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ORIGINAL ARTICLE
Year : 2019  |  Volume : 32  |  Issue : 1  |  Page : 301-304

Screening intelligence of children


1 Pediatrics Department, Faculty of Medicine, Menoufia University, Shebeen El-Kom, Egypt
2 Pediatrics Department, Shebin El-kom Teaching Hospital, Shebeen El-Kom, Egypt

Date of Submission01-May-2017
Date of Acceptance31-Jul-2017
Date of Web Publication17-Apr-2019

Correspondence Address:
Shereen R. A. El-Shiemy
Tanta, Gharbia
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/mmj.mmj_309_17

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  Abstract 


Objective
Screening intelligence of primary school children using the draw-a-person test (DAPT) in Tanta District El-Gharbia Governorate.
Background
Drawing is a form of expression and children draw what they know. The drawing tests were used since its conception for evaluating the personality, sensory deviates and intellectual development.
Patients and methods
One thousand apparently healthy primary school children from 6 to 12 years old in Tanta District, El-Gharbia Governorate are included in our study. All students were subjected to DAPT; their parents were asked to fulfil a questionnaire that included full name, date of birth, parent's job, degree of parents education and family income.
Results
Of the 1000 children, 501 were girls and 499 were boys, the mean age was 9.02 ± 1.41 (6–12) years. Significant correlations were found between intelligence quotient levels, socioeconomic standard, school achievement, BMI, residence and sex.
Conclusion
The DAPT is a useful developmental screening tool which can be used by pediatricians as a measure of intellectual maturity.

Keywords: draw-a-person test, intelligence, screening


How to cite this article:
El-Shafie AM, El-Lahouny DM, Omar ZA, El-Shiemy SR. Screening intelligence of children. Menoufia Med J 2019;32:301-4

How to cite this URL:
El-Shafie AM, El-Lahouny DM, Omar ZA, El-Shiemy SR. Screening intelligence of children. Menoufia Med J [serial online] 2019 [cited 2019 Jul 17];32:301-4. Available from: http://www.mmj.eg.net/text.asp?2019/32/1/301/256099




  Introduction Top


The drawing tests were used since its conception for a variety of evaluation including those of personality, sensory deviates, intellectual development and learning differences [1].

Draw-a-person test (DAPT) devised by Goodenough (1926) is one of the earliest drawing tests used to assess children's creativity, mental age and intellectual maturity [2].

Children usually start to notice relationships between the objects that they draw between 2 and 4 years of age. The human figure is usually drawn in the form of a head by adding parts like eyes, nose and mouth to a large circle [3].

The aim of this study was screening intelligence of primary school children and assessing factors affecting it using 'DAPT' in Tanta District, El-Gharbia Governorate.


  Patients and Methods Top


The present study included 1000 apparently healthy primary school children from 6 to 12 years old in Tanta District, El-Gharbia Governorate. The urban sample comprised 484 children at El-Eslah Primary School and the rural sample consisted of 516 children at Mahalet Roh Primary School from October 2015 to April 2016, where all students were subjected to history taking to exclude children with chronic diseases, anthropometric measurements including weight and height and DAPT.

Parents were given a questionnaire through the student that contained telephone number, full name, date of birth, any serious medical problems in the past, and also included degree of parents education, husbands occupation and family income.

Grading of school achievement was obtained: grade A (90–100, excellent), B (80–89, above average), C (70–79, average), D (60–69) and F (0–59).

Directions were given and every child was asked to draw a picture of a person, the very best picture that he/she can.

Raw scores were obtained and then converted to intelligence quotient (IQ) by modified Harris scoring system [4].

Statistical analysis

The data were collected, tabulated and statistically analyzed using SPSS 20 for Windows (SPSS Inc., Chicago, Illinois, USA).

Two types of statistics were done: descriptive and analytical (Student's t-test, one-way analysis of variance (F-test), post-hoc test, Pearson's and Spearman's correlation analysis, P value is considered significant if ≤ 0.05).


  Results Top


This study was carried out on 1000 primary school children between 6 and 12 years (mean age of 9.02 ± 1.41). They were 501 (50.1) girls and 499 (49.9%) boys [Table 1].
Table 1: Distribution of students regarding their characteristics

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As regards IQ results, children with average intelligence represented 95.90%, those with superior intelligence represented 3% while those with borderline intellectual function represented 1.10% [Table 2].
Table 2: Distribution of students regarding intelligence quotient level

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The IQ levels were higher among boys (99.74 ± 10.74) than girls (96.511 ± 0.20) with significant difference (P < 0.001) [Table 3].
Table 3: Distribution of sex regarding intelligence quotient level

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As regards residence, significantly higher IQ levels were among those with rural residence (100.98 ± 11.08) than with urban residence (95.08 ± 8.80) [Table 4].
Table 4: Distribution of residence regarding intelligence quotient level

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The IQ levels and socioeconomic standard were positively correlated to each other where those with higher socioeconomic standards had higher IQ scores (102.33 ± 10.78) in comparison with average (96.93 ± 9.77) and low socioeconomic standards (88.81 ± 9.57) [Table 5].
Table 5: Distribution of socioeconomic standard regarding intelligence quotient level

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The IQ level was significantly higher among students with grade 'A' school achievement (108.91 ± 11.57) than 'B' (99.04 ± 9.75), 'C' (92.18 ± 8.78) and 'D' (82.0 ± 4.19) school achievements (P < 0.001) [Table 6].
Table 6: Distribution of school achievement regarding intelligence quotient level

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The IQ levels were higher among students with overweight BMI (99.46 ± 11.87) than normal (98.45 ± 10.21), obese (97.74 ± 12.18) and underweight (96.68 ± 10.55) (P = 0.143) students [Table 7].
Table 7: Distribution of BMI categories regarding intelligence quotient level

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  Discussion Top


The IQ levels measured in childhood are predictive of real-life success, including educational achievement, occupational prestige, income and health [5].

Goodenough DAPT was traditionally used as a simple tool to measure mental development. There have been studies which showed good correlation between mental age assessed by DAPT with tests of IQ such as Stanford-Binet test with correlations ranging from 0.45 to 0.72 [6].

The study consisted of 1000 children between 6 and 12 years (female: male = 50.1: 49.9).

[Table 2] shows that the IQ levels ranged from 74 to 141 with a mean of 98.12 ± 10.46, which is considered higher than the Egyptian IQ measured by previous studies that were performed to assess international IQ of many countries world wide and this agrees with Liu and Lynn [7], where the mean full scale IQ of 12-years-old Chinese children using the Wechsler Intelligence Scale for Children – Revised (WISC-R) was 106.62 in men and 103.11 in women and disagrees with Imuta et al., [8], where the Egyptian IQ measured by Coloured Progressive Matrices was 84.2%

[Table 3] shows significant difference in IQ levels between men and women with P value less than 0.001. This comes up with a study by Liu and Lynn [7] who found that Chinese boys obtained a significantly higher Full Scale IQ than girls in WISC-R test.

This disagrees with a study in New Zealand by Imuta et al. [8], where t-test revealed that girls (M = 110.42, SD = 15.42) scored significantly higher on the DAPT: IQ than the boys (M = 102.70, SD = 12.86) [t (98)=22.72, P = 0.008].

[Table 4] shows a significant difference in IQ levels regarding residence where rural school students had higher levels than those living in urban; this is supported by Breslau et al. [9] who found that the IQ levels decline between 6 and 12 years in urban children but not in suburban using WISC-R.

This disagrees with Colom et al. [10] who found that Brazilian urban children were more intelligent than rural children along the intelligence distribution curve.

[Table 5] shows that IQ levels and socioeconomic standard were positively correlated where children with higher socioeconomic standards had higher IQ levels; this agrees with Von Stumm and Plomin [11] where children from higher socioeconomic standard backgrounds were more intelligent than their peers from low ones.

And disagrees with Brooks-Gun and Duncan [12] who postulated that though poverty is a significant risk factor for poorer cognitive achievement, not all poor children fail academically and that many of them are good academic achievers.

[Table 6] shows that children with grade 'A' school achievement had higher IQ levels in comparison with grade 'B', 'C' and 'D'.

Ohuche and Ohuche [13] concluded that the DAPT is a predictor of academic achievement in Sierra Leonian children in the first 3 years of primary school. They further suggested that in the higher grades of school (after 8 years) the DAPT does not differentiate among pupils and therefore does not predict their school achievement.

Ssali [14] found that pupils who had been rated as being in the 'poor' category by their teachers had the lowest mean scores on all the three scales whereas those that had been rated as being 'excellent' had the highest.

[Table 7] shows that the IQ levels were significantly higher among students with overweight BMI (99.46 ± 11.87) than normal (98.45 ± 10.21), obese (97.74 ± 12.18) and underweight (96.68 ± 10.55) children. This agrees with Ranabhat et al. [15] where they found that thin students had significant lower IQ levels than their peers with average and high BMI (P = 0.003).

Galvan et al. [16] have found an interaction between socioeconomic standard and obesity that affects the IQ of preschool children, in contrast to results from previous studies where obese children had lower performance on intelligence tests independent of their socioeconomic standard.

Hackman and Farah [17] found socioeconomic standard to be an important predictor of neurocognitive performance, particularly of executive function and language.

Cawley and Spiess [18] found a negative association between obesity and cognitive abilities of 6-year-old girls from Germany.


  Conclusion Top


From our results, the IQ levels of the students ranged from 74 to 141 with a mean of 98.12 ± 10.46, where 95.90% of them were of average intelligence. The IQ levels obtained by DAPT correlated significantly with the socioeconomic standard, school achievement, residence and BMI. IQ levels of men are significantly higher than women.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

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Liu J, Lynn R. Chinese sex differences in intelligence: some new evidence. Pers Individ Dif 2015; 75:90–93.  Back to cited text no. 7
    
8.
Imuta K, Scarf D, Pharo H, Hayne H. Drawing a close to the use of human figure drawings as a projective measure of intelligence 2013; 8:e58991.  Back to cited text no. 8
    
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Breslau N, Chilcoat HD, Susser ES, Matte T, Liang KY, Peterson EL. Stability and change in children's intelligence quotient scores: a comparison of two socioeconomically disparate communities. Am J Epidemiol Vol 2001;154:711–717.  Back to cited text no. 9
    
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Colom R, Mendoza C, Abad F. Generational changes on the draw-a-man test: a comparison of brazilian urban and rural children tested in 1930, 2002 and 2004. J Biosoc Sci 2006; 39:79–89.  Back to cited text no. 10
    
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Von Stumm S, Plomin R. Socioeconomic status and the growth of intelligence from infancy through adolescence. Intelligence 2015; 48:30–36.  Back to cited text no. 11
    
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Brooks-Gunn J, Duncan G. The effects of poverty on children. Future Child 1997; 7:55–71.  Back to cited text no. 12
    
13.
Ohuche NM, Ohuche RO. The draw-a-man test as a predictor of academic achievement. West Afr J Educ Vocational Meas 1973; 1:20–27.  Back to cited text no. 13
    
14.
Ssali R. Measuring educational potential with the draw a person test. Kenyatta University Institutional repository. 2012. Available from: http://ir library.ku.ac.ke/handle/123456789/4831. [Last accessed on 2017 Apr].  Back to cited text no. 14
    
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Ranabhat C, Kim CB, Park MB, Kim CS, Freidoony L. Determinants of body mass index and intelligence quotient of elementary school children in mountain area of Nepal: an explorative study. Children (Basel) 2016; 3:3.  Back to cited text no. 15
    
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Galvan M, Uauy R, Lopez-Rodriquez G, Kain J. Association between childhood obesity, cognitive development, physical fitness and social-emotional wellbeing in a transitional economy. Ann Hum Biol 2014;41:99–104.  Back to cited text no. 16
    
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Hackman D, Farah MJ. Socioeconomic status and the developing brain. Trends cogn Sci 2009; 13:65–73.  Back to cited text no. 17
    
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    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]



 

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