Factors Influencing Night-time Drivers Perceived Likelihood of Getting Caught for Drink- Driving

Transcription

1 T2007 Seattle, Washington Factors Influencing Night-time Drivers Perceived Likelihood of Getting Caught for Drink- Driving Jean Wilson *1, Ming Fang 1, Gabi Hoffmann 2. 1 Insurance Corporation of British Columbia, 910 Government Street, Victoria, BC V8W 3YB Canada; 2 Police Services Division, Ministry of Public Safety and Solicitor General, Hornby Street, Vancouver, BC V6Z 2E6, Canada. The purpose of the study was to determine the factors influencing drivers ratings of the likelihood of getting caught by police for drink-driving. The study used two approaches. First, individual predictors of perceived risk were examined through a regression model. Second, the study attempted to explain community differences in perceived risk, both across communities and across years, by examining community roadcheck enforcement data. The study was based on data collected from two night time roadside surveys conducted in three British Columbia communities in June 2003 and Approximately 2,000 drivers participated in each survey by providing a breath sample and answering a short series of questions. A separate multiple regression was run on each year of survey data. The dependent measure was the driver s 1-7 rating of the likelihood of a drinking driver being stopped by police. The predictor variables were driver age, gender and BAC reading, number of times through a roadcheck in the past 6 months and perceived effectiveness of the CounterAttack (roadcheck) program. The second approach consisted of comparing enforcement data provided by police for the years just prior to the survey years. Specifically, the aggregated monthly totals of roadcheck hours and drivers apprehended were examined for each of the 3 communities. Regression results for both years were very similar. The predictor variables, number of times through a roadcheck, belief in the effectiveness of the roadcheck program and driver BAC were all positively related to perceived likelihood of being stopped. The results also showed differences between cities in the mean perceived likelihood of being stopped. In one city, the mean was lower than in the other two, but remained stable from 2003 to In the other two cities, the mean rating of perceived risk dropped between 2003 and A similar and consistent pattern was observed for the number of times drivers reported going through roadchecks. Enforcement data tended to mirror the trends in levels of perceived risk and roadcheck experience in each community. The study provides evidence that personal experience with roadchecks influences a driver s perceived risk of being caught for drink-driving. The study also showed consistency between community levels of roadcheck activity and mean levels of perceived risk. Furthermore, drivers who drink are the ones most likely to perceive a higher risk. Although the latter result may appear counterintuitive, these drivers have a greater need to be aware of the risk than drivers who do not require external controls on their drink-driving behavior. Key Words: Perceived risk, Enforcement, Roadside survey Introduction The deterrence model provides the theoretical basis underlying the use of police roadchecks to control drink-driving. The model assumes that high visibility police enforcement targeting large numbers of drivers, especially when combined with media coverage, will increase the perceived

2 risk of detection among drivers exposed to the roadcheck experience, including those at risk of drink-driving (Homel, 1988). A higher level of perceived risk should be associated with a reduced tendency to drink and drive both at the individual and at the community level. While the logic seems intuitive, only a few studies have demonstrated an empirical relationship between levels of enforcement and levels of perceived risk among the population. Several studies have demonstrated an association between checkpoint programs and reductions in alcoholrelated crashes, but few have measured the intervening variable in the model, perceived risk of detection (Voas, Holder & Gruenewald, 1997). An Australian study (Harrison and Pronk, 1998) relying on telephone survey data reported that number of times drivers had witnessed drinkdriving enforcement in the past month was related to their perceived risk of detection for drinkdriving. Voas, Holder and Gruenewald (1997) found only weak evidence of a population level increase in perceived risk of arrest as a function of community level publicity and number of breathalyzers issued to police, but no relationship to checkpoint activity. However, they did find that perceived risk of arrest was negatively related to self-reported drink-driving among telephone survey respondents (the greater the perception of risk, the fewer reported drink-driving events). British Columbia has a long-standing impaired driving program, CounterAttack, whose main component is the use of province-wide high visibility police roadchecks. The enforcement component of the program is resourced by additional funding to pay for police overtime. The roadcheck campaigns are accompanied by advertising and media announcements although the level of coverage has varied by month and year. The purpose of the present study was to determine both individual level variables that influence perceived likelihood of detection for drink-driving and to relate population levels of perceived risk to levels of roadside checkstop enforcement in the community. Method The study was based on data collected from two roadside surveys conducted in three British Columbia communities, Vancouver, Abbotsford and Saanich, in June 2003 and A random method was used to select both survey sites and vehicles. Surveying took place from Wednesday through Saturday nights between 2100 hours and 0300 hours for one week in each city. In 2003, 2322 drivers provided both an interview and a breath sample and in 2006 full participation was obtained from 2074 drivers. The refusal rate for the breath sample was 7-8% of selected vehicles in both years while an additional 4-5% declined the interview. Breath samples were processed on site with an Intoxilyzer. A description of the survey methods can be found in Beirness et al, A question designed to measure the perceived likelihood of detection for drink-driving was asked: How likely do you think it is that a person who drives after drinking will be stopped by the police? The driver was instructed to respond with a number from 1-7, representing a scale of not at all likely to very likely. This rating was the dependent measure in the study. Note that the question of perceived risk was framed in the third person, so that all drivers could answer the question, even if they never engaged in drink-driving. Using SPSS, Version 15, a multiple regression model was run on each year s data for the following independent variables: driver age, driver sex, number of times the driver reported having been through a police roadcheck in the past 6 months, how effective the driver thought the CounterAttack (roadcheck) program was in influencing people s decision to drink and drive

3 (big effect versus small effect/ no effect) and driver blood alcohol reading, as measured by the Intoxilizer. The latter was classified as either zero (0-5 mg%) or positive (> 5 mg%). Drivers from all three communities were combined in the models. Cases with missing values on any of the variables were excluded (listwise deletion). Enforcement data were obtained for each of the three communities, Vancouver, Saanich and Abbotsford, for the years 2002 through These data were provided by the police as part of the enhanced enforcement standard reporting. For each month, they included: number of roadcheck visibility hours and number of 24-hour prohibitions (suspensions) issued. In British Columbia the count of 24-hour prohibitions is the most complete measure of drinking drivers detected and sanctioned, because it is always issued along with a more severe consequence but can also be issued alone where there may be insufficient evidence to charge. Examination of roadcheck enforcement data confirmed that in the three communities there was little or no CounterAttack roadcheck activity between January and June of any year. The CounterAttack program generally ran between June or July and December. The police may have conducted some roadchecks under regular hours, but unfortunately records are only available for roadchecks resourced by enhanced (overtime) funding. Since the survey was conducted in June, this means that the previous year is the best available comparison period in determining perceived risk rather than the 6 months immediately prior to the survey. For this reason, we used 2002 as the reference period for the 2003 survey and 2005 as the reference period for the 2006 survey. However, for 2005 the data were less complete due to a restructuring of the enforcement program. The only data available for Saanich for 2005 were the total number of 24-hour prohibitions issued under enhanced funding from January to December. As roadcheck hours were missing in 2005, they had to be imputed from 2004 data, using an average ratio of 1.35 roadcheck hours per prohibition issued, as calculated for The community census population was used as a denominator to create a ratio of roadcheck hours that was proportional to community size. Results Regression Analyses The demographic characteristics of the samples changed little from year to year. In 2003 the mean age of the final sample included in the regression model was 34.0, while in 2006 it was In both samples, 31.0% of drivers were female and 11% were BAC positive. The regression models for each of the two years yielded very similar results. In 2003 the total adjusted variance (R 2 ) in the dependent measure (rating of perceived risk of being stopped by police) accounted for by the model was.075 with F = 33.35, p<.0001 and in 2006, adjusted R 2 =.083 and F = 34.29, p < The regression coefficients and t-values for each survey year are shown in Table 1. All the selected variables made a significant contribution. Younger drivers and female drivers tended to perceive a higher level of risk than older and male drivers, however these relationships were weak and in 2006, the age effect was nonsignificant. Experience with roadchecks and belief in their effectiveness both made significant independent contributions to the model, although the latter was the stronger of the two predictors. These two predictors were only weakly intercorrelated (R=.08). The BAC reading was also related to perceived risk, with BAC positive drivers estimating a higher risk than BAC negative drivers. It was determined through separate correlation analysis that among BAC positive drivers the perceived risk did not

4 increase with increasing BAC. In other words the relationship between BAC and perceived risk of detection is not linear but rather, bimodal. Table 1. Beta coefficients and t-values for regression on perceived likelihood of a driving driver being stopped by police in 2003 and 2006 Model Unstd β Std. β t Sig. Unstd.β Std. β t Sig. Constant Age Sex (male) Times thru roadcheck BAC reading Perceived effectiveness Community comparisons The weighted mean ratings of perceived risk of a drinking driver being stopped by police for each of the three communities in 2003 and 2006 are shown in Figure 1. The means are weighted by traffic volume at each site to achieve sample representativeness. There was a substantial decrease in the mean rating of perceived likelihood of getting stopped by police for drink-driving between 2003 and 2006 in Saanich (t=4.28, p<.001 and in Abbotsford (t=4.19, p<.001) but essentially no change in Vancouver (t=0.77, p<.44). 4.5 Figure 1. Mean Perceived Likelihood of Being Stopped by Police for Drinking and Driving Mean Rating Vancouver Saanich Abbotsford The mean number of times through a Counter Attack roadcheck is shown in Figure 2. The pattern for Saanich and Abbotsford is similar and is consistent with the changes in perceived likelihood of drink-driving detection shown in Figure 1. For both communities, the decrease in mean number of times through a roadcheck in the past 6 months was significant (Saanich, t = 5.00, p<.001; Abbotsford, t = 3.42, p<.001). In Vancouver, the trend was divergent. Vancouver drivers reported slightly higher rates of going through roadchecks in 2006 than in 2003, although the difference was only marginally significant ( t = -2.16, p<.03).

5 Roadcheck enforcement statistics are presented in Table 2. Note that this table includes only roadcheck hours supported through enhanced funding. It is apparent that police visibility relative to population size was higher in Abbotsford and Saanich in 2002 than in Vancouver. In 2005, both Abbotsford and Saanich experienced a drop in visibility, while the decrease in Vancouver was much less. In fact absolute visibility hours increased in Vancouver in Although the 2005 data for Saanich are estimated and subject to inaccuracy, it appears likely that a substantial decrease occurred. All three places experienced a population increase between the two surveys, however it is unknown if the population increase would have a linear relationship with the likelihood of a roadcheck contact. Figure 2. Mean Number of Times through CounterAttack Roadcheck Mean Times Through CounterAttack Vancouver Saanich Abbotsford Table 2. Roadcheck enforcement summary data for the years prior to the roadside surveys Abbotsford Vancouver Saanich* Census population 115, , , , , ,102 Roadcheck hours - total ,277 1,761 1, (est.)** RC hours/pop X (est.) * Saanich data include the adjacent communities of Victoria, Oak Bay, Central Saanich and Esquimalt ** Roadcheck hours are estimated for Saanich in See Methods for imputation procedure

6 The percent of drivers with a BAC 50 mg% or greater is shown in Figure 3. All three communities experienced an increase in drivers in this BAC category in However the increase was significant only for Saanich, (likelihood ratio, χ2 = 5.84, p (2-sided) <.02), and approached significance for Vancouver, (χ2=2.71, p<.10). Figure 3. Percent of Drivers with BAC > 50 mg % Percent Vancouver Saanich Abbotsford Discussion The regression models showed that an individual driver s perceived risk of getting stopped for drink-driving is influenced by both their relatively recent experience of going through roadchecks, as well as their belief that roadchecks are effective in influencing the decision to drink and drive. Driver age and sex had a relatively weak association with perceived risk. Testing positive for alcohol was associated with a higher perceived risk of getting stopped for drink-driving, although this is not explained by more roadcheck experience. BAC positive and negative drivers had equivalent roadcheck experience. One could speculate that a drinking driver is more apprehensive about going through a roadcheck, and that increased fear of detection influenced the perception of risk. A nondrinking driver who has nothing to fear may have a more cynical view of perceived risk, especially as the question was worded in the third person. The overall variance accounted for by the model is rather small less than 10%, however it was not the intent of the study to identify all measurable sources of variance. Part of the unexplained variance is likely due to the fact that individuals interpret and use the rating scale differently a 6 to one person may mean something different than a 6 to someone else. There are also other factors that influence the perceived risk of detection for drink-driving that have not been addressed in the present study. One salient variable, exposure to media coverage and public awareness was not directly captured in the present study. Attitudes toward drink-driving were also not measured. The results support the logic model underlying the use of drink-driving police roadchecks. Communities with higher roadcheck activity were associated with higher ratings of perceived risk among nighttime drivers. Police reporting of roadcheck enforcement activity substantiated drivers aggregated self-reported experience with roadchecks. Downward shifts in community

7 roadcheck activity over time were associated with downward shifts in mean levels of perceived risk, and with a tendency, in at least one community, toward a larger proportion of higher BAC (>50 mg%) drivers. These associations, while all consistent with the causal model of drink-driving enforcement as presented by Voas, Holder and Gruenewald (1997) are only correlational. While it is tempting to assume that the observed decreases in enforcement, reported roadcheck experience, and perceived risk of detection along with the trend toward higher BAC drivers are all causally linked, the study does not enable this conclusion. The link to higher BACs is especially tenuous as many other factors including an upswing in the economy and a changing population could influence drinking and driving. The fact that Vancouver experienced an increase in drinking drivers without a corresponding decrease in enforcement suggests that extraneous factors are at play. Conclusion The study is strongly suggestive that high visibility police roadchecks are associated with higher levels of perceived risk in the community, and that the individual s level of perceived risk is influenced by personal experience with roadchecks and the strength of their belief in roadcheck effectiveness. References Beirness, DJ, Foss, RD, Wilson, RJ and Burch, B. (2004), Tracking the incidence of drinking drivers on the road at night in british Columbia: The results of roadside surveys. Proceedings T- 2004, International Conference on Alcohol, Drugs and Traffic Safety, Glasgow UK, August 8-13, Harrison, WA and Pronk, NJ (1998). An investigation of the relationship between traffic enforcement and the perceived risk of detection for driving offences. Monash University (MUARC) Report # 134, Homel, R (1988). Policing and punishing the drinking driver: Random breath-testing and the process of deterrence. New York: Springer-Verlag. Voas, RB, Holder, H and Gruenewald, PJ. (1997). The effect of drinking and driving interventions on alcohol-involved traffic crashes within a comprehensive community trial. Addiction, 92 (Supplement 2), S221-S236.