Skip to content
DraconiticResearch
Search Sources API
203,203 studies31 sourcesUpdated 12 min ago
Peer-reviewedCC BY-NC-ND 4.0Genetics in Medicine Open

Comparing patients’ perceptions and cognitive and emotional responses to pretest cancer genetic services delivered via chatbot vs standard of care: Findings from the BRIDGE trial

  • Yang Yi1,2
  • Jemar R. Bather3,4
  • Melody S. Goodman3,4
  • Rachelle Lorenz Chambers5
  • Sarah V. Colonna2,6
  • Rachel Hess7,8
  • Wendy K. Kohlmann2
  • Whitney F. Maxwell2
  • Rachel Monahan5,9
  • David W. Wetter7,10
  • Saundra S. Buys2,8
  • Kensaku Kawamoto11
2 more authors
  • Guilherme Del Fiol11
  • Kimberly A. Kaphingst1,2
11 affiliations
  1. 1Department of Communication, University of Utah, Salt Lake City, UT
  2. 2Huntsman Cancer Institute, Salt Lake City, UT
  3. 3Department of Biostatistics and Center for Anti-Racism, Social Justice & Public Health, School of Global Public Health, New York University, New York, NY
  4. 4Department of Biostatistics, School of Global Public Health, New York University, New York, NY
  5. 5Perlmutter Cancer Center, NYU Langone Health, New York, NY
  6. 6Breast/Gynecologic System of Excellence, VA Medical Center National TeleOncology, Durham, NC
  7. 7Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, UT
  8. 8Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, UT
  9. 9Department of Population Health, NYU Grossman School of Medicine, New York, NY
  10. 10Center for Health Outcomes and Population Equity (HOPE), Huntsman Cancer Institute, Salt Lake City, UT
  11. 11Department of Biomedical Informatics, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, UT
Read full textPDFDOICite

Abstract

Purpose: Chatbots are increasingly delivering genetic services, and we have shown equivalence between chatbot and standard of care (SOC) in the uptake of pretest genetic services and genetic testing. Here, we compare patients’ perceptions and cognitive and emotional responses to these 2 service delivery models.

Methods: Unaffected primary care patients aged 25 to 60 years who met family history–based criteria for genetic evaluation were randomized 1:1 to chatbot or SOC arms. Four weeks after completing genetic services, we surveyed participants to assess their perceptions and cognitive and emotional responses; we compared these between arms using one-way analyses of covariance and logistic regressions, adjusting for demographic and clinical covariates.

Results: Participants (N = 189) had highly or moderately positive perceptions of services and cognitive and emotional responses, and these were similar between arms. However, chatbot participants reported statistically significantly lower satisfaction with counseling (P = .026) and education (P = .005), attention maintenance (P = .001), and emotional support (P < .001) than SOC participants. Among those who received testing, chatbot participants reported significantly lower perceived utility (P = .044) and lower distress (P = .025) related to test results.

Conclusion: Patients reported positive perceptions and responses to both SOC and chatbot-delivered genetic services. However, enhancing emotional responsiveness and personalization may further improve the experience and perceived utility with chatbots.

Related

  1. Feline stress through owners’ eyes: comparing perceptions in veterinary clinics with and without designated cat-only areas or hours
    Annie Baltz
    Journal of Feline Medicine and SurgeryPeer-reviewedCC BY-NC 4.0Full textZoology & animal behaviourPMC
  2. Contribution of the Late Positive Potential to Emotional Memory: A Joint Neuro-Cognitive Approach to Memory Prediction
    R. Hellerstedt, J. Gunn, D. Talmi
    bioRxivPreprintAll rights reservedFull textNeurosciencebioRxiv
  3. Emotional arousal predicts pupil responses following a single attention shift between bright and dark moving stimuli
    Kei Kanari, Taihei Tsutsumi
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textNeuroscienceCrossref
  4. Comparing the efficacy of LORETA neurofeedback versus cognitive rehabilitation on working memory in children with learning disorders: A double-blind clinical trial.
    Shayan Alamdarifar, Jala Kalantari
    Journal of education and health promotionPeer-reviewedCC BY-NC-NDFull textNeuroscienceEurope PMC
  5. A Mathematical Model of Motivated Emotional Mind - Cognitive Embodied System
    Wiesław L. Galus, Janusz A. Starzyk
    arXivPreprintCC BY-NC-ND 4.0Full textNeurosciencearXiv

Cite

BibTeXRIS
BibTeX
@article{yi2026comparing,
  title = {{Comparing patients’ perceptions and cognitive and emotional responses to pretest cancer genetic services delivered via chatbot vs standard of care: Findings from the BRIDGE trial}},
  author = {Yang Yi and Jemar R. Bather and Melody S. Goodman and Rachelle Lorenz Chambers and Sarah V. Colonna and Rachel Hess and Wendy K. Kohlmann and Whitney F. Maxwell and Rachel Monahan and David W. Wetter and Saundra S. Buys and Kensaku Kawamoto and Guilherme Del Fiol and Kimberly A. Kaphingst},
  journal = {Genetics in Medicine Open},
  year = {2026},
  month = sep,
  doi = {10.1016/j.gimo.2026.104498},
  url = {https://doi.org/10.1016/j.gimo.2026.104498},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Comparing patients’ perceptions and cognitive and emotional responses to pretest cancer genetic services delivered via chatbot vs standard of care: Findings from the BRIDGE trial
AU  - Yang Yi
AU  - Jemar R. Bather
AU  - Melody S. Goodman
AU  - Rachelle Lorenz Chambers
AU  - Sarah V. Colonna
AU  - Rachel Hess
AU  - Wendy K. Kohlmann
AU  - Whitney F. Maxwell
AU  - Rachel Monahan
AU  - David W. Wetter
AU  - Saundra S. Buys
AU  - Kensaku Kawamoto
AU  - Guilherme Del Fiol
AU  - Kimberly A. Kaphingst
PY  - 2026
DA  - 2026/09/24
JO  - Genetics in Medicine Open
DO  - 10.1016/j.gimo.2026.104498
UR  - https://doi.org/10.1016/j.gimo.2026.104498
AB  - Purpose: Chatbots are increasingly delivering genetic services, and we have shown equivalence between chatbot and standard of care (SOC) in the uptake of pretest genetic services and genetic testing. Here, we compare patients’ perceptions and cognitive and emotional responses to these 2 service delivery models.  Methods: Unaffected primary care patients aged 25 to 60 years who met family history–based criteria for genetic evaluation were randomized 1:1 to chatbot or SOC arms. Four weeks after completing genetic services, we surveyed participants to assess their perceptions and cognitive and emotional responses; we compared these between arms using one-way analyses of covariance and logistic regressions, adjusting for demographic and clinical covariates.  Results: Participants (N = 189) had highly or moderately positive perceptions of services and cognitive and emotional responses, and these were similar between arms. However, chatbot participants reported statistically significantly lower satisfaction with counseling (P = .026) and education (P = .005), attention maintenance (P = .001), and emotional support (P < .001) than SOC participants. Among those who received testing, chatbot participants reported significantly lower perceived utility (P = .044) and lower distress (P = .025) related to test results.  Conclusion: Patients reported positive perceptions and responses to both SOC and chatbot-delivered genetic services. However, enhancing emotional responsiveness and personalization may further improve the experience and perceived utility with chatbots.
SN  - 2949-7744
ER  -