<i>Layla’s Got You</i>: Developing a tailored contraception chatbot for Black and Hispanic young women

Bonnevie, Erika; Lloyd, Tiffany D; Rosenberg, Sarah; Williams, Kara; Goldbarg, Jaclyn; Smyser, Joe

doi:10.1177/0017896920981122

Cited by 18 publications

(29 citation statements)

References 27 publications

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“…One study that stands out is the work of Bonnevie and colleagues [ 16 ], who describe the development of Layla , a trusted source of information in contraception and sexual health among a population at higher risk of unintended pregnancy. Layla was designed and developed through community-based participatory research, where the community that would benefit from the chatbot also had a say in its design.…”

Section: Resultsmentioning

confidence: 99%

“…Surprisingly, there is no obvious correlation between application domains, chatbot purpose, and mode of communication (see Multimedia Appendix 2 [ 6 , 8 , 9 , 16 - 18 , 20 - 45 ]). Some studies did indicate that the use of natural language was not a necessity for a positive conversational user experience, especially for symptom-checking agents that are deployed to automate form filling [ 8 , 46 ].…”

Section: Resultsmentioning

confidence: 99%

“…Studies that focused on the effectiveness of chatbots with regard to an assigned task, such as triage and symptom checking, lent themselves more easily to evaluation through user analytics (n=8). There was, however, limited evaluation of user experience (n=3), and chatbot development was rarely design-led—although there were notable exceptions, with 1 study identifying user principles in development [ 17 ]; 1 study following a human-centered design process with young adults treated for cancer [ 43 ]; and another using community based, participatory research to develop a chatbot [ 16 ]. A further limitation noted in the evaluation of widely deployed chatbots is that the data collected by the chatbot for further analysis do not hold personally identifiable information, so it is not possible to know if the targeted population are the actual users [ 16 ].…”

Section: Resultsmentioning

confidence: 99%

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The Development and Use of Chatbots in Public Health: Scoping Review

Wilson¹,

Marasoiu²

2022

JMIR Hum Factors

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Background Chatbots are computer programs that present a conversation-like interface through which people can access information and services. The COVID-19 pandemic has driven a substantial increase in the use of chatbots to support and complement traditional health care systems. However, despite the uptake in their use, evidence to support the development and deployment of chatbots in public health remains limited. Recent reviews have focused on the use of chatbots during the COVID-19 pandemic and the use of conversational agents in health care more generally. This paper complements this research and addresses a gap in the literature by assessing the breadth and scope of research evidence for the use of chatbots across the domain of public health. Objective This scoping review had 3 main objectives: (1) to identify the application domains in public health in which there is the most evidence for the development and use of chatbots; (2) to identify the types of chatbots that are being deployed in these domains; and (3) to ascertain the methods and methodologies by which chatbots are being evaluated in public health applications. This paper explored the implications for future research on the development and deployment of chatbots in public health in light of the analysis of the evidence for their use. Methods Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines for scoping reviews, relevant studies were identified through searches conducted in the MEDLINE, PubMed, Scopus, Cochrane Central Register of Controlled Trials, IEEE Xplore, ACM Digital Library, and Open Grey databases from mid-June to August 2021. Studies were included if they used or evaluated chatbots for the purpose of prevention or intervention and for which the evidence showed a demonstrable health impact. Results Of the 1506 studies identified, 32 were included in the review. The results show a substantial increase in the interest of chatbots in the past few years, shortly before the pandemic. Half (16/32, 50%) of the research evaluated chatbots applied to mental health or COVID-19. The studies suggest promise in the application of chatbots, especially to easily automated and repetitive tasks, but overall, the evidence for the efficacy of chatbots for prevention and intervention across all domains is limited at present. Conclusions More research is needed to fully understand the effectiveness of using chatbots in public health. Concerns with the clinical, legal, and ethical aspects of the use of chatbots for health care are well founded given the speed with which they have been adopted in practice. Future research on their use should address these concerns through the development of expertise and best practices specific to public health, including a greater focus on user experience.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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The Development and Use of Chatbots in Public Health: Scoping Review

Wilson¹,

Marasoiu²

2022

JMIR Hum Factors

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“…As a tool for providing tailored messaging, social listening, and 2-way dialogue, automated conversational agents, or chatbots, were cited early in the pandemic as a promising tool to offer COVID-19 health guidance on demand [ 19 , 20 ]. Chatbots have provided support on a range of health issues including chronic disease, addiction, reproductive health, depression, and anxiety, with promising adaptations of evidence-based interventions such as cognitive behavioral therapy [ 21 - 25 ]. This approach may appeal especially to young adults, since a substantial proportion of millennials, born from 1981-1996, are more trusting of web-based information and better equipped to use health technology than earlier generations [ 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

Chatbot-Delivered COVID-19 Vaccine Communication Message Preferences of Young Adults and Public Health Workers in Urban American Communities: Qualitative Study

Weeks¹,

Cooper²,

Sangha³

et al. 2022

J Med Internet Res

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Background Automated conversational agents, or chatbots, have a role in reinforcing evidence-based guidance delivered through other media and offer an accessible, individually tailored channel for public engagement. In early-to-mid 2021, young adults and minority populations disproportionately affected by COVID-19 in the United States were more likely to be hesitant toward COVID-19 vaccines, citing concerns regarding vaccine safety and effectiveness. Successful chatbot communication requires purposive understanding of user needs. Objective We aimed to review the acceptability of messages to be delivered by a chatbot named VIRA from Johns Hopkins University. The study investigated which message styles were preferred by young, urban-dwelling Americans as well as public health workers, since we anticipated that the chatbot would be used by the latter as a job aid. Methods We conducted 4 web-based focus groups with 20 racially and ethnically diverse young adults aged 18-28 years and public health workers aged 25-61 years living in or near eastern-US cities. We tested 6 message styles, asking participants to select a preferred response style for a chatbot answering common questions about COVID-19 vaccines. We transcribed, coded, and categorized emerging themes within the discussions of message content, style, and framing. Results Participants preferred messages that began with an empathetic reflection of a user concern and concluded with a straightforward, fact-supported response. Most participants disapproved of moralistic or reasoning-based appeals to get vaccinated, although public health workers felt that such strong statements appealing to communal responsibility were warranted. Responses tested with humor and testimonials did not appeal to the participants. Conclusions To foster credibility, chatbots targeting young people with vaccine-related messaging should aim to build rapport with users by deploying empathic, reflective statements, followed by direct and comprehensive responses to user queries. Further studies are needed to inform the appropriate use of user-customized testimonials and humor in the context of chatbot communication.

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“…Research has demonstrated how visual, conversational, and identity-related cues trigger “humanness heuristics” ( 18 , 19 ) and affective states in users similar to natural human communication ( 20 ). Design factors such as physical appearance ( 21 ), gender ( 22 , 23 ), and speech dialect ( 24 ) can be tailored to match users' cultural and demographic background and help to establish rapport ( 15 , 20 ) and perceptions of a CA's personality ( 25 ). Language-based cues are of particular importance due to their strong role in driving user engagement ( 1 ).…”

Section: Introductionmentioning

confidence: 99%

The Terms of “You(s)”: How the Term of Address Used by Conversational Agents Influences User Evaluations in French and German Linguaculture

Ollier

Nißen

Wangenheim

2022

Front. Public Health

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Background: Conversational agents (CAs) are a novel approach to delivering digital health interventions. In human interactions, terms of address often change depending on the context or relationship between interlocutors. In many languages, this encompasses T/V distinction—formal and informal forms of the second-person pronoun “You”—that conveys different levels of familiarity. Yet, few research articles have examined whether CAs' use of T/V distinction across language contexts affects users' evaluations of digital health applications.Methods: In an online experiment (N = 284), we manipulated a public health CA prototype to use either informal or formal T/V distinction forms in French (“tu” vs. “vous”) and German (“du” vs. “Sie”) language settings. A MANCOVA and post-hoc tests were performed to examine the effects of the independent variables (i.e., T/V distinction and Language) and the moderating role of users' demographic profile (i.e., Age and Gender) on eleven user evaluation variables. These were related to four themes: (i) Sociability, (ii) CA-User Collaboration, (iii) Service Evaluation, and (iv) Behavioral Intentions.Results: Results showed a four-way interaction between T/V Distinction, Language, Age, and Gender, influencing user evaluations across all outcome themes. For French speakers, when the informal “T form” (“Tu”) was used, higher user evaluation scores were generated for younger women and older men (e.g., the CA felt more humanlike or individuals were more likely to recommend the CA), whereas when the formal “V form” (“Vous”) was used, higher user evaluation scores were generated for younger men and older women. For German speakers, when the informal T form (“Du”) was used, younger users' evaluations were comparable regardless of Gender, however, as individuals' Age increased, the use of “Du” resulted in lower user evaluation scores, with this effect more pronounced in men. When using the formal V form (“Sie”), user evaluation scores were relatively stable, regardless of Gender, and only increasing slightly with Age.Conclusions: Results highlight how user CA evaluations vary based on the T/V distinction used and language setting, however, that even within a culturally homogenous language group, evaluations vary based on user demographics, thus highlighting the importance of personalizing CA language.

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Layla’s Got You: Developing a tailored contraception chatbot for Black and Hispanic young women

Cited by 18 publications

References 27 publications

The Development and Use of Chatbots in Public Health: Scoping Review

The Development and Use of Chatbots in Public Health: Scoping Review

Chatbot-Delivered COVID-19 Vaccine Communication Message Preferences of Young Adults and Public Health Workers in Urban American Communities: Qualitative Study

The Terms of “You(s)”: How the Term of Address Used by Conversational Agents Influences User Evaluations in French and German Linguaculture

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