Contact with nature has emotional benefits, but the psychological mechanism and potential moderator underlying the association between nature contact and emotion regulation remain unclear. The present study investigated how self-reported frequency of nature contact is associated with the use of emotion regulation strategies and explored the mediating role of nature connectedness (i.e., psychological connection to nature) and the moderating role of engagement with natural beauty. Employing mediation and moderated mediation analyses, in a cross-sectional sample of 2097 young adults aged 18–35 years old (M = 24.01, SD = 4.80) residing in urban China, we obtained three major findings. First, nature connectedness mediated the associations between direct/indirect nature contact and cognitive reappraisal as well as expressive suppression. Second, engagement with natural beauty moderated the path from direct/indirect nature contact to cognitive reappraisal in the mediation models. Third, engagement with natural beauty moderated the path from indirect nature contact to nature connectedness in the mediation models. Our study is the first to reveal mediating and moderating factors in the relationships among direct/indirect contact with nature, nature connectedness, engagement with natural beauty, and emotion regulation strategies. These findings provide support for the emotional health of nature contact and have implications for nature-based education and urban planning.

Purpose: Susceptibility distortions impact diffusion MRI data analysis and is typically corrected during preprocessing. Correction strategies involve three classes of methods: registration to a structural image, the use of a fieldmap, or the use of images acquired with opposing phase encoding directions. It has been demonstrated that phase encoding based methods outperform the other two classes, but unfortunately, the choice of which phase encoding based method to use is still an open question due to the absence of any systematic comparisons. Methods: In this paper we quantitatively evaluated six popular phase encoding based methods for correcting susceptibility distortions in diffusion MRI data. We employed a framework that allows for the simulation of realistic diffusion MRI data with susceptibility distortions. We evaluated the ability for methods to correct distortions by comparing the corrected data with the ground truth. Four diffusion tensor metrics (FA, MD, eigenvalues and eigenvectors) were calculated from the corrected data and compared with the ground truth. We also validated two popular indirect metrics using both simulated data and real data. The two indirect metrics are the difference between the corrected LR and AP data, and the FA standard deviation over the corrected LR, RL, AP, and PA data. Results: We found that DR-BUDDI and TOPUP offered the most accurate and robust correction compared to the other four methods using both direct and indirect evaluation metrics. EPIC and HySCO performed well in correcting b₀ images but produced poor corrections for diffusion weighted volumes, and also they produced large errors for the four diffusion tensor metrics. We also demonstrate that the indirect metric (the difference between corrected LR and AP data) gives a different ordering of correction quality than the direct metric. Conclusion: We suggest researchers to use DR-BUDDI or TOPUP for susceptibility distortion correction. The two indirect metrics (the difference between corrected LR and AP data, and the FA standard deviation) should be interpreted together as a measure of distortion correction quality. The performance ranking of the various tools inferred from direct and indirect metrics differs slightly. However, across all tools, the results of direct and indirect metrics are highly correlated indicating that the analysis of indirect metrics may provide a good proxy of the performance of a correction tool if assessment using direct metrics is not feasible.