Purpose: Employees at all organizational levels spend large portions of their work lives in meetings, many of which are not effective. Previous process-analytical research has identified counterproductive communication patterns to help explain why many meetings go wrong. This study aims to illustrate the ways in which counterproductive – and productive – meeting behaviors are related to individual work engagement and emotional exhaustion. Design/methodology/approach: The authors built a new research-based survey tool for measuring counterproductive meeting behaviors. An online sample of working adults (N = 440) was recruited to test the factor structure of this new survey and to examine the relationships between both good and bad meeting behaviors and employee attitudes beyond the meeting context. Findings: Using structural equation modeling, this study found that counterproductive meeting behaviors were linked to decreased employee engagement and increased emotional exhaustion, whereas good meeting behaviors were linked to increased engagement and decreased emotional exhaustion. These relationships were mediated via individual meeting satisfaction and perceived meeting effectiveness. Research limitations/implications: The study findings provide a nuanced view of meeting outcomes by showing that the behaviors that people observe in their meetings connect not only to meeting satisfaction and effectiveness but also to important workplace attitudes (i.e. employee engagement and emotional exhaustion). In other words, managers and meeting leaders need to be mindful of behavior in meetings, seek ways to mitigate poor behavior and seek opportunities to reward and encourage citizenship behavior. Originality/value: This study shows how good and bad meeting behaviors relate to employee perceptions of meeting effectiveness and individual job attitudes. The authors develop a science-based, practitioner-friendly new survey tool for observing counterproductive meeting behavior and offer a juxtaposition of good and bad meeting behaviors in a single model.