Conducting Clinical Research Using Crowdsourced Convenience Samples.

Area of Science:

• Clinical Psychology
• Human-Computer Interaction
• Research Methodology

Background:

• Crowdsourcing platforms like Amazon Mechanical Turk (MTurk) have revolutionized scientific research speed and scale.
• MTurk provides clinical scientists with accessible participants and streamlined recruitment/payment systems.
• The platform has been utilized for over five years, leading to extensive methodological study.

Purpose of the Study:

• To summarize existing knowledge on MTurk sample composition and data quality.
• To focus on findings pertinent to clinical psychological research.
• To address methodological challenges of using MTurk and other nonprobability samples in clinical science.

Main Methods:

• Review of existing literature on Amazon Mechanical Turk (MTurk) for research.
• Analysis of MTurk sample characteristics and data quality metrics.
• Identification and discussion of methodological issues specific to nonprobability samples in clinical research.

Main Results:

• MTurk is the most studied nonprobability sample, offering insights into its composition and data quality.
• Findings are particularly relevant for clinical psychological research applications.
• Methodological issues, though common to nonprobability samples, require specific attention for clinical scientists.

Conclusions:

• Amazon Mechanical Turk (MTurk) is a valuable tool for clinical research but requires careful methodological consideration.
• Understanding MTurk's sample characteristics and data quality is crucial for reliable clinical study outcomes.
• Strategies are needed to mitigate potential biases and challenges associated with using MTurk in clinical psychological research.