Coronaviruses and people with intellectual disability: an exploratory data analysis.
CORD-19 hides piles of ID-relevant COVID-19 papers that text-mining can surface in minutes.
01Research in Context
What this study did
The team fed the giant CORD-19 paper pile into text-mining software. They pulled out every abstract that mentioned both COVID-19 and intellectual disability.
After the computer sorted the papers, humans read the clusters to see what themes popped up.
What they found
Out of thousands of COVID-19 articles, only 259 talked about people with intellectual disability. The papers fell into five big buckets like health risk and service access.
The authors say this tiny slice shows the field is ignoring a whole group that often needs extra help during a pandemic.
How this fits with other research
Day et al. (2021) also mined big data, but they used prison records instead of abstracts. They found just 4.3% of prisoners had ID flagged, hinting that official counts miss people—just like CORD-19 misses ID-COVID studies.
Moeyaert et al. (2020) explains how to combine small single-case studies with multilevel modeling. If anyone ever wants to pool the few ID-COVID behavior studies, that paper gives the recipe.
Perske (2008) lists 53 false confessions from people with ID. Both papers build lists that warn society: if we don’t look, we overlook real risks—whether it’s police pressure or virus exposure.
Why it matters
If you serve adults with ID, you now have proof the research base is thin. Use the five themes as a cheat-sheet when you write grants or train staff. Point to the gaps to justify extra PPE, clearer health education, or telehealth slots. You can even run a quick CORD-19 search yourself before choosing interventions—make sure evidence exists for your folks, not just the general public.
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02At a glance
03Original abstract
BACKGROUND: Corona virus disease 2019 (COVID-19) has been announced as a new coronavirus disease by the World Health Organization. At the time of writing this article (April 2020), the world is drastically influenced by the COVID-19. Recently, the COVID-19 Open Research Dataset (CORD-19) was published. For researchers on ID such as ourselves, it is of key interest to learn whether this open research dataset may be used to investigate the virus and its consequences for people with an ID. METHODS: From CORD-19, we identified full-text articles containing terms related to the ID care and applied a text mining technique, specifically the term frequency-inverse document frequency analysis in combination with K-means clustering. RESULTS: Two hundred fifty-nine articles contained one or more of our specified terms related to ID. We were able to cluster these articles related to ID into five clusters on different topics, namely: mental health, viral diseases, diagnoses and treatments, maternal care and paediatrics, and genetics. CONCLUSION: The CORD-19 open research dataset consists of valuable information about not only COVID-19 disease but also ID and the relationship between them. We suggest researchers investigate literature-based discovery approaches on the CORD-19 and develop a new dataset that addresses the intersection of these two fields for further research.
Journal of intellectual disability research : JIDR, 2020 · doi:10.5281/zenodo.3715506