Are poor quality data just random responses?: A crowdsourced study of delay discounting in alcohol use disorder.

ABSTRACT: Crowdsourced methods of data collection such as Amazon Mechanical Turk (MTurk) have been widely adopted in addiction science. Recent reports suggest an increase in poor quality data on MTurk, posing a challenge to the validity of findings. However, empirical investigations of data quality in addiction-related samples are lacking. In this study of individuals with alcohol use disorder (AUD), we compared poor quality delay discounting data to randomly generated data. A reanalysis of prior published delay discounting data was conducted comparing included, excluded, and randomly generated data samples. Nonsystematic criteria were implemented as a measure of data quality. The excluded data was statistically different from the included sample but did not differ from randomly generated data on mu

SUBMITTER: Craft WH 

PROVIDER: S-EPMC10132324 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature