Diagnosing autism in low‐income countries: Clinical record‐based analysis in Sri Lanka

Hashan Peiris, Darshana Chitraka Wickramarachchi, Pradeepa Samarasinghe, Philip Vance, Dulangi Dahanayake, Veerandi Kulasekara, Madhuka Nadeeshani

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Article number1367
Pages (from-to)1358-1367
Number of pages10
JournalAutism Research
Volume15
Issue number7
Early online date16 Jun 2022
DOIs
Publication statusPublished (in print/issue) - 1 Jul 2022

Bibliographical note

Funding Information:
Grant Sponsor: Accelerating Higher Education Expansion and Development (AHEAD) Operation of the Ministry of Higher Education of Sri Lanka funded by the World Bank ( https://ahead.lk/result-area-3/ ).

Publisher Copyright:
© 2022 International Society for Autism Research and Wiley Periodicals LLC.

Keywords

  • ASD
  • ASD Diagnosing Standards
  • ASD Predictors
  • autism
  • CARS
  • classification
  • cultural factors
  • logistic regression
  • low-income countries
  • ASD diagnosing standards
  • ASD predictors
  • Poverty
  • Autistic Disorder/diagnosis
  • Humans
  • Child, Preschool
  • Male
  • Female
  • Retrospective Studies
  • Sri Lanka/epidemiology
  • Child
  • Autism Spectrum Disorder/diagnosis

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