Background: Conversational agents have the ability to reach people through multiple mediums, including the online space, mobile phones, and hardware devices like Alexa and Google Home. Conversational agents provide an engaging method of interaction while making information easier to access. Their emergence into areas related to public health and health education is perhaps unsurprising. While the building of conversational agents is getting more simplified with time, there are still requirements of time and effort. There is also a lack of clarity and consistent terminology regarding what constitutes a conversational agent, how these agents are developed, and the kinds of resources that are needed to develop and sustain them. This lack of clarity creates a daunting task for those seeking to build conversational agents for health education initiatives.
Objective: This scoping review aims to identify literature that reports on the design and implementation of conversational agents to promote and educate the public on matters related to health. We will categorize conversational agents in health education in alignment with current classifications and terminology emerging from the marketplace. We will clearly define the variety levels of conversational agents, categorize currently existing agents within these levels, and describe the development models, tools, and resources being used to build conversational agents for health care education purposes.
Methods: This scoping review will be conducted by employing the Arksey and O'Malley framework. We will also be adhering to the enhancements and updates proposed by Levac et al and Peters et al. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews will guide the reporting of this scoping review. A systematic search for published and grey literature will be undertaken from the following databases: (1) PubMed, (2) PsychINFO, (3) Embase, (4) Web of Science, (5) SCOPUS, (6) CINAHL, (7) ERIC, (8) MEDLINE, and (9) Google Scholar. Data charting will be done using a structured format.
Results: Initial searches of the databases retrieved 1305 results. The results will be presented in the final scoping review in a narrative and illustrative manner.
Conclusions: This scoping review will report on conversational agents being used in health education today, and will include categorization of the levels of the agents and report on the kinds of tools, resources, and design and development methods used.
International Registered Report Identifier (irrid): DERR1-10.2196/31923.
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http://dx.doi.org/10.2196/31923 | DOI Listing |
JMIR Cardio
December 2024
Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, Netherlands.
Health care is under pressure due to an aging population with an increasing prevalence of chronic diseases, including cardiovascular disease. Smoking and physical inactivity are 2 key preventable risk factors for cardiovascular disease. Yet, as with most health behaviors, they are difficult to change.
View Article and Find Full Text PDFJ Speech Lang Hear Res
December 2024
University of California, San Francisco.
Purpose: We investigate the extent to which automated audiovisual metrics extracted during an affect production task show statistically significant differences between a cohort of children diagnosed with autism spectrum disorder (ASD) and typically developing controls.
Method: Forty children with ASD and 21 neurotypical controls interacted with a multimodal conversational platform with a virtual agent, Tina, who guided them through tasks prompting facial and vocal communication of four emotions-happy, angry, sad, and afraid-under conditions of high and low verbal and social cognitive task demands.
Results: Individuals with ASD exhibited greater standard deviation of the fundamental frequency of the voice with the minima and maxima of the pitch contour occurring at an earlier time point as compared to controls.
Neuropsychiatr Dis Treat
December 2024
Department of Intelligent Systems, Jožef Stefan Institute, Ljubljana, Slovenia.
Background: The importance of computational psychotherapy is increasing due to the record high prevalence of mental health issues worldwide. Despite advancements, current computational psychotherapy systems lack advanced prediction and behavior change mechanisms using conversational agents.
Purpose: This work presents a computational psychotherapy system for mental health prediction and behavior change using a conversational agent.
BMC Glob Public Health
September 2024
Chobanian & Avedisian School of Medicine, Boston University, Boston, USA.
Background: Young women worldwide face problems like unwanted pregnancy and sexually transmitted infections. Providing sexual and reproductive health education to young women in low- and middle-income countries is a priority. It is unknown if using digital health interventions to deliver health education is effective in resource-constrained settings.
View Article and Find Full Text PDFJMIR Form Res
December 2024
Center for Technology Experience, AIT - Austrian Institute of Technology, Vienna, Austria.
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