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Digital health competence among healthcare professionals: A cross-sectional cluster analysis across 19 countries and regions
Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Finland ; Medical Research Centre, Oulu University Hospital, University of Oulu, Finland ; School of Healthcare and Nursing Sciences, Faculty of Health and Wellbeing, Northumbria University, United Kingdom ; Department of Evidence-Based Clinical Nursing, Division of Health Sciences, Graduate School of Medicine, University of Osaka, Japan.
Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Finland ; School of Healthcare and Nursing Sciences, Faculty of Health and Wellbeing, Northumbria University, United Kingdom.
Sydney Nursing School, Faculty of Medicine and Health, The University of Sydney, Australia ; School of Nursing, University of Hong Kong, Hong Kong SAR, China.
School of Nursing, Guangzhou University of Chinese Medicine, China.
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2026 (English)In: International Journal of Nursing Studies, ISSN 0020-7489, E-ISSN 1873-491X, Vol. 176, article id 105348Article in journal (Refereed) Published
Abstract [en]

Background: The worldwide acceleration of digital transformation in healthcare underscores the need for professionals to continuously adapt and sustain robust digital health competence, shaped not only by individual characteristics and institutional environments but also by broader social, cultural, and geopolitical factors.

Objective: This study aimed to identify distinct clusters of digital health competence among healthcare professionals across 19 diverse countries and regions, and to examine the factors influencing the development and distribution of these competence clusters.

Methods: A cross-sectional international survey study was conducted between 2023 and 2024, using a validated survey instrument measuring digital health competence and its influencing factors. Data were collected from healthcare professionals in 19 countries and regions (n = 6440; n = 5945 used for this study), following a harmonised protocol with shared demographic templates and instruments. K-means cluster analysis was employed to derive digital competence profiles, with comparative analyses conducted to investigate associations between the identified clusters and individual characteristics (e.g., age, education, professional experience).

Results: Five distinct clusters of digital health competence were identified: (1) Beginners, (2) Developing Professionals, (3) Emerging Users, (4) Proficient Practitioners, and (5) Pioneers. Higher competence clusters (4 and 5) were associated with younger age, higher education, hospital-based work, and stronger perceived support from management, organisational structures, and colleagues. In contrast, lower-performing clusters reported limited digital engagement and minimal support. Perceived leadership influence, particularly managerial commitment to digital change, was a key differentiator across clusters.

Conclusions: The findings demonstrate substantial variation in digital health competence across healthcare professionals internationally. Cluster-specific strategies, such as targeted upskilling, peer mentoring, and leadership engagement, are needed to address competence gaps. The results provide a foundation for policy development and workforce training frameworks aimed at strengthening digital readiness in global healthcare systems. Future research should explore longitudinal competence development and evaluate targeted interventions.

Place, publisher, year, edition, pages
Elsevier, 2026. Vol. 176, article id 105348
Keywords [en]
Cluster analysis, Competence, Digital health, Healthcare, Professionals, acceleration, adult, article, controlled study, coworker, cross-sectional study, digital transformation, female, health care personnel, health care system, human, male, mentoring, physician, vocational education
National Category
Health Care Service and Management, Health Policy and Services and Health Economy Public Health, Global Health and Social Medicine
Research subject
Wellbeing in long-term health problems (WeLHP)
Identifiers
URN: urn:nbn:se:his:diva-26156DOI: 10.1016/j.ijnurstu.2026.105348ISI: 001683100700001PubMedID: 41621343Scopus ID: 2-s2.0-105028950027OAI: oai:DiVA.org:his-26156DiVA, id: diva2:2037856
Note

CC BY 4.0

© 2026 The Authors

Received 18 September 2025, Revised 15 January 2026, Accepted 16 January 2026, Available online 21 January 2026, Version of Record 31 January 2026.

Correspondence Address: K. Mikkonen; Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland; email: Kristina.mikkonen@oulu.fi; CODEN: IJNUA

No funding source.

Available from: 2026-02-12 Created: 2026-02-12 Last updated: 2026-02-16Bibliographically approved

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Hallgren, Jenny

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1819202122232421 of 26
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