Longitudinal Study before and after the Fukushima Disaster. Vivianne H. M. Visschers* Michael Siegrist. ETH Zurich

Transcription

1 1 How a Nuclear Power Plant Accident Influences Acceptance of Nuclear Power: Results of a Longitudinal Study before and after the Fukushima Disaster Vivianne H. M. Visschers* Michael Siegrist ETH Zurich Intitute for Environmental Decisions (IED), Consumer Behavior Zurich, Switzerland * Address correspondence to Vivianne Visschers, ETH Zurich, Institute for Environmental Decisions, Consumer Behavior, Universitaetsstrasse 22 CHN J75.2, CH-8092 Zurich, Switzerland. Tel , Fax , vvisschers@ethz.ch.

2 2 Abstract Major nuclear accidents, such as the recent accident in Fukushima, Japan, have been shown to decrease the public s acceptance of nuclear power. However, little is known about how a serious accident affects people s acceptance of nuclear power and the determinants of acceptance. We conducted a longitudinal study (N = 790) in Switzerland: one survey was done five months before and one directly after the accident in Fukushima. We assessed acceptance, perceived risks, perceived benefits, and trust related to nuclear power stations. In our model, we assumed that both benefit and risk perceptions determine acceptance of nuclear power. We further hypothesized that trust influences benefit and risk perceptions and that trust before a disaster relates to trust after a disaster. Results showed that the acceptance and perceptions of nuclear power as well as its trust were more negative after the accident. In our model, perceived benefits and risks determined the acceptance of nuclear power stations both before and after Fukushima. Trust had strong effects on perceived benefits and risks, at both times. People s trust before Fukushima strongly influenced their trust after the accident. Additionally, perceived benefits before Fukushima correlated with perceived benefits after the accident. Thus, the nuclear accident did not seem to have changed the relations between the determinants of acceptance. Even after a severe accident, the public may still consider the benefits as relevant, and trust remains important for determining their risk and benefit perceptions. A discussion of the benefits of nuclear power seems most likely to affect the public s acceptance of nuclear power, even after a nuclear accident. Keywords: nuclear accident, Fukushima, longitudinal study, acceptance, social trust

3 3 1. INTRODUCTION On March 11, 2011, an enormous earthquake and its subsequent tsunami devastated the cooling systems of the Fukushima Daiichi nuclear power plant in Japan. As a result, vapor, cooling water, and explosive particles with radioactive elements were released or leaked from three reactors into the environment. The authorities decided to evacuate people living in a 30km radius around the power plant, and a 20km zone was declared a no-go area. The International Atomic Energy Association calculated the nuclear accident to be at level 7 on the International Nuclear and Radiological Event Scale (INES), this being the highest level. (1) Soon after the accident, discussions about the safety and future of nuclear power plants began in many countries around the world. Previous research shows that a major accident at a nuclear reactor strongly affects laypeople s attitudes toward nuclear power (e.g., refs. 2-4). The accident in Japan provided an opportunity to test additional hypotheses that have not been addressed in previous research regarding the effect of a nuclear accident on public perception. In a longitudinal study that included two waves, we examined how the accident at the nuclear power plant in Fukushima changed people s trust, their perceptions of benefits and risks, and their acceptance of nuclear power in the German-speaking part of Switzerland Public Perception of Nuclear Power after a Nuclear Accident After the accidents at the nuclear power plants in Chernobyl in 1986 and on Three Mile Island (TMI) in 1979, a large number of studies investigated people s attitudes toward nuclear power. Some studies compared laypeople s opinions of nuclear power before and after the disasters by comparing the findings of different samples both over time (5-7) and between countries. (8, 9) Additionally, a few longitudinal studies investigated attitudes assessed before and

4 4 after the catastrophic events, thus using the same sample of respondents. (2-4) These studies will be discussed in more detail below. Also, a few polls in the USA and Europe monitored the public s opinion of nuclear power (see refs for overviews). We are, of course, aware of the fact that a large number of studies have been conducted to investigate people s attitudes and acceptance of nuclear power stations and related facilities, as well as the determinants of these opinions (e.g., refs ) This introduction, however, concentrates on studies that intended to examine the effect of a nuclear accident on the public s opinion of this energy technology. Even though opinion polls revealed that the public s support for nuclear power had been decreasing since the mid-1970s in Europe and the US, (5, 10, 12) the two previous nuclear accidents (5, 7, seemed to have had additional negative impacts on people s attitudes toward nuclear power. 10, 11, 19-21) Hence, these nuclear accidents accelerated the decline in public support of nuclear power. Several studies investigated possible determinants of the more negative attitudes resulting from the nuclear accidents (e.g., refs. 8, 9, 20, 21). In countries that were exposed to higher radiological doses after Chernobyl, people s attitudes toward nuclear power became more negative than those of people in countries in which the exposure levels were lower. (9) Thus, the extent to which a nuclear accident challenged previous beliefs about nuclear power appeared to affect people s attitudes. A study in Sweden examining various specific groups (e.g., farmers, parents, and adolescents) showed that perceived risks of nuclear power were important predictors of people s nuclear power evaluation. (20) However, only negative consequences were included in this study; positive issues, such as perceived benefits of nuclear power, were not considered. A study conducted in the US after TMI included an assessment of the expected benefits of a new, local nuclear power plant and an assessment of its expected risks in order to explain the acceptance of

5 5 this new plant. (21) Additionally, respondents were asked to estimate the influence of the accident at TMI on their acceptance of the new plant. Both expected risks and expected benefits influenced acceptance of the local plant. The self-reported influence of TMI affected expected risks to a larger extent than did expected benefits. However, a self-reported measure of TMI influence is prone to biases, which may have indirectly resulted in perceived risks having a larger influence than perceived benefits. In a study that compared perceptions of nuclear power before and after Chernobyl between two different samples, indications of slightly higher risk perceptions were found after Chernobyl (though only among students) compared to before. (6) More interestingly, after the accident, people reported higher levels of dread, more knowledge about the risks of nuclear power, and a smaller degree of perceived severity of a nuclear accident. The latter was probably a result of increased knowledge about the number of casualties Previous Longitudinal Studies Regarding a Nuclear Accident To the best of our knowledge, only three studies have examined the impact of a nuclear accident on laypeople s perception of nuclear power while using a longitudinal, within-subjects design that is, including a survey before the accident and one survey or several surveys after the accident. (2-4) Following Menard, (22) we define a longitudinal study as a study that measures the same variables in the same respondents at two or more time points. All three previous longitudinal studies were conducted before and after the Chernobyl accident. Verplanken (3) was able to follow 154 Dutch people before and after Chernobyl (one month after and, again, six months after), measuring their attitudes and beliefs regarding nuclear power. A third follow-up survey was done nineteen months after the event, which included 103 respondents from the original sample. Although nuclear attitudes had become significantly more

6 6 negative directly after the accident compared to before the accident, they almost returned to pre- Chernobyl levels six months after the accident. However, nineteen months after the accident, public opinion again became more negative, perhaps due to widespread media coverage. Moreover, one-and-a-half years after the event, the accident appeared to increase respondents perceived probability of a nuclear accident occurring and to decrease their benefit perception of nuclear power. The correlations between nuclear attitudes and perceived risks and perceived benefits appeared strong at all times. However, the relation between people s nuclear power attitudes and their perceived probability of a serious nuclear accident occurring had become even stronger by the time the last measurement was completed, nineteen months after the accident. An increased risk perception may explain the increase in negative attitudes after one-and-a-half years compared to those attitudes held directly after the nuclear catastrophe. Nevertheless, Verplanken (3) did not examine the causal relation between risk perception and nuclear attitudes. The second longitudinal study regarding Chernobyl was conducted in England. (4) It consisted of pre- and post-incident measurements of public opinion taken around the time of the nuclear accident/. The measurements included 135 inhabitants of a town close to a nuclear power plant and residents who did not live far from an onshore oil installation. Acceptance of nuclear power stations was compared to that of oil wells, coal power stations, and other industrial plants. After Chernobyl, respondents showed less acceptance of nuclear power, whereas acceptance of the other plants had not changed. Moreover, Eiser and colleagues (4) related post-chernobyl attitudes toward nuclear power to acceptance, perceived risk from a hypothetical nuclear power station at various distances, respondents attention to news about the nuclear accident, and their level of fear evoked by this news. Prior negative nuclear attitudes were associated with a decrease in acceptance after the accident, more attention being paid to the news, and higher levels of fear

7 7 being felt about this news after the accident. Respondents risk perception was not influenced by their distance to the hypothetical nuclear plant. Another longitudinal study was done in the northwest of the USA in a town near a nuclear power plant. (2) The area was affected by a plume from Chernobyl that contained small amounts of radioactive material. The study included a survey five months before Chernobyl and a second survey one month after the accident. After the accident, the 69 respondents perceived fewer personal health effects, such as cancer, from the local nuclear power plant, although they were more occupied with the topic of nuclear power than they had been before the accident. Neither their perceived likelihood nor their perceived dread of a nuclear accident had changed since the incident. Midden and Verplanken (23) observed that attitudes toward nuclear power and beliefs about the consequences of nuclear power were not stable between several measurement points during the two years after the accident at Chernobyl. However, the authors could not compare these beliefs and attitudes to those before the accident. In sum, only a few studies investigated the effects of a nuclear accident using a longitudinal design. The two European full-longitudinal studies noted above found that people s views of nuclear power stations became more negative after the Chernobyl catastrophe. (3, 4) However, the attitude changes were relatively small. All three full-longitudinal studies could only compare acceptance of nuclear power between the two measures. (2-4) The possible determinants of acceptance, such as attitudes and beliefs, were only assessed after the catastrophe. Moreover, the studies had small sample sizes, ranging from less than 70 to 150 respondents Current Situation Since the accidents in Chernobyl and on TMI, a few developments have taken place in the

8 8 areas of science, society, politics, and the environment as part of a nuclear renaissance, i.e., a revival of nuclear energy production. (24) First, the political climate has changed. In the 1980s, during the Cold War, nuclear power came to be associated with atomic weapons and nuclear war. (10) People s fears about the latter may have affected their opinions of nuclear power stations. A study conducted in 2009 showed that Swiss people mainly associated nuclear power with energy. (25) In comparison, its associations with risks, accidents, and military use were much less frequently reported. Second, the need to reduce CO 2 emissions to mitigate climate change contributed to a more positive perception of nuclear power. (26) The influence of nuclear power s climate benefits on laypeople s acceptance appeared significant but relatively low. (27) A third, more important factor that seemed to drive the nuclear renaissance was the perceived economic benefits of nuclear power (e.g., ref. 27) A country with nuclear power plants can be less dependent on other countries, has a secure energy supply, and produces relatively cheap and sufficient energy to meet the needs of increasing energy consumption. Moreover, the total costs (including the environmental burden) of nuclear power appear to be much lower than those of fossil fuel power plants in Switzerland, such that nuclear power has come to be perceived as a cheap, green alternative. (28) These factors resulted in a more favorable public opinion about nuclear power in Switzerland and elsewhere before the accident in Fukushima. Whereas only 49% of the US population favored the use of nuclear power for electricity generation in 1983, this percentage increased to 74% in (29) Similarly, the number of Europeans who accept nuclear power seemed to have increased lately. Within the 27 EU member states, for example, the number of people supporting the expansion of nuclear power has recently increased (from 14% in 2006 to 17% in 2009), whereas the percentage of Europeans opposing nuclear power had decreased (from 39% in 2006

9 9 to 34% in 2009). (30) Since people s attitudes recently have been more in favor of using nuclear power compared to those in the 1970s and 1980s, a nuclear catastrophe may have less influence on the public s opinion of nuclear power compared to 25 years ago. It could be that although people do recognize the risks and negative consequences, the perceived benefits for the climate and for a secure energy supply are still the main determinants of people s acceptance. The nuclear accident in Fukushima provided an opportunity to examine this question. 2. RATIONALE AND MODEL The general aim of our study was to investigate the effect of the nuclear accident in Fukushima on people s perception and acceptance of nuclear energy in Switzerland. More specifically, we examined how this event affected the degree to which trust, perceived benefits, and perceived risks influenced people s acceptance of nuclear power stations. Thus, our main construct under investigation was people s acceptance of nuclear power stations before and after the accident in Japan. Therefore, acceptance of nuclear power stations before and after Fukushima were the latent variables to be explained in the model, which is presented in Fig.1. Previous research suggests that both risk and benefit perceptions determine acceptance of nuclear power. (27, 31) Furthermore, people s perceived benefits of a secure energy supply seem to have a stronger influence on acceptance than do perceived risks. (27) Little is known, however, about the stability of risk and benefit perceptions over time (see also refs. 2, 23). Therefore, it is unknown how a severe accident changes the impact of risk and benefit perceptions on acceptance of nuclear power. After a nuclear accident, perceived risks may be more important to acceptance of nuclear power compared to perceived benefits. In line with this explanation, Hughey and Sundstrom (21) found that after the accident at TMI, laypeople s acceptance of a new local nuclear

10 10 power plant was determined mainly by their hazard expectations and less by the expected benefits. We hypothesized that in 2010, before the nuclear accident, perceived risks of nuclear power would have a small, negative effect on acceptance (path a in Fig. 1), while perceived benefits would more strongly influence acceptance of this energy source (path b in Fig. 1). We further expected, as in the case of gene technology, (32, 33) that there would exist a causal path from perceived benefits to perceived risks (path c in Fig. 1). Perceived benefits are thought to influence perceived risks, and not the other way around, because the benefits of nuclear power, such as energy production and the lack of CO 2 emissions, are concrete and known. The benefits, therefore, result in a clear evaluation. The risks, though, are mostly vague and difficult to imagine for laypeople. For example, many people do not know the exact impact and probability of radioactive leakage. This unclear idea regarding the risks makes their perception easy to modify for cases in which they have conflicting beliefs about nuclear power. (34) That is, if people perceive that there are many benefits to nuclear power, they can easily reduce their perception of risks so that the conflict is solved. (Insert Fig. 1 about here) People seem to rely on social trust to assess risks and benefits if they have little knowledge of the technology or hazard. (35) They then assume that their level of trust in specific actors will provide a good indication of the risks and benefits of the technology. (36) Trust in the actors managing a hazard or technology has been found to be an important determinant of the perceived risks and benefits of various technologies and hazards, (36, 37) as well as that of nuclear energy. (17, 27, 37-40) Laypeople reported having relatively little knowledge of nuclear power in previous studies. (35, 41) Therefore, we hypothesized that in 2010, trust in the actors involved in nuclear

11 11 power was negatively related to perceived risks (path d in Fig. 1) and positively related to perceived benefits (path e in Fig. 1). After the accident in 2011, we expected a similar relation between risk perception, benefit perception, and acceptance of nuclear power stations. Thus, the same model explains laypeople s acceptance of nuclear power after the accident (paths f, g, and h in Fig. 1). Trust is a crucial variable that determines people s interpretation such accidents. (35, 42) Thus, we hypothesized that in 2011, trust would be important for determining risk perception (path i in Fig. 1) and benefit perception (path j in Fig. 1) because people rely on trust to interpret the accident. (43) In other words, for determining trust, value information seems to be more important than performance information. (43) Because values are relatively stable within individuals, we expected that trust in 2011 is strongly related to trust in 2010 (path k in Fig. 1), although the performance information may have reduced people s trust in the nuclear power industry and regulatory agencies after the nuclear accident. As shown in Fig. 1, we further presumed that risk and benefit perceptions, as well as acceptance, are not correlated across the two measurement points after controlling for trust. Besides testing the model presented in Fig. 1, we examined the mean changes of the main constructs included in the model. Based on the studies done after the two previous nuclear accidents, (2-4, 10) we expected that people s acceptance of nuclear power stations in Switzerland, their benefit perceptions, and their trust would decrease after the Fukushima nuclear accident, whereas perceived risks would increase. 3. METHOD 3.1. Procedure and Sample Data were collected in two waves. The first survey was conducted more than five months

12 12 before the earthquake and tsunami in Japan, at the end of September We sent a paper-andpencil questionnaire together with a stamped and addressed return envelope to a random sample of households in the German-speaking part of Switzerland. A computer program had randomly selected the sample from telephone directories. After four weeks, a reminder was sent to the addresses from which we had not received a completed survey. This was repeated after three weeks. In the end, we received 1,233 questionnaires (a response rate of 40%). The same group of respondents was asked to fill out a shorter version of the previous questionnaire two weeks after the catastrophic event, at the end of March This second survey was sent to the 1,233 addresses from the first survey. We sent one reminder to non-respondents after three weeks. In total, 929 questionnaires were returned (a response rate of 77%). In the instructions for the second survey, recipients were explicitly informed that the person who completed the first survey should also fill in the new survey. We reminded the respondents that their data from the previous survey and those of the new survey were anonymous and that only anonymized datasets were linked. We asked for each respondent s birth year and gender in order to match the datasets of the two surveys. Datasets with different birth years or genders were deleted. After omitting cases missing more than 20% of their data as well as cases with two or more missing data regarding the dependent variable acceptance of nuclear power stations, the dataset included 790 respondents, from which the analyses described in this paper were done Questionnaire The 2010 survey was about people s perceptions of nuclear power stations in Switzerland and included items regarding ten different constructs and demographics. Four constructs are of importance here: acceptance of nuclear power stations, risk perception, benefit perception, and trust. Each construct was measured with three items (see Table I for the items, their mean scores,

13 13 and their standard deviations). The items were assessed on 7-point Likert scales, with higher scores indicating higher values on the construct measured. The shorter questionnaire, filled out after the accident in Japan, contained the same items in order to assess acceptance of nuclear power, risk perception, benefit perception, and trust. In addition, we included two items that assessed respondents perceived similarity between the situations in Japan and Switzerland regarding nuclear accidents (e.g., It is very likely that a similar nuclear accident could happen in Switzerland ). (Insert Table I about here) 3.3. Data Analysis To be able to apply structural equation modeling (SEM) to our data, we had to replace any missing data in our data set. Forty-six respondents (5.8%) did not answer all of the survey questions that were identical in the two waves (24 items; see Table 1). Of the respondents with missing data, most of them missed one item (3.4% of the sample) or three items (1.3% of the sample). Using SPSS 18.0, we applied the Expectation-Maximization (EM) algorithm, based on the maximum likelihood approach, to replace missing values. The values of the items in the respective construct were used to estimate the missing values. We first tested the explanatory model of acceptance of nuclear power in 2010 and the explanatory model of acceptance of nuclear power in We then tested the full model presented in Fig. 1. All models were analyzed using structural equation modeling (SEM). SEM is a statistical analysis procedure that tests the fit between a hypothesized model and a data set. It combines confirmatory factor analysis, used to validate the measurements of latent factors, with regression analysis, which examines the paths between latent factors. Moreover, SEM can simultaneously examine several structural relations between latent constructs. Parameters were

14 14 estimated using the maximum likelihood method in the Analysis of Moment Structures program (AMOS) version We conducted a confirmatory factor analysis to check the quality of the constructs. All factor loadings (λs) were substantial (λs >.67) and significant, given that the critical ratios of all variables (i.e., the variable estimate divided by its standard error) were larger than 1.96 (ps < 0.05). The items thus represented their constructs well enough to be included in our model. In the full model, we correlated the error terms corresponding to the identical latent-factor measurements across time in order to get reliable estimates of the regression paths. (44) Error terms for the same measurements namely tend to correlate when they are assessed among the same sample across time, which is, of course, the case in our longitudinal study. For example, the measurement error of an item that belongs to the latent factor perceived risks in 2010 is related to the measurement error of the identical item in The factor loadings and the correlations between the error terms of the indicator variables are, for the sake of simplicity, not shown in Figures 1 and 3. Because our sample was relatively large, significant chi-square tests were insufficient for assessing the model s goodness of fit. Therefore, we used the comparative fit index (CFI), the standardized root mean square residual (SRMR), and the root mean square error of approximation (RMSEA) as criteria for our model. (45) All three statistics have value ranges between 0 and 1. A large SRMR indicates a poorly fitting model, whereas a SRMR smaller than.08 signifies a model that fits well to the data. For the RMSEA, a value equal to or smaller than.06 indicates a close fit. A CFI value equal to or over.95 indicates a good fit (see ref. 45 for an overview of the fit indices and their cut-off values). All these fit indices are descriptive; they are based not on inferential statistics but on rules of thumb to determine goodness of fit.

15 15 Additionally, we looked at the theoretical background of the model as a criterion for the fit of the model. (46) To see whether the model could be improved by including other relations between the constructs, we compared the theoretical background and the modification indices (MIs) with their respective expected parameter change (EPC). The values of the MIs indicate whether relations between certain items, latent constructs, and error terms could be included as these are likely to improve the model fit. We used the difference in χ² to test the improvement of the new model. 4. RESULTS 4.1. Respondents The mean age of our final sample of 790 respondents was years (SD = 15.02), and 67.2% (n = 531) of the respondents were male. Most respondents had finished vocational school (n = 324, 41.7%) or college or university (n = 242, 31%). Almost 19% of the sample had completed up to a higher secondary school level (n = 147), and 8.5% had only finished the country s obligatory school levels (n = 66). Our sample was older, included more men, more people with a college or university degree, and fewer people who had only finished obligatory (47, 48) school than was representative of the average Swiss population. We compared the respondents who participated in both surveys to those who had only completed the survey in 2010 (i.e., the non-respondents in the 2011 survey). Of the 304 nonrespondents, 287 cases remained after deleting those missing more than 20% of the 2010 data. The gender distribution was similar among respondents and non-respondents (χ²(1) =.12, p =.73). Non-respondents were slightly younger (M = 53.55, SD = 16.37) than respondents (M = 57.15, SD = 15.02), t(1,071) = -3.37, p =.001, r =.10. Also, respondents had a somewhat higher education level (18.6% with a higher-secondary-school education and 30.6% with a college- or university-level education) than non-respondents (13.6% with a higher-secondary-school

16 16 education and 26.1% with a college- or university-level education), U = 98,079.50, p =.01, r = Non-respondents showed more acceptance of nuclear power (M = 4.55, SD = 1.77) than respondents (M = 4.26, SD = 1.95), t(555.49) = 2.25, p =.03, r =.10. Non-respondents also perceived fewer risks from this technology (M = 3.57, SD = 1.47) than did respondents (M = 3.84, SD = 1.66), t(539.67) = -2.59, p =.01, r =.11. The respondents and non-respondents did not differ regarding perceived benefits and trust, ts < 1.77, ps > Acceptance of Nuclear Power Stations, Perceived Risks, Perceived Benefits, and Trust before and after Fukushima As can be seen in Table II, respondents acceptance of nuclear power stations in 2010 was around the midpoint of the 7-point rating scale, and it significantly decreased after the nuclear accident. Both perceived benefits and trust decreased significantly after the events in Japan. Respondents level of risk perception significantly increased after the nuclear accident. However, the sizes of the differences (i.e.,.79 at maximum for perceived risks, measured on 7-point Likert scales) between the two surveys indicate that respondents had not completely changed their views on nuclear power. Moreover, respondents saw the situation in Japan regarding nuclear power stations as being relatively similar to the situation in Switzerland, given that the mean perceived similarity was slightly above the midpoint of the 7-point scale (M = 4.54, SD = 1.85). (Insert Table II about here) 4.3. Separate Models for Explaining Acceptance of Nuclear Power Stations before and after the Nuclear Accident The model for explaining acceptance of nuclear power stations before the nuclear accident fit quite well to our data (χ²(49) = , p =.0001, CFI =.984, SRMR =.027, RMSEA =.052). The standardized regression weights of the paths were all significant and in the hypothesized

17 17 directions (ps <.001). However, the modification index (MI) between the two error terms of the items trust in science and trust in the Federal Office of Energy (FOE) in 2010 indicated that including the correlation between these two error terms in our model would result in a substantial improvement of our model fit. People probably see scientists and the FOE as independent actors with respect to nuclear power stations, and their independence may have a large role in people s trust evaluation of both actors; hence, our respondents rated them similarly. It therefore made sense to include the correlation between the two error terms in our 2010 model. As a result, the model fit indeed improved (χ²(48) = , p =.0001, CFI =.990, SRMR =.019, RMSEA =.041), which was found to be statistically significant (Δχ²(1) = 41.81, p < 0.001). All paths were significant (p <.001) and had similar directions and sizes of influence compared to our initial model, described above. Fig. 2 presents the final 2010 model, including the standardized coefficients (in regular font) but without the factor loadings. In 2010, perceived risks and perceived benefits explained 90% of the variance of acceptance of nuclear power stations. Perceived benefits had the largest influence on acceptance, and risk perception had a smaller negative relation to acceptance. Trust had a strong positive influence on perceived benefits in 2010 and a negative influence on perceived risks. As well, perceived benefits had a negative influence on perceived risks. The squared multiple correlations (SMCs) were substantial for perceived benefits (SMC =.59) and perceived risks (SMC =.79). (Insert Fig. 2 about here) The same model also explained well the data collected after the nuclear accident in Japan (χ²(49) = , p =.0001, CFI =.970, SRMR =.033, RMSEA =.075). The MIs again indicated that the correlation between the error terms of the items trust in science and trust in the FOE in 2011 would increase the model fit. We therefore tested a new model that included the correlation

18 18 between these two error terms. This, too, improved the model fit significantly (χ²(48) = , p =.0001, CFI =.979, SRMR =.026, RMSEA =.064, Δχ²(1) = 67.11, p < 0.001). In 2011, perceived benefits and perceived risks also largely contributed to the explained variance of acceptance of nuclear power stations (SMC =.94). Perceived benefits again had a strong positive influence on acceptance (see Fig. 2, standardized coefficients in bold font), whereas perceived risks had a smaller, negative effect on acceptance. Trust had a positive influence on perceived benefits and had a negative influence on perceived risks. Perceived benefits contributed negatively to perceived risks. The explained variances were again substantial for perceived benefits (SMC =.66) and perceived risks (SMC =.85) The Full Model In our SEM analysis of the full model (Fig. 1), we immediately included the correlations between the error terms of the items trust in the FOE and trust in science in 2010 and The hypothesized model fit quite well to our data (χ²(227) = , p =.0001, CFI =.968, SRMR =.053, RMSEA =.052). The standardized regression weights of the paths were all significant and in the hypothesized directions (ps <.001). The MIs suggested that including the path between perceived benefits in 2010 and perceived benefits in 2011 would substantially improve the model. This inclusion also made theoretical sense because the benefits of nuclear power remained the same; the nuclear accident had not affected them. People therefore relied on the perceived benefits before the nuclear accident in order to estimate the benefits after such an event. Including the path between the perceived benefits in 2010 and 2011 did result in a model that fit better to the data (χ²(226) = , p =.0001, CFI =.980, SRMR =.031, RMSEA =.042) and was found to be statistically significant (Δχ²(1) = , p < ). The combination of the explanatory models for 2010 and 2011 explained 95% of the variance regarding acceptance of

19 19 nuclear power plants in The SMCs of acceptance in 2010, trust in 2011, and perceived risks and perceived benefits in 2010 and 2011 were substantial (.61 < SMC <.92). The MIs did not suggest including any other relations that would substantially improve the model fit. Table I presents the standardized factor loadings of the individual items on the latent constructs in the final model. The correlations between the error terms corresponding to the identical latent factor measurements in 2010 and in 2011 ranged between.04 and.34. The direction of the paths described in the separate models remained the same in the full model (see Fig. 3). Additionally, perceived benefits in 2010 had a positive influence on perceived benefits in Similarly, trust in 2010 was strongly related to trust in When comparing the regression path between perceived risks and acceptance in 2010 to that of 2011, it looks as if perceived risks had a stronger influence on acceptance after the nuclear accident compared to before. We checked whether these paths were indeed significantly different by, first, restraining the two paths between perceived risks and acceptance in 2010 and in 2011 in a new model and then comparing the quality of the new model to that of the unrestrained model. (49) If the influence of risk perception on acceptance in 2011 was indeed larger than that in 2010, fixing these two paths should result in a significantly worse-fitting model. The new model with the two restrained paths had a good fit to the data (χ²(227) = , p =.0001, CFI =.980, SRMR =.031, RMSEA =.042), but the restrained model did not result in a statistically significantly worse-fitting (or better-fitting) model compared to the unrestrained model (Δχ²(1) = 1.92, p =.17). This result seems to indicate that the impact of risk perception on acceptance in 2010 was already similar to that in 2011 in the unrestrained version of the full model. (Insert Fig. 3 about here) In sum, 95% of the variance in our respondents acceptance of nuclear power stations after

20 20 the accident in Fukushima could be explained by their risk perception and benefit perception after the accident. The model suggests that there is both a direct effect of trust in 2011 and an indirect effect of trust in 2010 on perceived risks and benefits in Both before and after the nuclear accident, perceived benefits had the strongest influence on acceptance of nuclear power stations, compared to perceived risks. 5. DISCUSSION There is a lack of longitudinal studies in the domain of risk-perception research. Therefore, little is known about how technological accidents influence people s risk perception and acceptance of various technologies. The accident at Fukushima provided an opportunity to conduct a quasi-experimental study. A random sample of laypeople who participated in a survey about nuclear power in autumn 2010 answered the same set of questions about trust, perceived risks and benefits, and acceptance of nuclear power after the accident in Japan. In our model, we predicted that trust is a key factor, one that directly influences risk perception and benefit perception and that indirectly influences acceptance of nuclear power. Furthermore, we hypothesized that trust before the accident had a significant effect on trust after the accident. Our model explained the data very well. In the following paragraphs, we will first discuss the effect of the nuclear accident on people s perceptions and acceptance of nuclear power. We will then elaborate further on the role of trust concerning the acceptance of nuclear power stations. We will also suggest a few implications of our findings for risk communication about nuclear power stations. Lastly, we will provide some critical remarks about our study. To recap, our respondents reported higher levels of risk perception and lower levels of trust, perceived benefits, and acceptance regarding nuclear power plants after the nuclear accident

21 21 compared to before. Our findings, thus, seem to indicate that the nuclear accident in Fukushima resulted in a more negative perception of nuclear power and, hence, had important implications for the image of this energy technology among the public, at least in the short term. However, the influences of the determinants of acceptance risk perception, benefit perception, and trust seemed to remain stable over time. It is therefore very likely that because perceived benefits and trust decreased and perceived risks similarly increased, the acceptance of nuclear power plants also decreased. Past studies have shown that for gene technology, (32, 33) nanotechnology, (50) and nuclear power, (27) perceived benefits have a stronger impact on acceptance of the respective technology than do perceived risks. The present study not only appears to replicate this finding but also suggests that after a severe accident, the importance of perceived risks increases somewhat, although perceived benefits remain a more important predictor of acceptance. Thus, people may consider nuclear power s benefit for the energy supply and for a healthy economy to be more important to their acceptance of it than the possible risks that are associated with it. It may come as a surprise that risk perception appeared to have a smaller influence as benefit perception on acceptance of nuclear power stations after learning about the nuclear accident. Studies conducted after Chernobyl and TMI pointed toward the importance of risk perception on attitudes toward nuclear power. (20, 21) In our model, we were able to compare the influence of risk perception on acceptance to that of benefit perception, which showed that the impact of perceived risks had not changed much after the Fukushima accident and that perceived benefits remained the strongest predictor of acceptance. An explanation for these findings could be that our respondents had already acknowledged the risks of nuclear power before the nuclear accident and they therefore did not differ much in their risk perception both before and after the nuclear

22 22 accident. Alternatively, our respondents varied more regarding their benefit perception. Perceived benefits could therefore make a larger contribution toward explaining acceptance than could perceived risks. This finding is supported by findings from previous studies. Proponents of nuclear power have been found to be more ambivalent about this technology, seeing both its benefits and risks, and therefore have a less stable attitude toward nuclear power than opponents. (23) Moreover, people have been found either to have both positive and negative images about nuclear power or to have only negative images, but hardly any person reports only positive images. (51) Even proponents seem to acknowledge some risks of nuclear power. (25) Next to perceived benefits, social trust continued to be an important determinant in our full model. It influenced risk and benefit perceptions directly and, therefore, acceptance of the technology, though indirectly. Also, the high correlation between trust in 2010 and trust in 2011 seems to confirm the fundamental role of trust in risk perception, benefit perception, and acceptance. After the nuclear accident, the direct influence of trust on perceived benefits appeared smaller than before the nuclear accident. This was caused by the additional path between the perceived benefits at the two measurement times; thus, trust in 2010 not only influenced perceived benefits in 2011 through trust in 2011 but also through the connection between perceived benefits in 2010 and perceived benefits in These findings support the idea that trust remains fundamental to risk and benefit perceptions, even when new information about the hazard is available. The importance of trust is also in line with the Trust, Confidence, (36, 42) and Cooperation (TCC) model, which distinguishes between trust and confidence. According to this model, confidence is determined by past performance and competence, whereas social trust is determined by value similarity. The disaster in Japan, which can be viewed as past performance information, reduced people s trust. The reduction was rather small, however, given

23 23 the severity of the accident, which may imply that it is not performance information but value similarity that influenced people s trust. The second survey took place right after the accident. Future studies are needed in order to examine changes in trust over time. It is possible that the more time that passes after an accident, the less effect the accident will have on trust and, as a result, on acceptance of nuclear power. The findings of our longitudinal study seem to imply that even after a nuclear accident, perceived benefits remain the most important determinant of acceptance, compared to perceived risks. An implication of this finding for communication with the public after a nuclear accident may be that focusing on both the risks and benefits of nuclear power will change the public s acceptance of nuclear power. However, only concentrating on the risks will not significantly affect the public s opinion. In comparison, discussions about the benefits of nuclear power such as a secure energy supply or the lack of benefits, for that matter, are more likely to change people s acceptance of nuclear power. (27) Politicians in various countries reacted in different ways to the accident in Japan. In France and the USA, politicians did not reconsider nuclear power, whereas in Germany and Switzerland, politicians quickly abandoned their support of nuclear power. The public s change in opinion after the accident, however, did not appear to be extreme. As in previous studies, (3, 4) our respondents did not seem to change their attitudes about nuclear power drastically. Therefore, politicians should not react too quickly by changing nuclear policy on behalf of the public. Our study was a longitudinal survey, so we had the benefit of being able to follow changes in the perception and acceptance of nuclear power stations within the same sample of people. Our study, however, also had a few limitations. The first was that the second survey was sent out two weeks after the earthquake and tsunami in Japan. People may not have been able to form a firm

24 24 opinion about nuclear power stations so quickly after the event. The situation at the power plants in Fukushima was not stable at that time, so laypeople may have had the idea that a catastrophic event such as an explosion was still likely to occur or, conversely, that the problems in the reactors would soon be solved. This uncertainty may have resulted in attitudes and beliefs that are more negative or unstable than if the situation had been stabilized. If we had postponed the second measurement for a few weeks, our results may have been different (cf. ref. 3). Consequently, it would be interesting to follow our sample over time to examine these people s perceptions of nuclear power after the accident has ceased being in the news. It can be speculated whether and how public perception changes in the long term. It could be that the public s view of nuclear power remains more negative than it was before the accident, as was found after the Chernobyl accident in a Dutch study. (3) Verplanken suggested that due to this accident, the public was better able to imagine the occurrence of extremely unlikely events, such that the perceived risks of nuclear power remained high after Chernobyl. Alternatively, the public could return to the view of nuclear power that it had held before the Fukushima accident. Media coverage about the accident became less intense: the number of hits for the term Fukushima in the Swiss version of Google News was reduced to 612 hits six months after the event compared to about 11,500 hits four weeks after the accident. This reduction could have limited people s access to mental images about nuclear accidents (cf. ref. 3). Also, Swiss people may have readjusted their attitudes a few months after the accident by realizing that the physical consequences of the accident had happened far away and that the local situation was safe. (52) This latter effect may, of course, only apply to populations not directly affected by the nuclear accident in Fukushima. Another critical remark about our study is that we may not have included all relevant

25 25 determinants of nuclear power acceptance. For example, attitudes toward nuclear power have also been found to be related to fairness (15) and to concerns about climate change and the environment. (18) Also, our trust measure may not have comprised all relevant actors. As we wanted to investigate the role of social trust in our model, we assessed trust in three specific actors that are relevant for the management of nuclear power stations in Switzerland: the operators of the nuclear power stations, nuclear scientists, and the Swiss Federal Office of Energy (FOE). Nevertheless, the high factor loadings of all three items both before and after the nuclear accident seem to indicate that the three items are highly related and that they provide a good representation of the social trust construct. Similarly, we cannot explain the underlying cause of the decrease in public acceptance of nuclear power and its related concepts. As was the case regarding the previous nuclear accidents, media coverage was high, (53) and the public s view of this technology became more negative directly after the events in Fukushima. (3, 4) The study did not allow for an investigation of the influence of media on the effects we found. More research is therefore needed to fully understand what caused the increase in a negative view of nuclear power after the nuclear accident at Fukushima. An advantage of our study was that we could investigate changes in the perception of nuclear power within the same subjects. However, a disadvantage of our longitudinal survey was that we lost a number of respondents in the second wave. Consequently, our sample became older and better educated. Moreover, for some points, respondents views about nuclear power were less positive than those of non-respondents. In short, it could be that our final sample was less representative of the Swiss population than our initial sample, which may have affected our outcomes. When we compared the 2010 model that included the initial sample to the 2010 model

26 26 that included only respondents who had completed both surveys, the directions and strengths of the paths, as well as the explained variances, were similar in both models. Furthermore, because our final sample was more critical of nuclear power before Fukushima than was the complete 2010 sample, we may have underestimated the relations in our model. Particularly, we would expect that the influence of perceived benefits on acceptance of nuclear power stations to be larger, whereas the influence of perceived risks on acceptance would be smaller in a more representative sample, i.e., a sample with more respondents who were positive about nuclear power before the nuclear accident. One could criticize that the study was conducted in Switzerland. Switzerland is, of course, quite far from Japan. It may be that people in countries closer to Japan responded differently to the nuclear accident. Moreover, the Swiss energy situation may be different from that of other countries such that the survey results cannot be generalized to other countries. Switzerland depends on nuclear power stations for about 40% of its power generation. Three of the currently running reactors should be replaced by 2020 to maintain the same energy supply. By the time we conducted the second survey, the decision to postpone all applications for new nuclear power reactors had just been made (March 14, 2011). However, our finding that benefit perception mainly determined people s acceptance of nuclear power stations, both before and after the nuclear accident, is in line with the results of previous studies that showed the overwhelming influence of benefit perception on acceptance of other technologies. (31, 33) Therefore, we believe that our results can be generalized to other countries. In sum, our study is one of the few longitudinal studies that investigated the public s acceptance of nuclear power before and after a nuclear accident. We believe that it represents a major contribution to the limited knowledge available about this subject. After the nuclear

27 27 accident, the public s acceptance and perceptions of nuclear power stations as well as its trust in the stakeholders had become more negative. Nevertheless, our explanatory model did not show a shift in the importance of the relations between the constructs that explained people s acceptance of nuclear power stations. Therefore, a nuclear accident, although catastrophic for the people living near the plant and for the environment, does not appear to result in radical changes in the influences of perceived benefits, perceived risks, or trust on the acceptance of this technology. ACKNOWLEDGEMENT The first survey reported in this paper (conducted in 2010) was funded by Swissnuclear. Swissnuclear comprises representatives of the Swiss electric supply companies (Alpiq, Axpo, BKW, CKW and EGL), which are committed to the safe and economic operation of the nuclear power plants in Switzerland.

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34 34 Table I. Questionnaire Items per Scale in 2010 and 2011, Including their Mean Values (and Standard Deviations) and Standardized Factor Loadings in the Final Model M (SD) Standardized M (SD) Standardized Items per scale a Acceptance factor loadings factor loadings 1. Switzerland needs a lot of electricity; people should therefore accept nuclear 4.05 (2.25) (2.12).92 power stations. 2. Switzerland can renounce nuclear power stations without any problems. b 4.59 (2.13) (2.11) We need nuclear power stations in Switzerland because renewable energy 4.15 (2.21) (2.14).88 sources alone do not produce sufficient electricity. Perceived risks 4. I am very concerned about the dangers of nuclear power stations in 4.12 (1.98) (2.01).66 Switzerland. 5. The nuclear power stations that are built now or in the near future are safe. b 3.75 (1.89) (2.00) The catastrophe risks in new nuclear power stations are very small. b 3.63 (1.88) (2.01).85

35 M (SD) Standardized M (SD) Standardized Items per scale a Perceived Benefits factor loadings factor loadings 7. New nuclear power stations will protect Switzerland from an electricity 4.63 (2.06) (2.11).80 bottleneck. 8. The electricity price would become too high in Switzerland if the existing 4.24 (1.94) (1.99).77 nuclear power stations were not be replaced. 9. Industry would still have a secured energy supply without replacing the 4.24 (1.92) (1.97).80 existing nuclear power stations. b Trust 11. in scientists in the field of nuclear power (1.65) (1.77) in the Swiss Federal Office of Energy (1.58) (1.61) in the operators of nuclear power stations (2.00) (1.89).90 a All items were measured on 7-point Likert scales, with increasing scores indicating higher values on the item. b Item was recoded.

36 36 Table II. Means and Standard Deviations of the Four Constructs in 2010 and 2011, and Results of Paired-Samples t-tests between the Measurements in 2010 and M SD M SD t df Acceptance * 789 Perceived risks * 789 Perceived benefits * 789 Trust * 778 * p <.001. Note. All items measured on 7-point Likert scales.

37 37 FIGURE CAPTIONS. Fig. 1. Our Hypothesized Explanatory Model of Laypeople s Acceptance of Nuclear Power Stations before and after the Fukushima Disaster. Fig. 2. Results of Structural Equation Modeling Explaining Laypeople s Acceptance of Nuclear Power Stations before (Values in Regular Font) and after (Values in Bold Font) the Nuclear Accident in Japan, Including the Standardized Regression Weights and Squared Multiple Correlations (SMCs). Fig. 3. The Final Model Explaining Laypeople s Acceptance of Nuclear Power Stations before and after Fukushima, Including the Standardized Regression Weights and Squared Multiple Correlations (SMCs).

38 38

39 39 Note. All standardized regression weights are significant, p <.001. Standardized regression weights in regular font refer to data beforee the nuclear accident (2010), while values in bold font refer to data collected after the nuclear accident (2011).

40 Note. All standardized regression weights are significant, p <