From trust to translation: A trust-based, evidence-informed, and adaptive model for scalable technical assistance.

Abstract

Technical Assistance (TA) is an essential strategy for supporting organizational growth and aiding implementation of evidence-based interventions in mission-driven sectors, including education. While TA is crucial for addressing challenges and improving performance, the field has limited consensus on key features and best practices, particularly in the context of school safety. This paper explores the development, implementation, and application of the Trust-based, Evidence-informed, and Adaptive Model for Scalable Technical Assistance (TEAMS-TA), a comprehensive approach to providing tailored support for organizations, particularly schools, to address complex challenges in school safety. TEAMS-TA is rooted in data-driven decision-making and culturally responsive practices, ensuring that support is customized to meet unique organizational needs and available resources for individual schools, districts, or statewide systems. This model's focus on trauma-informed approaches, continuous feedback, and collaborative partnerships enhances effectiveness in addressing school safety, particularly for contexts with challenging circumstances. Through a multi-phase approach integrating proactive and responsive assistance, the model provides comprehensive support from needs assessment to crisis response, fostering long-term sustainability and capacity building. This paper discusses core model features, school safety applications, and potential for expansion to other sectors. It also identifies future research opportunities, including the effects of TA relationships and alternative frameworks for evaluating success.