Participants were recruited through advertisements at the university campus. A total of 171 participants completed an online screening with a German translation of the Trypophobia Questionnaire (TQ; Le et al. 2015). A total of 40 participants with the highest and lowest scores on the TQ were invited to the ERP study (32 women, 8 men; mean age = 22.87 years, SD = 3.34). Twenty participants were characterized by high Trypophobia Proneness (TP_high; TQ scores ≥ 29), whereas the other half was assigned to the TP_low group (TQ scores ≤ 19). Exclusion criteria for participation in the EEG study were neurological disorders and medication. The two groups did not differ in mean age (p = .79), years of education (p = .96) and gender ratio (see Table 1).
Clinical interview and questionnaires
A board-certified clinical psychologist conducted a structured clinical interview (Mini-DIPS; Margraf 1994) with all participants. The Mini-DIPS screens for anxiety disorders, affective disorders, somatic symptom disorders, eating disorders, substance abuse and psychotic symptoms. In addition, a trypophobia interview (developed by the authors) asked for the diagnostic criteria of a specific phobia according to DSM-5 (marked fear/disgust, active avoidance, clinically significant distress and/or functional impairment elicited by clusters of holes). Each criterion was rated by the participants on 9-point scales (1 = no disgust, fear, avoidance, impairment). Prior to the interview and EEG testing session, the participants completed the following questionnaires via an online screening:
The Trypophobia Questionnaire (TQ; Le et al. 2015; German translation) comprises 17 items that assess emotional (e.g., repulsion) and somatic responses (e.g., goosebumps) elicited by two images of trypophobic stimuli (lotus seed pods, honey comb). The presence of symptoms is rated on five-point scales ranging from 1 (“not at all”) to 5 (“extremely”). The sum score reflects trypophobia proneness. The Cronbach’s α of the scale was .88 in the present sample.
The Questionnaire for the Assessment of Disgust Proneness (QADP; Schienle et al. 2002) assesses the general tendency of a person to experience disgust across different situations (e.g., ‘You are just about to drink a glass of milk as you notice that it is spoiled’). The items are rated on 5-point scales (0 = not disgusting; 4 = very disgusting). The Cronbach’s α of the scale was .87.
The trait section of the State-Trait-Anxiety-Depression-Inventory (STADI; Laux et al. 2013) consists of four trait subscales (Arousal, Worrying, Dysthymia, Euthymia), each with five items. Trait Anxiety is comprised of Arousal (e.g., I’m getting nervous quickly) and Worrying, (e.g., I worry that something might happen); Trait Depression is determined based on the two subscales Dysthymia (e.g., I am sad) and Euthymia (e.g., I enyoy life). The items are rated on 4-point scales (1 = not all all, 4 = very much; scores for Euthymia are inverted). Higher sum scores suggest higher levels of trait anxiety/trait depression. The Cronbach’s alphas of the two trait scales were .88/.89 in the present sample.
The participants viewed a total of 120 pictures from four categories ‘Holes’, ‘Disgust’, ‘Fear’, and ‘Neutral’ (with 30 pictures each). Pictures depicting clusters of holes (e.g., lotus seed pods, sponges, corals, stone formations) were taken from the Internet and are comparable to the stimuli used by (Le et al. 2015). Generally fear-eliciting pictures (e.g., lions, sharks, weapons, aggression by humans), pictures with neutral items (e.g., household articles) and generally disgust-eliciting pictures (e.g., poor hygiene, spoiled food) were either taken from the International Affective Picture System (Lang et al. 2008)Footnote 1 or a validated picture set (disgust, fear, neutral) by Schienle et al. 2002).
Procedure and design
All participants completed the TQ, QADP, and STADI in an online survey. Then, the participants with the highest and lowest TQ scores were invited to a clinical interview. During the subsequent EEG session, the pictures (‘Holes’, ‘Disgust’, ‘Fear’, and ‘Neutral’) were displayed on a computer screen (diagonal: 22 inch; eye distance to the screen = 110 cm). The participants were instructed to passively view the images, which were presented in randomized order for 1500 ms each. Each image was preceded by a fixation cross (500-1000 ms). Five pictures per category were evaluated by the participants according to experienced disgust and fear on nine-point Likert scales (1 = not at all, 9 = very much) during the experiment.
The study was conducted in accordance with the Declaration of Helsinki and approved by the ethics committee of the University. All participants gave written informed consent.
Electrophysiological recordings and data analyses
Data were recorded with a Brain Amp 32 System (32 channel amplifier, Brain Vision Recorder Version 1.2; Brain Products, Gilching). Ag/AgCl electrodes were placed according to 10–20 system using an Easy Cap multitrode system (EASYCAP, Herrsching) on 31 positions (FP1, FP2, F7, F3, Fz, F4, F8, FC5, FC1, FC2, FC6, T7, C3, Cz, C4, T8, CP5, CP1, CP2, CP6, P7, P3, Pz, P4, P8, O1, O2, FT9, FT10, TP9, TP10). One electrode was placed supraorbital of the right eye in order to record vertical eye movement. Electrodes at FT9 and FT10 recorded horizontal eye movements. The reference electrode was placed on position FCz, the ground electrode on position FPz. The scalp was gently abraded with chloride-free electrolyte gel to keep electrode impedances below 5 kΩ. The sampling rate was 2500 Hz with a passband of 0.016–1000 Hz. For raw data analysis, the Brain Vision Analyzer (Version 2.0.4) was used. The sampling rate was set to 250 Hz. The data were re-referenced to averaged mastoid electrodes (TP9, TP10). Artifacts due to eye movements were corrected via the implemented ICA ocular correction software. Further artifact episodes (e.g., due to swallowing) were excluded after visual inspection (percentage of artifact-free trials: 96.2%; percentage of artifact-free trials did not differ between groups and conditions: all p > .22). The data were segmented in 1700 ms intervals (200 ms pre-stimulus, 1500 ms post-stimulus) and corrected to the 200 ms pre-stimulus baseline (i.e. subtraction of the averaged baseline from all points in the post-stimulus segment). A 30 Hz low-pass filter was applied.
Time windows and positions for early and late ERPs were selected based on previous research on specific phobia (e.g., Leutgeb et al. 2009). The selection was validated based on visual inspection of the grand averages and cortical maps. The following ERPs were analyzed: EPN/P100 (100–150 ms and 250–350 ms at O1, O2); N100/P200/N200 (100–150 ms, 150–200 ms and 250–350 ms at F3, Fz, F4), early and late LPPs (350–900 ms (see figure S1) and 900–1500 ms at P3, Pz, P4). The averaged activity in each cluster was used for statistical analyses.
The analyses showed no significant group or interaction effects for early components (P100, N100, P200, N200, EPN) and the late LPP. Therefore, these results are not reported.
Group differences regarding questionnaire scores were analyzed by means of independent t-tests. Analyses of variance (ANOVAs) with the between-subject factor GROUP (TP_high, TP_low) and the within-subject factor CATEGORY (Holes, Disgust, Fear, Neutral) were computed for affective picture ratings and ERP data. If sphericity violations (Mauchly test) occurred, Greenhouse–Geisser-corrected degrees of freedom are reported. Significant main effects were followed by post hoc t-tests. Effect sizes are expressed by partial eta squared (ηp2) or Cohen’s d. All statistical analyses were conducted with SPSS 25.