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Impact of the COVID-19 Pandemic on the Evolution of Prevalence and Patterns of Cannabis Use among First-Year University Students in Spain-UniHcos Project.

Lorena Botella-JuanAmezcua-Prieto CMaria Morales Suárez-VarelaRamona Mateos-CamposCarlos Ayan PerezAntonio José Molina de la TorreRocío Ortiz-MoncadaSusana Redondo-MartínJuan AlguacilGemma Blázquez-AbellánMiguel Delgado-RodríguezJessica Alonso-MoleroTania Fernandez-Villa
Published in: International journal of environmental research and public health (2022)
Among university students there has been evidence that the COVID-19 pandemic increased their psychological distress, exacerbated by social restrictions. The main objective of this study was to explore the impact of the COVID-19 pandemic on the prevalence and patterns of cannabis use among university students, in contrast to previous trends since 2012. Data from 10,522 first-year university students (73.3% female, M age 19 (SD = 1.6)) from eleven Spanish universities collected between 2012 and May 2022 was analysed. Prevalences of cannabis use and their differences by sex were studied, as well as changes in patterns of use and its use for coping during the pandemic. It was found that during lockdown, all prevalence rates of cannabis use decreased in both sexes, showing no statistically significant differences and increasing again in the new normal period in both. Among regular cannabis users, 79.7% reported maintaining or increasing their cannabis use during the pandemic, and of these, half reported using cannabis to cope. Moreover, cannabis use in the usual household increased during the lockdown. These results show that although the overall prevalence of cannabis use was reduced during the lockdown, regular users tended to maintain or increase cannabis use. This could imply two different patterns of use among students, one social and occasional versus the other regular, providing new lines of research for prevention and the implementation of social policies.
Keyphrases
  • risk factors
  • healthcare
  • sars cov
  • mental health
  • coronavirus disease
  • public health
  • quality improvement
  • magnetic resonance
  • primary care
  • machine learning
  • computed tomography
  • big data
  • artificial intelligence