Maximum Acceptable Risk Estimation Based on a Discrete Choice Experiment and a Probabilistic Threshold Technique

Choice Consistency in Discrete Choice Experiments: Does Numeracy Skill Matter?

OBJECTIVES

This study investigated the relationship between numeracy skills (NS) and choice consistency in discrete choice experiments (DCEs).

METHODS

A DCE was conducted to explore patients' preferences for kidney transplantation in Italy. Patients completed the DCE and answered 3-item numeracy questions. A heteroskedastic multinomial logit model was used to investigate the effect of numeracy on choice consistency.

RESULTS

Higher NS were associated with greater choice consistency, increasing the scale to 1.63 (P < .001), 1.39 (P < .001), and 1.18 (P < .001) for patients answering 3 of 3, 2 of 3, and 1 of 3 questions correctly, respectively, compared with those with no correct answers. This corresponded to 63%, 39%, and 18% more consistent choices, respectively. Accounting for choice consistency resulted in varying willingness-to-wait (WTW) estimates for kidney transplant attributes. Patients with the lowest numeracy (0/3) were willing to wait approximately 42 months [95% CI: 29.37, 54.68] for standard infectious risk, compared with 33 months [95% CI: 28.48, 38.09] for 1 of 3, 28 months [95% CI: 25.13, 30.32] for 2 of 3, and 24 months [95% CI: 20.51, 27.25] for 3 of 3 correct answers. However, WTW differences for an additional year of graft survival and neoplastic risk were not statistically significant across numeracy levels. Supplementary analyses of 2 additional DCEs on COVID-19 vaccinations and rheumatoid arthritis, conducted online, supported these findings: higher NS were associated with more consistent choices across different disease contexts and survey formats.

CONCLUSIONS

The findings suggested that combining patients with varying NS could bias WTW estimates, highlighting the need to consider numeracy in DCE data analysis and interpretation.

Comparing Discrete Choice Experiment with Swing Weighting to Estimate Attribute Relative Importance: A Case Study in Lung Cancer Patient Preferences

INTRODUCTION

Discrete choice experiments (DCE) are commonly used to elicit patient preferences and to determine the relative importance of attributes but can be complex and costly to administer. Simpler methods that measure relative importance exist, such as swing weighting with direct rating (SW-DR), but there is little empirical evidence comparing the two. This study aimed to directly compare attribute relative importance rankings and weights elicited using a DCE and SW-DR.

METHODS

A total of 307 patients with non-small-cell lung cancer in Italy and Belgium completed an online survey assessing preferences for cancer treatment using DCE and SW-DR. The relative importance of the attributes was determined using a random parameter logit model for the DCE and rank order centroid method (ROC) for SW-DR. Differences in relative importance ranking and weights between the methods were assessed using Cohen's weighted kappa and Dirichlet regression. Feedback on ease of understanding and answering the 2 tasks was also collected.

RESULTS

Most respondents (>65%) found both tasks (very) easy to understand and answer. The same attribute, survival, was ranked most important irrespective of the methods applied. The overall ranking of the attributes on an aggregate level differed significantly between DCE and SW-ROC (P < 0.01). Greater differences in attribute weights between attributes were reported in DCE compared with SW-DR (P < 0.01). Agreement between the individual-level attribute ranking across methods was moderate (weighted Kappa 0.53-0.55).

CONCLUSION

Significant differences in attribute importance between DCE and SW-DR were found. Respondents reported both methods being relatively easy to understand and answer. Further studies confirming these findings are warranted. Such studies will help to provide accurate guidance for methods selection when studying relative attribute importance across a wide array of preference-relevant decisions.

HIGHLIGHTS

Both DCEs and SW tasks can be used to determine attribute relative importance rankings and weights; however, little evidence exists empirically comparing these methods in terms of outcomes or respondent usability.Most respondents found the DCE and SW tasks very easy or easy to understand and answer.A direct comparison of DCE and SW found significant differences in attribute importance rankings and weights as well as a greater spread in the DCE-derived attribute relative importance weights.