Development of a Migraine Trigger Measurement System Using Surprisal

Background: Individuals with migraine continually seek to understand the causes, or “triggers,” of their attacks by considering variables such as foods, weather, stress, mood, behaviors, and sleep. Information‐theoretic measures such as “surprisal” offer a novel approach to quantifying the unpredictability and diversity of trigger exposures on a single standardized scale. Objectives: This study aimed to quantify the variability of migraine trigger exposures using surprisal and entropy measures and to evaluate their potential for stratifying individuals based on exposure patterns. Methods: This longitudinal daily diary study included participants with migraine who completed twice‐daily electronic diaries reporting exposures to a range of potential headache triggers. Surprisal values were calculated to quantify the unexpectedness of individual trigger exposures, while entropy values captured overall variability in trigger domains such as sleep, mood, daily stressors, dietary behaviors, and environmental encounters. Results: N = 109 individuals self‐reported 187 different headache triggers for up to 28 days, resulting in 540,876 trigger measurements. Participants exhibited substantial heterogeneity in surprisal and entropy values across trigger domains, reflecting diverse patterns of exposure both within and between individuals. Morning measures of sleep and mood showed moderate entropy, while evening measures of dietary patterns and environmental encounters exhibited greater variability. A few principal components explained most of the variability in surprisal values, suggesting these dimensions might characterize trigger exposure across variables. Conclusions: These findings reinforce the utility of surprisal measures for capturing nuanced patterns in the vast array of headache trigger data and support their potential as a measurement tool for understanding trigger exposures.