Paperfetcher: A tool to automate handsearch for systematic reviews

TL;DR

Paperfetcher is a free, open-source tool that automates the manual process of handsearching journals for systematic reviews, saving time and reducing errors, and also supports snowballing and easy data export.

Contribution

This paper introduces Paperfetcher, the first tool to automate handsearch with high usability and multidisciplinary focus, integrating snowballing and data export features.

Findings

Automates handsearch process for systematic reviews

Supports snowballing in both directions

Enables easy export of retrieved articles

Abstract

Handsearch is an important technique that contributes to thorough literature search in systematic reviews. Traditional handsearch requires reviewers to systematically browse through each issue of a curated list of field-specific journals and conference proceedings to find articles relevant to their review. This manual process is not only time-consuming, laborious, costly, and error-prone, but it also lacks replicability and cross-checking mechanisms. In an attempt to solve these problems, this paper presents a free and open-source Python package and an accompanying web-app, Paperfetcher, to automate handsearch for systematic reviews. With Paperfetcher's assistance, researchers can retrieve articles from designated journals within a specified time frame with just a few clicks. In addition to handsearch, this tool also incorporates snowballing in both directions. Paperfetcher allows researchers to download retrieved studies as a list of DOIs or as an RIS database to facilitate seamless import into citation management and systematic review screening software. To our knowledge, Paperfetcher is the first tool that automates handsearch with high usability and a multi-disciplinary focus.