# Randomized clinical trial of the sequence of genetic counseling and testing to optimize efficiency, patient empowerment and engagement, and medical adherence for diverse genetic testing indications

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2024 · $308,700

## Abstract

Project Summary
Patients are increasingly seeking genetic counseling and testing for genome-guided medical management.
There is an urgent need to re-examine the genetic counseling process to meet this growing demand. Genetic
counseling standard practice is a pre-test genetic counseling appointment followed by a short session to return
results. An emphasis on pre-test counseling to facilitate decision-making emerged with early models for
Huntington disease testing and genetic testing done in conjunction with prenatal procedures with risk of fetal
loss. There is little evidence this approach is optimal today. Shifting the primary genetic counselor-patient
interaction away from labor-intensive, repetitive, universal pre-test counseling to results-focused, tailored post-
test counseling has the potential to improve both patient outcomes and genetic counseling efficiency. Studies
suggest models other than one-to-one genetic counseling by a genetic counselor can achieve adequate pre-
test education. We recently developed educational genetics videos for the general population that are effective
and engaging. In a pilot study we found pre- and post-test genetic counseling for arrhythmogenic
cardiomyopathy led to similar increases in patient's empowerment and that post-test counseling reduced
cardiac anxiety more. Furthermore, genetic information alone does little to prompt behavior change, suggesting
a role for post-test counseling to activate behavioral responses. We propose a three-arm randomized clinical
trial to evaluate two complementary approaches to shifting the primary genetic counseling session post-test for
adults with two broad cardiovascular genetic counseling indications: panel testing and family-specific variant
testing. We will compare usual care (pre-test genetic counseling appointment, results returned by phone) with
online video-based pre-test genetic education with an optional (efficiency arm) or required (flipped arm) phone
call with a genetic counselor followed by a post-test genetic counseling appointment. One intervention arm is
designed to maximize efficiency by requiring only a single genetic counselor-patient interaction post-test with
pre-test counseling primarily by video. The other retains both a pre- and post-test genetic counselor-patient
interaction (one appointment, one phone call). This approach will allow us to pinpoint the tradeoffs involved in
each. We hypothesize that post-test genetic counseling will: 1) increase efficiency, 2) promote patient
empowerment and adherence, and 3) have similar psychosocial impact. Our study will also generate a genetic
counseling evidence base for understudied counseling indications. Our results have the potential to change the
standard genetic counseling model for adults seeking genome-guided medical management to an efficient
post-test model. Our multidisciplinary team is led by genetic counselors with substantial experience identifying
and overcoming challenges in the genetic counsel...

## Key facts

- **NIH application ID:** 10890827
- **Project number:** 5R01HG011902-04
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Cynthia A James
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $308,700
- **Award type:** 5
- **Project period:** 2021-09-22 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10890827

## Citation

> US National Institutes of Health, RePORTER application 10890827, Randomized clinical trial of the sequence of genetic counseling and testing to optimize efficiency, patient empowerment and engagement, and medical adherence for diverse genetic testing indications (5R01HG011902-04). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10890827. Licensed CC0.

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