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      Obtaining quality data using behavioral measures of impulsivity in gambling research with Amazon’s Mechanical Turk

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          Abstract

          Background and aims

          To date, no research has examined the viability of using behavioral tasks typical of cognitive and neuropsychology within addiction populations through online recruitment methods. Therefore, we examined the reliability and validity of three behavioral tasks of impulsivity common in addiction research in a sample of individuals with a current or past history of problem gambling recruited online.

          Methods

          Using a two-stage recruitment process, a final sample of 110 participants with a history of problem or disordered gambling were recruited through MTurk and completed self-report questionnaires of gambling involvement symptomology, a Delay Discounting Task (DDT), Balloon Analogue Risk Task (BART), Cued Go/No-Go Task, and the UPPS-P.

          Results

          Participants demonstrated logically consistent responding on the DDT. The area under the empirical discounting curve (AUC) ranged from 0.02 to 0.88 ( M = 0.23). The BART demonstrated good split-third reliability (ρs = 0.67 to 0.78). The tasks generally showed small correlations with each other (ρs = ±0.06 to 0.19) and with UPPS-P subscales (ρs = ±0.01 to 0.20).

          Discussion and conclusions

          The behavioral tasks demonstrated good divergent validity. Correlation magnitudes between behavioral tasks and UPPS-P scales and mean scores on these measures were generally consistent with the existing literature. Behavioral tasks of impulsivity appear to have utility for use with problem and disordered gambling samples collected online, allowing researchers a cost efficient and rapid avenue for conducting behavioral research with gamblers. We conclude with best-practice recommendations for using behavioral tasks using crowdsourcing samples.

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          Most cited references49

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          Impulsivity as a vulnerability marker for substance-use disorders: review of findings from high-risk research, problem gamblers and genetic association studies.

          There is a longstanding association between substance-use disorders (SUDs) and the psychological construct of impulsivity. In the first section of this review, personality and neurocognitive data pertaining to impulsivity will be summarised in regular users of four classes of substance: stimulants, opiates, alcohol and 3,4-methylenedioxymethamphetamine (MDMA). Impulsivity in these groups may arise via two alternative mechanisms, which are not mutually exclusive. By one account, impulsivity may occur as a consequence of chronic exposure to substances causing harmful effects on the brain. By the alternative account, impulsivity pre-dates SUDs and is associated with the vulnerability to addiction. We will review the evidence that impulsivity is associated with addiction vulnerability by considering three lines of evidence: (i) studies of groups at high-risk for development of SUDs; (ii) studies of pathological gamblers, where the harmful consequences of the addiction on brain structure are minimised, and (iii) genetic association studies linking impulsivity to genetic risk factors for addiction. Within each of these three lines of enquiry, there is accumulating evidence that impulsivity is a pre-existing vulnerability marker for SUDs.
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            Conducting Clinical Research Using Crowdsourced Convenience Samples.

            Crowdsourcing has had a dramatic impact on the speed and scale at which scientific research can be conducted. Clinical scientists have particularly benefited from readily available research study participants and streamlined recruiting and payment systems afforded by Amazon Mechanical Turk (MTurk), a popular labor market for crowdsourcing workers. MTurk has been used in this capacity for more than five years. The popularity and novelty of the platform have spurred numerous methodological investigations, making it the most studied nonprobability sample available to researchers. This article summarizes what is known about MTurk sample composition and data quality with an emphasis on findings relevant to clinical psychological research. It then addresses methodological issues with using MTurk--many of which are common to other nonprobability samples but unfamiliar to clinical science researchers--and suggests concrete steps to avoid these issues or minimize their impact.
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              Area under the curve as a measure of discounting.

              We describe a novel approach to the measurement of discounting based on calculating the area under the empirical discounting function. This approach avoids some of the problems associated with measures based on estimates of the parameters of theoretical discounting functions. The area measure may be easily calculated for both individual and group data collected using any of a variety of current delay and probability discounting procedures. The present approach is not intended as a substitute for theoretical discounting models. It is useful, however, to have a simple, univariate measure of discounting that is not tied to any specific theoretical framework.
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                Author and article information

                Journal
                jba
                JBA
                Journal of Behavioral Addictions
                J Behav Addict
                Akadémiai Kiadó (Budapest )
                2062-5871
                2063-5303
                06 December 2018
                December 2018
                : 7
                : 4
                : 1122-1131
                Affiliations
                [ 1 ]Department of Psychology, University of Calgary , Calgary, AB, Canada
                Author notes
                [* ]Corresponding author: Magdalen G. Schluter, MSc; Department of Psychology, University of Calgary, 2500 University Drive NW, Calgary T2N 1N4, AB, Canada; Phone: +1 403 210 9500; E-mail: Magdalen.schluter@ 123456ucalgary.ca
                Article
                10.1556/2006.7.2018.117
                6376390
                30522339
                87a65a31-c6b6-4595-a0d6-170d292c1075
                © 2018 The Author(s)

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited, a link to the CC License is provided, and changes – if any – are indicated.

                History
                : 20 February 2018
                : 23 July 2018
                : 12 October 2018
                : 10 November 2018
                Page count
                Figures: 1, Tables: 3, Equations: 0, References: 55, Pages: 10
                Funding
                Funding sources: None.
                Categories
                FULL-LENGTH REPORT

                Evolutionary Biology,Medicine,Psychology,Educational research & Statistics,Social & Behavioral Sciences
                gambling,impulsivity,MTurk,behavioral tasks,crowdsourcing

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