## 6 Discussion
[PERSON] [11] found _noise sensitivity_ to be associated with intelligence, self-confidence in social interactions, and \"desire for privacy\", but [PERSON] [55] reported that highly noise sensitive individuals tended to be less well-adjusted (that is, more neurotic) and less healthy. [PERSON] [13] also found that _noise sensitivity_ was associated with mental health problems, in particular depression, and [PERSON] [12] (p. 465) reported that it correlated negatively with _extraversion_. However, the relationship might not be straightforward. While [PERSON] and [PERSON] corroborated [PERSON]'s finding for \"low and middle extraverts\", they reported that the \"neurotic extraverts\" in their study were highly sensitive to noise [54] (p. 991). On the other hand, stable (i.e., non-neurotic) extraverts might have a higher tolerance for external stressors, and it has been suggested that this is associated with chronically lower levels of cortical arousal in such individuals (see [11] (p. 462); also [23]). Our present results corroborate the findings by [PERSON] et al. [15], producing robust evidence that _noise sensitivity_ can be predicted from _extraversion_ and _conscientiousness_. Note that _emotional stability_ was not a significant predictor in both of these studies. This might indicate that this specific personality trait is relatively independent of _noise sensitivity_; however, an interaction effect of the kind suggested by [54] cannot be ruled out. We believe that future studies might illuminate this question by working with alternative and complementary constructs of _noise sensitivity_ that are based on other data than self-report, such as behavioural and psychophysiological measurements. Because of the modest sample sizes in the listening tests we have conducted, both in terms of the number of stimuli and the number of participants, the present results have limited generalizability. We have shown that the explanatory strength of personality traits in the multivariate regressions was small, yet significant. Thus the influence of some traits might have been drowned in experiment noise. This limitation can be overcome by having larger participant groups, or by targeting specific traits, foremost _emotional stability_ and _noise sensitivity_. Moreover, the mechanisms behind how personality traits cause a bias in affective responses to soundscapes are not well understood. This question calls for work in theory as well as empirical approaches, such as comparing cognitive appraisal with individual physiological responses (e.g., [30; 57]). In a recent publication, [PERSON], [PERSON], and [PERSON] [5] laid out a roadmap for soundscape research, especially predictive modelling, which forms the basis for planning and design. The authors highlight the distinction between soundscape descriptors (predictants, which enter as dependent variables in a predictive model) and soundscape indicators (predictors, which enter as independent variables that describe stimuli). This perspective is important in the investigation and selection of variables for modelling. In our present work we adopted the SSQP [41] to generate soundscape descriptors (_Pleasantness_ and _Eventfulness_), and we selected stimuli variables (_type_ and \(N_{10}\), i.e., soundscape indicators) that were either predetermined or significant in the initial multivariate analysis. We have attempted to explain more of the variation in dependent variables (soundscape descriptors) by considering ratings from individual participants. Our results indicate that _Pleasantness_ and _Eventfulness_ might to a small yet probably significant extent be predicted by personality traits, over and above soundscape indicators. Trait variables could be seen as moderating variables in a predictive model.