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非洲背景下评估大学生心理健康的计算机自适应方法:使用Concerto的开源设置

Computerised adaptive method for assessing university undergraduates' mental well-being within an African context: An open-source set-up with Concerto.

作者信息

Oladele Jumoke I

机构信息

Department of Social Sciences education, Faculty of education, University of Ilorin, Nigeria.

University of Pretoria, South Africa.

出版信息

MethodsX. 2025 Jan 2;14:103140. doi: 10.1016/j.mex.2024.103140. eCollection 2025 Jun.

Abstract

This research presents the development of a computerised adaptive testing system for assessing university undergraduates' mental health in an African setting. An item pool of 375 items that reflect eight sub-constructs of mental well-being (coping with normal stress of life, realising potential, studying effectively, social interaction, school-life balance, emotional stability, healthy living, and belief system) was developed. FastTest was used to pilot-test the item using a sample of 406 undergraduate students from South Africa and Nigeria. Each candidate was given 100 items utilising the linear on-the-fly test administration. Four hundred and seven responses were received which was subjected to psychometric analysis using the Samejima's Graded IRT model to calibrate the items. One hundred and seventy-five items resulted which was used to design the mental wellbeing adaptive scale for use within the university community at no cost to the student and institution.1.Using concerto, the detailed inflow with an html embedded function is clearly explained.2.The scale dynamically adjusts the difficulty/relevance of questions based on respondents' previous answers, thereby enhancing precision and reducing users test burden.3.An adaptable, scalable, and culturally appropriate non-illness method for assessing students' mental wellbeing being an improvement on the linear form is presented.

摘要

本研究介绍了一种用于在非洲环境中评估大学生心理健康的计算机自适应测试系统的开发情况。开发了一个包含375个项目的题库,这些项目反映了心理健康的八个子结构(应对正常生活压力、发挥潜力、有效学习、社交互动、学校生活平衡、情绪稳定、健康生活和信仰体系)。使用FastTest对来自南非和尼日利亚的406名本科生样本进行了项目预测试。每位考生通过线性即时测试管理方式接受100个项目。共收到407份回答,并使用Samejima的分级IRT模型进行心理测量分析以校准项目。最终得到175个项目,用于设计心理健康自适应量表,供大学社区免费供学生和机构使用。1.使用协奏曲,带有html嵌入式功能的详细流入情况得到了清晰解释。2.该量表根据受访者之前的回答动态调整问题的难度/相关性,从而提高精度并减轻用户的测试负担。3.提出了一种适用于评估学生心理健康的、可适应、可扩展且符合文化背景的非疾病方法,这是对线性形式的一种改进。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8696/12255357/73302925ce69/ga1.jpg

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