title: The practicality and validity of directly elicited and SF-36 derived health state preferences in patients with low back pain.
abstract: Recent research has derived preference scores from the SF-36. We compare the practicality and construct validity of SF-36 derived preference scores with directly elicited time trade off (TTO) and visual analogue scale (VAS) scores. In this observational study, low back pain (LBP), patients were asked to complete disease specific, generic (SF-36), and health state preference (VAS and TTO) instruments. Baseline SF-36 responses were converted to preference scores using six published algorithms. Response rates for the SF-36 derived and TTO preference values were 354 of 379 (93%) and 303 of 379 (80%), respectively. Thirty patients were excluded from the TTO exercise because of difficulties comprehending the scaling task. Choice based methods (standard gamble, TTO) yielded higher and more uniform estimates of preference (0.77-0.79) than non-choice based methods (VAS) (0.42-0.70). Directly elicited TTO values were variable and had less power to distinguish among patients with differing severity of LBP. All SF-36 derived preferences exhibited a minimum threshold implying a potential floor effect for severely ill patients. SF-36 derived preferences demonstrated good practicality and construct validity in this setting, however different methods will yield disparate estimates of marginal benefit. This emphasises the need for a standardised algorithm for deriving SF-36 preference scores.
authors.affiliation: Department of Public Health & Primary Care, University of Cambridge, Robinson Way, Cambridge, CB2 2SR, UK. wh108@medschl.cam.ac.uk
authors.forename: William
authors.initials: W
authors.lastname: Hollingworth
authors.forename: Richard A
authors.initials: RA
authors.lastname: Deyo
authors.forename: Sean D
authors.initials: SD
authors.lastname: Sullivan
authors.forename: Scott S
authors.initials: SS
authors.lastname: Emerson
authors.forename: Darryl T
authors.initials: DT
authors.lastname: Gray
authors.forename: Jeffrey G
authors.initials: JG
authors.lastname: Jarvik
mesh_terms: D000465:Algorithms; D015331:Cohort Studies; D003657:Decision Making; D005260:Female; D006302:Health Services Research; D006801:Humans; D017116:Low Back Pain / Q000523:psychology* / Q000628:therapy; D008297:Male; D008875:Middle Aged; D017060:Patient Satisfaction / Q000706:statistics & numerical data*; D019057:Quality-Adjusted Life Years; D012647:Self-Assessment; D018434:Sickness Impact Profile; D026712:Value of Life; D014861:Washington