This talk will present a mixed methods approach to elicit and rank attributes of child health concerns that may worry parents of 6 to 12 year old children. First, focus groups were conducted with parents (n = 17) to identify factors that influence parental concern about child health and motivate parents to seek care from a health provider or engage in preventive behaviors. Focus group themes, a review of the literature, and expert opinion were synthesized to identify 13 relevant attributes of health concerns a child may face in the future. The survey was piloted with U.S. parents (n = 71). Parents were asked to complete a best-worst scaling (BWS) exercise, an alternative to category rating scales. Respondents were repeatedly asked to select which of a set of four attributes would worry them the least and which would worry them the most. The most and least concerning attributes were assessed first using best-worst scores (spanning -4 to 4) representing the number of times each attribute was designated as least or most worrying and secondly using a conditional logit model.
This talk will introduce the concept of best-worst scaling, discuss advantages of the use of best minus worst scores vs. logistic regression models for analysis, and discuss potential applications in the social sciences.