Thesis (Ph.D.)--University of Alberta, 2010. / A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Doctor of Philosophy, Department of Public Health Sciences. Title from pdf file main screen (viewed on April 28, 2010). Includes bibliographical references.

Orientadores: Mario Jino, Manoel Gomes de Mendonça Neto, Victor Robert basili / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-09T03:08:37Z (GMT). No. of bitstreams: 1 Cruzes_DanielaSoares_D.pdf: 5878913 bytes, checksum: 3daddec5bb0c08c955c288b74419bccc (MD5) Previous issue date: 2007 / Resumo: Enquanto é claro que existem muitas fontes de variação de um contexto de desenvolvimento de software para outro, não é claro, a priori, quais variáveis específicas influenciarão a eficácia de um processo, de uma técnica ou de um método em um determinado contexto. Por esta razão, o conhecimento sobre a engenharia de software deve ser construído a partir de muitos estudos, executados tanto em contextos similares como em contextos diferentes entre si. Trabalhos precedentes discutiram como projetar estudos relacionados documentando tão precisamente quanto possível os valores de variáveis do contexto para assim poder comparálos com os valores observados em novos estudos. Esta abordagem é importante, porém argumentamos neste trabalho que uma abordagem oportunística também é prática. A abordagem de análise secundária de estudos discutida neste trabalho (SecESE) visa combinar resultados de múltiplos estudos individuais realizados independentemente, permitindo a expansão do conhecimento experimental em engenharia de software. Usamos uma abordagem baseada na codificação da informação extraída dos artigos e dos dados experimentais em uma base estruturada. Esta base pode então ser minerada para extrair novos conhecimentos de maneira simples e flexível / Abstract: While it is clear that there are many sources of variation from one software development context to another, it is not clear a priori, what specific variables will influence the effectiveness of a process, technique, or method in a given context. For this reason, we argue that knowledge about software engineering must be built from many studies, in which related studies are run within similar contexts as well as very different ones. Previous works have discussed how to design related studies so as to document as precisely as possible the values of context variables and be able to compare with those observed in new studies. While such a planned approach is important, we argue that an opportunistic approach is also practical. This approach would combine results from multiple individual studies after the fact, enabling the expansion of empirical software engineering knowledge from large evidence bases. In this dissertation, we describe a process to build empirical knowledge about software engineering. It uses an approach based on encoding the information extracted from papers and experimental data into a structured base. This base can then be mined to extract new knowledge from it in a simple and flexible way / Doutorado / Engenharia de Computação / Doutor em Engenharia Elétrica

Boletín que incluye información científica sobre el COVID-19, incluye artículos científicos, artículos preprint y revisiones sistemáticas actualizado al 14 de Mayo de 2020.

Boletín que incluye información científica sobre el COVID-19, incluye artículos científicos, artículos preprint y revisiones sistemáticas actualizado al 15 de Mayo de 2020.

"Math anxiety is commonly defined as a feeling of tension, apprehension, or fear that interferes with math performance" (Ashcraft, 2002, p. 181). Symptoms of math anxiety are reported by 33% of students by the time they reach the age of 15, possibly contributing to this workforce dilemma (Organisation for Economic Co-operation and Development, 2013). Many models and perspectives of math anxiety have been established including conceptualizing math anxiety as a function of working memory deficits, sociocultural conditioning, lack of reappraisal, and anxiety as a precursor to escape-maintained behavior. Math anxiety is more common in individuals with certain disabilities, such as developmental dyscalculia and deaf and hard of hearing. Hembree (1990) conducted a meta-analysis of research evaluating intervention effects on math anxiety and its moderators. They reported that cognitive-behavioral interventions were most effective at reducing math anxiety. While definitions of, models examining, and causes and co-occurrences of math anxiety are well examined in current literature, Hembree's (1990) meta- analysis remains the only such investigation for the past 30 years. The purpose of the present study is to conduct an updated meta-analysis based on previous research (Hembree, 1990) but focused on interventions in K-12 school settings. We identified 11 articles between the years of 1990-2020 that met our inclusion criteria. From those articles, we calculated an omnibus effect size, tested homogeneity, evaluated publication bias, explored moderating variables, and assessed methodological rigor. Our Q statistic indicated homogeneity; however, the forest plot and I2 indicated a small amount of heterogeneity. The asymmetric shape of the funnel plot may be indicative of publication bias. The omnibus effect size was g = 0.316. The results of our moderator analysis indicated that math anxiety interventions produce the best results when conducted in targeted small groups. Additionally, three studies were considered methodologically sound. Our findings support the use of school-based interventions to reduce math anxiety, especially when those interventions are implemented as a targeted, small group intervention.

"Math anxiety is commonly defined as a feeling of tension, apprehension, or fear that interferes with math performance" (Ashcraft, 2002, p. 181). Symptoms of math anxiety are reported by 33% of students by the time they reach the age of 15, possibly contributing to this workforce dilemma (Organisation for Economic Co-operation and Development, 2013). Many models and perspectives of math anxiety have been established including conceptualizing math anxiety as a function of working memory deficits, sociocultural conditioning, lack of reappraisal, and anxiety as a precursor to escape-maintained behavior. Math anxiety is more common in individuals with certain disabilities, such as developmental dyscalculia and deaf and hard of hearing. Hembree (1990) conducted a meta-analysis of research evaluating intervention effects on math anxiety and its moderators. They reported that cognitive-behavioral interventions were most effective at reducing math anxiety. While definitions of, models examining, and causes and co-occurrences of math anxiety are well examined in current literature, Hembree's (1990) meta- analysis remains the only such investigation for the past 30 years. The purpose of the present study is to conduct an updated meta-analysis based on previous research (Hembree, 1990) but focused on interventions in K-12 school settings. We identified 11 articles between the years of 1990-2020 that met our inclusion criteria. From those articles, we calculated an omnibus effect size, tested homogeneity, evaluated publication bias, explored moderating variables, and assessed methodological rigor. Our Q statistic indicated homogeneity; however, the forest plot and I2 indicated a small amount of heterogeneity. The asymmetric shape of the funnel plot may be indicative of publication bias. The omnibus effect size was g = 0.316. The results of our moderator analysis indicated that math anxiety interventions produce the best results when conducted in targeted small groups. Additionally, three studies were considered methodologically sound. Our findings support the use of school-based interventions to reduce math anxiety, especially when those interventions are implemented as a targeted, small group intervention.

Background: In the United States, increasing ethnic diversity has been apparent. However, the epidemiology and trends of BKV genotypes remain unclear. This meta-analysis was conducted with the aim to assess the prevalence of BKV genotypes among kidney transplant (KTx) recipients in the United States. Methods: A comprehensive literature review was conducted through October 2018 utilizing MEDLINE, Embase, and Cochrane Database to identify studies that reported the prevalence of BKV subtypes and/or subgroups in KTx recipients in the United States. Pooled prevalence rates were combined using random effects, generic inverse variance method. The protocol for this study is registered with PROSPERO (no. CRD42019134582). Results: A total of eight observational studies with a total of 193 samples (urine, blood, and kidney tissues) from 188 BKV-infected KTX recipients were enrolled. Overall, the pooled estimated prevalence rates of BKV subtypes were 72.2% (95% confidence of interval [CI]: 62.7-80.0%) for subtype I, 6.8% (95% CI: 2.5-16.9%) for subtype II, 8.3% (95% CI: 4.4-15.1%) for subtype III, and 16.1% (95% CI: 10.4-24.2%) for subtype IV, respectively. While metaregression analysis demonstrated a significant positive correlation between year of study and the prevalence of BKV subtype I (slopes = +0.1023, P =.01), there were no significant correlations between year of study and percentages of BKV subtype II-IV (P >.05). Among KTx recipients with BKV subtype I, the pooled estimated percentages of BKV subgroups were 22.4% (95% CI: 13.7-34.5%) for subgroup Ia, 30.6% (95% CI: 17.7-47.5%) for subgroup Ib1, 47.7% (95% CI: 35.8-59.9%) for subgroup Ib2, and 4.1% (95% CI:1.2-13.3%) for subgroup Ic, respectively. Conclusion: BKV subtype I is the most prevalent subtype among KTx recipients in the United States and its prevalence seems to increasing overtime. Subgroup Ib2 is the most common subgroup among BKV subtype I.

BACKGROUND: The incidence and mortality of renal cell carcinoma (RCC) after kidney transplantation (KTx) remain unclear. This study's aims were (1) to investigate the pooled incidence/incidence trends, and (2) to assess the mortality/mortality trends in KTx patients with RCC. METHODS: A literature search was conducted using the MEDLINE, EMBASE and Cochrane databases from inception through October 2018. Studies that reported the incidence or mortality of RCC among kidney transplant recipients were included. The pooled incidence and 95% CI were calculated using a random-effect model. The protocol for this meta-analysis is registered with PROSPERO; no. CRD42018108994. RESULTS: A total of 22 observational studies with a total of 320,190 KTx patients were enrolled. Overall, the pooled estimated incidence of RCC after KTx was 0.7% (95% CI: 0.5-0.8%, = 93%). While the pooled estimated incidence of de novo RCC in the native kidney was 0.7% (95% CI: 0.6-0.9%, = 88%), the pooled estimated incidence of RCC in the allograft kidney was 0.2% (95% CI: 0.1-0.4%, = 64%). The pooled estimated mortality rate in KTx recipients with RCC was 15.0% (95% CI: 7.4-28.1%, = 80%) at a mean follow-up time of 42 months after RCC diagnosis. While meta-regression analysis showed a significant negative correlation between year of study and incidence of de novo RCC post-KTx (slopes = -0.05, = 0.01), there were no significant correlations between the year of study and mortality of patients with RCC ( = 0.50). Egger's regression asymmetry test was performed and showed no publication bias in all analyses. CONCLUSIONS: The overall estimated incidence of RCC after KTX was 0.7%. Although there has been a potential decrease in the incidence of RCC post-KTx, mortality in KTx patients with RCC has not decreased over time.

BACKGROUND: The adverse renal effects of proton pump inhibitors (PPIs) are increasingly recognized in both the general population and patients with chronic kidney disease. Several pharmacokinetic studies have also raised concerns regarding the interaction between PPIs and immunosuppressive drugs in transplant patients. Whether the adverse effects of PPIs have a clinical significance in kidney transplant recipients remains unclear. We performed this meta-analysis to assess the risk of adverse effects in kidney transplant recipients on PPI compared with those without PPI exposure. AIM: To investigate the risk of acute rejection, graft loss, hypomagnesemia, renal dysfunction, and overall mortality in kidney transplant recipients on PPI compared with those without PPI exposure. METHODS: A systematic review was conducted in MEDLINE, EMBASE, and Cochrane databases from inception through October 2018 to identify studies that evaluated the adverse effects of PPIs in kidney transplant recipients, including biopsy-proven acute rejection, graft loss, hypomagnesemia, renal function, and overall mortality. Effect estimates from the individual studies were extracted and combined using random-effect, generic inverse variance method of DerSimonian and Laird. The protocol for this meta-analysis is registered with PROSPERO, No. CRD42018115676. RESULTS: Fourteen observational studies with 6786 kidney transplant recipients were enrolled. No significant association was found between PPI exposure and the risk of biopsy-proven acute rejection at ≥ 1 year [pooled odds ratio (OR), 1.25; 95% confidence interval (CI), 0.82-1.91, = 55%], graft loss at 1 year (pooled OR = 1.30, 95%CI: 0.75-2.24, = 0%) or 1-year mortality (pooled OR = 1.53, 95%CI: 0.90-2.58, = 34%). However, PPI exposure was significantly associated with hypomagnesemia (pooled OR = 1.56, 95%CI: 1.19-2.05, = 27%). Funnel plots and Egger regression asymmetry test were performed and showed no publication bias. CONCLUSION: PPI use was not associated with significant risks of higher acute rejection, graft loss, or 1-year mortality. However, the risk of hypomagnesemia was significantly increased with PPI use. Thus, future studies are needed to assess the impact of PPIs on long-term outcomes.

PhD thesis assessing the role of non-randomized studies with randomized in evidence syntheses of health interventions. / Randomized studies (RS) are considered the best source of evidence for knowledge syntheses (e.g., systematic reviews, health technology assessments, health guidelines, among others) about healthcare interventions. Historically, non-randomized studies (NRS) have been usually discarded from knowledge syntheses of interventions due to their intrinsic risk of bias and confounding, and they are used only when RS are considered unfeasible or unethical to conduct. With better research methods in observational studies and new tools for the evaluation of risk of bias, NRS are more likely to be a helpful source of information when used as replacement, sequential, or complementary evidence. This, together with the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach, provide an opportunity for guiding decisions about using RS and NRS in knowledge synthesis and increasing our certainty in a body of evidence. This work aims to improve research synthesis methods by assessing the role and use of RS and NRS in knowledge syntheses using GRADE. This can help health professionals, researchers, guideline developers, and policy-makers build better and more complete healthcare recommendations. / Thesis / Doctor of Philosophy (PhD) / All recommendations about healthcare interventions (from common medicines to strategies to prevent diseases) should ideally come from an adequate synthesis (e.g., systematic reviews) of the least biased studies. Many researchers and authors of health syntheses consider randomized studies (RS), the ‘gold standard’ to demonstrate if an intervention is truly effective. Unfortunately, they are not always available, feasible, or ethical to conduct. Non-randomized studies (NRS), also called observational studies, can potentially provide complementary evidence for a research question. Unfortunately, they are usually considered of poorer quality because of their intrinsic nature of being prone to bias and confounding. In most circumstances, authors of syntheses discard these types of studies from the outset, without considering their potential for providing evidence that could complement or even replace that from randomized studies. This work aims to improve this situation by offering methods for evaluating the appropriateness of integrating both RS and NRS, guiding authors and researchers in cases where this is possible, hence increasing the certainty in a body of evidence and help all stakeholders reach decisions.