Understanding the Science of Effective Mentorship Networks for Underrepresented Researchers

项目摘要/摘要 我们的长期目标是确定有助于为来自 代表不足(UR)群体。有效的指导对留住早期职业研究人员至关重要 学术界。然而，来自UR小组的研究人员不太可能拥有有效的指导，这有助于 拨款和教职员工代表方面的差距。目前的趋势表明，二元导师制，即 是最常见的辅导形式，但可能不是最有效的辅导形式，尤其是对 代表不足的群体，因为它依赖于一个人提供学术和心理社会的许多方面 支持。我们假设，导师网络，包括具有不同角色的多名导师，是一种更 在留住和成功代表不足的研究人员方面，比导师二元组更有效的模型 学术界。导师网络如何影响研究成功，以及导师网络的哪些特点 对于早期职业生涯的重要性，UR研究人员还没有得到很好的理解。我们开发了一种新工具，名为 导师关系网络分析，评估和绘制个人的导师网络。我们将对此进行验证 UR职业发展(K)赠款的成功指导网络的工具和回顾特征 收件人。然后，我们将测试干预的可行性，以帮助UR研究人员建立有效的指导 网络。主要结果包括Mentor网络健壮性(即网络满足 受训人员)、职业成果和意图，以及以赠款和出版物衡量的研究成功。 次要结果包括研究成功的心理社会预测因素(例如研究自我效能)和 干预的可接受性和保真度。五年后，我们将更好地理解 成功的UR博士后研究人员的形成和随时间的变化，他们对职业生涯结果的影响，以及 UR导师网络的模式对成功至关重要。这些发现将满足人们对了解 最好是指导代表性不足的受训人员，告知对培训赠款和职业发展的投资 这些计划将缩小研究培训方面的指导差距。

Project Summary/Abstract Our long-term goal is to identify the factors that contribute to effective mentorship networks for researchers from underrepresented (UR) groups. Effective mentorship is critical for the retention of early career researchers in academia. However, researchers from UR groups are less likely to have effective mentorship, which contributes to disparities in grant funding and faculty representation. Current trends suggest that dyadic mentorship, which is the most common form of mentorship, may not be the most effective form of mentorship, especially for underrepresented groups, since it relies on one person to provide many aspects of academic and psychosocial support. We hypothesize that mentorship networks, which involve multiple mentors with various roles, is a more effective model than mentorship dyads for the retention and success of underrepresented researchers in academia. How mentorship networks affect research success and what characteristics of a mentorship network are important for early career UR researchers are not well-understood. We have developed a new tool called Mentorship Network Analysis that assesses and maps the mentoring network of individuals. We will validate this tool and retrospectively characterize successful mentoring networks of UR career development (K) grant recipients. Then, we will test the feasibility of an intervention that helps UR researchers build effective mentoring networks. Primary outcomes include mentor network robustness (i.e. the network is meeting the needs of the trainee), career outcomes and intentions, and research success as measured by grants and publications. Secondary outcomes include psychosocial predictors for research success (e.g. research self-efficacy) and intervention acceptability and fidelity. After five years, we will better understand how the mentorship networks of successful UR postdoctoral researchers form and change over time, their impact on career outcomes, and patterns of UR mentorship networks critical for success. The findings will fill a critical need to understand how best to mentor underrepresented trainees, informing investments in training grants and career development programs that will close the mentoring gap in research training.