Abstract
Background
Dysmenorrhea is a frequent and misdiagnosed symptom affecting the quality of life in young women. A working ability, location, intensity, days of pain, dysmenorrhea (WaLIDD) score was designed to diagnose dysmenorrhea and to predict medical leave.
Methods
This cross-sectional design included young medical students, who completed a self-administered questionnaire that contained the verbal rating score (VRS; pain and drug subscales) and WaLIDD scales. The correlation between scales was established through Spearman test. The area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, and likelihood ratio (LR +/−) were evaluated to diagnose students availing medical leave due to dysmenorrhea; moreover, to predict medical leave in students with dysmenorrhea, a binary logistic regression was performed.
Results
In all, 585 students, with a mean age of 21 years and menarche at 12 years, participated. Most of them had regular cycles, 5 days of menstrual blood flow and 1–2 days of lower abdominal pain. The WaLIDD scale presented an adequate internal consistency and strong correlation with VRS subscales. With a cutoff of >6 for WaLIDD and 2 for VRS subscales (drug subscale and pain subscale) to identify students with dysmenorrhea, these scales presented an area under the curve (AUC) ROC of 0.82, 0.62, and 0.67, respectively. To identify students taking medical leave due to dysmenorrhea, WaLIDD (cutoff >9) and VRS subscales (cutoff >2) presented an AUC ROC of 0.97, 0.68, and 0.81; moreover, the WaLIDD scale showed a good LR +14.2 (95% CI, 13.5–14.9), LR −0.00 (95% CI, undefined), and predictive risk (OR 5.38; 95% CI, 1.78–16.2).
Conclusion
This research allowed a comparison between two multidimensional scales regarding their capabilities, one previously validated and a new one, to discriminate among the general population of medical students, among those with dysmenorrhea or those availing medical leave secondary to dysmenorrhea. WaLIDD score showed a larger effect size than the pain and drug score in the students. In addition, this study demonstrated the ability to predict this combination of events.
Supplementary materials
Table S1 Dysmenorrhea scales’ effect sizes in relation to influential characteristics of pain measurement
Table S2 Baseline characteristics of university students related to medical leave
Table S3 Correlation between dysmenorrhea and other features
Table S4 Risk of incapability in relation to features of scores
Acknowledgments
Thanks are due to FUJNC and especially Dr Jaime García for allowing us to develop the present investigation within the School of Medicine; psychologist Yurley Campo Fontecha and OBGYN Henry Currea for their collaboration during the content validation phase of the questionnaire applied; and students Lilian Estupiñan, María Paula Bello, Angelica María Quintero, Natalia Pérez Malagón, and Jennifer Paola Martínez for helping us during the data collection phase.
Author contributions
AAT, LGP, FP, and MCMG drafted and contributed equally to the conception, design, study material collection, and systematization of information. AAT and MCM analyzed and interpreted the data. LGP, FP, VC, and MCB contributed to the instrument design and style correction. All authors contributed toward data analysis, drafting and critically revising the paper, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.
Disclosure
The authors report no conflicts of interest in this work.