Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2019  |  Volume : 32  |  Issue : 3  |  Page : 1037-1042

Screening intelligence of primary school children using 'draw-a-person test' in Mansoura district, Al Dakahlia Governorate


Department of Pediatrics, Faculty of Medicine, Menoufia University, Menoufia, Egypt

Date of Submission14-Nov-2017
Date of Acceptance15-Jan-2018
Date of Web Publication17-Oct-2019

Correspondence Address:
Mohamed A. M. Dagher
Mohamed Hassan Street, Moubarak City, Manosura
Egypt
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/mmj.mmj_790_17

Rights and Permissions
  Abstract 

Objective
The aim was to screen the intelligence level among primary school children using 'draw-a-person (DAP) test' in Dakahlia Governorate.
Background
For more than 100 years, clinicians and psychologists have studied children's drawing as a measure of one's cognitive ability. In 1926, Florence Goodenough developed a drawing test called the DAP test. The DAP test consists of having a child draw -a whole person on a piece of paper that is scored via a list of items that are commonly present in the drawings. It showed that a child's drawing is a reflection of one's intellectual skills and development.
Participants and methods
This cross-sectional study was carried out on 1012 of apparently healthy primary school children aged from 6 to 12 years in Mansoura district, Dakahlia Governorat from October 2015 to February 2016. Mansoura district includes 157 primary schools, of which three schools are in the central area including 1006 students, 75 schools in Mansoura east administration including 23 439 students, and 80 schools in Mansoua west administration including 27 630 students. The total number of students chosen was 1012 distributed to 32 schools, out of which 20 schools were in rural areas and 10 schools were in urban areas. All of them are governmental primary schools. No language schools and none of them received specific qualified drawing lessons. Children with hearing loss or mental disability were not included as they have separate nonincluded schools. Some students with physical disability not affecting the test were included, for example polio. All students in the study were subjected to an adequate assessment of history, full clinical examination, socioeconomic level, school achievement, and also subjected to DAP test.
Results
The study showed that children with superior intelligence represented 10.9%, those with average intelligence 69.2%, and with borderline intellectual function 17.3%, and children with mild mental retardation 2.7%. Also positive correlations were found between intelligence quotient (IQ) levels and socioeconomic standards, school achievement, residence, and BMI. There was no correlation between IQ levels and children's sex.
Conclusion
IQ levels obtained by DAP test were positively correlated with socioeconomic standards, BMI, residence, and school achievement. No correlation was found between IQ levels and sex.

Keywords: body mass index, draw-a-person test, intelligence, intelligence quotient, school achievement, socioeconomic standards


How to cite this article:
El-Shafie AM, El Lahony DM, Omar ZA, Dagher MA. Screening intelligence of primary school children using 'draw-a-person test' in Mansoura district, Al Dakahlia Governorate. Menoufia Med J 2019;32:1037-42

How to cite this URL:
El-Shafie AM, El Lahony DM, Omar ZA, Dagher MA. Screening intelligence of primary school children using 'draw-a-person test' in Mansoura district, Al Dakahlia Governorate. Menoufia Med J [serial online] 2019 [cited 2019 Nov 12];32:1037-42. Available from: http://www.mmj.eg.net/text.asp?2019/32/3/1037/268847




  Introduction Top


'Draw-a-person (DAP) test' is a projective test that allows an examinee to respond to questions through drawings. Projective tests can be applied in various settings from schools, corporations, and private practices. Assessing different psychological aspects include personality, family background, intelligence, physical and emotional abuse, depression, etc. [1]. Goodenough first became interested in figure drawing when she wanted to find a way to supplement the Stanford–Binet intelligence test with a nonverbal measure. The test was developed to assess the maturity in young people. Goodenough concluded that the amount of details involved in a child's drawing could be used as an effective tool. This led to the development of the first official assessment using figure drawing which was the DAP test. Over years, the test has been revised many times with added measures for assessing intelligence [2]. Harris later revised the test, including drawings of a woman and of themselves. Now considered the Goodenough–Harris test it has guidelines for assessing children from ages 6 to 17 years. Harris assumes that changes in a child's drawings of a man or a woman represent the development of cognitive complexity or intellectual maturity expressed by increasingly complex representations of the human figure. He regards the child's concept of a human figure as an index or sample of their concept generally. As Cox [3] in a comprehensive review notes, in Western cultures 'child's progress from a period of scribbling to the production of tadpole forms and then on to conventional forms, at first composed of segmented body parts, and then later of more contoured and integrated sections'. The aim of this work was to screen the intelligence level among primary school children using the 'DAP test' in the Dakahlia Governorate.


  Participants and Methods Top


After approval of the Local Institutional Ethics Committee of Mansoura educational affairs, and obtaining written consents from all student parents to participate in our study, the study was carried out on 1012 of apparently healthy primary school children aged from 6 to 12 years in Mansoura district, Dakahlia Governorate, At Shoha (rural) and Touril (urban) primary schools. This district consisted of both rural and urban cultures. From Octobetr 2015 to February 2016, the parents were given a questionnaire via the students which contained telephone number, full name, date of birth, any serious medical problems in the past, and also included the degree of education of parents, husband's occupation, family size, and family income to assess the socioeconomic level. All through the study, the children were subjected to complete clinical examination to exclude any chronic clinical problems as mentioned before in the study participants. Anthropometric measures (weight and height) were also recorded. All measurements were taken using the same type of apparatus and followed the same procedures. BMI was calculated using the equation: BMI = weight in kilograms divided by height in meters squared. School achievement was obtained by the marks of the previous year from participant's school records. Children of junior one class marks were obtained from the midterm, and grading of school achievement were obtained using the most common grading scale grade A (90–100, excellent), grade B (80–89, above average), grade C (70–79, average), grade D (60–69, usually the minimum passing grade), and grade F (0–59).

Draw-a-person test instruction and the test setting

The child must be seated at an individual table with enough space to draw. Before asking the student to DAP test, we ensured that the examiner makes sure that the child understands the instructions and feels comfortable with the test situation. Sufficient lighting is assured. Noise, visitors, and other distractions were avoided. There were no objects other than a pencil with soft lead and a sheet of white paper on the table. The administrator asks the children to DAP with no time limit. The administrator never makes any comment on the drawing, or asks the child to correct certain details, as this is not an art lesson but an attempt to ascertain the child's concept of the human figure. Any child refused to draw was encouraged and if not, he was given more time for testing. In testing, the teacher should follow these instructions which are also reproduced in the Annex C so that they can be photocopied for easier use. DO: Give a piece of white unlined paper and a pencil. The child should neither use a ruler or an eraser. The sheet of paper should have the size of an ordinary exercise book. SAY: 'I'd like you to draw some pictures for me. First, I'd like you to draw a picture of a man. Make the very best picture you can. Take your time and work very carefully and I'll tell you when to stop. Remember: be sure to draw the whole man. Please begin. DO: After 5 min, ask the child to finish. Observe if the child has any difficulties understanding (hearing or seeing) while drawing. After completion use the DAP scoring system to rate the drawing. By adding the scores of the 14 criteria, you get the total raw score (maximum = 64). This individual score can then be compared with the child's age group in order to find out at what percentile he or she is performing. Raw scores obtained from the participant's drawings are then converted to intelligence quotient (IQ) by modified Harris scoring guide [4] which includes: gross details (head present, legs present, arms present, trunk present, length of trunk greater than breadth, shoulders are indicated (abrupt broadening of the trunk below the neck). Attachments: both arms and legs attached to the trunk, arms and legs attached to the trunk at the correct points, neck present, outline of the neck, continuous with that of head, trunk, or both. Head details: eyes present (one or two), nose present, mouth present, nose and mouth in two dimensions, two lips shown, nostrils shown, hair shown, hair on more than the circumference of head and nontransparent – better than a scribble. Clothing: clothing presents (any clear representation of clothing), two articles of clothing nontransparent (e.g., hat, trousers). The entire drawing free from transparencies – sleeves and trousers must be shown. Four articles of clothing definitely indicated. 'should include four – hat, shoes, coat, shirt, necktie, belt, trousers'. Costume complete with incongruities 'business suit, soldier's costume and hat, sleeves, trousers and shoes must be shown'. Hand details (fingers present, any indication), correct number of fingers shown, fingers in two dimensions – length greater than breadth, the angle subtended not greater than 180°, opposition of thumb clearly defined, hand shown distinct from fingers and arm joints (arm joint shown – elbow, shoulder, or both), leg joint shown – knee, hip, or both, proportion (head not more than half or less than one-tenth of the trunk), arms equal to the trunk, but not reaching the knee, legs not less than the trunk not more than twice the trunk size, feet in two dimensions – not more than one-third or less than one-tenth of the leg, both arms and legs in two dimensions. Motor coordination (lines firm without marked tendency to cross, gap, or overlap). All lines firm with correct joining, outline of head without obvious irregularities, develop beyond the first crude circle, conscious control apparent, trunk outline. Score same as #3, arms and legs without irregularities, two dimensions and no tendency to narrow at the point of junction with trunk, features symmetrical (more likely to credit in profile drawings). Fine hand details (ears present: two in full face, one in profile), ears present in correct position and proportion. Eye details – brow or lashes shown, eye detail – pupil shown, eye detail – proportion. Length greater than width, eye detail – glance – only plus in profile, chin and forehead shown. Profile (projection of chin shown – usually + in profile), heel clearly shown. Body profile – head, trunk, and feet without error. The figure shown in true profile without error or transparency. For example, if a boy aged 8 years, and his raw drawing score was 29, the IQ was 103 using data from [Table 1].
Table 1: Draw-a-person test raw score conversion to intelligence score part 2

Click here to view


Statistical analysis

The results were statistically analyzed by SPSS version 20 (SPSS Inc., Chicago, Illinois, USA). Student's t-test was used to indicate collectively the presence of any significant difference between two mean for a normally distributed quantitative variable. One-way analysis of variance (F-test) was used to indicate collectively the presence of any significant difference between several mean for a normally distributed quantitative variable. Post-hoc test is used after one-way analysis of variance to show any significant difference between the individual groups. A P value of less than 0.05 was considered significant.


  Results Top


The results showed that the age of the studied group ranged from 6 to 12 years, the mean BMI was 15.72 ± 2.69, distributed as underweight (18.2%), normal (76.7%), overweight (3%), and obese (1.8%). Regarding residence: rural (51.6%), urban (48.4%). Regarding socioeconomic status (SES): low (13.7%), average (49.4%), high (36.9%). School achievement was accepted in 6.1%, good in 34.09%, very good in 52.8%, and excellent in 6.9% [Table 2]. Children with superior intelligence represented 10.9%, those with average intelligence were 69.2%, and with borderline intellectual function were 17.3%, and children with mild mental retardation were 2.7% [Table 3]. Children, who lived in an urban residence had higher IQ levels (103.11) in comparison with those who lived in rural areas (93.03). Also a strong positive correlation was found between socioeconomic standards and IQ levels; those with higher SES has higher IQ scores (105.18) in comparison with those with average (95.92) and low SES (85.55). There was a positive correlation between IQ levels and school achievement; those children who had higher school achievement ('excellent,' grade A) had a highest DAP test score (112.19) and IQ level among the whole studied sample and vice versa. There was significant correlation between IQ levels and BMI of children. There was no significant difference in IQ levels between men and women [Table 4].
Table 2: Distribution of the studied children regarding their characteristics

Click here to view
Table 3: Distribution of the studied children regarding intelligence quotient level

Click here to view
Table 4: Distribution of sex, residence, BMI, socioeconomic standard, and school achievement regarding intelligence quotient level

Click here to view



  Discussion Top


The assessment of intelligence has a long controversial history. But in recent years, one area that has received more intense focus on the study of cognition has been the assessment of neuropsychological functioning in children and adolescents [5]. Many studies conducted all over the world to find the impact of many risk factors those affect child cognition such as the education, occupation, and income of parents – indices of the families' SES – have been found to moderate the heritability of their children's intelligence such as Turkheimer et al. [6]. Since there are a number of risk factors that contribute to cognitive achievement, examining these factors in a cumulative risk model may be valuable because the cumulative risk may be more influential than any specific risk factor alone in predicting negative child development outcomes [7]. Cox and Howarth [8] reported significant differences in drawing by normal children and by children with developmental delays lagging 4 years behind normal. This study, with regard to IQ results, showed some findings. First, the distribution of IQ levels among the studied sample showed that children with superior intelligence consisting 10.9% of the studied sample, high percentage of average intelligence group (69.2%), borderline intellectual function (17.3%), and children with mild mental retardation (2.7%., with a mean IQ of 97.91 ± 9.92. The second point was that there was no significant difference in IQ levels between men and women. This comes up with a study conducted by Flynn and Rossi-Casé [9] who found that men and women achieved roughly equal IQ scores on Raven's Progressive Matrices after reviewing recent standardization samples in five modernized nations. Lynn [10], who contended that while it is correct that there is virtually no sex difference in average intelligence between the ages of 5 and 15 years, from the age of 16 years men begin to have greater average intelligence than women. This disagree with the 2004 meta-analysis by Irwing and Lynn [11] who found that the mean IQ of men exceeded that of women by up to five points on the Raven's Progressive Matrices test. The third finding is that children living in an urban residence had higher IQ levels in comparison with those living in rural areas, and this indicates a strong positive correlation between cognitive function and residency. This supports the study conducted by Emmett [12] who showed that the rural school children obtained lower scores than urban children, and that the spread in intelligence among them was also smaller. Tabriz et al. [13] found that the children's IQ, as determined by the Wechsler intelligence scale for children, administered as part of the study (living in metropolitan and urban areas and the level of children's fathers' education was positively related to IQ), and disagree with Naomi et al. [14],'stability and change in children's intelligence quotient scores' who found that IQ was lower among children living in urban areas than those of rural residence. Further research directed to investigate the relation between children IQ and residence may be helpful in recognizing the residence-related causes that may affect IQ levels, such as nutritional status, quality of education, genetic admixture and pollution. The fourth point was that a significant correlation was found between BMI and children's IQ: an IQ level was significantly higher among children with normal BMI than the underweight group. Moreover, normal children had a significantly higher IQ level than the obese group. And the IQ level of overweight children was significantly higher than the obese group. Tabriz et al. [13] found that a lower IQ score is associated with higher BMI. However, this relation appears to be largely mediated when the SES was considered. It may be suggested that hormones secreted from fat could have a damaging effect on cerebral cells, resulting in decreased brain function. Another explanation could be that as obesity is a widely known cardiovascular risk factor, leading to thickening and hardening of the blood vessels, this may also affect the cerebral vessels. The fifth finding: a strong positive correlation was found between socioeconomic standards and IQ levels; those children with high SES have higher DAP test scores and IQ levels in comparison with those with average and low SES. This is in agreement with Fernald et al. [15] who found a positive correlation between socioeconomic standards and IQ levels; those children with high SES have higher IQ levels. Children from disadvantaged family backgrounds score an average lower on intelligence tests than their higher SES peers [16], and their performance has been suggested to worsen over time, even if they did relatively well in early assessments. Conversely, high SES children are thought to gain in intelligence over time, even if they initially had a lower test score [17]. We think that this may be due to specific risk factors related to the SES, such as lack of family resources, parental support may lead to low IQ levels. Sirin [18] meta-analyzed data on roughly 100 000 students and found a mean correlation between cognitive ability and parental SES to be indicating a weak to moderate relationship. This finding is similar to what was reported by 1996 American Psychological Association Task Force report on intelligence. Given this correlation, the question arises as to whether it is IQ or SES which causes a variation in the other variable. The answer is almost certainly both [19]. The sixth finding was the positive correlation between IQ levels and school achievement; those children with higher school achievement 'grade A' have the highest 'DAP test' scores and IQ levels among the whole studied sample and vice versa. Our study came in line with a study in UK schools to relate scores on statewide standardized achievement tests to measure cognitive skills in a large and representative sample of students in a city that includes traditional district schools, exam schools, and charter public schools. They found a substantial positive correlation between cognitive skills and achievement test scores, especially in math. These correlations are consistent with prior studies relating working memory to academic performance (grades) in UK schools [20]. Laidra et al. [21] reported that students' achievement relies most strongly on their cognitive abilities through all grade levels.


  Conclusion Top


From the results of the study, the IQ levels obtained by the DAP test were positively correlated with socioeconomic standards, BMI, residence, and school achievement. No correlation was found between IQ levels and sex.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Fan RJ. A study on the kinetic family drawings by children with different family structures. Int J Art Des Educ 2012; 10:173–204.  Back to cited text no. 1
    
2.
Weiner I, Greene R. Handbook of personality assessment. Hoboken, NJ: John Wiley and Sons 2008; 483.  Back to cited text no. 2
    
3.
Cox MV. Drawings of people by australian aboriginal children. The intermixing of cultural styles. Int J Art Des Educ 1998; 17:71–79.  Back to cited text no. 3
    
4.
Naglieri JA. Draw-a-person. A quantitative scoring system manual. San Antonio, TX: The Psychological Corporation; 1988.  Back to cited text no. 4
    
5.
Sparrow SS, Davis SM. Recent advances in the assessment of intelligence and cognition. J Child Psychol 2000; 41:117–131.  Back to cited text no. 5
    
6.
Turkheimer E, Thomas C, Oltmanns TF. Factorial structure of pathological personality as evaluated by peers. J Abnorm Psychol 2003; 112:81–91.  Back to cited text no. 6
    
7.
Stevens GD. Gradients in the health status and developmental risks of young children. The combined influences of multiple social risk factors. Matern Child Health J 2006; 10:187–199.  Back to cited text no. 7
    
8.
Cox MV, Howarth C. Human figure drawing of normal children and those with severe learning difficulties. Brit J Dev Psychol 1989; 7:333–339.  Back to cited text no. 8
    
9.
Flynn J, Rossi-Casé L. Modern women match men on Raven's Progressive Matrices. Pers Indiv Differ 2011; 50:799–803.  Back to cited text no. 9
    
10.
Lynn R. Sex differences in brain size and intelligence. A paradox resolved. Pers Indiv Differ 1994; 17:257–271.  Back to cited text no. 10
    
11.
Irwing P, Lynn R. Sex differences in means and variability on the progressive matrices in university students: a meta-analysis. Br J Psychol 2005; 96:505–524.  Back to cited text no. 11
    
12.
Emmett WG. The intelligence of urban and rural children. Popul Stud 2011; 7:207–221.  Back to cited text no. 12
    
13.
Tabriz A, Sohrabi M-R, Roodaki A, et al. Relation of intelligence quotient and body mass index in preschool children. A community-based cross-sectional study. Nutr Diabetes 2015; 5:e176.  Back to cited text no. 13
    
14.
Naomi B, Howard D, Ezra S, Thomas M, Kung-Yee L, Edward L. Stability and change in children's intelligence quotient scores. A comparison of two socioeconomically disparate communities. Am J Epidemiol 2001; 154:711–717.  Back to cited text no. 14
    
15.
Fernald LC, Weber A, Galasso E, Ratsifandrihamanana L. Socioeconomic gradients and child development in a very low income population: evidence from Madagascar. Dev Sci 2011; 14:832–847.  Back to cited text no. 15
    
16.
Schoon I, Jones E, Cheng H, Maughan B. Family hardship, family instability, and cognitive development. J Epidemiol Community Health 2012; 66:716–722.  Back to cited text no. 16
    
17.
Feinstein L Very early cognitive evidence. CentrePiese 2003; 8:24–30.  Back to cited text no. 17
    
18.
Sirin SR. Socioeconomic status and academic achievement: a meta-analytic review of research. Rev Educ Res 2005; 75:417–453.  Back to cited text no. 18
    
19.
Neisser U, Boodoo G, Bouchard TJ Jr, Boykin AW, Brody N. Intelligence: knowns and unknowns. Am Psychol 1996; 51:77–101.  Back to cited text no. 19
    
20.
Alloway TP, Passolunghi MC. The relations between working memory and arithmetical abilities. A comparison between Italian and British children. Learn Individ Differ 2011; 21:133–137.  Back to cited text no. 20
    
21.
Laidra K, Pullmann H, Allik J. Personality and intelligence as predictors of academic achievement: a cross-sectional study from elementary to secondary school. Pers Individ Dif 2007; 42:441–451.  Back to cited text no. 21
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Participants and...
Results
Discussion
Conclusion
References
Article Tables

 Article Access Statistics
    Viewed36    
    Printed0    
    Emailed0    
    PDF Downloaded10    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]