162 resultados para meta-analytical study


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Anxiety disorders are increasingly acknowledged as a global health issue however an accurate picture of prevalence across populations is lacking. Empirical data are incomplete and inconsistent so alternate means of estimating prevalence are required to inform estimates for the new Global Burden of Disease Study 2010. We used a Bayesian meta-regression approach which included empirical epidemiological data, expert prior information, study covariates and population characteristics. Reported are global and regional point prevalence for anxiety disorders in 2010. Point prevalence of anxiety disorders differed by up to three-fold across world regions, ranging between 2.1% (1.8-2.5%) in East Asia and 6.1% (5.1-7.4%) in North Africa/Middle East. Anxiety was more common in Latin America; high income regions; and regions with a history of recent conflict. There was considerable uncertainty around estimates, particularly for regions where no data were available. Future research is required to examine whether variations in regional distributions of anxiety disorders are substantive differences or an artefact of cultural or methodological differences. This is a particular imperative where anxiety is consistently reported to be less common, and where it appears to be elevated, but uncertainty prevents the reporting of conclusive estimates.

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Aim Estimate the prevalence of cannabis dependence and its contribution to the global burden of disease. Methods Systematic reviews of epidemiological data on cannabis dependence (1990-2008) were conducted in line with PRISMA and meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. Culling and data extraction followed protocols, with cross-checking and consistency checks. DisMod-MR, the latest version of generic disease modelling system, redesigned as a Bayesian meta-regression tool, imputed prevalence by age, year and sex for 187 countries and 21 regions. The disability weight associated with cannabis dependence was estimated through population surveys and multiplied by prevalence data to calculate the years of life lived with disability (YLDs) and disability-adjusted life years (DALYs). YLDs and DALYs attributed to regular cannabis use as a risk factor for schizophrenia were also estimated. Results There were an estimated 13.1 million cannabis dependent people globally in 2010 (point prevalence0.19% (95% uncertainty: 0.17-0.21%)). Prevalence peaked between 20-24 yrs, was higher in males (0.23% (0.2-0.27%)) than females (0.14% (0.12-0.16%)) and in high income regions. Cannabis dependence accounted for 2 million DALYs globally (0.08%; 0.05-0.12%) in 2010; a 22% increase in crude DALYs since 1990 largely due to population growth. Countries with statistically higher age-standardised DALY rates included the United States, Canada, Australia, New Zealand and Western European countries such as the United Kingdom; those with lower DALY rates were from Sub-Saharan Africa-West and Latin America. Regular cannabis use as a risk factor for schizophrenia accounted for an estimated 7,000 DALYs globally. Conclusion Cannabis dependence is a disorder primarily experienced by young adults, especially in higher income countries. It has not been shown to increase mortality as opioid and other forms of illicit drug dependence do. Our estimates suggest that cannabis use as a risk factor for schizophrenia is not a major contributor to population-level disease burden.

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Background Although the detrimental impact of major depressive disorder (MDD) at the individual level has been described, its global epidemiology remains unclear given limitations in the data. Here we present the modelled epidemiological profile of MDD dealing with heterogeneity in the data, enforcing internal consistency between epidemiological parameters and making estimates for world regions with no empirical data. These estimates were used to quantify the burden of MDD for the Global Burden of Disease Study 2010 (GBD 2010). Method Analyses drew on data from our existing literature review of the epidemiology of MDD. DisMod-MR, the latest version of the generic disease modelling system redesigned as a Bayesian meta-regression tool, derived prevalence by age, year and sex for 21 regions. Prior epidemiological knowledge, study- and country-level covariates adjusted sub-optimal raw data. Results There were over 298 million cases of MDD globally at any point in time in 2010, with the highest proportion of cases occurring between 25 and 34 years. Global point prevalence was very similar across time (4.4% (95% uncertainty: 4.2–4.7%) in 1990, 4.4% (4.1–4.7%) in 2005 and 2010), but higher in females (5.5% (5.0–6.0%) compared to males (3.2% (3.0–3.6%) in 2010. Regions in conflict had higher prevalence than those with no conflict. The annual incidence of an episode of MDD followed a similar age and regional pattern to prevalence but was about one and a half times higher, consistent with an average duration of 37.7 weeks. Conclusion We were able to integrate available data, including those from high quality surveys and sub-optimal studies, into a model adjusting for known methodological sources of heterogeneity. We were also able to estimate the epidemiology of MDD in regions with no available data. This informed GBD 2010 and the public health field, with a clearer understanding of the global distribution of MDD.

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Background Depressive disorders were a leading cause of burden in the Global Burden of Disease (GBD) 1990 and 2000 studies. Here, we analyze the burden of depressive disorders in GBD 2010 and present severity proportions, burden by country, region, age, sex, and year, as well as burden of depressive disorders as a risk factor for suicide and ischemic heart disease. Methods and Findings Burden was calculated for major depressive disorder (MDD) and dysthymia. A systematic review of epidemiological data was conducted. The data were pooled using a Bayesian meta-regression. Disability weights from population survey data quantified the severity of health loss from depressive disorders. These weights were used to calculate years lived with disability (YLDs) and disability adjusted life years (DALYs). Separate DALYs were estimated for suicide and ischemic heart disease attributable to depressive disorders.Depressive disorders were the second leading cause of YLDs in 2010. MDD accounted for 8.2% (5.9%-10.8%) of global YLDs and dysthymia for 1.4% (0.9%-2.0%). Depressive disorders were a leading cause of DALYs even though no mortality was attributed to them as the underlying cause. MDD accounted for 2.5% (1.9%-3.2%) of global DALYs and dysthymia for 0.5% (0.3%-0.6%). There was more regional variation in burden for MDD than for dysthymia; with higher estimates in females, and adults of working age. Whilst burden increased by 37.5% between 1990 and 2010, this was due to population growth and ageing. MDD explained 16 million suicide DALYs and almost 4 million ischemic heart disease DALYs. This attributable burden would increase the overall burden of depressive disorders from 3.0% (2.2%-3.8%) to 3.8% (3.0%-4.7%) of global DALYs. Conclusions GBD 2010 identified depressive disorders as a leading cause of burden. MDD was also a contributor of burden allocated to suicide and ischemic heart disease. These findings emphasize the importance of including depressive disorders as a public-health priority and implementing cost-effective interventions to reduce its burden.Please see later in the article for the Editors' Summary.

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This paper describes students’ developing meta-representational competence, drawn from the second phase of a longitudinal study, Transforming Children’s Mathematical and Scientific Development. A group of 21 highly able Grade 1 students was engaged in mathematics/science investigations as part of a data modelling program. A pedagogical approach focused on students’ interpretation of categorical and continuous data was implemented through researcher-directed weekly sessions over a 2-year period. Fine-grained analysis of the developmental features and explanations of their graphs showed that explicit pedagogical attention to conceptual differences between categorical and continuous data was critical to development of inferential reasoning.

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Background Child sexual abuse is considered a modifiable risk factor for mental disorders across the life course. However the long-term consequences of other forms of child maltreatment have not yet been systematically examined. The aim of this study was to summarise the evidence relating to the possible relationship between child physical abuse, emotional abuse, and neglect, and subsequent mental and physical health outcomes. Methods and Findings A systematic review was conducted using the Medline, EMBASE, and PsycINFO electronic databases up to 26 June 2012. Published cohort, cross-sectional, and case-control studies that examined non-sexual child maltreatment as a risk factor for loss of health were included. All meta-analyses were based on quality-effects models. Out of 285 articles assessed for eligibility, 124 studies satisfied the pre-determined inclusion criteria for meta-analysis. Statistically significant associations were observed between physical abuse, emotional abuse, and neglect and depressive disorders (physical abuse [odds ratio (OR) = 1.54; 95% CI 1.16–2.04], emotional abuse [OR = 3.06; 95% CI 2.43–3.85], and neglect [OR = 2.11; 95% CI 1.61–2.77]); drug use (physical abuse [OR = 1.92; 95% CI 1.67–2.20], emotional abuse [OR = 1.41; 95% CI 1.11–1.79], and neglect [OR = 1.36; 95% CI 1.21–1.54]); suicide attempts (physical abuse [OR = 3.40; 95% CI 2.17–5.32], emotional abuse [OR = 3.37; 95% CI 2.44–4.67], and neglect [OR = 1.95; 95% CI 1.13–3.37]); and sexually transmitted infections and risky sexual behaviour (physical abuse [OR = 1.78; 95% CI 1.50–2.10], emotional abuse [OR = 1.75; 95% CI 1.49–2.04], and neglect [OR = 1.57; 95% CI 1.39–1.78]). Evidence for causality was assessed using Bradford Hill criteria. While suggestive evidence exists for a relationship between maltreatment and chronic diseases and lifestyle risk factors, more research is required to confirm these relationships. Conclusions This overview of the evidence suggests a causal relationship between non-sexual child maltreatment and a range of mental disorders, drug use, suicide attempts, sexually transmitted infections, and risky sexual behaviour. All forms of child maltreatment should be considered important risks to health with a sizeable impact on major contributors to the burden of disease in all parts of the world. The awareness of the serious long-term consequences of child maltreatment should encourage better identification of those at risk and the development of effective interventions to protect children from violence.

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Background We used data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010) to estimate the burden of disease attributable to mental and substance use disorders in terms of disability-adjusted life years (DALYs), years of life lost to premature mortality (YLLs), and years lived with disability (YLDs). Methods For each of the 20 mental and substance use disorders included in GBD 2010, we systematically reviewed epidemiological data and used a Bayesian meta-regression tool, DisMod-MR, to model prevalence by age, sex, country, region, and year. We obtained disability weights from representative community surveys and an internet-based survey to calculate YLDs. We calculated premature mortality as YLLs from cause of death estimates for 1980–2010 for 20 age groups, both sexes, and 187 countries. We derived DALYs from the sum of YLDs and YLLs. We adjusted burden estimates for comorbidity and present them with 95% uncertainty intervals. Findings In 2010, mental and substance use disorders accounted for 183·9 million DALYs (95% UI 153·5 million–216·7 million), or 7·4% (6·2–8·6) of all DALYs worldwide. Such disorders accounted for 8·6 million YLLs (6·5 million–12·1 million; 0·5% [0·4–0·7] of all YLLs) and 175·3 million YLDs (144·5 million–207·8 million; 22·9% [18·6–27·2] of all YLDs). Mental and substance use disorders were the leading cause of YLDs worldwide. Depressive disorders accounted for 40·5% (31·7–49·2) of DALYs caused by mental and substance use disorders, with anxiety disorders accounting for 14·6% (11·2–18·4), illicit drug use disorders for 10·9% (8·9–13·2), alcohol use disorders for 9·6% (7·7–11·8), schizophrenia for 7·4% (5·0–9·8), bipolar disorder for 7·0% (4·4–10·3), pervasive developmental disorders for 4·2% (3·2–5·3), childhood behavioural disorders for 3·4% (2·2–4·7), and eating disorders for 1·2% (0·9–1·5). DALYs varied by age and sex, with the highest proportion of total DALYs occurring in people aged 10–29 years. The burden of mental and substance use disorders increased by 37·6% between 1990 and 2010, which for most disorders was driven by population growth and ageing. Interpretation Despite the apparently small contribution of YLLs—with deaths in people with mental disorders coded to the physical cause of death and suicide coded to the category of injuries under self-harm—our findings show the striking and growing challenge that these disorders pose for health systems in developed and developing regions. In view of the magnitude of their contribution, improvement in population health is only possible if countries make the prevention and treatment of mental and substance use disorders a public health priority.

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Background Up-to-date evidence on levels and trends for age-sex-specific all-cause and cause-specific mortality is essential for the formation of global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013) we estimated yearly deaths for 188 countries between 1990, and 2013. We used the results to assess whether there is epidemiological convergence across countries. Methods We estimated age-sex-specific all-cause mortality using the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data. We generally estimated cause of death as in the GBD 2010. Key improvements included the addition of more recent vital registration data for 72 countries, an updated verbal autopsy literature review, two new and detailed data systems for China, and more detail for Mexico, UK, Turkey, and Russia. We improved statistical models for garbage code redistribution. We used six different modelling strategies across the 240 causes; cause of death ensemble modelling (CODEm) was the dominant strategy for causes with sufficient information. Trends for Alzheimer's disease and other dementias were informed by meta-regression of prevalence studies. For pathogen-specific causes of diarrhoea and lower respiratory infections we used a counterfactual approach. We computed two measures of convergence (inequality) across countries: the average relative difference across all pairs of countries (Gini coefficient) and the average absolute difference across countries. To summarise broad findings, we used multiple decrement life-tables to decompose probabilities of death from birth to exact age 15 years, from exact age 15 years to exact age 50 years, and from exact age 50 years to exact age 75 years, and life expectancy at birth into major causes. For all quantities reported, we computed 95% uncertainty intervals (UIs). We constrained cause-specific fractions within each age-sex-country-year group to sum to all-cause mortality based on draws from the uncertainty distributions. Findings Global life expectancy for both sexes increased from 65·3 years (UI 65·0–65·6) in 1990, to 71·5 years (UI 71·0–71·9) in 2013, while the number of deaths increased from 47·5 million (UI 46·8–48·2) to 54·9 million (UI 53·6–56·3) over the same interval. Global progress masked variation by age and sex: for children, average absolute differences between countries decreased but relative differences increased. For women aged 25–39 years and older than 75 years and for men aged 20–49 years and 65 years and older, both absolute and relative differences increased. Decomposition of global and regional life expectancy showed the prominent role of reductions in age-standardised death rates for cardiovascular diseases and cancers in high-income regions, and reductions in child deaths from diarrhoea, lower respiratory infections, and neonatal causes in low-income regions. HIV/AIDS reduced life expectancy in southern sub-Saharan Africa. For most communicable causes of death both numbers of deaths and age-standardised death rates fell whereas for most non-communicable causes, demographic shifts have increased numbers of deaths but decreased age-standardised death rates. Global deaths from injury increased by 10·7%, from 4·3 million deaths in 1990 to 4·8 million in 2013; but age-standardised rates declined over the same period by 21%. For some causes of more than 100 000 deaths per year in 2013, age-standardised death rates increased between 1990 and 2013, including HIV/AIDS, pancreatic cancer, atrial fibrillation and flutter, drug use disorders, diabetes, chronic kidney disease, and sickle-cell anaemias. Diarrhoeal diseases, lower respiratory infections, neonatal causes, and malaria are still in the top five causes of death in children younger than 5 years. The most important pathogens are rotavirus for diarrhoea and pneumococcus for lower respiratory infections. Country-specific probabilities of death over three phases of life were substantially varied between and within regions. Interpretation For most countries, the general pattern of reductions in age-sex specific mortality has been associated with a progressive shift towards a larger share of the remaining deaths caused by non-communicable disease and injuries. Assessing epidemiological convergence across countries depends on whether an absolute or relative measure of inequality is used. Nevertheless, age-standardised death rates for seven substantial causes are increasing, suggesting the potential for reversals in some countries. Important gaps exist in the empirical data for cause of death estimates for some countries; for example, no national data for India are available for the past decade.

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The mineral series triplite-zwieselite with theoretical formula (Mn2+)2(PO4)(F)-(Fe2+)2(PO4)(F) from the El Criolo granitic pegmatite, located in the Eastern Pampean Ranges of Córdoba Province, was studied using electron microprobe, thermogravimetry, and Raman and infrared spectroscopy. The analysis of the mineral provided a formula of (Fe1.00, Mn0.85, Ca0.08, Mg0.06)∑2.00(PO4)1.00(F0.80, OH0.20)∑1.00. An intense Raman band at 981 cm−1 with a shoulder at 977 cm−1 is assigned to the ν1 symmetric stretching mode. The observation of two bands for the phosphate symmetric stretching mode offers support for the concept that the phosphate units in the structure of triplite-zwieselite are not equivalent. Low-intensity Raman bands at 1012, 1036, 1071, 1087, and 1127 cm−1 are assigned to the ν3 antisymmetric stretching modes. A set of Raman bands at 572, 604, 639, and 684 cm−1 are attributed to the ν4 out-of-plane bending modes. A single intense Raman band is found at 3508 cm−1 and is assigned to the stretching vibration of hydroxyl units. Infrared bands are observed at 3018, 3125, and 3358 cm−1 and are attributed to water stretching vibrations. Supplemental materials are available for this article. Go to the publisher's online edition of Spectroscopy Letters to view the supplemental file.

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Interactions between the anti-carcinogens, bendamustine (BDM) and dexamethasone (DXM), with bovine serum albumin (BSA) were investigated with the use of fluorescence and UV–vis spectroscopies under pseudo-physiological conditions (Tris–HCl buffer, pH 7.4). The static mechanism was responsible for the fluorescence quenching during the interactions; the binding formation constant of the BSA–BDM complex and the binding number were 5.14 × 105 L mol−1 and 1.0, respectively. Spectroscopic studies for the formation of BDM–BSA complex were interpreted with the use of multivariate curve resolution – alternating least squares (MCR–ALS), which supported the complex formation. The BSA samples treated with site markers (warfarin – site I and ibuprofen – site II) were reacted separately with BDM and DXM; while both anti-carcinogens bound to site I, the binding constants suggested that DXM formed a more stable complex. Relative concentration profiles and the fluorescence spectra associated with BDM, DXM and BSA, were recovered simultaneously from the full fluorescence excitation–emission data with the use of the parallel factor analysis (PARAFAC) method. The results confirmed that on addition of DXM to the BDM–BSA complex, the BDM was replaced and the DXM–BSA complex formed; free BDM was released. This finding may have consequences for the transport of these drugs during any anti-cancer treatment.

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Background Symptoms of depression can be recurrent or limited to one episode. This study discusses the prospective association between psychological health, measured as change in depression symptoms, and the risk of diabetes mellitus in Australian women. Methods Data obtained from the Mater-University of Queensland Study of Pregnancy. Depression was measured using the Delusions-Symptoms: States Inventory. To examine possible transitions over time, depression was grouped into four categories and assessed at different phases over the 21-year period. Multiple logistic regression models and sensitivity analysis to assess the robustness of our analytical strategy were performed. Results Three hundred and one women reported diabetes 21 years after the index pregnancy. Almost one-third of the women who reported depression symptoms continued to report these at a subsequent follow-up (FU) phase. About 1 in 20 women who had not reported depression symptoms at the 5-year FU did so at the subsequent 14-year FU. In prospective analyses, we did not find a significant association between diabetes and negative change (not depressed to depressed, at subsequent phase); however, for women with positive history of symptoms of depression and women with persistent symptoms, there was a 1.97-fold (95% confidence interval [CI]: 1.14–3.40) to 2.23-fold (95% CI: 1.09–4.57) greater risk of diabetes. Conclusions Our study suggests that an increased risk of diabetes is significantly associated with persistent depression symptoms. It highlights the importance of recognizing depression symptoms in terms of women's psychological wellbeing and thus provides a basis for targeting those most at risk.

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Background There is growing evidence that the ghrelin axis, including ghrelin (GHRL) and its receptor, the growth hormone secretagogue receptor (GHSR), play a role in cancer progression. Ghrelin gene and ghrelin receptor gene polymorphisms have been reported to have a range of effects in cancer, from increased risk, to protection from cancer, or having no association. In this study we aimed to clarify the role of ghrelin and ghrelin receptor polymorphisms in cancer by performing a meta-analysis of published case–control studies. We conducted searches of the literature published up to January 2013 in MEDLINE using the PubMed search engine. Individual data on 8,430 cases and 14,008 controls from six case–control studies of an all Caucasian population were evaluated for three ghrelin gene (GHRL; rs696217, rs4684677, rs2075356) and one ghrelin receptor (GHSR; rs572169) polymorphism in breast cancer, esophageal cancer, colorectal cancer and non-Hodgkins lymphoma. Results In the overall analysis, homozygous and recessive associations indicated that the minor alleles of rs696217 and rs2075356 GHRL polymorphisms conferred reduced cancer risk (odds ratio [OR] 0.61-0.78). The risk was unchanged for breast cancer patients when analysed separately (OR 0.73-0.83). In contrast, the rs4684677 GHRL and the rs572169 GHSR polymorphisms conferred increased breast cancer risk (OR 1.97-1.98, p = 0.08 and OR 1.42-1.43, p = 0.08, respectively). All dominant and co-dominant effects showed null effects (OR 0.96-1.05), except for the rs572169 co-dominant effect, with borderline increased risk (OR 1.08, p = 0.05). Conclusions This study suggests that the rs696217 and rs2075356 ghrelin gene (GHRL) polymorphisms may protect carriers against breast cancer, and the rs4684677 GHRL and rs572169 GHSR polymorphisms may increase the risk among carriers. In addition, larger studies are required to confirm these findings.

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There is an increasing need in biology and clinical medicine to robustly and reliably measure tens-to-hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma, and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and 7 control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to sub-nanogram/mL sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and inter-laboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy isotope labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an inter-laboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality c`ontrol measures, enables sensitive, specific, reproducible and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

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The development of methods for real-time crash prediction as a function of current or recent traffic and roadway conditions is gaining increasing attention in the literature. Numerous studies have modeled the relationships between traffic characteristics and crash occurrence, and significant progress has been made. Given the accumulated evidence on this topic and the lack of an articulate summary of research status, challenges, and opportunities, there is an urgent need to scientifically review these studies and to synthesize the existing state-of-the-art knowledge. This paper addresses this need by undertaking a systematic literature review to identify current knowledge, challenges, and opportunities, and then conducts a meta-analysis of existing studies to provide a summary impact of traffic characteristics on crash occurrence. Sensitivity analyses were conducted to assess quality, publication bias, and outlier bias of the various studies; and the time intervals used to measure traffic characteristics were also considered. As a result of this comprehensive and systematic review, issues in study designs, traffic and crash data, and model development and validation are discussed. Outcomes of this study are intended to provide researchers focused on real-time crash prediction with greater insight into the modeling of this important but extremely challenging safety issue.

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Problem The Manchester Driver Behaviour Questionnaire (DBQ) is the most commonly used self-report tool in traffic safety research and applied settings. It has been claimed that the violation factor of this instrument predicts accident involvement, which was supported by a previous meta-analysis. However, that analysis did not test for methodological effects, or include contacting researchers to obtain unpublished results. Method The present study re-analysed studies on prediction of accident involvement from DBQ factors, including lapses, and many unpublished effects. Tests of various types of dissemination bias and common method variance were undertaken. Results Outlier analysis showed that some effects were probably not reliable data, but excluding them did not change the results. For correlations between violations and crashes, tendencies for published effects to be larger than unpublished ones and for effects to decrease over time were observed, but were not significant. Also, analysis using the proxy of the mean of accidents in studies indicated that studies where effects for violations are unknown have smaller effect sizes. These differences indicate dissemination bias. Studies using self-reported accidents as dependent variables had much larger effects than those using recorded accident data. Also, zero-order correlations were larger than partial correlations that controlled for exposure. Similarly, violations/accidents effects were strong only when there was also a strong correlation between accidents and exposure. Overall, the true effect is probably very close to zero (r<.07) for violations versus traffic accident involvement, depending upon which systematic tendencies in the data are controlled for. Conclusions: Methodological factors and dissemination bias have inflated the mean effect size of the DBQ in the published literature. Strong evidence of various artefactual effects is apparent. Practical Applications A greater level of care should be taken if the DBQ continues to be used in traffic safety research. Also, validation of self-reports should be more comprehensive in the future, taking into account the possibility of common method variance.