Related Experiment Video
Updated: Apr 7, 2026
07:50
A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
16.6K
Difficulty in detecting discrepancies in a clinical trial report: 260-reader evaluation.
Graham D Cole1, Matthew J Shun-Shin2, Alexandra N Nowbar3
1International Centre for Circulatory Health and g.cole@imperial.ac.uk.
International Journal of Epidemiology
|July 16, 2015
Summary
Most readers miss scientific discrepancies, with 95.3% of errors undetected. Even when specifically looking, most participants found no discrepancies, highlighting challenges in scientific literature review.
Area of Science:
- Medical research integrity
- Scientific publishing
- Data analysis and interpretation
Background:
- Scientific literature may contain errors, with discrepancies indicating potential issues in trial reports.
- Identifying these discrepancies is crucial for maintaining the accuracy of published research.
- This study focuses on the detection rate of discrepancies by a panel of readers.
Purpose of the Study:
- To quantify the number of discrepancies detected by readers examining a scientific article.
- To evaluate the effectiveness of readers in identifying inconsistencies within published research.
- To explore factors influencing discrepancy detection, such as time spent and author experience.
Main Methods:
- A convenience sample of 343 journal readers from seven countries was approached.
- 260 participants examined tables and figures of a published article for discrepancies.
- Reader experience and time spent on the task were recorded and analyzed.
Main Results:
- An overwhelming 95.3% of discrepancies were missed by participants.
- 62% of readers failed to identify any discrepancies.
- Increased time spent and prior publishing experience correlated with slightly higher discrepancy detection rates.
Conclusions:
- Detecting discrepancies in scientific literature is challenging, with most readers missing the majority of errors.
- The high rate of missed discrepancies underscores the importance of post-publication communication and verification.
- Readers support editorial actions to correct the scientific record when discrepancies are identified.
More Related Videos
08:36Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
Published on: April 19, 2024
1.3K
04:53A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
Published on: September 20, 2019
11.5K
Related Concept Videos
01:16Clinical Trials
11.2K
Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
There are four phases in a clinical trial. A phase one...
11.2K
01:27Confounding in Epidemiological Studies
1.0K
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
1.0K
01:29Bias in Epidemiological Studies
1.6K
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
1.6K
02:07Blind Procedures
13.9K
Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which...
13.9K
01:12Hazard Ratio
712
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
For example, in a clinical trial...
712
01:19Pharmacovigilance
2.0K
Post-marketing surveillance is a critical component of pharmaceutical regulation, often uncovering unanticipated adverse drug reactions (ADRs) once a drug is widely used over an extended period.
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
2.0K