Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

7.1K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
7.1K
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

11.5K
Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
11.5K
Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

11.1K
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...
11.1K
Fundamental Attribution Error01:14

Fundamental Attribution Error

13.8K
According to some social psychologists, people tend to overemphasize internal factors as explanations—or attributions—for the behavior of other people. They tend to assume that the behavior of another person is a trait of that person, and to underestimate the power of the situation on the behavior of others. They tend to fail to recognize when the behavior of another is due to situational variables, and thus to the person’s state. This erroneous assumption is...
13.8K
Random Error01:04

Random Error

9.8K
Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
9.8K
Margin of Error01:27

Margin of Error

7.7K
The margin of error is also called the maximum error of an estimate. The margin of error is the maximum possible or expected difference between the observed sample parameter value and the actual population parameter value. For proportion, it is the maximum difference between the value of sample proportion obtained from the data and the true value of population proportion. As the true value of the population parameter is not known, the margin of error is calculated using the sample statistic.
7.7K

You might also read

Related Articles

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

Sort by
Same author

Peripherally located type I vestibular hair cells are required for several motor behaviors and stimulus-evoked brainstem neural responses in adult mice.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2026
Same author

Mechanisms and pathophysiology in 'stingers' and brachial plexus injury.

Annals of joint·2026
Same author

Improving the Provision of Postoperative Driving Advice in Discharge Letters After Elective Inguinal Hernia Repair: A Quality Improvement Project.

Cureus·2025
Same author

Cleft Lip and Palate Publishing Trends From Authors in Low- and Middle-Income Countries in Cleft and Craniofacial Journals.

The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association·2025
Same author

An evaluation of spraying as a delivery method for human mesenchymal stem cells suspended in low-methyl pectin solutions.

Stem cell research & therapy·2025
Same author

Reply to Barbara Schildkraut, MD.

The Journal of nervous and mental disease·2024
Same journal

Accuracy of emergency physicians' probability estimates for acute coronary syndrome.

Diagnosis (Berlin, Germany)·2026
Same journal

Interfering factors in the normative diagnostic approach.

Diagnosis (Berlin, Germany)·2026
Same journal

Using generative AI to support clinical reasoning coaching: a theory-informed approach.

Diagnosis (Berlin, Germany)·2026
Same journal

Learning from what went right: a Safety-II application of the SIDER protocol to a case of occult breast cancer.

Diagnosis (Berlin, Germany)·2026
Same journal

Impact of clinical reasoning and diagnostic error education for nurses.

Diagnosis (Berlin, Germany)·2026
Same journal

Progress in mast cell activation syndrome: the global consensus-2 diagnostic criteria at six years.

Diagnosis (Berlin, Germany)·2026
See all related articles

Related Experiment Video

Updated: Feb 13, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.6K

Detecting diagnostic error in psychiatry.

James Phillips1

  • 11Department of Psychiatry, Yale School of Medicine, 88 Noble Avenue, Milford, CT 06460, USA.

Diagnosis (Berlin, Germany)
|March 16, 2018
PubMed
Summary
This summary is machine-generated.

Detecting diagnostic errors in psychiatry is challenging due to the lack of reliable diagnostic methods and biomarkers. This review explores current error detection strategies in psychiatric diagnosis.

Keywords:
diagnosisdiagnostic errorerrorpsychiatry

More Related Videos

Nanosensors to Detect Protease Activity In Vivo for Noninvasive Diagnostics
10:50

Nanosensors to Detect Protease Activity In Vivo for Noninvasive Diagnostics

Published on: July 16, 2018

17.0K
Multiplexed Isothermal Amplification Based Diagnostic Platform to Detect Zika, Chikungunya, and Dengue 1
06:18

Multiplexed Isothermal Amplification Based Diagnostic Platform to Detect Zika, Chikungunya, and Dengue 1

Published on: March 13, 2018

14.9K

Related Experiment Videos

Last Updated: Feb 13, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

12.6K
Nanosensors to Detect Protease Activity In Vivo for Noninvasive Diagnostics
10:50

Nanosensors to Detect Protease Activity In Vivo for Noninvasive Diagnostics

Published on: July 16, 2018

17.0K
Multiplexed Isothermal Amplification Based Diagnostic Platform to Detect Zika, Chikungunya, and Dengue 1
06:18

Multiplexed Isothermal Amplification Based Diagnostic Platform to Detect Zika, Chikungunya, and Dengue 1

Published on: March 13, 2018

14.9K

Area of Science:

  • Psychiatry
  • Medical Diagnostics

Background:

  • Psychiatric diagnosis relies on subjective criteria, unlike general medicine which often uses objective biomarkers.
  • The absence of laboratory tests and biomarkers complicates the validation of psychiatric diagnoses.

Purpose of the Study:

  • To review existing methods for detecting diagnostic errors in psychiatry.
  • To address the challenges posed by the inherent uncertainties in psychiatric diagnosis.

Main Methods:

  • Review of literature on diagnostic error detection in psychiatry.
  • Analysis of the limitations in psychiatric diagnostic validity.

Main Results:

  • Psychiatric diagnostic categories lack the validation provided by laboratory tests and biomarkers.
  • Error detection in psychiatry is less confident compared to general medicine due to diagnostic uncertainties.

Conclusions:

  • The inherent limitations in psychiatric diagnosis significantly impact the reliability of error detection.
  • Further research is needed to enhance the validity and error detection capabilities in psychiatric diagnostics.