Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues.

For optimal solutions in health care, decision makers inevitably must evaluate trade-offs, which call for multi-attribute valuation methods. Researchers have proposed using best-worst scaling (BWS) methods which seek to extract information from respondents by asking them to identify the best and worst items in each choice set. While a companion paper describes the different types of BWS, application and their advantages and downsides, this contribution expounds their relationships with microeconomic theory, which also have implications for statistical inference. This article devotes to the microeconomic foundations of preference measurement, also addressing issues such as scale invariance and scale heterogeneity. Furthermore the paper discusses the basics of preference measurement using rating, ranking and stated choice data in the light of the findings of the preceding section. Moreover the paper gives an introduction to the use of stated choice data and juxtaposes BWS with the microeconomic foundations.

Validation of the Food-Linked Virtual Response task.

This research validates a computerized dietary selection task (Food-Linked Virtual Response or FLVR) for use in studies of food consumption. In two studies, FLVR task responses were compared with measures of health consciousness, mood, body mass index, personality, cognitive restraint toward food, and actual food selections from a buffet table. The FLVR task was associated with variables which typically predict healthy decision-making and was unrelated to mood or body mass index. Furthermore, the FLVR task predicted participants' unhealthy selections from the buffet, but not overall amount of food. The FLVR task is an inexpensive, valid, and easily administered option for assessing momentary dietary decisions.