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Background: As research focuses on the concept of resilience, evidence suggests that greater levels of personal hope may have a mitigating effect on the mental health impact of adversity. In view of the adversity affecting rural communities, a better understanding of factors influencing personal hope may help identify foci for mental health promotion and mental illness prevention research and interventions. Aim: To explore the relationship between demographic, socioeconomic and mental health factors and personal hopefulness, including the influence of locality and remoteness. Method: Using data from two community-based longitudinal cohorts from New SouthWales - one urban and one rural - we analysed cross-sectional relationships between a range of factors and personal hopefulness using logistic regression techniques, as part of a common follow-up. Personal hopefulness was measured using a 12-item scale and scores were categorised as low (<2.5), medium (2.5-3.4) and high (≥3.5). Results: Of 2774 participants (53% female, mean age 69.1 years [SD 7.3, range 58-91 years], 36% living outside metropolitan areas) 32% had low, 51% had medium and 17% had high personal hopefulness scores. Several factors displayed univariate associations with personal hopefulness. In the multivariate model, five factors were independently associated with lower personal hopefulness: being older, having lower perceived prosperity, less frequent socialisation, experiencing high psychological distress or psychological impairment. Hopefulness was not associated with geographical location. Conclusion: The impact of current psychological distress and aspects of adversity on personal hopefulness over time should be further investigated in longitudinal research. Personal hopefulness did not differ across geographical location. [ABSTRACT FROM AUTHOR]

This paper, presented at the 2010 rural health researchers' National Scientific Symposium on Rural and Remote Health, provides an overview of large Australian population mental health cohort studies which have a focus on climate‐related and environmental adversity, social factors and mental health. These studies highlight the value of exploiting multiple exceptional datasets to better understand the drivers of rural health, including how to use population‐level research to improve health resources in non‐metropolitan areas. We show how the key characteristics of rural and remote mental health might be explored by exploiting the following cohort studies: Household, Income and Labour Dynamics in Australia Survey; Australian Rural Mental Health Study; Hunter Community Study; and Extending Treatments, Education and Networks in Depression study. Existing cohort studies that focus on significant rural and regional characteristics can be creatively analysed to better understand geographic variation in mental health. They have the potential to move understanding beyond simple prevalence to building knowledge about the trajectories of psychological distress and determinants of mental disorders and outcomes over time. [ABSTRACT FROM AUTHOR]