scholarly journals Case study on sexual and reproductive health and education: reflections on interlinkage and governance

10.5334/bao.j ◽  
2015 ◽  
pp. 89-107
Author(s):  
Susannah Mayhew ◽  
Elaine Unterhalter ◽  
Nigel Poole ◽  
Niheer Dasandi ◽  
Niall Winters
Keyword(s):  
Reproductive Health ◽  
Sexual And Reproductive Health

scholarly journals Research capacity strengthening for sexual and reproductive health: a case study from Latin America

2017 ◽  
Vol 14 (1) ◽  
Author(s):  
Rita Kabra ◽  
Marco Castillo ◽  
Mercedes Melián ◽  
Moazzam Ali ◽  
Lale Say ◽  
...  
Keyword(s):  
Latin America ◽  
Reproductive Health ◽  
Sexual And Reproductive Health ◽  
Research Capacity ◽  
Capacity Strengthening ◽  
Research Capacity Strengthening

Occupational Therapy and Sexual and Reproductive Health Promotion in Adolescence: A Case Study

2015 ◽  
Vol 23 (1) ◽  
pp. 19-28 ◽  
Author(s):  
Daniela Tavares Gontijo ◽  
Anna Carolina de Sena e Vasconcelos ◽  
Rosana Juliet Silva Monteiro ◽  
Vera Lúcia Dutra Facundes ◽  
Maria de Fátima Cordeiro Trajano ◽  
...  
Keyword(s):  
Health Promotion ◽  
Reproductive Health ◽  
Occupational Therapy ◽  
Sexual And Reproductive Health

scholarly journals An Artificial Intelligence Chatbot for Young People’s Sexual and Reproductive Health in India (SnehAI): Instrumental Case Study

10.2196/29969 ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. e29969
Author(s):  
Hua Wang ◽  
Sneha Gupta ◽  
Arvind Singhal ◽  
Poonam Muttreja ◽  
Sanghamitra Singh ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Reproductive Health ◽  
Language Processing ◽  
Sexual And Reproductive Health ◽  
Processing System ◽  
User Engagement ◽  
Social Good ◽  
Instrumental Case Study ◽  
Instrumental Case

Background Leveraging artificial intelligence (AI)–driven apps for health education and promotion can help in the accomplishment of several United Nations sustainable development goals. SnehAI, developed by the Population Foundation of India, is the first Hinglish (Hindi + English) AI chatbot, deliberately designed for social and behavioral changes in India. It provides a private, nonjudgmental, and safe space to spur conversations about taboo topics (such as safe sex and family planning) and offers accurate, relatable, and trustworthy information and resources. Objective This study aims to use the Gibson theory of affordances to examine SnehAI and offer scholarly guidance on how AI chatbots can be used to educate adolescents and young adults, promote sexual and reproductive health, and advocate for the health entitlements of women and girls in India. Methods We adopted an instrumental case study approach that allowed us to explore SnehAI from the perspectives of technology design, program implementation, and user engagement. We also used a mix of qualitative insights and quantitative analytics data to triangulate our findings. Results SnehAI demonstrated strong evidence across fifteen functional affordances: accessibility, multimodality, nonlinearity, compellability, queriosity, editability, visibility, interactivity, customizability, trackability, scalability, glocalizability, inclusivity, connectivity, and actionability. SnehAI also effectively engaged its users, especially young men, with 8.2 million messages exchanged across a 5-month period. Almost half of the incoming user messages were texts of deeply personal questions and concerns about sexual and reproductive health, as well as allied topics. Overall, SnehAI successfully presented itself as a trusted friend and mentor; the curated content was both entertaining and educational, and the natural language processing system worked effectively to personalize the chatbot response and optimize user experience. Conclusions SnehAI represents an innovative, engaging, and educational intervention that enables vulnerable and hard-to-reach population groups to talk and learn about sensitive and important issues. SnehAI is a powerful testimonial of the vital potential that lies in AI technologies for social good.

scholarly journals An Artificial Intelligence Chatbot for Young People’s Sexual and Reproductive Health in India (SnehAI): Instrumental Case Study (Preprint)

2021 ◽  
Author(s):  
Hua Wang ◽  
Sneha Gupta ◽  
Arvind Singhal ◽  
Poonam Muttreja ◽  
Sanghamitra Singh ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Reproductive Health ◽  
Language Processing ◽  
Sexual And Reproductive Health ◽  
Processing System ◽  
User Engagement ◽  
Social Good ◽  
Instrumental Case Study ◽  
Instrumental Case

BACKGROUND Leveraging artificial intelligence (AI)–driven apps for health education and promotion can help in the accomplishment of several United Nations sustainable development goals. SnehAI, developed by the Population Foundation of India, is the first Hinglish (Hindi + English) AI chatbot, deliberately designed for social and behavioral changes in India. It provides a private, nonjudgmental, and safe space to spur conversations about taboo topics (such as safe sex and family planning) and offers accurate, relatable, and trustworthy information and resources. OBJECTIVE This study aims to use the Gibson theory of affordances to examine SnehAI and offer scholarly guidance on how AI chatbots can be used to educate adolescents and young adults, promote sexual and reproductive health, and advocate for the health entitlements of women and girls in India. METHODS We adopted an instrumental case study approach that allowed us to explore SnehAI from the perspectives of technology design, program implementation, and user engagement. We also used a mix of qualitative insights and quantitative analytics data to triangulate our findings. RESULTS SnehAI demonstrated strong evidence across fifteen functional affordances: accessibility, multimodality, nonlinearity, compellability, queriosity, editability, visibility, interactivity, customizability, trackability, scalability, glocalizability, inclusivity, connectivity, and actionability. SnehAI also effectively engaged its users, especially young men, with 8.2 million messages exchanged across a 5-month period. Almost half of the incoming user messages were texts of deeply personal questions and concerns about sexual and reproductive health, as well as allied topics. Overall, SnehAI successfully presented itself as a trusted friend and mentor; the curated content was both entertaining and educational, and the natural language processing system worked effectively to personalize the chatbot response and optimize user experience. CONCLUSIONS SnehAI represents an innovative, engaging, and educational intervention that enables vulnerable and hard-to-reach population groups to talk and learn about sensitive and important issues. SnehAI is a powerful testimonial of the vital potential that lies in AI technologies for social good. CLINICALTRIAL

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