The authors test for differences in risk perceptions among different age groups

Field, Juanita V.

Schreer, George E.

English

UNH Scholars' Repository

RISK: Health, Safety & Environment (1990-2002)Volume 11 | Number 4 Article 4September 2000Age Differences in Personal Risk Perceptions: ANote on an Exploratory Descriptive StudyJuanita V. FieldGeorge E. SchreerFollow this and additional works at: https://scholars.unh.edu/riskPart of the Behavior and Behavior Mechanisms Commons, Cognition and Perception Commons,and the Developmental Psychology CommonsThis Article is brought to you for free and open access by the University of New Hampshire – School of Law at University of New Hampshire Scholars'Repository. It has been accepted for inclusion in RISK: Health, Safety & Environment (1990-2002) by an authorized editor of University of NewHampshire Scholars' Repository. For more information, please contact ellen.phillips@law.unh.edu.Repository CitationJuanita V. Field & George E. Schreer, Age Differences in Personal Risk Perceptions: A Note on an Exploratory Descriptive Study, 11 RISK287 (2000).Age Differences in Personal Risk Perceptions:A Note on an Exploratory Descriptive StudyJ uanita V. Field & George E. Schreer*IntroductionAge is the primary independent variable in developmentalpsychology research. Such research is often descriptive in nature: itinvolves comparing participants of different ages with regard to somebehavior (the dependent variable) in order to determine whether thebehavior may be differently described for different age groups.Knowing how perception of risk varies with age has practicalsignificance as well as theoretical importance. The purpose of thecurrent research is to examine how risk perception varies with age.Using typical social science format, this paper will first review theliterature related to developmental perception of risk. Then the methodused in the current study will be presented, followed by the statisticalresults and, finally, a discussion of our conclusions and theirimplications.While no studies were found using age as the independent variableand risk perception as the dependent variable, there are numerousstudies reported in the literature which examine personal risk andpreventive behaviors in children and adolescents. Most of these studiesare concerned with discovering relationships that may be used todiscourage risky behaviors (smoking, drinking) and encouragepreventive behaviors (exercise, healthy diet).1* Professor Field is Chair of the Psychology Department, Plymouth State College. Sheholds a Ph.D. (Lifespan Developmental Psychology) from West Virginia University. E-mail:jfield@oz.plymouth.edu. Professor Schreer holds a Ph.D. (Social Psychology) from SyracuseUniversity. He teaches in the Psychology Department, Manhattanville College.1 See, e.g., Barbara J. Tinsley et al., A Multimethod Analysis of Risk Perceptions andHealth Behaviors in Children, 57 Educ. & Psychol. Measurement 197 (1997); Barbara P.Hazard & Che-Fu Lee, Understanding Youth's Health-Compromising Behaviors in Germany:An Application of the Risk-Behavior Framework, 30 Youth & Soc'y 348 (1999); Susan Moore& Eleanora Gullone, Predicting Adolescent Risk Behavior Using a Personalized Cost-BenefitAnalysis, 25 J. Youth & Adolescence 343 (1996); Michael D. Resnick et al., ProtectingAdolescents from Harm: Findings from the National Longitudinal Study on AdolescentHealth, 278 JAMA 823 (1997).11 Risk Health, Safety & Environment 287 [Fall 2000]Both the "Theory of Reasoned Action" 2 and the "Health BeliefModel"'3 have been used as theoretical structures for research on risk;both assume rational behavior and both have been used to try to predictand control risk behaviors in different age groups. Neither modelspecifically addresses age as an independent variable in risk perception,although there is a recognition among scholars that age differences inperception of risk may influence behavior. For example, Moore andGullone applied a personalized cost-benefit analysis based on theassumption that adolescents define risk differently from the way adultsdefine it.4 The authors correlated perception of risk with actualbehavior and used the perception of positive and negative outcomes toexplain why adolescents and adults might view risks differently.Specifically, Moore and Gullone found adolescents engaged in behaviorthat the adolescents knew was risky. Based on this finding, they arguedthat, for adolescents, the possibility of pleasant outcomes outweigheddelayed or ambiguous negative outcomes which, for adults, might havehad a more deterrent or threatening effect. 5 Moore and Gulloneconcluded that adult emphasis on the dangers of some behaviors mightnot be an effective strategy for deterring adolescent participation in thebehaviors due to the differences in perceptions of positive and negativeoutcomes. 6 The necessity for altering models of rational behavior toinclude alternative meanings for different age groups is a strongargument for examining perception of personal risk as a function of age.The literature also provides guidance in terms of methodology.Slovic, Fischhoff, and Lichtenstein provided a basic model for askingparticipants to rank risks.7 Finucane and Maybery conducted a studyin Australia and compared their results with other cross-cultural studiesof rankings of the risks used in the original Slovic et al. study.8 They2 Icek Ajzen & Martin Fishbein, Understanding Attitudes and Predicting Social Behavior(1980).3 N. Janz & M.H. Becker, The Health Belief Model: A Decade Later, 11 Health Educ. Q.1 (1984).4 Moore & Gullone, supra note 1.5 See id.6 Id.7 Paul Slovic et al., Rating the Risks, 21 Env't 14 (1979).8 Id.; Melissa L. Finucane & Murray T. Maybery, Risk Perceptions in Australia, 79Psychol. Rep. 1331 (1996).Field & Schreer: Age Differences in Personal Risk Perceptions 289provided participants with 30 risk items on index cards; participantsordered the items from least risky to most risky and then rated eachitem for amount of risk in comparison to the other items. Thedefinition of risk was present risk of death from the hazard. Finucaneand Maybery concluded that while the five hazards ranked highest inrisk were similar for Australians, Americans, Norwegians, andHungarians, the differences suggested the necessity of investigating riskin specific populations and cultural groups. 9 It is a logical extension ofthis method to study participants of different age groups in order todetermine whether the cross-cultural similarities and differences alsoapply across ages.The current study developed from the literature concerningperception of personal risk and prevention among different age groupsand the literature using the methodology of ranking risks. The purposeof this research is to describe differences in perception of personal riskin different age groups.MethodParticipantsData was collected from 127 participants. Table 1 provides thefrequencies of gender and age groups. Participants were tested in apublic school, a summer program for adolescents, and college classes.The small number of participants in the youngest group reflects thedifficulty of obtaining permission to contact young children in groupsituations, particularly through schools. At the summer program,parents were asked directly for permission to contact their children, andTable 1Number and Percent of Participants by Age Level and GenderGender Age Level8-9 Years 11-15 Years 17-23 Years TotalMale 10 (7.8%) 31(24.4%) 28 (22.05%) 69 (53.5%)Female 4 (3.1%) 26 (20.5%) 28 (22.05%) 58 (45.7%)Total 14 (11.0%) 57 (44.9%) 56 (44.1%)9 Finucane & Maybery, supra note 8.11 Risk Health, Safety & Environment 287 [Fall 2000]all but two of those asked signed the parental consent letters. Bycontrast, seven of eight schools contacted would not give permission tosend letters to parents. Parental permission in terms of informedconsent was secured for all participants below college age. Adolescentand college student participants provided informed consent.Participants were from a relatively rural area of New England andattended small schools.MaterialsQuestionnaires were developed specifically for this study. Riskbehaviors were chosen on the basis of previous research, and participantswere asked to rank the behaviors in order of perceived risk and also torate the level of risk perceived to be associated with each behavior. Forsome of the behaviors, participants were also asked whether theyparticipate in the behavior. Whenever possible, the items chosen werethe same as those used by Slovic et al. and Finucane and Maybery. 10There were, however, some limitations upon the use of the entire listfrom the previous studies. For example, the current study focused onperception of personal risk associated with one's own behavior, sobroader hazards such as nuclear power and pesticides were excluded.Because of the sensitive nature of some of the behaviors, only sixwere used with all methods and all age groups. It would have beeninappropriate, for example, to ask eight-year-olds if they participate inunprotected sex. The behaviors used for all age groups were skiing,smoking cigarettes, playing soccer, playing computer games, drinkingalcohol, and not wearing a seatbelt in a car. The older participants werealso asked about using illegal drugs, using handguns, havingunprotected sex, ignoring stop signs, mountain climbing, hunting,swimming, and.biking. Some items were added to the list based on aprevious study of these behaviors by the current investigators andcolleagues. 11On the first questionnaire, given to all age groups, participants wereasked to indicate on a four-point scale how risky each behavior wasperceived to be and whether they participate in the behavior themselves.10 Slovic et al., supra note 7; Finucane & Maybery, supra note 8.11 See John Kulig et al., Consensus Estimates of Risky Behaviors: False Consensus forFriends but not the General Population. Poster presented at the NEPA Annual Mtg., Prov., RI(1998).Field & Schreer: Age Differences in Personal Risk Perceptions 291Rather than risk of death, as used in earlier studies, the questionnaireasked for ratings based on likelihood and degree of getting hurt. Again,this had to be appropriate for third graders, and to satisfy schoolauthorities and parents that the questionnaire itself did not pose anyrisk to the participants. The second questionnaire, given only to the twoolder groups, provided fourteen behaviors on randomly arranged cardsand asked participants to arrange the cards in order of risk. Participantswere then asked to rate each behavior independently on a ten-pointscale.Design and ProcedureThis was a cross-sectional study comparing three age groups;participants were tested in groups and responded to self-reportquestionnaires concerning their perceptions of risk associated withvarious behaviors. Three levels of age were delineated: 8-9 years(children), 11-15 years (adolescents), and 17-23 years (adults) based onthe ages of the participants and the normal age grades in the culture.Data was analyzed using a number of statistical procedures describedbelow. Since a number of statistical tests were conducted, a significancelevel of .01 was required to avoid capitalization on chance.ResultsTo determine whether perception of risk for the six variousbehaviors (alcohol, computer, seatbelt, skiing, smoking, and soccer)varied with age, ANOVAs were calculated for each of the behaviorswith age as the independent variable. A significant difference in riskratings by different age levels was found only for skiing F(2,123)=6.67,p=.002. The youngest group (8-9 years) perceived skiing as significantlymore risky than did the other age groups. Table 2 contains the meanrisk ratings by age levels. No significant effects for gender were found;therefore, gender was not a variable in subsequent analyses.For the older groups, scores were available for fourteen behaviors.Comparisons were made for the two older age groups (adolescent, 11-15, and adult, 17-23) by calculating t-tests using the ratings of risk asthe measure of the dependent variable. Adults, compared toadolescents, rated skiing as significantly more risky: t(98)=3.32, p=.001.This was the only age difference found between the adult and11 Risk: Health, Safety & Environment 287 [Fall 2000]adolescent groups on the fourteen variables analyzed using ratings as thedependent variable. When the rankings were used as the dependentvariable, Mann-Whitney tests revealed a significant difference betweenadults and adolescents in perception of risk for ignoring stop signs(p=.002). Adults gave higher risk rankings to ignoring stop signs ascompared to adolescents.Table 2Mean Risk Ratings* by Age Level and Behavior (for ANOVA)Behavior Age Level8-9 Years 11-15 Years 17-23 YearsAlcohol 3.9386 3.6429 3.5000Computer 1.0000 1.3571 1.1607Seatbelt 3.4286 3.4821 3.7143Skiing 3.7143 2.9107 3.1250Smoking 3.9286 3.6250 3.6786Soccer 2.9286 2.4821 2.6607* Rating of 1 to 4, 4=highest risk.A cross-cultural and cross-time analysis was conducted bycomparing relative rankings given by participants with rankings fromthe studies by Slovic et al. and Finucane and Maybery for the variableswhich the three studies examined in common. 12 Slovic et al.published rankings by U.S. participants in 1979, and Finucane andMaybery studied some of the same variables in 1996 in Australia. 13Table 3Rankings of Risk Behaviors from Three StudiesRanksRisk Finucane (1996) Slovik (1979) Field (1999)University College Adoles & CollegeSmoking .1 2 2Drinking 3 3 3Skiing 8 7 6Handguns 2 1 1Climbing 4 5 5Biking 5 6 7Swimming 6 8 8Hunting 7 4 412 Slovic et al., supra note 7; Finucane & Maybery, supra note 8.13 Id.Field & Schreer: Age Differences in Personal Risk Perceptions 293Thus, for the shared variables, adding the current study allowscomparing rankings in the U.S. and Australia at three different points intime. Table 3 lists the common variables and the relative rankings in thethree studies. A Friedman 2-way ANOVA found no significantdifferences between the ranks, given the same variables in two culturesat three different times.Table 4 contains the rankings provided by adolescents and adults inthe current study. Differences between adult and adolescent rankingsare few and minor; this is consistent with the above results.Table 4Ranks of Risk Behaviors by Adolescents and AdultsAge LevelAdolescent AdultBehavior Mean Median Relative* Mean Median Relative*Alcohol 5.41 5.00 5.0 6.20 6.00 6.5Biking 10.69 11.00 11.0 11.07 11.00 11.0Climbing 7.80 9.00 9.0 8.51 9.00 9.0Computer games 12.78 14.00 14.0 13.20 14.00 14.0Drugs 2.74 2.00 1.0 3.27 3.00 2.5Guns 4.79 4.00 3.5 3.93 3.00 2.5Hunting 6.93 7.50 8.0 7.75 8.00 8.0Seatbelts 6.09 6.00 6.5 6.20 6.00 6.5Sex (unprotected) 4.04 3.00 2.0 2.93 2.00 1.0Skiing 9.61 10.00 10.0 9.25 10.00 10.0Smoking 5.28 4.00 3.5 5.15 5.00 4.5Soccer 11.91 13.00 13.0 11.60 12.00 12.5Stop sign 6.20 6.00 6.5 4.78 5.00 4.5Swimming 10.98 11.50 12.0 11.20 12.00 12.5*Relative rank is rank within this array of median ranks.In order to determine whether actual performance of the behaviorwas related to perception of risk, for the variables for which this datawas collected on all participants (alcohol, computer, seatbelt, skiing,smoking, and soccer), Chi-square analyses with accompanying etacoefficients revealed significant relationships for (N=126) alcohol(p=.001, accounted for by high frequencies for adolescents) and seatbelt(p=.0002, accounted for by high frequencies for adolescents andadults). Thus, performance was related to perception of risk for alcoholby adolescents and for seatbelt by both adults and adolescents;participants who performed the behavior also perceived it to be risky.11 Risk. Health, Safety & Environment 287 [Fall 2000]Discussion and ConclusionThe most significant result of the current study is the finding of noage differences in perception of risk for most of the behaviors studied.The finding of no age differences in perception of risk for thesebehaviors means that people of all ages share a perception of how muchrisk is associated with each of the behaviors. Admittedly, the currentstudy is exploratory, and the number of children was limited. However,given the limitations, the results do suggest that it may not be necessaryto consider age as a factor in analysis of risk perception.Perhaps one reason for the dearth of studies is the difficulty ofcollecting data from children. Our societal concern with protectingyoungsters from risks may have resulted in children becomingunavailable as research participants as well as limitations on topics aboutwhich researchers may question children. Thus, knowing it is notnecessary to test children would have significant practical value.Finding no age differences in perception of personal risk has animportant implication in addition to that discussed above. By thirdgrade (8-9 years of age), we have made children aware of the personalrisks we, as adults, want them to be aware of. The question then iswhether the programs we supply to adolescents in an attempt to detertheir risk-taking is over-kill, or even counterproductive. Adult efforts atdeterrence identify the risks we are most concerned about. And theadolescent, developmentally predisposed to rebellion and risk-taking,knows exactly which behaviors to perform in order to create the mostconcern among adults. Applying Moore and Gullone's cost-benefitanalysis, the positive outcomes associated with rebellion and risk-taking(particularly reinforcement from peers) in terms of adult concern andoutrage may explain the attraction of behaviors which the adolescenthas recognized as risky since at least age eight. 14 We concur withMoore and Gullone's conclusion that adult identification of risks andassociated dangers may be an inappropriate strategy for reducing risktaking by adolescents. 15 This argument is not likely to be consideredpolitically correct in the current climate, but it is a notion which shouldbe explored with additional research. It may be that sensitizing children14 Moore & Gullone, supra note 1.15 IdField & Schreer: Age Differences in Personal Risk Perceptions 295to risks through about the third grade is all that is necessary ordesirable.It is interesting to note that the cross-culture and cross-timecomparisons of rankings of risk behaviors identified commonality inhow people in general perceive risk. Australians and Americans tendedto rank risky behaviors in essentially the same order, and Americanshave not changed with regard to that ranking over the last 20 years.Furthermore, the authors find it remarkable that these rankings weresimilar despite differences in instructions and procedures as well asdifferences in culture and time. The similarities must be incrediblyrobust to withstand the potential confounding influences of differenttimes, cultures, instructions, and procedures. A finding of differenceswould have been easily explained; the finding of commonality isamazing under the circumstances.11 Rislc Health, Safety & Environment 287 [Fall 2000]

Age Differences in Personal Risk Perceptions: A Note on an Exploratory Descriptive Study

University of New Hampshire

RISK: Health, Safety & Environment (1990-2002)
Volume 11 | Number 4 Article 4
September 2000
Age Differences in Personal Risk Perceptions: A
Note on an Exploratory Descriptive Study
Juanita V. Field
George E. Schreer
Follow this and additional works at: https://scholars.unh.edu/risk
Part of the Behavior and Behavior Mechanisms Commons, Cognition and Perception Commons,
and the Developmental Psychology Commons
This Article is brought to you for free and open access by the University of New Hampshire – School of Law at University of New Hampshire Scholars'
Repository. It has been accepted for inclusion in RISK: Health, Safety & Environment (1990-2002) by an authorized editor of University of New
Hampshire Scholars' Repository. For more information, please contact ellen.phillips@law.unh.edu.
Repository Citation
Juanita V. Field & George E. Schreer, Age Differences in Personal Risk Perceptions: A Note on an Exploratory Descriptive Study, 11 RISK
287 (2000).
Age Differences in Personal Risk Perceptions:
A Note on an Exploratory Descriptive Study
J uanita V. Field & George E. Schreer*
Introduction
Age is the primary independent variable in developmental
psychology research. Such research is often descriptive in nature: it
involves comparing participants of different ages with regard to some
behavior (the dependent variable) in order to determine whether the
behavior may be differently described for different age groups.
Knowing how perception of risk varies with age has practical
significance as well as theoretical importance. The purpose of the
current research is to examine how risk perception varies with age.
Using typical social science format, this paper will first review the
literature related to developmental perception of risk. Then the method
used in the current study will be presented, followed by the statistical
results and, finally, a discussion of our conclusions and their
implications.
While no studies were found using age as the independent variable
and risk perception as the dependent variable, there are numerous
studies reported in the literature which examine personal risk and
preventive behaviors in children and adolescents. Most of these studies
are concerned with discovering relationships that may be used to
discourage risky behaviors (smoking, drinking) and encourage
preventive behaviors (exercise, healthy diet).1
* Professor Field is Chair of the Psychology Department, Plymouth State College. She
holds a Ph.D. (Lifespan Developmental Psychology) from West Virginia University. E-mail:
jfield@oz.plymouth.edu. Professor Schreer holds a Ph.D. (Social Psychology) from Syracuse
University. He teaches in the Psychology Department, Manhattanville College.
1 See, e.g., Barbara J. Tinsley et al., A Multimethod Analysis of Risk Perceptions and
Health Behaviors in Children, 57 Educ. & Psychol. Measurement 197 (1997); Barbara P.
Hazard & Che-Fu Lee, Understanding Youth's Health-Compromising Behaviors in Germany:
An Application of the Risk-Behavior Framework, 30 Youth & Soc'y 348 (1999); Susan Moore
& Eleanora Gullone, Predicting Adolescent Risk Behavior Using a Personalized Cost-Benefit
Analysis, 25 J. Youth & Adolescence 343 (1996); Michael D. Resnick et al., Protecting
Adolescents from Harm: Findings from the National Longitudinal Study on Adolescent
Health, 278 JAMA 823 (1997).
11 Risk Health, Safety & Environment 287 [Fall 2000]
Both the "Theory of Reasoned Action" 2 and the "Health Belief
Model"'3 have been used as theoretical structures for research on risk;
both assume rational behavior and both have been used to try to predict
and control risk behaviors in different age groups. Neither model
specifically addresses age as an independent variable in risk perception,
although there is a recognition among scholars that age differences in
perception of risk may influence behavior. For example, Moore and
Gullone applied a personalized cost-benefit analysis based on the
assumption that adolescents define risk differently from the way adults
define it.4 The authors correlated perception of risk with actual
behavior and used the perception of positive and negative outcomes to
explain why adolescents and adults might view risks differently.
Specifically, Moore and Gullone found adolescents engaged in behavior
that the adolescents knew was risky. Based on this finding, they argued
that, for adolescents, the possibility of pleasant outcomes outweighed
delayed or ambiguous negative outcomes which, for adults, might have
had a more deterrent or threatening effect. 5 Moore and Gullone
concluded that adult emphasis on the dangers of some behaviors might
not be an effective strategy for deterring adolescent participation in the
behaviors due to the differences in perceptions of positive and negative
outcomes. 6 The necessity for altering models of rational behavior to
include alternative meanings for different age groups is a strong
argument for examining perception of personal risk as a function of age.
The literature also provides guidance in terms of methodology.
Slovic, Fischhoff, and Lichtenstein provided a basic model for asking
participants to rank risks.7 Finucane and Maybery conducted a study
in Australia and compared their results with other cross-cultural studies
of rankings of the risks used in the original Slovic et al. study.8 They
2 Icek Ajzen & Martin Fishbein, Understanding Attitudes and Predicting Social Behavior
(1980).
3 N. Janz & M.H. Becker, The Health Belief Model: A Decade Later, 11 Health Educ. Q.
1 (1984).
4 Moore & Gullone, supra note 1.
5 See id.
6 Id.
7 Paul Slovic et al., Rating the Risks, 21 Env't 14 (1979).
8 Id.; Melissa L. Finucane & Murray T. Maybery, Risk Perceptions in Australia, 79
Psychol. Rep. 1331 (1996).
Field & Schreer: Age Differences in Personal Risk Perceptions 289
provided participants with 30 risk items on index cards; participants
ordered the items from least risky to most risky and then rated each
item for amount of risk in comparison to the other items. The
definition of risk was present risk of death from the hazard. Finucane
and Maybery concluded that while the five hazards ranked highest in
risk were similar for Australians, Americans, Norwegians, and
Hungarians, the differences suggested the necessity of investigating risk
in specific populations and cultural groups. 9 It is a logical extension of
this method to study participants of different age groups in order to
determine whether the cross-cultural similarities and differences also
apply across ages.
The current study developed from the literature concerning
perception of personal risk and prevention among different age groups
and the literature using the methodology of ranking risks. The purpose
of this research is to describe differences in perception of personal risk
in different age groups.
Method
Participants
Data was collected from 127 participants. Table 1 provides the
frequencies of gender and age groups. Participants were tested in a
public school, a summer program for adolescents, and college classes.
The small number of participants in the youngest group reflects the
difficulty of obtaining permission to contact young children in group
situations, particularly through schools. At the summer program,
parents were asked directly for permission to contact their children, and
Table 1
Number and Percent of Participants by Age Level and Gender
Gender Age Level
8-9 Years 11-15 Years 17-23 Years Total
Male 10 (7.8%) 31(24.4%) 28 (22.05%) 69 (53.5%)
Female 4 (3.1%) 26 (20.5%) 28 (22.05%) 58 (45.7%)
Total 14 (11.0%) 57 (44.9%) 56 (44.1%)
9 Finucane & Maybery, supra note 8.
11 Risk Health, Safety & Environment 287 [Fall 2000]
all but two of those asked signed the parental consent letters. By
contrast, seven of eight schools contacted would not give permission to
send letters to parents. Parental permission in terms of informed
consent was secured for all participants below college age. Adolescent
and college student participants provided informed consent.
Participants were from a relatively rural area of New England and
attended small schools.
Materials
Questionnaires were developed specifically for this study. Risk
behaviors were chosen on the basis of previous research, and participants
were asked to rank the behaviors in order of perceived risk and also to
rate the level of risk perceived to be associated with each behavior. For
some of the behaviors, participants were also asked whether they
participate in the behavior. Whenever possible, the items chosen were
the same as those used by Slovic et al. and Finucane and Maybery. 10
There were, however, some limitations upon the use of the entire list
from the previous studies. For example, the current study focused on
perception of personal risk associated with one's own behavior, so
broader hazards such as nuclear power and pesticides were excluded.
Because of the sensitive nature of some of the behaviors, only six
were used with all methods and all age groups. It would have been
inappropriate, for example, to ask eight-year-olds if they participate in
unprotected sex. The behaviors used for all age groups were skiing,
smoking cigarettes, playing soccer, playing computer games, drinking
alcohol, and not wearing a seatbelt in a car. The older participants were
also asked about using illegal drugs, using handguns, having
unprotected sex, ignoring stop signs, mountain climbing, hunting,
swimming, and.biking. Some items were added to the list based on a
previous study of these behaviors by the current investigators and
colleagues. 
11
On the first questionnaire, given to all age groups, participants were
asked to indicate on a four-point scale how risky each behavior was
perceived to be and whether they participate in the behavior themselves.
10 Slovic et al., supra note 7; Finucane & Maybery, supra note 8.
11 See John Kulig et al., Consensus Estimates of Risky Behaviors: False Consensus for
Friends but not the General Population. Poster presented at the NEPA Annual Mtg., Prov., RI
(1998).
Field & Schreer: Age Differences in Personal Risk Perceptions 291
Rather than risk of death, as used in earlier studies, the questionnaire
asked for ratings based on likelihood and degree of getting hurt. Again,
this had to be appropriate for third graders, and to satisfy school
authorities and parents that the questionnaire itself did not pose any
risk to the participants. The second questionnaire, given only to the two
older groups, provided fourteen behaviors on randomly arranged cards
and asked participants to arrange the cards in order of risk. Participants
were then asked to rate each behavior independently on a ten-point
scale.
Design and Procedure
This was a cross-sectional study comparing three age groups;
participants were tested in groups and responded to self-report
questionnaires concerning their perceptions of risk associated with
various behaviors. Three levels of age were delineated: 8-9 years
(children), 11-15 years (adolescents), and 17-23 years (adults) based on
the ages of the participants and the normal age grades in the culture.
Data was analyzed using a number of statistical procedures described
below. Since a number of statistical tests were conducted, a significance
level of .01 was required to avoid capitalization on chance.
Results
To determine whether perception of risk for the six various
behaviors (alcohol, computer, seatbelt, skiing, smoking, and soccer)
varied with age, ANOVAs were calculated for each of the behaviors
with age as the independent variable. A significant difference in risk
ratings by different age levels was found only for skiing F(2,123)=6.67,
p=.002. The youngest group (8-9 years) perceived skiing as significantly
more risky than did the other age groups. Table 2 contains the mean
risk ratings by age levels. No significant effects for gender were found;
therefore, gender was not a variable in subsequent analyses.
For the older groups, scores were available for fourteen behaviors.
Comparisons were made for the two older age groups (adolescent, 11-
15, and adult, 17-23) by calculating t-tests using the ratings of risk as
the measure of the dependent variable. Adults, compared to
adolescents, rated skiing as significantly more risky: t(98)=3.32, p=.001.
This was the only age difference found between the adult and
11 Risk: Health, Safety & Environment 287 [Fall 2000]
adolescent groups on the fourteen variables analyzed using ratings as the
dependent variable. When the rankings were used as the dependent
variable, Mann-Whitney tests revealed a significant difference between
adults and adolescents in perception of risk for ignoring stop signs
(p=.002). Adults gave higher risk rankings to ignoring stop signs as
compared to adolescents.
Table 2
Mean Risk Ratings* by Age Level and Behavior (for ANOVA)
Behavior Age Level
8-9 Years 11-15 Years 17-23 Years
Alcohol 3.9386 3.6429 3.5000
Computer 1.0000 1.3571 1.1607
Seatbelt 3.4286 3.4821 3.7143
Skiing 3.7143 2.9107 3.1250
Smoking 3.9286 3.6250 3.6786
Soccer 2.9286 2.4821 2.6607
* Rating of 1 to 4, 4=highest risk.
A cross-cultural and cross-time analysis was conducted by
comparing relative rankings given by participants with rankings from
the studies by Slovic et al. and Finucane and Maybery for the variables
which the three studies examined in common. 12 Slovic et al.
published rankings by U.S. participants in 1979, and Finucane and
Maybery studied some of the same variables in 1996 in Australia. 13
Table 3
Rankings of Risk Behaviors from Three Studies
Ranks
Risk Finucane (1996) Slovik (1979) Field (1999)
University College Adoles & College
Smoking .1 2 2
Drinking 3 3 3
Skiing 8 7 6
Handguns 2 1 1
Climbing 4 5 5
Biking 5 6 7
Swimming 6 8 8
Hunting 7 4 4
12 Slovic et al., supra note 7; Finucane & Maybery, supra note 8.
13 Id.
Field & Schreer: Age Differences in Personal Risk Perceptions 293
Thus, for the shared variables, adding the current study allows
comparing rankings in the U.S. and Australia at three different points in
time. Table 3 lists the common variables and the relative rankings in the
three studies. A Friedman 2-way ANOVA found no significant
differences between the ranks, given the same variables in two cultures
at three different times.
Table 4 contains the rankings provided by adolescents and adults in
the current study. Differences between adult and adolescent rankings
are few and minor; this is consistent with the above results.
Table 4
Ranks of Risk Behaviors by Adolescents and Adults
Age Level
Adolescent Adult
Behavior Mean Median Relative* Mean Median Relative*
Alcohol 5.41 5.00 5.0 6.20 6.00 6.5
Biking 10.69 11.00 11.0 11.07 11.00 11.0
Climbing 7.80 9.00 9.0 8.51 9.00 9.0
Computer games 12.78 14.00 14.0 13.20 14.00 14.0
Drugs 2.74 2.00 1.0 3.27 3.00 2.5
Guns 4.79 4.00 3.5 3.93 3.00 2.5
Hunting 6.93 7.50 8.0 7.75 8.00 8.0
Seatbelts 6.09 6.00 6.5 6.20 6.00 6.5
Sex (unprotected) 4.04 3.00 2.0 2.93 2.00 1.0
Skiing 9.61 10.00 10.0 9.25 10.00 10.0
Smoking 5.28 4.00 3.5 5.15 5.00 4.5
Soccer 11.91 13.00 13.0 11.60 12.00 12.5
Stop sign 6.20 6.00 6.5 4.78 5.00 4.5
Swimming 10.98 11.50 12.0 11.20 12.00 12.5
*Relative rank is rank within this array of median ranks.
In order to determine whether actual performance of the behavior
was related to perception of risk, for the variables for which this data
was collected on all participants (alcohol, computer, seatbelt, skiing,
smoking, and soccer), Chi-square analyses with accompanying eta
coefficients revealed significant relationships for (N=126) alcohol
(p=.001, accounted for by high frequencies for adolescents) and seatbelt
(p=.0002, accounted for by high frequencies for adolescents and
adults). Thus, performance was related to perception of risk for alcohol
by adolescents and for seatbelt by both adults and adolescents;
participants who performed the behavior also perceived it to be risky.
11 Risk. Health, Safety & Environment 287 [Fall 2000]
Discussion and Conclusion
The most significant result of the current study is the finding of no
age differences in perception of risk for most of the behaviors studied.
The finding of no age differences in perception of risk for these
behaviors means that people of all ages share a perception of how much
risk is associated with each of the behaviors. Admittedly, the current
study is exploratory, and the number of children was limited. However,
given the limitations, the results do suggest that it may not be necessary
to consider age as a factor in analysis of risk perception.
Perhaps one reason for the dearth of studies is the difficulty of
collecting data from children. Our societal concern with protecting
youngsters from risks may have resulted in children becoming
unavailable as research participants as well as limitations on topics about
which researchers may question children. Thus, knowing it is not
necessary to test children would have significant practical value.
Finding no age differences in perception of personal risk has an
important implication in addition to that discussed above. By third
grade (8-9 years of age), we have made children aware of the personal
risks we, as adults, want them to be aware of. The question then is
whether the programs we supply to adolescents in an attempt to deter
their risk-taking is over-kill, or even counterproductive. Adult efforts at
deterrence identify the risks we are most concerned about. And the
adolescent, developmentally predisposed to rebellion and risk-taking,
knows exactly which behaviors to perform in order to create the most
concern among adults. Applying Moore and Gullone's cost-benefit
analysis, the positive outcomes associated with rebellion and risk-taking
(particularly reinforcement from peers) in terms of adult concern and
outrage may explain the attraction of behaviors which the adolescent
has recognized as risky since at least age eight. 14 We concur with
Moore and Gullone's conclusion that adult identification of risks and
associated dangers may be an inappropriate strategy for reducing risk
taking by adolescents. 15 This argument is not likely to be considered
politically correct in the current climate, but it is a notion which should
be explored with additional research. It may be that sensitizing children
14 Moore & Gullone, supra note 1.
15 Id
Field & Schreer: Age Differences in Personal Risk Perceptions 295
to risks through about the third grade is all that is necessary or
desirable.
It is interesting to note that the cross-culture and cross-time
comparisons of rankings of risk behaviors identified commonality in
how people in general perceive risk. Australians and Americans tended
to rank risky behaviors in essentially the same order, and Americans
have not changed with regard to that ranking over the last 20 years.
Furthermore, the authors find it remarkable that these rankings were
similar despite differences in instructions and procedures as well as
differences in culture and time. The similarities must be incredibly
robust to withstand the potential confounding influences of different
times, cultures, instructions, and procedures. A finding of differences
would have been easily explained; the finding of commonality is
amazing under the circumstances.
11 Rislc Health, Safety & Environment 287 [Fall 2000]



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Age Differences in Personal Risk Perceptions: A Note on an Exploratory Descriptive Study

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