ArticleJournal of clinical medicine2021
Areas of Interest and Attitudes towards the Pharmacological Treatment of Attention Deficit Hyperactivity Disorder: Thematic and Quantitative Analysis Using Twitter.
Article in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evaluating the evidence: a systematic review of reviews of the effectiveness and safety of digital interventions for ADHD.BMC psychiatry · 2025Pooled it
- Patterns of prescription stimulant initiation before and during the COVID-19 pandemic: a population-based time-series analysis.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2026Article
- Global Influence of Cannabis Legalization on Social Media Discourse: Mixed Methods Study.JMIR infodemiology · 2025Article
- Exploring Pain on Social Media: Observational Study on Perceptions and Discussions of Chronic Pain Conditions.JMIR infodemiology · 2025Observational
- Analysis of User-Generated Posts on Social Media of Adjuvant Analgesics: A Machine Learning Study.International journal of medical sciences · 2025Article
- Regional insights on tobacco-related tweets: unveiling user opinions and usage patterns.Frontiers in public health · 2024Article
- Exploring Perceptions About Paracetamol, Tramadol, and Codeine on Twitter Using Machine Learning: Quantitative and Qualitative Observational Study.Journal of medical Internet research · 2023Observational
- Using Twitter Data Analysis to Understand the Perceptions, Beliefs, and Attitudes about Pharmacotherapy Used in Rheumatology: An Observational Study.Healthcare (Basel, Switzerland) · 2023Article
- Assessment of beliefs and attitudes about electroconvulsive therapy posted on Twitter: An observational study.European psychiatry : the journal of the Association of European Psychiatrists · 2023Observational
- Areas of Interest and Social Consideration of Antidepressants on English Tweets: A Natural Language Processing Classification Study.Journal of personalized medicine · 2022Article
- Analyzing Psychotherapy on Twitter: An 11-Year Analysis of Tweets From Major U.S. Media Outlets.Frontiers in psychiatry · 2022Article
- Assessment of Antipsychotic Medications on Social Media: Machine Learning Study.Frontiers in psychiatry · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
We focused on tweets containing hashtags related to ADHD pharmacotherapy between 20 September and 31 October 2019. Tweets were 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. We created a dataset of 6568 tweets: 4949 (75.4%) related to stimulants, 605 (9.2%) to non-stimulants and 1014 (15.4%) to alpha-2 agonists. Next, we manually analyzed 1810 tweets. 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. 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 agonist-related tweets accumulating the highest proportion of positive consideration. We found the highest percentages of tweets with scientific links in those posts related to alpha-2 agonists. Stimulant-related tweets obtained the highest proportion 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.