AIMC Topic: Interviews as Topic

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Healthcare leaders' experiences of implementing artificial intelligence for medical history-taking and triage in Swedish primary care: an interview study.

BMC primary care
BACKGROUND: Artificial intelligence (AI) holds significant promise for enhancing the efficiency and safety of medical history-taking and triage within primary care. However, there remains a dearth of knowledge concerning the practical implementation ...

Navigating challenges and opportunities: Nursing student's views on generative AI in higher education.

Nurse education in practice
AIM: This qualitative study aims to explore the perspectives of nursing students regarding the application and integration of generative Artificial Intelligence (AI) tools in their studies.

Doctors' perception on the ethical use of AI-enabled clinical decision support systems for antibiotic prescribing recommendations in Singapore.

Frontiers in public health
OBJECTIVES: The increased utilization of Artificial intelligence (AI) in healthcare changes practice and introduces ethical implications for AI adoption in medicine. We assess medical doctors' ethical stance in situations that arise in adopting an AI...

Health consumers' ethical concerns towards artificial intelligence in Australian emergency departments.

Emergency medicine Australasia : EMA
OBJECTIVES: To investigate health consumers' ethical concerns towards the use of artificial intelligence (AI) in EDs.

Assessing AI Awareness and Identifying Essential Competencies: Insights From Key Stakeholders in Integrating AI Into Medical Education.

JMIR medical education
BACKGROUND: The increasing importance of artificial intelligence (AI) in health care has generated a growing need for health care professionals to possess a comprehensive understanding of AI technologies, requiring an adaptation in medical education.

Understanding the integration of artificial intelligence in healthcare organisations and systems through the NASSS framework: a qualitative study in a leading Canadian academic centre.

BMC health services research
BACKGROUND: Artificial intelligence (AI) technologies are expected to "revolutionise" healthcare. However, despite their promises, their integration within healthcare organisations and systems remains limited. The objective of this study is to explor...

Barriers and facilitators to technology acceptance of socially assistive robots in older adults - A qualitative study based on the capability, opportunity, and motivation behavior model (COM-B) and stakeholder perspectives.

Geriatric nursing (New York, N.Y.)
This study aimed to identify barriers and facilitators to older adults' acceptance of socially assistive robots from a stakeholder perspective. We enlisted 36 distinct stakeholders, including older adult, nurses, retirement home managers, and employe...

Prompts, Pearls, Imperfections: Comparing ChatGPT and a Human Researcher in Qualitative Data Analysis.

Qualitative health research
The impact of ChatGPT and other large language model-based applications on scientific work is being debated across contexts and disciplines. However, despite ChatGPT's inherent focus on language generation and processing, insights regarding its poten...

Identifying Main Themes in Diabetes Management Interviews Using Natural Language Processing-Based Text Mining.

Computers, informatics, nursing : CIN
This study aimed to identify the main themes from exit interviews of adult patients with type 2 diabetes after completion of a diabetes education program. Eighteen participants with type 2 diabetes completed an exit interview regarding their program ...

Capturing artificial intelligence applications' value proposition in healthcare - a qualitative research study.

BMC health services research
Artificial intelligence (AI) applications pave the way for innovations in the healthcare (HC) industry. However, their adoption in HC organizations is still nascent as organizations often face a fragmented and incomplete picture of how they can captu...