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      Moving beyond Green: Exploring the Relationship of Environment Type and Indicators of Perceived Environmental Quality on Emotional Well-Being following Group Walks

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          Abstract

          Against the backdrop of increasing interest in the relationship between Nature and health, this study examined the effect of perceived environment type and indicators of perceived environmental quality on short-term emotional well-being following outdoor group walks. Participants ( n = 127) of a national group walk program completed pre- and post-walk questionnaires for each walk attended ( n = 1009) within a 13-week study period. Multilevel linear modelling was used to examine the main and moderation effects. To isolate the environmental from the physical activity elements, analyses controlled for walk duration and perceived intensity. Analyses revealed that perceived restorativeness and perceived walk intensity predicted greater positive affect and happiness following an outdoor group walk. Perceived restorativeness and perceived bird biodiversity predicted post-walk negative affect. Perceived restorativeness moderated the relationship between perceived naturalness and positive affect. Results suggest that restorative quality of an environment may be an important element for enhancing well-being, and that perceived restorativeness and naturalness of an environment may interact to amplify positive affect. These findings highlight the importance of further research on the contribution of environment type and quality on well-being, and the need to control for effects of physical activity in green exercise research.

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            A systematic review of evidence for the added benefits to health of exposure to natural environments

            Background There is increasing interest in the potential role of the natural environment in human health and well-being. However, the evidence-base for specific and direct health or well-being benefits of activity within natural compared to more synthetic environments has not been systematically assessed. Methods We conducted a systematic review to collate and synthesise the findings of studies that compare measurements of health or well-being in natural and synthetic environments. Effect sizes of the differences between environments were calculated and meta-analysis used to synthesise data from studies measuring similar outcomes. Results Twenty-five studies met the review inclusion criteria. Most of these studies were crossover or controlled trials that investigated the effects of short-term exposure to each environment during a walk or run. This included 'natural' environments, such as public parks and green university campuses, and synthetic environments, such as indoor and outdoor built environments. The most common outcome measures were scores of different self-reported emotions. Based on these data, a meta-analysis provided some evidence of a positive benefit of a walk or run in a natural environment in comparison to a synthetic environment. There was also some support for greater attention after exposure to a natural environment but not after adjusting effect sizes for pretest differences. Meta-analysis of data on blood pressure and cortisol concentrations found less evidence of a consistent difference between environments across studies. Conclusions Overall, the studies are suggestive that natural environments may have direct and positive impacts on well-being, but support the need for investment in further research on this question to understand the general significance for public health.
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              Probing Interactions in Fixed and Multilevel Regression: Inferential and Graphical Techniques.

              Many important research hypotheses concern conditional relations in which the effect of one predictor varies with the value of another. Such relations are commonly evaluated as multiplicative interactions and can be tested in both fixed- and random-effects regression. Often, these interactive effects must be further probed to fully explicate the nature of the conditional relation. The most common method for probing interactions is to test simple slopes at specific levels of the predictors. A more general method is the Johnson-Neyman (J-N) technique. This technique is not widely used, however, because it is currently limited to categorical by continuous interactions in fixed-effects regression and has yet to be extended to the broader class of random-effects regression models. The goal of our article is to generalize the J-N technique to allow for tests of a variety of interactions that arise in both fixed- and random-effects regression. We review existing methods for probing interactions, explicate the analytic expressions needed to expand these tests to a wider set of conditions, and demonstrate the advantages of the J-N technique relative to simple slopes with three empirical examples.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                23 December 2014
                January 2015
                : 12
                : 1
                : 106-130
                Affiliations
                [1 ]Department of Psychology, Edge Hill University, St. Helens Road, Ormskirk, L39 4QP, UK
                [2 ]Social, Economic and Geographical Sciences Research Group, The James Hutton Institute, Craigiebuckler, Aberdeen, AB15 8QH, UK; E-Mail: katherine.irvine@ 123456hutton.ac.uk
                [3 ]Institute of Energy and Sustainable Development, De Montfort University, Leicester, LE1 9BH, UK
                [4 ]BioSS—Biomathematics and Statistics Scotland, Craigiebuckler, Aberdeen, AB15 8QH, UK; E-Mail: altea.lorenzo-arribas@ 123456bioss.ac.uk
                [5 ]Department of Family Medicine, University of Michigan Medical School, Ann Arbor, MI 48104, USA; E-Mail: swarber@ 123456umich.edu
                Author notes
                [* ]Author to whom correspondence should be addressed; E-Mail: melissa.marselle@ 123456gmail.com ; Tel. +44-(0)-161-295-2693; Fax: +44-(0)-161-295-5678.
                Article
                ijerph-12-00106
                10.3390/ijerph120100106
                4306852
                25546275
                a36d48d8-477e-42a5-8c13-f05878026f04
                © 2014 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 04 May 2014
                : 15 December 2014
                Categories
                Article

                Public health
                emotional well-being,perceived restorativeness,biodiversity,attention restoration theory,environmental quality indicators,green exercise,group walks

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