Decomposing trust-related decision making: dimensionality and predictability of phishing susceptibility in an adult lifespan sample.
Objectives Email phishing is a major source of fraud, costing individuals and organizations billions of dollars each year. Older adults are disproportionately vulnerable to phishing and are frequently targeted by scammers. As phishing increases in sophistication, there is a growing need to understan...
| Publicado en: | Journals of Gerontology Series B: Psychological Sciences & Social Sciences Vol. 81; no. 8; pp. 1 - 12 |
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| Autores principales: | , , , , , |
| Formato: | Artículo |
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Oxford University Press / USA
Aug2026
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=195931910&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 195931910 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 10795014 JGB jtl: Journals of Gerontology Series B: Psychological Sciences & Social Sciences issn: 10795014 maglogo: N pubinfo: dt: Aug2026 vid: 81 iid: 8 pid: 622 pub: Oxford University Press / USA artinfo: ui: 195931910 10.1093/geronb/gbag090 ppf: 1 ppct: 11 formats: tig: atl: Decomposing trust-related decision making: dimensionality and predictability of phishing susceptibility in an adult lifespan sample. aug: au: Wang, Shensheng Hakim, Ziad Pehlivanoglu, Didem Ebner, Natalie C Grilli, Matthew D Wilson, Robert C affil: School of Psychology, Georgia Institute of Technology, Atlanta, Georgia, United States Department of Psychology, University of Florida, Gainesville, Florida, United StatesDepartment of Psychology, University of Arizona, Tucson, Arizona, United States Department of Psychology, University of Florida, Gainesville, Florida, United StatesCenter for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, Florida, United States Department of Psychology, University of Arizona, Tucson, Arizona, United StatesMcKnight Brain Research Foundation, University of Arizona, Tucson, Arizona, United States su: Decision making Age distribution Trust Deception Aging Fraud Adults Middle age Old age Risk assessment Statistical correlation Mathematical variables Data security Research funding Prediction models Psychophysics Artificial neural networks Research Psychological vulnerability sug: subj: Decision making Age distribution Trust Deception Aging Fraud Adults Middle age Old age Other Computer Related Services Computer systems design and related services (except video game design and development) Risk assessment Statistical correlation Mathematical variables Data security Research funding Prediction models Psychophysics Artificial neural networks Research Psychological vulnerability keyword: adult aged aging copyrightHolder:The Gerontological Society of America copyrightYear:2026 Cyber security deception Deception detection decision making https://dx.doi.org/10.1093/geronb/gbag090 inLanguage:en life span Neural network modeling neural networks (computer) publisher:Oxford University Press sameAs:https://pubmed.ncbi.nlm.nih.gov/42166734/ signal detection (psychology) adult aged aging copyrightHolder:The Gerontological Society of America copyrightYear:2026 Cyber security deception Deception detection decision making https://dx.doi.org/10.1093/geronb/gbag090 inLanguage:en life span Neural network modeling neural networks (computer) publisher:Oxford University Press sameAs:https://pubmed.ncbi.nlm.nih.gov/42166734/ signal detection (psychology) ab: Objectives Email phishing is a major source of fraud, costing individuals and organizations billions of dollars each year. Older adults are disproportionately vulnerable to phishing and are frequently targeted by scammers. As phishing increases in sophistication, there is a growing need to understand the decision-making processes behind phishing susceptibility: What makes someone susceptible to phishing? Can their susceptibility be predicted, and does phishing susceptibility increase with age? Methods To address these important research questions, we take a data-driven approach, fitting a series of neural network models to data from an adult lifespan sample of human decision-making behavior in a phishing email detection task with demonstrated ecological validity. By varying the size of hidden layers in the neural networks, we systematically investigated the dimensionality of phishing susceptibility, asking how many characterizing features of a participant and an email are needed to predict successful detection of phishing emails. We further examined how these dimensions correlated with signal detection metrics and age to elucidate their psychological significance. Results As few as 6 dimensions captured almost half the variability in the data. 2 dimensions were differentially associated with sensitivity and criterion. 3 dimensions showed significant but distinct correlations with age. Discussion Phishing susceptibility is low-dimensional and moderately predictable. Multiple dissociable components contribute to phishing detection, with age exerting distinct, component-specific influences. This work illustrates the utility of neural network modeling for uncovering latent structure in phishing susceptibility and advances understanding of trust-related decision making in adulthood and aging. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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