Areas of Interest and Attitudes Towards the Pharmacological Treatment of Attention Deficit Hyperactivity Disorder: Thematic and Quantitative Analysis Using Twitter (Preprint)

BACKGROUND The treatment of ADHD is complex and may involve behavioral, psychological and educational interventions, as well as medication. Different pharmacological treatments have shown efficacy in reducing ADHD symptoms and improving daily functioning. Analysis of tweets has become a tool for understanding perceptions by the general population on health issues. OBJECTIVE Investigate the gap existing between its extensive scientific support and the lack of widespread prescription and adherence. We hypothesize that such a discrepancy may be influenced by a lack of knowledge of the positive effects among the population. Thus, we find it interesting and worthwhile to assess opinions and social interest on ADHD pharmacotherapy in Twitter. METHODS In this observational quantitative and qualitative study we focused on tweets containing hashtags related to ADHD pharmacotherapy between September 20th and October 31st 2019. Tweets were first classified as to whether they described medical issues or not. Tweets with medical content were classified according to the topic they referred to: side effects, efficacy, or adherence. Furthermore, we classified any links included within a tweet as either scientific or non-scientific. RESULTS We collected a total of 118,388 tweets, 111,820 of which were excluded according to the criteria of the study. This process led to the creation of a more concise dataset of 6,568 tweets: 4,949 (75.4%) related to stimulants, 605 (9.2%) to non-stimulants and 1,014 (15.4%) to alpha-2-agonists. Next, we manually analyzed 1,810 tweets: 1,000 tweets related to stimulants, 303 to non-stimulants and 507 to alpha-agonists. In the end, 481 (48%) of the tweets in the stimulant group, 218 (71.9%) in the non-stimulant group and 162 (31.9%) in the alpha-agonist group were considered classifiable according to the codebook. Stimulants accumulated the majority of tweets. Notably, the content that generated the highest frequency of tweets was that related to treatment efficacy, with alpha-2-agonists related tweets accumulating the highest proportion of positive consideration. We found the highest percentages of tweets with scientific links in those posts related alpha-2-agonists. CONCLUSIONS Stimulants related tweets obtained the highest probability of likes and were the most disseminated within the Twitter community. Understanding the public view of these medications is necessary to design promotional strategies aimed at the appropriate population.