Work-related impacts on doctors' mental health: a qualitative study exploring organisational and systems-level risk
Belinda Lunnay1, Kristen Foley2, Sharon Lawn3
1Torrens University Australia, Adelaide, South Australia, Australia belinda.lunnay@torrens.edu.au.
Background:
Protecting doctors' mental health has typically focused on individuals, rather than addressing organisational and structural-level factors in the work environment.
Objectives:
This study uses the socioecological model (SEM) to illuminate and explore how these broader factors inform the mental health of individual doctors.
Design:
Semi-structured interviews (20-25 hours) and ethnographic observations (90 hours) involving work shadowing doctors (n=14).
Participants:
Doctors representing various career stages, specialty areas, genders and cultural backgrounds.
Setting:
Three specialties in a public South Australian hospital. Thematic analysis revealed work-related risk factors for poor mental health.
Results:
The SEM framework was used to analyse the work environment's impact on doctors' mental health. The analysis identified how the layers interconnect to influence risk factors for individual doctors. Microsystem: lack of control over career advancement, disenfranchisement due to understaffing and concerns about handling complex cases relative to experience. Mesosystem: negative impacts of shift work and fragmented teams, leading doctors to absorb pressure despite exhaustion to maintain professional credibility. Exosystem: high patient loads with time constraints and geographical limitations hindering care delivery, compounded by administrative burdens. Macrosystem: the commercialisation of medicine emphasising corporatisation and bureaucratic processes, which devalues professional autonomy.
Conclusions:
This study highlights how doctors experience layers of interconnected factors that compromise their mental health but over which they have very little control. Interventions must therefore address these issues at organisational and systemic levels, for which starting points evident within our data are identified.
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