Preferences of oral nutritional supplement therapy among postoperative patients with gastric cancer: Attributes development for a discrete choice experiment

Abstract

Background

Adherence to oral nutritional supplement therapy among postoperative patients with gastric cancer is low. There is little knowledge about patients’ priorities and needs regarding oral nutritional supplement therapy. The discrete choice experiment is an innovative method used to elicit patients’ preferences. Good practice guidelines emphasize that the development of attributes and levels is a fundamentally important process.

Objective

To comprehensively describe the identification, refinement, and selection of attributes and levels for a discrete choice experiment.

Methods

A mixed-methods approach, consisting of three consecutive steps: a literature review, in-depth interviews, and focus groups. First, the literature review allowed quick identification of attributes and levels. Then, 15 in-depth interviews were conducted to gather a rich description of the experience of patients taking oral nutritional supplements after gastrectomy and to verify and enrich the attributes and levels list. Finally, four focus group participants discussed the wording of the attributes and levels and reduced the number of attributes to manageable numbers through voting ranking methods.

Results

Following the literature review and qualitative data collection, eight attributes were finally generated, each with two to three levels. The following attributes were included: 1) information provider; 2) health guidance approach; 3) adverse reactions; 4) flavor; 5) follow-up method; 6) follow-up frequency; 7) psychological support; 8) cost. These attributes covered the important attributes of nutritional preparations and health guidance included in ONS therapy that were relevant to patients.

Conclusions

This study’s mixed-methods approach has been found highly suitable to identify, refine and select attributes and levels for a discrete choice experiment. The three methods have pros and cons, and they complement each other, especially the analysis of qualitative data led to a deeper and broader understanding of attributes and levels.