Transgressive Humor and Adult Attachment: Raw Data, Analyses, and Stimuli

This dataset accompanies a study investigating how adult attachment dimensions (anxiety and avoidance) influence humor appreciation (laughter and acceptance) depending on the level of transgression in jokes. The main hypothesis was that attachment anxiety would predict greater engagement with humor (more laughter and acceptance), while attachment avoidance would predict lower appreciation, especially for jokes perceived as threatening or socially sensitive. The dataset includes responses from 117 Tunisian participants (76% female, M_age = 22.36) who completed the Relationship Scales Questionnaire (RSQ) and rated 15 culturally relevant jokes. Each joke was pre-rated for perceived transgression by eight independent coders using a 5-point Likert scale (1 = not at all transgressive, 5 = highly transgressive). Hierarchical cluster analysis identified three distinct transgression levels (low, moderate, high). Participants evaluated each joke on two dependent measures: 1. Laughter (binary: laughed vs. did not laugh), representing spontaneous emotional response. 2. Acceptance (Likert scale), capturing perceived moral or social acceptability. The data were analyzed using generalized linear mixed-effects models (GLMMs) to account for within-subject and item variability. Results showed that attachment anxiety predicted higher laughter and acceptance across transgression levels, suggesting a generalized tendency toward socioemotional engagement. In contrast, attachment avoidance was associated with reduced laughter but not necessarily lower acceptance, with this reduction concentrated on jokes involving vulnerability or taboo content. All files are included to ensure transparency and replicability: • Raw data: participant demographics, RSQ scores, joke-level responses. • Stimuli: full joke texts (translated in English), transgression ratings, and coding manual. • Analysis scripts: results of GLMM, EFA and analyses and clustering procedures.