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Screening for Autism Spectrum Disorders in Low and Middle Income Countries: An Integrative Review
In many low-resource communities globally, screening all children for Autism Spectrum Disorder (ASD) at clinical or educational settings is currently infeasible due to a lack of clinical and professional resources. Multistage case identification using standardized screening and diagnostic tools seems the most feasible option for epidemiological studies of ASD in these settings. However, little is known about the use of ASD screening tools outside of the higher income nations in which they were first developed and validated. The reported psychometric properties of ASD screeners in low-resource settings have not been compared across studies to provide guidance for screener selection. Additionally, recent studies suggest that variation may exist in the cross-cultural appropriateness of screener measures and administration methods.
Objectives:
To review the use of standardized screening tools in low-resource settings and to make recommendations for screening instrument selection and screening approaches in these settings.
Methods:
An integrative review was conducted to understand the use of ASD screening instruments in low- and middle-income countries from studies published between 1992 and 2014. Studies had to use or adapt an established ASD screener in a World Bank designated low or middle-income country and be published in English.
Results:
Twenty-one studies met the inclusion criteria and were reviewed: two were in low-income countries and nineteen in middle-income countries. Among these twenty-one, seventeen different screening instruments were used. Study populations ranged from children ages 18 months to adult. Of the twenty-one studies, thirteen reported psychometrics.
Common screeners included the Modified Checklist for Autism in Toddlers (M-CHAT) (sensitivity ranged 0.25-0.86, specificity ranged 0.77-0.80), Autism Behavior Checklist (sensitivity ranged 0.78-0.98, specificity 0.91) and the Social Communication Questionnaire (sensitivity ranged 0.66-0.94, specificity ranged 0.70-0.89). Sixteen studies assessed or sampled children in a clinical setting. Five studies were non-clinical, community-based. Two out of these five reported psychometric properties: the Twenty-Three questions (23Q) (sensitivity ranged 0.55-0.80, specificity ranged 0.77-0.92) in a Ugandan sample and M-CHAT (sensitivity 0.25, specificity: 0.77) in a Sri Lankan sample.
The majority of screening tools were administered to parents as self-complete. Due to study populations’ reported low-literacy and unfamiliarity with completing checklists, four studies administered screeners through an interview with caregivers. Translation and cultural adaptation of screeners were rarely reported or defined. Four studies reported collaboration with local community organizations and clinical resources during study design, recruitment, or screener translation and validation.
Conclusions:
This review found that seventeen different ASD screeners have been used in low-and middle-income settings with wide ranges of sensitivity and specificity. Clinical-based screening for ASD was the most widely reported method. However, community-based screening was also shown to be an effective method for identifying ASD in communities with limited clinical resources. Few studies reported collaboration with local community and clinical resources to ensure appropriate screener adaptation and study design, a practice in other branches of global mental health research. Improved reporting of psychometrics as well as screener administration and adaptation methods will enable the field to establish best practices for ASD research in low-resource settings globally.
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