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Journal of Risk Research

ISSN: 1366-9877 (Print) 1466-4461 (Online) Journal homepage: http://www.tandfonline.com/loi/rjrr20

‘Ambivalent’ individual preferences towardsbiotechnology in the European Union: products orprocesses?

Joan Costa‐Font Corresponding author & Elias Mossialos

To cite this article: Joan Costa‐Font Corresponding author & Elias Mossialos (2005)‘Ambivalent’ individual preferences towards biotechnology in the European Union: products orprocesses?, Journal of Risk Research, 8:4, 341-354, DOI: 10.1080/1366987042000275091

To link to this article: http://dx.doi.org/10.1080/1366987042000275091

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‘Ambivalent’ individual preferences towards

biotechnology in the European Union: products or

processes?

J O A N C O S T A - F O N T *

LSE Health and Social Care, London School of Economics and Political Science, Houghton Street, London WC2A2AE, UK and Departament de Teoria Economica, Universitat de Barcelona, Barcelona, Spain

E L I A S M O S S I A L O S

LSE Health and Social Care, London School of Economics and Political Science, Houghton Street, London WC2A2AE, UK

Abstract

Significant ambivalence is found when examining the explanatory dimensions of attitudes towards

biotechnology in the European Union; individuals’ decision—making is influenced by their percep-

tion of significant benefits and risks as well as moral concerns. In quantitatively analyzing the

determinants of attitudes, we argue that it might be misleading to interpret attitudes towards newbiotechnology applications without taking into account the existence of significant ambivalence in

revealed preferences. This paper empirically examines the magnitude and the impact of

ambivalence in explaining support for two specific biotech applications (Genetically Modified

(GM) food and GM medicines). The data employed are from the 1999 Eurobarometer Survey

52.1. Results reveal that although between 35 and 45% of respondents display ambivalent attitudes

towards biotechnology applications, ambivalence primarily affects less supportive attitudes, and

this result seems robust among specific biotech applications. Ambivalence is expected to continue

to play a key role in determining individual attitudes as long as available information continues tobe limited. Furthermore, ambivalence, as well as attitudes to biotechnology applications, seems to

be associated with the dimensions of the technology itself. Therefore, in the design of risk

communication policies, decision makers should ensure that individuals are well informed if public

perceptions are to be taken into account in public policy formation.

KEY WORDS: ambivalence; biotechnology; risk perceptions

1. Introduction

The extension of biotechnology is currently a matter of widespread concern in most

European Union (EU) countries (Hoban, 1996). Data from the 1996 and 1999

Eurobarometer Surveys (Table 1) reveal a noteworthy lack of support for certain

* Author to whom correspondence should be addressed. E-mail: j.costa-font@lse.ac.uk

Journal of Risk Research 8 (4), 341–354 (June 2005)

Journal of Risk ResearchISSN 1366-9877 print/ISSN 1466-4461 online # 2005 Taylor & Francis Ltd

http://www.tandf.co.uk/journalsDOI: 10.1080/1366987042000275091

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biotechnology applications (e.g., GM food), displaying a decreasing trend from 1996 to

1999.1 Studies using Eurobarometer surveys highlight significant heterogeneity within

biotechnology applications where there is opposition to genetically modified foods,

whereas the public remains supportive towards healthcare and environmental applications

(Gaskell et al., 1999, 2000, 2003). When examining individual attitudes there is a

‘suspicion’ over whether the public is able to provide a reasoned judgement based on their

understanding of what are the benefits and risks of biotechnology applications. Arguably,

the way that individuals learn and reason about biotechnology might to some extent

influence the weight that individuals place on moral beliefs when expressing attitudes.

Some studies point out that moral beliefs do exert an important influence on risk benefit

evaluations (Macer, 1994, 1996). Protests from key social reference groups, e.g.,

environmentalists on GMO products, or moral resistance from religious groups to certain

medical applications (Bauer et al., 2002), do play a key role in the risk learning process of

some individuals. In fact, decision-making in biotechnology seems to be the result of a

trade-off between two conflicting decision-making models, the first grounded on core

values and moral acceptability and an alternative model based on standard cost-benefit

analysis where risk beliefs are weighted against benefit perceptions. Some studies have

shown that risk perceptions are less influential than moral acceptability in shaping public

perceptions in each EU country across all applications examined by the Eurobarometer

1999 Survey (Gaskell et al., 2000).

The importance of moral beliefs as playing an influential role in determining attitudes

thus affects the way that risk analysis evaluates the acceptance of new technologies. The

conflict between two alternative decision models encompasses the emergence of

‘ambivalence’ in individual perceptions. Quantitative and qualitative research draws upon

the possible consequences of ‘ambivalence’ in public perceptions of biotechnology

procedures (Gaskell et al., 1999); that is, whether attitudes contain both positive and

negative elements which are positively associated (Katz and Hass, 1988). As a result,

individuals exhibit contradictory attitudes with respect to particular biotechnology

applications. This raises the question of whether or not we should take attitudes towards

biotech into consideration, and how to interpret them. Alternatively, if attitudes are to be

1 However, recent data from Eurobarometer Survey 58.0, 2002, show an increase in support (Gaskell et al., 2003).

Table 1. Support for ‘new technologies’ in the European Union (1996 and 1999).

Question: I am going to read out a list of areas in which new technologies are currently being

developed. For each of these areas, do you think it will improve our way of life in the next 20 years, it

will have no effect or it will make things worse?

1999 1996

Solar energy 73.54 73.81

Computers 78.22 76.56

Biotech 39.73 44.78

Telecom 80.69 80.85

New Materials 63.26 64.16

Space Exploration 49.82 48.80

Note: the index is adjusted by the probability of a DK answer in order to ensure comparability (Intra, 2000).

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used as a basis for public policy, an awareness of the effect of ambivalence on public

perceptions should mean that such decisions should be treated with some caution.

On one hand, qualitative research (Sheehy et al., 1998) reveals that even though

consumers demand freedom to choose between products, when it comes to biotechnology,

they feel ill-prepared to make ‘informed decisions’. On the other hand, the lay public

appears to perceive biotech applications as being beneficial, while simultaneously

identifying substantial potential human risks. Furthermore, the well-publicized con-

sequences of some specific biotech applications or products constitute a threat to

individuals’ values, causing significant ethical concerns, and for some people, evoking

dread (Gaskell, 1997). Some authors point out that the predominant ambivalence found

with regard to biotechnology applications is one of ‘public mistrust in technology’ due to a

fear of the new, coupled with public mistrust of the motivations of regulatory institutions

and innovating corporations (Gaskell et al., 2000). Accordingly, risk communication

policy should address public education as well as effective communication channels that

allow for greater transparency in reaching individual and social decisions about the

development of these technologies.

Theoretically, when rational individuals decide whether a particular technology should

be encouraged, they are assumed to apply a cost benefit rule that weighs up benefits and

risks in such a way that acceptance results when the benefits outweigh the risks. However,

when individuals suffer from a lack of knowledge, decision-making is no longer expected

to be rational, but rather based on so-called ‘blissful ignorance’. When the potential

damages are unknown, people show specific well-documented dread (Health and Tversky,

1991). Thus, individuals who show ambiguity aversion will accept only those technology

applications about which they already have some previous knowledge at their disposal

(Costa and Mossialos, 2002).

In this paper we argue that ambivalence in the perceptions of biotechnology

applications might be the result of a conflict between two alternative decision-making

models: one based on the expression of values and the alternative, the standard decision-

making model based on weighing up the costs (risks) and benefits. This phenomenon is

what surveys valuing contingent goods identify as the ‘embedding effect’; that is, when

individuals are asked to express their attitudes in a situation entailing little cost for

expressing individual views, there is little incentive to express ‘reasoned preferences’ based

on a comparison of expected benefits and costs. Instead, what is expressed is a composite

that includes moral values, together with perceptions of risks and benefits. Moral values

might either play a veto role and thus lead to extreme attitudes and/or they may affect the

weighing of benefits and risks, thus leading to attitudes being relatively unstable,

irrespective of the individual’s reasoning capacity. From a policy perspective the existence

of ‘ambivalence’ might lead to a lack of trust in public opinion in shaping science policy.

This paper empirically examines the determinants of ambivalence in perceptions of

biotechnology products in the European Union. We address three questions. First, the effect

of ambivalence in certain biotech applications. Second, whether ambivalence is associated

with information channels. That is, whether it is the result of a lack of education, whether it

can be explained by certain demographics or instead is the result of the influence of certain

reference groups (e.g., political parties or religious groups), which serve to amplify the social

perception of future negative consequences. Finally, we estimate the impact of ambivalence

on attitudes towards biotechnology. To undertake this task using multivariate techniques we

Preferences towards biotechnology in the EU 343

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empirically examine evidence based on a large representative sample of the EU population

collected from the Eurobarometer 1999 Survey 52.1.

Section two examines the issue of ambivalence as it applies to biotechnology, outlining

the main hypothesis to be tested. Section three presents the data and empirical methods.

Section four describes results and section five draws some conclusions.

2. Ambivalence and support for biotechnology

Traditionally attitudes were conceived as being either positive or negative towards an object.

However, the hypothesis of attitudes being ambivalent—that is, both positive and negative at

the same time—makes it necessary to conceive of attitudes as having two or more dimensions.

However, contrary to what a standard risk-benefit model would predict, ambivalence implies

that in certain individuals regarded as ambivalent, some dimensions should be relatively

independent or positively related, rather than highly negatively correlated (Kaplan, 1972).

The main constraint to individual behaviour regarding new technologies is the

significant difficulty encountered in attempting to improve knowledge of science or

access to that knowledge, which is sometimes needed to fully capture the expected

consequences of manipulating nature in some way. When knowledge is scarce, then one

might expect individuals to perceive decisions as not being voluntarily taken—due to the

resulting inability to control the consequences of their actions—which in turn, might lead

to the so-called precautionary attitudes—‘prevention is better than cure’. Risks associated

with biotechnology, even when they are purely ‘virtual’, are not voluntarily taken due to

the consumer’s lack of ‘comprehensive information’ (Costa and Mossialos, 2002). At this

point the media play a key role, coupled with the individual lack of knowledge. That is, the

natural reaction is an exaggeration of risk perceptions and moral concerns (Johnson and

Tversky, 1983).2 Empirical evidence shows that people prefer alternatives for which they

feel more ‘knowledgeable’ (Health and Tversky 1991). Lack of sufficient scientific evidence

on the possible long-term risks of genetic engineering leads to problems in understanding

the policy and behavioural implications provided by quantitative studies on biotech

attitudes and, to a certain extent, brings into question the degree to which we can trust the

public for science policy-making (Costa and Mossialos, 2003). Therefore, attitudes

towards biotechnology should be treated with some caution. A common feature is an

abundance of non-attitudes ‘don’t know’ (DK) answers. Twenty-five precent of

Europeans do not (or are unable to) reveal their attitudes towards a specific biotechnology

application. DK answers in the Eurobarometer 52.1 survey were associated with education

and age as well as with the degree of interview cooperation (Costa and Mossialos, 2002).

Ambivalence is important because it results in unstable attitudes (see Eagly and

Chaiken, 1993) and extreme responses toward the attitude object (Katz, 1981). A lack of

comprehensive information on the future effects of biotechnology, heterogeneity and

dispersion as well as the noise that may exist in information channels are expected to have

an influence on the ‘stability’ of individuals’ perceptions of biotech (Costa and Mossialos,

2002). The link between stability of perception towards biotech and ambivalence is thus

expected to be significant. An examination of attitudes towards biotech requires careful

2 One of the main limitations of risk communication in the media is that they often present facts out of context,leaving the public to evaluate the risks. Additionally, some messages, in exaggerating the vividness andinformation coverage, might lead to misconception of risks (Walhlberg and Sjoberg, 2000).

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analysis of information channels. Thus, if for any reason one might wish to obtain a

certain result, one might seek to place some emphasis on information communicating the

benefits, and conversely if one seeks the opposite effect one would place more emphasis on

the moral concerns associated with genetic engineering.

Ambivalence is routinely attributed to the limitations in an individuals’ reasoning

(in)competence due to lack of information combined with the simultaneous use of

conflicting dimensions available to the public in the information system when asking for

attitudes on biotechnology. Hence, ambivalence is acknowledged as a common decision-

making limitation when examining quantitative evidence on the support for certain

applications (Gaskell, 1997; Lujan and Todt, 2000; Heijis et al., 1993). Moral cognition has

been argued to adhere to a two-tiered architecture where moral reasoning is the result of

specialized, encapsulated modules, which automatically and effortlessly generate intuitions

(Bolender, 2001). It is common when evaluating the impact of new technologies that

individuals display ‘dual preferences’. If moral concerns, as we argue, are linked to expressed

values, and risk-benefit perceptions refer to individual’s reasoned attitudes, ambivalence

might then be the result of a conflict between values and attitudes. A lack of support for

biotechnology where there are few (if any) scientifically demonstrated risks resulting from

the techniques in question leads us to ascertain that lack of support might be the result of

values prevailing over attitudes. Conversely, support for biotech application would suggest

that in this conflict attitudes prevail. Some studies demonstrate that individuals who are

ambivalent display response amplification in attitudes (Maio et al., 1996). Hence, one

empirical question to test might be whether one dimension or another prevails.

The existence of ambivalence implies that attitudes towards biotech might differ depending

on the types of question posed (e.g., questions stressing the risks of specific applications might

enhance more unsupportive perceptions, or heterogeneous time valuation or inconsistencies

may result from context influence, e.g., if there has recently been a public scandal regarding

food or medical safety, in which case perceptions are assumed to be more sceptical). Safety

concerns are paramount among other concerns, suggesting, in turn, that risk considerations

are important dimensions that individuals take into account when evaluating biotech

procedures (Gaskell et al., 2000). Biotech procedures carry a number of benefits as argued by

proponents. The use of biotech procedures make it possible to feed more people in a more

efficient manner, facilitates the detection and prevention of diseases and has numerous clinical

applications. All of these applications ultimately increase both consumer and producer

welfare. Moral concerns seem to play a more important role in shaping attitudes towards

certain genetic engineering applications in which nature is significantly modified. In particular,

religious groups or environmentalists might express opposition to procedures that might cause

future irreversible damage to living organisms or to human beings.

Prior research indicates that ambivalence might be a specific feature in the formation of

attitudes towards certain biotech applications (Lujan and Todt, 2000). One possible

explanation of ambivalence is the hypothetical conflict between processes and products. If

this were the case, we should find significant differences in the degree of ambivalence

towards different biotech applications. Ambivalence leading to unclear preferences

means that processes are still questioned although the benefits are perceived. Therefore, if

individuals reveal an attitude towards biotechnology and are able to distinguish

between processes, then one should expect ambivalence to differ significantly across

applications.

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3. Data and methods

This study uses a non-original but extensively representative survey, the Eurobarometer

Survey 52.1 to study attitudes towards and perceptions of biotechnology products.3 Around

16 000 people were interviewed in 1999 in the EU 15 member states between October and

November 1996 and November and December 1999, respectively (INRA, 2000). The aim

of the survey was to elicit the public opinion for biotechnology applications and the

questions were developed by staff at the European Commission. Although the survey has

caveats, to our knowledge it is the only EU survey available that meets our research needs.

Principally, the caveats refer to the sampling procedure and the difficulties associated with

measuring income and education among EU member states. The survey was conducted on

a multi-stage random sampling basis rather than through pure random sampling.

Therefore, some concerns might arise with respect to its full cross-country representa-

tiveness. Furthermore, although the survey contains subjective information on education

and income, low associations between income/education thresholds and national data cast

some doubt on the ‘meaningfulness’ of aggregating those thresholds in a single sample.

Therefore, in the study we do not use income data and rely exclusively on education along

with variables that are proxies for income such as house size, and pension income received

to proxy socio-economic status.

This survey fits into the context of other related studies on attitudes to consumer risks

and may be a good instrument to examine the individual attitudes to risks derived from

scientific progress. In the 1999 Eurobarometer survey, the term biotech is referred to as

‘modern biotechnology’ in a broad sense.4 These surveys explore the acceptance of

biotechnology at the EU level and public knowledge on biotechnology. As shown in Table

1, biotechnology has been the least accepted form of new technology jointly with nuclear

technology when compared to alternative technologies. This study uses the Eurobarometer

52.1 (1999) survey, which was the latest database available at the time of writing this

paper. Interestingly, it is in 1999 where a peak is reported in revealed individual scepticism

towards biotechnology (Gaskell et al., 2003). From this survey we focus on acceptance as

well as its dimensions. The question was framed as follows:

To what extent do you agree or disagree that this application is (risky/useful/morally

acceptable/should be encouraged)? The context referred to six different biotechnology

procedures from which we selected two: GM food and GM medicines. Attitudes were measured

on an ordered scale from one to four, whereby four equals strong disagreement and one equals

strong agreement with each statement.

The specific applications subjected to public scrutiny were the following. For GM food,

the example used was the ‘use of modern biotechnology in the production of foods, for

example to make them higher in protein, keep longer or change the taste’ and for GM

medicines it referred to ‘introducing human genes into bacteria to produce medicines or

vaccines, for example to produce insulin for diabetics’.

Measuring individual ambivalence in providing attitudes can be undertaken ex-ante by

means of so-called objective indicators by combining the number of positive and negative

3 The study was developed by an international group co-ordinated by George Gaskell and Martin Bauer from theLondon School of Economics and the fieldwork was undertaken by INRA.4 The surveys included split questions, in which half of the sample were asked about ‘biotechnology’ and the otherhalf about ‘genetic engineering’.

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dimensions of an attitude, or alternatively by subjective indicators when individuals are

asked to express their personal attitude regarding a conflict. In this study, we adopt aspecific notion of ambivalence where an individual was classified as ambivalent if he/she

perceived a specific application as being risky and morally unacceptable (negative

dimensions) but also useful (positive dimension). Alternative combinations yielded the

same results. Unlike other studies (Thompson et al., 1995), dimensions were not measured

on a cardinal scale so that we could estimate an ambivalence index, but instead were

verified using a binary variable indicating whether individuals were ambivalent or not.

Ambivalence is expected to increase as a function of the extent to which the positive and

negative dimensions oppose each other. Empirical analysis was undertaken employingmultivariate logistic regression analysis for qualitative data and, because support for

specific applications is expressed in an ordered manner, we employed an ordered logit

model. In an ordered logit model the probability of (non)supporting or (non)strongly

supporting each application is a function of the same linear combination of the

explanatory variables assuming a logistic distribution function.

Covariates we are interested in refer to socio-demographics, that is, gender—measured

using a dummy variable that equals one if gender is male—and age—in years—as age

might influence the acquisition of information on the benefits and risks of newtechnologies. In order to control for people’s values we include both religiosity and lack

of religiosity as dummy variables. Moreover, in measuring attitudes we include a variable

capturing a global judgement of biotechnology. Because ambivalence might be a cognitive

phenomenon dependent on the individual capacity for information processing as well as

the amount of existing information, we introduce in our empirical model the education

level—proxied by the variable ‘schooling’ (educational level), measured in scales—as well

as cooperation with the interviewer. The significance of schooling might indicate that

certain information about GM food or GM medicines might require previous scienceinformation. Cooperation with the interviewer is expected to reflect that some people

might have provided an unreasoned judgement when interviewed.

The main research questions that we wish to address are the following:

N A. Is ambivalence a specific feature of certain biotech applications or is there

ambivalence in all processes? Are ambivalence levels similar?

N B. Is ambivalence the result of a significant lack of information or competence in

information processing? To what extent might the influence of certain reference

groups in expressing beliefs explain ambivalence?

N C. What is the influence of ambivalence on attitudes in weighting the risks and

benefits of biotechnology applications? Does ambivalence reduce support for biotech

applications?

4. RESULTS

Results are structured in order to provide answers to the central questions posed in thispaper. The first issue we examine refers to whether there are differences among

biotechnology applications. Table 2 reveals that although DK answers were not

significantly different among different applications, significant differences are identified

in individuals’ support between GM food and GM medicines. Roughly 30% of Europeans

approve of food biotech, whereas 54% support medical biotech applications. Therefore,

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arguably this indicates that there is not a rejection of processes as a whole and that

individuals are able to discriminate between different products. Respondents do not seem

to evaluate biotech processes equally, which in turn, might suggest that attitudes towards

specific applications of biotechnology might even be influenced by different determinants

and hypothetically the role of ambivalence might impart a different influence. An

important finding to highlight is that around 25% of the sample place no specific attitude

with regard to some biotech applications, which in turn exhibits a specific sort of scientific

ignorance whereby individuals lack ‘sufficient’ knowledge to make a judgement, as has

already been found in other studies (Costa and Mossialos, 2003).

Table 3 shows the partial correlation coefficients between acceptance and their

respective dimensions for the two biotech applications examined among different EU 15

member states. Interestingly, whereas for GM food very high and significant correlation

coefficients were identified between acceptance and risks perceptions, for GM medicines

correlation coefficients were not significant. Benefit perceptions for GM medicines

although statistically significant, were slightly less correlated with acceptance than was the

case for GM food. Interestingly, moral acceptability displays a positive correlation with

acceptance of GM medicines, whereas it exhibits a negative and significant coefficient for

GM food. This result suggests that different dimensions of acceptance might play a

different role in the support for different applications all encapsulated within

biotechnology. Furthermore, because the signs of the coefficients for moral acceptance,

risk perceptions as well as usefulness do not follow the same patterns, we might expect

some differences in the ambivalence towards both applications under examination.

Let us now turn to examine the extent to which there are ambivalent responses for GM

food and GM medicines as reported in Tables 4 and 5, respectively. Interestingly, a

significant core of responses was affected by ambivalence. We found that 43% and 34% of

responses referring to food biotech and medical biotech, respectively, did exhibit ambivalence

as defined in the study. That is, a very significant share of the population, regardless of the

process considered, seem to simultaneously agree that certain applications are risky and

useful, but at the same time morally unacceptable. However, the extent of ambivalence varied

among different applications, being greater for food biotech than for medical applications

Table 3. Partial correlation coefficients between benefit dimensions (1999).

Risky Useful Morally acceptable

GM food 20.83** 0.91** 20.59*

GM medicines 20.38 0.81** 0.95**

*Significant at 5%.**Significant at 1% level.

Table 2. Attitudes towards food and medical biotech (1999).

Question: To what extent do you agree or disagree that this application should be encouraged?

Strongly agree Tend to agree Tend to disagree Strongly disagree DK

GM food 9.6% 20.8% 19.6% 27% 23%

GM medicines 25.7% 27.9% 10% 9.6% 27%

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(A). That is, ambivalence does not seem to be a matter of a common rejection to a technique

as pointed out by Lujan and Todt (2001). Moreover, ambivalence was greater in Greece,

Denmark and Ireland as compared to Belgium, taken as a benchmark for purely empirical

reasons. Not surprisingly, these countries were the ones recording the least support for

biotechnology. This is an issue that we examine more extensively below.

The second issue of interest in this study refers to what determines ambivalence, and in

particular, what is the influence of education and socio-demographic determinants that

might proxy individual background information? Table 6 exhibits the results of a logistic

regression used to examine this issue. Covariates refer to demographic variables capturing

differences in the information acquisition channels. First, we should reinforce some of the

previous results by pointing out that there were significant differences in the determinants

of ambivalence between the two applications considered. Whereas age and gender were

significant variables for food biotech, they had no influence in the case of medical biotech

applications. Consistent with other studies (Gaskell et al., 1999; Costa and Mossialos,

2002), there is a ‘gender gap’ in attitudes. Focusing on the determinants of ambivalence in

food biotech, it was found that men are less ambivalent than women. Explanations for this

are less straightforward although we believe this may be due to the fact that males might

be less influenced by the use of GM food when it comes to social habits regarding food

consumption. Furthermore, age shows a quadratic effect for GM food, whereby young

cohorts are more likely to be ambivalent as compared to the very old age cohorts. Age

exerted no effect in explaining ambivalence in GM medicines. An explanation for this

might result from the amount of positive and negative information on GM food that has

been in the public domain over time. On the basis of this result one could argue that on the

one hand, younger people are more ambivalent because they are basically influenced by

Table 5. Ambivalence and support for medical biotech (1999).

Ambivalence Strongly

encouraged

Tend to

encourage

Tend to

discourage

Strongly

discourage

DK Total

No 2598 3226 810 184 3726 10 544

% 61.48 68.62 48.50 13.68 90.75 65.70

Yes 1628 1475 860 1.161 380 5504

% 38.52 31.38 51.50 86.32 9.25 34.30

Total 4226 4701 1670 1345 4106 16 048

Table 4. Ambivalence and support for food biotech (1999).

Ambivalence Strongly

encouraged

Tend to

encourage

Tend to

discourage

Strongly

discourage

DK Total

No 959 2411 1824 731 3126 9051

% 61.67 72.84 57.85 16.75 85.01 56.36

Yes 596 899 1329 3633 551 7008

% 38.33 27.16 42.15 83.25 14.99 43.64

Total 1555 3310 3153 4364 3677 16059

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recent public information, as well as their own private information channels. On the other

hand, older cohorts might instead be influenced by more ‘traditional lifestyles’ based on,

for example traditional food, and possibly they have received a larger flow of information

over time. Therefore, ambivalence regarding food biotech seems to be more prominent in

middle age groups, that is, those placed in between these two age cohorts.

The influence of social groups was significant for both applications considered. As one

might have expected, religious individuals were more ambivalent than those who were not

religious, the reason for this being that ambivalence is defined as the inconsistency of ‘two

logics’, the first being attitudes and the second being values. The question then becomes

Table 6. Determinants of ambivalent attitudes (1999).

Ambivalence GM food GM medicines

Coef. t-value Coef. t-value

Gender 20.06* 21.85 0.03 0.93

Age 0.21** 4.39 0.05 1.06

Age2 20.02** 23.67 20.01 21.28

Religious 0.22** 2.03 0.23** 2.02

Non-religious1 0.02 0.14 0.19 1.30

Cooperation 20.18** 27.76 0.03 24.05

Schooling_12 20.11** 22.24 20.22** 24.25

Schooling_22 20.01 20.28 20.06 21.50

Denmark 0.30** 4.04 20.13 21.65

Germany 20.36** 24.78 20.62** 27.56

Greece 0.35** 4.67 20.34** 24.34

Spain 20.21** 22.78 20.22** 22.848

France 20.73** 29.32 20.65** 27.98

Ireland 0.36** 4.82 0.43** 5.92

Italy 20.52** 26.82 20.54** 26.73

Luxembourg 20.67** 25.37 20.36** 24.11

Netherlands 20.78** 25.24 20.65** 26.59

Portugal 20.49** 26.56 0.09 1.27

UK 20.89** 210.57 20.64** 27.49

Austria 20.28** 23.78 20.66** 28.24

Sweden 20.65** 28.36 20.92** 210.63

Finland 20.75** 29.69 20.47** 25.99

Constant 0.08 0.87 20.18* 21.890

R2 0.07 0.08

LR 806 547

N 15 933 15 933

*Significant at 10% level.**Significant at 5% level or less.1We classify an individual as non-religious based on their response to a survey question on self-perception ofindividual religiosity whereby individuals could express an attitude ranging from ‘very religious’ to ‘veryunreligious’. The variable has been dichotomised as ‘religious’ and ‘non religious’ as shown in this table.2Schooling refers to education levels as defined in the Eurobarometer 52.1 in an ascending order. Schooling 1indicates no studies undertaken; Schooling 2 indicates primary school-level studies, while Schooling 3 refers tostudies higher than primary school-level. Therefore, Schooling 3 is the omitted variable.

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‘do values prevail?’ Very religious individuals are expected to emphasize values associated

with a preconception of modifying nature. On the basis of the significance and the positive

sign of the variable measuring religiosity, we argue that although they might perceive

benefits and risks, attitudes might be a value expression.

Finally, attitudes towards food biotech were extensively determined by the degree to

which individuals’ cooperate—in the interviewers’ opinion—in the interview. This might

indicate that part of the ambivalence in individuals’ attitudes can be attributed to

problems with the questionnaire among a number of participants. However, the most

interesting result with respect to the determinants of ambivalence is that education had a

negative and significant influence on ambivalence, suggesting that improving education

might lead to a reduction in ambivalence (B). This is a result that is often sustained by the

literature, but there was little empirical basis for doing so. Finally, individual (country)

effects were significant, suggesting important cross-country heterogeneity, thus high-

lighting the importance of cultural differences when examining perceptions. In particular,

in 1999, Denmark, Ireland and Greece were the countries where ambivalence was higher as

dummy variables show, where Belgium is taken as the basis for comparison.

Tables 4 and 5 display the distribution of ambivalent and support answers.

Interestingly, ambivalence does not result in ‘non-attitude answers’, but mainly in

unsupportive attitudes towards biotechnology. Looking more closely at the determinants,

Table 7 shows that ambivalence reduced support for biotech (C). Thus, reducing

ambivalence would lead to an increase in support for biotechnology. However, the effect

of ambivalence was different between applications, being greater for GM medicines than

Table 7. Determinants of support for biotech (ordered logit) (1999).

GM food1 GM medicines1

Coef. t-value Coef. t-value

Ambivalence 0.83** 23.21 1.54** 41.96

Gender 20.07** 22.31 20.26** 27.58

Age 0.06 1.24 0.09** 1.91

Age2 2361023 20.47 20.01 21.49

Religious 0.44** 3.67 0.35** 2.83

Non-religious 20.23 21.61 20.11 20.80

Cooperation 0.08** 3.05 20.02 20.98

Schooling_1 0.23** 4.36 0.32** 6.10

Schooling_2 0.10** 2.57 0.22** 5.33

Biotech judgement2 20.56 215.56 20.73** 220.33

Pseudo R2 0.06 0.10

Likelihood ratio 1132.5 3358

*Significant at 10% level.**Significant at 5% level or less.1Attitudes equal to 1 imply strong agreement that biotech should be encouraged and equal to 4 imply adisagreement with the statement that biotechnology should be encouraged. Therefore, a positive coefficientmeans a negative effect in support.2Biotech judgement refers to attitudes on whether or not biotechnology will improve the way of life in the next 20years.

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for GM food. Note that attitudes have been measured on an ordered scale of 1–4. Where

attitudes equal 1 this indicates strong agreement that biotech should be encouraged, and

when they equal 4 this implies disagreement with the statement that biotechnology should

be encouraged. Therefore, a positive coefficient means a negative effect in support for

biotechnology. That is, ambivalence reduces the support for the two applications

examined although the effect is more prominent in GM medicines. Attitudes are also

explained by the effect of gender, and as expected, women are more likely to express an

opposition to both biotechnology applications. Other significant variables were the subject

having a positive image of biotechnology—which was associated with a higher support for

GM medicines, religiosity—reducing support for both applications, and education—where

findings reveal that a higher educational attainment improves support for biotechnology.

Findings suggest that ambivalence is mainly concentrated among those respondents that

seem to oppose the use of biotechnology regardless of the specific application.

5. Conclusions

This paper has examined the extent to which ambivalence influences attitudes towards

biotech applications in the European Union 15 taken as a whole. We have found that

ambivalence is a significant feature to take into consideration when examining attitudes

even though it has a heterogeneous effect among different applications. According to our

results ambivalence does not seem to be the result of a tension between products and

processes. The fact that the level of education influenced both ambivalence and attitudes

suggests that increasing education might reduce ambivalence and consequently increase

support for both GM food and GM medicines. Findings support the hypothesis that

perceptions of the benefits and risks of new technologies might be strongly influenced by

the way in which individuals evaluate new information. Social learning theories stress the

fact that people learn according to the availability of information (Kanheman and

Tversky, 1972). Thus, an increase in information availability is expected to reduce

individuals’ ambivalence to a greater extent, and these attitudes could be examined in a

more straightforward way through the standard risks–benefit model.

From a policy perspective, this paper brings to the fore the empirical feature that

ambivalence limits the support for all biotech procedures, although to different degrees among

biotechnology applications. Moreover, ambivalence has little to do with ‘non-attitudes’ or DK

responses, but instead explains the lack of support for biotechnology applications, which

might in turn suggest a conflict between ‘values and attitudes’. According to the results

reported in this paper, it seems that the lack of support for a certain biotech application

indicates that values prevail over attitudes. That is, either the risk decision-making model is

vetoed by moral attitudes or moral concerns amplify risks so that acceptance declines.

In view of the results of this study, it would seem that individuals have difficulty in

reasoning on issues upon which they receive little information. Accordingly, ambivalence

is expected to continue to play a key role in determining individual attitudes as long as

available information continues to be limited. Furthermore, ambivalence, as well as

attitudes to biotechnology applications, seems to be associated with the dimensions of the

technology itself. Therefore, in the design of risk communication policies, decision makers

should ensure that individuals are well informed if public perceptions are to be taken into

account in public policy formation.

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Acknowledgements

We acknowledge the comments of Jonathan Baron, Adam Oliver, David McDaid, Jose

Luis Fernandez and the participants of the Hopes and Fears Conference, University of

Cambridge, September 2002 along with helpful comments from the three journal referees.

All possible errors are our own and the usual disclaimer applies. We are grateful to the

European Commission for providing financial support for this project (HPMF-CT-2000-

00947). We are also grateful to Anna Maresso for copy-editing the manuscript.

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