Behavior Prediction Through Direct and Indirect Measures

In Study 2, the observer judgments of anxious and angry behavior were predicted by the direct self-ratings. Additionally, the observer judgment of anxious behavior was predicted by the anxiousness IAT, and correlated with the duration of body adaptors and the frequency of nervous mouth movements. However, none of the behavioral anxiety and anger codings correlated significantly with either the direct measures or the IATs. The

same pattern of results was found for the shyness measures in Study 1. Thus, it is a difficult task to identify valid behavioral indicators that correlate with the observer judgments and direct or indirect personality self-concept measures. There might be several reasons why Study 2 failed to succeed in the search for valid behavioral cues.

Concerning the behavioral anger measures, the interaction between the experimenter and the participant after the computer crash was probably too short for aggregating sufficient anger indicators. The mean duration was 117 (SD = 21) seconds and ranged from 72 to 168 seconds. In contrast, the duration of the speech was three minutes for all participants. Importantly enough, the duration of the anger sequence did not correlate with either the observer anger judgment, direct or indirect angriness measures, or any of the anger codings (that were coded in frequencies per minute). Thus, behavioral anger measures were not confounded with the duration of the anger sequence.

Nevertheless, the anger sequence was relatively short, and most behavioral anger indicators were so infrequent that even intercoder reliability was unsatisfactory. This does not, however, imply that the anger induction was inapt for the observation of angry behavior since the direct angriness measures showed predictive validity for the observer anger judgment. As many earlier attempts to study anger in the lab (e.g., Pauls &

Stemmler, 2003; Wiedig, 2003), the present study only partially solved the problem that the anger sequence has to be both (a) long enough and (b) unrecognized by the participants.

Concerning the behavioral anxiety measures, the results from Egloff and Schmukle’s (2002) Study 4 were only partially replicated in the present study. In both studies the anxiousness IAT added incremental validity over direct measures to the prediction of anxious behavior. In contrast, the observer anxiety judgment was significantly predicted by direct anxiousness measures in the present study but not in Egloff and Schmukle’s Study 4. This might be due to the fact, that more direct anxiousness measures were included in the present study. The situation-specific direct measures, that is, the emotionality subscale of the Speaking Anxiety Questionnaire and the bipolar state anxiety items, were particularly strong predictors for the observer anxiety judgment in the present study. Yet, the trait form of the State Trait Anxiety Inventory also correlated marginally with the observer anxiety judgment, r = .19, p < .10, whereas this was not true for Egloff and Schmukle’s study, r = .12, n.s.. However, this correlation difference was only small, and the lack of predictive validity of the direct anxiousness measure in Egloff

and Schmukle’s Study 4 might also be attributed to the relatively small sample size (N = 33). Thus, the present study is in line with the expectation that direct measures show small to moderate validity for the prediction of behavior (Funder, 1999).

Differently from Egloff and Schmukle’s Study 4, the frequency of nervous mouth movements was not predicted by the anxiousness IAT in the present study. This could not have been attributed to a lack of cross-lab reliability of the behavioral coding since consistency between both labs was completely satisfactory. However, the anxiousness IATs of both studies differed with respect to the attribute categories and the attribute exemplars. Attribute categories were anxiety versus calmness in Egloff and Schmukle’s studies, and anxious versus self-confident in the present study. A possible post hoc explanation is that behavioral nervousness is more directly linked to a lack of calmness than to a lack of self-confidence. Therefore, the anxiety versus calmness IAT from Egloff and Schmukle might have shown better predictive validity.

Additionally, the participants in Egloff and Schmukle’s Study 4 showed more nervous mouth movements than the participants in the present study, t(131) = 2.74, p < .01.

Possibly, behavioral anxiety was higher in Egloff and Schmukle’s Study 4 due to the more evaluative nature of the speech task that asked the participants to summarize a scientific text instead of talking about euthanasia. Importantly enough, participants of both studies differed only marginally on the trait form of the State Trait Anxiety Inventory. Thus, differences between the studies should not be attributed to a general sample effect. In summary, it seems that interindividual differences in the personality self-concept of anxiousness are observed best, if one maximizes the evaluative character of the anxiety induction.

Altogether, the search for valid behavioral codings was not successful in Study 2.

However, I refrained from further behavioral analysis due to the position effects and the lack of convergent and discriminant validity that were found in the angriness IAT.

Nevertheless, the high correlations between the voice ratings and the observer judgments indicate that valid cues for interindividual differences in anxiousness and angriness may be found within the vocal expression of participants. Future studies of more objective vocal cues should explore this possibility.

5.5.4 Angriness, Agreeableness, Anger Expression, and Approach Behavior