ArticleEvidence-based complementary and alternative medicine : eCAM2021
Development of a Computerized Adaptive Test for Quantifying Chinese Medicine Syndrome of Myasthenia Gravis on Basis of Multidimensional Item Response Theory.
Article in Evidence-based complementary and alternative medicine : eCAM, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 1 citations in OpenAlex.
- Traditional Chinese medicine research on rare diseases: Publication trends and future perspectives.Intractable & rare diseases research · 2026Article
- Outcome of the efficacy of Chinese herbal medicine for functional constipation: A systematic review and meta-analysis.World journal of clinical cases · 2022Article
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Authors and funding
4 authors at 2 institutions in 1 country.
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Abstract
backgroundMaking comprehensive management of myasthenia gravis (MG) is a challenge in clinical practice due to heterogeneity and multiple comorbidities among patients.
aimTo develop an end-to-end instrument for individualized assessment of MG in the perspective of Chinese medicine (TCM) with the application of multidisciplinary quantification approaches.
methodsA self-administrated questionnaire was developed integrating typical symptoms of MG and spleen-kidney deficiency syndrome on basis of the conceptual framework of TCM. With data collected in a multicenter cross-sectional study, confirmatory factor analysis together with multidimensional item response theory (MIRT) was used for evaluating the psychometric property of the questionnaire. A computerized adaptive test was developed based on the MIRT model, and scores of syndrome factors were calculated in simulation. A logistics regression model was also estimated for evaluating the consistency between the quantitative result and the clinical diagnosis of syndrome from clinical practitioners.
resultWith 337 patients enrolled and assessed, the 14-item questionnaire was evaluated to be with adequate validity and reliability (Cronbach's alpha indices = 0.87, AIC = 195.827, BIC = 348.631, CFI = 0.921, RMR = 0.006, GFI = 0.954, RMSEA = 0.048, and
conclusionSetting typical symptoms of MG together with systemic discomforts in a computerized adaptive test on the basis of MIRT, this study proposed an innovative research paradigm for quantifying individual condition in the perspective of TCM with application of interdisciplinary approaches.
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