ArticleHeadache
Information theory and headache triggers.
Article in Headache. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- The impact of climatic factors on headache patterns: a 14-year time series analysis of cluster and tension-type headaches in primary care.Journal of oral & facial pain and headache · 2026Article
- Climatic sensitivity of migraine: a 14-year time series analysis of primary care consultations in Spain.Journal of oral & facial pain and headache · 2026Article
- Information-Theoretic Trigger Surprisal and Future Headache Activity.JAMA network open · 2025Article
- Enhancing Migraine Trigger Surprisal Predictions: A Bayesian Approach to Establishing Prospective Expectations.Entropy (Basel, Switzerland) · 2025Article
- Association Between Trigger Surprisal and Tension-Type Headache Attacks.Medical research archives · 2025Article
- Evaluating Migraine Trigger Surprisal: Associations with Migraine Activity.medRxiv : the preprint server for health sciences · 2025Article
- Pain medication beliefs in individuals with headache.Headache · 2024Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesThis secondary analysis evaluated the information content exhibited by various measurement strategies of commonly perceived causes, or "triggers," of headache attacks.
backgroundWhen evaluating triggers of primary headache attacks, the variation observed in trigger candidates must be measured to compare against the covariation in headache activity. Given the numerous strategies that could be used to measure and record headache trigger variables, it is useful to consider the information contained in these measurements.
methodsUsing previously collected data from cohort and cross-sectional studies, online data sources, and simulations, the Shannon information entropy exhibited by many common triggers was evaluated by analyzing available time-series or theoretical distributions of headache triggers. The degree of information, reported in bits, was compared across trigger variables, measurement strategies, and settings.
resultsA wide range of information content was observed across headache triggers. Due to lack of variation, there was little information, near 0.00 bits, in triggers like red wine and air conditioning. Most headache triggers exhibited more information when measured using an ordinal scale of presence/degree (e.g., absent, mild, moderate, severe) versus a present/absent binary coding. For example, the trigger "joy" exhibited 0.03 bits when assessed using binary coding but 1.81 bits when coded using an ordinal scale. More information was observed with the use of count data (0.86 to 1.75 bits), Likert rating scales (1.50 to 2.76 bits), validated questionnaires (3.57 to 6.04 bits), weather variables (0.10 to 8.00 bits), and ambulatory monitoring devices (9.19 to 12.61 bits).
conclusionsAlthough commonly used, all binary-coded measurements contain ≤1.00 bit of information. Low levels of information in trigger variables make associations with headache activity more difficult to detect. Assessments that balance information-rich measurements with reasonable participant burden using efficient formats (e.g., Likert scales) are recommended to enhance the evaluation of the association with headache activity.
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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.