We have demonstrated the feasibility of the NGT in prioritizing attributes for inclusion in DCEs. When many candidate attributes are identified from available sources or patient interviews, this approach may be beneficial for assessing the importance of these attributes to construct the DCE. Therefore, in situations where the number of attributes identified needs to be restricted, a two-stage analysis could be performed, in which a self-exploratory analysis reduces the number of attributes (using NGT for example) and a DCE is conducted with the restricted list of attributes to assess further preferences for the levels of the attributes. Other tools (eg, best-worst scaling, adaptive conjoint analysis where attributes are changed simultaneously) could be alternative approaches.
Starting from a comprehensive list of attributes for osteoporosis medication generated from the literature and expert opinion, we identified which medication attributes are important from the patient perspective. Rankings and discussion revealed four important attributes, ie, effectiveness, side effects, and mode and frequency of administration.
These results are interesting for designing DCE experiments, and are also worthwhile in themselves when aiming to improve therapeutic adherence. Poor adherence with osteoporosis medication is a well documented problem,20
which results in significant clinical and economic burden.21
Barriers to adherence include side effects, inconvenient dosing regimens, lack of information, and cost of medication.23
Providing patients with adequate information on the treatment options and involving them in decision-making may contribute to optimizing selection of treatment and improving adherence to therapy.24
Because drug therapies in osteoporosis differ in their side effect profiles as well as mode and frequency of administration, and these were considered to be important attributes in our research, sharing this information with patients could lead to optimized selection of treatment and improved adherence with therapy.
In the context of this study, the NGT discussions did not substantially affect rank order of preferences for the attributes in the total group when compared with rank order before the NGT discussion, indicating considerable agreement for the most important attributes. This suggests that a simple ranking exercise (or best-worst scaling) may perhaps be sufficient to determine the most important attributes. However, individual analyses have suggested that 80% of patients changed their ranking after discussion, and this could potentially be reflected in a different group ranking. Therefore, further investigations in other contexts, other diseases, and other decisional issues are needed to determine the added value of the NGT meeting when selecting and prioritizing attributes for a DCE or even other purposes.
The approach described here also has the advantage of being rigorous, systematic, and transparent, and so may improve the face validity of DCEs. Many papers have pointed out that conjoint analysis did not justify the selection of attributes very well.5
Recently, Coast et al explored issues associated with attribute development for DCEs, and contrasted different qualitative approaches in the development of DCEs based on experience generated in interviews.5
Our study generated further insight by providing additional experience from group discussions. The benefits of conducting qualitative research were also not restricted to the selection of attributes. Discussions have been interesting in terms of refining language5
and for conducting a Bayesian efficient design.27
However, application of such a method did not come without a cost. We estimate that the whole process of organizing, running, and analyzing the NGT cost about €10,000 (including about €1500 as an incentive to patients for time spent and 2–3 months of the services of a full-time researcher). However, we believe that the benefits of the approach make it highly cost-effective.
The NGT could also be useful in selecting the initial set of attributes. Participants could first be asked individually to generate a list of important medication attributes, followed by discussion refining the list by adding, merging, or removing attributes, and by the final individual ranking of the most important attributes. This was not done in our study because many potential attributes were already identified by the literature review and we also aimed to assess the impact of the NGT session on rank order. However, our patients had the opportunity to add attributes to the list. Our study could also have some important implications for further research in this area. First, misunderstanding of attributes is frequent, and a clear description and explanation of the attributes is required. Second, ranking many attributes could impose a substantial cognitive burden on respondents. Perhaps it would have been sufficient to ask patients to rank their five most important attributes. Rating scales per attribute could also be an alternative requiring less effort on the respondent’s part, but with more limited information on the relative importance of attributes. Further work should be done to assess and compare ranking/rating exercises. Third, the impact of the NGT discussion was shown to differ substantially between patients. It would be interesting in the future to identify reasons that could explain this. Finally, our study showed that the presenting order of attributes did have an impact on the results. Therefore, we recommend controlling for ordering effects in ranking exercises.
A limitation of this study is that we have not compared the attributes derived from NGT with other approaches (eg, expert opinion, best-worst scaling). The gold standard would be the preference revealed, but this outcome is also difficult to assess. Head-to-head comparisons of different techniques could help to assess and understand differences between approaches, although there may be practical limitations in developing such studies.5