ARTIFICIAL INTELLIGENCE IN MENTAL HEALTH EDUCATION IN JUNIOR SECONDARY SCHOOLS, NYAMIRA COUNTY

Abstract

The purpose of the study is to improve the accessibility and quality of mental health services via high technologies and new cognitive models with the aim of improving the screening and support of students' psychological needs. Both quantitative and qualitative approaches were used.  The study population was students in junior secondary schools in Kenya.  Stratified sampling was used by randomly picking a sample of about 500 students.  Data was collected using structured questionnaires, interviews and focus group discussions. Quantitative analysis involved using statistical packages such as SPSS or R to perform descriptive and inferential statistics.  Thematic analysed qualitative data. The results indicate an increase in the rates of mental health screening and detection among students following the implementation of AI-facilitated methods, with screening participation rising from 26% to 77% and the rates of detecting depression, anxiety, and behavior problems being high. Depression detection increased from 29% to 56%, anxiety and stress detection levels rose from 37% to 69% and 33% to 71%, respectively, illustrating the effectiveness of technology in addressing students' mental health needs. The study recommends that schools be compelled to actively integrate AI-based mental health screening tools to enhance early identification and intervention of students with psychological problems.

Keywords: Psychological needs, behavioral, mental health.

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