Journal of Pediatric Psychology Advance Access originally published online on June 25, 2006
Journal of Pediatric Psychology 2007 32(3):343-353; doi:10.1093/jpepsy/jsl009
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The Influences of Demographics and Individual Differences on Children’s Selection of Risky Pedestrian Routes
Department of Psychology, University of Alabama at Birmingham
All correspondence concerning this article should be addressed to Benjamin K. Barton, Department of Psychology, MacKinnon Building, University of Guelph, Guelph, Ontario N1G 2W1. E-mail: bbarton{at}uoguelph.ca.
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Abstract |
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Objective Thousands of American children under the age of 10 are injured annually as pedestrians. Despite the scope of this public health problem, knowledge about behavioral factors involved in the etiology of child pedestrian injury remains sparse. The present study considered the roles of age, gender, ethnicity, family income, and inhibitory control on children’s selection of safe pedestrian routes. Methods Children’s selections of risky pedestrian routes were examined in two laboratory analogue tasks. Multiple behavioral and self-report methods were used to measure temperamental inhibitory control. Results Children from lower-income families, children of ethnic minority background, younger children, and those with less temperamental control selected riskier pedestrian routes. Conclusions Prevention efforts might be tailored to focus on children at higher risk for pedestrian injury, such as younger, undercontrolled children.
Key words: child injury; inhibitory control; pedestrian safety; route selection.
Each year, approximately 18,000 American child pedestrians under the age of 10 are injured and over 400 are killed (National Center for Injury Prevention and Control [NCIPC], 2006
). Pediatric pedestrian injuries result in an estimated $11.7 billion annually in injury-related expenses (National Safety Council, 2001). Despite these data, knowledge about behavioral factors involved in the etiology of child pedestrian injury remains poor.
Risk for child pedestrian injury is partly a function of the physical environment. Identified environmental risk factors include poor visibility of oncoming traffic, lack of crosswalks and stoplights, and distracted drivers (Macpherson, Roberts, & Pless, 1998; Posner et al., 2002). However, children are involved in a dynamic interaction with their environments (Bronfenbrenner, 1977, 1986), and therefore, a complete description of etiological factors contributing to child pedestrian injury must also consider demographics and individual differences as risk factors.
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Demographic Risk Factors |
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A range of demographic factors is associated with child pedestrian risk. Epidemiological influences of age are perhaps the most straightforward. Middle childhood is a time of increased risk for pedestrian injury (Assailly, 1997
; U.S. Department of Transportation, 2001), with over 12,000 American children ages 5–9 experiencing a serious pedestrian injury in 2004 (NCIPC, 2006). As children grow older, between the ages of 5 and 9, their pedestrian skills gradually increase (Connelly, Conaglen, Parsonson, & Isler, 1998; Whitebread & Neilson, 2000). Concomitantly, children range farther from home while unsupervised (e.g., walking to school), perhaps accounting for the gradual increase in the injury rate during this period (Agran, Winn, & Anderson, 1994; NCIPC, 2006; Wills et al., 1997).
Other demographic factors relevant to child pedestrian safety are gender, ethnicity, and socioeconomic status. Gender has long been associated with risk for children’s pedestrian injury (Assailly, 1997; Macpherson, et al., 1998), with boys experiencing pedestrian injury at a rate roughly twice that of girls (NCIPC, 2006). American children from an ethnic minority background are at higher risk for pedestrian injury (Howard, Joseph, & Natale, 2005; King & Palmisano, 1992), probably because they more frequently live in urban areas with greater traffic density and higher rates of unemployment (Laflamme & Diderichsen, 2000; LaScala, Gerber, & Gruenewald, 2000). Pedestrian injury rates are indeed higher in low socioeconomic status urban areas with, in addition to higher traffic density, more crowded housing and fewer safe areas to play away from traffic (Laflamme & Diderichsen, 2000; Rivara & Barber, 1985).
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Temperament |
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In comparison with demographic factors, individual differences in temperament are less established as a behavioral risk factor for pediatric pedestrian injury. However, a range of epidemiological and laboratory-based studies offer suggestive evidence that there might be increased risk for pedestrian injury in children with less behavioral control (Briem & Bengtsson, 2000
; DiScala, Lescohier, Barthel, & Li, 1998; Hoffrage, Weber, Hertwig, & Chase, 2003; Pless, Taylor, & Arsenault, 1995; Whitebread & Neilson, 2000). In short, the argument is made that children with less behavioral control will not stop to think about the risks involved in a crossing, will not pause to search carefully for potential hazards, and will overlook visual obstacles in the process of crossing a roadway. Children with greater temperamental control will have greater safety throughout the process of crossing streets. |
Subcomponents of Street-Crossing Behaviors |
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Knowledge about epidemiological risks for injury is most useful if applied toward the development of prevention programs. To do so, it is critical to understand not just what factors predict pediatric pedestrian injury risk, but how and why those factors function. Lizette Peterson framed this objective as an identification of the behavioral antecedents and consequences of an injury event. In particular, she emphasized the importance of understanding the behavioral factors that occur before and contribute to a particular injury (Peterson, Farmer, & Mori, 1987
).
To evaluate the behavioral mechanisms contributing to pediatric pedestrian injury in the present paper, we considered the various cognitive steps required for a child to complete the complex task of crossing a street (Thomson et al., 2005). This technique helps pinpoint which particular aspects of a complex and potentially dangerous task such as crossing a street might be influenced by particular behavioral factors. As an example, temperamental control might influence a child’s judgment of when to cross a street but not perception of the speed of oncoming traffic.
Among the subcomponents of cognitive processing required to safely cross a street are judgment of the speed of approaching traffic from at least two directions, recognition of the size of traffic gaps and consideration of which gaps afford safe crossing, searching and scanning the environment for extraneous hazards, judgment of the distance across the road and the speed with which one can propel oneself across that span, and consideration of potentially occluding objects such as parked cars.
Safe street-crossing also requires consideration and selection of the optimal route to cross, which is the focus of this study. Selecting a safe street-crossing route involves, for example, choosing to cross at a crosswalk or other location at which traffic is regulated by a signal, rather than crossing mid-block or diagonally. Without selecting the safest location to cross a street, children might significantly increase their risk of injury by choosing a more expedient but riskier route.
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Selection of Safe Street-Crossing Routes |
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Children appear to become increasingly skilled at selecting safer pedestrian routes as they reach ages between 5 and 10. Studies using indoor laboratory and outdoor route selection tasks suggest younger children tend to select riskier routes. Early in childhood, 5- through 7-year-olds tend to select the most direct route to a destination, considering expedience (e.g., diagonal intersection-crossing) but not safety (e.g., use of marked crosswalks) in their selection of routes (Ampofo-Boateng & Thomson, 1991
; Ampofo-Boateng et al., 1993; Thomson, 1997). Young children also have difficulty identifying risk factors that might influence selection of routes—for example, they do not recognize the dangers of mid-street crossings and they fail to notice parked cars or shrubbery that might impede the view of oncoming traffic (Ampofo-Boateng & Thomson, 1991).
As children develop through middle childhood, they begin to adapt their behavior to discover and choose safer routes across streets to their destinations. They develop visual, perceptual, and selective attention skills that permit processing of multiple stimuli and consideration of the multiple factors required to safely choose a route across streets (Fenner, Heathcote, & Jerrams-Smith, 2000; Ridderinkhof, van der Molen, Band, & Bashore, 1997). By age 9, most children identify safe routes with skill similar to that of adults, understand the need to move to alternative but more distant crossing locations to preserve safety, and recognize parked cars and shrubbery as obstacles that might impede the view of oncoming traffic (Ampofo-Boateng & Thomson, 1991; Ampofo-Boateng et al., 1993).
Ethnicity and socioeconomic status also may be important factors linked to route selection. Epidemiological research consistently reports that the rate of pediatric pedestrian injury is higher among ethnic minorities and in low-income neighborhoods, probably because traffic volumes are higher and traffic environments more dangerous in areas in which these children live (Laflamme & Diderichsen, 2000). Although links to route selection are tenuous, there is no question that physical context plays a role in the development of pedestrian route selection skill. Developing in an area with high traffic volume and few safe areas, as many low-income and ethnic minority children do, might afford differing opportunities to develop and practice safe route selection and broad pedestrian skills in protected, comparatively safe areas.
The influences of gender and temperament on route selection are less clear. Previous investigations that considered gender found null results (Ampofo-Boateng & Thomson, 1991; Ampofo-Boateng et al., 1993; Thomson, 1997). Boys and girls selected routes with equivalent safety despite the fact that boys have much higher rates of pedestrian injury, risk-taking behavior, and lower temperamental control (Assailly, 1997; Schwebel & Barton, in press). The present study considered gender differences in route selection by using a larger sample than tested previously and by testing children’s route selection through both tabletop models and short vignettes.
The influence of temperament on children’s route selection is untested in the published literature to our knowledge. Because temperament, specifically inhibitory control, appears to be related to potentially injurious behavior patterns (Schwebel, 2004; Schwebel & Plumert, 1999; Schwebel & Barton, in press) and to pedestrian injury (Briem & Bengtsson, 2000; Hoffrage et al., 2003; Pless et al., 1995; Whitebread & Neilson, 2000), we anticipated children with lower inhibitory control might choose riskier routes in pedestrian environments.
This paper was designed, therefore, to investigate the roles of demographic factors (ethnicity, income, age, and gender) and individual differences (temperamental inhibitory control) in the specific pedestrian safety subcomponent of selecting safe routes across streets. Multiple measurement techniques were used to assess both temperamental control and pedestrian route selection among a sample of 6- through 10-year-old children. We hypothesized that younger children, boys, children from lower SES backgrounds, children from ethnic minority backgrounds, and children with poorer inhibitory control would select the riskiest pedestrian routes.
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Methods |
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Participants
Power analysis indicated a sample of 120 individuals would be sufficient to achieve a power of 0.85 (
= .05, f2 = 0.15 [medium effect]; Cohen, 1988). A sample of 122 six- through ten-year-old children (mean age = 100.76 months; SD = 19.53) and their parents (120 mothers, 2 fathers) were recruited through community advertisements and in cooperation with local schools. The sample was fairly evenly divided by gender, including 67 boys (age 6 = 23, age 8 = 26, age 10 = 18) and 55 girls (age 6 = 17, age 8 = 21, age 10 = 17). Ethnic composition was 68% Caucasian (age 6 = 26, age 8 = 33, age 10 = 24), 30% African-American (age 6 = 13, age 8 = 13, age 10 = 11), and 2% of other ethnicities. For each age group, mean annual household income was between $67,625 and $70,294 (SD = 27,057–28,190) and ranged from below $20,000 to over $100,000. Informed consent was obtained from all parents, and informed assent (as developmentally appropriate) from all children. The university’s institutional review board approved all procedures.
Procedure
Children completed all measures accompanied by researchers in a university laboratory. Mothers completed self-report measures in a nearby room. Families were given nominal compensation.
Inhibitory Control Measures
To minimize the risk of measurement error, three methods were used to assess temperamental inhibitory control (Campbell & Fiske, 1959): parent reports, child reports, and a structured behavioral battery.
Parent-Reported Inhibitory Control
The Child Behavior Questionnaire (CBQ; Rothbart, Ahadi, & Hershey, 1994) and Early Adolescent Temperament Questionnaire (EATQ; Capaldi & Rothbart, 1992) were used to gather parent-report measures of inhibitory control. The measures are designed as parallel instruments for different developmental stages. Parents of 6- and 7-year-olds completed the inhibitory control scale from the CBQ (13 items; = .66). Parents of 8-, 9-, and 10-year-olds completed the corresponding scale from the EATQ (5 items; = .60). Both measures exhibited strong psychometric properties in previous studies (Capaldi & Rothbart, 1992; Rothbart et al., 1994).
Child-Reported Inhibitory Control
The CBQ and EATQ were used as self-report temperament batteries for children. Six-year-olds completed an adapted oral measure of the CBQ inhibitory control scale (Schwebel, 2004). Internal reliability for this sample with 11 items was = .49. The inhibitory control scale from the child-report form of the EATQ (11 items; = .61) was completed by 8- and 10-year-olds.
Structured Behavioral Battery for Inhibitory Control
Children’s inhibitory control also was assessed using a behavioral battery of six tasks, detailed below in the order presented to children in the study. Most tasks were derived through review of studies using behavioral measures of inhibitory control in this age group (Kochanska, Murray, & Coy, 1997; Schwebel, 2004), and were scored using objective, discrete categories to maximize validity and reduce statistical non-normality.
In the Walk-a-Line task, a white piece of yarn measuring 10 feet (304.8 cm) was placed on the floor. Children were asked to walk from one end of the yarn to the other, then told to repeat the task "as slowly as possible" and then "as quickly as possible." The difference between the baseline time and the slow time was computed (Kochanska et al., 1997).
In the Draw-a-Circle task, children received a sheet of paper with two large printed circles and were asked to draw a third circle between the two circles already on the page (Kochanska et al., 1997). Children were then asked to draw two circles on similar pages, one as slowly as possible and the second as quickly as possible. The difference between the time taken to draw the slow circle and the baseline initial drawing time was computed (Kochanska et al., 1997).
In the Money task (adapted from Rodriguez, Mischel, & Shoda, 1989), children were seated at a table. Two transparent plastic boxes filled with prize money were located on the table along with a small bell. One box contained four dollars and the other contained six dollars. Children were told that the researcher needed to leave the room for a short time, and if they waited until the researcher returned, they could have the box with six prize dollars. Alternatively, children could ring the bell at any time to have the researcher return, but would get the box with only four prize dollars. The researcher left the room for a maximum of 4 min, or until the child rang the bell. Children received a dichotomous score for touching or not touching the bell. Children also received a dichotomous score for fidgeting behavior: 1 for sitting without much movement and 2 for moving a great deal or standing up.
In the Reach for the Sky task, children were asked to remove a play dollar bill from a rope slowly lowered toward them on a pulley system. Using a starting point computed from a previously measured baseline (starting point was 12 inches higher than the child’s maximum vertical reach while standing on tiptoes), a play dollar bill was lowered toward the child at a rate of 2 inches per second. Children were instructed to reach for the money when they thought they could get it, but were not permitted to jump. A dichotomous score was coded: child reached the money on the first attempt (indicating control to wait until the money was within reach) or multiple attempts were required to reach the money (indicating less controlled behavior).
In the Peeking task (Schwebel, 2004), children were told the researcher had "forgotten something in the other room" and were instructed to remain alone in the room until the researcher came "right back." As the researcher exited the room, he or she reminded the children, "Remember, don’t look under the blanket until all the games are done, because that’s where your prizes are kept." A large chest filled with prizes for participating in the study was left near the child and covered loosely with a bed sheet. Children were videotaped through a one-way mirror while alone in the room for 90 s. Children received an approach score: 1 for "child did not leave chair during 90 s interval," 2 for "left chair, but did not approach box," 3 for "approached box, but did not touch it," 4 for "touched box," 5 for "looked into box but did not touch toys," or 6 for "touched toys."
In the Prize-Choosing task (Schwebel, 2004), conducted at the end of the study session, children were informed they had "won" two prizes. The researcher opened a large chest of toys and displayed and discussed several toys. The presentation lasted approximately 60 s. Children received a score based on the number of interruptions made while the researcher presented the prizes: 0 for no interruptions, 1 for a single interruption, and 2 for multiple interruptions.
Pedestrian Route Selection Measures
As with temperament, multiple methods of measurement were invoked to assess children’s pedestrian route selection. Two types of measures were used: route selection on two tabletop models and route selection in four pedestrian vignettes. Note that these measures were designed only to assess children’s route selection in pedestrian environments, and were not designed to measure other aspects of the street-crossing process.
Tabletop Pedestrian Route Selection Task
Children used static tabletop models proportional at a 1:36 ratio for two real-life pedestrian settings. The first model was based on an intersection between a four-lane and a two-lane street in an urban setting. The second model was based on a T-shaped intersection between a major artery and a minor street in a residential setting. Streets and intersections on both models were marked with relevant pedestrian cues, including traffic lights, crosswalks, and road striping. Trees, shrubs, buildings, and parked unmovable vehicles were included in order to match the visual obstructions found in the real pedestrian settings. Pilot testing was done to ensure that children understood the tabletop street-crossing task. Evidence from previous research suggests children’s pedestrian route selections on tabletop tasks are similar to that found in outdoor simulations on real roads (Ampofo-Boateng & Thomson, 1991). In addition, evidence suggests the tabletop and outdoor methods work equally well as training tools for safer route selection (Ampofo-Boateng et al., 1993).
Children used a small wind-up toy to retrieve three numbered flags at selected locations on each model. Children were told to imagine they were on the street and to make the toy walk the way they would if they were on a real street. The wind-up toy was then placed at the starting position and the child was asked to choose a direction to start the crossing. Children released the wind-up toy and were allowed to make necessary adjustments in direction in order to reach the flag. Shorter but riskier routes required less time for the toy to reach a flag (e.g., crossing a street diagonally rather than perpendicularly). Longer routes required more time, but were safer. Routes were scored according to risk: crossing at a crosswalk with a traffic light = 1, crossing at a crosswalk without a traffic light = 2, crossing streets mid-block at a 90° angle to the curb = 3, and crossing streets or intersections diagonally = 4. In all, children completed six crossings (two models with three flags each) and received a single total score for risky pedestrian behavior on the tabletop models (range = 6–24).
Pedestrian Route Selection Vignettes
Four brief vignettes were read to children; at the end of each story, children were asked to choose from three pedestrian routes to reach a desirable or obligatory goal (e.g., buy ice cream from the ice cream truck). Each vignette was accompanied by an illustration on which, verbally or physically, children indicated their preferred route. As in the tabletop task, shorter routes were riskier but quicker; longer routes were safer but slower. The scoring scheme for the vignettes was identical to that of the tabletop task, and yielded a single score for risky pedestrian behavior in the vignettes (range = 4–16). Children’s pedestrian route selections using illustrations or photographs of roads are similar to outdoor methods in past research (Ampofo-Boateng & Thomson, 1991).
Intercoder Reliability
On all behavioral temperament and route selection tasks, two researchers independently rated children’s behavior for 39% of the sample (n = 48). All reliability measures were adequate (continuous variables, r = .92–1.00; categorical variables, 
= 0.91–1.00). The remaining portion of the sample was coded by a single researcher. Discrepancies between coders were resolved by using data from the primary coder, who coded the entire sample.
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Results |
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Analyses proceeded in three steps. First, behavioral temperament tasks were aggregated into a single measure. Second, descriptive statistics and correlation matrices were examined. Third, a series of three multiple linear regressions examined predictors of children’s pedestrian route selection.
Aggregation of the Behavioral Battery
All task variables were standardized and aggregated to create a single measure of inhibitory control, with tasks reversed as needed so that all measures represented more control. Before aggregation, a square-root transformation was applied to scores from the Walk-a-Line and Draw-a-Circle tasks to correct significant positive skew. Internal reliability was moderate, as has been found in other research using behavioral batteries designed to assess the same construct ( = .50; average inter-item correlation = .13; Schwebel, 2004).
Descriptive Statistics and Correlations
Descriptive statistics and relations between all variables of interest were examined (Table I). First, we examined interrelations between demographics and inhibitory control measures. Ethnicity and income were significantly and negatively related, r(120) = –.50, p < .01. Income was related to child-reported inhibitory control and the behavioral battery, r(120) = .24 and .20 respectively, p < .05. Age also was significantly related to scores on the behavioral battery, r(120) = .35, p < .01. Parent-report and child-report measures of inhibitory control were not related at a statistically significant level, r(120) = .18, and anticipated relations did not emerge between inhibitory control in the behavioral battery and parent- or (for the most part) child-reported inhibitory control behavior.
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Next, we examined relations between demographics, inhibitory control, and route selection measures. Income was significantly related to both the tabletop and vignette route selection tasks, r(120) = –.27 and –.38 respectively, p < .01. Ethnicity also was related to the behavioral temperament battery, r(120) = –.26, p < .01, and tabletop and vignette route selection tasks, r(120) = .41 and .45 respectively, p < .01. Significant relations were found between age and tabletop and vignette route selection tasks, r(120) = –.42 and –.31 respectively, p < .01. Consistent with previous research, no relation was found between gender and route selection. Risky pedestrian route selection on the tabletop model was related to risky selection in the vignettes, r(120) = .50, p < .01. Parent-reported inhibitory control also was not significantly related to route selection. However, significant relations were found between scores on the inhibitory control battery and the tabletop and vignette tasks, r(120) = –.28 and –.36 respectively, p < .01.
Regression Analyses
In a series of three analyses, each route selection measure was regressed on age, ethnicity, income, child-reported inhibitory control, and behavioral battery scores (Table II). Gender and parent-reported inhibitory control were excluded from these analyses because of a lack of relation with route selection measures. No problems with multicollinearity were found. Two children who were neither Caucasian nor African-American were identified by Cook’s and leverage scores as outliers, indicating they had undue influence on the regression fit, and were excluded from regression analyses.
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Results for the tabletop and vignette methods were similar. Age (ß = –.38 tabletop and –.18 vignette), ethnicity (ß = .19 tabletop and .18 vignette), and income (ß = –.17 tabletop and –.26 vignette) significantly predicted risky route selection in both the methods. Behaviorally-measured temperament (ß = –.10 tabletop and –.26 vignette) significantly predicted risky route selection measured in vignettes. Child reports of temperament did not significantly predict route selection in either analysis.
As a final test of the hypotheses, scores from the two route selection measures were standardized and then aggregated into a single measure (Epstein, 1983; Rushton, Brainerd, & Pressley, 1983). The aggregate route score was regressed on demographic and temperament measures. Results were consistent with the first two analyses—age, ethnicity, income, and behavioral inhibitory control scores, ß = –.33, .21, –.26, and –.21, respectively, significantly predicted risky pedestrian route selection.
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Discussion |
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The present study examined factors related to children’s selection of risky pedestrian routes. Younger age, ethnic minority status, lower family income, and lower temperamental inhibitory control predicted selection of riskier routes. Neither child gender nor child- or parent-reported temperament was significantly related to route selection.
Demographic Characteristics
Consistent with other research (Ampofo-Boateng & Thomson, 1991; Ampofo-Boateng et al., 1993; Thomson, 1997), younger children in the present sample failed to identify safe routes across pedestrian settings. Hearkening Piagetian theory (Piaget, 1970), children who have not yet developed full concrete operational abilities are unable to simultaneously consider and process multiple variables in a single situation. Pedestrian route selection is a rather complex problem, requiring children to evaluate multiple possible routes and the varying risks associated with each option. Cognitive developmentalists examining visual-spatial (Fenner et al., 2000) and selective attention (Ridderinkhof et al., 1997) skills, as well as pedestrian safety researchers considering visual search (Whitebread & Neilson, 2000) and distance/velocity perception (Hoffmann, Payne, & Prescott, 1980; Salvatore, 1974), discover that children develop the applicable skills to handle multiple stimuli between the ages of 5 and 10, usually displaying adult-like abilities by the early pubertal years. The same appears to be true of pedestrian route selection: not until the end of the middle childhood years are children apparently able to manipulate the multiple cognitive aspects of route selection with adult-like efficiency.
Although lower family income and ethnic minority status predicted riskier route selection, it seems unlikely that such children are inherently riskier pedestrians. Rather, a confluence of contextual factors may place such children at greater risk for pedestrian injury and, by extension, to riskier route selection. Such children often live in neighborhoods with higher density housing, higher traffic volume, and fewer areas to play away from traffic (Laflamme & Diderichsen, 2000; Rivara & Barber, 1985). Given these contextual factors, parents might limit their children’s opportunities to cross streets alone, thus also limiting their experience in selecting safer pedestrian routes. Rather than risky pedestrian behavior being characteristic of lower income and ethnic minority children, selecting riskier routes may be because of lack of safe pedestrian experience and training. The present study suggests ethnicity and income are related to the pedestrian behavioral subcomponent of route selection, but further research is necessary to explore the causal mechanisms behind this correlational link.
Although gender differences in pedestrian injury are well established in the epidemiological literature (Assailly, 1997; Macpherson et al., 1998), gender was not related to pedestrian route selection in correlational analyses, and was therefore excluded from the regression analyses. This finding, which replicates previous route selection research (Ampofo-Boateng & Thomson, 1991; Ampofo-Boateng et al., 1993; Thomson, 1997), suggests epidemiological findings that link gender with pedestrian safety are probably not explained by route selection, but rather by other subcomponents of safe street crossing. For example, recent research found girls engaged in safer pre-street-crossing behaviors than boys by attending better to oncoming traffic and by waiting more patiently before crossing (Barton & Schwebel, 2006). Thus, gender may be more important in determining the street-crossing behaviors children engage in after a route is chosen rather than in the process of selecting the route itself.
Inhibitory Control
As hypothesized, lower temperamental control was linked to riskier pedestrian route selection in this study. This finding, which corresponds to results from laboratory studies examining the role of temperament on children’s injury risk (Schwebel, 2004; Schwebel & Plumert, 1999) and to broader data on the role of temperament on children’s pedestrian safety (Briem & Bengtsson, 2000; Hoffrage et al., 2003; Pless et al., 1995; Whitebread & Neilson, 2000), is the first to identify route selection as one component of pedestrian safety that contributes to elevated risk for pedestrian injury among children with lower inhibitory control.
We found significant relations between our behavioral temperament battery and children’s route selection, but not between parent- or child-report measures of temperament and the route selection measures. We offer a few possible explanations for this surprising result.
First, measurement of temperament is notoriously challenging (Kagan, 1994; Rothbart & Bates, 1998). In this study, the paper-and-pencil measures of temperament did not correlate well with the behavioral measures (Rothbart & Bates, 1998), and several of the temperament measures had mediocre internal reliability. The different measures of temperament may have tapped somewhat different behavioral constructs, with the construct tapped by the behavioral temperament measure being more relevant to route selection than the others.
Second, method variance may have contributed to the results. Three possibilities can be identified here: (a) because the route selection tasks were somewhat behavioral in nature, they may have correlated with the behavioral temperament measure more strongly because of measure variance rather than conceptual relations; (b) one of the route selection measures (vignette) was administered amidst the behavioral temperament tasks, and children may have approached the route selection vignettes in a similar manner as the behavioral temperament tasks, which were rewarded activities, and thus sought or expected a reward while engaging in it; or (c) parent reports assess child temperament in the context of normal daily activities, in comparison with the behavioral battery which assessed temperament in a controlled laboratory setting; the laboratory setting may have contributed shared method variance to both behavioral temperament and pedestrian route selection measures.
Third, questionnaire measures of temperament may have related weakly to route selection because the present sample was limited to a normal community sample rather than a group of children with more extreme temperamental control problems. For example, a sample of children characterized by behavioral disorders such as oppositional defiant disorder or attention-deficit/hyperactivity disorder might show stronger relations to risk-taking behavior (Rowe, Maughan, & Goodman, 2004; Schwebel, Speltz, Jones, & Bardina, 2002).
Although the behavioral temperament measure significantly predicted route selection, behavioral temperament also was positively related to age, and one might speculate the significance of temperament as a predictor is simply an artifact of the relation of age to route selection. To test the unique relation of temperament to route selection, three post-hoc hierarchical regression analyses were conducted to predict route selection in the tabletop, vignette, and aggregated task measures. Children’s age, ethnicity, and family income were entered in the first step, and child-report and behavioral temperament measures in the second. Results were similar to the original interpretation. The behavioral temperament measure significantly and independently added to the model after age, ethnicity, and income for vignette and aggregate route selection measures, but not for the tabletop measure.
Implications for Injury Prevention
Being a safe pedestrian requires manipulation of a large number of complex cognitive tasks. Partial mastery of these tasks fails to offer safety from injury. This study considered the influences of demographic variables (age, ethnicity, and income) and inhibitory control on one component of safe pedestrian behavior—route selection—and discovered that each of these factors influence that aspect of pedestrian safety. From the perspective of intervention development, the findings suggest children from lower economic status and children of minority ethnic background might be targeted for pedestrian training. Findings also suggest that children with less temperamental control might be supervised more carefully, or trained more intensively, than their temperamentally controlled counterparts. Indeed, existing research using controlled laboratory methods suggests children with less temperamental control readily respond to the presence of a supervising parent (Schwebel & Bounds, 2003). Such an impact of supervision also may be found in pedestrian settings (Barton & Schwebel, 2006).
Eight- and especially 6-year-olds might also be targeted for pedestrian safety intervention (Ampofo-Boateng et al., 1993; Thomson et al., 2005). One method of targeting young children could be tailoring interventions to younger children’s developing cognitive abilities. Researchers should, for example, acknowledge young children’s undeveloped selective attention (Tabibi & Pfeffer, 2003) and memory skills (Morrison, Holmes, & Haith, 1974; Sheingold, 1973) that affect their ability to plan and execute safe pedestrian behaviors. As younger children’s cognitive ability to select safe pedestrian routes is likely to be minimal, increased physical and verbal supervision, as well as parental efforts to train children, also are required. The impact of supervision on injuries among young children in the home is well established (Morrongiello, 2005), and should be explored further in pedestrian settings.
In addition to active prevention methods targeting children most at risk, passive methods also must be continued. In areas where children frequently cross streets, such as in school zones, and near apartment communities or parks, physical barriers might be used to guide the flow of pedestrian traffic toward safe crossing locations. For example, children walking to a neighborhood park might be guided by shrubbery or fences toward a crosswalk where a signal regulates vehicular traffic.
Future research should also consider etiological factors in other components of pediatric pedestrian safety (Thomson et al., 2005). Although some work exists—most notably in topics like attendance to the speed of approaching traffic (Hoffmann et al., 1980; Salvatore, 1974; Siegler & Richards, 1979), choosing safe crossing gaps (Connelly et al., 1998; Lee, Young, & McLaughlin, 1984; Pitcairn & Edlmann, 2000), and the role of visual search skills (Whitebread & Neilson, 2000)—further inquiries would aid greatly in understanding the process of child pedestrian injury by identifying child risk factors to target for intervention attempts and ultimately to develop broadly-based pediatric pedestrian injury-prevention programs.
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Like all research, this study suffered from some limitations. We address three. First, one might argue that laboratory measures of pedestrian route selection—for example, the tabletop method—tap the same construct as behavioral temperament tasks. We view this overlap as a reflection of the fact that temperament drives pedestrian behaviors such as route selection. Temperamental traits such as inhibitory control are defined as patterns of reactivity to various situations (Rothbart & Bates, 1998
). The laboratory battery was designed to assess those patterns in a series of situations and, in combination with the parent- and self-report measures, is likely to constitute a reasonable approximation of each child’s temperamental trait. The pedestrian measures, though certainly influenced by temperamental traits, represent an assessment of behavior in pedestrian environments, not unfamiliar or novel situational events that were designed to elicit behavioral patterns of temperament. Second, ethnicity and income both were predictors of riskier route selection in the present sample, which had a mean income that was broad, but generally higher than the community as a whole. Given that pedestrian injuries are more frequent in lower-income neighborhoods and among ethnic minorities, this relation may in fact be even stronger in samples taken from such populations. Researchers should seek to include children from at-risk backgrounds in future studies in order to better explore behavioral etiology of pedestrian injuries among those populations.
Finally, although laboratory analogue measures of pedestrian behaviors are used frequently in the literature and appear to provide a reasonable approximation of children’s behaviors in real settings (Ampofo-Boateng & Thomson, 1991), they have drawbacks. Children crossing real streets are faced with dynamic complexity that is difficult to recreate in the laboratory, and future research might consider techniques to assess pedestrian behavior that have greater ecological validity but still protect research participants from real-life traffic.
Received October 31, 2005; revision received March 23, 2006; accepted May 31, 2006
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