Do whispering minds tingle alike? Exploring the relationship between ASMR-sensitivity, trait-ASMR, and trigger preference

The data set includes data from an extensive sample (n=16679) of individuals who view ASMR content. Taking a data-driven k-means cluster approach, this data set identifies individuals' trait-ASMR characteristics (High / Medium / Low) based on the psychometric properties of the ASMR-15 compared with a self-classification approach based on location of reported ASMR tingles (authentic vs non-authentic ASMR propensity). Using principal component analyses, this data set also classifies 58 ASMR triggers into meaningful categories based on tingle intensity. The results demonstrate group differences in trigger categorisation predominantly in response to trait-ASMR, but not self-classification. It provides further evidence that ASMR experience should be considered on a spectrum, where a dimensional approach focusing on trait-ASMR is more informative in explaining individual differences in ASMR experience.

本数据集涵盖了观看自主性感官经络反应（ASMR）内容的大规模样本数据，样本量达16679例（n=16679）。本数据集采用数据驱动的k-means聚类方法，基于ASMR-15量表的心理测量学属性识别个体的特质型ASMR特征（高/中/低），并与基于报告的ASMR麻感发生位置的自我分类方法（区分真实型与非真实型ASMR倾向）开展对比分析。此外，本数据集还通过主成分分析方法，基于麻感强度将58种ASMR触发刺激划分为具有实际意义的类别。分析结果显示，触发刺激分类的群体差异主要与特质型ASMR相关，而非自我分类结果。本数据集进一步证实，ASMR体验应被视为一个连续谱系，其中聚焦于特质型ASMR的维度化研究方法，可更有效地解释个体间的ASMR体验差异。