How did parks and greenspace use change three months into the pandemic? Parks and greenspace can help mental health but also may be sites of virus transmission.

Share

Target audience

Public Health officials; Parks and greenspace planners; Urban citizens

The problem

The COVID-19 pandemic has radically altered the risks associated with public space. Because the virus is socially communicable, members of the general public may avoid public space. Yet, public spaces such as parks and greenspace provide stress restoration benefits that are important during times of crisis. As such, it is unclear whether the general public is visiting parks during the pandemic more or less often than before the pandemic.

What we did and why

In this study we examined how the pandemic affected the general public’s patterns of behaviour in public space within a region in Southwestern Ontario. We explored whether the frequency of, as well as reason for, visiting parks or greenspace was self-reported as to have changed as a result of the pandemic. We also investigated whether demographic variables of age, gender, income, education, household density, household type, and city of residence predicted change in park and greenspace use.

Our study’s contribution

Our his study demonstrates a significant decrease in park and greenspace use three months into the pandemic. Change in frequency of park and greenspace visitation was significantly predicted by gender, reason for visitation, number of people in household, and income. Regarding these effects, it is speculated that the perception of COVID-19 transmission risk overrides the perceived stress restoration benefits of parks and greenspace.

Impacts for city policy and practice

Given the unprecedented effect the pandemic has had on population-level indices of mental health, consideration should be given to facilitating access to parks and greenspaces. This is particularly true for spaces that facilitate physical activities. Future research should investigate the motivational differences between genders, ages, and income levels, so that all members of the public are equitably supported by parks and greenspaces infrastructure during and after the pandemic.

Further information

Urban Realities Laboratory: We study the impact of urban design on human psychology. We employ a variety of methods from field studies of behaviour in urban and architectural settings to the use of immersive virtual reality to test predictions about urban behaviour in simulations.

Our goals are both to contribute to theory in environmental psychology and to develop tools that can be applied to specific problems and issues relating to the psychology of the built environment. We welcome inquiries from potential students and collaborators both within and outside the academic domain.

Full research article:

The effect of COVID-19 on parks and greenspace use during the first three months of the pandemic – a survey study by David Borkenhagen, Emily Grant, Robin Mazumder, Hanna R. Negami, Jatheesh Srikantharajah & Colin Ellard

Related posts

Understanding gardening for wildlife in London’s private residential gardens

We wanted to understand the types of gardening for wildlife taking place in London’s private gardens and the influence of demographic factors on the likelihood to garden for wildlife. We sent out a digital questionnaire to ask Londoners about their gardening for wildlife practices and their age, gender, ethnicity, religious beliefs, occupation, household income, accommodation type, home ownership status, garden type, shared garden or not, dependents, and conservation-organisation membership status.

Read More »

What determines better neighbouring among affordable housing residents in Metro Vancouver, Canada

At the intersection of urban and public health policy, the success of higher-density affordable housing solutions to serve an inclusive well-being agenda depends upon reducing the association of these lifestyles and built environments with loneliness and social isolation. We construct a pro-neighbouring index and test its predictors using an ordinal logistic regression model based on resident survey data.

Read More »