2.1 ItRunsInMyFamily.com and November 2019 10K Campaign
ItRuns is a web based FHx collection and hereditary cancer risk assessment tool developed by researchers at the Medical University of South Carolina and ItRunsInMyFamily.com LLC. ItRuns is a free, secure, browser-based, and mobile-first application that does not require the user to download software or to create an account.3 ItRuns uses a dialogue-based text chat interface to mimic human-to-human conversation providing its users a natural and engaging experience analogous to talking with providers. The current version of ItRuns uses an innovative chatbot interface that simulates a natural conversational dialogue to collect FHx from users. The chatbot engages users in a structured and intuitive way, rather than multiple pages of online forms, tables, or a series of complex questions compared to other tools. Upon completion of the ItRuns assessments, a personalized risk assessment report (section 3.2.1) is sent to the user's email address.3
This paper reports on data collected from an online FHx collection campaign conducted using ItRuns.11 This campaign was conducted between November 1, 2019 and November 30, 2019 in conjunction with Family Health History Month.11 The ItRuns team aimed to recruit at least 10,000 English-speaking users via paid and unpaid marketing campaigns through social media promotion, contacting previous users of ItRuns, using promotional banners on the ItRuns website, and direct contact with cancer support groups. Interested users completed the assessment using the ItRuns assessment link on mobile devices or computers. Users consented to take the ItRuns assessment by clicking on consent checkboxes within the assessment. This secondary analysis study was deemed not human subject research by the Medical University of South Carolina Institutional Review Board (Pro00094990).
2.2 ItRunsInMyFamily Workflow
This section provides a step-by-step description of the ItRuns assessment workflow divided into 13 subflows (SF) as explained below (See Fig. 1).
SF 1 | Introduction: The assessment begins with an introduction to Dokbot - the chatbot persona users engage with during the assessment.12 Dokbot introduces the user to the purpose of ItRuns and obtains informed consent.
SF 2 | Basic Demographics: Upon consent, Dokbot collects the user’s name and gender. Dokbot also asks if the user is 18 years or older. If yes, Dokbot continues with the assessment. If not, the assessment ends with a message explaining that users have to be at least 18 years of age to take the assessment.
SF 3 | Patient Cancer History: This step collects users' cancer history. If the user reports a history, Dokbot collects information related to the type of cancer and age of diagnosis. Some cancers include specific follow up questions. For example: for breast cancer, questions such as if the cancer was in one or both breasts.
SF 4 | Genetic Testing: Following the personal cancer questions, Dokbot asks the user if they have ever been tested for a genetic mutation in a cancer-causing gene. If answered yes, Dokbot asks if the result was positive and, if so, for which gene.
SF 5 | Family Cancer History: Dokbot then asks if anyone in the family has had cancer. If the user reports yes, Dokbot asks which relative, their name, cancer, age of diagnosis, as well as cancer-specific follow up questions, if the relative had any other cancers, if they are still alive, their current age or age when they died, and whether the family member has ever been tested for a genetic mutation in a cancer-causing gene. This sequence is repeated for each relative the user reports as having been diagnosed with cancer.
SF 6 | Pedigree: Dokbot asks the total number of daughters, sons, sisters, brothers, maternal aunts, maternal uncles, paternal aunts, paternal uncles in their family. Numbers of nieces and nephews were not assessed due to the complexity of the data and its limited utility. For female users, age when they had their first child is assessed during this sequence. In this manner, a 3-generation pedigree is collected.
SF 7 | Physical Traits: Dokbot collects users’ age, weight, and ancestral origin. If users indicate that they are of European descent, Dokbot asks whether they have Ashkenazi Jewish ancestry as these individuals are at a higher risk of BRCA gene mutation.13
SF 8 | Female Details: If the user is a female (indicated in SF 2), they are asked the age at menarche; if they have had their breasts, ovaries, or uterus removed, if they have gone through menopause and at what age; if they take hormone replacement therapy if they had a mammogram. If they have had a mammogram, Dokbot asks the date of the last mammogram and the history of dense breasts. They are also asked if they’ve had a breast biopsy, if yes, number of biopsies, any abnormal findings and type of abnormality.
SF 9 | Colorectal Cancer Screen: Dokbot asks all users about the history of colonoscopy. If yes, Dokbot further asks if polyps were found and, if so, the number and type.
SF 10 | Lifestyle: Dokbot collects a user’s zip code, smoking history, tobacco use and alcohol use. If the user reports having smoked cigarettes, Dokbot asks for their age when they started smoking and the age when they stopped; if they report they are no longer a current smoker, what number of cigarettes per day when they did smoke. Dokbot also collects ibuprofen and aspirin use.
SF 11 | Thank you and Email: Dokbot thanks the user for participation and collects the user’s email to send the ItRuns risk analysis report.
SF 12 | Recommendations and Report: Dokbot providers high-level risk recommendation based on family health history and guidelines for hereditary cancer risks. Dokbot also informs the user that a detailed report (section 2.4.1) will be shared via email.
SF 13 | Invite Friends: Users have an option to share ItRuns assessment with friends and relatives on Facebook by posting on their public profile.
2.2.1 ItRuns Risk Assessment Report
ItRuns uses ontologies, ontological reasoners, clinical practice guidelines, and web services to provide evidence-based recommendations to users based on their FHx. Owlready2 ontology module and Protégé ontology platform were used to develop a lightweight, patient-centric clinical practice guideline domain ontology using hereditary cancer criteria from the American College of Medical Genetics and Genomics and the National Cancer Comprehensive Network. The development of this ontology-driven clinical practice guideline criteria risk assessment is published in a separate publication.14 A risk analysis PDF report is emailed to participants who completed the ItRuns assessment. The report contains an Executive Summary, followed by a Guidelines section consisting of the hereditary cancer predisposition criteria the user meets and the published recommendations for cancer predisposition assessment they should follow. Next, the Health History section includes information about the user and their health history (including a family pedigree), a breakdown of relatives with cancer, relatives who are also at risk, and family cancer statistics for the user’s family. Finally, the Recommendations section includes additional details about the hereditary cancer syndrome the user for which the user might be at risk, available genetic counseling resources, and additional genetic testing information. The About section includes content about the product, contact information, support, references, and a legal disclaimer.
2.5 Data Analysis
Once the campaign was completed, telemetry data was extracted from the Dokbot database. A script was run to remove small amounts of unusable data, including records where a user loaded the ItRuns workflow but did not submit any single step as well as researcher/developer test records. Then, we extracted elements such as unique random user ID, step description, step start and end timestamps, etc. to assess the experience.
Using an analysis script, we quantified the telemetry data to calculate the usage, abandonment rate, and time per step. We tabulated and graphically represented this data using Microsoft Excel software. Descriptive measures were used to obtain the frequencies, percentages, mean, and median related to completion, abandonment rate, and time taken for each subflow and related steps.