尼日利亚东南部埃努古地区小学生的智商及其决定因素采用人画测验和乌鸦渐进式矩阵

K. Iloh, O. Chidiebere, O. Iloh, O. Igbokwe, E. Nwaneli, Uzoamaka C. Akubuilo
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摘要

儿童的智商在很大程度上取决于遗传因素。然而,孩子成长的社会环境对孩子的整体认知能力也起着重要的作用。患者和方法本横断面描述性研究采用多阶段抽样方法,在埃努古州埃努古-东地方政府地区招募了1122名6至12岁的学龄儿童,为期3个月。采用瑞文标准递进矩阵和画人测验(DAPT)来评估研究参与者的智商。本研究旨在评估两种智商评估系统与小学生智商的社会人口学决定因素的相关性。结果采用Raven智商评价体系,智力超常者73人(7.6%),智力超常者150人(15.7%),智力超常者293人(30.6%),智力超常者340人(35.5%),智力超常者101人(10.6%);采用DAPT智商评价体系,智力超常者258人(27%),智力超常者593人(62%);而有82人(8.6%)和24人(2.4%)被认为有智力缺陷。两个评分系统显示出轻微的一致性,一致性间信度系数()为0.093[95%置信区间(CI) 0.001-0.003]。在Raven评估系统下,学生的社会经济阶层[比值比(OR) 1.82 (95% CI 1.21-2.73), P=0.004]、母亲受教育程度[OR 0.38 (95% CI 0.23-0.63) P=0.001]和学校类型[OR 2.23 (95% CI 1.45-3.43) P=0.001]显著预测了研究参与者的次优智商。结论本研究发现了Raven和DAPT智商评估体系之间较差的解释一致性,以及在Raven智商评估体系下与次优智商相关的因素。
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Intelligence quotient and its determinants using Draw-A-Person Test and Ravens progressive matrices among primary school children in Enugu, Southeast Nigeria
Background The intelligence quotient of a child is determined to a large extent by genetic factors. However, the social context in which a child is brought up also plays a significant role in the overall cognitive capabilities of the child. Patients and methods This cross-sectional descriptive study enrolled 1122 school-aged children between the ages 6 and 12 years in the Enugu-East local government area of Enugu State over a 3-month period using the multistage sampling method. Raven’s Standardized Progressive Matrices and the Draw-A-Person Test (DAPT) were used to assess the intelligence quotient of the study participants. It aimed to assess the relatability of the two intelligent quotient (IQ) assessment system and sociodemographic determinants of IQ in school pupils. Results With the Raven system of IQ assessment, 73 pupils (7.6%) were noted to be above average intelligence, 150 (15.7%) had above average intelligence, 293 (30.6%) were considered to have average intelligence, while 340 (35.5%) and 101 (10.6%) were below average and intellectually defective, while the DAPT system categorized 258 of the pupils surveyed (27%) as having above average intelligence, 593 (62%) were considered to have average intelligence, while 82 (8.6%) and 24 (2.4%) were considered mentally deficient, respectively. Both scoring systems showed slight agreement with an interagreement reliability coefficient (қ) of 0.093 [95% confidence interval (CI) 0.001–0.003]. Pupils’ socioeconomic class [odds ratio (OR) 1.82 (95% CI 1.21–2.73), P=0.004], maternal educational [OR 0.38 (95% CI 0.23–0.63) P=0.001], and school type [OR 2.23 (95% CI 1.45–3.43) P=0.001] significantly predicted suboptimal IQ in study participants under the Raven assessment system. Conclusion Our study identified poor interrater agreement between the Raven and DAPT IQ assessment systems and factors that correlate with suboptimal IQ under the Raven system of IQ assessment.
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