Revised Contemplative Landscape Model (CLM): A reliable and valid evaluation tool for mental health-promoting urban green spaces

Due to rapid urbanization and an increase in mental health issues in urban populations, urban green spaces (UGS) design needs to be optimized to meet mental health and well-being promotion goals. However, existing frameworks and tools that aim to address this pressing need are often not adequately validated against health measures. The Contemplative Landscape Model (CLM), developed in 2016, is the first instrument that measures the quality of UGS and informs landscape design with regard to the mental health and well-being of people passively exposed to them. Recent studies with this tool and developments in UGS literature prompted the development and validation of a revised version of CLM presented here. The reliability and validity of CLM were tested with a panel of independent experts and showed better reliability/internal consistency (ω = .893; α = .890) than the original CLM. This time, validity was tested in two ways: (1) against neuropsychological data (electroencephalogram, EEG, and self-reported valence and arousal ratings), acquired during passive exposure to UGS scenes and (2) through factor analysis of experts’ UGS assessments. Validity testing showed that (1) CLM predicts brain activity patterns associated with mindfulness, relaxation, and positive mood, and (2) contemplativeness of landscapes is a valid construct undergird by two parallel factors both predicting beneficial EEG responses. In conclusion, CLM is an effective and robust instrument for assessing the visual quality of UGS predictive of mental health and well-being benefits in urban residents.