Evidence map›Paper›PMID 34658987›Full record

ArticleFrontiers in psychology2021

Criterion Validity of the Implicit Positive and Negative Affect Test: Prediction of Facial Affect Perception.

Anna-Sophie Weil, Vivien Günther, Frank Martin Schmidt, Anette Kersting, Markus Quirin, Thomas Suslow

Abstract read
In one paragraph

Article in Frontiers in psychology, 2021. 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

6 authors.

Anna-Sophie WeilDepartment of Psychosomatic Medicine and Psychotherapy, University of Leipzig Medical Centre, Leipzig, Germany.
Vivien GüntherDepartment of Psychosomatic Medicine and Psychotherapy, University of Leipzig Medical Centre, Leipzig, Germany.
Frank Martin SchmidtDepartment of Psychiatry and Psychotherapy, University of Leipzig Medical Centre, Leipzig, Germany.
Anette KerstingDepartment of Psychosomatic Medicine and Psychotherapy, University of Leipzig Medical Centre, Leipzig, Germany.
Markus QuirinSchool of Management, TU München, Munich, Germany.
Thomas SuslowDepartment of Psychosomatic Medicine and Psychotherapy, University of Leipzig Medical Centre, Leipzig, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study focused on the criterion-related validity of the Implicit Positive and Negative Affect Test (IPANAT). The IPANAT is thought to be a measure of automatic activation of cognitive representations of affects. In this study, it was investigated whether implicit affect scores differentially predict ratings of facial emotions over and above explicit affectivity. Ninety-six young female participants completed the IPANAT, the Positive and Negative Affect Schedule (PANAS) as an explicit measure of state and trait affectivity, and a task for the perception of facial emotions. Implicit negative affect predicted the perception of negative but not positive facial emotions, whereas implicit positive affect predicted the perception of positive but not negative facial emotions. The observed double-dissociation in the correlational pattern strongly supports the validity of the IPANAT as a measure of implicit affectivity and is indicative of the orthogonality and thus functional distinctness of the two affect dimensions of the IPANAT. Moreover, such affect-congruent correlations were absent for explicit affect scales, which additionally supports the incremental validity of the IPANAT.

Indexed as

criterion validityexplicit affectimplicit affectimplicit positive and negative affect test (IPANAT)perception of facial emotion

Identifiers

PMID34658987
PMCPMC8517336

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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.