Development of an endometriosis self-assessment tool for patient
A 21-item endometriosis self-assessment tool was developed and validated, demonstrating good reliability and ability to differentiate endometriosis from non-endometriosis.
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This study developed and evaluated an endometriosis self-assessment tool (ESAT) using items derived from in-depth interviews with 14 laparoscopically diagnosed endometriosis patients and an integrative literature review of endometriosis symptom experiences. In a descriptive, correlational non-experimental design, 142 participants (117 with endometriosis and 25 without) completed the ESAT, and the authors assessed content/construct validity and reliability, including nomological validity via correlations with quality-of-life scores; they also used exploratory factor analysis and receiver operator characteristic analyses. The ESAT yielded 21 items with four symptom components (gastrointestinal symptoms, dysmenorrhea, usual symptoms, and menstrual bleeding amount/characteristics), supported construct validity, and differentiated endometriosis from non-endometriosis with fair discrimination (cut-off 50; sensitivity 0.76, specificity 0.72, AUC >0.75). The paper notes that the ESAT is intended as a self-assessment rather than a hospital diagnostic test, with symptom evaluation framed around menstrual cycle phases; applicability beyond this design and sampling frame is not explicitly quantified. This paper is centrally about endometriosis — it focuses on developing and validating a patient-facing endometriosis self-assessment tool (ESAT).
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Cited by (5)
- Relationship between sedentary lifestyle and body mass index with the risk of endometriosis among adolescent girls at a senior high school 2025
- Exploring Self-Reported Symptoms for Developing and Evaluating Digital Symptom Checkers for Polycystic Ovarian Syndrome, Endometriosis, and Uterine Fibroids: Exploratory Survey Study (Preprint) 2024
- Measurement of changes to the menstrual cycle: A transdisciplinary systematic review evaluating measure quality and utility for clinical trials 2024
- Assessing the accuracy of a digital symptom checker tool for suggestion of reproductive health conditions: a clinical vignettes study 2023
- Assessment of a Digital Symptom Checker Tool's Accuracy in Suggesting Reproductive Health Conditions: Clinical Vignettes Study 2023
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