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Impact of work competencies on job performance among university counsellors.

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Title: Impact of work competencies on job performance among university counsellors.
Authors: Cao, Jie1 (AUTHOR), Abu Mansor, Nur Naha2 (AUTHOR), Li, Jinhua3 (AUTHOR) lijinghua@xnu.edu.cn
Source: PLoS ONE. 12/11/2024, Vol. 19 Issue 12, p1-25. 25p.
Subject Terms: *JOB performance, *STRUCTURAL equation modeling, *COUNSELORS, *SAMPLING (Process), *DATA analysis, *TASK performance
Abstract: This study aims to examine the relationship between work competency factors—namely knowledge, skills, traits, motives, and self-concepts—and job performance among university counsellors in China. Data were collected from 310 university counsellors using multiple sampling techniques. Partial Least Squares Structural Equation Modeling (PLS-SEM), via Smart-PLS version 3.3.2, was employed for data analysis. The findings revealed that four competency factors—knowledge, skills, traits, and motives—were significantly related to job performance among university counsellors in Hunan Province. These results contribute to a deeper understanding of the impact of work competencies on job performance. It can provide valuable insights for administrators and policymakers aiming to improve the competencies and performance of university counsellors, as well as to enhance the overall development of the counselling team. [ABSTRACT FROM AUTHOR]
Copyright of PLoS ONE is the property of Public Library of Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Impact of work competencies on job performance among university counsellors.
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  Data: <searchLink fieldCode="AR" term="%22Cao%2C+Jie%22">Cao, Jie</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Abu+Mansor%2C+Nur+Naha%22">Abu Mansor, Nur Naha</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Jinhua%22">Li, Jinhua</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> lijinghua@xnu.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22PLoS+ONE%22">PLoS ONE</searchLink>. 12/11/2024, Vol. 19 Issue 12, p1-25. 25p.
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  Data: *<searchLink fieldCode="DE" term="%22JOB+performance%22">JOB performance</searchLink><br />*<searchLink fieldCode="DE" term="%22STRUCTURAL+equation+modeling%22">STRUCTURAL equation modeling</searchLink><br />*<searchLink fieldCode="DE" term="%22COUNSELORS%22">COUNSELORS</searchLink><br />*<searchLink fieldCode="DE" term="%22SAMPLING+%28Process%29%22">SAMPLING (Process)</searchLink><br />*<searchLink fieldCode="DE" term="%22DATA+analysis%22">DATA analysis</searchLink><br />*<searchLink fieldCode="DE" term="%22TASK+performance%22">TASK performance</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study aims to examine the relationship between work competency factors—namely knowledge, skills, traits, motives, and self-concepts—and job performance among university counsellors in China. Data were collected from 310 university counsellors using multiple sampling techniques. Partial Least Squares Structural Equation Modeling (PLS-SEM), via Smart-PLS version 3.3.2, was employed for data analysis. The findings revealed that four competency factors—knowledge, skills, traits, and motives—were significantly related to job performance among university counsellors in Hunan Province. These results contribute to a deeper understanding of the impact of work competencies on job performance. It can provide valuable insights for administrators and policymakers aiming to improve the competencies and performance of university counsellors, as well as to enhance the overall development of the counselling team. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of PLoS ONE is the property of Public Library of Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1371/journal.pone.0315494
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        Text: English
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      – SubjectFull: JOB performance
        Type: general
      – SubjectFull: STRUCTURAL equation modeling
        Type: general
      – SubjectFull: COUNSELORS
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      – SubjectFull: DATA analysis
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              Text: 12/11/2024
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              Y: 2024
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