Preference-based health-state valuation methods such as discrete choice experiment (DCE) are claimed to be superior than attitude-based valuation methods like visual analogue scale (VAS) and time trade-off (TTO). We compared VAS, TTO, and DCE in terms of feasibility, reliability, and validity using vignettes depicting moderate-risk pregnancy at term.
People from the community (n = 97) participated in both a panel session and an individual home assignment. Each participant valuated 46 vignettes with VAS, TTO, and DCE. Each vignette consisted of five attributes: maternal health antepartum, time between diagnosis and delivery, process of delivery, maternal outcome, and neonatal outcome. The questionnaire included Feasibility, which we evaluated by questionnaire. Test–retest reliability and interobserver consistency were assessed by intraclass correlation (ICC), and variance consistency by generalization theory. Convergent validity was determined with ICC and Cohen's kappa; construct validity was determined with linear regression, multinomial logit modeling, and Kendall's Tau-b correlation (τ).
The DCE was reported as most feasible (DCE: 87% vs. VAS: 69% vs. TTO: 42%). Test–retest reliability was high overall and equal (VAS: ICC = 0.77; TTO: ICC = 0.79; DCE: κ = 0.78). The VAS had the highest interobserver reliability (ICC = 0.73). Convergent validity between VAS and DCE was high (κ = 0.79) and there was sufficient construct validity between VAS and DCE (τ = 0.68). The TTO yielded less optimal results. Generally, neonatal and maternal outcomes weighed most, whereas process outcomes weighed least in moderate-risk pregnancy at term.
In our context of multidimensional health states with complex trade-offs, DCE was superior to TTO and performed equal to VAS, with DCE displaying slightly higher user feasibility.