Table 1_Bridging the gap: enhancing data science and leadership knowledge and skills in the context of the public health workforce.docx

IntroductionThis 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.
MethodsQuantitative 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.
ResultsThe 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.
AnalysisThe 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.
DiscussionThis 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.

引言
本研究针对公共卫生人才培养领域的关键空白展开探索，聚焦公共卫生实践中数据可及性与复杂性持续提升的背景下，数据科学与领导力技能的培养需求。
研究方法
本研究采用定量与定性相结合的研究方法，包括与多元化公共卫生从业者开展的倾听座谈会。研究完成了人员招募与会后调研工作，并基于PPP框架（PPP Framework），采用现象学编码与分类编码方法对座谈会转录文本进行分析。
研究结果
本研究明确了公共卫生数据科学与领导力领域的三大核心概念：数据科学（data science）、数据素养（data literacy）与数据知情领导力（data-informed leadership），并为各概念制定了清晰的定义。研究同时凸显了公共卫生人才队伍在能力储备、资源可及性与培训体系方面存在的显著缺口，尤其体现在学术课程设置与真实公共卫生实践需求的匹配度不足层面。
分析
本研究揭示了当前公共卫生人才培养项目与从业者能力储备、履职表现及实际工作实践之间存在脱节现象。参与座谈的人员强调，亟需构建全面的领导力培养体系，并将数据科学与领导力相关内容融入现有课程框架。
讨论
本研究通过明确数据科学与领导力领域的核心概念与现存缺口，为强化公共卫生人才队伍建设奠定了重要基础。研究发现对政策制定、资源配置以及打造一支能够依托数据优化公共卫生成效的高素质人才队伍具有关键指导意义。本研究通过传递对未来公共卫生人才培养突破至关重要的科学知识，推动了公共卫生领域的发展与进步。