Autism Spectrum Disorder Analysis Dashboard

Published November 27, 2025

Data Analytics Software QA Janaka Alwis

Introduction

The Autism Spectrum Disorder (ASD) Analysis Dashboard with Dashtera is an advanced analytical solution designed to explore the relationships between behavioral traits, demographic factors, and autism screening results in adults. Dashtera serves as the backbone of this analysis, leveraging interactive visualizations to transform raw ASD screening data into actionable insights.

With its user-friendly interface, Dashtera enables healthcare professionals, researchers, and data scientists to:

Visualize demographic and regional ASD screening patterns.
Identify key behavioral and medical risk factors.
Support predictive modeling and decision-making for autism screening.

This article demonstrates how Dashtera uses the Autistic Spectrum Disorder Screening Data for Adults to create factor-specific dashboards, uncovering meaningful connections between behavioral features, demographics, and ASD outcomes.

Dataset

The dashboards are based on the Autistic Spectrum Disorder Screening Data for Adults, originally curated by Fadi Fayez Thabtah at the Manukau Institute of Technology, New Zealand.

The dataset combines behavioral screening scores (AQ-10 questionnaire) with demographic and individual characteristics to help classify adults as likely ASD-positive or ASD-negative.

Total Records: 704 individuals
Attributes: 21 features (10 behavioral + 10 demographics + 1 class variable)
Target Variable: ASD screening result (YES = Likely ASD, NO = Not likely ASD)
Contains Missing Values: Yes (e.g., ethnicity, relation fields)

Key Variables

Variable	Description
A1–A10 Scores	Ten binary behavioral traits from the AQ-10 screening test
age	Age of the individual (numeric, ≥18)
gender	Male or Female
ethnicity	Ethnic background (multiple categories)
jundice	Whether the individual had neonatal jaundice
austim	Family history of autism
contry_of_res	Country of residence
used_app_before	Whether the individual previously used the ASD app
relation	Who filled in the test (Self, Parent, Healthcare Professional, Relative, Others)
result	Screening score (0–10, sum of A1–A10)
Class/ASD	Target outcome (YES = ASD-positive, NO = ASD-negative)

About Dashtera

What is Dashtera?

Dashtera is a cloud-based, no-code dashboard platform that allows users to connect data sources and create interactive dashboards without programming. It empowers both beginners and advanced users to transform medical and behavioral datasets into insightful dashboards.

Key Features

Connects to various data sources (CSV, Excel, APIs, etc.)
Wide range of chart types, including advanced statistical visuals
Interactive drill-downs and dynamic filters
Shareable dashboards with flexible layouts
Supports calculated fields and transformations
User-friendly drag-and-drop interface

Advantages Over Similar Tools

Extremely easy to use—minimal technical expertise required
Rapid dashboard creation and deployment
Suitable for both beginners and advanced users
Lightweight yet powerful compared to Tableau or Power BI

Dashboard

Demographic Analysis

The Demographic Analysis Dashboard focuses on understanding participant distribution, demographics, and general ASD prevalence.

Charts Included

Participant Count by Country (Map chart)
ASD Percentage by Country (Map chart)
Gender Distribution (Pie chart) → Male: 52%, Female: 48%
ASD Class Distribution (Pie chart) → Yes: 27%, No: 73%
Previous App Usage (Pie chart) → Only 12 of 704 participants had used the app before
Ethnicity of ASD (Bar chart)
Relation vs Class (Bar chart)

Insights

Most participants are from Western countries, but representation spans over 50 nations.
Only 27% screened positive for ASD, while the majority (73%) screened negative.
The gender split is nearly even, reflecting balanced participation.
The relation factor shows that self-report dominates:
- Self-reported: 522 participants (365 No, 157 Yes).
- Parents, relatives, and healthcare professionals contribute smaller counts.
Missing/unknown relations appear in 95 cases, mostly with negative ASD classification.

Risk Factors Analysis

The Risk Factors Dashboard investigates medical and family-related risk factors, such as autism history and neonatal jaundice.

Charts Included

Autism Family History (Box Plot, Bar chart, Heatmap)
Jaundice at Birth (Box plot, Bar chart, Heatmap)

Insights

Family history of autism shows a significant correlation with positive ASD outcomes, confirming its role as a strong predictive factor.

Jaundice at birth displays weaker but noticeable differences in ASD prevalence. Participants with jaundice have slightly higher ASD screening positivity compared to those without.

Heatmaps make it easy to see clusters of high-risk categories when combining family history and jaundice with other factors.

Behavioral Features Analysis

The Behavioral Features Dashboard focuses on the AQ-10 screening results, which are the strongest indicators of ASD.

Charts Included

Screening Result vs Class (Bar chart)
ASD “Yes” Spider Chart (AQ-10 item analysis)
ASD “No” Spider Chart (AQ-10 item analysis)

Insights

Screening Score Trends:
- Scores 0–6 are mostly classified as NO (negative).
- Scores 7–10 strongly align with YES (positive).
- Threshold of ≥7 appears to be the cutoff for likely ASD.

Spider Chart (YES group):

- High agreement on A6, A9 (above 65%), showing strong autistic trait indicators.
- Traits like A5 and A8 have moderate agreement but still contribute.

Spider Chart (NO group):

- Opposite trends—participants mostly answered “0” (no autistic trait) across AQ-10 items.
- For example, A1, A3, and A4 show over 90% “0” responses, indicating typical behavioral patterns.

Autism-Spectrum Quotient

The AQ-10 (Autism-Spectrum Quotient – 10 item version) consists of the following standard questions.

These are designed to quickly screen for autistic traits in adults:

AQ-10 Item	Question (paraphrased for clarity)
A1	I often notice small sounds when others do not.
A2	I usually concentrate more on the whole picture, rather than on the small details.
A3	I tend to notice patterns in things all the time.
A4	I usually prefer to do things the same way over and over again.
A5	I find it difficult to work out people’s intentions.
A6	I prefer to do things alone rather than with others.
A7	I am fascinated by numbers or patterns.
A8	I find social situations easy.
A9	I frequently get so absorbed in one thing that I lose sight of other things.
A10	I find it difficult to make small talk with people.

Scoring:

Each answer indicative of an autistic trait is scored 1, otherwise 0.
Total score: 0–10
Cutoff: Usually >6 indicates a need for further diagnostic assessment.

These are the standard questions used internationally, so your dataset’s A1_Score to A10_Score corresponds directly to these questions, encoded as binary features.

Conclusion

The Autism Spectrum Disorder Analysis Dashboard with Dashtera bridges behavioral data analytics and medical screening, offering actionable insights into ASD prevalence and risk factors. It transforms the ASD screening dataset into an interactive tool that helps:

Healthcare professionals identify high-risk adults for referral.

Researchers uncover correlations between behavioral traits and medical/demographic factors.

Data scientists build predictive models for ASD screening and diagnosis.

By integrating demographic, risk factors, and behavioral dashboards with summary views, Dashtera empowers data-driven decision-making in autism screening research and healthcare.

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