Which factors drive the choice of the French-speaking Quebec population towards a COVID-19 vaccination programme: A discrete-choice experiment

ObjectivesThe aims of this study were to elicit preferences about the coronavirus disease 2019 (COVID-19) vaccine campaign in the general French-speaking adult Quebec population and to highlight the characteristics of the vaccine campaign that were of major importance.MethodsA discrete-choice experiment (DCE) was conducted between April and June 2021, in Quebec, Canada. A quota sampling method by age, gender and educational level was used to achieve a representative sample of the French-speaking adult population. The choice-based exercise was described by seven attributes within a vaccine campaign scenario. A mixed logit (MXL) model and a latent class logit (LCL) model were used to derive utility values. Age, gender, educational level, income and fear of COVID-19 were included as independent variables in the LCL.ResultsA total of 1883 respondents were included for analysis, yielding 22,586 choices. From these choices, 3425 (15.16%) were refusals. In addition, 1159 (61.55%) individuals always accepted any of the vaccination campaigns, while 92 individuals (4.89%) always refused vaccine alternatives. According to the MXL, relative weight importance of attributes was effectiveness (32.50%), risk of side effects (24.76%), level of scientific evidence (22.51%), number of shots (15.73%), priority population (3.60%), type of vaccine (0.61%), and vaccination location (0.28%). Four classes were derived from the LCL model and attributes were more or less important according to them. Class 1 (19.8%) was more concerned about the effectiveness (27.99%), safety (24.22%) and the number of shots (21.82%), class 2 (55.3%) wanted a highly effective vaccine (40.16%) and class 3 (17.6%) gave high value to the scientific evidence (42.00%). Class 4 preferences (7.4%) were more balanced, with each attribute having a relative weight ranging from 1.84% (type of vaccine) to 21.32% (risk of side effects). Membership posterior probabilities to latent classes were found to be predicted by individual factors such as gender, annual income or fear of COVID-19.ConclusionsVaccination acceptance relies on multiple factors. This study allowed assessment of vaccination-specific issues through a choice-based exercise and description of factors influencing this choice by segmenting the sample and drawing profiles of individuals. Moreover, besides effectiveness and safety, a major point of this study was to show the importance given by the general population to the level of scientific evidence surrounding vaccines.Patient or Public ContributionA small group of citizens was involved in the conception, design and interpretation of data. Participants of the DCE were all from the general population.