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Background: Genetic testing has become an integrated part of health care for patients with breast or ovarian cancer, and the increasing demand for genetic testing is accompanied by an increasing need for easy access to reliable genetic information for patients. Therefore, we developed a chatbot app (Rosa) that is able to perform humanlike digital conversations about genetic BRCA testing. Objective: Before implementing this new information service in daily clinical practice, we wanted to explore 2 aspects of chatbot use: the perceived utility and trust in chatbot technology among healthy patients at risk of hereditary cancer and how interaction with a chatbot regarding sensitive information about hereditary cancer influences patients. Methods: Overall, 175 healthy individuals at risk of hereditary breast and ovarian cancer were invited to test the chatbot, Rosa, before and after genetic counseling. To secure a varied sample, participants were recruited from all cancer genetic clinics in Norway, and the selection was based on age, gender, and risk of having a BRCA pathogenic variant. Among the 34.9% (61/175) of participants who consented for individual interview, a selected subgroup (16/61, 26%) shared their experience through in-depth interviews via video. The semistructured interviews covered the following topics: usability, perceived usefulness, trust in the information received via the chatbot, how Rosa influenced the user, and thoughts about future use of digital tools in health care. The transcripts were analyzed using the stepwise-deductive inductive approach. Results: The overall finding was that the chatbot was very welcomed by the participants. They appreciated the 24/7 availability wherever they were and the possibility to use it to prepare for genetic counseling and to repeat and ask questions about what had been said afterward. As Rosa was created by health care professionals, they also valued the information they received as being medically correct. Rosa was referred to as being better than Google because it provided specific and reliable answers to their questions. The findings were summed up in 3 concepts: "Anytime, anywhere"; "In addition, not instead"; and "Trustworthy and true." All participants (16/16) denied increased worry after reading about genetic testing and hereditary breast and ovarian cancer in Rosa. Conclusions: Our results indicate that a genetic information chatbot has the potential to contribute to easy access to uniform information for patients at risk of hereditary breast and ovarian cancer, regardless of geographical location. The 24/7 availability of quality-assured information, tailored to the specific situation, had a reassuring effect on our participants. It was consistent across concepts that Rosa was a tool for preparation and repetition; however, none of the participants (0/16) supported that Rosa could replace genetic counseling if hereditary cancer was confirmed. This indicates that a chatbot can be a well-suited digital companion to genetic counseling. [ABSTRACT FROM AUTHOR]

Objective: We aimed at developing a pilot version of an app (Rosa) that can perform digital conversations with breast or ovarian cancer patients about genetic BRCA testing, using chatbot technology, to identify best practices for future patient-focused chatbots.Methods: We chose a commercial chatbot platform and participatory methodology with a team of patient representatives, IT engineers, genetic counselors and clinical geneticists, within a nationwide collaboration. An iterative approach ensured extensive user and formal usability testing during the development process.Results: The development phase lasted for two years until the pilot version was completed in December 2019. The iteration steps disclosed major challenges in the artificial intelligence (AI)-based matching of user provided questions with predefined information in the database, leading initially to high level of fallback answers. We therefore developed strategies to reduce potential language ambiguities (e.g. BRCA1 vs BRCA2) and overcome dialogue confusion. The first prototype contained a database with 500 predefined questions and 67 corresponding predefined answers, while the final version included 2257 predefined questions and 144 predefined answers. Despite the limited AI functionality of the chatbot, the testing revealed that the users liked the layout and found the chatbot trustworthy and reader friendly.Conclusions: Building a health chatbot is challenging, expensive and time consuming with today's technology. The users had a positive attitude to the chatbot, and would use it in a real life setting, if given to them by health care personnel.Practice Implications: We here present a framework for future health chatbot initiatives. The participatory methodology in combination with an iterative approach ensured that the patient perspective was incorporated at every level of the development process. We strongly recommend this approach in patient-centered health innovations. [ABSTRACT FROM AUTHOR]

The article focuses on the Chatbots and artificial intelligence to scale genetic information delivery. Topics discussed include awareness and availability of genetic information is on the rise, through research-based sequencing, clinical testing, consumer-driven initiatives; and chatbot is a software program or ‘virtual assistant' that is designed to simulate human conversation; and Chatbots use natural language processing to gather patient data, anticipate questions, and predict responses.

Background: Genetic testing is increasing in patients newly diagnosed with cancer. This study investigated the levels, course and predictors of cancer-related distress, defined as intrusion and avoidance, in women undergoing BRCA1/2 testing without pretest genetic counseling shortly after a diagnosis of breast or ovarian cancer. Material and methods: Unselected for family history or age, 259 women with breast cancer and 50 women with ovarian cancer, underwent BRCA1/2 testing shortly after diagnosis. Cancer-related distress was measured with the Impact of Event Scale before and after genetic testing. In order to identify predictors of distress, the subscale scores were regressed on baseline predictor variables including sociodemographic and medical variables, perceived social support, and decisional conflict regarding genetic testing. Results: The mean levels of intrusion and avoidance were in the moderate range both before and after genetic testing with a statistically significant decline during follow-up. Younger age, shorter time since diagnosis, lower levels of social support, and a diagnosis of ovarian cancer predicted higher levels of both intrusion and avoidance. In addition, higher levels of decisional conflict and living with a partner predicted higher levels of intrusion. Conclusions: Women having genetic testing shortly after a diagnosis of breast or ovarian cancer had a moderate mean level of cancer-related distress, which decreased with time. Health personnel offering genetic testing to newly diagnosed women with breast or ovarian cancer should be aware of the potential predictors for increased cancer-related distress identified in this study: younger age, less perceived social support, higher levels of decisional conflict regarding genetic testing, and living with a partner. [ABSTRACT FROM AUTHOR]