1. INTRODUCTION

One explanation for these public-versus-expert risk controversies holds that they are due to the public’s failure to understand the scientific data. They can thus be avoided by communicating technical information more effectively, especially via the mass media. This view is widely shared by technical experts, and is tacitly accepted by much research documenting the public’s low “science literacy.” (Note 6) But studies of the link between technical knowledge and support for controversial technologies show mixed results.(2–14)

In stark contrast to the “knowledge breeds support” view is the argument advanced by Mazur that the more technical information the media provide about a risk controversy (e.g., nuclear power), the more concerned the audience will be, even if the information is thought by experts to be reassuring.(15,16) Merely by mentioning potential problems, the coverage may make those problems seem more likely. A third possibility is that technical information in the mass media might interact with other attributes of the news story to affect risk perceptions. For example, technical detail might make a story more credible, thus heightening the alarm from an alarming story, while confirming the reassurance of a reassuring story. One test of this hypothesis found no such interaction; it also found no direct effect of technical detail on readers’ alarm or reassurance.(17)

A competing set of explanations for public-versus-expert risk conflicts holds that the public responds less to the seriousness of a risk (or its knowledge about seriousness as obtained from the media) than to such factors as trust, control, fairness, and courtesy. Sandman,(18–20) Hance et al.,(21,22) and Sandman et al.(23) have proposed the labels “hazard” and “outrage” to refer, respectively, to the technical and the nontechnical aspects of risk. Using different vocabulary, many others have also noted and studied the importance of these nontechnical aspects of risk perception, among them Kasperson,(24) Bord,(25) Krimsky and Plough,(26) Johnson,(27) Covello et al.,(28) Covello and Allen,(29) and Slovic.(30)

In Sandman’s terminology, “hazard” is the product of risk magnitude and probability, while “outrage” is a function of whether people feel the authorities can be trusted, whether control over risk management is shared with affected communities, etc. Supporters of this distinction argue that hazard and outrage are both components of risk deserving attention, and that laypeople have had as little success communicating what they consider significant about risks to the experts as the experts have had communicating to the public. No matter how serious the risk is (in hazard terms), and no matter how much technical detail is used to explain it, this view maintains that the degree of outrage is likely to determine much of the public’s response to the risk.

The predominant strategy in much research on risk perception has been to ask people to rate the riskiness of an assortment of hazards, and then to rate the same hazards on several other attributes thought by the investigators to be related to risk perception. Factor analysis or other statistical analysis of the ratings then reveals relationships between risk perception and the hazard attributes under investigation. This methodology omits the social context in which risk judgments are made, although we know that judgments about risk in the abstract can be very different from judgments about specific, personally relevant risk situations.(5, 31,32) Furthermore, when large numbers of risk ratings are factor-analyzed much can be learned about the sources of risk perception, but the imputation of causality is unjustified. Finally, some factors in risk perception, including important outrage variables, are so tied to situations that they simply cannot be studied from lists of hazards. Anecdotal discussions of agency–community and company–community interactions usually focus on such factors as trust, power-sharing, respect for community concerns, openness to community suggestions, and promptness and completeness in releasing risk information. (Note 7) Because they are not characteristics of the hazard itself, but rather of an agency’s or company’s approach to managing the hazard, most of these factors have been difficult to study via the riskiness-ratings methodology.

There are legitimate reasons, of course, why most studies of risk perception have not been experimental. (There are exceptions, of course; see Slovic.)(33) We cannot experimentally manipulate the attributes of existing hazardous substances, activities, and technologies. Ethics and logistics prevent exposing people to hazards varied systematically by attribute — nor do the environmental problems facing communities cooperate by differing one attribute at a time.

Simulation is one way to take advantage of the inferential power provided by experimental research to study situational variables. In the three studies reported here, an effort was made to create hypothetical hazard situations realistic enough to elicit risk judgments like those that would occur with actual hazards. All three studies examine the same central hypothesis, that manipulation of the reported behavior (in a hypothetical news story) of the organization managing a risk controversy will lead to variations in subjects’ outrage, and therefore to variations in the perceived seriousness of the risk. (Note 8) In the third study, moreover, the outrage effect is experimentally compared with the effects of manipulating hazard seriousness and amount of technical information provided in the story. (Note 9)

2.  STUDY ONE ^{(Note 10)}

2.1. Method

The study questionnaire asked for judgments about the seriousness of the risk on a 6-point scale (1 = no risk at all; 6 = very serious risk). Next, it asked how trustworthy the agency spokesman seemed (1 = very trustworthy; 4 = not trustworthy at all) and whether the spokesman appeared to be withholding important information (1 = definitely is; 4 = definitely not). The fourth question presented a list of words describing how someone might feel if he or she lived in the community described: angry, helpless, frightened, safe, alarmed, relieved, concerned, pleased, confused, and annoyed. Subjects could choose as many items as they liked to describe how they thought they would feel. Finally, the “incinerator” story questionnaire asked whether the facility should be built (1 = definitely yes; 4 = definitely not). Each questionnaire concluded with demographic items. Extensive pilot testing with college students and nonstudents ensured that none of the situations was viewed as presenting risks so high or so low that ceiling or floor effects would make it impossible to observe differences between versions.

Subjects were a cluster sample of adult residents of single-family homes in East Brunswick, New Jersey, a middle-income to upper-middle-income suburban community. Research assistants went door-to-door to recruit individuals. Only adults at least 18 years of age (one person per household) were eligible to participate. People who agreed were given two news stories, one on the “barrels” and one on the “incinerator,” and a stamped envelope addressed to the “Environmental Information Project” at Rutgers University. All four combinations of the outrage manipulation were used: high on the first story and high on the second, high-low, low-high, and low-low. The two stories appeared in random order. Subjects were asked to read the stories and send back the questionnaire in the next day or two. In order to lower refusal rates, subjects’ names and addresses were not requested. This meant, however, that reminders could not be used to increase response rates from those who agreed to take part.

2.2. Results

Analyses of variance in the data on seriousness, trustworthiness, and secrecy were done for each story separately, using the variables outrage (high or low) and story reading order (first or second). Emotion checklists were compared by Fisher’s exact test. Story reading order showed no main effects or interactions with outrage, and is not discussed further. Table I shows the outrage manipulation results.

The two “barrels” stories produced significantly different perceptions of agency trustworthiness and secrecy, as intended, as well as significant differences in anger, confusion, and annoyance. However, the perceived seriousness of the risk was only marginally greater in the high-outrage condition (P < .08 (Note 12)). The “incinerator” stories were less successful in producing different ratings for trust, secrecy, and emotional responses, and yielded no significant difference in perceived seriousness.

Correlations between trust and perceived seriousness were .61 and .62 for the “barrels” and “incinerator” stories, respectively (P’s < .0001). Correlations between perceived agency secrecy and perceived seriousness were .53 and .63 for the two stories (P’s < .0001). These high correlations suggest (but do not demonstrate) that a stronger manipulation of trust and secrecy might have had more impact on risk perception.

3.   STUDY TWO ^{(Note 13)}

3.1. Method

Only one story was used, a revision of the one dealing with barrels of chemical waste. This story was selected because it had been much more successful in creating different perceptions of trust and openness than the story about the incinerator.

The questions on perceived risk seriousness, agency trustworthiness, and withholding of information were unchanged from Study One. The checklist of emotions retained only the choices of angry, frightened, safe, concerned, annoyed, and alarmed.

The key change in procedure is that study participants were not permitted to review the story when answering the questions. Subjects were also asked to complete the questionnaire immediately instead of returning it by mail.

The story was revised to increase the differences between the two versions. In Study One, the two versions did not diverge until the third paragraph, and even then the differences required careful reading. In the excerpts in Display 1, the low-outrage condition is on the left.

The two versions used for Study Two (Display 2), by contrast, show their differences earlier and more obviously. Once again, the low-outrage condition is on the left.

Note that in Study One, “outrage” was operationalized solely in terms of agency communication behavior thought likely to generate an outraged response. In Study Two, by contrast, the high-outrage version also presented subjects with an explicitly outraged community, while the low-outrage version showed the community to be calm and cooperative. Study Two stories thus included two kinds of reported behavior: of the agency spokesperson and of neighborhood residents. (Such “person in the street” reactions to government statements are typical of news stories on environmental issues.) These two sets of behaviors may have joint, separate, or even offsetting effects on risk perception — but it is useful to determine whether outrage in general affects risk perception before designing studies to tease apart its constituents.

3.2 Results

4. STUDY THREE ^{(Note 15)}

4.1. Method

4.1.1. Manipulations

The seriousness manipulation varied the estimated toxicity of perchloroethylene, the estimated exposures resulting from the spill, and the number of people exposed. It is appropriate to multiply these sources of variation to get the overall difference in seriousness (not necessarily perceived seriousness) between the two treatments: The high-seriousness condition was about five orders of magnitude (a hundred thousand times) worse than the low-seriousness condition. The technical detail manipulation consisted of several additional paragraphs of information on exposure pathways and toxicological studies, absent in the low-technical detail condition and present in the high-technical detail condition.

The outrage manipulation was more extreme than in Study One, but much less extreme than in Study Two, with its arguably unrealistic depiction of agency behavior in the high-outrage condition. As in Study Two, reported community outrage, not just the agency spokesperson’s behavior, was manipulated, but the manipulations were less extreme. Four typical paragraphs appear in Display 3; the low-outrage condition is on the left.

The study focused on two questions: the extent to which agency behavior and community outrage increase people’s risk perception of low-risk events, and the extent to which technical detail decreases people’s risk perception of low-risk events. The outrage and technical detail manipulations were presented at both low and high levels, in a 2 x 2 design, with seriousness kept low. In addition, a fifth high-seriousness condition was included (with outrage and technical detail both kept low) to assess the magnitude of outrage and technical detail effects compared to seriousness effects.

4.1.2 Instrument

Three response measures were used to assess perceived risk — one affective, one cognitive, and one behavioral. Once again, 6-point Likert-type scales were used, with a “no opinion” option as well. Subjects were asked: “If you lived in the area, how worried would you be about the risk from the PERC spill?” (WORRY); “How important do you consider the risk posed by this situation?” (IMPORTANT RISK); and “If you lived in the area, how willing would you be to spend $500 to have your water tested for PERC after the spill?” (INTENTION TO TEST).

WORRY and IMPORTANT RISK correlated +.72, but the correlations between WORRY and INTENTION TO TEST and between IMPORTANT RISK and INTENTION TO TEST were both only +.21, statistically significant but small. Although SERIOUS RISK was originally conceived as a check on the seriousness manipulation, correlations between SERIOUS RISK and WORRY and between SERIOUS RISK and IMPORTANT RISK were +.65 and +.67, respectively. WORRY, IMPORTANT RISK, and SERIOUS RISK were therefore collapsed into a single index variable called PERCEIVED RISK, with INTENTION TO TEST, the behavioral measure, kept separate. Combining WORRY, IMPORTANT RISK, and SERIOUS RISK into a composite index provided a more reliable (coefficient = .78) and therefore more sensitive response measure.

Two pilot studies for Study Three (using university student subjects and just the high-high-high and low-low-low treatments) had shown that a general measure of risk aversion was significantly related to the risk perception response measures, and that use of risk aversion as a covariate improved the sensitivity of the analysis. Four items developed by Weinstein(31,38) were therefore included to assess subjects’ risk aversion. Each item consisted of a statement about environmental risk with which subjects were asked to rate their agreement or disagreement on 7-point Likert-type scales. Choices ranged from very strongly disagree to very strongly agree; statements were phrased so that low ratings indicated acceptance of risks and high ratings indicated risk aversion.

As in Weinstein’s studies,(31,38) two dimensions of risk aversion — SOCIETAL RISK AVERSION and PERSONAL RISK AVERSION — were assessed, using two items each. A risk aversion score was derived for each dimension by adding the ratings for the two items measuring that dimension. The SOCIETAL RISK AVERSION items asked subjects about their agreement with two statements: “The public has the right to demand zero pollution from industry” and “An industry that pollutes should not be allowed to stay open, no matter how little pollution it produces.” The PERSONAL RISK AVERSION items measured people’s agreement with two statements: “If there was even the slightest amount of asbestos in my home, I would remove it” and “I try to avoid all food additives and preservatives.” Although the two risk aversion variables turned out to have a + .54 correlation, their correlations with other variables in the study had quite different patterns, justifying the decision to keep them separate.

Data on three demographic variables, SEX, AGE, and EDUCATION, were also collected.

4.1.3. Subjects and Procedures

Using a prepared script, trained interviewers obtained a cluster sample, canvassing every home in an identified area. To make sure the sample was balanced by age and sex, interviewers alternated the type of subject asked for at the door between oldest/youngest (over 18) and male/female. Half of the subjects received the story, then the six-item survey instrument, and finally the risk aversion/demographic questionnaire; the other half received the risk aversion/demographic questionnaire first, then the story, then the survey instrument. No order effects were found, and this variable will not be discussed further. All subjects were asked to return the story before receiving the survey, to prevent them from rereading the story in search of the “right” answers.

4.2. Results

4.2.1. Effects of Outrage

Table III. Response Measure Means, Standard
Deviations, and Significance Tests for Mean
Differences Between Outrage Conditions (Study Three)

Variable	Low   Outrage	High   Outrage	Mean  difference	F-value significance
Perceived risk
(Mean) (SD) (N)	13.42 3.30 254	14.18 3.06 245	0.76	F(1,495) = 6.99 **
Intention to test
(Mean) (SD) (N)	3.16 1.77 240	3.36 1.81 233	0.20	F(1,469) = 1.51 NS
Perceived appropriateness
(Mean) (SD) (N)	3.71 1.28 254	2.50 1.42 245	-1.21	F(1,495) = 99.79 ****
Perceived detail
(Mean) (SD) (N)	3.69 1.25 254	3.30 1.39 245	-0.39	F(1,495) =10.61 **
*P < .05; **P < .01; ***P < .001; ****P < .0001.

As predicted, outrage had a significant, if small, effect on PERCEIVED RISK (P < .01). (Note 18) Subjects who read high-outrage stories saw the risk as more important, serious, and worrisome than did those who read low-outrage stories. Outrage did not significantly affect INTENTION TO TEST, however.

An interesting and unexpected finding was the small but significant effect of outrage on PERCEIVED DETAIL. (Note 19) Subjects who read high-outrage stories judged that they had significantly less technical detail than subjects who read low-outrage stories (P < .01). As we shall see, the actual amount of technical detail in the stories had no significant effect on PERCEIVED DETAIL. This suggests that if an agency or company behaves satisfactorily otherwise, people tend to judge that it is providing enough information as well, while if its behavior is improper or offensive the information given is more likely to be thought insufficient. Perhaps “outrageous” agency behavior makes people distrust the technical detail coming from the agency, or distracts them from the detail actually present, or makes them require more detail then they would have required had agency behavior been more responsive.

4.2.2. Effects of Technical Detail

The technical detail manipulation was intentionally kept within the range of journalistic possibility. More extreme variations might be more visible to readers, and have more impact on their risk perceptions. (And more extreme variations are feasible in other formats, such as brochures or interpersonal interactions.) But within the range tested, variation in technical detail had no effect on PERCEIVED RISK, INTENTION TO TEST, or even PERCEIVED DETAIL. (Note 20)

4.2.3. Effects of Seriousness

Mean ratings for SERIOUS RISK were marginally higher in the high-seriousness condition than in the low-seriousness condition (the difference between the means was less than a third of a standard deviation, P < .05). (Note 21) The manipulation worked, in other words, but just barely; subjects who read a news story reporting a substantially more serious risk perceived it to be slightly more serious than those who read the low-risk news story. Note that subjects in the two pilot studies accurately reported exposure, toxicity, and related factors to be higher when they were in fact higher (P’s < .0001). Thus, the small effect of manipulated seriousness on perceived seriousness probably is not due to any failure to detect the manipulation. Rather, people apparently see the seriousness of a risk as more than the outcome of such factors as exposure and toxicity. The high correlations of SERIOUS RISK with WORRY and IMPORTANT RISK, which led to its inclusion in the PERCEIVED RISK composite index variable, underscore the point. The seriousness manipulation had no effect on WORRY, IMPORTANT RISK, or PERCEIVED RISK, nor on INTENTION TO TEST.

Mean ratings of PERCEIVED APPROPRIATENESS were somewhat lower in the high-seriousness than in the low-seriousness condition, a result also significant at P < .05. In other words, when the risk reported was more serious, subjects saw the agency’s behavior as less appropriate than when the risk was lower. Though this finding was not predicted, it is not surprising that people should expect more from the agency when the risk is more serious, and thus find the same agency behavior less acceptable in the high-seriousness condition. (Note 22) The objective risk, in short, has less effect on the public’s perception of risk than it has on the public’s perception of agency response.

4.2.4. Regression Analyses of the Response Variables

Both models found significant multiple correlations between response measures and predictor variables, with the strongest relationship for PERCEIVED RISK (adjusted R² = .25, P < .0001). This is not a strong relationship; clearly many factors other than those measured in this study affect PERCEIVED RISK. The relationship for INTENTION TO TEST was still weaker (adjusted R² = .14, P < .0001).

The patterns of prediction were substantially different. For PERCEIVED RISK, the strongest predictor in terms of uniquely contributed variance was SOCIETAL RISK AVERSION (about 7% of the variance, P < .001), followed by PERCEIVED APPROPRIATENESS (4% of the variance, P < .001). (Note 23) The higher the SOCIETAL RISK AVERSION and perceived outrage (lower PERCEIVED APPROPRIATENESS of the agency response), the higher was the PERCEIVED RISK. In addition, higher PERCEIVED RISK was associated with significantly higher PERCEIVED DETAIL, lower EDUCATION, and female rather than male subjects.

Neither OUTRAGE nor TECHNICAL DETAIL made a significant unique contribution to the variance in PERCEIVED RISK, although their respective manipulation checks, PERCEIVED APPROPRIATENESS and PERCEIVED DETAIL, did. When the two manipulation checks were dropped from the regression analysis, TECHNICAL DETAIL still had no significant unique effect on PERCEIVED RISK. But OUTRAGE then was a significant predictor (P < .05), with a regression coefficient of .10, accounting uniquely for just under 1% of the variance.

For the INTENTION TO TEST variable, only three predictors made significant unique contributions: EDUCATION (7% of the variance, P < .0001), PERSONAL RISK AVERSION (3% of the variance, P < .0001), and PERCEIVED RISK (2% of the variance, P < .01). The more educated and the more averse to personal risk-taking individuals were, the greater their inclination to test. (Note 24) In addition, those who saw the risk in the story as more serious, important, and worrisome (the three components of the PERCEIVED RISK composite index variable) were more inclined to test.

5. Discussion

Study One found a very weak relationship for one news story and none for the other. But the sample was small, the dependent variable was a single question, and the differences between the stories were subtle. There was a strong correlation for both stories between perceived agency trustworthiness and secrecy and the perceived seriousness of the risk. But the outrage manipulation did not strongly affect perceived trustworthiness and secrecy. In Study Two, the sample was larger and the story differences much more extreme. In addition, subjects were not permitted to review the story to determine their answers. Strong relationships emerged between the experimental outrage manipulation and perceived seriousness.

Study Three had a much larger sample and a much more sensitive design, with risk aversion as a covariate and a 3-item index of perceived risk (seriousness, worry, importance). The stories were less obviously different than in the second study, but more so than in the first. Here the outrage manipulation significantly affected perceived risk, though not the one-item measure of intention to test. By contrast, a seriousness manipulation of roughly five orders of magnitude barely affected perceived seriousness and did not affect other components of perceived risk. And experimental manipulation of the amount of technical detail in the story did not significantly affect any dependent variables.

Among the three variables examined in these studies, in other words, outrage was the most powerful in its impact on risk perception. The studies suggest that an agency or company that deals responsively, openly, and respectfully with concerned citizens, and succeeds in avoiding hostile public reactions, is likely to reduce risk perceptions by doing so — much more than by providing technical information or even by reducing the technical risk by several orders of magnitude.

Nonetheless, the regression analysis in Study Three shows that outrage is a significant but by no means a strong predictor of risk perception, much less of self-protective behavior. Education, sex, and risk aversion — all factors beyond the control of the agency or corporate communicator— are more potent still. And all the factors assessed in the research reported here together accounted for relatively small percentages of the variance in perceived risk, and still smaller percentages of the variance in behavioral intentions. Clearly, many other factors, as yet unknown, are at work.

In fact, the outrage manipulation was not significantly related to perceived risk in the regression analysis except when perceived appropriateness was omitted. Whether people consider an agency’s or a company’s behavior outrageous seems to matter a good deal in risk perception. How closely the public’s view of agency behavior tracks actual agency–community interactions remains to be determined.

The use of hypothetical news stories adds three more caveats. Study Three compared effects of outrage as reflected in news stories with technical detail as given in news stories. Other, more personal vehicles might work very differently. People who attend a public meeting, receive an informational brochure, or telephone an agency with questions can acquire far more technical detail than the few extra paragraphs of the high-technical detail condition in Study Three — and they acquire it in a very different setting. Similarly, each of these settings might convey agency responsiveness or unresponsiveness and community acceptance or outrage very differently. The effects of outrage vis-à-vis technical detail and other variables need to be studied in contexts other than newspaper journalism.

The second caveat concerns the fact that the news stories in all three studies were hypothetical. Subjects were asked to imagine that the stories had appeared in their local newspapers and that their own communities were faced with the situations described. It is impossible to say how realistic subjects found these simulations and how realistically they responded to them. It seems likely that the effects of outrage on risk perception were suppressed by the hypothetical nature of the study, while the effects of seriousness and technical detail were more likely augmented — that is, we would expect subjects to be more attentive to data and less liable to outrage in these studies than they would be in a real situation. But no research findings back this supposition.

Finally, real community hazard situations develop over days, months, or even years; the simulations compress these histories into written materials that take only a few minutes to read. Once again, we consider it likely that the distortion is conservative, that prolonged exposure to a risk controversy makes people more responsive to outrage and less responsive to seriousness and technical detail than they were in this research. Yet no studies demonstrate or dispute this point either.

Note also that the research reported here treats outrage as a single variable, though it is in fact a cluster of related — and perhaps not so closely related — variables. (Note 25) Among the factors varied in the hypothetical news stories were agency secretiveness/openness, agency courtesy/contemptuousness, agency responsiveness/unresponsiveness to community input, etc. In Study Two and Study Three, the community’s reported response (angry, suspicious, and frightened or grateful, trusting, and calm) was also varied. These factors are all conceptually distinguishable from one another. Furthermore, Sandman and colleagues have applied the term “outrage” to a far wider range of variables, including less interactional ones like voluntariness, familiarity, dread, and the like.(18–22) To develop a powerful explanatory model of the effects of outrage on risk perception, these variables must be teased apart experimentally (not just through factor analysis of survey data) to measure their effects independently.

Nonetheless, the evidence so far suggests strongly that the outrage cluster (communicator behavior, community response, and the communicator–community interaction) has a substantial impact on people’s perception of risk. As government agencies and corporations struggle to reassure communities about risks that represent small threats to health and environmental quality, much that determines the public response is beyond the risk manager’s control: risk aversion, demographics, etc. But how risk managers interact with communities is very much in their control. Further research is needed to guide this interaction, to help risk managers avoid exacerbating outrage in the public’s response to low-consequence hazards.

Notes

Notes 1 through 5 were old addresses and contact information for the authors, and were deleted from this version.

6.    See Miller,(1) for example.

7.    See for example Refs. 19–22.

8.    Note that the term “outrage,” used strictly, should refer to the public’s response to a risk or to the behavior of risk managers; it should not refer to characteristics of the risk or the management behavior themselves. Nonetheless, throughout this paper the variations in reported agency behavior (open vs. secret, compassionate vs. contemptuous, etc.) will be referred to as the outrage manipulation.

9.    Both the notion that technical information in the media affects audience risk perception and the notion that media “outrage information” affects risk perception share a focus on how journalists approach risk controversies. The research literature on media coyerage of risk is beyond the scope of this article. For a “manual” on how sources attempt to influence risk coverage, see Sandman et al.(34)

10.    This study was conducted by Neil D. Weinstein and Peter M. Sandman. The assistance of Hannah Vo Dinh and Katherine Curcio in collecting the data is gratefully acknowledged. For a more complete analysis and copies of the materials and instrument, see Weinstein.(35)

11.    The study reported here was conducted simultaneously with a study assessing the effects on risk perception of individual vs. societal responsibility for a hazard and of existing vs. newly proposed hazards. Subjects received either one set of materials or the other at random. The data on response rate and demographics apply to the combined samples for the two studies.

12.    All statistical analyses reported in this paper were two-tailed.

13.    This study was carried out by Patrick H. Bivona, David P. Cho, John D’Angelo, and Christine D. Garcia under the direction of Peter M. Sandman. For a more complete analysis and copies of the materials and instrument, see Ref. 35.

14.    It is of course possible that in the high-outrage condition readers were less inclined than in the low-outrage condition to believe the technical information provided by the agency. This replicates a familiar pattern in risk controversies, where the key technical information often comes from sources who are also managing the risk, and whose courtesy, compassion, openness, and the like may determine whether the technical information is accepted. A study in which the risk information came from neutral third parties would be useful.

15.    This study was carried out by Peter M. Sandman, Paul M. Miller, and Branden B. Johnson. Grateful acknowledgement is made to: Caron Chess and Kandice L. Salomone, who provided critical assistance in the development of the news stories and the design and interpretation of two pilot studies; JoAnn M. Valenti, who assisted in the development of the news stories; Neil D. Weinstein, who advised on the development of the instruments; and Jennifer Field, who coordinated the data collection and data entry. An advisory committee at the New Jersey Department of Environmental Protection provided counsel on technical accuracy and realism in the depiction of agency behavior. For a more complete analysis and copies of the materials and instruments used, see Sandman and Miller.(36)

16.    Two pilot studies were conducted, using student subjects and only two versions of the story (high-high-high and low-low-low). Results of the pilot studies led to changes in the text of the story, in the conceptualization of the independent variables, and in the measurement of both independent and dependent variables. For a complete discussion of the pilot study methods and findings, see Ref. 36, pp.15–41.

17.    Cohen(39) and Cohen and Cohen(40) note that the size of an effect can be measured by dividing the difference between the means by the standard deviation; they suggest the convention that a quotient of .2 represents a small effect, .5 is a medium effect, and .8 is a large effect. By this standard, the effect of the outrage manipulation on PERCEIVED APPROPRIATENESS is large.

18.    By the standard suggested by Cohen(39) and Cohen and Cohen(40) (described in the previous note), this effect is small.

19.    This effect, too, would be considered small by the standard of the two previous notes.

20.    See Ref. 37 for a fuller discussion of alternative hypotheses and research topics on technical detail.

21.    See note 17.

22.    There was no high-seriousness high-outrage condition in the study reported here, so it is impossible to determine whether there is an interaction effect of seriousness and outrage. It is conceivable that the failure to prevent a serious risk is seen by many people as inappropriate and outrageous agency performance by definition. Even if the agency handles a high-risk incident superbly, the mere fact that the incident occurred may lead to low PERCEIVED APPROPRIATENESS; this would constitute, in essence, a floor for outrage when seriousness is high.

23.    The unique proportion of variance accounted for by each independent variable was computed from standardized partial regression weights using the formula provided in Cohen and Cohen,(40) p. 483.

24.    It is interesting that SOCIETAL RISK AVERSION was so closely connected to PERCEIVED RISK, while PERSONAL RISK AVERSION played an important role in INTENTION TO TEST. Considering an environmental risk serious, important, and worrisome is apparently tied to values such as corporate environmental accountability. Actually intending to do something about the risk, however, seems to have a closer tie to other self- protective behaviors, such as avoiding food additives and cleaning up home asbestos. To some extent self-protective behavior may be a personal characteristic that cuts across the many distinctions among risks. Radon research, for example, has found a stronger relationship between radon testing and personal risk aversion than between radon testing and societal risk aversion — or, indeed, between radon testing and radon knowledge.(41) See also Wildavsky and Dake(42) for a finding that people with “egalitarian” views were societally more risk-averse than others, but personally tended to be risk-takers.

25.    Note that seriousness and technical detail are also clusters. Seriousness, for example, includes probability, magnitude, exposure, etc. Technical detail includes various sorts of content (detail on exposure, toxicity, epidemiology, etc.), as well as variations in tone, clarity, and the like. See Ref. 37.

Acknowledgments

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8. B. B. Johnson and B. Baltensperger, “Community Risk Perception: A Pilot Study,” in L. B. Lave (ed.), Risk Assessment and Management (New York, Plenum, 1987), pp. 337–344.

9. D. Golding, S. Krimsky, and A. Plough, “Evaluating Risk Communication: Narrative vs. Technical Presentations of Information about Radon,” Risk Analysis 27–35 (1992).

10. A. J. Wyner and D. E. Mann, Seismic Safety Policy in California: Local Governments and Earthquakes (Report to the National Science Foundation, Washington, D.C., U.S. Department of Commerce, 1983).

11. B. B. Johnson, “Advancing Understanding of Knowledge’s Role in Lay Risk Perception,” RISK: Issues in Health and Safety 189–212 (1993).

12. F. R. Johnson and A. Fisher, “Conventional Wisdom on Risk Communication and Evidence from a Field Experiment,” Risk Analysis 209–213 (1989).

13. N. D. Weinstein and P. M. Sandman, “A Model of the Precaution Adoption Process: Evidence from Home Radon Testing,” Health Psychology 170–180 (1992).

14. N. D. Weinstein and P. M. Sandman, “Predicting Homeowners’ Mitigation Response to Radon Test Data,” Journal of Social Issues 63–83 (1992).

15. A. Mazur, “Media Coverage and Public Opinion on Scientific Controversies,” Journal of Communication 106–115 (1981).

16. A. Mazur, “Nuclear Power, Chemical Hazards, and the Quantity of Reporting,” Minerva 294–323 (1990).

17. K. L. Salomone, News Content and Public Perceptions of Environmental Risk: Does Technical Risk Information Matter After All? (New Brunswick, New Jersey, Environmental Communication Research Program, 1992).

18. P. M. Sandman, “Risk Communication: Facing Public Outrage,” EPA Journal 21–22 (1987).

19. P. M. Sandman, “Risk = Hazard + Outrage: A Formula for Effective Risk Communication” (videotape) (Akron, Ohio, American Industrial Hygiene Association, 1991).

20. P. M. Sandman, Responding to Community Outrage: Strategies for Effective Risk Communication (Fairfax, Virginia, American Industrial Hygiene Association, 1993).

21. B. J. Hance, C. Chess, and P. M. Sandman, Improving Dialogue with Communities: A Risk Communication Manual for Government (Trenton, New Jersey, Division of Science and Research, New Jersey Department of Environmental Protection, 1988).

22. B. J. Hance, C. Chess, and P. M. Sandman, Industry Risk Communication Manual (Boca Raton, Florida, CRC Press/Lewis Publishers, 1990).

23. P. M. Sandman, N. D. Weinstein, and M. L. Klotz, “Public Response to the Risk from Geological Radon,” Journal of Communication 93–108 (1987).

24. R. E. Kasperson, “Six Propositions on Public Participation and Their Relevance for Risk Communication,” Risk Analysis 275–281 (1986).

25. R. J. Bord, “Public Cooperation as a Social Problem: The Case of Risky Wastes” (Annual Meeting of the American Association for the Advancement of Science, February 14–18, 1987, Chicago).

26. S. Krimsky and A. Plough, Environmental Hazards: Communicating Risks as a Social Process (Dover, Massachusetts, Auburn House, 1988).

27. B. B. Johnson, “Accounting for the Social Context of Risk Communication,” Science and Technology Studies 103–111 (1987).

28. V. T. Covello, P. M. Sandman, and P. Slovic, Risk Communication, Risk Statistics, and Risk Comparisons (Washington, D.C., Chemical Manufacturers Association, 1988).

29. V. T. Covello and F. W. Allen, “Seven Cardinal Rules of Risk Communication” (U.S. Environmental Protection Agency, Washington D.C., April 1988).

30. P. Slovic, “Perception of Risk,” Science 280–285 (1987).

31. N. D. Weinstein, Public Perception of Environmental Hazards: Attitudes of the Public and the Department of Environmental Protection Toward Environmental Hazards (Trenton, New Jersey, Division of Science and Research, New Jersey Department of Environmental Protection, 1989).

32. L. Sjöberg, “Perceived Risk, Risk Object, and Perceived Control” (annual meeting of the Society for Risk Analysis, December 6–9, 1992, San Diego).

33. P. Slovic, “The Role of Trust in Risk Perception and Risk Management” (annual meeting of the Society for Risk Analysis, December 6–9, 1992, San Diego).

34. P. M. Sandman, D. B. Sachsman, and M. R. Greenberg, The Environmental News Source: Providing Environmental Risk Information to the Media (New Brunswick, New Jersey, Environmental Communication Research Program, Rutgers University, 1992).

35. N. D. Weinstein, “Simulation Studies of Hazard Perception” (Division of Science and Research, New Jersey Department of Environmental Protection, Trenton, New Jersey, March 1, 1989).

36. P. M. Sandman and P. M. Miller, “Outrage and Technical Detail: 'The Impact of Agency Behavior on Community Risk Perception” (Division of Science and Research, New Jersey Department of Environmental Protection, January 1991).

37. B. B. Johnson, P. M. Sandman, and P. M. Miller, “Testing the Role of Technical Information in Public Risk Perception,” RISK — Issues in Health and Safety 341–364 (1992).

38. N. D. Weinstein, Public Perception of Environmental Hazards: Statewide Poll of Environmental Perceptions (Trenton, New Jersey, Division of Science and Research, New Jersey Department of Environmental Protection, 1987).

39. J. Cohen, Statistical Power Analysis for the Behavioral Sciences, 2nd. ed. (Hillsdale, New Jersey, Lawrence Erlbaum, 1988).

40. J. Cohen and P. Cohen, Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences, 2nd. ed. (Hillsdale, New Jersey, Lawrence Erlbaum, 1983).

41. N. D. Weinstein, P. M. Sandman, and N. E. Roberts, Public Response to the Risk from Radon, 1988-1989 (Trenton, New Jersey, Division of Environmental Quality, New Jersey Department of Environmental Protection, November 1989).

42. A. Wildavsky and K. Dake, “Theories of Risk Perception: Who Fears What and Why?” Daedalus (Fall 1990), pp. 41–60.

Peter M. Sandman 59 Ridgeview Rd. Princeton NJ 08540-7601	Phone: 1-609-683-4073 Fax: 1-609-683-0566 Email: peter@psandman.com
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