Browsing by Subject "pelvic pain"
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Item Big Data and Dysmenorrhea: What Questions Do Women and Men Ask About Menstrual Pain?(Liebert, 2018-10) Chen, Chen X.; Groves, Doyle; Miller, Wendy R.; Carpenter, Janet S.; School of NursingBackground: Menstrual pain is highly prevalent among women of reproductive age. As the general public increasingly obtains health information online, Big Data from online platforms provide novel sources to understand the public's perspectives and information needs about menstrual pain. The study's purpose was to describe salient queries about dysmenorrhea using Big Data from a question and answer platform. Materials and Methods: We performed text-mining of 1.9 billion queries from ChaCha, a United States-based question and answer platform. Dysmenorrhea-related queries were identified by using keyword searching. Each relevant query was split into token words (i.e., meaningful words or phrases) and stop words (i.e., not meaningful functional words). Word Adjacency Graph (WAG) modeling was used to detect clusters of queries and visualize the range of dysmenorrhea-related topics. We constructed two WAG models respectively from queries by women of reproductive age and bymen. Salient themes were identified through inspecting clusters of WAG models. Results: We identified two subsets of queries: Subset 1 contained 507,327 queries from women aged 13–50 years. Subset 2 contained 113,888 queries from men aged 13 or above. WAG modeling revealed topic clusters for each subset. Between female and male subsets, topic clusters overlapped on dysmenorrhea symptoms and management. Among female queries, there were distinctive topics on approaching menstrual pain at school and menstrual pain-related conditions; while among male queries, there was a distinctive cluster of queries on menstrual pain from male's perspectives. Conclusions: Big Data mining of the ChaCha® question and answer service revealed a series of information needs among women and men on menstrual pain. Findings may be useful in structuring the content and informing the delivery platform for educational interventions.Item Development and Testing of the Dysmenorrhea Symptom Interference (DSI) Scale(2020-07-17) Chen, Chen X.; Murphy, Tabitha; Ofner, Susan; Yahng, Lilian; Krombach, Peter; LaPradd, Michelle; Bakoyannis, Giorgos; Carpenter, Janet S.; School of NursingDysmenorrhea affects most reproductive-age women and increases the risk of future pain. To evaluate dysmenorrhea interventions, validated outcome measures are needed. In this two-phase study, we developed and tested the dysmenorrhea symptom interference scale. During the scale-development phase (n = 30), we created a nine-item scale based on qualitative data from cognitive interviews. During the scale-testing phase (n = 686), we evaluated reliability, validity, and responsiveness to change. The scale measures how dysmenorrhea symptoms interfere with physical, mental, and social activities. Internal consistency was strong with Cronbach's α > 0.9. Test-retest reliability was acceptable (r = 0.8). The scale showed satisfactory content validity, construct validity (supported by confirmatory factor analysis), concurrent validity, and responsiveness to change. The minimally important difference was 0.3 points on a scale with a possible total score ranging from 1 to 5. This new psychometrically sound scale can be used in research and clinical practice to facilitate the measurement and management of dysmenorrhea.Item Dysmenorrhea Symptom-Based Phenotypes: A Replication and Extension Study(2020-09-16) Chen, Chen X.; Carpenter, Janet S.; Ofner, Susan; LaPradd, Michelle; Fortenberry, J. Dennis; School of NursingItem Perceived Ineffectiveness of Pharmacological Treatments for Dysmenorrhea(2020-10-07) Chen, Chen X.; Carpenter, Janet S.; LaPradd, Michelle; Ofner, Susan; Fortenberry, J. Dennis; School of NursingBackground: 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.