ArticleScientific reports2022
Visualization of estimated prevalence of CES-D positivity accounting for background factors and AIS scores.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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
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Who cites it
2 citing papers in PubMed.
- Article
- A review of sleep-related indicators measured in large population-based cohort studies in Japan.Environmental health and preventive medicine · 2026Review
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Development of methods for population screening is necessary to improve the efficiency of secondary prevention of diseases. Until now, a common cutoff has been used for all people in the data set. However, if big data for health information can be used to modify individual cutoffs according to background factors, it may avoid wasting medical resources. Here we show that the estimated prevalence of the Center for Epidemiologic Studies Depression Scale positivity can be visualized by a heatmap using background factors from epidemiological big data and scores from the Athens Insomnia Scale. We also show that cutoffs based on the estimated prevalence can be used to decrease the number of people screened without decreasing the number of prevalent cases detected. Since this method can be applied to the screening of different outcomes, we believe our work can contribute to the development of efficient screening methods for various diseases.
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