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Greetings everyone,
For November at criminaljusticeaccess.com, be sure to check out Research Briefs and explore an improved understanding of jurors’ assessment of eyewitness testimony, learn about profiling efforts to distinguish between single victim and serial rapists, understand how marijuana using mental health professionals relate risk to their marijuana using clients, and consider crime incident risk factors that support the use of tactical officers as opposed to their reported over-use.
Evaluating Witness Testimony: Juror Knowledge, False Memory, and the Utility of Evidence-Based Directions
Helm, The International Journal if Evidence & Proof, 2021
Helm states that there is a general assumption that jurors are capable of accurately assessing the truthfulness of witnesses, including the accuracy of their recollections of the incident in question, based on their own experiences with memory recall. However, research in law and the cognitive sciences suggest that they do in fact have difficulty assessing the validity of other individuals’ memories. Jurors understand that factors like fearful and stressful emotions and intoxication, and observation circumstances such as distance from an event or lighting, will affect the recording of a memory. However they are less knowledgeable about the factors that affect memory recall, such as suggestion, after the memory is encoded, which can alter the recall of specifics or generate inaccurate or nonexistent events. This is problematic as false or misleading eyewitness testimony has been identified as a leading cause of wrongful convictions. Distinguishing between true and false memories can be challenging and jurors likely have a poor understanding of the cues that suggest a memory could be false. Juries are provided little guidance in identifying false memories and make mistakes based on intuitive concepts of memories rather than established cognitive science. Helm suggests how legal procedure can facilitate the presentation of information in this way, specifically in cases involving potential false memory.
False memories can be generated in a few ways. For example, source misattribution can occur when people are incapable of distinguishing between two or more sources of their memories. The image that people generate in their minds when thinking about an occurrence can be confused and misattributed to something that happened in reality. False memories can also be generated spontaneously when people recall the gist of something occurring. This familiarity with a person or event but not a specific, verbatim, precise recollection can result in a false memory For example, recalling a general description of an offender may produce a familiarity but is lacking in enough precise details that would determine the suspect is not a true match for the offender, which results in misidentification of a suspect. Helm also notes that “spontaneous false memory can also arise as a result of what is known as change blindness where a witness does not notice that a perpetrator and a bystander are actually different people. These errors can lead to an occurrence known as unconscious transference, or the familiar bystander effect. This effect refers to a memory error whereby a witness identifies a familiar, but innocent person, as an offender. For example, research has shown a tendency to misidentify an innocent bystander to a crime as an offender or to identify a familiar person from an entirely different context as an offender”.
While research has demonstrated how false memories can occur and is well accepted and understood in legal contexts, lay persons’ viewpoints on the generation of false memories diverge from the experts and as well are over confidant in the accuracy of memories. Helm states this lack of understanding must be accounted for and corrected by legal procedure. Direction can be provided to jurors, warning them of a need for caution before convicting a defendant in reliance on the correctness of the identification, debunk relevant memory “myths” (such as the belief that a confident witness is always reliable), list potential influential encoding factors, or explain relevant discrepancies in witness statements. It is also possible to call expert witnesses to explain memory pitfalls to jurors and judges.
Helm states that “in order to be effective, directions relating to witness memory must both appropriately alter juror knowledge relating to witness memory, and facilitate the application of that knowledge in a case context.” However in referencing the Turnbull directions in use in England and Wales, they may do neither and are essentially ineffective. As in the U.S., judges are not memory experts and the application of juror direction is dependent on the discretion of judges and that many cases are moved through the system based solely on eyewitness information. However, even if accurate information regarding memory is presented to jurors there may be a problem in the delivery of this information through a relatively superficial judicial direction following the presentation of the evidence. With jurors having their own “common sense” intuitions of about memory that needs to be dispelled, the relevant research and information about memory must be related with enough detail and background to be persuasive enough to update jurors beliefs. To influence jurors a more central direct approach may not be influential enough to change jurors’ minds. For example simply giving direction to the jurors that a confidant witness may not be accurate will be unlikely to change a juror’s mind as it lacks the meaningful information for the jurors to evaluate and substantiate the claim.
A different approach to jurors may be necessary as research indicates the leading model of jury decision making, the Story Model, indicates juries make decision by a narrative “story” organization on trial information. Evidence is incorporated into a narrative that explains what happened and verdicts are reached by matching the best fitting narrative to a verdict category. Their mental representations of evidence in story structure indicate that “jurors are more likely to remember evidence that is consistent with the story associated with their verdict, and that jurors are likely to find evidence more important where that evidence has a causal role in the story that is associated with their verdict”. Existing direction on witness testimony based on their recollections is insufficient to establish an understanding with jurors how those concerns may apply or how they fit into their narratives. For example, not being given detailed information, based on research, on the types of situations were witnesses may not be reliable or credible, or how jurors can be helped evaluate whether the “confident witness” is indeed accurate. Also, directions may be too cursory to be effectively incorporated into their narratives. Jurors too often consider the overall gist, or inferred meaning of the evidence, provided rather than verbatim details. It’s thus necessary to make the evidence and directions regarding it more meaningful to jurors, which will facilitate more informed decision making. Overly simplified directions by a judge that “warns the jury that even a witness who is very confident may be incorrect, but without being told why this might be the case, or being given examples of the types of other cases in which memory has been impaired in this way, it is likely to be difficult for jurors to extract meaning from it appropriately”. Lacking this context may result in either jurors being dismissive of all witness evidence, jurors not attributing meaning to the information at all and disregarding it in decision making, or attributing meaning to the information in a biased way-judging the importance of the warning based on their unrelated conceptions of the case-for example if they feel overall that the defendant seems guilty they might conclude that although confident witnesses can be wrong, the confidence in the case at hand does signal accuracy. A third problem exists if the directions are not provided prior to the presentation of evidence as it will be difficult for jurors to incorporate this new information into a narrative that has already been constructed or they will simply alter the understanding of this new information to fit into the already established narrative.
Helm states to be effective juror instruction about the accuracy and validity of witness testimony should follow these guidelines:
Helm’s recent research sought support for these contentions utilizing 411 participants as mock jurors reading case vignettes. Participants were grouped into no instruction, basic instruction, and detailed training instruction groups and were also asked a series of memory questions rating their agreement with statements regarding 1) Eyewitness testimony about an event often reflects not only what they actually saw but also information they obtained later on, 2) Eyewitnesses sometimes identify as a culprit someone they have seen in another situation or context, and 3) An eyewitness’s confidence can be influenced by factors that are unrelated to identification accuracy. Helm’s results provide support for more in-depth training instruction for jurors. Basic instruction did increase consensus with existing scientific research on false memory compared to no instruction to a small degree. However, the training instruction was clearly more effective at increasing the level of juror belief with the scientific consensus. The training group, but not the basic instruction group, also indicated an influence on case outcomes. In vignettes with weak evidence less guilty verdicts were produced, however in strong evidence cases the training direction did not influence the number of guilty verdicts, which Helm states demonstrated that training directions helped jurors effectively identify an enhanced risk of false memory, rather than just introducing a general skepticism of towards any eyewitness testimony.
While the study did have some limitations it did indicate that more specific detailed instruction can assist jurors in making informed decisions and can be utilized with other juror misconceptions such as witnesses that are inconsistent are lying or mistaken (when they could be influenced by trauma), or in using them to dispel rape myths. Helm states more work needs to be done in research with real life juries, which can lead to policy that can be put into actual practice in the courtroom.
Helm, R. K. (2021). Evaluating witness testimony: Juror knowledge, false memory, and the utility of evidence-based directions. The International Journal of Evidence & Proof, 25(4), 264-285.
Predicting Rapist Type Based on Crime-Scene Violence, Interpersonal Involvement, and Criminal Sophistication in U.S. Stranger Rape Cases
Mellick, Jeglic, Bogaard, International Journal of Police Science & Management, 2021
The authors contend that in stranger rape cases, physical evidence like DNA and fingerprints may be absent or inconclusive and that in these cases, offender profiling, linking crime scene behavior to an offender, may be useful in resolving those cases. Similarities in crime scene behaviors may point to offenders whose past offenses may have exhibited the same behaviors or suggest a certain type of offender has perpetrated the offenses.
While offender profiling may in some ways be lacking scientific rigor, two assumptions underlie profiling: the consistency assumption and the homology assumption. Consistency assumes that the actions of any offender are consistent across offenses, i.e. there will be a repetition of particular aspects of behavior if the same offender engages in the same type of offense again, such as in serial murder or serial rape. Homology assumes a likeness between the character of an offender and the behavior they engage in at a crime scene, so rather than differentiating between offenders by the presence or absence of singular individual behaviors it examines groups of behaviors across groups of offenders. This “accounts for the possibility that a serial offender may not engage in the exact same behavior across a series of crimes, or likewise, that two different offenders may not engage in the same exact behavior but have rather thematically similar behavior”.
Rapists can be classified based on their behavioral themes by analyzing their crime scene behavior. As these offenders interact with other people in a similar way in non-criminal scenarios, they will interact with victims in a similar way during their offenses. This means it’s possible to link a crime and offender based on their behavioral themes. So a serial offender will exhibit similar behavior across similar offenses, and offender distinctiveness, meaning that two offenders will not behave in the exact same way, makes it possible to distinguish between them.
The authors state that previous research has found different themes explain the differences between rapists; themes of hostility, involvement, and control. Hostility entails overtly aggressive interaction, involvement pertains to physical or verbal attempted contact with the victim such as kissing, complimenting, or reassuring the victim, and control utilizes a surprise attack or weapon to control the victim. Other research suggests similar theme methodology, such as hostility, dominance, and compliance gaining. However, the behaviors tied to these themes may be altered or varied in the offense depending on the context of the situation, namely the victims behavior, making analysis of the factors important in understanding offender behavior. Offenders’ level of initiating violence, victim age, and offender mobility are all factors that will affect the characteristics of the behavioral themes, Offenders will also decide how to act based on the effort, rewards, and costs involved in their course of action which contributes to their profile.
The authors state it’s also important to distinguish between single victim rapists and serial rapists but there has been little research examining the differences between the two. However, research has indicated that single victim rapists are usually known to their victims and use a confidant approach compared to the overwhelming characteristics of serial rapists being strangers to their victims and utilizing surprise attacks. Some research in this area indicates more violence and interpersonal contact (such as inducing the victim to participate) with single victim rapists than serial rapists, however serial rapists show more criminal sophistication (in avoidance of detection and apprehension) in comparison. While stranger rape is more difficult for the police to investigate, their crime scene characteristics can be used to profile offenders. The authors contend that while research has examined serial rapes, single victim rapes, and stranger rapes separately, or comparing serial rapists to single victim rapists, no studies have compared single victim rapes and serial rapes in the stranger rapist context. In the authors’ study, they sought to examine these differences in the stranger rape context hypothesizing that single victim rapists would use more violence and interpersonal contact while serial rapists would show a greater criminal sophistication than there single victim counterparts.
Utilizing the case files of 3,168 male sex offenders they composed a sub-sample of stranger rapes involving 244 single victim rapists (SVR) and 141 serial rapists (SER) (37% White, 47% Black, and 14% Latino) whose victims were 84% female. The violence component examined the amount of physical violence and included offender threats and oral, anal, and digital penetration. The criminal sophistication component involved, the use of weapons, drugs and alcohol, isolation of the offense location, bondage or incapacitation of the victim, and grooming or luring the victim. The interpersonal theme examined whether the offender caressed the victim, performed oral sex on them, induced participation, or introduced pornography into the crime.
Significant differences were found in the demographics of SVR and SER with most SVR being single while SER tended to be divorced. Significant racial differences were also found. While SVR were more evenly represented among White (35%), Black (45%) and Latino (18%), the SER sub-sample demonstrated fewer Latinos were represented (8%) and Whites comprised 40% and Blacks 51%.
Significant differences existed in the three crime scene behaviors between SVR and SER. In the violence theme there were no significant differences between most penetration and actual physical violence between the two groups however, SVR were more likely to use threats of violence and digital penetration compared to SER. Significant differences were also found in different areas of criminal sophistication. Compared to SVR, SER were significantly more likely to use a weapon, more likely to use a gun or knife as a weapon, incapacitate/choke their victims, and groom/meet or lure their victims to a location. However SVR were more likely to have used drugs or alcohol during the crime and commit the crime in an unknown or new location, compared to SER. The only significant difference in the interaction theme was that SER were more likely to induce participation from the victims compared to SVR. The significant characteristics, placed in a logistic regression model for prediction of type of rapist was found to explain 35% of the variance in rapist type and overall correctly classified 75.8 percent of the type of rapist cases.
The authors conclude that “these findings could be used to identify potential suspects in stranger rape cases because the crime scene information could help law enforcement determine whether they are looking for individuals who have committed these types of crimes previously and may already be in the system”. They also suggest that “the crime-scene behaviors associated with serial rapists could also be used to identify unknown offenders as possible serial offenders. This includes individuals who may have committed sexual offenses before, but who have never been caught and cases where offenders have just started their rape career. This allows for law enforcement to narrow down their suspect pool and thus assist the investigation”.
While this study is exploratory the findings can guide future research by testing the predictive power in actual crime scenes as well as more closely examine different regions and cultural groups as well as include more crime scene characteristics not examined here such as developmental factors, triggering behaviors before an attack, or the cognitive processes involved in the offender’s planning before an attack.
Mellink, I. S., Jeglic, E. L., & Bogaard, G. (2021). Predicting rapist type based on crime-scene violence, interpersonal involvement, and criminal sophistication in US stranger rape cases. International Journal of Police Science & Management, 14613557211036564.
Cannabis Use Among Mental Health Professionals: A Qualitative Study of Cannabis-Related Risk Perceptions
Ghelani, Journal of Drug Issues, 2021
The author recognizes that there are potential risks and harms in marijuana use. Research indicates the potential for issues of dependence, cognitive deficits, anxiety, and the risks of driving while intoxicated. These risks may be poorly understood or not attributed to marijuana use if users assume that marijuana is considered to be harmless, specifically considering the current legal status of marijuana in Canada.. The author explores whether mental health professionals who were themselves marijuana users, were cognizant of the risks that do exist in treating individuals who were also marijuana users.
The small qualitative Canadian study consisted of seven professionals (three social workers, two psychotherapists, a nurse, and a nurse practitioner) whose clients worked with marijuana users and explored the extent that study participants were aware of and addressed marijuana use risk with their clients and in their own use.
Overall, all the participants recognized the psychosocial risks involved in marijuana use by their clients and in some cases, when relevant, in their own use. Anxiety, panic, and avoidance behavior was the most prevalent risks mentioned by the participants, especially amongst young and/or inexperienced users, though two participants noted they do experience some anxiety in social situations. Most of the participants noted that marijuana use could also negatively affect interpersonal relationships through anxiety caused by peer pressure or a fear of separation from their peers who used. Some participants noted the effects on clients stemming from tension in parental or spousal relationships from non-users, as well as the social stigma that results when their clients are viewed as “criminal”, a “stoner”, or ” lazy” because of their marijuana use. The participants were also very well aware of the dangers of driving while intoxicated on marijuana and related how chronic use may also affect employment if their clients’ jobs require the operation of a vehicle.
Beyond social issues, the participants also discussed the cognitive and neurological impairments and risks their clients might face or experience. Five of the participants discussed how marijuana use could lead to psychosis and exacerbate symptoms of schizophrenia. The suggestion put forth to their clients was to stop using cannabis because they were experiencing symptoms along the schizophrenic spectrum, with some participants noting that cannabis has the potential to make young people more vulnerable to psychosis or for long term users to be more resistant to anti-psychotic medications. Most of participants discussed how cognitive functioning could be impaired, especially in the brains of adolescents and young adults, cautioning against their use of marijuana. Some participants discussed the possibility of decreased motivation and reduced day to day function with some clients as well as how it may affect memory, attention, and concentration. Two participants themselves noted that it decreases their concentration and smoking too much “allows their mind to wander”. Most of the participants noted that these issues can affect education and employment function and cautioned their clients from using before or during work, or when starting a new position, as memory issues, motivation, and interaction with others can be negatively affected.
Four of the participants noted the potential for cannabis use to lead to a chronic habit or dependence. Unhealthy use patterns like “wake and bake” (starting the morning by getting high) may signal dependence. Two of the participants expressed some concerns about developing a psychological dependence themselves, such as habitual use in a situation where they felt like they should have refrained, or in using to calm themselves or help cope with stressful situations rather than utilizing other methods.
The authors discuss how the framework of rational choice can be utilized to examine these results. While the participants and their clients are aware of the risks or negative outcomes that can be associated with marijuana use, in the cost benefit analysis the benefits such as relaxation, mood enhancement, relief of anxiety, and pain relief outweigh the potential costs for both study participants and their clients as well. Indeed, few of the participants noted any negative outcomes from their use but they all held a comprehensive understanding of the potential risks. Interestingly, while there is some evidence of small physiological risk from marijuana use, only one of the participants mentioned the potential pulmonary or cardiovascular effects. However this may stem from a greater focus from the participants on the psychosocial aspects of use as it relates to their employment field. The study does provide evidence that legalization, acceptance, and use does not preclude mental health professions from recognizing the potential risks involved with marijuana use nor does it inhibit them from sharing that information and treating clients who may be struggling with use, abuse or dependence issues.
Ghelani, A. (2021). Cannabis Use Among Mental Health Professionals: A Qualitative Study of Cannabis-Related Risk Perceptions. Journal of Drug Issues, 51(4), 679-689
The Role of Context in Understanding the Use of Tactical Officers: A Brief Research Note
Jenkins, Semple & Bennell, International Journal of Police Science & Management, 2021
The authors note that the use of tactical officers and services are being utilized more frequently in North America and in more incidents than in what is typically recognized as high risk incidents, like hostage taking, such as in proactive policing and warrant service. Some observers are concerned that these activities are disproportionally focused on minority communities. While the authors do give consideration to the view that the use of tactical police officers and services may not be called for in all instances, where they are used the authors contend that view often doesn’t consider the risk factors in those incidents that suggest the appropriateness and utility of those officers and services. They state that analyses of tactical operations use too often focuses on the type of call rather than the risk factors that may be present in the calls themselves. What might appear to be a relatively benign domestic disturbance type call may not account for risk factors like the violent or resistive history of the subject, situational factors like intoxication, and the presence of weapons. Feedback from tactical officers indicated these risk factors are typically in play in the calls that they respond to but these risk factors are typically not examined in studies of the use of tactical officers. The authors sought to use their current project to analyze more detailed contextual factors in the use of Canadian tactical officers. Using the same Winnipeg Police service data used in a previous study to suggest an increase in the use of tactical officers, the authors broke out the contextual data from the incidents to analyze the risk assessment for these types of situations. A coding scheme was setup and the four contextual risk factors analyzed were the history of the subject, (for example, their propensity of violence toward the police), the state of the individual, (for example, intoxication), the subject making threats to their own or others safety, and the belief that weapons were present, along with other contextual data contained in incident reports. Call type was also hierarchically coded to indicate the level of risk in the type of call.
Analyzing differences in the number of tactical responses between 2013 and 2016 indicated that a significant increase in deployment (from 474 in 2013 to 2757 in 2016) was more of a result in a change in reporting rather than change in their actual use. Data showed tactical officers responded to 78 different types of calls, though the vast majority (81% ) were reactive as opposed to planned operations. The most common calls tactical officers responded to were active warrant arrests, gun and weapons calls, shots fired, breaking and entering, domestics, alarm calls, suspicious persons, and well-being checks.
In regard to weapons believed to be on the scene, despite the variation in calls, on average, 60% of the calls indicated a weapon was involved, with more weapons present in the 2016 data than in 2013. Of the weapons believed to be present firearms were mostly commonly reported in 2013 (42%) and in 2016 (48%). In the cases where additional information reported, call types that indicated a firearm was likely to be present on the scene, such as gun call, shots, fired, and gunshot wound, made up approximately half the calls where guns were thought to be present. However, of the calls in which a firearm was believed to be present, 59% of those calls were not firearm related. The authors state the findings suggest that simply looking at the call type is not a reliable indicator of the presence of weapons and suggests a variability of situations within call categories. It also appears that weapons are frequently believed to be present on seemingly benign calls like domestic disturbances, traffic incidents, and warrant executions, etc. With the concern over the use of tactical officers responding to “routine” calls the authors sought to determine how frequently firearms were believed to be present at some of these reportedly routine calls. The presence of firearms were believed to be present at 45% of suicidal threat and mental well being checks, as well as half of warrant executions and domestic disturbances, suggesting these are not low risk routine calls but actually pose a significant risk to officers and the public.
The other risk factor with enough additional information to be analyzed was the subjects’ history. Less information on the subject was available on reactive calls that tactical officers responded to (28% of tactical officer calls) versus planned operations (like warrant executions). The most frequently reported history risk factors in incidents were possessing weapons (8%), gang affiliations and previous murder or attempted murder charges (slightly greater than 1% for each). However 6% of calls also entailed the individual making explicit threats toward themselves, the public or the police.
The research indicated that the majority of tactical officer responses were utilized in planned operation like warrant executions which entailed a variety of entry approaches from no-knock (approximately 1/3 of warrant executions), to knock and announce, knock and talk, or surround and call out, as well as being involved in subject takes downs and surveillance. Exploratory analysis between the roles of tactical officers and the belief that weapons were present on the scene, utilizing Chi Square, found a significant relationship. Specifically, knock and talk, and knock and announce, were used significantly more when no weapons were believed to be present compared to situations where firearms were believed to be present, while surround and call out and high risk takedowns were used significantly more when weapons were believed to be present. No knock entries were significantly more frequent when the belief that weapons were not present suggesting other factors, such as the likelihood of destroying evidence, contributed to that entry method, supported by the evidence that controlled drug and substance warrants made up nearly all the no knock warrants.
The authors conclude that a view that tactical officers are misused on routine calls, including warrant executions, and should be scaled back, misjudges the seemingly benign nature of these calls. Rather, the belief that weapons were present at the majority of these calls and that call type was generally not of indicative of the risk posed to the public or officers as the belief in weapons being present at supposedly low risk situations prompted the use of tactical officers. Thus the belief that a tactical response is unwarranted in routine calls may be a misguided view when this additional context is included. The authors did recognize that the limited contextual information in some call data prevents them from making policy recommendations but rather illustrates that contextual data is an important consideration in regard to making tactical police utilization and policy decisions. However this does require policing agencies to collect more detailed contextual information more frequently, in a standardized manner, in order to better assess the use of these officers and the policies recommendation affecting their deployment.
Jenkins, B., Semple, T., Bennell, C., & Huey, L. (2021). The role of context in understanding the use of tactical officers: A brief research note. International Journal of Police Science & Management, 23(4), 385-391.
Criminal Justice Access Mission Statement
Catering to practitioners, scholars and the public, Criminal Justice Access (CJA) brings historical, original, and current criminal justice research, practitioner interviews, and crime data together in an easily accessible and user-friendly format. The field of criminal justice is broad so CJA is devoted toward focusing on issues in policing, Part One Crimes, drugs, gangs, and deviance. By aggregating and summarizing data and information from literature in the criminal justice field, CJA tries to simplify the process of keeping abreast of current criminal justice research and information. I will be publishing content monthly so check back at see what’s new.
As this is my first month of publishing, there are no archived posts, however be sure to check the site categories. For November:
Research Briefs covering a possible new role for detectives, clearance rate differences in gun homicides vs gun assaults, reluctance in talking to the police, and differences in attitudes towards stop and search
At Issue looks at marijuana driving impairment and roadside testing
For Discussion explores recognizing a beat management philosophy called beat integrity
US Crime Data focusing on seven Part One Crimes from the UCR
Original Research is featuring past academic research by the author with this month featuring my PhD dissertation, a qualitative study of patrol officer behavior and decision making
Editorials and Opinions examines a possible deviance continuum from motorcycle enthusiast to outlaw through the mechanism of differential association
Introduction
This literature review will examine marijuana’s effects on driving performance, determining impairment levels, and the use and effectiveness of Drug Recognition Experts (DREs) and roadside testing in making determinations of driving under the influence of marijuana. Marijuana use and acceptance is on the rise and this has contributed to more incidence of drugged driving. 34 states have legalized medical marijuana, and while some strains are produced with relatively higher CBD to THC ratios to optimize their medical use, some strains ostensibly sold for medical purposes may have a relatively high THC level that has the potential for misuse. Legalization at the state level has been expanding. Currently 11 states and Washington D.C. have legalized recreational marijuana, while in 15 states decriminalization has been an ongoing process. When combined with a change in public perception, this can lead to increased incidence of driving under the influence of marijuana. A 2001 study examining roadside testing found that of 209 positive drug tests, 113 indicated cannabis (Steinmeyer, et al). A ten-year Swedish study found measurable THC levels between 18 and 36 percent of suspected drugged drivers (Jones, et al. 2008) and a UK lab sample of over 3,600 suspected drugged drivers showed 58% were positive for cannabis (Wolff and Johnston, 2014).
What was once an underlying marijuana subculture decades ago, has now reached a new level of acceptance in overall society as research has dispelled some of the myths about marijuana use and its negative consequences, and revealed suggested medical uses and benefits. Marijuana awareness, and its use, are also becoming more normalized with depictions in popular media in the form of news reports and specials, programming focusing both specifically and tangentially on its use, movie and TV characters using marijuana in a normalized context similar to how drinking has been portrayed, and websites that describe and rate different strains of marijuana as well as provide growing and usage tips. This normalization may contribute to some users minimizing the risks of driving while high.
Research into Driving Effects
Marijuana users have believed, and research has shown, that frequent users who are experienced drivers are able to compensate to a certain degree for marijuana’s effects while driving (Robbe, 1998; Kelly, 2004; Sewell, et al, 2009; Wolff and Johnston, 2014; Micallef et al, 2018) and some users forward the argument that driving high is safer than driving drunk (Kelly, 2004) . However, marijuana can impair driving performance, but typically in a way that differs from the effect of alcohol on driving performance. In research, impairment identification testing while under the influence of THC typically measures car following (maintaining distance with a car under varying speeds) and the standard deviation in lateral position (SDLP), or lane tracking (amount of weaving off center within the lane), as well as some other driving related tasks. Studies typically provided THC in two ways, either in 100-300 microgram/kilogram of subject body weight, or in 10-30 milligram doses of THC, irrespective of subject body weight.
Many studies when examining driving performance find significant effects on car following and SDLP. Robbe (1998) found at higher doses of THC tracking and following were significantly negatively affected compared to a control group and Ramaekers et al’s (2000) research revealed that low doses only moderately impair drivers actual driving performance in those areas Micallef, et al (2018), also found THC had a significant effect on lane tracking. However, a 2001 Netherlands study didn’t find any significant difference in visual search frequency with a 100 microgram/Kg THC dose (Lamers, et al). In 2009, Sewell and colleagues reviewed marijuana driving impairment studies and found, beside marijuana effects on driving being dose dependent, that there were differences in the type of impairment between alcohol and marijuana. Marijuana’s effects are more pronounced with tasks requiring a higher automatic driving function as opposed to alcohol’s more pronounced effects on conscious, cognitive function. SLP is affected by marijuana and not subject to compensatory behavior the way other driving functions are, and other effects like poor speedometer monitoring, increased decision time in passing, and increased time in responding to a light change or sudden sound were also present. Alcohol was implicated more in pursuit tracking, divided attention, signal detection, hazard perception, and lowered concentration, reaction time, and hand-eye coordination.
Research has shown the driving impairment effects are dose, and frequency of past use, dependent, as well as demonstrating significant effects differences from placebo or control groups at the THC levels used for testing. But how marijuana contributes to car crashes also requires examination. In 2014, Romano and Pollini, examining 12 years of crash data, found 26% of single car fatal crashes involved a drug other than alcohol, with cannabinoids present in approximately a quarter of those cases. However, previous work has not provided a clear indication of marijuana’s influence. Kelly (2004) in a review of driving studies found inconsistent associations of THC with traffic accident involvement. A 2005 multivariate study found that once accounting for things like speed, seatbelt use, and BAC, marijuana use was no longer a significant factor in car crash injury. However, it was a significant factor in those that identified as habitual marijuana users (Blows, et al). In 2014, Wolff and Johnston reviewing a meta-analysis showed that drivers were twice as likely to be involved in a car accident with a THC blood plasma level of 5 micrograms/liter. Huestis (2015) in her review of two recent meta analyses found a significantly increased crash risk (2-2.6 times more likely) with a measurable amount of THC and a six-fold increased risk at a 5 microgram/liter level. However, in 2016 Rogeberg and Elvik found that marijuana involvement in crash risk is low to moderate, similar to a BAC level of .04-.05.
While the possibility of increased risk of car crashes may yet to be determined because of dose dependent effects and other factors, research has been consistent on the effects of combining a small amount of alcohol with marijuana. BACs of .04-.05 when combined with even low levels of THC significantly increased the severity of driving impairment, resulting in impairment equal to a BAC of .08-1.9 (Robbe, 1998; Ramaekers, et al, 2000; Blows et al, 2005; Sewell, 2009; Huestis, 2015).
Determining and Setting Intoxication and Impairment Standards and Limits
As a practical application, identifying and utilizing THC levels in determining impairment for drivers in the real world is important for state legislatures and municipalities in legalization states, as well as for those adjoining states, and other states considering legalization, as the country continues to progress toward greater medical and recreational legalization. Standards are typically expressed as THC parts per volume of oral fluid or serum/plasma concentrations, either as nanograms/milliliter or as micrograms/liter (note that these are equivalent measures-1 nanogram/milliliter = 1 microgram/liter). Setting driving limits typically take two approaches; a per se approach, where any amount of THC above a preset limit indicates a violation of the law, similar to the .08 BAC limit currently used in the U.S. but could also resemble a zero-tolerance level where any detectable THC amount is a violation of law. The other approach is to determine a THC fluid concentration that indicates impairment, often based on driving performance deficits comparable to a specified BAC level.
The approaches vary around the world, and approaches and levels can change or be set by a combination of research, politics, and public opinion. In 2007, a toxicology lab survey in 24 states found cutoff and confirmation levels of THC ranged from 2 to 70 ng/ml. While recommending that a 2 ng/ml confirmation level be used in drugged driving investigations, it is a level based more on good analytic methodology and lab practice than in an indication of impairment (Farrell, et al, 2007). While European workplace testing typically has a cutoff (the drug screening point where a concentration above the cutoff indicates a positive test for the substance, and below that point is a negative result) of 10 ng/ml (Moore, 2012) European driving limits varied widely; Sweden (a zero-tolerance country) sets a cutoff at .3 micrograms/liter, Germany-.5, France-1.0, Norway-1.3(declaring it an impairment limit), Switzerland-1.5 (declaring it a prosecution limit), and Portugual-3. A Swiss study of drug impaired drivers found that a 5 microgram/liter fluid level correlated to observable driving impairment (Wolff and Johnston, 2014). However, a German study from 2007 suggested a range of 7-10 micrograms/liter as a non-zero per se limit after finding that it correlated to an impairment comparable to a .05 BAC and that concentrations below 10 micrograms/liter were not associated with increased accident risk (Grotenherman, et al). Huestis (2015), in reflecting on an appropriate measure for the U.S. suggests a two-tiered approach, similar to what is used in some European countries and Australia. that when combined with driver education, has been shown to deter drugged driving. It provides for a small fine and driver education for exceeding a per se limit and provides for a more severe penalty and criminal prosecution for demonstrated impairment.
Testing for Marijuana Intoxicated Drivers
Regardless of where the cutoff points are established, the concern for law enforcement is utilizing the tools at their disposal to identify drivers who are intoxicated or impaired. Drug Recognition Experts (DREs) and roadside testing can be utilized both on active patrol and at driving checkpoints. DRE use is expanding and the options for roadside testing include oral fluid (saliva) testing with point of collection testing (POCT) that can provide results in minutes. Time can be an important factor as THC concentration levels peak approximately 15 minutes after smoking but then go on a rapid decline over the first hour after smoking, and drops even further between one and three hours after smoking. However, while THC levels drop off quickly, the subjective high of the user declines at a much slower rate, meaning people who have a broad range of THC levels may exhibit the same level of being high, and thus impairment.
DRE Effectiveness
According to Brown, (2001), the DRE program was first started as a partnership between the LAPD and National Highway Traffic Safety Administration (NHTSA) in the 80’s and the program became more popular in the 90’s, resulting in the majority of states utilizing DREs in law enforcement agencies. The International Association of Chiefs of Police (IACP) is the national certifying agency for DREs and instructors.
There are three phases of training and DREs must re-certify based on the past two years of their evaluations. Typically, DREs are called in during a DUI traffic stop when the suspected driver appears intoxicated from something other than alcohol. The DRE evaluation is a 12-step process that involves a BAC test, pulse checks, eye examinations, temperature, muscle rigidity, and ingestion exams, interviews with the suspect and arresting officer, a standardized field sobriety test (SFST), the DRE’s opinion, and a toxicology test. Some studies have demonstrated moderate to high effectiveness in determining intoxication and drug classification. A 1995 Phoenix PD study compared DRE opinions to the toxicology reports and found DREs identified at least one of the drugs in 91% of the samples confirmed as containing drugs and overall the DREs impaired decisions were correct 83.5 %. Marijuana was the drug most often missed though, and the study notes it’s unknown whether this was due to DRE accuracy, or the time course of the drug (Burns and Adler, 1995). A 2002 study found that when DREs reports were stripped of all information except DRE observations, the DREs tested were 95% accurate in determining intoxication and 81% accurate in identifying the cannabis category. Beirness, et al (2009) examined over 1,300 Canadian DRE evaluations and found the DREs were 95% accurate in determining true positives, 80% accurate in determining true negatives, and 92% accurate on drug classification, compared to lab results.
However, in 2009 Porath-Waller, Beirness, and Beasley were examining whether a simpler approach to the DRE evaluation could be utilized, focusing on the most relevant of the twelve physiological testing criteria for the three most common classifications; stimulants, cannabis, and narcotics. They found nine of the criteria were more predictive of drug category including pulse rate, condition of the eyes and eyelids, lack of convergence, hippus, reaction to light, rebound dilation, systolic blood pressure, and the presence of injection sites with an overall accuracy of 81% across the three drug classifications, however only 72% accuracy in identifying cannabis.
Other research has focused on the SFST. In 2014, Porath-Waller and Beirness examined three components of the SFST in determining THC impairment; the Horizontal Gaze Nystagmus (HGN), the One Leg Stand (OLS), and the Walk And Turn (WAT). Their results showed only the OLS was a significant predictor of THC. In a two-year study, Declues et al (2016) found that while SFTSs are sensitive to marijuana impairment that there was no correlation between SFTS performance and an average 9 ng/ml THC level, however the number of SFTS cues were greater the higher the THC level. Their study found that the WAT was a better indicator of marijuana intoxication that the OLS (contrary to DRE evaluation studies) and the Lack Of Convergence (circular tracking with eye cross) was also a strong indicator. Hartman et al (2016) arrived at somewhat different conclusions. In their study they found no difference in SFST performance between those above and below 5 ng/ml. They found the Finger To Nose test was the best predictor of cannabis intoxication, along with MRB eyelid tremors, OLS sway, pupil rebound dilation and two or more WAT cues.
Brown, in 2001, did raise an issue related to the accuracy of DRE’s and whether they can provide valid, reliable, expert testimony. He argues because DREs are labeled as experts and are construed by juries to be giving expert testimony then the basis of their evaluations should be subjected to Daubert or Frye tests of evidence admissibility. Brown considers the program would or should not pass these tests as they have not faced peer reviewed evaluations, or general acceptance in the relevant scientific community. However, some court rulings have concluded that the twelve-step evaluation is not scientifically novel enough to warrant putting it to the test of admissibility. Brown believes that with reviews of different DRE programs indicating correct hit rates of between 47 and 86%, and with only a 75% correct hit rate needed for re-certification, that DRE evaluations should not be considered reliable scientific, technical, or specialized knowledge and should continue to face challenges of admissibility in court.
ROADSIDE TESTING
THC can be found in high levels in the saliva immediately after smoking, and similar to blood serum levels, declines quickly in the first hour and steadily downward over a few hours (Cone, 1993). Roadside testing has focused on oral fluid testing as opposed to urine or blood for a number of reason including, it is less intrusive, a smaller amount of fluid is needed for a sample, it’s easier to administer, can identify parent drugs, not just metabolites, has a close correlation to serum drug concentrations, and provides quicker results (Cone, 1993; Verstraete, 2005; Bosker, 2009; Huestis, 2011). A 2001 German study of roadside testing found they were 97.6% accurate compared to lab results, with no false negatives and only 2.4% false positives. In a 2009 Australian study of random roadside testing, cannabis was the third most common drug, found in 26% of drugged drivers. Their results showed that oral fluid testing correctly identified targeted drugs 98% of the time.
But there are some caveats to oral fluid testing. Delays in testing may yield negative results if cutoffs are set too low, (Cone and Huestis, 2007) and there is a lack of conclusive evidence tying THC levels to the subjective high, (Cone, 1993) and thus, possible impairment. Verstraete (2005) considers that there should be a better correlation between drug presence and impairment, better discrimination for cannabis, better proficiency in testing, and safeguards against passive contamination before oral fluid testing will be forensically reliable. Earlier devices suffered from poor accuracy and current devices still lacked adequate reliability (Boker et al, 2009) but Huestis (2011) predicts that the move to oral fluid testing will expand as better tests become available.
Evaluations of more recent devices provided varying results. A 2007 study of the RapiScan tester demonstrated a 96% accuracy for positive samples and 100% accuracy for negative samples but was more sensitive to stimulants than cannabis (Dewey et al, 2007). Couch and associates’ 2008 study of ten different tests including RapiScan, DrugWipe, and OraLab showed nine of the ten devices were accurate in identifying THC but all had a much higher cutoff than the 4 ng/ml suggested by SAMSHA. A European Union 2011 study evaluated eight testers on sensitivity (ability to detect a positive result), specificity (distinguishing between negative and positive samples) and accuracy (the rate of true results compared to false results). Cutoff levels for the devices varied between 5 to 100 ng/ml. Specificity ranged between 90 and 100% but sensitivity was poor, ranging from 20-60%, resulting in accuracy between 78-88% for the five best performing devices. None of these multidrug testers had over 80% in each of the three measurement categories. A 2012 Italian study of four different devices found the sensitivity ranged from 38-92% accurate compared to lab results. In 2019, a Brazilian study analyzed four devices for ease of use, operational success, and acceptable analysis and collection time, using feedback from patrol officers. Three of the four devices were rated in the 80th percentile in these categories. To complicate things, some drugged drivers may be trying to confound the test by using different fluids or mouthwashes to dilute a possible sample. de Castro (2014) found that a commercial product designed to dilute for the test was ineffective, but a plain water mouthwash at 3 hours after use was effective in dropping THC to below 25 ng/ml. However, developments continue to be made in oral fluid testing. Plouffe et al (2017) describe a new roadside testing technique they were developing, utilizing existing fluorescent scanners, that’s highly reliable, can utilize a cutoff of 1 ng/ml or lower, and from sample insertion to readout, take less than 10 minutes to complete.
IMPLICATIONS
As improvements are made in oral fluid roadside testing, the role of a DRE may be scaled back to assisting in drug investigations or in cases involving an indeterminate drug, as may be the case as synthetic designer drugs continue to be developed and find their way into the recreational market. But in order to make oral fluid testing a viable means of deterring, detecting and stopping drugged driving, yet distinguishing from residual THC in the system that has no effect on driving performance, reasonable, science-based decisions will need to be made regarding per se or impairment levels, and the proper testing device for the intended purpose, such as the suitability of using the device for a DUID checkpoint. Jurisdictions should also be prepared for legal challenges to the admissibility of testimony from DREs as well as challenges to the reliability of some testing devices. Despite some drawbacks still present in oral fluid testing devices and the validity in determining impairment by THC level, it is the direction that roadside testing is moving. As such, jurisdictions and legislatures will need to stay current on the best testing equipment, and best practices and research, in this continually emerging field.
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