Service utilisation by rural residents with mental health problems

Centre for Rural Mental Health, Monash University, School of Psychiatry, Psychology and Psychological Medicine, Bendigo Health Care Group, Bendigo, Vic., Australia.
Australasian Psychiatry (Impact Factor: 0.56). 06/2007; 15(3):185-90. DOI: 10.1080/10398560601123724
Source: PubMed

ABSTRACT To examine the level and type of service utilisation by rural residents for mental health problems, and to explore the influence of level of need, sociodemographic factors and town size on such service use.
This was a cross-sectional, community-based study. Subjects were recruited from three locales in rural north-west Victoria: a large regional centre, towns of 5,000-20,000 population and towns of <5,000 population. Three hundred and ninety-one individuals (54% females) participated. A logistic regression analysis was used to investigate which factors (i.e. need, sociodemographic and town size) predicted lifetime help-seeking for emotional or mental problems from formal health providers in the study sample.
Factors that predicted having ever sought help from a formal health provider for emotional or mental health problems were: a lifetime and/or current psychiatric disorder, being female, being separated, divorced or widowed, and living in medium sized towns (population 5,000-20,000).
While traditionally known predictors of help-seeking, i.e need and gender, were associated with help seeking in this study, help seeking for mental health problems was also more common amongst individuals living in medium sized rural towns than those living in a large regional city. Possible explanations include availability, accessibility and organisation of services, and individual and/or community attitudes towards help seeking.

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    • "As part of their involvement in a RCT of the effectiveness of a community-based intervention, the Alcohol Action in Rural Communities (AARC) project, 20 rural communities in New South Wales (NSW), Australia, participated in this study. Communities were invited to participate if they had a population between 5,000 and 20,000 (n=27), a population size identified as likely to be optimal for effective activation of community-based studies (Judd et al. 2007). Of the 27 communities that met this first criterion, three were excluded because they were within 100 km of an urban centre (population≥100,000) and were, therefore, likely to utilise health services and resources of those centres rather than in their own communities. "
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