Preparing to implement Floreciendo with Latina teens and their female caregivers: Integrating implementation science and the multiphase optimization strategy framework

为在拉丁裔青少年及其女性照护者中实施Floreciendo项目做准备:整合实施科学和多阶段优化策略框架

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Abstract

BACKGROUND: Practical examples of studies integrating implementation science and the multiphase optimization strategy (MOST) framework are lacking. Floreciendo is a sexual and reproductive health program for Latina teens and their female caregivers, adapted from the IMARA evidence-based program. PURPOSE: We prepared for delivering Floreciendo by developing an implementation plan to support the program's adoption and sustainment. METHODS: Drawing on a community-based participatory research approach, we used qualitative methods to explore program logistics, implementation determinants and strategies, adoption, and sustainability. We positioned our study activities within the preparation phases of both the MOST and the EPIS frameworks. We conducted and rapidly analyzed seven focus group discussions-one with Latina teens (n = 9), one with female caregivers (n = 6), four with organizational staff (n = 32), and one with IMARA staff (n = 6)-and seven key informant interviews. RESULTS: Participants described community organizations as the preferred location for workshops in offering a "safe space." They recommended workshop delivery on two days over separate weekends. Teens and caregivers requested relatable, bilingual Latina facilitators. Implementation barriers were raised (e.g. work conflicts) with strategies to address them (e.g. provide stipends). Organizational adoption was perceived as likely since the workshop addresses clients' needs and fits with organizational values. Recommendations for sustainment included identifying funding opportunities specific to each organization. CONCLUSIONS: Findings directly informed our immediate plans to optimize Floreciendo using the MOST framework and principles and our long-term goals for adoption and sustainability. Implementation science can strengthen studies using the MOST framework.

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