Since health information is intended to support patients and citizens in the process of shared decision-making, their personal values and preferences play an important role in the decision-making process (1). To support this group of people in the clarification of their individual values and preferences, value clarification tools are used as part of decision aids (2). This includes various methods and strategies designed to help users to gain clarity about their personal values and preferences regarding medical interventions and to communicate these in order to reach a decision the outcome of which is consistent with their personal values and preferences (2).
Generally, explicit and implicit value clarification tools are differentiated. The user of implicit value clarification tools only thinks about what is important for his/her own decision. The users of explicit value clarification tools are involved in an interactive process in which attributes that are decisive for the therapy or diagnostic option are reflected on and evaluated with regard to their subjective importance on a rating scale (1, 3). Since evidence-based health information should generally be required to present different options in such a way that they enable an implicit clarification of preferences, the focus here is on explicit value clarification tools. In the process, it will be discussed whether value clarification tools improve the decision-making process (1, 2).
The developers use various formats based on different theories (e.g. the Differentiation and Consolidation Theory, Fuzzy Trace Theory) (4). Typical representations are similar to a scale with positive attributes (benefits) on the one side and negative attributes (risks) on the other side, which are evaluated by the patients in their subjective importance, resulting in a preference for or against a therapy option according to the given preferences (1). Another possibility are rating and ranking exercises in which predetermined attributes are sorted according to the subjective importance. Each attribute is then classified according to how much it influences the actual decision. Finally, the patient receives an evaluation of his/her assigned preferences, which illustrate the tendency to a certain option (5).