STRENGTHS AND LIMITATIONS OF THIS STUDY
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The use of the entire dataset population augmented the strength of the analysis.
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The use of logistic regression analysis allows for several sociodemographic factors to be simultaneously assessed to elicit appropriate risk and protective factors.
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The validated Cannabis Abuse Screening Test enhanced the reliability of the findings, given its frequent use in population sample studies.
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Driving under the influence information was self-reported, which can be affected by recall bias.
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This study could not establish causal relationships due to the nature of the cross-sectional data.
Introduction
The World Health Organization (WHO) highlights drug driving as a significant risk factor for road traffic accidents,1 and further acknowledges that vehicular crashes are not only among the top 10 causes of demise across all age groups but also the leading cause of death among young individuals under 30.2 Accordingly, driving under the influence (DUI) of drugs represents a massive public health concern for the global community.3–7 While DUI has historically referred to alcohol, cannabis is evidently the second leading drug detected among drivers involved in road traffic injuries and fatalities worldwide.8 9 This remains foreseeable, as it continues to be widely used globally, as stated by the latest World Drug Report.10
Legislative changes cultivate a growing concern that less restrictive laws might increase the prevalence of cannabis use in the general population and, thereby, its use among vehicle drivers. Several studies have confirmed this trend and denoted that cannabis prevalence among the populace is rising, as is the frequency of driving under its influence.11–14 Mounting data suggest that vehicular accidents due to impaired driving will increase15–17 as more countries decriminalise recreational and medicinal cannabis use. Moreover, the risk of cannabis dependence will likely escalate as a competitive market allows for easier access to more affordable and potent cannabis products.18
The impact of legalisation and decriminalisation has also likely contributed to changing risk perceptions regarding cannabis use19 and the influence it exudes on driving behaviours.20 The misconception that drug driving is not perceived to be risky behaviour21 and the contrasting belief that cannabis is the safest drug to use and drive22 as it improves driving capability,23 24 presents a significant challenge in discouraging DUI of cannabis (DUIC).
Despite the accumulated evidence over the preceding four decades, that suggests cannabis use impairs driver reaction time, visual acuity and spatial awareness, and encourages risky decision-making,25–28 cannabis users perceive DUIC as being less dangerous than DUI of alcohol (DUIA).29 30 Notwithstanding, extant literature highlights cannabis use is associated with higher risks of vehicular crash and fatality,31–33 which is exponentially elevated when used with alcohol.34–37 Contemporary research, however, is less conclusive as it pertains to the dose–response effects of delta-9-tetrahydrocannabinol (THC) on driving skills, with a number of studies showing a positive association between elevated levels of THC and impairment38 39 while others found no clear relationship.40
In Jamaica, a number of smaller-sized studies have reported an association between victims of vehicular crashes and evidence of cannabis use.41 42 Findings from these studies revealed victims were male drivers and young adults predominantly under the age of 30.41 42 However, the accrued data from these studies would have been prior to the legislative changes in 2015 that decriminalised and permitted the possession of two ounces of cannabis for personal use, and the establishment of a legal medicinal cannabis industry.43 44 It is suggested that the strong inclination for cannabis use among Jamaicans is enhanced due to recent amendments to the island’s Dangerous Drugs Act that endorsed decriminalisation,45 among other factors, including strong sociocultural practices and religious beliefs.46 47
That being the case, the rapidly evolving legal landscape surrounding cannabis and the resulting shifts in social norms regarding its use, necessitates a closer examination of the various factors associated with DUIC. To date, no studies in the Caribbean have used nationally representative data to determine cannabis use patterns, the sociodemographic characteristics, and the risk perception of using cannabis and its association with developing dependence in vehicle drivers that may DUIC.
Objectives
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To determine the prevalence of cannabis use patterns among vehicle drivers, including those who DUIC and those who are heavy cannabis users that DUIC.
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To examine the association between developing cannabis dependence and the risk perception of smoking cannabis among drivers.
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To investigate the sociodemographic factors associated with DUIC.
Methods
Study design, sample size and data source
This study is a secondary data analysis of the National Household Survey, Jamaica 2016. The target population comprised all respondents who identified as drivers of motorised vehicles. The sample analysed in this study was a subset of 1060 participants. This research extracted variables relevant to cannabis use patterns, dependence, risk perception and the associated sociodemographic characteristics of DUIC in vehicle drivers. This study contained no identifying data on respondents, and researchers made no direct or indirect contact with any respondents.
The original study was a cross-sectional survey of a national population sample investigating the prevalence and patterns of drug use among Jamaicans between the ages of 12 and 65.48 Data were collected between April and July 2016, targeting 357 households per parish, totalling a nationally representative sample of 4623 dwellings. The data were collected from a standardised questionnaire developed by the Inter-American Drug Abuse Control Commission and the Inter-American Observatory on Drugs, and conducted through a partnership with Jamaica’s National Council on Drug Abuse.
The survey employed a stratified multistage sampling design in which the primary sampling units were the Enumeration Areas (EAs). Jamaica comprises 14 parishes and 22 EAs per parish. In each EA, systematic random sampling was used to draw 16 households, from which one individual was randomly selected as the survey respondent. Sampling weights were calculated to account for selection probability, non-response, and population distribution and applied to ensure that the weighted sample distribution matched the population distribution of age and sex categories.48
Study variables
Cannabis use prevalence
Using the target variables, the prevalence of cannabis use was calculated for the periods of lifetime (ever use), past year (chronic) and past month (current) use. Responses were coded as 1=yes and 2=no. For heavy cannabis use, respondents were asked to state how many days they had smoked marijuana over the past 30 days. Responses indicating 20 days or more demonstrate heavy use as defined by the European Monitoring Centre for Drugs and Drug Addiction.49
Driving under the influence of cannabis
The National Household Survey questionnaire asked respondents, ‘Have you driven a vehicle in the past 12 months?’ and ‘During the past 12 months, have you driven a vehicle while you were under the influence of illegal drugs?’ The response options were 1=yes, 2=no. Using a method previously described in the literature,50 DUIC only was defined as an affirmative response to the survey question, ‘During the past 12 months, have you driven a vehicle while you were under the influence of illegal drugs?’ (limited to respondents who reported past-year cannabis use and no other illicit drug use). Individuals who reported using cannabis in the past year but did not report any other illegal drug use during that same time period, and also reported DUI of drugs in the past year, were considered to have driven under the influence of cannabis only in the past year. Statistical computations also extracted respondents who were past month (current) cannabis users that answered ‘yes’ to the question ‘During the past 12 months, have you driven a vehicle while you were under the influence of illegal drugs?’ to determine those vehicle drivers who were current users that DUIC only. The term illegal drugs included cannabis, crack, cocaine, heroin and 3,4-methylenedioxymethamphetamine (MDMA).
Cannabis dependence
Cannabis dependence was assessed using the Cannabis Abuse Screening Test (CAST). It is often used for the identification of cannabis use disorder.51 It encompasses a six-item scale in which a score of less than 3 indicates users with a low risk of dependence, a score of 3–6 represents users with a moderate risk of dependence, and a score of 7 or more determines users with a high risk of dependence.52 For this study, the CAST scores were recategorised into two groups where a score greater than or equal to 7 was defined as a high risk of dependence and a score of less than or equal to 6 was defined as not a high risk of cannabis dependence.
Risk perception
Perception of risk associated with frequent or infrequent use of marijuana was investigated in the initial survey by asking participants, ‘In your opinion, please indicate the risk level of smoking marijuana sometimes and smoking marijuana often’. Participants indicated their risk level along a Likert scale continuum: (1) no risk, (2) low risk, (3) moderate risk, (4) high risk and (5) I don’t know the risk. For the secondary analysis, response options were recategorised to reflect 0=no to low-risk and 1=moderate to high-risk to examine respondents who had indicated some level of perceived risk. The option ‘I don’t know the risk’ was excluded as an underrepresented category with insufficient frequencies that may introduce variability and bias in interpreting the results.53
Sociodemographic characteristics
Sociodemographic characteristics that might influence cannabis use in drivers were included as covariates. Respondents were asked to state their sex (1=male, 0=female) and geographical location (recategorised into 1=urban and 0=rural). Respondents’ age was categorised into two groups—1=34 years and under, representing young adults as suggested by Franssen et al54 and 0=over 35 years. Respondents were asked ‘Are you the head of household’. The response options were 1=yes, 0=no. Educational status was assessed by asking respondents, ‘What is the highest educational level that you have achieved?’ Ten response options were recategorised into 1=tertiary level, 0=below tertiary level. The item corresponding to marital status had seven response options recategorised into two choices: 1=married, 0=unmarried. The respondents were asked to disclose the household’s total monthly income from a list of 15 possibilities. These were recategorised into 1=JA$50 000 and under or 0=over JA$50 000. The options ‘don’t know’ or ‘no response’ was considered missing variables. The item on religious affiliation had 26 response options that were recategorised as 1=Christian, 0=non-Christian. For occupation, respondents were asked to describe their job from a list of eleven options. These were recategorised into 1=machine operators or 0=non-machine operators.
Statistical analysis
Descriptive statistical analysis was performed to determine the prevalence of cannabis use among vehicle drivers and to describe the associated sociodemographic characteristics. These were represented in frequencies, means and percentages. Bivariate analysis examining the association between the risk perception of smoking cannabis sometimes or often and the risk of dependence among vehicle drivers was done using Pearson’s χ2 test. Logistic regression analyses were done to identify sociodemographic protective and risk factors for DUIC. Covariates included in the model were age (over 35 years as the reference category), occupation (non-machine operators as the reference category), marital status (unmarried as the reference category), sex (female as the reference category), education (below tertiary level as the reference category), religion (non-Christian as the reference category), household income (over JA$50 000 as the reference category), head of household (‘no’ responses as the reference category) and geographical location (rural as the reference category). Statistical analyses were conducted using R software, V.4.2.0. Multicollinearity between the study variables was explored using variance inflation factor (VIF) (with multicollinearity being defined as VIF>2.5).The Hosmer-Lemeshow statistic tested for goodness of fit of the regression model. The data were presented in the form of tables and text. ORs and 95% CIs were recorded. A p<0.05 was considered statistically significant.48
Results
Prevalence
Table 1 demonstrates the prevalence of cannabis use in the total population (n=4623) and among the vehicle driver population (n=1060). Approximately one in four individuals was a vehicle driver (23%). Among those in the population who reported lifetime use of cannabis, 60.1% reported use in the past year and 53.9% reported use in the past month. Of the 1060 vehicle drivers, 125 (11.8%) admitted DUI of illegal drugs (DUI-ID) in the past year. Of those who admitted to DUI-ID, 110 drivers were cannabis users only (92%), indicating that 10.4% of drivers admitted to DUIC in the past year.
Of the 1060 vehicle drivers, 245 vehicle drivers admitted to being current cannabis users, of which 111 drivers admitted to DUI-ID. Of the 111 drivers who admitted to DUI-ID, five persons used drugs other than cannabis (one person each used heroin, crack and cocaine and two persons used MDMA). Excluding these 5 individuals, 106 drivers who admitted DUI-ID used cannabis only. This is approximately 43.3% and indicates that two in five Jamaicans, who are drivers and are current cannabis users, operate a vehicle under the influence of cannabis only.
Of the 106 drivers who admitted to DUIC only, 92 were heavy cannabis users (use 20 days or more in a month). This is 86.8% and indicates that 9 out of 10 Jamaican drivers, who were current cannabis users and admitted to DUI, were heavy users.
Sociodemographic factor findings
Table 2 shows the sociodemographic characteristics of population vehicle drivers. The mean age of respondents was 36.56 years (SD±12.582). Most drivers were male (70.6%), employed (72.6%), unmarried (61.0%), of Christian beliefs (72.8%), living in rural areas (54.5%) and with a less than tertiary-level education achievement (83.3%).
Table 2 also displays demographics for drivers who admit to being a current cannabis user who DUIC only. Most were male (93.4%), the head of household (77.4%) and operated machinery (55.1%) as part of their job description. Most drivers had achieved less than tertiary-level education achievement (93.4%). Household income is the sole variable where data were not recorded in 137 cases of drivers in the population, and 16 cases of drivers who are current cannabis users who DUIC only.
Risk perception and cannabis dependence findings
Table 3 summarises the risk perception of smoking cannabis sometimes or often and level of use according to the CAST questionnaire among vehicle drivers. Approximately 54% and 29% of drivers reported no to low-risk perception to smoking cannabis sometimes and often, respectively.
Forty-four per cent of drivers who reported no to low-risk perception to smoking cannabis sometimes had a high risk of cannabis dependence (CAST≥7), whereas 28% of drivers who reported moderate to high-risk perception to smoking cannabis sometimes had a high risk of cannabis dependence (CAST≥7). This indicates that drivers with a no to low-risk perception to smoking cannabis sometimes were more likely to be dependent on cannabis and this difference was statistically significant (p<0.001).
Fifty-two per cent of drivers who reported no to low-risk perception to smoking cannabis often had a high risk of cannabis dependence (CAST≥7), whereas 30% of drivers who reported moderate to high-risk perception to smoking cannabis often had a high risk of cannabis dependence (CAST≥7). This indicates that drivers with a no to low-risk perception to smoking cannabis often were more likely to be dependent on cannabis and this difference was statistically significant (p<0.001).
Estimation of ORs for sociodemographic factors associated with DUIC
Table 4 shows the results of a logistic regression analysis performed to assess the associations between DUIC in the past year and select sociodemographic factors. There was no multicollinearity found among the independent variables used in the analysis. The Hosmer-Lemeshow test shows the p value at 0.497 (p>0.05), which indicates the model fits the data. The model illustrates statistically significant relationships for several factors.
Drivers 34 years and under were 2.97 times (95% CI 1.71 to 5.29, p<0.001) more likely than those 35 years and older to report DUIC in the past year. Drivers who were the head of household and operated machinery as part of their job were 2.22 times (95% CI 1.10 to 4.75, p=0.031) and 1.87 times (95% CI 1.09 to 3.24, p=0.023) more likely to report DUIC in the past year than those who were not the head of household or in non-machinery operated positions. Similarly, male drivers were 4.14 times (95% CI 1.59 to 14.20, p=0.009) more likely than females drivers to report DUIC in the past year.
The model also indicated that there were statistically significant inverse relationships for two of the factors. Married drivers were 58% less likely than unmarried drivers to report DUIC in the past year. Alternately, the result can also be interpreted that the odds of DUIC are 2.38 times higher among unmarried drivers. Similarly, drivers who matriculated up to a tertiary-level education were 74% less likely to report DUIC in the past year than drivers with less than a tertiary-level education. Alternately, the result can also be interpreted that the odds of DUIC are 3.85 times higher among drivers with less than a tertiary education. Drivers who were Christian-affiliated and living in a household that earned JA$50 000 or lower per month reduced the risk of DUIC in the past year. These inverse associations were, however, not statistically significant.
Discussion
This study is the first of its kind in the Caribbean region and sheds light on the impact of DUIC on a national population. The findings reveal that a significant number of Jamaican drivers who use cannabis, operate a vehicle under its influence, with more than 10% conceding to this unsafe and risky practice. It is worth noting the occurrence is eight times greater than the reported mean prevalence of 1.32% (range 0.0%–5.99%) in general driving populations across 13 participant countries of The European Union’s Driving under the Influence of Drugs, Alcohol and Medicines project.8 The high proclivity towards its use among Jamaicans, no doubt as a result of social and cultural influence,46 47 represents a worrying proposition given that extensive research demonstrates that cannabis use while driving, or under its influence, may impair driving ability.55
The second key finding is that among past-month cannabis users, more than 2 in 5 (43.3%) drivers report driving a vehicle while under the influence of cannabis (DUIC). This represents a marked difference compared with similar respondents in a previous study who admitted to DUI of alcohol (18%).56 Indeed, in terms of exposure, DUIC was far more commonplace among the Jamaican driving population than DUI of alcohol. A plausible rationale is that the effects of DUIC have not received the same level of public awareness as DUI of alcohol. Moreover, current legislation provides minimal legal deterrence to DUIC, lacking an effective roadside drug driving testing strategy and comprising a fine of approximately US$65 that is unlikely to dissuade offender motorists.57
The third critical finding is that the more frequent cannabis users are more likely to report DUIC. This study denoted that approximately 9 out of 10 Jamaicans who were past-month cannabis users and reported DUIC admitted to being heavy users (use 20 days or more in a month). The compelling significance of this finding is that a number of studies highlight the increased odds of motor vehicle crashes associated with acute cannabis intoxication,31 32 58 mainly because the psychoactive effects may persist for a significant period of time.59
The fourth key finding demonstrated a significant association between risk perception and the risk of developing cannabis dependence among vehicle drivers. Expectedly, drivers with no to low-risk perceptions of smoking cannabis showed higher risks of cannabis dependence. However, a salient finding is that approximately 30% of drivers with moderate to high-risk perception of smoking cannabis, whether sometimes or often, were also associated with an increased risk of cannabis dependence. Indeed, it may be beneficial to address the misperception that smoking cannabis is not dangerous among drivers who perceive it as less risky. Additionally, directing drivers who have been convicted or suspended for this behaviour towards a remedial programme, similar to those mandated for drunk driving, could prove effective.60 However, the high prevalence of cannabis dependence among drivers who acknowledge smoking cannabis as being harmful further underscores the fact that DUIC is becoming more socially acceptable,61 normative62 and less perceived as a risky behaviour.21
Finally, this study also revealed several sociodemographic factors associated with DUIC. Regression analysis indicated that being a young adult, employed in a job operating machinery, of the male sex, and the head of the household were predictive of DUIC, whereas being married and having a tertiary-level education were protective factors. Interestingly, the risk factors accrued were similar to those observed for DUIA among Jamaican drivers demonstrated in previous research.56 As such, the opportunity for legislators to include DUIC as part of an overall national DUI interventional effort, allow for comprehensive and collaborative efforts that a siloed approach to policymaking is unlikely to foster. Accordingly, a further call to improve data collection protocols regarding DUI behaviours and increase sobriety checkpoints in Jamaica, represent replicable and cost-effective strategies that have found favour in other low-income and middle-income countries (LMICs).63
Cumulatively, the findings of this study have heightened concerns regarding DUIC among Jamaican drivers, particularly in light of the island’s increasing annual road fatality rate.64 The legislation regarding drug driving must comply with global benchmarks. International policy-makers have sought to model drug-driving laws on those that have proven effective for DUI of alcohol, inclusive of a strategy that encourages roadside drug testing. DUIC can be measured through observed impairment in a Standardised Field Sobriety Test65–67 or Drug Evaluation and Classification68 programme by a police officer or by using point‐of‐collection testing devices.69 These strict policies use a per se or zero-tolerance approach, meaning that if THC is detected at or above a specific concentration in a biological sample, the driver is considered to have committed a DUIC offence, regardless of their level of impairment. Several countries, including Norway and Denmark, alongside a number of states in the USA,69 70 have adopted per se limits ranging from 2 to 5 ng/mL THC on oral fluid and blood tests, where studies demonstrate the first indications of impairment may occur, while other nations such as Australia endorse the de-facto zero-tolerance approach.71 While some studies establish that a level of 3.7 ng/mL THC is equivalent to the legal blood alcohol concentration of 0.05 g/dL accepted in a number of countries,72 73 other studies in the USA suggest an absence of a dose-dependent relationship between THC level and driving impairment, especially among frequent users where tolerance may be a factor.40 74 Notably, the accumulated literature regarding the impact of roadside drug testing remains in its infancy, given that most countries would have recently embarked on legislative reform. Notwithstanding, a number of contemporary research have yielded promising results that endorse the importance of roadside testing as part of a DUIC deterrence initiative.75–77
Driving necessitates a higher level of mental and motor dexterity, making it an intrinsically complex undertaking.78 The misperception that DUIC is not risky and that cannabis use adjunctly improves driving skills21 23 is further highlighted by this study’s prevailing finding that a substantial number of drivers (between approximately 30% and 50%) demonstrated a no to low-risk perception of smoking cannabis. This notable risk tolerance or lack thereof may also represent a concern in the workplace, given that DUIC drivers were predominantly employed in machine-operated jobs. Notwithstanding, cannabis-impaired driving, certainly within the Jamaican context, is likely also influenced by recent decriminalisation and medicalisation44 policies as seen elsewhere that have adopted a similar stance,79 and undoubtedly enhanced by sociocultural acceptance,47 easy access48 and availability of higher potency products.80 Accordingly, a calculated national initiative should seek to review current cannabis policy, include more robust regulatory mechanisms and disseminate a public education programme on the risks associated with cannabis use and driving as part of an overall prevention and deterrence effort. Furthermore, the data gleaned may provide the groundwork for policy change in reducing DUIC behaviours per recommendations established in other territories that have similarly endorsed decriminalisation or legalisation.81–85
One of the study’s limitations was that DUI information was self-reported, which can be affected by recall bias. Moreover, the inclination of many of the survey participants to give ‘socially acceptable’ answers and not admit any illegal activities might also introduce a response bias. Notably, this research could not establish causal relationships due to the nature of the cross-sectional data. However, one of the study’s strengths is that the validated CAST enhanced the reliability of the findings given that it is frequently used worldwide in national population sample studies.52 Although the data analysed in this study were collected in 2016, the findings are of immense value for national policy, providing a foundation for further research to build on and vitally fill a knowledge gap, especially in LMICs where global research is scarce.
Conclusion
Two in five Jamaican drivers, who currently smoke cannabis, drive under its influence, with over 85% engaging in heavy use. Public health implications necessitate stakeholders consider roadside drug testing of drivers as part of developing evidence-based policy in mitigating the safety risks posed by DUIC. Moreover, the rising prevalence of cannabis use and availability of higher potency products in a legally and socially tolerant setting, position Jamaica as a key research collaborator in developing policies dissuading cannabis-impaired driving, which may be applicable and replicated in other sister LMICs.
Data availability statement
Data are available on reasonable request. The data that support the findings of this study are available from the National Council on Drug Abuse, Jamaica, and the Inter-American Drug Abuse Control Commission (CICAD) but restrictions apply to the availability of these data, which were used under licence for the current study and are not publicly available. For access to the database, contact Mrs Uki Atkinson, research analyst, at [email protected]
Ethics statements
Patient consent for publication
Ethics approval
This study involves human participants and the Ministry of National Security in Jamaica approved the National Drug Use Prevalence Survey. The secondary data analysis was approved by the University of the West Indies Ethics Committee, Mona (Ref: CREC-MN.8,2021/2022). Participants gave informed consent to participate in the study before taking part.
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