About the report
Disability and Health Journal published this study in May 2025. Carlo Tramontano, Claudio Barbaranelli, Julia Carroll, Maria Deluca, Jenny Enderby, Nora Groce, and CIP’s Daniel Mont co-authored it. Mont also chaired the Washington Group’s Analytical Working Group, the team that helped develop the census and survey questions this new approach builds on.
Children with disabilities don’t fit neatly into one box. Yet most tools used to measure disability among children rely on a single cut-off point: a child either meets it, or doesn’t. New research co-authored by Daniel Mont of the Center for Inclusive Policy (CIP) takes a different approach to the Child Functioning Module (CFM), one designed to better reflect how disability actually manifests in children’s lives.
What Is the Child Functioning Module?
UNICEF and the Washington Group on Disability Statistics developed the CFM together. It asks about children’s difficulties across six areas: seeing, hearing, moving, communicating, thinking, and managing emotions. Countries collect this data through UNICEF’s Multiple Indicator Cluster Surveys (MICS). Today, it’s the main tool for comparing data on children with disabilities across countries, especially in low- and middle-income settings.
Why a Single Cut-Off Isn't Enough
The CFM uses cut-off points to count how many children have a disability. That works for headline numbers. But it hides something important: two children can cross the same cut-off and still need completely different support. One child might have difficulty walking and with self-care. Another might struggle with communication and emotional regulation. A single yes-or-no label can’t tell that story, and policymakers lose useful detail because of it.
A New Way to See the Data: Six Disability Profiles
The researchers used MICS data from seven African countries and tried a different method, in two steps.
Who Is Most Likely to Go Without Care Needs Satisfied?
People with self-care or communication-related functional difficulties were significantly more likely to report unsatisfied care needs. On the other hand, higher and having a job both reduced the likelihood of going without adequate care.
Step 1: Confirmatory Factor Analysis
First, they checked whether the six domains in the CFM held up statistically across countries. In other words, do children’s answers actually cluster the way the module assumes they will?
Step 2: Latent Profile Analysis
Then, they looked for natural groupings within that data. Instead of one dividing line, this method revealed six distinct profiles among children with disabilities. Each profile reflects a different combination of difficulties children face together, not just how many boxes they check.
What Does This Mean for Policy?
This shift matters for real decisions. Instead of one flat number, governments and service providers get a clearer picture of who needs what kind of support. Education systems, health services, and social protection programs can respond to the actual needs of children with disabilities, not a single broad category. It also opens up better ways to think about developmental disability worldwide, and how resources get shared once “disability” stops meaning just one thing.
