Cultural Differences in Revaluative Attributions

Abstract

Culture can impact cognitive processes, including effects on causal attributions. This study examined cultural differences in revaluative attributions when two potential causes of an outcome are initially present, but new relevant causal information is later available, suggesting potential adjustments could be made with respect to the original judgment. Study 1 (N = 206) found that both Chinese and American participants showed revaluative attributions regarding the target cause when a nontarget cause was decreased in its validity during a subsequent phase. That is, the target cause was later judged as more valid when a nontarget cause was decreased in validity (the deflation effect). However, only American participants exhibited a significant decrease in the perceived validity of a target cause when the nontarget cause was increased in its validity (the inflation effect). Study 2 (N = 189) replicated these findings and also showed that dialectical thinking was a mediator of this cultural difference in revaluative attributions. The present study shows that culturally shaped cognitive processing can influence multicausal inferences.

Keywords

revaluative attribution culture inflation effect deflation effect dialectical thinking

The ability to generate causal relations among events in the environment allows organisms to predict and control their surroundings. An extensive published literature exists examining the processes underlying judgments of cause and effect relationships when a single potential cause is predictive of an outcome (e.g., Allen & Jenkins, 1980; Katagiri, Kao, Simon, Castro, & Wasserman, 2007; see Alloy & Tabachnik, 1984; Young, 1995, for reviews). More recently, the attribution processes that occur when there are many potential causes available have been debated (Katagiri et al., 2007; Young, 1995; see also Mackintosh, 1975; Pearce & Hall, 1980; Rescorla & Wagner, 1972; Van Hamme & Wasserman, 1994). It has been long known that potential causes will compete for causal status during attributional processes (Baetu, Baker, Darredeau, & Murphy, 2005; Baker, Mercier, Vallee-Tourangeau, Frank, & Pan, 1993; Wasserman & Berglan, 1998). People tend to ignore the value of some events that are potentially relevant to the outcome of concern when they are making inferences in a situation in which many potential causes are present (Downing, Sternberg, & Ross, 1985). People often discount the causal role of other possible factors when a dominant cause is available (Downing et al., 1985; Kelley, 1972; Schustack & Sternberg, 1981).

Cultural Differences in Causal Inference

Cross-cultural research in the past two decades has attempted to examine cultural differences in attribution processes and the culturally based worldview responsible for these differences. Published work has tested attributions in stable situations and has shown that people from different cultures vary in the ways that attributions are made (Choi, Dalal, Kim-Prieto, & Park, 2003; Ji, Nisbett, & Su, 2001; Maddux & Yuki, 2006; Nisbett, Peng, Choi, Norenzayan, 2001). For example, people from Western cultures, such as Americans, tend to focus on one cause whereas people from Eastern cultures, such as Chinese, tend to consider a broad range of factors (Choi et al., 2003; Maddux & Yuki, 2006; Menon, Morris, Chiu, & Hong, 1999). Also, Westerners’ attributional choices have been found to be made using a process of comparing the alternatives based on a single dimension, while the Easterners’ justification for their choice involved a compromise of more dimensions (Nisbett et al., 2001).

Dialectical thinking (DT) is a culturally based thinking style shaped by the prevalent epistemology or worldview in Eastern Asia, and it has been used to address these cultural differences in attribution. Dialectical thinkers believe that events in the world are dynamic and flexible (the “principle of change”), are full of contradictions (the “principle of contradiction”), and are connected such that no event is isolated or independent of others (the “principle of relationship or holism”; Peng & Nisbett, 1999). DT affects people’s cognitive strategy during the attribution process in a situation where multiple potential causes are present. With respect to such strategies, dialectical thinkers tend to be tolerant of opposing possibilities. They believe that the seemingly (by some) contradictory perspectives are not mutually exclusive, and that all of the views may contain some truth or value. In other words, people who are high on DT try to retain all possibilities, and they try to find a “middle way” to solve the problem (Nisbett et al., 2001). Alternatively, people who are low on DT tend use a strategy called differentiation to solve problems, in which a cause is either strongly considered influential or strongly considered not influential. The result of the “differentiation” strategy is that people tend to use more unicausal versus multicausal inferences (Peng & Nisbett, 1999).

Revaluative Attributions

As environmental conditions vary and our initial attributions can be mistaken or incomplete, it is adaptive to adjust an initial attribution when new information about the potential cause or event is acquired. The phenomenon in which changes in the causal status of a nontarget cause can then influence the causal status of a target cause is referred to as “revaluative attributions” or “retrospective revaluations” (e.g., Gershman, Markman, & Otto, 2014; Jamieson, Hannah, & Crump, 2010).

A revaluative attribution is an attribution made regarding two competing causes after gaining new information about one of the potential causes at a subsequent time. A retrospective revaluation procedure typically involves two phases. During initial training, people learn that two potential causes are candidates for producing the outcome. Attributions are presumably made regarding the extent that these causes may be responsible for the outcome, and usually both causes are considered moderately responsible or predictive of the outcome. The two causes compete so that each is typically perceived as responsible to some extent, but neither cause is perceived as a large causal factor. In a second phase, one nontarget cause is reduced in validity, that is, its causal status is decreased. This effect is sometimes referred to as “deflation” of the competing nontarget cause. This is expected to cause a compensatory increase in the causal status of the target cause. The “target cause” refers to the event that is of focal interest in the study (i.e., the cause that may potentially change in its perceived validity based on the deflation or inflation of the nontarget cause). Alternatively, a nontarget cause can be increased in its causal status in this second phase (sometimes called “inflation” of a competing nontarget cause). This is expected to cause a compensatory reduction in the judged causal status of the target cause.

Cultural Differences in Revaluative Attribution

As mentioned, environmental conditions undergo change and people often face more than one explanation for an event; adjustments in attributions may be needed. Existing cross-cultural research focused exclusively on attributions in stable situations. This limits our understanding of answers to some valuable questions, such as to what extent do people allow their inferences to adapt when new information arrives, and are there cultural differences in such adaptation? If so, what cultural-based factor is responsible for the difference?

Although retrospective revaluation is a good candidate to address these issues, all retrospective revaluation research in humans has been conducted in Western countries. People from Eastern countries differ from those in Western countries in attributions involving multiple potential causes. It seems unlikely that the revaluative attribution effects found in people from Western countries represent the way that Easterners react in a changing situation. An investigation of cultural differences in revaluative attributions can extend our understanding of how culture influences people’s attribution processes.

More specifically, when one possible cause increases in its validity (inflation), Westerners (presumably low in DT) can be expected to use the “differentiation strategy,” as described earlier. That is, they will pick the most valid cause and devalue the other cause. However, Easterners (those presumably high in DT) may not perceive the causes as competing, or may tend to tolerate competing causes. The increase in validity of one cause need not reduce the validity of another cause for these individuals. Therefore, people from Eastern countries may be less likely to adjust the causal value of one cause based on updated information about the alternative cause in the inflation situation. However, the culturally based reasoning style may not result in a difference in the deflation situation. After one cause has been proven less valid (“deflation”), the other cause can be viewed as a sufficient cause for the outcome. It is reasonable for Easterners as well as Westerners to recognize this sufficiency status of the other cause, and this deflation manipulation can be expected to increase the validity of the other cause. In other words, a deflation effect was expected to occur regardless of the reasoning style used. It was predicted that individuals of both cultures would exhibit deflation effects, but only Westerners would show an inflation effect.

Current Studies

We tested these hypothesized cultural differences in revaluative attribution in two studies. In Study 1, we tested the cultural differences in attribution using food allergy scenarios (e.g., Baetu et al., 2005; Van Hamme & Wasserman, 1994; Wasserman & Berglan, 1998; Wasserman & Castro, 2005). In Study 2, we sought to replicate our findings from Study 1, and added certain control conditions. In addition, the DT scale was added to test the role of DT in the cultural differences for the revaluative attributions. In addition to hypothesizing that American participants would show more of an inflation effect than Chinese participants, while there would be no cultural difference in the deflation effect, we further predicted that DT would mediate the culture difference in the inflation effect.

Study 1

Method

Participants

Participants were 92 Chinese undergraduate students from a university in Beijing, China, and 114 American undergraduates from a large state university in the middle of the United States. Students were given course credit for their participation. In the U.S. sample, 53% of the students were male and 87% were freshmen. In the Chinese sample, 32% were males and 46% were freshmen. The Chinese questionnaire was translated from the English into Chinese, and then back-translated by different English–Chinese bilingual individuals; discrepancies in meaning were discussed and resolved to yield an equivalent questionnaire in both languages.

Procedure

Participants were asked to complete a questionnaire. The questionnaire first introduced an imaginary scenario that instructed participants to imagine themselves as allergists, and their job was to determine which food(s) produce allergic reactions (e.g., Baetu et al., 2005; Van Hamme & Wasserman, 1994; Wasserman & Berglan, 1998; Wasserman & Castro, 2005). Tasks were embedded in a story with an assumed patient making them potentially more realistic and vivid. The participants first provided an initial rating on two pairs of food (yogurt and walnuts, bananas and mushrooms); one pair was used for the inflation condition and other pair was used for the deflation condition. All participants received both inflation and deflation manipulations. For all ratings, participants answered using a 9-point Likert-type scale whether they thought a food substance was responsible for an allergic reaction (1 = definitely would not, 3 = probably would not, 5 = maybe, 7 = probably would, 9 = definitely would).

After the initial rating, all participants in Phase 1 received information about these two pairs of foods. Specifically, participants read in Phase 1 that the patient ate one pair of food and had an allergic response, and also ate the other pair of foods and had an allergic reaction. They were then asked again (the second rating) to rate the likelihood that those foods caused a reaction. Participants then received new information (Phase 2) regarding food consumption and allergy information, and were asked once again to rate those foods using the Likert-type scale (the third rating). The new information included an inflation manipulation and a deflation manipulation. In the inflation condition (yogurt and walnuts), the new information provided in Phase 2 of the procedure revealed that yogurt alone caused an allergic reaction (inflation) when it was consumed alone (walnuts were the target cause in this condition). In the deflation condition (mushroom and bananas), the new information provided in Phase 2 showed that banana alone did not cause (deflation) an allergic reaction (mushrooms were the target cause in this condition). See the procedure illustrated in Table 1.

Table 1.

The Stimuli Used in Study 1.

Revaluative type	Phase 1 allergy record			Phase 2 allergy record
Revaluative type	Date	Food record	Whether allergy occurred	Date	Food record	Whether allergy occurred
Inflation task	Monday	Yogurt + walnuts	Allergy	Wednesday	Yogurt	Allergy
Deflation task	Tuesday	Bananas + mushrooms	Allergy	Thursday	Banana	No allergy

Results

Gender and class standing in college were not found to produce a main effect of the ratings in the inflation scenarios, F = 0.51, p = .47, and F = 0.52, p = .47, respectively, or in the deflation scenarios, F = 0.38, p = .54 and F = 0.67, p = .42, respectively, nor did they significantly interact with culture or treatment in the inflation scenarios, Fs < 1.33, ps > .25, or in the deflation scenarios, Fs < 1.06, ps > .30. Therefore, they were not included in the following analyses. Descriptive statistics are reported in Table 2.

Table 2.

Descriptive Statistics of Studies1 and 2.

Revaluative type	Condition	Ratings	Study 1				Study 2
			Chinese		American		Chinese		American
			M	SD	M	SD	M	SD	M	SD
Inflation	Control	Pre					5.04	1.55	5.66	1.36
	(–/Yogurt B)	Post					4.57	1.65	5.21	1.85
	Experimental	Pre	4.98	2.02	7.15	1.70	4.95	1.47	5.58	1.38
	(walnuts/Yogurt D)	Post	4.43	1.74	5.01	2.52	4.69	1.67	4.72	2.32
Deflation	Control	Pre					5.00	1.53	5.86	1.44
	(–/Yogurt H)	Post					4.96	1.82	5.46	1.81
	Experimental	Pre	6.47	1.91	6.70	1.80	5.01	1.47	5.77	1.45
	(mushrooms/Yogurt J)	Post	6.73	2.02	6.68	2.42	5.79	2.52	6.69	2.58
Dialectical thinking							4.10	0.38	3.59	0.48

Note. The food in the parentheses shows the stimuli. The first one was used in Study 1 and the second one was used in Study 2. In Study1, there is no control stimuli.

Manipulation check

To check whether participants were sensitive to the revaluative manipulation regarding the changes in the casual status of the two nontarget cues, yogurt (used for the inflation manipulation) and banana (used for the deflation manipulation), the revaluation effect was tested using the repeated ratings of yogurt and banana—ratings given after Phase 1 and ratings given after the Phase 2 revaluation manipulation. Analysis of the repeated ratings of yogurt, the nontarget food used in the inflation condition, using an ANCOVA, with the initial rating of yogurt controlled, showed a significant main effect of revaluative treatment, that is, a change in the two ratings, F(1, 202) = 126.99, p < .001, while the main effect of culture and the interaction between revaluation and culture were not significant.

An ANCOVA conducted on the repeated ratings of banana, the nontarget food used in the deflation condition, with the initial rating of banana controlled, showed that there was a significant main effect of the revaluation treatment, F(1, 200) = 22.12, p < .001, and a significant interaction between revaluation treatment and culture, F(1, 204) = 9.82, p = .002. This interaction revealed that the decrease occurred less for the Chinese participants’ ratings of banana (M = −2.27, SD = 2.03) than for the American participants’ ratings of banana (M = −3.29, SD = 2.63), but deflation occurred for both groups of participants. Thus, both manipulations appeared to be successful.

The inflation effect

The two cultures expressed different baseline response ratings to walnut prior to yogurt being inflated, so this initial rating of walnut was used as a covariate in the analyses. An ANCOVA examining the repeated ratings of walnuts (target food) with culture, treatment, their interaction, as well as the initial rating on walnuts as a covariate yielded a significant interaction between treatment and culture, F(1, 202) = 6.33, p = .013, η² = 0.03. To explore the interaction, an ANCOVA was conducted on the data separately for Chinese and American participants. Results showed no main effect of revaluative treatment for Chinese, F(1, 90) = 3.15, p = .079, but a significant effect of treatment occurred for Americans, F(1, 110) = 4.35, p = .039. That is, while controlling for initial ratings, the Americans, but not the Chinese, significantly decreased their ratings on walnuts (the target food) after they learned that yogurt (the nontarget food), when presented alone, was an effective cause of the allergy. In other words, a revaluative inflation effect was found for the American individuals but not the Chinese. Interaction plots of the adjusted means are presented in Figure 1.

Figure 1.

Interaction of inflation treatment and culture in Study 1.

The deflation effect

A similar ANCOVA to that above using repeated ratings of mushroom (the target food) and initial ratings of mushroom as a covariate obtained a significant main effect of the treatment, F(1, 201) = 8.73, p = .004, η² = 0.04, but no significant interaction of treatment and culture occurred, F(1, 201) = 1.47, p = .227, indicating that the deflation effect occurred for both Chinese and American participants. The rating for the target food (M = 6.58, SD = 0.11) increased significantly (M = 6.70, SD = 0.16) after the participants learned that banana (the nontarget food) was not an effective cause of the allergy. Plots of the adjusted means are presented in Figure 2.

Figure 2.

Interaction of deflation treatment and culture in Study 1.

Study 1 obtained a cultural difference in revaluative attributions such that American participants produced an “inflation effect,” whereas Chinese participants showed no such effect. That is, when an alternative, nontarget stimulus was elevated in its causal status, American participants decreased the status of the target cause in its perceived causal value. Both participants from the United States and China yielded a comparable “deflation effect.” That is, when a nontarget stimulus was later reduced in its causal status, the target stimulus resulted in a consequent increase in causal status.

Study 2

Study 1 revealed a cultural difference in revaluative attributions when people subsequently learned that one (nontarget) event was a particularly effective cause. Study 2 examined this effect using a slightly different design. First, control scenarios were added, as explained in the “Method” section. Second, yogurt was used exclusively as the causal food in Study 2 to reduce the cultural differences in baseline ratings shown in Study 1. Given that yogurt produced the smallest cultural difference in the initial rating in Study 1, yogurt was deemed the best food item to use. Also, the food stimuli in Study 1 (mushrooms, yogurt, etc.) were not counterbalanced with respect to their treatment (target food, nontarget food, inflated food, deflated food), and so the exclusive use of yogurt in Study 2 addressed this issue. Finally, another important goal of the study was to explore a factor that may explain the cultural effects; DT was measured in this study.

Method

Participants

Participants were 114 Chinese undergraduate students from a university in Beijing, China, and 75 American undergraduates from a large state university in the middle of the United States. In the American sample, 41% were males, and 71% were freshman. In the Chinese sample, 19% were males, and 97% were freshman. American students were given course credit for their participation, and Chinese students were given monetary rewards (5RMB) for their participation. The questionnaire was translated first from English into Chinese, and then back-translated by a second bilingual individual into English to ensure that the original meaning was retained.

Measures

Participants first were asked to complete the Dialectical Self Scale (DSS; Spencer-Rodgers, Srivastava, et al., 2010, as cited in Spencer-Rodgers, Peng, Wang, & Hou, 2004), using a 5-point Likert-type scale with higher scores indicating higher DT. DSS is the only scale known to measure DT, and it (or its early version) has been used in many published cross-cultural studies, which includes 32 items (Cheng, 2009; Hui, Fok, & Bond, 2009; Spencer-Rodgers, Peng, & Wang, 2010; Zell et al., 2013). The Cronbach’s alpha of the whole scale for the American sample was .67, whereas that for the Chinese sample was .48. Given the low alphas, especially that of the Chinese sample, we conducted some item-level analyses and factor analyses. Item analyses showed that Chinese participants’ reversed item ratings and nonreversed item ratings were unexpected positively related (p = .40); using only either reversed items or nonreversed items could improve the reliability of the DT measure in the Chinese sample. Exploratory factor analysis showed that Chinese participants’ responses on the nonreversed items were loaded on eight factors, whereas Americans’ responses on the nonreversed items were loaded on five factors. For reversed items, responses of both groups were loaded on six factors. Furthermore, as DSS follows a theoretical three-factor design (Spencer-Rodgers, Srivastava, et al., 2010, as cited in Spencer-Rodgers et al., 2004), we conducted another factor analysis based on the three-factor structure. For reversed items, only 2 out of 16 items were loaded on different factors across cultural groups, whereas for nonreversed items, 10 out of 16 items were loaded on different factors across cultural groups, and some items did not clearly load on any factors or had a negative loading estimate in the Chinese sample. Tables 3 and 4 show the factor loadings of reversed items and nonreversed items of two samples. These results suggested that the structural quality of the reversed items differed less in the two samples, and they represented the theoretical structure better than nonreversed items in the Chinese sample. Thus, in the analysis below, we used the mean of the reversed items as the DT score (the results using the full scale score are reported in the “Notes” section). The Cronbach’s alpha of those items for the American sample was .71, whereas that for the Chinese sample was .63.

Table 3.

Factor Analysis on Reversed Items With Chinese and American Samples.

Item	American samples			Chinese samples
Item	Factor 1	Factor 2	Factor 3	Factor 1	Factor 2	Factor 3
If I think I am right, I am willing to fight to the end	0.70	0.24	0.00	0.62	−0.03	−0.13
I have a strong sense of who I am and don’t change my views when others disagree with me	0.67	0.10	−0.01	0.63	0.24	0.15
I usually behave according to my principles	0.62	−0.20	0.38	0.76	−0.11	−0.01
I believe my habits are hard to change^a	0.53	−0.13	−0.08	−0.13	0.21	0.47
My core beliefs don’t change much over time	0.51	0.02	0.15	0.57	0.02	0.04
When I am solving a problem, I focus on finding the truth	0.48	0.31	0.27	0.62	0.10	−0.05
I have a definite set of beliefs, which guide my behavior at all times	0.42	−0.02	0.35	0.62	0.00	−0.13
If I’ve made up my mind about something, I stick to it	0.38	0.28	−0.32	0.52	−0.31	0.21
If there are two opposing sides to an argument, they cannot both be right	−0.22	0.78	−0.01	−0.10	0.66	−0.03
Believing two things that contradict each other is illogical	−0.06	0.72	0.00	−0.12	0.43	0.26
For most important issues, there is one right answer	0.20	0.66	0.03	0.19	0.65	0.13
I find that if I look hard enough, I can figure out which side of a controversial issue is right	0.30	0.47	0.22	0.04	0.63	0.06
I find that my world is relatively stable and consistent	−0.12	0.10	0.69	−0.19	0.29	0.39
I am the same around my family as I am around my friends	0.40	−0.17	0.60	0.20	−0.11	0.61
My outward behaviors reflect my true thoughts and feelings^a	0.16	0.20	0.59	0.55	−0.23	0.10
I believe my personality will stay the same all of my life	0.03	0.01	0.55	0.09	0.09	0.76

The item loaded on different factors across cultural groups.

Table 4.

Factor Analysis on Nonreversed Items With Chinese and American Samples.

Item	American samples			Chinese samples
Item	Factor 1	Factor 2	Factor 3	Factor 1	Factor 2	Factor 3
I sometimes believe two things that contradict each other^a,b	0.84	0.06	−0.11	0.18	0.31	−0.21
I often find that things will contradict each other	0.79	0.24	0.10	0.43	0.03	−0.05
I often find that my beliefs and attitudes will change under different contexts^a	0.73	0.13	0.20	0.24	0.61	0.13
There are always two sides to everything, depending on how you look at it^a	0.70	−0.05	−0.14	−0.25	0.46	−0.45
I often change the way I am, depending on who I am with	0.56	0.13	−0.03	0.56	−0.09	0.10
I am constantly changing and am different from one time to the next	0.49	0.21	0.38	0.70	0.04	−0.18
I find that my values and beliefs will change depending on who I am with	0.47	−0.01	0.53	0.63	0.10	0.30
I sometimes find that I am a different person by the evening than I was in the morning^a,b	0.40	0.14	0.05	0.19	0.26	0.18
I prefer to compromise than to hold on to a set of beliefs	−0.07	0.72	0.12	0.04	0.65	0.01
I can never know for certain that any one thing is true^a,b	0.06	0.69	0.19	0.13	0.25	−0.69
When two of my friends disagree, I usually have a hard time deciding which of them is right	0.16	0.68	−0.14	−0.15	0.41	0.71
I have a hard time making up my mind about controversial issues^a	0.26	0.65	−0.28	0.25	0.06	0.47
My world is full of contradictions that cannot be resolved^a	0.20	0.56	0.29	0.50	0.30	−0.05
The way I behave usually has more to do with immediate circumstances than with my personal preferences^a	0.28	0.39	−0.25	0.64	0.01	0.08
When two sides disagree, the truth is always somewhere in the middle^a,b	0.24	0.13	−0.56	−0.12	0.45	−0.13
When I hear two sides of an argument, I often agree with both^a	0.11	0.14	0.62	0.02	0.54	0.06

The item loaded on different factors across cultural groups.

The item had a negative load or did not clearly load on any factor.

Procedure

As in Study 1, participants worked on two judgment tasks with imagined scenarios in which they served as allergists. All subjects received an “inflation task” (Yogurts A-E) and a “deflation task” (Yogurts G-K). In each task, there was an experimental comparison of yogurts and a corresponding control comparison of yogurts. Thus, experimental and control conditions were within-participant, and inflation and deflation manipulations were also a within-subject factor. Participants were asked to differentiate the yogurts based on their labels (e.g., Yogurt B). They judged the causal status of the yogurts with respect to whether they produced allergic responses on a 9-point Likert-type scale (1 = definitely would not, 3 = probably would not, 5 = maybe, 7 = probably would, 9 = definitely would). These judgments were made on two occasions: (1) a rating after the initial treatment (Phase 1), but before the inflation or deflation phase (Phase 2), and (2) a rating after Phase 2. The order of the tasks (deflation and inflation) as presented in the questionnaire was counterbalanced, as well as the order of testing of the target stimuli, and nontarget stimuli during the second assessment. The procedure is illustrated in Table 5.

Table 5.

The Stimuli Used in Study 2.

Revaluative type	Condition	Phase 1 allergy record			Phase 2 allergy record
Revaluative type	Condition	Date	Food record	Whether allergy occurred	Date	Food record	Whether allergy occurred
Inflation task	Control	Monday	Yogurt A + Yogurt B	Allergy	Wednesday	Yogurt E	Allergy
Inflation task	Experimental	Tuesday	Yogurt C + Yogurt D	Allergy	Thursday	Yogurt C	Allergy
Deflation task	Control	Monday	Yogurt G + Yogurt H	Allergy	Wednesday	Yogurt K	No allergy
Deflation task	Experimental	Tuesday	Yogurt I + Yogurt J	Allergy	Thursday	Yogurt I	No allergy

In the inflation task, Yogurts C and D were used in the experimental condition, and Yogurt D was the target food. These yogurts were presented together in Phase 1. Participants were first told that this pair of yogurts was consumed and an individual had an allergic reaction after consuming them. Then, participants were asked to rate the likelihood of each yogurt as the source of allergy. In Phase 2, the inflation manipulation revealed that the nontarget food from the experimental condition, Yogurt C, led to an allergy when it was consumed alone. Thus, Yogurt C was inflated, and the effects of inflation of Yogurt C on the judged causal value of Yogurt D were assessed.

Also, Yogurts A and B were presented together as control stimuli for the inflation treatment, and subjects were told that a patient had an allergic reaction after consuming them in Phase 1. However, in Phase 2, neither of these foods was inflated, and they could therefore serve as comparison stimuli for Yogurts C and D. Instead, a fifth (control) yogurt, Yogurt E, was given inflation treatment in Phase 2, as it was revealed that Yogurt E led to an allergy when it was consumed alone. The inflation of Yogurt E was not expected to affect any another yogurt because Yogurt E had not been paired with another yogurt during the study, and would not, therefore, be in competition with another yogurt for causal status. This control assessed any changes in the target (experimental) yogurt caused by any other factors (e.g., effects of a yogurt receiving repeated ratings), if any should occur.

In the deflation task, Yogurts I and J were used in the experimental condition, and Yogurt J was the target food. Participants were first told that these yogurts were consumed and the patient had an allergic reaction. They were then asked to rate the likelihood of each yogurt as the source of allergy. In Phase 2, information revealed that the nontarget food from the experimental condition (Yogurt I) did not lead to an allergy when it was consumed alone. Thus, Yogurt I was deflated, and the effects of deflation of Yogurt I on the judged causal value of Yogurt J were assessed.

Also, Yogurts G and H were presented together as control stimuli for the deflation treatment in Phase 1 as causes of an allergic reaction, and neither of these foods was deflated in Phase 2. They could thereby serve as comparison stimuli for Yogurts I and J. A fifth (control) yogurt, Yogurt K, was given deflation treatment in Phase 2 such that Yogurt K did not lead to an allergy when it was consumed alone. The treatment of Yogurt K was not expected to affect any other yogurts because Yogurt K was not paired with another yogurt and would not, therefore, be in competition with another yogurt for causal status. This control serves as the same function as Yogurt E for the inflation procedure.

Results

Gender and class were again not found to produce any main effects on the ratings in the inflation scenarios, F = 0.88, p = .349, and F = 0.70, p = .405, respectively, or deflation scenarios, F = 0.08, p = .777, and F = 0.02, p = .896, respectively, nor did they significantly interact with culture, treatment, or condition in the inflation scenarios, Fs < 2.63, ps > .11, or in the deflation scenarios, Fs < 3.28, ps > .07. The results showed that they were not valid covariates; therefore these two variables were not included in following analyses. Descriptive statistics are reported in Table 2.

Manipulation check

For the inflation task, the changes before and after the manipulation of nontarget yogurt in the experimental condition, Yogurt C, and the nontarget yogurt in the control condition, Yogurt A, were assessed. An ANOVA with repeated ratings was conducted, with culture (Chinese vs. Americans), revaluation treatment (before inflation vs. after inflation), and condition (experimental vs. control) as predictors. Results produced a significant interaction between revaluative treatment and condition, F(1, 182) = 146.90, p < .001. That is, as expected, the nontarget food in the experimental condition, Yogurt C, showed a larger increase in its validity after the inflation treatment, M = 1.88, SD = 2.52, t(183) = 10.23, p < .001, than the nontarget food in the control condition, Yogurt A did, M = 0.66, SD = 2.43, t(184) = 3.72 p < .001. The three-way interaction between revaluation treatment, condition, and culture was not significant, F(1, 182) = 1.30, p = .256, suggesting no cultural difference in the inflation manipulation on the nontarget stimuli. Also, no main effect of culture or interactions of culture with any other factors occurred, Fs < 3.14, p > .07.

For the deflation task, the changes before and after the manipulation of the nontarget yogurt in the experimental condition, Yogurt I, and the nontarget yogurt in the control condition, Yogurt G, were assessed. An ANOVA with repeated ratings was conducted, with culture (Chinese vs. Americans), revaluation treatment (before deflation vs. after deflation), and condition (experimental vs. control) as predictors. The interaction between revaluation treatment and condition was significant, F(1, 182) = 64.89, p < .001. There was, as expected, a significantly greater change in Yogurt I, M = −2.62, SD = 2.91, t(184) = 12.24, p < .001, than for the control stimulus, Yogurt G, which was not deflated, M = −0.14, SD = 1.74, t(183) = 1.10, ns, and there was no three-way interaction, F(1, 182) = 0.90, p = .345. These results suggest that the deflation manipulation was successful in the experimental condition, and there was no culture difference in the effect of the deflation manipulation. There was a culture and condition interaction, F(1, 182) = 4.44, p = .037. However, this difference was constant across assessments and was not the focus of this article, and it should not have influenced the critical results.

The inflation effect

A similar ANOVA to those above examining repeated ratings on Yogurts D (the target stimulus) and B (a control stimulus), from the inflation task, was performed. A significant three-way interaction between culture (Chinese vs. Americans), revaluation treatment (before inflation vs. after inflation), and condition (experimental vs. control) appeared, F(1, 183) = 4.37, p = .038, η² = 0.02. For the American participants, the interaction between revaluative treatment and condition was significant, F(1, 70) = 4.21, p = .044, with ratings that decreased more after the inflation manipulation in the experimental condition (Yogurt D), M = −0.86, SD = 2.20, t(70) = −3.29, p < .005, than in the control condition (Yogurt B), M = −0.45, SD = 1.61, t(70) = −2.36, p < .05. However, for Chinese participants, the interaction between revaluative treatment and experimental versus control conditions was not significant, F(1, 113) = 1.30, p = .257, indicating that ratings in the experimental condition did not change significantly differently than ratings in the control condition. Interaction plots of the adjusted means are presented in Figure 3.

Figure 3.

Interaction of inflation treatment, control versus experimental conditions, and culture in Study 2.

The deflation effect

An ANOVA conducted on the repeated ratings of Yogurt J (the target stimulus) and H (a control stimulus) was performed, and the results obtained a significant two-way interaction between revaluative treatment (before deflation vs. after deflation), and condition (experimental vs. control), F(1, 183) = 22.27, p < .001, η² = 0.12, but the three-way interaction was not significant, F(1, 183) = 0.51, p = .478, suggesting that the increases in ratings across revaluative treatments differed by condition, but not by culture. For the experimental condition, participants from both cultures increased their ratings more after the deflation manipulation (Yogurt J, pre: M = 5.30, SD = 1.50; post: M = 6.14, SD = 2.57), t(184) = 4.12, p < .001, than their ratings for the control condition (Yogurt H, pre: M = 5.33, SD = 1.55; post: M = 5.15, SD = 1.83), t(184) = 1.41, ns. Plots of the adjusted means are presented in Figure 4.

Figure 4.

Interaction of deflation treatment, control versus experimental conditions, and culture in Study 2.

Mediated moderation test

DT was considered as a potential mediator in the culture effect on the revaluative attribution processes during the inflation task. In this study, the culture effect was examined by estimating its interaction effect with treatment. Hence, mediated moderation tests were conducted to explore the role of DT. In other words, we tested whether DT mediated the interaction effect between culture, revaluation treatment (before inflation vs. after inflation) and condition (experimental vs. control) on the validity ratings. Rather than using a Sobel test that is often used in a pure mediation situation, we utilized the multiple-step method proposed by Muller, Judd, and Yzerbyt (2005) to test the mediated moderation effect. In Step 1, we assessed the moderation effect of culture, which made use of the same model as the test for the inflation effect for the target stimuli. The significant three-way interaction between culture, treatment and condition indicated a moderation effect of culture, p = .038. Step 2 tested the effect of culture on the proposed mediator, DT. Results showed a significant cultural difference in DT ratings, F(1, 187) = 16.45, p < .001. Chinese (M = 3.81, SD = 0.61) reported higher DT than Americans (M = 3.43, SD = 0.67).¹ In Step 3, the participants’ DT scores were included along with their interaction with condition, treatment, and culture as predictors for ratings. Here, the mediation effect was tested by estimating the three-way interaction between DT, treatment, and condition. Results showed that this interaction was significant, F(1, 181) = 4.51, p = .035, η² = 0.02,² whereas the three-way interaction between revaluative treatment, condition, and culture described above was no longer significant, F(1, 181) = 2.91, p = .090,³ indicating that DT mediated the moderation effect of culture on revaluative attributions in the inflation task. The full models of the three steps are shown in Table 6.

Table 6.

The Mediated Moderation Models.

Variables	Step 1		Step 2 (using the full scale)		Step 2 (using the improved scale)		Step 3 (using the full scale)		Step 3 (using the improved scale)
Variables	F	p	F	p	F	p	F	p	F	p
Culture	5.67	.0183	64.62	<.0001	16.45	<.0001	1.00	.3178	0.00	.9747
Time	21.29	<.0001					0.25	.6182	1.48	.2249
Time × Culture	1.74	.1894					3.41	.0665	0.53	.4692
Condition	0.42	.5155					0.92	.3368	0.25	.6162
Condition × Culture	4.68	.0319					2.49	.1161	0.56	.4572
Time × Condition	3.64	.0580					3.36	.0686	3.33	.0697
Culture × Time × Condition	4.37	.0380					2.10	.1490	2.91	.0898
DT							1.10	.2952	0.26	.6126
DT × Culture							0.45	.5031	0.18	.6678
DT × Time							0.01	.9258	0.19	.6643
DT × Condition							0.61	.4374	0.11	.7413
DT × Time × Culture							2.96	.0873	0.27	.6031
DT × Condition × Culture							3.20	.0754	1.26	.2634
DT × Time × Condition							3.98	.0476	4.51	.0350
DT × Condition × Time × Culture							1.19	.2769	1.51	.2203

Note. In Steps 1 and 3, the dependent variable is the rating on target or nontarget trials. In Step 2, the dependent variable is the rating on DT. The bold terms showed the important values indicating the mediated moderation effect. The improved scale used all reversed items. DT = dialectical thinking.

Study 2, using an improved procedure relative to that of Study 1, again obtained a cultural difference in the inflation effect; an inflation effect was not observed for Chinese, whereas Americans exhibited this effect. As with Study 1, Study 2 obtained a comparable deflation effect for Chinese and American participants. Together, the studies show cultural differences for the inflation effect but not for deflation effects, consistent with our hypotheses. Study 2 also showed that DT mediated the effect of culture on revaluative attributions.

Discussion

Attributions can be influenced by cognitive style that is shaped by culture (Nisbett et al., 2001). Previous literature has established that significant cultural variance exists with respect to attributions per se, whereas the current study examines cultural effects on attributions when new information is later acquired, and the new information suggests that potential adjustments might be required regarding the original judgment. This research provides the first evidence of cultural differences in revaluative attributions. In total, 395 participants were recruited in Studies 1 and 2, and the pattern of the cultural differences in revaluative attribution was found in both studies, suggesting that this finding is reliable. Although the present studies used only a single domain (allergies), dozens of published reports examining attibution effects used this same type of allergy task (attributing allergic reaction to food substances; for example, Baetu et al., 2005; Van Hamme & Wasserman, 1994; Wasserman & Berglan, 1998; Wasserman & Castro, 2005), but as mentioned below, one important aim for future work is to explore these findings in other domains.

The current study makes two distinct contributions to understanding cultural differences in attribution processes. First, the effect of cultural differences in attributions is not just limited to the initial judgments people make (e.g., Nisbett et al., 2001) but also influences the changes in attributions when new (nontarget) information is presented that potentially suggests updating of the validity of the other (target) cause. Previous studies examining such effects have found that people tend to decrease their ratings on one of the paired potential causes (two stimuli presented together as potentially competing causes) when the other cause was inflated (e.g., Miller & Matute, 1996), and these studies were conducted in Western countries. The current studies suggest that reactions to revaluative treatments are not always the same for Easterners and Westerners, at least given the present procedure.

Second, using this procedure, the current study reveals that this cultural difference occurs for the inflation situation, but not the deflation situation. This result was found in both studies. It is not altogether surprising that an asymmetrical effect would be obtained for “inflation” and “deflation” of a nontarget cause. Many asymmetries for inflation and deflation have been noted in the research literature (see Miller & Matute, 1996, for a review).

The present research suggests that a cultural difference occurs for the inflation effect because the Chinese are higher on DT, indicating that they tend to attribute multiple causes as factors producing an effect when the causes compete (Nisbett et al., 2001) and are valid. Inflating the validity of one cause need not diminish the validity of the other. However, in the deflation scenario, when one cause’s validity was deflated, that cause was no longer legitimate, and individuals from both cultures experienced an increase in the validity of the alternative cause. Individuals who are high or low on DT can be expected to focus on the remaining valid cause and increase its validity. In another words, the deflation manipulation did not result in a cultural difference because the target cause potentially became the only valid cause after deflation, and this was true for all participants. However, again, when one cause’s validity was inflated, individuals high on DT maintained that the other cause was still valid; they preferred to use more reasons to explain an event and appeared to be more tolerant of the competing causes. For individuals who are low on DT, the elevated validity of one cause can, due to less tolerance regarding the alternative, competing cause, produce a lower judgment for the other cause. They used a differentiation strategy in the inflation situation and discounted the noninflated cause.

As hypothesized, we found that DT is an important factor that mediated the culture difference. DT is a way to process contradiction and change. People who are high on DT will accept contradiction and changes more easily, and are less likely to experience cognitive dissonance when the situation involves conflicts or changes (see Spencer-Rodgers, Williams, & Peng, 2010, for a review). Participants in the present studies received a change in information during a later phase. While making revaluative attributions, people who are low on DT may tend to resolve any conflict by believing that the inflated cause is the “right” cause, whereas the other cue is now the “wrong” cause of the outcome; however, people who are high on DT may maintain the possibility that the other cue can also remain as a valid cause. The present study demonstrated the processing of multiple causes for outcomes using a revaluation procedure and showed that culturally shaped cognitive patterns can have an important influence on attributions.

It is useful to consider the present findings in the context of attribution theory research and cross-cultural psychology research in general. Research on attribution theory and judgments of cause and effect have often found that people discount some casual candidates at the expense of others. Research extending over decades has observed that people limit causes of events to as few as possible (e.g., Kelley, 1973). However, given that most of this research has been conducted with Western participants, it is valuable to examine if individuals of Eastern cultures use the same strategy as Western individuals. The present demonstration that Easterners do not show as much retrospective revaluation in the case of “inflation” provides evidence that individuals high or low on DT use different processing strategies or at least are differentially sensitive to changes in attributional validity. Previous research using stable circumstances showed influences of culturally based thinking styles on people’s process of cause selection in attribution in an unchanging situation (e.g., Nisbett et al., 2001). The current research expands this literature by examining the cultural differences in changing circumstances, which provided new evidence that culturally based thinking style has dynamic influences on people’s attributions. That is, a culturally based thinking style, as DT tested in the current study, may have dual influences on both initial selection and reactive adjustment processes during attributional reasoning. In sum, these findings extend our understanding regarding how people attribute causes to effects in a changing circumstance and the role of culturally based thinking style in this process.

Limitations and Future Research

This is the first study to examine cultural differences in revaluation attributions, yet the current study has limitations and many issues for future studies exist. First, the reliability of the DT scale seems less reliable for the Chinese sample than the American sample. Although it has been used in a handful of studies, more research is needed to validate these scales and perhaps create a new scale better suited for studies of reasoning, attributions, and decision making. Also, we tested the cultural variance in some basic inferences regarding the consumption of food substances and the occurrence of an allergic response. Yet, allergic response assessment is just one type of attribution. Future studies should examine if the cultural differences in revaluative attribution occur when scenarios involve social interaction (i.e., a person assigns credit or blame to another individual). Finally, future studies should attempt to tighten their demographic variables more. For example, the Chinese sample was recruited from an introductory psychology class where monetary compensation was provided, whereas U.S. participants were given course credit compensation. Also, in our analyses, gender and class did not produce a main effect nor interact with other variables. The use of a balanced sample (equal number of males and females) with identical forms of compensation, while equating for all factors except for cultural differences, is desirable.

The mechanism of how DT influenced the inflation effect or what motivates the present attribution differences was not examined in the current study. Previous research suggests that people who are low in DT tend to use more unicausal inferences in cognition and experience more emotional discomfort when processing contrasting information (Spencer-Rodgers, Peng, & Wang, 2010; Williams & Aaker, 2002). The inference strategies people use and the affective reactions people have may serve as additional direct mediators of the group difference, and why a larger inflation effect occurs in American participants than in Chinese participants. Presumably, the inflation of the nontarget cause may serve as a motivational trigger to eliminate any discomfort by focusing on the single, nontarget cause, and produce discounting of the target cause. High DT people may not have the motivation to adjust their reasoning in this way, and, thus, show less of an inflation effect. Alternatively, it is possible that all people have the same amount of discomfort regardless of the DT level, but different groups may deal with it differently: People who are high on DT may tolerate the discomfort, whereas people who are low on DT attempt to reduce the discomfort by changing their attributions.

Alternatively, inflation effects may occur more for those low in DT than those high in DT because, although the initial process results in comparable revaluation for both DT levels, those high in DT then readjust their attribution back to the preinflation status. In this way, an initial inflation adjustment is not expressed in behavior for those individuals high on DT. Finally, the present studies did not test whether revaluative attributions are effortful or automatic processes, and this issue is worthy of empirical consideration. There is evidence of competition in the learning about cues in implicit processing tasks, suggesting the possibility that revaluative processes may be noneffortful (Moris, Cobos, Luque, & Lopez, 2014). The current study only tested the mediation effect of DT, but future studies can include measures of other culturally based cognitive styles or strategies, such as analytic thinking versus holistic thinking, to capture a more complete picture of culture differences in retrospective revaluation and attribution processes. In sum, the present study demonstrates that cultural factors can influence the cognitive process during revaluative attribution.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

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