Factors Influencing Telemedicine Adoption Among Healthcare Professionals in Geriatric Medical Centers: A Technology Acceptance Model Approach

Tammy Porat-Packer, Gizell Green, Cochava Sharon, Riki Tesler

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Telemedicine has gained significance, especially during the COVID-19 pandemic, offering remote healthcare solutions. However, its adoption in geriatric medical centers (GMCs) remains limited. Understanding the factors influencing telemedicine acceptance among care teams in geriatric medical centers is crucial for successful implementation. Aim: This study examines behavioral factors influencing telemedicine adoption among care teams in Israeli geriatric medical centers through the lens of the Technology Acceptance Model. Methods: A cross-sectional study was conducted with 406 healthcare professionals from four geriatric medical centers in Israel. Participants completed a self-administered questionnaire measuring self-efficacy, subjective norms, anxiety, resistance to change, perceived usefulness, perceived ease of use, and intention to use telemedicine. Structural equation modeling was used to analyze the data. Results: Perceived ease of use mediated the associations between self-efficacy and perceived usefulness and between subjective norms and perceived usefulness, demonstrating how confidence shapes technology acceptance. Perceived usefulness mediated the association between perceived ease of use and intention to use. Perceived ease of use did not mediate the relationship between anxiety or resistance to technological changes and perceived usefulness. Conclusions: The study highlights the importance of perceived ease of use and usefulness in promoting telemedicine adoption among geriatric medical center care teams, emphasizing the need for targeted interventions to enhance these perceptions.

Original languageEnglish
Article number1367
JournalBehavioral Sciences
Volume15
Issue number10
DOIs
StatePublished - Oct 2025

Keywords

  • healthcare professionals
  • organizational behavior
  • self-efficacy
  • social influence
  • structural equation modeling
  • technology acceptance
  • technology anxiety
  • telemedicine

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