# Clarifying Research Article Classifications: A Proposal for Defining Original Studies, Systematic, Scoping, Integrative, and Narrative Reviews, and Case Reports

## TL;DR

This paper proposes a clear system to classify research articles, aiming to reduce confusion and improve clarity in academic publishing.

## Contribution

A new taxonomy for research article types based on methodological rigor and knowledge generation.

## Key findings

- Original studies can use secondary data and still be considered original if they generate new knowledge.
- Peer review often misunderstands the requirements for different review types, such as expecting systematic data extraction in narrative reviews.
- Harmonizing journal policies can enhance transparency and integrity in scientific reporting.

## Abstract

The academic publishing landscape increasingly demands precision in research reporting and article classification. However, confusion persists over the distinctions between original studies and systematic, scoping, integrative, and narrative reviews, particularly when studies use secondary or aggregated data. This paper critically examines the defining features of each article type, highlights frequent misconceptions in peer review (e.g., the expectation for systematic data extraction in narrative reviews), and proposes a clear taxonomy based on methodological rigor and knowledge generation. We argue that originality should be defined by creating new knowledge, not by the exclusive use of primary data. Through literature examples and classification criteria, we call for harmonization across journals and editorial policies to improve clarity, transparency, and the integrity of scientific reporting.