title: Feasibility, reliability, and validity of three health-state valuation methods using multiple-outcome vignettes on moderate-risk pregnancy at term.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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).
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Academic Medical Centre—University of Amsterdam, Amsterdam,The Netherlands. d.bijlenga@amc.uva.nl
authors.forename: Denise
authors.initials: D
authors.lastname: Bijlenga
authors.forename: Erwin
authors.initials: E
authors.lastname: Birnie
authors.forename: Gouke J
authors.initials: GJ
authors.lastname: Bonsel
mesh_terms: D000328:Adult; D000368:Aged; D036861:Delivery, Obstetric / Q000379:methods / Q000523:psychology; D005260:Female; D006801:Humans; D016014:Linear Models; D008429:Maternal Welfare / Q000523:psychology; D008875:Middle Aged; D015588:Observer Variation; D010147:Pain Measurement; D057240:Patient Preference / Q000523:psychology; D011247:Pregnancy; D011248:Pregnancy Complications / Q000191:economics / Q000523:psychology* / Q000628:therapy; D011256:Pregnancy Outcome / Q000523:psychology; D015203:Reproducibility of Results; D012307:Risk Factors; D011795:Surveys and Questionnaires / Q000592:standards; D055815:Young Adult