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Related Concept Videos

Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Diagnostic and Statistical Manual of Mental Disorders (DSM)01:27

Diagnostic and Statistical Manual of Mental Disorders (DSM)

The Diagnostic and Statistical Manual of Mental Disorders (DSM) serves as the primary classification system for mental health disorders, providing standardized diagnostic criteria for clinicians and researchers. First published by the American Psychiatric Association (APA) in 1952, the DSM has undergone several revisions to reflect evolving psychiatric understanding. The fifth edition, DSM-5, released in 2013, introduced key updates that expanded diagnostic categories and modified diagnostic...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

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:
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Bias01:22

Bias

Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
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...

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Related Experiment Videos

What's the Meta Now? More Updates on the Problems with Systematic Reviews.

Lesley Uttley1, Yuliang Weng2, Louise Falzon1

  • 1School of Medicine and Population Health, University of Sheffield, Sheffield, United Kingdom.

Journal of Clinical Epidemiology
|June 27, 2026
PubMed
Summary
This summary is machine-generated.

Systematic reviews face persistent issues in quality and reporting, despite some improvements. Ongoing efforts are needed to ensure trustworthy evidence synthesis and address global research gaps.

Keywords:
Systematic reviewauthorshipconflicts of interestglobal research representationmeta-researchresearch integritytrustworthy evidence

Related Experiment Videos

Area of Science:

  • Meta-research
  • Evidence synthesis
  • Scientific publishing

Background:

  • Systematic reviews are crucial for evidence synthesis but often suffer from recurring conduct and reporting problems.
  • This living systematic review, in its third version, examines these persistent issues across academic literature.

Purpose of the Study:

  • To update and analyze recurring problems in systematic reviews.
  • To identify emerging themes and assess methodological quality trends over time.

Main Methods:

  • Updated literature searches (to May 2025) of meta-research and editorial articles.
  • Analysis of eligible articles to identify recurring and emerging themes.
  • Presentation of methodological quality indicators for included meta-research.

Main Results:

  • 209 additional articles included; low methodological quality and lack of protocols remain prevalent.
  • Spin in abstracts, conflicts of interest, and reporting deficiencies persist, especially in clinical practice guideline evidence.
  • Improvements in reporting are inconsistent; authorship and included research lack global representativeness.
  • 69 distinct problems identified, including misalignment with global disease burden; AI/automation use is variably reported.
  • Meta-research quality shows a greater proportion meeting indicators in recent updates.

Conclusions:

  • Problems with systematic reviews are widespread and consistent across updates.
  • Incremental reporting improvements coexist with persistent concerns regarding transparency, bias, and representativeness.
  • Future efforts must focus on evaluating interventions and aligning incentives for trustworthy evidence synthesis.