Real-Time Sharing and Expression of Migraine Headache Suffering on Twitter: A Cross-Sectional Infodemiology Study - Nascimento, Thiago D; DosSantos, Marcos F; Danciu, Theodora; DeBoer, Misty; van Holsbeeck, Hendrik; Lucas, Sarah R; Aiello, Christine; Khatib, Leen; Bender, MaryCatherine A; Zubieta, Jon-Kar; DaSilva, Alexandre F (JMIR Publications, 2014)
BackgroundAlthough population studies have greatly improved our understanding of migraine, they have relied on retrospective self-reports that are subject to memory error and experimenter-induced bias. Furthermore, these studies also lack specifics from the actual time that attacks were occurring, and how patients express and share their ongoing suffering. ObjectiveAs technology and language constantly evolve, so does the way we share our suffering. We sought to evaluate the infodemiology of self-reported migraine headache suffering on Twitter. MethodsTrained observers in an academic setting categorized the meaning of every single "migraine" tweet posted during seven consecutive days. The main outcome measures were prevalence, life-style impact, linguistic, and timeline of actual self-reported migraine headache suffering on Twitter. ResultsFrom a total of 21,741 migraine tweets collected, only 64.52% (14,028/21,741 collected tweets) were from users reporting their migraine headache attacks in real-time. The remainder of the posts were commercial, re-tweets, general discussion or third person's migraine, and metaphor. The gender distribution available for the actual migraine posts was 73.47% female (10,306/14,028), 17.40% males (2441/14,028), and 0.01% transgendered (2/14,028). The personal impact of migraine headache was immediate on mood (43.91%, 6159/14,028), productivity at work (3.46%, 486/14,028), social life (3.45%, 484/14,028), and school (2.78%, 390/14,028). The most common migraine descriptor was "Worst" (14.59%, 201/1378) and profanity, the "F-word" (5.3%, 73/1378). The majority of postings occurred in the United States (58.28%, 3413/5856), peaking on weekdays at 10:00h and then gradually again at 22:00h; the weekend had a later morning peak. ConclusionsTwitter proved to be a powerful source of knowledge for migraine research. The data in this study overlap large-scale epidemiological studies, avoiding memory bias and experimenter-induced error. Furthermore, linguistics of ongoing migraine reports on social media proved to be highly heterogeneous and colloquial in our study, suggesting that current pain questionnaires should undergo constant reformulations to keep up with modernization in the expression of pain suffering in our society. In summary, this study reveals the modern characteristics and broad impact of migraine headache suffering on patients' lives as it is spontaneously shared via social media.