Modulating stimulus intensity to improve clinical outcomes in aphasia treatment

摘要 确定最佳处理强度对于设计和实施任何 失语症的治疗方案。然而，治疗强度是一个复杂的结构和关于变量的信息 对其进行调整仍然是模棱两可和有限的。神经科学和临床文献中报道的研究 支持强化治疗的需要，以诱导长期的神经可塑性变化，而认知 心理学文献表明，通过分布式时间表来维持学习效果最好。一些研究表明 查看了单字命名任务的剂量参数，但关于剂量的证据有限 侧重于训练较大单位的产出的治疗参数，如句子或甚至 相互关联的话语。一种临床上经常使用并有证据证明其有效性的方法是SCRIPT 训练。关于剧本训练的最佳剂量(即重复次数)，目前知之甚少 随着脚本中每句话的时间推移)，这是促进最佳结果所需的。 在这项建议中，我们对调制刺激变量的影响进行了双因素随机对照试验，特别是 刺激练习分配和刺激重复。我们使用了一种具有实验性的基线脚本处理 对其有效性的支持，并允许操纵这些变量。确保独立性 和保真度，治疗是在受控的计算机环境(台式机和平板电脑)中提供的。为了避免临床医生- 可能影响治疗的相关变量，如专业知识和个性因素，判刑 在治疗期间由具有高视觉语音清晰度和情感的拟人化代理建模 表情。 关于“最佳结果”，推广是任何治疗方法的最终目标。因此， 主要结果是对谈话的概括衡量。次要措施解决短期问题 采购、长期维护和响应概括，以评估超过基线的收益， 不同的影响和相互作用。移动连接的无线可穿戴喉部传感器允许跟踪 在家里和社区交谈的时间作为治疗有效性和转院的衡量标准。为了隐私，它 不录制音频。 学习的结果和计算模型(泛化、短期习得和长期习得 维护)将提供新的证据，以填补当前科学理解中关于 失语症治疗方法的有效性及临床应用。更广泛地说，研究结果将有助于 告知神经沟通障碍的临床实践和治疗；虚拟临床医生指导 该提案开发的干预措施有可能减少昂贵的临床医生与患者之间的时间 是长期康复所必需的。 。

Abstract Determining the optimal intensity of treatment is essential to the design and implementation of any treatment program for aphasia. Yet, treatment intensity is a complex construct and information on the variables modulating it remain ambiguous and limited. Studies reported in the neuroscience and clinical literature support the need for intensive treatment to induce long-term neuroplastic changes while the cognitive psychology literature suggests that learning is best maintained with distributed schedules. A few studies have looked at dose parameters for single word naming tasks, but there is limited evidence regarding dose parameters for treatments that focus on training the production of larger units, such as sentences or even connected discourse. One approach that is frequently used clinically and has evidence for its efficacy is script training. Little is currently known regarding the optimum dose of script training (i.e., the number of repetitions over time of each sentence within the script) that is required to promote the best outcomes. In this proposal we conduct a two-factor RCT on the effects of modulating stimulus variables, specifically stimulus practice distribution and stimulus repetition. We use a baseline script treatment that has experimental support regarding its efficacy, and that allows the manipulation of these variables. To ensure independence and fidelity, treatment is provided in a controlled computer environment (desktop and tablet). To avoid clinician- related variables such as expertise and personality factors that may influence treatment, sentences are modeled during treatment by an anthropomorphic agent with high visual speech intelligibility and affective expressions. With regard to “best outcomes”, generalization is the ultimate goal of any treatment approach. Therefore, the primary outcome is a generalization measure of conversation. Secondary measures address short-term acquisition, longer-term maintenance, and response generalization for assessing gain over baseline, differential effects, and interactions. A mobile-connected wireless wearable laryngeal sensor allows tracking of talk time at home and in the community as a measure of treatment effectiveness and transfer. For privacy, it does not record audio. Results and computational models of learning (generalization, short-term acquisition, and longer-term maintenance) will contribute new evidence to fill critical gaps in current scientific understanding regarding the effectiveness and clinical application of aphasia treatment approaches. More generally, findings will help to inform clinical practice and treatment of neurologic communication disorders; the virtual clinician guided intervention that the proposal develops has the potential to reduce costly clinician-client time otherwise required for long-term rehabilitation. .