Perceived Ineffectiveness of Pharmacological Treatments for Dysmenorrhea

Abstract

Background: Dysmenorrhea affects most reproductive-aged women. Common dysmenorrhea treatments vary in their effectiveness across individuals. Little is known about factors associated with perceived treatment ineffectiveness. The objectives of this study were to describe the perceived ineffectiveness of common pharmacological treatments for dysmenorrhea and investigate factors associated with perceived treatment ineffectiveness. Materials and Methods: In this cross-sectional study, 678 women with dysmenorrhea (aged 14-42) provided data on perceived treatment ineffectiveness, dysmenorrhea symptom-based phenotypes, demographics, clinical factors, and psychobehavioral characteristics. We used Fisher's exact tests to compare treatment ineffectiveness across three symptom-based phenotypes. We used logistic regressions to explore associations of phenotype, demographic, clinical, and psychobehavioral correlates of perceived treatment ineffectiveness. Results: Percentages perceiving treatments as ineffective were 29.3%-35.6% nonsteroidal anti-inflammatory drugs, 49.9% acetaminophen, and 39.3% combined oral contraceptive pills (OCPs). Factors associated with perceived ineffectiveness varied across treatments and included symptom-based phenotypes, clinical, and psychobehavioral factors. For ibuprofen and acetaminophen, women with severe (vs. mild) pain phenotype and higher number of chronic pain conditions were more likely to perceive the treatments as ineffective. For OCPs, women with severe pain (vs. mild) phenotype, comorbid gynecological condition, less anxiety, and worse depressive symptoms were more likely to perceive the treatment as ineffective. Conclusion: A significant percentage of women reported ineffectiveness of dysmenorrhea treatments. Phenotypes, clinical, and psychobehavioral factors were associated with treatment ineffectiveness. Future research should test if symptom-based phenotypes are associated with treatment effectiveness in clinical trials and investigate other factors that affect dysmenorrhea treatment effectiveness, so treatments can be tailored to individuals.