not be construed in the same way across cultures, and this can potentially undermine the validity of their findings (Berry et al., 2002; Cohen, 2007). In other words, members of different cultures may understand the instructions in divergent ways, and determining whether discrepancies in responses to the experimental manipulations are caused by true cultural differences or a result of poor translations or misconstruals can be tricky. Two options for addressing this problem are ensuring that researchers have a good understanding of the cultures being studied and/or involving representatives from each of the cultures being studied in research design and implementation (Heine, 2010a; J. G. Miller, 2004).
Table 5.1
Response styles.
In Chapter 3 we discussed how response biases can influence participant answers to surveys and questionnaires. Although response biases can be a challenge within a culture, they can also pose a problem when surveying individuals from different cultures (Berry et al., 2002; Grimm & Church, 1999). For instance, the extremity bias described earlier is more common among some groups, such as African Americans, than others, such as East Asians (Chen, Lee, & Stevenson, 1995; Hui & Triandis, 1989). Culture-based response biases can be challenging to overcome, and perhaps the best way to prevent them from confounding psychological studies is to gather data from individuals using several different methods in hopes of finding convergent or consistent results (Cohen, 2007). In this way, possible biases in any one method can be revealed and corrected via other methods.
Sampling.
An additional problem that can arise when conducting cross-cultural research is determining how to sample across cultures or persons within cultures (Berry et al., 2002; Matsumoto & Juang, 2004). How does the researcher decide which cultures to choose? Sometimes this can be a matter of convenience, such as when the researchers have direct contacts in more than one culture. Other times psychologists select cultures that are likely to be or have been previously shown to be different on a key variable, such as individualism/collectivism. Both researchers and students must remember the fact that there is great variation between nations despite the fact that these nations may be similar in their overall levels of individualism/collectivism. Once the cultures have been chosen, researchers then must determine which samples in the cultures to include in the research. Given the enormous variability within cultures, care must be taken when selecting samples to ensure that they are as equivalent as possible (J. G. Miller, 2004). White participants from, say, working class Manchester, UK, may be very different from White participants living in a wealthy suburb of London. Moreover, a mostly White sample drawn from an elite U.S. educational institution may be different in terms of socioeconomic variables from a sample drawn from an elite university in, say, Kenya. As a result, researchers should be cautious in their interpretation of results from cross-cultural studies. Potential confounds related to differences in samples that cannot be avoided need to be considered, and generalizations to other cultures should be made judiciously (Cohen, 2007).
Self-Reflection 5.1
Measuring Individualism/Collectivism (Part 1)
As we have discussed, the individualism/collectivism dimension is one of the most widely researched cross-cultural variables (Na, Kosinski, & Stillwell, 2015; Taras et al., 2014). Although researchers have often placed nations and cultures in either the individualism or collectivism category, this variable is truly dimensional—there are many points along a continuum that reflect varying degrees—and there is a fair amount of intranational or intracultural variation. In other words, not all people in individualistic nations (like the United States) are individualistic, and not all people in collectivistic nations (e.g., China) are collectivistic (Ralston et al., 2014). For research purposes, we need to know where each participant in a study falls on this dimension. In this chapter, we describe some of the challenges to cross-cultural research, and there are many ways to measure this or related dimensions. To get a rough idea as to your IC level, take a minute and answer the following questions from a brand new scale and then turn the page to interpret your score. For “class,” simply think about students in your grade/year of college (e.g., freshmen, sophomore, etc.).
Table 5.2
Source: Yanagida, T., Strohmeier, D., Toda, Y., & Spiel, C. (2014). The Self Group Distinction Scale: A new approach to measure individualism and collectivism in adolescents. Psychological Test and Assessment Modeling, 56, 304–313.
Self-Reflection 5.2
Measuring Individualism/Collectivism (Part 2)
To determine your score, add up your responses to Questions 1 through 7 and for Questions 8 through 14. Then subtract the total of the “you” questions from the total of the “class” questions. If the number is negative, simply drop the negative sign. Next divide your answer by 7 to obtain a mean. These items are from the Self Group Distinction Scale (SGD) that was developed for adolescents, but of course, the underlying dimension is not limited to that age group (Yanagida, Strohmeier, Toda, & Spiel, 2014). The means for the Japanese (mostly collectivistic) and Austrian (mostly individualistic) participants were .33 and .72. The higher the number, the more a person separates her or himself from the group, and therefore the more individualistic that person appears to be.
Detecting Deception
How good are you at determining when someone is lying? What signs do you look for? Lying is quite prevalent: Most of us lie at least once or twice per day (DePaulo, Kashy, Kirkendol, Wyer, & Epstein, 1996). One diary study suggests that college students lie in one out of every three social interactions, whereas nonstudents do so in about one in five of their interactions (DePaulo et al., 1996). We also tend to engage in more deception with those with whom we are less familiar than those we are closer to (DePaulo & Kashy, 1998). You may be surprised to learn that our ability to detect lies from facial expressions and other nonverbal behavior is surprisingly weak, despite what we see in popular television dramas (Ambady & Weisbuch, 2010; Bond & DePaulo, 2006). A recent meta-analysis of over 200 studies, most of which involved detecting lies from audiovisual materials, found that people successfully distinguish truth from lies at barely above chance rates, around 54% (See Table 5.3) (Bond & DePaulo, 2006). This detection rate drops to 51% if observers are given only visual information (i.e., the sound is muted) (Bond & DePaulo, 2006).
Robert DeNiro administers a lie detector to Ben Stiller in Meet the Parents.
© AF archive / Alamy Stock Photo.
In a large meta-analysis that examined 142 studies, no evidence was found for any individual systematic differences in lie detection accuracy; in other words, personality, education, gender, and other characteristics were not significantly correlated with accuracy (Bond, Jr. & DePaulo, 2008).
Despite the frequency of lying, we are not particularly good at differentiating truths from lies when given only nonverbal cues. Why aren’t we better? One reason is that we tend to assume that people are telling the truth and therefore are not generally on the lookout for lies (Bond & DePaulo, 2006). A second reason is that people hold inaccurate beliefs about which nonverbal cues might reveal that a person is lying. Research shows that, in general, nonverbal cues to deceit are more difficult to detect than verbal ones (DePaulo et al., 2003). Despite common preconceptions, there is no evidence of differences in
