Affiliation:
1. Institute of Information Systems, University of Applied Sciences Hof, Hof, Germany
2. Institute of Medical Psychology and Medical Sociology, University of Rostock, Rostock, Germany
3. Headache Center Frankfurt, Frankfurt, Germany
Abstract
Background: The aim of this work is to analyze reports of migraine attacks collected online in the citizen science project CLUE with respect to gender- and migraine type-specific differences in drug effectiveness and pain perception. Citizen science project data collection opens the possibility to examine these differences based on a large number of individual attacks instead of a simple survey of patients. Methods: One thousand three hundred and ninety four participants reported 47,274 migraine attacks via an online platform and smartphone apps. The reports contained information on the acute medications taken, the evaluation of their effect, and information on pain parameters such as pain intensity, origin, and localization. Chi-square tests were used to investigate whether the effect of acute medications and pain parameters differed when collated by gender and migraine type (migraine with and without aura). Results: Our participants rated the effectiveness of triptans as significantly better than that of ibuprofen. For triptans, significant differences in effectiveness were found when migraine types were distinguished, but no difference was found between genders. For ibuprofen, there were no differences between migraine types but significant differences between gender groups. Examination of pain parameters reveals differences between groups in pain intensity, pain origin, and pain location. The differences are statistically significant, but the effects are small. Conclusions: Despite some methodological limitations, web-based data collection is able to support findings from clinical trials in a real-world setting. Due to the high numbers of participants included and attacks reported, even small differences in medication efficacy and pain parameters between the groups considered can be demonstrated to be statistically significant.
Funder
Bundesministerium für Bildung und Forschung