Literature DB >> 30489114

The use of crowdsourcing in addiction science research: Amazon Mechanical Turk.

Justin C Strickland1, William W Stoops1.   

Abstract

Crowdsourcing, the use of the Internet to outsource work to a large number of people, has witnessed a dramatic growth over the past decade. One popular crowdsourcing option, Amazon Mechanical Turk (MTurk), is now commonly used to sample participants for psychological research. Addiction science is positioned to benefit greatly from crowdsourced sampling due to the ability to efficiently and effectively tap into populations with specific behavioral and health histories. The primary objective of this review is to describe the utility of crowdsourcing, broadly, and MTurk, specifically, for conducting research relevant to substance use and misuse. Studies in psychological and other health science have supported the reliability and validity of data gathered using crowdsourced samples. Promising research relevant to addiction science has also been conducted, including studies using cross-sectional designs and those for measure development purposes. Preliminary work using longitudinal methods and for interventions development has also revealed the potential of MTurk for studying alcohol and other drug use through these designs. Additional studies are needed to better understand the benefits, as well as the limits and constraints, of research conducted through crowdsourced online platforms. Crowdsourcing, such as on MTurk, can ultimately provide an important complement to existing methods used in human laboratory, clinical trial, community intervention, and epidemiological research. The combinations of these methodological approaches could help improve the rigor, reproducibility, and overall scope of research conducted in addiction science. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Entities:  

Mesh:

Year:  2018        PMID: 30489114     DOI: 10.1037/pha0000235

Source DB:  PubMed          Journal:  Exp Clin Psychopharmacol        ISSN: 1064-1297            Impact factor:   3.157


  64 in total

1.  The impact of naturalistic cannabis use on self-reported opioid withdrawal.

Authors:  Cecilia L Bergeria; Andrew S Huhn; Kelly E Dunn
Journal:  J Subst Abuse Treat       Date:  2020-03-30

2.  Modeling Treatment-Related Decision-Making Using Applied Behavioral Economics: Caregiver Perspectives in Temporally-Extended Behavioral Treatments.

Authors:  Shawn P Gilroy; Brent A Kaplan
Journal:  J Abnorm Child Psychol       Date:  2020-05

3.  Reward, Relief and Habit Drinking: Initial Validation of a Brief Assessment Tool.

Authors:  Erica N Grodin; Spencer Bujarski; Alexandra Venegas; Wave-Ananda Baskerville; Steven J Nieto; J David Jentsch; Lara A Ray
Journal:  Alcohol Alcohol       Date:  2019-12-01       Impact factor: 2.826

4.  Recruiting older adult participants through crowdsourcing platforms: Mechanical Turk versus Prolific Academic.

Authors:  Anne M Turner; Thomas Engelsma; Jean O Taylor; Rashmi K Sharma; George Demiris
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

5.  Evaluating non-medical prescription opioid demand using commodity purchase tasks: test-retest reliability and incremental validity.

Authors:  Justin C Strickland; Joshua A Lile; William W Stoops
Journal:  Psychopharmacology (Berl)       Date:  2019-03-29       Impact factor: 4.530

6.  An Assessment of the Rapid Decline of Trust in US Sources of Public Information about COVID-19.

Authors:  Carl A Latkin; Lauren Dayton; Justin C Strickland; Brian Colon; Rajiv Rimal; Basmattee Boodram
Journal:  J Health Commun       Date:  2020-10-02

7.  Cartoon-based e-cigarette marketing: Associations with susceptibility to use and perceived expectations of use.

Authors:  Matthew G Kirkpatrick; Tess Boley Cruz; Jennifer B Unger; Josseline Herrera; Sara Schiff; Jon-Patrick Allem
Journal:  Drug Alcohol Depend       Date:  2019-06-08       Impact factor: 4.492

8.  Contribution of cannabis-related cues to concurrent reinforcer choice in humans.

Authors:  Justin C Strickland; Joshua A Lile; William W Stoops
Journal:  Drug Alcohol Depend       Date:  2019-04-17       Impact factor: 4.492

9.  Development and Validation of the Recognizing Addictive Disorders Scale: A Transdiagnostic Measure of Substance-Related and Other Addictive Disorders.

Authors:  Meagan M Carr; Karen K Saules; Jennifer D Ellis; Angela Staples; David M Ledgerwood; Tamara M Loverich
Journal:  Subst Use Misuse       Date:  2020-07-29       Impact factor: 2.164

10.  Randomized comparison of two web-based interventions on immediate and 30-day opioid overdose knowledge in three unique risk groups.

Authors:  Cecilia L Bergeria; Andrew S Huhn; Kelly E Dunn
Journal:  Prev Med       Date:  2019-05-10       Impact factor: 4.018

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