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Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/76025, first published .
Man programming a Pepper robot with a laptop in a lab

Understanding the Role of Clinical Decision Support Systems Among Hospital Nurses Using the FITT (Fit Between Individuals, Tasks, and Technology) Framework: Qualitative Study

Understanding the Role of Clinical Decision Support Systems Among Hospital Nurses Using the FITT (Fit Between Individuals, Tasks, and Technology) Framework: Qualitative Study

Journals

  1. Foscolou A, Kostara C, Gioxari A. Evaluating a Clinical Decision Support System for Optimizing Total Parenteral Nutrition in Adult Oncology Patients. Nutrients 2026;18(4):640 View
  2. Erdogan H, Ulcay D, Afsar F. Beyond alarm fatigue: nurses’ experiences of behavioral nudge fatigue in digital clinical environments. BMC Nursing 2026;25(1) View
  3. Frascarelli C, Concardi A, Mangione E, Negrelli M, Porta F, Tulino M, Sorino J, Marra A, Fusco N, Guerini-Rocco E, Venetis K. Conditional Generative AI in Oncology Diagnostics. Applied Sciences 2026;16(8):4015 View
  4. Di Muzio B, Salaran S, Morgan B, Woo A, Perry C, Jarema A, Hawkings P, Cameron P, Law M. Implementation of Electronic Clinical Decision Support for Radiology Referrals: The Role of Governance, Clinician Engagement and Education. Emergency Medicine Australasia 2026;38(4) View
  5. Yuwanto M, Yosep I, Pramukti I, Mediawati A. Self‐Leadership and Caring as Foundations of Relational Accountability in Nursing Clinical Judgement: A Conceptual Analysis. Nursing Open 2026;13(8) View
  6. Han X, Li X, Li M, Tian T, Shi K, Shi Y, Zhang F. Knowledge, attitudes, and practices of gynecologic oncology nurses toward patient decision aids for fertility preservation: a cross-sectional study in Zhengzhou, China. Frontiers in Public Health 2026;14 View
  7. Berkhout M, Leenen J, Smit K, van Houwelingen T. Evaluation of a Decision Mining Tool for Nursing Quality Improvement by Hospital Nurses: Theory-Guided Qualitative Study. JMIR Formative Research 2026;10:e100274 View
  8. Su H, Zou Y, Hu Y, Yuan Z, Yu Z, Yang C, Zhang Q, Qin W. From Task‐Technology Fit to Self‐Perceived Performance Impact Among Nurses: Exploring the Statistical Mediation of Self‐Reported Utilization of the Clinical Nursing Information System: A Cross‐Sectional Study. Nursing Open 2026;13(9) View
  9. Egerson D, Westlake S, Sesser A, Thompson D, McConnell M, Evans K. Evaluating Decision-Support Tools for Conservation Program Participation: A Stakeholder Assessment of the CRP Menu Tool. Environmental Management 2026;76(10) View
  10. Wang X, Sun Z, Lee G, Dykes P, Hu Y, Mu W, Zhang C, Zou Z, Xu L. Nurses’ Engagement in Digital Health Clinical Trials Using Unobtrusive Monitoring Technologies: Constructivist Grounded Theory Study. Journal of Medical Internet Research 2026;28:e90982 View
  11. Badawy W, Shaban M. When the algorithm and the bedside disagree: Nurses' critical experiences of overreliance, override, deskilling, and accountability in AI-enabled and algorithmic clinical practice—A multicentre qualitative study. Applied Nursing Research 2026;92:152147 View

Books/Policy Documents

  1. Thaveenthiran P, Jithoo R, Logothetis and Kon Mouzakis I. Traumatic Brain Injury - Updates on Global Treatment Strategies and Technology Applications [Working Title]. View