A randomized factorial experiment to optimize the design of a culturally tailored breast cancer screening outreach chatbot intervention

Introduction: The main objective of this study is to assess the effects of chatbot persona and communication style on trust and intention to use for scheduling breast cancer screening (BCS). Methods: We conducted a mixed-methods analysis of a randomized factorial experiment to evaluate different chatbot designs for a BCS intervention. The study protocol is registered on ClinicalTrials.gov (NCT05472064). We tested different conditions in a 2 × 2 experimental design using a Black woman persona presented either as a primary care doctor or a breast cancer survivor and a communication style that was either direct or polite, compared with a control condition. Results: Among the experimental conditions, the doctor-polite condition was the most preferred in terms of both trust and intention to use, compared with the control. Qualitative feedback indicated that the doctor persona and polite communication style were perceived as professional and friendly, respectively. While some participants appreciated representation in the use of a Black woman persona and found it relatable, others perceived it as stereotyping, patronizing, or targeting. Discussion: Overall, both quantitative and qualitative findings indicate that a culturally tailored doctor persona with polite messaging may enhance trust and increase intention to use the chatbot for scheduling BCS through professional interactions that are perceived as warm and friendly. The development of culturally tailored personas should be done with caution to prevent the perpetuation of stereotypes in chatbot persona development.

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Publication Details

Journal
Frontiers in Digital Health
Published
2026-04-22
DOI
https://doi.org/10.3389/fdgth.2026.1720531
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

A randomized factorial experiment to optimize the design of a culturally tailored breast cancer screening outreach chatbot intervention

Raina Langevin, Ryan P. Kyle, Leah M. Marcotte, Shayla Akande et al.
Frontiers in Digital Health
AI in Service Interactions
article

A randomized factorial experiment to optimize the design of a culturally tailored breast cancer screening outreach chatbot intervention

Raina Langevin, Ryan P. Kyle, Leah M. Marcotte, Shayla Akande, Katie Arriaga, Pranuti Kalidindi, Gary Hsieh
article en

Abstract

Introduction: The main objective of this study is to assess the effects of chatbot persona and communication style on trust and intention to use for scheduling breast cancer screening (BCS). Methods: We conducted a mixed-methods analysis of a randomized factorial experiment to evaluate different chatbot designs for a BCS intervention. The study protocol is registered on ClinicalTrials.gov (NCT05472064). We tested different conditions in a 2 × 2 experimental design using a Black woman persona presented either as a primary care doctor or a breast cancer survivor and a communication style that was either direct or polite, compared with a control condition. Results: Among the experimental conditions, the doctor-polite condition was the most preferred in terms of both trust and intention to use, compared with the control. Qualitative feedback indicated that the doctor persona and polite communication style were perceived as professional and friendly, respectively. While some participants appreciated representation in the use of a Black woman persona and found it relatable, others perceived it as stereotyping, patronizing, or targeting. Discussion: Overall, both quantitative and qualitative findings indicate that a culturally tailored doctor persona with polite messaging may enhance trust and increase intention to use the chatbot for scheduling BCS through professional interactions that are perceived as warm and friendly. The development of culturally tailored personas should be done with caution to prevent the perpetuation of stereotypes in chatbot persona development.

Frontiers in Digital HealthVol. 8
University of Washington (US)
Openalex Percentile: Top 20%
AI in Service Interactions
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A randomized factorial experiment to optimize the design of a culturally tailored breast cancer screening outreach chatbot intervention — Raina Langevin, Ryan P. Kyle, et al. · Frontiers in Digital Health (2026) | TGRS Research Map | TGRS