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"Don't … Break Down on Tuesday Because the Mental Health Services are Only in Town on Thursday": A Qualitative Study of Service Provision Related Barriers to, and Facilitators of Farmers' Mental Health Help-Seeking.

Caitlin VayroCharlotte BrownlowMichael J IrelandSonja March
Published in: Administration and policy in mental health (2020)
The suicide rate of farmers is approximately double that of the general Australian population, yet farmers employ fewer help-seeking behaviours (Arnautovska et al. in Soc Psychiatry Psychiatr Epidemiol 49:593-599, 2014; Brew et al. in BMC Public Health 16:1-11, 2016). Therefore, it is crucial to understand if, and how health services and system might influence farmer help-seeking. To shed light on this, the current study employed qualitative semi-structured interviews with 10 farmers, 10 farmers' partners and 8 medical practitioners. Thematic analysis, guided by Braun and Clarke's (Qual Res Psychol 3:77-101, 2006) techniques, was used to analyse the data. Three themes were devised concerning the interaction between farmers and health services, including 'health service interactions', 'services are provided within a complex system' and 'emerging technologies: the users, practitioners, and systems'. The findings underscore the importance of interactions between a farmer and a service provider, with farmers wanting their provider to have an understanding of farming life. Help-seeking was also shaped by access, availability, and practitioner constancy. Lastly, a complex relationship between digital mental health services and farmer help-seeking was reported, with factors related to the farmers, the practitioners and the infrastructure/systems discussed. The outcomes have implications for health service and policy reform, developing and providing interventions for farmers to promote health services interaction as a way of mental health help-seeking.
Keyphrases
  • mental health
  • primary care
  • public health
  • mental illness
  • healthcare
  • type diabetes
  • adipose tissue
  • south africa
  • big data
  • health insurance
  • insulin resistance
  • artificial intelligence
  • drug induced