Optimizing the attribute selection process for stated preference study:a study based on best-worst scaling
Objective To explore how to determine the attributes of stated preference research more scientifically and reasonably.Methods Based on the best-worst scaling object case(BWS-1)method,a BWS-1 questionnaire was generated using a balanced incomplete block design.Data collection was conducted among type 2 diabetes mellitus(T2DM)patients in Hainan and Jiangsu provinces.Data analysis was performed using counting analysis and conditional logit model to obtain the priority order of each attribute.Results The results of BWS-1 using the counting and modelling approach showed high consistency.Among the 11 attributes,the top three attributes influencing the preference for second-line antihyperglycemic medications selection in T2DM patients were blood glucose control effectiveness,cardiovascular protection capability,and risk of hypoglycemic events,while the last three factors were dosing frequency,mode of administration and bone fracture.Based on literature review,qualitative research,and BWS-1 results,the seven attributes of discrete choice experiment and best-worst scaling profile case(BWS-2)were determined as follows:treatment efficacy,weight change,hypoglycemic events,gastrointestinal side effects,cardiovascular health,mode of administration and out-of-pocket cost.Conclusion BWS-1 can serve as an effective tool for determining the attributes of stated preference research.However,it is not recommended to solely rely on the priority ranking of BWS-1 results to determine the scope of attributes for stated preference research.It is necessary to conduct a specific analysis in conjunction with the research's policy objectives and real-world circumstances.
万方数据
维普
