Article
Does A Major Earthquake Change Attitudes and Well-Being Judgments? A Natural Experiment
Social Psychological and Personality Science 1-8 ª The Author(s) 2017 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/1948550617707016 journals.sagepub.com/home/spp
Shigehiro Oishi1, Florian Kohlbacher2, and Hyewon Choi1
Abstract Does a major natural disaster change life satisfaction? This study is a rare natural experiment, in which roughly half of the respondents completed the survey before and the other half completed it after the Great East Japan Earthquake of March 11, 2011. A series of regression discontinuity design analyses showed that those who completed the survey after the earthquake reported being less satisfied with their lives than those who happened to complete the survey before the earthquake. There were no discontinuity on demographic variables and other consumer attitudes. The main findings remained virtually unchanged when we controlled for Big Five personality traits and demographic variables. Together, the current findings suggest that the experience of a major natural disaster changes their life satisfaction at least in the short run. Keywords natural disaster, attitudes, well-being judgments
This article reports a rare natural experiment, in which roughly half of the respondents completed the survey before the Great East Japan Earthquake happened, and the other half completed it afterward. The current study presents a unique opportunity to examine whether life satisfaction changes as the function of a national tragedy. Recent studies have shown that major natural disasters affect human psychology (see Neria, Galea, & Norris, 2009; Norris et al., 2002; Silver & Garfin, 2016, for reviews). For instance, the residents whose houses were damaged in the 1995 Hanshin Awaji Earthquake were less satisfied with their lives and reported more negative affect and health problems than those whose houses were not damaged 16 years after the earthquake (Oishi et al., 2015). This was true even after controlling for the socioeconomic status at the time of the earthquake (see also Burger & Palmer, 1992; Tiefenbach & Kohlbacher, 2015; Uchida, Takahashi, & Kawahara, 2014). Similarly, previous studies showed that people’s adaptation to a major negative event such as divorce and widowhood is not complete (see Diener, Lucas, & Scollon, 2006; Luhmann, Hofmann, Eid, & Lucas, 2012, for review). For instance, 8 years after the death of their spouses, widows and widowers were less satisfied with their lives than before their spouses got seriously ill (Lucas, Clark, Georgellis, & Diener, 2003). However, the studies on major life events suffer from unmeasured third-variable problems. The difficulty of examining the role of a natural disaster as well as divorce and widowhood is that it is impossible to conduct a randomized controlled experiment because these events cannot be randomly assigned
to participants. Thus, the best possible method to study the effect of a natural disaster is a natural experiment, in which roughly half of the participants are exposed to the “treatment” and the other half are not, and that the assignment is close to as-if randomly assigned (see Dunning, 2012, for various examples in social sciences). This study took advantage of the coincidental timing of a nationally representative survey conducted around March 11, 2011, the day the Northern Japan suffered great earthquakes (Magnitude 9.0) and tsunami that killed over 15,000. Roughly half of the respondents happened to complete the survey before March 11, 2011, whereas roughly half of the respondents completed it after March 11, 2011. Because respondents who completed the survey before March 11, 2011, did not know that the large earthquake would hit the Northern part of Japan, this created a so-called natural experiment. The difference between respondents who completed before and those who completed after the earthquake is kept minimal by the random event (here the earthquake). Of course, one might expect that those who completed the survey earlier should be higher in conscientiousness and education than those who completed it later.
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Department of Psychology, University of Virginia, Charlottesville, VA, USA The Economist Intelligence Unit, Tokyo, Japan
Corresponding Author: Shigehiro Oishi, Department of Psychology, University of Virginia, P.O. Box 400400, Charlottesville, VA 22904, USA. Email:
[email protected]
2 Fortunately, the survey included the brief measure of Big Five personality traits as well as demographic variables. Thus, we were able to statistically control for personality differences and demographic variables, making these 2 groups fairly equivalent with the exception of the key variable, the devastating earthquake. Another advantage of the current study over many studies on hedonic adaptation is that we were able to capture daily fluctuations in the life satisfaction of respondents. In contrast, most hedonic adaptation studies had intervals of years, as they used ongoing or biannual surveys (e.g., Lucas et al., 2003; Oishi et al., 2015; see however, Holman, Silver, Mogle, & Scott, 2016, for a longitudinal study with shorter intervals). Thus, it is difficult to discern how quickly people react and adapt to a major event such as an earthquake. Our data shed light on a more precise time course of adaption to a major earthquake. Although there is no study on a precise time course of adaptation to a major earthquake, there are several relevant studies on terrorism and mass shootings that report a precise time course. For instance, a study that analyzed the diaries of 1,084 US bloggers spanning the 2 months prior to and after the September 11 attacks found that the bloggers used more negative emotions, cognitive words (e.g., think, because), and socially oriented words, such as friend, talk, share, and personal pronouns other than “I,” right after the attacks (Cohn, Mehl, & Pennebaker, 2004). However, these changes lasted only 2 weeks. A recent study on the 2012 Sandy Hood Elementary School shooting found that the tweets about the incidence decreased substantially within a month of the shooting, so did the words associated with sadness (Doré, Ort, Braverman, & Ochsner, 2015). These studies suggest that life satisfaction after the earthquake will be likely to return to the before-earthquake level within 1 or 2 months. The survey was mainly concerned with consumers’ attitudes toward new technology and consumer products, although it also included life satisfaction and a brief Big Five measure. Based on previous research on hedonic adaptation to a major natural disaster (e.g., Oishi et al., 2015), we predicted that respondents after March 11 would report lower levels of life satisfaction than respondents before March 11. We also hypothesized that their consumerism (attitudes toward purchasing new products) would decrease after the devastating earthquake. This hypothesis is based on the previous finding that those who experienced a major earthquake and a terrorist attack tend to be less ego-centric and more prosocial (Cohn et al., 2004; Li, Li, Decety, & Lee, 2013; Stephens, Hamedani, Markus, Bergsieker, & Eloul, 2009). When faced with many deaths and suffering, people may consider consumerism frivolous. Thus, we reasoned that the post-3-11 respondents would show less desire for new consumer products than the pre-3-11 respondents. Finally, we predicted that their general attitudes toward consumer products (e.g., “products are getting shoddier and shoddier”) and how old their current cell phones are should not be different before and after the major earthquake because they are concerned with concrete targets (e.g., quality of
Social Psychological and Personality Science XX(X) products, age of cell phone) that should not be affected by an earthquake. By examining changes in life satisfaction, consumerism, and generic attitude, we were able to determine how general or specific the effect of an earthquake is.
Method Participants Participants were 1,575 Japanese middle aged to older adults (762 men, 813 women) who responded to the mail surveys. The mean age was 61.03 (SD = 11.90, Range = 40–96). They were sampled using a national probability sampling based on the region, gender, and age. There are eight regions in Japan. The sample size was determined to have sufficient representation from each of the eight regions (1,600 would have roughly 200 respondents per region).
Procedures and Materials The survey questionnaires were sent out initially on February 24, 2011. They were returned between March 1 and May 23, 2011. On April 27, a reminder was sent for those who had not returned the survey. Roughly half of the respondents (N = 792) were likely to have completed the survey before Friday, March 11, 2011 (the survey was returned to the survey company on Tuesday, March 15, 2011, or before), whereas the other half (N = 783) were likely to have completed the survey after March 11, 2011 (the survey was returned on Wednesday, March 16 or later). Thus, this survey was a rare natural experiment, as respondents who completed the surveys before the earthquake had not known that the earthquake would happen soon. The survey questionnaire included several attitudinal questions toward technology uses (e.g., cell phone, computer), consumer behavior, life satisfaction, personality, and demographic questions. For the purpose of our research, we used the 2 consumerism items: “I look forward to purchasing new products” and “I like buying brand-new products” (1 = not at all true, 4 = neither true nor untrue, 7 = definitely true, α = .91). Life satisfaction was assessed with 3 items: satisfaction with life now, satisfaction with life with over the past 1 to 2 years, and satisfaction with life over the past 3 to 5 years (1 = completely dissatisfied, 4 = neither satisfied nor dissatisfied, 7 = completely satisfied). It should be noted that the time frame of past 1 to 2 years and past 3 to 5 years included March 11, 2011, for those who completed the survey after March 11, 2011. Generic attitudes toward technology include “Products are getting shoddier and shoddier,” “Technical terms sound like confusing jargon to me,” and “I have avoided technology because it is unfamiliar to me” on the 7-point scale (1 = strongly disagree to 7 = strongly agree). Big Five personality traits were assessed with Rammstedt and John’s (2007) 10 items on the 7-point scale (1 = strongly disagree to 7 = strongly agree).
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Table 1. Descriptive Statistics of Study 1: Japanese Respondents Who Completed the Survey Before and After March 11, 2011. Key Variables Desire for new products Life satisfaction now Life satisfaction past 1–2 years Life satisfaction past 3–5 years Age Income Education Married Extroversion Neuroticism Conscientiousness Agreeableness Openness to experiences Products shoddier Technical terms jargons Avoid technology Cell phone year
Before 3-11
After 3-11
t-value
d
3.43 (1.55)
3.26 (1.48)
2.20
.11
4.64 (1.23) 4.60 (1.26)
4.37 (1.27) 4.31 (1.26)
4.19 4.44
.21 .23
4.60 (1.28)
4.36 (1.29)
3.74
.19
61.30 3.14 2.48 .74 3.87 4.17 4.50 4.64 4.27
(11.73) (1.73) (1.03) (.44) (.99) (.94) (1.09) (.89) (1.10)
60.76 3.02 2.34 .70 3.66 4.24 4.36 4.67 4.10
(12.07) 0.89 .04 (1.72) 1.33 .07 (1.00) 2.87 .15 (.46) 1.77 .09 (1.04) 3.99 .20 (.97) –1.46 –.07 (1.05) 2.60 .13 (.84) –.85 .04 (1.08) 3.07 .16
3.46 (1.20) 5.06 (1.49)
3.53 (1.21) 5.15 (1.48)
–1.13 –.06 –1.15 –.06
4.30 (1.65) 3.02 (3.21)
4.43 (1.62) 3.16 (3.28)
–1.49 –.08 –.75 –.04
Results Descriptive statistics and effect sizes are shown in Table 1. As predicted, the respondents who completed the survey after March 11, 2011, indicated lower levels of desire to purchase new products than those who completed the survey before March 11, t(1549) = 2.196, p = .028, 95% CI for the mean difference = [.014; .078], d = .11. The event of March 11, 2011, appears to have suppressed the desire for new products. Next, we examined whether respondents’ life satisfaction differed before and after 3-11. In all three time frames, the respondents who completed the survey after 3-11 reported lower levels of life satisfaction: t(1560) = 4.190, p < .001, 95% CI for the mean difference = [.137, .388], d = .21, for life satisfaction now; t(1558) = 4.443, p < .001, 95% CI for the mean difference = [.193, .445], d = .23, for the past 1 to 2 years; and t(1559) = 3.737, p < .001, 95% CI for the mean difference = [.145; .402], d = .19, for the past 3 to 5 years. As predicted, generic attitudes toward technology such as products are getting shoddier and shoddier, or complaints about technical jargons did not differ before and after the earthquake. Also, the age of respondents’ cell phone did not differ before and after the earthquake. Thus, t-tests showed that the differences are fairly specific to desire to purchase new products and life satisfaction.
Regression Discontinuity Design Analyses Although t-tests are intuitive ways to test the overall difference before and after the earthquake, the current data also provide an opportunity to utilize the regression discontinuity design (West,
Figure 1. The regression discontinuity design analysis on life satisfaction now (1 = completely dissatisfied, 7 = completely satisfied). The size of circle is proportional to the number of respondents returned on that day. 0 = March 11, 2011, completed/March 15, 2011, returned. To the left, 1 to 14 days, to the right, +1 to +69 days.
Biesanz, & Pitts, 2000). West, Biesanz, and Pitts (2000) called regression discontinuity design “one of the strongest alternatives to the randomized experiment” (p. 58). Unlike t-tests, regression discontinuity design tests whether an outcome measure (here the level of life satisfaction and desire to purchase new products) indeed precipitously dropped after the event of March 11. Specifically, we regressed life satisfaction on the date that the survey was returned and the discontinuation dummy variable. Because the surveys received by the survey company on or before March 15, 2011 (Tuesday) were likely to be completed before March 11, 2011 (Friday), we centered the date on March 15 (i.e., March 1 = −14, March 2 = −13, March 3 = −12…March 15 = 0, March 16 = 1, March 17 = 3…May 23 = 69). For the discontinuity dummy variable, the surveys completed before March 11 and received on or before March 15 = 0; the surveys completed after March 11 and received on or after March 16 = 1. As can be seen in Figure 1, we find clear evidence of discontinuity, b = −.340, 95% CI [−.508, −.173], SE = .085, β = −.134, t(1559) = −3.987, p < .001. In contrast, the regression slope was flat before the earthquake, b = .003, 95% CI [−.001, .007], SE = .002, β = .046, t(1559) = 1.373, p = .170. That is, life satisfaction of the respondents increased by a .003 everyday until March 11 (or receiving date of March 15), but after March 11, then it decreased by a .340 point on average. We compared the model with the return date only with the model with the return date and the discontinuity variable, using hierarchical regression analysis. The regression model with the return date and the discontinuity variable, F(2, 1559) = 9.391, p < .001, was significantly better than the simple model, F(1, 1560) = 2.856, p = .091, Fchange(1, 1559) = 15.898, p < .001, R2change = .012. We used the same regression discontinuity design model for satisfaction of the past 1 to 2 years. The results were very similar to the aforementioned results, b = −.348, 95% CI [−.517,
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Figure 2. The regression discontinuity design analysis on life satisfaction past 1 to 2 years (1 = completely dissatisfied, 7 = completely satisfied). The size of circle is proportional to the number of respondents returned on that day. 0 = March 11, 2011, completed/ March 15, 2011, returned. To the left, 1 to 14 days, to the right, +1 to +69 days.
−.179], SE = .086, β = −.136, t(1557) = −4.047, p < .001, for the discontinuity variable; b = .001, 95% CI [−.073, .013], SE = .002, β = .017, t(1557) = .513, p = .608, for the preMarch 11 regression slope (see Figure 2). The model with the return date and the discontinuity variable, F(2, 1,557) = 12.382, p < .001, was again significantly better than the simple model with the date of return only, F(1, 1,558) = 8.303, p = .004, Fchange(1, 1557) = 16.380, p < .001, R2change = .014. The results for satisfaction of past 3 to 5 years were also nearly identical, b = −.317, 95% CI [−.489, −.145], SE = .088, β = −.122, t(1558) = −3.618, p < .001, for the discontinuity variable; and b = .002, 95% CI [−.003, .006], SE = .002, β = .025, t(1558) = .749, p = .454, for the pre-March 11 regression slope (see Figure 3). Again, the model with the date of the return and the discontinuity variable, F(2, 1,558) = 8.969, p < .001, was significantly better than the simple model, F(1, 1,559) = 4.814, p = .028, F change (1, 1558) = 13.088, p < .001, R2change = .011. In short, the regression discontinuity model analyses showed that life satisfaction did not differ by the date of the survey returned before the earthquake. However, consistent with our prediction, these analyses showed that life satisfaction did drop significantly by a .317 to .348 point after the earthquake (see Figures 1–3). In contrast, although the t-test showed a significant difference in desire to purchase new products before and after March 11, the regression discontinuity design showed that the drop was not statistically significant, b = −.157, 95% CI [−.360, .047], SE = .104, β = −.051, t(1548) = −1.508, p = .132.
Specificity of the Findings Next, we tested whether our findings were specific to life satisfaction by conducting the same regression discontinuity design model with other variables that one might not expect similar
Social Psychological and Personality Science XX(X)
Figure 3. The regression discontinuity design analysis on life satisfaction past 3 to 5 years (1 = completely dissatisfied; 7 = completely satisfied). The size of circle is proportional to the number of respondents returned on that day. 0 = March 11, 2011, completed/ March 15, 2011 returned. To the left, 1 to 14 days, to the right, +1 to +69 days.
patterns of discontinuity such as age, gender, marital status, education, and household income of the respondents before and after the earthquake. In other words, we tested whether the age, gender, marital status, education, and household income of the respondents who completed the survey after the earthquake were different from those who completed it before the earthquake. As expected, none of these demographic variables showed a significant discontinuity effect after the earthquake: age (t = −.439, p = .660), gender (Wald = .002, p = .966), marital status (Wald = .668, p = .414), education (t = −1.082, p = .279), and household income (t = −1.578, p = .115; see Table 2 for full results). That is, unlike life satisfaction, respondents’ age, gender, marital status, education, and household income did not suddenly change after the earthquake. We also conducted the regression discontinuity design model on personality traits. Here the type of persons who sent in surveys early might be different from those who sent in late. We did find a discontinuity effect for extroversion, b = −.244, 95% CI [−.381, −.107], SE = .070, β = −.118, t(1556) = −3.501, p < .001, but did not find the discontinuity effect for agreeableness (t = .671, p = .502), conscientiousness (t = −1.753, p = .080), neuroticism (t = 1.515, p = .130), or openness (t = −1.315, p = .189, see Table 2 for full results). That is, those who completed the survey before the earthquake were more extroverted than those who completed it after the earthquake. The level of conscientiousness of respondents dropped marginally after the quake, but the level of agreeableness, neuroticism, and openness did not differ between before and after the earthquake. Because the survey was mainly concerned with consumer attitudes and behaviors related to technology, we were also able to check specificity of the discontinuity effect with generic consumer attitudes for which we did not expect to see the discontinuity effect of the earthquake. For instance, we saw no
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Table 2. Regression Discontinuity Design Analyses: A Sudden Change After the Earthquake? Dependent Variables Life satisfaction now Life satisfaction past 1–2 years Life satisfaction past 3–5 years Desire for new products Age Gender* Income Education Married* Extroversion Neuroticism Conscientiousness Agreeableness Openness to experiences Products shoddier Technical terms jargons Avoid technology Cell phone year
B (SE) –.340 –.348 –.317 –.157 –.355 .006 –.193 –.075 –.123 –.244 .099 –.128 .040 –.098 .099 .033 .052 –.038
(.085) (086) (.088) (.104) (.808) (.136) (.122) (.069) (.150) (.070) (.066) (.073) (.059) (.074) (.083) (.102) (.112) (.245)
95% CI [–.508, [–.517, [–.489, [–.360, [–1.941, [.770, [–.432, [–.211, [.659, [–.381, [–.029, [–.272, [–.077, [–.243, [–.063, [–.166, [–.168, [–.518,
–.173] –.179] –.145] .047] 1.230] 1.313] .047] .061] 1.187] –.107] .228] .015] .156] .048] .261] .233] .272] .443]
B –.134 –.136 –.122 –.051 –.015 1.006 –.055 –.037 .885 –.118 .051 –.059 .023 –.044 .041 .011 .016 –.006
t
p
–3.987 –4.047 –3.618 –1.508 –.439 .002 –1.578 –1.082 .668 –3.501 1.515 –1.753 .671 –1.315 1.198 .326 .462 –.153
