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Currently submitted to: JMIR Nursing

Date Submitted: Jan 6, 2026
Open Peer Review Period: Jan 14, 2026 - Mar 11, 2026
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Mapping the conceptual landscape of Nursing Omics: a theoretical analysis of a multi-omics-inspired framework for nursing informatics

  • Shuangdui Ji; 
  • Shuping Guo; 
  • Donglian Zheng; 
  • Shilin Ma; 
  • Fuzhen Ma; 
  • Changqi Yin

ABSTRACT

Background:

The nursing field is facing unprecedented challenges driven by an explosion of heterogeneous data, persistent data silos, and increasing complexity in clinical decision-making. These issues underscore the urgent need for a systematic, integrative framework to organize and leverage nursing information effectively.

Objective:

This paper aims to conceptualize “Nursing Omics” a novel, multi-omics inspired integrative framework for future-oriented nursing informatics.

Methods:

Using a theoretical development approach, we draw on paradigms from genomics, proteomics, and other omics disciplines, integrating core principles from nursing informatics, systems science, and data science to construct a coherent conceptual architecture.

Results:

We propose a formal definition of Nursing-Omics and introduce a multidimensional integrative framework comprising the Intervenomics, Responsomics, Behaviomics, Exposomics, Experienomics. The framework is grounded in four foundational principles: holism, dynamism, data-driven insight, and individualization.

Conclusions:

Nursing-Omics offers a transformative paradigm for the systematic integration of nursing data, enabling precision decision-making, accelerating knowledge generation, and advancing intelligent, person-centered care. It represents a critical direction for the evolution of nursing informatics in the era of digital health. Clinical Trial: NO


 Citation

Please cite as:

Ji S, Guo S, Zheng D, Ma S, Ma F, Yin C

Mapping the conceptual landscape of Nursing Omics: a theoretical analysis of a multi-omics-inspired framework for nursing informatics

JMIR Preprints. 06/01/2026:90958

DOI: 10.2196/preprints.90958

URL: https://preprints.jmir.org/preprint/90958

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