Evidence map›Paper›PMID 42332242›Full record

ArticleJournal of community genetics2026

Development and feasibility testing of a conversational chatbot supporting genetic education and testing for hereditary cancer.

Samuel Tundealao, Emily Heidt, Sherry Grumet, Marc D Schwartz, Beth N Peshkin, Jinghua An, Scott T Walters, Lindsay O'Boyle, Deborah Toppmeyer, Anita Y Kinney

Registry-linked trialAbstract read
In one paragraph

Article in Journal of community genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06184867 (Choices About Genetic Testing And Learning Your Risk With Smart Technology), which is not on this map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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.

NCT06184867 nacompletednot on this map

Choices About Genetic Testing And Learning Your Risk With Smart Technology

TypeinterventionalSponsorRutgers, The State University of New JerseyRan2023 to 2025Enrolled50ConditionsOvarian Cancer, Fallopian Tube Cancer, Peritoneal Cancer, Breast CancerArmsRelational Agent (RA), Enhanced Usual Care (EUC)
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Samuel TundealaoRutgers Cancer Institute, 195 Little Albany St, New Brunswick, NJ, 08901, USA.
Emily HeidtRutgers Cancer Institute, 195 Little Albany St, New Brunswick, NJ, 08901, USA.
Sherry GrumetRutgers Cancer Institute, 195 Little Albany St, New Brunswick, NJ, 08901, USA.
Marc D SchwartzLombardi Comprehensive Cancer Center, Georgetown University, 3800 Reservoir Rd NW, Washington, DC, 20007, USA.
Beth N PeshkinLombardi Comprehensive Cancer Center, Georgetown University, 3800 Reservoir Rd NW, Washington, DC, 20007, USA.
Jinghua AnIndiana University School of Nursing, 600 Barnhill Dr, Indianapolis, IN, 46202, USA.
Scott T WaltersUniversity of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA.
Lindsay O'BoyleRutgers Cancer Institute, 195 Little Albany St, New Brunswick, NJ, 08901, USA.
Deborah ToppmeyerRutgers Cancer Institute, 195 Little Albany St, New Brunswick, NJ, 08901, USA.
Anita Y KinneyRutgers Cancer Institute, 195 Little Albany St, New Brunswick, NJ, 08901, USA. ak1617@sph.rutgers.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study describes the development and feasibility testing of a digital health guide (DHG) to streamline genetic education, reduce barriers, and promote informed genetic testing (GT) decisions among cancer survivors. This study reports on the DHG's development, usability testing, acceptability, feasibility, and preliminary efficacy in improving genetic counseling (GC) and GT access for cancer survivors. Guided by the Ottawa Decision Support Framework, the DHG prototype was developed following community engagement with cancer patients and at-risk relatives from diverse sociodemographically backgrounds. It was refined through user (content-focused) and usability (functionality-focused) testing. Pilot trial participants provided data through semi-structured interviews and usability assessments. Qualitative data were analyzed using the Framework Method. The preliminary impact of the DHG on GC and GT uptake, and informed decision-making, was assessed in a feasibility and accessibility trial. The Chatbot Usability Questionnaire score for the DHG was 70.3 (IQR = 12.5), indicating good acceptability. The DHG also facilitated GT uptake (73.3%) compared to enhanced usual care (EUC; 7.7%). Pretest GC was requested by 1 of 13 patients in the EUC arm, while no request (0 of 15 patients) was made in the DHG arm. Users' feedback led to clearer language, improved navigation, and stronger messaging regarding data security. DHG participants had lower decisional conflict (33.37 ± 21.09) and decision regret (17.5 ± 16.50) than those in the EUC arm (53.25 ± 22.66 and 37.08 ± 17.38, respectively). The digital intervention is feasible, acceptable, and a promising strategy for expanding GT access and promoting informed decision-making. Further testing in a definitive randomized controlled trial is warranted. Clinical trial registration. This study was preregistered at the NIH clinical trial registry ( https://clinicaltrials.gov/study/NCT06184867 ).

Indexed as

CancerChatbotsDigital guidesGenetic educationGenetic testing

Identifiers

PMID42332242
PMCPMC13287281

What Socratic holds

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Registered trials

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 Socratic graph.