Examining the differences in perceived legal and non-legal factors between drink driving and drug driving

Abstract

Drink and drug driving countermeasures have several similarities, yet also have a number of differences. To improve the effectiveness of these countermeasures, it is important to delineate the perceptions of both legal and non-legal factors between drink driving and drug driving. This study aimed to understand these differences and how legal and non-legal factors uniquely contribute to future intentions to engage in these illegal behaviours. A total of 546 licensed drivers who have a history of using both alcohol and drugs (marijuana, MDMA, and/or ice/speed) responded to an online survey that included legal deterrence measures as well as established measures of non-legal factors for both drink driving and drug driving. The non-legal factors included the fear of physical loss (e.g., fear of injuring yourself or others), social loss (e.g., social disapproval) and internal loss (e.g., guilt). Participants were more likely to report drug driving compared to drink driving, with a higher perceived chance of being caught for drink driving and more experience avoiding punishment for drug driving. Physical loss to others and internal loss were higher for drink driving. For both models, punishment avoidance was a significant predictor. Certainty of apprehension and severity punishment were only significant deterrents for drug driving, not drink driving. The threat of physical loss to oneself was a significant deterrent for drink driving, not drug driving. The results show that legal and non-legal deterrents are rated as lower for drug driving compared to drink driving, yet legal sanctions are still a deterrent for drug driving. Further, non-legal countermeasures are needed for both drink and drug driving that increase drivers’ perceived fear of physical loss to others, internal loss, and social sanctions associated with the behaviours.

Keywords

Deterrence drink driving drug driving random breath testing roadside drug testing

Introduction

Driving under the influence of drugs and alcohol is widely considered to be a major public health concern that is responsible for thousands of avoidable deaths (World Health Organization, 2018). Over 20 per cent of fatalities across the globe (including but not limited to Australia, Canada, Austria, Cambodia, Norway, United States, United Kingdom) have been attributed to drink driving (International Transport Forum, 2017). More recently, in Queensland, Australia (where this study took place), over 22 per cent of fatalities in 2020 were attributed to drink driving motorists (Queensland Government, 2022). Driving under the influence impacts judgment, reflexes, lane positioning, and vision, which increases crash risk, dependent on blood alcohol content (BAC) (Queensland Government, 2022). For instance, driving with a BAC of more than 0.10 increases crash risk up to 70 per cent (Department of Transport and Main Roads, 2015).

In terms of drug driving, it has been reported that over 15 per cent of Australian drivers’ have driven under the influence of drugs (Australian Institute of Health and Welfare, 2017). Further, in Queensland between 2011 and 2015, 48 per cent of road crash fatalities had illicit drugs detected in their system (Davey et al., 2020). Clearly, drug driving is a prominent issue in Australia, with 1 in 5 random drug tests being positive (Anderson et al., 2021). Yet, even more concerning is the increased crash risk upwards of 35 per cent when driving under the influence of drugs (Chihuri & Li, 2017; Governors Highway Safety Association, 2018). Taken together, the current literature provides strong evidence that drink and drug driving pose a major risk to road safety in Australia and throughout the world. As a result, Australian officials have implemented strong enforcement initiatives in the form of random breath testing (RBT) and roadside drug testing (RDT). These enforcement programs have been considered to be the most intensive worldwide (Davey & Sheldrake, 2017). RBT operations involve police officers stopping vehicles at any time of the day or night for either a mobile or static roadside breath test and measuring if drivers are above the legal blood alcohol limit (in Australia, this limit is .05; Australian Government Department of Health, 2021). Meanwhile, RDTs can also occur at mobile or static roadside testing sites and consist of a police officer obtaining a mandatory saliva sample which is analysed for the presence of select drugs. However, drug testing is more expensive and time consuming than breath testing which has resulted in RDTs being more targeted (Davey & Sheldrake, 2017) and occurring less frequently than RBTs. For example, according to the Queensland Police 2018–2019 Annual Report (Queensland Government, 2019), over 2.66 million random breath tests were conducting during the reporting period, detecting more than 16,000 drink driving offences. However, only 70,000 roadside drug tests were conducted in the same period, with approximately one in five drivers testing positive.

Deterrence theory has typically been used to examine how legal enforcement and punishment can influence engagement in offending behaviour. The perceived certainty of apprehension has been considered the most important component of classical deterrence theory (Beccaria, 1764/2007) and has regularly been suggested to be the most important contributor in deterrence research (Homel, 1988; Nagin et al., 2015; Piquero et al., 2011). Notably, deterrence theory is based on the idea that an individual is deterred by their perceptions of enforcement and sanctions, as opposed to objective measures. Specifically, it is these perceptions of the certainty of being caught, as opposed to the objective chance of being caught, that are suggested to impact engagement in offending behaviour (Andenaes, 1974; Piquero et al., 2011; Zimring & Hawkins, 1973). Consequently, to increase the deterrent effect for drink and drug driving, it is important that drivers’ perceptions of being apprehended for the offence are maximized. Despite objective measures demonstrating the number of RDTs are much lower than the number of RBTs (in Queensland, more than 70 000 roadside drug tests and more than 2.66 million random breath tests were conducted between 2018 and 2019; Queensland Government, 2019), research has yet to compare how drivers’ perceptions of the certainty of being apprehended differ for drink driving compared to drug driving. This is especially pertinent given that RBTs and RDTs can look similar in appearance (e.g., they both consist of a police van stopping drivers on the side of the road, and in some cases both RBTs and RDTs can be conducted simultaneously).

However, when comparing drivers’ perceptions of certainty of apprehension related to drink driving and drug driving, it is important to also take into account drivers experiences with punishment avoidance. Specifically, committing an offence but avoiding punishment has been found to be one of the most influential factors in the continuation of offending behaviour due to weakening individuals’ perceptions of the certainty of being apprehended for the offence (Stafford & Warr, 1993), and this variable has been found to be a strong predictor for both drink driving (e.g., Freeman & Watson, 2006) and drug driving (Armstrong et al., 2018; Watling et al., 2010). Punishment avoidance is a more objective measure of past experiences (as opposed to perceptions), which could lower drivers perceived certainty of being apprehended for an offence. As such, it could be suggested that punishment avoidance may have a moderating effect on the relationship between certainty of apprehension and engagement in offending behaviour, such that punishment avoidance would decrease the predicted positive relationship between certainty and offending behaviour. Therefore, when examining differences between subjective deterrence measures for drink driving and drug driving, it is important to also consider how drivers’ experiences with punishment avoidance for the behaviours would differ.

An individual’s perceived severity of punishment has been suggested to be the next most important component of deterrence theory (Piquero et al., 2011), suggesting that if a driver perceives the severity of the punishment as high, they are less likely to engage in the offending behaviour. In Queensland, Australia, where this study took place, the punishment for drug driving has a set penalty, regardless of the amount of drugs detected in the system for a first time offence. This penalty for a first offence can involve licence disqualification between 1 and 9 months, a fine of up to AUD$1929 and a maximum imprisonment term of up to 3 months (Queensland Government, 2021a). Meanwhile, a drink driving penalty increases depending on the amount of alcohol that is detected in the system. For a first offence, the minimum penalty is the same as the drug driving penalty, while the maximum penalty for drink driving can include licence disqualification for up to 6 months, a fine of up to AUD$3859 and a maximum imprisonment term of up to 9 months (Queensland Government, 2021b). For comparison, the appendix displays the minimum and maximum penalties for drink and drug driving in the additional Australian states and territories. To date, there has been no literature to compare drivers’ perceived severity of penalty between drink driving and drug driving.

Non-legal deterrents to drink and drug driving

When considering comparing perceptions of legal sanctions between drink driving and drug driving, it would be considered a large oversight to omit non-legal factors. Homel (1988) argued that non-legal deterrents should be considered relevant in determining whether a person will perform an illegal behaviour. Homel (1988) expanded on deterrence theory to create a deterrence-based model that incorporates the non-legal sanctions of 1) the threat of physical loss to oneself (i.e., I might get hurt) and to others (i.e., someone else might get hurt), 2) the threat of internal loss (i.e., I might feel guilty), and 3) the threat of social loss (i.e., my friends/family might judge me). While these non-legal variables have been identified to contribute to less drink driving (e.g., Freeman et al., 2016, 2020) there is a large gap in the literature in relation to the application of these variables to drug driving. Further, it is possible drivers’ perceptions of physical loss, internal loss, and social sanctions differ between drink driving and drug driving. Comparing these perceptions between the two behaviours would allow a deeper understanding of how factors outside of legal deterrence have a differential impact on engagement in drink driving compared to drug driving.

The current study

Despite the similarities in drink and drug driving enforcement, and the important role perceptions play in deterring drivers from these behaviours (Freeman & Watson, 2006; Piquero et al., 2011; Watling et al., 2010), there is a large gap in the literature in relation to how drivers’ perceptions of deterrence differ between these two behaviours. This is especially applicable to the behaviours of drink and drug driving considering the large difference in enforcement rates between the behaviours (Queensland Government, 2019). Further, research has also yet to explore how non-legal factors differ between drink driving and drug driving. Understanding the differences in deterrent perceptions and non-legal perceptions between drink driving and drug driving, as well as identifying how these factors have a differing impact on engagement in each of the offending behaviours, can help elucidate what areas are currently effective, and what areas need improvement for both drink driving and drug driving countermeasures. Therefore, two aims were developed to address this large gap in the literature. The first aim was to understand the differences in deterrence perceptions (including perceived certainty of apprehension, severity of punishment and experiences with punishment avoidance) as well as differences in non-legal factors (including perceived physical loss, social loss, and internal loss), between drink driving and drug driving. The second aim was to identify how these legal and non-legal factors influence future intentions to engage in the illegal behaviours. Considering the focus on drink and drug driving, this study only included participants who have previously reported ever using both alcohol and drugs.

Method

Participants and procedure

The study involved a total of 546 participants, consisting of 390 females (71%) and 156 (29%) males, aged between 18 and 69 years (M = 33.68, SD = 12.93). Participants were recruited online (through Facebook and email), and the University of the Sunshine Coast’s student participation in research program. Course credit was rewarded to student participants, whereas all others were able to enter a prize draw to win one of 20 $50 Visa gift cards. On average, participants held their license for 11.74 years. The current sample was unique in that it consisted exclusively of licensed drivers who had used both illicit drugs and alcohol in the past. Respondents who failed to meet these criteria were excluded from analyses. The University of the Sunshine Coast Human Research Ethics Committee approved the study (approval S201406).

Materials–survey

Demographic data

Demographic data including age, gender, license type, crash history, and post drink and drug behaviour were assessed. An open question to assess how frequently participants reported driving per week was also used. To determine if participants met the criteria of previous history with consuming both alcohol, participants were asked “have you ever consumed alcohol?” and “how often do you have a drink containing alcohol?” which was measured on a scale from 1 (never) to 5 (4 or more times per week). To determine if participants met the criteria for a previous history with drug use, participants were asked “Have you ever taken illegal drugs?”. As roadside drug tests in Queensland only test for cannabis, ice/speed and ecstasy (MDMA), participants were also asked how often they use each type of drug on a scale of 1 (never) to 7 (every day).

Legal and non-legal deterrence perceptions

Homel’s non-legal variables were based on previously established items (e.g., Freeman et al., 2016, 2020; Homel, 1988) and each variable was assessed with two items. These variables included: physical loss to self (e.g. “I think that drink/drug driving would increase my risk of getting injured”), physical loss to others (e.g. “I think that drink/drug driving would pose a serious risk to others”), social loss (e.g. “If I was caught for drink/drug driving, I would be ashamed if my friends found out”), and internal loss (e.g. “I would feel stupid for drink/drug driving).

The deterrence variables were also based on previously established items (e.g., Armstrong et al., 2018; Freeman et al., 2016; Freeman & Watson, 2006; Watling et al., 2010). Certainty of apprehension was assessed with, “If I did drink/take drugs and drive, I would worry that I would get caught”. Severity of punishment was assessed with the average of two items “I won’t drink/take drugs and drive because I don’t want to lose my licence” and “I won’t drink/take drugs and drive because I don’t want to get a fine”. Punishment avoidance was assessed with “I drink/take drugs and drive regularly without being caught”. All items, apart from the certainty of apprehension items, were scored on a 6-point Likert scale, scored from 1 (strongly disagree) to 6 (strongly agree). The certainty items were scored between 0 (not at all likely) and 10 (very likely). Internal reliability was assessed and findings displayed in Table 1.

Table 1.

Cronbach’s alpha reliability for included measures.

Deterrence variables	Number of items	Drink driving	Drug driving
		α	α
Physical loss (self)	Two items	.863	.925
Physical loss (others)	Two items	.823	.951
Severity of punishment	Two items	.795	.909
Social loss	Two items	.872	.902
Internal loss	Two items	.918	.937

Future intentions to drink and drug drive

Two items were included to assess drivers’ perceived likelihood of driving under the influence of alcohol and drugs in the future, including “how likely is it that you will drive a motor vehicle up to four hours after using an illegal drug in the future?” and “how likely is it that you will drive when over the legal limit for alcohol in the future.” These items were measured on a scale ranging from (1) very unlikely to (10) very likely.

Statistical analysis

T-tests were conducted to compare the deterrent variables (including drivers’ perceived certainty of apprehension, severity of punishment and experiences with punishment avoidance) and non-legal variables (fear of physical loss, internal loss, and social sanctions) between drink driving and drug driving. Further, two hierarchal linear regression analyses were conducted to examine the impact of demographic variables, deterrence variables and non-legal variables on 1) drink driving and 2) drug driving. As discussed in the introduction, punishment avoidance may moderate the relationship between the perceived certainty of being apprehended and engagement in offending behaviour, reducing the strength of the direct relationship. Therefore, the interaction of punishment avoidance and perceived certainty of apprehension was included in the regression models. To avoid problems with high multicollinearity due to the inclusion of the interaction term, the variables of certainty of apprehension and punishment avoidance were centred (Aiken et al., 1991). An interaction term between certainty of apprehension and punishment avoidance was created with the centred variables. An interaction plot was only included when the interaction result was significant. In the hierarchal linear regressions, all variables, except for gender, were continuous. Gender was dummy coded so that 0 = females and 1 = males (i.e., females was the referent category). To address issues associated with normality and heteroscedasticity of the regressions, bootstrapping was performed using bias corrected and accelerated 95% confidence intervals with 2000 samples (Field, 2013). All other assumptions were met.

Results

Demographic details of license status¹ and previous crash history are included in Table 2.

Table 2.

Motor vehicle licence status and previous crash history of participants.

Variable	N	%
Licence
Open	378	69.2
Provisional 2	115	21.1
Provisional 1	41	7.5
Learner	6	1.1
Commercial	3	0.5
Motor vehicle crash (at fault)^a
Yes	110	20.1
No	436	79.9
Reason for crash
Other distraction	45	40.9
Fatigue	18	16.4
Mobile phone use	17	15.5
Speeding	12	10.9
Drug driving	6	5.5
Drink driving	2	1.8

In the previous five years.

The current sample consisted of alcohol and drug users. Overall, 537 participants (98%) reported drinking alcohol, with most participants drinking two to four times per month (37%), followed by two to three times per week (25%), monthly or less (25%), and four or more times per week (13%). All participants reported using drugs and alcohol in the past, with only 4.6% (i.e., 25 participants) of the sample having never used cannabis. The frequency of use for different drugs is presented in Table 3. A total of 258 participants (47%) reported driving when they thought they were above blood alcohol limit, 208 participants (38%) reported driving when they knew they were over the blood alcohol limit, and 159 participants (29%) reported driving within four hours of consuming drugs in the past. In total, 97 participants (18%) reported previously driving when they knew they were above the legal alcohol, as well as driving within 4 h of consuming illegal drugs.

Table 3.

Frequency and nature of drug use.

	Cannabis %	Methamphetamine %	MDMA %
Never	4.7	83.7	44.4
Tried once or twice	49.2	12.4	32.5
A few times a year	24.4	2.1	14.1
Monthly	5.3	0.4	4.1
Weekly	4.9	0.6	0.6
Most days	6.2	0.4	0
Every day	5.4	0.6	0.4

Note. N = 533, with 13 missing.

The majority of participants had never been caught for drink (N = 503; 92%) or drug driving (N = 521; 95%). Thirty-three participants (6%) had been caught drink driving once and eight (1.5%) had been caught twice. Only two (.3%) had been caught drink driving more than twice. Six participants (1.1%) reported being caught drug driving, with the majority having been caught once. Since few participants had received a punishment for drink or drug driving, the variable of experiencing punishment for the offence was not used in the subsequent analyses.

Comparison of perceived deterrents to drink and drug driving

Pairwise comparisons were conducted to compare the relative perceived deterrents that prevented participants from engaging in drink and drug driving (see Table 4). Certainty of apprehension (t [496] = 2.51, p = .012), perceived internal loss, (t [496] = 2.24, p = .026), and perceived physical loss to others (t [496] = 3.43, p = .001), were significantly higher for drink driving compared to drug driving, while punishment avoidance (t [496] = −3.30, p = .001) and future intentions to engage in the behaviour (t [527] = -.202, p = .044) were higher for drug driving compared to drink driving. In other words, participants perceived their likelihood of being caught, experiencing internal loss, and causing harm to others to be greater when drink driving compared to drug driving. Participants reported more regular experiences of punishment avoidance (i.e., getting away with the illegal behaviour) when drug driving. Participants also reported to be significantly more likely to drug drive, rather than drink drive, in the future.

Table 4.

Paired samples t-test results comparing perceptions and future intentions regarding drink driving and drug driving.

	M (SD) Drug driving	M (SD) Drink driving	t	df	p
Certainty	8.38 (2.76)	8.66 (2.29)	2.51	496	.012
Severity	5.13 (1.28)	5.20 (1.12)	1.44	496	.150
Internal loss	5.23 (1.35)	5.34 (1.18)	2.24	496	.026
Social loss	4.94 (1.48)	4.97 (1.35)	0.51	496	.610
Physical loss self	5.28 (1.25)	5.35 (1.10)	1.58	496	.115
Physical loss others	5.28 (1.27)	5.45 (1.04)	3.43	496	.001
Punishment avoidance	1.60 (1.40)	1.39 (1.04)	−3.30	496	.001
Future intention to drink / drug drive	1.37 (2.75)	1.14 (2.04)	−2.02	527	.044

Regression model predicting future intentions to drink drive

The hierarchal linear regression model for drink driving (presented in Table 5) was significant in the first step, F (3, 321) = 4.14, p < .01, adjusted R² = .028. Gender was the only variable to predict a change in future intention to drink drive, with males being more likely to engage in the behaviour.

Table 5.

Regression model predicting future intentions to drive under the influence of alcohol using demographic variables, perceived non-legal sanctions, and legal sanctions.

	β	sr²	p	95% CI
	β	sr²	p	Lower	Upper
Step 1: Adjusted R² = .028
Gender	.180	.031	.006	.268	1.249
Age	−.089	.008	.061	−.027	.000
Driving frequency	.000	.000	.999	−.012	.037
Step 2: Adjusted R² = .429
Gender	.073	.005	.119	−.077	.675
Age	−.042	.002	.27	−.017	.004
Driving frequency	−.006	.000	.852	−.009	.019
Centred Certainty of Apprehension	.040	.001	.334	−.038	.105
Centred Punishment Avoidance	.615	.272	< .001	.784	1.398
Interaction term Certainty_PA	−.047	.002	.591	−.092	.158
Severity of punishment	−.066	.004	.205	−.262	.062
Step 3: Adjusted R² = .476
Gender	.045	.002	.305	−.188	.513
Age	−.052	.003	.160	−.018	.513
Driving frequency	−.021	.000	.522	−.012	.015
Certainty of apprehension	.049	.002	.226	−.028	.111
Punishment Avoidance	.527	.181	< .001	.601	1.265
Interaction term Certainty_PA	−.017	.000	.845	−.076	.164
Severity of punishment	.023	.000	.642	−.106	.201
Physical loss (other)	−.016	.000	.804	−.277	.188
Physical loss (self)	−.191	.010	.049	−.659	−.030
Internal loss	−.081	.002	.397	−.431	.178
Social loss	−.018	.000	.759	−.195	.146

Note. Bootstrapping was performed using bias corrected and accelerated 95% confidence intervals with 2000 samples, due to non-normally distributed and heteroscedastic data.

The regression model was also significant in the second step, with the inclusion of the legal variables (perceived certainty of apprehension, experiences of punishment avoidance, the interaction term between certainty of apprehension and punishment avoidance, and perceived severity of punishment), F (7317) = 35.75, p < .001, adjusted R² = .429, R² change = .404. The experience of punishment avoidance was found to predict a significantly and meaningfully greater intention to drink drive in the future. Certainty of apprehension, the interaction between certainty of apprehension and punishment avoidance, and severity of punishment did not have a significant impact on future intention to drink drive, over and above demographic factors.

The regression model was significant in the final step with the inclusion of Homel’s non-legal variables of fear of physical loss of self and others, internal loss and social sanctions, F (11, 313) = 27.75, p < .001, adjusted R² = .476, R²change = .053. The threat of experiencing physical loss to oneself was the only non-legal deterrent that was found to predict a change in future intentions to drink drive. Drivers who perceived a higher threat of physical loss to themselves were less likely to report the intention to drink drive in the future. There was no significant relationship between future intentions to drink drive and perceived fear of physical loss of others, internal loss and social sanctions.

Regression model predicting future intentions to drug drive

For the hierarchal linear regression model predicting future intentions to drug drive (presented in Table 6), the first step with the inclusion of gender, age, and driving frequency was significant, F (3294) = 6.79, p < .001, adjusted R² = .055. Gender was found to significantly predict future intentions to drug drive in the first step of the regression model, with males being more likely to drug drive than females. Age and driving frequency did not significantly influence future intentions to drug drive.

Table 6.

Regression model predicting future intentions to drive under the influence of drugs using demographic variables, perceived non-legal sanctions, and legal sanctions.

	B	sr²	p	95% CI
	B	sr²	p	Lower	Upper
Step 1: Adjusted R² = .055
Gender	.191	.034	.008	.268	1.249
Age	−.006	.000	.926	−.027	.000
Driving frequency	.135	.017	.376	−.012	.037
Step 2: Adjusted R² = .494
Gender	.070	.004	.150	−.077	.675
Age	−.005	.000	.936	−.017	.044
Driving frequency	.025	.001	.627	−.009	.019
Certainty of Apprehension	−.125	.01	.025	−.038	.105
Punishment Avoidance	.425	.132	< .001	.784	1.398
Interaction term Certainty_PA	−.189	.025	.003	−.092	.158
Severity of punishment	−.168	.019	.019	−.262	.062
Step 3: Adjusted R² = .594
Gender	.004	.000	.900	−.188	.513
Age	−.035	.001	.409	−.018	.002
Driving frequency	.010	.000	.828	−.012	.015
Centred Certainty of apprehension	−.089	.005	.077	−.028	.111
Centred Punishment Avoidance	.311	.065	<.001	.601	1.265
Interaction term Certainty_PA	−.109	.008	.048	−.076	.164
Severity of punishment	.002	.000	.971	−.106	.201
Physical loss (other)	−.096	.003	.233	−.277	.188
Physical loss (self)	−.275	.017	.056	−.659	−.030
Internal loss	−.020	.000	.871	−.431	.178
Social loss	−.119	.005	.063	−.195	.146

Note. Bootstrapping was performed using bias corrected and accelerated 95% confidence intervals with 2000 samples, due to non-normally distributed and heteroscedastic data.

The regression model was significant in the second step with the inclusion of the deterrence variables, F (7, 290) = 42.34, p < .001, adjusted R² = .494, R²change = .441. Certainty of apprehension, punishment avoidance, the interaction between punishment avoidance and certainty of apprehension, and the perceived severity of punishment all predicted changes in future intentions to drug drive. Specifically, drivers who perceived themselves as more likely to get caught (i.e., a high perceived certainty of apprehension) and expected the punishment to be severe reported being less likely to drug drive in the future. Meanwhile, drivers who had successfully avoided punishment in the past had considerably greater intentions to drug drive in the future. The interaction plot that demonstrates how experiencing punishment avoidance moderates the relationship between the perceived certainty of apprehension and engagement in drug driving is included in Figure 1. Examination of the plot demonstrates that, at high experiences of punishment avoidance, drivers with a higher perceived certainty of being apprehended were less likely to drug drive, while those with lower perceived certainty of apprehension were more likely to drug drive. Meanwhile, at low punishment avoidance, future intention to engage in drug driving was similar for drivers with both a low and high perceived certainty of being apprehended.

Figure 1.

Plot of the interaction effect of punishment avoidance on the relationship between the perceived certainty of being apprehended and future intention to engage in drug driving.

The regression model was significant in the third step with the inclusion of the non-legal variables, F (11, 286) = 40.58, p < .001, adjusted R² = .594, R²change = .104. Consistent with the drink driving model, there was no significant relationship between future intentions to drug drive and perceived fear of physical loss to others, internal loss and social sanctions. In contrast to the drink driving model, physical loss to oneself was not a significant predictor of future intention to drug drive.

Discussion

The current study aimed to understand the differences in deterrence, as well as differences in non-legal sanctions, between drink driving and drug driving. The second aim was to identify how these factors influence future intentions to engage in the illegal behaviours. This study examined a unique and informative population of drivers who reported having used drugs and alcohol in the past. Almost half admitted to having previously driven when they thought themselves to be over the legal alcohol limit, while approximately a third had driven within four hours of taking an illegal drug. These results demonstrate the current sample consisted of a large portion of drivers who had previously driven under the influence of alcohol, drugs, or both. Notably, participants reported a significantly higher intention to drug drive in the future compared to drink drive. This study found a number of important differences in deterrence and non-legal sanctions between drink and drug driving, which have important implications for future research, as well as for countermeasures, and the allocation of resources to preventing these two behaviours.

Legal deterrents

There were significant differences in the perceived legal deterrents to drink and drug driving in the current sample. Specially, drivers perceived their likelihood of being caught to be more likely when drink driving than drug driving. This sentiment likely reflects a historical trend in which drug testing has been considerably less frequent than drink driving in Queensland (Queensland Government, 2019). While still a reality, recent increases in Queensland drug testing have begun to challenge this assumption (Mills et al., 2021). However, it should also be acknowledged that there were more drink drivers than drug drivers in the sample (despite the population consisting of drivers who have reported consuming both alcohol and illicit drugs), which may also be impacting the results. Further, there has been less media campaigns related to the risks of drug driving in comparison to drink driving, which may also help explain these results. It is also noteworthy that there was no significant difference in drivers’ perceived severity of punishment between drink driving and drug driving. The legal penalty can differ quite dramatically between these two behaviours, with a set penalty for drug driving (Queensland Government, 2021a) and an incremental penalty for drink driving, with the minimum penalty being the same as the drug driving penalty (Queensland Government, 2021a). It may be suggested that drivers are unaware of the different penalties between these two behaviours, which is why there was no significant difference in perceived severity of punishment.

Importantly, drivers reported successfully avoiding punishment for drug driving more regularly than drink driving. That is, participants were driving under the influence of drugs and yet were evading capture. Previous research has found punishment avoidance to be a strong predictor of drink driving (Szogi et al., 2017) and drug driving (Watling et al., 2010) likely due to the fact that it reinforces the belief that a driver can get away with the illegal behaviour. This result can also help explain why drivers have a higher perceived certainty of being caught for drink driving compared to drug driving; those who do drug drive experience punishment avoidance more often, which lowers their perceived certainty of being apprehended for the offence.

When considering the differences in perceived legal deterrents between drink driving and drug driving, it is also important to acknowledge that the literature is much clearer on the risks associated with drink driving compared to drug driving. For example, it is well established that BAC levels over .04 are related to a higher crash risk (Borkenstein et al., 1964, 1974). Meanwhile, a clear link between the concentration of drugs in a driver’s system and crash risk has yet to be established (e.g., Lacey, 2016). However, it has been suggested that driving performance is affected up to 4 h and 30 min after smoking cannabis (Marcotte et al., 2022), with a recent study identifying 58% of a sample of 803 Queensland drug users reported driving within 4 h of consuming either cannabis, MDMA, or methamphetamines (Mills et al., 2022). Further, recent modelling has suggested that a 50% increase in roadside drug testing has resulted in an estimated saving of 55 serious injuries and 3 fatalities (Cameron et al., 2021). These results provide some support for the dangers associated with drug driving, yet it is still unclear if the current legislation for drug driving (i.e., driving with any trace of an illegal substance in the blood) is optimal for reducing crashes. Therefore, while this study looks at how the current legal factors influence engagement in drink driving and drug driving, future research is needed to determine 1) to what extent driving under the influence of drugs impacts driving ability and 2) if the legislation surrounding drug driving needs to be updated to take such findings into account.

Non-legal deterrents

The perceived threat of physical loss to others and internal loss were also considered significantly higher in the case of drink driving rather than drug driving. That is, drivers believe themselves to be more likely to cause a crash, injuring or killing another person, if they were under the influence of alcohol, instead of drugs. Equally, drivers perceive the internal deterrent, such as feelings of personal shame, to be stronger if they were to drink drive, rather than drug drive. These findings are consistent with Freeman et al. (2016), who found significant associations between physical loss, internal loss, and self-reported drink driving behaviour. Further, previous research has found that driving while intoxicated with alcohol was viewed as higher risk than driving with cannabis in their system (Arkell et al., 2020; Lenné et al., 2001; Swift et al., 2010; Wickens et al., 2019). These findings help to further explain the results from this study, especially considering the majority of the sample had reported using cannabis.

Taken together, drivers were found to perceive the threat of legal and non-legal deterrents to be greater for drink driving than drug driving. Moreover, avoiding punishment for drug driving was more common than for drink driving. Given this combination of influences, it is logical that participants reported greater future intentions to drug drive than to drink drive.

Predicting drink driving

The overall regression model was found to contain considerable predictive ability, explaining half of the variance in future intentions to drink drive. In the model, more frequent punishment avoidance was a significant predictor of a high intention to drink drive while those who feared the threat of physical loss to themselves were significantly less likely to report an intention to drink drive in the future. Punishment avoidance was considered a strong predictor of future drink driving, consistent with the results of Szogi et al. (2017). Previous studies have also identified the threat of physical loss to be a significant predictor of drink driving behaviour (Freeman et al., 2016). The current study adds a level of nuance by revealing that the threat of physical loss to oneself, but not others, is predictive of drink driving. On a practical level, it would appear that drivers who are concerned that drink driving will compromise their own safety are less likely to perform the illegal behaviour. However, whether or not a driver was concerned about the physical loss of others, personal disappointment (internal loss), or social disapproval did not appear to influence the tendency to drink drive. This is despite the perceived fear of physical loss to others and internal loss being rated as significantly higher for drink driving compared to drug driving. Therefore, it may be suggested that while these non-legal factors are more salient for drink driving, they still need to be further increased in order to have an effective influence on reducing drink driving behaviour.

Predicting drug driving

The regression model predicting drug driving was found to have considerable predictive ability, surpassing that of drink driving. Punishment avoidance was a significant predictor of future intention to drug drive, mirroring the model for drink driving. Specifically, those who had experienced punishment avoidance were more likely to drug drive in the future while those who feared the threat of physical loss to themselves were less likely to drug drive in the future. Punishment avoidance has previously been identified as a predictor of drug driving (Watling et al., 2010). Moreover, the predominance of punishment avoidance in predicting drink and drug driving is consistent with its well-established ability to predict future illegal behaviour in general (Freeman & Watson, 2006; Paternoster & Piquero, 1995; Piquero & Paternoster, 1998; Piquero & Pogarsky, 2002; Sitren & Applegate, 2007). Given this recurring finding, it is likely that drink and drug driving will continue to occur so long as drivers are able to perform these illegal behaviours and get away with them. As such, increasing the reach and intensity of drug and alcohol roadside testing can be considered a priority.

Unlike the drink driving model, it was found that both the perceived certainty of apprehension and the severity of punishment were significant deterrents for drug driving. This is in contrast to previous drug driving research that was also conducted in Queensland (Watling et al., 2010), and despite the perceived certainty of apprehension being significantly lower for drug driving compared to drink driving. Therefore, it may be suggested that recent police efforts to increase drug driving enforcement (Mills et al., 2021) has acted as an effective deterrent for the behaviour. However, it should also be acknowledged that Queensland RBTs (introduced in 1982) have been in place for a much longer time period than RDTs (introduced in 2007). Therefore, it may also be suggested that RDTs are currently a deterrent for drink driving due to the recency of their implementation, while this research may not be capturing a substantial impact of RBTs on drink driving behaviour due to limited changes in this enforcement method over the last 40 years. Nevertheless, more research is needed to elucidate the reasons why the perceived certainty of apprehension was a deterrent for drug driving, but not drink driving, despite being perceived as higher for drink driving.

To the best of the authors’ knowledge, this is the first study to demonstrate a moderating relationship with punishment avoidance on the negative relationship between the perceived certainty of being apprehended and future intentions to drug drive. Based on Stafford and Warr’s (1993) reconceptualized deterrence theory, it may be suggested that those who have experienced punishment avoidance more often are also engaging in the behaviour more often. Therefore, the results of the interaction effect serve to further highlight the importance of a high perceived certainty of apprehension for higher risk drivers that are likely to engage in drug driving more often. This may be achieved by increasing exposure to enforcement practices for drug driving; however, more research is needed to explore this further.

Meanwhile, the significant severity of punishment result is a promising finding considering the penalty for drug driving can be higher than the punishment for drink driving (yet the severity of punishment was not a deterrent for drink driving). As discussed above, this may be due to drivers not knowing the differences in penalty for the behaviours. It may also be suggested that drivers associate the drug driving penalty with the penalty for other drug-related offences. Notably (and consistent with the drink driving results), fear of physical loss of others, internal loss and social sanctions did not significantly predict a lower intention to drug drive, suggesting these areas need to be improved to have a more substantial impact on drug driving behaviour. However, while fear of physical loss to oneself was a significant predictor of less frequent drink driving, this variable was not a significant predictor for drug driving, suggesting increased focus need to be given to highlight the risks of drug driving. This is not surprising, given Australia has frequent road safety campaigns that highlight the risks of drink driving, but very few campaigns that target the risks of drug driving.

Practical applications

Overall, it can be suggested that the findings from this study reveal two potential routes for reducing the incidence of drink and drug driving. First, considering the deterrent impact of legal sanctions on drug driving despite the substantially lower number of RDTs compared to RBTS, it may be suggested that interventions that heighten drivers’ perceived likelihood of being caught may be beneficial. This may include increased media coverage, high visibility drug testing operations with signage, and generally increased police presence in the community. Second, considering how drivers perceived physical loss of others, internal loss, and social sanctions were not significant predictors for both drink driving and drug driving, it may be suggested that non-legal countermeasures need to focus on increasing drivers’ fear of these factors. For example, many campaigns in the domain of road safety have encouraged passengers to speak up about the driving behaviour of their friends or family (see Weston & Hellier, 2018), therefore involving drivers’ peers may also be beneficial in such non-legal countermeasures. Given the current findings, drug and drink driving may benefit from a similar approach. This is also an important are for future research to explore.

Limitations and future research

There are a number of limitations that should be considered when interpreting the findings of the current study. Firstly, a convenience sample was utilized, limiting the generalizability of the findings. The researchers attempted to control for this concern through stringent eligibility criteria, such that those who had not previously used drugs and alcohol were excluded. However, it should be acknowledged that participants primarily resided in metropolitan and regional areas of Queensland, Australia, and the sample had a larger proportion of females than males. Further, the self-report nature of the design, and the fact that most variables relied on one or two questions, may have resulted in social desirability bias or other response biases. Future researchers are encouraged to further explore the nuanced perceptions that explain why a person chooses to drink and drug drive, respectively. In particular, further research that compares these two illegal behaviours would be of considerable value.

In addition, this research focussed on deterrence theory-based constructs; however, future research would benefit from also comparing the impact of exposure to RBTs and RDTs on engagement in the offending behaviours. Previous research has identified that being exposed to RDTs two or more times was associated with higher perceptions of the perceived certainty of being apprehended for drug driving (Mills et al., 2022). Meanwhile, research has shown that exposure to RBTs was not associated with perceptions of apprehension certainty for drink driving (Freeman et al., 2021). As explained above, this may be due to RBTs being well integrated into society, originally being implemented in 1982, while RDTs are a more recent implementation. Therefore, exposure to RDTs may see a larger effect on deterrent perceptions. Comparing experiences with, and exposure to RBTs and RDTs specifically will allow further understanding of how experiences and perceptions may differ between drink driving and drug driving.

Concluding remarks

This study identified differences in legal and non-legal factors between drink driving and drug driving. While there were many similarities between the two (most likely due to the similar enforcement method that is used for both behaviours), the most prominent differences that emerged involved the significant deterrent effect of the perceived certainty of apprehension and severity of punishment for drug driving that was not evident for drink driving. These findings highlight the importance of perceptions in deterring drivers from drug driving and suggest that current legal countermeasures can be effective for drug driving. However, the findings may be partially attributed to RDTs being implemented more recently than RBTs. It should also be acknowledged that avoiding punishment predicted more frequent engagement in drink driving and drug driving, highlighting that increasing enforcement remains an important area to prevent further drink and drug driving offences. Further, the results highlight that more non-legal countermeasures are required to increase drivers’ perceptions of internal loss, physical loss of others and social sanctions for both drink driving and drug driving.

Supplemental Material

sj-docx-1-anj-10.1177_26338076221114481 - Supplemental material for Examining the differences in perceived legal and non-legal factors between drink driving and drug driving

Supplemental material, sj-docx-1-anj-10.1177_26338076221114481 for Examining the differences in perceived legal and non-legal factors between drink driving and drug driving by Verity Truelove, Benjamin Davey and Natalie Watson-Brown in Journal of Criminology

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Motor Accident Insurance Commission (grant number Road Safety Research Collaboration funding).

ORCID iD

Verity Truelove

Supplemental material

Supplemental material for this article is available online.

Notes

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