Background: The rapid growth of telemedicine offers convenience, flexibility, and accessibility for patients to have health care services worldwide. To succeed in telemedicine, health care practitioners and telemedicine tools must engage patients through effective communication. However, a research gap exists in understanding the communication strategies used in telemedicine and how they effectively engage patients. Objective: This study aims to identify communication strategies influencing patient engagement in telemedicine with provider-patient interactions, as well as how included studies evaluate patient engagement through a systematic review. Methods: We searched the literature comprehensively using 6 databases, Web of Science, PubMed, Scopus, MEDLINE, CINAHL, and Embase, from inception to October 2025. We included empirical, English-language studies that examined communication strategies affecting patient engagement in telemedicine with provider-patient interactions. Studies lacking actual patients or provider-patient interactions in telemedicine were excluded. We used content analysis to identify texts that were related to Theme 1: the communication strategies affecting patient engagement, and Theme 2: evaluation of patient engagement. Coded texts were analyzed to develop subthemes and themes of identified communication strategies. Methods for evaluating patient engagement were summarized. A narrative synthesis was conducted because of heterogeneity across study design and outcomes. We used the Mixed Methods Appraisal Tool to assess the quality of research included in this study. Results: This study systematically reviewed 34 peer-reviewed articles, revealing 3 overarching themes of effective communication strategies that enhance patient engagement: interpersonal communication strategies, with 6 subthemes (building relationships, supportive attitude, interactive dialogic loop, nonverbal communication, professionalism and accuracy, and tailored communication); team-level communication strategies, with 3 subthemes (training and preparation, teamwork and care coordination, and cultural and linguistic sensitivity); and system-level communication strategies, with 3 subthemes (usefulness of information, ease of use, and data privacy and security). We also found that included studies predominantly used qualitative research methods, such as semistructured interviews and focus groups, to collect patient engagement data. Conclusions: This review provides an innovative synthesis of communication strategies that promote patient engagement in telemedicine by integrating interpersonal (micro), team (meso), and system-level (macro) perspectives. Unlike previous reviews that focused on single aspects or levels of communication, this study offers a holistic framework that advances theoretical understanding of how multilevel communication strategies collectively shape patient engagement. Practically, the findings offer actionable guidance for health care professionals, telemedicine developers, and policymakers seeking to enhance the quality and sustainability of telemedicine services. In real-world settings, the identified strategies can inform professional training, platform design, and policy development to support patient-centered digital care. This review is the first to systematically bring together communication strategies for patient engagement in telemedicine across all 3 levels. Future research should build on this framework by developing and validating quantitative measures of patient engagement and examining the relationships between communication strategies and telemedicine outcomes.

Nature Medicine, Published online: 29 December 2025; doi:10.1038/s41591-025-04027-5

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arXiv:2511.11635v1 Announce Type: cross Abstract: High-quality personalized question banks are crucial for supporting adaptive learning and individualized assessment. Manually designing questions is time-consuming and often fails to meet diverse learning needs, making automated question generation a crucial approach to reduce teachers' workload and improve the scalability of educational resources. However, most existing question generation methods rely on single-agent or rule-based pipelines, which still produce questions with unstable quality, limited diversity, and insufficient alignment with educational goals. To address these challenges, we propose EduAgentQG, a multi-agent collaborative framework for generating high-quality and diverse personalized questions. The framework consists of five specialized agents and operates through an iterative feedback loop: the Planner generates structured design plans and multiple question directions to enhance diversity; the Writer produces candidate questions based on the plan and optimizes their quality and diversity using feedback from the Solver and Educator; the Solver and Educator perform binary scoring across multiple evaluation dimensions and feed the evaluation results back to the Writer; the Checker conducts final verification, including answer correctness and clarity, ensuring alignment with educational goals. Through this multi-agent collaboration and iterative feedback loop, EduAgentQG generates questions that are both high-quality and diverse, while maintaining consistency with educational objectives. Experiments on two mathematics question datasets demonstrate that EduAgentQG outperforms existing single-agent and multi-agent methods in terms of question diversity, goal consistency, and overall quality.