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The reliability of a systematic review's conclusions depends heavily on the quality of the included studies and the rigor of the review process. Assessing the risk of bias is a critical component in evaluating the validity of studies and ensuring the accuracy of systematic reviews. This scoping review aims to provide an overview of existing quality appraisal tools for assessing the risk of bias in systematic reviews. By mapping the landscape of available tools and evaluating their characteristics, this review seeks to guide researchers in selecting the most suitable instruments for their specific review needs. Additionally, identifying gaps and areas for improvement in current tools will help inform future development and refinement of risk of bias assessment methodologies.

We revisit the estimate of the mass fluctuation amplitude, sigma_8, from the observational X-ray cluster abundance. In particular, we examine the effect of the systematic difference between the cluster virial mass estimated from the X-ray spectroscopy, M_{vir, spec}, and the true virial mass of the corresponding halo, M_{vir}. Mazzotta et al. (2004) recently pointed out the possibility that alpha_M = M_{vir, spec}/M_{vir} is systematically lower than unity. We perform the statistical analysis combining the latest X-ray cluster sample and the improved theoretical models and find that sigma_8 \sim 0.76 +/- 0.01 + 0.50 (1-alpha_M) for 0.5 \le alpha_M \le 1, where the quoted errors are statistical only. Thus if alpha_M \sim 0.7, the value of sigma_8 from cluster abundance alone is now in better agreement with other cosmological data including the cosmic microwave background, the galaxy power spectrum and the weak lensing data. The current study also illustrates the importance of possible systematic effects in mapping real clusters to underlying dark halos which changes the interpretation of cluster abundance statistics.

In this paper we provide a comprehensive study of statistical inference in linear and allied models which exhibit some analytic perturbations in their design and covariance matrices. We also indicate a few potential applications. In the theory of perturbations of linear operators it has been known for a long time that the so-called ``singular perturbations'' can have a big impact on solutions of equations involving these operators even when their size is small. It appears that so far the question of whether such undesirable phenomena can also occur in statistical models and their solutions has not been formally studied. The models considered in this article arise in the context of nonlinear models where a single parameter accounts for the nonlinearity.

In PYTHIA6 (PYTHIA8) once the transverse momentum $p_T$ of a generated particle is randomly sampled, $p_x$ and $p_y$ are set on the circle with radius of $p_T$ randomly. This may largely suppress the development of the final hadronic state transverse momentum anisotropy from the initial state spatial asymmetry. We modify PYTHIA6.4 by randomly setting $p_x$ and $p_y$ on the circumference of an ellipse with the half major and minor axes being $p_T(1+\delta_p)$ and $p_T(1-\delta_p)$, respectively. The modified PYTHIA6.4 is then employed to systematically study the charged particle transverse momentum asymmetry in the minimum bias pp collisions at $\sqrt s$=0.9, 7, and 14 TeV. The ALICE data on the transverse sphericity as a function of charged multiplicity, $(N_{ch})$, are well reproduced with the modified PYTHIA6.4. It is found that the predicted charged particle $v_2$ upper limit is a measurable value, $\sim 0.12$, in the minimum bias pp collisions at $\sqrt s$=7 TeV. We suggest a systematic measurement for the particle transverse momentum sphericity, eccentricity (ellipticity), and elliptic flow parameter.

Systematic reviews are the highest evidence in the hierarchy of research, however when these studies are reported with high risk of bias and low methodological quality they may affect the quality of the Evidence Based Practice (EBP) for non and micro invasive treatment of dental caries in primary and permanent teeth

One of the difficulties of artificial intelligence is to ensure that model decisions are fair and free of bias. In research, datasets, metrics, techniques, and tools are applied to detect and mitigate algorithmic unfairness and bias. This study aims to examine the latest existing knowledge about bias and unfairness in machine learning (ML) models with the RSL methodology and a bibliometric analysis. A Systematic Review was carried out between 2021 and early 2022 found 128 articles published between 2017 and 2022 in the Scopus, IEEE Xplore, Web of Science, and Google Scholar knowledge bases, 45 were chosen based on their Abstract and the optimization of search strings. The results indicate that articles mainly focus on bias and unfairness identification and mitigation techniques and types, presenting tools, statistical methods, key metrics and datasets commonly used for experimentation on bias issues. In terms of the main types of bias, we emphasize data, algorithm, and user interaction, with relation to the following mitigation methods: pre-processing, in-processing, and post-processing. The use of Equalized Odds (EO), Equality of Opportunity (EOO), and Demographic (DP) Parity as the primary measures of justice further highlights the significance of sensitive attributes in mitigating biases. The 25 datasets that were found include a range of areas, including criminal justice image enhancement, financial, education, product pricing, and health, and the bulk of them contain sensitive features. In relation to the tools, we highlight that not all of them are used in any practical studies, and the Aequitas was the most mentioned of them. However, a drawback of these works is the scarcity of multi-class and multi-metric investigations, which are found in just a few papers and restrict the study to binary-focused methodologies. %limitations Furthermore, the results indicate that different fairness metrics do not present uniform results for a given use case, and that more research with varied model architectures is necessary to standardize which ones are more appropriate for a given context. It is also crucial to emphasize the relevance of the fact that all researches have addressed the algorithm's transparency, or its capacity to explain how decisions are made.

The project consists of a systematic review and quantitative meta-analysis of probabilistic reasoning bias ('jumping to conclusions' or JTC) in schizophrenia spectrum disorder, and its hypothesized association, within the disorder, with a) delusions, b) negative symptoms and c) poor performance on tests of cognitive function.

Ponatinib, a third-generation tyrosine kinase inhibitor (TKI), has shown efficacy in Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph+ ALL), including cases with and without BCR-ABL1 kinase domain mutations. This meta-analysis compares ponatinib with other TKIs (imatinib, dasatinib, nilotinib etc.) in terms of complete molecular response (CMR), overall survival (OS), and event-free survival (EFS).

Using Artificial Intelligence (AI) to streamline the SR process is a novel approach in medical education with limited studies available. To further add to this groundbreaking approach, this study is proposed to compare the accuracy and efficiency of AI in automating the systematic review process specifically in detecting risk of bias in pre-selected articles. A comparative approach will be used to evaluate two open-source AI programs against human reviewers. Accuracy will be measured by comparing the bias detected by human reviewers versus bias detected by the AI programs. Overall acceptability of review will also be measured.

With this systematic review we aim to explore/assess updated information to understand how female victims are conceptualized by judges and prosecutors, the way victims’ features are considered in gender-based crimes, namely sexual violence (rape and sexual harassment) and intimate partner violence (IPV).

We here reported the protocol following PRISMA-P (Preferred Reporting Items for Systematic review and Meta-Analysis Protocols) 2015 checklist https://www.equator-network.org/reporting-guidelines/prisma-protocols/

This meta-research study seeks to extract, examine, and synthesize information to describe and quantify the extent to which selection bias, specifically collider stratification bias, and modern causal inference methods to address this bias are considered in recently published observational studies of survivors of a first stroke in high impact neurology journals.

This meta-research study seeks to extract, examine, and synthesize information to describe and quantify the extent to which selection bias, specifically collider stratification bias, and modern causal inference methods to address this bias are considered in recently published observational studies of survivors of a first stroke in high impact neurology journals.

This systematic review and meta-analysis aims to identify, evaluate, and synthesize evidence on prognostic factors associated with osteoarthritis (OA) progression in adults. OA is a major public health concern and a leading cause of disability. Yet, there is significant variability in how disease progression is defined and which factors are associated with it. This review will address these gaps by critically appraising studies that assess the predictive value of a broad range of potential prognostic factors—demographic, clinical, imaging, biochemical, lifestyle, and novel risk factors. Eligible studies will include adults diagnosed with OA using standardized or equivalent diagnostic criteria and must report on at least one prognostic factor related to OA progression. Outcomes of interest include symptomatic progression (e.g., pain and functional decline), radiographic progression (e.g., joint space narrowing or Kellgren and Lawrence grade), and surgical endpoints (e.g., joint replacement). These outcomes will be analyzed separately due to their distinct clinical trajectories. The review will follow a rigorous methodology that is aligned with PRISMA 2020 and CHARMS guidelines. It will include observational cohort and nested case-control studies and studies developing or validating prognostic models. The risk of bias will be assessed using the QUIPS tool for single-factor studies and PROBAST+AI for multivariable models, including machine learning-based approaches. Meta-analyses will be conducted where data are sufficiently homogeneous, and meta-regression and subgroup analyses will explore variability related to joint site, sex, disease onset age, and outcome type. Expected outcomes include the identification of consistent and high-quality prognostic indicators of OA progression, assessing heterogeneity and risk of bias in existing studies, and insights into the comparative value of machine learning models. The findings will guide clinical decision-making, improve risk stratification, and inform future research design. The review will be disseminated through peer-reviewed publications, conference presentations, and a plain-language summary for clinicians and patients.

This article is from PLoS ONE , volume 9 . Abstract Transportation of samples is essential for large-scale biobank projects. However, RNA degradation during pre-analytical operations prior to transportation can cause systematic bias in transcriptome data, which may prevent subsequent biomarker identification. Therefore, to collect high-quality biobank samples for expression analysis, specimens must be transported under stable conditions. In this study, we examined the effectiveness of RNA-stabilizing reagents to prevent RNA degradation during pre-analytical operations with an emphasis on RNA from peripheral blood mononuclear cells (PBMCs) to establish a protocol for reducing systematic bias. To this end, we obtained PBMCs from 11 healthy volunteers and analyzed the purity, yield, and integrity of extracted RNA after performing pre-analytical operations for freezing PBMCs at −80°C. We randomly chose 7 samples from 11 samples individually, and systematic bias in expression levels was examined by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR), RNA sequencing (RNA-Seq) experiments and data analysis. Our data demonstrated that omission of stabilizing reagents significantly lowered RNA integrity, suggesting substantial degradation of RNA molecules due to pre-analytical freezing. qRT-PCR experiments for 19 selected transcripts revealed systematic bias in the expression levels of five transcripts. RNA-Seq for 25,223 transcripts also suggested that about 40% of transcripts were systematically biased. These results indicated that appropriate reduction in systematic bias is essential in protocols for collection of RNA from PBMCs for large-scale biobank projects. Among the seven commercially available stabilizing reagents examined in this study, qRT-PCR and RNA-Seq experiments consistently suggested that RNALock, RNA/DNA Stabilization Reagent for Blood and Bone Marrow, and 1-Thioglycerol/Homogenization solution could reduce systematic bias. On the basis of the results of this study, we established a protocol to reduce systematic bias in the expression levels of RNA transcripts isolated from PBMCs. We believe that these data provide a novel methodology for collection of high-quality RNA from PBMCs for biobank researchers.

Prior research demonstrates that examiner unfamiliarity negatively affects the optimal performance of handicapped preschoolers. The present investigation sought to determine whether examiner unfamiliarity also interferes with the optimal performance of handicapped school-age pupils and nonhandicapped children. Sixty-four subjects (16 language-handicapped and 16 nonhandicapped preschoolers and 16 language-handicapped and 16 nonhandicapped school-age students) were tested twice during a period of 2 weeks, once by a familiar examiner and once by an unfamiliar examiner, within a crossover design. A significant interaction was obtained for examiner familiarity and handicapped status, indicating that whereas nonhandicapped subjects scored similarly when tested by familiar and unfamiliar examiners, handicapped children scored higher with the familiar tester. Thus, findings indicated that examiner unfamiliarity negatively affects both language-handicapped preschool and school-age children's performance relative to a normative population; it appears to depress selectively handicapped children's test performance, thereby indicating that an examiner's unfamiliarity constitutes a negatively, systematically biasing condition and threatens the validity of handicapped students' test performance. (Author)

Geographical distribution of the bias and variability of the error in the 500 and 1000mb geopotential height forecasts produced by the National Mereorological Center's operational six-layer baroclinic model was investigated. Forecasts and the verifying observations for six winter seasons beginning with the 1973-74 winter were used. It was found that the model systematically damps out the amplitude of the climatological mean surface highs and lows, and 500mb troughs and ridges. Typical values of the bias in the mean 500mb standing wave troughs are on the order of 60 meters; in these regions the bias accounts for up to 30% of the rms error. Throughout the forecast period, the standard deviation of the forecast error about its own mean shows regional contrasts similiar to climatological standard deviation patterns. These non-systematic forecast errors tend to be largest in storm tracks over the western oceans and quite small at low latitudes. Normalization of the standard deviation of the error by the climatological standard deviation of the observation results in a relatively featureless field except for a monotonic pole-to-equator increase. The normalized errors are larger at the 1000mb level than at the 500mb level over most of the hemisphere but they are of comparable magnitude over the eastern Atlantic and Europe. The vertical structure of the error field, as manifested in the geographical distributions of the correlation between the 1000 and 500mb forecast error, and the ratio of the amplitudes of error fluctuations at those levels, was found to be similar to that of real atmospheric fluctuations.

We report the discovery of a serious bias in galaxy photometry reported in the 2MASS Extended Source Catalog (Jarrett et al. 2000). Due to an undetermined flaw in the 2MASS surface photometry routines, isophotal and total magnitudes calculated by their methods underestimate the luminosity of galaxies from 10% to 40%. This is found to be due to incorrectly determined scalelengths and isophotal radii, which are used to define the aperture sizes for Kron and total fluxes. While 2MASS metric aperture luminosities are correct (and, thus, colors based on those apertures), comparison to other filters (e.g. optical) based on total magnitudes will produce erroneous results. We use our own galaxy photometry package (ARCHANGEL) to determine correct total magnitudes and colors using the same 2MASS images, but with a more refined surface brightness reduction scheme. Our resulting colors, and color-magnitude relation, are more in line with model expectations and previous pointed observations.

Note this registration has been withdrawn: This systematic review and meta-analysis aims to identify, evaluate, and synthesize evidence on prognostic factors associated with osteoarthritis (OA) progression in adults. OA is a major public health concern and a leading cause of disability. Yet, there is significant variability in how disease progression is defined and which factors are associated with it. This review will address these gaps by critically appraising studies that assess the predictive value of a broad range of potential prognostic factors—demographic, clinical, imaging, biochemical, lifestyle, and novel risk factors. Eligible studies will include adults diagnosed with OA using standardized or equivalent diagnostic criteria and must report on at least one prognostic factor related to OA progression. Outcomes of interest include symptomatic progression (e.g., pain and functional decline), radiographic progression (e.g., joint space narrowing or Kellgren and Lawrence grade), and surgical endpoints (e.g., joint replacement). These outcomes will be analyzed separately due to their distinct clinical trajectories. The review will follow a rigorous methodology that is aligned with PRISMA 2020 and CHARMS guidelines. It will include observational cohort and nested case-control studies and studies developing or validating prognostic models. The risk of bias will be assessed using the QUIPS tool for single-factor studies and PROBAST+AI for multivariable models, including machine learning-based approaches. Meta-analyses will be conducted where data are sufficiently homogeneous, and meta-regression and subgroup analyses will explore variability related to joint site, sex, disease onset age, and outcome type. Expected outcomes include the identification of consistent and high-quality prognostic indicators of OA progression, assessing heterogeneity and risk of bias in existing studies, and insights into the comparative value of machine learning models. The findings will guide clinical decision-making, improve risk stratification, and inform future research design. The review will be disseminated through peer-reviewed publications, conference presentations, and a plain-language summary for clinicians and patients.

We present new tests to identify stationary position-dependent additive shear biases in weak gravitational lensing data sets. These tests are important diagnostics for currently ongoing and planned cosmic shear surveys, as such biases induce coherent shear patterns that can mimic and potentially bias the cosmic shear signal. The central idea of these tests is to determine the average ellipticity of all galaxies with shape measurements in a grid in the pixel plane. The distribution of the absolute values of these averaged ellipticities can be compared to randomized catalogues; a difference points to systematics in the data. In addition, we introduce a method to quantify the spatial correlation of the additive bias, which suppresses the contribution from cosmic shear and therefore eases the identification of a position-dependent additive shear bias in the data. We apply these tests to the publicly available shear catalogues from the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS) and the Kilo Degree Survey (KiDS) and find evidence for a small but non-negligible residual additive bias at small scales. As this residual bias is smaller than the error on the shear correlation signal at those scales, it is highly unlikely that it causes a significant bias in the published cosmic shear results of CFHTLenS. In CFHTLenS, the amplitude of this systematic signal is consistent with zero in fields where the number of stars used to model the PSF is higher than average, suggesting that the position-dependent additive shear bias originates from undersampled PSF variations across the image.

Forensic cognitive bias is defined as “the class of effects through which an individual's preexisting beliefs, expectations, motives, and situational context influence the collection, perception, and interpretation of evidence during the course of a criminal case” (Kassin et al, 2013). Although ‘bias’ is conventionally used in the context of discrimination, cognitive bias does not necessarily pertain to errors due to negligence, misconduct or incompetence. Rather, cognitive biases are simply systematic errors in judgement that occur following the overreliance on heuristics (mental shortcuts that facilitate efficient problem solving), often subconscious in nature (Kunkler & Roy, 2023). Thus, not only are cognitive biases difficult to recognise and mitigate, but their subconscious nature also implies all are susceptible regardless of skill or ethics (Thallapureddy et al., 2023). As such, forensic cognitive bias and non-relevant contextual information can lead to errors in evidence analysis which can perhaps impact the reliability of forensic decision making. A previous systematic review of 29 research studies, identifying cognitive biases such as confirmation bias, influenced forensic analysts' conclusions (Cooper and Meterko, 2019). Cooper and Meterko’s (2019) review concluded that forensic scientists were susceptible to cognitive bias, proposing structural changes are necessitated to minimise its impact. The findings of this review support the implementation of blind testing procedures, independent verification, and limiting contextual bias to improve forensic accuracy. Following the publication of Cooper and Meterko (2019), Curley et al. (2020) ascertained that several studies on forensic bias are limited by small sample sizes, lack of proper controls, and low ecological validity. While cognitive bias is a concern in forensic science, Curley et al. (2020) argued that more robust research is needed to determine its true effect in practice, suggesting that better-designed studies, procedural safeguards, and interdisciplinary collaboration could ensure forensic decisions are as accurate and impartial as possible.

We describe a method for computing the biases that systematic signals introduce in parameter estimation using a simple extension of the Fisher matrix formalism. This allows us to calculate the offset of the best fit parameters relative to the fiducial model, in addition to the usual statistical error ellipse. As an application, we study the impact that residual systematics in tomographic weak lensing measurements. In particular we explore three different types of shape measurement systematics: (i) additive systematic with no redshift evolution; (ii) additive systematic with redshift evolution; and (iii) multiplicative systematic. In each case, we consider a wide range of scale dependence and redshift evolution of the systematics signal. For a future DUNE-like full sky survey, we find that, for cases with mild redshift evolution, the variance of the additive systematic signal should be kept below 10^-7 to ensure biases on cosmological parameters that are sub-dominant to the statistical errors. For the multiplicative systematics, which depends on the lensing signal, we find the multiplicative calibration m0 needs to be controlled to an accuracy better than 10^-3. We find that the impact of systematics can be underestimated if their assumes redshift dependence is too simplistic. We provide simple scaling relations to extend these requirements to any survey geometry and discuss the impact of our results for current and future weak lensing surveys.

Systematic reviews are an important type of research for people making health-related decisions. However, it is unknown how systematic review processes, findings, and their dissemination are influenced by private sector activities and commercial bias. This umbrella review aims to understand if, and how, this is happening, and how these processes can be protected from business interests.

This willingness-to-pay experiment tests between two candidate mechanisms underlying the undervaluation of monetary savings over time from higher energy efficiency, a phenomenon called 'the energy paradox'. One mechanism is a utility-weighting based concept of concentration bias. The other mechanism is a tendency towards underestimation when performing intuitive summation. The framing of the monetary savings from a car with lower running costs, and the framing of the additional payment for this car, is manipulated between-subjects. The mechanisms make different predictions regarding the pattern of results between framing conditions.

This systematic review aims to identify and synthesize existing research that has combined electroencephalography (EEG) with the Implicit Association Test (IAT) to investigate implicit bias. By systematically reviewing the literature, this study will provide a comprehensive overview of how EEG has been used to capture the neural correlates of implicit associations across different domains, including race, gender, mental health, and substance use. A key focus of this review is to characterize the methodological approaches employed in these studies. This includes examining the EEG parameters used, such as electrode placement, frequency bands, and event-related potentials (ERPs) commonly analyzed in response to implicit bias tasks. Additionally, the review will consider variations in IAT design, including stimulus categories and response conditions, as well as the characteristics of the study populations, such as sample size, demographics, and distinctions between clinical and non-clinical groups. Beyond identifying and categorizing existing research, this review will synthesize the findings to determine common patterns in the neural processing of implicit bias. Particular attention will be given to well-documented ERP components such as the P300, N400, and late positive potential (LPP), which have been implicated in cognitive and affective processing related to bias. The methodological quality of the included studies will also be assessed to evaluate the reliability, validity, and consistency of findings across the literature.

Stereotype is defined as a series of generalized and widely shared beliefs that define and characterize a group or class of individuals. When related to gender, stereotypes attribute specific characteristics to men and women both with regard to behaviors considered appropriate for each group, and the roles that each can play within society. There seems to be a great heterogeneity around the analysis of attitudes based on gender stereotypes both with regard to the methods used and their components. We aim to conduct a systematic review to answer the folowing research questions: (1) What are the methods used by psychology to study gender bias in children? (2) What are the components of attitudes based on gender stereotypes? Main objective: Operationally define the components of attitudes based on gender stereotypes and the methods used by psychology to study this phenomenon in children. The online databases PubMed, PsycInfo, BVS, Web of Science and Scopus will be covered. This review will include published articles without publication date and / or language restriction and articles obtained from search results in bibliographic references. Only experimental studies will be included. No search restriction will be set. As this is a systematic review of a qualitative construct, the main data are observational. Thus, the intervention corresponds to the focus that each of the studies gave when investigating gender bias in children. The first screening, carried out by the title of the article, will be done by two reviewers. If there are doubts about the eligibility of the article by the title, the reading of the abstract will be used as a second screening procedure. In case of disagreement, a third reviewer will evaluate the article and define whether or not it will be included in the review. The selection of articles will follow the following criteria: (1) Inclusion criteria: • Studies on gender bias; • Studies whose participants are children up to 12 years old; • Studies of experimental design; • Psychology studies; • Studies published in any language; • Without publication deadline. (2) Exclusion criteria: • Studies on other subjects; • Studies carried out with adolescents and / or adults; • Non-experimental studies; • Studies of other areas of knowledge The data will be synthesized by items and based on the STROBE criteria. The data will be presented in tables by group of variables such as year of publication, number and age range of participants, use or not of any evaluation instrument, methods used to conduct the research, evaluated construct.

1. First, to develop a measure to rate narrative bias in titles and abstracts of randomised controlled trials and systematic reviews. 2. Second, the classification will be used to identify the extent to which narrative bias is evident in randomised controlled trials and systematic reviews investigating cannabinoids, cannabis or cannabis-based medicine for pain management.

This study aims to analyze the prevalence of selection bias in systematic reviews focused on the management of dental caries in children and adolescents. Additionally, it seeks to investigate the association between this bias and factors such as journal impact factor, adherence to the PRISMA guidelines, risk of bias assessment (ROBIS), and methodological quality (AMSTAR). Given the critical role of systematic reviews in synthesizing evidence, informing clinical decision-making, and supporting the development of trustworthy clinical practice guidelines, identifying and quantifying selection bias is essential to ensure the reliability of conclusions drawn from these studies. This meta-research study will use a pre-existing sample of systematic reviews, previously registered on the Open Science Framework (OSF) under the project “SPIN in systematic reviews on the management of caries lesions in children and adolescents” (https://doi.org/10.17605/OSF.IO/SQ423). Data extraction will be performed independently by two reviewers and will include key study characteristics such as publication year, country of the corresponding author, journal impact factor, citation count, adherence to PRISMA guidelines, risk of bias assessment, and methodological quality. Selection bias will be assessed based on criteria such as clarity and justification of inclusion/exclusion criteria, comprehensiveness of search strategies, inclusion of studies with potential conflicts of interest, and whether the last literature search was conducted close to the publication date. The ROBIS tool will be used to evaluate risk of bias, while AMSTAR will assess methodological quality. Statistical analyses will be conducted using Jamovi software, employing chi-square tests to determine associations between selection bias and journal impact factor, risk of bias, and methodological quality. It is hypothesized that selection bias is highly prevalent in systematic reviews on dental caries management in children and adolescents. Furthermore, this bias is expected to be associated with lower impact factors journals, lower adherence to PRISMA guidelines, and poorer methodological quality. By identifying these patterns, the study aims to highlight the need for more rigorous methodologies in systematic reviews, contributing to improved evidence reliability and the production of higher-quality recommendations in clinical practice guidelines. This research will provide critical insights into the integrity of systematic reviews in pediatric dentistry, reinforcing the importance of high methodological standards to enhance the quality, applicability, and trustworthiness of evidence-based recommendations, particularly those informing clinical practice guidelines.

A systematic review of studies investigating the effect of attention bias modification on body dissatisfaction. We hypothesise that attention training interventions can change attention biases, and that by doing so, attention training interventions can alter body dissatisfaction.

This article is from Systematic Reviews , volume 2 . Abstract Background: Selective publication of studies, which is commonly called publication bias, is widely recognized. Over the years a new nomenclature for other types of bias related to non-publication or distortion related to the dissemination of research findings has been developed. However, several of these different biases are often still summarized by the term 'publication bias'. Methods/Design: As part of the OPEN Project (To Overcome failure to Publish nEgative fiNdings) we will conduct a systematic review with the following objectives:- To systematically review highly cited articles that focus on non-publication of studies and to present the various definitions of biases related to the dissemination of research findings contained in the articles identified.- To develop and discuss a new framework on nomenclature of various aspects of distortion in the dissemination process that leads to public availability of research findings in an international group of experts in the context of the OPEN Project.We will systematically search Web of Knowledge for highly cited articles that provide a definition of biases related to the dissemination of research findings. A specifically designed data extraction form will be developed and pilot-tested. Working in teams of two, we will independently extract relevant information from each eligible article.For the development of a new framework we will construct an initial table listing different levels and different hazards en route to making research findings public. An international group of experts will iteratively review the table and reflect on its content until no new insights emerge and consensus has been reached. Discussion: Results are expected to be publicly available in mid-2013. This systematic review together with the results of other systematic reviews of the OPEN project will serve as a basis for the development of future policies and guidelines regarding the assessment and prevention of publication bias.

We are conducting a systematic literature review that aims to investigate implicit anti-fat bias and its correlates. Anti-fat bias refers to the social devaluation of, and subsequent stereotypes and discrimination towards, individuals perceived to have excess body weight. The implicit aspect consists of individuals’ internalisation of negative beliefs that unconsciously influence the perception of people considered ‘fat’. Weight stigma is one of the remaining forms of socially accepted stigma and continues to contribute to negative physical and psychological health outcomes. The rates of anti-fat bias continue to rise and understanding related variables may help inform interventions targeting implicit weight bias reductions, as most lack efficacy in altering individuals' attitudes and behaviours in the long-term, despite potential for short-term malleability. This project aims to thoroughly and comprehensively study and synthesise the information on implicit anti-fat bias in hopes of fuelling the development of more efficacious interventions to reduce this form of prejudice, and in turn, weight-based discrimination generally. We have no a priori hypotheses for this review.

This is a cross-sectional study of systematic reviews, meta-analyses and RCTs in paediatric surgery. There are two parts: qualitative and quantitative.

Background: A number of school systems worldwide have proposed and implemented later school start times as a means of avoiding the potentially negative impacts that early morning schedules can have on adolescent students. Even mild sleep deprivation has been associated with significant health and educational concerns: increased risk for accidents and injuries, impaired learning, aggression, memory loss, poor self-esteem, and changes in metabolism. Although researchers have begun to explore the effects of delayed school start time, no one has conducted a rigorous review of evidence to determine whether later school start times support adolescent health, education, and well-being. Objectives: We aimed to assess the effects of a later school start time for supporting health, education, and well-being in high school students. Secondary objectives were to explore possible differential effects of later school start times in student subgroups and in different types of schools; to identify implementation practices, contextual factors, and delivery modes associated with positive and negative effects of later start times; and to assess the effects of later school start times on the broader community (high school faculty and staff, neighborhood, and families). Search methods: We conducted the main search for this review on 28 October 2014 and updated it on 8 February 2016. We searched CENTRAL as well as 17 key electronic databases (including MEDLINE, Embase, ERIC, PsycINFO, and Sociological Abstracts), current editions of relevant journals and organizational websites, trial registries, and Google Scholar. Selection criteria: We included any randomized controlled trials, controlled before-and-after studies, and interrupted time series studies with sufficient data points that pertained to students aged 13 to 19 years and that compared different school start times. Studies that reported either primary outcomes of interest (academic outcomes, amount or quality of sleep, mental health indicators, attendance, or alertness) or secondary outcomes (health behaviors, health and safety indicators, social outcomes, family outcomes, school outcomes, or community outcomes) were eligible. Data collection and analysis: At least two review authors independently determined inclusion and exclusion decisions through screening titles, abstracts, and full-text reports. Two review authors independently extracted data for all eligible studies. We presented findings through a narrative synthesis across all studies. When two or more study samples provided sufficient information to permit effect size calculations, we conducted random-effects meta-analyses to synthesize effects across studies. Results: Our search located 17 eligible records reporting on 11 unique studies with 297,994 participants; the studies examined academic outcomes, amount and quality of sleep, mental health indicators, attendance, and student alertness. Overall, the quality of the body of evidence was very low, as we rated most studies as being at high or unclear risk of bias with respect to allocation, attrition, absence of randomization, and the collection of baseline data. Therefore, we cannot be confident about the effects of later school start times. Preliminary evidence from the included studies indicated a potential association between later school start times and academic and psychosocial outcomes, but quality and comparability of these data were low and often precluded quantitative synthesis. Four studies examined the association between later school start times and academic outcomes, reporting mixed results. Six studies examined effects on total amount of sleep and reported significant, positive relationships between later school start times and amount of sleep. One study provided information concerning mental health outcomes, reporting an association between decreased depressive symptoms and later school start times. There were mixed results for the association between later school start times and absenteeism. Three studies reported mixed results concerning the association between later school start times and student alertness. There was limited indication of potential adverse effects on logistics, as the qualitative portions of one study reported less interaction between parents and children, and another reported staffing and scheduling difficulties. Because of the insufficient evidence, we cannot draw firm conclusions concerning adverse effects at this time. It is important to note the limitations of this evidence, especially as randomized controlled trials and high-quality primary studies are difficult to conduct; school systems are often unwilling or unable to allow researchers the necessary control over scheduling and data collection. Moreover, this evidence does not speak to the process of implementing later school starts, as the included studies focused on reporting the effects rather than exploring the process. Authors' conclusions: This systematic review on later school start times suggests several potential benefits for this intervention and points to the need for higher quality primary studies. However, as a result of the limited evidence base, we could not determine the effects of later school start times with any confidence. [Additional funding was provided by: (1) Department of Public Health Sciences, Canada; and (2) Canadian Institutes of Health Research and the Population Health Intervention Research Network, Canada.]

A methodological systematic review

A methodological systematic review

This research investigates whether body dissatisfaction is related to an attentional bias towards low fat bodies in non-clinical female populations. We will conduct a systematic review and, if appropriate, meta-analyses of cross-sectional studies to determine whether women with high body dissatisfaction direct more attention towards low fat bodies than women with low body dissatisfaction.

A systematic review assessing the risk of bias in the exercise science literature

Collider bias, or stratifying data by a covariate consequence rather than cause (confounder) of treatment and outcome, plagues randomised and observational trauma research. Of the seven trials of prehospital hypertonic saline in dextran (HSD) that have been evaluated in systematic reviews, none found an overall between-group difference in survival, but four reported significant subgroup effects. We hypothesised that an avoidable type of collider bias often introduced inadvertently into trauma comparative effectiveness research could explain the incongruous findings. Methods: The two most recent HSD trials, a single-site pilot and a multi-site pivotal study, provided data for a secondary analysis to more closely examine the potential for collider bias. The two trials had followed the a priori statistical analysis plan to subgroup patients by a post-randomisation covariate and well-established surrogate for bleeding severity, massive transfusion (MT), 10 unit of red blood cells within 24h of admission. Despite favourable HSD effects in the MT subgroup, opposite effects in the non- transfused subgroup halted the pivotal trial early. In addition to analyzing the data from the two trials, we constructed causal diagrams and performed a meta-analysis of the results from all seven trials to assess the extent to which collider bias could explain null overall effects with subgroup heterogeneity. Results: As in previous trials, HSD induced significantly greater increases in systolic blood pressure (SBP) from prehospital to admission than control crystalloid ( p = 0.003). Proportionately more HSD than control decedents accrued in the non-transfused subgroup, but with paradoxically longer survival.

Bias is inescapable in the social world. Any one person has only a singular experience of life, and that experience becomes the lens through which they seek out, interact with, and interpret the world around them. Too often, bias grows insidious and malicious; enabling systems of oppression and reifying false evaluations as natural truth (Crenshaw, 2006; Jackson, Jr. & Weidman, 2005). Given technology’s capacity to amplify bias (boyd & Crawford, 2012; Buolamwini & Gebru, 2018), we conduct a systematic review of communication literature in computational social science (CSS). Informed by this review, our primary contribution is the development of a conceptual framework to help researchers interrogate and mitigate bias across key stages of the research process. We argue that mitigating bias in CSS faces at least two interconnected challenges. The first is that science itself is social, and researchers are subject to the same biases we aim to mitigate. Each researcher is rooted in a paradigm that influences their ontological, epistemological, and axiological perspective, ultimately shaping what questions they ask, what data they use, and how they analyze and interpret their findings (Shugars, 2024a; Webb Williams, 2024). This may result in bias in what populations or issues are studied, such as the ongoing disparity of research tending to examine Western, Educated, Industrial, Rich, Democratic (WEIRD) societies (Henrich et al., 2010) or the reliance on Twitter as a model organism of social platform research (Tufekci, 2014). The impacts of such bias become even more insidious when coupled with the second challenge: empirical approaches—and computational methods in particular—may serve to reinforce and enhance existing biases (Buolamwini & Gebru, 2018; D’Ignazio & Klein, 2020; Shugars, 2024b). Indeed, modern statistics is built largely on the shoulders of eugenicists, whose practices of cranial measurements and IQ tests provided a numerical veneer of objectivity to their racist ideology (Jackson, Jr. & Weidman, 2005). Critical scholars have long warned of the danger in interpreting subjective measurements as objective reality, arguing that our empiricist society is too quick to conflate numerical interpretations as natural truth. Unfortunately, there is reason to believe computational methods have only exacerbated this concern. Computational approaches often rely on large datasets of uncertain provenance, such as digital traces of online behavior (Lazer et al., 2021; Lazer & Ognyanova, 2024). This data is typically passively generated as people use digital services to navigate their daily lives. While such ready-made data can provide valuable insights, researchers rarely have access to full knowledge of how such datasets were constructed or what biases they may reflect (Lazer & Ognyanova, 2024; Salganik, 2019). Furthermore, the scale of such data typically requires standardization and reliance on algorithms, both of which can perpetuate existing inequalities. For example, the common preprocessing step of restricting a corpus to English-language text may disproportionately remove African American Vernacular English or other forms of speech deemed non-standard (Blodgett et al., 2016). Simultaneously, the use of black-box algorithms makes it challenging to determine whether and how bias is reflected in the resulting model (Shugars, 2024a). Finally, algorithmic output is reliant on human interpretation, which again raises the specter of human bias cloaked in the mantle of objective fact. Algorithmic-informed judgments are used in decisions about bail, insurance, and other life-changing matters, often with little thought to the bias baked in at every step of the process. References Blodgett, S. L., Green, L., & O’Connor, B. (2016). Demographic dialectal variation in social media: A case study of African-American English. In J. Su, K. Duh, & X. Carreras (Eds.), Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (pp. 1119–1130). Association for Computational Linguistics. https://doi.org/10.18653/v1/D16-1120 boyd, d., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication & Society, 15(5), 662–679. https://doi.org/10.1080/1369118X.2012.678878 Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. Proceedings of the 1st Conference on Fairness, Accountability and Transparency, 77–91. https://proceedings.mlr.press/v81/buolamwini18a.html Crenshaw, K. W. (2006). Race, reform, and retrenchment: Transformation and legitimation in antidiscrimination law. In Law and social movements. Routledge. D’Ignazio, C., & Klein, L. F. (2020). Data feminism. MIT Press. Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world? Behavioral and Brain Sciences, 33(2–3), 61–83. https://doi.org/10.1017/S0140525X0999152X Jackson, Jr., J. P., & Weidman, N. M. (2005). The origins of scientific racism. The Journal of Blacks in Higher Education, 50(1), 66–79. https://www.jstor.org/stable/25073379 Lazer, D., Hargittai, E., Freelon, D., Gonzalez-Bailon, S., Munger, K., Ognyanova, K., & Radford, J. (2021). Meaningful measures of human society in the twenty-first century. Nature, 595, 189–196. https://doi.org/10.1038/s41586-021-03660-7 Lazer, D., & Ognyanova, K. (2024). The future of computational social science. In J. M. Box-Steffensmeier, D. P. Christenson, & V. Sinclair-Chapman (Eds.), Oxford handbook of engaged methodological pluralism in political science (pp. 1–22). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780192868282.013.50 Salganik, M. J. (2019). Bit by bit: Social research in the digital age. Princeton University Press. Shugars, S. (2024a). A matter of perspective: Computational social science and researcher choice. In J. M. Box-Steffensmeier, D. P. Christenson, & V. Sinclair-Chapman (Eds.), Oxford handbook of engaged methodological pluralism in political science (vol 1) (p. 0). Oxford University Press. https://doi.org/10.1093/oxfordhb Shugars, S. (2024b). Critical computational social science. EPJ Data Science, 13(1), 13. https://doi.org/10.1140/epjds/s13688-023-00433-2 Tufekci, Z. (2014, April 15). Big questions for social media big data: Representativeness, validity and other methodological pitfalls. Proceedings of the 8th International AAAI Conference on Weblogs and Social Media. ICWSM, Ann Arbor, MI. https://doi.org/10.48550/arXiv.1403.7400 Webb Williams, N. (2024). What type of data are images? In J. M. Box-Steffensmeier, D. P. Christenson, & V. Sinclair-Chapman (Eds.), Oxford handbook of engaged methodological pluralism in political science (vol 1) (p. 0). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780192868282.013.47

In this report, we find the \mbh estimated from the formalism of Wang et al. (2009)[1] are more consistent with those from the \mbh-$\sigma_*$ relation than those from previous single-epoch mass estimators, using a large sample of AGNs. Furthermore, we examine the differences between the line widths of \hb and \mgii in detail by comparing their line profiles. The flux around the line core and that in the wing of both \hb and \mgii show an opposite variation tendency, which indicates the BLR is multi-componential. The contribution of the wing makes the FWHM deviate from $\sigma_{line}$, and thus bias the \mbh estimated from previous single-epoch mass estimators. Thus the correction on the formalism suggested by Wang et al. (2009)[1] is crucial to \mbh estimation.

In this systematic review and meta-analysis, we aim to examine whether there is an association between trait anger and hostile attribution bias (HAB). Our investigation is grounded in Charles Spielberger’s State-Trait Theory of Anger, which distinguishes transient states of anger from a stable disposition to experience anger—trait anger—which persists independently of whether a person is currently angry. It is the effect of trait anger that we seek to investigate. We hypothesize that trait anger is positively associated with HAB, such that individuals with a greater propensity toward anger will exhibit higher levels of HAB. In addition, we aim to explore potential moderators of this relationship. To this end, part of our research will be exploratory. At this stage, we anticipate examining the following moderators: gender, age, type of Trait Anger measure, type of HAB measure, whether participants underwent an emotional induction prior to the HAB assessment, and the nature of that induction (e.g., provocation, recall of experiences involving specific emotions). Additional moderators may be included if they emerge as theoretically or empirically relevant during the review process.

Clinical prediction models(CPMs) are used to predict health-related outcomes for individual patients and are defined as any combination of two or more predictors (variables, characteristics) used to estimate the probability or risk of an individual having a specific outcome (diagnosis) or developing a specific outcome (prognosis).1-3Properly conducted and adequately reported CPMs studies are crucial for the effective implementation of these models in clinical practice and can help clinicians make the best evidence-based decisions.4 The rise of modern data-driven modeling techniques has advanced the development of CPMs research in biomedical literature, leading to the rapid emergence of studies. Despite extensive research, the number of these models used in clinical practice is very limited, contributing to research waste.5 The primary reason for this is the uneven quality of reporting and methodology in CPMs studies, with some publications highlighting concerns about methodological quality.6-8 Deficiencies in study design, methodology, conduct, and analysis may lead to a high risk of research bias, resulting in skewed estimates of the model's predictive performance, thus reducing its accuracy and applicability.9 10 Using CPMs with high risk of bias can lead to unnecessary or inadequate interventions, adversely affecting patient health and health systems. Aims Therefore, the purpose of study was to synthesize and rigorously assess the risk of bias and completeness of the reporting in SRs of CPMs models and to reveal the current status so that some of the limitations and challenges can be observed clearly in the process of conducting and reporting an SR of CPMs.

Stage 1 IPA at PCI RR

This article is from PLoS Medicine , volume 10 . Abstract : Maira Bes-Rastrollo and colleagues examine whether financial conflicts of interest are likely to bias conclusions from systematic reviews that investigate the relationship between sugar-sweetened beverages and weight gain or obesity.Please see later in the article for the Editors' Summary

In recent years, rape and serious sexual offences (RASSO) have become an area of increasing attention in criminal justice research, particularly in relation to jury bias and impartiality. However, despite this heightened focus, significant uncertainties remain regarding the fairness and efficacy of jury decision-making in RASSO trials. Specifically, the influence of bias in jury decision making and how to reduce this bias. This systematic review seeks to address these issues by synthesizing existing literature on jury bias in RASSO trials, focusing on how various forms of bias (e.g., race bias and rape myth bias) influence jury decision-making. The review will also examine and assess strategies suggested in the literature designed to mitigate these biases, such as implicit bias training, jury instructions, and pre-trial education. If a sufficient number of relevant studies are identified, a quantitative synthesis will be performed to assess the effectiveness of these strategies in reducing bias among jurors. By analyzing current research, particularly those related to ecological validity, this review aims to provide actionable insights that could inform future reforms to improve jury impartiality in RASSO trials as well as areas for further research.

The need to reduce intergroup bias is increasingly in the public consciousness, with movements against racism, sexism, transphobia and other forms of intergroup bias and prejudice becoming more prominent. An increasing body of recent research has indicated that interpersonal confrontation of intergroup bias (also known as bystander anti-prejudice: Stewart et al., 2014) is an effective method for reducing intergroup bias (e.g. Chaney & Sanchez, 2018; Czopp et al., 2006). However, there has not yet been a systematic review and meta-analysis in the area. This is important, both to take stock of this field of research, shed light on potential moderators of the effect, and provide guidance for future research. The current meta-analysis aims to fill that gap, providing a useful synthesis of the current research, and a quantitative exploration of the moderators of the effectiveness of confrontation as an intergroup bias-reduction technique. NOTE: In the pre-registration document it notes the search strategy for OpenGrey and PsyArXiv as: prejudice OR anti-prejudice OR anti-racis* OR anti-sexis* OR discriminat* OR stereotyp* OR stigma* OR “intergroup bias” OR anti-muslim OR anti-islamophob* OR islamophob* OR anti-fat OR “bystander anti-*” OR “prejudice reduction” AND “bystander intervention” OR “bystander confrontation” OR confrontation This is incorrect, the correct search strategy is: ( prejudice OR anti-prejudice OR anti-racis* OR anti-sexis* OR discriminat* OR stereotyp* OR stigma* OR “intergroup bias” OR anti-muslim OR anti-islamophob* OR islamophob* OR anti-fat OR “bystander anti-*” OR “prejudice reduction” ) AND ( “bystander intervention” OR “bystander confrontation” OR confrontation )

We aim systematically review studies on intimate partner domestic violence (IPDV) against women and evaluate its impact on attentional bias.

We aim systematically review studies on intimate partner domestic violence (IPDV) against women and evaluate its impact on attentional bias.

The aim of this project is to create a systematic review conserning citation bias in healthcare publications.

Food information has a high reward value for human beings, and may be more so for those who are overweight or obese. Attention bias towards or away from food stimuli appears to be related to clinical symptoms in disordered eating and obesity. A popular task to assess attentional bias is the dot probe task. However, several studies have shown that the dot probe task has low reliability, making it a poor candidate to study individual differences or assess changes. A recent study (van Ens et al., 2019), however, seems to suggest that, by using a long stimulus presentation duration (3 seconds or longer), reaction time index may have acceptable internal and good test-retest reliability; in addition, although eye-tracking based first fixation measure had poor internal and test-retest reliability, the total dwell time measure had excellent internal and acceptable test-retest reliability. But several confounding factors and major limitations in this study may affect the validity and generalizability of the results: 1) it was mentioned that the color and complexity between food and nonfood stimuli were carefully matched, but it was not clear how; moreover, important physical properties such as luminance and contrast were not controlled for. Therefore, it was not clear whether any bias observed between food and nonfood images might be due to potential physical differences in luminance, contrast, etc. 2) Only 20 food stimuli (10 for high caloric density and 10 for low caloric density) were used, each presented for four times in the experiment. The limited number of images raises the question of generalizability across different food images; and repetitive presentations of images raises the possibility that any bias observed might not be due to attention per se but might relate to memory. 3) It was mentioned that appetizing stimuli were used to draw participants’ attention but it was not clear whether and how tastefulness was actually measured, which is important given individual differences in food preference. Moreover, caloric density was used, but it might not be a good index of healthfulness, since healthfulness, too, can be subjective. 4) reliability was measured only by Pearson’s correlation, which is a limited measure of reliability; for example, it does not take into account systematic differences between testing sessions. 5) the food and nonfood images were presented for 3 seconds, which is much longer than typically used in the dot probe task. It is then not clear how presentation duration might affect attentional bias and its reliability. Therefore, we plan to conduct a systematic investigation of the reliability of eye tracking based attention bias to food images in the dot-probe task using both reaction time and eye tracking measures. We plan to do so in two studies. In study 1, we resolve the confounds and limitations identified above with a few key innovations: 1) to control for differences in physical properties between food and nonfood stimuli, we use diffeomorphic transformed images based on the food images to serve as low-level control stimuli; 2) to improve generalizability and avoid the memory confound, we will increase the number of food images from 20 to 288, with each food image presented only once; 3) to control for individual differences in subjective perception, healthfulness and tastiness of the food items are rated by each participant individually, with the ratings then used to divide the food images into four groups (low healthfulness and low tastiness, low healthfulness and high tastiness, high healthfulness and low tastiness, and high healthfulness and high tastiness); 4) to provide a comprehensive evaluation, reliability is assessed by Pearson’s correlation coefficients/intraclass correlation coefficients (ICC), standard errors of measurement, and Cronbach’s alpha. In study 2, we also systematically investigate the role of presentation duration and the role of image repetitions in attention bias, by manipulating stimulus duration (100 ms, 500 ms, 1000 ms, vs. 3000 ms) and repetitions (1 time vs. 4 times).