Evaluating and Improving the Quality of Survey Data From Panel and Crowd-Sourced Samples: A Practical Guide for Psychological Research

Public Health Significance The findings demonstrate that while Qualtrics's paid internal data quality process flags and remove many low-quality participants, there is still a large portion of participants that should be screened for quality issues by researchers manually. The presented study provides a practical guide for implementing a rigorous data screening procedure to maximize the quality of panel and crowd-sourced survey data. The use of crowd-sourced and panel survey data in addiction research has become widespread. However, the validity of data obtained from newer panels such as Qualtrics has not been extensively evaluated. Furthermore, few addiction researchers appear to employ previously recommended guidelines for maximizing the quality of data obtained from panel samples. The goals of the present study were as follows: (a) to evaluate the quality of survey data obtained from Qualtrics including an evaluation of the company's internal data screening process and (b) to provide a practical implementation guide for data screening practices that maximize the quality of data obtained via panel and crowd-sourced samples. To address the goals, two panel samples evaluating vaping and video gaming behaviors were recruited in Canada via Qualtrics and underwent Qualtrics's internal data screening process before being rigorously rescreened by the authors. The results demonstrate that while Qualtrics's paid internal data quality process flags and removes many low-quality participants, there is still a large portion of participants presented by Qualtrics as high-quality that are likely low-quality responses that need to be screened out. The presented methodology provides a rigorous data screening protocol, including step-by-step application, for crowd-sourced samples in addictive behavior research for maximizing data quality. Researchers should be cautious in the use of Qualtrics data for administration of addiction survey research and are encouraged to use additional data screening procedures to maximize data quality.

Automated summary

This study evaluates the quality of survey data obtained from Qualtrics and provides a practical method for data screening to maximize the quality of panel and crowd-sourced samples. The results show that while Qualtrics's internal data quality process removes many low-quality participants, there are still high-quality participants that are likely to be low-quality responses and need to be screened out.