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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Mar 26, 2026
Date Accepted: Jul 21, 2026

The final, peer-reviewed published version of this preprint can be found here:

Digital Health Competence and Attitudes Toward AI Among Health Care Professionals: Convergent Mixed Methods Study

Jimenez-Garcia S, Domingo-Pozo M, Garcia-Rodriguez J, Tomás D, Ortiz-Perez D, Mikkonen K, Jarva E, Vizcaya-Moreno MF

Digital Health Competence and Attitudes Toward AI Among Health Care Professionals: Convergent Mixed Methods Study

J Med Internet Res 2026;28:e96170

DOI: 10.2196/96170

Digital Health Competence and Attitudes Towards Artificial Intelligence Among Healthcare Professionals: A Convergent Mixed-Methods Study.

  • Segundo Jimenez-Garcia; 
  • Manuela Domingo-Pozo; 
  • Jose Garcia-Rodriguez; 
  • David Tomás; 
  • David Ortiz-Perez; 
  • Kristina Mikkonen; 
  • Erika Jarva; 
  • M. Flores Vizcaya-Moreno

ABSTRACT

Background:

Digital transformation is reshaping healthcare systems and requires healthcare professionals to develop advanced digital health competencies. The integration of artificial intelligence (AI) in the workplace introduces new demands in evaluation, oversight, and ethical responsibility. However, evidence linking validated measures of digital health competence with professionals’ attitudes toward AI is limited.

Objective:

This study aimed to: (1) assess digital health competence among healthcare professionals in Spain, (2) examine organizational conditions supporting competence development, (3) explore perceptions about AI use in the workplace, and (4) test the association between digital health competence and AI attitudes.

Methods:

A national cross-sectional convergent mixed-methods study was conducted from November 2023 to January 2024. A voluntary convenience sample of healthcare professionals (n=229) participated. Digital health competence was measured with the DigiHealthCom (42 items; 5 domains), and associated factors with the DigiComInf (15 items; 3 domains), both on a 4-point Likert scale. Structural validity was evaluated by Confirmatory Factor Analysis (CFA). AI perceptions were explored with qualitative content analysis of open-ended responses. AI attitudes were categorized (positive, negative, ambivalent, uncertain) and analyzed by multinomial logistic regression, adjusted for age and sex.

Results:

Participants were mostly nurses and middle-aged professionals (M=45.9; SD=10). The mean DigiHealthCom total score was 3.01 (SD=0.51). Scores were highest for ICT competence (3.34) and lowest for evaluation and implementation competence (2.83). The DigiComInf mean was 2.51 (SD=0.57), with organizational planning lowest (2.21). CFA supported the factor structures (DigiHealthCom: CFI=0.95, RMSEA=0.049; DigiComInf: CFI=0.95, RMSEA=0.084). AI attitudes were mainly positive (58.3%). Qualitative findings indicated that conditional optimism was linked to requirements for training, governance, and human oversight. Higher digital health competence was independently associated with greater odds of a positive rather than negative AI attitude (OR=4.47, 95% CI 1.81-11.06, p=0.001).

Conclusions:

Digital health competence linked to attitudes toward AI among healthcare professionals. Gaps in evaluative and implementation competence, along with limited organizational support, may constrain responsible AI integration. Strengthening advanced digital competencies is central to preparing the workforce for regulated AI-enabled healthcare systems.


 Citation

Please cite as:

Jimenez-Garcia S, Domingo-Pozo M, Garcia-Rodriguez J, Tomás D, Ortiz-Perez D, Mikkonen K, Jarva E, Vizcaya-Moreno MF

Digital Health Competence and Attitudes Toward AI Among Health Care Professionals: Convergent Mixed Methods Study

J Med Internet Res 2026;28:e96170

DOI: 10.2196/96170

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