ArticleAERA open
Data Deidentification for Data Sharing in Educational and Psychological Research: Importance, Barriers, and Techniques.
Article in AERA open. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Design, implementation, and evaluation of IIIDDS: a structured WhatsApp case-discussion curriculum in undergraduate radiology education.Frontiers in medicine · 2026Article
- Education researchers' beliefs and barriers towards data sharing.Quality & quantity · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
In this manuscript, we discuss the importance of data sharing in educational and psychological research, emphasizing the historical context of data sharing, the current open science movement, and the so-called replication crisis. We additionally explore the barriers to data sharing, particularly the fear of incorrectly deidentifying data or accidentally including private information. We then highlight the importance of deidentifying data for data sharing. Finally, we present specific techniques for data deidentification, namely non-perturbative and perturbative methods, and make recommendations for which techniques are relevant for specific types of variables. To assist readers in implementing the material from this study, we have additionally created an interactive tutorial as a Shiny web application, which is publicly available and free to use.
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.