Insufficient effort responding (IER) refers to a lack of effort when answering survey or questionnaire items. Such items typically offer more than two ordered response categories, with Likert-type scales as the most prominent example. The underlying assumption is that the successive categories reflect increasing levels of the latent variable assessed. This research investigates how IER affects the intended category order of Likert-type scales, focusing on the category thresholds in the polytomous Rasch model. In a simulation study, we examined several IER patterns in datasets generated from the mixture model for IER (MMIER). The key findings were (a) random responding and overusing the non-extreme categories of a five-category scale were each associated with high frequencies of disordered category thresholds; (b) raising the IER rate from 5% to 10% led to a substantial increase in threshold disordering, particularly among easy and difficult items; (c) narrow distances between adjacent categories (0.5 logits) were associated with more frequent disordering, compared with wide distances (1.0 logits). Two real-data examples highlighted the efficiency and utility of the MMIER for detecting latent classes of respondents exhibiting different forms of IER. Under the MMIER, the frequency of disordered thresholds was reduced substantially in both examples. The discussion focuses on the practical implications of using the MMIER in survey research and points to directions for future research.