Literature DB >> 27893213

Reliability and validity of data obtained from alcohol, cannabis, and gambling populations on Amazon's Mechanical Turk.

Hyoun S Kim1, David C Hodgins1.   

Abstract

Researchers recently have begun using Mechanical Turk (MTurk), an online crowdsourcing platform, to recruit addiction populations. However, whether the data obtained from substance users and gamblers on MTurk are reliable and valid is unknown. Herein, we assessed the internal and retest reliability of and concurrent and convergent validity of data obtained from addiction populations on MTurk. Current drinkers (N = 208), cannabis users (N = 200), and gamblers (N = 200) residing in the United States completed measures of alcohol, cannabis, and gambling severity, psychological constructs (e.g., impulsivity) related to addictions, overt and subtle measures of valid responding, and motivations for completing MTurk studies. Of the original sample, 88-92% of participants who provided informed consent for recontact completed a reassessment 1 week later. The internal consistency of the addiction severity measures ranged from α = .75 to .93. The stability over 1 week ranged from κ = .57 to .70 for categorical classification, and intraclass correlation coefficient (ICC) = .71 to .86 for continuous measures. The addiction measures were significantly correlated with each other and with other constructs related to addictive behaviors. Overall, 80-85% of participants provided valid responses. They reported attending and answering questions honestly, with financial motives being the most frequently endorsed motivation. After invalid responses were excluded, results remained the same for alcohol and gambling, but significant differences emerged for the cannabis sample. The results suggest that the self-report data obtained from alcohol and gambling populations are of high quality, however, caution is warranted with cannabis populations. MTurk shows promise as a recruitment tool for some addictive behaviors. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Entities:  

Mesh:

Year:  2016        PMID: 27893213     DOI: 10.1037/adb0000219

Source DB:  PubMed          Journal:  Psychol Addict Behav        ISSN: 0893-164X


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