Evidence map›Paper›PMID 42141109›Full record

ArticleScientific reports2026

Age-related patterns in the creation of social prediction models: a study using immersive virtual reality.

Libera Siciliano, Maria Pyasik, Gaetano Tieri, Valentina Ciot, Claudia Salera, Nicole Urbini, Viola Oldrati, Andrea Ciricugno, Giusy Olivito, Renato Borgatti and 4 more

Abstract read
In one paragraph

Article in Scientific reports, 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. 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

14 authors.

Libera Siciliano *Department of Human Sciences, Link Campus University, Rome, Italy. l.siciliano@unilink.it.
Maria Pyasik *Scientific Institute, IRCCS E. Medea, Pasian di Prato, Udine, Italy. maria.pyasik@lanostrafamiglia.it.
Gaetano TieriVirtual Reality Lab, Department of Law and Digital Society, Unitelma Sapienza University, Rome, Italy.
Valentina CiotDepartment of Life Sciences, University of Trieste, Trieste, Italy.
Claudia SaleraSmArt Lab, IRCCS Santa Lucia Foundation, Rome, Italy.
Nicole UrbiniAtaxia Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy.
Viola OldratiScientific Institute, IRCCS E. Medea, Bosisio Parini, Lecco, Italy.
Andrea CiricugnoIRCCS Mondino Foundation, Pavia, Italy.
Giusy OlivitoAtaxia Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy.
Renato BorgattiIRCCS Mondino Foundation, Pavia, Italy.
Marco IosaSmArt Lab, IRCCS Santa Lucia Foundation, Rome, Italy.
Zaira CattaneoDepartment of Human and Social Sciences, University of Bergamo, Bergamo, Italy.
Cosimo UrgesiScientific Institute, IRCCS E. Medea, Pasian di Prato, Udine, Italy.
Maria LeggioAtaxia Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy.

Funding

IRCCS E. Medea Ricerca Corrente 2024-2025Ministero della Salute RF-2021-12374279Ministero dell'Istruzione, dell'Università e della Ricerca PRIN 20203LT7H3Sapienza Università di Roma RG124190F579BA6E
6 · The paper itself

Abstract

Exposure to environmental regularities allows individuals to build internal models, supporting the integration of prior expectations with sensory input in social contexts. However, how social prediction models develop across age and experience remains unclear. To address this, we investigated whether the formation of social predictive models varies across age and experiences in neurotypical individuals (early adolescents, young adults, and adults). Participants completed, in counterbalanced order, two scenarios of an immersive virtual reality (IVR) task that facilitates the creation of top-down predictions during action perception, requiring the participants to implicitly associate the hand movement of four avatars toward one preferred object among three. Self-report questionnaires and standard social cognition tests were used to assess embodiment, presence, usability in the IVR setting, and the direct association between the novel IVR task and social-cognitive tests. Results showed significant performance improvement from the first to the second scenario in all groups, indicating learning and refinement of predictive models. Early adolescents performed significantly worse and showed a lower learning rate than adult groups, who did not differ from each other, suggesting slower formation of social prior expectations in early adolescents. The IVR paradigm was feasible across all age groups and proved valid for assessing social processing. These findings support a developmental trajectory in which the creation of predictive internal models improves with age and experience.

Indexed as

Social CognitionVirtual RealityAdolescentAdultAge FactorsAvatarFemaleHumansMaleYoung AdultAdolescenceAdulthoodImmersive virtual realityPrior expectationsTop-down social predictions

Identifiers

PMID42141109
PMCPMC13369978

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.