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Cited by 0Artificial Intelligence in Healthcare and EducationInnovations in Medical EducationHealth Education and Validation

Assessment Instruments for Artificial Intelligence Literacy in Healthcare Professionals: A Scoping Review

Open access
Mies-Padilla, Sergio, Rodríguez-Suárez, Claudio-Alberto, González-de la Torre, Héctor·2026·Information
DOI 10.3390/info17090914
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Abstract

Artificial Intelligence is being integrated into clinical practice within regulatory frameworks that assign healthcare professionals responsibility for human oversight, making AI literacy a core professional competency; however, there is little consensus on how it should be measured. This scoping review maps the instruments used to assess AI literacy among healthcare professionals, together with the domains they cover and the psychometric properties they report. Following the Joanna Briggs Institute framework and PRISMA-ScR, five databases were searched for primary studies published from 2017 onwards in English or Spanish. Screening was supported by an active-learning framework, and methodological quality was appraised with JBI tools. Thirty-nine studies were included, predominantly involving nurses and physicians. Methodological quality was heterogeneous, with the main weaknesses concentrated in the identification and handling of confounding factors. The instruments fell into validated standardized scales and study-specific ad hoc questionnaires that seldom report structural validation. Item-level deconstruction suggested a two-level thematic framework: three competence domains—cognitive-conceptual (82.1%), practical-clinical (69.2%), and ethical-regulatory (56.4%)—and two co-assessed domains corresponding to dispositions and organizational context (84.6% and 38.5%). Measurement in this field is fragmented, and reliance on unvalidated instruments limits international comparability. Assessment and training should prioritize critical appraisal of outputs, ethical data governance, and human oversight.

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Registry

Crossref · 10.3390/info17090914

Cites

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Cites

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Research works printed but not linked: 5

  1. Doorn, 2025, The AI Act: Responsibilities and obligations for healthcare professionals and organizations, Diagn. Interv. Radiol., 32, 273
  2. Gustafsson, 2015, Beyond dichotomies: Competence viewed as a continuum, Z. Psychol., 223, 3
  3. Polatgil, 2023, Adaptation of the Artificial Intelligence Literacy Scale into Turkish, Sos. Bilim. Nicel Araşt. Derg., 3, 99
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Authors
Mies-Padilla, S., Rodríguez-Suárez, C.-A., & González-de la Torre, H.
Affiliations
  • Hospital Universitario Insular de Gran Canaria (ES)
  • Universidad de Las Palmas de Gran Canaria (ES)
  • Department of Nursing, Faculty of Healthcare Science, University of Las Palmas de Gran Canaria (ULPGC), 35016 Las Palmas de Gran Canaria, Spain
Corresponding author
Rodríguez-Suárez, Claudio-Alberto
ORCID
Venue
Information
Publisher
MDPI AG
Published
2026-09-18
Volume
17
Issue
9
Pages
914
ISSN
2078-2489 (ISSN-L)
DOI
10.3390/info17090914
OpenAlex
W7214024584
Semantic Scholar
2fa04a35605409e04573b4bc93850ae65398c7d5
Cited by
0
References
74
FWCI
0.00
Type
journal article
Language
en
Open access
Licence
Locations
  • Information (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
  • Social Sciences › Education › Health Education and Validation
Keywords
AI literacy, healthcare workers, assessment instruments, psychometric properties, clinical implementation of AI, human oversight, AI ethics, AI regulation, nurses, physicians, competency domains, AI literacy training, measurement validation

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