Abstract

This paper explores the validity (sensitivity and specificity) of different cut-off levels of the UNICEF/Washington Group Child Functioning Module (CFM) and the inter-rater reliability between teachers and parents as proxy respondents, for disaggregating Fiji’s education management information system (EMIS) by disability. The method used was a cross-sectional diagnostic accuracy study comparing CFM items to standard clinical assessments for 472 primary school aged students in Fiji. Whilst previous domain-specific results showed “good” to “excellent” accuracy of the CFM domains seeing, hearing, walking and speaking, newer analysis shows only “fair” to “poor” accuracy of the cognitive domains (learning, remembering and focusing attention) and “fair” of the overall CFM (area under the Receiver Operating Characteristic curve: 0.763 parent responses, 0.786 teacher responses). Severe impairments are reported relatively evenly across CFM response categories “some difficulty”, “a lot of difficulty” and “cannot do at all”. Most moderate impairments are reported as “some difficulty”. The CFM provides a core component of data required for disaggregating Fiji’s EMIS by disability. However, choice of cut-off level and mixture of impairment severity reported across response categories are challenges. The CFM alone is not accurate enough to determine funding eligibility. For identifying children with disabilities, the CFM should be part of a broader data collection including learning and support needs data and undertaking eligibility verification visits.

Highlights

  • It is critical that education data systems are disaggregated by disability to measure progress in achieving access to quality education for children with disabilities, and efforts to enable this are moving forward globally

  • This paper focuses on the performance of the Child Functioning Module (CFM) as a whole

  • This study used a draft of the CFM (5–17 year age group) current at February 2015, with permission from UNICEF and the Washington Group

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Summary

Introduction

It is critical that education data systems are disaggregated by disability to measure progress in achieving access to quality education for children with disabilities, and efforts to enable this are moving forward globally. Disability-disaggregated education data are required to track progress towards various frameworks including the Convention on the Rights of Persons with Disabilities (CRPD) [1], the Sustainable Development Goals (SDG) [2] and the Incheon Strategy to “Make the. Information Systems (EMISs) by disability, and the importance of doing so using tools which are valid and internationally comparable [2,4,5]. Given the complexity of disability measurement, efforts to develop and agree upon tools for disability measurement that are valid, feasible and comparable have taken statisticians and researchers decades.

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