PUB - Publikationen an der Universität Bielefeld

**Background**
The perception of the affective quality of stimuli with regard to valence and arousal has mostly been studied in laboratory experiments. Population-based research may complement such studies by accessing larger, older, better balanced, and more heterogeneous samples. Several characteristics, among them age, sex, depression, or anxiety, were found to be associated with affective quality perception. Here, we intended to transfer valence and arousal rating methods from experimental to population-based research. Our aim was to assess the feasibility of obtaining and determining the structure of valence and arousal ratings in the setting of the large observational BiDirect Study. Moreover, we explored the roles of age, sex, depression, and anxiety for valence and arousal ratings of words. **Methods**
704 participants provided valence and arousal ratings for 12 written nouns pre-categorized as unpleasant, neutral, or pleasant. Predictors of valence and arousal ratings (i.e. age, sex, depression, and anxiety) were analyzed for six outcomes that emerge by combining two affective dimensions with three words categories. Data were modeled with multiple linear regression. Relative predictor importance was quantified by model-explained variance decomposition. **Results**
Overall, average population-based ratings replicated those found in laboratory settings. The model did not reach statistical significance in the valence dimension. In the arousal dimension, the model explained 5.4% (unpleasant), 4.6% (neutral), and 3.5% (pleasant) of the variance. (Trend) effects of sex on arousal ratings were found in all word categories (unpleasant: increased arousal in women; neutral, pleasant: decreased arousal in women). Effects of age and anxiety (increased arousal) were restricted to the neutral words. **Conclusions**
We report results of valence and arousal ratings of words in the setting of a large, observational, population-based study. Method transfer yielded acceptable data quality. The analyses demonstrated small effects of the selected predictors in the arousal dimension.