The Development of a Holistic and Quantitative Tool for the Assessment and Improvement of Survey Quality.

There are a variety of guidelines and methods available to measure and assess survey quality. Most of these are based on qualitative descriptions. In practice, they are not easy to implement and it is very difficult to make comparisons between surveys. Hence there is a theoretical and pragmatic demand to develop a mainly quantitative based survey assessment tool. This research aimed to meet this need and make contributions to the evaluation and improvement of survey quality. Acknowledging the critical importance of measurement issues in survey research, this thesis starts with a comprehensive introduction to measurement theory and identifies the types of measurement errors associated with measurement procedures through three experiments. Then it moves on to describe concepts, guidelines and methods available for measuring and assessing survey quality. Combining these with measurement principles leads to the development of a quantitative based statistical holistic tool to measure and assess survey quality. The criteria, weights and subweights for the assessment tool are determined using Multi-Criteria Decision-Making (MCDM) and a survey questionnaire based on the Delphi method. Finally the model is applied to a database of surveys which was constructed to develop methods of classification, assessment and improvement of survey quality. The model developed in this thesis enables survey researchers and/or commissioners to make a holistic assessment of the value of the particular survey(s). This model is an Excel based audit which takes a holistic approach, following all stages of the survey from inception, to design, construction, execution, analysis and dissemination. At each stage a set of criteria are applied to assess quality. Scores attained against these assessments are weighted by the importance of the criteria and summed to give an overall assessment of the stage. The total score for a survey can be obtained by a combination of the scores for every stage weighted again by the importance of each stage. The advantage of this is to construct a means of survey assessment which can be used in a diagnostic manner to assess and improve survey quality.

Imaging of activated complement using ultrasmall superparamagnetic iron oxide particles (USPIO) - conjugated vectors: an in vivo in utero non-invasive method to predict placental insufficiency and abnormal fetal brain development.

In the current study, we have developed a magnetic resonance imaging-based method for non-invasive detection of complement activation in placenta and foetal brain in vivo in utero. Using this method, we found that anti-complement C3-targeted ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles bind within the inflamed placenta and foetal brain cortical tissue, causing a shortening of the T2* relaxation time. We used two mouse models of pregnancy complications: a mouse model of obstetrics antiphospholipid syndrome (APS) and a mouse model of preterm birth (PTB). We found that detection of C3 deposition in the placenta in the APS model was associated with placental insufficiency characterised by increased oxidative stress, decreased vascular endothelial growth factor and placental growth factor levels and intrauterine growth restriction. We also found that foetal brain C3 deposition was associated with cortical axonal cytoarchitecture disruption and increased neurodegeneration in the mouse model of APS and in the PTB model. In the APS model, foetuses that showed increased C3 in their brains additionally expressed anxiety-related behaviour after birth. Importantly, USPIO did not affect pregnancy outcomes and liver function in the mother and the offspring, suggesting that this method may be useful for detecting complement activation in vivo in utero and predicting placental insufficiency and abnormal foetal neurodevelopment that leads to neuropsychiatric disorders.