Evidence and Future Directions for Pediatric Health Care Chatbots: Systematic Review
Journal of Medical Internet Research ·
Background: Pediatric health care requires distinct considerations, including caregiver involvement and developmental differences in cognition and communication as children gain autonomy, particularly as pediatric health care chatbots gradually emerge. Because childhood and adolescence are formative periods for health behaviors and self-management practices, pediatric chatbots also warrant evaluation against long-term rather than immediate outcomes. Objective: This study aimed to characterize and synthesize the available evidence on pediatric health care chatbots evaluated for health-related outcomes. Furthermore, by identifying gaps in the existing literature, we sought to propose specific considerations for the design, evaluation, and implementation of pediatric health care chatbots. Methods: PubMed, Embase, Scopus, PsycINFO, the Cochrane Library, and the Web of Science were systematically searched without publication year restrictions. Randomized controlled trials, mixed methods, and observational studies that evaluated health care chatbots for children (aged <19 y) or caregivers and assessed health-related outcomes were included. Nonoriginal papers, end-of-life or palliative care studies, and non-English publications were excluded. Study quality was assessed using the Mixed Methods Appraisal Tool and the Oxford Levels of Evidence 2. Results: A total of 9 studies were included, with 5 (55.6%) involving pediatric participants only, while 4 (44.4%) involved caregivers. Six (66.7%) studies lacked a comparator, and only 3 (33.3%) chatbots were AI-based. Health and psychosocial outcomes were mixed, often showing null findings in objective clinical metrics despite some subjective improvements. Behavioral and cognitive outcomes generally showed favorable changes but relied heavily on subjective evaluations. Although chatbots demonstrated explicit developmental tailoring, with designs shifting from caregiver-mediated approaches in early childhood to autonomous, privacy-focused platforms for adolescents, definitive conclusions regarding their robust associations with health-related outcomes cannot be drawn. This is primarily due to pervasive methodological limitations, including the lack of active comparator groups, reliance on short-term metrics, and significant study heterogeneity. Conclusions: Pediatric health care chatbots are emerging across diverse health care contexts, but the current evidence remains limited and heterogeneous. This review identified developmentally relevant considerations, including caregiver involvement, age-appropriate communication, and developmental differences, that may warrant explicit attention in future chatbot design, evaluation, and implementation.
Background: Pediatric health care requires distinct considerations, including caregiver involvement and developmental differences in cognition and communication as children gain autonomy, particularly as pediatric health care chatbots gradually emerge. Because childhood and adolescence are formative periods for health behaviors and self-management practices, pediatric chatbots also warrant evaluation against long-term rather than immediate outcomes. Objective: This study aimed to characterize and synthesize the available evidence on pediatric health care chatbots evaluated for health-related outcomes. Furthermore, by identifying gaps in the existing literature, we sought to propose specific considerations for the design, evaluation, and implementation of pediatric health care chatbots. Methods: PubMed, Embase, Scopus, PsycINFO, the Cochrane Library, and the Web of Science were systematically searched without publication year restrictions. Randomized controlled trials, mixed methods, and observational studies that evaluated health care chatbots for children (aged <19 y) or caregivers and assessed health-related outcomes were included. Nonoriginal papers, end-of-life or palliative care studies, and non-English publications were excluded. Study quality was assessed using the Mixed Methods Appraisal Tool and the Oxford Levels of Evidence 2. Results: A total of 9 studies were included, with 5 (55.6%) involving pediatric participants only, while 4 (44.4%) involved caregivers. Six (66.7%) studies lacked a comparator, and only 3 (33.3%) chatbots were AI-based. Health and psychosocial outcomes were mixed, often showing null findings in objective clinical metrics despite some subjective improvements. Behavioral and cognitive outcomes generally showed favorable changes but relied heavily on subjective evaluations. Although chatbots demonstrated explicit developmental tailoring, with designs shifting from caregiver-mediated approaches in early childhood to autonomous, privacy-focused platforms for adolescents, definitive conclusions regarding their robust associations with health-related outcomes cannot be drawn. This is primarily due to pervasive methodological limitations, including the lack of active comparator groups, reliance on short-term metrics, and significant study heterogeneity. Conclusions: Pediatric health care chatbots are emerging across diverse health care contexts, but the current evidence remains limited and heterogeneous. This review identified developmentally relevant considerations, including caregiver involvement, age-appropriate communication, and developmental differences, that may warrant explicit attention in future chatbot design, evaluation, and implementation.