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Mobile Phone-Based Chatbot for Family Planning and Contraceptive Information

Part of the Lecture Notes in Computer Science book series (LNISA,volume 11582)

Abstract

This study is about a mobile phone-based Chatbot specifically designed to provide information about family planning and contraceptives. Chatbot is essentially a text-messaging service that follows a decision-tree structure to provide feedback to users. The Chatbot was built using a text-messaging platform developed by Trext and can be accessed in the United States by sending ‘BCS’ as a text message to phone number +1-313-228-3034. The contents of Chatbot are derived from the Balanced Counseling Strategy (BCS) prepared by The Population Council. UTAUT model of technology adoption was employed to assess the attitudinal and behavioral factors that determine the intention to use Chatbot. The study included 49 participants, age 18 and above, married or in a relationship. Regression analysis show positive attitude as the main predictor of behavioral intention to use Chatbot to acquire family planning related information. Consequently, positive attitude was determined by effort expectancy and performance expectancy to use the Chatbot. The study has implications to design mobile phone-based texting services to help mothers, husbands and community health providers to learn about family planning in a private, interactive and enjoyable manner. To the best of our knowledge, this is the first study to systematically evaluate the effectiveness of a mobile phone-based Chatbot for family planning counseling. The study is a proof-of-concept with limited number of participants within USA. However, the study offers implications to scale-up existing family planning interventions both domestically and internationally.

Keywords

  • Chatbot
  • Family planning
  • SMS
  • Mobile health
  • UTAUT

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Correspondence to Syed Ali Hussain .

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Hussain, S.A., Ogundimu, F., Bhattarai, S. (2019). Mobile Phone-Based Chatbot for Family Planning and Contraceptive Information. In: Duffy, V. (eds) Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Healthcare Applications. HCII 2019. Lecture Notes in Computer Science(), vol 11582. Springer, Cham. https://doi.org/10.1007/978-3-030-22219-2_26

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  • DOI: https://doi.org/10.1007/978-3-030-22219-2_26

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