Assessing Students’ Data Literacy Across Healthcare Disciplines: Development and Cross-Sectional Validation Study (Preprint)

<sec> <title>BACKGROUND</title> <p>Processes in healthcare are more and more AI- and therefore data-driven, requiring healthcare professionals to competently collect, manage, interpret and communicate health data. Despite this growing demand, validated instruments for assessing data literacy among healthcare students remain scarce.</p> </sec> <sec> <title>OBJECTIVE</title> <p>To develop and provide initial validation of a self-report questionnaire assessing data literacy proficiency levels among healthcare students by examining its ability to discriminate between study programs with diverse proficiency levels (known-groups validity).</p> </sec> <sec> <title>METHODS</title> <p>A cross-sectional online survey was conducted among healthcare students at a German University of Applied Sciences. The questionnaire was developed based on the data literacy framework by Ridsdale et al., measuring 22 data competencies across five knowledge areas using 72 items, supplemented by three items on prior data science knowledge and seven demographic items. Reporting followed the CHERRIES checklist for web-based surveys. Data was analyzed descriptively, as well as by conducting a Chi-square test and two MANCOVAs to evaluate differences in students’ data literacy across six healthcare-related study programs.</p> </sec> <sec> <title>RESULTS</title> <p>A total of N=192 healthcare students (excluding medicine) participated in the survey, n=155 fully completed questionnaires were included. All participants reported basic, above average data competencies on 4-point Likert scales (M=2.66, SD=.35). Notably, data literacy ratings differed significantly across study programs in accordance with their curricula (V=.277, F(25, 740)=1.736, p=.015, partial n²=.055 and V=1.117, F(110, 655)=1.713, p&lt;.001, partial n²=.223); students exposed to data-oriented course content rated their competencies significantly higher than others (e.g. Medical Informatics: M=2.87, SD=.24; Nursing: M=2.52, SD=.33). While these differences were most pronounced regarding advanced competencies, data ethics competencies were rated uniformly high across all participants (M=3.26, SD=.54).</p> </sec> <sec> <title>CONCLUSIONS</title> <p>The varying levels of self-reported data literacy demonstrate that the questionnaire successfully captured students’ self-reported data competencies. Notably, these competencies were more pronounced in the data- and science-oriented bachelor’s degree programs Medical Informatics and Health Care Management, and in the master’s degree program Health Care than in those with a therapeutic focus, the bachelor’s degree programs Nursing, Applied Therapy Sciences, and Applied Midwifery Science. The instrument may support the identification of educational needs and inform the development of discipline-specific data literacy curricula for future healthcare professionals.</p> </sec>