Schizophrenia (SCZ) is a debilitating disorder with a prevalence of approximately 1 % worldwide. SCZ is known to have a high degree of genetic and clinical heterogeneity and is a major health problem worldwide. The integrin-β 3 subunit gene (ITGB3) gene at 17q21.32 has been implicated in psychiatric disorders. We therefore hypothesized that ITGB3 gene polymorphisms might also play a role in SCZ and age at onset (AAO) of SCZ. We investigated the genetic associations of 23 single-nucleotide polymorphisms (SNPs) of the ITGB3 gene with AAO in SCZ in two Caucasian samples (2,166 cases and 2,525 controls) using linear regression analysis and meta-analysis. We observed four ITGB3-SNPs associated with AAO in SCZ in a non-Genetic Association Information Network (GAIN) sample (p < 10-3). Three of these four SNPs were replicated in the GAIN sample. The SNP rs16941771 was most significantly associated with AAO (p = 7.47 × 10-5). Meta-analysis showed that 6 of 23 SNPs were associated with AAO. The haplotype analysis also supports the association of ITGB3 with AAO. Three disease-associated SNPs were located at species-conserved regions, indicating functional importance. This is the first report which shows that ITGB3 variants are associated with AAO in SCZ, providing direct evidence of the use of AAO as an intermediate phenotype to dissect the complex genetics of SCZ.

Schizophrenia (SCZ) is a debilitating disorder with a prevalence of approximately 1 % worldwide. SCZ is known to have a high degree of genetic and clinical heterogeneity and is a major health problem worldwide. The integrin-β 3 subunit gene (ITGB3) gene at 17q21.32 has been implicated in psychiatric disorders. We therefore hypothesized that ITGB3 gene polymorphisms might also play a role in SCZ and age at onset (AAO) of SCZ. We investigated the genetic associations of 23 single-nucleotide polymorphisms (SNPs) of the ITGB3 gene with AAO in SCZ in two Caucasian samples (2,166 cases and 2,525 controls) using linear regression analysis and meta-analysis. We observed four ITGB3-SNPs associated with AAO in SCZ in a non-Genetic Association Information Network (GAIN) sample (p < 10-3). Three of these four SNPs were replicated in the GAIN sample. The SNP rs16941771 was most significantly associated with AAO (p = 7.47 × 10-5). Meta-analysis showed that 6 of 23 SNPs were associated with AAO. The haplotype analysis also supports the association of ITGB3 with AAO. Three disease-associated SNPs were located at species-conserved regions, indicating functional importance. This is the first report which shows that ITGB3 variants are associated with AAO in SCZ, providing direct evidence of the use of AAO as an intermediate phenotype to dissect the complex genetics of SCZ.

Objectives: We meta-Analyzed the effect of meditation on blood pressure (BP), including both transcendental meditation and non-Transcendental meditation interventions. Methods: We identified randomized controlled trials (RCTs) that examined the BP responses to meditation interventions through a systematic literature search of the PubMed, ABI/INFORM, MEDLINE, EMBASE, PsycINFO, and CINAHL databases (from January 1980 to October 2015). We meta-Analyzed the change in SBP and DBP, stratified by type of meditation (transcendental meditation vs. nontranscendental meditation intervention) and by type of BP measurement [ambulatory BP monitoring (ABPM) vs. non-ABPM measurement]. Results: Nineteen studies met the eligibility criteria. Among the studies using the ABPM measurement, the pooled SBP effect estimate was-2.49mmHg [95% confidence interval (CI):-7.51, 2.53] for transcendental meditation intervention (statistically insignificant) and-3.77mmHg (95% CI:-5.33,-2.21) for nontranscendental meditation interventions, whereas the pooled DBP effect estimate was-4.26mmHg (95% CI:-6.21,-2.31) for transcendental meditation interventions and-2.18mmHg (95% CI:-4.28,-0.09) for nontranscendental meditation interventions. Among the studies using the non-ABPM measurement, the pooled SBP effect estimate from transcendental meditation interventions was-5.57mmHg (95% CI:-7.41,-3.73) and was-5.09mmHg with non-Transcendental meditation intervention (95% CI:-6.34,-3.85), whereas the pooled effect size in DBP change for transcendental meditation interventions was-2.86mmHg (95% CI:-4.27,-1.44) and was-2.57mmHg (95% CI:-3.36,-1.79) for nontranscendental meditation interventions. Conclusion: Non-Transcendental meditation may serve as a promising alternative approach for lowering both SBP and DBP. More ABPM-measured transcendental meditation interventions might be needed to examine the benefit of transcendental meditation intervention on SBP reduction.

Background: Current recommended treatment options for primary headache disorders are suboptimal in that effective pain relief is untimely and associated with side effects. Objective: The primary aim of this thesis was to evaluate the effectiveness and attitudes towards an alternative treatment option, the sphenopalatine ganglion (SPG) block which belongs to a class of procedures known as peripheral nerve blocks (PNBs). Methods: We conducted a systematic review and meta-analysis studying the effectiveness of PNBs for the treatment of primary headache disorders. We also conducted a national postal survey among Canadian emergency physicians to identify current practice patterns and perspectives on PNBs. Results: We found PNBs are effective for rapid pain relief compared to placebo at 15 minutes (MD = -1.17; 95% CI: -1.82 to -0.51) and 30 minutes (MD = -0.99; 95% CI: -1.66 to -0.32). Only 55.6% of physicians have experience with PNBs (95% CI: 0.48 to 0.65) and we discovered the SPG block is the least commonly practiced type of PNB; the majority of physicians believe these procedures are safe (85%) and effective (55.1%). A future trial is needed to compare the SPG block against standard treatment. Conclusion: The SPG block may be used as an adjunct therapy for faster effective pain relief. Current physicians would consider PNBs as a first-line alternative given evidence from a future trial. A future trial is needed to compare the SPG block against standard treatment.

Symptoms of mental illness such as anxiety and depression diminish functioning, cause distress, and create an economic burden to individuals and society. This meta-analysis was designed to evaluate the effectiveness of video based interventions (VBIs) for the treatment of adults in mental health settings. VBIs comprise four different ways of using video in mental health therapy, including video modeling, video exposure, video feedback, and videos used for psychoeducation. Bandura's social learning theory, Beck's cognitive theory, and Dowrick's theory of feedforward learning form the theoretical framework for understanding how VBIs work. The research questions were: (a) what is the range of effect sizes for VBI in mental health treatment of adults? (b) what is the mean standardized effect size for VBI in this context? and (c) what categorical variables, such as type of mental health issue or specific VBI application, moderate the effect of VBI? A comprehensive literature search strategy and coding plan for between-group studies was developed; the overall effect size for the 60 included studies equaled 0.34. A meta-regression was conducted; although the results were not significant, it is possible that type of VBI may be a moderator. Subgroup analyses by mental health outcome found the largest effect size, 0.48, for caregiving attitude and the smallest effect size, 0.21, for depression. Although the results of this meta-analysis were mixed, this study provides preliminary support for VBI use with adults as an evidence-based treatment. VBIs can contribute to positive social change by improving mental health treatment for the benefit of individuals, families, and society.

Effective software performance testing is essential to the development and delivery of quality software products. Many software testing investigations have reported software performance testing improvements, but few have quantitatively validated measurable software testing performance improvements across an aggregate of studies. This study addressed that gap by conducting a meta-analysis to assess the relationship between applying Design of Experiments (DOE) techniques in the software testing process and the reported software performance testing improvements. Software performance testing theories and DOE techniques composed the theoretical framework for this study. Software testing studies (n = 96) were analyzed, where half had DOE techniques applied and the other half did not. Five research hypotheses were tested, where findings were measured in (a) the number of detected defects, (b) the rate of defect detection, (c) the phase in which the defect was detected, (d) the total number of hours it took to complete the testing, and (e) an overall hypothesis which included all measurements for all findings. The data were analyzed by first computing standard difference in means effect sizes, then through the Z test, the Q test, and the t test in statistical comparisons. Results of the meta-analysis showed that applying DOE techniques in the software testing process improved software performance testing (p < 05). These results have social implications for the software testing industry and software testing professionals, providing another empirically-validated testing methodology. Software organizations can use this methodology to differentiate their software testing process, to create more quality products, and to benefit the consumer and society in general.

Le réchauffement climatique est un problème majeur pour le monde scientifique et les sociétés. La concentration de dioxyde de carbone a augmenté de 45% depuis la période préindustrielle (Harris, 2010), conséquence des activités humaines déséquilibrant le cycle du carbone mondial. Cela se traduit par un réchauffement de la planète avec des impacts dramatiques sur la terre et encore plus pour les populations fragiles.Parmi les solutions d'atténuation, une meilleure utilisation du sol est proposée. En effet, les sols ont la plus grande capacité d'échange de carbone avec l'atmosphère et renferment un stock important de carbone. Une augmentation minime du stock de carbone du sol, les échanges de carbone entre l'atmosphère et le sol plus favorables à la séquestration du carbone dans le sol compenseraient les émissions de carbone provenant de la combustion des combustibles fossiles. Cependant, la dynamique du carbone dans le sol souffre encore de connaissances insuffisantes. Il subsiste alors une grande incertitude quant à la réponse du carbone du sol aux changements climatiques et aux changements d'affectation des terres.Plusieurs modèles mécanistiques ont été développés pour mieux comprendre la dynamique du carbone du sol. Cependant, ces modèles mécanistes ont encore une vue incomplète des processus physiques affectant la matière organique (MO) du sol. Il faudra beaucoup de temps pour obtenir un modèle complet et à jour de la dynamique des sols.Dans ma thèse, nous avons proposé un modèle statistique bayésien visant à décrire la dynamique verticale du carbone du sol. Cela se fait grâce à la modélisation du carbone organique du sol et aussi des données radiocarbone, car elles illustrent le temps de séjour de la MO et donc la dynamique du carbone du sol. Cette approche statistique visait à mieux représenter les incertitudes sur la dynamique du carbone du sol et quantifier les effets des facteurs climatiques et environnementaux sur le carbone des sols superficiels et profonds.Cette méta-analyse a été réalisée sur une base de données de 344 profils, collectés à partir de 87 articles scientifiques et archéologiques et paléoclimatologiques, sous différentes conditions climatiques et environnementales.Un modèle non linéaire hiérarchique avec effets aléatoires a été proposé pour modéliser la dynamique verticale du radiocarbone en fonction de la profondeur. Les techniques de sélection bayésiennes, récemment publiées, ont été appliquées aux couches latentes de notre modèle, elles-mêmes liées par une relation linéaire aux facteurs climatiques et environnementaux. Le Bayesian Group Lasso, le Bayesian Sparse Group Selection(BSGS) et le Bayesian Effect Fusion(BEF) ont été testés pour identifier les principaux prédicteurs explicatifs catégoriels et le Stochastic Search Variable Selection pour identifier les prédicteurs explicatifs numériques influents. Une comparaison de ces techniques bayésiennes a été effectuée sur la base des critères de sélection du modèle bayésien pour spécifier quel modèle a le meilleur pouvoir prédictif En plus de la sélection de prédicteurs catégoriels, le BSGS permet de formuler une probabilité d'inclusion a posteriori pour chaque niveau dans les prédicteurs catégoriels comme type de sol et type d'écosystème. En outre, le BEF a permis de fusionner les types de sol et les types d’écosystèmes qui, selon le BEF, sont supposés avoir les mêmes effets sur nos réponses d’intérêts que la réponse du radiocarbone du sol arable.L'application de ces techniques a permis de prédire, en moyenne et au niveau mondial, la dynamique verticale du radiocarbone dans le cas d'une augmentation de température et de changement d’usage des sols. Par exemple, nous avons étudié l'impact de la déforestation des forêts tropicales et leur remplacement par des terres cultivées sur la dynamique du carbone du sol. La même analyse statistique a également été effectuée pour mieux comprendre la dynamique verticale de la teneur en carbone du sol. / Global warming is a major issue for both the scientific world and societies. The concentration of carbon dioxide has increased by 45% since the pre-industrial era (Harris, 2010) as a consequence of human activities, unbalancing the global carbon cycle. This results in global warming with dramatic impacts on the Earth, particularly for fragile populations.Amongst mitigation solutions, a better use of soil is proposed. Soils have the largest capacity of carbon exchanges with the atmosphere and contain a large stock of carbon. A tiny increase in this soil carbon stock and in carbon exchanges between atmosphere and soil would be more favorable to soil carbon sequestration and would compensate for carbon emissios from burning fossil fuel. However, soil carbon dynamics still suffers from insufficient knowledge. There remains therefore a huge uncertainty about the soil carbon response to climate and land-use changes.While several mechanistic models have been developed to better understand the dynamics of soil carbon, they provide an incomplete view of the physical processes affecting soil organic matter (OM). It will be long before a complete and updated soil dynamics model becomes available.In my thesis, I propose a Bayesian statistical model aiming at describing the vertical dynamics of soil carbon. This is done thanks to the modeling of both soil organic carbon and of radiocarbon data as they illustrate the residence time of organic matter and thus the soil carbon dynamics. The purpose of this statistical approach was to better represent the uncertainties on soil carbon dynamics and to quantify the effects of climatic and environmental factors on both surface and deep soil carbon.This meta-analysis was performed on a database of 344 profiles, collected from 87 soil science papers and the literature in archeology and paleoclimatology, under different climate conditions (temperature, precipitation, etc.) and environments (soil type and type of ecosystem).A hierarchical non-linear model with random effects was proposed to model the vertical dynamics of radiocarbon as a function of depth. Bayesian selection techniques, recently published, were applied to the latent layers of the model, which in turn are linked by a linear relationship to the climatic and environmental factors. The Bayesian Group Lasso with Spike and Slab Prior (BGL-SS), the Bayesian Sparse Group Selection (BSGS) and the Bayesian Effect Fusion model-based clustering (BEF) were tested to identify the significant categorical explanatory predictors (soil type, ecosystem type) and the Stochastic Search Variable Selection method to identify the influential numerical explanatory predictors. A comparison of these Bayesian techniques was made based on the Bayesian model selection criteria (the DIC (Deviance Information Criterion), the Posterior Predictive Check, etc.) to specify which model has the best predictive and adjustment power of the database profiles. In addition to selecting categorical predictors, the BSGS allows the formulation of an a posteriori inclusion probability for each level within the categorical predictors such as soil type and ecosystem type (9 soil types and 6 ecosystem types were considered in our study). Furthermore, the BEF made it possible to merge the types of soil as well as the types of ecosystem, which according to the BEF, are considered to have the same effects on the responses of interest here, such as the response of the topsoil radiocarbon.The application of these techniques allowed us to predict, on average and on a global level, the vertical dynamics of the radiocarbon in the case of a temperature increase of 1, 1.5 and 2 °C, and in the case of a change in vegetation cover. For example, we studied the impact of deforesting tropical forests and replacing them by cultivated land on soil carbon dynamics. The same statistical analysis was also done to better understand the vertical dynamics of soil carbon content.

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Type 2 diabetes is a life-threatening condition, and it is rapidly growing in the world. If patients receive adequate education and support, they can manage their diabetes-related tasks effectively and reduce the severe complications of this disease. However, traditional self-management education and practices were not very effective in stimulating behaviour change and addressing patients’ diversified needs and expectations. Mobile text messaging is a promising method for type 2 diabetes self-management as it can provide continuous and customized support to these patients. However, there is a lack of knowledge about the optimal approach to designing and delivering mobile text messages. Hence, this dissertation aimed to define effective message strategies for mobile text messaging interventions targeting type 2 diabetes self-management. This manuscript-based dissertation consists of three complementary studies. The first manuscript includes a systematic review and a meta-analysis of tailored mobile text messaging interventions on type 2 diabetes self-management. It examines the tailoring strategies, message content, and structure and identifies the moderators of effectiveness in these interventions. The second manuscript includes a systematic review and a meta-synthesis of qualitative evidence on patients’ experiences and perspectives of mobile text messaging studies. The third manuscript consists of a prospective qualitative study to explore the text messaging design and delivery preferences of patients. In the first and second studies, the comprehensive search strategy included major electronic databases, key journal searches, and hand searches of the reference lists of related systematic reviews and meta-analyses. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and Cochrane Collaboration's guidelines and recommended tools were used for data extraction, risk of bias and critical appraisal assessments, data analysis and reporting. Within a social marketing framework, the third study included semi-structured interviews and a thematic analysis of the main findings. In the first manuscript, 13 eligible trials were included for the systematic review and 11 eligible trials were further analyzed in the meta-analysis. This study concluded that tailored mobile text messaging interventions could improve glycemic control in patients with type 2 diabetes. The subgroup analyses revealed the importance of some moderators such as message delivery, message direction, message frequency, and using multi-modalities. In the second manuscript, the systematic review included 14 eligible studies, and the thematic synthesis included 13 eligible studies. Patients emphasized the importance of tailored text message design and delivery. They felt “supported” by using text messaging and improved their communication with family/friends and care providers. Mobile text messaging increased patients’ self-awareness, knowledge and control of diabetes. The third study explored that mobile text messages could be more effective if they are gain-framed and written in a standard format. Patients favoured the text messages that included simple and direct tone and provided statistical evidence. The findings demonstrated patients’ needs and expectations for advanced tailoring strategies in both message content and delivery. Together, the manuscripts fill a significant gap and inform research and practice for the development of more effective message strategies that could lead to reducing the spread of type 2 diabetes worldwide. / Graduate / 2022-05-12

This study aims to review thirteen coastal restoration projects considering the various ecosystem services provided by restoration and estimates the economic value of one of the ecosystem services of restoration. These ecosystem services include water quality improvement, fish and benthic species productivity, shoreline stabilization, oyster abundance, and marsh growth. The projects represent a set of large-scale projects within Alabama and Mississippi, with construction and monitoring costs ranging from $2.3 million to $50 million per project. To determine the economic value of one of the ecosystem services of coastal restoration projects, I used the meta-analysis method to estimate the willingness to pay (WTP) for coastal water quality improvements. The estimated function from the meta-analysis is applied to parameters specific to the study area. The WTP for improved coastal water quality, from a baseline of fishable but likely to degrade, to an improved fishing catch rate, is $203 per household annually among residents of Alabama and Mississippi.