Digital mental health interventions (DMHIs) have the potential to expand treatment access for anxiety but often have low user engagement. The present study analyzed differences in psychosocial outcomes for different behavioral engagement patterns in a free web-based cognitive bias modification for interpretation (CBM-I) program. CBM-I is designed to shift interpretation biases common in anxiety by providing practice thinking about emotionally ambiguous situations in less threatening ways. Using data from 697 anxious community adults undergoing five weekly sessions of CBM-I in a clinical trial, we extracted program use markers based on task completion rate and time spent on training and assessment tasks. After using an exploratory cluster analysis of these markers to create two engagement groups (whose patterns ended up reflecting generally more vs. less time spent across tasks), we used multilevel models to test for group differences in interpretation bias and anxiety outcomes. Unexpectedly, engagement group did not significantly predict differential change in positive interpretation bias or anxiety. Further, participants who generally spent less time on the program (including both training and assessment tasks) improved in negative interpretation bias (on one of two measures) significantly more during the training phase than those who spent more time (and post hoc tests found were significantly older and slightly less educated). However, participants who generally spent less time had a significant loss in training gains for negative bias (on both measures) by 2-month follow-up. Findings highlight the challenge of interpreting time spent as a marker of engagement and the need to consider cognitive and affective markers of engagement in addition to behavioral markers. Further understanding engagement patterns holds promise for improving DMHIs for anxiety.