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<p>The metaverse is a cutting-edge digital innovation with transformative potential in healthcare, offering enhanced training, remote consultations, and improved patient engagement. However, its adoption faces several critical limitations. This study investigates barriers to integrating the metaverse in healthcare within the Health 5.0 framework. Employing a mixed-method approach combining a Systematic literature review, Delphi, Total Interpretive Structural Modeling (TISM), and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) techniques, 10 key barriers were identified and examined for their interrelationships and classified based on their driving and dependence power. The findings map the structural hierarchy of these barriers, distinguishing high-driving from high-dependence factors. Results show that extensive capital requirements, mental health concerns, and ethical and legal challenges emerge as primary driving forces. Other significant linkages include a lack of digital strategy and management support, skill shortages, interoperability challenges, limited awareness, and inadequate technical infrastructure. Data privacy and security concerns, the digital divide, and accessibility appear as highly dependent barriers that require focused intervention. The research provides a structured framework to support policymakers, healthcare administrators, and technology developers in developing targeted strategies for the adoption of the metaverse in healthcare.</p>

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Structuring barriers to metaverse adoption in Health 5.0: insights from TISM and MICMAC analysis

  • 期刊论文

  • 发表日期：

    2025年11月11日

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  • Neha Singh,
  • Nupur Soti,
  • Jancy Phore,
  • Ashish Kumar,
  • Bharti,
  • A. K. Saini

摘要

The metaverse is a cutting-edge digital innovation with transformative potential in healthcare, offering enhanced training, remote consultations, and improved patient engagement. However, its adoption faces several critical limitations. This study investigates barriers to integrating the metaverse in healthcare within the Health 5.0 framework. Employing a mixed-method approach combining a Systematic literature review, Delphi, Total Interpretive Structural Modeling (TISM), and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) techniques, 10 key barriers were identified and examined for their interrelationships and classified based on their driving and dependence power. The findings map the structural hierarchy of these barriers, distinguishing high-driving from high-dependence factors. Results show that extensive capital requirements, mental health concerns, and ethical and legal challenges emerge as primary driving forces. Other significant linkages include a lack of digital strategy and management support, skill shortages, interoperability challenges, limited awareness, and inadequate technical infrastructure. Data privacy and security concerns, the digital divide, and accessibility appear as highly dependent barriers that require focused intervention. The research provides a structured framework to support policymakers, healthcare administrators, and technology developers in developing targeted strategies for the adoption of the metaverse in healthcare.