Prior studies linking grit — defined as perseverance and passion for long-term goals — to performance are beset by contradictory evidence. As a result, commentators have increasingly declared that grit has limited effects. We propose that this inconsistent evidence has occurred because prior research has emphasized perseverance and ignored, both theoretically and empirically, the critical role of passion, which we define as a strong feeling toward a personally important value/preference that motivates intentions and behaviors to express that value/preference. We suggest that combining the grit scale — which only captures perseverance — with a measure that assesses whether individuals attain desired levels of passion will predict performance. We first metaanalyzed 127 studies (n = 45,485) that used the grit scale and assessed performance, and found that effect sizes are larger in studies where participants were more passionate for the performance domain. Second, in a survey of employees matched to supervisor-rated job performance (n = 422), we found that the combination of perseverance, measured through the grit scale, and passion attainment, measured through a new scale, predicted higher performance. A final study measured perseverance and passion attainment in a sample of students (n = 248) and linked these to their grade-point average (GPA), finding that the combination of perseverance and passion attainment predicted higher GPAs in part through increased immersion. The present results help resolve the mixed evidence of grit's relationship with performance by highlighting the important role that passion plays in predicting performance. By adequately measuring both perseverance and passion, the present research uncovers grit's true predictive power.

J.M. Jachimowicz, A. Wihler, E.R. Bailey, and Adam Galinsky
Journal Article
Publication Date
Proceedings of the National Academy of Sciences

Full Citation

Jachimowicz, J.M., A. Wihler, E.R. Bailey, and Adam Galinsky
. “Why grit requires perseverance and passion to positively predict performance.”
Proceedings of the National Academy of Sciences
, (January 01, 2018):