Are you for real? Maximizing participant eligibility on Amazon's Mechanical Turk

Kim, Hyoun S.; Hodgins, David C.

doi:10.1111/add.15065

Cited by 17 publications

(7 citation statements)

References 18 publications

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“…To ensure data quality, minimum qualifications were specified to initiate the survey (task approval rating > 97%, successful completion of more than 100, but fewer than 10,000 tasks, US-based IP address) [50]. Additional checks were embedded within the survey to screen out potential use of virtual private networks (VPNs) to mimic US-based IP addresses, eliminate bots, and manage careless responses [51]. Failing at these checkpoints resulted in immediate termination of the task and exclusion from the study, but no other exclusion criteria were applied.…”

Section: Data Collectionmentioning

confidence: 99%

Misinformation about COVID-19: evidence for differential latent profiles and a strong association with trust in science

2021

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Background The global spread of coronavirus disease 2019 (COVID-19) has been mirrored by diffusion of misinformation and conspiracy theories about its origins (such as 5G cellular networks) and the motivations of preventive measures like vaccination, social distancing, and face masks (for example, as a political ploy). These beliefs have resulted in substantive, negative real-world outcomes but remain largely unstudied. Methods This was a cross-sectional, online survey (n=660). Participants were asked about the believability of five selected COVID-19 narratives, their political orientation, their religious commitment, and their trust in science (a 21-item scale), along with sociodemographic items. Data were assessed descriptively, then latent profile analysis was used to identify subgroups with similar believability profiles. Bivariate (ANOVA) analyses were run, then multivariable, multivariate logistic regression was used to identify factors associated with membership in specific COVID-19 narrative believability profiles. Results For the full sample, believability of the narratives varied, from a low of 1.94 (SD=1.72) for the 5G narrative to a high of 5.56 (SD=1.64) for the zoonotic (scientific consensus) narrative. Four distinct belief profiles emerged, with the preponderance (70%) of the sample falling into Profile 1, which believed the scientifically accepted narrative (zoonotic origin) but not the misinformed or conspiratorial narratives. Other profiles did not disbelieve the zoonotic explanation, but rather believed additional misinformation to varying degrees. Controlling for sociodemographics, political orientation and religious commitment were marginally, and typically non-significantly, associated with COVID-19 belief profile membership. However, trust in science was a strong, significant predictor of profile membership, with lower trust being substantively associated with belonging to Profiles 2 through 4. Conclusions Belief in misinformation or conspiratorial narratives may not be mutually exclusive from belief in the narrative reflecting scientific consensus; that is, profiles were distinguished not by belief in the zoonotic narrative, but rather by concomitant belief or disbelief in additional narratives. Additional, renewed dissemination of scientifically accepted narratives may not attenuate belief in misinformation. However, prophylaxis of COVID-19 misinformation might be achieved by taking concrete steps to improve trust in science and scientists, such as building understanding of the scientific process and supporting open science initiatives.

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Section: Data Collectionmentioning

confidence: 99%

Misinformation about COVID-19: evidence for differential latent profiles and a strong association with trust in science

2021

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“…50 Additional checks were embedded within the survey to screen out potential use of virtual private networks (VPNs) to mimic US-based IP addresses, eliminate bots, and manage careless responses. 51 Failing at these checkpoints resulted in immediate termination of the task and exclusion from the study, but no other exclusion criteria were applied. Participants who successfully completed the survey were compensated $1.00 USD.…”

Section: Data Collectionmentioning

confidence: 99%

“…VPNs) to mimic US-based IP addresses, eliminate bots, and manage careless responses 51. Failing at these checkpoints resulted in immediate termination of the task and exclusion from the study, but no other exclusion criteria were applied.…”

mentioning

confidence: 99%

Misinformation about COVID-19: Evidence for Differential Latent Profiles and a Strong Association with Trust in Science

Agley

Xiao

2020

Preprint

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BackgroundThe global spread of coronavirus disease 2019 (COVID-19) has been mirrored by diffusion of misinformation and conspiracy theories about its origins (such as 5G cellular networks) and the motivations of preventive measures like vaccination, social distancing, and face masks (for example, as a political ploy). These beliefs have resulted in substantive, negative real-world outcomes but remain largely unstudied.MethodsThis was a cross-sectional, online survey (n=660). Participants were asked about the believability of five selected COVID-19 narratives, their political orientation, their religious commitment, and their trust in science (a 21-item scale), along with sociodemographic items. Data were assessed descriptively, then latent profile analysis was used to identify subgroups with similar believability profiles. Bivariate (ANOVA) analyses were run, then multivariable, multivariate logistic regression was used to identify factors associated with membership in specific COVID-19 narrative believability profiles.ResultsFor the full sample, believability of the narratives varied, from a low of 1.94 (SD=1.72) for the 5G narrative to a high of 4.56 (SD=1.64) for the zoonotic (scientific consensus) narrative. Four distinct belief profiles emerged, with the preponderance (70%) of the sample falling into Profile 1, which believed the scientifically accepted narrative (zoonotic origin) but not the misinformed or conspiratorial narratives. Other profiles did not disbelieve the zoonotic explanation, but rather believed additional misinformation to varying degrees. Controlling for sociodemographics, political orientation and religious commitment were marginally, and typically non-significantly, associated with COVID-19 belief profile membership. However, trust in science was a strong, significant predictor of profile membership, with lower trust being substantively associated with belonging to Profiles 2 through 4.ConclusionsBelief in misinformation or conspiratorial narratives may not be mutually exclusive from belief in the narrative reflecting scientific consensus; that is, profiles were distinguished not by belief in the zoonotic narrative, but rather by concomitant belief or disbelief in additional narratives. Additional, renewed dissemination of scientifically accepted narratives may not attenuate belief in misinformation. However, prophylaxis of COVID-19 misinformation might be achieved by taking concrete steps to improve trust in science and scientists, such as building understanding of the scientific process and supporting open science initiatives.

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“…Using a competing platform that is similar to mTurk, researchers were also able to replicate well-established experimental findings [23]. For this study, in response to recent concerns about non-compliant mTurk workers [24], checks were embedded in the Qualtrics survey to eliminate potential bots, avoid duplicate responses, and ensure eligibility.…”

Section: Data Collectionmentioning

confidence: 99%

Opioid use, motivation to quit, and treatment status related to COVID-19: a cross-sectional study

et al. 2021

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Objective Persons who use opioids may be at elevated risk of harm from the coronavirus disease 2019 (COVID-19) pandemic, yet few data currently exist that can be used to examine this risk. As part of a rapid response survey, this study measured opioid users’ perceptions of risk or harm from COVID-19, as well as potential changes in motivation to quit, frequency of use, and engagement with treatment. Data collected from Amazon’s Mechanical Turk (n = 562) were analyzed. Results Participants perceived modest risk elevation from COVID-19 due to their opioid use, and perceived moderate risk to themselves or their community from COVID-19. Since learning about COVID-19, 31.2% reported decreasing their opioid use, and 26.0% reported increased motivation to quit. Thirty-seven percent of participants reported both their use and motivation to quit stayed the same; 16.6% reported decreased use and increased motivation to quit. Participants who reported that their opioid use increased after learning about COVID-19, or whose motivation to quit opioids decreased, were more likely to also be engaged in treatment than those whose use or motivation stayed the same. These preliminary findings suggest that there likely is an association between COVID-19, opioid use, and treatment engagement that merits further in-depth investigation.

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Are you for real? Maximizing participant eligibility on Amazon's Mechanical Turk

Cited by 17 publications

References 18 publications

Misinformation about COVID-19: evidence for differential latent profiles and a strong association with trust in science

Misinformation about COVID-19: evidence for differential latent profiles and a strong association with trust in science

Misinformation about COVID-19: Evidence for Differential Latent Profiles and a Strong Association with Trust in Science

Opioid use, motivation to quit, and treatment status related to COVID-19: a cross-sectional study

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