Using child maintenance as a tool to enhance the circumstances, outcomes and wellbeing of lone mothers and children

本研究旨在探讨支付/不支付子女抚养费对一系列儿童和单亲家庭的社会经济和其他结果的影响。为此，它将使用来自儿童和家长的纵向定量数据以及来自儿童的定性数据。本课题的研究问题是：1.；支付/不支付子女抚养费如何影响单亲家庭的社会经济状况？（例如，关于贫穷、物质匮乏和财政脆弱性）支付/不支付子女抚养费对儿童有何影响？（例如，幸福感，优势和困难，参与同龄人团体，管理联系/金钱问题，以及与居民和非居民父母的关系）支付/不支付子女抚养费对单亲父母有何影响？（例如，幸福、心理健康和分居父母之间的关系质量/冲突？）方法研究的定量方面使用千年队列研究（MCS）数据来探索支付/不支付儿童抚养费对一系列结果的影响，例如：贫困；物质匮乏;非居民父母与子女之间的关系/冲突，以及离异父母之间的关系/冲突；儿童和孕产妇福祉；儿童的长处和困难，以及其他数据允许。利用统计分析的结果，将确定用于定性研究的主题。例如，这可以包括年轻人采取行动，减轻不支付子女抚养费的影响，并缓解父母之间的紧张关系。MCS追踪的是2000年出生的人。它在英国的初始样本量为18818人。第六波数据于2017年投入使用，收集了有关儿童和父母生活的详细信息。在这里，年轻人是第一次的主要受访者，还有一份针对父母的问卷。MCS数据足够丰富，本项目可以深入探讨抚养儿童的频率/数量对单亲母亲和儿童的情况、结果和福祉的影响。定量研究方法包括：(1)二元logistic回归分析，以探索与支付/不支付相关的特征；(2)倾向得分匹配，其中两组受访者在关键特征上匹配，一组接受子女抚养，另一组不接受子女抚养，以探索儿童和单亲家庭的社会经济和其他结果的差异；(3)建立结构方程模型，确定抚养子女对这些结果的直接和间接影响及其途径。通过MCS的专用问卷和定性方法，儿童是研究的一部分。这种混合方法方法将利用定量分析的结果确定用于定性研究的主题，并在可能的情况下，从定量样本中抽取定性样本。这样，定量和定性的因素将充分结合和互补，而不是单独研究同一主题。作为一名学生，我将从学习使用这个数据集中受益匪浅，因为它丰富、纵向和全面，可以帮助回答许多与儿童和家庭有关的政策和研究问题。虽然取决于定量分析的初步结果，但我预计将对大约30名年轻人进行定性访谈，以提供足够的多样性来回答研究问题。需要适当考虑敏感的采访和道德规范。

This research aims to explore the impacts of the payment/non-payment of child maintenance on a range of child and lone-parent socioeconomic and other outcomes. To do so it will use longitudinal quantitative data from children and parents and qualitative data from children.The research questions for this project are:1.How does the payment/non-payment of child maintenance affect the socioeconomic situation of lone-parent families? (e.g. in relation to poverty, material deprivation and financial vulnerability)2.How does the payment/non-payment of child maintenance affect children? (e.g. wellbeing, strengths & difficulties, participation in their peer group, managing issues of contact/money, and relationships with resident and non-resident parents)3.How does the payment/non-payment of child maintenance affect lone parents? (e.g. wellbeing, mental health, and quality of the relationship/conflict between separated parents?)MethodologyThe quantitative aspect of the research uses the Millennium Cohort Study (MCS) data to explore the impacts of the payment/non-payment of child maintenance on a range of outcomes such as: poverty; material deprivation; relationships/conflict between non-resident parents and children, and between separated parents; child and maternal well-being; child strengths & difficulties, and others as the data permit. Using the results of the statistical analyses, themes would be identified for use in the qualitative research. This could include, for example, young people's actions to mitigate the effects of non-payment of child maintenance and to diffuse tensions between their parents.The MCS follows individuals born in 2000. It has an initial UK sample size of 18,818. Wave 6 of the data became available in 2017 and collects detailed information on children's and parents' lives. Here, the young person is the main respondent for the first time and there is also a questionnaire for parents. The MCS data are sufficiently rich for this project to thoroughly explore the impacts of the frequency/amount of child maintenance on the circumstances, outcomes and well-being of lone-mothers and children.The quantitative research methods would include: (1) binary logistic regression analyses to explore the characteristics associated with payment/non-payment, (2) propensity score matching, where two groups of respondents are matched on key characteristics, one receives child maintenance/the other does not, to explore differences in child and lone-parent socioeconomic and other outcomes; and (3) structural equation modelling to identify direct and indirect effects and pathways of child maintenance on these outcomes. Children are part of the research via the dedicated questionnaire of the MCS and via qualitative methods. This mixed-methods approach will use the results of the quantitative analysis to identify themes for use in the qualitative research and, where possible, the qualitative sample would be drawn from the quantitative sample. In this way, the quantitative and qualitative elements will be fully integrated and complementary rather than separate strands investigating the same topic. As a student i would benefit greatly from learning to use this dataset as it is rich, longitudinal and comprehensive and can help answer many policy and research questions pertaining to children and families. While dependent on the initial results of the quantitative analysis, i anticipate qualitative interviews with approximately 30 young people will be undertaken, providing sufficient diversity to answer the research questions. Due account of sensitive interviewing and ethics will be required.