GF Strong Rehabilitation Research Lab, Vancouver Coastal Research Institute, Vancouver, British Columbia; Department of Occupational Science and Occupational Therapy, The University of British Columbia, Vancouver, British Columbia.
GF Strong Rehabilitation Research Lab, Vancouver Coastal Research Institute, Vancouver, British Columbia; Department of Integrated Sciences, The University of British Columbia, Vancouver, British Columbia.
Arch Phys Med Rehabil. 2020 Jun;101(6):1025-1040. doi: 10.1016/j.apmr.2020.01.008. Epub 2020 Feb 12.
Assistive technologies (ATs) support independence and well-being in people with cognitive, perceptual, and physical limitations. Given the increasing availability and diversity of ATs, evaluating the usefulness of current and emerging ATs is crucial for informed comparison. We aimed to chart the landscape and development of AT evaluation tools (ETs; ATETs) across disparate fields in order to improve the process of AT evaluation and development.
We performed a scoping review of ATETs through database searching of MEDLINE, Embase, CINAHL, HaPI, PsycINFO, Cochrane Reviews, and Compendex as well as citation mining.
Articles explicitly referencing ATETs were retained for screening. We included ETs if they were designed to specifically evaluate ATs.
We extracted 5 attributes of ATETs: AT category, construct evaluated, conceptual frameworks, type of end user input used for ATET development, and presence of validity testing.
From screening 23,434 records, we included 159 ATETs. Specificity of tools ranged from single to general ATs across 40 AT categories. Satisfaction, functional performance, and usage were the most common constructs of 103 identified. We identified 34 conceptual frameworks across 53 ETs. Finally, 36% incorporated end user input and 80% showed validation testing.
We characterized a wide range of AT categories with diverse approaches to their evaluation based on varied conceptual frameworks. Combining these frameworks in future ATETs may provide more holistic views of AT usefulness. ATET selection may be improved with guidelines for conceptually reconciling results of disparate ATETs. Future ATET development may benefit from more integrated approaches to end user engagement.
辅助技术 (AT) 支持认知、感知和身体受限者的独立性和幸福感。鉴于 AT 的可用性和多样性不断增加，评估当前和新兴 AT 的有用性对于知情比较至关重要。我们旨在绘制不同领域的 AT 评估工具 (ET) 即 ATET 的全景图和发展情况，以改进 AT 评估和开发的过程。
我们通过对 MEDLINE、Embase、CINAHL、HaPI、PsycINFO、Cochrane Reviews 和 Compendex 数据库进行搜索以及引文挖掘，对 ATET 进行了范围性回顾。
保留明确引用 ATET 的文章进行筛选。如果 ET 旨在专门评估 AT，则将其包括在内。
我们提取了 ATET 的 5 个属性：AT 类别、评估的构建、概念框架、用于开发 ATET 的终端用户输入类型以及有效性测试的存在。
通过筛选 23,434 条记录，我们纳入了 159 种 ATET。工具的特异性从单一到一般 AT 不等，涵盖 40 个 AT 类别。满意度、功能表现和使用是 103 个已识别的最常见构建。我们在 53 个 ET 中识别了 34 个概念框架。最后，36%的工具纳入了终端用户输入，80%的工具进行了有效性测试。
我们根据不同的概念框架，对广泛的 AT 类别进行了描述，并采用了不同的方法对其进行评估。在未来的 ATET 中结合这些框架可能会提供对 AT 有用性的更全面的看法。通过为概念上协调不同 ATET 的结果提供指南，可能会改进 ATET 的选择。未来的 ATET 开发可能会受益于更集成的终端用户参与方法。
