A necessary conversation to develop chatbots for HIV studies: qualitative findings from research staff, community advisory board members, and study participants.
Warren Scott ComuladaRoxana RezaiStephanie SumstineDalmacio Dennis FloresTara KerinManuel A OcasioDallas SwendemanM Isabel Fernándeznull nullPublished in: AIDS care (2023)
Chatbots increase business productivity by handling customer conversations instead of human agents. Similar rationale applies to use chatbots in the healthcare sector, especially for health coaches who converse with clients. Chatbots are nascent in healthcare. Study findings have been mixed in terms of engagement and their impact on outcomes. Questions remain as to chatbot acceptability with coaches and other providers; studies have focused on clients.To clarify perceived benefits of chatbots in HIV interventions we conducted virtual focus groups with 13 research staff, eight community advisory board members, and seven young adults who were HIV intervention trial participants (clients). Our HIV healthcare context is important. Clients represent a promising age demographic for chatbot uptake. They are a marginalized population warranting consideration to avoid technology that limits healthcare access.Focus group participants expressed the value of chatbots for HIV research staff and clients. Staff discussed how chatbot functions, such as automated appointment scheduling and service referrals, could reduce workloads while clients discussed the after-hours convenience of these functions. Participants also emphasized that chatbots should provide relatable conversation, reliable functionality, and would not be appropriate for all clients. Our findings underscore the need to further examine appropriate chatbot functionality in HIV interventions.
Keyphrases
- hiv testing
- healthcare
- men who have sex with men
- hiv positive
- antiretroviral therapy
- hiv infected
- human immunodeficiency virus
- mental health
- hepatitis c virus
- hiv aids
- young adults
- physical activity
- clinical trial
- randomized controlled trial
- machine learning
- public health
- type diabetes
- endothelial cells
- health information
- south africa
- high throughput
- metabolic syndrome
- social media
- phase ii
- weight loss
- skeletal muscle