in health-related tasks that were not associated with doctor-patient relationships, such as scheduling patient appointments or follow-ups (84.2%). Fear of losing the 'human touch' associated with doctors was a common theme within qualitative coding, suggesting a potential conflict between the implementation of AI and patient-centered care. In addition, decision self-efficacy was associated with higher levels of comfort with AI, but there were also concerns about losing decision-making control, workforce changes, and cost concerns. A small majority of participants mentioned that AI could be useful for doctors and lead to more equitable care but only when used within limits. CONCLUSION: The application of AI in medical care is rapidly advancing, but oversight, regulation, and guidance addressing critical aspects of patient-centered care are lacking. While there is no evidence that AI will undermine patient-physician relationships at this time, there is concern on the part of patients regarding the application of AI within medical care and specifically as it relates to their interaction with physicians. Medical guidance on incorporating AI while adhering to the principles of patient-centered care is needed to clarify how AI will augment medical care.

Public alert and warning system literature review in the USA: identifying research gaps and lessons for practice.

As emergencies continue to impact communities in the USA on an unprecedented scale, it is imperative for communities to look for effective ways to keep people safe and reduce future impacts. Public alert and warning systems are an effective means of accomplishing these goals. As such, researchers have studied public alert and warning systems extensively in the USA. Due to the plethora of studies on public alert and warning systems, a systematic and comprehensive synthesize is needed to understand what has been studied and their major findings and identify practical lessons that can be used to further improve public alert and warning systems. Hence, the goal of this study is to answer the following two questions: (1) What are the major findings from public alert and warning system research? (2) What policy and practical lessons can be gleaned from public alert and warning system research to improve public alert and warning system research and practice? We answer these questions by conducting a systematic and comprehensive review of the public alert and warning system literature, starting with a keyword search. The search produced 1737 studies, and we applied six criteria (e.g., the study has to be a peer-reviewed article, dissertation, or conference paper), which narrowed the number of studies to 100. After a reverse citation search, that number increased to 156 studies. Analysis of the 156 studies, the results reveal 12 emergent themes regarding the major findings from public alert and warning system research. The results also reveal eight emergent themes related to the policy and practical lessons. We then offer recommended topics for future research as well as outline some policy and practical recommendations. We conclude by summarizing the findings and discussing the limitations of the study.