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

Longitudinal Research02:20

Longitudinal Research

11.7K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
11.7K

You might also read

Related Articles

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

Sort by
Same author

Agreement between ganglion cell-inner plexiform layer metrics from widefield optical coherence tomography and Goldmann II, III, and V in glaucoma.

Optometry and vision science : official publication of the American Academy of Optometry·2026
Same author

OCT-based optic neuropathy diagnosis using explainable and privacy-preserving machine learning.

Scientific reports·2026
Same author

Quantitative Markers of Neural Changes, Retinal Thickness, and Responses to Electrical Stimulation in Retinal Degeneration.

Ophthalmology science·2026
Same author

Clinical Effective Dynamic Range and the Measurement Floor of SITA-Faster Visual Field Tests.

Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)·2026
Same author

A staged approach to the number and frequency of visual field testing for detecting glaucoma progression.

Ophthalmology. Glaucoma·2026
Same author

Volumetric Analysis of Perimetry Tests to Guide Central Testing: The Functional Vulnerability Zone.

Ophthalmology science·2026
Same journal

Split-Spectrum Amplitude-Decorrelation Optoretinography Detects Impaired Photoreceptor Function in Age-Related Macular Degeneration.

Ophthalmology science·2026
Same journal

Genome-Wide Association Study for Glucocorticoid-Induced Ocular Hypertension.

Ophthalmology science·2026
Same journal

Assessing Polypoidal Choroidal Vasculopathy-Related OCT Features in the TENAYA and LUCERNE Trials.

Ophthalmology science·2026
Same journal

Quantitative Analysis of Choroidal Thickness and Blood Flow in Thyroid-Associated Ophthalmopathy Using Ultra-Widefield Swept-Source OCT Angiography.

Ophthalmology science·2026
Same journal

Epiretinal Membrane Is Associated with Acquired Vitelliform Lesion Morphometrics in Intermediate Age-Related Macular Degeneration.

Ophthalmology science·2026
Same journal

Multisource Machine Learning Model for Detecting Referral-Warranted Retinopathy of Prematurity.

Ophthalmology science·2026
See all related articles

Related Experiment Video

Updated: May 5, 2026

Dynamic Visual Tests to Identify and Quantify Visual Damage and Repair Following Demyelination in Optic Neuritis Patients
12:23

Dynamic Visual Tests to Identify and Quantify Visual Damage and Repair Following Demyelination in Optic Neuritis Patients

Published on: April 14, 2014

14.6K

Predicting Variability and Reliability in Visual Field Testing: Short- and Long-Term Approaches.

Jack Phu1,2, Henrietta Wang1, Jeremy C K Tan3,4

  • 1School of Optometry and Vision Science, University of New South Wales, Kensington, New South Wales, Australia.

Ophthalmology Science
|February 18, 2026
PubMed
Summary
This summary is machine-generated.

Computer simulations show that while long-term visual field (VF) variability estimation is challenging, intensive short-term testing can reliably determine VF measurement reliability and variability within days.

Keywords:
24-2FrontloadedPerimetryStandard automated perimetryVisual fields

More Related Videos

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential
07:11

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential

Published on: May 25, 2020

6.9K
Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition
07:45

Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition

Published on: July 21, 2020

5.0K

Related Experiment Videos

Last Updated: May 5, 2026

Dynamic Visual Tests to Identify and Quantify Visual Damage and Repair Following Demyelination in Optic Neuritis Patients
12:23

Dynamic Visual Tests to Identify and Quantify Visual Damage and Repair Following Demyelination in Optic Neuritis Patients

Published on: April 14, 2014

14.6K
Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential
07:11

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential

Published on: May 25, 2020

6.9K
Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition
07:45

Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition

Published on: July 21, 2020

5.0K

Area of Science:

  • Ophthalmology
  • Medical Technology
  • Data Science

Background:

  • Visual field (VF) testing is crucial for diagnosing and monitoring eye conditions.
  • Accurate measurement of VF variability and reliability is essential for clinical decision-making.
  • Current methods may not efficiently capture intrinsic measurement variability.

Purpose of the Study:

  • To predict intrinsic measurement variability and reliability in visual field (VF) results.
  • To utilize a computer simulation model for predicting VF data loss.
  • To establish critical timeframes for estimating VF variability and reliability.

Main Methods:

  • Simulated 100,000 subjects over 20 years (long-term) and 28 days (short-term) with varying VF test frequencies.
  • Estimated variability and reliability using a rolling window until 3 consecutive visits met a 5% threshold.
  • Defined critical time to estimating variability (TcV) and reliability (TcR) based on consecutive clinical criteria and comparison with ground truth (TgV, TgR).

Main Results:

  • Intensive short-term VF testing (1 test/day) determined reliability and variability within 5 days.
  • Long-term testing (4 tests/visit, monthly) required years to estimate variability (median 6 years for TcV).
  • Estimated variability and reliability showed clinically small differences from ground truth; reliability was the main predictor for TcR/TgR.

Conclusions:

  • Longitudinal estimation of VF variability is impractical in clinical settings.
  • Intensive, short-term VF testing provides reliable variability and reliability rates efficiently.
  • A framework is provided to assess the impact of variability on detecting VF changes over time.