Evidence map›Paper›PMID 41696933›Full record

ArticleCognitive science2026

Parsing Interactive Social Cognition: Mentalizing Accuracy and Propensity in Dyadic Contexts.

Lyra Pradhan, Katherine Rice Warnell

Abstract read
In one paragraph

Article in Cognitive science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Lyra PradhanDepartment of Psychology, Texas State University.
Katherine Rice WarnellDepartment of Psychology, Texas State University.ORCID 0000-0003-3694-7952

Funding

Psi ChiTexas State University
6 · The paper itself

Abstract

Successful social interaction requires attending to and accurately processing others' thoughts and feelings, a social cognitive skill known as mentalizing. To date, however, mentalizing has most frequently been assessed in nondyadic contexts, leaving open questions as to whether variability in real-world interactive social cognitive performance is due to trait-level differences or to properties of particular interactions. The current study examined mentalizing about one's social partner in both close social dyads (n = 50 dyads) and stranger dyads (n = 52 dyads). Within these dyadic contexts, we measured empathic accuracy-or the ability to accurately infer another's thoughts and feelings-and mind-mindedness, the propensity to spontaneously discuss another's mental states. We found that for both pre-existing close dyads and stranger dyads, the empathic accuracy of one partner significantly correlated with the empathic accuracy of the other partner, suggesting that empathic accuracy may be better conceptualized as a property of the specific social interaction rather than solely an individual trait. In contrast, across both dyad types, one partner's level of mind-mindedness did not relate to their partner's mind-mindedness. Further, a noninteractive measure of mentalizing accuracy did not show dyadic concordance. Individual levels of empathic accuracy, mind-mindedness, and noninteractive mentalizing accuracy were also uncorrelated. These findings underscore the importance of taking a multifaceted approach to measuring social cognition that considers the role of social context.

Indexed as

EmpathyInterpersonal RelationsMentalizationSocial CognitionSocial InteractionSocial PerceptionTheory of MindAdolescentAdultFemaleHumansMaleYoung AdultEmpathic accuracyMentalizingMind‐mindednessSocial cognitionSocial interactionTheory of mind

Identifiers

PMID41696933
PMCPMC12908434

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.