Division of Cardiology and Cardiovascular Medicine, Department of Heart, Vascular, and Thoracic, Children's Institute, Cleveland Clinic Children's, Cleveland, OH, United States.
Cleveland Clinic Children's Center for Artificial Intelligence, Department of Heart, Vascular, and Thoracic, Children's Institute, Cleveland Clinic Children's, Cleveland, OH, United States.
J Med Internet Res. 2024 Nov 15;26:e57628. doi: 10.2196/57628.
Increasing adoption of sensor-based digital health technologies (sDHTs) in recent years has cast light on the many challenges in implementing these tools into clinical trials and patient care at scale across diverse patient populations; however, the methodological approaches taken toward sDHT usability evaluation have varied markedly.
This review aims to explore the current landscape of studies reporting data related to sDHT human factors, human-centered design, and usability, to inform our concurrent work on developing an evaluation framework for sDHT usability.
We conducted a scoping review of studies published between 2013 and 2023 and indexed in PubMed, in which data related to sDHT human factors, human-centered design, and usability were reported. Following a systematic screening process, we extracted the study design, participant sample, the sDHT or sDHTs used, the methods of data capture, and the types of usability-related data captured.
Our literature search returned 442 papers, of which 85 papers were found to be eligible and 83 papers were available for data extraction and not under embargo. In total, 164 sDHTs were evaluated; 141 (86%) sDHTs were wearable tools while the remaining 23 (14%) sDHTs were ambient tools. The majority of studies (55/83, 66%) reported summative evaluations of final-design sDHTs. Almost all studies (82/83, 99%) captured data from targeted end users, but only 18 (22%) out of 83 studies captured data from additional users such as care partners or clinicians. User satisfaction and ease of use were evaluated for 83% (136/164) and 91% (150/164) of sDHTs, respectively; however, learnability, efficiency, and memorability were reported for only 11 (7%), 4 (2%), and 2 (1%) out of 164 sDHTs, respectively. A total of 14 (9%) out of 164 sDHTs were evaluated according to the extent to which users were able to understand the clinical data or other information presented to them (understandability) or the actions or tasks they should complete in response (actionability). Notable gaps in reporting included the absence of a sample size rationale (reported for 21/83, 25% of all studies and 17/55, 31% of summative studies) and incomplete sociodemographic descriptive data (complete age, sex/gender, and race/ethnicity reported for 14/83, 17% of studies).
Based on our findings, we suggest four actionable recommendations for future studies that will help to advance the implementation of sDHTs: (1) consider an in-depth assessment of technology usability beyond user satisfaction and ease of use, (2) expand recruitment to include important user groups such as clinicians and care partners, (3) report the rationale for key study design considerations including the sample size, and (4) provide rich descriptive statistics regarding the study sample to allow a complete understanding of generalizability to other patient populations and contexts of use.
近年来，基于传感器的数字健康技术（sDHT）的采用率不断提高，这使得人们更加关注如何在不同的患者群体中大规模地将这些工具应用于临床试验和患者护理中所面临的诸多挑战；然而，在评估 sDHT 可用性的方法学方面，差异很大。
本综述旨在探讨目前报告与 sDHT 人为因素、以人为中心的设计和可用性相关数据的研究现状，为我们正在开发的 sDHT 可用性评估框架提供信息。
我们对 2013 年至 2023 年期间发表并在 PubMed 中索引的研究进行了范围界定综述，其中报告了与 sDHT 人为因素、以人为中心的设计和可用性相关的数据。在进行了系统的筛选过程后，我们提取了研究设计、参与者样本、使用的 sDHT 或 sDHT 类型、数据采集方法以及捕获的可用性相关数据类型。
我们的文献检索共返回 442 篇论文，其中 85 篇论文符合入选标准，83 篇论文可用于数据提取且不受限制。共有 164 种 sDHT 进行了评估；141 种（86%）sDHT 为可穿戴工具，其余 23 种（14%）sDHT 为环境工具。大多数研究（55/83，66%）报告了最终设计 sDHT 的总结性评估。几乎所有研究（82/83，99%）都从目标最终用户那里获取了数据，但只有 18 项研究（83 项研究中的 18 项，22%）从其他用户（如护理伙伴或临床医生）那里获取了数据。分别有 83%（136/164）和 91%（150/164）的 sDHT 评估了用户满意度和易用性；然而，仅分别有 11%（150/164）、4%（66/164）和 2%（33/164）的 sDHT 报告了可学习性、效率和可记性。共有 14 种（9%）sDHT（164 种中的 14 种）根据用户理解呈现给他们的临床数据或其他信息的程度（可理解性）或他们应完成的操作或任务（可操作性）进行了评估。报告中存在明显的差距，包括缺乏样本量的基本原理（25%的研究和 31%的总结性研究报告了 21/83 项）以及不完整的社会人口统计学描述性数据（完整的年龄、性别/性别和种族/民族报告了 14/83 项，占研究的 17%）。
根据我们的发现，我们为未来的研究提出了四项可操作的建议，这将有助于推进 sDHT 的实施：（1）考虑对技术可用性进行深入评估，而不仅仅是用户满意度和易用性；（2）扩大招募范围，纳入重要的用户群体，如临床医生和护理伙伴；（3）报告关键研究设计考虑因素的基本原理，包括样本量；（4）提供关于研究样本的丰富描述性统计信息，以全面了解在其他患者群体和使用环境中的推广性。
