Department of Forestry and Forest Ecology, Faculty of Environmental Management and Agriculture, University of Warmia and Mazury in Olsztyn, Pl. Łódzki 2, 10-727 Olsztyn, Poland.
Department of Counseling, Educational Psychology, and Foundations, Mississippi State University, Starkville, MS 39759, USA.
Int J Environ Res Public Health. 2020 Sep 16;17(18):6731. doi: 10.3390/ijerph17186731.
In this study, a method for predicting the preferred pleasantness induced by different forest environments, represented by virtual photographs, was proposed and evaluated using a novel Anti-Environmental Forest Experience Scale psychometric test. The evaluation questionnaire contained twenty-one items divided into four different subscales. The factor structure was assessed in two separate samples collected online (sample 1: = 254, sample 2: = 280). The internal validity of the four subscales was confirmed using exploratory factor analysis. Discriminant validity was tested and confirmed using the Amoebic Self Scale (spatial-symbolic domain). Concurrent validity was confirmed using the Connectedness to Nature Scale. Predictive validity was based on an assessment of pleasantness induced by nine different photographs (control-urban landscapes, forest landscapes, dense forest landscapes), with subscales differently correlated with the level of pleasantness assessed for each photograph. This evaluation instrument is appropriate for predicting preferred pleasantness induced by different forest environments.
在这项研究中，我们提出了一种使用新型抗环境森林体验量表心理测试来预测不同森林环境（由虚拟照片表示）所引起的偏好愉悦感的方法，并对其进行了评估。评估问卷包含二十一个项目，分为四个不同的分量表。在两个在线收集的独立样本中（样本 1：n=254，样本 2：n=280）评估了因子结构。使用探索性因子分析确认了四个分量表的内部有效性。使用阿米巴自我量表（空间-符号领域）测试并确认了判别有效性。使用与自然的联系量表确认了同时有效性。预测有效性是基于对九张不同照片（控制-城市景观、森林景观、茂密森林景观）引起的愉悦感的评估，其中各分量表与为每张照片评估的愉悦感水平呈不同程度的相关。该评估工具适用于预测不同森林环境所引起的偏好愉悦感。
