Psychological capital as a personal resource in the JD-R model

Steven L. Grover, Stephen T. T. Teo, David Pick, Maree Roche, Cameron J. Newton

Research output: Contribution to journalArticlepeer-review

124 Citations (Scopus)

Abstract

Purpose
The purpose of this paper is to demystify the role of the personal resource of psychological capital (PsyCap) in the job demands-resources model. The theory suggests that personal resources directly influence perceptions of job demands, job resources, and outcomes. Alternatively, personal resources may moderate the impact of job demands and job resources on outcomes.

Design/methodology/approach
A survey of 401 nurses working in the Australian healthcare sector explores the relations among PsyCap, job demands and resources, and psychological well-being and work engagement.

Findings
The results suggest that PsyCap directly influences perceptions of job demands and resources and that it directly influences the outcomes of well-being and engagement. Furthermore, job demands and job resources mediate the relation of PsyCap with well-being and engagement, respectively.

Research limitations/implications
The moderation effect of PsyCap was not supported, which suggests that PsyCap relates to perceptions as opposed to being a coping mechanism. This finding therefore narrows the scope of personal resources in this important model.

Originality/value
The importance of this study lies in its exploration of various ways that personal resources can influence this dominant model and in analyzing the global construct of PsyCap as opposed to some of its constituent parts.
Original languageEnglish
Pages (from-to)968-984
Number of pages17
JournalPersonnel Review
Volume47
Issue number4
Early online date11 May 2018
DOIs
Publication statusPublished - 25 May 2018
Externally publishedYes

Keywords

  • Quantitative
  • Nurses
  • Psychological capital
  • JD-R model
  • Engagement
  • Personal resources

Fingerprint

Dive into the research topics of 'Psychological capital as a personal resource in the JD-R model'. Together they form a unique fingerprint.

Cite this