Screening and alcohol brief interventions in antenatal care: a realistic evaluation

Background: Prenatal alcohol consumption is one of the leading preventable causes of birth defects, including fetal alcohol syndrome and learning disabilities. Although there is strong evidence of the benefits of screening and alcohol brief interventions (ABIs) in reducing hazardous and harmful drinking among the primary care population, evidence of its effectiveness with the antenatal care population is limited. Nevertheless, the Scottish Government is incorporating an alcohol screening and ABI programme as part of the routine antenatal care provided to women in a bid to protect the health and safety of the unborn child and improve subsequent health and developmental outcomes. This research therefore seeks to increase understanding of the factors that are likely to influence the effectiveness of this recently implemented programme. It also aims to explore the extent to which contemporary issues such as change in guidelines regarding alcohol consumption during pregnancy influences perceptions and attitudes, and the possible implications of these on the screening and ABI delivery. Methods: The study described in this thesis employed a realistic evaluation methodology. Realistic evaluation is a theory-driven approach to investigating social programmes. It is concerned with hypothesising, testing and refining programme theories by exploring the interaction of contexts, mechanisms and outcomes. To identify the relevant screening and ABI programme theories, two separate systematic reviews, a critical review and four face-to-face interviews were undertaken with health policy implementers. The findings were used to construct context, mechanism and outcomes propositions. The propositions were then tested by conducting individual interviews with seventeen pregnant women and fifteen midwives, a further six midwifery team leaders were involved in a focus group discussion. A thematic approach using a hybrid of inductive and deductive coding and theme development informed the qualitative analysis. Results: In the context of uncertainties regarding the threshold of drinking that causes fetal harm, pregnant women reported that screening assessment helped them to reflect on their drinking behaviour and facilitate behaviour change. For women who drank at hazardous and harmful levels before attending the booking appointment, screening and ABI may be helpful in terms of eliciting behaviour change. However, they may not be very beneficial in terms of reducing harm to the fetus as it has been found that drinking during the first trimester poses the most risk to the fetus. Training and resources provided to midwives as part of the screening and ABI programme were found to be facilitating mechanisms that midwives indicated improved their skills and confidence. However, most of the midwives had not subsequently employed the motivational interviewing skills required for the ABI delivery, as many of the pregnant women reported that they reduced or abstained from alcohol consumption once pregnancy was confirmed. The outcome noted was that midwives confidence decreased leading to missed opportunities to appropriately deliver the ABI to eligible women. The small numbers of women being identified for ABI meant midwives rarely delivered the ABI. This negatively influenced midwives attitudes as they then accorded ABI low priority in their workload. Other disenabling mechanisms noted to be hampering the implementation of the screening and ABI initiative included midwives contending with competing priorities at the booking appointments, and the lack of adequate rapport between midwives and pregnant women at the booking appointment to discuss alcohol issues appropriately, leading to women providing socially desirable responses to screening questions. Conclusions: The findings of this study has generated greater explanations of the working of the screening and ABI programme in antenatal care setting and has provided transferable lessons that can be used by others intending to implement similar programmes in other settings

Reconstruction of three-dimensional facial geometric features related to fetal alcohol syndrome using adult surrogates

Fetal alcohol syndrome (FAS) is a condition caused by prenatal alcohol exposure. The diagnosis of FAS is based on the presence of central nervous system impairments, evidence of growth abnormalities and abnormal facial features. Direct anthropometry has traditionally been used to obtain facial data to assess the FAS facial features. Research efforts have focused on indirect anthropometry such as 3D surface imaging systems to collect facial data for facial analysis. However, 3D surface imaging systems are costly. As an alternative, approaches for 3D reconstruction from a single 2D image of the face using a 3D morphable model (3DMM) were explored in this research study. The research project was accomplished in several steps. 3D facial data were obtained from the publicly available BU-3DFE database, developed by the State University of New York. The 3D face scans in the training set were landmarked by different observers. The reliability and precision in selecting 3D landmarks were evaluated. The intraclass correlation coefficients for intra- and inter-observer reliability were greater than 0.95. The average intra-observer error was 0.26 mm and the average inter-observer error was 0.89 mm. A rigid registration was performed on the 3D face scans in the training set. Following rigid registration, a dense point-to-point correspondence across a set of aligned face scans was computed using the Gaussian process model fitting approach. A 3DMM of the face was constructed from the fully registered 3D face scans. The constructed 3DMM of the face was evaluated based on generalization, specificity, and compactness. The quantitative evaluations show that the constructed 3DMM achieves reliable results. 3D face reconstructions from single 2D images were estimated based on the 3DMM. The MetropolisHastings algorithm was used to fit the 3DMM features to 2D image features to generate the 3D face reconstruction. Finally, the geometric accuracy of the reconstructed 3D faces was evaluated based on ground-truth 3D face scans. The average root mean square error for the surface-to-surface comparisons between the reconstructed faces and the ground-truth face scans was 2.99 mm. In conclusion, a framework to estimate 3D face reconstructions from single 2D facial images was developed and the reconstruction errors were evaluated. The geometric accuracy of the 3D face reconstructions was comparable to that found in the literature. However, future work should consider minimizing reconstruction errors to acceptable clinical standards in order for the framework to be useful for 3D-from-2D reconstruction in general, and also for developing FAS applications. Finally, future work should consider estimating a 3D face using multi-view 2D images to increase the information available for 3D-from-2D reconstruction

Statistical and Machine Learning Methods for Pattern Identification in Environmental Mixtures

Background: Statistical and machine learning techniques are now being incorporated into high-dimensional mixture research to overcome issues with traditional methods. Though some methods perform well on specific tasks, no method consistently outperforms all others in complex mixture analyses, largely because different methods were developed to answer different research questions. The research presented here concentrates on answering a single mixtures question: Are there exposure patterns within a mixture corresponding with sources or behaviors that give rise to exposure? Objective: This dissertation details work to design, adapt, and apply pattern recognition methods to environmental mixtures and introduces two methods adapted to specific challenges of environmental health data, (1) Principal Component Pursuit (PCP) and (2) Bayesian non-parametric non-negative matrix factorization (BN²MF). We build on this work to characterize the relationship between identified patterns of in utero endocrine disrupting chemical (EDC) exposure and child neurodevelopment. Methods: PCP---a dimensionality reduction technique in computer vision---decomposes the exposure mixture into a low-rank matrix of consistent patterns and a sparse matrix of unique or extreme exposure events. We incorporated two existing PCP extensions that suit environmental data, (1) a non-convex rank penalty, and (2) a formulation that removes the need for parameter tuning. We further adapted PCP to accommodate environmental mixtures by including (1) a non-negativity constraint, (2) a modified algorithm to allow for missing values, and (3) a separate penalty for measurements below the limit of detection (PCP-LOD). BN²MF decomposes the exposure mixture into three parts, (1) a matrix of chemical loadings on identified patterns, (2) a matrix of individual scores on identified patterns, and (3) and diagonal matrix of pattern weights. It places non-negative continuous priors on pattern loadings, weights, and individual scores and uses a non-parametric sparse prior on the pattern weights to estimate the optimal number. We extended BN²MF to explicitly account for uncertainty in identified patterns by estimating the full distribution of scores and loadings. To test both methods, we simulated data to represent environmental mixtures with various structures, altering the level of complexity in the patterns, the noise level, the number of patterns, the size of the mixture, and the sample size. We evaluated PCP-LOD's performance against principal component analysis (PCA), and we evaluated BN²MF's performance against PCA, factor analysis, and frequentist nonnegative matrix factorization (NMF). For all methods, we compared their solutions with true simulated values to measure performance. We further assessed BN²MF's coverage of true simulated scores. We applied PCP-LOD to an exposure mixture of 21 persistent organic pollutants (POPs) measured in 1,000 U.S. adults from the 2001--2002 National Health and Nutrition Examination Survey (NHANES). We applied BN²MF to an exposure mixture of 17 EDCs measured in 343 pregnant women in the Columbia Center for Children’s Environmental Health's Mothers and Newborns Cohort. Finally, we designed a two-stage Bayesian hierarchical model to estimate health effects of environmental exposure patterns while incorporating the uncertainty of pattern identification. In the first stage, we identified EDC exposure patterns using BN²MF. In the second stage, we included individual pattern scores and their distributions as exposures of interest in a hierarchical regression model, with child IQ as the outcome, adjusting for potential confounders. We present sex-specific results. Results: PCP-LOD recovered the true number of patterns through cross-validation for all simulations; based on an a priori specified criterion, PCA recovered the true number of patterns in 32% of simulations. PCP-LOD achieved lower relative predictive error than PCA for all simulated datasets with up to 50% of the data < LOD. When 75% of values were < LOD, PCP-LOD outperformed PCA only when noise was low. In the POP mixture, PCP-LOD identified a rank three underlying structure. One pattern represented comprehensive exposure to all POPs. The other two patterns grouped chemicals based on known properties such as structure and toxicity. PCP-LOD also separated 6% of values as extreme events. Most participants had no extreme exposures (44%) or only extremely low exposures (18%). BN²MF estimated the true number of patterns for 99% of simulated datasets. BN²MF's variational confidence intervals achieved 95% coverage across all levels of structural complexity with up to 40% added noise. BN²MF performed comparably with frequentist methods in terms of overall prediction and estimation of underlying loadings and scores. We identified two patterns of EDC exposure in pregnant women, corresponding with diet and personal care product use as potentially separate sources or behaviors leading to exposure. The diet pattern expressed exposure to phthalates and BPA. One standard deviation increase in this pattern was associated with a decrease of 3.5 IQ points (95% credible interval: -6.7, -0.3), on average, in female children but not in males. The personal care product pattern represented exposure to phenols, including parabens, and diethyl phthalate. We found no associations between this pattern and child cognition. Conclusion: PCP-LOD and BN^2MF address limitations of existing pattern recognition methods employed in this field such as user-specified pattern number, lack of interpretability of patterns in terms of human understanding, influence of outlying values, and lack of uncertainty quantification. Both methods identified patterns that grouped chemicals based on known sources (e.g., diet), behaviors (e.g., personal care product use), or properties (e.g., structure and toxicity). Phthalates and BPA found in food packaging and can linings formed a BN²MF-identified pattern of EDC exposure negatively associated with female child intelligence in the Mothers and Newborns cohort. Results may be used to inform interventions designed to target modifiable behavior or regulations to act on dietary exposure sources

Examining perinatal healthcare process among refugee women resettled in the US

Maternal mortality is a global public health concern. At present, the US reports the highest number of maternal deaths among all Global North countries. Research shows disparities in maternal care access and outcomes by race, ethnicity, and country of origin. Refugee women are one of the most vulnerable groups who are disproportionately disadvantaged due to their social positioning. Their disposition in the global world is quickly emerging to be a major global public health crisis. They are also 20 times more likely to die from pregnancy related factors compared to their native counterparts. However, maternal research on refugee women is limited. Study aimed to examine Bhutanese refugee women’s maternal care process and experience when receiving perinatal care in the US and explored provider’s perspectives on providing care to various groups of refugee women. Care process was examined using a constructivist grounded theory model through an inductive constant comparative analysis using semi-structured interviews with Bhutanese refugee women (n=15), field observation notes from a larger CBPR study (n=28), and semi-structured interviews with providers (n=11) such as healthcare practitioners (n=6), medical interpreters (n=4), and resettlement official (n=1). Two major thematic findings that impacted refugee women’s care interaction process were care continuity and health history. These findings were grounded in the experiences of Bhutanese refugee women and various providers who shared their experiences giving care to refugee women. These thematic findings highlight the need for a cultural understanding of refugee women’s pre-resettlement experience that is unique to each refugee subgroup and addressing structural challenges to adequate care giving through a culturally responsive approach

Foetal Alcohol Spectrum Disorders (FASD): the parent perspective on education and implications for educational psychologists (EPs)

This study gathered the voice of adoptive parents and foster carers who parent a child with a confirmed diagnosis of foetal alcohol spectrum disorders (FASD). Their views were explored in relation to their experiences of the family-school interaction, their perceptions of their child’s experience of school, as well as their experiences of educational psychologist (EP) involvement with their child. The study was underpinned by a solution-oriented approach (O’Hanlon & Weinder-Davis, 2003), which enabled a range of experiences including difficult, positive and any nuances which are positioned in-between, to be captured. A qualitative study using semi-structured interviews was conducted with eight adoptive parents and one pair of foster carers. Braun and Clarke’s (2006; 2021) six phases of reflexive thematic analysis (TA) was used inductively through which four themes were identified: ‘Understanding the Individual’, ‘Sense of Belonging’, ‘Collaboration and Communication’ and ‘Knowledge and Awareness of FASD’. The findings highlighted that parents of children with FASD consider school to be overwhelmingly challenging for their children. This related in part to within-child factors linked to FASD, however, to a greater extent these difficulties were systemic. This study adds to the current evidence-base which indicates that parents play a crucial role in the educational lives of children with FASD, as well as the findings that barriers to the family-school interaction are plentiful. This research adds support to the importance of effective family-school communication which authentically accounts for parents’ views and their expertise. The need for improved knowledge and understanding of FASD within the school system and amongst EPs is also emphasised. Moving forwards, recommendations for how EPs might undertake a more supportive role in this context are provided

Epidemiology of prenatal alcohol use and fetal alcohol spectrum disorder

Prenatal alcohol exposure (PAE) can lead to fetal alcohol spectrum disorder (FASD). FASD refers to a range of lifelong conditions caused by PAE, characterised by a distinctive facial phenotype, growth deficiencies and/or neurobehavioural impairments. This thesis presents four studies that I conducted to address knowledge gaps relevant to the epidemiology of PAE and FASD. First, objective measures of PAE are essential for identifying children at risk of adverse outcomes. Biomarkers have been advocated for use in universal PAE screening programs but their validity had not been comprehensively evaluated. I conducted a systematic review and found that biomarker test performance varied widely across studies. The quality of published studies was low, resulting in insufficient evidence to support the use of objective measures of PAE in practice. Second, the prevalence of FASD in the UK was unknown. Active case ascertainment studies have not been possible due to funding and ethical issues. To overcome these issues, I developed an algorithm to estimate FASD prevalence using existing data from a population-based birth cohort in England (ALSPAC). Up to 17% of children met criteria for FASD, indicating that it is a significant public health concern. Third, although PAE is the sole necessary cause of FASD, it is not always sufficient. Understanding risk factors for FASD is important for informing prevention strategies. However, existing studies have mostly been limited to discussion of association, rather than causation. I produced a causal diagram to depict hypothesised causal pathways to FASD. I used this diagram to guide analyses in a FASD risk factor study, reported below. Finally, I investigated FASD risk factors using multivariable logistic regression within the ALSPAC cohort. Prenatal stress, smoking and mental health problems increased the odds of FASD. Social support and folic acid supplementation were protective. These results indicate novel potential targets for FASD intervention

The American Academy of Health Behavior 2019 Annual Scientific Meeting: Theory and Applications of Multiple Health Behavior Change

The American Academy of Health Behavior (AAHB) hosted it\u27s 19th Annual Scientific Meeting at the Westin Poinsett in Greenville, SC March 10-13, 2019. The meeting\u27s theme was Theory and Applications of Multiple Health Behavior Change. This publication describes the meeting theme and includes the refereed abstracts presented at the 2019 Annual Scientific Meeting