BackgroundMechanical Turk (MTurk) is an online portal operated by Amazon where ‘requesters’ (individuals or businesses) can submit jobs for ‘workers.’ MTurk is used extensively by academics as a quick and cheap means of collecting questionnaire data, including information on alcohol consumption, from a diverse sample of participants. We tested the feasibility of recruiting for alcohol Internet intervention trials through MTurk.MethodsParticipants, 18 years or older, who drank at least weekly were recruited for four intervention trials (combined sample size, N = 11,107). The same basic recruitment strategy was employed for each trial – invite participants to complete a survey about alcohol consumption (less than 15 min in length, US$1.50 payment), identify eligible participants who drank in a hazardous fashion, invite those eligible to complete a follow-up survey ($10 payment), randomize participants to be sent or not sent information to access an online intervention for hazardous alcohol use. Procedures where put in place to optimize the chances that participants could only complete the baseline survey once.ResultsThere was a substantially slower rate of recruitment by the fourth trial compared to the earlier trials. Demographic characteristics also varied across trials (age, sex, employment and marital status). Patterns of alcohol consumption, while displaying some differences, did not appear to vary in a linear fashion between trials.ConclusionsIt is possible to recruit large (but not inexhaustible) numbers of people who drink in a hazardous fashion. Issues for online intervention research when employing this sample are discussed.
While the Internet has become a popular and effective strategy for recruiting substance users into research, there is a large risk of recruiting duplicate individuals and Internet bots that pose as humans. Strategies to mitigate these issues are outlined and categorized into two groups: (1) automatic techniques which are often embedded into surveys and (2) ongoing manual techniques implemented during recruitment. Potential limitations of these strategies are discussed, and an example of the prevalence of duplicate data within a substance using sample is provided. Overall, it is recommended that researchers consider the use of routine strategies to mitigate the risks associated with recruiting online samples such as: verifying participant contact information, IP address checks, and ongoing cross-checking of participant information for duplicates, similarities and inconsistencies.
ObjectivesTo determine whether Amazon's Mechanical Turk (MTurk) might be a viable means of recruiting participants for online intervention research. This was accomplished by conducting a randomized controlled trial of a previously validated intervention with participants recruited through MTurk.MethodsParticipants were recruited to complete an online survey about their alcohol use through the MTurk platform. Those who met eligibility criterion for age and problem drinking were invited to complete a 3-month follow-up. Those who agreed were randomized to receive access to an online brief intervention for drinking or were assigned to a no intervention control group (i.e., thanked and told that they would be re-contacted in 3 months).ResultsA total of 423 participants were recruited, of which 85% were followed-up at 3-months. All participants were recruited in 3.2 h. Only 1/3 of participants asked to access the online brief intervention did so. Of the 4 outcome variables (number of drinks in a typical week, highest number on one occasion, number of consequences, AUDIT consumption subscale), one displayed a significant difference between conditions. Participants in the intervention group reported a greater reduction between on the AUDIT consumption subscale between baseline and 3-month follow-up compared to those in the no intervention control group (p = 0.004).ConclusionsDespite the current pilot showing only limited evidence of impact of the intervention among participants recruited through MTurk, there is potential for conducting trials employing this population (particularly if methods are employed to make sure that participants receive the intervention). This potential is important as it could allow for the rapid conduct of multiple trials during the development stages of online interventions.
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