The strong emphasis placed on improving equality and well-being for all in the Sustainable Development Goals underscores the importance of tackling persistent within-country disparities in maternal mortality and poor health outcomes. Addressing maternal healthcare access barriers is, thus, crucial, particularly in low-resource settings. Numerous studies investigating determinants of maternal healthcare service use in Ethiopia exist but are limited by their focus on individual and household factors, and by methodological weaknesses. A nuanced understanding of the role of socioeconomic and geographic context in influencing access to care is needed to respond effectively. Maternity waiting homes (MWHs) are a potential strategy to address geographical barriers that delay women’s access to obstetric care. However, in addition to concerns about service quality, there is limited evidence on their effectiveness and on what models meet women’s needs. My research goals were, therefore, to contribute to the understanding of what contextual factors influence maternal healthcare service use in general; and to determine whether or not upgraded MWHs operating in an enabling environment could improve delivery care use in rural Ethiopia. My primary data sources were household surveys conducted as part of a cluster-randomized controlled trial evaluating MWHs and local leader training in Jimma Zone, Ethiopia. Random effects multivariable logistic regression analysis of survey data brought to light the social and financial resources that facilitate MWH use, highlighting the need for complementary interventions to make access more equitable. Spatial analyses identified subnational variation in service use at a finer scale than routinely reported and unmasked local variation in the relevance and magnitude of associations between individual-, interpersonal-, and health system factors and maternal healthcare use. These findings have implications for relying upon homogenous national responses to improve equality in access to care and health outcomes. Finally, analysis of trial data found a non-significant effect of interventions on delivery care use likely due to implementation issues and extraneous factors. The need to generate strong evidence of effectiveness of MWHs in improving maternal healthcare service use using sustainable and equitable MWH models using methods appropriate for complex intervention evaluation remains.

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Background: The cluster randomized trial design randomly assigns groups of people to different treatment arms. This dissertation aimed to (1) develop machine learning algorithms to identify cluster trials in bibliographic databases, (2) assess reporting of methodological and ethical elements in hemodialysis-related cluster trials, and (3) assess how well two covariate-constrained randomization methods balanced baseline characteristics compared with simple randomization. Methods: In study 1, we developed three machine learning algorithms that classify whether a bibliographic citation is a CRT report or not. We only used the information available in an article citation, including the title, abstract, keywords, and subject headings. In study 2, we conducted a systematic review of CRTs in the hemodialysis setting to review the reporting of key methodological and ethical issues. We reviewed CRTs published in English between 2000 and 2019 and indexed in MEDLINE or EMBASE. In study 3, we assessed how well two covariate-constrained randomization methods balanced baseline characteristics compared with simple randomization. Results: In study 1, we successfully developed high-performance algorithms that identified whether a citation was a CRT. Our algorithms had greater than 97% sensitivity and 77% specificity in identifying CRTs. For study 2, we found suboptimal conduct and reporting of methodological issues of CRTs in the hemodialysis setting and incomplete reporting of key ethical issues. For study 3, where we randomized 72 clusters, constraining the randomization using historical information achieved a better balance on baseline characteristics than simple randomization; however, the magnitude of benefit was modest. Conclusions: This dissertation's results will help researchers quickly identify cluster trials in bibliographic databases (study 1) and inform the design and analyses of future Canadian trials conducted within the hemodialysis setting (study 2 & 3). / Thesis / Doctor of Philosophy (PhD) / The cluster trial design randomly assigns groups of people to different treatment arms rather than individuals. Cluster trials are commonly used in research areas such as education, public health, and health service research. Examples of clusters can include villages/communities, worksites, schools, hospitals, hospital wards, and physicians. This dissertation aimed to (1) develop machine learning algorithms to identify cluster trials in bibliographic databases, (2) assess reporting of methodological and ethical elements in hemodialysis-related cluster trials, and (3) identified best practices for randomly assigning hemodialysis centers in cluster trials. We conducted three studies to address these aims. The results of this dissertation will help researchers quickly identify cluster trials in bibliographic databases (study 1) and inform the design and analyses of future Canadian trials conducted within the hemodialysis setting (study 2 & 3).

This study compared 3 approaches for handling a fourth level of nesting structure when analyzing data from a cluster-randomized trial (CRT). CRTs can include 3 levels of nesting: repeated measures, individual, and cluster levels. However, above the cluster level, there may sometimes be an additional potentially important fourth level of nesting (e.g., schools, districts, etc., depending on the design) that is typically ignored in CRT data analysis. The current study examined the impact of ignoring this fourth level, accounting for it using a model-based approach, and accounting it using a design-based approach on parameter and standard error (SE) estimates. Several fixed effect and random effect variance parameters and SEs were biased across all 3 models. In the 4-level model, most SE biases decreased as the number of level 3 clusters increased and as the number of level 4 clusters decreased. Also, random effect variance biases decreased as the number of level 3 clusters increased. In the 3-level and complex models, SEs became more biased as the weight level 4 carried increased (i.e., larger intraclass correlation, more clusters at that level). The current results suggest that if a meaningful fourth level of nesting exists, future researchers should account for it using design-based approach; the model-based approach is not recommended. If the fourth level is not practically important, researchers may ignore it altogether.

Schools are increasingly expected to prevent and decrease violence, substance use, and other problem behaviors linked to academics and prepare students to be contributing members of society. One approach with proven success in promoting positive outcomes related to a broad range of student behaviors and personal characteristics is social-emotional learning, also known as positive youth development or social-emotional and character development (SECD) programs. Currently, little is known about the relationship between SECD and these outcomes in low-income, urban, minority populations. The present studies (a) examine key methodological design issues in conducting a cluster-randomized trial with such populations, and (b) assess whether an intervention designed to promote SECD was effective in improving the SECD developmental status of children from this population. Data for this study come from the Chicago cluster-randomized controlled trial (CRCT) of Positive Action (PA). The trial was longitudinal at the school level with a place-focused intent-to-treat design at the student level. This CRCT collected data on children in grades 3 through 8, for a total of 6 years and 8 data collection points. Manuscript #1 focuses on the design, sample, planned analyses, and a latent class analysis (LCA) of mobility patterns. Specifically, the setting and recruitment of schools is described, as well as the process by which schools were matched into pairs and randomized into PA or control, including the list of criteria for school eligibility and variables used for matching. Additionally, this paper thoroughly describes the primary analyses to test for program effects using three-level growth curve models (time nested within students nested within schools), as well as several sensitivity analyses that will also be conducted when evaluating this program. Further, this manuscript discusses secondary tests of meditation and moderation, which will assist in the understanding of how the program works (mediation) and for whom (moderation). Finally, this paper also provides several descriptive statistics and characteristics of the students and teachers in this sample. In terms of baseline equivalency, PA and control schools did not significantly differ on matching variables before or during the trial. Minimal differences were found on baseline reports from students, teachers, and parents; half of these differences favored PA students and half favored control students. Manuscript #2 focuses on the intervention effects on the student-, teacher-, and parent-reported social-emotional outcomes assessed during the Chicago CRCT, following the analytic procedures outlined in the first paper and focusing on the effectiveness of PA on social-emotional outcomes. Results indicate that PA had a significant effect on student self-reports of prosocial interactions, honesty, self-development, self-control, respect for parents and teachers, empathy, altruism, positive actions/feelings, negative moral center, and aggressive problem solving. Additionally, it was found that PA had marginal effects on teacher-reported responsibility. Minimal differences by gender were found; no differences by mobility status were found. Together, these two papers involved a sample of students in a high-risk setting; generating improvements can be particularly difficult in urban areas. The empirical evidence of effectiveness of a SECD program in a high-risk population, as demonstrated in the present study, should serve as a call to action for policymakers and school officials who are increasingly challenged to positively impact not only academic achievement, but also behavior and character development. / Graduation date: 2012