View in EDS HTML Full Text PDF Full Text

One Factor to Bind Them All: Visual Foraging Organization to Predict Patch Leaving Behavior with ROC Curves

Saved in:
Bibliographic Details
Title: One Factor to Bind Them All: Visual Foraging Organization to Predict Patch Leaving Behavior with ROC Curves
Language: English
Authors: Marcos Bella-Fernández (ORCID 0000-0001-6621-0199), Manuel Suero Suñé, Alicia Ferrer-Mendieta, Beatriz Gil-Gómez de Liaño
Source: Cognitive Research: Principles and Implications. 2025 10.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 22
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Online Searching, Visual Aids, Mass Media, Search Strategies, Time Management, Organization, Foreign Countries, College Students, Young Adults, Student Behavior, Predictor Variables, Factor Analysis
Geographic Terms: Spain (Madrid)
DOI: 10.1186/s41235-025-00624-7
ISSN: 2365-7464
Abstract: Predicting quitting rules is critical in visual search: Did I search enough for a cancer nodule in a breast X-ray or a threat in a baggage airport scanner? This study examines the predictive power of search organization indexes like best-r, mean ITD, PAO, or intersection rates as optimal criteria to leave a search in foraging (looking for several targets among distractors). In a sample of 29 adults, we compared static and dynamic foraging. Also, we reanalyze data from diverse foraging tasks in the lifespan already published to replicate results. Using ROC curves, all results consistently show that organization measures outperform classic intake rates commonly used in animal models to predict optimal human quitting behavior. Importantly, a combination of organization and traditional intake rates within a unitary factor is the best predictor. Our findings open a new research line for studying optimal decisions in visual search tasks based on search organization.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1466167
Database: ERIC
Full text is not displayed to guests.
Description
Abstract:Predicting quitting rules is critical in visual search: Did I search enough for a cancer nodule in a breast X-ray or a threat in a baggage airport scanner? This study examines the predictive power of search organization indexes like best-r, mean ITD, PAO, or intersection rates as optimal criteria to leave a search in foraging (looking for several targets among distractors). In a sample of 29 adults, we compared static and dynamic foraging. Also, we reanalyze data from diverse foraging tasks in the lifespan already published to replicate results. Using ROC curves, all results consistently show that organization measures outperform classic intake rates commonly used in animal models to predict optimal human quitting behavior. Importantly, a combination of organization and traditional intake rates within a unitary factor is the best predictor. Our findings open a new research line for studying optimal decisions in visual search tasks based on search organization.
ISSN:2365-7464
DOI:10.1186/s41235-025-00624-7