Please use this identifier to cite or link to this item: http://ir.mu.ac.ke:8080/jspui/handle/123456789/6536
Title: Incorporating respondent‑driven sampling into web‑based discrete choice experiments: preferences for COVID‑19 mitigation measures
Authors: Johnson, Courtney A
Tran, Dan N
Mwangi, Ann
Sosa‑Rubí, Sandra G.
Chivardi, Carlos
Romero‑Martínez, Martín
Pastakia, Sonak
Robinson, Elisha
Mayo‑Wilson, Larissa Jennings
Galárraga, Omar
Keywords: Discrete choice experiment
Respondent driven sampling
COVID-19
Non pharmaceutical interventions
Issue Date: 25-Nov-2021
Publisher: Springer
Abstract: To slow the spread of COVID-19, most countries implemented stay-at-home orders, social distancing, and other nonpharmaceutical mitigation strategies. To understand individual preferences for mitigation strategies, we piloted a web-based Respondent Driven Sampling (RDS) approach to recruit participants from four universities in three countries to complete a computer-based Discrete Choice Experiment (DCE). Use of these methods, in combina tion, can serve to increase the external validity of a study by enabling recruitment of popu lations underrepresented in sampling frames, thus allowing preference results to be more generalizable to targeted subpopulations. A total of 99 students or staf members were invited to complete the survey, of which 72% started the survey (n=71). Sixty-three partic ipants (89% of starters) completed all tasks in the DCE. A rank-ordered mixed logit model was used to estimate preferences for COVID-19 nonpharmaceutical mitigation strategies. The model estimates indicated that participants preferred mitigation strategies that resulted in lower COVID-19 risk (i.e. sheltering-in-place more days a week), fnancial compensa tion from the government, fewer health (mental and physical) problems, and fewer fnan cial problems. The high response rate and survey engagement provide proof of concept that RDS and DCE can be implemented as web-based applications, with the potential for scale up to produce nationally-representative preference estimates.
URI: https://doi.org/10.1007/s10742-021-00266-4
http://ir.mu.ac.ke:8080/jspui/handle/123456789/6536
Appears in Collections:School of Medicine

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.