ArticleJournal of Korean medical science2026
Validation of Self-Reported Disease History in Korea: A National Health Insurance Cohort Study.
Article in Journal of Korean medical science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
backgroundSelf-reported disease history is widely used in epidemiological studies but is susceptible to misclassification. This study aimed to evaluate the accuracy of self-reported history of hypertension, diabetes, dyslipidemia, and stroke in Korea and to identify factors associated with reporting accuracy.
methodsWe analyzed data from the National Health Insurance Service (NHIS)-National Sample Cohort (2002-2019) for participants aged ≥ 40 years who underwent health check-ups (n = 312,367 for hypertension, 291,356 for diabetes, 289,596 for dyslipidemia, and 278,296 for stroke). Self-reported disease history was compared with medical claims records, which served as the reference standard for diagnosis history. Sensitivity, specificity, positive predictive value, negative predictive value, and observed agreement were calculated. Logistic regression models identified factors associated with false negative responses.
resultsSelf-reported prevalence was substantially lower than claims-based prevalence across all conditions: hypertension (33.9% vs. 47.9%), diabetes (15.0% vs. 36.1%), dyslipidemia (14.7% vs. 66.8%), and stroke (2.0% vs. 7.7%). Sensitivity was highest for hypertension (69.9%), followed by diabetes (40.7%), dyslipidemia (21.6%), and stroke (21.8%). Specificities exceeded 99% for all conditions. Factors reflecting greater healthcare engagement-advanced age and higher comorbidity burden-were associated with better reporting accuracy. Longer duration since initial diagnosis improved sensitivity for chronic conditions, while longer time since last hospital visit decreased sensitivity for hypertension and dyslipidemia.
conclusionSelf-reported disease history in the NHIS health check-up demonstrates high specificity but variable sensitivity across conditions, with underreporting being the primary concern. Temporal factors and healthcare engagement patterns significantly influence reporting accuracy. Our disease-specific validation parameters provide essential benchmarks for bias correction in epidemiological research and clinical practice in Korea, particularly for conditions with lower reporting sensitivities.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.