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

Halo Effect

Halo Effect

The halo effect is a cognitive bias in which an individual's overall impression influences judgments about their specific traits. This psychological phenomenon leads people to associate positive characteristics with those they perceive as generally good and negative characteristics with those they view as bad. This effect is particularly influential in social perception, professional evaluations, and decision-making processes.The Psychological Basis of the Halo EffectThe halo effect is rooted...

Common Leveling Mistakes and Errors

Common Leveling Mistakes and Errors

A survey team is tasked with determining the elevation difference between points Point A and Point B, separated by uneven terrain. They use a leveling instrument and a leveling rod.Common MistakesMisreading the Rod: During a backsight reading at Point A, the instrumentman observes the rod partially obscured by tall grass. Instead of reading 1.135 m, they mistakenly record 1.735 m due to the misalignment of the crosshair with the wrong graduation. This error adds 0.600 m to all subsequent...

Systematic Error: Methodological and Sampling Errors

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...

Types of Errors: Detection and Minimization

Types of Errors: Detection and Minimization

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...

Cognitive Dissonance

Cognitive Dissonance

Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...

Errors occurring during blood pressure monitoring

Errors occurring during blood pressure monitoring

Blood pressure monitoring is a crucial clinical procedure in diagnosing and managing various cardiovascular conditions. Despite its significance, the accuracy of blood pressure measurements can be compromised by multiple factors, potentially leading to either falsely high or low readings. These inaccuracies are critical as they can significantly impact patient care. So, it is vital to understand these challenges deeply and adopt strategic approaches to minimize errors.
Several factors...

You might also read

Related Articles

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

Sort by

Same author

Commentary: Stakeholder Dissonance Impedes Medical Device Cyber-Risk Reduction.

Biomedical instrumentation & technology·2018

Same author

The use, misuse, and abuse of design controls.

IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society·2010

Same author

A systems engineering perspective on the human-centered design of health information systems.

Journal of biomedical informatics·2005

See all related articles

Search research articles

Related Experiment Video

Updated: May 25, 2026

Errors as a Means of Reducing Impulsive Food Choice

Errors as a Means of Reducing Impulsive Food Choice

Published on: June 5, 2016

Reducing latent errors, drift errors, and stakeholder dissonance.

George M Samaras¹

¹Samaras & Associates, Inc., 7755 Soda Creek Road, Pueblo, CO 81005, USA.

Work (Reading, Mass.)

|February 10, 2012

Summary

This summary is machine-generated.

Healthcare information technology (HIT) can transform healthcare delivery, but quality improvements lag. System use errors, not individual mistakes, hinder progress by originating in technology development and deployment.

Related Experiment Videos

Last Updated: May 25, 2026

Errors as a Means of Reducing Impulsive Food Choice

Errors as a Means of Reducing Impulsive Food Choice

Published on: June 5, 2016

Area of Science:

Healthcare Information Technology (HIT)
Health Services Research
Human Factors Engineering

Background:

Healthcare information technology (HIT) is promoted to enhance patient safety, effectiveness, and cost savings in healthcare delivery.
Quality improvement in healthcare has not matched gains seen in other industries, potentially due to a lack of clinical domain knowledge among experts.
A misunderstanding of work errors in healthcare, focusing on system use errors over individual user errors, persists.

Purpose of the Study:

To analyze the origins and impact of system use errors in healthcare information technology (HIT).
To identify factors contributing to the limited success of quality improvement efforts in healthcare IT implementation.
To highlight the role of stakeholder needs and requirement translation in HIT development and deployment.

Main Methods:

Analysis of system development and deployment processes for healthcare information technology.
Examination of stakeholder needs, wants, and desires (NWDs) and their translation into technical requirements.
Identification of error types, including stakeholder dissonance, latent errors, and drift errors, within HIT systems.

Main Results:

System use errors, stemming from technology development and deployment, are a primary barrier to HIT's transformative potential.
Failure to recognize and address conflicting stakeholder NWDs leads to stakeholder dissonance.
Errors in translating NWDs into requirements (latent errors) and requirements into specifications (drift errors) contribute to system failures.

Conclusions:

Effective HIT implementation requires a deeper understanding of system use errors and their origins in the development lifecycle.
Addressing stakeholder dissonance and ensuring accurate translation of needs into technical specifications are crucial for successful HIT deployment.
Recognizing and mitigating system use errors is essential for realizing the intended benefits of healthcare information technology.