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

Digital transformation is reshaping health care systems and requires health care professionals to develop advanced digital health competencies. The integration of AI into clinical practice introduces new demands related to critical evaluation, human oversight, ethical responsibility, and regulatory compliance. However, evidence linking validated measures of digital health competence with health care professionals' attitudes toward AI remains limited.

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

A national cross-sectional convergent mixed methods study was conducted between November 2023 and January 2024 with a voluntary convenience sample of 229 health care professionals. Digital health competence was assessed using DigiHealthCom (digital health competence instrument; 42 items, 5 domains) and DigiComInf (the aspects associated with digital health competence instrument; 15 items, 3 domains). Confirmatory factor analysis evaluated structural validity. Open-ended responses regarding AI perceptions were explored using inductive qualitative content analysis. AI attitudes were classified into 4 categories (positive, negative, ambivalent, and uncertain), and their association with digital health competence was examined using multinomial logistic regression adjusted for age and sex.

Participants were predominantly female (169/229, 73.8%) and nurses (123/229, 53.7%), with a mean age of 45.9 (SD 10) years. Overall digital health competence was moderate (mean 3.01, SD 0.51), with the highest scores in information and communication technology competence (3.34, SD 0.63) and the lowest in competence related to evaluating and implementing digital solutions (2.83, SD 0.63). Organizational and educational support for competence development was also moderate (mean 2.51, SD 0.57), with organizational planning receiving the lowest DigiComInf scores (2.21, SD 0.76). Confirmatory factor analysis supported the proposed factor structures for both instruments (DigiHealthCom: comparative fit index=0.95, root-mean-square error of approximation=0.049; DigiComInf: comparative fit index=0.95, root-mean-square error of approximation=0.084). Most participants expressed positive attitudes toward AI in the workplace (134/228, 58.77%). Qualitative findings revealed a pattern of conditional optimism, with expected benefits for efficiency and patient care balanced by concerns regarding training, governance, regulation, and human oversight.

Digital health competence was positively associated with health care professionals' attitudes toward AI. However, the cross-sectional design does not allow conclusions regarding the direction of this association. Deficiencies in higher-order competencies in evaluation and implementation, together with limited organizational support, highlight areas that may benefit from targeted educational and organizational strategies to promote the safe and responsible use of AI in health care.