Cultural Differences in the Subjective Experience of Emotion: When and Why They Occur

Cross‐cultural comparisons of subjective emotional experience are common, and virtually any comparison of nations or different ethnic groups is bound to yield some differences and some similarities. While nobody doubts the considerable intercultural variability in subjective or self‐reports of emotion, more attention needs to be given to when and why and these differences occur. In this article, we explore factors that accentuate or attenuate cultural differences in the subjective experience of emotion. We propose that cultural norms shape emotional experiences to different degrees depending on the time frame of the emotional experience, the valence of the emotion, and even the specific emotion being compared. We review the research that supports this view and we highlight new avenues of research that are likely to shed light on cultural differences in the subjective experience of emotions.     

Timing at the Start of Associative Learning

Some theories of associative learning imply that time plays a fundamental role in the acquisition process. Consistent with these theories, this paper presents evidence that the time from the onset of a conditioned stimulus (CS) until presentation of the unconditioned stimulus (US) is learned very rapidly at the start of training. We report two autoshaping studies and a study on aversive conditioning in goldfish in which we examine timing at the start of conditioning. We also review data from a number of other conditioning preparations, including fear-potentiated startle, appetitive conditioning in rats, and eyeblink conditioning in rabbits, that report conditioned response (CR) timing early in training. Acquisition speed and the very first expressions of conditioned responding often show sensitivity to the time of US presentation. In instances where temporal control is slowly expressed, it is likely due to performance factors, not to slow learning about time. In fact, the learning about time may be a necessary condition for associative learning.     

The Development of the Universal Ethnic Identity Scale (UEIS) for use in an Australian context

The aim of the present research was to develop a measure that assessed the level of ethnic identification of adults from diverse ethnic backgrounds, as well as individuals' level of ethnic identification with a host culture following migration. In the first study, an ethnically diverse sample of 275 people (138 males and 137 females) responded to a range of new items, as well as items drawn from related scales. Factor analysis revealed three dimensions of ethnic identity that were labelled, “Pride in Ethnic Background and Language,”“Liking for Traditional and Social Activities of my Ethnic Group,” and “Sense of Belonging to This (host) Country.” This factor structure was evaluated in a second study with 1,007 (552 males, 455 females) adults from culturally and linguistically diverse backgrounds. A two‐factor structure provided the most parsimonious fit to the data but further investigation of the factor structure within ethnically diverse samples was recommended. The results are discussed in relation to theories of social identity as well as research on ethnic identification and adaptation.     

Clinical status of at-risk individuals 5 years later: further validation of the psychometric high-risk strategy

The authors hypothesized that at-risk individuals identified on the basis of their Chapman scale scores would be diagnosed with schizophrenia-spectrum disorders at follow-up. In the present study, the authors interviewed 135 young adults approximately 5 years following their initial assessment. The at-risk groups included high scorers on the Perceptual Aberration and/or Magical Ideation Scales (n=59) and high scorers on the revised Social Anhedonia Scale (n=32). The control participants (n=44) scored below 0.5 SD of the same-sex group means on all the scales. At the follow-up, the groups differed in terms of their likelihood of having a schizophrenia-spectrum diagnosis, Chi2(2)=9.79, p<.01. The at-risk groups reported more frequent and severe psychotic-like experiences relative to the control group. These findings support the predictive validity of the Chapman psychosis-proneness scales and may enhance the power of early detection efforts.     

The effect of gaze on gaze direction while looking at art

In highly controlled cuing experiments, conspecific gaze direction has powerful effects on an observer’s attention. We explored the generality of this effect by using paintings in which the gaze direction of a key character had been carefully manipulated. Our observers looked at these paintings in one of three instructional states (neutral, social, or spatial) while we monitored their eye movements. Overt orienting was much less influenced by the critical gaze direction than what the cuing literature might suggest: An analysis of the direction of saccades following the first fixation of the critical gaze showed that observers were weakly biased to orient in the direction of the gaze. Over longer periods of viewing, however, this effect disappeared for all but the social condition. This restriction of gaze as an attentional cue to a social context is consistent with the idea that the evolution of gaze direction detection is rooted in social communication. The picture stimuli from this experiment can be downloaded from the Psychonomic Society’s Archive of Norms, Stimuli, and Data, www.psychonomic.org/archive.     

Memory search for the first target modulates the magnitude of the attentional blink

The resolution of temporal attention is limited in a manner that makes it difficult to identify two targets in short succession. This limitation produces the phenomenon known as the attentional blink (AB), in which processing of a first target (T1) impairs identification of a second target (T2). In the AB literature, there is broad agreement that increasing the time it takes to process T1 leads to a larger AB. One might, therefore, predict that increasing the number of possible T1 identities, or target set, from 1 to 16 would lead to a larger AB. We were surprised to find that this manipulation of T1 difficulty had no influence on AB magnitude. In subsequent experiments, we found that AB magnitude interacts with T1 processing time only under certain circumstances. Specifically, when the T1 task was either well masked or had to be completed online, we found a reliable interaction between AB magnitude and the target set size. When neither of these conditions was fulfilled, there was no interaction between target set size and the AB. Previous research found that when the target set changes from trial to trial, trials with more possible targets elicited a larger AB. In the present study, the target set is held constant, reducing the demands on working memory. Nevertheless, AB magnitude still interacts with target set size, as long as the T1 task cannot be processed offline. Thus, the act of searching memory delays subsequent processing, even when the role of working memory has been minimized.