AI-powered whatsapp chatbots for maternal and child health: a quasi-experimental study among pregnant women in Indonesia
DOI:
https://doi.org/10.12928/jcp.v7i2.13858Keywords:
Health Information Access, Health Literacy, Maternal Health, Meta AI-Chatbot, Pregnant WomenAbstract
Maternal and child health remains a critical priority in global health strategies, particularly in achieving the Sustainable Development Goals (SDGs). In Indonesia, maternal mortality remains significantly higher than the SDG target, underscoring the urgent need for accessible and high-quality maternal health information. Digital innovations, such as Artificial Intelligence (AI)-based chatbots, have emerged as promising tools to help bridge this gap. This study aimed to evaluate the effectiveness of a Meta-AI chatbot delivered via WhatsApp in improving pregnant women’s access to maternal and child health information. A quasi-experimental one-group pretest–posttest design was employed, involving 30 pregnant women in Singasari Village, Tasikmalaya Regency. Participants received a one-time training session on accessing health information—particularly related to pregnancy care—through the Meta-AI WhatsApp chatbot, supported by a guidance booklet. Data were collected using a validated and reliable questionnaire that assessed participants’ knowledge and skills before and after the intervention. Paired sample t-tests were used to compare pre- and post-intervention scores. The results demonstrated significant improvements in both knowledge and skills. Knowledge scores increased from 5.00 (SD = 2.00) to 9.40 (SD = 0.85), t(29) = 29.0, p < 0.001, Cohen’s d = 1.88, 95% CI [1.27, 2.47]. Similarly, skills scores rose from 26.5 (SD = 5.40) to 36.7 (SD = 3.02), t(29) = 29.0, p < 0.001, Cohen’s d = 2.31, 95% CI [1.61, 2.99]. These findings indicate that the Meta AI chatbot, accessed via WhatsApp, significantly enhanced pregnant women’s knowledge and skills, thereby improving access to accurate maternal health information, strengthening health literacy, and supporting informed decision-making. Future research should explore the long-term effects of this intervention and its potential integration into public health systems.
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