Supporting Reassigned Hospital Staff During the COVID-19 Pandemic in the Montreal Region: What Does it say About Leadership Styles?
Lara GautierMorgane GabetArnaud DuhouxLola TraversonValéry RiddeKate ZinszerPierre-Marie DavidPublished in: The Canadian journal of nursing research = Revue canadienne de recherche en sciences infirmieres (2023)
Globally, the COVID-19 pandemic took a high toll on health human resources, especially in contexts where these resources were already fragile. In Quebec, to make up for the shortage of health human resources, and to contain the COVID-19 outbreaks in long-term care facilities, many hospital staff (including a majority of nurses) were sent to those facilities, with varying degrees of support. Building on the body of evidence linking leadership style and resilience, we conducted a qualitative comparative analysis of two hospitals in the Montreal Metropolitan Area, Quebec. We explored respondents' experience of psychosocial support tools provided to hospital staff reassigned to COVID-affected facilities. Data from 27 in-depth interviews with high- and mid-level managers, and front-line workers, was analyzed through the lens of leadership styles. Our findings highlighted how the design and implementation of support tools revealed major differences across the two hospitals' leadership styles (i.e., one hospital expressing leader-centered styles vs. the other expressing follower-centered leadership styles). The expression of these leadership styles was largely shaped by recent policies, notably a major political reform of 2015, which enforced more centralized decision-making. Our study offered additional empirical evidence that leadership styles fostering the recovery of health human resources may be a key indicator of successful response to crises.
Keyphrases
- healthcare
- endothelial cells
- public health
- mental health
- sars cov
- coronavirus disease
- induced pluripotent stem cells
- decision making
- adverse drug
- acute care
- health information
- primary care
- mild cognitive impairment
- climate change
- machine learning
- quality improvement
- health insurance
- long term care
- human health
- social media
- single cell
- big data
- long non coding rna