Crowdsourcing Methods in Addiction Science: Emerging Research and Best Practices
Crowdsourcing platforms such as Amazon Mechanical Turk, Prolific, and Qualtrics Panels have become a dominant form of sampling in recent years. Crowdsourcing enables researchers to effectively and efficiently sample research participants with greater geographic variability, access to hard-to-reach p...
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Veröffentlicht in: | Experimental and clinical psychopharmacology 2022-08, Vol.30 (4), p.379-380 |
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description | Crowdsourcing platforms such as Amazon Mechanical Turk, Prolific, and Qualtrics Panels have become a dominant form of sampling in recent years. Crowdsourcing enables researchers to effectively and efficiently sample research participants with greater geographic variability, access to hard-to-reach populations, and reduced costs. These methods have been increasingly used across varied areas of psychological science and essential for research during the COVID-19 pandemic due to their facilitation of remote research. Recent work documents methods for improving data quality, emerging crowdsourcing platforms, and how crowdsourcing data fit within broader research programs. Addiction scientists will benefit from the adoption of best practice guidelines in crowdsourcing as well as developing novel approaches, venues, and applications to advance the field.
Public Health Significance
The following set of articles in this special issue describes best practice methods and novel applications of crowdsourcing in addiction and psychological science. These articles advance the field and present practical guidelines and open-source resources for researchers using crowdsourcing in future work. |
doi_str_mv | 10.1037/pha0000582 |
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Public Health Significance
The following set of articles in this special issue describes best practice methods and novel applications of crowdsourcing in addiction and psychological science. These articles advance the field and present practical guidelines and open-source resources for researchers using crowdsourcing in future work.</description><identifier>ISSN: 1064-1297</identifier><identifier>ISBN: 9781433896033</identifier><identifier>ISBN: 1433896036</identifier><identifier>EISSN: 1936-2293</identifier><identifier>DOI: 10.1037/pha0000582</identifier><identifier>PMID: 35862134</identifier><language>eng</language><publisher>United States: American Psychological Association</publisher><subject>Addiction ; Behavior, Addictive ; Best Practices ; COVID-19 ; Crowdsourcing ; Crowdsourcing - methods ; Experimental Methods ; Experimental Subjects ; Human ; Humans ; Online Experiments ; Pandemics ; Statistical Validity</subject><ispartof>Experimental and clinical psychopharmacology, 2022-08, Vol.30 (4), p.379-380</ispartof><rights>2022 American Psychological Association</rights><rights>2022, American Psychological Association</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a3582-fe234e637a37f734b64a82c4d17e42412e3d0fe624982009f973786941ceee8d3</citedby><orcidid>0000-0003-1077-0394</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27923,27924</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35862134$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Reed, Derek D</contributor><contributor>Stoops, William W</contributor><contributor>Strickland, Justin C</contributor><contributor>Amlung, Michael</contributor><creatorcontrib>Strickland, Justin C.</creatorcontrib><creatorcontrib>Amlung, Michael</creatorcontrib><creatorcontrib>Reed, Derek D.</creatorcontrib><title>Crowdsourcing Methods in Addiction Science: Emerging Research and Best Practices</title><title>Experimental and clinical psychopharmacology</title><addtitle>Exp Clin Psychopharmacol</addtitle><description>Crowdsourcing platforms such as Amazon Mechanical Turk, Prolific, and Qualtrics Panels have become a dominant form of sampling in recent years. Crowdsourcing enables researchers to effectively and efficiently sample research participants with greater geographic variability, access to hard-to-reach populations, and reduced costs. These methods have been increasingly used across varied areas of psychological science and essential for research during the COVID-19 pandemic due to their facilitation of remote research. Recent work documents methods for improving data quality, emerging crowdsourcing platforms, and how crowdsourcing data fit within broader research programs. Addiction scientists will benefit from the adoption of best practice guidelines in crowdsourcing as well as developing novel approaches, venues, and applications to advance the field.
Public Health Significance
The following set of articles in this special issue describes best practice methods and novel applications of crowdsourcing in addiction and psychological science. 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Public Health Significance
The following set of articles in this special issue describes best practice methods and novel applications of crowdsourcing in addiction and psychological science. These articles advance the field and present practical guidelines and open-source resources for researchers using crowdsourcing in future work.</abstract><cop>United States</cop><pub>American Psychological Association</pub><pmid>35862134</pmid><doi>10.1037/pha0000582</doi><tpages>2</tpages><orcidid>https://orcid.org/0000-0003-1077-0394</orcidid><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; EBSCOhost APA PsycARTICLES |
subjects | Addiction Behavior, Addictive Best Practices COVID-19 Crowdsourcing Crowdsourcing - methods Experimental Methods Experimental Subjects Human Humans Online Experiments Pandemics Statistical Validity |
title | Crowdsourcing Methods in Addiction Science: Emerging Research and Best Practices |
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