Evidence map›Paper›PMID 37308323›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2023

The case for expressing nursing theories using ontologies.

Elizabeth E Umberfield, Patricia A Ball Dunlap, Marcelline R Harris

Open access · hybridAbstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 1 country.

Elizabeth E UmberfieldDivision of Nursing Research, Department of Nursing, Mayo Clinic, Rochester, Minnesota, USA.ORCID 0000-0001-5029-1158
Patricia A Ball DunlapCenter for Digital Health, Mayo Clinic, Rochester, Minnesota, USA.
Marcelline R HarrisEmeritus, School of Nursing, University of Michigan, Ann Arbor, Michigan, USA.ORCID 0000-0002-3957-6643
Mayo Clinic · USUniversity of Maryland, Baltimore · USUniversity of Michigan · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nursing and informatics share a common strength in their use of structured representations of domains, specifically the underlying notion of 'things' (ie, concepts, constructs, or named entities) and the relationships among those things. Accurate representation of nursing knowledge in machine-interpretable formats is a necessary next step for leveraging contemporary technologies. Expressing validated nursing theories in ontologies, and in particular formal ontologies, would serve not only nursing, but also investigators from other domains, clinical information system developers, and the users of advanced technologies such as artificial intelligence that seek to learn from the real-world data and evidence generated by nurses and others. Such efforts will enable sharing knowledge and conceptualizations about phenomena across the domains of nursing and generating, testing, revising, and providing theoretically-based perspectives when leveraging contemporary technologies. Nursing is well situated for this work, leveraging intentional and focused collaborations among nurse informaticists, scientists, and theorists.

Indexed as

Artificial IntelligenceNursing TheoryHumansInformaticsSemanticsartificial intelligencenursing theoryontologiessemanticsterminology systems

Identifiers

PMID37308323
PMCPMC10586024
OpenAlexW4380371590

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.