Background: Living near, recreating in, and feeling psychologically connected to nature are all associated with better overall mental health. This study aims to better understand people’s feelings towards different types of natural and built green space environments in the highly urbanized ‘garden city’ of Singapore. The key research question addresses the matter of what types of green space elicit positive (Eudemonic) or negative (Apprehensive) affective responses. Type of environment (natural and built), frequency of experience (high and low) and childhood location (urban, suburban, rural) were tested for effects of Eudemonia and Apprehension. 288 adults and university students residing in Singapore completed a survey that asked them to report affective states in response to images of 10 locally different environment types and to complete measures of nature connectedness, childhood location, frequency of visit to natural/built environments, and dispositional anxiety, as well as demographic items for age and gender.
This data record contains:
- Qualtrics survey data in SPSS (.spss), tab delimited (.dat) and open document (.ods) format.
- Supplementary material in PDF format (.pdf) containing the Mean (sd) ratings of Apprehension (A, anxious, isolated, lonely) and Eudemonia (E, alive, awe, connected, contemplative, empathy, freedom, fun, refreshed, relaxed, serene, talkative) for 10 types of environment.
The Qualtrics survey included the following:
- Participant demographics:
- Age in years (continuous)
- Gender (categorical: Male, Female, Nonbinary)
- Categorisation of urban green space in Singapore:
- 20 photographs of urban green spaces in Singapore (stimuli).
- 10 categories of urban green spaces consisted of: beach, forest, grassy field, heritage street, modern city street, rooftop garden, river, town park, wetland, and woodland.
- Two photographs that were best suited to each category according to participant responses (i.e., highest frequency of category selection) were used as stimuli for the study, with a total of 20 photographs selected.
- Experiential feeling states (Eudemonia & Apprehension) (interval) (20 x 14 items).
- “Imagine yourself in the environment shown above. To what extent would you feel the following?”
- Responses were recorded on a 7-point scale ranging from not at all (1) to extremely (7).
- Frequency of experience in green space (interval) (20 x 1 item).
- “On average, how often do you visit or experience the type of environment as the one shown above?” Responses were recorded on a 5-point scale ranging from never (1) to very often (5).
- Childhood location (categorical) (1 item). “In what sort of location did you spend the majority of your childhood?” Urban (Modernised city, city-centre, many buildings with few trees, high traffic), Suburban (More greenery than city-centre but still developed, outside the main city area, neighbourhood towns, moderate traffic), Rural (Mostly greenery, few facilities, low traffic, “kampung” environment).
- Nature Connectedness Index (NCI) (interval) (6 items). "The next items will help us understand how you feel about nature and natural environments. Remember, this is not a test so there are no 'right' or 'wrong' answers. We want to understand how you feel about nature." The six items draw on five pathways to nature connectedness: emotion, beauty, contact, meaning and compassion. Participants respond using a 7-point scale ranging from completely agree (1) to completely disagree (7). Raw scores were transformed using a weighted points index ranging from zero to 100.
- Brief State-Trait Anxiety Inventory (STAIT-5) (interval) (5 items). “A number of statements which people have used to describe themselves are given below. Read each statement and then select the number at the end of the statement that indicates how you generally feel.” Responses are recorded on a 4-point scale ranging from not at all (1) to very much so (4).
Software/equipment used to create/collect the data: Qualtrics Online Survey Software through JCU licence
Software/equipment used to manipulate/analyse the data: SPSS, Microsoft Excel