Evidence map›Paper›PMID 36519150›Full record

ArticleAffective science2022

Decoding the Regulator: Accuracy and Bias in Emotion Regulation Judgments.

Lameese Eldesouky, Yue Guo, Katlin Bentley, Tammy English

Abstract read
In one paragraph

Article in Affective science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Lameese EldesoukyDepartment of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, USA.ORCID 0000-0003-4977-8203
Yue GuoDepartment of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, USA.
Katlin BentleyDepartment of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, USA.
Tammy EnglishDepartment of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, USA.

Funding

AGING AND DEVELOPMENTT32AG000030 · NIA · WASHINGTON UNIVERSITY · PI DENISE HEAD, Jeffrey M Zacks · 1985 to 2026
$9.7M
NIA NIH HHS T32 AG000030
6 · The paper itself

Abstract

Accurately judging emotion regulation (ER) may help facilitate and maintain social relationships. We investigated the accuracy and bias of ER judgments and their social correlates in a two-part study with 136 married couples (ages 23-85 years). Couples completed trait measures of their own and their partner's suppression, reappraisal, and situation selection. On a separate day, they discussed a conflict, then rated their own and their partner's suppression during the discussion. Couples accurately judged their partner's trait level use of all ER strategies, but they were most accurate for suppression. In contrast, they did not accurately judge state suppression; they showed a similarity bias, such that their own use of state suppression predicted judgments of their partner's suppression. Greater relationship satisfaction predicted positive biases at the trait level (e.g., overestimating reappraisal, underestimating suppression), but not the state level. Relationship length did not predict ER accuracy or bias. Findings suggest ER is more detectable at the trait level than state level and for strategies with more behavioral cues. Greater relationship satisfaction may signal positive perceptions of partners' ER patterns. Supplementary Information: The online version contains supplementary material available at 10.1007/s42761-022-00144-3.

Indexed as

AccuracyBiasEmotion regulationPersonality judgmentRelationships

Identifiers

PMID36519150
PMCPMC9743848

What OpenQuestion holds

Textmetadata
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.