Experiences of greenspace and wellbeing for asylum seekers and refugess (ASARs) in Leeds

该项目旨在进一步调查ASARs中绿色空间与福祉之间的相关性。研究问题Q1: ASARs最重视绿色空间的哪些方面，哪些观念、经验、实践和障碍影响了这些价值观？Q2 . ASARs最看重的绿地特征和设施是否反映在其所在地区？Q3如何使用干预措施来增强城市绿地对ASARs的心理健康益处？方法参与第一季度和第三季度研究的参与者将通过利兹寻求庇护者支持网络等组织通过机会抽样招募。Q1。使用photovoice，参与者将被要求发送最多10张他们在利兹喜欢参观的户外空间的照片。然后，他们将被邀请参加一个半结构化的面试，讨论他们的照片。在一个简短的图片问答环节中，同样的参与者也会看到绿色空间的图片，并被问及他们对这些空间的偏好和体验。将使用杰弗逊转录和主题分析，主题将为项目的其余部分提供研究方向。Q2。以上访谈将阐明ASARs最看重的户外特征。利用全国人口普查数据，将确定具有高BAME人口和低平均工资的中间层超级产出地区，因为asar倾向于交叉这些群体。地理信息系统将帮助测量从这些街道到asar价值特征的距离。这些将通过分层随机抽样进行抽样，以便选择与asar值特征距离不同的街道。将在这些街道上使用标准化的心理健康问卷（例如沃里克-爱丁堡心理健康量表[19]）进行调查，以便与现有研究进行比较。心理健康评分和到asar价值特征的距离将被关联以调查任何影响。其他影响因素和混杂因素，如收入，将在分析中考虑。对参与者心理健康的复杂影响可以用有向无环图来表示。第三季。在访谈中确定的绿色空间障碍将为干预措施的设计提供信息，以增加ASAR从绿色空间中获益。这将与参与者共同设计，以确保设计是相关的，根据经验，并解决参与者认为最关键的障碍。

This project aims to investigate further the correlation between greenspace and wellbeing amongst ASARsResearch Questions Q1 Which aspects of greenspace are most valued by ASARs, and what perceptions, experiences, practices, and barriers inform these values? Q2 Are the features and facilities of greenspace most-valued by ASARs reflected in their local areas? Q3 How can an intervention be used to enhance the mental wellbeing benefits of urban greenspaces for ASARs? Methods Participants for research of Q1 and Q3 will be recruited via opportunity sampling through organisations such as Leeds Asylum Seekers Support Network. Q1. Using photovoice, participants will be requested to send in up to 10 photos each of outdoor spaces they like to visit in Leeds. They will then be invited to a semi-structured interview to discuss their photos. In a short photo elicitation session, the same participants will also be shown images of greenspaces and asked questions to gauge their preferences and experiences of them. Jefferson transcription and thematic analysis will be used and themes will inform the research directions for the rest of the project. Q2. The above interviews will illuminate the outdoor features most valued by ASARs. Using national census data, middle layer super output areas with high BAME populations and low average salaries will be identified, as ASARs tend to intersect these groups. GIS will help measure distances from these streets to ASAR-valued features. These will be sampled via stratified random sampling so that streets with different distances to ASAR-valued features are selected. Surveys will be conducted on these streets using a standardised mental health questionnaire (e.g. Warwick-Edinburgh Mental Wellbeing Scale[19]) to allow comparison with existing studies. Mental health score and distance to ASAR-valued features will be correlated to investigate any effect. Other influencing and confounding factors, like income, will be accounted for in analysis. Complex influences on participant mental health may be represented using a directed acyclic graph. Q3. Barriers to greenspace identified in the interviews will inform the design of an intervention to increase ASAR's benefit from greenspace. This will be co-designed with participants to ensure the design is relevant, informed by experience, and addresses the barriers seen as most critical by participants.