Chandni Hindocha1,2,3, Erin A McClure4,5. 1. Clinical Psychopharmacology Unit, Department of Clinical, Educational and Health Psychology, University College London, Faculty of Brain Sciences, University College London, London, UK. 2. Translational Psychiatry Research Group, Research Department of Mental Health Neuroscience, Division of Psychiatry, Faculty of Brain Sciences, University College London, London, UK. 3. University College Hospital National Institute of Health Research (NIHR) Biomedical Research Centre, London, UK. 4. Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA. 5. Hollings Cancer Center, Medical University of South Carolina, Charleston, SC, USA.
Abstract
BACKGROUND: Nationally representative data of cannabis-tobacco co-use have shown that these substances are closely entwined and have significant adverse health consequences, although population-level harms of co-use are largely unknown. Current epidemiological research does not assess co-use in a manner that has yielded the necessary data to draw conclusions regarding health effects. This has given rise to a hidden population of co-users who go under-served. Therefore, this paper has two aims: (1) to review new challenges in the collection of co-use data due to rapidly changing regulations of cannabis and nicotine products and (2) to provide recommendations for the terminology and assessment of co-use. ARGUMENT: We argue that: (1) the prevalence of co-use is not being assessed accurately at a population level and (2) changes in legalization have created novel challenges, but without proper monitoring the impact on co-use will go undetected. We propose a three-level tiered set of recommendations for co-use assessments, which includes assessments of cannabis, tobacco and co-use metrics ranging from least burdensome (self-report of co-administered products) to most burdensome (assays, event-level data). CONCLUSIONS: We propose that clinical studies begin to incorporate cannabis-tobacco co-use assessments to justify better their inclusion in clinical trials and national surveillance surveys. Integration of co-use assessments will aid in understanding the true impact on co-use of the changing cannabis and tobacco/nicotine regulatory environments. Co-use is prevalent and problematic, and the ability to make conclusions about its health outcomes is hindered by lack of nuance in data collection. If you do not measure it, you cannot manage it.
BACKGROUND: Nationally representative data of cannabis-tobacco co-use have shown that these substances are closely entwined and have significant adverse health consequences, although population-level harms of co-use are largely unknown. Current epidemiological research does not assess co-use in a manner that has yielded the necessary data to draw conclusions regarding health effects. This has given rise to a hidden population of co-users who go under-served. Therefore, this paper has two aims: (1) to review new challenges in the collection of co-use data due to rapidly changing regulations of cannabis and nicotine products and (2) to provide recommendations for the terminology and assessment of co-use. ARGUMENT: We argue that: (1) the prevalence of co-use is not being assessed accurately at a population level and (2) changes in legalization have created novel challenges, but without proper monitoring the impact on co-use will go undetected. We propose a three-level tiered set of recommendations for co-use assessments, which includes assessments of cannabis, tobacco and co-use metrics ranging from least burdensome (self-report of co-administered products) to most burdensome (assays, event-level data). CONCLUSIONS: We propose that clinical studies begin to incorporate cannabis-tobacco co-use assessments to justify better their inclusion in clinical trials and national surveillance surveys. Integration of co-use assessments will aid in understanding the true impact on co-use of the changing cannabis and tobacco/nicotine regulatory environments. Co-use is prevalent and problematic, and the ability to make conclusions about its health outcomes is hindered by lack of nuance in data collection. If you do not measure it, you cannot manage it.
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