Priorities for a Comprehensive Post-Legalization Cannabis Research Agenda in Canada

Predictors of perceived symptom change with acute cannabis use for mental health conditions in a naturalistic sample: A machine learning approach

BACKGROUND

Despite limited clinical evidence of its efficacy, cannabis use has been commonly reported for the management of various mental health concerns in naturalistic field studies. The aim of the current study was to use machine learning methods to investigate predictors of perceived symptom change across various mental health symptoms with acute cannabis use in a large naturalistic sample.

METHODS

Data from 68,819 unique observations of cannabis use from 1307 individuals using cannabis to manage mental health symptoms were analyzed. Data were extracted from Strainprint®, a mobile app that allows users to monitor their cannabis use for therapeutic purposes. Machine learning models were employed to predict self-perceived symptom change after cannabis use, and SHapley Additive exPlanations (SHAP) value plots were used to assess feature importance of individual predictors in the model. Interaction effects of symptom severity pre-scores of anxiety, depression, insomnia, and gender were also examined.

RESULTS

The factors that were most strongly associated with perceived symptom change following acute cannabis use were pre-symptom severity, age, gender, and the ratio of CBD to THC. Further examination on the impact of baseline severity for the most commonly reported symptoms revealed distinct responses, with cannabis being reported to more likely benefit individuals with lower pre-symptom severity for depression, and higher pre-symptom severity for insomnia. Responses to cannabis use also differed between genders.

CONCLUSIONS

Findings from this study highlight the importance of several factors in predicting perceived symptom change with acute cannabis use for mental health symptom management. Mental health profiles and baseline symptom severity may play a large role in perceived responses to cannabis. Distinct response patterns were also noted across commonly reported mental health symptoms, emphasizing the need for placebo-controlled cannabis trials for specific user profiles.

The Use of Cannabinoids for Insomnia in Daily Life: Naturalistic Study

Background

Insomnia is a prevalent condition that presents itself at both the symptom and diagnostic levels. Although insomnia is one of the main reasons individuals seek medicinal cannabis, little is known about the profile of cannabinoid use or the perceived benefit of the use of cannabinoids in daily life.

Objective

We conducted a retrospective study of medicinal cannabis users to investigate the use profile and perceived efficacy of cannabinoids for the management of insomnia.

Methods

Data were collected using the Strainprint app, which allows medicinal cannabis users to log conditions and symptoms, track cannabis use, and monitor symptom severity pre- and postcannabis use. Our analyses examined 991 medicinal cannabis users with insomnia across 24,189 tracked cannabis use sessions. Sessions were analyzed, and both descriptive statistics and linear mixed-effects modeling were completed to examine use patterns and perceived efficacy.

Results

Overall, cannabinoids were perceived to be efficacious across all genders and ages, and no significant differences were found among product forms, ingestion methods, or gender groups. Although all strain categories were perceived as efficacious, predominant indica strains were found to reduce insomnia symptomology more than cannabidiol (CBD) strains (estimated mean difference 0.59, SE 0.11; 95% CI 0.36-0.81; adjusted P<.001) and predominant sativa strains (estimated mean difference 0.74, SE 0.16; 95% CI 0.43-1.06; adjusted P<.001). Indica hybrid strains also presented a greater reduction in insomnia symptomology than CBD strains (mean difference 0.52, SE 0.12; 95% CI 0.29-0.74; adjusted P<.001) and predominant sativa strains (mean difference 0.67, SE 0.16; 95% CI 0.34-1.00; adjusted P=.002).

Conclusions

Medicinal cannabis users perceive a significant improvement in insomnia with cannabinoid use, and this study suggests a possible advantage with the use of predominant indica strains compared with predominant sativa strains and exclusively CBD in this population. This study emphasizes the need for randomized placebo-controlled trials assessing the efficacy and safety profile of cannabinoids for the treatment of insomnia.