自闭症和非自闭症青少年远程麦克风系统:对视听任务参与度的影响

IF 2.6 2区 医学 Q1 AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY Ear and Hearing Pub Date : 2024-09-23 DOI:10.1097/AUD.0000000000001581
Kacie Dunham-Carr, Nisha Mailapur, Bahar Keçeli-Kaysili, Jacob I Feldman, Emily Thompson, Hilary Davis, Anne Marie Tharpe, Erin Picou, Tiffany G Woynaroski
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引用次数: 0

摘要

研究目的最近的一项研究为使用远程麦克风(RM)系统提高自闭症青少年的噪声监听能力提供了经验支持。有人提出,RM 系统的效果可能是通过提高这类人群的参与度来实现的。本研究使用行为编码来测试自闭症和非自闭症青少年在生态有效的嘈杂环境中聆听的效果:我们借鉴了最近一项实验研究中的现有数据,在这项研究中,56 名青少年(32 名自闭症患者,24 名非自闭症患者)完成了噪音环境下的听力任务,他们报告了自己在使用或不使用 RM 系统的情况下对视听音节、单词、句子和段落的感知情况;参与者之间的条件是平衡的。正如之前所报道的,感知准确性随刺激复杂程度的变化而变化,使用 RM 系统后总体上有所提高,但各组之间的提高幅度并无显著差异。参与者在两种条件下完成 "噪声中聆听 "任务的视频录像均由天真编码员通过 5 秒钟、部分时间间隔编码系统进行编码,包括:(a) 参与任务(以参与者在任务中表现出行为的时间间隔比例为指标);(b) 在任务中对特定刺激的口头抗议(以参与者在任务中表现出针对特定刺激的口头抗议行为的时间间隔比例为指标)。任务中行为的例子包括关注屏幕和完成任务活动。抗议行为的例子包括抱怨刺激音量过大或听不见。通过心理物理任务、触觉反应能力和非语言智商,对参与者的实际年龄、自闭症特征、语言能力、视听言语整合能力进行了评估,以预测和/或调节对相关行为的影响:总体而言,参与者高度投入任务,很少出现抗议现象,分别反映了超过 90% 和少于 0.5% 的编码间隔。我们没有发现小组或 RM 系统的使用对任务参与度有任何统计学上的显著影响。非自闭症青少年参与 "噪声中倾听 "任务的平均时间间隔为 97.45%,而自闭症青少年参与 "噪声中倾听 "任务的平均时间间隔为 94.25%。相比之下,在 "噪声中倾听 "任务中,"RM"(0.04% 的时间间隔)与 "无 RM"(0.2% 的时间间隔)条件下,针对特定刺激的口头抗议平均明显减少。在这一行为编码结果中,没有与组别相关的影响。此外,特定的参与者特征也会影响不同参与者在不同条件下的参与度。在不使用 RM 系统时,语言能力和非语言智商越高,参与度越高。使用 RM 系统时,自闭症特征的增加和视听言语时间结合窗口的扩大预示着参与度的降低,而视听整合程度的提高预示着使用 RM 系统时参与度的增加:本研究的结果表明,使用 RM 系统可减少针对特定刺激的言语抗议,这可能反映了在噪音中聆听时的参与困难。本研究扩展了我们之前的研究,为自闭症和非自闭症青少年使用 RM 系统提供了更多的实证支持。
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Remote Microphone Systems for Autistic and Nonautistic Youth: Effects on Audiovisual Task Engagement.

Objectives: A recent study has provided empirical support for the use of remote microphone (RM) systems to improve listening-in-noise performance of autistic youth. It has been proposed that RM system effects might be achieved by boosting engagement in this population. The present study used behavioral coding to test this hypothesis in autistic and nonautistic youth listening in an ecologically valid, noisy environment.

Design: We drew on extant data from a recent experimental study in which 56 youth (32 autistic, 24 nonautistic) matched at the group level on age and biological sex completed listening-in-noise tasks wherein they reported their perception of audiovisual syllables, words, sentences, and passages with and without an RM system; conditions were counter-balanced across participants. As previously reported, perceptual accuracy varied with stimulus complexity and overall improved with the RM system, with improvements not significantly different between groups. Video recordings of participants completing listening-in-noise tasks in both conditions were coded via a 5-second, partial-interval coding system by naive coders for (a) engagement in the task (indexed via proportion of intervals in which participants displayed on-task behaviors) and (b) verbal, stimulus-specific protesting in the task (indexed via proportion of intervals in which participants displayed verbal, stimulus-specific protesting behaviors). Examples of on-task behaviors included attending to the screen and completing task activities. Examples of protesting behaviors included complaining about stimuli volume or the inability to hear. Chronological age, autism features, language ability, audiovisual speech integration as measured by psychophysical tasks, tactile responsiveness, and nonverbal intelligence quotient were evaluated as putative predictors and/or moderators of effects on behaviors of interest.

Results: In general, participants were highly engaged in the task, and there were few protests, reflecting more than 90% and fewer than 0.5% of coded intervals, respectively. We did not detect any statistically significant effects of group or RM system use on task engagement. Nonautistic youth were engaged in the listening-in-noise task for an average of 97.45% of intervals, whereas autistic youth were engaged in the listening-in-noise task for an average of 94.25% of intervals. In contrast, verbal, stimulus-specific protesting in the listening-in-noise task was significantly reduced, on average, in the RM (0.04% of intervals) versus the No RM (0.2% of intervals) conditions. There were no effects related to group for this behaviorally coded outcome. In addition, select participant characteristics predicted engagement within conditions across participants. Greater language ability and nonverbal intelligence quotient predicted increased engagement when not using an RM system. Increased features of autism and wider temporal binding windows for audiovisual speech predicted reduced engagement while using an RM system, and greater audiovisual integration predicted increased engagement while using an RM system.

Conclusions: The results of this study suggest that RM system use reduces verbal, stimulus-specific protesting, which likely reflects difficulty engaging when listening in noise. The present study extends our previous study to provide additional empirical support for RM system use in autistic and nonautistic youth.

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来源期刊
Ear and Hearing
Ear and Hearing 医学-耳鼻喉科学
CiteScore
5.90
自引率
10.80%
发文量
207
审稿时长
6-12 weeks
期刊介绍: From the basic science of hearing and balance disorders to auditory electrophysiology to amplification and the psychological factors of hearing loss, Ear and Hearing covers all aspects of auditory and vestibular disorders. This multidisciplinary journal consolidates the various factors that contribute to identification, remediation, and audiologic and vestibular rehabilitation. It is the one journal that serves the diverse interest of all members of this professional community -- otologists, audiologists, educators, and to those involved in the design, manufacture, and distribution of amplification systems. The original articles published in the journal focus on assessment, diagnosis, and management of auditory and vestibular disorders.
期刊最新文献
Associations Between Vestibular Perception and Cognitive Performance in Healthy Adults. Sounds of Nature and Hearing Loss: A Call to Action. Breathy Vocal Quality, Background Noise, and Hearing Loss: How Do These Adverse Conditions Affect Speech Perception by Older Adults? Effects of Tympanic Membrane Electrodes on Sound Transmission From the Ear Canal to the Middle and Inner Ears. The Optimal Speech-to-Background Ratio for Balancing Speech Recognition With Environmental Sound Recognition.
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