Scoring System for the Japanese Version of the ICECAP-A.

PURPOSE

This study aimed to develop a value set for the Japanese version of the Investigating Choice Experiments CAPability Measure for Adults (ICECAP-A).

PATIENTS AND METHODS

A total of 400 participants were recruited. Survey 1, conducted utilizing a self-report format, collected demographic data and responses to well-being scales, including the ICECAP-A, the Investigating Choice Experiments CAPability Measure for Older People (ICECAP-O), and the EuroQol 5 Dimensions (EQ-5D), among others. Participants who completed Survey 1 were invited to participate in Survey 2. In Survey 2, an interview-based assessment, participants engaged in best-worst scaling, where they identified the most and least favorable situations in each of the 16 hypothetical scenarios. A mixed-mixed multinomial logit (MM-MNL) model was utilized to estimate preference parameters, accounting for individual heterogeneity and latent classes.

RESULTS

The estimated parameters and tariffs indicated that all five attributes contributed to an individual's capability for well-being, consistent with prior studies. The attributes were ranked in order of importance as follows: "enjoyment" (24.8% of the space), "attachment" (22.1%), "stability" (19.5%), "autonomy" (17.9%), and "achievement" (15.6%). For "enjoyment" and "attachment", the differences between levels 1 and 2 and between levels 2 and 3 were equally large. In contrast, for all other attributes, the greatest differences were observed between levels 1 and 2. Across all attributes, the differences between levels 3 and 4 were comparatively smaller.

CONCLUSION

We developed a Japanese version of the ICECAP-A and demonstrated the feasibility of utilizing best-worst scaling in a non-European context. This approach allows for a more precise evaluation of quality of life (QoL) among individuals with chronic conditions, caregivers, and the general population. Future research should assess the scale's sensitivity in capturing changes in capability over time.