ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2025
A novel CAT method for QoL screening: proof-of-principle study with comparisons to standard methods.
Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeThis 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.
methodsLSCAT'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).
resultsLSCAT 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.
conclusionThese results suggest that LSCAT is a promising method for developing valid and efficient screening tools in HR-QoL research and practice.
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