Paid online convenience samples in gambling studies: questionable data quality

Abstract

The use of non-probability Internet panels and crowdsource websites is increasing in gambling research. These paid online sampling methods offer a convenient and inexpensive recruitment strategy. The quality of data may be questionable due to careless responding and identity misrepresentation which can bias study results. It is necessary to investigate data quality given the important implications of gambling research in guiding policy decisions, public health initiatives, and treatments. In this review article, we 1) critically analyze the advantages and limitations of paid online recruitment methods, including associated threats to data quality in the gambling literature; 2) present findings from a rapid review of gambling studies using online panel and crowdsource data; and 3) outline recommendations for maximizing data quality and trustworthiness of findings. Substantially overinflated problem gambling rates were found in the 63 gambling studies we reviewed; less than one-quarter had incorporated data quality checks and reported participation rates. Future studies should incorporate pre-registration of methodology and analysis plans, robust participant screening procedures, mid-survey attention and response consistency items, and an analysis of response quality post data collection. Applying these recommendations to nonrepresentative online panel and crowdsource-based studies may enhance the replicability of findings in additional studies using representative samples

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