Mining social media data on marijuana use for Post Traumatic Stress Disorder

BackgroundWe seek to evaluate factors that could potentially impact the public's attitudes to PTSD related marijuana use on Twitter. MethodsWe collected tweets that contained the PTSD and Post Trauma Stress Disorder from August 1, 2015 to April 15, 2016 (n=1,253,872 tweets). A Nave Bayes model was constructed to classify tweets into two opinion polarities (support vs. neutral/against marijuana use for PTSD). ResultsThe marijuana related tweets were predominated by the supporting opinions (89.6%). The public opinions about marijuana use for PTSD on Twitter were significantly associated with state-level legislation. States that legalized medical and recreational marijuana use had the highest prevalence of support tweets (1.30.6), followed by the states that legalized medical but not recreational use (0.50.3) and the states that had no laws legalizing marijuana (0.20.1, p<0.0001). A higher prevalence of support tweets was associated with states with a lower proportion of youth (r=0.35, p=0.01) and a higher education rate (r=0.38, p=0.006). ConclusionTwitter data suggest a proliferation of supporting marijuana use for PTSD treatments, especially in the states that legalized medical and/or recreational use of marijuana. We found a proliferation of PTSD tweets that support marijuana use on Twitter.The prevalence of supporting marijuana use was correlated with state legal statues.Age, education and income were associated with the prevalence of support tweets.Educational campaigns on adverse effects of marijuana use are critically needed.

[1]  M. J. Mcdermott,et al.  Marijuana dependence moderates the effect of posttraumatic stress disorder on trauma cue reactivity in substance dependent patients. , 2016, Drug and alcohol dependence.

[2]  Hongying Dai,et al.  Mining social media data for opinion polarities about electronic cigarettes , 2016, Tobacco Control.

[3]  Melissa J. Krauss,et al.  Twitter chatter about marijuana. , 2015, The Journal of adolescent health : official publication of the Society for Adolescent Medicine.

[4]  Jianqiang Hao,et al.  Electronic cigarette and marijuana use among youth in the United States. , 2017, Addictive behaviors.

[5]  Wenli Zhang,et al.  Predicting Asthma-Related Emergency Department Visits Using Big Data , 2015, IEEE Journal of Biomedical and Health Informatics.

[6]  Marcel Salathé,et al.  Assessing Vaccination Sentiments with Online Social Media: Implications for Infectious Disease Dynamics and Control , 2011, PLoS Comput. Biol..

[7]  Melissa J. Krauss,et al.  "Hey Everyone, I'm Drunk." An Evaluation of Drinking-Related Twitter Chatter. , 2015, Journal of studies on alcohol and drugs.

[8]  S. Emery,et al.  A cross-sectional examination of marketing of electronic cigarettes on Twitter , 2014, Tobacco Control.

[9]  Ed H. Chi,et al.  Tweets from Justin Bieber's heart: the dynamics of the location field in user profiles , 2011, CHI.

[10]  Oded Susskind,et al.  The VA/DOD Clinical Practice Guideline for Management of Post-Traumatic Stress (update 2010): development and methodology. , 2012, Journal of rehabilitation research and development.

[11]  Michael J. Paul,et al.  National and Local Influenza Surveillance through Twitter: An Analysis of the 2012-2013 Influenza Epidemic , 2013, PloS one.

[12]  Louisa Degenhardt,et al.  Factors associated with the timing and onset of cannabis use and cannabis use disorder: results from the 2007 Australian National Survey of Mental Health and Well-Being. , 2014, Drug and alcohol review.

[13]  Samhsa The NSDUH Report: Substance Use and Mental Health Estimates from the 2013 National Survey on Drug Use and Health: Overview of Findings , 2014 .

[14]  Rudolf H. Moos,et al.  The impact of posttraumatic stress disorder on cannabis quit success , 2015, The American journal of drug and alcohol abuse.

[15]  K. Denecke,et al.  Social Media and Internet-Based Data in Global Systems for Public Health Surveillance: A Systematic Review , 2014, The Milbank quarterly.

[16]  Virgílio A. F. Almeida,et al.  Detecting Spammers on Twitter , 2010 .

[17]  Maeve Duggan,et al.  Social Media Update 2016 , 2016 .

[18]  D. Murthy Twitter: Social Communication in the Twitter Age , 2013 .

[19]  Anka A Vujanovic,et al.  Posttraumatic stress disorder and cannabis use characteristics among military veterans with cannabis dependence. , 2013, The American journal on addictions.

[20]  Raphael Mechoulam,et al.  Preliminary, Open-Label, Pilot Study of Add-On Oral Δ9-Tetrahydrocannabinol in Chronic Post-Traumatic Stress Disorder , 2014, Clinical Drug Investigation.

[21]  Francois R. Lamy,et al.  "Time for dabs": Analyzing Twitter data on marijuana concentrates across the U.S. , 2015, Drug and alcohol dependence.

[22]  Jerry M. Sollinger,et al.  THE INVISIBLE WOUNDS OF WAR: , 2020, Echoes of Trauma and Shame in German Families.

[23]  George A Fraser,et al.  The Use of a Synthetic Cannabinoid in the Management of Treatment‐Resistant Nightmares in Posttraumatic Stress Disorder (PTSD) , 2009, CNS neuroscience & therapeutics.

[24]  Terri Tanielian,et al.  Invisible Wounds of War. Psychological and Cognitive Injuries, Their Consequences, and Services to Assist Recovery , 2008 .

[25]  Jianqiang Hao,et al.  Geographic variations in electronic cigarette advertisements on Twitter in the United States , 2017, International Journal of Public Health.

[26]  Michael Höfler,et al.  What predicts incident use of cannabis and progression to abuse and dependence? A 4-year prospective examination of risk factors in a community sample of adolescents and young adults. , 2002, Drug and alcohol dependence.

[27]  B. Lewis,et al.  Methods of using real-time social media technologies for detection and remote monitoring of HIV outcomes. , 2014, Preventive medicine.