Evidence map›Paper›PMID 42314027›Full record

ArticleNursing inquiry2026

Beyond Deskilling: Reframing Skill Disruption Among Internationally Educated Nurses as a Problem of Skill Governance.

Daniel Joseph E Berdida

Abstract read
In one paragraph

Article in Nursing inquiry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Daniel Joseph E BerdidaDepartment of Nursing, North Private College of Nursing, Arar, Northern Border, Saudi Arabia.ORCID https://orcid.org/0000-0002-5001-6946

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Internationally educated nurses are increasingly central to healthcare systems facing persistent workforce shortages, ageing populations, and rising care demands. Yet research continues to show that migration and workforce entry are often accompanied by significant disruption to professional practice. Although these experiences are commonly described through the language of deskilling, post-migration skill change is still often framed as a linear process of adaptation and eventual professional equivalence. In this discursive paper, I argue that linear accounts of post-migration skill adjustment are analytically limited because they obscure how host healthcare systems shape what counts as legitimate nursing competence. I propose instead that deskilling, upskilling, unskilling, and mis-skilling should be understood as overlapping and sometimes contradictory outcomes of how these systems regulate, recognize, and reorganize nursing labor. Drawing on nursing workforce scholarship, professional regulation literature, migration studies, and the sociology of work, I reframe skill disruption as a structural effect of skill governance, shaped by risk management, selective recognition, and the preservation of professional hierarchies. A conceptual model of skill governance is presented to show how prior expertise is filtered through regulatory and organizational processes, producing uneven forms of professional incorporation. This reframing has implications for workforce policy, regulatory practice, and nursing leadership by shifting attention from individual adaptation to system accountability and more equitable forms of workforce integration.

Indexed as

Clinical CompetenceNurses, InternationalEmigration and ImmigrationHumansdeskillinginternationally educated nursesmigrationmis‐skillingnursing regulationskill governanceworkforce integration

Identifiers

PMID42314027
PMCPMC13479398

What OpenQuestion holds

Textmetadata
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.