Bendall Robert C A, Royle Sam, Dodds James, Watmough Hugh, Gillman Jamie C, Beevers David, Cassidy Simon, Short Ben, Metcalfe Paige, Lomas Michael J, Graham-Kevan Draco, Gregory Samantha E A
School of Health and Society, University of Salford, Allerton Building, Frederick Road, Salford, M5 4WT, UK.
Centre for Applied Health Research, University of Salford, Salford, UK.
Behav Res Methods. 2024 Dec 19;57(1):21. doi: 10.3758/s13428-024-02556-4.
The growing interest in harnessing natural environments to enhance mental health, including cognitive functioning and mood, has yielded encouraging results in initial studies. Given that images of nature have demonstrated similar benefits, they are frequently employed as proxies for real-world environments. To ensure precision and control, researchers often manipulate images of natural environments. The effectiveness of this approach relies on standardization of imagery, and therefore, inconsistency in methods and stimuli has limited the synthesis of research findings in the area. Responding to these limitations, the current paper introduces the Salford Nature Environments Database (SNED), a standardized database of natural images created to support ongoing research into the benefits of nature exposure. The SNED currently exists as the most comprehensive nature image database available, comprising 500 high-quality, standardized photographs capturing a variety of possible natural environments across the seasons. It also includes normative scores for user-rated (801 participants) characteristics of fascination, refuge and prospect, compatibility, preference, valence, arousal, and approach-avoidance, as well as data on physical properties of the images, specifically luminance, contrast, entropy, CIELAB colour space parameter values, and fractal dimensions. All image ratings and content detail, along with participant details, are freely available online. Researchers are encouraged to use this open-access database in accordance with the specific aims and design of their study. The SNED represents a valuable resource for continued research in areas such as nature-based therapy, social prescribing, and experimental approaches investigating underlying mechanisms that help explain how natural environments improve mental health and wellbeing.
利用自然环境来促进心理健康(包括认知功能和情绪)的兴趣日益浓厚,初步研究已取得了令人鼓舞的成果。鉴于自然图像已显示出类似的益处,它们经常被用作现实世界环境的替代物。为确保精确性和可控性,研究人员经常对自然环境图像进行操控。这种方法的有效性依赖于图像的标准化,因此,方法和刺激的不一致限制了该领域研究结果的综合。针对这些局限性,本文介绍了索尔福德自然环境数据库(SNED),这是一个标准化的自然图像数据库,旨在支持对自然接触益处的持续研究。SNED目前是现存最全面的自然图像数据库,包含500张高质量、标准化的照片,捕捉了四季中各种可能的自然环境。它还包括用户对魅力、庇护和前景、兼容性、偏好、效价、唤醒以及趋近-回避等特征的评分(801名参与者),以及图像物理属性的数据,特别是亮度、对比度、熵、CIELAB颜色空间参数值和分形维数。所有图像评分和内容细节,以及参与者细节均可在网上免费获取。鼓励研究人员根据其研究的具体目标和设计使用这个开放获取的数据库。SNED是自然疗法、社会处方以及研究潜在机制的实验方法等领域持续研究的宝贵资源,这些机制有助于解释自然环境如何改善心理健康和幸福感。