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Mindfulness as a Predictor of Migraine-Related Disability: Evidence from a Cross-Sectional Study

Nandana K Nair, A. Mukundan, S. Rajkumar, Hunny Kalra

International journal of research and review, 2025

110 participants

Abstract

Background: Migraines are prevalent neurological disorders characterized by severe headaches, nausea, and heightened sensory sensitivities, often triggered by various environmental and physiological factors. Although not life-threatening, migraines can significantly impair daily functioning and are associated with increased cardiovascular risk, particularly in cases with aura. Aim: This study aimed to investigate the association between mindfulness and migraine-related disability and to explore whether mindfulness may alleviate migraine impact by reducing stress.

Methods: A cross-sectional design was employed involving 110 adults with clinically diagnosed migraines, aged 18 to 65 years, recruited through purposive sampling. Participants completed the Mindful Attention Awareness Scale and the Migraine Disability Assessment. Data were analyzed using descriptive statistics, Pearson’s product-moment correlation, and linear regression analyses.

Results: There was a significant negative correlation between mindfulness and migraine-related disability (r = −0.334, p<.001), indicating that higher mindfulness is associated with lower disability. Regression analysis confirmed mindfulness as a significant negative predictor of migraine-related disability (β=−0.334), accounting for 11.2% of the variance (R2=0.112).

Conclusion: These findings highlight the potential of mindfulness-based interventions as non-pharmacological strategies to reduce migraine-related disability by mitigating…

How strong is the evidence?

Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 110 participants or records.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

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