Smoked marijuana attenuates performance and mood disruptions during simulated night shift work.

Abstract

1. Introduction

Drug abuse, if unchecked, could lead to a possible loss to business of more than $200 billion per year due to increased absenteeism, accidents, and medical costs (Slavit et al., 2009). Certain employees are more susceptible to drug use than others. For example, individuals who work nonstandard schedules, such as rotating or night shifts, are almost twice as likely to use illicit drugs as those working standard day shift schedules (SAMSHA, 2008; Frone, 2006). This issue becomes more concerning when one considers the fact that shift-workers account for approximately 20% of all workers in developed countries (Eastman et al., 1995; Beers, 2000). Rotating shift work, particularly night-shift work, requires individuals to alter their normal sleep-wake cycles and perform during times when their circadian rhythms make them least alert (for a review, see Arendt, 2010). Hence, shift-workers have higher rates of workplace-related injuries (Dembe et al., 2008; Stimpfel et al., 2015), performance decrements (Fido and Ghali, 2008; Thompson et al., 2016) and reduced productivity (Akerstedt, 1998).

Many shift workers use stimulants, sedatives or both in an effort to offset shift work-related disruptions. Low to moderate doses of stimulants (e.g., amphetamine, caffeine, modafinil) have been reported to be effective countermeasures for mood and performance decrements caused by sleep deprivation and fatigue (e.g., Hart et al., 2003b, 2006; Schweitzer et al., 2006; Walsh et al., 1990), while sedatives have been demonstrated to improve sleep quality (e.g., Porcu et al., 1997; Hart et al., 2003a, 2005). On the other hand, certain types of drug use by shift workers might exacerbate diminished performance, mood alterations, and sleep disturbances associated with shift work. Cannabis [Δ⁹-tetrahydrocannabinol (Δ⁹-THC)-containing products including marijuana and hashish], the most widely used illicit drug in the world (UNODC, 2015), is of particular concern. In the United States, 28 states and Washington D.C. have passed ballot initiatives allowing patients to use marijuana on the advice of their physicians. Furthermore, eight states now allow adults to legally purchase and use the substance for recreational purposes. Even before these recent developments, marijuana was the most commonly detected illicit drug in the workplace, accounting for approximately 50% of all positive urine toxicology screens (Quest Diagnostics, 2010). Because it may take several weeks for marijuana to be fully cleared from the system (Ellis et al., 1985; Huestis et al., 1996), a urine toxicology screen that is positive for marijuana metabolites does not provide information about time of use, nor an individual’s possible level of intoxication or her/his ability to perform workplace-related operations. The sheer number of marijuana users combined with data showing that 2 million Americans (i.e., 1.6% of the workforce) report being intoxicated on the drug while at work at some point (Frone, 2006), however, suggest the importance of understanding the potential contributions of marijuana use to workplace productivity and safety.

Data from laboratory studies assessing the acute effects of smoked marijuana in experienced users show that the drug produces paradoxical effects; it enhances ratings of alertness and stimulation (e.g., Haney et al., 1999; Hart et al., 2001, 2002) but facilitates sleep (e.g., Vandrey et al., 2011). The drug’s effect on performance depends upon the marijuana use history of research participants. That is, infrequent users tend to display marked disruptions during intoxication (e.g., Fant et al., 1998; Curran et al., 2002; D’Souza et al., 2004), whereas frequent users show little performance alterations (e.g., Hart et al., 2001, 2010; Vadhan et al., 2007; Ramaekers et al., 2009; Schwope et al., 2012). One consistent disruptive effect observed in frequent smokers, however, is that marijuana increases the amount of time participants need to complete cognitive tasks (e.g., Hart, 2001). This finding could have important implications in real world settings, such as in the workplace, where rapid decisions may be required.

There is little information about the effects of marijuana on performance or other measures (e.g., mood, sleep) of individuals subjected to work conditions that mimic those in the natural ecology. Thus, the purpose of this study was to examine the effects of smoked marijuana on the daytime and nighttime performance during shift work in current marijuana smokers. We developed a controlled laboratory model of shift work in order to more closely model the real world work environment. Participants live in a residential laboratory and work 3 days on a day shift (0830–1730h) and 3 days on a night shift (0030–0930h), with shift condition switching several times during the study. This within-participants model facilitates the examination of abrupt work shift change-related alterations in human behavior and the interactive effects of drugs on these alterations. We hypothesized that marijuana would exacerbate night-shift-related performance decrements but improve mood.

2. Methods

3. Results

4. Discussion

Psychomotor performance and subjective-effect ratings were altered during the night shift compared to the day shift: performance and a few subjective ratings were decreased (e.g., “Self-Confident”), whereas other ratings were increased (e.g., “Tired”). These results are consistent with data from previous investigations on the effects of rotating work schedules on human performance and mood under controlled laboratory conditions (e.g., Reid and Dawson, 2001; Sharkey et al., 2001; Hart et al., 2003a, b). Contrary to our prediction, smoked marijuana did not exacerbate night shift-related disruptions. Instead, the drug mainly attenuated night shift-related disruptions in frequent marijuana smokers.

As expected, when participants worked on the night shift and received placebo, their performance was disrupted in several domains. The most pronounced alterations were noted on tasks that measured attention and vigilance. Specifically, participants performed significantly worse on the DAT (measures of speed and hit latency) and the RIT (measures of hits and misses) on all 3 nights of the night shift. In addition, inhibitory control disruptions, as measured by two separate tasks (i.e., DAT: false alarms and RIT: false alarms), were observed on 2 of the 3 nights. These findings replicate data collected under similar conditions (Reid and Dawson, 2001; Sharkey et al., 2001; Hart et al., 2003a, b, 2005, 2006) and confirm that individuals who are required to make abrupt work shift schedule changes are prone to performance decrements. The study design used here is similar to irregular or rapidly rotating shift schedules in the natural ecology (Sallinen and Keckland, 2010), and the current data are also congruent with recent findings from a study conducted in a more naturalistic setting. Chang et al., (2011) compared the performance of nurses working 2, 3, or 4 consecutive nights and found more perceptual and motor ability disruptions among nurses who worked two consecutive nights compared with those who worked four consecutive nights. The results indicate that performance disruptions are more pronounced during the first few days of the night shift. Taken together, the data suggest that an acclimation period greater than 24 hours might be necessary in order to offset shift schedule change-related disruptions.

One possible explanation for the performance decrements observed during the night shift is that the abrupt change in work schedule produced sleep disruptions that affected next-day performance. Indeed, objective and subjective sleep measures lend partial support for this view. Data from the Nightcap® showed that total sleep time was reduced by 2.5 hrs on the first night of the night shift. These data replicate previous findings indicating that night shift work is associated with 2–4 hrs of reduced sleep (Torsvall et al., 1989; Åkerstedt, 1995; Niu et al., 2011). Furthermore, participants reported reduced sleep quality on the first night of the night shift: e.g., their estimates of total sleep time and ratings of sleep satisfaction were significantly lower. Mood was also disrupted during the night shift. Participants reported feeling less “Self-Confident” on all three nights they worked on the night shift and endorsed items indicating that they were tired, miserable, and unmotivated on at least two nights. These data are consistent with previous findings when participants were abruptly placed on a night shift work schedule (Hart et al., 2003a, b).

It is noteworthy that performance disruptions persisted throughout the three nights that participants worked on the night shift, while measures of daytime sleep improved by the second day. One potential reason for these data is short-term circadian misalignment. Working on the night shift forces the body to function during the circadian trough of alertness, potentially compounding problems caused by sleep deprivation. Thus, the enduring performance disruptions may reflect a slow adjustment of the circadian rhythm and/or an accumulation of sleep debt that prevents optimal performance. Indeed, previous research has indicated that the speed of circadian adjustment is approximately 1 hr per day, meaning that it would require at least 1 week for a diurnal cycle to switch to a nocturnal circadian cycle (Wever, 1980; Hastings, 1998). While we did not assess circadian phase, the current data show that daytime sleep improved over the course of three nights of night-shift work. Therefore, we speculate that a longer acclimation period to night shift conditions would also improve performance.

We predicted that smoking marijuana would exacerbate performance disruptions during the night shift. This hypothesis was not supported. The drug produced limited effects on performance on the first night of the night shift but attenuated decrements on subsequent nights. On the second night, marijuana lessened performance disruptions on four measures. Both active Δ⁹-THC concentrations reduced disruptions in inhibitory control (e.g., RIT: false alarms) and recall (e.g., Digit task: total entered) and only the larger concentration lessened disruptions in sustained attention (e.g., RIT: hits and misses). On the third night, marijuana also attenuated shift-related performance decrements: both Δ⁹-THC concentrations lessened disruptions in domains measuring reaction time (e.g., DAT: hit latency), vigilance/sustained attention (e.g., DAT: misses and maximum speed; RIT: hits), and recall (e.g., Digit: total entered).

The above effects were observed, despite the fact that both Δ⁹-THC concentrations markedly increased ratings of forgetfulness on two nights of the night shift; ratings of inability to concentrate were also increased on one night. It might be that these subjective ratings would have had to be dramatically altered in order to observe deleterious performance effects because the current participants were tolerant to many marijuana-related cognitive impairing effects. Indeed, they reported smoking marijuana on a regular basis, on average 3.5 days per week.

To our knowledge, the current study is the first investigation of marijuana-related effects during simulated shift work, making it difficult to compare our results to earlier research in this area. Previously, we reported that stimulant medications such as methamphetamine and modafinil attenuated many night shift-related performance decrements (Hart et al., 2003b, 2006). It is tempting to speculate that the stimulant-like properties of marijuana played a role in decreasing night shift-related performance decrements observed in the current study. When participants smoked cigarettes containing the larger Δ⁹-THC concentration, they reported feeling markedly more stimulated and less tired on the majority of nights (Figure 2 and Tables 2–4). But, marijuana-related effects were comparatively small (methamphetamine and modafinil attenuated virtually all night-shift-related performance disruptions), and immediately after marijuana administration (i.e., up to 90 minutes) there was a trend towards disruptive performance effects, followed by marijuana-associated improvements that persisted over the course of the remaining work period. Thus, the mechanism through which marijuana attenuated night-shift-related performance decrements remains unclear.

A possible explanation for the current results is that marijuana aided in overall sleep recovery during the night shift. The larger concentration increased both objective and subjective measures of total sleep time, and improved sleep quality as measured by ratings of “Satisfied Sleep.” In general, marijuana-related effects on sleep are smaller than, but congruent with, the sleep medication zolpidem (Hart et al., 2003a, 2005). Together, these observations suggest that marijuana cigarettes containing low to moderate Δ⁹-THC concentrations offset some disruptions caused by work shift schedule changes, but further research is needed to elucidate the mechanism(s) mediating these effects.

The present findings should be considered in the context of several important caveats. The current study did not assess a broad range of Δ⁹-THC concentrations. It is likely that increasing Δ⁹-THC concentrations or the number of joints smoked would have exacerbated night shift-related disruptions. Similarly, the current study participants were experienced marijuana users who smoked multiple times each week (i.e., more than three times per week). It is well documented that frequent marijuana users show fewer behavioral signs of disruption during intoxication than infrequent users. Thus, the generality of the present findings might be limited, as a different pattern of results might have been obtained if infrequent users were studied. Relatedly, it is possible that because study participants were frequent marijuana smokers, they may have experienced marijuana withdrawal symptoms during placebo conditions and such symptoms could have influenced study findings. This seems less likely because withdrawal symptoms are typically observed only in heavy marijuana smokers, or individuals who smoke multiple marijuana cigarettes on a daily (or near daily) basis (Haney, 2005). Heavy marijuana smokers were excluded from this study in order to avoid this potential confound. Finally, the current study participants were subjected to abrupt work schedule changes with little time to acclimate, whereas some individuals working night shifts do so for extended periods of time. Therefore, the findings may be relevant only to individuals who undergo abrupt changes in work schedules without an acclimation period.

In conclusion, these data demonstrate that performance, sleep, and mood are disrupted during night shift work when participants are subjected to abrupt shift changes. The data further show that marijuana cigarettes containing low to moderate Δ⁹-THC concentrations can decrease some night shift-related performance and mood disruptions. Because these are the first data describing these effects, future studies are needed before broad conclusions are drawn.

Acknowledgments

Footnotes

References