R.grid
18/06/2026
๐ง๐ต๐ฒ ๐ฝ๐ฒ๐ผ๐ฝ๐น๐ฒ ๐๐ถ๐๐ต ๐๐ต๐ฒ ๐ต๐ถ๐ด๐ต๐ฒ๐๐ ๐๐๐ฝ๐ฝ๐ผ๐ฟ๐ ๐ป๐ฒ๐ฒ๐ฑ๐ ๐ฎ๐ฟ๐ฒ ๐ผ๐ณ๐๐ฒ๐ป ๐๐ต๐ฒ ๐น๐ฒ๐ฎ๐๐ ๐ฟ๐ฒ๐ฝ๐ฟ๐ฒ๐๐ฒ๐ป๐๐ฒ๐ฑ ๐ถ๐ป ๐๐ต๐ฒ ๐ฟ๐ฒ๐๐ฒ๐ฎ๐ฟ๐ฐ๐ต ๐บ๐ฒ๐ฎ๐ป๐ ๐๐ผ ๐๐ฒ๐ฟ๐๐ฒ ๐๐ต๐ฒ๐บ.
As ๐๐๐๐ถ๐๐๐ถ๐ฐ ๐ฃ๐ฟ๐ถ๐ฑ๐ฒ ๐๐ฎ๐ and ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐๐ถ๐๐ฎ๐ฏ๐ถ๐น๐ถ๐๐ ๐ช๐ฒ๐ฒ๐ธ overlap, itโs important to recognize that many autistic people with intellectual disability remain significantly underrepresented in research.
A widely cited analysis of more than 300 autism studies found that 94% of participants did not have intellectual disability, despite intellectual disability being far more common across the autistic population. Non-speaking and minimally verbal autistic people were almost entirely absent from research samples.
In other words, some of the people most affected by gaps in healthcare and support systems are also among the least represented in the evidence shaping their care.
Exclusion impacts the evidence itself. It influences what researchers understand, what healthcare systems prioritize, and which patient experiences are reflected in clinical decision-making.
Many of these barriers are structural:
โข ๐ฐ๐ผ๐ป๐๐ฒ๐ป๐ ๐ฝ๐ฟ๐ผ๐ฐ๐ฒ๐๐๐ฒ๐ ๐๐ต๐ฎ๐ ๐ฎ๐ฟ๐ฒ ๐ป๐ผ๐ ๐ฎ๐ฑ๐ฎ๐ฝ๐๐ฒ๐ฑ ๐ณ๐ผ๐ฟ ๐ฑ๐ถ๐ณ๐ณ๐ฒ๐ฟ๐ฒ๐ป๐ ๐ฐ๐ผ๐บ๐บ๐๐ป๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐ป๐ฒ๐ฒ๐ฑ๐
โข ๐๐ฒ๐ป๐๐ผ๐ฟ๐-๐ต๐ฒ๐ฎ๐๐ ๐ฐ๐น๐ถ๐ป๐ถ๐ฐ๐ฎ๐น ๐ฒ๐ป๐๐ถ๐ฟ๐ผ๐ป๐บ๐ฒ๐ป๐๐
โข ๐ฎ๐๐๐๐บ๐ฝ๐๐ถ๐ผ๐ป๐ ๐ฎ๐ฟ๐ผ๐๐ป๐ฑ ๐ฐ๐ฎ๐ฝ๐ฎ๐ฐ๐ถ๐๐ ๐ผ๐ฟ ๐ฝ๐ฎ๐ฟ๐๐ถ๐ฐ๐ถ๐ฝ๐ฎ๐๐ถ๐ผ๐ป
โข ๐๐ฟ๐ฎ๐๐ฒ๐น ๐ฎ๐ป๐ฑ ๐๐ฐ๐ต๐ฒ๐ฑ๐๐น๐ถ๐ป๐ด ๐ฟ๐ฒ๐พ๐๐ถ๐ฟ๐ฒ๐บ๐ฒ๐ป๐๐
โข ๐น๐ถ๐บ๐ถ๐๐ฒ๐ฑ ๐ฐ๐ผ๐บ๐บ๐๐ป๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ถ๐๐ต ๐ฐ๐ฎ๐ฟ๐ฒ๐ด๐ถ๐๐ฒ๐ฟ๐, ๐ฎ๐ฑ๐๐ผ๐ฐ๐ฎ๐๐ฒ๐, ๐ผ๐ฟ ๐๐๐ฝ๐ฝ๐ผ๐ฟ๐ ๐๐ฒ๐ฎ๐บ๐
โข ๐ฟ๐ฒ๐๐ฒ๐ฎ๐ฟ๐ฐ๐ต ๐๐ผ๐ผ๐น๐ ๐ฎ๐ป๐ฑ ๐๐ผ๐ฟ๐ธ๐ณ๐น๐ผ๐๐ ๐๐ต๐ฎ๐ ๐๐ฒ๐ฟ๐ฒ ๐ป๐ฒ๐๐ฒ๐ฟ ๐ฑ๐ฒ๐๐ถ๐ด๐ป๐ฒ๐ฑ ๐ถ๐ป๐ฐ๐น๐๐๐ถ๐๐ฒ๐น๐
These challenges extend far beyond autism-specific studies. An autistic person with intellectual disability participating in cancer research, cardiovascular research, mental health research, or any other clinical study may still encounter the same barriers.
Inclusivity depends on research environments and operational processes that recognize different communication styles, sensory needs, and lived experiences from the beginning.
When entire groups are consistently excluded from research, the evidence base becomes incomplete.
๐ง๐ต๐ผ๐๐ฒ ๐บ๐ถ๐๐๐ถ๐ป๐ด ๐ณ๐ฟ๐ผ๐บ ๐ฐ๐น๐ถ๐ป๐ถ๐ฐ๐ฎ๐น ๐ฟ๐ฒ๐๐ฒ๐ฎ๐ฟ๐ฐ๐ต ๐ฎ๐ฟ๐ฒ ๐๐ป๐ฑ๐ฒ๐ฟ๐ฟ๐ฒ๐ฝ๐ฟ๐ฒ๐๐ฒ๐ป๐๐ฒ๐ฑ ๐ถ๐ป ๐๐ต๐ฒ ๐ณ๐๐๐๐ฟ๐ฒ ๐ผ๐ณ ๐ต๐ฒ๐ฎ๐น๐๐ต๐ฐ๐ฎ๐ฟ๐ฒ.
As Pride Month begins, weโre sharing insights from A***n, Community Partnership Associate at Research Grid, on the importance of building stronger connections between research and the communities that have historically been overlooked or underserved within healthcare systems.
Across clinical research, there is growing recognition that broader representation improves the quality, relevance, and applicability of research. That includes strengthening understanding of how treatments work across different populations and helping research better reflect real-world patient experiences.
Long-term progress depends on sustained community engagement, accessible communication, and creating research environments where people feel informed, respected, and comfortable participating.
Through our work with a global network of 99,000+ community groups, we see firsthand how trust, visibility, and ongoing dialogue can help make research more inclusive and accessible over time.
More inclusive research leads to stronger data, more informed healthcare decisions, and ultimately better outcomes across patient populations.
๐ ๐บ๐ฎ๐ท๐ผ๐ฟ ๐ฏ๐น๐ถ๐ป๐ฑ ๐๐ฝ๐ผ๐ ๐ถ๐ป ๐บ๐ฒ๐ฑ๐ถ๐ฐ๐ถ๐ป๐ฒ ๐ถ๐ ๐๐ผ๐บ๐ฒ๐ปโ๐ ๐ต๐ฒ๐ฎ๐น๐๐ต.
For ๐ช๐ผ๐บ๐ฒ๐ปโ๐ ๐๐ฒ๐ฎ๐น๐๐ต ๐๐ฎ๐, weโre sharing insights from ๐ฃ๐ฟ๐ผ๐ณ. Bola Grace, PhD, MBA, Professor of Practice at UCL, on AI opportunities in advancing womenโs health research and care.
Womenโs health has historically been treated as a niche category in research despite impacting half the global population.
Prof. Grace, shares how AI can address longstanding gaps in womenโs health research, particularly in areas of menstrual health, diagnosis, treatment, and clinical understanding.
High quality, replicable data, in women's health relies on 2 key factors to reduce risk gaps:
1. More inclusive research practices that facilitate representation
2. Broadening access to participation in clinical studies
At Research Grid, we believe improving womenโs health outcomes starts with improving how research is delivered with smart technology that offers:
โข ๐ฏ๐ฒ๐๐๐ฒ๐ฟ ๐ฎ๐ฐ๐ฐ๐ฒ๐๐ ๐๐ผ ๐ฟ๐ฒ๐๐ฒ๐ฎ๐ฟ๐ฐ๐ต
โข ๐บ๐ผ๐ฟ๐ฒ ๐ฟ๐ฒ๐ฝ๐ฟ๐ฒ๐๐ฒ๐ป๐๐ฎ๐๐ถ๐๐ฒ ๐ฎ๐ป๐ฑ ๐ฟ๐ฒ๐๐ฎ๐ถ๐ป๐ฒ๐ฑ ๐ฒ๐ป๐ด๐ฎ๐ด๐ฒ๐บ๐ฒ๐ป๐
โข ๐ฟ๐ฒ๐ฑ๐๐ฐ๐๐ถ๐ผ๐ป ๐ถ๐ป ๐ผ๐ฝ๐ฒ๐ฟ๐ฎ๐๐ถ๐ผ๐ป๐ฎ๐น ๐ฏ๐ฎ๐ฟ๐ฟ๐ถ๐ฒ๐ฟ๐
โข ๐๐บ๐ฎ๐ฟ๐๐ฒ๐ฟ ๐ฎ๐ป๐ฑ ๐บ๐ผ๐ฟ๐ฒ ๐ฒ๐ณ๐ณ๐ถ๐ฐ๐ถ๐ฒ๐ป๐ ๐ถ๐ป๐ณ๐ฟ๐ฎ๐๐๐ฟ๐๐ฐ๐๐๐ฟ๐ฒ
Each of these plays a role in helping studies reach broader populations and generate better data, especially for women's health research.
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