Validating the UNICEF/Washington Group Child Functioning Module as a method for disaggregating Fiji’s Education Management Information System
AffiliationNossal Institute for Global Health
Document TypePhD thesis
Access StatusOpen Access
© 2019 Dr. Beth Sprunt
Disability disaggregation of education management information systems (EMIS) is vital to inform policies and resourcing for disability-inclusive education and evaluate progress towards targets. The approach to disaggregation must use a valid and reliable method for identifying children with disabilities. The UNICEF/Washington Group Child Functioning Module (CFM) is recommended by the United Nations for identifying children with disabilities and has been recommended for disaggregating education program data by disability. In the context of an education sector support program in Fiji, this research aimed to validate a method for disaggregating Fiji’s EMIS by disability. A cross-sectional diagnostic accuracy study was undertaken in which teacher and parent CFM responses for 472 primary-aged students were compared to reference standard clinical assessments in five domains: vision, hearing, musculoskeletal, speech and cognition. Receiver operating characteristic curves (depicting the trade-off between sensitivity and specificity) were constructed and optimal cut-off points and inter-rater reliability were assessed. Nested survey data on learning and support needs were analysed to explore whether combining CFM data on activity and participation data with data on environmental factors related to LSN (educational adjustments, assistive technology and personal assistance requirements) more accurately identifies children with disabilities. The study produced a range of novel findings. Diagnostic accuracy of parent observations related to seeing, walking and speaking was stronger than that of teachers, however teacher accuracy was very acceptable. Conversely, for cognitive domains teacher accuracy was far stronger than parents. The CFM domains seeing, hearing, walking and speaking showed “good” to “excellent” accuracy, however remembering and focusing attention showed only “fair” to “poor” accuracy. The domain learning was “good” with teachers as respondents, but only “fair” with parent respondents. As a whole, the CFM had “fair” accuracy (area under the Receiver Operating Characteristic curve: 0.763 parent responses, 0.786 teacher responses). Severe impairments were reported relatively evenly across CFM response categories “some difficulty”, “a lot of difficulty” and “cannot do at all”. If the cut-off level for identifying children with disabilities were “a lot of difficulty”, nearly 40% of children with moderate clinical impairments and 28% of children with severe impairments would miss out on services as they were reported as having “some difficulty”. On the other hand, the rates of false positives would be very high if the cut-off “some difficulty” were used. Combining data from the CFM with LSN data shows potential to increase the accuracy of domain-specific disability identification and, crucially, identification of children with disabilities amongst those reported as having “some difficulty” on the CFM. The CFM alone is not accurate enough for the purpose of disaggregating Fiji’s EMIS by disability. The choice of cut-off level and the mixture of severity of impairments reported across response categories are particular challenges for the CFM. Combining CFM data with data on educational adjustments, assistive technology and personal assistance requirements could improve disability identification accuracy. Follow-up verification visits are required to confirm funding eligibility due to inherent risks of tools based on self-report.
KeywordsUNICEF/Washington Group Child Functioning Module; disability disaggregation; education management information system; validation; Fiji
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