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Related Concept Videos

Data Validation01:15

Data Validation

Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
Data Validation01:03

Data Validation

Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
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...
Decision Making: P-value Method01:09

Decision Making: P-value Method

The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
Reliability and Validity01:29

Reliability and Validity

Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
Lazarus's Cognitive Appraisal Theory01:20

Lazarus's Cognitive Appraisal Theory

Cognitive psychologist Richard Lazarus proposed the cognitive-mediational theory of emotions, which emphasizes how individuals' assessments of stressors significantly affect their experience of stress. According to Lazarus, the stress response is determined by a two-step appraisal process: primary appraisal and secondary appraisal. These cognitive appraisals help individuals evaluate the potential impact of a stressor and determine the adequacy of their coping resources.
Primary Appraisal:...

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Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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Rethinking Methodological Appraisal in Overviews of Systematic Reviews: A Participatory Validation Framework.

Clovis Mariano Faggion1, Paul M H Dummer2, Venkateshbabu Nagendrababu3

  • 1Department of Periodontology and Operative Dentistry, University Hospital Münster, Münster, Germany.

Journal of Clinical Epidemiology
|June 12, 2026
PubMed
Summary
This summary is machine-generated.

A new participatory validation framework enhances transparency in overviews of systematic reviews. It involves overview authors and systematic review authors collaborating to improve methodological appraisal credibility.

Keywords:
Meta-AnalysisMethodologyPeer ReviewReproducibility of ResultsRisk of BiasSystematic Reviews

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Area of Science:

  • Evidence synthesis
  • Systematic review methodology
  • Research integrity

Background:

  • Overviews of systematic reviews (umbrella reviews) synthesize evidence for clinical practice and policy.
  • Methodological appraisal of systematic reviews is crucial but remains interpretive and variable.
  • Tools like AMSTAR 2 and ROBIS are used, yet ratings differ significantly across research teams.

Purpose of the Study:

  • To propose a participatory validation framework to address challenges in methodological appraisal of systematic reviews within overviews.
  • To enhance transparency, credibility, and interpretability of appraisal processes.
  • To provide a pragmatic strategy for improving evidence synthesis guidance.

Main Methods:

  • Overview authors conduct independent methodological appraisals of included systematic reviews.
  • Authors of included systematic reviews are invited to comment on and reassess these judgments.
  • Areas of agreement and disagreement are transparently documented without requiring consensus.

Main Results:

  • The framework is feasible within existing workflows with minimal disruption.
  • Ethical considerations like self-serving bias are mitigated through independent appraisal, anonymous reassessment, and transparent reporting.
  • Potential limitations include selective participation and administrative burden.

Conclusions:

  • The participatory validation framework improves transparency and interpretability of methodological appraisal in overviews.
  • It makes concordance and discordance visible, rather than establishing a single definitive rating.
  • This approach offers richer guidance for authors, guideline developers, policymakers, and the evidence synthesis community.