Crowdsourcing Methods in Addiction Science: Emerging Research and Best Practices INTRODUCTION

被引:7
作者
Strickland, Justin C. [1 ]
Amlung, Michael [2 ,3 ]
Reed, Derek D. [2 ,3 ]
机构
[1] Johns Hopkins Univ, Dept Psychiat & Behav Sci, Sch Med, 5510 Nathan Shock Dr, Baltimore, MD 21224 USA
[2] Univ Kansas, Dept Appl Behav Sci, Lawrence, KS 66045 USA
[3] Cofrin Logan Ctr Addict Res & Treatment, Lawrence, KS USA
关键词
crowdsourcing; methods; mTurk; Prolific; validity;
D O I
10.1037/pha0000582
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
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.
引用
收藏
页码:379 / 380
页数:2
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