Effectiveness of technology-supported ultrasound training in prenatal diagnosis through an adaptive image recognition training system (AdaptUS)

Background Prenatal diagnostics, particularly ultrasound examinations, are vital for monitoring fetal development and detecting potential complications. Traditional ultrasound training often lacks adequate focus on image recognition and interpretation, which are crucial for accurate diagnostics. This study evaluates the effectiveness of the AdaptUS module, a technology-supported, adaptive learning platform designed to enhance ultrasound diagnostic skills in prenatal medicine. Methods A prospective cross-sectional study was conducted with 76 medical students from the German University Hospital, divided into an intervention group (n = 37) and a control group (n = 39). The intervention group engaged with the AdaptUS module, which adjusts its content based on individual performance. More precisely, it is a learning program for ultrasound images that, while not directly adaptive to the user’s skill level, can be considered adaptive in the sense that incorrectly answered images are presented again for re-interpretation. However, the images are currently shown at random and are not yet adjusted to the user’s abilities, ensuring that the challenge is consistent but not tailored to skill level. It is important to note that this is not an ultrasound image software, but rather an image interpretation software designed to help users improve their diagnostic skills through repeated exposure to medical images. In contrast, the control group did not receive this training. Both groups were assessed on their ultrasound diagnostic skills at the beginning and end of the semester using a series of 16 questions, which involved interpreting images correctly rather than a standard multiple-choice format. Statistical analysis was performed to compare the pre- and post-test results within and between the groups. Results The intervention group showed a significant improvement in their mean test scores, increasing from 70.9% to 86.0% (p < 0.001), while the control group’s scores decreased slightly from 62.0% to 59.0%, though this change was not statistically significant. The difference in score improvements between the intervention and control groups was statistically significant (p < 0.001). The feedback from students in the intervention group was overwhelmingly positive, highlighting the system’s flexibility in addressing individual learning needs and suggesting its potential for broader integration into medical curricula. Discussion The AdaptUS training module significantly enhances ultrasound diagnostic skills, particularly in prenatal medicine, by providing a personalized learning experience that addresses the gaps in traditional training methods. The success of AdaptUS underscores the importance of integrating adaptive learning technologies into medical education to bridge the gap between theoretical knowledge and practical application. Future research should explore the long-term impact of such training on clinical practice and consider incorporating advanced technologies like virtual reality to further enhance educational outcomes.

Schlagwörter

ultrasound training, adaptive learning, prenatal diagnosis, medical education, image recognition, gamification, cognitive bias

Fachgebiet (DDC)

150 - Psychologie

Projekt

Veranstaltung

Startdatum der Ausstellung

Enddatum der Ausstellung

Startdatum der Konferenz

Enddatum der Konferenz

Datum der letzten Prüfung

ISBN

ISSN

0016-5751
1438-8804

Sprache

Englisch

Während FHNW Zugehörigkeit erstellt

Ja

Zukunftsfelder FHNW

Publikationsstatus

Veröffentlicht

Begutachtung

Peer-Review der ganzen Publikation

Open Access-Status

Gold

Lizenz

Zitation

Sachs, T., Michel, S., Koziol, K., Kunz, A., Wittek, A., Neubauer, R., Klinkhammer, H., Weimer, J., Strizek, B., & Recker, F. (2025). Effectiveness of technology-supported ultrasound training in prenatal diagnosis through an adaptive image recognition training system (AdaptUS). Geburtshilfe Und Frauenheilkunde, 85(3), 323–332. https://doi.org/10.1055/a-2510-7185

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