Utilizing User Preferences in Designing the AGILE (Accelerating Access to Gender-Based Violence Information and Services Leveraging on Technology Enhanced) Chatbot

Anne Ngũnjiri, Peter Memiah (), Robert Kimathi, Fernando A. Wagner, Annrita Ikahu, Eunice Omanga, Emmanuel Kweyu, Carol Ngunu and Lilian Otiso
Additional contact information
Anne Ngũnjiri: LVCT Health Kenya, Nairobi P.O. Box 19835-00202, Kenya
Peter Memiah: Graduate School, University of Maryland, 620 W. Lexington Street, Baltimore, MD 21201, USA
Robert Kimathi: LVCT Health Kenya, Nairobi P.O. Box 19835-00202, Kenya
Fernando A. Wagner: School of Social Work, University of Maryland, 525 W. Redwood Street, Baltimore, MD 21201, USA
Annrita Ikahu: LVCT Health Kenya, Nairobi P.O. Box 19835-00202, Kenya
Eunice Omanga: LVCT Health Kenya, Nairobi P.O. Box 19835-00202, Kenya
Emmanuel Kweyu: Faculty of Information Technology, Strathmore University, Nairobi P.O. Box 59857-00200, Kenya
Carol Ngunu: Department of Health, Nairobi City County, Nairobi P.O. Box 30075-00100, Kenya
Lilian Otiso: LVCT Health Kenya, Nairobi P.O. Box 19835-00202, Kenya

IJERPH, 2023, vol. 20, issue 21, 1-16

Abstract: Introduction: Technology advancements have enhanced artificial intelligence, leading to a user shift towards virtual assistants, but a human-centered approach is needed to assess for acceptability and effectiveness. The AGILE chatbot is designed in Kenya with features to redefine the response towards gender-based violence (GBV) among vulnerable populations, including adolescents, young women and men, and sexual and gender minorities, to offer accurate and reliable information among users. Methods: We conducted an exploratory qualitative study through focus group discussions (FGDs) targeting 150 participants sampled from vulnerable categories; adolescent girls and boys, young women, young men, and sexual and gender minorities. The FGDs included multiple inquiries to assess knowledge and prior interaction with intelligent conversational assistants to inform the user-centric development of a decision-supportive chatbot and a pilot of the chatbot prototype. Each focus group comprised 9–10 members, and the discussions lasted about two hours to gain qualitative user insights and experiences. We used thematic analysis and drew on grounded theory to analyze the data. Results: The analysis resulted in 14 salient themes composed of sexual violence, physical violence, emotional violence, intimate partner violence, female genital mutilation, sexual reproductive health, mental health, help-seeking behaviors/where to seek support, who to talk to, and what information they would like, features of the chatbot, access of chatbot, abuse and HIV, family and community conflicts, and information for self-care. Conclusion: Adopting a human-centered approach in designing an effective chatbot with as many human features as possible is crucial in increasing utilization, addressing the gaps presented by marginalized/vulnerable populations, and reducing the current GBV epidemic by moving prevention and response services closer to people in need.

Keywords: chatbot; violence; adolescent health (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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