Digital literacy and online child abuse among primary school children in Langata Sub-county, Nairobi City County in Kenya

Abstract

Kenya introduced Digischool to public primary schools to prepare children for today’s digital world attracting a cyber-threat landscape. Utilising a descriptive cross-sectional design within a concurrent mixed approach, the study examined the relationship between digital literacy intervention and online child abuse among primary school children in Langata sub-county. Targeted, were children between 9 and 17 years from private and public primary schools, teachers, parents and policy makers and child protection officers. Godden’s formula informed purposive and random sampling of 384 respondents, plus a 10% (423) respondents for Key Informant interviews and focused discussions. Quantitative and qualitative data was analysed using both descriptive and inferential statistics and content analysis with the help of SPSS version 22 and Nvivo version 12 respectively. The study revealed stakeholders intervened in online child abuse at various levels using a number of strategies. The study revealed a significant relationship between the type of school and exposure to online. Since the p-value (0.000) was less than alpha (0.05) and we conclude there was a significant relationship between the type of school and exposure to online child abuse. There is need for a systems thinking and concerted multi-sectorial approach to improvement of digital literacy hence protecting children online.

Design and evaluation of child abuse web-based application for parent education & strengthen

“…Today, information technology is an important factor that provides countless opportunities and benefits such as saving money, time and the possibility of accessing information [ 23 ]. The use of information technology in the field of disease control and prevention has been able to help people to overcome many challenges and limitations such as lack of access to information, dispersion of information, face-to-face visits, distance from medical centers and cost of care services [ 24 ].…”