Evidence map›Paper›PMID 36895756›Full record

ArticleFrontiers in psychology2023

Psychometric evaluation of the academic involution scale for college students in China: An application of Rasch analysis.

Yanchao Yang, Yan Peng, Wangze Li, Shan Lu, Chen Wang, Sirui Chen, Jialiang Zhong

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
8.0field-weighted citation impact, top 2% of its field
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

17 citing papers in PubMed, 24 citations in OpenAlex.

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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

7 authors at 2 institutions in 4 countries.

Yanchao YangNorth China University of Science and Technology, Tangshan, China.
Yan PengNorth China University of Science and Technology, Tangshan, China.
Wangze LiNorth China University of Science and Technology, Tangshan, China.
Shan LuNorth China University of Science and Technology, Tangshan, China.
Chen WangNorth China University of Science and Technology, Tangshan, China.
Sirui ChenFaculty of Education, University of Macau, Taipa, Macao SAR, China.
Jialiang ZhongNorth China University of Science and Technology, Tangshan, China.
North China University of Science and Technology · CNUniversity of Macau · MO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent academic attention on educational involution in China underpins the need for a valid and reliable instrument to precisely measure college students' academic involution behaviors. Seeing the scarcity of a proper instrument, the current study attempted to analyze the item-level psychometric properties of the newly developed Academic Involution Scale for College Students (AISCS) in China by using a Rasch model. A total of 637 college students in a public university in northern China participated in the study. Data were examined with respect to unidimensionality, rating scale functioning, item fit statistics, item polarity, item- and person-level reliability and separation, item hierarchy and invariance across educational background with Winsteps. The results show that AISCS was a single unidimensional construct with good psychometric properties. Although two items demonstrated differential item functioning, it is plausible given the differences between assessment methods for undergraduates and postgraduates. Limitations and future research directions with regard to sample selection, inclusion of more validity evidence and adding prospective additional academic involution were discussed.

Indexed as

academic involutioncollege studentsRasch analysisscale developmentscale validation

Identifiers

PMID36895756
PMCPMC9990466
OpenAlexW4321452575

What OpenQuestion holds

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LicenceCC BY
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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.