Evidence map›Paper›PMID 35391989›Full record

ArticleFrontiers in psychology2022

Measuring Conceptual Associations

Ching-Lin Wu, Pei-Zhen Chen, Hsueh-Chih Chen

Abstract read
In one paragraph

Article in Frontiers in psychology, 2022. 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

3 authors.

Ching-Lin WuProgram of Learning Sciences, National Taiwan Normal University, Taipei City, Taiwan.
Pei-Zhen ChenDepartment of Educational Psychology and Counseling, National Taiwan Normal University, Taipei City, Taiwan.
Hsueh-Chih ChenInstitute for Research Excellence in Learning Sciences, National Taiwan Normal University, Taipei City, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple versions of the Chinese Remote Associates Test (CRAT) have been developed. Thus far, all CRATs have employed verbal stimuli; other forms of stimuli have not yet been used. In this context, the present study compiled a Chinese Visual Remote Associates Test (CVRAT) that conforms to the Chinese language and culture based on a picture naming database. The developed CVRAT has two versions, CVRAT-A and CVRAT-B, each comprising 20 test questions. A typical CVRAT question consists of three stimuli pictures, requiring respondents to propose a target word that is semantically associated with all the pictures. When compiling the CVRAT, this study first selected target words, sifted through stimuli words and corresponding pictures, and analyzed pilot test questions. After compilation, their reliability and validity were examined. The results showed that the CVRAT had moderate internal consistency reliability, good criterion-related validity for the Chinese Word Remote Associates Test (CWRAT), Chinese Radical Remote Associates Test (CRRAT), Chinese Compound Remote Associates Test (CCRAT), insight problem-solving, as well as acceptable discriminant validity for fluency, flexibility, and originality of a divergent thinking test. In other words, CVRAT can effectively measure remote associative capability and provides a figural creativity test that facilitates the understanding of different kinds of remote associations.

Indexed as

creativityfree associationpicture namingremote associates testvisualization

Identifiers

PMID35391989
PMCPMC8980321

What OpenQuestion holds

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LicenceCC BY
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.