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

You might also read

Related Articles

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

Sort by
Same journal

Self-face recognition under self-implicating threat: preserved self-prioritization and recalibrated control dynamics.

Cognitive research: principles and implications·2026
Same journal

Out of sight, out of mind? How discarded items shape environmental judgments.

Cognitive research: principles and implications·2026
Same journal

Implicit learning of social information in contextual cueing.

Cognitive research: principles and implications·2026
Same journal

A downside of conceptual metaphor: metaphoric alignments of black and white.

Cognitive research: principles and implications·2026
Same journal

Visual attention in bilingual instructional videos: effects of audiovisual congruency and subtitle language.

Cognitive research: principles and implications·2026
Same journal

Predicting accuracy in eyewitness showups: confidence and response time in the laboratory, confidence in the field.

Cognitive research: principles and implications·2026
See all related articles

Related Experiment Video

Updated: Sep 24, 2025

Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model
06:30

Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model

Published on: May 24, 2019

5.4K

Target-rate effect in continuous visual search.

Louis K H Chan1, Winnie W L Chan2

  • 1Psychology Unit, School of Continuing Education, Hong Kong Baptist University, Shek Mun, Hong Kong. clouis@graduate.hku.hk.

Cognitive Research: Principles and Implications
|May 7, 2022
PubMed
Summary
This summary is machine-generated.

Continuous visual search, like lifeguarding, shows a target-rate effect. Rare targets in continuous monitoring tasks lead to slower responses and more misses, similar to the low-prevalence effect (LPE) in regular search.

Keywords:
Continuous visual searchDynamic visual searchLow-prevalence effectSignal detectionSurveillanceTarget-prevalence effectVigilance

More Related Videos

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss
07:12

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

578
Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

10.0K

Related Experiment Videos

Last Updated: Sep 24, 2025

Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model
06:30

Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model

Published on: May 24, 2019

5.4K
Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss
07:12

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

Published on: April 11, 2025

578
Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

10.0K

Area of Science:

  • Cognitive Psychology
  • Human Factors Engineering
  • Visual Perception

Background:

  • Real-world visual search often involves continuous monitoring (e.g., surveillance, lifeguarding) with infrequent targets.
  • Previous research primarily focused on discrete search tasks (e.g., baggage screening), neglecting continuous monitoring scenarios.
  • The low-prevalence effect (LPE), where target detection is impaired when targets are rare, is well-documented in discrete search but less understood in continuous search.

Purpose of the Study:

  • To investigate whether a target-rate effect, analogous to the LPE, exists in continuous visual search tasks.
  • To determine if the behavioral characteristics of this effect in continuous search mirror those observed in discrete search.
  • To explore the impact of target rarity on performance metrics like response time and accuracy in continuous monitoring.

Main Methods:

  • Designed a continuous visual detection task where participants searched for a target feature (e.g., specific color) within a stream of items with gradually changing features.
  • Conducted four experiments manipulating the rate or relative frequency of target appearance.
  • Measured hit response times (RTs) and miss rates as primary performance indicators.

Main Results:

  • Demonstrated significant target-rate effects in continuous visual search, characterized by slower hit RTs and higher miss rates when targets were rare.
  • Observed similar target-rate effects when considering the relative frequencies of two distinct target features.
  • The performance decrements associated with target rarity in continuous search align with findings from discrete search tasks.

Conclusions:

  • Continuous visual search exhibits a target-rate effect comparable to the low-prevalence effect (LPE) found in discrete search.
  • The behavioral patterns observed suggest that the underlying mechanisms influencing target detection under rarity conditions may generalize across different search paradigms.
  • These findings have implications for designing effective monitoring systems and training protocols for real-world continuous visual search tasks.