Evidence map›Paper›PMID 38064163›Full record

ArticleJournal of cancer survivorship : research and practice2025

The ENGAGE study: evaluation of a conversational virtual agent that provides tailored pre-test genetic education to cancer patients.

Kala Visvanathan, Dana Petry, Michelle S McCullough, Betty May, Ramkrishnan Tenkasi, Nitin Sharma, Catherine A Klein, Angelisa Johnson, Gisselle Killian, Melissa Camp and 10 more

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of cancer survivorship : research and practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Chatbots for breast cancer education: a systematic review and meta-analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
    Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors at 4 institutions in 1 country.

Kala VisvanathanJohns Hopkins School of Medicine and Bloomberg School of Public Health, #E6142 615 N. Wolfe Street, Baltimore, MD, 21231, USA. kvisvan1@jhu.edu.
Dana PetryJohns Hopkins School of Medicine, Baltimore, MD, USA.
Michelle S McCulloughJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Betty MayJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Ramkrishnan TenkasiGoodwin College of Business, Benedictine University, Lisle, IL, USA.
Nitin SharmaOptra Health, San Jose, CA, USA.
Catherine A KleinJohns Hopkins School of Medicine, Baltimore, MD, USA.
Angelisa JohnsonJohns Hopkins School of Medicine, Baltimore, MD, USA.
Gisselle KillianJohns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Melissa CampJohns Hopkins School of Medicine, Baltimore, MD, USA.
Channing J PallerJohns Hopkins School of Medicine, Baltimore, MD, USA.
Rima CouziJohns Hopkins School of Medicine, Baltimore, MD, USA.
Mary WilkinsonJohns Hopkins School of Medicine, Baltimore, MD, USA.
Lisa JacobsJohns Hopkins School of Medicine, Baltimore, MD, USA.
Julie LangeJohns Hopkins School of Medicine, Baltimore, MD, USA.
Danijela JelovacJohns Hopkins School of Medicine, Baltimore, MD, USA.
Michael A CarducciJohns Hopkins School of Medicine, Baltimore, MD, USA.
Mehran HabibiJohns Hopkins School of Medicine, Baltimore, MD, USA.
Gauri NaikOptra Health, San Jose, CA, USA.
Ashwin KotwaliwaleOptra Health, San Jose, CA, USA.
Johns Hopkins Medicine · USJohns Hopkins University · USOptra (United States) · USBenedictine University · US

Funding

Translational Research Central ServicesP30CA006973 · NCI · JOHNS HOPKINS UNIVERSITY · PI ALAN KEITH MEEKER · 1985 to 2026
$208.6M
NCI NIH HHS P30 CA006973
6 · The paper itself

Abstract

purposeNovel approaches are needed to ensure all patients with cancer have access to quality genetic education before genetic testing to enable informed treatment decisions. The purpose of this study was to test the use of an artificial intelligence (AI) intervention for the delivery of genetic education by non-genetic providers to patients with cancer undergoing active treatment.

methodsA conversational AI-based application was developed on the HealthFAX platform to provide tailored genetic education to patients with cancer and tested at Johns Hopkins Hospital between April 2021 and Feb 2022. Patients' responses around the adoption, use, and experience of the AI application were assessed.

resultsOut of 64 individuals who consented to the study, 51 accessed the tool. The responding participants had a mean age of 61 years (ranging from 30-90 years) with 39 individuals undergoing active treatment for breast cancer and 12 for advanced prostate cancer. All patients chose to complete the tool at home. The median time between study enrollment and AI application initiation was 1 day, and the median time to complete the application was 24 min. All participants in their survey responses felt that the tool was secure, easy to use, liked the convenience of viewing it at home, and felt it provided valuable information. Eighteen percent of participants viewed the application with a family member. Ninety-eight percent of the participants completed their genetic education prior to receiving their test results. In 16%, a pathogenic variant was identified.

conclusionsThe 51 patients who adopted the AI application were highly satisfied with its usability and convenience. Our results support the continued evaluation of this cost-effective AI application in a large-scale study. IMPLICATIONS FOR CANCER SURVIVORS: Tailored pre-test genetic education can be successfully delivered to patients with cancer undergoing active treatment via an AI application at their convenience.

Indexed as

Artificial IntelligenceGenetic CounselingGenetic TestingNeoplasmsPatient Education as TopicAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedAI-assisted patient educationAI for cancer survivorshipAI in cancersAI in healthcareConversational AIScaling clinical processes with conversational AI

Identifiers

PMID38064163
OpenAlexW4389485950

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.