Anastasios Psychogyiopoulos, Niels Smits, L Andries van der Ark
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A novel CAT method for QoL screening: proof-of-principle study with comparisons to standard methods.
Purpose: This proof-of-principle study investigated a novel Computer Adaptive Testing (CAT) method termed Latent-class and Sum score based Computerized Adaptive Testing (LSCAT), developed for screening purposes. LSCAT was assessed for its ability to accurately predict depression symptoms during health-related quality of life (HR-QoL) screenings.
Methods: LSCAT's performance was compared with two benchmark CAT methods, Stochastic Curtailment (SC) and Decision Tree based Computer Adaptive Testing (DTCAT), using data from the Patient Health Questionnaire-9 (PHQ-9).
Results: LSCAT consistently outperformed both SC and DTCAT in terms of predictive accuracy, achieving the lowest rates of Type I error. Furthermore, LSCAT's Type II error rates were at least as low as those of SC and significantly lower than those of DTCAT across all simulation scenarios.
Conclusion: These results suggest that LSCAT is a promising method for developing valid and efficient screening tools in HR-QoL research and practice.
期刊介绍：
Quality of Life Research is an international, multidisciplinary journal devoted to the rapid communication of original research, theoretical articles and methodological reports related to the field of quality of life, in all the health sciences. The journal also offers editorials, literature, book and software reviews, correspondence and abstracts of conferences.
Quality of life has become a prominent issue in biometry, philosophy, social science, clinical medicine, health services and outcomes research. The journal''s scope reflects the wide application of quality of life assessment and research in the biological and social sciences. All original work is subject to peer review for originality, scientific quality and relevance to a broad readership.
This is an official journal of the International Society of Quality of Life Research.
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