Bridging the gap: enhancing data science and leadership knowledge and skills in the context of the public health workforce.

Authors

Diana Hamer, Madelyn Gustafson, Christine Ortiz Gumina, Danielle C Landis, Patricia Bockelman, Elaina Perry, Sarah D Matthews

Published in

Frontiers in public health. Volume 13. Pages 1505869. Epub Apr 29, 2025.

Abstract

This study addresses critical gaps in public health workforce development, focusing on data science and leadership skills amidst increasing data accessibility and complexity in public health practice.
Quantitative and qualitative research methods were employed, including listening sessions with diverse public health professionals. Recruitment and post-session surveys were conducted, and session transcripts were analyzed using phenomenological and categorical coding methods based on the PPP Framework.
The research identified three core concepts in public health data science and leadership: data science, data literacy, and data-informed leadership. Clear definitions for each concept were developed. Significant gaps in workforce capacity, accessibility, and training were highlighted, particularly in aligning academic curricula with real-world public health needs.
The study revealed a disconnect between current public health programs and workforce preparedness, performance, and practice. Participants emphasized the need for comprehensive leadership development programs and integration of data science and leadership components into existing curricula.
This work provides a foundation for strengthening the public health workforce by identifying key concepts and gaps in data science and leadership. The findings have implications for policy development, resource allocation, and building a competent workforce capable of leveraging data for improved public health outcomes. This research contributes to advancing the field of public health by communicating scientific knowledge crucial for future breakthroughs in workforce development.

PMID:
40371273
Bibliographic data and abstract were imported from PubMed on 15 May 2025.

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