Objective: Opioid use has reached an epidemic proportion in Canada and the United States that is mostly attributed to excess availability of prescribed opioids for pain. This excess in opioid use led to an increase in the prevalence of opioid use disorder (OUD) requiring treatment. The most common treatment recommendations include medication-assisted treatment (MAT) combined with psychosocial interventions. Clinical trials investigating the effectiveness of MAT, however, have a limited focus on effectiveness measures that overlook patient-important outcomes. Despite MAT, patients with OUD continue to suffer negative consequences of opioid use. Patient goals and personalized medicine are overlooked in clinical trials and guidelines, thus missing an opportunity to improve prognosis of OUD by considering precision medicine in addiction trials. Methods: In this mixed-methods study, patients with OUD receiving MAT (n=2,031, mean age 39.1 years [SD 10.7], 44% female) were interviewed to identify patient goals for MAT. Results: The most frequently reported patient-important outcomes were to stop treatment (39%) and to avoid all drugs (25%). Conclusion: These results are inconsistent with treatment recommendations and trial outcome measures. We discuss theses inconsistencies and make recommendations to incorporate these outcomes to achieve patient-centered and personalized treatment strategies.

Background: The rapid outbreak of Coronavirus diseases (COVID-19) originating in Wuhan, China, and the subsequent declaration of a state of “pandemic” on March 11, 2020 has necessitated a widespread global response to manage and control the transmission, spread and impact of COVID-19. Mobile technology has been leveraged in a number of ways to control the spread of COVID-19, including to support knowledge translation. Mobile applications are accessible, acceptable, easily adopted, and have the ability to support social distancing efforts. The following review assesses the mobile applications currently available to address COVID-19 and seeks existing studies in the literature that evaluate such applications. Methods: 3 databases (Embase, Web of Science and PubMed), 2 application stores (GooglePlay and Apple’s App Store) and google search engine were searched from inception until April 05, 2020 using key words and search strings to identify relevant apps and/or literature. Reviews of the obtained results were examined by two reviewers in double-blind nature and assessed for inclusion or exclusion. Results: 36 studies, 72 websites and 312 mobile-based applications were identified through searches. 14 applications met the inclusion criteria and were analyzed. Additional eHealth tools identified through the search strategy were considered for supplemental analysis (including online dashboards and applications not available through application stores).Conclusion: This review provides a brief assessment of the goals of applications addressing COVID-19, the types of approaches being used by these applications, and draws conclusions on the needs not being met by such application-based interventions. Innovation and collaboration between government, healthcare organizations and application developers is needed to address the identified gaps and facilitate the successful harnessing of mobile applications in the management of COVID-19.

Background With the increase in cannabis use rates, cannabis use disorder is being reported as one of the most common drug use disorders globally. Cannabis use has several known physical, psychological, and social adverse events, such as altered judgement, poor educational outcomes, and respiratory symptoms. The propensity for taking cannabis and the development of a cannabis use disorder may be genetically influenced for some individuals. Heritability estimates suggest a genetic basis for cannabis use, and several genome-wide association studies (GWASs) have identified possible regions of association, albeit with inconsistent findings. This systematic review aims to summarize the findings from GWASs investigating cannabis use and cannabis use disorder. Methods This systematic review incorporates articles that have performed a GWAS investigating cannabis use or cannabis use disorder. MEDLINE, Web of Science, EMBASE, CINAHL, GWAS Catalog, GWAS Central, and NIH Database of Genotype and Phenotype were searched using a comprehensive search strategy. All studies were screened in duplicate, and the quality of evidence was assessed using the quality of genetic association studies (Q-Genie) tool. All studies underwent qualitative synthesis; however, quantitative analysis was not feasible. Results Our search identified 5984 articles. Six studies met our eligibility criteria and were included in this review. All six studies reported results that met our significance threshold of p ≤ 1.0 × 10–7. In total 96 genetic variants were identified. While meta-analysis was not possible, this review identified the following genes, ANKFN1, INTS7, PI4K2B, CSMD1, CST7, ACSS1, and SCN9A, to be associated with cannabis use. These regions were previously reported in different mental health conditions, however not in relation to cannabis use. Conclusion This systematic review summarized GWAS findings within the field of cannabis research. While a meta-analysis was not possible, the summary of findings serves to inform future candidate gene studies and replication efforts. Systematic Review Registration PROSPERO CRD42020176016.

BackgroundCannabis is the most commonly used substance among patients in methadone maintenance treatment (MMT) for opioid use disorder. Current treatment programmes neither screen nor manage cannabis use. The recent legalisation of cannabis in Canada incites consideration into how this may affect the current opioid crisis.AimsInvestigate the health status of cannabis users in MMT.MethodPatients were recruited from addiction clinics in Ontario, Canada. Regression analyses were used to assess the association between adverse health conditions and cannabis use. Further analyses were used to assess sex differences and heaviness of cannabis use.ResultsWe included 672 patients (49.9% cannabis users). Cannabis users were more likely to consume alcohol (odds ratio 1.46, 95% CI 1.04–2.06, P = 0.029) and have anxiety disorders (odds ratio 1.75, 95% CI 1.02–3.02, P = 0.043), but were less likely to use heroin (odds ratio 0.45, 95% CI 0.24–0.86, P = 0.016). There was no association between cannabis use and pain (odds ratio 0.98, 95% CI 0.94–1.03, P = 0.463). A significant association was seen between alcohol and cannabis use in women (odds ratio 1.79, 95% CI 1.06–3.02, P = 0.028), and anxiety disorders and cannabis use in men (odds ratio 2.59, 95% CI 1.21–5.53, P = 0.014). Heaviness of cannabis use was not associated with health outcomes.ConclusionsOur results suggest that cannabis use is common and associated with psychiatric comorbidities and substance use among patients in MMT, advocating for screening of cannabis use in this population.Declaration of interestNone.

Background The rapid outbreak of Coronavirus diseases (COVID-19) originating in Wuhan, China, and the subsequent declaration of a state of “pandemic” on March 11, 2020 has necessitated a widespread global response to manage and control the transmission, spread and impact of COVID-19. Mobile technology has been leveraged in a number of ways to control the spread of COVID-19, including to support knowledge translation. Mobile applications are accessible, acceptable, easily adopted, and have the ability to support social distancing efforts. The following review assesses the mobile applications currently available to address COVID-19 and seeks existing studies in the literature that evaluate such applications. Methods 3 databases (Embase, Web of Science and PubMed), 2 application stores (GooglePlay and Apple’s App Store) and google search engine were searched from inception until April 05th 2020 using key words and search strings to identify relevant apps and/or literature. Reviews of the obtained results were examined by two reviewers in double-blind nature and assessed for inclusion or exclusion. Results 36 studies, 72 websites and 312 mobile-based applications were identified through searches. 14 applications met the inclusion criteria and were analyzed. Additional eHealth tools identified through the search strategy were considered for supplemental analysis (including online dashboards and applications not available through application stores). Conclusion This review provides a brief assessment of the goals of applications addressing COVID-19, the types of approaches being used by these applications, and draws conclusions on the needs not being met by such application-based interventions. Innovation and collaboration between government, healthcare organizations and application developers is needed to address the identified gaps and facilitate the successful harnessing of mobile applications in the management of COVID-19.