Evidence map›Paper›PMID 41363968›Full record

ArticleJournal of the experimental analysis of behavior2026

Test-retest reliability for a social discounting of personal information task.

Stacy Willson, Paul Romanowich, Kevin Barba De La Mora, Qian Chen

Abstract read
In one paragraph

Article in Journal of the experimental analysis of behavior, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Test-retest reliability for a social discounting of personal information task.Journal of the experimental analysis of behavior · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Stacy WillsonElectrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA.
Paul RomanowichPsychology Department, Gonzaga University, Spokane, WA, USA.ORCID https://orcid.org/0000-0002-0911-0826
Kevin Barba De La MoraElectrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA.
Qian ChenElectrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA.

Funding

Department of Energy/National Nuclear Security Administration DE-NA0003985
6 · The paper itself

Abstract

Increasing cybercrime rates means identifying potential victims is critically important. Social discounting tasks show that individuals share less personally identifying information as social distance increases. However, the test-retest reliability and uniqueness of this measure is unclear. The current study assessed social discounting for personally identifying information (SDPII), delay discounting, risk taking, and personality at two measurement waves 30 days apart for 64 undergraduate students. Test-retest reliability was statistically significant for the SDPII and all other measures, replicating previous studies. SDPII rates were not significantly correlated with other measures during both measurement waves, showing discriminant validity. SDPII rates were lower than those reported in a previous study but were still well described by a hyperbolic discounting function, suggesting replicability across studies. The high test-retest reliability, uniqueness, and replicability of the SDPII suggests that it may quantitatively identify cybercrime victimization. Future research should test which measure or combination of measures can accurately predict scam and cybercrime victimization to inform data-based interventions.

Indexed as

Delay DiscountingSocial BehaviorAdolescentAdultCyberbullyingFemaleHumansMalePersonalityReproducibility of ResultsRisk-TakingYoung Adultcybersecuritypsychometricsscamsselfishnesssharing

Identifiers

PMID41363968
PMCPMC13500364

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.