The Impact of Universal Basic Income on Health and Wellbeing: A Qualitative Realist Review

METHODOLOGY
The review focuses on critical analysis of qualitative data on the CMOs of UBI/UCT-trials related to health inequalities and wellbeing in developed and developing countries. Following research sub-questions will be addressed:

1) How do context and underlying mechanisms influence social determinants and health outcomes of the population under investigation?
2) Is there a difference in perceived health outcomes between developed (HICs) and developing countries (LMICs) implementing a UBI or UCT? And if so, why?
3) Is there any difference in perceived health and wellbeing within countries (and for whom is it beneficial)?
Data Synthesis Strategy and Coding

Oliver (2012) suggests using a grounded theory approach (constructivism) as a framework for the realist review is lacking. Data analysis was performed on three levels within the 13 primary selected papers. First, the narrative data recorded by the researchers with stakeholders were coded through an inductive process which led to open coding. This was followed by axial and selective coding in creating themes (Castleberry and Nolen 2018). It is often argued one dataset should be represented by one theme; Gibbs (2018) counters this argument and proposes the use of several themes within a dataset whenever it is needed in clarifying and representing the data. In appreciating the data correctly, a re-code of the same data was performed one week after the initial coding (Miles, Huberman and Saldana 2013). The authors state this methodology to enhance the saturation of the data improving internal consistency. Researchers’ relevant discourse in their findings and discussions were coded line-by-line and analysed through the CMO-approach in retrieving the deeper social and health determinants involved (Jagosh 2019). The data selection, relevant CMOs and their relationships towards the outcomes were put in flowcharts facilitating the uncovering of patterns (Jagosh et al. 2014; Jagosh 2019). The interactions and relationships between the uncovered data are represented by arrows leading to a comprehensive framework creating insight in the deep-layers behind the intervention through ontological reasoning for the CMO (Dalkin et al 2015; Jagosh 2019). Ontological assumptions seek to understand reality (‘what is’) in which we objectified our own perception in recognising what and how things work (Rawnsley 1998; Scotland 2012).

FINDINGS

Overall, we can summarise the findings for beneficiaries of a UBI/UCT grant in three ontological themes arising prominently in relation to non-recipients or welfare dependent populations: less stigma and shame, financial stability, societal trust and improved health and wellbeing. Adding to this assertion, it was noticed the grant also had a positive effect on the community at large. More gender equity could not be retrieved as religion and tradition impose a patriarchal system.

方法论
本项研究聚焦于对发达国家和发展中国家与健康不平等及福祉相关的UBI/UCT试验的CMO（关键管理对象）定性数据的批判性分析。以下研究子问题将得到探讨：
1) 研究背景和潜在机制如何影响调查人群的社会决定因素和健康结果？
2) 在实施UBI或UCT的发达国家（高收入国家）和发展中国家（低收入国家）之间，感知的健康结果是否存在差异？如果是的话，原因是什么？
3) 在国内（对谁有益）感知的健康和福祉是否存在差异？
数据综合策略与编码
Oliver（2012）建议使用扎根理论方法（建构主义）作为现实主义评论的框架。数据分析在13篇选定的主要论文的三个层面上进行。首先，研究者与利益相关者记录的叙事数据通过归纳过程进行编码，进而形成开放式编码。随后，通过轴心编码和选择性编码创建主题（Castleberry和Nolen 2018）。通常认为，一个数据集应代表一个主题；Gibbs（2018）反驳了这一论点，并提议在需要澄清和表示数据时，在数据集中使用多个主题。为了正确欣赏数据，初始编码一周后对同一数据进行重新编码（Miles, Huberman和Saldana 2013）。作者表示，这种方法旨在提高数据的饱和度，从而增强内部一致性。研究者在其发现和讨论中的相关话语通过逐行编码，并通过CMO方法分析，以检索更深层次的社会和健康决定因素（Jagosh 2019）。数据选择、相关CMO及其与结果之间的关系通过流程图呈现，以促进模式的揭示（Jagosh et al. 2014；Jagosh 2019）。揭示的数据之间的相互作用和关系通过箭头表示，形成一个全面的框架，通过CMO的形而上学推理，对干预措施背后的深层层次产生洞察（Dalkin et al 2015；Jagosh 2019）。形而上学假设旨在理解现实（‘是什么’），其中我们对象化了我们的感知，以识别事物及其运作的方式（Rawnsley 1998；Scotland 2012）。
发现
总体而言，我们可以总结UBI/UCT补助金受益者的发现，三个形而上学主题在非受助者或福利依赖人口的相关性中突出显现：减少耻辱和羞愧感、财务稳定、社会信任以及改善健康和福祉。此外，还观察到该补助金对整个社区也有积极影响。由于宗教和传统强加父权制体系，未能检索到更多性别平等的信息。