TY - JOUR
T1 - Conversational agents for health and well-being across the life course
T2 - protocol for an evidence map
AU - Guerreiro, Mara Pereira
AU - Angelini, Leonardo
AU - Henriques, Helga Rafael
AU - Kamali, Mira El
AU - Baixinho, Cristina
AU - Balsa, João
AU - Félix, Isa Brito
AU - Khaled, Omar Abou
AU - Carmo, Maria Beatriz
AU - Cláudio, Ana Paula
AU - Caon, Maurizio
AU - Daher, Karl
AU - Alexandre, Bruno
AU - Padinha, Mafalda
AU - Mugellini, Elena
N1 - Funding Information:
This study is part of the Harnessing the Power of Conversational e-Coaches for Health and Well-being Through Swiss-Portuguese Collaboration project, which was awarded a grant for joint Swiss-Portuguese academic projects and funded by the Haute Ecole Spécialisée de Suisse occidentale (University of Applied Sciences and Arts Western Switzerland) and the Conselho Coordenador dos Institutos Superiores Politécnicos (Portuguese Polytechnics Coordinating Council). The sponsors did not have any role in the design, execution, and reporting of the study.
Publisher Copyright:
© The Author(s), 2021.
PY - 2021/9
Y1 - 2021/9
N2 - Background: Conversational agents, which we defined as computer programs that are designed to simulate two-way human conversation by using language and are potentially supplemented with nonlanguage modalities, offer promising avenues for health interventions for different populations across the life course. There is a lack of open-access and user-friendly resources for identifying research trends and gaps and pinpointing expertise across international centers. Objective: Our aim is to provide an overview of all relevant evidence on conversational agents for health and well-being across the life course. Specifically, our objectives are to identify, categorize, and synthesize-through visual formats and a searchable database-primary studies and reviews in this research field. Methods: An evidence map was selected as the type of literature review to be conducted, as it optimally corresponded to our aim. We systematically searched 8 databases (MEDLINE; CINAHL; Web of Science; Scopus; the Cochrane, ACM, IEEE, and Joanna Briggs Institute databases; and Google Scholar). We will perform backward citation searching on all included studies. The first stage of a double-stage screening procedure, which was based on abstracts and titles only, was conducted by using predetermined eligibility criteria for primary studies and reviews. An operational screening procedure was developed for streamlined and consistent screening across the team. Double data extraction will be performed with previously piloted data collection forms. We will appraise systematic reviews by using A Measurement Tool to Assess Systematic Reviews (AMSTAR) 2. Primary studies and reviews will be assessed separately in the analysis. Data will be synthesized through descriptive statistics, bivariate statistics, and subgroup analysis (if appropriate) and through high-level maps such as scatter and bubble charts. The development of the searchable database will be informed by the research questions and data extraction forms. Results: As of April 2021, the literature search in the eight databases was concluded, yielding a total of 16,351 records. The first stage of screening, which was based on abstracts and titles only, resulted in the selection of 1282 records of primary studies and 151 records of reviews. These will be subjected to second-stage screening. A glossary with operational definitions for supporting the study selection and data extraction stages was drafted. The anticipated completion date is October 2021 Conclusions: Our wider definition of a conversational agent and the broad scope of our evidence map will explicate trends and gaps in this field of research. Additionally, our evidence map and searchable database of studies will help researchers to avoid fragmented research efforts and wasteful redundancies. Finally, as part of the Harnessing the Power of Conversational e-Coaches for Health and Well-being Through Swiss-Portuguese Collaboration project, our work will also inform the development of an international taxonomy on conversational agents for health and well-being, thereby contributing to terminology standardization and categorization. 10.2196/26680.
AB - Background: Conversational agents, which we defined as computer programs that are designed to simulate two-way human conversation by using language and are potentially supplemented with nonlanguage modalities, offer promising avenues for health interventions for different populations across the life course. There is a lack of open-access and user-friendly resources for identifying research trends and gaps and pinpointing expertise across international centers. Objective: Our aim is to provide an overview of all relevant evidence on conversational agents for health and well-being across the life course. Specifically, our objectives are to identify, categorize, and synthesize-through visual formats and a searchable database-primary studies and reviews in this research field. Methods: An evidence map was selected as the type of literature review to be conducted, as it optimally corresponded to our aim. We systematically searched 8 databases (MEDLINE; CINAHL; Web of Science; Scopus; the Cochrane, ACM, IEEE, and Joanna Briggs Institute databases; and Google Scholar). We will perform backward citation searching on all included studies. The first stage of a double-stage screening procedure, which was based on abstracts and titles only, was conducted by using predetermined eligibility criteria for primary studies and reviews. An operational screening procedure was developed for streamlined and consistent screening across the team. Double data extraction will be performed with previously piloted data collection forms. We will appraise systematic reviews by using A Measurement Tool to Assess Systematic Reviews (AMSTAR) 2. Primary studies and reviews will be assessed separately in the analysis. Data will be synthesized through descriptive statistics, bivariate statistics, and subgroup analysis (if appropriate) and through high-level maps such as scatter and bubble charts. The development of the searchable database will be informed by the research questions and data extraction forms. Results: As of April 2021, the literature search in the eight databases was concluded, yielding a total of 16,351 records. The first stage of screening, which was based on abstracts and titles only, resulted in the selection of 1282 records of primary studies and 151 records of reviews. These will be subjected to second-stage screening. A glossary with operational definitions for supporting the study selection and data extraction stages was drafted. The anticipated completion date is October 2021 Conclusions: Our wider definition of a conversational agent and the broad scope of our evidence map will explicate trends and gaps in this field of research. Additionally, our evidence map and searchable database of studies will help researchers to avoid fragmented research efforts and wasteful redundancies. Finally, as part of the Harnessing the Power of Conversational e-Coaches for Health and Well-being Through Swiss-Portuguese Collaboration project, our work will also inform the development of an international taxonomy on conversational agents for health and well-being, thereby contributing to terminology standardization and categorization. 10.2196/26680.
KW - Artificial intelligence
KW - Chatbot
KW - Conversational agent
KW - E-coach
KW - Health
KW - Intervention
KW - Relational agent
KW - Virtual assistant
KW - Virtual humans
KW - Well-being
UR - http://www.scopus.com/inward/record.url?scp=85115622372&partnerID=8YFLogxK
U2 - 10.2196/26680
DO - 10.2196/26680
M3 - Article
C2 - 34533460
AN - SCOPUS:85115622372
SN - 1929-0748
VL - 10
JO - JMIR Research Protocols
JF - JMIR Research Protocols
IS - 9
M1 - e26680
ER -