Strategies for monitoring mentoring relationship quality to predict early program dropout.

Abstract

We examined data from a nationally implemented mentoring program over a 4‐year period, to identify demographic and relationship characteristics associated with premature termination. Data were drawn from a sample of 82,224 mentor and mentees. We found matches who reported shared racial or ethnic identities were associated with lower likelihood of premature termination as was mentee's positive feelings of the relationship. We also found that, if data were used as a screening tool, the data were suboptimal for accuracy classifying premature closure with sensitivity and specificity values equal to 0.43 and 0.75. As programs and policymakers consider ways to improve the impact of mentoring programs, these results suggest programs consider the types of data being collected to improve impact of care.