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Contemporary clinical trials communications · 2026

Adapting Nurse AMIE for rural oncology populations: A FRAME-guided analysis of a technology-enabled supportive care intervention.

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Schleicher Erica, Baker Stephen, West Sara, Doerksen Shawna E, Calo William A, Schmitz Kathryn H

Аннотация

BACKGROUND: Nurse AMIE (Addressing Malignancies in Individuals Everyday) is a technology-enabled intervention developed to improve symptom self-management and quality of life in cancer patients. As the intervention was translated from earlier pilot trials for patients with metastatic breast cancer (NA-MBC) to a voice-activated version on Amazon Echo Show for women with metastatic breast cancer (NA-Echo), and finally to a rural advanced cancer population including all cancer types (NA-Rural), systematic documentation of adaptations was needed to ensure transparency and support future dissemination.

OBJECTIVE: To systematically describe and classify adaptations made in translating prior versions of Nurse AMIE using the Framework for Reporting Adaptations and Modifications to Evidence-Based Interventions (FRAME).

METHODS: A mixed-methods analysis was conducted documenting three Nurse AMIE iterations: NA-MBC, NA-Echo, and NA-Rural. Adaptations were documented from research team meeting notes, stakeholder interviews, protocol revisions, and prior trial usage data, then coded using FRAME domains.

RESULTS: Nineteen planned adaptations were identified, all occurring during the pre-implementation phases of successive iterations. Adaptations were primarily contextual and content-related, targeting population eligibility, intervention duration, symptom assessment, interface design, and broader dissemination. Core intervention components were retained across all iterations. No training, evaluation, or fidelity-inconsistent adaptations were documented.

CONCLUSIONS: FRAME-guided documentation revealed a coherent set of intentional, proactive adaptations that expanded Nurse AMIE's reach from metastatic breast cancer to rural adults with a broad range of advanced cancer types while preserving fidelity. Findings support informed scale-up and replication of the intervention in underserved oncology populations.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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