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Adapting Nurse AMIE for rural oncology populations: A FRAME-guided analysis of a technology-enabled supportive care
Erica Schleicher1, Stephen Baker2, Sara West1
1Division of Hematology Oncology, School of Medicine, University of Pittsburgh, UPMC Hillman Cancer Center, The Assembly, 5051 Centre Ave, Suite 5014, Pittsburgh, PA, 15213, USA.
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.
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