How to Collect Data on Disability


By: EducationLinks, USAID

In recent years, there has been a paradigm shift in the way we perceive disability. Once regarded as a medical problem that requires fixing, disability is now largely viewed through a social construct lens, in which we acknowledge that society creates barriers—environmental, attitudinal and institutional—that limit opportunities for certain individuals to participate in society on an equal basis as others. 

Education is no stranger to these barriers; children and youth with disabilities face numerous obstacles to accessing education. A first step toward addressing these barriers is to collect data on learners with disabilities to design, monitor and evaluate inclusive education programs. USAID Education activities are required to report data on learners with disabilities, and the Center for Education provides disability data guidance and tools to assist Missions and Implementing Partners. 

The foundation for USAID’s guidance is the social model of disability and the Washington Group on Disability Statistics (WG) approach to collecting data on disability. Aligning with the World Health Organization’s conceptual framework for measuring disability, the WG created the WG Short Set of Questions on Disability (WG Short Set) to produce data comparable across countries, which helps standardize global data collection and ensure consistency in reporting on indicators. The WG questions are designed to focus on levels of difficulty doing daily activities like walking, seeing and hearing that a person may experience in an unaccommodating environment. As of 2021, over 75 countries use this method.




Best Practices for Collecting Data in Disabilities

We’ve provided the tips below to help you collect data on learners with disabilities.

Use the right tools 

Select a data collection tool whose purpose aligns with yours. Misalignment between your data collection tool and the purpose could lead to the wrong conclusions. The interactive Disability Identification Tool Selection Guide helps researchers select the tools that most closely align with their data collection purpose. Before applying a new data collection tool, remember to allow time for pilot testing and analysis to confirm the tool’s validity.

Select the right respondents and interviewers. Once you have the right data collection tool, it’s important to work with respondents and interviewers to validate that tool. For example, the Child Functioning Module (CFM) has been validated for use with trained interviewers and with parents or legal guardians as respondents. This tool should not be used with children and youth as respondents unless it’s pilot-tested with that group first. When possible, recruit persons with disabilities as interviewers.

Get the right sample size. Make sure you have a sufficiently large sample because the ability to disaggregate by type of disability, sex, or other factors may be limited if the sample size is not large enough. To fully understand marginalization and its effects, disaggregation analyses can be very important.

Set considerations. When collecting data at the school level for prevalence purposes, consult evidence from household-based surveys, which can capture information on out-of-school children and youth not captured in school-based surveys.

Adapt and translate your tools. Some tools may need to be translated and adapted to be appropriate for respondents’ language and culture. When translating and adapting these tools, make sure that questions retain their original meaning and that resulting data are

comparable and accurate. The WG provides guidance to ensure that translated questionnaires maintain equivalence of measurement across languages and dialects.

Conduct the proper training. Those involved in data collection should receive the right training. As with the application of any survey, training content and duration can vary considerably. To learn more about how to obtain well-trained interviewers and high-quality data, check out our guide on Best Practices in Generating Data on Learners with Disabilities.

Provide accommodations as needed. Provide accommodations like sign language interpreters, interviewers who can sign, or large script and/or braille questionnaires to ensure equal participation and representation of persons with disabilities. Reasonable accommodations should be made available for both respondents and interviewers with disabilities. Where identified respondents are unable to respond (even with the provision of reasonable accommodations), researchers may, on a case-by-case basis, attempt to identify an appropriate proxy respondent who knows the respondent well and can answer on their behalf, consistent with data privacy protections and IRB approval. 

Be ethical. Given the sensitive nature of data on individuals with disabilities, take into account particular considerations regarding consent and assent requirements and the use and dissemination of resulting data. These requirements may differ when data are being collected for individual identification versus prevalence or data disaggregation purposes and depending on who the respondent is. See more ethical considerations you should be aware of here


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