Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Confounding in Epidemiological Studies

Confounding in Epidemiological Studies

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...

Strategies for Assessing and Addressing Confounding

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...

Bias in Epidemiological Studies

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:

Blinding

Blinding

Blinding is a commonly used method of not telling participants which treatment a subject is receiving. Blinding is a critical part of a randomized control trial or RCT. It reduces the bias that affects the results. In an RCT, blinding is used in the form of a placebo. A placebo effect occurs when untreated subjects falsely believe they have received the treatment and report improved symptoms. A placebo or a dummy treatment is administered to subjects to negate the bias caused by such an effect.

Observational Studies

Observational Studies

Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Correction: Somatic morbidity in bipolar disorders.

International journal of bipolar disorders·2026

Same author

Long-Term Opioid Therapy Tapering and Risk of Substance Use Disorder and Overdose: Differences by Opioid Dose and Duration.

Journal of general internal medicine·2026

Same author

Mapping persistence and change in psychological problems during the transition to adolescence: Adding, subtracting, shifting, and persisting.

JCPP advances·2026

Same author

Measured and Estimated Glomerular Filtration Rates and Risk of Adverse Health Outcomes.

JAMA·2026

Same author

Somatic morbidity in bipolar disorders.

International journal of bipolar disorders·2026

Same author

Evaluation of clinical utility in emulated clinical trials.

European journal of epidemiology·2026

Search research articles

Related Experiment Video

Updated: Dec 22, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Accounting for Confounding in Observational Studies.

Brian M D'Onofrio^1,2, Arvid Sjölander², Benjamin B Lahey³

¹Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana 47405, USA;

Annual Review of Clinical Psychology

|May 9, 2020

Summary

This summary is machine-generated.

This review guides clinical psychology researchers in using causal inference methods to rigorously test hypotheses about risk factors in observational studies, addressing confounding for better behavioral health research.

Keywords:

causal diagram causation confounding natural experiments propensity scores quasi-experiments

More Related Videos

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Published on: January 9, 2016

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

Related Experiment Videos

Last Updated: Dec 22, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Published on: January 9, 2016

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

Area of Science:

Epidemiology and Biostatistics
Clinical Psychology
Behavioral Health Research

Background:

Observational studies in clinical psychology often struggle to account for confounding variables.
Advances in causal inference offer new tools for analyzing risk factors.
There is a need for rigorous hypothesis testing in behavioral health etiology and treatment.

Purpose of the Study:

To equip clinical psychology researchers with methods for robustly testing competing hypotheses.
To highlight the importance of causal inference in observational research.
To address the critical issue of confounding in studying risk factors.

Main Methods:

Review of theoretical issues in causation and causal diagrams.
Description of analytic approaches for measured confounding.
Explanation of designs for unmeasured confounding.

Main Results:

Causal diagrams aid in identifying and testing hypotheses.
Analytic and design-based approaches can mitigate confounding.
Strengths and limitations of various methods are discussed.

Conclusions:

Implementing causal inference techniques enhances the rigor of observational studies.
Addressing confounding is crucial for understanding behavioral health problems.
These methods support more accurate etiological and treatment research.