Crowdsourcing methods in addiction science: Emerging research and best practices

Area of Science:

• Psychological science
• Addiction science

Background:

• Crowdsourcing platforms (e.g., Amazon Mechanical Turk, Prolific) are increasingly dominant for research participant sampling.
• These platforms facilitate remote research, essential during the COVID-19 pandemic.
• They offer advantages like geographic variability, access to hard-to-reach populations, and reduced costs.

Purpose of the Study:

• To highlight the benefits and methods of using crowdsourcing for research participant sampling.
• To emphasize the importance of best practices and novel applications in crowdsourcing for addiction science.
• To document emerging platforms and data quality improvement techniques.

Main Methods:

• Review of current literature on crowdsourcing platforms in research.
• Documentation of methods for improving data quality in crowdsourced samples.
• Identification of emerging crowdsourcing platforms and their applications.

Main Results:

• Crowdsourcing provides efficient, cost-effective, and geographically diverse participant sampling.
• Remote research capabilities of crowdsourcing were vital during the COVID-19 pandemic.
• Established methods exist for improving data quality and integrating crowdsourced data into research programs.

Conclusions:

• Addiction scientists should adopt best practice guidelines for crowdsourcing.
• Development of novel approaches and applications for crowdsourcing is encouraged to advance the field.
• Crowdsourcing represents a valuable and evolving methodology for psychological and addiction research.