PDF(Pubmed)
Abstract：
BACKGROUND: Cross-neurotype differences in social communication patterns contribute to high unemployment rates among adults with autism. Adults with autism can be unsuccessful in job searches or terminated from employment due to mismatches between their social attention behaviors and society\'s expectations on workplace communication.
OBJECTIVE: We propose a behavioral intervention concerning distribution of attention in triadic (three-way) conversations. Specifically, the objective is to determine whether providing personalized feedback to each individual with autism based on an analysis of their attention distribution behavior during an initial conversation session would cause them to modify their orientation behavior in a subsequent conversation session.
METHODS: Our system uses an unobtrusive head orientation estimation model to track the focus of attention of each individual. Head orientation sequences from a conversation session are analyzed based on five statistical domains (eg, maximum exclusion duration and average contact duration) representing different types of attention distribution behavior. An intervention is provided to a participant if they exceeded the nonautistic average for that behavior by at least 2 SDs. The intervention uses data analysis and video modeling along with a constructive discussion about the targeted behaviors. Twenty-four individuals with autism with no intellectual disabilities participated in the study. The participants were divided into test and control groups of 12 participants each.
RESULTS: Based on their attention distribution behavior in the initial conversation session, 11 of the 12 participants in the test group received an intervention in at least one domain. Of the 11 participants who received the intervention, 10 showed improvement in at least one domain on which they received feedback. Independent t tests for larger test groups (df>15) confirmed that the group improvements are statistically significant compared with the corresponding controls (P<.05). Crawford-Howell t tests confirmed that 78% of the interventions resulted in significant improvements when compared individually against corresponding controls (P<.05). Additional t tests comparing the first conversation sessions of the test and control groups and comparing the first and second conversation sessions of the control group resulted in nonsignificant differences, pointing to the intervention being the main effect behind the behavioral changes displayed by the test group, as opposed to confounding effects or group differences.
CONCLUSIONS: Our proposed behavioral intervention offers a useful framework for practicing social attention behavior in multiparty conversations that are common in social and professional settings.
OBJECTIVE: We propose a behavioral intervention concerning distribution of attention in triadic (three-way) conversations. Specifically, the objective is to determine whether providing personalized feedback to each individual with autism based on an analysis of their attention distribution behavior during an initial conversation session would cause them to modify their orientation behavior in a subsequent conversation session.
METHODS: Our system uses an unobtrusive head orientation estimation model to track the focus of attention of each individual. Head orientation sequences from a conversation session are analyzed based on five statistical domains (eg, maximum exclusion duration and average contact duration) representing different types of attention distribution behavior. An intervention is provided to a participant if they exceeded the nonautistic average for that behavior by at least 2 SDs. The intervention uses data analysis and video modeling along with a constructive discussion about the targeted behaviors. Twenty-four individuals with autism with no intellectual disabilities participated in the study. The participants were divided into test and control groups of 12 participants each.
RESULTS: Based on their attention distribution behavior in the initial conversation session, 11 of the 12 participants in the test group received an intervention in at least one domain. Of the 11 participants who received the intervention, 10 showed improvement in at least one domain on which they received feedback. Independent t tests for larger test groups (df>15) confirmed that the group improvements are statistically significant compared with the corresponding controls (P<.05). Crawford-Howell t tests confirmed that 78% of the interventions resulted in significant improvements when compared individually against corresponding controls (P<.05). Additional t tests comparing the first conversation sessions of the test and control groups and comparing the first and second conversation sessions of the control group resulted in nonsignificant differences, pointing to the intervention being the main effect behind the behavioral changes displayed by the test group, as opposed to confounding effects or group differences.
CONCLUSIONS: Our proposed behavioral intervention offers a useful framework for practicing social attention behavior in multiparty conversations that are common in social and professional settings.
摘要：
背景：社会交往模式的跨神经类型差异导致自闭症成人的高失业率。由于社会关注行为与社会对工作场所交流的期望不匹配，自闭症成年人可能无法成功求职或终止工作。
目的：我们提出了一种行为干预措施，涉及三联（三方）对话中注意力的分布。具体来说,目的是确定在初始会话期间基于对自闭症患者注意力分布行为的分析为自闭症患者提供个性化反馈是否会导致他们在随后的会话中改变其定向行为.
方法：我们的系统使用不显眼的头部方向估计模型来跟踪每个个体的注意力焦点。基于五个统计领域分析对话会话中的头部方向序列(例如，最大排除持续时间和平均接触持续时间)代表不同类型的注意力分布行为。如果参与者的行为超过非自闭症平均水平至少2个SD，则会向参与者提供干预。干预使用数据分析和视频建模以及有关目标行为的建设性讨论。24名没有智力障碍的自闭症患者参加了这项研究。参与者被分为测试组和对照组，每组12名参与者。
结果：根据他们在初始会话中的注意力分布行为，测试组中的12名参与者中有11名接受了至少一个领域的干预。在接受干预的11名参与者中，图10示出了在其上接收到反馈的至少一个域中的改进。较大测试组（df>15）的独立t检验证实，与相应的对照组相比，该组的改善具有统计学意义（P<0.05）。Crawford-Howellt检验证实，与相应的对照组相比，78％的干预措施显着改善（P<0.05）。额外的t检验比较测试组和对照组的第一次对话会话和比较对照组的第一次和第二次对话会话导致无显着差异。指出干预是测试组表现出的行为变化背后的主要影响，与混杂效应或群体差异相反。
结论：我们提出的行为干预为在社会和职业环境中常见的多方对话中实践社会关注行为提供了一个有用的框架。
目的：我们提出了一种行为干预措施，涉及三联（三方）对话中注意力的分布。具体来说,目的是确定在初始会话期间基于对自闭症患者注意力分布行为的分析为自闭症患者提供个性化反馈是否会导致他们在随后的会话中改变其定向行为.
方法：我们的系统使用不显眼的头部方向估计模型来跟踪每个个体的注意力焦点。基于五个统计领域分析对话会话中的头部方向序列(例如，最大排除持续时间和平均接触持续时间)代表不同类型的注意力分布行为。如果参与者的行为超过非自闭症平均水平至少2个SD，则会向参与者提供干预。干预使用数据分析和视频建模以及有关目标行为的建设性讨论。24名没有智力障碍的自闭症患者参加了这项研究。参与者被分为测试组和对照组，每组12名参与者。
结果：根据他们在初始会话中的注意力分布行为，测试组中的12名参与者中有11名接受了至少一个领域的干预。在接受干预的11名参与者中，图10示出了在其上接收到反馈的至少一个域中的改进。较大测试组（df>15）的独立t检验证实，与相应的对照组相比，该组的改善具有统计学意义（P<0.05）。Crawford-Howellt检验证实，与相应的对照组相比，78％的干预措施显着改善（P<0.05）。额外的t检验比较测试组和对照组的第一次对话会话和比较对照组的第一次和第二次对话会话导致无显着差异。指出干预是测试组表现出的行为变化背后的主要影响，与混杂效应或群体差异相反。
结论：我们提出的行为干预为在社会和职业环境中常见的多方对话中实践社会关注行为提供了一个有用的框架。
