Social Communication Questionnaire
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Social Communication Questionnaire

Last Updated

Purpose

The Social Communication Questionnaire (SCQ) is a brief, 40-item yes/no response, caregiver-report screening of symptoms associated with autism spectrum disorder (ASD). Two forms are available, Current, which looks at the child’s last 3 months, and Lifetime, which looks at the child’s entire developmental history.

Link to Instrument

https://www.wpspublish.com/scq-social-communication-questionnaire

Acronym SCQ

Area of Assessment

Behavior
Communication
Infant & Child Development
Language

Assessment Type

Proxy

Administration Mode

Paper & Pencil

Cost

Not Free

Actual Cost

$175.00

Cost Description

Online SCQ Kit- $175.00
Physical SCQ Kit- $193.00

CDE Status

NINDS CDE Notice of Copyright
Social Communication Questionnaire (SCQ)

Availability

Please visit this website for more information about the instrument: Social Communication Questionnaire.

Classification

Supplemental – Highly Recommended: Cerebral Palsy (CP).
Supplemental: Epilepsy and Neuromuscular Disease (NMD).

Populations

Congenital Disorders
Pediatric Disorders
Intellectual Disability

Key Descriptions

  • Formerly known as the Autism Screening Questionnaire
  • SCQ is available in two forms (Lifetime and Current), both of which have 40 yes-no questions.
  • Developmental history and current behaviors of the child are assessed
  • Items-level scores “0” or “1” are determined by caregivers’ report of “no” or “yes” answers.
  • The answer to item 1 dictates which items are to be added to determine the Total Score. If “yes” to Item 1, then add Items 2 to 40. If “no” to Item 1, then add Items 8 to 40.
  • Subscale scores can be obtained for (1) Reciprocal Social Interaction, (2) Communication, and (3) Restricted, Repetitive, and Stereotyped Patterns of Behavior. However, there is limited research about the subscales, and they are not available in the AutoScore forms.
  • For diagnostic screening purposes, the Lifetime form, which looks at the child’s entire development history, is used. Total scores above the cut-off (score of 15 in the original study by Berument et al., 1999) is indicative of possible ASD and warrants further assessment (e.g., Autism Diagnostic Interview, Revised (ADI-R)).
  • If scores are used to track potential change in severity of autism spectrum disorder symptoms, the Current form, which looks at the child’s last 3 months, should be used.

Number of Items

40

Equipment Required

  • Manual and forms

Time to Administer

Approximately 10 minutes or less minutes

Required Training

Reading an Article/Manual

Required Training Description

Parents can complete the questionnaire independently. However, interpretation and use should be undertaken by a professional who specializes in the care of autistic individuals. The clinician interpreting and using results for intervention should have (1) a master’s degree or related field (e.g., occupational therapy, speech-language pathology, social work, special education) or (2) a bachelor’s degree in psychology or related field plus license or certification that requires experience in assessment.

Age Ranges

Preschool

2 - 5

years

Child

6 - 12

years

Adolescent

13 - 17

years

Adult

18 - 64

years

Instrument Reviewers

Daphne Boucher MScOT (C); Chloe Orellana, MS, OTR; Liyi Straly, MS, OTR; and Brocha Stern, PhD, OTR/L, MOT (New York University)

ICF Domain

Participation

Measurement Domain

Cognition
Emotion
Participation & Activities

Professional Association Recommendation

None available--last searched on 5/31/2023.

Considerations

  • The SCQ is recommended to evaluate anyone over age 4.0, as long as their mental age exceeds 2.0 years.
  • The SCQ is a screening questionnaire and is not suitable for individual diagnosis.
  • Multiple translations are available

Intellectual Disability

back to Populations

Cut-Off Scores

Adults with Intellectual Disability (ID): (Sappok et al., 2015; n = 151; aged 15-76, mean age = 37.2 (12.8); n = 83 combined ID and ASD, n = 68 ID only; German sample)

  • Score of 15 suggestive of ASD
    • SCQ-Current: 98% sensitivity, 47% specificity
    • SCQ-Lifetime: 92% sensitivity, 22% specificity
  • Score of 18 on SCQ-Current highly suggestive of ASD: 89% sensitivity, 66% specificity
  • Score of 20 on SCQ-Lifetime highly suggestive of ASD: 79% sensitivity, 48% specificity

Normative Data

Adults with ID: (Sappok et al., 2015)

SCQ mean total scores (SD) by severity of intellectual disability, diagnosis, and SCQ version

SCQ-Current

    Total

    ASD

Non-ASD

All levels of ID

19.6 (6.1)

22.8 (4.1)

15.5 (5.6)

Mild ID

18.6 (7.6)

23.4 (6.4)

14.9 (6.5)

Moderate ID

19.4 (6.4)

23.4 (4.0)

14.7 (5.5)

Severe-Profound ID

20.2 (4.6)

21.9 (3.2)

17.4 (5.1)

SCQ-Lifetime

    Total

    ASD

Non-ASD

All levels of ID

22.9 (7.2)

24.4 (6.7)

19.5 (7.4)

Mild ID

22.7 (9.4)

27.8 (6.7)

15.3 (8.0)

Moderate ID

22.7 (6.2)

23.6 (6.1)

20.3 (6.4)

Severe-Profound ID

23.3 (7.2)

23.4 (7.5)

23.0 (7.0)

 

Criterion Validity (Predictive/Concurrent)

Adults with ID: (Sappok et al., 2015)

  • Adequate: ROC-AUC = 0.85 for SCQ-Current (cut-point of 15)
  • Adequate: ROC-AUC = 0.70 for SCQ-Lifetime (cut-point of 15)

Construct Validity

Adults with ID: (Sappok et al., 2015)

  • Excellent convergent validity between SCQ-Current and PDD-MRS (r = 0.62)
  • Adequate convergent validity between SCQ-Current and Autism Diagnostic Observation Schedule (ADOS) (r = 0.52)
  • Poor convergent validity between SCQ-Current and ADI-R (r = 0.09)
  • Excellent convergent validity between SCQ-Lifetime and ADI-R (r = 0.67)
  • Poor convergent validity between SCQ-Lifetime with PDD-MRS (r = 0.25)
  • Poor convergent validity between SCQ-Lifetime with ADOS (r = 0.01)

Pediatric Disorders

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Cut-Off Scores

Preschool children with developmental problems: (Allen et al., 2007; n = 81; aged 24-84 months)

  • Cut-off score of 15 indicative of ASD

Age

Sensitivity

Specificity

Total (2-6 years)

    60%

    70%

24-36 months

    56%

    29%

37-48 months

    82%

    79%

49-60 months

    40%

    85%

61-84 months

    25%

    85%

 

  • Cut-off score of 11 indicative of ASD

Age

Sensitivity

Specificity

Total (2-6 years)

    93%

    58%

24-36 months

    89%

    29%

37-48 months

   100%

    58%

49-60 months

   100%

    69%

61-84 months

    67%

    64%

 

Children with special education needs and in general population: (Chandler et al., 2007; At-risk subsample: n = 255, mean age 10.3 (0.4) years; Low-risk school subsample: n = 411, mean age 12.0 (0.3); General population subsample: n = 247, mean age 11.5 (0.6))

  • At-risk subsample: ≥15 as the cut-off to differentiate children with ASD from children with non‐spectrum diagnoses: 88% sensitivity, 72% specificity
  • At-risk subsample: ≥22 as the cut-off to differentiate children with childhood autism from those without autism, using clinical diagnosis as the gold standard: 90% sensitivity, 86% specificity

 

Children with special education needs: (Charman et al., 2007; n = 119; age range = 9-13 years, mean age = 10.2 (0.4))

  • Cut off score of ≥15 indicative of ASD: 86% sensitivity and 78% specificity

Children with possible ASDs or participants in autism research: (Corsello et al., 2007; n = 590; age range = 2-16 years old)

  • ≥15 as the cut-off to differentiate children with ASDs from children with non‐spectrum diagnoses

Age

Sensitivity

Specificity

Total (2-16 years)

    71%

    71%

< 5 years

    68%

    74%

5-7 years

    63%

    67%

8-10 years

    71%

    82%

>11 years

    80%

    66%
  • ≥22 as the cut-off to differentiate autism from no autism: 45% sensitivity, 84% specificity

Children in an autism clinic or preschool clinic: (Eaves & Ho, 2006; n = 151, female = 32), age range = 36-82 months, mean age = 61.5 months (9.2))

  • Cut-off score of ≥11 indicative of ASD: 91% sensitivity, 35% specificity
  • Cut-off score of ≥15 indicative of ASD: 71% sensitivity, 79% specificity.
  • An abbreviated version of the SCQ (includes only the 15 items that showed statistically significant differentiation of p < .05) improved screening accuracy with a cut-off score of ≥15: 78% sensitivity, 65% specificity

Children at high risk for Autism: (Oosterling et al., 2009; n = 238; age range = 8-44 months, mean age = 29.6 months (6.4); 90% Dutch sample)

  • Cut-off score of 11 for ASD vs. non-ASD: 84% sensitivity, 28% specificity
  • Cut-off score of 15 for ASD vs. non-ASD: 66% sensitivity, 64% specificity

ADHD: (Schwenck & Freitag, 2014; n = 216; mean age = 12.28 (2.87); German sample)

  • Cut-off score of 15 for differentiating between ASD and non-ASD: 78% sensitivity
  • Cut-off score of 11 for differentiating between ASD and non-ASD: 92% sensitivity

 

Group Comparison

Optimal Cut-off

Sensitivity

Specificity

ASD vs. typically developing

           9

    88%

    84%

Autism vs. typically developing

          11

    92%

    87%

ASD + ADHD vs. typically developing

          12

   100%

    90%

Autism vs. ADHD

          14

    83%

    92%

ASD vs. ADHD

          14

    68%

    92%

ASD + ADHD vs. ADHD

          15

    91%

    95%

 

School-aged children with ID: (Witwer & Lecavalier, 2007; n = 49; age range = 4-14 years, Pervasive Developmental Disorder (PDD) = 36 with mean age = 8.3 years (2.3), Intellectual Disability (ID) only = 13 with mean age = 10.2 (2.5))

  • Optimal cut-off score of 15 indicative of pervasive developmental disorder (PDD): 92% sensitivity, 62% specificity

 

Normative Data

Preschool children with developmental problems: (Allen et al., 2007)

  • Mild developmental disabilities mean score = 14 (3.7)
  • Mild/moderate developmental disabilities mean score = 19 (5.6)
  • Moderate developmental disabilities mean score = 19 (7.4)

 

Children with special education needs and in general population: (Chandler et al., 2007)

  • At-risk subsample:
    • Non-ASD weighted mean score = 10.8 (6.1)
    • Other ASD weighted mean score = 19.6 (6.6)
    • ASD mean weighted score = 26.6 (4.4)
  • Low-risk school subsample mean score = 4.1 (4.7)
  • General population subsample mean score = 4.7 (5.0)

 

Children with special education needs: (Charman et al., 2007)

  • Non-ASD mean score = 9.5 (1.1)
  • Other-ASD mean score = 19.2 (1.1)
  • Childhood autism mean score = 25.8 (0.5)

 

Children in an autism clinic or preschool clinic: (Eaves & Ho, 2006)

  • Verbal group (n = 121) mean score = 14.08
  • Nonverbal group (n = 30) mean score = 15.37

 

Children at high risk for autism: (Oosterling et al.)

  • Autism (n = 103) mean score = 18.4 (5.4)
  • ASD-other (n = 57) mean score = 14.7 (5.9)
  • Non-ASD (n = 78) mean score = 13.5 (5.4)

 

ADHD: (Schwenck & Freitag, 2014)

  • ADHD mean score = 7.94 (4.23)
  • ASD mean score: 16.64 (6.68)
  • ASD + ADHD mean score: 22.46 (5.70)
  • Typically developing mean score: 5.42 (3.73)

 

School-aged children with ID: (Witwer & Lecavalier, 2007)

  • PDD group mean score = 23.1 (6.3)
  • ID group mean score = 12.4 (6.0)

 

Criterion Validity (Predictive/Concurrent)

Children with special education needs and in general population: (Chandler et al., 2007)

  • At-risk subsample: Adequate: ROC-AUC = 0.88 (95% CI 0.82-0.93) – cut-off of ≥15 for discriminating ASD vs. non-ASD status
  • At-risk subsample: Excellent: ROC-AUC = 0.93 (95% CI 0.90-0.96) – cut-off of ≥22 for discriminating childhood autism vs. non-childhood autism

 

Children with special education needs: (Charman et al., 2007)

  • SCQ-lifetime cut off score of ≥15: Excellent: AUC = 0.90 for predicting ASD vs. non-ASD status
  • Excellent concurrent validity: correlation with ADI-R (r = 0.83)

 

Children with possible ASDs or participants in autism research: (Corsello et al., 2007)

  • Adequate: ROC-AUC = 0.77 – cut-off of ≥15 for discriminating ASD vs. non-ASD status
  • Adequate: ROC-AUC = 0.74– cut-off of ≥22 for discriminating childhood autism vs. non-childhood autism
  • Excellent concurrent validity: correlation between SCQ and ADI-R total scores (r = 0.73)

 

Children at high risk for Autism: (Oosterling et al., 2009; n= 238; Age 8-44 months, mean 29.6 months (6.4); Dutch sample)

  • Poor: ROC-AUC = 0.67 (95% CI 0.60-0.74) – cut-off of 11 or 15 for discriminating ASD vs. non-ASD status
  • Adequate: ROC-AUC = 0.74 (95% CI 0.68-0.81) – cut-off of 4 for discriminating ASD vs. non-ASD status with abbreviated 16-item SCQ

 

ADHD: (Schwenck & Freitag, 2014)

  • Substantial agreement between classification of SCQ with cut-off of 15 and diagnosis from Autism Diagnostic Observation Schedule/ADI-R: κ = .79

 

Group Comparison

Optimal Cut-off

   ROC-AUC

ASD vs. typically developing

           9

Excellent .94

Autism vs. typically developing

          11

Excellent: .97

ASD + ADHD vs. typically developing

          12

Excellent: .99

Autism vs. ADHD

          14

Excellent: .93

ASD vs. ADHD

          14

Adequate: .86

ASD + ADHD vs. ADHD

          15

Excellent: .98

 

School-aged children with ID: (Witwer & Lecavalier, 2007)

  • Excellent: ROC-AUC = 0.89 (95% CI, .80, .98) – cut-off of 15 for discriminating between PDD and non-PDD

 

Construct Validity

ADHD: (Schwenck & Freitag, 2014)

  • Adequate bivariate correlations between SCQ and ADHD symptom scores of Observer Rating Scale for ADHD for inattention (r = .40), hyperactivity (r = .40), and impulsivity (r = .35), highlighting good discriminant validity

 

Children in an autism clinic or preschool clinic: (Eaves & Ho, 2006)

  • Poor correlation with verbal and performance IQs (VIQ and PIQ): r = -.22 and -.23, respectively
  • Poor correlation with Vineland Adaptive Behavior Composite (VABC): r = -.30
  • Adequate correlation with Childhood Autism Rating Scale (CARS): r = .40

Congenital Disorders

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Cut-Off Scores

Down Syndrome: (Magyar et al., 2012; n = 447; age range = 4-14 years, 11 months)

  • SCQ-Lifetime (“SCQ-39”) cut-off score of 10.5: 73% sensitivity, 76% specificity
  • Abbreviated SCQ (“SCQ-31”) cut-off score of 6.5: 82% sensitivity, 68% specificity

Normative Data

Tuberous Sclerosis Complex (TSC): (Granader et al., 2010; n = 21; aged 5-18 years, mean age 10.14 (4.3) years)

  • Mean SCQ-Lifetime Total: 13.10 (SD 7.54)
  • 9 participants (42.9%) had scores above the cut-off of ≥15

Internal Consistency

Down Syndrome: (Magyar et al., 2012)

  • SCQ-Lifetime (“SCQ-39”): Excellent: Guttman's λ-2 = 0.88
  • Abbreviated SCQ (“SCQ-31”): Excellent: Guttman's λ-2 = 0.92

Criterion Validity (Predictive/Concurrent)

Down Syndrome: (Magyar et al., 2012)

  • SCQ-Lifetime (“SCQ-39”): Adequate: ROC-AUC = 0.78 (cut-off of 10.5)
  • Abbreviated SCQ (“SCQ-31”): Adequate: ROC-AUC = 0.82 (cut-off of 6.5)

Construct Validity

TSC: (Granader et al., 2010)

  • Excellent convergent validity of SCQ-lifetime total with Social Responsiveness Scale (r = 0.61)

 

Down Syndrome: (Magyar et al., 2012)

  • Excellent convergent validity of SCQ-Lifetime (“SCQ-3”) and ADI-R subscales (r ranged from .62-.80)
  • Excellent convergent validity on abbreviated SCQ-Lifetime (“SCQ-31”) and ADI-R subscales (r ranged from .60-.82)

Content Validity

Down Syndrome: (Magyar et al., 2012)

  • Exploratory and confirmatory factor analyses (n = 188 for each) identified two factors: “Social-Communication” and “Stereotyped Behavior and Unusual Interests”

Bibliography

Allen, C. W., Silove, N., Williams, K., & Hutchins, P. (2007). Validity of the Social Communication Questionnaire in assessing risk of autism in preschool children with developmental problems. Journal of Autism and Developmental Disorders, 37, 1272–1278. https://doi.org/10.1007/s10803-006-0279-7

Berument, S. K., Rutter, M., Lord, C., Pickles, A., & Bailey, A. (1999). Autism screening questionnaire: diagnostic validity. The British journal of psychiatry,175, 444–451. https://doi.org/10.1192/bjp.175.5.444

Chandler, S., Charman, T., Baird, G., Simonoff, E., Loucas, T., Meldrum, D., Scott, M., & Pickles, A. (2007). Validation of the Social Communication Questionnaire in a population cohort of children with autism spectrum disorders. Journal of the American Academy of Child & Adolescent Psychiatry, 46(10), 1324–1332. https://doi.org/10.1097/chi.0b013e31812f7d8d

Charman, T., Baird, G., Simonoff, E., Loucas, T., Chandler, S., Meldrum, D., & Pickles, A. (2007). Efficacy of three screening instruments in the identification of autistic-spectrum disorders. The British Journal of Psychiatry, 191(6), 554–559. https://doi.org/10.1192/bjp.bp.107.040196

Corsello, C., Hus, V., Pickles, A., Risi, S., Cook Jr., E. H., Leventhal, B. L., & Lord, C. (2007). Between a ROC and a hard place: Decision making and making decisions about using the SCQ. Journal of Child Psychology and Psychiatry, 48(9), 932–940. https://doi.org/10.1111/j.1469-7610.2007.01762.x

Eaves, L. C., Wingert, H. D., Ho, H. H., & Mickelson, E. C. R. (2006). Screening for autism spectrum disorders with the Social Communication Questionnaire. Journal of Developmental & Behavioral Pediatrics, 27(2), S95-S103. https://doi.org/10.1097/00004703-200604002-00007

Granader, Y. E., Bender, H. A., Zemon, V., Rathi, S., Nass, R., & MacAllister, W. S. (2010). The clinical utility of the Social Responsiveness Scale and Social Communication Questionnaire in tuberous sclerosis complex. Epilepsy & Behavior, 18(3), 262–266. https://doi.org/10.1016/j.yebeh.2010.04.010

Magyar, C. I., Pandolfi, V., & Dill, C. A. (2012). An initial evaluation of the Social Communication Questionnaire for the assessment of autism spectrum disorders in children with Down syndrome. Journal of Developmental & Behavioral Pediatrics, 33(2), 134–145. https://doi.org/10.1097/DBP.0b013e318240d3d9

Oosterling, I. J., Swinkels, S. H., van der Gaag, R. J. Visser, J. C., Dietz, C., & Buitelaar, J. K. (2009). Comparative analysis of three screening instruments for autism spectrum disorder in toddlers at high risk. Journal of Autism and Developmental Disorders, 39(6), 897–909. https://doi.org/10.1007/s10803-009-0692-9

Rutter, M., Bailey, A., & Lord, C. (2003). The Social Communication Questionnaire: Manual. Western Psychological Services.

Sappok, T., Diefenbacher, A., Gaul, I., & Bölte, S. (2015). Validity of the Social Communication Questionnaire in adults with intellectual disabilities and suspected autism spectrum disorder. American Journal on Intellectual and Developmental Disabilities, 120(3), 203–214. https://doi.org/10.1352/1944-7558-120.3.203

Schwenck, C., & Freitag, C. M. (2014). Differentiation between attention-deficit/hyperactivity disorder and autism spectrum disorder by the Social Communication Questionnaire. ADHD Attention Deficit and Hyperactivity Disorders, 6(3), 221–229. https://doi.org/10.1007/s12402-014-0147-9

Witwer, A. N., & Lecavalier, L. (2007). Autism screening tools: An evaluation of the Social Communication Questionnaire and the Developmental Behaviour Checklist–Autism Screening Algorithm. Journal of Intellectual & Developmental Disability, 32(3), 179–187. https://doi.org/10.1080/13668250701604776

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