Digital health competencies in European public health residents: evaluation through a validated assessment tool and an educational intervention.
1
Department of Public health, Sapienza University, Roma, Italy
2
European Network of Multidisciplinary Residents in Public Health, Paris, France
3
Department of Sciences of Public Health and Pediatrics, University of Turin, Turin, Italy
4
Department of SUOC Prevention and Surveillance of Infectious and Chronic Diseases, Department of Preventionciences of Public Health and Pediatrics, Local Health Authority, Ancona, Italy
5
Institut de Recerca Sant Pau (IR SANT PAU), Barcelona, Spain
6
Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
7
Department of Medical and Surgical Science, Alma Mater Studiorum, University of Bologna, Bologna, Italy
8
Department of Public Health, University of Pavia, Pavia, Italy
9
Centre d’Investigation Clinique Guyane Amazonie, Cayenne, French Guiana
10
UA17 INSERM Santé des Populations en Amazonie, Université de Guyane, Cayenne, French Guiana
11
Departmental Unit of Taormina, Department of Prevention, Local Health Authority, Messina, Italy
12
Faculty of Health Sciences, Libertas International University, Zagreb, Croatia
Popul. Med. 2026;8(Supplement Supplement 1):A899
ABSTRACT
BACKGROUND:
Persistent gaps remain between the recognized importance of digital health (DH) in Public Health (PH) practice and workforce's competencies. No validated tool is currently available to assess DH competencies among PH professionals. This study aimed to develop and validate a questionnaire assessing competencies and attitudes in DH among PH residents, and to evaluate baseline competencies and short-term changes following a targeted educational intervention.
METHODS:
A 30-item questionnaire was developed using a modified Delphi approach informed by the DECODE framework. Items assessed competencies and attitudes across four domains in DH: professionalism, patient and population, health information systems, and health data science. The questionnaire was validated through expert review, principal component analysis (PCA), and Cronbach’s alpha. It was administered before and after DH training sessions to PH residents attending the EuroNet MRPH Spring Meeting 2025. Pre–post differences were analyzed using Welch’s t-test.
RESULTS:
Ninety-three residents completed the baseline survey and sixty-eight the post-intervention survey. Baseline results showed high interest in DH (mean 4.8/6) and strong perceived training needs (mean 5.3/6), contrasted with low self-reported academic training (mean 2.4/6). PCA supported a two-component structure distinguishing attitudes from competencies (ρ = 0.48). Internal consistency was good across domains (α = 0.78–0.91). Post-intervention analyses showed statistically significant improvements, primarily in competency-based items related to interoperability, data governance, privacy regulation, and computational thinking (Δ up to +1.2, p < 0.05).
CONCLUSIONS:
European PH residents demonstrate high interest and perceived training needs in DH, contrasted with low self-reported academic training. Short educational interventions can yield modest competency gains; however, sustained and curriculum-integrated training is needed. The proposed questionnaire represents a promising tool for assessing DH competencies and guiding workforce development in Public Health.
Persistent gaps remain between the recognized importance of digital health (DH) in Public Health (PH) practice and workforce's competencies. No validated tool is currently available to assess DH competencies among PH professionals. This study aimed to develop and validate a questionnaire assessing competencies and attitudes in DH among PH residents, and to evaluate baseline competencies and short-term changes following a targeted educational intervention.
METHODS:
A 30-item questionnaire was developed using a modified Delphi approach informed by the DECODE framework. Items assessed competencies and attitudes across four domains in DH: professionalism, patient and population, health information systems, and health data science. The questionnaire was validated through expert review, principal component analysis (PCA), and Cronbach’s alpha. It was administered before and after DH training sessions to PH residents attending the EuroNet MRPH Spring Meeting 2025. Pre–post differences were analyzed using Welch’s t-test.
RESULTS:
Ninety-three residents completed the baseline survey and sixty-eight the post-intervention survey. Baseline results showed high interest in DH (mean 4.8/6) and strong perceived training needs (mean 5.3/6), contrasted with low self-reported academic training (mean 2.4/6). PCA supported a two-component structure distinguishing attitudes from competencies (ρ = 0.48). Internal consistency was good across domains (α = 0.78–0.91). Post-intervention analyses showed statistically significant improvements, primarily in competency-based items related to interoperability, data governance, privacy regulation, and computational thinking (Δ up to +1.2, p < 0.05).
CONCLUSIONS:
European PH residents demonstrate high interest and perceived training needs in DH, contrasted with low self-reported academic training. Short educational interventions can yield modest competency gains; however, sustained and curriculum-integrated training is needed. The proposed questionnaire represents a promising tool for assessing DH competencies and guiding workforce development in Public Health.
| eISSN: | 2654-1459 |
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