Scholarlink

Background <p>The rapid integration of artificial intelligence (AI) in healthcare presents transformative potential, enhancing diagnostic accuracy, decision-making, and operational efficiency. However, the successful adoption of AI depends significantly on healthcare providers’ perceptions and attitudes, which influence its acceptance and implementation in clinical settings.</p> Aim <p>This review aimed to systematically examine existing literature to explore healthcare providers’ perceptions and attitudes regarding AI, highlighting key factors that shape trust, acceptance, and resistance.</p> Methods <p>Guided by PRISMA 2020, a comprehensive literature search was conducted across six databases, including PubMed, Scopus, and Web of Science, targeting studies published between January 2015 and March 2025. Eligible studies included qualitative, quantitative, and mixed-methods research focused on practicing healthcare providers. Data were synthesized using thematic analysis to extract and interpret key findings.</p> Results <p>Five core themes emerged: (1) General awareness and understanding of AI, highlighting a gap between recognition and operational knowledge; (2) Perceived benefits and opportunities, emphasizing diagnostic accuracy and workflow efficiency; (3) Concerns and perceived risks, including fear of job displacement, ethical ambiguity, and algorithmic bias; (4) Trust and acceptance, where direct experience and participatory design increased confidence in AI tools; and (5) Contextual influences, showing that age, role, and institutional environment shape perceptions.</p> Conclusion <p>Healthcare providers’ attitudes toward AI are complex and shaped by technical, ethical, and contextual factors. To ensure successful and equitable integration, AI deployment must prioritize trust-building, participatory design, clear regulation, and tailored training. Human-centered approaches are essential to align AI innovations with the needs and values of clinical practice.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Perceptions and attitudes of healthcare providers toward artificial intelligence: a systematic review

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月19日

查看全文
  • Daifallah M. Alrazeeni,
  • Maryam Alharrasi,
  • Moustaq Karim Khan Rony,
  • Chandana Rani Halder,
  • Fatema-Tuj-Johora Dhola,
  • Asha Aktery,
  • Israth Jahan Tama

摘要

Background

The rapid integration of artificial intelligence (AI) in healthcare presents transformative potential, enhancing diagnostic accuracy, decision-making, and operational efficiency. However, the successful adoption of AI depends significantly on healthcare providers’ perceptions and attitudes, which influence its acceptance and implementation in clinical settings.

Aim

This review aimed to systematically examine existing literature to explore healthcare providers’ perceptions and attitudes regarding AI, highlighting key factors that shape trust, acceptance, and resistance.

Methods

Guided by PRISMA 2020, a comprehensive literature search was conducted across six databases, including PubMed, Scopus, and Web of Science, targeting studies published between January 2015 and March 2025. Eligible studies included qualitative, quantitative, and mixed-methods research focused on practicing healthcare providers. Data were synthesized using thematic analysis to extract and interpret key findings.

Results

Five core themes emerged: (1) General awareness and understanding of AI, highlighting a gap between recognition and operational knowledge; (2) Perceived benefits and opportunities, emphasizing diagnostic accuracy and workflow efficiency; (3) Concerns and perceived risks, including fear of job displacement, ethical ambiguity, and algorithmic bias; (4) Trust and acceptance, where direct experience and participatory design increased confidence in AI tools; and (5) Contextual influences, showing that age, role, and institutional environment shape perceptions.

Conclusion

Healthcare providers’ attitudes toward AI are complex and shaped by technical, ethical, and contextual factors. To ensure successful and equitable integration, AI deployment must prioritize trust-building, participatory design, clear regulation, and tailored training. Human-centered approaches are essential to align AI innovations with the needs and values of clinical practice.