Design of Chatbot Persona for Breast Cancer Screening Outreach Among Black Women
Condition: Breast Cancer
MeSH terms: Breast Neoplasms
Study type: Observational

Summary: 
      Breast cancer screening disparities among Black women persist despite health system
      recognition and outreach. However, current evidence on how to tailor and optimize
      implementation strategies for breast cancer screening outreach is limited. The proposed study
      is part of a larger project to design a chatbot for breast cancer screening outreach to Black
      women and will focus on optimizing the chatbot persona. Using the Multiphase Optimization
      Strategy (MOST) framework, the investigators will conduct a randomized factorial experiment
      to assess the individual components of chatbot persona for breast cancer screening and
      identify which components have the greatest effect on trust and engagement for Black women.
      This information will guide the design of an optimized chatbot intervention that achieves the
      primary outcomes.
    

Detailed description: 
      The goal of this study is to determine the optimal delivery of initial chatbot messages for
      culturally tailored breast cancer screening outreach. Mistrust of the medical system has been
      identified as a significant barrier to mammography screening among Black women. Yet, while
      tailored interventions for breast cancer screening exist, the optimal design of a tailored
      intervention to engender trust is unknown. Chatbots have been shown to increase levels of
      trust in web-based information, though adoption of chatbots may depend on chatbot
      characteristics. The investigators propose to use the Multiphase Optimization Strategy
      (MOST), a framework for developing efficacious, efficient, scalable and cost-effective
      interventions, to assess the performance of chatbot intervention components and their
      interactions.

      The chatbot message delivery will be systematically varied across two components, each of
      which is represented by a separate factor in the 2x2x1 factorial study design with a control
      arm. Specifically, each participant will be randomly assigned to one of five separate
      experimental conditions. Conditions include: (1) chatbot with a primary care doctor persona
      and direct communication style; (2) chatbot with a breast cancer survivor persona and direct
      communication style; (3) chatbot with a primary care doctor persona and indirect
      communication style; and (4) chatbot with a breast cancer survivor persona and indirect
      communication style. All participants will complete a survey regarding their perceptions
      about the initial outreach messages from the chatbot.

      The main effects will be estimated of the two experimental factors and their interactions on
      the study's primary outcomes - trust in the chatbot system to use for breast cancer screening
      education and scheduling, and intention to use. This information will guide the design of an
      optimized chatbot persona that achieves the primary outcomes.

      Participants will be enrolled if they are Black individuals who qualify for breast cancer
      screening residing in the United States who are between the ages of 40-74. Recruitment will
      be conducted on Prolific, an online participant pooling platform, and Amazon Mechanical Turk
      (MTurk), a crowdsourcing platform used for research recruitment. Prolific will be used given
      the platform's ability for selecting the participant population. However, due to the limited
      number of individuals within the inclusion criteria on Prolific, and if needed participants
      will also be recruited on MTurk. Participants will be asked to view the chatbot messages and
      respond to questions to assess trust, engagement, and directness of the chatbot.
    

Intervention name(s): Persona: Primary care doctor; Persona: Breast cancer survivor; Communication Style: Direct; Communication Style: Indirect
Intervention type(s): Other; Other; Other; Other
Intervention description(s): The chatbot persona is a Black woman who is a primary care doctor.; The chatbot persona is a Black woman who is a breast cancer survivor.; The chatbot messages are characterized by commands and direct addresses (''you'').; The chatbot messages are characterized by subjunctive modal verb forms (''would like'') and cooperative addresses (''we", "let's").
Sampling method: Non-Probability Sample
Study population: 
        Black or African American women between the ages of 40-74 years old and residing in the
        United States.
      
Keywords: Breast cancer screening; Healthcare disparities; Chatbot; Multiphase optimization strategy (MOST)