Evidence map›Paper›PMID 37126523›Full record

ArticlePloS one2023

Translating trait to state assessment: The case of grandiose narcissism.

Fien Heyde, Bart Wille, Evy Kuijpers, Jasmine Vergauwe, Joeri Hofmans

Abstract read
In one paragraph

Article in PloS one, 2023. 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. Level-specific reliability coefficients from the perspective of latent state-trait theory.The British journal of mathematical and statistical psychology · 2026
    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

5 authors.

Fien HeydeDepartment of Developmental, Personality, and Social Psychology, Ghent University, Gent, Belgium.ORCID 0000-0002-3993-3532
Bart WilleDepartment of Developmental, Personality, and Social Psychology, Ghent University, Gent, Belgium.
Evy KuijpersDepartment of Work and Organizational Psychology, Vrije Universiteit Brussel, Brussel, Belgium.
Jasmine VergauweDepartment of Developmental, Personality, and Social Psychology, Ghent University, Gent, Belgium.
Joeri HofmansDepartment of Work and Organizational Psychology, Vrije Universiteit Brussel, Brussel, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although interest in within-person variability in grandiose narcissism is growing, measurement tools are lacking that allow studying fluctuations in this personality characteristic in a differentiated manner (i.e., distinguishing narcissistic admiration and rivalry). This study explores whether a measurement approach using the six-item version of the Narcissistic Grandiosity Scale (NGS Rosenthal et al. (2007)) and six additional newly formulated adjectives allows assessing state admiration and rivalry. Structural characteristics and convergent validity of this approach were examined in an experience sampling study in which 114 adults participated, providing state assessments twice a day (total number of observations = 1306). Multilevel bifactor analyses revealed three factors (i.e., one general and two specific factors) at both within- and between-person levels. Further, admiration and rivalry showed a pattern of within-person associations with fluctuations in self-esteem and Big Five states that were consistent with theoretical expectations. Finally, average state admiration and average state rivalry correlated substantively with trait measures of these respective constructs assessed one week prior to the experience sampling design.

Indexed as

NarcissismPersonalityAdultHumansInterpersonal RelationsPersonality DisordersSelf Concept

Identifiers

PMID37126523
PMCPMC10150985

What OpenQuestion holds

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LicenceCC BY
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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.