What Is Available for Case Identification in Autism Research in Mainland China?

Research in Autism Spectrum Disorders 7 (2013) 579–590

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Research in Autism Spectrum Disorders

Jo urnal homepage: http://ees.elsevier.com/RASD/default.asp

What is available for case identiﬁcation in autism research in mainland China?

a,b, b b c b

Xiang Sun *, Carrie Allison , Bonnie Auyeung , Fiona E. Matthews , Simon Baron-Cohen , a

Carol Brayne

Cambridge Institute of Public Health, Department of Public Health and Primary Care, University of Cambridge, Forvie Site, Robinson Way, CB2 0SR, UK

Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18b Trumpington Road, CB2 2AH, UK

MRC Biostatistics Unit, Cambridge Institute of Public Health, Forvie Site, Robinson Way, CB2 0SR, UK

A R T I C L E I N F O A B S T R A C T

Little is known about research on Autism Spectrum Conditions (ASC) in mainland China.

Article history:

Received 22 August 2012 The few available studies in mainland China have shown the screening and diagnostic

Received in revised form 26 November 2012 instruments for ASC used in mainland China were different from the West. Literature on

Accepted 27 November 2012 screening and diagnostic instruments and criteria were reviewed and current available

instruments were identiﬁed and evaluated. Eight screening instruments and two

Keywords: diagnostic instruments were identiﬁed. The Clancy Autism Behaviour Scale (CABS), the

Autism

Autism Behaviour Checklist (ABC) and the Childhood Autism Rating Scale (CARS) were the

Screening instrument

most frequently used instruments in mainland China. They were adopted from the West

Diagnostic instrument

more than two decades ago for detecting individuals with Childhood Autism but not the

Mainland China

whole autism spectrum. Standardised instruments need to be validated and adopted into

autism research in mainland China.

1. Introduction

The term Autism Spectrum Conditions (ASC) is used to describe a group of childhood-onset neurodevelopmental

disorders characterised by impairments in social interaction and communication, and the presence of repetitive and

stereotyped behaviours, interests and activities (World Health Organisation, 1993). Recent epidemiological studies reported

that the prevalence estimate of ASC was around 1 percent of the general population, which is much higher than earlier

studies indicated (Fombonne, 2009). As the prevalence estimates increase, the detection of ASC has drawn more attention

worldwide than before (Baird et al., 2001; Barbaro & Dissanayake, 2010; Rice et al., 2007).

Recent epidemiological research has adopted a two-stage process for case identiﬁcation in the general population

(Baron-Cohen et al., 2009; Kim et al., 2011). The ﬁrst stage is screening and the second stage is diagnostic assessment. The

aim of screening is to identify and distinguish individuals who are more likely to have the condition of interest from those

who are less likely to have it (Webb, 2005). Screening instruments are used to detect the condition before the usual time

of diagnosis. In terms of ASC, the screening instruments are usually checklists with questions related to possible autistic

features. Individuals with positive screening results are then referred for more standard diagnosis (Porta, 2008).

Screening for autism has been proposed by many researchers (Baird et al., 2001; Duby & Johnson, 2009). Different

* Corresponding author at: Cambridge Institute of Public Health, Department of Public Health and Primary Care, University of Cambridge, Forvie Site,

Robinson Way, University of Cambridge, CB2 0SR, UK. Tel.: +44 01223 763833; fax: +44 01223 330300.

E-mail address: [email protected] (X. Sun).

580 X. Sun et al. / Research in Autism Spectrum Disorders 7 (2013) 579–590

screening instruments have been developed to detect potential cases in speciﬁc age ranges and/or for speciﬁc subtypes

on the spectrum (Norris & Lecavalier, 2010; Vostanis, Smith, Chung, & Corbett, 1994).

In terms of diagnostic assessment, as there has been no absolute test for ASC, because no clear biomarkers are available,

diagnostic instruments for ASC largely depend on the information from parents and direct observation of the affected child.

A number of diagnostic instruments have been developed, such as the Autism Diagnostic Observational Schedule (Lord,

Rutter, DiLavore, & Risi, 2001), the Diagnostic Interview for Social and Communication Disorder (Wing, Leekam, Libby,

Gould, & Larcombe, 2002), the Autism Diagnostic Interview Revised (Rutter, LeCouteur, & Lord, 2003) and the

developmental, dimensional and diagnostic interview (Skuse et al., 2004). The combination of the ADOS and the ADI-R has

been used more frequently in recent large-scale epidemiological research for case conﬁrmation of ASC (Levy, Mandell, &

Schultz, 2009).

There has been limited research on the current situation of ASC in mainland China, which refers to 23 provinces and 5

autonomous regions, excluding Hong Kong and Macao. A previous review reported that the prevalence of Childhood Autism

in mainland China was 10.3 per 10,000, which was much lower than Western estimates (Sun & Allison, 2009). In most

previous Chinese studies, the Clancy Autism Behaviours Scale (CABS) and the Autism Behaviour Checklist (ABC) were used as

screening instruments, and the Childhood Autism Rating Scale (CARS) was used as diagnostic instrument. These instruments

are not frequently used in prevalence studies in the West, which suggested that the screening and diagnostic instruments

used in mainland China are different from those used in Western studies (Sun & Allison, 2009). This paper sets out to

investigate the utility of instruments for ASC that have been applied to the Chinese population in mainland China. Learning

from what is available can help to decide whether it is necessary to introduce and adopt more recent and advanced

instruments for autism research to mainland China.

This paper has three objectives: to identify the instruments and criteria that have been used for case identiﬁcation for ASC

in mainland China; to report the validity and reliability of these instruments; to summarise the current methodology and

propose directions for future research in ASC in mainland China.

2. Methods

2.1. Literature searches

Systematic literature searches were conducted using four databases from the establishment year of each database to

2011 for publications related to screening and diagnostic instruments for ASC in mainland China (Figs. 1 and 2). The two

English databases were PubMed and Web of Knowledge. The other two were Chinese databases, including China Web of

Knowledge and Weipu. The search methodology used in the English and Chinese databases was not identical. In the English

databases systematic searching was conducted using three steps: Step 1 used the terminology of conditions such as ‘autism’

Fig. 1. Search strategy for identifying validation studies in English databases.

X. Sun et al. / Research in Autism Spectrum Disorders 7 (2013) 579–590 581

Search 1:

Weipu database (searched on 27 December 2011)

Yea rs (1989-2011)

Step 1: “Gu Du Zheng (Autism)”/ [Key words] OR “Zi Bi Zheng (Autism)/ [Key

words] OR “Gudu Zheng Pu Xi Zhang Ai (Autism Spectrum)”/ [Key words] OR

“Gu Fan Xing Fa Yu Zhang Ai (Pervasive developmental disorder)”/all [Key

words] OR “Ai Si Be Ge (Asperger)”/ [Key words]

Step 2: “Validation”/ [Key words] OR “Screen”/ [Key words] OR “Screening test”

OR “Validity”/ [Key words] or “Reliability”/ [Key words] AND results in Step 1

China Web of Knowledge (searched on 27 December 2011)

Yea r (1989-2011)

Step 1: “Gu Du Zheng (Autism)”/ [Key words] OR “Zi Bi Zheng (Autism)/ [Key

words] OR “Gudu Zheng Pu Xi Zhang Ai (Autism Spectrum)”/ [Key words] OR

“Gu Fan Xing Fa Yu Zhang Ai (Pervasive developmental disorder)”/all [Key

words] OR “Ai Si Be Ge (Asperger)”/ [Key words]

Step 2: “Validation”/ [Key words] OR “Screen”/ [Key words] OR “Screening test”

OR “Validity”/ [Key words] or “Reliability”/ [Key words] AND results in Step 1

Search 2:

Weipu database/China Web of Knowledge (searched on 27 December 2011)

Yea r (1989-2011)

“Gu Du Zheng (Autism)”/ [Key words] OR “Zi Bi Zheng (Autism)”/ [Key words]

Fig. 2. Search strategy for identifying validation studies in Chinese databases.

or ‘autism spectrum’; Step 2 deﬁned the study region as ‘China’; and Step 3 was speciﬁc to screening or validation studies. In

the Chinese databases no study region was deﬁned for searching in Search 1; in Search 2, only the Chinese terminology of

‘autism’ was used for a broader search in order to capture the studies that might have been missed by Search 1.

2.2. Study selection

The papers identiﬁed from the systematic searches were examined against the following inclusion criteria. (1) The study

should focus on a screening tool, diagnostic tool or diagnostic criteria. (2) The sample should be population based or clinically

based with a clear sample size. (3) The reference diagnostic method should be clearly indicated in terms of diagnostic

instruments, criteria or clinical judgement. (4) The validity or reliability of the tool should be provided. When it was not clear

whether or not the paper should be included, the paper itself was examined when possible.

2.3. Data extraction

After excluding the duplications using Reference Manager, the following variables were extracted from the identiﬁed

papers: screening instrument, cut-off of instrument, sample characteristics, diagnostic instrument, diagnostic criteria,

reliability, and validity of the instruments.

3. Results

3.1. Studies identiﬁed

The results of the ﬁrst search in each database were as follows: three papers from PubMed; 12 papers from Web of

Knowledge; 44 papers from Weipu; and 14 papers from China Web of Knowledge. After removing duplicates (n = 18),

abstracts were reviewed. The papers (n = 38) identiﬁed in the four databases were excluded from this review for the

following reasons: (1) the study sample was not from the population in mainland China (n = 6); (2) the study did not focus on

either screening or diagnostic instrument or diagnostic criteria (n = 29); (3) the study did not provide validity or reliability of

the instrument (n = 3). One paper from the English databases and 18 papers from the Chinese databases met the inclusion

criteria. After the second search of the Chinese databases, another three papers were identiﬁed, which had not been

identiﬁed in the ﬁrst search either in the English or the Chinese databases. In total 22 studies on 9 screening instruments and

2 diagnostic instruments were included for review (Fig. 3). Fifteen studies focused on screening instruments, six studies were

on diagnostic instruments, and four studies were on diagnostic criteria. Three studies investigated more than one topic. A

summary of the studies and their characteristics is provided in Appendix A.

582 X. Sun et al. / Research in Autism Spectrum Disorders 7 (2013) 579–590

Fig. 3. Search results of studies on screening and diagnostic instruments.

3.2. Screening instruments

The screening instruments that have been applied to the Chinese population in mainland China include: Autism

Behaviour Checklist (ABC); Clancy Autism Behaviour Scale (CABS); Checklist for Autism in Toddlers-23 (CHAT-23); Modiﬁed

Checklist of Autism in Toddlers (M-CHAT); Autism Spectrum Screening Questionnaire (ASSQ); Flinders Observational

Schedule of Pre-verbal Autistic Characteristics-Revised (FOSPAC-R); Waterville Autistic Behaviour Scales (WABS); Early

Autism Screening Items (EASI), and Pictorial Autism Screening Scale for Infant and Toddler (PASS-IT).

3.2.1. Autism Behaviour Checklist

The ABC was developed by Krug, Arick, and Almond (1980). It was designed to be applied to individuals aged between 18

months and 35 years (Krug et al., 1980; Miranda-Linne & Melin, 2002). The ABC has 57 items, with each item rating between

1 and 4. The cut-off of the ABC is 53 (53). It can be administrated by the clinicians and can also be ﬁlled in by the parents

without prior training (Williams, 2003).

X. Sun et al. / Research in Autism Spectrum Disorders 7 (2013) 579–590 583

The ABC was ﬁrst introduced into China for autism screening and diagnosis in 1989 (Tao, 1999; Wang, Wang, & Shen,

2003). The Chinese version of the ABC contains 57 items, including 10 items for tapping sensory behaviours (total score 30),

11 items for relationships (total score 35), 12 items for the use of physical development (total score 28), 13 items for

language (total score 31), and 11 items for daily living skills (total score 25).

Seven studies examined the utility of the ABC in Chinese samples. All seven studies were conducted within clinical

settings. During clinical referral, the children were ﬁrst given a diagnosis of Childhood Autism, and the parents then

ﬁlled in the ABC. Four of them used the ABC in both children with Childhood Autism and children without autism (Li,

Zhong, Cai, Chen, & Zhou, 2005a; Lu & Yang, 2004; Yang, Huang, Jia, & Chen, 1993), while the other three only examined

the ABC in children with Childhood Autism (Wang, Wang, & Wang, 2003; Wang, Wang, & Shen, 2003; Yin, Chen, Luo, &

Li, 2011). The age of studied samples ranged from 1.5 to 16 years. Three diagnostic criteria were used for case

identiﬁcation, including the International Statistical Classiﬁcation of Disease and Related Health Problems, 10th edition,

(World Health Organisation, 1993) the Diagnostic and Statistical Manual of Mental Disorders, 3rd/4th edition (American

Psychiatric Association, 1980, 1994) and the Chinese Classiﬁcation of Mental Disorders, 3rd edition (Chinese Society of

Psychiatry, 2001). The percentage agreement between the ABC and diagnostic criteria was calculated in six studies to

examine the utility of the ABC. The percentage agreement was the number of children who scored above the cut-off of

the screening instrument divided by the number of cases recruited. Four studies reported a high percentage agreement

(80–86.3%) between the ABC and ICD-10 (Lu & Yang, 2004; Wang, Zai, & Zhen, 2002; Wang, Wang, & Wang, 2003;

Wang, Wang, & Shen, 2003). However, the sensitivity and speciﬁcity were not provided in these four studies. Two

validation studies reported the validity of the ABC (Li et al., 2005a; Yang et al., 1993). The ﬁrst validation study of the

ABC recommended a cut-off of 31 for screening (Yang et al., 1993), which reported a sensitivity of 100 percent and a

speciﬁcity of 100 percent. Using the cut-off of 31, the other validation study reported a sensitivity of 97 percent and a

speciﬁcity of 89 percent (Li et al., 2005a). The cut-offs adopted in these studies were different. Three studies adopted

53, two adopted 56, and two adopted 31. Studies also recommended different scores (50–72) on the ABC as cut-offs for

the diagnosis of Childhood Autism. One study reported that the ABC had good internal consistency in 178 children with

autism (Cronbach’s a = 0.81), and the percentage agreement between the ABC and the CCMD-3 was 89 percent (Yin

et al., 2011).

3.2.2. Clancy Autism Behaviour Scale

The CABS was ﬁrst published in 1969 (Clancy, Dugdale, & Rendle-Short, 1969). However, no literature was found focusing

on the utility of the CABS in Western populations. The Chinese version of the CABS was designed to be completed by parents.

It contains 14 items, with each item rated on three frequency levels, including ‘Never (score 0)’, ‘Occasionally (score 1)’ and

‘Often (score 2)’. If the child scores equal to or higher than 14, and less than 3 items are scored as ‘Never’, and more than 6

items as ‘Often’, the child should be considered as screening positive for Childhood Autism.

Six studies were identiﬁed, of which four met the inclusion criteria. The other two were excluded because they did not

report either validity or reliability. All four studies were conducted in clinical settings (Li et al., 2005a; Li, Zhong, Cai, Chen, &

Zhou, 2005b; Wang, Wang, & Wang, 2003; Wang, Wang, & Shen, 2003). Two studies recruited both children with autism and

children without autism (Li et al., 2005a; Zhang, 2006). The study samples were aged between 1.5 and 8 years. The ICD-10

and DSM-IV were used as diagnostic criteria. Two studies reported high agreement (95%) between the CABS and ICD-10

(Wang, Wang, & Wang, 2003; Wang, Wang, & Shen, 2003). The agreement between the CABS and DSM-IV was 87 percent (Li

et al., 2005a). One study used clinical judgement for case conﬁrmation without specifying the diagnostic criteria (Zhang,

2006). Two studies adopted 14 as a cut-off for the CABS (Wang, Wang, & Wang, 2003) while one study adopted a cut-off of 6

(Li et al., 2005a). The validity of CABS was reported in two studies (Li et al., 2005a; Zhang, 2006), and both suggested a good

validity of the CABS (sensitivity: 88%, 91%; speciﬁcity: 82%).

3.2.3. Checklist for Autism in Toddlers and its modiﬁed version

The CHAT includes nine questions for parents and ﬁve observations of the child (Baron-Cohen, Allen, & Gillberg, 1992). It

takes between 10 and 15 min to complete. The applicable age for the CHAT as a screening instrument is 18 months (Baron-

Cohen et al., 1992). It has been thoroughly validated and evaluated in Western populations (Baron-Cohen et al., 2000). The

CHAT has been adopted by American researchers and was modiﬁed as the M-CHAT (Dumont-Mathieu & Fein, 2005; Yama,

Freeman, Graves, Yuan, & Karen, 2012). Researchers in Hong Kong developed a screening instrument, the CHAT-23, for

screening in toddlers by combining the M-CHAT (23 questions) with graded scores and the observational Section B of the

CHAT (Wong et al., 2004). To be labelled positive on the CHAT-23, the child should meet one of the following criteria: ﬁrst,

individual scores should be positive on more than 6 out of the 23 items; second, of the 7 core items on the CHAT-23, the

individual scores should be positive on more than 2 items.

So far, only one study has investigated the utility of the CHAT-23 (Wu et al., 2010) and two studies reported the

utility of the M-CHAT in Chinese samples (Gong et al., 2011; Zhang, Tan, Xiao, Zhang, & Zhang, 2011). All three studies

were conducted in children of no older than three years using DSM-IV as the diagnostic criteria. The sensitivity of the

CHAT-23 was 94 percent and speciﬁcity was 88 percent when applied to the general population (Wu et al., 2010). This

study indicated that the validity of CHAT-23 in this sample was higher than in the ﬁrst study in Hong Kong. It

suggested that this might have been due to the relatively small size of the case group (n = 51) compared with the

control group (n = 482) in this study. Two studies on the M-CHAT were conducted in clinical samples. However, using

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similar methodology, two studies reported quite different results on test validity of the M-CHAT. One study reported

that sensitivity was 96 percent, and speciﬁcity was 60 percent (Gong et al., 2011), while the other reported that

sensitivity was 72 percent and speciﬁcity was 95 percent (Zhang, 2006).

3.2.4. Autism Spectrum Screening Questionnaire

The Autism Spectrum Screening Questionnaire (ASSQ) was originally developed as a screening tool to detect Asperger’s

syndrome in the general population of school-aged children by Ehlers and Gillberg (Ehlers & Gillberg, 1993; Ehlers, Gillberg,

& Wing, 1999). The applicable age range of ASSQ is between 7 and 16 years (Ehlers et al., 1999). It was developed according to

the diagnostic criteria for ASC in ICD-10 and DSM-IV (Kopp & Gillberg, 2011; Mattila et al., 2009). The ASSQ contains 27 items

and each item was rated on a 3-point scale as follows: 0 indicating normal, 1 indicating maybe abnormal, and 2 indicating

deﬁnite abnormality (Mattila et al., 2009). The score of the ASSQ ranges from 0 to 54 with a recommended cut-off at 13. The

ASSQ takes only 10 min to complete. The sensitivity of the parent’s version of the ASSQ was 91 percent and speciﬁcity was 77

percent (Ehlers et al., 1999).

One validation study of the ASSQ in the Chinese population was identiﬁed. The ASSQ was applied to children with ASC

(n = 94) and typically developing children (n = 120), as well as children with other conditions (n = 71) (Guo et al., 2011).

Using a cut-off of 12 (12), the sensitivity of the ASSQ was 96 percent and speciﬁcity was 83 percent. This study

examined the performance of the ASSQ using the Receiver Operating Characteristic (ROC), which reported an area under

curve (AUC) of the ASSQ of 0.957 (Guo et al., 2011). No validation of the ASSQ was conducted in the general Chinese

population.

3.2.5. Flinders Observational Schedule of Pre-verbal Autistic Characteristics-Revised

The Flinders Observational Schedule of Pre-verbal Autistic Characteristics-Revised (FOSPAC-R) was developed by

researchers at Flinders University Australia (Yong, 2001). It was designed for the detection of Childhood Autism as early as 12

months old. The FOSPAC-R contains 17 items and rates on a 3-level scale, including normal behaviours, between normal and

abnormal behaviours, and abnormal behaviours. It takes between 15 and 20 min to complete. Only one study was identiﬁed

that validated the FOSPAC-R in clinical settings. The sample contained 27 children with Childhood Autism, 27 typically

developing children, and 27 children with mental retardation. This study ﬁrst applied the FOSPAC-R to the study sample, and

the test positives were then further examined using the CHAT and diagnosed using DSM-IV by clinicians. Using a cut-off of

14, the validity of the FOSPAC-R for distinguishing children with Childhood Autism from the others was good

(sensitivity = 96%, speciﬁcity = 93%).

3.2.6. Waterville Autistic Behaviour Scales

The Waterville Autistic Behaviours Scales (WABS) was developed from the diagnostic criteria of ASC in DSM-IV and ICD-

10 (Song, Fang, & Sun, 2009). It contains four domains, including social behaviours, language and communication,

behaviours, and interests, as well as movement and cognition. One study investigated the validity of the WABS within

children having Childhood Autism, children with mental disorder and typically developing children (Song et al., 2009). This

study recommended a cut-off of 51.5 and reported a sensitivity of 100 percent and speciﬁcity of 97 percent.

3.2.7. Early Autism Screening Items

The Early Autism Screening Items (EASI) was developed by an American researcher, Larry Burd, and has not yet been

validated in the West (Zhang et al., 2011). The validation of the Chinese EASI was the ﬁrst validation study since it was

developed in the West. The Chinese EASI contains 46 items. Each item is scored between 0 and 2 according to the frequency

and degree of autistic behaviours. Never or seldom is indicated by 0, 1 indicates sometimes, and 2 indicates often. A total

score of less than 40 is recommended as the cut-off. The study sample consisted of 25 children with ASC and 400 typically

developing children. The cases were previously diagnosed by clinicians using DSM-IV. The sensitivity of EASI was 80

percent and speciﬁcity was 75 percent (Zhang et al., 2011). The percentage agreement between the EASI and DSM-IV was 75

percent.

3.2.8. Pictorial Autism Screening Scale for Infant and Toddler

The PASS-IT was also developed by Larry Burd, and consists of 25 pictures of different facial expressions or gestures. The

pictures were designed to be shown to parents or caregivers to recall whether or not their child exhibited the expressions or

gestures shown in the picture. The parents were asked to give an answer of yes or no with a score of 1 and 0 respectively. A

total score of less than 20 (20) was recommended as a cut-off. In the validation study of the EASI, the PASS-IT was applied to

the same sample. The sensitivity of PASS-IT was 88 percent and speciﬁcity was 64 percent (Zhang et al., 2011). The

agreement between the PASS-IT and DSM-IV was 66 percent.

3.3. Diagnostic instruments

Studies on two diagnostic instruments were identiﬁed: Childhood Autism Rating Scale (CARS) and Autism Diagnostic

Interview (ADI). The Autism Diagnostic Observation Schedule (ADOS) was only introduced without any validation studies.

X. Sun et al. / Research in Autism Spectrum Disorders 7 (2013) 579–590 585

3.3.1. Childhood Autism Rating Scale

The Childhood Autism Rating Scale (CARS) was developed by Schopler, Reichler, and Renner (1988). It is a behaviour and

observation scale that is considered especially effective for differentiating children with mild, moderate and severe autism,

as well as discriminating between children with autism and those with mental retardation (Eaves & Milner, 1993; Magyar &

Pandolﬁ, 2007; Pereira, Riesgo, & Wagner, 2008; Stella, Mundy, & Tuchman, 1999). It includes a wide range of diagnostic

criteria and evaluates the child’s behaviours on 15 dimensions (Perry, Condillac, Freeman, Dunn-Geier, & Belair, 2005). Many

studies have reported relatively high reliability of the CARS (Garﬁn, McCallon, & Cox, 1988; Sevin, Matson, Coe, Fee, & Sevin,

1991).

The Chinese version of the CARS contains 15 items. The rating ranges between 1 and 4 on each item, indicating the

following: ‘appropriate behaviours for the child’s age’, ‘mildly abnormal’, ‘moderate abnormal’, and ‘severe abnormal’. The

total score of the CARS is 60 and the cut-off for Childhood Autism is 30.

Four studies that investigated the utility of the CARS were identiﬁed (Li et al., 2005a, 2005b; Lu & Yang, 2004; Yin et al.,

2011). All four studies were conducted within clinical settings, three of which recruited both children with autism and

children without autism. The age of study samples ranged from 1.8 to 16 years. Three diagnostic criteria were used,

including DSM-IV, ICD-10, and CCMD-3. All four studies adopted a cut-off of 30 on the CARS for diagnosis of Childhood

Autism. The agreement between the CARS and diagnostic criteria was high (97–100 percent). The validity of the CARS as a

diagnostic instrument for Childhood Autism was reported as excellent (sensitivity = speciﬁcity = 100%) by two studies (Li

et al., 2005a, 2005b). One study (Yin et al., 2011) reported that the internal consistency of the CARS was acceptable

(Cronbach’s a = 0.78).

3.3.2. Autism Diagnostic Interview and Autism Diagnostic Observational Schedule

The ADI was developed by Rutter, Le-Couteur and Lord (Le-Couteur et al., 1989). It is a standardised, face-to-face,

semi-structured diagnostic protocol for interviewing parents or caregivers of individuals referred for a possible ASC. In

the West, the current version, the Autism Diagnostic Interview-Revised (ADI-R), has been widely used in autism

research (Rutter et al., 2003). The ADI-R is an 85-page booklet containing 111 items in 3 core domains of ASC (Gray,

Tonge, & Sweeney, 2008), including social interaction, communication and repetitive and stereotyped behaviours,

interests and activities (RBIA). Each item is on a 4-scale rating from 0 to 3: ‘0’ indicates no evidence for abnormality; ‘2–

3’ indicates obvious evidence for abnormality. The ADI was introduced into mainland China in 1998. Two studies were

conducted in clinical settings to investigate the validity of the ADI in Chinese populations (Guo & Liu, 2002; Liu, Guo,

Guo, Yang, & Jia, 2004). Both studies applied the ADI in children with Childhood Autism and children with other mental

conditions. One study reported that 15 out of 16 items in the social interaction domain could statistically distinguish

children with autism from children without autism (p < 0.01). In the communication domain, 11 out of 13 items could

differentiate children with autism from children without autism (p < 0.01). In the RBIA domain, 4 out of 8 items

signiﬁcantly differentiated children with autism from children without autism (p < 0.01) (Guo & Liu, 2002). The inter-

rater reliability of the ADI in the social interaction domain was good in 15 out of 16 items (Kappa 0.68). The inter-

rater reliability was good in 10 out of 13 items (Kappa 0.68) in the communication domain. The reliability was good

(Kappa 0.68) in 3 out of 8 items in the RBIA domain (Guo & Liu, 2002). It suggested that the relatively lower validity

and reliability of the RBIA domain of the Chinese ADI was due to the low speciﬁcity of the items in this domain,

according to previous studies (Fombonne, 1992; Yirmiya, Sigman, & Freeman, 1994), but not due to potential cultural

inﬂuence (Guo & Liu, 2002).

The other study investigated the reliability and validity of parts of the items on the ADI that were identiﬁed by the ﬁrst

study. The second study examined 17 items on the ADI: seven items from the social interaction domain, six from the

communication domain and four from the RBIA domain (Liu et al., 2004). It reported that the inter-rater reliability of 11 out

of 17 items was moderate (Kappa: 0.43–0.58), and the reliability of another ﬁve items was good (Kappa: 0.6–0.64). Only one

item had fair inter-rater reliability (Kappa = 0.29). The test–retest reliability of nine items was good (Kappa: 0.61–0.73), and

the remaining eight items had moderate reliability (Kappa: 0.4–0.58). This revealed that all items could signiﬁcantly

(p < 0.001) distinguish children with Childhood Autism from children with other mental conditions or typically developing

children (Liu et al., 2004).

The Autism Diagnostic Observational Schedule (ADOS) is a semi-structured, standardised, play-based observational

instrument (Lord et al., 2000). The assessment was designed to create a ‘social world’ for the subject to interact with the

examiner (Klein-Tasman, Risi, & Lord, 2007). The ADOS was ﬁrst mentioned in the introductory report of the ADI (Guo &

Yang, 1998). However, the ADOS has not been applied to the Chinese population in the reviewed literature.

3.4. Comparison of diagnostic criteria

Four diagnostic criteria were used by Chinese clinicians: ICD-10 (World Health Organisation, 1993), DSM-III-R (American

Psychiatric Association, 1987), DSM-IV (American Psychiatric Association, 1994) and the Chinese Children Mental Diagnosis

(CCMD-2/2-R/3) (Chinese Society of Psychiatry, 1984, 1993, 2001). The ﬁrst three are the same criteria used in Western

countries while the last one has been used only in mainland China.

Four studies were identiﬁed, which focused on the agreement between different diagnostic criteria of autism in

mainland China (Guo, Wan, & Shan, 2002; Liu & Jia, 2006; Tan, Ke, & Lu, 1998; Zhang, 2006). One study compared the

586 X. Sun et al. / Research in Autism Spectrum Disorders 7 (2013) 579–590

diagnostic results between ICD-10, DSM-IV and CCMD-2-R within a sample of 95 children with Childhood Autism (Tan

et al., 1998). The clinical judgement was the reference criteria. It reported that the percentage agreement between

CCMD-2-R and clinical judgement was 90 percent; agreement between DSM-IV and clinical judgement was 97 percent;

and agreement between ICD-10 and clinical judgement was 96 percent. This study also reported that the percentage

agreement between CCMD-2-R and the other two international criteria – DSM-IV and ICD-10 – was 48 and 59 percent

respectively. One study investigated the percentage agreement between CCMD-2-R, CCMD-3 and ICD-10. The sample

consisted of 117 children with Childhood Autism previously diagnosed by clinical judgement (Guo et al., 2002). This

study reported a percentage agreement of 100 percent between CCMD-3 and ICD-10 (Kappa = 1.00, p < 0.001); and an

agreement of 95.8 percent between CCMD-2-R and ICD-10 (Kappa = 0.92, p < 0.001). One study investigated the

agreement between CCMD-3 and DSM-IV within 255 clinically diagnosed autistic cases, which reported an agreement of

96.1 percent (Liu & Jia, 2006). Another study compared the diagnostic results between DSM-IV and clinical judgement

within a sample of 65 children with autism and 65 children without autism. It reported that the percentage agreement

between DSM-IV and clinical judgement was 100 percent; and the sensitivity of DSM-IV was 96 percent and speciﬁcity

was 92 percent (Zhang, 2006).

4. Discussion

4.1. Current screening and diagnostic instruments in mainland China

This study examined the available screening, diagnostic instruments and criteria for autism in mainland China. The most

frequently used instruments for screening in mainland China were the CABS and ABC. The most frequently used diagnostic

instrument was the CARS. The ADI was only validated without adoption in epidemiological research, while the ADOS has not

been applied to the Chinese population (Tang, Guo, Rice, Wang, & Cubells, 2010). It has been recommended that the

sensitivity and speciﬁcity of a screening instrument should be between 70 and 80 percent in order to be considered

psychometrically sound (Glascoe, 2005). The validity of the CABS, ABC, CARS, CHAT-23 and ASSQ was reported as good in

previous studies reviewed in this paper (sensitivity > 80%, speciﬁcity > 80%). These instruments were well respected and

widely used, but they were used mainly to capture cases of Childhood Autism. Considering the life-long course and

complexity of the condition, they might be weak in detecting cases of Asperger’s syndrome or PDD-NOS. In addition, the

CARS was also used as a second-stage screening instrument in previous prevalence studies in mainland China (Liu et al.,

2004; Zhang, Xu, & Zhang, 2005).

The most frequently used screening instruments were introduced to China in the late 1980s, and there have been very few

updates regarding the contents since they were ﬁrst translated and validated. In particular, the CABS was developed in 1969

and widely used in autism research in mainland China (Clancy et al., 1969); however, the data on its validity and reliability in

the West was lacking. The CARS and ABC were also adopted early and they are still in use for ASC research in the West

(Fernandes & Miilher, 2008; Perry et al., 2005). The CHAT and the M-CHAT were developed relatively recently and have been

validated and adopted widely in research on ASC in the West (Baron-Cohen et al., 1992, 2000; Yama et al., 2012). The WABS,

FOSPAC-R, EASI, and PASS-IT were developed most recently and have not been widely adopted or studied in the West (Zhang

et al., 2011).

4.2. Limitations of review

There are several limitations of this review. First, the literature search was conducted using four databases. It is possible

that there are studies that were not identiﬁed because they were not published in major journals. However, the search

methodology was systematic, with double-checking using a second search in all databases; it was unlikely that publication

and selection bias could inﬂuence the results. Second, as all the papers were in Chinese, and the data was extracted and

translated into English by the ﬁrst author only, and there could be language implications. Thus, it would be valuable to have

a second reader for data extraction and translation. Third, the results presented for the validity and reliability of

instruments were summarised according to the analytical methods stated in each paper. However, since the detailed

description of analytical approaches was generally lacking in reviewed papers, the analytical methods were assumed from

the presentation of results in each paper. Thus, there might be misinterpretation of the analytical approaches of the

reviewed studies.

4.3. Critique of research methodology in reviewed studies

In the reviewed studies, the information related to subject selection and diagnostic procedures was generally missing.

The lack of useful research techniques would make it difﬁcult to replicate the research or compare the results with other

studies.

In terms of sampling method, the samples in reviewed studies were drawn mostly from clinical patients who already had

an autism diagnosis before the validation took place (17, 89.5%). Two studies selected children with other subtypes of ASC as

cases, while other studies only selected children with Childhood Autism (Guo et al., 2011; Liu et al., 2007). Only two studies

identiﬁed cases prospectively within the general population (Wu et al., 2010; Yang et al., 2010).

X. Sun et al. / Research in Autism Spectrum Disorders 7 (2013) 579–590 587

After the diagnosis, cases were examined by clinicians using screening instruments. Then, the performance of the

screening instruments was compared with the previous diagnosis. The clinicians in the research were generally not blind to

the diagnostic status of the participants. This could bias the results of screening validity and reliability as well as the

comparison of the diagnosis.

Six studies investigated the utility of instruments in children with Childhood Autism without comparable controls. Those

studies that had a control group did not provide information on whether the controls were drawn from the same population

as the cases. Therefore, it is possible that the results generated from such studies may be confounded by variables other than

the autistic condition.

The screening instruments used in mainland China often had two cut-offs. The lower cut-off was used for screening and

the higher cut-off for diagnosis. The individuals who scored above the lower cut-off were considered a potential case of

autism, and those who scored above the higher cut-off were given an autism diagnosis. The cut-off for the same screening

instrument varied among reviewed studies, which made it difﬁcult to compare their results.

The analytical methods on the validity and reliability of instruments varied among reviewed studies. There were

four approaches: (1) simple percentage: examine the performance of an instrument by calculating the percentage of

cases identiﬁed by the instrument among the number of already known cases recruited in the study to generate the

agreement between screening instruments and the reference diagnostic criteria; (2) Cohen’s Kappa agreement test: a

statistical measure of inter-rater agreement for qualitative items. It investigates the extent to which there is an

agreement other than that expected by chance (Cohen, 1968); (3) validity: using sensitivity and speciﬁcity; (4)

statistic test to investigate whether the instruments can distinguish children with autism from children without

autism, such as the chi-square test.

Some studies reported particularly high sensitivity and specificity (sensitivity = 100%, specificity = 100%), such as the first

validation study of the ABC (Yang et al., 1993). However, the samples of these studies consisted of very severe autistic cases

and typically developing children. Those samples were not representative of the children on the whole autism spectrum in

the general population. The details of analytical methodology were generally lacking in reviewed papers. The type of analysis

could only be learned from the presentation of results. The usage of different statistical methods led to difﬁculty in justifying

these results and comparing them among studies.

4.4. Case identiﬁcation and further direction of ASC in mainland China

As the reported prevalence of ASC has increased considerably in Western epidemiological studies (Fombonne, 2009),

the public health issues regarding individuals with ASC have attracted great attention (Brownson, Newschaffer, & Ali-

Abarghoui, 1997; Rice, Schendel, Cunniff, & Doernberg, 2004). China has a population of more than 1.37 billion. If

Western prevalence estimates for ASC (around 1%) are accurate and cross-culturally stable, then, when applied to China,

13.7 million individuals are expected to have ASC. However, research in this area is limited and the available studies

suggested a much lower prevalence in the Chinese population. This may be due in part to the lack of recognition of this

condition. Thus, improvement in case identiﬁcation could help an understanding of the current situation of ASC in

mainland China. The screening and diagnostic instruments for ASC should have the ability to capture not only the most

obvious autistic features but also the more subtle ones, since individuals on the borderline of the spectrum also need to

be identiﬁed and helped. The lack of screening and diagnostic instruments for the whole autism spectrum leads to

difﬁculty in the comparison between East and West. It also leads to difﬁculty in policy-making and service provision

towards individuals with ASC. Most importantly, it will lead to individuals with milder conditions struggling for help.

Among identiﬁed instruments, the CHAT-23 and ASSQ were developed for the whole autism spectrum, and much

evidence for their utility has been provided by Western studies. Although these two instruments have been applied to the

Chinese population only once, they have demonstrated acceptable validity as screening instruments for ASC. However,

the CHAT-23 is only applicable to young children at a mental age of between 18 and 24 months (Wong et al., 2004), and

the utility of ASSQ in the general population still requires investigation. Furthermore, the utility of adopted instruments

needs to be conﬁrmed with the diagnosis made by standardised diagnostic instruments in the general population. In this

way, a large population study of ASC can be achieved in mainland China. Thus, the adoption of advanced and well-

developed screening and diagnostic instruments to China is needed in order to improve the epidemiological and

aetiological research on ASC in mainland China.

4.5. Conclusions

Studies on screening and diagnostic instruments for ASC in mainland China are limited. Two screening instruments, the

ABC and CABS, have been more thoroughly studied in mainland China. Both of them were adopted from the West more than

two decades ago to detect potential cases of Childhood Autism. The CARS has been most frequently used as the diagnostic

instrument in autism research in mainland China. The ADI was introduced but has not been thoroughly adopted. There is a

lack of consistency in study methodology among identiﬁed studies, especially the varied adoption of cut-offs. Therefore, it is

difﬁcult to make comparisons among studies. There is an urgent need to introduce more advanced and well-developed

screening and diagnostic instruments to mainland China, as well as more standardised research methodology for the

development of such instruments for ASC in the future. 588 Appendix A

Validity and reliability of screening and diagnostic instruments in mainland China.

Tool Author Case no. Cases age Sample Control no. Control age Cut-off for Cut-off Sensitivity Speciﬁcity Agreement Reference (mean age) source suspicion for diagnosis percentage standard

ABC Yang et al. (1993) 60 2–17 (6.37) Clinical 157 (MR) 7–17 (11.7) 31 50 31 cut-off: 100% 31 cut-off: 100% – DSM-III-R 108 (N) 4–8 (6.3) 50 cut-off: 97% 50 cut-off: 100% Wang et al. (2002) 20 2.33–11 (4) Clinical 20 (ADHD) 6–12 (8.5) 53 68 – – 80% ICD-10 Wang, Wang, and 20 2–8 (4.5) Clinical 0 – 56 72 – – 85% ICD-10 Wang (2003) Wang, Wang, and 22 2–8 (4.6) Clinical 0 – 56 72 – – 86% ICD-10 Shen (2003) X.

Lu and Yang (2004) 43 1.83–16 Clinical 31 (N) 2–14 53 67 – – 81% ICD-10 Sun Li et al. (2005a) 28 1.5–3 (26 children) Clinical 34 (N) 1.5–3 (31 children); 31 – 97% 89% 94% DSM-IV

I7 (2 children) I7 (2 children) et

89% – CCMD-3 Yin et al. (2011) 178 – Clinical 0 – – 53 Cronbach’s al.

a = 0.81 /

CABS Wang, Wang, and 20 2–8 (4.5) Clinical 0 – 14 – – – 95% ICD-10 Research Wang (2003) Wang, Wang, and 22 2–8 (4.6) Clinical 0 – 14 – – – 96% ICD-10

Shen (2003) in

Li et al. (2005a) 28 1.5–3 (26 children) Clinical 34 (N) 1.5–3 (31 children); 6 – 91%, 82% 87% DSM-IV Autism I7 (2 children) I7 (2 children)

Zhang (2006) 65 2.5–4 Clinical 65 (N) – – – 88% 82% – Clinical Spectrum judgement CHAT-23 Wu et al. (2010) 535 1.5–2 General 0 – (1) I6 items positive in Either meet Either meet – DSM-IV population 23 items; (2) I2 items (1) or (2): 94% (1) or (2): 88%

positive in 7 key items Disorders M-CHAT Zhang et al. (2011) 25 0.96–2.92 (1.9) Clinical 400 (N) 1.75–2.75 (2) (1) I3 items positive in Either meet Either meet 94% DSM-IV 23 items; (2) I2 items (1) or (2): 72% (1) or (2): 95%

positive in 6 key items 7

Gong et al. (2011) 93 1.2–3 (2.3) Clinical 85 (N) 1–2.9 (2) (1) I3 items positive in 96% 60% – DSM-IV (2013) 23 items; (2) I2 items

positive in 6 key items 579–590 ASSQ Guo et al. (2011) 94 3.9–9.6 (6.75) Clinical 120 (N) 4.7–7.3 (6) 12 – 96% 83% – DSM-IV 71 (MD) 10.8–16.8 (13.8) WABS Song et al. (2009) 30 – Special 30 (MD) – 51.5 – 100% 97% – Clinical school judgement 33 (N) – FOSPAC-R Yang et al. (2010) 27 1–1.42 Clinical 27 (N) 1–1.42 14 – 96% 93% – DSM-IV 27 (MD) 1–1.42 CHAT EASI Zhang et al. (2011) 25 0.96–2.92 (1.9) Clinical 400 (N) 1.75–2.75 (2) 40 – 80% 75% 75% DSM-IV aPASS-ITLu andZhang Yang et (2004) al. (2011)4325 1.83–16 0.96–2.92 (1.9) Clinical Clinical 31 (N) 400 (N) 2–14 1.75–2.75 (2) 30 20 36 – – 88% – 64% 98% 66% ICD-10 DSM-IV CARS Li et al. (2005a) 28 1.5–3 (26 children) Clinical 34 (N) 1.5–3 (31 children); 30 – 100% 100% 100% DSM-IV I7 (2 children) I7 (2 children) Li et al. (2005b) 41 2–10 (3.8) Clinical 34 (MD) 3–11 (4.5) – 30 100% 100% 100% DSM-IV Yin et al. (2011) 178 – Clinical 0 – 30 37 Cronbach’s a = 0.78 97% – CCMD-3 a Diagnostic instrument; CABS: Clancy Autism Behaviour Scale; ABC: Autism Behaviour Checklist; CARS: Childhood Autism Rating Scale; CHAT: Checklist of Autism in Toddlers; M-CHAT: Modiﬁed Checklist of Autism in Toddlers; ASSQ: Autism Spectrum Screening Questionnaire; WABS: Waterville Autistic Behaviour Scales; FOSPAC-R: Flinders Observational Schedule of Pre-verbal Autistic Characteristics-Revised; EASI: Early Autism Screening Items; PASS-IT: Pictorial Autism Screening Scale for Infant and Toddler; N: typical developed children; MR: mental retardation; ADHD: attention deﬁciency and hyperactivity disorder; MD: mental disorders.

X. Sun et al. / Research in Autism Spectrum Disorders 7 (2013) 579–590 589

Acknowledgements

XS was partly funded by the Waterloo Foundation, Cambridge Commonwealth Trust and Clare Hall of the University of

Cambridge. SBC, CA, and BA were funded by the Medical Research Council UK, the Wellcome Trust, and the team were funded

by the NIHR CLAHRC for Cambridgeshire and Peterborough NHS Foundation Trust during the period of this work. FM was

funded by MRC UK.

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