Using a standardized sound set to help characterize misophonia: The international affective digitized sounds

Misophonia is a condition characterized by negative affect, intolerance, and functional impairment in response to particular repetitive sounds usually made by others (e.g., chewing, sniffing, pen tapping) and associated stimuli. To date, researchers have largely studied misophonia using self-report measures. As the field is quickly expanding, assessment approaches need to advance to include more objective measures capable of differentiating those with and without misophonia. Although several studies have used sounds as experimental stimuli, few have used standardized stimuli sets with demonstrated reliability or validity. To conduct rigorous research to better understand misophonia, it is important to have an easily accessible, standardized set of acoustic stimuli for use across studies. Accordingly, in the present study, the International Affective Digitized Sounds (IADS-2), developed by Bradley and Lang [1], were used to determine whether participants with misophonia responded to cert..., Group differences in sound ratings were examined using a two-way, mixed analysis of covariance (2 groups x 3 sound types, where “group” corresponds to participants with misophonia or controls, and “sound type” refers to positive, negative, or neutral sounds) on four dependent variables (ratings of valence, arousal, similarity, and avoidance). When statistically significant interactions were observed for sound type, pairwise comparisons were used to determine group differences on each dependent variable, as well as mean differences between sound type on each dependent variable. All analyses were conducted using IBM SPSS27 statistical software. The first step in the data analytic plan included cleaning and screening the dataset by (a) inspecting all variables for data entry errors (none were observed), and (b) examining the normality of distributions across study variables. Next, bivariate correlations were explored to examine the relationships among variables and determine whether it wou..., , # Using a standardized sound set to help characterize misophonia: The international affective digitized sounds [https://doi.org/10.5061/dryad.kh18932fd](https://doi.org/10.5061/dryad.kh18932fd) ## Description of the data and file structure MQincluded is the group variable. MQincluded=1 describes all participants who meet misophonia criteria and were included in the dataset. MQincluded=0 describes healthy controls. All variable names for the measures have descriptors in the \"label\" column of SPSS. Average ratings for the dependent variables are found at the end of the variable view in SPSS, as well as PANAS positive and negative scores and the AIM total score. ## Sharing/Access information Data was derived from the following sources: * Amazon Mechanical Turk ## Code/Software SPSS syntax is included with the data upload.Â恐音症（Misophonia）是一种以针对他人通常发出的特定重复性声音（如咀嚼、嗅探、敲击钢笔等）及相关刺激产生负面情绪、耐受度下降与功能受损为特征的病症。迄今为止，研究者主要通过自我报告量表对恐音症开展研究。随着该领域的快速拓展，评估方法亟需升级，纳入更多能够区分恐音症患者与健康人群的客观测评手段。尽管已有多项研究使用声音作为实验刺激，但极少有研究采用经信效度验证的标准化刺激集。若要开展严谨的研究以更好地理解恐音症，构建一套易于获取、可跨研究使用的标准化声学刺激集至关重要。据此，本研究采用由Bradley与Lang[1]开发的国际情感数字化声音库（International Affective Digitized Sounds, IADS-2），旨在探究恐音症参与者对特定声音的反应……。本研究通过双因素混合协方差分析（2组×3声音类型，其中“组”对应恐音症参与者与健康对照组，“声音类型”指代正性、负性或中性声音），针对四项因变量（效价、唤醒度、相似性与回避度评分）检验组间差异。当观察到声音类型存在统计学意义的交互效应时，采用事后两两比较以明确各因变量上的组间差异，以及不同声音类型在各因变量上的均值差异。 所有分析均采用IBM SPSS 27统计软件完成。数据分析流程的第一步包括数据集的清理与筛查：(a) 检查所有变量的数据录入错误（未发现异常）；(b) 检验研究变量的分布正态性。随后，通过双变量相关分析探究变量间的关联，以判断是否……。 # 采用标准化声音集表征恐音症：国际情感数字化声音库 [https://doi.org/10.5061/dryad.kh18932fd](https://doi.org/10.5061/dryad.kh18932fd) ## 数据与文件结构说明 MQincluded为分组变量。其中MQincluded=1代表符合恐音症诊断标准且被纳入本数据集的所有参与者；MQincluded=0代表健康对照人群。所有测评变量的名称均在SPSS的“标签（label）”列中附有描述信息。因变量的平均评分可在SPSS变量视图的末尾找到，同时还包括正性与负性情感量表（PANAS）得分以及AIM总分。 ## 共享与获取说明 本数据集源自以下来源： * 亚马逊机械 Turk（Amazon Mechanical Turk） ## 代码与软件 数据集上传文件中包含SPSS语法文件。