# Medical Theses and Derivative Articles: Dissemination Of Contents and Publication Patterns

**Authors:** Mercedes Echeverria, David Stuart, Tobias Blanke  
**arXiv:** [1707.04439](https://arxiv.org/abs/1707.04439)  
**Date:** 2017-07-14  
**Summary page:** https://www.summarizepaper.com/en/paper/1707.04439v1/

## Key points

- The study investigates dissemination of contents and publication patterns resulting from doctoral theses in universities
- Focuses on derivative articles that are published as a result of theses but have received little attention in previous studies
- Authors aim to identify how derivative articles can be recognized through text analysis based on the full-text of medical theses and articles that share authorship
- Methodology involves exploiting full-text articles according to organization of scientific discourse (IMRaD) using TurnItIn plagiarism tool
- Discussion section's text similarity rate can differentiate between derivative and non-derivative articles
- 85% of derivative articles had their thesis author listed first, while supervisors participated as co-authors in 100% of such articles
- 42% of authorship credit was retained by thesis authors in derivative articles compared to an average of 6.4 co-authors for non-derivative ones
- 87.5% of derivative articles were published before or in the same year as their respective thesis completion date
- Doctoral students' publications are often derived from their dissertations, with supervisors playing a significant role in co-authoring these derivatives.
- Study sheds light on an important aspect of academic publishing within universities and highlights how derivative articles can be identified through text analysis methods.

## Summary

The study titled "Medical Theses and Derivative Articles: Dissemination Of Contents and Publication Patterns" conducted by Mercedes Echeverria, David Stuart, and Tobias Blanke investigates the dissemination of contents and publication patterns resulting from doctoral theses in universities. The research focuses on derivative articles that are published as a result of theses but have received little attention in previous studies. The authors aim to identify how derivative articles can be recognized through text analysis based on the full-text of medical theses and articles that share authorship. The methodology applied in this study involves exploiting the full-text articles according to organization of scientific discourse (IMRaD) using TurnItIn plagiarism tool. The findings reveal that the Discussion section's text similarity rate can differentiate between derivative and non-derivative articles. Additionally, it was found that 85% of derivative articles had their thesis author listed first, while supervisors participated as co-authors in 100% of such articles. Furthermore, 42% of authorship credit was retained by thesis authors in derivative articles compared to an average of 6.4 co-authors for non-derivative ones. The time differential regarding the year of thesis completion showed that 87.5% of derivative articles were published before or in the same year as their respective thesis completion date. These results suggest that doctoral students' publications are often derived from their dissertations, with supervisors playing a significant role in co-authoring these derivatives. Overall, this study sheds light on an important aspect of academic publishing within universities and highlights how derivative articles can be identified through text analysis methods. It provides valuable insights into publication patterns resulting from doctoral dissertations and emphasizes the significance of supervisor involvement in co-authoring derivatives.