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Medical research archives · 2026

A scalable dissemination model for training faculty in mentor development and networking.

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Sood Akshay, Tigges Beth, Helitzer Deborah

Аннотация

Faculty success in academia depends on effective mentoring and developmental networks, yet shortages in trained mentors, limited networking skills and inconsistent mentoring quality impact career advancement. While structured mentor development programs improve mentor competency and curriculum-based training improves networking self-efficacy, these programs are widely unavailable and/or underutilized. To address this gap, we evaluated scalable, evidence-based faculty training programs disseminated to academic institutions across the United States using the Project ECHO (Extension of Community Health Outcomes) telementoring model. Two interventions-Mentor Development and Mentoring Networks-were implemented from 2023 to 2025. Participation, demographics and reach were tracked, while surveys assessed knowledge, content relevance, intent to apply knowledge, communication, barriers and perceived impact. Knowledge gains were measured by comparing retrospective pre/post- test scores on a Likert scale. A total of 821 Mentor Development and 556 Mentoring Networks attendances were recorded, with mean attendance of 20.5 and 15.4 unique individuals, respectively. Both programs showed significant increases in knowledge (p<0.001; Cohen's d = 1.3 and 1.7, respectively). Participants reported strong intentions to apply the content (means = 4.6, 4.6), high relevance (means = 4.0, 3.9), and improved communication and collaboration within teams (means = 4.2, 4.4). Reported impacts included improved knowledge (84-94%), skills (59-61%), and performance (32-36%), with limited time and resources as the most common barriers. The Project ECHO model is a feasible, scalable approach for disseminating mentor development and networking training to strengthen academic workforce capacity and reduce inequities across diverse, real-world academic settings.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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