Published on in Vol 15, No 4 (2013): April

Tweaking and Tweeting: Exploring Twitter for Nonmedical Use of a Psychostimulant Drug (Adderall) Among College Students

Tweaking and Tweeting: Exploring Twitter for Nonmedical Use of a Psychostimulant Drug (Adderall) Among College Students

Tweaking and Tweeting: Exploring Twitter for Nonmedical Use of a Psychostimulant Drug (Adderall) Among College Students

Journals

  1. Alvaro N, Conway M, Doan S, Lofi C, Overington J, Collier N. Crowdsourcing Twitter annotations to identify first-hand experiences of prescription drug use. Journal of Biomedical Informatics 2015;58:280 View
  2. Kim Y, Kim J. Using photos for public health communication: A computational analysis of the Centers for Disease Control and Prevention Instagram photos and public responses. Health Informatics Journal 2020;26(3):2159 View
  3. Cavazos-Rehg P, Sowles S, Krauss M, Agbonavbare V, Grucza R, Bierut L. A content analysis of tweets about high-potency marijuana. Drug and Alcohol Dependence 2016;166:100 View
  4. Sarker A. A customizable pipeline for social media text normalization. Social Network Analysis and Mining 2017;7(1) View
  5. Tofighi B, Aphinyanaphongs Y, Marini C, Ghassemlou S, Nayebvali P, Metzger I, Raghunath A, Thomas S. Detecting illicit opioid content on Twitter. Drug and Alcohol Review 2020;39(3):205 View
  6. Witcraft S, Veronica Smith C, Ann Pollard M, Dixon L. Is Greek affiliation a prescription for drug abuse? Examining misuse of prescription stimulants and downers in high school and college. Journal of American College Health 2020;68(7):678 View
  7. Kagashe I, Yan Z, Suheryani I. Enhancing Seasonal Influenza Surveillance: Topic Analysis of Widely Used Medicinal Drugs Using Twitter Data. Journal of Medical Internet Research 2017;19(9):e315 View
  8. Thompson L, Rivara F, Whitehill J. Prevalence of Marijuana-Related Traffic on Twitter, 2012–2013: A Content Analysis. Cyberpsychology, Behavior, and Social Networking 2015;18(6):311 View
  9. Fisher B, Witherow K, Kruis N. Book Review: Nancy E. Marion, Drug Policy and the Criminal Justice System. Criminal Justice Policy Review 2020;31(5):783 View
  10. Alvaro N, Miyao Y, Collier N. TwiMed: Twitter and PubMed Comparable Corpus of Drugs, Diseases, Symptoms, and Their Relations. JMIR Public Health and Surveillance 2017;3(2):e24 View
  11. Sarker A, Gonzalez-Hernandez G, Ruan Y, Perrone J. Machine Learning and Natural Language Processing for Geolocation-Centric Monitoring and Characterization of Opioid-Related Social Media Chatter. JAMA Network Open 2019;2(11):e1914672 View
  12. Netherland J, Hansen H. The War on Drugs That Wasn’t: Wasted Whiteness, “Dirty Doctors,” and Race in Media Coverage of Prescription Opioid Misuse. Culture, Medicine, and Psychiatry 2016;40(4):664 View
  13. Mackey T, Liang B, Strathdee S. Digital Social Media, Youth, and Nonmedical Use of Prescription Drugs: The Need for Reform. Journal of Medical Internet Research 2013;15(7):e143 View
  14. Tse C, Bridges S, Srinivasan D, Cheng B. Social Media in Adolescent Health Literacy Education: A Pilot Study. JMIR Research Protocols 2015;4(1):e18 View
  15. Aikins R, Zhang X, McCabe S. Academic Doping: Institutional Policies Regarding Nonmedical use of Prescription Stimulants in U.S. Higher Education. Journal of Academic Ethics 2017;15(3):229 View
  16. Cuomo R, Cai M, Shah N, Li J, Chen W, Obradovich N, Mackey T. Characterising communities impacted by the 2015 Indiana HIV outbreak: A big data analysis of social media messages associated with HIV and substance abuse. Drug and Alcohol Review 2020;39(7):908 View
  17. Fogel J, Travis Y. Twitter use related to reality television characters: Association with increased marijuana use. Journal of Organizational Computing and Electronic Commerce 2017;27(2):152 View
  18. Watson G, Arcona A, Antonuccio D. The ADHD Drug Abuse Crisis on American College Campuses. Ethical Human Psychology and Psychiatry 2015;17(1):5 View
  19. Schootman M, Nelson E, Werner K, Shacham E, Elliott M, Ratnapradipa K, Lian M, McVay A. Emerging technologies to measure neighborhood conditions in public health: implications for interventions and next steps. International Journal of Health Geographics 2016;15(1) View
  20. Barnes M, Hanson C, Giraud-Carrier C. The Case for Computational Health Science. Journal of Healthcare Informatics Research 2018;2(1-2):99 View
  21. Kim S, Marsch L, Hancock J, Das A. Scaling Up Research on Drug Abuse and Addiction Through Social Media Big Data. Journal of Medical Internet Research 2017;19(10):e353 View
  22. Hanson C, Cannon B, Burton S, Giraud-Carrier C. An Exploration of Social Circles and Prescription Drug Abuse Through Twitter. Journal of Medical Internet Research 2013;15(9):e189 View
  23. Anton C. Adverse drug reactions and social media. Adverse Drug Reaction Bulletin 2014;286(1):1103 View
  24. Alhabash S, VanDam C, Tan P, Smith S, Viken G, Kanver D, Tian L, Figueira L. 140 Characters of Intoxication: Exploring the Prevalence of Alcohol-Related Tweets and Predicting Their Virality. SAGE Open 2018;8(4):215824401880313 View
  25. Golder S, Norman G, Loke Y. Systematic review on the prevalence, frequency and comparative value of adverse events data in social media. British Journal of Clinical Pharmacology 2015;80(4):878 View
  26. Dal Moro F. Online Survey on Twitter: A Urological Experience. Journal of Medical Internet Research 2013;15(10):e238 View
  27. Lardon J, Abdellaoui R, Bellet F, Asfari H, Souvignet J, Texier N, Jaulent M, Beyens M, Burgun A, Bousquet C. Adverse Drug Reaction Identification and Extraction in Social Media: A Scoping Review. Journal of Medical Internet Research 2015;17(7):e171 View
  28. Ashford R, Curtis B. Commentary on Cohn and Colleagues: Discussions of Alcohol Use in an Online Social Network for Smoking Cessation: Analysis of Topics, Sentiment, and Social Network Centrality (ACER , 2019). Alcoholism: Clinical and Experimental Research 2019;43(3):401 View
  29. Raghupathi V, Fogel J. Facebook advertisements and purchase of weight-loss products. Journal of Medical Marketing: Device, Diagnostic and Pharmaceutical Marketing 2013;13(4):201 View
  30. Harrison A, Harrison K, Armstrong I. Discriminating malingered attention Deficit Hyperactivity Disorder from genuine symptom reporting using novel Personality Assessment Inventory validity measures. Applied Neuropsychology: Adult 2019:1 View
  31. Shutler L, Nelson L, Portelli I, Blachford C, Perrone J. Drug Use in the Twittersphere: A Qualitative Contextual Analysis of Tweets About Prescription Drugs. Journal of Addictive Diseases 2015;34(4):303 View
  32. Bartlett C, Wurtz R. Twitter and Public Health. Journal of Public Health Management and Practice 2015;21(4):375 View
  33. Kalyanam J, Mackey T. A Review of Digital Surveillance Methods and Approaches to Combat Prescription Drug Abuse. Current Addiction Reports 2017;4(4):397 View
  34. Finfgeld-Connett D. Twitter and Health Science Research. Western Journal of Nursing Research 2015;37(10):1269 View
  35. Hockenhull J, Wood D, Dargan P. The Availability of Modafinil and Methylphenidate Purchased from the Internet in the United Kingdom Without a Prescription. Substance Use & Misuse 2020;55(1):56 View
  36. Paul M, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1 View
  37. Braithwaite S, Giraud-Carrier C, West J, Barnes M, Hanson C. Validating Machine Learning Algorithms for Twitter Data Against Established Measures of Suicidality. JMIR Mental Health 2016;3(2):e21 View
  38. Vagwala M, Bicquelet A, Didziokaite G, Coomber R, Corrigan O, Singh I. Towards a Moral Ecology of Pharmacological Cognitive Enhancement in British Universities. Neuroethics 2017;10(3):389 View
  39. Chan B, Lopez A, Sarkar U, Hildt E. The Canary in the Coal Mine Tweets: Social Media Reveals Public Perceptions of Non-Medical Use of Opioids. PLOS ONE 2015;10(8):e0135072 View
  40. Michalak E, McBride S, Barnes S, Wood C, Khatri N, Balram Elliott N, Parikh S. Bipolar disorder research 2.0: Web technologies for research capacity and knowledge translation. Journal of Evaluation in Clinical Practice 2017;23(6):1144 View
  41. Cotter K, Smokowski P. Perceived Peer Delinquency and Externalizing Behavior Among Rural Youth: The Role of Descriptive Norms and Internalizing Symptoms. Journal of Youth and Adolescence 2016;45(3):520 View
  42. Daniulaityte R, Chen L, Lamy F, Carlson R, Thirunarayan K, Sheth A. “When ‘Bad’ is ‘Good’”: Identifying Personal Communication and Sentiment in Drug-Related Tweets. JMIR Public Health and Surveillance 2016;2(2):e162 View
  43. Ranney M, Genes N. Social media and healthcare quality improvement: a nascent field. BMJ Quality & Safety 2016;25(6):389 View
  44. Fogel J, King K. Perceived Realism and Twitter Use Are Associated with Increased Acceptance of Cosmetic Surgery among Those Watching Reality Television Cosmetic Surgery Programs. Plastic and Reconstructive Surgery 2014;134(2):233 View
  45. Fogel J, Zhuk A. Direct-to-consumer prescription medication advertisements and obtaining prescriptions with or without a doctor’s prescription. Health Marketing Quarterly 2019;36(3):220 View
  46. Kim M, Kim J, Kim S, Jeong J. Twitter Analysis of the Nonmedical Use and Side Effects of Methylphenidate: Machine Learning Study. Journal of Medical Internet Research 2020;22(2):e16466 View
  47. ElTayeby O, Eaglin T, Abdullah M, Burlinson D, Dou W, Yao L. A feasibility study on identifying drinking-related contents in Facebook through mining heterogeneous data. Health Informatics Journal 2019;25(4):1756 View
  48. Muralidhara S, Paul M. #Healthy Selfies: Exploration of Health Topics on Instagram. JMIR Public Health and Surveillance 2018;4(2):e10150 View
  49. O'Connor K, Sarker A, Perrone J, Gonzalez Hernandez G. Promoting Reproducible Research for Characterizing Nonmedical Use of Medications Through Data Annotation: Description of a Twitter Corpus and Guidelines. Journal of Medical Internet Research 2020;22(2):e15861 View
  50. Liu J, Ho M, Lu L, Xiao G. Recent Themes in Social Networking Service Research. PLOS ONE 2017;12(1):e0170293 View
  51. Li J, Xu Q, Shah N, Mackey T. A Machine Learning Approach for the Detection and Characterization of Illicit Drug Dealers on Instagram: Model Evaluation Study. Journal of Medical Internet Research 2019;21(6):e13803 View
  52. Carreiro S, Chai P, Carey J, Chapman B, Boyer E. Integrating Personalized Technology in Toxicology: Sensors, Smart Glass, and Social Media Applications in Toxicology Research. Journal of Medical Toxicology 2017;13(2):166 View
  53. Bevan J, Gomez R, Sparks L. Disclosures about important life events on Facebook: Relationships with stress and quality of life. Computers in Human Behavior 2014;39:246 View
  54. Sznitman S. Analysing Twitter as an Opportunity to Understand Substance Use. SSRN Electronic Journal 2015 View
  55. Simpson S, Adams N, Brugman C, Conners T. Detecting Novel and Emerging Drug Terms Using Natural Language Processing: A Social Media Corpus Study. JMIR Public Health and Surveillance 2018;4(1):e2 View
  56. Sequeira R, Gayen A, Ganguly N, Dandapat S, Chandra J. A Large-Scale Study of the Twitter Follower Network to Characterize the Spread of Prescription Drug Abuse Tweets. IEEE Transactions on Computational Social Systems 2019;6(6):1232 View
  57. Fogel J, Adnan M. Trust for pharmaceutical company direct-to-consumer prescription medication advertisements. Health Policy and Technology 2018;7(1):26 View
  58. Daniulaityte R, Nahhas R, Wijeratne S, Carlson R, Lamy F, Martins S, Boyer E, Smith G, Sheth A. “Time for dabs”: Analyzing Twitter data on marijuana concentrates across the U.S.. Drug and Alcohol Dependence 2015;155:307 View
  59. Sarker A, DeRoos A, Perrone J. Mining social media for prescription medication abuse monitoring: a review and proposal for a data-centric framework. Journal of the American Medical Informatics Association 2020;27(2):315 View
  60. Matsuzaka S, Knapp M. Anti-racism and substance use treatment: Addiction does not discriminate, but do we?. Journal of Ethnicity in Substance Abuse 2020;19(4):567 View
  61. Hu H, Phan N, Chun S, Geller J, Vo H, Ye X, Jin R, Ding K, Kenne D, Dou D. An insight analysis and detection of drug-abuse risk behavior on Twitter with self-taught deep learning. Computational Social Networks 2019;6(1) View
  62. Su Z, Mackert M, Li X, Han J, Crook B, Wyeth B. “Study Natural” without Drugs: An Exploratory Study of Theory-Guided and Tailored Health Campaign Interventions to Prevent Nonmedical Use of Prescription Stimulants in College Students. International Journal of Environmental Research and Public Health 2020;17(12):4421 View
  63. Yin Z, Fabbri D, Rosenbloom S, Malin B. A Scalable Framework to Detect Personal Health Mentions on Twitter. Journal of Medical Internet Research 2015;17(6):e138 View
  64. LaBelle S, Ball H, Weber K, White A, Hendry A. The Rethink campaign to reduce the normalization of prescription stimulant misuse on college campuses. Communication Quarterly 2020;68(1):1 View
  65. Thaikla K, Pinyopornpanish K, Jiraporncharoen W, Angkurawaranon C. Cannabis and Kratom online information in Thailand: Facebook trends 2015–2016. Substance Abuse Treatment, Prevention, and Policy 2018;13(1) View
  66. Thackeray R, Neiger B, Burton S, Thackeray C. Analysis of the Purpose of State Health Departments' Tweets: Information Sharing, Engagement, and Action. Journal of Medical Internet Research 2013;15(11):e255 View
  67. Chary M, Genes N, Giraud-Carrier C, Hanson C, Nelson L, Manini A. Epidemiology from Tweets: Estimating Misuse of Prescription Opioids in the USA from Social Media. Journal of Medical Toxicology 2017;13(4):278 View
  68. Lamy F, Daniulaityte R, Sheth A, Nahhas R, Martins S, Boyer E, Carlson R. “Those edibles hit hard”: Exploration of Twitter data on cannabis edibles in the U.S. Drug and Alcohol Dependence 2016;164:64 View
  69. Thackeray R, Burton S, Giraud-Carrier C, Rollins S, Draper C. Using Twitter for breast cancer prevention: an analysis of breast cancer awareness month. BMC Cancer 2013;13(1) View
  70. Fogel J, Shlivko A. Reality Television Programs Are Associated With Illegal Drug Use and Prescription Drug Misuse Among College Students. Substance Use & Misuse 2016;51(1):62 View
  71. Ranney M, Chang B, Freeman J, Norris B, Silverberg M, Choo E, Mycyk M. Tweet Now, See You In the ED Later? Examining the Association Between Alcohol-related Tweets and Emergency Care Visits. Academic Emergency Medicine 2016;23(7):831 View
  72. Huesch M, Chetlen A, Segel J, Schetter S. Frequencies of Private Mentions and Sharing of Mammography and Breast Cancer Terms on Facebook: A Pilot Study. Journal of Medical Internet Research 2017;19(6):e201 View
  73. Mackey T, Kalyanam J, Katsuki T, Lanckriet G. Twitter-Based Detection of Illegal Online Sale of Prescription Opioid. American Journal of Public Health 2017;107(12):1910 View
  74. Salimian P, Chunara R, Weitzman E. Averting the Perfect Storm: Addressing Youth Substance Use Risk From Social Media Use. Pediatric Annals 2014;43(10) View
  75. Conway M, O’Connor D. Social media, big data, and mental health: current advances and ethical implications. Current Opinion in Psychology 2016;9:77 View
  76. Lamy F, Daniulaityte R, Zatreh M, Nahhas R, Sheth A, Martins S, Boyer E, Carlson R. "You got to love rosin: Solventless dabs, pure, clean, natural medicine." Exploring Twitter data on emerging trends in Rosin Tech marijuana concentrates. Drug and Alcohol Dependence 2018;183:248 View
  77. Tricco A, Zarin W, Lillie E, Jeblee S, Warren R, Khan P, Robson R, Pham B, Hirst G, Straus S. Utility of social media and crowd-intelligence data for pharmacovigilance: a scoping review. BMC Medical Informatics and Decision Making 2018;18(1) View
  78. Kazemi D, Borsari B, Levine M, Dooley B. Systematic review of surveillance by social media platforms for illicit drug use. Journal of Public Health 2017;39(4):763 View
  79. Yang J, Tsou M, Jung C, Allen C, Spitzberg B, Gawron J, Han S. Social media analytics and research testbed (SMART): Exploring spatiotemporal patterns of human dynamics with geo-targeted social media messages. Big Data & Society 2016;3(1):205395171665291 View
  80. Mackey T, Nayyar G. Digital danger: a review of the global public health, patient safety and cybersecurity threats posed by illicit online pharmacies. British Medical Bulletin 2016;118(1):110 View
  81. McDermott H, Lane H, Alonso M. Working smart: the use of ‘cognitive enhancers’ by UK university students. Journal of Further and Higher Education 2021;45(2):270 View
  82. Harrison A, Armstrong I. Differences in performance on the test of variables of attention between credible vs. noncredible individuals being screened for attention deficit hyperactivity disorder. Applied Neuropsychology: Child 2020;9(4):314 View
  83. Sarker A, O’Connor K, Ginn R, Scotch M, Smith K, Malone D, Gonzalez G. Social Media Mining for Toxicovigilance: Automatic Monitoring of Prescription Medication Abuse from Twitter. Drug Safety 2016;39(3):231 View
  84. Kalyanam J, Katsuki T, R.G. Lanckriet G, Mackey T. Exploring trends of nonmedical use of prescription drugs and polydrug abuse in the Twittersphere using unsupervised machine learning. Addictive Behaviors 2017;65:289 View
  85. Katsuki T, Mackey T, Cuomo R. Establishing a Link Between Prescription Drug Abuse and Illicit Online Pharmacies: Analysis of Twitter Data. Journal of Medical Internet Research 2015;17(12):e280 View
  86. Schwab-Reese L, Hovdestad W, Tonmyr L, Fluke J. The potential use of social media and other internet-related data and communications for child maltreatment surveillance and epidemiological research: Scoping review and recommendations. Child Abuse & Neglect 2018;85:187 View
  87. Brandt S, Taverna E, Hallock R. A survey of nonmedical use of tranquilizers, stimulants, and pain relievers among college students: Patterns of use among users and factors related to abstinence in non-users. Drug and Alcohol Dependence 2014;143:272 View
  88. Kamiński M, Szymańska C, Nowak J. Whose Tweets on COVID-19 Gain the Most Attention: Celebrities, Political, or Scientific Authorities?. Cyberpsychology, Behavior, and Social Networking 2021;24(2):123 View
  89. van Draanen J, Tao H, Gupta S, Liu S. Geographic Differences in Cannabis Conversations on Twitter: Infodemiology Study. JMIR Public Health and Surveillance 2020;6(4):e18540 View
  90. Al-Garadi M, Yang Y, Cai H, Ruan Y, O’Connor K, Graciela G, Perrone J, Sarker A. Text classification models for the automatic detection of nonmedical prescription medication use from social media. BMC Medical Informatics and Decision Making 2021;21(1) View
  91. Kaur S, Kaul P, Zadeh P. Monitoring the Dynamics of Emotions during COVID-19 Using Twitter Data. Procedia Computer Science 2020;177:423 View
  92. Petersen M, Petersen I, Poulsen C, Nørgaard L. #studydrugs–Persuasive posting on Instagram. International Journal of Drug Policy 2021:103100 View
  93. Hockenhull J, Black J, Bletz A, Margolin Z, Olson R, Wood D, Dart R, Dargan P. An evaluation of online discussion relating to nonmedical use of prescription opioids within the UK. British Journal of Clinical Pharmacology 2021;87(4):1637 View
  94. Sharif S, Guirguis A, Fergus S, Schifano F. The Use and Impact of Cognitive Enhancers among University Students: A Systematic Review. Brain Sciences 2021;11(3):355 View
  95. Alvarez-Mon M, de Anta L, Llavero-Valero M, Lahera G, Ortega M, Soutullo C, Quintero J, Asunsolo del Barco A, Alvarez-Mon M. Areas of Interest and Attitudes towards the Pharmacological Treatment of Attention Deficit Hyperactivity Disorder: Thematic and Quantitative Analysis Using Twitter. Journal of Clinical Medicine 2021;10(12):2668 View

Books/Policy Documents

  1. Moreno M, Pumper M. The Wiley Handbook of Psychology, Technology, and Society. View
  2. Sevigny E, Fuleihan B. The Handbook of Drugs and Society. View
  3. An Z, McLaughlin M, Hou J, Nam Y, Hu C, Park M, Meng J. Social Computing and Social Media. View
  4. Hu H, Phan N, Geller J, Vo H, Manasi B, Huang X, Di Lorio S, Dinh T, Chun S. Computational Data and Social Networks. View
  5. Forlini C, Partridge B, Lucke J, Racine E. Handbook of Neuroethics. View
  6. Del Vigna F, Avvenuti M, Bacciu C, Deluca P, Petrocchi M, Marchetti A, Tesconi M. Advances in Intelligent Data Analysis XV. View
  7. Optican A, Cavazos-Rehg P. Child and Adolescent Psychiatry and the Media. View
  8. ElTayeby O, Eaglin T, Abdullah M, Burlinson D, Dou W, Yao L. Advances in Artificial Intelligence: From Theory to Practice. View
  9. Sevarino K, Shelby B. Psychiatry. View
  10. Wangia-Anderson V, Dua P. Health Professionals' Education in the Age of Clinical Information Systems, Mobile Computing and Social Networks. View
  11. Dempsey R. Chemically Modified Minds. View