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