As low- and middle-income countries transition from paper to digital systems, family planning programs can benefit from unprecedented opportunities to improve services. Investments in digital health tools have expanded exponentially, but information on what works—and what does not— remains limited and scattered. As investments have increased, digital applications and data fragmentation have proliferated, but stakeholders are moving towards more coordinated efforts to scale digital health solutions, support countries’ digital health infrastructure, and share evidence-based learnings.
This Digital Health Compendium enables users to explore case studies across a range of digital health technologies used to enhance family planning programs mainly in sub-Saharan Africa, but also in other regions of the world. Digital health applications in family planning programs can be broadly classified as those affecting demand generation, service delivery, supply chain management, and the policy and enabling environment. In many low- and middle-income countries, digital health innovations were adopted earlier in other health sectors, including HIV/AIDS, maternal and child health, and noncommunicable disease prevention and response. As a result, much of the impact evidence is likewise restricted to those sectors. To advance greater adoption of digital technology in family planning programs, more data and information on the challenges, opportunities, scalability, and results are needed. This compendium aims to consolidate emerging information and data on applications of digital technology in family planning programs to inform adoption and scale-up of successful approaches.
All of the case studies were submitted by the implementing organizations and include a description of the digital health intervention, program context, and, if available, important findings and lessons learned through rigorous evaluations or program data. The compendium facilitates a quick search for case studies based on the target user for digital health intervention, building block for the digital health enabling environment, family planning program classification, and country location. The case studies give policy and program decisionmakers insights on real-world applications of digital health, promising practices, challenges, and other lessons that can be applied to current and future programs.
New
An innovative chatbot in India that was purposefully conceptualized and designed by the Population Foundation of India to educate and inspire adolescents and young adults to live healthy lives, promote sexual and reproductive health (SRH), and advocate for health and well-being of women and girls.
The Population Foundation of India
The Population Foundation of India
ONGOING
The Population Foundation of India
Hua Wang
Services and Applications
Demand Generation
An innovative chatbot in India that was purposefully conceptualized and designed by the Population Foundation of India to educate and inspire adolescents and young adults to live healthy lives, promote sexual and reproductive health (SRH), and advocate for health and well-being of women and girls.
With a population of approximately 1.4 billion, India accounts for about 18% of all people on the planet [1] with half of this population being under the age of 25 years. [2] Despite policy commitments and significant strides made in recent years, the informational needs of adolescents and youth are poorly met, quality education about SRH is highly limited, contraceptive practices are heavily skewed toward female sterilization, and unsafe abortions are rampant. [3-6] In particular, young people in India have limited awareness of contraception and sexually transmitted infections; their knowledge base consists of inaccurate information, and their family life education is highly insufficient. [7]
Although the government of India endorsed a national adolescent health program to support access to SRH services since 2014, direct contact with frontline health workers, even by married young women, remained extremely low. In addition, contact with unmarried youth and the use of SRH services at adolescent-friendly health clinics are almost completely amiss. [8] Uncomfortable and embarrassed to ask, young people in India have increasingly referred to web-based platforms to look for answers to SRH questions and have garnered misleading or incorrect information. [9,10]
At the beginning of 2020, India boasted of 1.1 billion mobile phone connections, covering 78% of the population. [11] With attractive pricing from India-based telecom giants, such as Jio, internet penetration and social media use through mobile networks are rapidly growing. [11,12] Facebook (Meta platforms) is an obvious leader in the social media space in India, with 320 million users. [13] With this massive expansion of information infrastructure comprising wireless networks, digital technologies, and social media, Indian youths, both in urban and rural areas, are increasingly being plugged into this technology web. The SnehAI chatbot aims to provide a safe space for Indian youth to have conversations about SRH, dispel sex-related myths and taboos, offer accurate information about safe sex and contraceptive choices, and address mental health concerns.
Chatbots are automated nonhuman agents that engage in conversations with human actors [14]. By design, the user experience in a chatbot strives to be pleasant, as it mimics a scenario in which 2 humans are talking with each other. A chatbot responds by accessing information stored in large digital data repositories. Chatbots quickly sieve what is relevant and convert programming codes into expressions that humans can understand. Although chatbots are often text-based, their capabilities have exploded since the pioneering program ELIZA, an early natural language processing computer program [15], especially in their increased sophistication and accuracy in understanding natural language using artificial intelligence (AI) technologies [16,17]. Machine learning, a method of data analysis that automates analytical model building, makes the deployment of AI immensely valuable for disseminating information.
SnehAI represents the first Hinglish (Hindi + English).
AI chatbot that is co-created with and for young people, especially those from vulnerable sections of society, to deliberately facilitate communication about SRH topics and promote social and behavioral change [18,19]. SnehAI provides an unusual repository of educational knowledge in an entertaining and engaging container, commonly referred to as entertainment-education or edutainment [20,21] In April 2020, SnehAI (version 2.0) was launched with a natural language processing (NLP) platform and better content flow to make it more intelligent in conversations with users [19]. It is required that an individual be a user of Facebook Messenger to chat with SnehAI
The aggregate dashboard analytics data on SnehAI user behaviors was examined over a period of 5-month. A total of 8,170,879 messages were exchanged between SnehAI and 135,263 unique chatbot users, including 5,100,449 (62.42%) outgoing messages from the chatbot to the users and 3,070,430 (37.58%) incoming messages from the users to the chatbot. The ratios between outgoing and incoming messages were consistently around 60:40 over time, with the exception of repeated outgoing messages in July (such as technical errors). Specifically, incoming messages from the users to the chatbot were sent through free texts (1,599,339/2,878,908, 52.09%); clickable reactions (1,279,569/2,878,908, 41.67%); or GIFs, audios, images, and videos (191,522/2,878,908, 6.24%).
The average user engagement with SnehAI was 1.9 sessions, 7.6 minutes, and 56.2 messages exchanged. The time spent by top users increased from 2 to 3 hours in the first 3 months to 7 hours in 14 sessions in August and 14 hours in 47 sessions in September.
User engagement was also tracked through the content categories, including both guided flows using clickable reactions and the handling of free-text messages using NLP. From onboarding to learning about SnehAI, to its privacy policy, and its main menu to the videos, stories, games, helplines, and query responses through NLP, the chatbot users traversed across these content areas for 1,430,416 times over the course of 5 months. Approximately half (705,305/1,430,416, 49.31%) of these interactions were about the chatbot responding to the user queries, including small talks and any questions related to themes of health communication. The next highest frequency content category was user enrolment (257,042/1,430,416, 17.97%), about SnehAI (115,131/1,430,416, 8.05%), privacy policy (96,305/1,430,416, 6.73%), main menu (83,692/1,430,416, 5.85%), helplines (71,211/1,430,416, 4.98%), stories (61,582/1,430,416, 4.31%), games (20,897/1,430,416, 1.46%), and videos (19,251/1,430,416, 1.35%). These trends in content engagement distribution were relatively consistent (with occasional fluctuations).
Our analytics tracking data showed a count of 99,936 typed text messages from the users that SnehAI handled and responded through the NLP system with queries related to the six topical themes 
safe sex practices, such as consent, frequency of sexual intercourse, oral and anal sex, impact of other health ailments on sex life, and unplanned pregnancy (57,158/99,936, 57.19%); choice of family planning methods, such as male and female condoms, oral contraceptive pills, intrauterine devices, injectables, and SRH-related themes, such as abortion, sexual intercourse during and after pregnancy, polycystic ovarian disease, and infertility issues (6287/99,936, 6.29%); female reproductive health concerning menstruation (e.g., regularity, pain, discharge, and spotting), virginity, and premarital sex (13,965/99,936, 13.97%); adolescent sexual health issues, such as nightfall, masturbation, pornography, sexual stamina, erectile dysfunction, and STIs (15,160/99,936, 15.17%); adolescent mental health issues regarding peer pressure and bullying (2343/99,936, 2.34%); and nutrition and social determinants of health, such as child marriage and gender equality (4623/99,936, 4.63%).
SnehAI chatbot user gender-disaggregated data revealed an extreme gender gap
among the unique chatbot users over the 5-month period, 93% (125,795/135,263) were male, 6.8% (9198/135,263) were female, and 0.2% (270/135,263) unknown. This gender ratio was disproportionally skewed toward male users compared with that in the United Nations Development Programme report on the gender distribution of internet users (29% female) and Facebook users (22% female) in India [12]. This might be a function of female users facing gender disparities in mobile device ownership and low digital media literacy in India. Also, the 15,000 queries that were sampled by the data science team established a behavioral pattern that revealed that female users exhibited significantly lower self-confidence in their conversations with SnehAI
As the first Hinglish (Hindi and English) AI chatbot deliberately designed for social and behavior change communication, SnehAI is an innovative, unique, and promising app for engaging vulnerable and hard-to-reach populations groups in the context of SRH education and discussion. It offered a private, non-judgmental, and safe space for users to talk about otherwise sensitive topics, obtain accurate and trustworthy information, access national services through toll-free helplines, and seek personalized consultations. It also opened up exciting opportunities to leverage the emotional appeal of storytelling through thoughtful yet entertaining content, positive outlook of an avatar, relatable verbal and nonverbal expressions, and friendly tone of voice to effectively engage young people in talking and learning about SRH. SnehAI will further be scaled up to reach potential beneficiaries within and beyond India.
Wang H, Gupta S, Singhal A, et al. (20220 An Artificial Intelligence Chatbot for Young People’s Sexual and Reproductive Health in India (SnehAI): Instrumental Case Study. J Med Internet Res. 2022;24(1): e29969. Published 2022 Jan 3. Available online: https://bit.ly/3sICCub [Last accessed 19th March, 2022]