Understanding the Science of Effective Mentorship Networks for Underrepresented Researchers

项目总结/摘要 我们的长期目标是确定有助于研究人员有效导师网络的因素， 代表性不足（UR）群体。有效的指导对于留住早期职业研究人员至关重要， 学术界然而，来自UR组的研究人员不太可能有有效的指导，这有助于 拨款和教师代表性的差异。目前的趋势表明， 是最常见的指导形式，可能不是最有效的指导形式，特别是对于 代表性不足的群体，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，其中涉及多个导师与各种角色，是一个更 有效的模式，而不是导师二人组的保留和成功的代表性不足的研究人员， 学术界导师网络如何影响研究成功以及导师网络的特征 对早期职业生涯很重要，UR研究人员还没有很好地理解。我们开发了一种新工具， 指导网络分析，评估和映射个人的指导网络。我们会证实这一点 工具和回顾性地描述UR职业发展（K）赠款的成功辅导网络 受惠人士然后，我们将测试干预的可行性，帮助UR研究人员建立有效的指导 网络.主要成果包括指导网络的稳健性（即网络满足了 培训生），职业成果和意图，以及研究成功，以赠款和出版物衡量。 次要结果包括研究成功的社会心理预测因素（如研究自我效能）， 干预的可接受性和忠实性。五年后，我们将更好地了解 成功的UR博士后研究人员的形式和变化随着时间的推移，他们对职业成果的影响， 工发组织代表指导网络的模式对成功至关重要。这些发现将填补一个关键的需要，了解如何 最好是辅导代表性不足的受训人员，为培训赠款和职业发展投资提供信息 这些项目将缩小研究培训中的指导差距。

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.