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

Accuracy and Precision

Accuracy and Precision

Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. Highly accurate measurements...

Accuracy and Precision

Accuracy and Precision

Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. Highly accurate measurements...

Scientific Nature of Social Psychology

Scientific Nature of Social Psychology

Social psychology is a scientific discipline dedicated to understanding how individuals think, feel, and behave in social contexts. Unlike common sense, which relies on anecdotal experiences and intuition, social psychology employs systematic research and empirical methods to ensure objectivity and reliability. This distinction is fundamental in distinguishing scientifically supported findings from mere speculation.Four fundamental scientific values guide a structured approach to research in...

Statistical Analysis: Overview

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...

Uncertainty in Measurement: Accuracy and Precision

Uncertainty in Measurement: Accuracy and Precision

Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.

Random and Systematic Errors

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...

You might also read

Related Articles

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

Sort by

Same author

Designing a Self-Guided Digital Intervention for Self-Management of Shoulder Pain in People Living With Spinal Cord Injury: Tutorial on Using a Person-Based Approach.

JMIR mHealth and uHealth·2026

Same author

Feasibility and acceptability of WeCare Mentoring, an online peer mentoring program for aged care support workers.

Innovation in aging·2025

Same author

Experiences and perspectives of thriving (or not) as Māori and Pacific allied health professionals.

The New Zealand medical journal·2025

Same author

Development of an e-mentoring intervention for support workers in aged care: A qualitative study.

Geriatric nursing (New York, N.Y.)·2025

Same author

The effectiveness of peer-led interventions to improve work-related psychosocial outcomes and reduce turnover of support workers in residential aged care: A systematic review and meta-analysis.

International journal of nursing studies advances·2024

Same author

A six-month telerehabilitation programme delivered via readily accessible technology is acceptable to people following stroke: a qualitative study.

Physiotherapy·2023

Search research articles

Related Experiment Video

Updated: Jun 13, 2026

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

Measuring what matters: does 'objectivity' mean good science?

Nicola M Kayes¹, Kathryn M McPherson

¹Health and Rehabilitation Research Institute, AUT University, Auckland, New Zealand. nkayes@aut.ac.nz

Disability and Rehabilitation

|April 14, 2010

Summary

This summary is machine-generated.

Objectivity in measurement tools is often assumed superior, but this study reveals potential limitations in

More Related Videos

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Published on: February 26, 2014

Knowing What Counts: Unbiased Stereology in the Non-human Primate Brain

Knowing What Counts: Unbiased Stereology in the Non-human Primate Brain

Published on: May 14, 2009

Related Experiment Videos

Last Updated: Jun 13, 2026

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Published on: February 26, 2014

Knowing What Counts: Unbiased Stereology in the Non-human Primate Brain

Knowing What Counts: Unbiased Stereology in the Non-human Primate Brain

Published on: May 14, 2009

Area of Science:

Measurement in Health Sciences
Rehabilitation Research
Scientific Validity

Background:

Self-report measures have acknowledged limitations.
The limitations of 'objective' measurement tools are often overlooked.
Objectivity is frequently assumed to guarantee scientific validity and robustness.

Purpose of the Study:

To critically evaluate the assumption that objective measures are inherently more valid than subjective ones.
To explore the implications of prioritizing objectivity in measure selection.
To propose an alternative framework for selecting appropriate measurement tools.

Main Methods:

Critical evaluation of a specific 'objective' measurement tool.
Analysis of the scientific literature concerning measurement in rehabilitation.
Conceptual analysis of measurement properties and their implications.

Main Results:

An 'objective' measure exhibited significant limitations upon critical review.
Unquestioning adoption of objective measures may hinder scientific advancement in rehabilitation.
Flawed conclusions and clinical decisions may arise from inadequately validated objective measures.

Conclusions:

Classifying measures as simply 'objective' or 'subjective' is an oversimplification.
The primary criteria for measure selection should be fitness for purpose and mathematical validity.
Combining objective and subjective measures may be necessary for comprehensive assessment.