Evidence map›Paper›PMID 42676346›Full record

ArticleFrontiers in psychology2026

Psychological capital matters: a methodological proof-of-concept for dual-dimensional student competitiveness assessment.

Qicui Du, Long Xu

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. 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

2 authors.

Qicui DuSchool of Stomatology, Qilu Medical University, Zibo, Shandong, China.
Long XuSchool of Basic Medical Sciences, Qilu Medical University, Zibo, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: In the contemporary era of boundaryless careers and Industry 5.0, sustainable employability refers not only to obtaining an initial job but also to maintaining and developing meaningful employment through adaptable human, social, and psychological resources. Traditional evaluation systems in higher education continue to rely heavily on visible cognitive signals such as cumulative grade point average (CGPA), thereby creating a hard-skill bias and leaving psychosocial resources weakly signaled. This study proposes a Balanced Weight-Constrained Fuzzy Analytic Hierarchy Process (BW-FAHP) as a methodological proof-of-concept for dual-dimensional student competitiveness assessment. Methods: The publicly available Kaggle campus-placement dataset ( Results: Imposing a transparent equilibrium between cognitive-academic and psychosocial-behavioral indicators changed candidate rankings relative to a GPA-centric benchmark and revealed a potentially overlooked high-potential profile characterized by average academic scores but strong behavioral resources. The balanced score also showed stronger alignment with the simulated placement criterion than the GPA-centric benchmark. Discussion: The stronger alignment should be interpreted as internal criterion alignment under the stated simulation assumptions rather than as evidence of real-world predictive superiority. The study provides a transparent and reproducible framework for making soft-skill assumptions explicit and offers a foundation for future validation using primary longitudinal data, validated psychosocial measures, and formal expert elicitation.

Indexed as

behavioral competenciescareer construction theoryfuzzy analytic hierarchy processhigher education policyholistic assessmentpsychological capitalsignaling theorysustainable employability

Identifiers

PMID42676346
PMCPMC13526538

What OpenQuestion holds

Textmetadata
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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.