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The role of team compassion in mitigating the impact of hierarchical bullying

Published online by Cambridge University Press:  17 May 2023

Ben Farr-Wharton
Affiliation:
Edith Cowan University (ECU), Perth, Australia
Ace Volkmann Simpson
Affiliation:
Brunel University, London, England
Yvonne Brunetto*
Affiliation:
SCU, Bilinga, Australia
Tim Bentley
Affiliation:
Edith Cowan University (ECU), Perth, Australia
*
Corresponding author: Yvonne Brunetto, E-mail: yvonne.brunetto@scu.edu.au
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Abstract

Hierarchical bullying in public healthcare organizations is an entrenched negative behaviour that results in a range of adverse outcomes for staff, including diminished wellbeing. This study integrates social exchange and conservation of resources theories as a lens for formulating hypotheses and employs multilevel statistical modelling to examine whether team-level compassion moderates the impact of hierarchical bullying on wellbeing. Using multilevel statistical modelling, the study analysed cross-sectional data from 632 healthcare workers nested within 48 teams in a single public health district in Australia. The findings indicate that work teams with higher levels of team compassion can mitigate the negative effects of hierarchical bullying on employee wellbeing. The results imply that investing in developing compassion within teams is an effective strategy for mitigating some harmful effects of hierarchical bullying on employee outcomes.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press in association with the Australian and New Zealand Academy of Management
Figure 0

Figure 1. Hypothetical model.

Figure 1

Table 1. Within- and between-level instrument reliability

Figure 2

Table 2. Descriptive statistics and correlations

Figure 3

Figure 2. Results from multilevel moderations 1 × (1−>1) model. *p > .5, **p > .01, ***p > .000. Within n = 632, between n = 48. Estimator = Bayes (one tailed), integration = 4.

Figure 4

Figure 3. Interaction testing – hierarchical bullying on wellbeing moderated by team-level compassion