Mobile Assessment of Acute Effects of Marijuana on Cognitive Functioning in Young Adults: Observational Study

Effects of acute cannabis inhalation on reaction time, decision-making, and memory using a tablet-based application

BACKGROUND

Acute cannabis use has been demonstrated to slow reaction time and affect decision-making and short-term memory. These effects may have utility in identifying impairment associated with recent use. However, these effects have not been widely investigated among individuals with a pattern of daily use, who may have acquired tolerance. The purpose of this study was to examine the impact of tolerance to cannabis on the acute effects as measured by reaction time, decision-making (gap acceptance), and short-term memory.

METHODS

Participants (ages 25-45) completed a tablet-based (iPad) test battery before and approximately 60 min after smoking cannabis flower. The change in performance from before to after cannabis use was compared across three groups of cannabis users: (1) occasional use (n = 23); (2) daily use (n = 31); or (3) no current use (n = 32). Participants in the occasional and daily use group self-administered ad libitum, by smoking or vaping, self-supplied cannabis flower with a high concentration of total THC (15-30%).

RESULTS

The occasional use group exhibited decrements in reaction time (slowed) and short-term memory (replicated fewer shapes) from before to after cannabis use, as compared to the no-use group. In the gap acceptance task, daily use participants took more time to complete the task post-smoking cannabis as compared to those with no use or occasional use; however, the level of accuracy did not significantly change.

CONCLUSIONS

The findings are consistent with acquired tolerance to certain acute psychomotor effects with daily cannabis use. The finding from the gap acceptance task which showed a decline in speed but not accuracy may indicate a prioritization of accuracy over response time. Cognitive and psychomotor assessments may have utility for identifying impairment associated with recent cannabis use.

Influence of pregabalin maintenance on cannabis effects and related behaviors in daily cannabis users

No medications are approved for cannabis use disorder (CUD), though a small clinical trial demonstrated that the voltage-dependent calcium channel (VDCC) ligand gabapentin reduced cannabis use in treatment seekers. VDCCs are modulated by cannabinoid (CB) ligands, and there are shared effects between CB agonists and VDCC ligands. This overlapping neuropharmacology and the initial clinical results supported the evaluation of pregabalin, a "next-generation" VDCC ligand, as a CUD medication. Two separate placebo-controlled, double-blind, counterbalanced, within-subjects human laboratory studies tested placebo and 300 (N = 2 females, 11 males; Experiment [EXP] 1) or 450 (N = 3 females, 11 males; EXP 2) mg/day pregabalin in cannabis users who were not seeking treatment or trying to reduce/quit their cannabis use. The protocol consisted of two outpatient maintenance phases (11 days in EXP 1 and 15 days in EXP 2) that concluded with four experimental sessions within each phase. During experimental sessions, maintenance continued, and participants completed two 2-day blocks of sampling and self-administration sessions to determine the reinforcing effects of smoked cannabis (0% and 5.9% delta⁹-tetrahydrocannabinol [THC]), as well as subjective, attentional bias, performance, and physiological responses. In addition, naturalistic cannabis use, side effects, sleep quality, craving, and other self-reported substance use were measured during pregabalin maintenance. Cannabis was self-administered and produced prototypical effects, but pregabalin generally did not impact the effects of cannabis or alter naturalistic use. These human laboratory results in cannabis users not trying to reduce/quit their use do not support the efficacy of pregabalin as a stand-alone pharmacotherapy for CUD. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Remote detection of Cannabis-related impairments in performance?

RATIONALE

Researchers have traditionally studied the effects of psychoactive drugs such as Cannabis in controlled laboratory settings or relied on retrospective self-reports to measure impairment. However, advances in technology afford opportunities to conduct assessments remotely.

OBJECTIVES

We considered whether objective click-stream data (time and number of clicks spent on a webpage) during an online survey could supplement self-reports of substance use problems.

METHODS

The clickstream data of participants (n = 236) were examined as they completed an online study which included validated psychometric tests (Cannabis Use Disorders Identification Test-Revised, Grit-O, Kessler Psychological Distress Scale, and Brief Self Control Scale). Clickstream data were compared to self-reported Cannabis use.

RESULTS

People reporting Cannabis use within the last 4 weeks required more time and more clicks to complete the online survey, and this was specifically associated with reported frequency of use, duration of impairment, and problems with memory and concentration. Longer amounts of time and more clicks on the online questionnaire were associated with more recent Cannabis use rather than demographic factors or stimulant use.

CONCLUSIONS

These results imply clickstream data remotely detected indecision or other deficits associated with previous Cannabis use.

Interaction of Gut Microbiota and Brain Function in Patients With Chronic Insomnia: A Regional Homogeneity Study

Recent studies have shown that the human gut microbiota (GM) plays a critical role in brain function and behavior via the complex microbiome–gut–brain axis. However, knowledge about the underlying relationship between the GM and changes in brain function in patients with chronic insomnia (CI) is still very limited. In this prospective study, 31 CI patients and 30 healthy controls were recruited. Resting-state functional magnetic resonance imaging scans were performed and brain functional alterations in CI patients were evaluated using the regional homogeneity (ReHo) method. We collected fecal samples of CI patients and used 16S rDNA amplicon sequencing to assess the relative abundance (RA) and alpha diversity of the GM. We also performed extensive sleep, mood, and cognitive assessments. Then, we tested for potential associations between the GM profile, ReHo alterations, and neuropsychological changes in CI patients. Our results showed associations between the RA of Lactobacilli, ReHo values in the left fusiform gyrus, and depression scores in CI patients. We also found some bacterial genera related to ReHo values of the right triangular inferior frontal gyrus. In addition, the RA of genus Coprobacter was correlated with ReHo values of the left angular gyrus and with specific cognitive performance. These findings revealed complex relationships between GM, brain function, and behavior in patients with CI.

Mobile phone sensor-based detection of subjective cannabis intoxication in young adults: A feasibility study in real-world settings

BACKGROUND

Given possible impairment in psychomotor functioning related to acute cannabis intoxication, we explored whether smartphone-based sensors (e.g., accelerometer) can detect self-reported episodes of acute cannabis intoxication (subjective "high" state) in the natural environment.

METHODS

Young adults (ages 18-25) in Pittsburgh, PA, who reported cannabis use at least twice per week, completed up to 30 days of daily data collection: phone surveys (3 times/day), self-initiated reports of cannabis use (start/stop time, subjective cannabis intoxication rating: 0-10, 10 = very high), and continuous phone sensor data. We tested multiple models with Light Gradient Boosting Machine (LGBM) in distinguishing "not intoxicated" (rating = 0) vs subjective cannabis "low-intoxication" (rating = 1-3) vs "moderate-intensive intoxication" (rating = 4-10). We tested the importance of time features (i.e., day of the week, time of day) relative to smartphone sensor data only on model performance, since time features alone might predict "routines" in cannabis intoxication.

RESULTS

Young adults (N = 57; 58 % female) reported 451 cannabis use episodes, mean subjective intoxication rating = 3.77 (SD = 2.64). LGBM, the best performing classifier, had 60 % accuracy using time features to detect subjective "high" (Area Under the Curve [AUC] = 0.82). Combining smartphone sensor data with time features improved model performance: 90 % accuracy (AUC = 0.98). Important smartphone features to detect subjective cannabis intoxication included travel (GPS) and movement (accelerometer).

CONCLUSIONS

This proof-of-concept study indicates the feasibility of using phone sensors to detect subjective cannabis intoxication in the natural environment, with potential implications for triggering just-in-time interventions.