ArticleCureus2026
ItemSight: Development of a Shiny Application for Simplified Item Analysis of Type A Multiple-Choice Questions.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Item analysis is a vital step in educational assessment to check the quality of multiple-choice questions (items). Traditional item analysis methods using spreadsheets or statistical software are often time-consuming, error-prone, and challenging for educators with limited programming expertise. To address these issues, ItemSight, an intuitive software for item analysis, was developed to automate and simplify the psychometric evaluation of test items. The software was developed using the R-Shiny framework. It computes item difficulty, discrimination index, distractor efficiency, internal consistency (if an item is deleted), and point-biserial correlation. To run the software, users need R and RStudio with installed packages and the code we provide. After analysis, the report can be easily exported in comma-separated values (CSV) format for further analysis. All data remains stored locally on the user's computer, ensuring privacy. Currently, the software supports only type A multiple-choice questions (four options with a single best answer). It can be accessed and used through RStudio without any cost. The tool serves as a valuable resource for educators and researchers in medical and allied health sciences, promoting evidence-based improvement of assessment quality.
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.