ArticleBMC medical education2025
Enhancing professional communication training in higher education through artificial intelligence(AI)-integrated exercises: study protocol for a randomised controlled trial.
Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Disclosure is not documentation: an open science framework for documenting generative AI use in scholarly research and publication workflows.Research integrity and peer review · 2026Article
- The Presence and Nature of AI-Use Disclosure Statements in Medical Education Journals: A Bibliometric Study.Perspectives on medical education · 2026Article
- Development of a Clinical Clerkship Mentor Using Generative AI and Evaluation of Its Effectiveness in a Medical Student Trial Compared to Student Mentors: 2-Part Comparative Study.JMIR medical education · 2025Article
- Validating GenAI feedback in suicide prevention training: a mixed-methods study of QPR skill assessment.Frontiers in medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundEffective communication skills are fundamental for health care professionals, yet conventional training methods face challenges in scalability and accessibility due to resource constraints. The emergence of artificial intelligence (AI), particularly generative AI, offers innovative ways for enhancing communication skills training by simulating realistic conversational scenarios and providing personalised, adaptive feedback. This manuscript is presented as study protocol for a cluster-randomised controlled trial that aims at evaluating the efficacy of an AI-supported higher education training protocol incorporating generative AI exercises to enhance communication competencies among psychology students.
methodsIn this cluster-randomised controlled trial, psychology students enrolled in communication skill seminars at a medium sized university in a medium sized German city will participate. Classes will be assigned within a parallel group design to the AI condition (AI-enhanced exercises alongside teaching-as-usual, TAU, that includes classical exercises) or the control condition (TAU only). Additional non-randomised comparison classes will comprise students with TAU only, but not be part of main analyses. The primary outcome is the change in communication skills from baseline, assessed through questions reflecting the communication techniques emphasised in the training. Secondary outcomes include communication skills, self-efficacy and self-concept, motivation, attitudes toward AI, user experience with the AI tool, student evaluations of course quality, and feasibility aspects such as uptake and usability. Data will be collected via online surveys and the university's teaching platform. Statistical analyses will employ mixed models to evaluate the intervention's impact. DISCUSSION: This study will provide empirical evidence on the effectiveness and feasibility of integrating AI into higher education communication skills training. Successful integration of AI-enhanced training could revolutionise educational practices by offering scalable, accessible, and personalised learning experiences. The findings may have broader implications for incorporating AI tools in various educational and professional training contexts, while addressing ethical considerations and promoting responsible use of AI in education.
trial registrationThis trial has been pre-registered on the Open Science Framework (OSF) under identifier 'th6f4'.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.