Wolf Eduard, Morisse Karsten, Meister Sven
Health Informatics, Faculty of Health, School of Medicine, Witten/Herdecke University, Witten, Germany.
Healthcare Department, Fraunhofer Institute for Software and Systems Engineering, Speicherstraße 6, Dortmund, 44147, Germany, 49 231-97677 ext 450.
JMIR Hum Factors. 2025 Jul 16;12:e65029. doi: 10.2196/65029.
Performance-related musculoskeletal disorders are common among musicians, requiring precise diagnostic and therapeutic approaches. Physiotherapists face unique challenges due to the complex relationship between musculoskeletal health and the demands of musical performance. Traditional methods often lack the necessary precision for this specialized field. Integrating clinical movement analysis (CMA) with clinical decision support (CDS) could improve diagnostic accuracy and therapeutic outcomes by offering detailed biomechanical insights and facilitating data-driven decision-making.
This study aimed to identify design requirements for an interactive dashboard that aids clinical decision-making by incorporating CMA to assist physiotherapists in managing musculoskeletal disorders in musicians.
A qualitative user research study was conducted, using human factors engineering methods from problem-driven research, user-centered design, and decision-centered design. Data collection included a domain-specific literature review, workflow observations, and focus group discussions with domain experts, including 4 physiotherapist experts and an expert for clinical reasoning and applied biomechanics. This qualitative data was triangulated to characterize the domain, identify the CMA workflow, user needs, key cognitive tasks, and decision requirements. These insights were translated into concrete design requirements.
A workflow for integrating musician-specific CMA into physiotherapy was established. In total, 21 user requirements, 7 key cognitive tasks, and 5 key decision requirements were defined, along with 49 design seeds. Key features identified include (1) efficient integration of musician-specific biomechanical findings into therapy, (2) combining heterogeneous data types for holistic assessment, (3) providing an adaptive overview of patient-related information, (4) using adequate visual representations and interaction techniques, (5) facilitating efficient visual-interactive analysis of findings and treatment results, and (6) enabling preparation and export of therapy findings and analysis results. Additionally, 14 CDS recommendations and 11 technical prerequisites were identified. These requirements guide the design of an interactive tool featuring advanced visualization, interactive data exploration capabilities, and contextual integration of clinical and biomechanical data.
An interactive physiotherapy dashboard with CDS incorporating CMA data holds significant potential to enhance decision-making in physiotherapy for musicians with performance-related musculoskeletal disorders. By addressing cognitive demands and integrating advanced visualization techniques, the tool can support physiotherapists in making more accurate assessments, potentially improving patient outcomes, reducing injury recurrence, and supporting musicians' career longevity. Ongoing research is essential to refine such a tool and validate its usability, decision support, and clinical effectiveness. Future work should explore advanced analytics, adapt to various CMA systems, and expand applications across musicians and therapeutic domains to enhance its impact.
与演奏相关的肌肉骨骼疾病在音乐家群体中很常见，需要精确的诊断和治疗方法。由于肌肉骨骼健康与音乐演奏要求之间的复杂关系，物理治疗师面临着独特的挑战。传统方法往往缺乏针对这一专业领域所需的精确性。将临床运动分析（CMA）与临床决策支持（CDS）相结合，可以通过提供详细的生物力学见解并促进数据驱动的决策制定，提高诊断准确性和治疗效果。
本研究旨在确定一个交互式仪表板的设计要求，该仪表板通过纳入CMA来辅助临床决策，以帮助物理治疗师管理音乐家的肌肉骨骼疾病。
进行了一项定性用户研究，采用了问题驱动研究、以用户为中心的设计和以决策为中心的设计中的人因工程方法。数据收集包括特定领域的文献综述、工作流程观察以及与领域专家的焦点小组讨论，其中包括4名物理治疗师专家以及一名临床推理和应用生物力学专家。对这些定性数据进行三角测量，以描述该领域的特征，确定CMA工作流程、用户需求、关键认知任务和决策要求。这些见解被转化为具体的设计要求。
建立了将针对音乐家的CMA整合到物理治疗中的工作流程。总共定义了21项用户需求、7项关键认知任务和5项关键决策要求，以及49个设计要点。确定的关键特性包括：（1）将针对音乐家的生物力学研究结果有效整合到治疗中；（2）结合不同的数据类型进行全面评估；（3）提供与患者相关信息的自适应概述；（4）使用适当的视觉表示和交互技术；（5）促进对研究结果和治疗效果进行高效的视觉交互分析；（6）能够准备和导出治疗结果及分析结果。此外，还确定了14项CDS建议和11项技术前提条件。这些要求指导了一个交互式工具的设计，该工具具有先进的可视化、交互式数据探索功能以及临床和生物力学数据的上下文整合。
一个结合了CMA数据的带有CDS的交互式物理治疗仪表板，在增强对患有与演奏相关肌肉骨骼疾病的音乐家的物理治疗决策方面具有巨大潜力。通过满足认知需求并整合先进的可视化技术，该工具可以支持物理治疗师进行更准确的评估，有可能改善患者治疗效果、减少损伤复发并支持音乐家的职业寿命。持续的研究对于完善这样一个工具并验证其可用性、决策支持和临床有效性至关重要。未来的工作应探索先进的分析方法，适应各种CMA系统，并扩展在音乐家和治疗领域的应用，以增强其影响力。
