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Research Article Open access CC BY 4.0

Digital Platform–Based Instructions and Adolescents’ Knowledge and Perception of Sexual-Risk Behaviour Consequences in Public Secondary Schools in Owerri Municipal, Nigeria

Adanna Nneoma Chukwuocha, Anyalewechi Eunice Nwoke, Chidozie Joakin Nwaokoro, Ugonma Winnie Dozie, Chikadibia Kizito Odinaka, Ijeoma Fredrica Obodoechi, Chidinma Nkem Igwe, Okoro Chisomuaga Chidinma, Oluchi Gloria Onyechere, Ngozi Victoria Akam, Joy Victoria Osuoji

Advances in Research · pp. 298–308 · Published 5 Jun 2026

10.9734/air/2026/v27i31652

Abstract

Background: This study is an extract from a larger body of work. Adolescents are particularly vulnerable to engaging in risky sexual behaviours due to developmental changes, peer influence, and limited access to accurate sexual health information. Digital platforms have emerged as innovative channels for delivering sexual health education, but evidence on their effectiveness among Nigerian adolescents remains limited. Aim: This study examined the influence of digital platform–based education on adolescents’ knowledge and perception of the consequences of sexual-risk behaviours in public secondary schools in Owerri Municipal, Nigeria. Methods: A pretest–post-test quasi-experimental design was employed among 255 adolescents aged 14–19 years selected from government-owned secondary schools in Owerri Municipal out of a population of 5,146 students. Participants were assigned to three intervention groups: Traditional Lecture Method (TLM), WhatsApp Method (WAM), and Artificial Intelligence Method (AIM: Meta AI/ChatGPT), with 85 students in each group. Data were collected using a structured and pretested questionnaire assessing knowledge and perception of consequences of sexual-risk behaviours. Data were analysed using descriptive statistics and inferential statistics in SPSS version 23, including paired t-tests, ANOVA, and Bonferroni post-hoc tests, with significance set at p < 0.05. Results: Participants had a mean age of 16.8 ± 1.65 years, and most were Christians (96.9%) and Igbo (95.7%). Overall, 87.1% had previously heard about sexual risk behaviours. Baseline knowledge was high for common consequences such as HIV/AIDS and teenage pregnancy (95.3–100%), but relatively low for reproductive organ damage (42.4–65.9%) and HPV/cervical cancer risks (29.4–60.0%). After the intervention, knowledge improved significantly across all groups: TLM (mean difference = 0.304 ± 0.356, t = 7.882, p < 0.0001), WAM (0.257 ± 0.307, t = 7.712, p < 0.0001), and AIM (0.302 ± 0.281, t = 9.904, p < 0.0001). Post-intervention knowledge reached 100% for several items, including awareness of sexually transmitted infections and teenage pregnancy. Bonferroni comparison showed significant differences between TLM and WAM (MD = 0.0764, p < 0.001) and WAM and AIM (MD = 0.0764, p < 0.001), but no difference between TLM and AIM (p = 1.000). For perception, baseline scores ranged from 3.765 to 4.612 (out of 5). While no significant differences existed at pretest (F = 0.416, p = 0.667), significant differences were observed at posttest (F = 5.339, p = 0.018). Post-hoc analysis indicated that WAM (MD = 0.217, p = 0.041) and AIM (MD = 0.222, p = 0.036) significantly outperformed TLM in improving perceptions of sexual-risk consequences. Conclusion: Digital platform–based sexual health education significantly improved adolescents’ knowledge and perceptions of the consequences of sexual-risk behaviours. Technology-driven approaches, particularly WhatsApp and AI-supported learning, demonstrated greater effectiveness than traditional lecture methods in enhancing perception and understanding of sexual health risks.

Adolescents artificial intelligence education sexual behaviours

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