Prevalence and Correlates of ADHD Among Adolescent Students in Nigeria

Abstract

Objective: To determine the prevalence and psychosocial correlates of ADHD among adolescents in Jos, Nigeria. Method: A cross-sectional descriptive two-stage study of 487 randomly selected participants using Kiddie–Schedule for Affective Disorders and Schizophrenia–Present and Lifetime Version (K-SADS-PL), Raven’s Standard Progressive Matrix (SPM) and the Children’s Global Assessment Score (CGAS). Results: The prevalence of ADHD was 8.8%. The subtypes found were inattentive (3.08%), hyperactive-impulsive (2.05%), and combined (3.08%); male:female ratio of 1.4:1. ADHD was significantly associated with use of substance by father (odds ratio [OR] = 0.35; 95% confidence interval [CI] = [0.154, 0.781]), use of substance by mother (OR = 0.2; 95% CI = [0.055, 0.711]), and lower education of mother (OR = 0.3 95% CI = [0.116, 0.693]). Poor quality of handwriting (χ² = 8.120; p = .010) and impaired global functioning (t test = 10.756; p < .001) were significantly associated with ADHD in the adolescents. Conclusion: Given the burden of ADHD, efforts should be made to establish a system for the early identification and management.

Keywords

ADHD ADHD-associated problems ADHD impairment ADHD subtypes adolescent ADHD

Introduction

ADHD is a complex neuropsychiatric condition that is characterized by the inability to marshal and sustain attention, regulate activity levels, and moderate activities that require complicated co-ordination (Gillberg, 2003; Rappley, 2005). It is mainly associated with age-inappropriate symptoms of inattention, motor restlessness, and impulsive behavior (Diagnostic and Statistical Manual of Mental Disorders [5th ed.]; DSM-5; American Psychiatric Association [APA], 2013). It is one of the most common neuro-behavioral conditions of childhood (American Academy of Pediatrics, 2011; Erol, Simsek, Oner, & Munir, 2008), with associated broad functional impairment in both childhood and adolescence (Biederman, Faraone, & Monuteaux, 2002; Pedersen, Heath, & Surbury, 2007; Schmitz et al., 2002; Trani et al., 2011). This may extend into adult life (Ramsey & Rostin, 2008; Simon, Czobor, Balint, Meszaros, & Bitter, 2009).

Wide-ranging prevalence rates are quoted for ADHD by different national surveys. These range from 1.9% to 19% of school-aged children (Adewuya & Famuyiwa, 2007; Burd, Klug, Coumbe, & Kerbeshian, 2003; Faraone, Sergeant, Gillberg, & Biederman, 2003; Ruchkin, Lorberg, Koposov, Schwab-Stone, & Sukhodolsky, 2008). The review of ADHD in sub-Saharan Africa reported a prevalence range of 5.4% to 8.7% among children (Bakare, 2012).There is very little information on ADHD among adolescent population in Nigeria and especially in the North-Central part of Nigeria when compared with other parts of Nigeria (Abiodun et al., 2011; Adewuya & Famuyiwa, 2007; Egbochukwu & Abikwi, 2007; Ndukuba, Odinka, Muomah, Obindo, & Omigbodun, 2014), and relatively little work done in sub-Saharan African (Kashala, Tylleskar, Elgen, Kayembe, & Sommerfelt, 2005; Meyer & Sagvolden, 2006; Prithivirajh & Edwards, 2011; Walker, Venter, & van der Walt, 2011). Studies from other parts of Nigeria by Adewuya and Famuyiwa (2007) and Ndukuba et al. (2014) reported a prevalence of 8.7% and 6.6%, respectively.

Researchers have noted that despite the existence of studies on the epidemiology of ADHD from the five continents of the world, there are relatively fewer studies from African countries (Bakare, 2012; Meyer, Eilertsen, Sundet, Tshifularo, & Sagvolden, 2004; Spencer, Biederman, & Mick, 2007). With a higher prevalence of psychosocial risk factors in developing countries, there may be an equal or even higher prevalence of ADHD and other similar disorders. It has been suggested that, epidemiological and neuropsychological studies in developing countries should be carried out to determine the nature of ADHD in these countries (Bakare, 2012).

The Nigerian population is predominantly a youthful one, with about 44% of her estimated 160 million people, aged 15 years and below (National Bureau of Statistics, 2006). This study, therefore, is aimed at assessing the prevalence of ADHD and psychosocial correlates of the disorder in school-aged adolescents in the North-Central region of Nigeria. Understanding the prevalence of ADHD, psychosocial correlates and any associated impairments in the adolescent population is an important step toward providing knowledge that can be used to educate parents, teachers, and policy makers concerned with child and adolescent health.

Method

Design and Setting

This was a cross-sectional descriptive two-staged study of adolescents in secondary schools in Jos metropolis, in North-Central Nigeria.

Sample

The sample comprise of 505 adolescent students aged 11 to 19 drawn from 5 schools after a multi-stage sampling that involved stratifications into private and public schools. This was then followed by systematic sampling to select the five schools and individuals in the selected schools. Twenty students declined to participate in the study either due to parental refusal, absence of parents, or non-assent by the students. Eighteen students were excluded from the final analysis because of incomplete data from the socio-demographic questionnaire. Therefore, 487 students information were used for the analysis; made up of 251 (51.5%) males and 236 (48.5%) females, with mean age of 14.09 years (SD = ±1.85), with 90% of the students aged 16 years and below, and the age group 11 to 13 years constituting 46% of the population studied (Table 1).

Table 1.

Socio-demographic Characteristics of the Participants.

Socio-demographic variables (N = 487)	n (%)
Gender
Male	251 (51.5)
Female	236 (48.5)
Age (years)
≤13	224 (46)
≥14	263 (54)
Family type
Monogamous	360 (74)
Polygamous	127 (26)
Care provider (living with)
Both parents	385 (79.1)
Others^a	102 (20.9)
Family size
≤5 siblings	399 (81.9)
>5 siblings	88 (18.1)
Birth order
First position	141 (29)
Other positions	346 (71)
Current marital status of parents
Married	420 (86.2)
Others (separated/divorced, widowed, never married)	67 (13.8)
Religion
Christianity	322 (66.1)
Islam	165 (33.9)

Others: Included in this group are adolescents living with only mother, father, grandparents, aunts, and other family members.

Instruments

The instruments used for data collection included a self-administered socio-demographic ADHD variable questionnaire to collect information on age, gender, birth order, religion, family background, and the level of education and occupation of each parent and the size and structure of the family; Kiddie–Schedule for Affective Disorders and Schizophrenia–Present and Lifetime Version (K-SADS-PL; Kaufman, Birmaher, Brent, Rao, & Ryan, 1996); Raven’s Standard Progressive Matrix (SPM; Raven, Raven, & Court, 2000); and Children’s Global Assessment Scale (CGAS; Shafer, Shaffer, O’Connor, & Stokman, 1983).

The K-SADS-PL assesses both lifetime and current psychiatric diagnosis (Kaufman et al., 1996). It is a semi-structured diagnostic interview for children and adolescents based on Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; APA, 1994) criteria. Depending on the severity of key current and past symptoms reported in the screening interview, any five diagnostic supplements (Affective Disorders, Psychotic Disorders, and Others) can be administered. Kaufman, Birmaher, and Brent in 1997 reported that the inter-rater agreement in scoring screens and diagnoses was high (range = 98%-100%). The K-SADS-PL has been used extensively in studies of psychiatric disorders in the child and adolescent age group in several cultures, including Nigeria (Adewuya, Ola, & Aloba, 2007; Gureje & Omigbodun, 1995; Gureje et al., 1994; Shahrivar, Kousha, Moallemi, Tehrani-Doost, & Alaghband-Rad 2010). In a study by Gureje and colleagues (1994), the inter-rater agreement was good: averaging 80% for depression items, 93% for anxiety-related disorders, and 100% for conduct and attention deficit hyperactivity disorders. The ADHD supplement was used in this study.

To assess intelligence, the Raven’s Standard Progressive Matrices (SPM) was used. It is said to be culturally indifferent and is also recommended for areas where there are no standardized IQ tests (Raven et al., 2000). The SPM is a non-verbal assessment tool designed to measure an individual’s ability to perceive and think clearly, make meaning out of confusion, and formulate new concepts when faced with novel information (Pearson, 2007). The matrix consists of multiple-choice tests of abstract reasoning. In each test item, a candidate is asked to identify the missing segment required to complete a larger pattern. The SPM comprises five sets (A-E) of 12 items each, with each item within a set becoming increasingly difficult, requiring greater cognitive capacity to encode and analyze information. Each set has a maximum score of 12, with a total score of 60 for all the five sets. The internal consistency estimate for the SPM total raw score was 0.88. The SPM scores correlated (convergent validity) with scores on the subsets of Wechsler Adult Intelligence Scale III (Raven, Raven, & Court, 2000).

The SPM has been used in different parts of Nigeria to assess intellectual performance and capability of adolescents even though no normative values have been established (Ijarotimi & Ijadunola, 2007; Maqsud, 1980).

CGAS is a numeric scale (1-100) designed to provide a global measure of level of functioning in children and adolescents (Schaffer et al., 1983). This CGAS was used to assess the social, educational, and psychological functioning of the adolescents, with score of ≤70 indicating functional impairment (Bird, Canino, Rubio-Stipec, & Ribera, 1987). The CGAS has been used in children and adolescent in Nigeria (Bakare, Agomoh, Eaton, Ebigbo, & Onwukwe, 2011; Tunde-Ayinmode, Adegunloye, Ayinmode, & Abiodun, 2012). For this study, the mean score of students with ADHD was compared with individuals without ADHD.

Procedure

The study was approved by the Institutional Health Research Ethical Committee of Jos University Teaching Hospital and University of Jos, Nigeria. Permission was obtained from the Ministry of Education of the state and the selected five schools. The study was conducted in the two stages. The first stage involved giving the selected students two sets of consent forms, a consent form for their parents and an assent form to be filled by the students. The filled forms were collected and the selected adolescents were given the self-administered socio-demographic questionnaire, whereas the ADHD screening section of the K-SAD-PL was interview administered. Those who screened positive for ADHD were then assessed for a definitive diagnosis of ADHD using the ADHD Behavioural Disorder Supplement. All interviews were conducted either in the library, the principal’s office, or in an empty classroom depending on the available space in the school to ensure privacy.

The second stage involved the administration of the Raven’s SPM and an assessment of functioning using the CGAS to those who were diagnosed with ADHD and 10% of students who had a negative screen (described as Non-ADHD Group). The non-ADHD group was selected by picking the next student that screened negative after each student diagnosed with ADHD, with their age and sex matched.

The K-SADS-PL interview was conducted by the lead author and two Resident doctors in psychiatry after attaining good inter-rater reliability of 0.97 (97%) for the ADHD symptoms and 0.89 (89%) for the assessment of functioning. The first and second stages were conducted within 2 weeks in most cases, such that each school was completed before proceeding to the next school. On the average first stage of the study, socio-demographic questionnaire and ADHD Screen, took about 10 min, whereas the second stage took between 45 and 60 min for one participant.

Data Analysis

Data entry and analysis was done using the Statistical Package for Social Sciences (SPSS) Version 15.01 for Microsoft Window Software Package (SPSS, 2006). Frequencies and cross-tabulation of variables were generated to check for data entry errors and missing values. The prevalence of ADHD, psychosocial and demographic correlates were determined using descriptive statistical tools, such as means, standard deviations, and frequency tables. The relationship and significance of association between ADHD, psychosocial, demographic variables, use of psychoactive substances by parents, quality of handwriting, and academic performance was tested using the Chi-square test, with Yates correction applied where appropriate. The level of significance was set at .05, two-tailed. The odds ratios were calculated for variables found to be significantly associated with ADHD. The student t test or ANOVA, where appropriate, was used to test the relationship between intelligence, global functioning, and ADHD.

Result

In this sample, 74% of the study participants were from monogamous family settings and 79.1% were living with both biological parents. Majority of the participants had less than six siblings (81.9%) and only 29% were first born in birth order. The majority (86.2%) of the parents of the adolescents was married, and the provision of care for the majority (79.1%) was by both parents (Table 1).

Prevalence of ADHD

With the use of the K-SADS-PL, the prevalence of ADHD was found to be 8.8% (43 students), with 15 (34.9%) having the predominantly inattentive subtype, 10 (23.2%) had the predominantly hyperactive-impulsive subtype, 15 (34.9%) had the combined subtype and 3 (7%) had the ADHD NOS (Table 2).

Table 2.

Distribution of the Subtypes of ADHD.

Subtype	Frequency	%
Inattentive	15	34.9
Hyperactive-impulsive	10	23.2
Combined	15	34.9
ADHD NOS	3	7

Note. NOS = Not Otherwise Specified.

Of the 43 students who had ADHD, 25 were males (10%) and 18 were females (7.6%). This represents a male to female ratio of 1.4:1. This difference was not statistically significant (χ² = 0.822, p = .364; Tables 3). Females were more likely to be diagnosed with the predominantly inattentive subtype of ADHD than males with a ratio 2:1. For the predominantly hyperactive-impulsive and combined subtypes of ADHD, males had a higher representation with male-to-female ratio of 4:1 and 1.14:1, respectively. Students aged 13 years and below had a higher prevalence rate of ADHD (12.1%) than those above 13 years (6.1%). The difference was statistically significant (χ² = 5.356; p = .021; Table 2).

Table 3.

Socio-demographic Factors and ADHD (N = 487).

Socio-demographic variables	ADHD diagnosis	No ADHD diagnosis	χ²	p value
Socio-demographic variables	n (%)	n (%)	χ²	p value
Gender
Male (n = 248)	25 (10)	226 (90)	0.822	.364
Female (n = 239)	18 (7.6)	218 (92.4)	0.822	.364
Age
≤13 years (n = 224)	27 (12.1)	197 (87.9)	5.356	.021
>13 years (n = 263)	16 (6.1)	247 (93.9)	5.356	.021
Family type
Monogamous (n = 422)	38 (9)	384 (91)	0.121	1.000^a
Polygamous (n = 65)	5 (7.7)	60 (92.3)	0.121	1.000^a
Marital status
Living together (n = 420)	38 (9.1)	382 (90.9)	0.180	.819^a
Not living together (n = 67)^b	5 (7.5)	62 (92.5)	0.180	.819^a
Family size^c
≤5 family members (n = 399)	38 (9.5)	361 (90.5)	1.322	.304^a
>5 family member (n = 88)	5 (5.6)	83 (94.3)	1.322	.304^a
Birth order
1st born (n = 141)	16 (11.3)	125 (88.7)	1.563	.211
Others (n = 346)	27 (7.8)	319 (92.2)	1.563	.211
Educational level of mother
No formal education (n = 35)	8 (22.9)	27 (77.1)	9.218	.007^a
Formal education (n = 452)	35 (7.7)	417 (92.3)	9.218	.007^a
Educational level of father
No formal education (n = 19)	4 (21.1)	15 (78.9)	3.669	.077^a
Formal education (n = 468)	39 (8.3)	429 (91.7)	3.669	.077^a

Fisher’s exact test applied; df = 1.

Comprising of separated, divorced, and widowed parents.

Family size was assessed by the number of children in the family.

Socio-demographic Characteristics and ADHD

Table 3 shows the different socio-demographic characteristics of the study population. The marital status of parents, either married or not (9.1% vs. 7.5%; p = .819), family type, either monogamous or polygamous (9.0 vs. 7.7%; p = 1.000), family size of either one to five members or greater than five (9.5% vs. 5.6%; p = .304) and birth order of either first born or other birth orders (11.3% vs. 7.8%; p = .211) were not statistically significant. However, students whose mothers had no formal education reported higher rates of ADHD compared with those whose mothers had at least a primary education (22.9% vs. 7.7%). This difference was statistically significant (χ² = 9.218; p = .007). But the education of fathers was not statistically significant (21.1% vs. 8.3% p = .077).

Association of Use of Psychoactive Substances by Parents With Diagnosis of ADHD

The fathers of adolescents with ADHD had a higher rate (25.6%) of use of psychoactive substances such as cigarette, other tobacco-containing substances, and alcohol than those without ADHD (8.8%). This difference was statistically significant (χ² = 12.007; p = .002). Also, mothers of students with ADHD had a higher rate of use of psychoactive substances (11.6%) as against 1.6% for the non-ADHD students. This difference also was statistically significant (Fisher’s exact test = 16.480; p = .002; Table 4).

Table 4.

Use of Psychoactive Substances by Parents’ School Performance as Factor Associated With ADHD.

Variables	ADHD		χ²	p value
Variables	Present (n = 43)	Absent (n = 444)	χ²	p value
Use of psychoactive substances by fathers
Yes	11 (25.6)	39 (8.8)	12.007	.002
No	32 (74.4)	405 (91.2)	12.007	.002
Use of psychoactive substances by mothers
Yes	5 (11.6)	7 (1.6)	16.480	.002^a
No	38 (88.4)	437 (98.4)	16.480	.002^a
Quality of handwriting
Poor	9 (20.9)	35 (7.90)	8.120	.010^a
Good	34 (79.1)	409 (92.1)	8.120	.010^a
Average position in class
1-20	35 (81.4)	394 (88.7)	2.015	.156^a
<20	8 (18.6)	50 (11.3)	2.015	.156^a
Repeating a class
Nil	39 (90.7)	411 (92.6)	2.015	.156^a
≥1	4 (9.3)	33 (7.4)	2.015	.156^a

Fisher’s exact test; df = 1.

Impairment of Functioning Using the CGAS

Using the CGAS, the mean score of those with ADHD was lower (64.26, SD = ±8.90; “some difficulty in a single area”) compared with those without ADHD (90.48, SD = ±7.06; “superior functioning in all areas”). This difference was statistically significant (t test = 15.644; p < .001). Male students with ADHD had a lower mean score in the CGAS of 60.72 (SD = ±7.40) than female students with ADHD with 66.80 (SD = ±9.15). This difference was statistically significant (t test = 2.321; p = .025). The hyperactive-impulsive subtype of ADHD had the lowest mean score of 63 (SD = ±6.20) and was followed by the combined subtype with 64.73 (SD = ±8.15) and the inattentive subtype with 65.67 (SD = ±11.32). This difference was not statistically significant (t test = 0.537; p = .660).

Association of Academic Performance, Quality of Handwriting, and Intelligence and ADHD

There was no significant statistical difference between students with ADHD and those without ADHD in there academics, which was assessed through the average position in class as a function of total score in all subjects in the preceding year and a report of repeating a class or classes (Table 4). When asked to assess the quality of their handwriting compared with that of their classmates, 20.5% of the ADHD participants reported their handwriting as being poor, while 7.7% of those without a diagnosis of ADHD reported having poor handwriting. This difference was statistically significant (χ² = 8.120; p = .010; Table 4). Students with ADHD had a lower mean score on the Raven’s SPM (37.67, SD = ±11.05) compared with the students without ADHD (39.21, SD = ±9.16). This difference was not statistically significant (t test = 0.451; p = .653). Males with ADHD had a slightly lower mean score on the SPM of 37.08 (SD = ±11.05) than females who had a score of 38.50 (SD = ±11.30). The difference was not statistically significant (Table 5). The predominantly hyperactive-impulsive subtype of ADHD had the lowest score on the SPM, though it was not statistically significant (Table 5).

Table 5.

Gender and ADHD Subtype Distribution of Intelligence in Students With ADHD.

Variables	M intelligence scores on SPM (SD)	t test	p value
Gender
Males	37.08 (11.06)	0.412^a	.683
Females	38.50 (11.30)	0.412^a	.683
ADHD subtype
Predominantly inattentive	39.13 (13.44)	1.296^b	.289
Predominantly hyperactive-impulsive	33.80 (11.40)	1.296^b	.289
Combined	40.33 (7.70)
ADHD NOS	30.00 (8.19)

Note. SPM = Raven’s Standard Progressive Matrices.

df = 2.

ANOVA, df = 3.

Logistic Regression on Variables Associated With ADHD

Variables found to be associated with ADHD were put into logistic regression analysis. These factors include use of substance by father, use of substance by mother, educational level of mother and age. The following variables were found to be associated with ADHD: use of substance by father 0.35 (95% confidence interval [CI] = [0.154, 0.781]), use of substance by mother 0.2 (95% CI = [0.055, 0.711]), and educational level of mother 0.3 (95% CI = [0.116, 0.693]; Table 6). Age of the individual did not show association on logistic regression.

Table 6.

Logistic Regression on Variables Found to be Associated With ADHD.

Variables^a	Wald estimate	Odds ratio	p value	95% confidence interval
Variables^a	Wald estimate	Odds ratio	p value	Upper	Lower
Use of substance by father	6.537	0.347	0.011	0.154	0.781
Use of substance by mother	6.158	0.198	0.013	0.055	0.711
Educational level of mother	7.631	0.283	0.006	0.116	0.693
Age	3.585	1.918	0.058	0.977	3.765

Note. df = 1.

Variables entered into the equation include age, educational level of mother, use of substance by father and mother.

Discussion

The prevalence of ADHD was found to be 8.8% in this study. This is in keeping with the prevalence of 6% to 13% obtained in an adolescent population worldwide survey (Skounti Philalithis, & Galanaki, 2007). Other studies around the world reported similar prevalence rates among adolescent populations such as 9.2% in United States, 9.2% in Russia, 8.3% in Iran, 7.7% in Japan, and 6.8% in Australia (Graetz, Sawyer, Hazell, Arney, & Baghurst, 2001; Mohammadi et al., 2008; Ramtekkar, Reiersen, Todrov, & Todd, 2010; Ruchkin et al., 2008). Whereas some studies showed higher prevalence rates such as in the studies from Colombia with 17.1% (Pineda, Lopera, Henao, Palacio, & Castellanos, 2001), 17.1% in Brazil (Vasconcelos et al., 2003), and 18% in Germany (Baumgaertel, Wolraich, & Dietrich, 1995), other studies reported lower rates like 4.8 in Germany (Huss, Hőlling, Kurth, & Schlack, 2008) and 3.7% in Sweden (Kadesjo & Gillberg, 1998). Higher prevalence rates have been linked to the use of rating scales instead of diagnostic instruments and also studies that combined children and adolescents as their study population (Graetz et al., 2001; Nolan, Gadow, & Sprafkin, 2001; Pineda et al., 2001; Vasconcelos et al., 2003). Studies which reported rates within the worldwide pooled prevalence range of 5% to 10% (Polanczyk, de Lima, Horta, Biederman, & Rohde, 2007), either used both rating scales and interview-based instruments or used only the interview-based instruments. Mohammadi et al. (2008) used the K-SAD-PL in 12- to 17-year-old adolescents and obtained a prevalence of 8.3%.

All the three major subtypes of ADHD were reported in this study. The prevalence rates of the predominantly inattentive, predominantly hyperactive-impulsive, and the combined subtypes were 3.08%, 2.05%, and 3.08%, respectively. Two studies from Nigeria reported similar findings with the predominantly hyperactive-impulsive subtype having the least and the inattentive subtype having the highest prevalence rate (Adewuya & Famuyiwa, 2007; Ambuabunos, Ofovwe, & Ibadin, 2011). The study by Ambuabunos et al. (2011) reported prevalence rates for inattentive, hyperactive-impulsive, and combined subtypes at 3.6%, 1.63%, and 2.37%, respectively. Adewuya and Famuyiwa (2007) found that the prevalence of the subtypes was predominantly inattentive 4.9%, predominantly hyperactive-impulsive 1.2%, and combined 2.6%. Similar findings were also reported in the United States (Froehlich et al., 2007) and other international population-based studies (Baumgaertel et al., 1995; Graetz et al., 2006). It has been suggested that population characteristics and cultural differences may contribute to the variation in the prevalence of the ADHD subtypes (Skounti & Betts, 2011).

Gender variation in the prevalence rate was found in this study to have a lower male to female ratio. Whereas many other studies reported a male to female prevalence ratio of between 2:1 and 4:1 (Adewuya & Famuyiwa, 2007; Gaub & Carlson, 1997; Pineda et al., 2003; Ramtekkar et al., 2010), this study found a 1.4:1 ratio. A gender ratio, similar to the one found in this study, was reported in an Iranian study of 1,105 adolescents aged 12 to 17 years. Mohammadi and colleagues (2008) reported a male to female ratio of 1.63:1. A recent Nigerian study, also reported a lower male to female ratio of 1.71:1 (Ambuabunos et al., 2011). The lower male to female gender difference in the study compared with others is largely due to the age range of this study which strictly studied adolescents between the ages of 10 and 19 years. Other studies which reported a higher male to female ratio either combined both children and adolescents or studied only children. The high gender ratio difference in ADHD usually reduces in adolescence and the adult population (Ramtekkar et al., 2010).

Females were more likely to be diagnosed with the predominantly inattentive subtype of ADHD than males in this study with a male to female ratio of 1:2. The male to female ratio for the predominantly hyperactive-impulsive and combined subtypes were 4:1 and 1.14:1, respectively. This result is comparable with a systematic review of Iranian children and adolescents which reported the hyperactive-impulsive subtype to be more prevalent in boys and the inattentive subtype to be more prevalent in girls (Shooshtary et al., 2010). The findings that the inattentive subtypes is more prevalent in females and the hyperactive-impulsive subtype in males were also supported by another meta-analysis on the gender difference of ADHD, where it was concluded that girls with ADHD seem to cluster more in the inattentive subtype than do boys (Gaub & Carlson, 1997).

This study showed that students aged 13 years and below had a higher prevalence rate of ADHD at 12.1% than those above 13 years with 6.1%. This is in keeping with most research studies that found higher prevalence rates in the younger age group, and that the prevalence of ADHD declines with age (Biederman, Mick, & Faraone, 2000; Ramtekkar et al., 2010).

In this study, students whose mothers had no formal education reported higher rates of ADHD. This is similar to a study from the United States which reported that low maternal and paternal educational levels increased the risk of ADHD (St. Sauver et al., 2004). It had been reported that low parental education is associated with low income and low socio-economic class which in turn correlates with ADHD (Hjern, Weitoft, & Lindblad, 2010).

In this study, both parents of adolescents with ADHD had a higher rate of use of psychoactive substances than adolescents without ADHD. This finding is in keeping with various studies that showed a positive correlation between parental use of psychoactive substances such as alcohol, cigarettes, and caffeine-containing drinks, and ADHD (Clark, Cornelius, Woods, & Vanyukov, 2004; Martin et al., 2008; Parvaresh, Ziaaddini, Kheradmond, & Bayati, 2010). The mechanism behind psychoactive substance use, especially intrauterine exposure to alcohol and caffeine, and overactivity is suggested to operate through enhanced dopamine induced changes in motor behavior (Mill & Petronis, 2008). The dysfunction of dopaminergic neurotransmission in the central nervous system is thought to be part of the etiology of ADHD (Faraone & Khan, 2006).

Adolescents with ADHD in this study reported having a poorer handwriting when they compared theirs with other classmates. This finding is similar to that of other studies which suggested that individuals with ADHD have impaired handwriting performance, characterized by illegible written material and inappropriate speed of execution, compared with youths without ADHD (Peeple, Searls, & Wellingham-Jones, 1995; Racine, Majnemer, Shevell, & Snider, 2008). Although an objective assessment using scales or checking the sample handwriting was not done, the students were asked to do a self-appraisal of their handwriting. It has been documented that individuals with ADHD are more likely to exaggerate their competence (Gerdes, Hoza, & Pelham, 2003; Hoza, Pelham, Dobbs, Owens, & Pillow, 2002). Hence, the students’ assessment is more likely to be a true reflection of their handwriting. The reason for this impairment appears to be the high prevalence of motor impairment in individuals with ADHD (Gillberg, 2003; Kaiser, Shoemaker, Albaret, & Geuze, 2014). There appears to be comorbidity between ADHD and developmental coordination disorder (Gillberg, 2003).

The overall rate of having to repeat a class for individuals with ADHD in this study was higher than students without ADHD. Various studies have also reported higher rates of repeating a class and poor academic performance in students with ADHD (Ambuabunos, Ofovwe, & Ibadin, 2010; Daley & Birchwood, 2010). ADHD is associated with impaired academic functioning, a higher risk of placement in special education classrooms, school failure, and dropout (DuPaul, 2007) which frequently signifies a chronic course that is viewed as a lifelong disorder requiring developmental and academic intervention (DuPaul, 2007). The lower academic performance in individuals with ADHD has been linked to the core symptoms of the disorder in the form of inattention, hyperactivity, and impulsiveness (Daley & Birchwood, 2010). However, cofounders like transfer of parents, family conflicts, and active failure were not controlled for in this study.

When the CGAS was used in measuring impairment, students with ADHD had a significantly lower score than those without ADHD. Barkley and associates (2006) reported that individuals with ADHD were likely to have more impairments than healthy controls.

Using the Raven’s SPM as a test of intelligence, adolescents with ADHD in this study scored slightly lower than students without ADHD. Male students with ADHD also had a lower score on the SPM compared with female students with ADHD. The students with the predominantly hyperactive-impulsive type of ADHD had the lowest SPM score. Various meta-analyses have reported that the association between intelligence (IQ) and ADHD are generally modest, with the mean influence on IQ probably amounting to 2 to 7 IQ points (Jepsen, Fagerlund, & Mortensen, 2009). A few studies, however, reported that individuals with ADHD, especially the combined type, scored higher on tests of creative thinking than similar IQ peers without ADHD (Brandau et al., 2007). Individuals with ADHD contributed more to a higher number of correct solutions to problems in cooperative groups than was observed in groups without these students (Zentall, Kuester, & Craig, 2011). These conflicting results could be attributed to attentional bias such as attraction to novelty as a contributor to the development of creativity (Zentall, 2005), and however, because some IQ subtests require working attention, and IQ level can be lowered (Jepsen et al., 2009).

Conclusion

The results of the present study among school-going adolescents in Jos, Nigeria, are similar to results of both local and international studies. A higher prevalence rate is associated with younger age of individuals, poor quality of handwriting, global functional impairment, and use of psychoactive substances by parents. It is therefore important for parents, school authorities, mental health professionals, and departments in the ministries of education and health to be aware of ADHD and work toward its early detection and management.

Strengths and Limitations

One of the limitations of the study is the interview of the adolescents only. It would have been better to have obtained information from the parents also as they are better at reporting externalizing symptoms such as ADHD compared with adolescents. Also the parents of the adolescents would have been better assessors of their psychoactive substance use than the adolescents who gave the information. A history of perinatal and postnatal complications, parental history of psychiatric illness and other comorbid conditions, like substance abuse disorder in adolescents, all of which can affect the findings of ADHD were not obtained. Although a cross-sectional study, this study used structured instrument in assessing ADHD, as well as IQ test, and is one of the very few studies examining ADHD in our environment using diagnostic interview instrument.

Clinical Implication

Further community-based studies are needed to replicate the findings of this study, and to investigate the prevalence in the general community, thereby taking into consideration adolescents who are not in school. Subsequent studies should also explore the possibility of longitudinal evaluation of the effects of ADHD on academics and drop-out rate.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

M. U. Umar is a lecturer with Bayero University Kano and a consultant psychiatrist with Aminu Kano Teaching Hospital, Nigeria. He has interest in child and adolescent psychiatry and epidemiology of mental illness.

J. T. Obindo is an associate professor with the University of Jos and a consultant psychiatrist with Jos University Teaching Hospital, Nigeria.

O. O. Omigbodun is a professor of psychiatry with University of Ibadan, and the principal investigator to the Centre for Child and Adolescent Mental Health, University of Ibadan, Nigeria.

References

Abiodun

O. A.

Tunde-Ayinmode

M. F.

Adegunloye

O. A.

Ayinmode

B. A.

Sulyman

Unaogu

N. N.

. . . Agbabiaka

(2011). Psychiatric morbidity in paediatric primary care clinic in Ilorin, Nigeria. Journal of Tropical Paediatrics, 57, 173-178.

Adewuya

A. O.

Famuyiwa

O. O.

(2007). Attention deficit hyperactivity disorder among Nigerian primary school children: Prevalence and comorbid conditions. European Child Adolescent Psychiatry, 16, 10-15.

Adewuya

A. O.

Ola

B. A.

Aloba

O. O.

(2007). Prevalence of major depressive disorders and a validation of the Beck’s depression inventory among adolescents. European Child Adolescent Psychiatry, 16, 287-292.

Ambuabunos

A. E.

Ofovwe

G. E.

Ibadin

O. M.

(2010). Socio-demographic determinants and impact on academic performance of attention deficit/hyperactivity disorder in school children in Benin City, Nigeria. Sahel Medical Journal, 13(3), 120-127.

Ambuabunos

A. E.

Ofovwe

G. E.

Ibadin

O. M.

(2011). Community survey of attention-deficit/hyperactivity disorder among primary school pupils in Benin City, Nigeria. Annals of African Medicine, 10, 91-96.

American Academy of Pediatrics, Subcommittee on Attention-Deficit/Hyperactivity Disorder, Committee on Quality Improvement. (2011). Clinical practice guideline: Treatment of the school-aged child with attentiondeficit/hyperactivity disorder. Pediatrics, 128(5),1007-1022.

American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author.

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.

Bakare

M. O.

(2012). Attention deficit hyperactivity symptoms and disorder (ADHD) among African children: A review of epidemiology and co-morbidities. African Journal of Psychiatry, 15(5), 358-361.

10.

Bakare

M. O.

Agomoh

A. O.

Eaton

Ebigbo

P. O.

Onwukwe

J. U.

(2011). Functional status and its associated factors in Nigerian adolescents with bipolar disorder. African Journal of Psychiatry, 14, 388-391.

11.

Barkley

R. A.

Cunningham

C. E.

Gordon

Faraone

S. V.

Lewandowski

Murphy

K. R.

(2006). ADHD symptoms vs. impairment: Revisited. ADHD Report, 14, 1-9.

12.

Baumgaertel

Wolraich

M. L.

Dietrich

(1995). Comparison of diagnostic criteria for attention deficit disorder in a German elementary school sample. Journal of American Academy of Child & Adolescent Psychiatry, 34, 629-638.

13.

Biederman

Faraone

S. V.

Monuteaux

M. C.

(2002). Differential effects of environmental adversity by gender: Rutter’s index of adversity in a group of boys and girls with and without ADHD. American Journal of Psychiatry, 158, 1556-1562.

14.

Biederman

Mick

Faraone

S. V.

(2000). Age-dependent decline of symptoms of attention deficit hyperactivity disorder: Impact of remission definition and symptoms type. American Journal of Psychiatry, 157, 816-818.

15.

Bird

H. R.

Canino

Rubio-Stipec

Ribera

J. C.

(1987). Further measures of the psychometric properties of the children’s global assessment scale. Archives of General Psychiatry, 44, 821-824.

16.

Brandau

Daghofer

Hollerer

Kaschnitz

Kellner

Kirchmair

. . . Schlagbauer

(2007). The relationship between creativity, teacher ratings on behaviour, age, and gender in pupils from seven to ten years. Journal of Creative Behaviour, 41, 91-113.

17.

Burd

Klug

M. G.

Coumbe

M. J.

Kerbeshian

(2003). Children and Adolescents with attention deficit-hyperactivity disorder: I. Prevalence and cost of care. Journal of Child Neurology, 18, 555-561.

18.

Clark

D. B.

Cornelius

Woods

D. S.

Vanyukov

(2004). Psychopathology risk transmission in children of parents with substance use disorders. American Journal of Psychiatry, 161, 685-691.

19.

Daley

Birchwood

(2010). ADHD and academic performance: Why does ADHD impact on academic performance and what can be done to support ADHD children in the classroom? Child Care and Health Development, 36, 455-464.

20.

DuPaul

G. J.

(2007). School-based interventions for students with attention deficit hyperactivity disorder. Current status and future directions. Schools Psychology, 36, 183-194.

21.

Egbochukwu

E. O.

Abikwi

M. I.

(2007). The prevalence of attention deficit hyperactivity disorder (ADHD) among primary school pupils of Benin metropolis, Nigeria. Journal of Human Ecology, 22, 317-322.

22.

Erol

Simsek

Oner

Munir

(2008). Epidemiology of attention problems among Turkish children and adolescents. Journal of Attention Disorders, 1, 538-545.

23.

Faraone

S. V.

Khan

(2006). Candidate gene studies of attention-deficit/hyperactivity disorder. Journal of Clinical Psychiatry, 67, 13-20.

24.

Faraone

S. V.

Sergeant

Gillberg

Biederman

(2003). The worldwide prevalence of ADHD: Is it an American condition? World Psychiatry, 6, 104-113.

25.

Froehlich

T. E.

Lanphear

B. P.

Epstein

J. N.

Barbaresi

W. J.

Katusic

S. K.

Kahn

R. S.

(2007). Prevalence, recognition and treatment of attention-deficit/hyperactivity disorder in a national sample of US children. Archive of Pediatric & Adolescent Medicine, 161, 857-864.

26.

Gaub

Carlson

C. L.

(1997). Gender differences in ADHD: A meta-analysis and critical review. Journal of American Academy of Child & Adolescent Psychiatry, 36, 1036-1045.

27.

Gerdes

A. C.

Hoza

Pelham

W. E.

(2003). Attention-deficit/hyperactivity disordered boys’ relationships with their mothers and fathers: Child, mother, and father perceptions. Developmental Psychopathology, 15, 363-382.

28.

Gillberg

(2003). Deficit in attention, motor control, and perception: A brief review. Archives of Disease in Childhood, 88, 904-910.

29.

Graetz

B. W.

Sawyer

M. G.

Baghurst

Ettridge

(2006). Are ADHD gender patterns moderated by sample sources? Journal of Attention Disorders, 10(1), 36-43.

30.

Graetz

B. W.

Sawyer

M. G.

Hazell

P. L.

Arney

Baghurst

(2001). Validity of DSM-IV ADHD subtypes in a nationally representative sample of Australian children and adolescents. Journal of American Academy of Child & Adolescent Psychiatry, 40, 1410-1417.

31.

Gureje

Omigbodun

O. O.

(1995). Children with mental disorder in primary care: Functional status and risk factors. Acta Psychiatrica Scandinavica, 92, 310-314.

32.

Gureje

Omigbodun

O. O.

Gater

Acha

Ikuesan

B. A.

Morris

(1994). Psychiatric disorders in a paediatric primary care clinic. British Journal of Psychiatry, 165, 527-530.

33.

Hjern

Weitoft

G. R.

Lindblad

(2010). Social adversity predicts ADHD-medication in school children: A national cohort study. Acta Paediatrica, 99, 920-924.

34.

Hoza

Pelham

W. E.

Dobbs

Owens

J. S.

Pillow

(2002). Do boys with attention-deficit/hyperactivity disorder have positive illusory self-concepts? Journal of Abnormal Psychology, 111, 268-278.

35.

Huss

Hőlling

Kurth

B. M.

Schlack

(2008). How often are German children and adolescents diagnosed with ADHD? Prevalence based on the judgment of health care professionals: Results of the German Health and Examination Survey (KIGGS). Child and Adolescent Psychiatry, 17(Suppl. 1), 52-58.

36.

Ijarotimi

O. S.

Ijadunola

K. T.

(2007). Nutritional status and intelligence quotient of primary school children in Akure community of Ondo State, Nigeria. Tanzania Health Research Bulletin, 9, 70-76.

37.

Jepsen

J. R. M.

Fagerlund

Mortensen

E. L.

(2009). Do attention deficits influence IQ assessment in children and adolescents with ADHD? Journal of Attention Disorders, 12, 551-562.

38.

Kadesjo

Gillberg

(1998). Attention deficits and clumsiness in Swedish 7-year-old children. Developmental Medicine and Child Neurology, 40, 796-804.

39.

Kaiser

M. L.

Shoemaker

M. M.

Albaret

J. M.

Geuze

R. H.

(2014). What is the evidence of impaired motor skills and motor control among children with attention deficit hyperactivity disorder (ADHD)? Systematic review of the literature. Research in Developmental Disabilities, 6, 338-357.

40.

Kashala

Tylleskar

Elgen

Kayembe

K. T.

Sommerfelt

(2005). Attention deficit hyperactivity disorder among school children in Kinshasa, Democratic Republic of Congo. African Health Sciences, 5, 172-181.

41.

Kaufman

Birmaher

Brent

(1997). Schedule for affective disorders and Schizophrenia for School-aged children–Present and Lifetime (K-SADS-PL): Initial reliability and validity data. Journal of American Academy of Child & Adolescent Psychiatry, 36, 980-988.

42.

Kaufman

Birmaher

Brent

Rao

Ryan

(1996). The schedule for affective disorders and schizophrenia for school-age children. Pittsburgh, PA: University of Pittsburgh Medical Center.

43.

Maqsud

(1980). Relationship between sociometric status and moral judgment in secondary school girls. West African Journal of Educational and Vocational Measurement, 5, 13-17.

44.

Martin

C. A.

Cook

Woodring

J. H.

Burkhardt

Guenthner

Omar

H. A.

Kelly

T. H.

(2008). Caffeine use: Association with nicotine use, aggression, and other psychopathology in psychiatric and paediatric outpatient adolescents. Scientific World Journal, 8, 512-516.

45.

Meyer

Eilertsen

D. E.

Sundet

J. M.

Tshifularo

J. G.

Sagvolden

(2004). Cross-cultural similarities in ADHD-like behaviour amongst South African primary school children. South African Journal of Psychology, 34, 123-139.

46.

Meyer

Sagvolden

(2006). Fine motor skills in South African children with symptoms of ADHD: Influence of subtypes, gender, ages and hand dominance. Behavioural and Brain Function, 2, 3-44.

47.

Mill

Petronis

(2008). Pre- and peri-natal environmental risks for attention-deficit hyperactivity disorder (ADHD): The potential role of epigenetic processes in mediating susceptibility. Journal of Child Psychology and Psychiatry, 49, 1020-1030.

48.

Mohammadi

M. R.

Alavi

Mahmoudi-Gharaei

Tehrani-Doost

Shahrivar

Saadat

(2008). Prevalence of psychiatric disorders amongst adolescents in Tehran. Iran Journal of Psychiatry, 3, 100-104.

49.

National Bureau of Statistics. (2006). Federal Republic of Nigeria 2006 population census. Official gazette (FGP 71/52007/2500(OL24): Legal Notice on Publication of the details of the Breakdown of the National and State Provisional 2006 Census. Retrieved from http://www.nigerianstat.gov.ng/

50.

Ndukuba

A. C.

Odinka

P. C.

Muomah

R. C.

Obindo

J. T.

Omigbodun

O. O.

(2014). ADHD among rural southeastern Nigerian primary school children: Prevalence and psychosocial factors. Journal of Attention Disorders. Advance online publication. doi:10.1177/1087054714543367

51.

Nolan

E. E.

Gadow

K. D.

Sprafkin

(2001). Teacher reports of DSM-IV ADHD, ODD, and CD symptoms in school children. Journal of American Academy of Child & Adolescent Psychiatry, 40, 241-249.

52.

Parvaresh

Ziaaddini

Kheradmond

Bayati

(2010). Attention deficit hyperactivity disorder (ADHD) and conduct disorder in children of drug dependent parents. Journal of Addiction Health, 2, 89-94.

53.

Pearson. (2007). Development of Raven’s Standard Progressive Matrices (SPM). San Antonio, TX: Author.

54.

Pedersen

S. J.

Heath

Surbury

P. R.

(2007). Lower extremity response time performance in boys with ADHD. Journal of Attention Disorder, 10, 343-349.

55.

Peeple

E. E.

Searls

D. T.

Wellingham-Jones

(1995). Attention-deficit hyperactivity disorder: A longitudinal case study of handwriting characteristics. Perception and Motor Skills, 81, 1243-1252.

56.

Pineda

D. A.

Lopera

Henao

G. C.

Palacio

J. D.

Castellanos

F. X.

(2001). Confirmation of the high prevalence of attention deficit disorder in a Colombian community. Review of Neurology, 32, 217-222.

57.

Pineda

D. A.

Lopera

Palacio

J. D.

Ramirez

Henao

G. C.

(2003). Prevalence estimates of attention-deficit/hyperactivity disorder: Differential diagnosis and comorbidities in Colombian sample. International Journal of Neuroscience, 113(91), 49-71.

58.

Polanczyk

de Lima

M. S.

Horta

B. L.

Biederman

Rohde

L. A.

(2007). The worldwide prevalence of ADHD: A systematic review and metaregression analysis. American Journal of Psychiatry, 164, 942-948.

59.

Prithivirajh

Edwards

S. D.

(2011). An evolution of a stress management intervention for parents of children with attention deficit/hyperactivity disorder. Inkanyiso Journal of Humanities and Social Science, 3, 32-37.

60.

Racine

M. B.

Majnemer

Shevell

Snider

(2008). Handwriting performance in children with attention deficit hyperactivity disorder (ADHD). Journal of Child Neurology, 23, 399-406.

61.

Ramsey

J. R.

Rostain

A. L.

(2008). Adult ADHD research: Current status amd future directions. Journal of Attention Disorders, 11(6), 624-627.

62.

Ramtekkar

U. P.

Reiersen

A. M.

Todrov

A. A.

Todd

R. D.

(2010). Sex and age differences in attention-deficit/hyperactivity disorder symptoms and diagnoses: Implications for DSM-IV and ICD-11. Journal of American Academy of Child & Adolescent Psychiatry, 49, 217-228.

63.

Rappley

M. D.

(2005). Attention-deficit-hyperactivity disorder. New England Journal of Medicine, 356, 165-173.

64.

Raven

J. C.

Court

H. J.

(2000). Raven manual: Section 3, standard progressive matrices, including the parallel and plus versions, 2000 edition. Oxford, UK: Oxford Psychologists Press.

65.

Ruchkin

Lorberg

Koposov

Schwab-Stone

Sukhodolsky

D. G.

(2008). ADHD symptoms and associated psychopathology in a community sample of adolescent from the European North of Russian. Journal of Attention Disorders, 12, 54-63.

66.

St. Sauver

J. L.

Barbaresi

W. J.

Katusic

S. K.

Colligan

R. C.

Weaver

A. L.

Jacobsen

S. J

. (2004). Early life risk factors for attention-deficit/hyperactivity disorder: A population-based cohort study. Mayo Clinical Practice, 79, 1124-1131.

67.

Schaffer

Gould

M. S.

Brasic

Ambrosini

Fisher

Bird

Aluwahlia

S. A.

(1983). Children’s global assessment scale (CGAS). Archives of General Psychiatry, 40, 1228-1231.

68.

Schmitz

Cadore

Paczko

Kipper

Chaves

Rohde

L. A.

Knijnik

(2002). Neuropsychological performance in DSM-IV ADHD Subtypes: An exploratory study with untreated adolescents. Canadian Journal of Psychiatry, 47, 863-869.

69.

Shafer

S. Q.

Shaffer

O’Connor

P. A.

Stokman

C. J.

(1983). Hard thoughts on neurological soft signs. In Rutter

(Ed.), Developmental neuropsychiatry (pp. 133-143). New York, NY: Guilford Press.

70.

Shahrivar

Kousha

Moallemi

Tehrani-Doost

Alaghband-Rad

(2010). The reliability and validity of Kiddies–Schedule for Affective Disorders and Schizophrenia–Present and Lifetime Version–Persian Version. Child and Adolescent Mental Health, 15, 97-102.

71.

Shooshtary

M. H.

Chimeh

Najafi

Mohammadi

M. R.

Yousefi-Nouaie

Rahimi-Mvaghae

(2010). The prevalence of attention deficit hyperactivity disorder in Iran: A systematic review. Iran Journal of Psychiatry, 5, 88-92.

72.

Simon

Czobor

Balint

Meszaros

Bitter

(2009). Prevalence and correlates of adult attention deficit hyperactivity disorder: Meta-analysis. British Journal of Psychiatry, 194, 204-211.

73.

Skounti

Betts

(2011, May 26-29). Prevalence of ADHD subtypes worldwide. Abstract from 3rd International Congress on ADHD: From Childhood to Adult Disease, Berlin, Germany.

74.

Skounti

Philalithis

Galanaki

(2007). Variations in prevalence of attention deficit hyperactivity disorder. European Journal of Pediatrics, 166, 117-123.

75.

Spencer

T. J.

Biederman

Mick

(2007). Attention-deficit/hyperactivity disorder: Diagnosis, life span, comorbidity, and neurobiology. Journal of Paediatric Psychology, 32, 631-642.

76.

SPSS. (2006). SPSS 15.0.1 Command Syntax Reference. Chicago, IL: Author.

77.

Trani

M. D.

Casini

M. P.

Capuzzo

Gentile

Bianco

Menghini

Vicari

(2011). Executive and intellectual functions in attention-deficit/hyperactivity disorder with and without comorbidity. Brain and Development, 33, 462-469.

78.

Tunde-Ayinmode

Adegunloye

Ayinmode

Abiodun

(2012). Psychiatric disorders in children attending a Nigerian primary care unit: Functional impairment and risk factors. Child and Adolescent Psychiatry and Mental Health, 6, 28. doi:10.1186/1753-2000-6-28.

79.

Vasconcelos

M. M.

Werner

Jr Malheiros

A. F.

Lima

D. F.

Santos

I. O.

Barbosa

J. B.

(2003). Attention deficit/hyperactivity disorder prevalence in an inner city elementary school. Arquivos de Neuro-psiquiatria, 61, 67-73.

80.

Walker

Venter

van der Walt

(2011). Prevalence of attention deficit hyperactivity disorder (ADHD): Symptomatology and psychiatric comorbidity among adolescents diagnosed with ADHD in childhood. South African Journal of Psychiatry, 17, 2-28.

81.

Zentall

S. S.

(2005). Theory- and evidence-based strategies for children with attentional problems. Psychology Schools, 42, 821-836.

82.

Zentall

S. S.

Kuester

D. A.

Craig

B. A.

(2011). Social behaviour in co-operative groups: Students at-risk for ADHD and their peers. Journal of Educational Research, 104, 24-41.