Employing computational linguistics techniques to identify limited patient health literacy: Findings from the ECLIPPSE study is a dataset published in Health Services Research (2020). On theSindex it has a DataRank of 0.829, placing it in the top 24.3% of the data-sharing corpus. It has been cited 23 times, with 18 citing works in its 1-hop citation network.
Ranks in the top 24% for downstream scientific impact
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.477
From this paper's citation signal
Citation Network Contribution
0.352
From 9 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 18 citers.
National Institutes of Health
Grant: NLM R01 LM012355
National Institute of Child Health and Human Development
Grant: R01 HD46113
Institute of Education Sciences
Grant: R305A180261
Office of Naval Research
Grant: N00014‐17‐1‐2300
National Institute of Diabetes and Digestive and Kidney Diseases
Grant: P30 DK092924
National Institute of Diabetes and Digestive and Kidney Diseases
Grant: R01 DK065664
NICHD NIH HHS
Grant: R01 HD046113
NLM NIH HHS
Grant: R01 LM012355
National Institutes of Health
Grant: 1R01DK065664-01A1
Ethnic Disparities in Diabetes Complications
National Institutes of Health
Grant: 1R01HD046113-01
Educational Disparities in Diabetes Complications
National Institutes of Health
Grant: 5R01LM012355-04
The Next Frontier in Diabetes Communication: Promoting Health Literacy in the Era of Secure Messaging
National Institutes of Health
Grant: 5P30DK092924-08
Health Delivery Systems Center for Diabetes Translational Research
FWCI
3.07
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals