Related Experiment Video
Updated: Dec 18, 2025

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
Relationship among factors affecting research misconduct in medical sciences in Iran
Amirhossein Mardani1,2, Maryam Nakhoda3, Ehsan Shamsi Gooshki4
1Medical Ethics and History of Medicine Research Center, Tehran University of Medical Sciences , Tehran, Iran.
Abstract:
This study aims to determine the relationship among factors affecting research misconduct within the research system of medical sciences in Iran. Using phenomenography, the perceptions of individuals involved in the activities of macro, meso, and micro levels of the research system were investigated and 13 affecting factors were identified. The DEMATEL method revealed complicated and intertwined relationships among these factors based on the experts' judgment. Most of the macro and meso factors were in the cause group and most of the micro factors were in the effect group. The results showed that critical factors such as "Monitoring and dealing with research misconduct," "Transparency in research," "Management of journals" and "Ethical considerations in the publication of research results" escalate research misconduct. The study indicated that track the relationship among factors in the research system can provide the opportunity to explain research misconduct on a transitional path from macro to micro level.
More Related Videos
Related Concept Videos
Ethics in Research
Factors Affecting Illness
For instance, risk factors are connected to illness,...
Obedience
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Bias
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
Bias in Epidemiological Studies

