Evidence map›Paper›PMID 37504788›Full record

ArticleJournal of Intelligence2023

The Meso-Expression Test (MET): A Novel Assessment of Emotion Perception.

Matthew L LaPalme, Sigal G Barsade, Marc A Brackett, James L Floman

Abstract read
In one paragraph

Article in Journal of Intelligence, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Matthew L LaPalmeYale Center for Emotional Intelligence, Yale University, New Haven, CT 06511, USA.ORCID 0000-0002-0902-1313
Sigal G BarsadeWharton, University of Pennsylvania, Philadelphia, PA 19104, USA.
Marc A BrackettYale Center for Emotional Intelligence, Yale University, New Haven, CT 06511, USA.
James L FlomanYale Center for Emotional Intelligence, Yale University, New Haven, CT 06511, USA.ORCID 0000-0003-0587-5271

Funding

Chan Zuckerberg Initiative NA
6 · The paper itself

Abstract

Emotion perception is a primary facet of Emotional Intelligence (EI) and the underpinning of interpersonal communication. In this study, we examined meso-expressions-the everyday, moderate-intensity emotions communicated through the face, voice, and body. We theoretically distinguished meso-expressions from other well-known emotion research paradigms (i.e., macro-expression and micro-expressions). In Study 1, we demonstrated that people can reliably discriminate between meso-expressions, and we created a corpus of 914 unique video displays of meso-expressions across a race- and gender-diverse set of expressors. In Study 2, we developed a novel video-based assessment of emotion perception ability: The Meso-Expression Test (MET). In this study, we found that the MET is psychometrically valid and demonstrated measurement equivalence across Asian, Black, Hispanic, and White perceiver groups and across men and women. In Study 3, we examined the construct validity of the MET and showed that it converged with other well-known measures of emotion perception and diverged from cognitive ability. Finally, in Study 4, we showed that the MET is positively related to important psychosocial outcomes, including social well-being, social connectedness, and empathic concern and is negatively related to alexithymia, stress, depression, anxiety, and adverse social interactions. We conclude with a discussion focused on the implications of our findings for EI ability research and the practical applications of the MET.

Indexed as

assessmentEIemotionemotional intelligence

Identifiers

PMID37504788
PMCPMC10381771

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.