Francois R Lamy1, Raminta Daniulaityte2, Ramzi W Nahhas3, Monica J Barratt4, Alan G Smith5, Amit Sheth5, Silvia S Martins6, Edward W Boyer7, Robert G Carlson2. 1. Center for Interventions, Treatment, and Addictions Research, Department of Population and Public Health Sciences, Wright State University, Dayton, OH, United States; Ohio Center of Excellence in Knowledge-enabled Computing, Department of Computer Science and Engineering, Wright State University, Dayton, OH, United States. Electronic address: francois.lamy@wright.edu. 2. Center for Interventions, Treatment, and Addictions Research, Department of Population and Public Health Sciences, Wright State University, Dayton, OH, United States; Ohio Center of Excellence in Knowledge-enabled Computing, Department of Computer Science and Engineering, Wright State University, Dayton, OH, United States. 3. Department of Population and Public Health Sciences, Wright State University, Dayton, OH, United States; Department of Psychiatry, Wright State University, Dayton, OH, United States. 4. Drug Policy Modelling Program, National Drug and Alcohol Research Centre, UNSW Australia; National Drug Research Institute, Faculty of Health Sciences, Curtin University, Australia; Centre of Population Health, Burnet Institute, Australia. 5. Ohio Center of Excellence in Knowledge-enabled Computing, Department of Computer Science and Engineering, Wright State University, Dayton, OH, United States. 6. Department of Epidemiology, Columbia University, New York, NY, United States. 7. Brigham and Women's Hospital, Harvard Medical School, MA, United States.
Abstract
BACKGROUND: Synthetic Cannabinoid Receptor Agonists (SCRA), also known as "K2" or "Spice," have drawn considerable attention due to their potential of abuse and harmful consequences. More research is needed to understand user experiences of SCRA-related effects. We use semi-automated information processing techniques through eDrugTrends platform to examine SCRA-related effects and their variations through a longitudinal content analysis of web-forum data. METHOD: English language posts from three drug-focused web-forums were extracted and analyzed between January 1st 2008 and September 30th 2015. Search terms are based on the Drug Use Ontology (DAO) created for this study (189 SCRA-related and 501 effect-related terms). EDrugTrends NLP-based text processing tools were used to extract posts mentioning SCRA and their effects. Generalized linear regression was used to fit restricted cubic spline functions of time to test whether the proportion of drug-related posts that mention SCRA (and no other drug) and the proportion of these "SCRA-only" posts that mention SCRA effects have changed over time, with an adjustment for multiple testing. RESULTS: 19,052 SCRA-related posts (Bluelight (n=2782), Forum A (n=3882), and Forum B (n=12,388)) posted by 2543 international users were extracted. The most frequently mentioned effects were "getting high" (44.0%), "hallucinations" (10.8%), and "anxiety" (10.2%). The frequency of SCRA-only posts declined steadily over the study period. The proportions of SCRA-only posts mentioning positive effects (e.g., "High" and "Euphoria") steadily decreased, while the proportions of SCRA-only posts mentioning negative effects (e.g., "Anxiety," 'Nausea," "Overdose") increased over the same period. CONCLUSION: This study's findings indicate that the proportion of negative effects mentioned in web forum posts and linked to SCRA has increased over time, suggesting that recent generations of SCRA generate more harms. This is also one of the first studies to conduct automated content analysis of web forum data related to illicit drug use.
BACKGROUND: Synthetic Cannabinoid Receptor Agonists (SCRA), also known as "K2" or "Spice," have drawn considerable attention due to their potential of abuse and harmful consequences. More research is needed to understand user experiences of SCRA-related effects. We use semi-automated information processing techniques through eDrugTrends platform to examine SCRA-related effects and their variations through a longitudinal content analysis of web-forum data. METHOD: English language posts from three drug-focused web-forums were extracted and analyzed between January 1st 2008 and September 30th 2015. Search terms are based on the Drug Use Ontology (DAO) created for this study (189 SCRA-related and 501 effect-related terms). EDrugTrends NLP-based text processing tools were used to extract posts mentioning SCRA and their effects. Generalized linear regression was used to fit restricted cubic spline functions of time to test whether the proportion of drug-related posts that mention SCRA (and no other drug) and the proportion of these "SCRA-only" posts that mention SCRA effects have changed over time, with an adjustment for multiple testing. RESULTS: 19,052 SCRA-related posts (Bluelight (n=2782), Forum A (n=3882), and Forum B (n=12,388)) posted by 2543 international users were extracted. The most frequently mentioned effects were "getting high" (44.0%), "hallucinations" (10.8%), and "anxiety" (10.2%). The frequency of SCRA-only posts declined steadily over the study period. The proportions of SCRA-only posts mentioning positive effects (e.g., "High" and "Euphoria") steadily decreased, while the proportions of SCRA-only posts mentioning negative effects (e.g., "Anxiety," 'Nausea," "Overdose") increased over the same period. CONCLUSION: This study's findings indicate that the proportion of negative effects mentioned in web forum posts and linked to SCRA has increased over time, suggesting that recent generations of SCRA generate more harms. This is also one of the first studies to conduct automated content analysis of web forum data related to illicit drug use.
Authors: Andrej Grigoryev; Sergey Savchuk; Aleksandra Melnik; Natal'ja Moskaleva; Jurij Dzhurko; Mihail Ershov; Aleksandr Nosyrev; Aleksandr Vedenin; Boris Izotov; Irina Zabirova; Vladimir Rozhanets Journal: J Chromatogr B Analyt Technol Biomed Life Sci Date: 2011-03-26 Impact factor: 3.205
Authors: Usha Lokala; Francois R Lamy; Raminta Daniulaityte; Amit Sheth; Ramzi W Nahhas; Jason I Roden; Shweta Yadav; Robert G Carlson Journal: Comput Math Organ Theory Date: 2018-10-25 Impact factor: 2.023
Authors: Francois R Lamy; Raminta Daniulaityte; Monica J Barratt; Usha Lokala; Amit Sheth; Robert G Carlson Journal: Drug Alcohol Depend Date: 2020-06-12 Impact factor: 4.492