Establishing Intervention Priorities for Nonverbal Communication in Autistic Adults

尽管非语言交流困难（NVC）是任何年龄自闭症诊断的必要条件，但 目前有专门针对幼儿期以后这些技能的循证干预措施。因此，年龄较大的儿童 自闭症谱系的成年人仍然不支持一个具有广泛影响的核心挑战， 的影响。我们的长期目标是制定和实施有针对性的干预措施，以提高NVC的支出。 自闭症的成年人，但在知识上存在两个差距。首先，在开发新的NVC干预措施之前， 从自闭症成年人自身的角度评估前瞻性干预方案至关重要; 自闭症成年人想要摆脱干预仍是未知数。如果干预措施没有得到有效执行， 在制定这些政策时，没有征求社区的意见，而这些社区总有一天会从中受益。二是由于 自闭症固有的异质性，"一刀切"的干预不是一个现实的目标;相反，不同的轮廓， 能力和残疾可能映射到不同的干预优先事项，这可能有助于有针对性的，个别的， 虚拟化干预发展。这笔赠款将通过建立基础知识来解决这些差距 关于（1）自闭症成年人如何体验NVC，（2）他们想从干预中得到什么，以及（3） 个人差异反映在影响模式和干预优先次序上。我们将使用一个连续的 混合方法设计（定量→定性），与社区的自闭症成员协商， 地方协作，有两个具体目标：（1）发现与NVC影响相关的数据驱动的行为概况 和干预的愿望，这将告知如何最好地匹配个人的干预措施;（2）了解 自闭症成人对NVC体验和干预的定性观点。在目标1中， 自闭症成年人（n = 400）将完成关于他们的沟通技巧，NVC经验和愿望的调查， 干预机器学习回归和典型相关分析将对个体预测因子进行建模， NVC的影响和干预的愿望，并确定最具预测性的个体差异的组合 需要NVC干预的背景。在目标2中，我们将重新招募n = 40名调查参与者， 对他们的目标1回答进行后续半结构化访谈。采访将阐明的具体性质， 有问题的和成功的NVC互动;为什么需要和不需要干预的原因;以及首选- 干预目标和形式。我们将使用主题分析来分析访谈数据;调查结果将用于 制定社区起草的NVC干预发展指南。贡献将是巨大的- 因为它们将为投资资源以支持 成人自闭症社区。这项研究是创新的，因为它代表了一个实质性的背离， 从目标人群的意见、经验和观点入手，改变现状。知识 生成的将解析自闭症沟通技能的异质性，并有可能指导发展， 选择个性化的干预措施，以满足最大的需求领域，最大的成功机会。

Although difficulty with nonverbal communication (NVC) is required for a diagnosis of autism at any age, no evidence-based interventions exist specifically targeting these skills beyond toddlerhood. Thus, older children and adults on the autism spectrum remain unsupported for a core challenge with wide-reaching func- tional impacts. Our long-term goal is to develop and implement targeted interventions to improve NVC expe- riences for autistic adults, yet two gaps in knowledge exist. First, before developing novel NVC interventions, it is critical to evaluate prospective intervention options from the perspectives of autistic adults themselves; what autistic adults want out of intervention remains unknown. Significant resources could be wasted if interventions are developed without consulting the communities who will one day seek to benefit from them. Second, due to the heterogeneity inherent to autism, a “one size fits all” intervention is not a realistic goal; rather, distinct profiles of ability and disability are likely to map onto different intervention priorities, which could facilitate targeted, indi- vidualized intervention development. This grant will address these gaps by establishing foundational knowledge about (1) how autistic adults experience NVC, (2) what they want out of intervention, and (3) how patterns of individual difference map onto patterns of impact and intervention priority. We will use an explanatory-sequential mixed methods design (Quantitative → Qualitative), in consultation with autistic members of a community-aca- demic collaborative, with two specific aims: (1) Discover data-driven behavioral profiles relevant to NVC impact and desire for intervention that will inform how to best match individuals to interventions; and (2) Understand autistic adults’ perspectives on NVC experience and intervention qualitatively. In Aim 1, a diverse sample of autistic adults (n=400) will complete surveys about their communication skills, NVC experiences, and desire for intervention. Machine learning regression and canonical correlation analysis will model individual predictors of NVC impact and desire for intervention and identify combinations of individual differences most predictive of contexts for which NVC intervention is desired. In Aim 2 we will re-recruit n=40 survey participants to complete follow-up semi-structured interviews about their Aim 1 responses. Interviews will elucidate the specific nature of problematic and successful NVC interactions; reasons why intervention is and is not desired; and preferred in- tervention targets and formats. We will analyze interview data using thematic analysis; findings will be used to develop community-drafted guidelines for NVC intervention development. Contributions will be significant be- cause they will provide strong empirical and community-based justification for investing resources in support of the adult autistic community. This research is innovative because it represents a substantive departure from the status quo by starting with the opinions, experiences, and perspectives of the target population. Knowledge generated will parse the heterogeneity of communication skills in autism, and has the potential to guide devel- opment of individualized interventions to meet the greatest areas of need with the greatest chance of success.