Adapting a Complex Health Intervention Guided by the Core Functions and Form Model: A Methodology and Case Example of Participatory Adaptation

Background : Adapting evidence-based interventions (EBIs) to fit local contexts while preserving fidelity to core mechanisms is challenging, particularly for complex, multicomponent interventions. The Core Functions and Forms (CFF) model distinguishes essential intervention mechanisms (core functions) from adaptable delivery strategies (forms), offering a principled approach to balance fidelity and tailoring. We applied CFF to adapt hospital discharge EBIs for patients with non-English language preference (NELP). Methods : Using Steps 1 and 2 of the ADAPT framework integrated with CFF, we convened an Adaptation Team to (1) rate the importance of core functions for NELP discharge care, (2) generate and evaluate forms—divided into specific forms (concrete components) and cross-cutting forms (e.g., who delivers, when, where, and how)—and (3) refine a pilot intervention. We collected participant demographics, audio-recorded and transcribed four facilitated meetings, and administered structured ranking and rating surveys via REDCap. Two analysts conducted rapid content extraction within one week of each meeting to compile ideas for subsequent rounds. Quantitative synthesis included mean importance rankings and mean impact and feasibility scores (1–10 scale). Specific forms were catalogued by corresponding core function. Results : The Adaptation Team (n=13) included clinicians, nurses, professional interpreters, social workers, and patient/caregiver representatives with lived NELP experience. The highest-ranked core functions were "understand and address patient priorities" and "assess and address linguistic and cultural needs." For intervention delivery, physicians were rated highest for impact (mean=9.5) but lowest for feasibility (mean=4.8), while nurses, social workers, and community health workers offered better balance with high impact (mean range 8.1–8.5) and greater feasibility (mean range 7.3–7.4). In-person contact during admission plus post-discharge follow-up was rated most impactful (mean=9.4) but least feasible (mean=4.3), though feasibility improved with remote delivery (mean=8.0). For language concordance, remote delivery by a language-concordant provider best balanced impact (mean=8.1) and feasibility (mean=8.3). Conclusions : This work demonstrates operational integration of CFF into ADAPT, coupling theory-driven function specification with systematic stakeholder engagement. Key innovations include applying CFF across a family of related discharge EBIs to enable reuse of shared mechanisms and explicitly separating specific from cross-cutting forms to highlight implementation-relevant decisions.