Article

Comparing AI and Human Coding of NIH Grant Abstracts to Identify Innovations in Opioid Addiction Treatment

2026-02-17

Abstract excerpt

Large language models (LLMs) are increasingly used for qualitative analysis in substance use research, yet their performance relative to human coders remains underexplored. This study compares ChatGPT-4.0 with human coders in identifying and describing the core innovation of NIH grants focused on reducing opioid overdose. A total of 118 NIH HEAL Initiative grant abstracts were independently coded by ChatGPT and hu...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: fe25db91-971e-579b-a87d-12a3e7a4af8f
DOI: 10.64898/2026.02.13.26346235

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Comparing AI and Human Coding of NIH Grant Abstracts to Identify Innovations in Opioid Addiction TreatmentDOI 10.64898/2026.02.13.26346235Read

Large Language Models in Psychology: Application in the Context of a Systematic Literature Review.Semantic proximity Read

Can ChatGPT write better scientific titles? A comparative evaluation of human-written and AI-generated titlesSemantic proximity Read

Can ChatGPT write better scientific titles? A comparative evaluation of human-written and AI-generated titlesSemantic proximity Read

Can AI Match Human Experts? Evaluating LLM-Generated Feedback on Resident Scholarly ProjectsSemantic proximity Read

Large Language Models for Large-Scale, Rigorous Qualitative Analysis in Applied Health Services ResearchSemantic proximity Read

ACCORD-AI: an exploratory evaluation of large language models for drafting consensus voting itemsSemantic proximity Read

Large Language Models for Thematic Analysis in Healthcare Research: A Blinded Mixed-Methods Comparison with Human AnalystsSemantic proximity Read

Assessing the feasibility and acceptability of a bespoke large language model pipeline to extract data from different study designs for public health evidence reviewsSemantic proximity Read

Prompt-driven large language model for evidence extraction in implementation science: exploring semantic similarity between manual and automated coding across studiesSemantic proximity Read

How good are large language models for automated data extraction from randomized trials?Semantic proximity Read

Large Language Models (LLMs) for Evidence Synthesis: An Exploratory Evaluation and A New Approach for Automated Data Extraction and ValidationSemantic proximity Read

Artificial Intelligence in Surgical Qualitative Research: A Comparison of Human and AI-Assisted Thematic AnalysisSemantic proximity Read