ScholarOne - Insufficient Effort Responding and Adolescent Respondents: Measurement, Extent, and Prediction

This paper addresses insufficient effort responding (IER), a significant issue in survey research affecting data quality. We focus on IER prediction through nonreactive measures and gauge its prevalence in a pupil population, leveraging a sizable online survey of adolescents. The analysis uncovers IER as a nonmarginal issue that varies considerably by gender, migration status, and school type. Utilizing Random Forest models, we evaluate nonreactive measures’ predictive power for IER, notably response time, intra-individual response variability, and Mahalanobis distance. The findings highlight the future research value of these measures, emphasizing the strong influence of response time. We also explore the relationship between predictors and IER and find that shorter response times and less response variability correspond to a greater likelihood of IER. This study illustrates the potential of nonreactive measures and advanced machine learning techniques for predicting IER and highlights the necessity for further research.