A Novel System for Supporting Autism Diagnosis Using Home Videos: Iterative Development and Evaluation of System Design.
A Novel System for Supporting Autism Diagnosis Using Home Videos: Iterative Development and Evaluation of System Design.
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DOI：
10.2196/mhealth.4393
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发表时间：
2015-06-17
影响因子：
5
通讯作者：
Arriaga RI
中科院分区：
文献类型：
--
作者：
Nazneen N;Rozga A;Smith CJ;Oberleitner R;Abowd GD;Arriaga RI
观察自然环境中的行为对于获得对儿童行为的准确和全面的评估很有价值，但实际上仅限于临床观察。研究表明，从父母第一次开始担心到孩子最终被诊断出患有自闭症之间存在着显着的时间间隔。这种滞后可能会延迟已被证明可以改善发育结果的早期干预措施。开发和评估异步系统的设计，该系统允许父母轻松收集有关孩子行为的临床有效的家庭视频，并支持诊断医生完成自闭症的诊断评估。首先，对 11 名临床医生和 6 个家庭进行了访谈，以征求利益相关者对系统概念的反馈。接下来，根据家庭在受控的类似家庭的实验环境中使用该系统的经验以及涉及领域专家的参与式设计过程，对该系统进行了迭代设计。最后，系统设计的现场评估由 5 个儿童家庭（4 个曾被诊断为自闭症，1 个儿童处于正常发育状态）和 3 名诊断医生进行。每个家庭都有 2 名诊断医生，在不知道孩子之前的诊断状态的情况下，通过我们的系统独立完成了自闭症诊断。我们比较了两位诊断医生之间的评估结果以及每位诊断医生与孩子之前的诊断状态之间的评估结果。通过迭代设计过程产生的系统包括（1）NODA smartCapture，一款基于手机的应用程序，供家长在家中记录规定的视频证据； (2) NODA Connect，一个门户网站，供诊断医生指导家庭视频收集、访问发育历史，并通过将视频中标记的行为证据与《精神疾病诊断和统计手册》标准联系起来进行评估。诊断医生根据临床判断得出诊断结果。在现场评估过程中，无需事先培训，家长就可以轻松地（5分制中的平均评分为4分）使用该系统记录视频证据。在现场评估期间记录的所有家庭视频证据中，96% (26/27) 被认为对于执行自闭症诊断具有临床有用性。对于 4 名儿童（3 名患有自闭症，1 名正常发育），两位诊断医生独立得出了正确的诊断状态（自闭症与典型）。总体而言，在通过 NODA Connect 进行的 91% 的评估 (10/11) 中，诊断医生自信地（5 分制平均评分为 4.5）得出了与孩子之前的诊断状态相匹配的诊断结果。现场评估表明，该系统的设计使父母能够轻松记录孩子行为的临床有效证据，并使诊断医生能够完成诊断评估。这些结果揭示了适当设计的远程医疗技术的潜力，以支持使用家庭捕获的家庭视频进行临床评估。这种评估模型可以很容易地推广到直接观察行为在评估过程中发挥核心作用的其他条件。
Observing behavior in the natural environment is valuable to obtain an accurate and comprehensive assessment of a child’s behavior, but in practice it is limited to in-clinic observation. Research shows significant time lag between when parents first become concerned and when the child is finally diagnosed with autism. This lag can delay early interventions that have been shown to improve developmental outcomes. To develop and evaluate the design of an asynchronous system that allows parents to easily collect clinically valid in-home videos of their child’s behavior and supports diagnosticians in completing diagnostic assessment of autism. First, interviews were conducted with 11 clinicians and 6 families to solicit feedback from stakeholders about the system concept. Next, the system was iteratively designed, informed by experiences of families using it in a controlled home-like experimental setting and a participatory design process involving domain experts. Finally, in-field evaluation of the system design was conducted with 5 families of children (4 with previous autism diagnosis and 1 child typically developing) and 3 diagnosticians. For each family, 2 diagnosticians, blind to the child’s previous diagnostic status, independently completed an autism diagnosis via our system. We compared the outcome of the assessment between the 2 diagnosticians, and between each diagnostician and the child’s previous diagnostic status. The system that resulted through the iterative design process includes (1) NODA smartCapture, a mobile phone-based application for parents to record prescribed video evidence at home; and (2) NODA Connect, a Web portal for diagnosticians to direct in-home video collection, access developmental history, and conduct an assessment by linking evidence of behaviors tagged in the videos to the Diagnostic and Statistical Manual of Mental Disorders criteria. Applying clinical judgment, the diagnostician concludes a diagnostic outcome. During field evaluation, without prior training, parents easily (average rating of 4 on a 5-point scale) used the system to record video evidence. Across all in-home video evidence recorded during field evaluation, 96% (26/27) were judged as clinically useful, for performing an autism diagnosis. For 4 children (3 with autism and 1 typically developing), both diagnosticians independently arrived at the correct diagnostic status (autism versus typical). Overall, in 91% of assessments (10/11) via NODA Connect, diagnosticians confidently (average rating 4.5 on a 5-point scale) concluded a diagnostic outcome that matched with the child’s previous diagnostic status. The in-field evaluation demonstrated that the system’s design enabled parents to easily record clinically valid evidence of their child’s behavior, and diagnosticians to complete a diagnostic assessment. These results shed light on the potential for appropriately designed telehealth technology to support clinical assessments using in-home video captured by families. This assessment model can be readily generalized to other conditions where direct observation of behavior plays a central role in the assessment process.