PsyPost deploys audit program to track retracted and corrected scientific studies in its archive

The science news outlet PsyPost has launched an automated program to track any retractions, corrections, or alterations made to the scientific studies it has previously covered in its extensive archive. The software, written in Python, scans the website's nearly 16,000 articles to find studies linked to publisher records, and cross-references those identifiers with databases from Retraction Watch and Crossref.

After reviewing its full archive, the program found six studies that had been withdrawn or corrected. Now running on a regular schedule, the program will flag any study PsyPost has reported earlier that has since been retracted or changed in any way. This automated check aims to preserve the credibility of PsyPost's content by keeping readers informed about updates to previously covered research.

The program works in four stages. First, it extracts Digital Object Identifiers (DOIs) from the articles, which act as unique codes for each study. Next, it compares these DOIs to databases of retractions and corrections, identifying any that align with the studies PsyPost has covered. Minor changes, like typo corrections, are filtered out, leaving only significant retractions and expressions of concern.

Finally, the program alerts the editorial team about any studies that need updating. When the editorial team reviews an alert, they add a notice to the affected article explaining the change, and the program marks the task as completed. Editors are able to review and refine the system as needed, preventing false alarms and ensuring the scientific integrity of the information provided to readers.