Effects of Excluding Those Who Report Having "Syndomitis" or "Chekalism" on Data Quality: Longitudinal Health Survey of a Sample From Amazon's Mechanical Turk.

ABSTRACT:

Background

Researchers have implemented multiple approaches to increase data quality from existing web-based panels such as Amazon's Mechanical Turk (MTurk).

Objective

This study extends prior work by examining improvements in data quality and effects on mean estimates of health status by excluding respondents who endorse 1 or both of 2 fake health conditions ("Syndomitis" and "Chekalism").

Methods

Survey data were collected in 2021 at baseline and 3 months later from MTurk study participants, aged 18 years or older, with an internet protocol address in the United States, and who had completed a minimum of 500 previous MTurk "human intelligence tasks." We included questions about demographic characteristics, health conditions (including the 2 fake conditions), and the

SUBMITTER: Hays RD 

PROVIDER: S-EPMC10439462 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature