Discrete Choice Experiments
Discrete choice experiments (DCEs) are used to assess individual preferences. In health, these are usually preferences for health states or outcomes, for treatments, or for services. DCEs can be helpful for understanding how people making trade-offs between different components of a treatment or service, and for predicting which treatments people will actually take.
Best-worst scaling (BWS) studies are useful for identifying the relative importance of different characteristics of a health state, service or treatment. In a BWS, participants are shown a list of characteristics and asked which one is 'best' and which one is 'worst'. BWS studies may be easier for people to complete than DCEs. With PreferApp you can run Type 1, Type 2 and Type 3 BWS surveys.
Other preference elicitation types
While DCEs and BWS studies are increasingly common in healthcare, sometimes a more straight-forward approach is needed. PreferApp includes other preference elicitation methods, like ranking tasks, Likert scales, and constant sum tasks. These tasks are quick to set-up and easy for participants to complete.
Discrete Choice Experiments with up to 4 options, including sequential 'opt out'.
Best worst scaling (Type 1, 2 and 3)
Blocks for your experimental designs so people are randomized to different questions, and within each block, can be randomized to different question orders and attribute orders.
Conventional questions: multiple choice (single and multiple answer), grid questions, numeric questions, and open ended questions.
Free text pages
Ability to embed images and videos into each page.
Skip logic to branch to different questions based on responses.
Hidden variables and lookup tables (so based on the responses to a question, you can lookup a value and embed that in a future question)
Data from external sources (e.g. you can import data from REDCap and use it in your surveys)
Real time results based on DCE/BWS responses (e.g. live checks for inconsistency, feedback weights based on Max diff calculations or previous mixed logit calculations)
Simple interface for uploading experimental designs
Colour Code Attributes
Built-in Skip Logic