Flagging insufficient effort responses in surveys: Stopping rule to prevent insufficient or excessive removal of doubtful data

Detecting participants not exerting sufficient effort (e.g., answering randomly; termed 'insufficient effort responding' or IER) in self -report surveys is crucial but intricate. Challenges of appropriately removing IER resemble a surgeon excising necrotic tissue without being inadequate, excessive, or incorrect. Current cutoff criteria for stopping the elimination of suspected IER responses are often arbitrary. This study proposes an external criterion strategy to identify the optimal cutoff values for various IER detection methods. We investigated the change in correlations between the IER-containing scale (e.g., motivation) and the external criterion (e. g., academic performance, socioeconomic status index, or another questionnaire scale) utilizing simulated and authentic international survey data. The findings revealed that the stopping rule and consequently, the optimal cutoff values for IER detection methods, can be accurately identified by locating the inflection point in the correlation plot with the external criterion. Practical strategies are recommended for applied researchers.