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Psychological determinants of risk taking by children: An integrative model and implications for interventions



To draw on empirical findings of the psychological factors that cause elementary-school children to engage in risky play behaviors that can lead to injury, with the aim of developing an integrative model that can support intervention-program planning. An extensive review of literature on this topic was conducted, determinants of risk taking for which there was empirical support were identified, and results were synthesized to create an integrative model of children's risk taking. Research on risk taking in children is limited, but the findings support the importance of examining child, family and socio-environmental factors to understand children's risk-taking behaviors. Development of a model outlining the determinants of risk behaviors can provide a foundation for initiatives that aim to reduce such behaviors and prevent childhood injuries.
Psychological determinants of risk taking by children: an
integrative model and implications for interventions
Barbara A Morrongiello, Jennifer Lasenby-Lessard
See end of article for
authors’ affiliations
Correspondence to:
Dr B A Morrongiello,
Psychology Department,
University of Guelph,
Guelph, Ontario N1G 2W1,
Canada; bmorrong@
Accepted 6 November 2006
Injury Prevention 2007;13:20–25. doi: 10.1136/ip.2005.011296
Objectives: To draw on empirical findings of the psychological factors that cause elementary-school children
to engage in risky play behaviors that can lead to injury, with the aim of developing an integrative model that
can support intervention-program planning.
Methods: An extensive review of literature on this topic was conducted, determinants of risk taking for which
there was empirical support were identified, and results were synthesized to create an integrative model of
children’s risk taking.
Results: Research on risk taking in children is limited, but the findings support the importance of examining
child, family and socio-environmental factors to understand children’s risk-taking behaviors.
Conclusions: Development of a model outlining the determinants of risk behaviors can provide a foundation
for initiatives that aim to reduce such behaviors and prevent childhood injuries.
nintentional injuries are a leading cause of death and
hospitalization during childhood.
Research examining
the determinants of risk taking shows the multi-
determined nature of injury-risk behaviors. The present report
introduces an integrative model based on these research
findings, and discusses implications for interventions that seek
to reduce physical risk-taking behaviors in children 6–12 years
of age. To develop the model, we reviewed published research
and selected for discussion empirically supported determinants
of risk taking in children, giving particular attention to factors
amenable to intervention.
Journal articles written in English reporting studies of children
6–12 years of age and published from 1990 to 2005 were
identified in MEDLINE, ERIC and PSYCLIT databases; refer-
ence lists of retrieved publications also were subsequently
reviewed. Search terms included child*and youth crossed with
each of the following terms: risk tak*, injury risk behav*, risk*
beh*, risk compensation, sensation seeking and injur* risk;
note: the asterisk allows retrieval of articles containing any
variation of the word stem (eg, risk tak* = risk take, risk taking
and risk taker). Abstracts and titles were reviewed by the
authors and, after discussion (which sometimes involved
reviewing the entire article), reports of empirical studies agreed
upon were retrieved and reviewed. Findings were synthesized
to identify unique determinants of risk taking and to develop
the model reported. Illustrative studies were selected for
citation (ie, the most extensive study and/or recent publication)
to support the model; however, no formal criteria were used to
assess the quality of the research reported.
Numerous models explain risk taking during adolescence
however, most are based on research investigating delinquency
or risk behaviors that would not routinely apply to children of
elementary age (eg, illicit drug use, alcohol consumption and
unprotected sex). No such models have been developed to
explain physical risk taking among elementary-school children
(6–12 years of age). The accumulation of evidence during the
past several years, however, now provides a foundation for the
development of such a model. As shown in fig 1, children’s risk
taking is a multi-determined outcome, with child, parent and
social-situational factors all influencing this behavior.
In the following sections, research from each of these
domains of influence is reviewed, and implications of these
findings for intervention programming are discussed. We
acknowledge that some degree of risk taking is necessary for
development, adaptive functioning and/or survival. The litera-
ture reviewed is concerned with understanding poor decision
making about risk taking that increases the risk of injury.
Moreover, although epidemiological data show that macro-
level factors extending beyond the individual and family (eg,
socioeconomics, culture and neighborhoods) also affect injury
these factors are not discussed in detail because the
focus of this paper is limited to factors that are amenable to
Figure 1 Empirically supported determinants of children’s risk decisions.
intervention programming. However, we certainly acknowledge
that macro-level factors can influence children’s injuries and
may affect the overall effectiveness of intervention programs.
Therefore, it may be important to consider these factors when
designing and evaluating such programs.
Children make many risk-taking decisions when they are
unsupervised. It is important to understand how individual
characteristics influence these decisions.
There are surprisingly few studies on the developmental aspects
of risk taking in children between 6 and 12 years of age. It has
been shown that hazard identification improves with age,
older children are more optimistic than younger ones that
injury will not occur,
and that older children are more likely
than younger ones to accept responsibility for resulting
However, older children have not been shown
necessarily to engage in greater risk taking than younger
Thus, what seems to matter more in predicting risk
taking or avoidance are individual child attributes (eg,
cognitions, temperament—see below), rather than age itself.
Sex has been shown to have a strong influence on children’s
tendency to take risks, and on their injury rates. Consistent
with epidemiological evidence that boys experience more
frequent injuries than girls, laboratory research and studies in
real-life situations show that boys engage in greater risk taking
than girls.
1 2 12–14
Moreover, sex is an attribute that influences
how many other factors operate to affect risk taking by
children. Thus, sex is one of the few factors for which
interactive effects have been systematically studied. As will
become evident in the remainder of this report, although boys
and girls both sometimes take significant physical risks, they
often have different motivations and thoughts about risk
taking. Because of this, intervention programs that aim to
change these underlying factors to reduce risk taking may need
to be designed differently for boys and girls in order to be
Consistent with numerous psychological models of health
behaviors (eg, Health Beliefs Model
; Theory of Planned
), children who appraise danger as low, judge their
personal vulnerability for injury to be low, and believe that the
potential severity of injury is not great, are more likely to take
12 17–19
Interestingly, because of the attributions children
make for injury outcomes, experiencing injuries does not
necessarily alter these cognitions or lead to risk avoidance. In
fact, children who attribute an injury outcome to bad luck,
rather than their own behaviors, are very likely to repeatedly
engage in the same behavior that led to an initial injury.
finding, coupled with the fact that parents assume that children
do learn risk avoidance from injury experiences,
20 21
may help to
explain why experiencing a medically attended injury does not
reduce the likelihood of children experiencing another such
injury, but actually predicts future injury.
Differences in injury-relevant cognitions also help to explain
why boys engage in greater risk taking than girls. Girls think in
terms of ‘‘Can I get hurt’’, whereas boys think in terms of ‘‘How
hurt might I get’’.
Boys are also more likely than girls to
erroneously attribute injuries to bad luck when their own
behavior is often responsible.
Therefore, interventions that can
effect changes in these cognitions could be successful in
evoking reductions in risk behaviors. Such interventions have
been developed for adults and adolescents.
There are also
recent reports of successfully changing cognitions among
elementary-school children.
Children’s emotional responses in risk situations influence how
they behave, and differ for boys and girls. Specifically,
anticipation of positive feelings of fun and excitement leads
to increased risk taking, whereas anticipation of fear leads to
risk avoidance.
Boys are more likely than girls to report
experiencing fun and excitement in risk situations, which
explains their greater readiness to engage in risk behaviors.
18 33
These few studies are the first to document that risk
decisions in children are driven not only by what they think
(ie, rational processes) but also by what they feel or expect to
feel when taking risks (ie, irrational processes). In fact, recent
evidence shows that emotional predictors of risk decisions are
statistically significant even after controlling for cognitive
influences on risk taking.
Thus, interventionists now have
two domains by which they may effect changes in children’s
risk taking: cognitions and emotions.
The more experience a child has with an activity, the greater
tolerance for risk taking the child shows for that activity. The
basis for this increased risk taking is a personal belief that they
can successfully manage the increased risk.
Grouping by age
and mixing children who have low experience with those who
have high experience (eg, in schoolyards, on playgrounds, on
sports teams and at camps), therefore, may increase the risk for
children with low experience because of the exposure to
modeling of high-risk behaviors by children with greater
experience (see the section Social-situational factors).
Motivations for why children decide to engage in risk taking or
risk avoidance vary with sex. Boys’ reasons for their risk
decisions show that they consider fun and convenience, and
often have overinflated beliefs about how effectively they can
manage the risk. By contrast, girls focus more on safety
concerns in deciding how to behave, which leads to greater risk
Interventions that target boys, therefore, may need
to deal with more issues than just safety awareness.
Children who are high in impulsiveness and activity levels
engage in greater risk taking and experience more injuries,
although these children show no deficits in knowledge of safety
or injury prevention.
Children high in sensation seeking (ie,
daring, novelty and thrill-seeking behaviors),
37 41
who are
oppositional (ie, non-compliant and difficult for parents to
or who overestimate their physical abilities
43 44
show greater risk taking. Sensation seeking also has been
shown to lead to increased risk compensation when wearing
safety gear, which means that wearing safety gear is particu-
larly likely to lead to greater risk taking than when not wearing
the gear among high sensation seekers.
By contrast, children
high in inhibitory control (ie, capacity to inhibit inappropriate
behaviors) engage in less risk taking and experience fewer
injuries than children low on this trait.
Although interventions may be unlikely to effect changes in
these disposition-based behaviors, identifying these children
with high injury risk may prove useful for targeting increased
supervision to ensure the safety of children with these
behavioral attributes. In addition, recent intervention research
suggests that tailoring interventions with some of these child
attributes in mind can greatly increase effectiveness.
Children’s risk taking 21
screening to identify high sensation seekers
would allow one
to direct interventions to children most likely to show risk
33 35
Through socialization, explicit teaching, and modeling prac-
tices, families exert a strong influence on the behaviors of their
members. Surprisingly, although there is a plethora of research
showing family influences on adolescent health risk behaviors
fat intake
and seat belt usage
studies assessing these effects on children’s risk taking are
much less systematic and limited in number.
Research on socialization practices shows that both mothers
and fathers respond similarly to each other, but differently to
the risk behaviors of sons and daughters. Sons receive explicit
encouragement for risk taking, whereas daughters receive
cautions about risk taking and about their vulnerability for
injury. These socialization differences are evident as early as
2 years of age and persist through at least 8 years of age.
54 55
Moreover, even when children show exactly the same risk
behaviors with the same degree of competence, mothers
intervene more frequently and quickly to stop risk behaviors
by daughters than sons.
Mothers are also more likely to
interpret behaviors that could lead to injury in terms of safety
for daughters, but in terms of discipline for sons.
Reports by children indicate awareness of parent expecta-
tions about what would constitute acceptable risk taking,
although sons and daughters respond differently to this
knowledge. Daughters are more likely to comply with how
they believe their parents would like them to behave, whereas
sons are more likely to engage in greater risk taking than their
parents would prefer.
Girls are also more likely than boys to
tell their parents about minor injuries and near-injury events,
which would provide even further opportunity for parental
intervention in risk avoidance for girls.
Interventions that
target increasing children’s awareness of parental or adult
norms for how they should behave, therefore, may influence
girls’ risk decisions, but are unlikely to have much effect on
boys’ risk decisions.
Parents’ behaviors
Although parents’ teaching has been found to be the best
predictor of children’s current safety practices, parents’
practices have been found to be the best predictor of how
children intend to behave once they reach adulthood.
Essentially, when parents model risk behavior while demand-
ing safety practices from their children, they are effectively
teaching children to believe that ‘‘safety is for kids’’. The fact
that parents’ modeling of risk behaviors can potentially have a
long-term effect on their child’s risk practices suggests that
interventions to reduce risk of injury in multi-generational
work contexts (eg, agricultural worksites) may have to target
the behaviors of senior and junior family members (eg, father
and sons) to evoke reductions in risk practices.
Older same-sex siblings also have been shown to influence the
risk decisions of younger ones. Whether their intention is to
promote greater risk taking or risk avoidance, older siblings are
quite effective in knowing what to say to alter the decisions of
their younger siblings.
Moreover, younger siblings are
particularly susceptible to the influence of their older sibling
when they rate the quality of the relationship very positively.
Older siblings who were boys most often focused on the value
of having fun when trying to influence their younger brother.
By contrast, older female siblings most often focused on safety-
related issues.
In addition, the greater the number of
persuasive arguments made, the greater the success in
convincing the younger sibling to change their risk decision.
Thus, persistence by the persuader pays off, evoking change in
the behavior of the persuadee.
Interventions that wish to reduce risk behaviors in children
of school age, therefore, may improve their chances of success
by having an older sibling communicate about risk avoidance,
rather than an adult or age-mate peer with whom the target
child has no or a limited personal relationship. The importance
of the target child respecting and valuing the opinion of the
messenger is clearly evident in these findings. Thus, if one can
identify famous figures (eg, sports stars and popular musicians)
who children respect and whose opinion they value, recruiting
these individuals to encourage children to engage in safety
practices may prove successful to promote these practices.
Social-situational factors that influence children’s risk taking
can be quite extensive and diverse. However, we have limited
our focus to those for which there is empirical support.
Many have said that elementary-school children are at greatest
risk for injury when they are with peers.
58 59
Indeed, even by
6 years of age children are aware that boys and girls differ in
risk taking, and they show different expectations for peer risk
taking depending on sex of the peer.
Oral persuasion skills are
well developed by 8 years of age
; hence, elementary-school
children can be considerably influenced by their friends’
endorsements to participate in high-risk activities.
36 57 62–64
Children also select best friends who are highly similar to
themselves in their level of tolerance for risk taking, and they
know this about one another.
These friendship choices may
reinforce and further contribute to children’s already existing
tendencies (due to individual characteristics and/or family and
parent factors as outlined previously) to take physical risks.
These findings highlight the potential benefits of targeting
dyads or groups of friends, instead of individuals, in interven-
tions that seek to reduce children’s risk behaviors. Intervention
programs that aim to instill feelings of shared responsibility for
each other’s safety may prove particularly successful. Programs
for adolescents (eg, drunk driving) have shown some success
when they target peer groups and emphasize shared responsi-
bility. Similar approaches could prove to be useful for reducing
younger children’s risk taking. Programs that draw on peers to
communicate persuasive messages about risk avoidance,
particularly messages delivered by close friends, also may prove
particularly successful in evoking reductions in risk behaviors.
However, tailoring programs based on sex of the target
audience may be necessary to achieve success.
Children’s risk decisions are also influenced by non-oral
(observational) information, which allows for peer influences
among children who do not even know one another. It has been
shown that if the risk taker displays a facial expression that
communicates confidence (eg, smiling), then children rate the
behavior as low in injury risk, whereas displaying a fearful
facial expression leads to greater perception of injury risk.
Moreover, girls assign more significance to this wary facial
expression than boys, leading to greater risk avoidance by girls
than boys.
These findings indicate that increased perceptions of risk
may suffice to deter imitative risk taking by girls but not by
boys. Exposing boys to information that more strongly
communicates fear and/or potential consequences of risk taking
(eg, injury experiences of age mates) may be necessary to have
22 Morrongiello, Lasenby-Lessard
increased perceptions of risk translate into reduced risk taking;
in fact, results of a recent intervention study provide support for
this premise.
Recent evidence also indicates that the mere presence of an
observing unknown peer can lead both boys and girls to make
riskier choices.
Thus, although the quality of the relationship
seems to be important for oral persuasion towards more risky
it does not seem to be as important for non-oral
(observational) influences. The literature on psychological
interventions contains programs aimed at developing resistance
skills in order to ‘‘inoculate’’ against future, somewhat
unpredictable, social situations that might lead one to consider
increased risk taking. Drawing on theories of psychological
the aim is to build self-awareness about
feelings or thoughts that are likely to occur in social situations
pressuring for increased risk taking, and to teach children to
use these emotions or thoughts to evoke strategies they have
learned (eg, self talk messages) to resist such pressure favoring
risk taking. This inoculation approach has been shown to
reduce health risk behaviors (eg, drug use, smoking and alcohol
consumption) among adolescents.
It may also prove useful
to enhance resistance to situational pressures for risk taking
among elementary-school children.
Media exposure also has been shown to influence children’s
behavior, particularly via television viewing. Content analyses
of children’s television programs show that the frequency of
injury-risk behaviors by characters far exceeds modeling of
safety behaviors, and most of the risk behaviors portrayed do
not result in any injuries that have substantive negative or
sustained consequences for the victim.
Research examining
the effect of television on children’s behavior shows that
exposure to programs that portray high risk taking results in
greater physical risk taking in hypothetical situations.
Similarly, exposing school-age children to an educational safety
video reduces their willingness to take risks, and increases their
awareness of hazards in common situations.
The implications of these findings for interventions are clear:
safety education television programming may be effective in
reducing childhood risk taking and raising awareness of
hazards. Policy-based interventions to mandate reductions in
the modeling of risk taking in children’s programming seem
likely to have an effect by reducing real-life risk behaviors.
Immediate contextual demands
Finally, children have also been shown to shift to increased risk
taking when the immediate demands of the social situation favor
these behaviors. Adults tend to perform behaviors that are
convenient, even though these behaviors may increase the
likelihood of injury to themselves or to their children.
evidence with children showed the same effect.
When presented
different possible paths of travel that pitted distance against safety
(eg, the most convenient and fastest route was the riskiest one,
the least convenient and slowest route was the safest), most
children endorsed taking a more risky (convenient) route than
was originally planned, and cited ‘‘convenience’’ as the reason for
increasing their level of risk taking. This shift to greater risk taking
was significantly greater for boys than for girls. Children justified
their endorsement of a riskier path by changing their cognitive
and emotional appraisals of risk to support their new riskier
Intervention programs need to make children aware of
these situational determinants of risk taking, and attempt to
promote children’s resistance to such immediate situational
pressures. Using the types of inoculation intervention approaches
outlined earlier may help achieve this aim.
One of the greatest challenges to injury prevention is the variety
of ways in which injuries result and, consequently, the
potential range of intervention strategies. On the basis of the
research findings reviewed, targeting micro-level factors is
essential for interventions that aim to curtail injuries by
reducing risk taking during the elementary years. Specifically,
the research points to a number of potential targets for
intervention (ie, what the intervention aims to alter), including
children’s attitudes, beliefs, cognitions and emotions. Although
these targets may be more familiar to psychologists than to
public health professionals, extensive research with adults and
adolescents provides insights into how to evoke changes in
these factors at the individual level.
30–32 76–78
These findings can
provide foundational knowledge on how to develop interven-
tion programs to target these key determinants of children’s
risk taking. Of course, how one intervenes and the tactics used
to disseminate the intervention are likely to achieve most
success by also considering more macro-level factors, such as
neighborhood attributes
(eg, neighborhood friends commu-
nicating norms about risk taking, resources available to support
safe play, etc), cultural considerations
(eg, culture-based
differences in the value placed on risk v safe behaviors, or in
attitudes about interpreting injuries as ‘‘accidents’’) and
economic factors
(eg, resources available to support risk v
safety practices). Thus, in developing interventions for children
of elementary-school age, there is a need not only to target
individual attributes but also to consider the child within the
broader socioeconomic context of family, friends, neighborhood
and culture in order to maximize opportunities for success.
As shown in fig 1, children’s risk taking is a multi-determined
outcome that is influenced by a variety of child, parent and family,
and social-situational factors, and is set within a broader context
of socioeconomic and cultural characteristics. The findings from
numerous studies confirm that each of the determinants shown in
fig 1 individually predicts risk-taking decisions in children
6–12 years of age, and many factors interact with sex and
contribute to explain why boys engage in greater risk taking than
girls. Although further research is needed to determine how these
factors interact to influence risk taking, our current knowledge
base is sufficiently developed to support the planning of evidence-
based interventions to reduce inappropriate risk taking that
increases injury risk among elementary-school children.
Key points
Despite the importance of understanding children’s risk
taking in order to develop effective interventions, no prior
attempt has been made to provide an integrative
synthesis of what is known.
Reviewing existing literature shows that children’s risk
taking is multi-determined and influenced by child
attributes, parent–family characteristics and social–situa-
tional factors.
Empirical evidence has been synthesized to create a
model that provides a foundation of knowledge to
support development of injury-prevention interventions.
Drawing on the research findings and factors highlighted
in this model, numerous suggestions for interventions to
reduce children’s risk taking are provided.
Children’s risk taking 23
Preparation of the manuscript was supported by grants to the first
author from the Canadian Institutes of Health Research, and by a grant
to the second author from the Ontario Neurotrauma Foundation.
Authors’ affiliations
Barbara A Morrongiello, Jennifer Lasenby-Lessard, Psychology
Department, University of Guelph, Guelph, Ontario, Canada
Competing interests: None.
1 Baker SP, O’Neil B, Ginsburg MJ, et al. The injury fact book, 2nd edn. New York:
Oxford University Press, 1992.
2 Canadian Institute of Child Health. The health of Canada’s children: a CICH
profile, 3rd edn. Ottawa: Canadian Institute of Child Health, 2000.
3 Arnett J. Reckless behaviour in adolescence: a developmental perspective. Dev
Rev 1992;12:339–73.
4 Baumrind D. A developmental perspective on adolescent risk taking in
contemporary America. New Dir Child Dev 1987;37:93–125.
5 Furby L, Beyth-Marom R. Risk taking in adolescence: a decision making
perspective. Dev Rev 1992;12:1–44.
6 Jessor R. Risk behavior in adolescence: a psychosocial framework for
understanding and action. J Adolesc Health 1991;12:597–605.
7 Baumrind D. Self-regulation and risk-taking. In: Lipsitt L, Mitnick L, eds.
Adolescent exploratory behavior: precursors and consequences. Norwood, NJ:
Ablex, 1992:109–42.
8 Overpeck MD, Jones D, Trumble A, et al. Socioeconomic and racial/ethnic
factors affecting non-fatal medically-attended injury rates in US children. Inj Prev
9 Vaughan E, Anderson C, Argran P, et al. Cultural differences in young children’s
vulnerability to injuries: a risk and protection perspective. Health Psychol
10 Mackey M, Reid DC, Moher D, et al. Systematic review of the relationship
between childhood injury and socio-economic status. Health Canada, H39-473/
1999E; 1999. Available at:
cyfh/safe and supportive/resources/Injury.pdf/.
11 Hillier LM, Morrongiello BA. Age and gender differences in school-age children’s
appraisals of injury risk. J Pediatr Psychol 1998;23:229–38.
12 Morrongiello BA, Rennie H. Why do boys engage in more risk taking than girls?
The role of attributions, beliefs, and risk appraisals. J Pediatr Psychol
13 Morrongiello BA, Dawber T. Toddlers’ and mothers’ behaviors in an injury-risk
situation: implications for sex differences in childhood injuries. J Appl Dev
Psychol 1998;19:625–39.
14 Rivara FP, Bergman AB, LoGerfo JP, et al. Epidemiology of childhood injuries. II.
Sex differences in injury rates. Am J Dis Child 1982;136:502–6.
15 Janz NK, Becker MH. The Health Belief Model: a decade later. Health Educ Q
16 Beck L, Ajzen I. Predicting dishonest actions using the theory of planned
behavior. J Res Pers 1991;25:285–301.
17 Morrongiello BA. Children’s perspectives on injury and close-call experiences:
sex differences in injury-outcome processes. J Pediatr Psychol
18 Peterson L, Brazeal T, Oliver K, et al. Gender and developmental patterns of
affect, belief and behaviors in simulated injury events. J Appl Dev Psychol
19 Peterson L, Oliver KK, Brazeal TJ, et al. A developmental exploration of
expectations for and beliefs about preventing bicycle collision injuries. J Pediatr
Psychol 1995;20:13–22.
20 Morrongiello BA, Dayler L. A community-based study of parents’ knowledge,
attitudes and beliefs related to childhood injuries. Can J Public Health
21 Morrongiello BA, Hogg K. Mothers’ reactions to children misbehaving in ways
that can lead to injury: implications for gender differences in children’s risk taking
and injuries. Sex Roles 2004;50:103–18.
22 Bijur P, Golding J, Haslum M, et al. Behavioral predictors of injury in school-age
children. Am J Dis Child 1988;142:1307–12.
23 Eminson CJ, Jones H, Goldacre M. Repetition of accidents in young children.
J Epidemiol Community Health 1986;40:170–3.
24 Jaquess DL, Finney JW. Previous injuries and behavior problems predict
children’s injuries. J Pediatr Psychol 1994;19:79–89.
25 Kendrick D. Accidental injury attendances as predictors of future admission.
J Public Health Med 1993;15:171–4.
26 Manheimer DI, Dewey J, Mellinger GD, et al. 50,000 child-years of accidental
injuries. Public Health Rep 1966;81:519–33.
27 McPhillips H, Gallaher M, Koepsell T. Children hospitalized early and increased
risk for future serious injury. Inj Prev 2001;7:150–4.
28 Speltz ML, Gonzales N, Sulzbacher S, et al. Assessment of injury risk in young
children: a preliminary study of the injury behavior checklist. J Pediatr Psychol
29 Boyce WT, Sobolewski S. Recurrent injuries in school children. Am J Dis Child
30 Conner M, Norman P. Predicting health behavior: research and practice with
social cognitive models. Philadelphia, PA: Open University Press, 1996.
31 Glanz K, Rimer BK, Lewis F. Health behaviour and health education: theory,
research, and practice. San Francisco: Jossey Bass, 2002.
32 Chunn J, ed. The health behavioral change imperative:theory, education, and
practice in diverse populations. New York, USA: Kluwer, 2002.
33 Morrongiello BA, Matheis S. Determinants of children’s risk-taking in different
social-situational contexts: the role of cognitions and emotions in predicting
children’s decisions. J Appl Dev Psychol 2004;25:303–26.
34 Cook S, Peterson L, DiLillo D. Fear and exhilaration in response to risk: an
extension of a model of injury risk in a real-world context. Behav Ther
35 Morrongiello BA, Sedore L. The influence of child attributes and social-situational
context on school-age children’s risk taking behaviors that can lead to injury.
J Appl Dev Psychol 2005;26:347–61.
36 Morrongiello BA, Dawber T. Social and cognitive influences on school-age
children’s risk-taking decisions. Can J Behav Sci 2004;36:255–66.
37 Matheny A, Fisher JE. In:, Wolraich M, Routh D, eds. Behavioral perspectives on
children’s accidents. Greenwich: JAI, 1984:221–63.
38 Matheny A. Psychological characteristics of childhood accidents. J Soc Issues
39 Zuckerman BS, Duby JC. Developmental approach to injury prevention. Pediatr
Clin North Am 1985;32:17–29.
40 Mori L, Peterson L. Knowledge of safety of high and low active-impulsive boys:
implications for child injury prevention. J Clin Child Psychol 1995;24:370–6.
41 Morrongiello BA, Lasenby J. Finding the daredevils: development of a sensation
seeking scale for children that is relevant to physical risk taking. Accid Anal Prev
42 Schwebel DC, Speltz M, Jones K, et al. Unintentional injury in boys with and
without early onset of disruptive behavior. J Pediatr Psychol 2002;27:727–37.
43 Plumert JM, Schwebel DC. Social and temperamental influences on children’s
overestimation of their physical abilities: links to accidental injuries. J Exp Child
Psychol 1997;67:317–37.
44 Morrongiello BA, Lasenby J, Walpole B. Risk compensation: Why do children
show it in reaction to wearing safety gear? J Appl Dev Psychol in press.
45 Schwebel D, Plumert JM. Longitudinal and concurrent relations between
temperament, ability estimation, and accident proneness. Child Dev
46 Palmgreen P, Donohew L, Lorch E, et al. Sensation seeking, message sensation
value, and drug use as mediators of PSA effectiveness. Health Commun
47 Everett M, Palmgreen P. Influence of sensation seeking, message sensation value,
and program context on the effectiveness of anti-cocaine PSAs. Health Commun
48 Lorch E, Palmgreen P, Donohew L, et al. Program context, sensation seeking, and
attention to televised anti-drug public service announcements. Hum Commun Res
49 Stephenson M. Message sensation value and sensation seeking as determinants
of message processing. Lexington: University of Kentucky, 1999.
50 Chassin L, Presson C, Todd M, Rose J, et al. Maternal socialization of adolescent
smoking: the intergenerational transmission of parenting and smoking. Dev
Psychol 1998;34:1189–201.
51 Duncan SC, Duncan TE, Strycker LA. Family influences on youth alcohol use: a
multiple-sample analysis by ethnicity and gender. J Ethn Subst Abuse
52 Rossow I, Rise J. Concordance of parental and adolescent health behaviours.
Soc Sci Med 1994;38:299–305.
53 Page R. Role of parental example in preadolescents’ use of seat belts. Psychol
Rep 1986;59:985–6.
54 Morrongiello BA, Dawber T. Parental influences on toddlers injury-risk
behaviors: are sons and daughters socialized differently? J Appl Dev Psychol
55 Morrongiello BA, Dawber T. Mothers’ responses to sons and daughters
engaging in injury-risk behaviors on a playground: implications for sex
differences in injury rates. J Exp Child Psychol 2000;76:89–103.
56 Morrongiello BA, Bellissimo A, Corbett M. ‘‘Do as I say, not as I do’’: family
influences on children’s safety behaviors. Health Psychology. In press.
57 Morrongiello BA, Bradley MD. Sibling power: influence of older siblings’
persuasive appeals on younger siblings’ judgements about risk taking
behaviours. Inj Prev 1997;3:23–8.
58 Sandels S. An overall view of children in traffic. In: Jackson R, eds. Children, the
environment, and accidents. Kent, England: Pitman Medical, 1977.
59 Wilson MH, Baker SP, Teret SP, et al. Saving children: a guide to injury
prevention. New York & Oxford: Oxford University Press, 1991.
60 Morrongiello BA, Midgett C, Stanton KL. Gender biases in children’s appraisals
of injury risk and other children’s risk-taking behaviors. J Exp Child Psychol
61 Levin E, Rubin K. Getting others to do what you want them to do: the development
of children’s requestive strategies. In: Nelson K, eds. Children’s language.
Hillsdale, NJ: Erlbaum, 1983:22–49.
62 Christensen S, Morrongiello B. The influence of peers on children’s judgements
about engaging in behaviors that threaten their safety. J Appl Dev Psychol
63 Jones DC. Persuasive appeals and responses to appeals among friends and
acquaintances. Child Dev 1985;56:757–63.
64 Bigelow BJ, Tesson G, Lewko JH. The social rules that children use: close friends,
other friends, and ‘‘other kids’’ compared to parents, teachers, and siblings.
Int J Behav Dev 1992;15:315–35.
24 Morrongiello, Lasenby-Lessard
65 Duryea EJ, Ransom MV, English G. Psychological immunization: theory,
research, and current health behavior applications. Health Educ Q
66 Morrongiello BA, Matheis S. Addressing the issue of child-injury prevention: a
behavioral intervention to reduce fall-risk behaviors on playgrounds. Under
67 McGuire W. Social psychology. In: Dodwell PC, eds. New horizons in
psychology. Middlesex: Penguin Books, 1972:219–42.
68 Glynn TJ. Essential elements of school-based smoking prevention programs. J Sch
Health 1989;59:181–8.
69 Tobler N. Meta-analysis of 143 adolescent drug prevention programs:
quantitative outcome results of program participants compared to controlor
comparison group. J Drug Issues 1986;16:537–67.
70 Tobler N. Meta-analysis of adolescent drug prevention programs. NY: State
University of New York at Albany, 1995.
71 Potts R, Henderson J. The dangerous world of television. Child Environ Q
72 Potts R, Runyan D, Zerger A, et al. A content analysis of safety behaviors of
television characters. J Pediatr Psychol 1996;21:517–28.
73 Greenberg B. Television and role socialization: an overview. In: Pearl D,
Bouthilet L, Lazar J, eds. Television and social behaviour: ten years of scientific
progress. Washington, DC: US Government printing office, 1982:179–90.
74 Potts R, Doppler M, Hernandez M. Effects of television content on physical risk-
taking in children. J Exp Child Psychol 1994;58:321–31.
75 Potts R, Swisher L. Effects of televised safety models on children’s risk taking and
hazard identification. J Pediatr Psychol 1998;23:157–63.
76 Fabrigar L, Petty R. The role of the affective and cognitive bases of attitudes in
susceptibility to affectively and cognitively based persuasion. Pers Soc Psychol
Bull 1999;25:363–81.
77 Leventhal H, Leventhal E, Cameron L. Representations, procedures, and affect in
illness self-regulation. In: Baum A, Revenson T, Singer J, eds. Handbook of health
psychology. Mahwah, NJ: Erlbaum, 2001:19–47.
78 Rothman AJ, Salovey P. Shaping perceptions to motivate healthy behavior: the
role of message framing. Psychol Bull 1997;121:3–19.
79 Westaby L, Loew K. Risk taking and injury among youth workers: examining the
social influence of supervisors, coworkers, and parents. J Appl Psychol
80 Conrad P, Bradshaw Y, Lamsudin R, et al. Helmets, injuries and cultural
definitions: motorcycle injury in urban Indonesia. Accid Anal Prev
81 Hayakawa H, Fischbeck P, Fischhoff B. Traffic statistics and risk perceptions in
Japan and the United States. Accid Anal Prev 2000;21:827–35.
82 Unicef. Child deaths by injury in rich nations. Report no 2. 2001.
83 Melinder K, Andersson R. The impact of structural factors on the injury rate in
different European countries. Eur J Public Health 2001;11:301–8.
Children’s risk taking 25
... Aspects of temperament and personality may relate directly or inversely to child injury risk. Specifically, increased activity level, impulsiveness, and sensation seeking are linked with greater risk of unintentional injury, whereas greater inhibitory control is associated with decreased risk of unintentional injury (Barton & Schwebel, 2007;Morrongiello & Lasenby-Lessard, 2007;Schwebel & Gaines, 2007). ...
... Prior Experiences. Children's individual experiences and cognitions regarding specific risky behaviors, prior injury events, and safety learning can influence their risk of future injury events (Morrongiello & Lasenby-Lessard, 2007;Schwebel & Gaines, 2007). As children gain more experience with a risky behavior (e.g., riding a bicycle), their confidence in their ability to perform the activity without injury can lead to decreased perceptions of risk and increased risk taking (e.g., not wearing a helmet; Peterson et al., 1994). ...
... When children have experienced a prior injury event, caregivers frequently assume children learn to be However, children who attribute their injuries to chance or bad luck rather than their own actions are likely to repeat the risky behavior. Rather than decreasing risk, prior injury events predict future injury events (Morrongiello & Lasenby-Lessard, 2007). Individual differences also exist in children's opportunity and ability to acquire, retain, and apply safety-related information. ...
Objective: Complex environmental, social, and individual factors contribute to unintentional childhood injury events. Understanding context-specific antecedents and caregiver attributions of childhood injury events can inform the development of locally-targeted interventions to reduce injury risk in rural Uganda. Methods: Fifty-six Ugandan caregivers were recruited through primary schools and completed qualitative interviews regarding 86 unintentional childhood injury events. Descriptive statistics summarized injury characteristics, child location and activity, and supervision at time of injury. Qualitative analyses informed by grounded theory identified caregiver attributions of injury causes and caregiver actions to reduce injury risk. Results: Cuts, falls, and burns were the most common injuries reported. At the time of injury, the most common child activities were farming and playing and the most common child locations were the farm and kitchen. Most children were unsupervised. In cases where supervision was provided, the supervisor was typically distracted. Caregivers most often attributed injuries to child risk-taking but also identified social, environmental, and chance factors. Caregivers most often made efforts to reduce injury risk by teaching children safety rules, but also reported efforts to improve supervision, remove hazards, and implement environmental safeguards. Conclusion: Unintentional childhood injuries have a significant impact on injured children and their families, and caregivers are motivated to reduce child injury risk. Caregivers frequently perceive child decision-making a primary factor in injury events and respond by teaching children safety rules. Rural communities in Uganda and elsewhere may face unique hazards associated with agricultural labor, contributing to a high risk of cuts. Interventions to support caregiver efforts to reduce child injury risk are warranted.
... These findings have several important implications for prevention and clinical practice. To address such an important contemporary health issue, one must begin with the young people themselves, trying to change their attitudes, beliefs, how they think about their body, and what behaviours they subsequently choose to engage in (Morrongiello & Lasenby-Lessard, 2007). Interventions commonly consider weight perception and overt risk-taking as separate issues, yet there may be value in considering them together as common factors and experiences. ...
Objective: Perceptions of body weight represent an important health issue for Canadian adolescents. While associations between weight perception and mental health concerns like eating disorder symptomatology are well established, there is need for more Canadian evidence about how weight perception is associated with overt risk-taking among adolescents, and further how such associations differ by biological sex. Methods: We conducted a national analysis of grade 9-10 students participating in the 2017-2018 cycle of the Health Behaviour in School-aged Children (HBSC) study in Canada. This analysis described contemporary patterns of alternate weight perception and then examined the strength and statistical significance of such associations by biological sex, with tobacco, alcohol, and cannabis use, binge drinking, fighting, and illicit drug use as outcomes. Behaviours were considered both individually and in combination. Analyses were descriptive and analytical, with regression models accounting for the nested and clustered nature of the sampling approach. Results: Responses from 2135 males and 2519 females were available for a complete case series analysis. A total of 26% and 35% of males and females, respectively, perceived themselves as "too fat" while 20% and 9% identified as "too thin". Females perceiving themselves as "too fat" reported higher likelihoods of engaging in individual and scaled indicators of overt risk-taking. Conversely, among males, alternate weight perception was associated with lower levels of such behaviours. Conclusion: As males and females perceive and react to weight perception differently, clinical and health promotion strategies should be developed and uniquely targeted to groups of adolescents in regards to weight perception and risk-taking.
... In the United States, fewer children are reported to be playing adventurously than their parents did as children (Clements, 2004) and the spaces where children play most adventurously, in green spaces and indoor play centres, are the spaces where children in Britain are playing the least . This decline in adventurous play and the reduction in opportunities for adventurous play can be explained by several factors, including cultural attitudes towards risk, school, peer, familial and parent factors (Brussoni et al., 2012;Morrongiello and Lasenby-Lessard, 2007;Nesbit et al., 2021). The role of parents is particularly important, as they can facilitate or restrict access to play activities, as well as intervene to disrupt or stop the play (McFarland and Laird, 2020). ...
Rationale: Adventurous play, where children take age-appropriate risks involving uncertainty, fear, and thrill, is positively associated with children's physical health, mental health, and development. There is growing concern that children's access to and engagement with adventurous play opportunities are declining in Westernised countries, which may have negative implications for children's health. Objective: The current study aimed to ascertain the facilitators of and barriers to children's adventurous play most identified by parents in Britain and to determine whether these differ across socio-demographic and geographic groups. Methods: This study analysed the responses of a nationally representative sample of 1919 parents who took part in the British Children's Play Survey. Two open-ended questions asked parents to identify what they perceive to be the facilitators of and barriers to their child's adventurous play. A quantitative coding scheme, developed using the qualitative framework identified by Oliver et al. (2022), was applied to parents' responses. Results: A diversity in the most identified facilitators and barriers was found, including concerns about the risk of injury from adventurous play and the safety of society, positive attitudes about the benefits of adventurous play, as well as factors related to child attributes. In general, these were consistently identified across different socio-demographic and geographic groups, although some differences were found in barriers. Conclusions: The findings of this research support the identification of key targets for those working with parents to improve children's adventurous play opportunities and ultimately their physical and mental health. Future research should seek to design and tailor interventions by asking parents about the support they would value.
... Male gender also had greater frequency for all mode of injuries except firearm injuries and animal bite. The explanation for this high frequency in male than female may be due to the higher frequency of exposure to injury risk in the activities the boys expose every day (Morrongiello and Lessard, 2007). These findings are in accordance to other studies in Egypt (Elbaih et al., 2016) and with other studies conducted in all over the world (Mattila et al., 2004& Kalkan et al., 2016. ...
... According to Morrongiello and Lessard model (2007), personal characteristics (age, gender, behavioral attitudes, experiences, individual values and motivations, moods); family and parents (socialization practices, learning practices, parenting styles, sibilant impacts, parents' patterning); and social or situational factors (verbal encouragements, observational learning impacts, en-couraging motivational conditions) all interact to bring about risk taking or prevent an accident [8]. ...
Bu çalışma okul öncesi dönem çocuklarının riskli oyun oynamalarında okullarının fiziksel ortamlarının öğretmen algılarına etkisinin incelenmesi amacı ile yapılmıştır. Çalışmanın örneklemini 2021-2022 eğitim öğretim yılında Afyonkarahisar İl Milli Eğitim Müdürlüğü’ne bağlı 344 okul öncesi öğretmeni oluşturmaktadır. Çalışmada, veri toplama aracı olarak okul öncesi öğretmenlerinin kişisel bilgilerinin yer aldığı “Genel Bilgi Formu” ve Karaca ve Uzun (2020) tarafından geliştirilen “Erken Çocukluk Riskli Oyun Değerlendirme Aracı-Öğretmen Formu (EÇRODA-ÖF)” kullanılmıştır. Araştırmanın analizinde, elde edilen verilerin normal dağılmadığı belirlenerek, iki değişken için Mann Whitney U Testi ile ikiden fazla değişkenler için Kruskal Wallis H Testi kullanılarak analiz edilmiştir. Araştırma sonucunda, okul türü, sınıf mevcudu ve yardımcı personelde anlamlı fark bulunmuş, oyun odası ve araç gereç değişkenlerinde anlamlı farklılık saptanamamıştır. Araştırma sonucunda eğitimcilere, araştırmacılara ve yöneticilere önerilerde bulunulmuştur.
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Type 1 diabetes mellitus (T1DM) is a chronic and lifelong condition that requires adequate behavior management in order to meet desired health outcomes. The effects of T1DM on the neurocognitive functioning of affected individuals raise concerns about how the disease may influence executive functioning. Inhibition is a core component of executive functioning, and plays a vital role in self-regulation and the restriction of impulsive behaviors. Inhibition may thus play a vital role in the behavior management of people with T1DM. The aim of this study was to identify current gaps in existing knowledge regarding the relationship between T1DM, inhibition, and behavior management. This study employed a critical review design to analyze and synthesize the current scientific literature. Twelve studies were identified through an appraisal process, and the data extracted were thematically analyzed and integrated. The findings of this study indicate that a possible cycle arises between these three constructs, in which T1DM affects inhibition, inhibition affects behavior management, and poor behavior management affects inhibition. It is recommended that future research should focus more specifically on this relationship.
The study examined the extent, demographics and risks for child pedestrian, burns and drowning mortality in Johannesburg. Information on the demographics, scene and temporal circumstances for childhood injury deaths from 2000 to 2010 was gleaned from the National Injury Mortality Surveillance System. Descriptive statistical methods were used. The study recorded 756 pedestrian (8.7/100,000), 439 drowning (5.1/100,000), and 399 burn injury deaths (4.6/100,000) among children aged 0-14 years. Male children were the main victims, with male-to-female ratios of 2.3 for drowning, 1.7 for pedestrian and 1.2 for burn mortality. The pattern of child mortality differed across age groups with older children recording higher rates for pedestrian deaths and younger children higher rates for the non-traffic deaths. Pedestrian and burn mortality especially affected black children, while drowning affected both black and white children. The time, day and month of greatest injury mortality varied by injury cause, with e.g. pedestrian mortality common in afternoons and evenings, weekends, and dispersed across the year although increasing towards year end. The study highlighted the salience of differentiating risks for childhood injuries by discrete external cause for purposes of informing prevention responses.
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Two experiments were conducted to examine whether attitudes based on affect or cognition were more susceptible to persuasive appeals that matched versus mismatched the basis of attitudes. Experiment 1 provided evidence for a relative affective/cognitive persuasion matching effect and suggested that this matching effect could not be accounted for by attribute matching rather than affective/cognitive matching. Regardless of whether the persuasive appeal matched or mismatched the attitude on the attribute dimension, an affective/cognitive persuasion matching effect occurred. Experiment 2 examined whether the affective/cognitive matching effect could be accounted for by direct/indirect experience persuasion matching. Holding the direct/indirect experience distinction constant, results again demonstrated a relative affective/cognitive persuasion matching effect. Analyses of both experiments using previously validated measures of affect and cognition confirmed that manipulations of the affective and cognitive bases of attitudes were successful.
Health experts independently state that the most critical urban problems are preventable. This brings an added challenge to public health practitioners working in inner cities with predominately minority communities. In addition to deadly diseases - including transmittable diseases - violence, whether it is physical, sexual or child abuse, is the other predominant morbidity factor that urban areas confront. Because of these concerns, there is a need for health professionals working with the communities to critically examine health behavior theories and prevention methodologies. Additionally, new prevention practices and programs need to be developed for community-based interventions to better serve the populations in need including programs in: -HIV Prevention; -Evaluation and Policy Research; -Cancer Prevention and Screening; -Urban Public Health Policy; -Youth Violence Prevention.
A survey of 256 middle-school students showed that parental example plays an important role in the use of seat belts by preadolescent children. Those who reported having ever seen one of their parents wear a seat belt were significantly more likely to wear their own seat belts than children who reported not ever seeing their parents wear a seat belt.
Presented is a meta-analysis of the outcome results for 143 adolescent drug prevention programs to identify the most effective program modalities for reducing teenage drug use. Glass' et al. (1981) meta-analysis techniques provided a systematic approach for the accumulation, quantification and integration of the numerous research findings. Five major modalities were identified and their effect sizes computed for five distinctly different outcomes: Knowledge, Attitudes, Use, Skills and Behavior measures. The magnitude of the effect size was found dependent on the outcome measure employed and the rigor of the experimental design. These factors were controlled for through use of a standard regression analysis. Peer Programs were found to show a definite superiority for the magnitude of the effect size obtained on all outcome measures. On the ultimate criteria of drug use, Peer Programs were significantly different than the combined results of all the remaining programs (p < .0005). Peer Programs maintained high effect size for alcohol, soft drugs and hard drugs, as well as for cigarette use. Recommendations are made concerning the effectiveness of the underlying theoretical assumption for the different program modalities. Future programming implications are discussed as Peer Programs were identified as effective for the average school-based adolescent population, but the Alternatives programs were shown to be highly successful for the “at risk” adolescents such as drug abusers, juvenile delinquents or students having school problems.
SECTION I: INTRODUCTION: Overview of the injury problems Overview of the book: the role of decision makers: schools and child care centers - health care providers - public agencies - legislators/regulators - law enforcement professionals - voluntary organizations - designers, architects, builders, and engineers - business and industry - mass media SECTION II: THE ROADWAY ENVIRONMENT: Motor vehicle occupants Users of other motorized vehicles Pedestrians Bicyclists SECTION III: THE HOME ENVIRONMENT: Fires and burns Poisoning Choking/aspiration/suffocation Falls Animals Firearms Assaults Suicide and suicide attempts SECTION IV: THE SCHOOL AND RECREATION ENVIRONMENT: Playground injuries Sports injuries Drowning and other water-related injuries Concluding remarks: A call to action Appendices Abbreviations and glossary.
Objective—To determine if infants hospitalized for any reason before 90 days of age are at increased risk for future serious injury. Setting—Washington State. Methods—A population based retrospective cohort study, using data from Washington State birth and death certificates linked to a statewide hospital discharge database for the years 1989 through 1997. Participants included healthy full term infants born in Washington State between 1989 and 1995. A total of 29 466 infants hospitalized <90 days of age (early hospitalization) were compared to 29 750 randomly selected infants not hospitalized early. The primary outcome was an injury resulting in hospitalization or death between 3–24 months. Results—Among infants hospitalized early, 76/10 000 had a subsequent serious injury before age 2, compared with 47/10 000 infants without an early hospitalization (relative risk (RR) 1.6; 95% confidence interval (CI) 1.3 to 2.0). In a multivariate model including maternal age and parity, the adjusted RR for serious injury associated with early hospitalization was 1.5 (95% CI 1.2 to 1.8). Infants hospitalized early were three times as likely to be hospitalized between 3–24 months of age for intentional injury compared with infants not hospitalized early (RR 3.3; 95% CI 1.1 to 10.1). Conclusions—Infants hospitalized in the first three months of life for any reason were 50% more likely to have a subsequent serious injury compared with infants not hospitalized early and were also at increased risk of intentional injury. This identifiable group of infants might be suitable for targeted childhood injury prevention programs including those involving prenatal and postnatal visits.
Characteristics of physical injuries were examined in a content analysis of children's television programs. A sample of 57 programs was coded for type of injury, cause of injury, severity of injury consequences, others' responses to injury victim, and victim characteristics. Results indicated a rate of 15 injuries per hour, with significant differences in injury rate according to program time-slot. The majority of injuries resulted from impacts with objects, were intentionally caused, had only minor consequences, and were not followed by any response from other characters. Victims of injury were usually adult males or animal characters. Implications of the findings are discussed within a context of social learning of injury information by child viewers.
This paper explored a model that predicted children's actual injury risk behavior from their current typical reported reactions of excitement versus fear in risky play situations. Fourth-grade children were asked to report on their current typical levels of fear and excitement in response to common play situations, including those involving play in the water. A week or more later, the same children were observed during their turn at free play on the diving board of a local swimming pool. Reporting that current responses to risky play situations resulted in fear was related to lower rates of actual risky behavior and higher rates of protective behavior, whereas reporting current responses of exhilaration to risky situations was related to higher rates of some kinds of actual risky behavior. These relationships were even stronger when only water-related play situations were considered. The data are consistent with findings from observed behavior where the risk was academic, social, or sportsrelated failure rather than injury. Further, this is the first study to document that children's perceptions of their own current cognitive reactions to risky play situations predict their actual concurrent risky behavior in a potential physical injury situation. Thus, these findings suggest an important tool for future prevention programs.