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Prevalence of attention deficit hyperactivity disorder among primary school children in Cachar, Assam, North-East India

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Background: Attention deficit hyperactivity disorder (ADHD) is characterised by a pattern of diminished sustained attention and higher levels of impulsivity in a child or adolescent than expected for someone of that age and developmental level. Aims: Our study aims at the following- (i) To identify the prevalence of ADHD among children in primary schools. (ii) To identify the gender difference, age distribution, and distribution of socioeconomic class in the prevalence of ADHD. (iii) To identify the subtypes of ADHD. (iv) To assess the presence of any comorbid illnesses and to assess the association of various comorbidities with the subtypes of ADHD. Materials and methods: Three hundred children aged between six and 11 years were selected from two schools in Cachar district, Assam, India. The presence of ADHD was assessed by using the Conner’s Abbreviated Rating Scale (CARS) given to parents and teachers, and then reassessment for typing of ADHD and any comorbidies were done by the Vanderbilt scale. Statistical analysis: Statistical analysis was done by Graph Pad prism for windows version 6.01 and Statistical Package for the Social Sciences (SPSSv22). Descriptive statistics was used to summarise the data. Results: The prevalence of ADHD among primary school children was found to be 12.66%. Prevalence was found to be higher among the boys, those belonging to lower middle socioeconomic class, and in the age groups of seven and eight years. Conclusion: The prevalence of ADHD is high among primary school children.
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among primary school children in Cachar, Assam,
North-East India
Prosenjit Ghosh1,
Hasina Anjuman Choudhury2,
Robin Victor3
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Correspondence: Dr. Hasina Anjuman
Choudhury, Post Graduate Trainee, Department
of Psychiatry, Room no. 201, New PG Hostel,
Silchar Medical College & Hospital, Ghungoor,
Silchar-788014, Assam, India. anjuman25aug@
UHGLɣPDLOFRP
Received: 19 March 2017
Revised: 1 November 2017
Accepted: 12 November 2017
Epub: 6 July 2018
DOI: 10.5958/2394-2061.2018.00025.3
Abstract
Background$WWHQWLRQGH¿FLW K\SHUDFWLYLW\GLVRUGHU $'+'LV FKDUDFWHULVHGE\D
pattern of diminished sustained attention and higher levels of impulsivity in a child
or adolescent than expected for someone of that age and developmental level.
Aims: Our study aims at the following- (i) To identify the prevalence of ADHD among
children in primary schools. (ii) To identify the gender difference, age distribution,
and distribution of socioeconomic class in the prevalence of ADHD. (iii) To identify
the subtypes of ADHD. (iv) To assess the presence of any comorbid illnesses and
to assess the association of various comorbidities with the subtypes of ADHD.
Materials and methods: Three hundred children aged between six and 11 years
were selected from two schools in Cachar district, Assam, India. The presence
of ADHD was assessed by using the Conner’s Abbreviated Rating Scale (CARS)
given to parents and teachers, and then reassessment for typing of ADHD and any
comorbidies were done by the Vanderbilt scale. Statistical analysis: Statistical
analysis was done by Graph Pad prism for windows version 6.01 and Statistical
Package for the Social Sciences (SPSSv22). Descriptive statistics was used to
summarise the data. Results: The prevalence of ADHD among primary school
children was found to be 12.66%. Prevalence was found to be higher among the
boys, those belonging to lower middle socioeconomic class, and in the age groups
of seven and eight years. Conclusion: The prevalence of ADHD is high among
primary school children.
Keywords: Parents. School Teachers. Comorbidity.
INTRODUCTION
Attention decit hyperactivity disorder (ADHD) is a
neuropsychiatric condition aecting pre-schoolers, children
and adolescents, and even adults all over the world. In ADHD,
“there is a persistent pattern of inattention, hyperactivity-
impulsivity, or both”.[1] Such behaviours are also age-
inappropriate. ere are three subtypes of ADHD which are
usually of inattention, hyperactive-impulsive, and combined
inattentive/hyperactive impulsive.[2] It is also the most
frequently occurring mental health disorder in children.[3,4]
Estimated prevalence is found to be in between four to eight
per cent.[5] It is well-known that ADHD is associated with
psychiatric and developmental disorders such as oppositional
deant disorder (ODD), conduct disorder, anxiety disorders,
depressive disorders, and speech and learning disorders.[2]
In children with ADHD, there is signicant limitation in
functioning across dierent settings. e aected children
exhibit constellation of behavioural problems depending on
the type of ADHD and the comorbidities. e parents or
caregivers of these children also face varying degrees of stress
and disharmony in their day to day life.
ere are many studies conducted worldwide to check
the prevalence of ADHD and its associated comorbidities,
but regarding Indian context, such studies are limited. While
most of the studies done so far are on clinically referred cases,
and the major drawbacks of those studies were small sample
size and failure to use a denite diagnostic criteria.
In India, the prevalence of ADHD has been reported
from 1.6 to 17.9%.[6,7] While school based study on children
between the ages of six to 11 years from India (Kerala)
reported the prevalence as 11.3% with the highest prevalence
between nine to ten years.[8] Another study reveals a wide
range of prevalence rates between two and 17%.[9] A similar
study done in North India on children between the ages of
ten to 15years reported the prevalence to be six per cent.[10]
ADHD is characterised by heterogeneity and involves various
other comorbid psychiatric disorders. International studies
have shown comorbidities ranging from 60-100%. e most
common comorbidity in children with ADHD reported
in these studies has been ODD, ranging from 50-60%.
ODD is reported to be higher in the combined subtype and
signicantly lower in inattentive subtype.[11]
ISSN 2394 - 2053 (Print)
ISSN 2394 - 2061 (Online)
RNI: ASSENG/2016/70661
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OJPAS® | Volume 9 | Issue 2 | July-December 2018 131
In an Indian study, the conditions associated with ADHD
were found to be poor academic performance, reading
diculty, writing diculty, behavioural diculties, and poor
social behaviour.[8] Apart from these, another Western study,
revealed that comorbid rates of ADHD and anxiety disorders
was approximately 25% in both community and clinical
samples[11]. Some other comorbidities associated with ADHD
were conduct disorder, bipolar aective disorder, major
depressive disorder, communication disorder, substance use
disorder, obsessive compulsive disorder (OCD), elimination
disorder, social phobia, and separation anxiety disorder.[12]
Another study reported that ADHD was also associated with
comorbidities, especially disruptive behaviour disorders.[9]
Our study aims at selecting primary school going
children of Cachar district, Assam, India and adjoining areas,
and to nd out the prevalence of ADHD in this part of the
country. To the best of our knowledge, this study would be
rst of its kind in this area.
Aims and objectives
(i) To identify the prevalence of ADHD among children in
primary schools.
(ii) To identify the gender dierence, age distribution, and
distribution of socioeconomic class in the prevalence of
ADHD.
(iii) To identify the subtypes of ADHD.
(iv) To assess the presence of any comorbid illnesses and to
assess the association of various comorbidities with the
subtypes of ADHD.
MATERIALS AND METHODS
Sample
e sample consisted a total of 400 primary school going
students between six to 11 years of age selected randomly
from two dierent schools in Cachar district, Assam, India.
Inclusion criteria
1. Students from both the sexes were included.
2. Every h student according to the roll number was
selected to avoid selection bias as far as possible.
Exclusion criteria
1. Students below the age of six years and above 11years.
2. Students having any other diagnosed medical illness.
3. ose students whose parents did not give consent
to participate in the study or students who could not
reproduce the proforma.
Tools
1. Conner’s Abbreviated Rating Scale (CARS): is
is a rating scale that consists of several behavioural
parameters for the diagnosis of ADHD. is was rated
by both the parents and the teachers. In this scale, those
who scored above 15 by both teachers and parents are
levelled to have ADHD features.[13]
2. Vanderbilt ADHD Rating Scale (VADRS): is scale has
two versions- one for the teacher (VADTRS) and the
other for parent (VADPRS). ese scales are meant for
conrmation of ADHD as well as for typing of ADHD
and also to screen other comorbid conditions associated
with ADHD, like ODD, conduct disorder, anxiety, mood
disorders, or any other learning disabilities.
VADRS are based on the h edition of the Diagnostic
and Statistical Manual of Mental Disorders (DSM-5) criteria
for ADHD diagnosis and include versions specic for parents
and teachers. is rating scales eectively distinguish between
children with and without ADHD and also assess accurately
the subtypes of ADHD.
Parent rating scales (VADPRS)
e DSM-5 criteria is adapted for the home setting and it
is a 55-question rating scale. In addition, the VADPRS also
includes screening questions for conduct disorder, ODD,
anxiety, and depression.
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e DSM-5 criteria is adapted for the school setting and it is
a 43-question rating scale. e teacher version also includes
screening for mood and anxiety symptoms, learning disability,
and rating of the child’s classroom performance.
e illustration of psychometric properties and clinical
utility of both the versions have been done in several studies
ever since the introduction of the teacher rating scale in
1998[14] and the parent rating scale in 2003.[15] ese were
further reconrmed via recent clinical studies in 2013.[16,17]
Recent studies have also reported that VADPRS may be helpful
in assessing children who meet or do not meet diagnostic
criteria for those comorbidities like conduct disorder, ODD,
anxiety and depression.[18]
3. Prasad’s classication of social class:[19] is scale
was developed by B.G. Prasad, which is an income based scale
and so it needs to be constantly updated. It helps in measuring
the socioeconomic class of an individual in community. is
scale can be used on both urban and rural population, and it
is based on the per capita income of the individual. ere are
ve social classes as mentioned below:
I. upper class
II. upper middle class
III. middle class
IV. lower middle class
V. lower class
Methodology
Before conducting the study, approval from the Institutional
Human Ethics Committee (IHEC) was obtained. is was a
cross-sectional study involving 400 primary school children
aged between six and 11 years (rst to fourth standard)
selected on a random basis from two dierent schools in
Cachar district. At the outset, permission from the school
authority was obtained. A written informed consent form
was given to the parents through the children. Out of 400
students, only 300 students nally participated in the study
either because some of their parents did not give consent and
some of them could not reproduce the interview sheet. is
sample consisted of 177 boys and 123girls.
Ghosh et al.
132 OJPAS® | Volume 9 | Issue 2 | July-December 2018
e sample was also broadly divided into two groups
based on their socioeconomic status:
(a) 150 children selected from a government-aided school
with Bengali as its medium of instruction, belonging to
either lower or middle socioeconomic status.
(b) 150 children selected from a dierent school, which
followed English as their medium of instruction,
belonging to middle or higher socioeconomic status.
is was done to avoid selection bias. All the tools were
translated into Bengali and then translated back to
English for ensuring correct translation. is was done
for the convenience of parents and teachers. e ow
chart below schematically represents the methodology of
sample selection (Figure1).
CARS was given to the teachers and to the parents of the
children. Based on the score obtained as per both the teachers
and parents rating, presence of ADHD was identied. For the
children identied in the study as having ADHD, VADTRS
and VADPRS were given to the teachers and their parents to
identify the subtypes of ADHD, and to screen some comorbid
conditions like ODD, conduct disorder, learning disorder,
anxiety/depression, and impairment in classroom behaviour
performance. Both the scales (CARS and VADRS) were given
to both parents and teachers to compare the teachers and
parent’s rating scores.
Statistical analysis
Appropriate data was collected, tabulated, and statistical
analysis was done by GraphPad prism for windows
version6.01 and Statistical Package for the Social Sciences
(SPSSv22) (SPSS Inc., Chicago, USA).[20] Descriptive
statistics was used to summarise the data. Fisher’s Exact test
and Pearsons Chi-square test were applied to nd out the
p-value and the statistical signicance, wherever necessary.
e signicance was determined at p<0.05.
RESULTS
Prevalence of ADHD
e case records of 300 children who have met the inclusion
and exclusion criteria were analysed. e majority were boys
(n=177) and others were girls (n=123). Out of 300 students,
38 students were found to have ADHD based on CARS
scoring as per both teachers and parents, so prevalence of
ADHD among primary school going children in this region
was found to be 12.66%.
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distribution of socioeconomic class of ADHD
ADHD was more prevalent in the boys than in the girls. Total
number of boys selected were 177, of which 32 had ADHD. So
prevalence of ADHD in the boys was 18.07%. Total number
of girls selected were 123, of which six had ADHD. Hence
prevalence of ADHD in the girls was 4.87%. In total, among
the 38 children identied as having ADHD, 84.21% (32)
were boys while 15.79% (six) were girls. e boy: girl ratio
being5:1.
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Children with ADHD were also stratied on the basis of their
age into six groups. e prevalence rate in each age group
was identied and shown in Figure 2. e children were
predominantly between the age groups of seven and eight
years.
ADHD and socioeconomic status
In our study, out of 300 children, 164 children belonged to
higher socioeconomic class, 134 children belonged to middle
socioeconomic class and only two children belonged to lower
socioeconomic class. e middle class was again divided into
lower middle (57), middle (56), and upper middle class (21).
e majority of the ADHD patients were found belonging
to lower middle socioeconomic class (21.05%), followed by
upper middle (19.04%), middle (10.71%), and lastly in higher
class (9.75%). However, on applying Student’s paired t test,
this dierence in prevalence among dierent socioeconomic
class, was found to be statistically not signicant (p=0.1234).
Subtypes of ADHD
e subtypes of ADHD among the school children were
assessed as per VADRS. ere are three subtypes of ADHD,
namely ADHD inattentive type (ADHD-IT), ADHD
hyperactive type (ADHD-HT), and ADHD combined type
(ADHD-CT) which includes the features of both inattentive
type and hyperactive type. e most common subtype in our
study groups was combined (65.79%) followed by inattentive
(23.69%) and then hyperactive (10.52%).
Comorbidities with ADHD
Out of 38 ADHD children, 34 were found to have one or
more than one comorbidities at a time, while remaining
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OJPAS® | Volume 9 | Issue 2 | July-December 2018 133
four children do not have any associated problem, i.e.84.5%
reported the presence of one or more than one comorbidities.
As per VADRS, we attempted to assess the other comorbidities
with ADHD. e presence of comorbidities that could be
screened with the help of this scale were: ODD/conduct
disorder, anxiety/depression, learning disability, and
impairment in classroom behaviour performance. e most
common comorbidity in our study was the ODD/conduct
disorder (76.31%), followed closely by learning disability
(65.78%), impairment in classroom behaviour performance
(50%), and least prevalent was anxiety/depression (18.42%)
(Table1).
In our study, when the individual comorbidities were
analysed against gender, using Fisher’s Exact test, anxiety/
depressive disorder was found to be more in girl children
with ADHD and that was statistically signicant. Rest of the
comorbidities were more in boy children with ADHD but
those were statistically not signicant (Table2).
Subtypes of ADHD and associated
comorbidities
As we can see, 96% of combined type, 75% of hyperactive
type, and 22.22% of inattentive type had ODD/conduct
disorder. While 55.5% of inattentive type, 25% of hyperactive
type, and only four per cent of combined type had anxiety/
depression. While learning disability was most common in
combined type (72%), followed by inattentive type (66.6%)
and hyperactive type (25%). Also, 56% of combined type,
50% of hyperactive type, and 33.3% of inattentive type had
impairment in classroom behaviour performance (Table3).
us, when overall comorbidities were analysed
according to the subtypes, an association was found.
ereaer, individual comorbidities against subtype were
analysed and it was found that ODD to be signicantly
more associated with the combined type (96%) and anxiety/
depression to be signicantly more associated with the
inattentive type of ADHD (55.55%) while learning disability
and classroom behaviour performance were more common
with the combined type (72% and 56% respectively) (Table4).
DISCUSSION
e prevalence of ADHD in the present study was 12.66%
which is in accordance with other studies conducted in
developing country like India.[8] is is consistent with that
of several studies which showed a wide range of prevalence
rates between two per cent and 17%.[6,7] e boy to girl
ratio in the current study was found to be 5:1, which is also
in accordance with another study that show that ADHD is
more common in boys than in girls.[8] is result of gender
dierence in the present study is similar to that of earlier
studies, which reports the ratio ranging from 10:1 in clinically
referred sample and 3:1 in a community sample.[21] In our
study, ADHD was predominantly found in the age groups
of seven and eight years. is nding is consistent with a
previous study which have reported increased prevalence of
ADHD among children aged seven years or lesser.[22]
In the current study, CARS scoring by both teachers
and parents were found to be almost similar and only those
which have less discrepancy were chosen. is study also
revealed a signicant variation in the prevalence of ADHD
between the children from higher and those from the middle
socioeconomic status. Majority of the students belonged
to a lower middle socioeconomic strata (21.05%). Several
studies showed that ADHD is more common in lower
socioeconomic strata,[8] which is dierent from the ndings
in the current study. is is probably because in the current
study, the majority of the students belonged to middle or
higher socioeconomic strata and only 0.66% belonged to
lower socioeconomic strata. Although in current study, the
ndings were statistically not signicant, the fact that the
socioeconomic background is one of the important risk
factors for the development of ADHD is further strengthened
by the reports in the present study.[23]
When the subtypes were analysed, the most common
subtype was found to be the combined type (65.79%) followed
by inattentive type (23.69%) and hyperactive/impulsive type
(10.52%), which was in accordance with other studies.[24]
ADHD is a condition that is almost always associated with
one or other comorbidities. Studies from India have reported
the rate of comorbidities in children with ADHD to be in the
range of 40-86.3%.[12] In our study, the rate of comorbidities
in ADHD children was found to be 84.21%, which have either
one or more than one comorbidities.
ere are several studies, wherein many other
comorbidities such as major depressive disorder, borderline
Table 1: Percentage prevalence of various types of comorbidities in our study group
Comorbidities Boy (n=32) Girl (n=6) Total Prevalence % (n=38)
2SSRVLWLRQDOGH¿DQWGLVRUGHUFRQGXFWGLVRUGHU 26 3 29 76.31
Anxiety/depression 2 5 7 18.42
Learning disability 22 3 25 65.78
Classroom behaviour performance 17 2 19 50
Figure 2:'LVWULEXWLRQRI DWWHQWLRQGH¿FLWK\SHUDFWLYLW\GLVRUGHU$'+'DPRQJ
different age groups.
Ghosh et al.
134 OJPAS® | Volume 9 | Issue 2 | July-December 2018
intellectual functioning, seizures, enuresis, disorders of
written expression and mathematics, etc. were assessed. In
India, a study on a clinic based sample in 2000 and later in
2013 in a community based sample, dierent comorbidities
like academic diculties, diculties related to peers, and
behavioural problems were mentioned.[8,22] But in those
studies, despite presence of diculties that were highlighted,
no clinical diagnosis of these comorbidities was made. In the
present study also, only four comorbidities were screened
and no clinical diagnosis was made. e four comorbidities
were ODD/conduct disorder, anxiety/depression, learning
disorder, and impairment in classroom hehaviour
performance, which were assessed. e most common
comorbidity associated with ADHD was found to be ODD/
conduct disorder (76.3%), followed by learning disability
(65.78%), then impaired classroom hehaviour performance
(50%), and anxiety/depression (18.42%). In one study, the
most common comorbid condition was found to be ODD
followed by anxiety and reading disorder.[24] us, our study
is also in accordance to the previous ndings. e results
of international studies reviewed by Biederman et al.,[11]
reported 30-50% of ADHD cases to be accompanied by
conduct disorder, 15-75% by mood disorders, and 25%
by anxiety disorders. Palaniappan et al.,[12] in their study
conducted structured interviews in children with ADHD and
found ODD as the most common disorder (25%) followed
by anxiety disorders, like obsessive compulsive disorder
(OCD0(8.3%), separation anxiety (1.7%), and social phobia
(1.7%). So, our study is similar to the ndings by both
international and Indian studies.
Besides, many studies have revealed that the development
of antisocial personality is also comorbid with ADHD.
Diagnosing such multifactorial neuropsychiatric condition
in the children and intervening at the earliest will denitely
help the children improve their academic and behaviour
performance, and prevent the development of numerous
other comorbid conditions.
is study, however, did not show any kind of statistically
signicant dierence in the subtypes of ADHD among boys
and girls. Astudy by Biederman et al.[21] has shown that
girls were more likely to have predominantly inattentive
type of ADHD than boys. However, of the four associated
comorbidities, anxiety/depression was found to be more
among girls than boys and it was statistically signicant.
When comorbidities were studied according to subtype,
majority of studies have found the combined type to have
higher ratio of comorbid disorders than the other two types
of ADHD. Our study also showed presence of ODD/conduct
disorder to be more associated with combined subtype of
ADHD while anxiety/depression to be more associated with
inattentive subtype of ADHD, and these were statistically
signicant. Moreover, learning disability and impaired
classroom behaviour performance were more common
with the combined subtype; but, those were statistically not
signicant. is is not in accordance with a study which
revealed disruptive behaviours like conduct disorder and
ODD were higher in the hyperactive group.[7]
Limitations of our study
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of both ADHD and the associated comorbidities.
Table 2: Distribution of various types of comorbidities across the
gender
Comorbidities Boy (n=32) Girl (n=6) p-value
2SSRVLWLRQDOGH¿DQW
disorder/conduct
disorder
26 3 0.1311, NS
Anxiety/depression 2 5 0.0002, S
Learning disability 22 3 0.3924, NS
Classroom behaviour
performance
17 2 0.6599, NS
161RWVLJQL¿FDQW66LJQL¿FDQW
Table 3: Subtypes of ADHD and associated comorbidities
Comorbidities Subtypes of ADHD
ADHD-CT (n=25) ADHT-IT (n=9) ADHD-HT (n=4)
2SSRVLWLRQDOGH¿DQWW\SHFRQGXFWGLVRUGHU 24 (96%) 2 (22.22%) 3 (75%)
Anxiety/depression 1 (4%) 5 (55.55%) 1 (25%)
Learning disability 18 (72%) 6 (66.66%) 1 (25%)
Classroom behaviour performance 14 (56%) 3 (33.33%) 2 (50%)
$'+'$WWHQWLRQGH¿FLWK\SHUDFWLYLW\GLVRUGHU&7&RPELQHGW\SH,7,QDWWHQWLYHW\SH+7+\SHUDFWLYHW\SH
Table 4: Association of comorbidities according to subtypes of ADHD
Comorbidities Subtypes of ADHD Chi-square df p-value
ADHD-CT ADHD-IT ADHD-HT
2SSRVLWLRQDOGH¿DQWGLVRUGHUFRQGXFWGLVRUGHU 24 (96%) 2 (22.22%) 3 (75%) 16.903 6 0.0096, S
Anxiety/depression 1 (4%) 5 (55.55%) 1 (25%)
Learning disability 18 (72%) 6 (66.66%) 1 (25%)
Classroom behaviour performance 14 (56%) 3 (33.33%) 2 (50%)
$'+'$WWHQWLRQGH¿FLWK\SHUDFWLYLW\GLVRUGHU&7&RPELQHGW\SH,7,QDWWHQWLYHW\SH+7+\SHUDFWLYHW\SHGI'HJUHHRIIUHHGRP66LJQL¿FDQW161RW
VLJQL¿FDQW
$WWHQWLRQGH¿FLWK\SHUDFWLYLW\GLVRUGHU
OJPAS® | Volume 9 | Issue 2 | July-December 2018 135
t ćJTJTBDSPTTTFDUJPOBMTUVEZBOEOPUBMPOHJUVEJOBMPOF
t /P GPMMPXVQ XBT EPOF PG UIF TUVEFOUT XIP XFSF
diagnosed with ADHD and its comorbidities.
Strength of the study
t ćF NBKPS MJNJUBUJPOT JO UIF QSFWJPVT TUVEJFT BSF UIBU
the identication of ADHD was made from samples
through clinically referred cases. Our study has been
done through community sampling and it has provided
us a more uniform view about the prevalence of ADHD
in this area.
t 4JODFDIJMESFOXJUI UIJT EJTPSEFSTQFOEBMBSHF BNPVOU
of time at school; school history and teachers’ reports
are important in evaluating the symptoms and forming
a diagnosis.
To the best of our knowledge, this study is one which
is rst of its kind in this region, and the ndings are almost
similar with most studies conducted in a similar age group
and other parts of the country. e high prevalence of this
multifactorial childhood disorder, in which poverty may
be a risk factor, the high rate of comorbidities, multiple
comorbidities, and the dierence in comorbidities according
to gender and subtype, and thereby making the diagnosis a
more complex in nature and further also adds to the existing
literature.
Conclusion
We conclude that ADHD is one of the highly prevalent
neuropsychiatric disorders in childhood and is associated
with clinically signicant impairment in multiple aspects
of life. For early diagnosis and handling the illness better, it
is essential to design an intervention programme, wherein
all the areas of impairment in children with ADHD can
be identied in details. Further, methodological rigorous
studies, both longitudinal and cross-sectional, are supposed
to be done to understand this disabling childhood disorder.
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... The subjects in the present study comprised only of male children and adolescents. This reflects the gender distribution of health-seeking patterns of ADHD in the country where it is seen that the majority (75%-80%) of children and adolescents seeking treatment for ADHD are males [6,8]. ...
... Combined type of ADHD was the predominant subtype of ADHD in our study. This is in concordance with findings from various studies done in India and elsewhere [6,8,9]. ...
... [6] and 55% [7], respectively. A study by Ghosh et al. [8] found the rate of comorbidities in ADHD children to be much higher at 84.21%. The rate of psychiatric comorbidities in international studies range between 56% -88% [11,12]. ...
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... However, the prevalence estimated in number of studies is limited to certain geographical location and wide variability of the prevalence is also observed in the studies. For example, the prevalence in individuals aged between 6 and 18 years in Kashmir was 4.31%, [11] whereas in individuals aged between 6 and 12 years in Bangalore, it was 2.3%, [12] in individuals aged between 6 and 18 years in Odisha was 3.66%, [13] in individuals aged between 10 and 16 years in New Delhi was 6.4%, [14] in individuals aged between 6 and 11 years in Assam was 12.66%, [15] and in individuals aged between 8 and 11 years in Tamil Nadu was 8.8%. [16] Therefore, it is highly significant to analyze all the available data in an integrated manner so that a national prevalence of the disease burden can be estimated. ...
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... [5,6] Again, a study conducted in Assam shows that the prevalence of childhood behavioural problem, i.e. attention-deficit/hyperactivity disorder (ADHD) is 12.66% among children aged six to 11 years. [7] The high prevalence of childhood mental health problems demands their early identification and intervention. ...
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To evaluate the clinical utility of the cutoff recommendations for the Vanderbilt ADHD Diagnostic Parent Rating Scale (VADPRS) comorbidity screening scales provided by the American Academy of Pediatrics/National Initiative for Children's Healthcare Quality and to examine alternative cutoff strategies for identifying and ruling out disorders commonly comorbid with attention-deficit/hyperactivity disorder. A sample of 215 children (142 with attention-deficit/hyperactivity disorder), ages 7 to 11 years, participated in the study. Parents completed the VADPRS and were administered a diagnostic interview to establish diagnoses of oppositional defiant disorder (ODD), conduct disorder (CD), anxiety, and depression. The clinical utility of the VADPRS comorbidity screening scales were examined. ResuLTS: The recommended American Academy of Pediatrics/National Initiative for Children's Healthcare Quality cutoff strategies did not have adequate clinical utility for identifying or ruling out comorbidities, with the exception of the VADPRS ODD cutoff strategy, which reached adequate levels for ruling out a diagnosis of ODD. An alternative cutoff approach using total sum scores was superior to the recommended cutoff strategies across all diagnoses in terms of ruling out a diagnosis, and this was particularly evident for anxiety/depression. Several individual items on the ODD and CD scales also had acceptable clinical utility for ruling in diagnoses. The VADPRS comorbidity screening scales may be helpful in determining which children likely do not meet diagnostic criteria for ODD, CD, anxiety, or depression. This study suggests that using a total sum score provides the greatest clinical utility for each of these comorbidities and demonstrates the need for further research examining the use of dimensional assessment strategies in diagnostic decision making.
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Attention deficit hyperactivity disorder is a heterogeneous disorder of unknown etiology. Little is known about the comorbidity of this disorder with disorders other than conduct. Therefore, the authors made a systematic search of the psychiatric and psychological literature for empirical studies dealing with the comorbidity of attention deficit hyperactivity disorder with other disorders. The search terms included hyperactivity, hyperkinesis, attention deficit disorder, and attention deficit hyperactivity disorder, cross-referenced with antisocial disorder (aggression, conduct disorder, antisocial disorder), depression (depression, mania, depressive disorder, bipolar), anxiety (anxiety disorder, anxiety), learning problems (learning, learning disability, academic achievement), substance abuse (alcoholism, drug abuse), mental retardation, and Tourette's disorder. The literature supports considerable comorbidity of attention deficit hyperactivity disorder with conduct disorder, oppositional defiant disorder, mood disorders, anxiety disorders, learning disabilities, and other disorders, such as mental retardation, Tourette's syndrome, and borderline personality disorder. Subgroups of children with attention deficit hyperactivity disorder might be delineated on the basis of the disorder's comorbidity with other disorders. These subgroups may have differing risk factors, clinical courses, and pharmacological responses. Thus, their proper identification may lead to refinements in preventive and treatment strategies. Investigation of these issues should help to clarify the etiology, course, and outcome of attention deficit hyperactivity disorder.
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These practice parameters review the literature on children, adolescents, and adults with attention-deficit/hyperactivity disorder (ADHD). There are three types of ADHD: predominantly inattentive, predominantly hyperactive-impulsive, and combined. Together, they occur in as many as 10% of boys and 5% of girls of elementary school age. Prevalence declines with age, although up to 65% of hyperactive children are still symptomatic as adults. Frequency in adults is estimated to be 2% to 7%. Assessment includes clinical interviews and standardized rating scales from parents and teachers. Testing of intelligence and academic achievement usually are required. Comorbidity is common. The cornerstones of treatment are support and education of parents, appropriate school placement, and pharmacology. The primary medications are psychostimulants, but antidepressants and alpha-adrenergic agonists are used in special circumstances. Other treatments such as behavior modification, school consultation, family therapy, and group therapy address remaining symptoms.
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This study examines the psychometric properties of the Vanderbilt AD/HD Diagnostic Teacher Rating Scale (VADTRS) and provides preliminary normative data from a large, geographically defined population. The VADTRS consists of the complete list of DSM-IV AD/HD symptoms, a screen for other disruptive behavior disorders, anxiety and depression, and ratings of academic and classroom behavior performance. Teachers in one suburban county completed the scale for their students during 2 consecutive years. Statistical methods included (a) exploratory and confirmatory latent variable analyses of item data, (b) evaluation of the internal consistency of the latent dimensions, (c) evaluation of latent structure concordance between school year samples, and (d) preliminary evaluation of criterion-related validity. The instrument comprises four behavioral dimensions and two performance dimensions. The behavioral dimensions were concordant between school years and were consistent with a priori DSM-IV diagnostic criteria. Correlations between latent dimensions and relevant, known disorders or problems varied from .25 to .66.
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To identify the psychosocial and clinical correlates of attention-deficit hyperactivity disorder (ADHD) in a community sample of children and to examine the validity of a subclinical form of ADHD. The sample of 449 children (mean age 9.2 years, SD 1.78; 53.6% boys) participated in the second stage of a community survey. Of these, 359 (80%) screened positive at stage 1. On the basis of a structured diagnostic interview with a parent, children were classified into 1 of 3 mutually exclusive groups: ADHD (n = 89), subthreshold ADHD (n = 100), and non-ADHD (n = 260). As measured by the Children's Global Assessment Scale, the ADHD group was more impaired than the subthreshold group, which was more impaired than the non-ADHD group (p < .05 for each test). Children in the ADHD group were more likely to be male, to have mothers with a history of psychiatric treatment, to have fathers with a history of excessive alcohol use, and to live in low-income families with higher levels of family dysfunction (p < .05 for all variables). A model containing male gender, family dysfunction, and low income was most predictive of ADHD status (p < .01). ADHD was also associated with psychiatric comorbidity, especially disruptive behavior disorders. These results support a dimensional approach to ADHD. More severe forms of ADHD are associated with psychosocial adversity and psychiatric comorbidity.