Risk Analysis, Vol. 25, No. 5, 2005 DOI: 10.1111/j.1539-6924.2005.00672.x

Perception of Mobile Phone and Base Station Risks

Michael Siegrist,1∗ Timothy C. Earle,2 Heinz Gutscher,3 and Carmen Keller3

Perceptions of risks associated with mobile phones, base stations, and other sources of elec-tromagnetic fields (EMF) were examined. Data from a telephone survey conducted in theGerman- and French-speaking parts of Switzerland are presented (N = 1,015). Participantsassessed both risks and benefits associated with nine different sources of EMF. Trust in theauthorities regulating these hazards was assessed as well. In addition, participants answereda set of questions related to attitudes toward EMF and toward mobile phone base stations.According to respondents’ assessments, high-voltage transmission lines are the most riskysource of EMF. Mobile phones and mobile phone base stations received lower risk ratings.Results showed that trust in authorities was positively associated with perceived benefits andnegatively associated with perceived risks. People who use their mobile phones frequentlyperceived lower risks and higher benefits than people who use their mobile phones infre-quently. People who believed they lived close to a base station did not significantly differ intheir level of risks associated with mobile phone base stations from people who did not believethey lived close to a base station. Regarding risk regulation, a majority of participants werein favor of fixing limiting values based on the worst-case scenario. Correlations suggest thatbelief in paranormal phenomena is related to level of perceived risks associated with EMF.Furthermore, people who believed that most chemical substances cause cancer also worriedmore about EMF than people who did not believe that chemical substances are that harmful.Practical implications of the results are discussed.

KEY WORDS: Electromagnetic fields; mobile phones; risk perception; trust

1. INTRODUCTION

The number of people who use mobile phoneshas dramatically increased in Europe and in theUnited States in recent years. This increased de-mand has led to the construction of more base sta-tions. For the 3G/UMTS-Net that will be introducedin Europe soon, twice the number of base stationswill be needed than for today’s GSM-net (second

1 Swiss Federal Institute of Technology, Human-EnvironmentInteraction, ETH Centre HAD, CH-8092 Zurich, Switzerland.

2 Western Washington University, WA, USA.3 University of Zurich, Switzerland.∗ Address correspondence to Michael Siegrist, Swiss Federal

Institute of Technology, Human-Environment Interaction, ETHCentre HAD, CH-8092 Zurich, Switzerland; michael.siegrist@env.ethz.ch.

generation). Therefore, even more base stations willbe built in the near future. Concerned citizens inGermany (Asendorpf, 2002) and in Switzerland, how-ever, are fighting against the construction of base sta-tions in their neighborhoods and in the vicinity ofschools. Faced with a conflict between demand formore transmission facilities and public opposition tothem, telecommunication companies and authoritiesare forced to take into account the risks perceived bylay people.

Few studies dealing with lay people’s perceptionsof risks associated with cell phones or base stationshave been published. A study by Siegrist et al. (2003)examined the influence of trust and confidence on theacceptance of a base station in one’s neighborhood.The goal of that study was to test a trust model inthe applied context of EMF, not to assess the levels

1253 0272-4332/05/0100-1253$22.00/1 C© 2005 Society for Risk Analysis

1254 Siegrist et al.

of risk associated with different sources of EMF. Re-sults suggested that trust and confidence strongly im-pact the acceptance of a neighborhood base station.Poortinga and Pidgeon (2003) examined the factorsthat influence trust in the authorities responsible forregulating mobile phones. Results of their survey in-dicated that general trust, skepticism, and value simi-larity affect levels of trust. A study by Sjoberg (2002)showed that people associate “unknown effects” withmobile phones. Similar findings were obtained in aGerman survey (Zwick & Ruddat, 2002): respondentsviewed risks associated with mobile phones as highlyuncertain. The possible effects and the extent of therisks were judged to be uncertain. There are otherrisks associated with cell phones in addition to thosefrom EMF. White et al. (2004), for example, examinedthe perception of risks arising from mobile phone usewhile driving.

Perceptions of electromagnetic field risks associ-ated with high-voltage transmission lines and othersources of EMF have been examined in several stud-ies (Furby et al., 1988; Gregory & von Winterfeldt,1996; Morgan et al., 1985; Wiedemann et al., 2003).MacGregor et al. (1994) assessed lay people’s beliefsabout EMFs as a cause of health disorders. The high-est ratings were obtained for cancer and birth defects.Respondents in this study also showed strong sup-port for corrective measures such as warning labels,appliance shielding, and further research.

1.1. Results of Studies Utilizing thePsychometric Paradigm

Psychometric studies have focused on the identi-fication of factors that determine public perception ofdifferent hazards (Slovic, 1987). In these studies, par-ticipants assessed various characteristics of a broadrange of potential hazards, and principal componentsanalysis was used to identify the factors that deter-mined the perception of these hazards. The perceivedrisks associated with different sources of EMF wereexamined. Results suggested that fields from largepower lines are perceived as little-known risks and asrisks with some dread potential (Morgan et al., 1985).The authors concluded that possible negative healtheffects associated with the EMF of high-voltage trans-mission lines may have a fairly high “signal potential.”In other words, even minor effects would receiveconsiderable media attention, and people might askfor stricter regulations. Morgan et al. (1985) also ex-amined the perception of fields from electric blan-kets. Results indicated that people perceive electric

blankets to be little-known risks with a low dread po-tential. Since the participants in this study were 116alumni of Carnegie Mellon University, generalizationof the results is problematic. In a study conducted inChile, Bronfman and Cifuentes (2003) included theitem “cell-phone transmission antennas” in their listof hazards, and respondents perceived base stations asa little-known hazard with medium dread potential.

In these studies utilizing the psychometricparadigm, averages are taken across all participants.Results of recent studies, however, indicate that thereare substantial individual differences in risk percep-tion (Marris et al., 1997; Siegrist et al., 2005). Thissuggests that lay people’s risk perceptions cannotbe explained by a model based on aggregated data.Clearly, more research that examines factors account-ing for individual differences in risk perception isneeded. Siegrist et al. (2005) conducted a three-waycomponent analysis in order to detect and describe theinternal structure of three-way data. Results of thatstudy showed that lay people assess mobile phones asa new hazard with unobservable consequences. Sim-ilar assessments were observed for hazards like foodpreservatives and x-rays.

1.2. Health Effects of EMF

Numerous epidemiological studies have exam-ined possible health effects of EMF. Based on theirreview of the literature, Ahlbom and colleagues con-cluded that there is no chronic disease for whichan etiological relation to EMF can be regarded asestablished (Ahlbom et al., 2001). High levels ofradio frequency energy can rapidly heat biologicaltissue. Research to date, however, has not demon-strated adverse thermal health effects (U.S. GeneralAccounting Office, 2001). Rothman (2000) reviewedthe epidemiological literature examining the healthrisks of mobile phones. Regarding risks associatedwith base stations, he concluded that “the few stud-ies to date of populations near microwave, radio,and television towers have produced no consistentfinding of increased risk, but these studies typ-ically exhibit problems with exposure assessmentor geography-related confounding” (Rothman, 2000,p. 1839). Breckenkamp et al. (2003) reviewed nine co-hort studies examining effects on human health fromexposure to radio frequencies/microwaves. In mostof the reviewed studies, an increased risk for varioustypes of cancer was found for exposed patients. How-ever, Breckenkamp et al. (2003) concluded that the re-sults were inconsistent. The unknown details of actual

Perception of EMF 1255

exposure were one of the most important limitationsof the reviewed studies. In several epidemiologicalstudies, associations between exposure to power-linemagnetic fields and childhood leukemia have beenobserved (Brain et al., 2003). Based on the availablestudies, it cannot be denied that mobile phones andbase stations could have the potential to induce ad-verse health reactions (Hyland, 2000). Epidemiolog-ical studies examining the health impacts of mobilephone use or base stations are limited to diseaseswith short induction period, because mobile phonesare a relatively new technology. Based on the avail-able research, the Stewart report (Independent Ex-pert Group on Mobile Phones, 2000) recommended aprecautionary approach. The use of mobile phones bychildren for nonessential calls, for example, is discour-aged. The most well-established health risk associatedwith mobile phones is the higher probability of motorvehicle collisions when drivers are using their mobilephones (Redelmeier & Tibshirani, 1997).

1.3. Rationale of the Present Study

It is important to better understand people’s con-cerns regarding risks associated with mobile phonetechnology. In this study, lay people’s perceptions ofthe risks of nonionizing radiation (e.g., high-voltagetransmission lines, radio frequencies, infrared) wereexamined. The main focus of the study was the mea-surement of the perceived risks of, and attitudes to-ward, the EMF associated with mobile phones andmobile phone base stations. The results of previousstudies (e.g., Siegrist & Cvetkovich, 2000; Sjoberg &af Wahlberg, 2002) guided the selection of factorsfor inclusion in the present study. Additional factorsmay also be important in explaining perception ofEMF risks. The telephone methodology utilized in thepresent survey, however, imposed strict limitations onthe number of factors that could be examined.

2. METHOD

2.1. Participants

The data for this study come from a telephone sur-vey conducted in the German- and French-speakingparts of Switzerland. A random sample of 1,015 per-sons between 18 and 74 years of age was interviewedby telephone.4 Interviews were conducted in June

4 Telephone numbers were randomly selected; cell phone numberswere excluded because they are not listed in the phone book. Theperson answering the phone was interviewed.

and July 2002. The response rates were about 39%in the German-speaking part and about 29% in theFrench-speaking part.5

Fifty-seven percent (n = 583) of the participantswere female, and 43% (n = 432) were male. The meanage was 45 years (SD = 14.52). Four persons did notreport their age. Seventeen percent of the participantswere between 18 and 29 years old, 22% were between30 and 39 years old, 32% were between 40 and 54 yearsold, and 29% were 55 years or older. Seventy-five per-cent (n = 762) of the interviews were conducted in theGerman-speaking part, and 25% (n = 253) were con-ducted in the French-speaking part of Switzerland.

2.2. Questionnaire

The interviewer first explained to participantsthat base stations are needed to enable communica-tion between mobile phones. After this short intro-duction, participants were asked to associate freelyabout the concept of a base station for mobile phones,following a method similar to the one used by Slovicet al. (1991). Respondents were asked to indicate theirfirst thought or association; they were then asked howpositive or negative they perceived this associationto be.

Participants then were asked to make three judg-ments about each of nine EMF-emitting technologies.The nine technologies are listed in Table I. Judgmentswere to be made on (1) the perceived risks of eachtechnology, (2) the perceived benefits of each tech-nology, and (3) the degree of trust placed in the au-thorities who regulate each technology. The item onperceived risk said: “I will mention different sourcesof electro-magnetic radiation. Indicate, using a num-ber between 1 and 5, how risky you perceive the ra-diation emitted by these technologies to be, for Swisssociety as a whole. One means no risk at all, and 5means very high risk.” The item on perceived bene-fit said: “In general, how beneficial do you considereach of the following technologies to be, for Swiss so-ciety as a whole? One means no benefit at all, and 5means very high benefit.” The item on perceived trustsaid: “In general, how much trust do you have in theauthorities who regulate the following technologies?One means no confidence at all, and 5 means veryhigh confidence.”

5 Response rates were calculated as: “Response rate” = (“num-ber of completed interviews”)/(“number in sample-number noteligible”).

1256 Siegrist et al.

Table I. Means and Standard Errors ofthe Mean of Perceived Risks, Perceived

Benefits, and Trust in Authorities

Perceived Risks Perceived Benefits Trust

Source M SE M SE M SE

Mobile phones 2.93 0.034 3.36 0.036 2.72 0.033Mobile phone base stations 3.26 0.035 3.32 0.036 2.73 0.034Radio transmitter 2.17 0.034 4.14 0.032 3.46 0.034TV transmitter 2.38 0.036 3.75 0.036 3.40 0.035Microwave oven 2.56 0.042 2.41 0.040 2.76 0.038TV 2.23 0.034 3.50 0.038 3.34 0.036High-voltage transmission lines 3.64 0.041 4.07 0.035 3.29 0.038Infrared lamp (e.g., in restaurants) 2.35 0.039 2.27 0.036 2.83 0.037Railway power lines 2.65 0.040 4.27 0.030 3.60 0.036

Note: N varies between 950 and 1,012, reflecting missing values.

Respondents also answered true/false questionsmeasuring knowledge (e.g., “The earth has a naturalelectromagnetic field.”). In addition, items measuringbelief in paranormal phenomena and attitudes towardvarious aspects of mobile phones and mobile phonebase stations were included in the interview.

3. RESULTS

3.1. Associations Evoked by Base Stations

The free associations evoked by the term “basestations” were, on average, slightly negative. On ascale ranging from −5 (negative) to +5 (positive) amean value of −0.87 (SD = 3.06, N = 934) was ob-served, 95% CFI = −0.87 ± 0.20. Fifty-one percentof the respondents mentioned negative, 24% of therespondents mentioned neutral, and 25% of the re-spondents mentioned positive free associations. Re-garding the dominant, negative free associations ofbase stations for mobile phones, 34% of the respon-dents (n = 160) mentioned concepts like electromag-netic radiation pollution (“electrosmog”), irradiation,and similar concepts. Associations related to publichealth, illness, headache, or general health damageswere mentioned by 18% of the respondents (n =84). Aesthetic reasons were important for 9% of therespondents (n = 44), whereas 7% (n = 33) of therespondents mentioned antennas or mobile phones;another 7% (n = 31) mentioned general terms likerisk, danger, or anxiety.

The negative/positive assessment of the associa-tion was significantly correlated with perceived risks.Participants having negative free associations per-ceived more risk associated with base stations thanparticipants having positive free associations, r =−0.35 (p < 0.001). Similar results were observed for

risks associated with mobile phones, r = −0.24 (p <

0.001).

3.2. Trust and Perceived Risks and Benefits

Participants assessed the risks, benefits, and trustin authorities associated with different sources ofEMF. Means are shown in the first column of Table I.Results of an analysis of variance with repeated mea-sures indicated that participants evaluated the varioussources differently (F(8,7168) = 239.68, p < 0.001).Participants perceived greater risks associated withbase stations (M = 3.26) than with mobile phones(M = 2.93). According to lay people’s assessments,high-voltage transmission lines (M = 3.64) were themost risky source of EMF. The risk assessments ofthe various sources were highly correlated; there-fore, a principal components analysis was conducted.According to the scree plot, a solution with oneprincipal component was sufficient (41.5% varianceexplained). A summative rating scale was constructedthat was used in subsequent analyses. This scale, mea-suring perceived risks associated with EMF, had goodinternal consistency (α = 0.82).

Means of the assessed benefits of selected EMFsources are presented in Column 2 of Table I. Ananalysis of variance with repeated measures yieldeda significant effect, (F(8,7736) = 545.90, p < 0.001).Infrared lamp (M = 2.27) and microwave oven (M =2.41) received low ratings. Ratings for mobile phones(M = 3.36) and for base stations (M = 3.32) wereabove the theoretical middle point of the scale. Ben-efit assessments were highly correlated. Results of aprincipal components analysis showed that one factorwas sufficient to explain the correlations. This solutionexplained 37% of the total variance. The internal con-sistency of this scale, measuring the perceived benefits

Perception of EMF 1257

Table II. Correlations Between Perceived Risks, PerceivedBenefits, and Trust in Authorities

Source PB/PR PR/TR PB/TR

Mobile phones −0.18∗∗ −0.24∗∗ 0.29∗∗Mobile phone base stations −0.14∗∗ −0.24∗∗ 0.28∗∗Radio transmitter −0.11∗∗ −0.14∗∗ 0.21∗∗TV transmitter −0.16∗∗ −0.17∗∗ 0.24∗∗Microwave oven −0.22∗∗ −0.31∗∗ 0.34∗∗TV −0.14∗∗ −0.16∗∗ 0.28∗∗High-voltage transmission lines −0.11∗ −0.17∗∗ 0.29∗∗Infrared lamp (e.g., in restaurants) 0.02 −0.16∗∗ 0.31∗∗Railway power lines −0.13∗∗ −0.13∗∗ 0.28∗∗

PR = perceived risk, PB = perceived benefit, TR = Trust inauthorities.p < 0.01, ∗∗p < 0.001.Note: N varies between 935 and 1,006, reflecting missing values.

associated with various sources of EMF, was good(α = 0.78).

Participants were asked about their level of trustin the authorities responsible for regulating the tech-nologies emitting EMF. The means are shown inColumn 3 of Table I. An analysis of variance withrepeated measures yielded a significant main effect,(F(8,7376) = 191.64, p < 0.001). Mobile phones (M =2.72) and base stations (M = 2.73) received the low-est ratings. The trust ratings were highly correlated. Aprincipal components analysis showed that one factorexplained 57.8% of the total variance. Eigenvalues forthe other factors were below 1. The internal consis-tency of the trust scale was very high (α = 0.91).

Correlations between perceived risks, perceivedbenefits, and trust in authorities for each of the ninetechnologies are shown in Table II. For all items ex-cept infrared lamp, significant negative correlationsbetween perceived risks and perceived benefits wereobserved. Trust in authorities was significantly corre-lated with perceived risks and perceived benefits forall nine items. Results showed that trust was morestrongly related with perceived benefits than withperceived risks. It should also be noted that effectsizes were comparable to those observed in studiesusing convenience samples (Siegrist & Cvetkovich,2000).

To replicate the findings by Siegrist andCvetkovich (2000), showing that correlations betweenperceived risks and perceived benefits were causedby a third variable, trust, partial correlations werecomputed. In Table III, partial correlation coeffi-cients between perceived risks and perceived benefits,controlling for trust, are shown for each item. With

Table III. Partial Correlations Between Perceived Risks andPerceived Benefits, Controlling for Trust in Authorities

Source PB/PR

Mobile phones −0.11∗∗Mobile phone base stations −0.07Radio transmitter −0.08∗TV transmitter −0.13∗∗Microwave oven −0.13∗∗TV −0.10∗High-voltage transmission lines −0.06Infrared lamp (e.g., in restaurants) 0.08Railway power lines −0.10∗∗

PR = perceived risk, PB = perceived benefit.∗p < 0.01, ∗∗p ≤ 0.001.Note: N varies between 935 and 1,006, reflecting missing values.

the exception of the item “infrared lamp,” control-ling for trust resulted in smaller associations betweenperceived risks and perceived benefits.

3.3. Exposure and Perceived Risks and Benefits

Seventy-three percent (n = 735) of the respon-dents were owners of mobile phones. Persons owninga mobile phone perceived significantly lower mobilephone risks (M = 2.86) than persons who did not owna mobile phone (M = 3.12), t (1001) = 3.52, p < 0.001.A smaller but significant difference was observed forrisks associated with base stations: owners of mobilephones perceived significantly lower risks (M = 3.21)than nonowners (M = 3.39), t (997) = 2.30, p < 0.05.Differences in risk perception between participantshaving and participants not having a mobile phonewere larger for mobile phone risks than for base sta-tion risks.

Owners of mobile phones were asked about theirfrequency of usage. Thirty-two percent (n = 217) ofthe respondents reported using their mobile phones0–1 × per week, 29% (n = 200) 2–5 × per week, 14%(n = 96) 6–10 × per week, 13% (n = 90) 11–20 ×per week, and 12% (n = 80) 20 × per week. Correla-tions between the frequency of mobile phone use andperceived risks and benefits associated with mobilephones and base stations are shown in Table IV. Peo-ple who reported frequent use of their mobile phonesperceived fewer risks and more benefits than peoplewho reported infrequent use.

Respondents were asked whether they lived closeto a base station or not. Thirty-six percent (n = 363)indicated that they lived close to a base station, and

1258 Siegrist et al.

Table IV. Correlations Between Risks and Benefits Associatedwith Mobile Phones and Base Stations with Estimated Frequencyof Mobile Phone Use and Estimated Distance from a Base Station

Perceived Risks Perceived Benefits

Mobile Base Mobile BasePhone Station Phone Station

Frequency ofmobilephone use

−0.17∗∗ −0.17∗∗ 0.31∗∗ 0.23∗∗(n = 681) (n = 678) (n = 683) (n = 682)

Distance from abase station

0.05 0.08 0.08 0.11∗(n = 347) (n = 347) (n = 349) (n = 349)

∗p < 0.05, ∗∗p < 0.001.

35% (n = 357) indicated that they did not live closeto a base station. Twenty-nine percent (n = 295) ofthe respondents did not answer this question. Peoplewho believed that they lived close to a base station didnot significantly differ in their level of risks associatedwith base stations from people who did not believethat they lived close to a base station. Respondentsclaiming to live close to a base station were furtherasked to estimate the distance between their homeand the base station. Eight percent (n = 27) of theserespondents chose the category 0–50 m, 11% (n =39) 50–100 m, 41% (n = 144) 100–500 m, and 40%

Table V. Responses to Attitude Questions

Items 1 (%) 2 (%) 3 (%) 4 (%) 5 (%) DN (%)

Electromagnetic radiation pollution emitted by mobile phonebase stations is sufficiently regulated.

15 25 31 14 11 5

For children and teenagers, the use of cell phones should berestricted due to possible health risks.

10 13 17 20 40 1

The health status of people living close to a base stationshould be monitored.

7 10 17 25 41 1

People living close to a base station should participate morethan they have in the past in the decision on where theantennas are built.

8 9 16 22 44 1

Fixing limiting values should always be based on the worstcase.

5 8 19 24 44 1

Electromagnetic radiation pollution from mobile phone basestations causes cancer.

15 20 35 15 11 5

Most chemical substances cause cancer. 17 20 28 17 16 2The way that plants and animal react to electromagnetic

radiation pollution is a reliable predictor how humanswould react.

10 15 27 25 20 4

People are overly worried that they could develop cancer dueto electromagnetic radiation pollution.

14 17 29 19 19 2

Note: Respondents were asked to express their attitude using a number between 1 (indicating no agreement at all) and 5 (absolutelyagreement).

(n = 139) 500 m and more. Correlations between es-timated distances and perceived risks and perceivedbenefits associated with mobile phones and base sta-tions are shown in Table IV. No significant associationwas observed for estimated distance and risks asso-ciated with a base station. A significant, but small,correlation was observed for estimated distance andbenefits associated with a base station (r = 0.11, p <

0.05)

3.4. Attitudes Toward and Beliefs about EMF

Responses to questions about attitudes towardand beliefs about EMF are shown in Table V. A sub-stantial segment of the participants was not convincedthat mobile phone base stations were regulated suf-ficiently. Given the fact that the limiting values inSwitzerland are lower than in most other Europeancountries (Wiedemann et al., 2001), this result is sur-prising. Participants were especially concerned aboutsituations in which children and teenagers were in-volved. Sixty percent of the participants agreed that,for children and teenagers, the use of cell phonesshould be restricted due to possible health risks. Sixty-six percent of the respondents were in favor of moni-toring the health status of people living close to basestations, and 66% were also convinced that peopleliving close to base stations should be involved in the

Perception of EMF 1259

process of deciding where to build a base station. Peo-ple strongly believed that limiting values should bebased on worst-case scenarios. Sixty-eight percent ofthe respondents agreed with this approach, with only13% disagreeing.

Thirty-six percent of the respondents believedthat EMF emitted by mobile phone base stationscauses cancer. As a comparison, respondents wereasked to express their agreement or disagreementwith the statement, “Most chemical substances causecancer.” Participants agreed slightly more with thestatement related to chemical substances than withthe statement related to EMF. However, responses tothe two statements were highly correlated, r = 0.46(p < 0.001).

Participants were rather confident in their beliefthat the ways in which plants and animals react toelectromagnetic radiation pollution are reliable pre-dictors of how humans would react. Forty-five percentof the respondents agreed with this statement, andonly 25% disagreed. Respondents expressing highlevels of confidence in plant and animal experimentswere more convinced that electromagnetic radiationcauses cancer than persons lacking such confidence,r = 0.32 (p < 0.001).

Trust in the authorities who regulate base stationswas negatively correlated with the judgment that newregulations are necessary. Trust in these authoritieswas also significantly correlated with responses to-ward the items “electromagnetic radiation pollutionemitted by mobile phone base stations is sufficientlyregulated” (r = 0.29, p < 0.001), “the health status ofpeople living close to a base station should be mon-itored” (r = −0.13, p < 0.001), “people living closeto a base-station should participate more than theyhave in the past in the decision on where to build theantennas” (r = −0.23, p < 0.001), and “fixing limit-ing values should always be based on the worst case”(r = −0.18, p< 0.001).

3.5. Knowledge about EMF and its Regulation

People’s knowledge about EMF was assessed bytwo questions. Past research indicates that some peo-ple can detect 50 Hz electromagnetic fields (Leitgeb& Schrottner, 2003; Mueller et al., 2002). Sixty-fivepercent of the participants (n = 666) were convincedthat there are persons who can detect such fields, 16%(n = 161) chose the neutral point of the scale, and 16%(n = 166) did not believe that humans could detectweak electromagnetic fields. Most respondents cor-rectly answered a question on whether the earth has

a natural electric field. Eighty-six percent answered“yes” (n = 874), 4% answered “no” (n = 43), and 9%(n = 95) answered “don’t know.”

As pointed out earlier, regulations regardingEMF are much stricter in Switzerland than in mostEuropean countries (Wiedemann et al., 2001). How-ever, only 39% (n = 394) of the respondents chosethe “more severe” option in response to the question,“Are the regulations regarding mobile phone base sta-tions in Switzerland more severe, comparably severe,or less severe than in most EU countries?” Thirty-twopercent of the respondents (n = 327) chose “compa-rably severe,” 7% (n = 70) chose “less severe,” and22% (n = 221) responded with “don’t know.”

Perception of current regulations influenced re-actions to the statement, “People are overly wor-ried that they could develop cancer due to electro-magnetic radiation pollution.” An analysis of vari-ance indicated significant differences, F(3,993) = 3.85,p < 0.01. Means shown in Table VI suggest thatawareness of regulations reduced perceived risks thatelectromagnetic radiation pollution could cause can-cer. Thus, public awareness of strong limiting val-ues might decrease the levels of perceived risks as-sociated with base stations and other sources ofEMF.

The various mobile phone companies couldchoose to build their base stations at the same orat different locations. Respondents were confrontedwith the following question: “From the standpoint ofpublic health, what is the most reasonable approachfor locating base stations in a residential area? Asmany base stations as possible at the same location,as many locations as possible, or does it not matterat all?” Twenty-four percent of the respondents (n =243) were convinced that locating as many base sta-tions as possible at the same location would be best

Table VI. Mean Responses (Standard Deviations) to theStatement “People Worry Too Much that They Could Develop

Cancer Due to Electro-Smog” Subject to Perceived SwissRegulations

Assessment of the Regulations in SwitzerlandCompared with Most EU Countries

More Severe Similar Less Severe Don’t Know

3.27b (1.29) 3.11a,b (1.24) 2.87a (1.45) 2.95a,b (1.35)(n = 388) (n = 324) (n = 70) (n = 215)

Note: N = 997. Means with different superscripts (a, b) are signifi-cantly different (Tukey-test, p < 0.05). Respondents were askedto express their attitude using a number between 1 (indicating noagreement at all) and 5 (absolutely agreement).

1260 Siegrist et al.

for public health. Forty percent of the respondents(n = 400) would choose as many locations as possible.Eighteen percent of the respondents (n = 181) chose“doesn’t matter” option, and another 18% (n = 184)chose “don’t know.”

3.6. Results of a Multiple Regression Analysis

The influences of several predictors on the per-ceived risks associated with EMF were examinedthrough the use of multiple regression analysis. Paststudies have indicated that benefit and trust both af-fect perceived risks (Siegrist, 2000). Therefore, thetrust and benefit scales as described in Section 3.2were entered as predictors. Several studies have ob-served gender differences in risk perception. Womenseem to be more concerned than men about risks as-sociated with technologies (Brody, 1984; Greenberg& Schneider, 1995). Gender therefore was added aspredictor in the regression analysis. The two knowl-edge questions (“There are persons who can detectweak electromagnetic fields,” and “The earth has anatural electro-magnetic field”) were also included inthe analysis.

People may perceive substances produced by hu-mans as carcinogenic. Responses to the item “Mostchemical substances cause cancer” were utilized as ameasure for the conviction that “artificial” substancescause harm, and added to the regression predictors.A study by Slovic et al. (1995) suggests that most tox-icologists disagree with this item.

In a recent article, Sjoberg and af Wahlberg (2002)found that higher consciousness beliefs and beliefin paranormal phenomena were correlated with per-

Table VII. Results of MultipleRegression Analysis with Perceived

Risks Associated with EMF asDependent Variable

Independent Variables Standardized Coefficients t-Value

Gendera 0.09∗ 3.06Belief in paranormal phenomena 0.15∗∗ 4.70Most chemical substances cause cancer 0.22∗∗ 7.28There are persons who can detect weak

electromagnetic fields0.10∗ 3.02

The earth has a natural electromagneticfieldb

−0.01 −0.44

Benefit −0.17∗∗ −5.25Trust −0.16∗∗ −4.96Languagec −0.02 −0.52

∗p < 0.01; ∗∗p ≤ 0.001.aMale was coded as 0, female as 1.bResponse “no” and “don’t know” were coded as 0, response “yes” was coded as 1.cGerman-speaking part was coded as 0, the French-speaking part as 1.Note: N = 927, R2 = 0.23, adjusted R2 = 0.22.

ceived risks. In the present study, three items mea-suring belief in paranormal phenomena were utilized(e.g., “Spiritual healing and laying on of hands aremore effective than scientists believe,” “Rose quartzhelps protect against rays emitted by screens”). Asummative rating scale was constructed and used inthe multiple regression analysis. This scale, measuringbelief in paranormal phenomena, has a satisfactoryinternal consistency (α = 0.69).

Finally, the dummy variable “Language” was en-tered in the regression analysis. This variable coulduncover possible differences in risk perception be-tween respondents from the German- and French-speaking parts of Switzerland.

Results of the multiple regression analysis, shownin Table VII, suggest that there are people who gen-erally believe that man-made substances cause harm.The item “Most chemical substances” was the pre-dictor with the highest standardized coefficient. Forthe variables “Benefit” and “Trust,” expected resultswere observed. People perceiving more benefits intechnologies emitting EMF and having more trust inthe authorities responsible for regulating these tech-nologies perceived lower risks than people perceivingfewer benefits and having less trust. People believingin paranormal phenomena, and being skeptical aboutscience, perceived higher risks than people havingconfidence in science and not believing in paranormalphenomena. The knowledge item “There are personswho can detect weak electromagnetic fields” had apositive influence on perceived risks. However, theknowledge question “The earth has a natural electro-magnetic field” was not a significant predictor. Onereason for the latter result might be that relatively

Perception of EMF 1261

few people answered this question incorrectly. Forgender, the expected result was observed. Womenperceived higher risks than men. Finally, respondentsfrom the German-speaking part of Switzerland didnot differ in the level of perceived risks from theirFrench-speaking counterparts.6

4. DISCUSSION

Results of the present study indicate that, for amajority of Swiss people, base stations for mobilephones evoke negative associations. Most respon-dents mentioned abstract associations like electro-magnetic radiation pollution, irradiation, or illnesses.However, free associations evoked by the term “basestation” were less negative and much more abstractthan those obtained for gene technology (Siegrist,2003) or for a nuclear waste repository (Slovic et al.,1991). The negative/positive assessment of the associ-ations evoked by “base station” was significantly cor-related with perceived risks. People who expressednegative associations of base stations perceived morerisks than people describing neutral or positive im-ages. Results of the present research, therefore, arein line with recent studies suggesting that the affectheuristic is an important determinant of risk percep-tion (Finucane et al., 2000; Slovicet al., 2002; Slovicet al., 2004).

Participants evaluated risks of different sourcesof EMF. Lay people’s risk assessments for high-voltage transmission lines were higher than for mobilephone base stations. Interestingly, there are public dis-cussions about base stations and their possible healtheffects, but there are almost no discussions about high-voltage transmission lines in Switzerland anymore.One explanation for this result is the fact that thereare currently many more cases of base station con-struction than transmission line construction.7 Basedon the risk assessments and the associations evokedby the term “base station,” it can be concluded that asignificant part of the population might endorse localopposition against new base stations.

Participants were especially concerned about sit-uations in which children and teenagers are involved.Sixty percent of the participants agreed that the use

6 An anonymous reviewer suggested that age could influenceperceived risks associated with EMF. Inclusion of age in theregression analysis showed, however, that age is not a significantpredictor.

7 This explanation was suggested by an anonymous reviewer.

of cell phones by children and teenagers should berestricted due to possible health risks. Lay people’sassessments seem to be in line with experts’ assess-ments that preadolescent children may be more vul-nerable than adults (Hyland, 2000). Whether parentsin fact discourage the use of cell phones because theyfear adverse health effects cannot be answered on thebasis of the present study, of course. This and otherquestions related to possible restrictions in the usageof cell phones due to fear of health risks should beexamined in future studies.

Perceived risks of various sources of EMF werehighly correlated. Those persons who are concernedabout risks associated with mobile phone base sta-tions are also concerned about other sources of EMF,such as high-voltage transmission lines or microwaveovens. Perceptions of benefits and trust ratings werehighly correlated as well.

With the exception of the infrared lamp hazard,negative correlations between perceived risks andperceived benefits were observed. We, therefore, suc-cessfully replicated findings of earlier studies in whichrisk ratings and benefit ratings were also correlated(Alhakami & Slovic, 1994). Further analyses showedthat, for all nine hazards, trust was significantly corre-lated with perceived risk and perceived benefit. Con-trolling for trust substantially reduced correlationsbetween benefits and perceived risks. Findings of ear-lier studies (Siegrist & Cvetkovich, 2000)—that trustin institutions that regulate hazards influences lev-els of perceived risks and benefits—were successfullyreplicated. Since trust can be viewed as a form of af-fect (Jones, 1996), results of the present study furthersupport the hypothesis that affect is an important fac-tor in risk perception (Finucane et al., 2000; Slovicet al., 2002).

Perceived risks and frequency of mobile phoneuse were negatively correlated. People who usedtheir mobile phones frequently perceived fewer risksthan people who used their mobile phones infre-quently. Familiarity with a technology may reducerisks perceived. However, an alternative explanationcannot be ruled out. It could be that people who per-ceive more risks use their mobile phones less fre-quently than people who are not concerned aboutEMF.

There was no correlation between the estimateddistance from one’s home to the closest base stationand the risks associated with a base station. One rea-son for this result could be that people underestimatethe rate at which EMF levels decrease with increasing

1262 Siegrist et al.

distance from a source. Such an explanation is sup-ported by Morgan et al. (1990), who found that peoplestrongly underestimated the rate at which EMF de-creases with distance from source.

Although the regulations regarding EMF aremuch stricter in Switzerland than in most Europeancountries (Wiedemann et al., 2001), only 39% of therespondents were correct about this comparison. Fur-ther, people who were aware of the strong regulationsin Switzerland perceived lower risks than people whowere not aware of them. These results suggest, there-fore, that regulations may decrease perceived risks.Strict regulations are not sufficient; the existence ofsuch measures must be communicated to the public.There is an alternative explanation for the observedresults, however. People who are better informedabout regulations may also be better informed aboutthe low risks from mobile phones.

Lack of trust comes at a high price for society.Participants who had low levels of trust in the author-ities responsible for regulating base stations asked formore regulations than people with high levels of trust.The stricter regulations some people are asking for areexpensive. The results of the present study suggest,therefore, that lack of trust leads to higher transac-tion costs. As a consequence, lack of trust can make atechnology more expensive due to an accompanyingdemand for stricter regulations. It is an open ques-tion, at present, whether the costs of stricter regula-tions outweigh the costs that may be associated withpossible health effects.

Utilizing multiple regression analysis, the impactsof a variety of factors on the perception of EMF riskswere examined. Reaction to the item “Most chemi-cal substances cause cancer” was the best predictor.People who are concerned about chemical substancesare also concerned about EMF. This suggests that,for some people, technology is associated with harm,and, for other people, technology is not primarily as-sociated with harm. Belief in paranormal phenom-ena was also a significant predictor. Results observedby Sjoberg and af Wahlberg (2002) were successfullyreplicated. The influence of these two predictors sug-gests that beliefs not supported by most scientists caninfluence lay perceptions of risk. The study of Slovicet al. (1995) suggests, for example, that a majorityof toxicologists do not agree with the statement thatmost chemicals do cause cancer. Thus, scientific ar-guments on the safety of EMF may not be effec-tive in changing the minds of people who are con-cerned about all chemicals and people who believe

in paranormal phenomena. We may have to acceptthat, for some people, a scientific discourse is nota valid discourse and, therefore, does not influencetheir perceptions of risk. This is a challenge for riskcommunication because scientific arguments may bemost convincing for people who are not concernedabout EMF. People who perceive EMF as risky be-lieve less in science and are, therefore, more skepticalwhen confronted with scientific evidence.

Overall, participants indicated that they wouldlike to have tough regulations and stronger involve-ment of the people living close to a base station. Thiscomes with a price tag, of course. The question ofwhether people would still ask for tougher regula-tions if they had to pay more for the usage of cellphones cannot be answered, however, on the basis ofthe results of this study.

Some limitations of the present study should beaddressed. The person answering the phone, not arandom person in the household, was interviewed.This might be a bias. Furthermore, due to the cho-sen sampling strategy, smaller households are over-represented in the sample. In the present survey, onlyEMF risks were examined. Participants have the ten-dency to use the entire response scale, regardless ofthe risks examined. Therefore, one should be cautiousin interpreting the absolute values and in comparingthem with results of other studies. A large number ofstatistical tests were employed in the present study.As a result, the p-values may be inflated and shouldbe interpreted with some caution.

An alternative explanation of the results in thepresent survey would be that education influencestrust, belief in paranormal phenomena, and riskperception.8 Past research suggests that educationweakly influences trust in government (Dalton, 2005).In the present survey, education was not measured,and this alternative explanation cannot be tested.Given the weak influence of education on trust, how-ever, it does not seem likely that the correlations ob-served in the present study would vanish if educationlevel were statistically controlled.

The present study utilized a quantitative surveyapproach. Consequently, the question of why somepeople think that cell phones or power lines are riskycannot be fully answered. It remains unclear how,according to the thinking of some lay people, EMFmay influence health. In future studies, the mental

8 This alternative explanation was suggested by an anonymousreviewer.

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model approach (Cox, Niewohner et al., 2003; Morganet al., 2002), combined with the think-aloud method(Earle, 2003), should be used. Such research couldprovide the basis for a better understanding of therisk perception of lay people in the domain of elec-tromagnetic fields.

ACKNOWLEDGMENTS

The article is based on work supported by theResearch Cooperation Sustainable Mobile Commu-nication, ETH Zurich, Switzerland.

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