Evidence map›Paper›PMID 40378129›Full record

ArticlePloS one2025

Professional identity and its relationships with AI readiness and interprofessional collaboration.

Wafa'a Ta'an, Sadeq Damrah, Mohammed M Al-Hammouri, Brett Williams

Abstract readMulticenter Study
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

Wafa'a Ta'anCommunity and Mental Health Nursing Department, Faculty of Nursing, Jordan University of Science and Technology, Irbid, Jordan.ORCID 0000-0002-4381-8772
Sadeq DamrahDepartment of Mathematics and Physics, College of Engineering, Australian University, Safat, Kuwait.ORCID 0000-0002-5500-3685
Mohammed M Al-HammouriCommunity and Mental Health Nursing Department, Faculty of Nursing, Jordan University of Science and Technology, Irbid, Jordan.
Brett WilliamsDepartment of Paramedicine, Monash University, Clayton, Victoria, Australia.ORCID 0000-0001-6307-1779

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn contemporary healthcare practices, the convergence of Artificial Intelligence (AI) and interprofessional collaboration represents a transformative era marked by unprecedented opportunities and challenges. The introduction of AI technologies is assumed to lead to changes in the nature of interprofessional collaboration that require revisiting the already established professional identity; however, research is lacking in the area.

objectiveTo examine professional identity and its relationships with AI readiness domains and interprofessional collaboration components.

methodsA multisite cross-sectional research design was used to recruit 512 participants from different healthcare professions in Jordan between November 14th, 2023, and February 13th, 2024. The Medical Artificial Intelligence Readiness Scale and the Readiness for Interprofessional Learning Scale were used in data collection. Data analysis included descriptive, correlation, and comparative analyses.

resultsProfessional identity significantly and positively correlated with artificial intelligence readiness total and subscale scores with ρ ranging from 0.37 to 0.47 (p < .01). In addition, professional identity significantly correlated with interprofessional teamwork and collaboration (ρ=0.79, p < .01) and the roles and responsibilities components of interprofessional collaboration (ρ=0.37, p < .01). Professional identity was significantly higher among male participants and participants with experience of five years or higher.

conclusionThe study sets the grounding roles to develop the healthcare workforce's professional identity within the dynamic healthcare environment in the age of artificial intelligence and interprofessional collaboration. The study highlights areas of development for healthcare managers and practitioners, such as AI interprofessional collaboration-based training, targeting both artificial intelligence domains and interprofessional collaboration components while preserving a positive professional identity.

Indexed as

Artificial IntelligenceCooperative BehaviorHealth PersonnelInterprofessional RelationsSocial IdentificationAdultCross-Sectional StudiesFemaleHumansJordanMaleMiddle AgedSurveys and Questionnaires

Identifiers

PMID40378129
PMCPMC12083793

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.