Page 14 - Thomas Gültzow
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Chapter 1



                 in making a decision about whether to participate in a clinical trial, i.e., individuals could
                 choose  between  two  options:  (1)  participate  in  the  clinical  trial  or  (2)  receive  standard
                 treatment [32]. Those two options have certain characteristics. For example, participation in
                 the clinical trial allows participants to receive an innovative treatment with potential new
                 benefits, while receiving standard treatment does not come with the burden of additional
                 monitoring [32]. The VCM could then help individuals to identify their personal values and
                 preferences,  e.g.,  the  VCM  might  help  someone  to  identify  that  they  highly  value  the
                 potential benefits which would reveal their overall preference for the clinical trial as opposed
                 to standard treatment [32].

                 Generally  speaking,  VCMs  tend  to  be  divided  into  implicit  VCMs  that  lack  interactive
                 elements (e.g., tables that make options' characteristics explicit and leave the actual value
                 clarification  to  the  user),  and  explicit  VCMs  that  include  interactive  elements  for  value
                 clarification [34]. In general, explicit VCMs are much more studied [34] and several studies
                 have found promising effects compared to implicit VCMs. In a study by Abhyankar et al. [30],
                 no VCM was compared with both an implicit VCM and an explicit VCM in the previously
                 described decision-making context (i.e., whether to participate in a clinical trial). It was found
                 that the decisions of participants in the explicit VCM group showed more characteristics of
                 informed decision making, that participants felt less ambivalent about the options, and less
                 uncertain about the decision and their values overall [32]. Other evidence especially points
                 to positive long-term effects: In a study by Feldman-Stewart et al. [37] it was shown that
                 decisional conflict was unaffected by their explicit VCM immediately after having used the
                 DA. On the other hand, positive effects emerged on feeling prepared for decision making
                 after the decision had been made, while positive effects on decisional regret only emerged
                 after a year [37].

                 Explicit VCMs can be further subdivided and range from methods such as rating scales (e.g.,
                 by making use of Likert scales) to math model-based methods [38]. Recent evidence has
                 shown  that  the  potential  effect  of  explicit  VCMs  on  value-consistent  decision  making  is
                 moderated by whether users are supported in understanding the implications of their values
                 [39,40]. To illustrate, Witteman et al. have shown in a series of studies that the most effective
                 VCMs in terms of value-consistent decision making show VCM-users to what extent options
                 (fail  to)  align  with  their  identified  values  [40].  For  example,  in  one  of  their  studies,
                 participants were given an online application consisting of dynamic web sliders representing
                 both  values  and  preferences.  Those  web  sliders  were  then  linked,  meaning  that  for
                 participants  who  indicated  that  a  particular  value  is  very  important  to  them,  the  slider
                 representing the preference moved equally [40]. Another possible way to support users in
                 understanding the implications of their values would be to provide tailored advice based on
                 these values that shows users which options match their values and can thus be considered
                 preferred options. However, all of this has been tested in a healthcare context only and up



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