This PhD is part of an NHMRC/European Commission-funded project exploring the benefits of prescribing nature-based social activities to reduce loneliness and improve mental health. The project aims to better understand the effects of green space and biodiversity on loneliness and mental well-being and help create a framework for Nature-Based Social Prescribing (NBSP).
Our partners in Barcelona, Helsinki, Prague, Cuenca and Marseille are working with different vulnerable communities to test the effectiveness of various nature-based interventions. In Melbourne, we will be working with LGBTQI+ refugees and asylum seekers to co-design and run a local study exploring the impact of nature-based social activities. The Melbourne team is also responsible for proposing a methodology to measure the impact of environmental characteristics of green space (eg. level of biodiversity, site features) most likely to lead to beneficial outcomes. The PhD student will have access to a global data set to analyse correlations between the characteristics of the nature experience and loneliness outcomes.
The research involved in this PhD would suit a candidate with qualifications and/or professional experience in ecology, conservation science, health/psychology and/or human geography. The candidate should also have an interest in, and motivation for, biological conservation – particularly in urban environments. Knowledge of basic ecological theory is desirable. Applicants should also be familiar with a broad range of research methods (e.g. meta-analysis, interviews, site visits, focus groups, photovoice, participatory action research, observational approaches, and surveys). The position will require collaboration with both a small local team and a diverse, international team. The successful candidate will be involved in collecting and analysing local study data, and will also undertake analysis of datasets generated by our partners in Barcelona, Helsinki, Prague, Cuenca and Marseille. An interest in interdisciplinary research, international collaboration and analysing diverse/large data sets will be beneficial for this candidature.
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