Introduction to this series of blogs This is the first of four blogs on the topic of how AI can assist in assembling datasets for meta-analyses. The four blogs are organized by the following topics: Using ChatGPT to Assist with Literature Searching Using ChatGPT to Assist with Collecting and Organizing Studies Using SysRev for Title and Abstract Screening and Data Extraction Lessons Learned These blogs chronicle my efforts to learn about how AI can assist in the process of selecting studies...

Introduction In the previous post, I described how I used ChatGPT to help reason through the conceptual structure of a meta-analysis on inflation and subjective well-being and to arrive at a set of Boolean search terms suitable for use across multiple bibliographic databases. That post ended at a natural stopping point: the search logic was defined, inclusion and exclusion criteria were explicit, and the remaining task was to take those search terms into the world and see how they behaved in...

NOTE : This blog is coauthored with Anne Jayasekara and Weilun (Allen) Wu Introduction This is the third blog in a series on how AI can assist in assembling datasets for meta-analyses. The first blog described how ChatGPT was used to develop a systematic literature search strategy for studies on the relationship between inflation and subjective well-being. The second blog described how that search strategy was executed across four bibliographic databases — Scopus, Business Source Complete,...