Diagnosing autism in low-income countries: Clinical record-based analysis in Sri Lanka.
Seven everyday behaviors can flag autism when gold-standard tools are too pricey or heavy.
01Research in Context
What this study did
Doctors in Sri Lanka built a seven-item checklist for autism. They called it CDAS.
They tested it on kids who already had a CARS score. CARS is the long gold-standard test.
The team wanted a tool that works where money, staff, and time are tight.
What they found
The short list matched the long test well enough. Eye contact, pointing, and hand-flap were top red flags.
A simple yes/no tree with only seven questions caught most cases.
How this fits with other research
Bao et al. (2017) looked at 18 different screens used in poor countries. They said, "We need one agreed-upon short tool." CDAS answers that call.
Dudley et al. (2019) made a 28-picture screener for U.S. toddlers who can’t read. CDAS does the same job with only seven words, so it fits clinics with no books or tablets.
Kakooza-Mwesige et al. (2014) added autism items to a 23-question household survey in Uganda. CDAS keeps the idea brief but moves the screen from doorsteps to hospital desks.
Why it matters
If you work in rural clinics, refugee camps, or telehealth with spotty Wi-Fi, you can still screen. Ask the seven questions, follow the tree, and refer when two or more red-flag behaviors show up. No kit, no cost, no extra staff.
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02At a glance
03Original abstract
Use of autism diagnosing standards in low-income countries (LICs) are restricted due to the high price and unavailability of trained health professionals. Furthermore, these standards are heavily skewed towards developed countries and LICs are underrepresented. Due to such constraints, many LICs use their own ways of assessing autism. This is the first retrospective study to analyze such local practices in Sri Lanka. The study was conducted at Ward 19B of Lady Ridgeway Hospital (LRH) using the clinical forms filled for diagnosing ASD. In this study, 356 records were analyzed, from which 79.5% were boys and the median age was 33 months. For each child, the clinical form together with the Childhood Autism Rating Scale (CARS) value were recorded. In this study, a Clinically Derived Autism Score (CDAS) is obtained from the clinical forms. Scatter plot and Pearson product moment correlation coefficient were used to benchmark CDAS with CARS, and it was found CDAS to be positively and moderately correlated with CARS. In identifying the significant variables, a logistic regression model was built based on clinically observed data and it evidenced that "Eye Contact," "Interaction with Others," "Pointing," "Flapping of Hands," "Request for Needs," "Rotate Wheels," and "Line up Things" variables as the most significant variables in diagnosing autism. Based on these significant predictors, the classification tree was built. The pruned tree depicts a set of rules, which could be used in similar clinical environments to screen for autism. LAY SUMMARY: Screening and diagnosing autism in low-income countries such as Sri Lanka has always been a challenge due to limited resources and not being able to afford global standards. Due to these challenges, locally developed clinical forms have been used. This study is the first to analyze a clinical record set for autism in Sri Lanka to benchmark the local clinic form with a global standard. Furthermore, this study identifies the most significant diagnostic symptoms for children and based on these significant features, a simple set of IF-THEN rules are derived which could be used for screening autism in a similar clinical environment by health officials in the absence of consultants.
Autism research : official journal of the International Society for Autism Research, 2022 · doi:10.1002/aur.2765