| Literature DB >> 24197412 |
Arianne J van der Wal1, Hannah M Schade, Lydia Krabbendam, Mark van Vugt.
Abstract
An important barrier to enduring behavioural change is the human tendency to discount the future. Drawing on evolutionary theories of life history and biophilia, this study investigates whether exposure to natural versus urban landscapes affects people's temporal discount rates. The results of three studies, two laboratory experiments and a field study reveal that individual discount rates are systematically lower after people have been exposed to scenes of natural environments as opposed to urban environments. Further, this effect is owing to people placing more value on the future after nature exposure. The finding that nature exposure reduces future discounting-as opposed to exposure to urban environments-conveys important implications for a range of personal and collective outcomes including healthy lifestyles, sustainable resource use and population growth.Entities:
Keywords: biophilia; evolutionary psychology; life history; nature; sustainability; temporal discounting
Mesh:
Year: 2013 PMID: 24197412 PMCID: PMC3826228 DOI: 10.1098/rspb.2013.2295
Source DB: PubMed Journal: Proc Biol Sci ISSN: 0962-8452 Impact factor: 5.349
Figure 1.Percentage of participants that preferred the ‘x’ amount of euros in 90 days over the 100 euros now (Experiment 1), including the average individual indifference point for each condition. Nature condition differs significantly from the urban condition (p < 0.05).
Figure 2.Percentage of participants that were indifferent at the different discount-rate parameters (k) (Experiment 2), including the average individual indifference point for each condition. Nature condition differs significantly from the urban condition (p < 0.05).
Figure 3.Percentage of participants that preferred the ‘x’ amount of euros in 90 days over the 100 euros now (Experiment 3), including the average individual indifference point for each condition. Nature condition differs significantly from the urban condition (p < 0.05).