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Translation and usability of autism screening and diagnostic tools for Autism Spectrum
Conditions in India.
Rudra A1, Banerjee S
2, Singhal N
3, Barua M
3, Mukerji S
2, Chakrabarti B
1,4
1 School of Psychology and Clinical Language Sciences, University of Reading, UK
2 Creating Connections, Kolkata, India
3 Action for Autism, National Centre for Autism, Delhi, India
4 Autism Research Centre, University of Cambridge, UK
Banerjee S is now at University of Haifa, Haifa, Israel.
[NOTE: This is the final author-version of the manuscript, the formatted and published version is
available at the journal website at : http://onlinelibrary.wiley.com/doi/10.1002/aur.1404/abstract]
Correspondence concerning this article should be addressed to:
Dr. Bhismadev Chakrabarti
School of Psychology and Clinical Language Sciences,
University of Reading, Reading RG6 6AL, UK
Email: [email protected]
Phone: +44 118 378 5551 Fax: +44 118 378 6715
Grant sponsor: Autism Speaks
Lay Abstract:
Among all the major developing countries, India is conspicuous by the absence of an estimate of
autism prevalence. One key reason for this absence is the the lack of availability of standardized
screening and diagnostic tools (SDT) for autism in regional languages in India. To address this gap,
we translated four widely-used SDT (Social Communication Disorder Checklist, Autism Spectrum
Quotient, Social Communication Questionnaire, Autism Diagnostic Observation Schedule) into
Hindi and Bengali, two of the main regional languages (~360 million speakers) and tested their
usability. We tested these translated instruments on 170 children with and without autism, and found
that scores of children with autism were significantly and reliably different from those of control
children. This provides the first evidence that these SDTs are useable in Hindi and Bengali, and
provides the essential toolkit for future autism epidemiological research in this region.
Abstract:
There is a critical need for screening and diagnostic tools (SDT) for Autism Spectrum Conditions
(ASC) in regional languages in South Asia. To address this, we translated four widely used SDT
(Social Communication Disorder Checklist, Autism Spectrum Quotient, Social Communication
Questionnaire, Autism Diagnostic Observation Schedule) into Bengali and Hindi, two main regional
languages (~360 million speakers), and tested their usability in children with and without ASC. We
found a significant difference in scores between children with ASC (N=45 in Bengali, N=40 in
Hindi) and typically developing children (N=43 in Bengali, N=42 in Hindi) on all SDTs. These
results demonstrate that these SDT are usable in South Asia, and constitute an important resource
for epidemiology research and clinical diagnosis in the region.
Keywords: Screening; Global mental health; Translation; Cultural
Abbreviations: ASC, SCDC, TQ, SCQ, AQ-C, ADOS, SDT
ASC= Autism Spectrum Conditions
SCDC= Social Communication Disorder Checklist
SCQ= Social Communication Questionnaire
AQ-C= Autism Quotient- Children’s version
ADOS= Autism Diagnostic Observation Schedule
TQ= Ten Questions
SDT= Screening and Diagnostic Tools
In most of the developed world, autism can be identified by the age of 3 years (Howlin & Moorf,
1997) and as early as 18 months in some cases (Baird et al., 2000; Baron-Cohen et al., 1996). Early
identification of ASC is necessary for early intervention, which is associated with better outcome
(Eikeseth, 2009). Early identification relies crucially on the availability of standardised and
validated diagnostic tools. This is particularly relevant for developing countries such as India,
where there is a widespread lack of awareness about autism, and a shortage of trained professionals.
A number of screening and diagnostic tools for autism have been developed over the past decades
(Charman & Gotham, 2012; Corsello et al., 2007). However, these tools are neither available nor
characterised in local languages in South Asia, where the majority of the population is not proficient
in English. The only related measure that is internationally used and well-characterised in this
population, that is available in local languages is the WHO Ten Questions (TQ), which is a
screening measure for severe childhood disability (Zaman et al., 1990). The TQ screens for major
developmental disorders (e.g. epilepsy, blindness, hearing and speech problems, mental retardation
and motor disability), and is not specific to autism. To address this gap in the availability of
appropriate autism screening and diagnostic tools (SDT), the aim of the current study was to
translate some of the widely used SDTs into two main South Asian languages, i.e. Bengali and
Hindi. These two languages have the fifth largest number of speakers in the world (total number of
speakers estimated over 360 million people (estimates from www.ethnologue.com).
Kanner (Kanner, 1943) was the first to report that critical symptoms of autism included a lack of
communicative eye contact, delayed language development, ritualistic repetitive behaviour, and a
general deficit in social understanding. The DSM-IV and ICD-10 criteria for ASD refined these
early observations by using the following features for diagnosis: atypicalities in socialization and
communication, as well as restricted interests and repetitive behaviour (APA, 2000). These refined
criteria have been used to develop SDT for ASC, which include, among others, the Social and
Communication Questionnaire (SCQ) (Berument, Rutter, Lord, Pickles, & Bailey, 1999) and the
Autism Diagnostic and Observation Schedule (ADOS) (Lord et al., 2000).
It is generally believed that the core features of ASC are relatively universal. However, it is not
known how autistic symptoms manifest themselves differently across cultures. Cultural factors can
influence the definition and recognition of symptoms, as well as their treatment (Daley & Sigman,
2002). This may create a gap between cultures in how ASC is detected and managed. The first step
to bridging this cultural gap is to ensure that the tools used for screening and diagnoses are available
in a range of languages. This is particularly challenging for ASC, as subtle features of social-
communication behaviour are captured differently by different languages. Subtle cultural
differences may be missed due to language if the tools are used in English. E.g. in both Hindi and
Bengali (unlike in English), there is an honorific second and third person pronoun that is used to
address individuals who are senior in age or who have met for the first time. Individuals with ASC
might make the distinction between first, second or third pronoun but may show deficits in
choosing the appropriate second or third person pronoun. The formal you translates as ‘aap or
aapni’; in comparison to ‘Tu or Tui’ for a younger person and ‘Tum’ for peers and friends. Using a
diagnostic tool in English may not capture the subtleties because of a single second person pronoun
(you). Additionally, different beliefs held by health professionals regarding the time of appearance
of symptoms (some Indian professionals believe Indian children may speak their first word at 1.5
years of age and a delay in language should not be a point of concern until 3 years of age) may lead
to differential diagnosis. Cultural differences in beliefs held by health professionals such as that
mentioned above may lead to varied opinions in prioritising symptomatology for ASC (Daley &
Sigman, 2002).
A wide variability in the prevalence of autism is noted across the world (Elsabbagh et al., 2012).
(Matson & Kozlowski, 2011) suggest that these increases maybe due to changes in diagnostic
criteria over time, new assessment instruments, differences in cultural norms for identifying ASC,
inaccurate diagnoses, utilization of different research methodologies to identify prevalence
estimates or genetic differences between populations.
Specifically within Asia, estimates vary widely across time and country (China: 0.003%- 0.17%,
Japan: 0.011%-0.21% (Sun & Allison, 2010); South Korea: 2.64% (Kim et al., 2011). Sun and
Allison suggest that the heterogeneity of SDTs used in Asia contributed to this observed variability.
Eight screening instruments have been used for the 26 prevalence studies in Asia. Five studies in
Japan have used an 18-month health checklist (HC-18) (Honda, Shimizu, Imai, & Nitto, 2005;
Honda, Shimizu, Misumi, Niimi, & Ohashi, 1996; Kawamura, Takahashi, & Ishii, 2008; Sugiyama
& Abe, 1989; Tanoue, Oda, Asano, & Kawashima, 1988). In China, five studies used the Chinese
Autism Behaviour Scale (CABS)(Zhang & Ji, 2005), 2 used the translated version of the Autism
Behaviour Checklist (ABC) (Volkmar et al., 1988), and others used a translated version of the
Checklist for Autism in Toddlers (CHAT) (Baron-Cohen et al., 2000; Wong et al., 2004). The local
Bryson’s Screening Scale was used in Indonesia while an Iranian study used the Childhood
Symptom Inventory-4 (CSI-4) (Gadow & Sprafkin, 1994; Ghanizadeh, 2008). A recent Korean
study used a translated and validated version of the ASSQ followed by ADOS and ADI to confirm
diagnostic status.
As is evident from the discussion above, a number of SDTs (including the AQ, SCQ, ADOS) for
ASC have been translated in other languages in countries such as Brazil, Italy, China and Spain
(Canal-Bedia et al., 2011; Pereira, Riesgo, & Wagner, 2008; Ruta, Mazzone, Mazzone,
Wheelwright, & Baron-Cohen, 2011). However, none of these tools are available in any of the
major regional languages of India. Availability of such widely used diagnostic tools in major
regional languages can help standardise the diagnosis of autism in individuals who do not speak
English fluently.
The lack of availability of appropriate screening tools in local languages contributes to the paucity
of epidemiological studies of autism conducted in South Asia– where India is the largest country
without a population-based estimate of the prevalence of autism (Elsabbagh et al., 2012; Sun &
Allison, 2010). While small scale hospital based studies of the prevalence of autism have been
carried out (Juneja, Mukherjee, & Sharma, 2005) these do not provide an estimate of the prevalence
of autism in the general population.
It is vital to have access to both screening and diagnostic tools for autism in a low-resource setup
such as India. Screening tools can be used quickly and easily, have high sensitivity, and does not
require much training to administer. Accordingly, these tools are best suited to raise red flags for
any child who might show autism-related symptoms. Screening tools can be administered by health
visitors in charge of existing nationwide programmes such as those on vaccination against polio. In
contrast, diagnostic tools have higher specificity, take longer to administer, and need specialized
training for those administering (Filipek et al., 1999). In our study we take the first step by
translating 2 screening instruments (SCDC and AQ-C) and 2 diagnostic tools (SCQ and ADOS) into
two major regional languages (Hindi and Bengali).
We chose the following 4 SDTs for their different characteristics: the SCDC is a short instrument
that is suitable as a quick screen for autism in the general population; the AQ-C is designed to
capture the distribution of autistic traits across the diagnostic divide in the general population; while
the SCQ and ADOS are reliable diagnostic measures for autism.
It is expected that availability of a range of these well validated tools in local languages will a)
facilitate future epidemiological research into autism in India, b) ensure greater consistency and
comparability between studies of ASC around the world, and c) allow sufficient flexibility to local
researchers to choose an instrument of their choice depending on the research aim, and thereby help
develop clinical and research resources. The SDTs are described in the following section.
Methods
Tools
The four SDTs translated and validated in the current study were as follows:
1) Social Communication Disorder Checklist (SCDC) (Skuse, Mandy, & Scourfield, 2005) is a 12
item questionnaire suitable for a quick and sensitive screening of autistic traits in children. It has
previously been used on the ALSPAC (Avon Longitudinal Study of Parents and Children) cohort
(Skuse et al., 2009). The tool has been validated on children with a mean age of 10.6 years
(5-17 years) and has shown high sensitivity (0.90), and moderate specificity (0.69) (Skuse, Mandy,
& Scourfield, 2005). Parents are expected to answer questions which best describes their child’s
behaviour in the past 6 months. Each item on the scale is rated 0,1,or 2, according to whether the
behaviour has been seen over the past 6 months. The maximum possible score is 24, corresponding
to the highest level of autistic symptomatology. The cut off for ASC on SCDC, based on the
ALSPAC cohort, is suggested to be 9 (Skuse, et al., 2009). In the ALSPAC study Social and
Communication Disorders Checklist scores were continuously distributed in the general population
and this shows that it can be used as a first level screening tool for autism in a population based
survey (Skuse, et al., 2009).
2) Autism Spectrum Quotient- Child version (AQ-C) is a 50 item parent-report questionnaire that
quantifies the distribution of autistic traits in children between 4 to 11 years old, on both sides of the
diagnostic divide (Auyeung, Baron-Cohen, Wheelwright, & Allison, 2008). The range of scores on
the AQ-C is 0–150. It assesses five areas associated with autism and the broader phenotype: social
skills, attention switching, attention to detail, communication, and imagination. Each item is scored
1 for a response in the ‘autistic’ direction and 0 for a ‘non-autistic’ response. The cut- off for ASC is
76.
3) Social Communication Questionnaire (SCQ) is a 40-item parent-report questionnaire, used
widely to aid diagnosis. The SCQ can be administered on children above 4 years (Berument, et al.,
1999). It has two versions: current and lifetime. The lifetime form is completed in reference to an
individual’s entire developmental history and the current form is completed in reference to the
individual’s behaviour in the most recent 3-month period. Each item is answered with a yes/no, and
assigned a point rating of 1, to indicate presence of abnormal behaviour/ absence of normal
behaviour, and 0 otherwise. The cut-off for ASC is suggested to be 15, but for younger children a
cut-off of 11 has also been suggested (Allen, Silove, Williams, & Hutchins, 2007; Corsello et al.,
2007).
4) Autism Diagnostic Observation Schedule – The Autism Diagnostic Observation Schedule
(ADOS) is the most widely used tool for assessing and diagnosing ASD, across developmental
levels, and language skills. It is a semi–structured, standardized assessment of communication,
social interaction, and play or imaginative use of materials for individuals who have been referred
because of possible autism or other pervasive developmental disorders. The ADOS consists of four
modules, depending on the particular developmental and language level of the individual. Coding
for each behaviour observed is then scored to get three different categories of scores, namely,
Communication, Social Interaction and Stereotyped Behaviours and Restricted Interests (Lord, et
al., 2000). Diagnosis is made using a subset of items from communication and social interaction
subscales. The ADOS provides 3 categories of diagnosis: Autism, ASD and non-ASD. In module 1,
the cut-off score is 12 for Autism, 8 for ASD and <7 for non-ASD. In module 3, the cut- off score is
9 for Autism, 7/8 for ASD, and <6 for non-ASD.
Translation
All four SDTs described above were translated into Bengali and Hindi. The Western Psychological
Services (WPS) guidelines for translation were followed for ADOS and SCQ. This required an
individual from the research team in each city to be trained to research competence for use of the
instrument. A formal agreement was signed with the WPS, who coordinated the evaluation of the
blind back-translations with the original authors/copyright-holders of the instruments. Translators
were identified in Kolkata and Delhi who were fluent in the regional languages of both cities (i.e.
Bengali and Hindi, respectively). They were briefed on key features of ASC by the research team in
collaboration with the local autism centre. Special care was taken to ensure that the translation was
culturally appropriate (e.g. reference to children’s games, major festivals). Blind back translation
was carried out by a recognized linguistic expert. The translations and the back translations were
evaluated for concordance by the bilingual members of the research team, and sent to the original
developers/copyright holders of the SDT (The WPS for ADOS and SCQ, Simon Baron-Cohen for
the AQ-C, David Skuse for the SCDC). This cycle was repeated multiple times until the original
developers as well as the potential user base (represented by the research team) reached consensus.
Usability of translated tools
To test the usability of the translated SDTs, these were administered on a sample of children who
had a clinical diagnosis of Autism or ASD using ICD-10/DSM-IV criteria, and a group of control
children. We based our study design on previous published translations of ASC screening and
diagnostic tools in other languages (Wong et al., 2004; Ruta, Mazzone, Mazzone, Wheelwright, &
Baron-Cohen, 2011; Bölte & Poustka, 2004; Chojnicka & Płoski, 2011). Accordingly, a two-group
case-control design was used for testing the usability of all SDTs. The translated AQ-C, SCQ, and
SCDC were printed and given to parents, who returned these in person/ by post. Two of the four
modules (1 and 3) of the ADOS were validated to capture the largest spread in receptive language
ability of the participants in this age range, in light of the available resources. Receptive language
ability was measured using the Vineland Adaptive Behaviour Scale (VABS). This in turn, helped
determine the appropriate ADOS module to administer. Each module of the ADOS was
administered by a research-trained ADOS administrator Ethical approval for this study was obtained
from the Action for Autism Institutional Review Board (IRB), and all parents provided informed
consent before taking part in this research.
Participants
The Hindi translations were validated in Delhi, and the Bengali translations were validated in
Kolkata, in view of the primary spoken languages in these two cities. The inclusion criterion was
that all participants must communicate at home primarily in Bengali in Kolkata or in Hindi in Delhi.
The TQ was administered on all control and ASC participants to ensure that none of the children
had vision, hearing or learning disabilities.
The ASC group in Delhi was drawn from Action for Autism (National Centre for Autism) and the
ASC group in Kolkata was drawn from the Autism Society of West Bengal (ASWB). Only children
who had a primary clinical diagnosis of Autism/ Autism Spectrum Disorder according to the DSM-
IVTR/ICD-10 criteria from a recognised clinician were selected for testing usability. The above
centres attract children from a range of socio-economic backgrounds. Controls were recruited from
the mainstream schools / general population by word of mouth, and were selected so as not to have
a clinical diagnosis for any mental health condition. This was confirmed by a clinical psychologist
in the research team. The age range for participants was chosen to be 4 to 7 years since this captures
a high enough age when most autism-relevant behaviours are clearly manifested (and not too high
to avoid major compensatory changes in behaviour) (Lord, Rutter, & Le Couteur, 1994).
Children with serious disabilities of hearing, vision, motor and known neurological co-morbidities
such as Down Syndrome were excluded from the study. For parent-report tools (i.e. SCQ, SCDC,
AQ-C), the case and the control groups were matched on chronological age. For the ADOS, cases
and controls were tested on the Vineland Adaptive Behaviour Scale (receptive language domain) to
determine the appropriate ADOS module to be administered. The cases and controls were not age
matched for the ADOS sample since a majority of the children with ASC also had language delay.
All statistical analysis was performed using SPSS version 19 (Illinois, USA).
Results
Usability of Bengali SDTs
N= 188 participants (77 individuals with an Autism/ Autism Spectrum Disorder diagnosis and 111
controls) in all were tested for the usability of the Bengali SDTs. Table 1 provides the participant
demographics and sample size for the usability of each Bengali SDT.
Table 2 presents the mean scores and the standard deviations of the ASC and control sample for all
Bengali SDTs. For all 4 SDTs, cases scored significantly differently from controls. Specifically for
SCDC, all 40 ASC children scored greater than or equal to 9, while 1 of the 40 controls met the cut
off score of 9. For calculating the AQ-C scores with <5 missing items, the formula for missing
items suggested by (Hoekstra, Bartels, Verweij, & Boomsma, 2007) was used. On this instrument,
30 cases and none of the controls scored equal to or above the suggested cut-off score of 76.
On the SCQ, 40 cases and none of the controls scored equal to or above the suggested cut-off score
of 15. Figure 1 shows the cumulative distribution of the scores received by the ASC and control
children on the SCDC, AQ-C, and SCQ. On ADOS modules 1 and 3, all of the cases, and none of
the controls met the cut off score of 12 and 10 respectively (on the combined communication and
social score). Table 2 shows the mean scores in all 3 domains of the ADOS module 1 and 3. Figure
2 plots the cumulative frequency of scores for ASC and controls for ADOS module 1 and 3.
Usability of Hindi SDTs
N=172 participants (91 with an Autism or Autism Spectrum Disorder diagnosis and 81 with no
clinical diagnosis) in all took part in the usability of the Hindi SDTs. Table 3 provides the
participant demographics and sample size for the usability of each Hindi SDT.
Table 4 presents the mean scores and the standard deviations of the ASC and control sample for all
Hindi SDTs. For all 4 SDTs, cases scored significantly differently from controls. Specifically for the
SCDC, 39 of the 41 ASC children met the cut-off of 9. 15 of the control children also met the cut-
off of 9. For the AQ-C, 30 cases and 8 controls scored equal to or above the suggested cut-off score
of 76. On the SCQ, 30 cases but no controls scored equal to or above the suggested cut-off score of
15. Figure 1 show the cumulative distribution of the scores received by the ASC and control
children on the SCDC, AQ-C, and SCQ. On both ADOS modules 1 and 3, all the cases, and none of
the controls met the cut off score of 12 and 10 (on the combined communication and social score).
Table 4 shows the mean scores in all 3 domains of the ADOS module 1 and 3. Figure 2 plots the
cumulative frequency of scores for ASC and controls for ADOS module 1 and 3.
Discussion
In this study, we report the first translation of four widely used tools for autism screening and
diagnosis (SCDC, AQ-C, SCQ, ADOS) into two major South Asian languages (Hindi and Bengali),
and test their usability in a sample of children with and without a diagnosis of ASC. The results are
similar to those obtained with the original version of the tools in western countries, and provide
evidence that these tools can be used in South Asia.
All tools showed the expected pattern of significant differences between cases and controls (Tables
2 and 3). Specifically for the SCDC, the mean score received by the ASC group on the Bengali and
Hindi SCDC (13.45 and 13.78 respectively) was slightly lower that that obtained for the autism
group in the ALSPAC cohort (mean= 16.6, S.D= 5.7) (Skuse et al., 2007). This can be explained by
the fact that the mean age of the autistic group in the Skuse et al. study was greater (8.9 years) than
both our Bengali and Hindi ASC sample (5.83 and 3.68 years respectively). Accordingly, some of
the behavioural features relevant to autistic sympotmatology might not have developed in our
sample to the extent that these are easily spotted by teachers/ parents.
The AQ-C was a developed in the UK as a tool to capture the general population variability in
autistic traits and not as a diagnostic instrument. While it showed the expected difference between
cases and controls, the mean score for the ASC group reported in a British population by (Auyeung,
et al., 2008) of 104.8 is somewhat higher than that we obtained with both the Hindi and Bengali
translations (98.8 and 87.2 respectively). As with the SCDC, this difference maybe because the
mean age range of the Auyeung et al. sample (7.8-9.3 years) was significantly higher than the
sample in the current study (3.7-5.7 years). Several of the questions may therefore not have applied
directly to younger participants of our study, such as 'would rather go to a library than party' or
'would rather go to a theatre than a museum'.
The SCQ is a well-validated tool to verify a diagnosis of autism. In our current study, the mean
score for the ASC sample for both Bengali and Hindi was well above the recommended cut off of
15 (19.15 and 18.42). It was similar to the mean score (24.23) reported in the original paper (Rutter
et al. 1999). The mean scores obtained on all 3 domains namely, Communication, Social Interaction
and Repetitive behaviour and Stereotyped pattern, for the cases was also higher than the controls for
both Bengali and Hindi. We further investigated the children who did not meet the cut-off scores on
the Bengali translation of the SCQ. 4.3% of these children had a diagnosis of Asperger syndrome.
The ADOS is one of the best validated diagnostic interviews for autism. In our current sample for
ADOS module 1, all participants met the cut-off for Autism. In contrast, a majority of participants
for module 3 had a clinical diagnosis of ASD, which may explain why they met the cut off for ASD
but not for autism.
While the sample size for ADOS usability in our study is small, it is of the same order as has been
used to validate previous translations of the ADOS (Bölte & Poustka, 2004; Chojnicka & Płoski,
2011). Future studies should replicate these results in a larger sample. Another limitation of the
study is the restricted age range of the sample. Future studies should validate these measures across
a wider age range and also test the sensitivity and specificity of all these instruments against
children with other developmental disorders.
Since Bengali and Hindi are the largest regional languages of South Asia, spoken in urban and rural
areas, we anticipate a more useful application of our translated tools rather than the original English
versions. Moreover, the translated versions of the screening tools (e.g. SCDC) has the potential to
piggyback on existing nationwide health initiatives such as vaccination drives. As mental health
resources are developed in South Asia through governmental and non-governmental intiatives, it is
hoped that availability of well-characterised autism diagnostic tools (SCQ and ADOS) in the
regional languages would find wider use.
These preliminary results allow us to conclude that the translated SDTs can be used by literate
service providers in both rural and urban areas for screening and diagnosis for ASC. This represents
a significant step toward measuring the prevalence of ASC using globally used tools, and in turn
can quantify the need for appropriate services in India. Early diagnosis of ASC along with routine
developmental surveillance is vital for effective intervention. To this end, availability of well-
characterised SDTs in local languages provides a critical first step.
Conclusion
In this study, we translated four major screening and diagnostic tools for ASC into Hindi and
Bengali, and tested their usability on a case-control sample in two Indian cities (Kolkata and Delhi).
The translated instruments were found to show similar properties to the original instruments. This
has direct implications for improving diagnosis of ASC by clinicians in both rural and urban areas
within India where English is not the first language as well as other countries in South Asia where
Hindi and Bengali are widely used. Availability of these translated tools also builds vital research
capacity in the South Asian region, for measuring the prevalence of autism, as well as investigating
other (e.g. genetic, environmental) factors underlying ASC.
Acknowledgements
The authors wish to thank Jai Ranjan Ram, Tony Charman, Simon Baron-Cohen, Lynne Murray,
and Tom Loucas for their valuable input. This research was supported by Autism Speaks USA.
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Tables
Table 1: Participant Demographics for Bengali SDT validation sample [*** denotes significant at
p<0.001; ns denotes not significant at p<0.05]
Screening and
Diagnostic
Tools
ASC Control T-test
statistic (for
age)
N Male
%
Female
%
Mean
age
(yrs)
N Male
%
Female
%
Mean
age
(yrs)
SCDC 40 87.5 12.5 5.83 40 80 20 5.68 0.610(ns)
AQ-C 38 89.7 10.3 5.74 41 53.3 46.7 5.73 0.018(ns)
SCQ 47 89.4 10.6 5.45 43 48.8 51.2 5.65 -0.759(ns)
ADOS module 1 21 90.5 9.5 5.2 19 47.4 52.6 1.96 9.565***
ADOS module 3 18 83.3 16.7 11.91 19 78.9 21.1 5.02 11.588***
Table 2: Bengali SDT validation: ASC and control scores [*** denotes significant at p<0.001]
Screening Tools ASC Control T-test statistics
N Mean SD N Mean SD
SCDC 40 13.45 3.234 40 1 2.172 20.212 ***
AQ-C 38 87.18 15.318 41 36.76 14.239 15.162 ***
SCQ 47 19.15 5.912 43 2.37 2.279 17.453 ***
Domains
Communication 47 5.81 2.48 43 0.95 1.31 11.452 ***
Social Reciprocal
Interaction
47 7.70 3.4 43 0.60 1.12 13.055 ***
Repetitive Behaviour
and Stereotyped
Pattern
47 4.81 1.78 43 0.67 0.89 13.747 ***
ADOS module 1
Domains
Communication 21 6.57 1.53 19 0.79 0.79 14.74 ***
Social Interaction 21 11.24 2.81 19 0.84 0.9 15.41 ***
Stereotyped and
Restricted Behaviour
21 5.19 0.814 19 0.53 0.7 19.37 ***
ADOS module 3
Domains
Communication 18 2.44 0.62 19 0.84 0.602 8.002 ***
Social Interaction 18 6.78 3.02 19 0.95 1.43 7.57 ***
Stereotyped and
Restricted Behaviour
18 4.22 2.42 19 0.58 0.77 6.26 ***
Table 3: Participant Demographics for Hindi SDT validation sample [*** denotes significant at
p<0.001; ns denotes not significant at p<0.05]
Screening
and
Diagnostic
Tools
ASC Control T-test
statistic
(age)
N Male
%
Female
%
Mean
age
(yrs)
N Male
%
Female
%
Mean
age
(yrs)
SCDC 41 86 14 3.68 38 51.2 46.5 4.8 -1.207(ns)
AQ-C 37 81.1 18.9 3.7 40 55 42.5 4.76 -1.662(ns)
SCQ 41 82.9 17.1 4.36 53 47.2 50.9 4.86 -0.117(ns)
ADOS
module 1
22 81.8 18.2 4.44 20 61.1 36.1 1.76 4.062***
ADOS
module 3
22 81.8 18.2 9.16 20 50 45 6.44 3.074***
Table 4: Hindi SDT validation: ASC and control scores
Screening Tools ASC Control T-test statistics
N Mean SD N Mean SD
SCDC 41 13.78 4.28 38 8.13 4.44 5.762 ***
AQ-C 37 98.86 35.36 40 62.90 27.15 5.027 ***
SCQ 41 18.42 5.44 53 5.13 3.49 14.37 ***
Domains
Communication 41 5.81 2.48 53 0.95 1.31 11.452 ***
Social Reciprocal
Interaction
41 7.70 3.4 53 0.60 1.12 13.055 ***
Repetitive Behaviour
and Stereotyped
Pattern
41 4.81 1.78 53 0.67 0.89 13.747 ***
ADOS module 1
Domains
Communication 22 5.95 1.68 20 1.85 1.35 8.69 ***
Social Interaction 22 10.36 2.97 20 2.1 1.37 11.38 ***
Stereotyped and
Restricted Behaviour
22 4.41 1.89 20 1.3 0.92 6.65 ***
ADOS module 3
Domains
Communication
Social Interaction 22 5.36 1.29 20 0.95 0.99 12.29 ***
Stereotyped and
Restricted Behaviour
22 8.41 2.92 20 1.4 1.14 10.04 ***
22 1.68 1.52 20 0 0 4.93 ***
Figure Captions
Fig 1: The top panel (a, b, c) shows the cumulative distribution of the scores received by the ASC
and control children on the SCDC, AQ-C, and SCQ in Bengali. The bottom panel (d, e,f) shows the
cumulative distribution of the scores received by the ASC and control children on the SCDC, AQ-C,
and SCQ in Hindi.
Fig. 2: The top panel (a, b) shows the cumulative distribution of scores received by the ASC and
control children on the ADOS module 1 and module 3 in Bengali. The bottom panel (c,d) shows the
Cumulative distribution of the scores received by the ASC and control children on the ADOS
module 1 and module 3 in Hindi.
