Each year, approximately 90,000 adolescents and young adults (AYA; National Cancer Institute defined age 15-
39 years at cancer diagnosis) are diagnosed with cancer. Despite increasing recognition that over 10% of AYAs
harbor a pathogenic or likely pathogenic germline mutation in cancer predisposition genes, we know that many
AYA do not get genetic testing, particularly at centers where there is limited access to genetic services. Focused
efforts on the delivery of genetic services in the community setting, where many AYAs receive their care are
needed to improve outcomes in this population. To address this important gap in genetic testing among AYAs
and to address the need for innovative and effective models for delivery of genetic services in community
oncology practices, we propose that an enhanced multimodality eHealth remote genetic services delivery model
could increase uptake of genetic counseling and genetic testing among AYA. Our enhanced eHealth delivery
model builds upon related research demonstrating high uptake of web-based pre-test counseling as an
alternative to pre-test counseling with a genetic counselor with no difference in patient reported outcomes (R01
CA190871:Bradbury). Further, we propose to incorporate chatbot technology into our web-based alternative to
address patient-specific questions and to increase engagement and provide service reminders and educational
support throughout the delivery model. The overall goal of the study is to evaluate if our enhanced eHealth and
chatbot enabled delivery model can increase uptake of genetic services and provide non-inferior patient
reported outcomes as compared to the standard model for remote services. We will recruit AYA patients through
the NCORP (National Cancer Institute Community Oncology Research Program). We propose a randomized
study in 396 AYA cancer patients (18-39 YO at enrollment) in community practices to evaluate the efficacy of an
enhanced eHealth and chatbot enabled delivery model as compared to remote genetic counseling and testing
to increase uptake of cancer genetic testing in AYA (Aim 1). In Aim 2, we will evaluate the efficacy of the
enhanced eHealth and chatbot enabled delivery model to provide non-inferior short-term and longitudinal
cognitive (e.g. knowledge), affective (e.g. distress), and behavioral outcomes (e.g. cancer screening and
communication to relatives) and costs (Aim 2a), and moderators of these short-term and longitudinal patient
outcomes to understand who benefits more or less from the delivery intervention (Aim 2b). Concurrently, we will
conduct a CFIR (Consolidated Framework for Implementation Research)-informed process evaluation to
understand moderators of intervention usage and patient outcomes and facilitators and barriers to future
implementation and sustainability of these delivery models to AYA cancer patients (Aim 3).
