Evidence map›Paper›PMID 29717529›Full record

ArticleHuman brain mapping2018

Estimation of vocational aptitudes using functional brain networks.

Yul-Wan Sung, Yousuke Kawachi, Uk-Su Choi, Daehun Kang, Chihiro Abe, Yuki Otomo, Seiji Ogawa

Abstract read
In one paragraph

Article in Human brain mapping, 2018. 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. 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

7 authors.

Yul-Wan SungKansei Fukushi Research Institute, Tohoku Fukushi University, Sendai, Japan.
Yousuke KawachiKansei Fukushi Research Institute, Tohoku Fukushi University, Sendai, Japan.
Uk-Su ChoiNeuroscience Research Institute, Gachon University, Incheon, Republic of Korea.ORCID 0000-0001-6698-0898
Daehun KangKansei Fukushi Research Institute, Tohoku Fukushi University, Sendai, Japan.
Chihiro AbeKansei Fukushi Research Institute, Tohoku Fukushi University, Sendai, Japan.
Yuki OtomoKansei Fukushi Research Institute, Tohoku Fukushi University, Sendai, Japan.
Seiji OgawaKansei Fukushi Research Institute, Tohoku Fukushi University, Sendai, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The success of human life in modern society is highly dependent on occupation. Therefore, it is very important for people to identify and develop a career plan that best suits their aptitude. Traditional test batteries for vocational aptitudes are not oriented to measure developmental changes in job suitability because repeated measurements can introduce bias as the content of the test batteries is learned. In this study, we attempted to objectively assess vocational aptitudes by measuring functional brain networks and identified functional brain networks that intrinsically represented vocational aptitudes for 19 job divisions in a General Aptitude Test Battery. In addition, we derived classifiers based on these networks to predict the aptitudes of our test participants for each job division. Our results suggest that the measurement of brain function can indeed yield an objective evaluation of vocational aptitudes; this technique will enable a person to follow changes in one's job suitability with additional training or learning, paving a new way to advise people on career development.

Indexed as

AptitudeConnectomeOccupationsAptitude TestsCareer ChoiceFemaleHumansMagnetic Resonance ImagingMaleNerve NetPsychometricsStudentsYoung Adultbrain function networksclassifiermulticlassresting-state fMRIsupport vector machinevocational aptitudes

Identifiers

PMID29717529
PMCPMC6866321

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.