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Effect of AI-Based Health Chatbots on Health Information-Seeking among University Students in Nigeria

Abstract

Health information-seeking is an important component of health literacy, disease prevention, informed decision-making, and appropriate utilization of healthcare services among university students. University students increasingly use digital technologies and online platforms to obtain information about symptoms, diseases, medications, nutrition, mental health, sexual and reproductive health, and other health-related concerns. However, the quality, accuracy, accessibility, and reliability of online health information may vary considerably, and students may encounter misinformation or experience difficulties identifying trustworthy sources. Artificial intelligence (AI)-based health chatbots provide an emerging digital health communication tool that can offer conversational responses to health-related questions and provide users with information at any time. Their accessibility, convenience, privacy, and interactive nature may encourage students to seek health information more frequently. However, concerns regarding accuracy, misinformation, privacy, inappropriate self-diagnosis, and failure to recognize situations requiring professional medical attention may affect their usefulness. Against this background, this study investigates the effect of AI-based health chatbots on health information-seeking among university students in Nigeria. The study will be anchored on the Technology Acceptance Model, Health Belief Model, and Health Literacy Framework. The Technology Acceptance Model explains how perceived usefulness, perceived ease of use, and users' attitudes toward AI-based health chatbots may influence their willingness to use the technology for health information-seeking. The Health Belief Model explains how perceived susceptibility, perceived severity, perceived benefits, perceived barriers, and cues to action may influence students' motivation to seek health information. The Health Literacy Framework emphasizes the ability to access, understand, evaluate, and appropriately apply health information obtained from digital sources. Collectively, these theoretical perspectives provide a suitable framework for explaining how AI-based health chatbots may influence health information-seeking among university students in Nigeria. The study will adopt a quantitative quasi-experimental or analytical cross-sectional research design. The study population will comprise undergraduate and postgraduate students aged 18 years and above enrolled in selected public and private universities across Nigeria. A multistage sampling technique will be used to select geopolitical zones, states, universities, faculties or departments, and eligible students. AI-based health chatbot use will be assessed using indicators such as frequency of chatbot use, duration of use, types of health questions asked, perceived usefulness, ease of use, accessibility, response speed, privacy perceptions, trust in chatbot responses, frequency of interaction, and use of chatbot information alongside other health-information sources. Health information-seeking will be assessed using indicators such as frequency of seeking health information, range of health-information sources consulted, seeking information about symptoms and diseases, preventive health information-seeking, medication-related information-seeking, mental health information-seeking, sexual and reproductive health information-seeking, verification of health information, consultation with healthcare professionals, and use of health information to guide healthcare decisions. Data will be collected using structured questionnaires, digital health information-seeking assessment tools, chatbot-use records where available and voluntarily provided, and relevant university health-service records. Descriptive statistics will be used to summarize students' characteristics, digital health-information use, chatbot exposure, and health information-seeking patterns. Inferential statistical techniques, including chi-square tests, t-tests, correlation analysis, and logistic or multiple regression analysis where appropriate, will be used to determine the effect of AI-based health chatbots on health information-seeking. Where a quasi-experimental design is adopted, health information-seeking scores before and after exposure to an AI-based health chatbot may be compared with those of a comparison group to determine changes associated with the intervention. Diagnostic tests will also be conducted to assess the reliability, validity, and robustness of the findings. The study is expected to find that AI-based health chatbots have a significant positive effect on health information-seeking among university students in Nigeria. Students exposed to AI-based health chatbots are expected to demonstrate greater frequency and engagement in seeking health information compared with students without comparable exposure. The conversational nature of chatbots may allow students to ask follow-up questions, clarify unfamiliar health concepts, and obtain information privately, which may be particularly useful for sensitive topics such as sexual health, mental health, substance use, and reproductive health. The accessibility of chatbots may also reduce some barriers associated with limited healthcare availability and inconvenient clinic schedules. However, inaccurate or incomplete responses, overreliance on AI-generated information, privacy concerns, misinformation, inadequate health literacy, and failure to seek professional care when necessary may limit the benefits of chatbot-based health information. The study therefore expects appropriately designed, evidence-informed, privacy-conscious, and professionally supported AI-based health chatbots to contribute significantly to improved health information-seeking among university students in Nigeria. The study is expected to contribute to the literature on artificial intelligence in healthcare, digital health, health information-seeking, health literacy, health communication, university student health, health technology adoption, and public health in Nigeria. The findings will provide useful information to the Federal Ministry of Health and Social Welfare, Federal Ministry of Education, National Universities Commission, university managements, university health centres, healthcare professionals, digital health developers, technology providers, development partners, and policymakers regarding the responsible use of AI-based technologies for health communication. The study will also provide evidence-based recommendations for developing reliable AI-based health information tools, strengthening privacy and data-protection measures, incorporating professional health oversight, educating students about the limitations of AI-generated health information, promoting verification of health information, and establishing clear pathways for referral to qualified healthcare professionals when students require clinical assessment or treatment.

Keywords: AI-based health chatbots, artificial intelligence, health information-seeking, university students, digital health, health literacy, health communication, health technology, healthcare information, Nigeria, public health.