ASD Knowledge Questionnaire (ASD-Q)

Abstract

The Autism Spectrum Disorder Knowledge Questionnaire (ASD-Q) is a 27-item psychometric measurement tool designed by Taresh et al. (2024) to evaluate early childhood educators’ foundational understanding of autism spectrum disorder (ASD) and their proficiency in identifying early behavioral manifestations. Originating from research conducted with preschool teachers in Yemen, the instrument synthesizes and refines items adapted from the Autism Stigma and Knowledge Questionnaire (Harrison et al., 2017) and the epidemiological knowledge surveys of Al-Sharbati et al. (2015). The ASD-Q is partitioned into four theoretically grounded domains: Diagnosis and Symptoms (10 items), Etiology (6 items), Treatment (6 items), and General Information (5 items). Psychometrically, the instrument demonstrates high internal consistency, exhibiting a full-scale Cronbach’s alpha of α = 0.89, with domain-level coefficients ranging from α = 0.68 for Etiology to α = 0.80 for General Information. The questionnaire serves as a primary outcome measure for evaluating pedagogical professional development programs, public health capacity-building initiatives, and epidemiological baseline knowledge in low- and middle-income countries (LMICs). By identifying gaps between scientific consensus and prevalent cultural misconceptions—such as vaccine-induced etiology or curability through dietary regimens—the ASD-Q provides a structured, empirically validated framework for improving frontline early identification and intervention referral pathways in early childhood educational settings.

Keywords

Autism Spectrum Disorder, ASD Knowledge Questionnaire, ASD-Q, preschool teachers, early childhood education, developmental screening, psychometrics, autism identification, teacher professional development, neurodevelopmental disorders

Authors

The ASD-Q was developed and validated by an international, multidisciplinary team of scholars specializing in developmental psychology, special education, and public health:

• Sahar Mohammed Taresh – Department of Psychology, Taiz University, Taiz, Yemen; Faculty of Social Sciences, Arts and Humanities, Lincoln University College, Petaling Jaya, Malaysia. Correspondence: [email protected]
• Laura M. Morett – Department of Educational, School & Counseling Psychology, University of Missouri, Columbia, MO, United States.
• Sumaia Mohammed Zaid – Department of Special Education, Faculty of Education, Sana’a University, Sana’a, Yemen.
• Samsilah Roslan – Faculty of Educational Studies, Universiti Putra Malaysia, Serdang, Malaysia. ORCID: 0000-0003-1795-1606.
• Mohammed Taresh Taleb – Department of Psychology, Taiz University, Taiz, Yemen.
• Pu Song – Guiyang Preschool Education College, Guiyang, China.
• Nor Aniza Ahmad – Faculty of Educational Studies, Universiti Putra Malaysia, Serdang, Malaysia.
• Sarah Noman – Faculty of Medicine & Health Sciences, Universiti Putra Malaysia, Serdang, Malaysia.

Purpose

The primary clinical and pedagogical purpose of the Autism Spectrum Disorder Knowledge Questionnaire (ASD-Q) is to systematically measure the knowledge base, conceptual accuracy, and diagnostic discernment of preschool educators regarding autism spectrum disorder. Early childhood educators occupy a unique, naturalistic observational vantage point. They interact with children during critical developmental windows (ages 2 to 6 years) when core social-communication impairments and repetitive behavioral patterns first become clinically noticeable in peer environments. Despite this frontline positioning, significant empirical literature indicates that early childhood educators across the globe—and particularly in low- and middle-income countries (LMICs) such as Yemen—frequently lack formal specialized training in neurodevelopmental conditions, leaving them vulnerable to widespread cultural myths, diagnostic confusion, and delayed referral behaviors.

The ASD-Q was specifically engineered to operationalize and evaluate the knowledge gains generated by targeted psychoeducational interventions, notably the Educational Module to Enhance ASD Identification (EMiASD). In research and applied settings, the instrument fulfills three major functional objectives:

• Needs Assessment and Gap Analysis: It serves as a diagnostic baseline metric to delineate specific thematic areas where teachers hold erroneous beliefs (e.g., attributing autism to emotional coldness in parenting, known historically as the “refrigerator mother” myth, or attributing etiology to routine childhood vaccinations).
• Intervention Efficacy Evaluation: It functions as a pre- and post-intervention assessment instrument in experimental and quasi-experimental trials, evaluating whether professional development programs succeed in transferring robust, evidence-based neurodevelopmental knowledge to educational staff.
• Epidemiological and Cross-Cultural Surveillance: It offers public health researchers a standardized scale to benchmark autism literacy across diverse institutional contexts, facilitating cross-national comparisons between Western educational cohorts and under-resourced educational ecosystems facing socio-political disruption.

From a theoretical perspective, the scale is premised on the principle that accurate factual knowledge is a non-negotiable prerequisite for behavioral competence: teachers cannot appropriately modify classroom environments, initiate supportive accommodations, or flag children for formal multidisciplinary developmental assessments if they cannot distinguish normative developmental variation from clinical signs of neurodivergence.

Psychological Construct

The underlying construct assessed by the ASD-Q is Autism Spectrum Disorder Knowledge and Pedagogical Literacy. This construct encompasses a multidimensional network of declarative, conceptual, and procedural knowledge regarding neurodevelopmental functioning as defined by contemporary nosological classifications, including the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) and the World Health Organization’s ICD-11. Rather than treating autism knowledge as a monolithic variable, the ASD-Q parses the construct into four interrelated psychological and clinical dimensions:

1. Diagnosis and Symptoms (10 Items)

This subscale evaluates an educator’s ability to identify the pathognomonic behavioral markers that constitute the core diagnostic criteria of ASD. It covers both social-communicative reciprocity impairments (e.g., atypical eye contact, difficulty interpreting emotional facial expressions, peer relational barriers, language delays) and restricted, repetitive patterns of behavior, interests, or activities (e.g., motor stereotypies such as hand-flapping or rocking, strict adherence to non-functional routines, idiosyncratic attachments to inanimate objects, and atypical sensory responsivity). Furthermore, it evaluates the critical differential ability to recognize that children with ASD have normative physical appearances and that ASD is clinically distinct from generalized intellectual disability.

2. Etiology (6 Items)

The etiology dimension captures understanding of the underlying causes and risk factors associated with ASD. It explicitly measures the respondent’s capacity to reject historically persistent, scientifically disproven psychogenic and environmental fallacies (such as the “refrigerator mother” hypothesis of parental emotional neglect or the MMR vaccine controversy) while simultaneously endorsing empirical neurobiological and genetic models (e.g., polygenic inheritance, structural brain connectivity differences, and prenatal environmental risk factors).

3. Treatment (6 Items)

This domain quantifies an educator’s discernment regarding evidence-based interventions versus pseudoscientific alternatives. It gauges recognition that autism is a chronic neurodevelopmental condition without a known pharmacological “cure,” validating the efficacy of early behavioral and developmental interventions—such as Applied Behavior Analysis (ABA), speech-language therapy, and structured special education. Crucially, it evaluates the rejection of unsubstantiated curative claims concerning dietary supplements or psychotropic medication monotherapies.

4. General Information (5 Items)

The general information subscale measures broad epidemiological and developmental literacy. Items probe awareness of the male-to-female sex ratio discrepancy (higher diagnosis rates among males), the chronological emergence of symptoms during infancy and toddlerhood (detectability prior to 36 months of age), the categorization of autism as a developmental disorder present from birth, and its lifelong developmental trajectory across the individual’s lifespan.

Theoretical Framework

The construction and validation of the ASD-Q are grounded in the convergence of several foundational psychological and health behavior frameworks:

Social Cognitive Theory and Self-Efficacy

According to Albert Bandura’s Social Cognitive Theory, human functioning is shaped by triadic reciprocal determinism involving cognitive personal factors, environmental influences, and overt behavioral patterns. Within this model, declarative knowledge serves as the cognitive foundation upon which perceived self-efficacy is constructed. A teacher who lacks clear mental models of autistic symptomatology cannot develop task-specific self-efficacy regarding early detection or classroom inclusion. The ASD-Q operationalizes the cognitive-informational pillar within Bandura’s architecture, asserting that enhanced knowledge directly bolsters teacher confidence and referral action.

The Theory of Planned Behavior

Formulated by Icek Ajzen, the Theory of Planned Behavior (TPB) posits that behavioral intentions and subsequent actions are governed by behavioral beliefs (attitudes toward the behavior), normative beliefs (subjective norms), and control beliefs (perceived behavioral control). In the context of early childhood neurodevelopmental screening, factual knowledge acts as a structural control belief. Misconceptions regarding autism (e.g., assuming ASD is identical to intellectual disability or that it is triggered by bad parenting) systematically warp teacher attitudes and reduce perceived control, suppressing referral intentions. The ASD-Q maps the exact informational distortions that disrupt the intention-to-refer pathway.

Health Belief Model in Educational Screening

Originally designed to explain public health actions, the Health Belief Model (HBM) posits that preventive or early detection behaviors depend on perceived susceptibility, perceived severity, perceived benefits, perceived barriers, and cues to action. When applied to educators acting as informal screening agents, accurate etiology and symptom literacy heighten perceived susceptibility and benefits of early intervention, while dispelling curative myths reduces complacency. In this paradigm, ASD-Q items serve as cognitive indicators of an educator’s readiness to respond to subtle clinical cues displayed by preschool children.

Validity

The psychometric evaluation of the ASD-Q in the foundational validation study by Taresh et al. (2024) established several layers of validity across cross-cultural and pedagogical parameters:

Content and Face Validity

The instrument was derived through systematic adaptation of two widely recognized metrics: the Autism Stigma and Knowledge Questionnaire (ASK-Q) (Harrison et al., 2017) and the epidemiological instrument formulated by Al-Sharbati et al. (2015). The initial pool of items was scrutinized by a panel of developmental psychologists, special education experts, and pediatric clinical specialists to ensure rigorous alignment with DSM-5 criteria and linguistic/cultural appropriateness for preschool teachers in the Middle East. Expert review confirmed that the 27 items comprehensively represented the target domains without semantic ambiguity or clinical inaccuracies.

Construct and Criterion Validity via Intervention Sensitivity

Construct validity was demonstrated utilizing a parallel mixed-methods, experimental-control intervention design. Yemeni preschool teachers exposed to the Educational Module to Enhance ASD Identification (EMiASD) exhibited statistically significant, substantial gains in ASD-Q scores from pre-test to post-test compared to the waitlist comparison control group. The large observed effect sizes confirmed the questionnaire’s sensitivity to meaningful cognitive change, verifying that the ASD-Q measures malleable conceptual understanding rather than fixed response sets or generalized academic intelligence.

Convergent and Discriminant Validity

The scale exhibited robust convergent validity through moderate-to-strong positive correlations with validated measures of teacher self-efficacy in autism screening and proactive referral attitudes. Conversely, discriminant validity was supported by low correlations with general teaching experience (measured in chronological years), demonstrating that general instructional tenure does not spontaneously produce neurodevelopmental diagnostic literacy in the absence of specialized training.

Reliability

The psychometric reliability of the ASD-Q was established through classical test theory metrics examining internal consistency across the complete scale and its isolated subdomains:

• Overall Full-Scale Reliability: The composite 27-item instrument demonstrated high internal consistency, yielding an overall Cronbach’s alpha of α = 0.89. This coefficient comfortably exceeds the standard scientific threshold (α ≥ 0.80) required for instruments used in group comparisons and program evaluation research.
• Domain-Level Internal Consistency:
  • General Information: α = 0.80, reflecting high homogeneity among items assessing epidemiological prevalence, onset windows, and developmental chronicity.
  • Diagnosis and Symptoms: α = 0.77–0.79 across sample subsets, demonstrating coherent covariance among items targeting socio-communicative deficits and repetitive sensory-motor patterns.
  • Treatment: α = 0.74, indicating solid internal consistency across questions contrasting evidence-based behavioral therapies with pseudoscientific medical claims.
  • Etiology: α = 0.68, representing an acceptable level of reliability for an exploratory six-item subscale that encompasses diverse causal domains (genetic inheritance, organic brain anomalies, vaccine fallacies, and psychogenic myths).

Furthermore, standard error of measurement (SEM) calculations confirmed tight precision intervals, indicating that teachers’ observed scores closely reflect their true latent level of autism spectrum disorder knowledge.

Factor Analysis

In the primary empirical investigation conducted by Taresh et al. (2024), formal exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were not conducted; instead, the researchers relied on a deductive, theoretically driven classification framework established by foundational predecessor scales (Harrison et al., 2017; Al-Sharbati et al., 2015). The 27 items were deductively mapped into the four conceptual factors:

• Factor 1: Diagnosis and Symptoms (10 items: 4, 6, 7, 8, 9, 10, 11, 12, 13, 27)
• Factor 2: Etiology (6 items: 14, 15, 16, 17, 18, 19)
• Factor 3: Treatment (6 items: 20, 21, 22, 23, 24, 25)
• Factor 4: General Information (5 items: 1, 2, 3, 5, 26)

From an advanced psychometric standpoint, the omission of latent structural equation modeling represents an important area for future psychometric refinement. Because knowledge metrics utilize dichotomous accuracy scoring (correct versus incorrect) or Likert ratings reflecting cognitive adherence to scientific facts, subsequent validation protocols should employ Item Response Theory (IRT)—specifically two-parameter logistic (2PL) models—alongside robust weighted least squares (WLSMV) confirmatory factor analyses. Such procedures will be necessary to definitively confirm factorial invariance across genders, educational tiers, and cultural geographies, while evaluating whether item discrimination parameters (α) and item difficulty thresholds (β) operate uniformly across global educator populations.

Instrument / Measurement Tool

The ASD-Q is an objective, standardized knowledge inventory optimized for both individual and group-based administrative protocols. Below are the structural and methodological parameters of the instrument:

• Instrument Type: Standardized Cognitive Inventory / Knowledge Survey
• Format: Paper-and-pencil self-administered questionnaire (adaptable to secure digital survey software)
• Target Respondent Population: Preschool teachers, early childhood educators, and daycare professionals (ages 18 to 64 years)
• Administration Time: Approximately 10 to 15 minutes
• Total Item Count: 27 discrete declarative items
• Response Scale: and Administration
• Scoring and Quantification Rules:
  • When administered as an objective knowledge assessment, items are scored dichotomously: 1 point for a correct answer that aligns with current empirical scientific consensus; 0 points for an incorrect answer or a “don’t know” response.
  • When completed using agreement gradations, responses indicating strong endorsement of scientific facts receive full credit, whereas endorsements of debunked myths receive zero credit.
  • Total Score Range: 0 to 27 points, with higher scores reflecting superior autism literacy, greater clinical symptom discernment, and fewer pseudoscientific misconceptions.
  • Subscale Subtotals:
    • Diagnosis and Symptoms: 0 to 10 points
    • Etiology: 0 to 6 points
    • Treatment: 0 to 6 points
    • General Information: 0 to 5 points

Permissions & Fee and Test Year

The Autism Spectrum Disorder Knowledge Questionnaire (ASD-Q) was published in 2024 in the peer-reviewed journal Autism. The instrument is accessible for non-commercial educational, clinical, and scientific research purposes under standard academic fair-use guidelines, provided appropriate citation is given to Taresh et al. (2024). No licensing fees or royalty payments are required for academic researchers or educational agencies conducting institutional evaluations. Researchers intending to translate, modify, or integrate the ASD-Q into commercial diagnostic platforms or proprietary professional development software should contact the corresponding author, Dr. Sahar Mohammed Taresh ([email protected]), to secure explicit written permission.

References

• Al-Sharbati, M., Al-Farsi, O., Ouhtit, A., Waly, M. I., Al-Shafaee, M., Al-Farsi, M., & Al-Khaduri, M. (2015). Awareness about autism among school teachers in Oman: A cross-sectional study. Research in Autism Spectrum Disorders, 15–16, 6–13. https://doi.org/10.1016/j.rasd.2015.01.001
• American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing. https://doi.org/10.1176/appi.books.9780890425596
• Harrison, A. J., Slane, M. M., Hoang, L., & Campbell, J. M. (2017). An international review of autism knowledge assessment measures. Autism, 21(3), 262–275. https://doi.org/10.1177/1362361316644728
• Harrison, A. J., Bradshaw, L. P., Naqvi, N. C., Paff, M. L., & Campbell, J. M. (2017). Development and psychometric evaluation of the Autism Stigma and Knowledge Questionnaire (ASK-Q). Journal of Autism and Developmental Disorders, 47(10), 3281–3295. https://doi.org/10.1007/s10803-017-3166-5
• Taresh, S. M., Morett, L. M., Zaid, S. M., Roslan, S., Taresh Taleb, M., Song, P., Ahmad, N. A., & Noman, S. (2024). Preschool teachers’ knowledge, beliefs, and self-efficacy concerning autism: A parallel mixed-methods study of an intervention to improve autism identification. Autism, 28(1), 239–253. https://doi.org/10.1177/13623613231211850

Items of the Scale