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Beliefs, motives and situational factors related to pedestrians’ self-reported behavior at signal-controlled crossings
Transportation Research Part F 3 (2000) 1±13
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Beliefs, motives and situational factors related to pedestriansÕ self-reported behavior at signal-controlled crossings D. Yagil * Department of Human Services, Faculty of Social Welfare and Health Studies, University of Haifa, Mount Carmel, Haifa 31905, Israel Received 24 November 1999; received in revised form 3 January 2000; accepted 5 January 2000
Abstract The study examined pedestriansÕ self-reported road-crossing behavior in relation to beliefs regarding the consequences of the behavior incorporated in the health belief model, instrumental and normative motives for compliance with safety rules, and situational factors. A questionnaire was administered to 205 students at two Israeli higher education institutions. The results show that crossing against a `DonÕt walk' sign is predicted by perceived consequences of the behavior, as well as by normative motives. The results revealed consistent gender dierences: womenÕs perception of their susceptibility to an accident resulting from an unsafe crossing is higher than that of men; women also report more than men that they are motivated by normative and instrumental considerations. Nevertheless, for women unsafe crossing is predicted only by instrumental motives, whereas for men both normative and instrumental motives predict unsafe crossing behavior. Among the situational variables, the presence of other pedestrians is related to the self-reported crossing behavior of women, whereas trac volume is related to that of men. The results are discussed with regard to similarities and dierences between pedestrians and drivers in compliance with safety laws. Ó 2000 Elsevier Science Ltd. All rights reserved. Keywords: Pedestrians; Health motives; Risk taking; Gender; Road-crossing behaviour
1. Introduction A considerable amount of research on pedestriansÕ behavior has focused on high-risk groups, namely children and elderly people (Assailly, 1997). These studies have explored such issues as exposure to accident risk (Pardo, 1988; Tight, 1988), perceptions of risk (Andrew, 1990),
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judgments relating to safe crossing (Ampofo, Thomson, Grieve & Pitcairn, 1993; Andrew, 1996; Connelly, Isler & Parsonson, 1996), development of road user abilities (Demetre, 1997) and training for safe crossing (Cross & Pitkethly, 1991; Preusser & Lund, 1988; Thomson, 1997; Van Schagen & Rothengatter, 1997). Other studies relating to pedestriansÕ safety have examined the way driversÕ behavior is aected by interventions, such as signs asking drivers to stop for pedestrians (Van Houten & Malenfant, 1992), public education ¯yers (Malenfant & Van Houten, 1990) and signalization (Garder, 1989). A few studies have examined directly the population of adult pedestrians. For example, Van Houten, Malenfant and Rolider (1985) investigated the eect of an intervention on the willingness of pedestrians to signal their intention to cross the street. Andrew (1996) analyzed the impact of demographic variables on the behavior of checking for oncoming trac before crossing an intersection. Firth (1982) maintains that pedestrians as a road user group deserve particular attention because they are the most vulnerable in terms of accident statistics: ``...pedestrians have a higher accident rate than any other group. It is only by studying their behavior in detail that an attempt can be made to ascertain to what extent behavior contributes to these accidents (p. 42)''. The present study explores the relationship of road crossing with the factors included in the health belief model, instrumental and normative motives and situational variables. 1.1. The health belief model The health belief model (Becker, 1974; Rosenstock, 1966) was formulated to account for precautionary health behaviors. According to the model, such behavior is in¯uenced by the following cognitive factors: cues to action, such as information regarding the importance of the behavior; perceived threat, which consists of perceived susceptibility and perceived seriousness of the risk factor; perceived bene®ts, and barriers related to the behavior. These behaviors are affected by demographic and psycho-social variables. The model was applied to road-safety behavior in order to predict helmet use among cyclists (Arnold & Quine, 1994) and safe-riding behavior among motorcyclists (Rutter, Quine & Chesham, 1995). 1.2. Motives for compliance with road safety laws Another perspective that is likely to account for pedestriansÕ crossing behavior relates to their motives for compliance with safety laws. Tyler (1990) argues that the dierent types of motives are re¯ected in two perspectives of obedience to laws. According to the instrumental perspective people are in¯uenced by gains and losses relating to obeying or disobeying the law. The normative perspective explains the sense of obligation to obey the law as a function of personal values. Whereas the instrumental perspective focuses on compliance with the law as a response to external forces, the normative perspective emphasizes the process of internalization of the law (Kelman, 1961). Several studies found that instrumental considerations, such as the perceived danger involved in a trac violation, aect the behavior of drivers (Fuller, 1991; Shinar & McKnight, 1986). The
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normative considerations, however, such as a sense of obligation to obey the law, were also found to be related to compliance with trac laws (Yagil, 1998a,b,c). 1.3. Situational factors aecting road-safety behavior PedestriansÕ road-crossing behavior is aected by the presence of other pedestrians and their behavior. Andrew (1996) found that the fewer the number of other pedestrians crossing the intersection, the greater is the tendency for pedestrians in all age groups to check for oncoming trac. Dannick (1973) concluded that the presence of a law-adhering pedestrian signi®cantly increases the probability that other pedestrians will adhere to a `donÕt walk' signal; a law-violating model, however, was found to in¯uence more pedestrians. Russel, Wilson and Jenkins (1976) found that a high-status model in¯uenced the behavior of more pedestrians than did a low-status model. Mood is an internal situational factor that is also likely to be relevant to pedestriansÕ safety behavior, as it has been seen to aect the safety behavior of drivers. Matthews and Desmond (1995) found that the negative mood related to aggression, relates positively to accident involvement and trac violations, whereas a negative mood related to anxiety and the dislike of driving, is negatively related to the performance of trac violations. Finally, physical factors relating directly to road-crossing behavior, such as trac volume, and conditions relating indirectly to this behavior, such as darkness and weather conditions, are also likely to aect crossing behavior (Andrew, 1991). In summary, the present study examines road-crossing from several perspectives that are relevant to such safety-related behavior: Beliefs relating to the possible consequences of the behavior, motives aecting compliance with road-safety laws, and situational factors. The following questions will be addressed with regard to self-reported road crossing behavior: 1. Does the health belief model account for pedestriansÕ road-crossing behavior? 2. Which motives for compliance with safety-related laws predict road-crossing behavior? 3. Which situational factors are related to road-crossing behavior? 4. Are there gender dierences in beliefs and motives relating to road-crossing behavior? The question relating to gender dierences is based on studies showing that gender dierences in pedestrians behavior are found to exist among children (Finlayson, 1972) as well as among adults (Henderson & Jenkins, 1974; Andrew, 1990).
2. Method 2.1. Respondents Respondents were 203 students at two higher education institutions in the north of Israel. A total of 104 (51%) were male and 99 (49%) female. The age range was 18±37, the average being 24 years old. The average age for men was 24 (S.D. 30) whereas the average age for women was 23 (S.D. 4). Table 1 presents the distribution of respondents in regard to relevant road-crossing variables.
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Table 1 Distribution of respondents in regard to places and frequency of road crossings Average number of signal-controlled intersections crossed per day 0±1 29% 2±3 39% 4 or more 32% Self reported frequency of crossing places with high trac volume Very frequently 16% Frequently 32% Sometimes 33% Rarely 14% Very rarely 5% Major mode of transportation Car 61% Bus 29% Walking 10%
Respondents were approached individually by a research assistant and asked to participate in a study examining various aspects of pedestriansÕ behavior. Following their agreement to participate in the study, they were asked to complete a written questionnaire, an activity lasting 20±30 min. 2.2. Measures Unsafe pedestrian behaviors were measured with ®ve items referring to crossing the road: Not crossing at the pedestrian crossing; Crossing with a `donÕt walk' signal; Walking on the road and not on the pavement; Crossing the road while running; Crossing without watching for cars. Respondents indicated the frequency of performing each behavior on a ®ve-point scale (1 `never' to 5 `frequently'). Cronbach's a is .66. The scales measuring beliefs, motives and the eect of situational variables refer to the speci®c behavior of crossing with or against a `walk'/`donÕt walk' sign. Respondents were asked whether they thought there was a law that prohibited crossing while the sign ¯ashed Ôdon't walkÕ; in all, 92% of the respondents replied positively. Thus, the scales measuring beliefs, motives and the eect of situational variables refer to the speci®c behavior of crossing when a `walk'/`donÕt walk' directive appeared on a signaled intersection. 2.2.1. Beliefs related to road crossing The measurement of the variables included in the health belief model was based on the method used by Rutter et al. (1995) to examine the attitudes of motorcyclists. Perceived susceptibility to being involved in an accident was measured by asking: `Compared to other pedestrians, what is the probability that you will be involved in an accident while crossing when the trac light is ÔdonÕt walkÕ?' The answers were given on a ®ve-point scale (1 `much lower probability'; 3 `same probability'; 5 `much higher probability').
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Perceived seriousness of onesÕ involvement in an accident was measured by asking: `To what extent will an involvement in an accident while crossing when the sign is ÔdonÕt walkÕ aect each of four areas in your life': (a) work, (b) education, (c) family, and (d) social life. The answers were given on a ®ve-point scale (from 1 `to a very small extent' to 5 `to a very large extent'). CronbachÕs a is .91. Perceived bene®ts and barriers were measured by presenting a list of possible positive and negative outcomes of crossing while the sign is ÔdonÕt walkÕ: `saves time'; `prevents inconvenience'; `prevents boredom'; `endangers lives'; `leads to encounter with a police ocer'; `annoys drivers'; `makes a bad impression'. Respondents were asked to indicate their agreement with the belief that each outcome actually happens (from `1 strongly disagree' to 5 `strongly agree'). CronbachÕs a is .53. 2.2.2. Normative motives A sense of obligation to obey laws relating to pedestrian behavior was measured with ®ve items. Three items referred to safety behavior laws: ``Trac laws should be obeyed, regardless of whether they seem logical''; ``It is sometimes all right to cross the road with a `donÕt walk' signal, if one makes sure that there is no trac in the area''; ``Walk signals are mainly designated for children and elderly people''. These items were ranked on a ®ve-point scale (1 `absolutely wrong' to 5 `absolutely correct'). Belief in the law was measured with two items referring the motivation to wait for a ÔwalkÕ sign out of the belief that the law is important: ``I wait for a `walk' sign because I believe that it is important to comply with the law''; ``I wait for a walk sign because I believe that the road safety laws protect pedestrians''. These items were ranked on a ®ve-point scale (1 `to a very small extent' to 5 `to a very large extent'). 2.2.3. Instrumental motives Perceived danger of crossing against a `donÕt walk' sign was ranked on a 10-point scale, which allows for a relatively high level of dierentiation in danger evaluations (Brown & Copeman, 1995). Perceived likelihood of an encounter with the police was measured with one item: `What is the probability that a police ocer will approach a pedestrian who has crossed while the sign is ÔdonÕt walkÕ?' Answers were given on a ®ve-point scale (1 `very low probability' to 5 `very high probability'). 2.2.4. Situational factors The eect of situational factors was examined by asking how the presence of the following factors would aect the respondentÕs behavior at a crossing with a `walk' sign: `high-trac volume', `no trac volume', `darkness', `bad weather', `long duration of a `don't walk' sign', `good mood', `bad mood', `presence of other pedestrians who do not cross', `presence of other pedestrians who cross with a `donÕt walk' signal', `no other pedestrians at the walk signal', `presence of children', `presence of a familiar person'. The responses were given on a seven-point scale (1 `increases the likelihood that I will cross while the sign is ÔdonÕt walkÕ'; 4 `does not aect my
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behavior'; 7 `increases the likelihood that I will cross while the sign is Ôwalk''). CronbachÕs a is .72. Social desirability was measured with a shortened version of the measure developed by Crowne and Marlowe (1964). The original questionnaire consisted of 32 questions. Eight items were included in the present study. CronbachÕs a is .58. The indices used for statistical analyses were composed by averaging the mean scores of respondents on the relevant items.
3. Results The results are presented in three parts. Part one presents regression analyses predicting selfreported unsafe road crossing with the components of the health belief model and with normative and instrumental motives. The second part predicts unsafe road crossing with situational factors. These analyses were conducted for the entire sample as well as separately for men and women. The third part presents the frequency of self-reported unsafe pedestrian behaviors among men and women. Social desirability was controlled in all the regression analyses. 3.1. Beliefs and motives relating to unsafe road crossing Table 2 presents means of the components of the health belief model: beliefs regarding susceptibility, seriousness, bene®ts and barriers relating to crossing when there is a `donÕt walk' sign. Gender dierences were found in t-tests for independent samples: women perceive their susceptibility to be higher than men (M 2.98 and M 2.60, respectively; t(1,187) 2.83, P < .05); believe more that their social life will be aected by an injury (M 3.78 and M 3.62, respecTable 2 Means and standard deviations of beliefs regarding susceptibility, seriousness, bene®ts and barriers relating to crossing with a `donÕt walk' sign M Susceptibility Perceived seriousness of injury Work Studies Family Social life Perceived bene®ts Saves time Prevents inconvenience Prevents boredom Perceived barriers Endangers lives Annoys drivers Might lead to encounter with a police ocer Makes a bad impression
S.D.
2.79
.94
3.95 3.93 3.83 3.70
1.14 1.19 1.23 1.24
3.74 3.06 2.52
.97 1.07 1.25
4.19 3.84 3.72 3.18
.83 1.01 1.02 1.02
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tively; t(1,200) .89, P < .05); and believe more that crossing against a ÔdonÕt walkÕ sign will annoy drivers (M 3.93 and M 3.75, respectively; t(1,200) 1.27, P < .01). Table 3 presents the means of instrumental and normative motives for compliance with road safety laws. t-tests for independent samples show that men and women dier in their respect for the law, as well as their perception of the danger involved in unsafe crossing: men believe more than do women that walking signals are designated for children and the elderly (M 1.90 and M 1.34, respectively; t(1, 198) )4.12, P < .01); women give a higher evaluation to the chances of being approached by a police ocer than do men (M 291 and M 2.53, respectively; t (1,199) 2.19, P < .01). The results of regression analyses predicting self-reported crossing with a `donÕt walk' sign, with components of the health belief model and normative and instrumental motives, are presented in Table 4. These results show that the prediction of road crossing with the health belief model and motives is signi®cant [F(9,172) 13.47, P < .01]. Normative motivation expressed in a sense of obligation to obey the law has the largest contribution to the prediction of crossing; perceived bene®ts are positively related to unsafe behavior, whereas perceived barriers as well as estimated danger are negatively related to the behavior. The analyses conducted separately for men and women show that for men unsafe crossing is predicted by normative motives as well as perceived bene®ts; for women, however, crossing behavior is predicted by perceived bene®ts and perceived danger of crossing. 3.2. Situational factors Table 5 presents the means and standard deviations of the perceived eect of situational variables on self-reported behavior at a walking signal. The results show that a high trac volume, more than any other factor, is perceived as increasing the tendency to wait for the ÔwalkÕ sign; lack of trac increases the tendency to cross with a ÔdonÕt walkÕ sign. Among the physical factors, darkness is perceived to be the most in¯uential and to increase the tendency to wait for the Table 3 Means and standard deviations of normative and instrumental motives for waiting for a `walk' sign Normative motives A sense of obligation to obey the law Trac laws should be obeyed, regardless of whether they seem logical It is sometimes all right to cross the road with a `donÕt walk' signal, if one makes sure that there is no trac in the area Walk signals are mainly designated for children and elderly people Belief in the law Waiting for the `walk' sign because I believe it is important to comply with the law Waiting for the `walk' sign because I believe the law protects Instrumental motives Perceived danger of crossing with a `donÕt walk' signal The probability that a police ocer will approach a pedestrian who crosses while the sign ¯ashes `donÕt walk' a
Scale of 1±10.
M
S.D.
3.69 2.90
1.17 1.46
1.63
.99
3.48 3.00
1.22 1.25
7.65 2.72
2.20a 1.22
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Table 4 Regression analyses of self-reported unsafe pedestrian behavior on the health belief model and instrumental/normative motives
Health belief model Perceived susceptibility Perceived seriousness Perceived bene®ts Perceived barriers Normative motivation A sense of obligation to obey the law Belief in the law Instrumental motivation Perceived danger Perceived risk of Apprehension R2 *
Entire sample
Men
women
B
Beta
B
Beta
B
Beta
).00 ).05 .24 ).21
).00 ).05 .18 ).13
.02 ).09 .27 ).18
.02 ).10 .18 ).11
).12 .00 .24 ).21
).09 .00 .21 ).13
).38 ).19
).30 ).19
).38 ).22
).29 ).21
).26 ).12
).20 ).12
).06 .01 .41
).13 .07
).05 ).02 .44
).10 ).03
).10 .11 .38
).22 .14
P < .05. P < .01.
**
Table 5 Means and standard deviations of the perceived eect of situational variables on behavior at a `walk' signala Trac volume High-trac volume No trac volume Physical conditions Darkness Bad weather Long duration of a `don't walk' sign Mood Good mood Bad mood Other pedestrians Presence of other pedestrians who do not cross Presence of other pedestrians who cross with a `donÕt walk' signal No other pedestrians at the walk signal Presence of children Presence of a person you know
M
S.D.
2.50 )1.27
1.06 1.87
1.22 ).49 ).74
1.44 1.75 1.74
.97 ).30
1.49 1.46
84 ).37 ).00 1.55 .32
1.13 1.46 1.18 1.38 1.43
a
Note: For presentation purposes, the scale was transformed so that 3 indicates crossing with a ÔwalkÕ sign, )3 indicates crossing with a ÔdonÕt walkÕ sign and 0 indicates that the factor has no eect on the behavior.
ÔwalkÕ sign. Bad mood and good mood are perceived to have opposite eects on pedestriansÕ behavior: bad mood decreases safe behavior whereas good mood increases the tendency to behave safely.
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The presence of children as well as the presence of other pedestrians who do not cross increase the tendency to wait for a ÔwalkÕ sign. No dierences were found between men and women with regard to the self-reported eect of any of the situational factors. Table 6 presents the results of multivariate regression analyses predicting the self-reported frequency of unsafe crossing with situational factors. The results show that situational variables signi®cantly predict road crossing (F(5,193) 4.11, P < .01); only trac volume, however, contributes signi®cantly to the prediction of crossing behavior. The regression analyses conducted according to gender, show several dierences between men and women: men are aected more by trac volume and physical conditions, women by the presence of others and by beliefs about the behavior of others. 3.3. Gender dierences in road crossing behavior Table 7 presents the means of the self-reported frequency of performing pedestrian behaviors. Dierences between men and women in the frequency of performing unsafe behaviors were examined with t-tests for independent samples. A signi®cant dierence (t(1,201) 2.46, P < .05) was found only with regard to the frequency of crossing with a ÔdonÕt walkÕ sign, which is higher among men (M 2.92) than among women (M 2.58).
Table 6 Multivariate regression analyses of the self-reported frequency of crossing with a ÔdonÕt walkÕ signal on situational factors Entire sample B Trac volume Physical conditions Mood Presence of others R2 *
).25 ).00 .00 .00
Men Beta ).26 ).00 .00 ).01 .07
Women
B
Beta
).28 ).30 .00 .00
).28 ).24 .03 ).03 .18
B
Beta
).19 .18 .00 ).38
).21 .21 .01 ).25 .05
P < .05. P < .01.
**
Table 7 Means and standard deviations of self-reported frequency of unsafe pedestrian behaviors and their perceived danger
Not crossing at the pedestrian crossing Crossing with a `donÕt walk' signal Walking on the road and not on the pavement Crossing the road while running Crossing without watching for cars
M
S.D.
Percentage performing the behavior frequently
3.56 2.74 2.36 2.13 1.33
.96 1.06 .99 1.01 .76
53 23 13 10 4
10
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4. Discussion The purpose of the study was to examine attitudes relating to the self-reported road-crossing behavior of adult pedestrians. The ®rst question was whether pedestriansÕ road-crossing behavior can be accounted for by the health belief model. The study demonstrated that of the components of the model, pedestriansÕ beliefs regarding the barriers and bene®ts relating to unsafe roadcrossing contribute signi®cantly to the prediction of behavior. The contribution of perceived barriers and bene®ts to the prediction of road crossing is of a similar magnitude. Barriers and bene®ts have a similar weight in the decision whether to cross or not to cross with a `donÕt walk' sign. The second question referred to the relationship of normative and instrumental motives with self-reported road crossing. Normative motives in this study contributed to the prediction of the behavior more than did instrumental motives and more than the components of the health belief model. The ®nding suggests that the motives related to pedestriansÕ compliance with safety rules are dierent from driversÕ motives; the latter were found to be instrumental and normative in a similar degree (Fuller, 1991; Yagil 1998a,b, 1999). Crossing the road with a `donÕt walk' sign is likely to be perceived as less dangerous and as less likely to result in apprehension than the commission of trac violations. Furthermore, pedestriansÕ sense of control over the results of their behavior is likely to be stronger than that of drivers, both in regard to an accident and in regard to apprehension. Thus, when pedestrians avoid crossing the road with a `donÕt walk' sign, they are likely to attribute their restraint to personal values rather than to gain/loss considerations. An additional factor that might explain the dierence between driversÕ and pedestriansÕ motives is the visibility of deviant pedestrians versus the anonymity of deviant drivers. Thus, for pedestrians, social norms enhance compliance with the law whereas drivers are likely to feel less compelled to conform. Nevertheless, it should also be noted that as the respondents of the present study were relatively young, these results might re¯ect the tendency of younger people to attribute more importance to normative than to instrumental considerations (Yagil, 1998b). The third question was related to the perceived eect of situational variables on pedestriansÕ road-crossing behavior. The results showed that trac volume constituted the most in¯uential situational factor. Among women, the presence and behavior of other pedestrians was a highly in¯uential factor. Other pedestrians who do not cross with a `donÕt walk' sign, however, were perceived to be more in¯uential than pedestrians who do cross. Thus other pedestrians, apparently aect road-crossing behavior, not because they serve as role models, but because they stimulate conformity. Crossing the road while other pedestrians wait for the `walk' sign is likely to be perceived as violation of the norms and result in a negative image; on the other hand, refraining from crossing with a `donÕt walk' sign even though other pedestrians cross, might actually be interpreted as stemming from personal principles and thus enhance a sense of moralistic behavior. The dierent physical setting of these two situations is also likely to have an impact: crossing while other pedestrians wait for the `walk' sign implies being watched from the back by the other pedestrians, which might stimulate uncomfortable feelings. Watching other pedestrians cross, however, is likely to be an emotionally neutral experience. The forth question referred to gender dierences. Analyses of the results separately for men and for women revealed consistent gender dierences in beliefs and motives related to road crossing:
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Men report crossing with a `donÕt walk' sign more frequently, and express weaker instrumental and normative motives for safe crossing. These results are similar to the ®ndings of Andrew (1991) who concluded that women are more careful in their behavior as pedestrians. Similar results were found with young children (Assailly, 1997). Furthermore, women perceive themselves as more susceptible to an accident while crossing against a `donÕt cross' sign. Nevertheless, among men crossing behavior is predicted by normative motives but not by the instrumental motive of perceived danger. Women, on the other hand, are motivated by perceived danger more than by normative motives. These results are similar to ®ndings in regard to driving, which indicate that women evaluate the danger involved in the commission of trac violations more highly than do men (Dejoy, 1992). Gender dierences also showed up with regard to the perceived eect of situational factors: whereas road crossing among women is perceived as predicted by the presence and behavior of other pedestrians, among men it is perceived as being in¯uenced by the trac volume and physical conditions. Thus, women are more in¯uenced by their social environment, whereas men seem to be more concerned with the physical aspects of the setting. The results regarding gender dierences in pedestrianÕs behavior are similar to dierences in men and womenÕs driving behavior and in attitudes towards driving violations. For example, Harre, Field and Kirkwood (1996) found that men, more than women, engage in unsafe driving behaviors, such as driving after drinking and speeding. Men underestimate the hazards involved in various driving activities more than women (Dejoy, 1992), evaluate trac violations less seriously than do women (Moyano, 1997; Agostinelli & Miller, 1994), and are more angered than women by the presence of the police (Deenbacher, Oetting & Lynch, 1994). In summary, the results show that safe crossing in aected by perceived consequences of the behavior but not by perceived vulnerability and seriousness. Thus, attitude change activities referring to unsafe pedestrian behavior should undermine possible bene®ts and emphasize the dangers involved in such behaviors. Normative motives were also found to be in¯uential, especially among men. Thus the law-abiding aspect of road crossing, which is a neglected aspect of pedestriansÕ behavior, should be emphasized along with its potential consequences. In other words, unsafe crossing should be presented as a deviant behavior which does not agree with the general conduct of law-abiding citizens. The present study examined pedestriansÕ behaviors through their own reports. Self-reports of behavior are frequently employed in studies examining the commission of driving violations, exploring the relationships between driversÕ behaviors and their attitudes (for example, Groeger & Brown, 1989; Jonah & Dawson, 1986; Parker, Manstead, Stradling & Reason, 1990). Furthermore, a questionnaire measuring social desirability was included in the study and used to control the regression analyses. Nevertheless, self-reported behavior, especially negative behavior, is likely to be biased. It is likely that the data relating to self-reported road crossing behavior re¯ect a tendency toward under-report. The sample included in the present study consisted of students only. As most studies of pedestrians focused on either children or the elderly, the purpose of the present study was to examine relatively young adults. Furthermore, it was believed that students spend more time as pedestrians than employed adults, as they are less likely to own a car. Nevertheless as the sample is biased in terms of education, further research with samples representing lower levels of education might be desirable.
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Some of the measures used in the study had low internal reliabilities. This is likely to be due to the small number of items included in these measures. For example, social desirability was measured with items selected from the original questionnaire. In future studies it is desirable to increase the number of items measuring each variable.
References Agostinelli, G., & Miller, W. (1994). Drinking and thinking: how does personal drinking aect judgments of prevalence and risk? Journal of Studies on Alcohol, 55, 327±337. Ampofo, B. K., Thomson, J. A., Grieve, R., & Pitcairn, T. (1993). A developmental and training study of children's ability to ®nd safe routes to cross the road. British Journal of Developmental Psychology, 11, 31±45. Andrew, H. W. (1990). Perception of risk and curb standing at street corners by older pedestrians. Perceptual and Motor Skills, 70, 1363±1366. Andrew, H. W. (1991). Factors in¯uencing pedestriansÕ cautiousness in crossing streets. Journal of Social Psychology, 131, 367±372. Andrew, H. W. (1996). The safety of older pedestrians at signal-controlled crossings. International Journal of Aging and Human Development, 42, 65±79. Arnold, L., & Quine, L. (1994). Predicting helmet use among schoolboy cyclists: An application of the Health Belief Model. In D.R. Rutter, & L. Quine, Social psychology and health: european perspective. Aldershot: Avebury. Assailly, J. P. (1997). Characterization and prevention of child pedestrian accidents: an overview. Journal of Applied Developmental Psychology, 18, 257±262. Becker, H. M. (1974). The health belief model and personal health behavior. NJ: Slack. Brown, I. D., & Copeman, A. K. (1995). DriversÕ attitudes to the seriousness of road trac oences considered in relation to the design of sanctions. Accident Analysis and Prevention, 7, 15±26. Connelly, M. L., Isler, R., & Parsonson, B. S. (1996). Child pedestrians' judgments of safe crossing gaps at three dierent vehicle approach speeds: a preliminary study. Education and Treatment of Children, 19, 19±29. Cross, R. T., & Pitkethly, A. (1991). Concept modi®cation approach to pedestrian safety: a strategy for modifying young children's existing conceptual framework of speed. Research in Science and Technological Education, 9, 93±106. Crowne, D. P., & Marlowe, D. (1964). The approval motive: studies in evaluative dependence. New York: Wiley. Dannick, L. I. (1973). In¯uence of an anonymous stranger on a routine decision to act or not to act: an experiment in conformity. Sociological Quarterly, 14, 127±134. Deenbacher, J. L., Oetting, E. R., & Lynch, R. S. (1994). Development of a driving anger scale. Psychological Reports, 74, 83±91. Dejoy, D. M. (1992). An examination of gender dierences in trac accident risk perception. Accident Analysis and Prevention, 24, 237±246. Demetre, J. D. (1997). Applying developmental psychology to childrenÕs road safety: problems and prospects. Journal of Applied Developmental Psychology, 18, 263±270. Finlayson, H. M. (1972). ChildrenÕs road behavior and personality. British Journal of Educational Psychology, 42, 225±232. Firth, D. E. (1982). Pedestrian behavior. In A.J. Chapman, F.M. Wade, & H.C. Foot, Pedestrian accidents. Chichester: Wiley. Fuller, R. (1991). The modi®cation of individual road user behavior. In M. Koornstra, & J. Christensen, Enforcement and rewarding strategies and eects. Proceedings of the International Road Safety Symposium, Copenhagen. Leidschendam: SWOV. Garder, P. (1989). Pedestrian safety at trac signals: a study carried out with the help of a trac con¯icts technique. Accident Analysis and Prevention, 21, 435±444. Groeger, J. A., & Brown, I. D. (1989). Assessing one's own and others' driving ability: in¯uence of sex age and experience. Accident Analysis and Prevention, 21, 155±168.
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Harre, N., Field, J., & Kirkwood, B. (1996). Gender dierences and areas of common concern in the driving behaviors and attitudes of adolescents. Journal of Safety Research, 27, 163±173. Henderson, L. F., & Jenkins, D. M. (1974). Response of pedestrians to trac challenge. Transport Research, 8, 71±74. Jonah, B. A., & Dawson, N. E. (1986). Youth and risk: age dierences in risky driving risk perception and risk utility. Alcohol Drugs and Driving, 3, 13±29. Kelman, H. C. (1961). Processes of opinion change. Public Opinion Quarterly, 25, 57±78. Malenfant, L., & Van Houten, R. (1990). Increasing the percentage of drivers yielding to pedestrians in three Canadian cities with a multifaceted safety program. Health Education Research, 5, 275±279. Matthews, G., & Desmond, P. A. (1995). Stress as a factor in the design of in-car driving-enhancement systems. Travail Humain, 58, 109±129. Moyano, D. E. (1997). Evaluation of trac violation behaviors and the causal attribution of accidents in Chile. Environment and Behavior, 29, 264±282. Pardo, J.S. (1988). The exposure of Spanish children to accident risk as pedestrians. In J.A. Rothengatter, & R. de Bruin, Road user behavior: theory and research (pp. 192±196). Assen, Netherlands: Van Gorcum. Parker, D., Manstead, A. S. R., Stradling, S. G., & Reason, J. T. (1990). Determinants of intention to commit driving violations. Accidents Analysis and Prevention, 24, 117±134. Preusser, D. F., & Lund, A. K. (1988). And Keep on Looking: a ®lm to reduce pedestrian crashes among 9 to 12 years olds. Journal of Safety Research, 19, 177±185. Rosenstock, I. M. (1966). Why people use health services. Milbank Memorial Fund Quarterly, 44, 94. Russell, J. C., Wilson, D. O., & Jenkins, J. F. (1976). Informational properties of jaywalking models as determinants of imitated jaywalking: an extension to model sex race and number. Sociometry, 39, 270±273. Rutter, D. R., Quine, L., & Chesham, D. J. (1995). Predicting safe riding behavior and accidents: demography beliefs and behavior in motorcycling safety. Psychology and Health, 10, 369±386. Shinar, D., & McKnight, A.J. (1986). The eects of enforcement and public information on compliance. In L. Evans, & R.C. Schwing, Human behavior and trac safety. New York: Plenum. Thomson, J. A. (1997). Developing safe route planning strategies in young child pedestrians. Journal of Applied Developmental Psychology, 18, 271±281. Tight, M. R. (1988). A study of the accident involvement and exposure to risk of child pedestrians on journeys to and from school in urban areas. In J.A. Rothengatter, & R. de Bruin, Road user behavior: theory and research. (pp. 185±191). Assen, Netherlands: Van Gorcum. Tyler, T. (1990). Why people obey the law. New Haven: Yale University Press. Van Schagen, I., & Rothengatter, J. A. (1997). Classroom instruction versus roadside training in trac safety education. Journal of Applied Developmental Psychology, 18, 283±292. Van-Houten, R., & Malenfant, L. (1992). The in¯uence of signs prompting motorists to yield before marked crosswalks on motor vehicle pedestrian con¯icts at crosswalks with ¯ashing amber. Accident Analysis and Prevention, 24, 217±225. Van-Houten, R., Malenfant, L., & Rolider, A. (1985). Increasing driver yielding and pedestrian signaling with prompting feedback and enforcement. Journal of Applied Behavior Analysis, 18, 103±1107. Yagil, D. (1998a). Gender and age dierences in attitudes toward trac laws and trac violations. Transportation Research F, 1, 123±135. Yagil, D. (1998b). Instrumental and normative motives for compliance with trac laws among young and older drivers. Accident Analysis and Prevention, 30, 417±424. Yagil, D. (1998c). IÕm OK ± YouÕre not OK: driversÕ attitudes toward police ocers enforcing trac laws. An International Journal of Police Strategies and Management, 21, 339±353.
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Beliefs, motives and situational factors related to pedestriansÕ self-reported behavior at signal-controlled crossings D. Yagil * Department of Human Services, Faculty of Social Welfare and Health Studies, University of Haifa, Mount Carmel, Haifa 31905, Israel Received 24 November 1999; received in revised form 3 January 2000; accepted 5 January 2000
Abstract The study examined pedestriansÕ self-reported road-crossing behavior in relation to beliefs regarding the consequences of the behavior incorporated in the health belief model, instrumental and normative motives for compliance with safety rules, and situational factors. A questionnaire was administered to 205 students at two Israeli higher education institutions. The results show that crossing against a `DonÕt walk' sign is predicted by perceived consequences of the behavior, as well as by normative motives. The results revealed consistent gender dierences: womenÕs perception of their susceptibility to an accident resulting from an unsafe crossing is higher than that of men; women also report more than men that they are motivated by normative and instrumental considerations. Nevertheless, for women unsafe crossing is predicted only by instrumental motives, whereas for men both normative and instrumental motives predict unsafe crossing behavior. Among the situational variables, the presence of other pedestrians is related to the self-reported crossing behavior of women, whereas trac volume is related to that of men. The results are discussed with regard to similarities and dierences between pedestrians and drivers in compliance with safety laws. Ó 2000 Elsevier Science Ltd. All rights reserved. Keywords: Pedestrians; Health motives; Risk taking; Gender; Road-crossing behaviour
1. Introduction A considerable amount of research on pedestriansÕ behavior has focused on high-risk groups, namely children and elderly people (Assailly, 1997). These studies have explored such issues as exposure to accident risk (Pardo, 1988; Tight, 1988), perceptions of risk (Andrew, 1990),
*
Tel.: +972-4824-9282; fax: +972-4824-9135. E-mail address: [email protected] (D. Yagil).
1369-8478/00/$ - see front matter Ó 2000 Elsevier Science Ltd. All rights reserved. PII: S 1 3 6 9 - 8 4 7 8 ( 0 0 ) 0 0 0 0 4 - 8
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judgments relating to safe crossing (Ampofo, Thomson, Grieve & Pitcairn, 1993; Andrew, 1996; Connelly, Isler & Parsonson, 1996), development of road user abilities (Demetre, 1997) and training for safe crossing (Cross & Pitkethly, 1991; Preusser & Lund, 1988; Thomson, 1997; Van Schagen & Rothengatter, 1997). Other studies relating to pedestriansÕ safety have examined the way driversÕ behavior is aected by interventions, such as signs asking drivers to stop for pedestrians (Van Houten & Malenfant, 1992), public education ¯yers (Malenfant & Van Houten, 1990) and signalization (Garder, 1989). A few studies have examined directly the population of adult pedestrians. For example, Van Houten, Malenfant and Rolider (1985) investigated the eect of an intervention on the willingness of pedestrians to signal their intention to cross the street. Andrew (1996) analyzed the impact of demographic variables on the behavior of checking for oncoming trac before crossing an intersection. Firth (1982) maintains that pedestrians as a road user group deserve particular attention because they are the most vulnerable in terms of accident statistics: ``...pedestrians have a higher accident rate than any other group. It is only by studying their behavior in detail that an attempt can be made to ascertain to what extent behavior contributes to these accidents (p. 42)''. The present study explores the relationship of road crossing with the factors included in the health belief model, instrumental and normative motives and situational variables. 1.1. The health belief model The health belief model (Becker, 1974; Rosenstock, 1966) was formulated to account for precautionary health behaviors. According to the model, such behavior is in¯uenced by the following cognitive factors: cues to action, such as information regarding the importance of the behavior; perceived threat, which consists of perceived susceptibility and perceived seriousness of the risk factor; perceived bene®ts, and barriers related to the behavior. These behaviors are affected by demographic and psycho-social variables. The model was applied to road-safety behavior in order to predict helmet use among cyclists (Arnold & Quine, 1994) and safe-riding behavior among motorcyclists (Rutter, Quine & Chesham, 1995). 1.2. Motives for compliance with road safety laws Another perspective that is likely to account for pedestriansÕ crossing behavior relates to their motives for compliance with safety laws. Tyler (1990) argues that the dierent types of motives are re¯ected in two perspectives of obedience to laws. According to the instrumental perspective people are in¯uenced by gains and losses relating to obeying or disobeying the law. The normative perspective explains the sense of obligation to obey the law as a function of personal values. Whereas the instrumental perspective focuses on compliance with the law as a response to external forces, the normative perspective emphasizes the process of internalization of the law (Kelman, 1961). Several studies found that instrumental considerations, such as the perceived danger involved in a trac violation, aect the behavior of drivers (Fuller, 1991; Shinar & McKnight, 1986). The
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normative considerations, however, such as a sense of obligation to obey the law, were also found to be related to compliance with trac laws (Yagil, 1998a,b,c). 1.3. Situational factors aecting road-safety behavior PedestriansÕ road-crossing behavior is aected by the presence of other pedestrians and their behavior. Andrew (1996) found that the fewer the number of other pedestrians crossing the intersection, the greater is the tendency for pedestrians in all age groups to check for oncoming trac. Dannick (1973) concluded that the presence of a law-adhering pedestrian signi®cantly increases the probability that other pedestrians will adhere to a `donÕt walk' signal; a law-violating model, however, was found to in¯uence more pedestrians. Russel, Wilson and Jenkins (1976) found that a high-status model in¯uenced the behavior of more pedestrians than did a low-status model. Mood is an internal situational factor that is also likely to be relevant to pedestriansÕ safety behavior, as it has been seen to aect the safety behavior of drivers. Matthews and Desmond (1995) found that the negative mood related to aggression, relates positively to accident involvement and trac violations, whereas a negative mood related to anxiety and the dislike of driving, is negatively related to the performance of trac violations. Finally, physical factors relating directly to road-crossing behavior, such as trac volume, and conditions relating indirectly to this behavior, such as darkness and weather conditions, are also likely to aect crossing behavior (Andrew, 1991). In summary, the present study examines road-crossing from several perspectives that are relevant to such safety-related behavior: Beliefs relating to the possible consequences of the behavior, motives aecting compliance with road-safety laws, and situational factors. The following questions will be addressed with regard to self-reported road crossing behavior: 1. Does the health belief model account for pedestriansÕ road-crossing behavior? 2. Which motives for compliance with safety-related laws predict road-crossing behavior? 3. Which situational factors are related to road-crossing behavior? 4. Are there gender dierences in beliefs and motives relating to road-crossing behavior? The question relating to gender dierences is based on studies showing that gender dierences in pedestrians behavior are found to exist among children (Finlayson, 1972) as well as among adults (Henderson & Jenkins, 1974; Andrew, 1990).
2. Method 2.1. Respondents Respondents were 203 students at two higher education institutions in the north of Israel. A total of 104 (51%) were male and 99 (49%) female. The age range was 18±37, the average being 24 years old. The average age for men was 24 (S.D. 30) whereas the average age for women was 23 (S.D. 4). Table 1 presents the distribution of respondents in regard to relevant road-crossing variables.
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Table 1 Distribution of respondents in regard to places and frequency of road crossings Average number of signal-controlled intersections crossed per day 0±1 29% 2±3 39% 4 or more 32% Self reported frequency of crossing places with high trac volume Very frequently 16% Frequently 32% Sometimes 33% Rarely 14% Very rarely 5% Major mode of transportation Car 61% Bus 29% Walking 10%
Respondents were approached individually by a research assistant and asked to participate in a study examining various aspects of pedestriansÕ behavior. Following their agreement to participate in the study, they were asked to complete a written questionnaire, an activity lasting 20±30 min. 2.2. Measures Unsafe pedestrian behaviors were measured with ®ve items referring to crossing the road: Not crossing at the pedestrian crossing; Crossing with a `donÕt walk' signal; Walking on the road and not on the pavement; Crossing the road while running; Crossing without watching for cars. Respondents indicated the frequency of performing each behavior on a ®ve-point scale (1 `never' to 5 `frequently'). Cronbach's a is .66. The scales measuring beliefs, motives and the eect of situational variables refer to the speci®c behavior of crossing with or against a `walk'/`donÕt walk' sign. Respondents were asked whether they thought there was a law that prohibited crossing while the sign ¯ashed Ôdon't walkÕ; in all, 92% of the respondents replied positively. Thus, the scales measuring beliefs, motives and the eect of situational variables refer to the speci®c behavior of crossing when a `walk'/`donÕt walk' directive appeared on a signaled intersection. 2.2.1. Beliefs related to road crossing The measurement of the variables included in the health belief model was based on the method used by Rutter et al. (1995) to examine the attitudes of motorcyclists. Perceived susceptibility to being involved in an accident was measured by asking: `Compared to other pedestrians, what is the probability that you will be involved in an accident while crossing when the trac light is ÔdonÕt walkÕ?' The answers were given on a ®ve-point scale (1 `much lower probability'; 3 `same probability'; 5 `much higher probability').
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Perceived seriousness of onesÕ involvement in an accident was measured by asking: `To what extent will an involvement in an accident while crossing when the sign is ÔdonÕt walkÕ aect each of four areas in your life': (a) work, (b) education, (c) family, and (d) social life. The answers were given on a ®ve-point scale (from 1 `to a very small extent' to 5 `to a very large extent'). CronbachÕs a is .91. Perceived bene®ts and barriers were measured by presenting a list of possible positive and negative outcomes of crossing while the sign is ÔdonÕt walkÕ: `saves time'; `prevents inconvenience'; `prevents boredom'; `endangers lives'; `leads to encounter with a police ocer'; `annoys drivers'; `makes a bad impression'. Respondents were asked to indicate their agreement with the belief that each outcome actually happens (from `1 strongly disagree' to 5 `strongly agree'). CronbachÕs a is .53. 2.2.2. Normative motives A sense of obligation to obey laws relating to pedestrian behavior was measured with ®ve items. Three items referred to safety behavior laws: ``Trac laws should be obeyed, regardless of whether they seem logical''; ``It is sometimes all right to cross the road with a `donÕt walk' signal, if one makes sure that there is no trac in the area''; ``Walk signals are mainly designated for children and elderly people''. These items were ranked on a ®ve-point scale (1 `absolutely wrong' to 5 `absolutely correct'). Belief in the law was measured with two items referring the motivation to wait for a ÔwalkÕ sign out of the belief that the law is important: ``I wait for a `walk' sign because I believe that it is important to comply with the law''; ``I wait for a walk sign because I believe that the road safety laws protect pedestrians''. These items were ranked on a ®ve-point scale (1 `to a very small extent' to 5 `to a very large extent'). 2.2.3. Instrumental motives Perceived danger of crossing against a `donÕt walk' sign was ranked on a 10-point scale, which allows for a relatively high level of dierentiation in danger evaluations (Brown & Copeman, 1995). Perceived likelihood of an encounter with the police was measured with one item: `What is the probability that a police ocer will approach a pedestrian who has crossed while the sign is ÔdonÕt walkÕ?' Answers were given on a ®ve-point scale (1 `very low probability' to 5 `very high probability'). 2.2.4. Situational factors The eect of situational factors was examined by asking how the presence of the following factors would aect the respondentÕs behavior at a crossing with a `walk' sign: `high-trac volume', `no trac volume', `darkness', `bad weather', `long duration of a `don't walk' sign', `good mood', `bad mood', `presence of other pedestrians who do not cross', `presence of other pedestrians who cross with a `donÕt walk' signal', `no other pedestrians at the walk signal', `presence of children', `presence of a familiar person'. The responses were given on a seven-point scale (1 `increases the likelihood that I will cross while the sign is ÔdonÕt walkÕ'; 4 `does not aect my
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behavior'; 7 `increases the likelihood that I will cross while the sign is Ôwalk''). CronbachÕs a is .72. Social desirability was measured with a shortened version of the measure developed by Crowne and Marlowe (1964). The original questionnaire consisted of 32 questions. Eight items were included in the present study. CronbachÕs a is .58. The indices used for statistical analyses were composed by averaging the mean scores of respondents on the relevant items.
3. Results The results are presented in three parts. Part one presents regression analyses predicting selfreported unsafe road crossing with the components of the health belief model and with normative and instrumental motives. The second part predicts unsafe road crossing with situational factors. These analyses were conducted for the entire sample as well as separately for men and women. The third part presents the frequency of self-reported unsafe pedestrian behaviors among men and women. Social desirability was controlled in all the regression analyses. 3.1. Beliefs and motives relating to unsafe road crossing Table 2 presents means of the components of the health belief model: beliefs regarding susceptibility, seriousness, bene®ts and barriers relating to crossing when there is a `donÕt walk' sign. Gender dierences were found in t-tests for independent samples: women perceive their susceptibility to be higher than men (M 2.98 and M 2.60, respectively; t(1,187) 2.83, P < .05); believe more that their social life will be aected by an injury (M 3.78 and M 3.62, respecTable 2 Means and standard deviations of beliefs regarding susceptibility, seriousness, bene®ts and barriers relating to crossing with a `donÕt walk' sign M Susceptibility Perceived seriousness of injury Work Studies Family Social life Perceived bene®ts Saves time Prevents inconvenience Prevents boredom Perceived barriers Endangers lives Annoys drivers Might lead to encounter with a police ocer Makes a bad impression
S.D.
2.79
.94
3.95 3.93 3.83 3.70
1.14 1.19 1.23 1.24
3.74 3.06 2.52
.97 1.07 1.25
4.19 3.84 3.72 3.18
.83 1.01 1.02 1.02
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7
tively; t(1,200) .89, P < .05); and believe more that crossing against a ÔdonÕt walkÕ sign will annoy drivers (M 3.93 and M 3.75, respectively; t(1,200) 1.27, P < .01). Table 3 presents the means of instrumental and normative motives for compliance with road safety laws. t-tests for independent samples show that men and women dier in their respect for the law, as well as their perception of the danger involved in unsafe crossing: men believe more than do women that walking signals are designated for children and the elderly (M 1.90 and M 1.34, respectively; t(1, 198) )4.12, P < .01); women give a higher evaluation to the chances of being approached by a police ocer than do men (M 291 and M 2.53, respectively; t (1,199) 2.19, P < .01). The results of regression analyses predicting self-reported crossing with a `donÕt walk' sign, with components of the health belief model and normative and instrumental motives, are presented in Table 4. These results show that the prediction of road crossing with the health belief model and motives is signi®cant [F(9,172) 13.47, P < .01]. Normative motivation expressed in a sense of obligation to obey the law has the largest contribution to the prediction of crossing; perceived bene®ts are positively related to unsafe behavior, whereas perceived barriers as well as estimated danger are negatively related to the behavior. The analyses conducted separately for men and women show that for men unsafe crossing is predicted by normative motives as well as perceived bene®ts; for women, however, crossing behavior is predicted by perceived bene®ts and perceived danger of crossing. 3.2. Situational factors Table 5 presents the means and standard deviations of the perceived eect of situational variables on self-reported behavior at a walking signal. The results show that a high trac volume, more than any other factor, is perceived as increasing the tendency to wait for the ÔwalkÕ sign; lack of trac increases the tendency to cross with a ÔdonÕt walkÕ sign. Among the physical factors, darkness is perceived to be the most in¯uential and to increase the tendency to wait for the Table 3 Means and standard deviations of normative and instrumental motives for waiting for a `walk' sign Normative motives A sense of obligation to obey the law Trac laws should be obeyed, regardless of whether they seem logical It is sometimes all right to cross the road with a `donÕt walk' signal, if one makes sure that there is no trac in the area Walk signals are mainly designated for children and elderly people Belief in the law Waiting for the `walk' sign because I believe it is important to comply with the law Waiting for the `walk' sign because I believe the law protects Instrumental motives Perceived danger of crossing with a `donÕt walk' signal The probability that a police ocer will approach a pedestrian who crosses while the sign ¯ashes `donÕt walk' a
Scale of 1±10.
M
S.D.
3.69 2.90
1.17 1.46
1.63
.99
3.48 3.00
1.22 1.25
7.65 2.72
2.20a 1.22
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Table 4 Regression analyses of self-reported unsafe pedestrian behavior on the health belief model and instrumental/normative motives
Health belief model Perceived susceptibility Perceived seriousness Perceived bene®ts Perceived barriers Normative motivation A sense of obligation to obey the law Belief in the law Instrumental motivation Perceived danger Perceived risk of Apprehension R2 *
Entire sample
Men
women
B
Beta
B
Beta
B
Beta
).00 ).05 .24 ).21
).00 ).05 .18 ).13
.02 ).09 .27 ).18
.02 ).10 .18 ).11
).12 .00 .24 ).21
).09 .00 .21 ).13
).38 ).19
).30 ).19
).38 ).22
).29 ).21
).26 ).12
).20 ).12
).06 .01 .41
).13 .07
).05 ).02 .44
).10 ).03
).10 .11 .38
).22 .14
P < .05. P < .01.
**
Table 5 Means and standard deviations of the perceived eect of situational variables on behavior at a `walk' signala Trac volume High-trac volume No trac volume Physical conditions Darkness Bad weather Long duration of a `don't walk' sign Mood Good mood Bad mood Other pedestrians Presence of other pedestrians who do not cross Presence of other pedestrians who cross with a `donÕt walk' signal No other pedestrians at the walk signal Presence of children Presence of a person you know
M
S.D.
2.50 )1.27
1.06 1.87
1.22 ).49 ).74
1.44 1.75 1.74
.97 ).30
1.49 1.46
84 ).37 ).00 1.55 .32
1.13 1.46 1.18 1.38 1.43
a
Note: For presentation purposes, the scale was transformed so that 3 indicates crossing with a ÔwalkÕ sign, )3 indicates crossing with a ÔdonÕt walkÕ sign and 0 indicates that the factor has no eect on the behavior.
ÔwalkÕ sign. Bad mood and good mood are perceived to have opposite eects on pedestriansÕ behavior: bad mood decreases safe behavior whereas good mood increases the tendency to behave safely.
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9
The presence of children as well as the presence of other pedestrians who do not cross increase the tendency to wait for a ÔwalkÕ sign. No dierences were found between men and women with regard to the self-reported eect of any of the situational factors. Table 6 presents the results of multivariate regression analyses predicting the self-reported frequency of unsafe crossing with situational factors. The results show that situational variables signi®cantly predict road crossing (F(5,193) 4.11, P < .01); only trac volume, however, contributes signi®cantly to the prediction of crossing behavior. The regression analyses conducted according to gender, show several dierences between men and women: men are aected more by trac volume and physical conditions, women by the presence of others and by beliefs about the behavior of others. 3.3. Gender dierences in road crossing behavior Table 7 presents the means of the self-reported frequency of performing pedestrian behaviors. Dierences between men and women in the frequency of performing unsafe behaviors were examined with t-tests for independent samples. A signi®cant dierence (t(1,201) 2.46, P < .05) was found only with regard to the frequency of crossing with a ÔdonÕt walkÕ sign, which is higher among men (M 2.92) than among women (M 2.58).
Table 6 Multivariate regression analyses of the self-reported frequency of crossing with a ÔdonÕt walkÕ signal on situational factors Entire sample B Trac volume Physical conditions Mood Presence of others R2 *
).25 ).00 .00 .00
Men Beta ).26 ).00 .00 ).01 .07
Women
B
Beta
).28 ).30 .00 .00
).28 ).24 .03 ).03 .18
B
Beta
).19 .18 .00 ).38
).21 .21 .01 ).25 .05
P < .05. P < .01.
**
Table 7 Means and standard deviations of self-reported frequency of unsafe pedestrian behaviors and their perceived danger
Not crossing at the pedestrian crossing Crossing with a `donÕt walk' signal Walking on the road and not on the pavement Crossing the road while running Crossing without watching for cars
M
S.D.
Percentage performing the behavior frequently
3.56 2.74 2.36 2.13 1.33
.96 1.06 .99 1.01 .76
53 23 13 10 4
10
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4. Discussion The purpose of the study was to examine attitudes relating to the self-reported road-crossing behavior of adult pedestrians. The ®rst question was whether pedestriansÕ road-crossing behavior can be accounted for by the health belief model. The study demonstrated that of the components of the model, pedestriansÕ beliefs regarding the barriers and bene®ts relating to unsafe roadcrossing contribute signi®cantly to the prediction of behavior. The contribution of perceived barriers and bene®ts to the prediction of road crossing is of a similar magnitude. Barriers and bene®ts have a similar weight in the decision whether to cross or not to cross with a `donÕt walk' sign. The second question referred to the relationship of normative and instrumental motives with self-reported road crossing. Normative motives in this study contributed to the prediction of the behavior more than did instrumental motives and more than the components of the health belief model. The ®nding suggests that the motives related to pedestriansÕ compliance with safety rules are dierent from driversÕ motives; the latter were found to be instrumental and normative in a similar degree (Fuller, 1991; Yagil 1998a,b, 1999). Crossing the road with a `donÕt walk' sign is likely to be perceived as less dangerous and as less likely to result in apprehension than the commission of trac violations. Furthermore, pedestriansÕ sense of control over the results of their behavior is likely to be stronger than that of drivers, both in regard to an accident and in regard to apprehension. Thus, when pedestrians avoid crossing the road with a `donÕt walk' sign, they are likely to attribute their restraint to personal values rather than to gain/loss considerations. An additional factor that might explain the dierence between driversÕ and pedestriansÕ motives is the visibility of deviant pedestrians versus the anonymity of deviant drivers. Thus, for pedestrians, social norms enhance compliance with the law whereas drivers are likely to feel less compelled to conform. Nevertheless, it should also be noted that as the respondents of the present study were relatively young, these results might re¯ect the tendency of younger people to attribute more importance to normative than to instrumental considerations (Yagil, 1998b). The third question was related to the perceived eect of situational variables on pedestriansÕ road-crossing behavior. The results showed that trac volume constituted the most in¯uential situational factor. Among women, the presence and behavior of other pedestrians was a highly in¯uential factor. Other pedestrians who do not cross with a `donÕt walk' sign, however, were perceived to be more in¯uential than pedestrians who do cross. Thus other pedestrians, apparently aect road-crossing behavior, not because they serve as role models, but because they stimulate conformity. Crossing the road while other pedestrians wait for the `walk' sign is likely to be perceived as violation of the norms and result in a negative image; on the other hand, refraining from crossing with a `donÕt walk' sign even though other pedestrians cross, might actually be interpreted as stemming from personal principles and thus enhance a sense of moralistic behavior. The dierent physical setting of these two situations is also likely to have an impact: crossing while other pedestrians wait for the `walk' sign implies being watched from the back by the other pedestrians, which might stimulate uncomfortable feelings. Watching other pedestrians cross, however, is likely to be an emotionally neutral experience. The forth question referred to gender dierences. Analyses of the results separately for men and for women revealed consistent gender dierences in beliefs and motives related to road crossing:
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Men report crossing with a `donÕt walk' sign more frequently, and express weaker instrumental and normative motives for safe crossing. These results are similar to the ®ndings of Andrew (1991) who concluded that women are more careful in their behavior as pedestrians. Similar results were found with young children (Assailly, 1997). Furthermore, women perceive themselves as more susceptible to an accident while crossing against a `donÕt cross' sign. Nevertheless, among men crossing behavior is predicted by normative motives but not by the instrumental motive of perceived danger. Women, on the other hand, are motivated by perceived danger more than by normative motives. These results are similar to ®ndings in regard to driving, which indicate that women evaluate the danger involved in the commission of trac violations more highly than do men (Dejoy, 1992). Gender dierences also showed up with regard to the perceived eect of situational factors: whereas road crossing among women is perceived as predicted by the presence and behavior of other pedestrians, among men it is perceived as being in¯uenced by the trac volume and physical conditions. Thus, women are more in¯uenced by their social environment, whereas men seem to be more concerned with the physical aspects of the setting. The results regarding gender dierences in pedestrianÕs behavior are similar to dierences in men and womenÕs driving behavior and in attitudes towards driving violations. For example, Harre, Field and Kirkwood (1996) found that men, more than women, engage in unsafe driving behaviors, such as driving after drinking and speeding. Men underestimate the hazards involved in various driving activities more than women (Dejoy, 1992), evaluate trac violations less seriously than do women (Moyano, 1997; Agostinelli & Miller, 1994), and are more angered than women by the presence of the police (Deenbacher, Oetting & Lynch, 1994). In summary, the results show that safe crossing in aected by perceived consequences of the behavior but not by perceived vulnerability and seriousness. Thus, attitude change activities referring to unsafe pedestrian behavior should undermine possible bene®ts and emphasize the dangers involved in such behaviors. Normative motives were also found to be in¯uential, especially among men. Thus the law-abiding aspect of road crossing, which is a neglected aspect of pedestriansÕ behavior, should be emphasized along with its potential consequences. In other words, unsafe crossing should be presented as a deviant behavior which does not agree with the general conduct of law-abiding citizens. The present study examined pedestriansÕ behaviors through their own reports. Self-reports of behavior are frequently employed in studies examining the commission of driving violations, exploring the relationships between driversÕ behaviors and their attitudes (for example, Groeger & Brown, 1989; Jonah & Dawson, 1986; Parker, Manstead, Stradling & Reason, 1990). Furthermore, a questionnaire measuring social desirability was included in the study and used to control the regression analyses. Nevertheless, self-reported behavior, especially negative behavior, is likely to be biased. It is likely that the data relating to self-reported road crossing behavior re¯ect a tendency toward under-report. The sample included in the present study consisted of students only. As most studies of pedestrians focused on either children or the elderly, the purpose of the present study was to examine relatively young adults. Furthermore, it was believed that students spend more time as pedestrians than employed adults, as they are less likely to own a car. Nevertheless as the sample is biased in terms of education, further research with samples representing lower levels of education might be desirable.
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Some of the measures used in the study had low internal reliabilities. This is likely to be due to the small number of items included in these measures. For example, social desirability was measured with items selected from the original questionnaire. In future studies it is desirable to increase the number of items measuring each variable.
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