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Purpose: Children continue to experience chemotherapy-induced nausea and vomiting (CINV), despite effective antiemetic medications. Recommendations in clinical practice guidelines are underpinned by narrative syntheses and meta-analyses that compare only two treatments. This means not all antiemetics have been compared to one another, and estimates remain imprecise. We apply network meta-analysis (NMA) to overcome these limitations by comparing multiple treatments simultaneously. Methods: A systematic review identified and critically appraised RCTs comparing antiemetics recommended and licensed for the prevention of CINV in children. Bayesian NMA compared and ranked antiemetic effectiveness for the outcomes complete (CR) and partial response (PR) in the acute, delayed, and overall phases, nausea, and decreased food intake. Antiemetics given with and without dexamethasone were compared in separate networks as their underlying populations differed. Results: Sixteen RCTs (3115 patients receiving moderately (MEC) or highly emetogenic chemotherapy (HEC)) were included. When given with dexamethasone, NK1 antagonists with ondansetron ranked highest for CR and PR in the acute and overall phases, PR in the delayed phase, and decreased food intake. Post hoc analysis shows further a benefit of adding olanzapine to regimens of aprepitant and ondansetron. Ondansetron ranked lower than palonosetron, for CR in the delayed and overall phases, and ondansetron was less effective than palonosetron for nausea prevention. Rankings for other regimens, including those given without dexamethasone, were uncertain or inconsistent across outcomes. Conclusions: Our findings serve to support the current recommendations of olanzapine (when given with aprepitant and ondansetron) and NK1 antagonists’ regimens receiving HEC, but note that evidence of a significant difference in relative benefit, between patients receiving MEC and HEC, does not yet exist. Recommendations for palonosetron as the preferred 5HT3 antagonists may be extended, particularly, to those who are at high risk of nausea. [ABSTRACT FROM AUTHOR]

Carbon pricing is a key component of current climate policy agendas. There are a variety of societal and health impacts from carbon pricing interventions (e.g. from improved air quality). A better understanding of potential health impacts and how they depend on context and policy design is crucial to improve the political feasibility and fairness of carbon pricing. Recent reviews have synthesized evidence on the effectiveness, equity and perceptions of carbon pricing and on the health co-benefits of mitigation. This review provides a narrative structured synthesis of the health impacts of carbon pricing. We identified 58 relevant publications of which all were modelling studies. We classify review findings into policy-relevant categories, synthesizing information on how carbon pricing affects health outcomes when implemented in different contexts, in isolation or as part of policy mixes. Findings suggest that internalization of health co-benefits in optimal price level estimates could lead to substantial mitigation in some regions. There are also opportunities to design carbon pricing to improve health outcomes, including through progressive or targeted use of revenues to improve food security, subsidize healthier diets or promote active transportation. Revenue use, price differentiation, market size and permit allocation of emissions trading schemes (ETS), and interaction with other public health or mitigation policies all influence health outcomes. Overall, the health impacts of carbon pricing are highly context-specific and further evidence is needed, particularly on health inequalities and ex-post analysis. However, existing evidence suggests that it is possible to design health-beneficial carbon pricing policies, thus enhancing policy acceptability and feasibility. Key policy insights: Internalizing health co-benefits into optimal carbon pricing estimates could lead to substantial emission reductions in some regions, although additional action is needed to encourage price levels compatible with climate targets Health co-benefits can be boosted through key elements of policy design including price differentiation across commodities and regions, revenue use or ETS design Careful policy design can enhance health gains at a small or insignificant cost in terms of climate mitigation effectiveness and efficiency. The implementation of carbon pricing as part of broader policy mixes with a strong focus on progressivity and equity is crucial to achieving health co-benefits [ABSTRACT FROM AUTHOR]

Background: Accurate reporting of outcomes is crucial for interpreting the results of randomized controlled trials (RCTs). However, selectively reporting outcomes in publications to achieve researchers' anticipated results still occurs frequently. This study aims to investigate the prevalence of selective reporting of outcomes in RCTs on treating acute ischemic stroke (AIS), identify factors contributing to this issue, and assess its potential impact on the degree and direction of intervention effect. Methods: A search was conducted in MEDLINE, Embase, and the Cochrane Library to collect interventional RCTs on AIS published from 2020 to 2022. Full texts of RCTs were reviewed, and only those reporting International Clinical Trials Registry Platform primary registry numbers were included. Registration information of the RCTs was extracted from the registry platforms and compared with the publications' details to assess the selective reporting of outcomes. Bayesian multilevel logistic regression was used to analyze the reasons behind selective reporting. Results: Among the total of 159 AIS RCTs identified, 82 (51.6%) were ultimately included, as they reported registration numbers, which encompassed 819 outcomes. Among them, 72 RCTs (87.8%) and 497 outcomes (60.7%) exhibited selective reporting. Omission-type selective reporting (downgrading, omitting, or ambiguously reporting) accounted for 36.4%, while addition-type selective reporting (upgrading, adding, or altering the measurement scope of outcomes) comprised 63.6%. Omission-type selective reporting correlated with negative results (OR: 7.39; 95% CI: 4.08—13.44), whereas addition-type selective reporting correlated with positive results (OR: 2.07; 95% CI: 1.34—3.26) and publication in journals that are not in the top quartile of the Journal Citation Reports (OR: 2.48; 95% CI: 1.15—5.38). Conclusions: Registered interventional AIS RCTs still face significant issues regarding selective reporting of outcomes. Therefore, it is necessary to further evaluate the influence of selective reporting bias on the positive results obtained from individual AIS RCTs and the systematic reviews based on these RCTs. [ABSTRACT FROM AUTHOR]

The product Bayes factor (PBF) synthesizes evidence for an informative hypothesis across heterogeneous replication studies. It can be used when fixed‐ or random effects meta‐analysis fall short. For example, when effect sizes are incomparable and cannot be pooled, or when studies diverge significantly in the populations, study designs, and measures used. PBF shines as a solution for small sample meta‐analyses, where the number of between‐study differences is often large relative to the number of studies, precluding the use of meta‐regression to account for these differences. Users should be mindful of the fact that the PBF answers a qualitatively different research question than other evidence synthesis methods. For example, whereas fixed‐effect meta‐analysis estimates the size of a population effect, the PBF quantifies to what extent an informative hypothesis is supported in all included studies. This tutorial paper showcases the user‐friendly PBF functionality within the bain R‐package. This new implementation of an existing method was validated using a simulation study, available in an Online Supplement. Results showed that PBF had a high overall accuracy, due to greater sensitivity and lower specificity, compared to random‐effects meta‐analysis, individual participant data meta‐analysis, and vote counting. Tutorials demonstrate applications of the method on meta‐analytic and individual participant data. The example datasets, based on published research, are included in bain so readers can reproduce the examples and apply the code to their own data. The PBF is a promising method for synthesizing evidence for informative hypotheses across conceptual replications that are not suitable for conventional meta‐analysis. [ABSTRACT FROM AUTHOR]

Aims: Epigenetics has significantly evolved and emerged as important players in the pathogenesis of neurodegenerative diseases. However, a scientometric synthesis of such changes over time is currently lacking. Methods: We conducted a comprehensive search of the Web of Science Core Collection from inception until November 5, 2022, using appropriate keywords. Our primary objective was to employ scientometric analysis to depict changes in keywords over time and to assess the structure and credibility of clusters. Additionally, we examined the network of research (countries, institutions, and authors) using CiteSpace and VOSviewer. Results: We identified 25 clusters with well-structured networks (Q = 0.82) and highly credible clustering (S = 0.91) from 16,181 articles published between 1999 and 2022. Our findings are as follows: (a) the literature and research interest concerning the epigenetics of neurodegenerative diseases are continuously growing; (b) the three most productive countries are the USA, China, and Germany; (c) international collaborative relationships exist, alongside small, isolated collaboration networks of individual institutions. Conclusion: The number and impact of global publications on the epigenetics of neurodegenerative diseases have expanded rapidly over the past 20 years. This review provides valuable guidelines for researchers interested in neurodegenerative diseases research. [ABSTRACT FROM AUTHOR]

Background: We conducted an NIHR-funded evidence synthesis project, reviewing evidence relating to interventions for perceptual disorders following stroke. This related paper describes how people with lived experience of stroke-related perceptual disorders contributed to and influenced the project, and identifies lessons for future review projects. Methods: We planned our patient and public involvement and engagement (PPIE) activities within a study protocol, described according to the domains of the ACTIVE framework; these were founded on principles for good practice in PPIE. Activities occurred across the lifespan of the project, consisting primarily of group discussions and voting to determine if there was consensus. To assess impact and individual experiences, we sought feedback using an evaluation form after each discussion, and conducted an online meeting at the end of the project to allow further reflection. Results: We recruited five people to a Lived Experience Group, including two stroke survivors and three carers. Members attended one face-to-face meeting during the development of the review. Subsequent activities were all held online due to the COVID-19 pandemic; with six online meetings, plus email interactions. Positive impacts of the Lived Experience Group on the reviews included clear definitions of key terms, selection of outcome measures, agreement on implications of review findings, and identification of research recommendations. Key challenges identified related to the complexity of the topic and challenges in the use of new online technology as a consequence of the COVID-pandemic. Conclusions: A number of lessons were learned during this project. Specific recommendations for future PPIE are to ensure that those involved have an opportunity to get to know one another, and to provide optional sessions to increase familiarity with online meeting software, clear explanations of the purpose of involvement and specific feedback after each activity. These lessons should be considered when planning the PPIE within future reviews. Plain English summary: We reviewed research into treatments for disorders of perception after stroke. These disorders reduce a person's ability to recognise and understand information from their senses. We involved people affected, to ensure that (i) their experiences were reflected and (ii) this complex topic was treated in a clear and understandable way. This paper discusses their involvement, the impact it had, and the lessons learnt. We involved five people affected, within a dedicated 'Lived Experience Group'. Two members were stroke survivors, while three were carers. Their activities spanned the whole duration of the project. An initial face-to-face meeting with the entire research team was followed by six online activities (because of COVID-19 related restrictions) and email communication. The Lived Experience Group had a clear impact on the review. This included creating clear definitions of key terms, selecting which tests of treatment effectiveness were most important, determining the real-world meaning of the review findings, and agreeing the recommendations for stroke survivors, clinicians and researchers based on these findings. Key challenges were the complexity of the topic and terminology, the difficulty of using new technology, and the loss of personal connections arising from this mode of working. This study demonstrates how online involvement can successfully engage stroke survivors in research. It also suggests strategies to improve future work, such as providing time and support to both practice new technologies, and for social engagement. [ABSTRACT FROM AUTHOR]

Ecological stability is a vital component of natural ecosystems that can inform effective conservation and ecosystem management. Furthermore, there is increasing interest in making comparisons of stability values across sites, systems and taxonomic groups, often using comparative synthetic approaches, such as meta‐analysis. However, these synthetic approaches often compare/contrast systems where measures of stability mean very different things to the taxa involved. Here, we present results from theoretical models and empirical data to illustrate how differences in growth rates among taxa influence four widely used metrics of ecological stability of species abundances responding to pulse perturbations: resilience, recovery, resistance and temporal stability. We refer to these classic growth‐rate‐dependent metrics as 'realised' stability. We show that realised resilience and realised temporal stability vary as a function of organisms' growth rates; realised recovery depends on the relation between growth rate and sampling duration; and realised resistance depends on the relation between growth rate and sampling interval. To account for these influences, we introduce metrics intended to be more independent of growth rates, which we refer to as 'intrinsic' stability. Intrinsic stability can be used to summarise the overall effects of a disturbance, separately from internal recovery processes – thereby allowing more general comparisons of disturbances across organisms and contexts. We argue that joint consideration of both realised and intrinsic stability is important for future comparative studies. [ABSTRACT FROM AUTHOR]

Background: To inform global ambitions to end AIDS, evaluation of progress toward HIV incidence reduction requires robust methods to measure incidence. Although HIV diagnosis date in routine HIV/ AIDS surveillance systems are often used as a surrogate marker for incidence, it can be misleading if acquisition of transmission occurred years before testing. Other information present in data such as antibody testing dates, avidity testing result, and CD4 counts can assist, but the degree of missing data is often prohibitive. Methods: We constructed a Bayesian statistical model to estimate the annual proportion of first ever HIV diagnoses in Scotland (period 2015–2019) that represent recent HIV infection (ie, occurring within the previous 3–4 months) and incident HIV infection (ie, infection within the previous 12 months), by synthesizing avidity testing results and surveillance data on the interval since last negative HIV test. Results: Over the 5-year analysis period, the model-estimated proportion of incident infection was 43.9% (95% CI: 40.9 to 47.0), and the proportion of recent HIV infection was 21.6% (95% CI: 19.1 to 24.1). Among the mode of HIV acquisition categories, the highest proportion of recent infection was estimated for people who inject drugs: 27.4% (95% CI: 20.4 to 34.4). Conclusions: The Bayesian approach is appropriate for the high prevalence of missing data that can occur in routine surveillance data sets. The proposed model will aid countries in improving their understanding of the number of people who have recently acquired their infection, which is needed to progress toward the goal of HIV transmission elimination. [ABSTRACT FROM AUTHOR]

Background: Systematic review or systematic literature review (SLR) methodologies are a powerful tool for evidence‐based decision making. The method originated in the medical sciences but has since been adopted by other disciplines, including engineering education (EE). Purpose: We aimed to answer two research questions: (i) To what extent is the SLR research method being applied in EE? (ii) How closely are SLRs published in EE following established reporting guidelines for the methodology? Scope/Method: We searched Inspec, Compendex, and ERIC for engineering‐related SLRs and meta‐analyses (MAs). We included English language papers that contained an explicit SLR search, or where it appeared the methodology was intended by the author(s). We completed a data extraction process for 21 descriptive and quality‐related items, including engineering discipline, which allowed us to identify the EE studies analyzed in this article. Results: This sub‐analysis presents the results of 276 EE‐related reviews. We found the use of SLR/MA methods is growing in EE, with 93% of papers published during 2015–2022. However, we found that authors are not generally following established guidelines for reporting their methods and findings. Conclusions: Not following the best practices for conducting and reporting SLRs can result in the presentation of incorrect summaries and analyses due to missed evidence. Including search experts (e.g., librarians) trained in conducting SLRs can improve review quality. There is also an opportunity for EE‐related publishers to recruit experts trained in conducting SLRs as peer reviewers to participate in evaluating submitted reviews. [ABSTRACT FROM AUTHOR]

Background: Given the growing population of older adults globally, e-Health plays an indispensable role in the chronic disease management of multimorbidity. However, qualitative evidence that synthesizes the experiences of older adults with multimorbidity using e-Health service is currently lacking. The objective was to explore the experiences and perceptions of e-Health care in community-based settings among the older adults with multimorbidity. Methods: Seven electronic databases including PubMed, The Cochrane Library, Cumulative Index to Nursing and Allied Health Literature, Embase, Web of Science, China National Knowledge Infrastructure, and Chinese BioMedical Literature were searched, and the search was limited to studies from inception to September 1, 2023. Screening, data extraction, and quality appraisal were conducted independently by two reviewers. Thomas and Harden's thematic synthesis methodology was applied to synthesize the original themes. The methodological quality of included studies was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Research, and the confidence of synthesized themes was evaluated by the Confidence in the Evidence from Reviews of Qualitative Research approaches. Results: Ten studies with moderate methodological quality met eligibility criteria and were included finally. Studies were conducted in four countries with 235 participants who were living with multiple chronic conditions. Among the 10 included studies, 37 credible findings were extracted and interpreted into 3 synthesized themes and 12 subthemes: (1) advantages and benefits perceived during e-Health service, (2) multidimensional challenges and negative experience posed by e-Health service, and (3) preferences, suggestions, and expectations for future e-Health improvement. The confidence in the majority of the three final synthesized themes was rated between "low" and "moderate" scales. Conclusions: The findings of this study provide new insights into implementing tailored e-Health care for older adults with multimorbidity. Further research should emphasize on realizing the potential value of e-Health service based on users' needs and perspectives to promote age-friendliness in geriatric practice. [ABSTRACT FROM AUTHOR]

Patient-reported outcome measures (PROMs) have emerged as a promising approach to involve patients in their treatment process. Beyond serving as outcome measures, PROMs can be applied to provide feedback to healthcare providers and patients, thereby offering valuable insights that can improve health outcomes and care processes. This overview offers a comprehensive synthesis of the effects of PROM feedback, contributing to the evidence-based discussion on PROMs' potential to enhance patient care. Following Cochrane Collaboration recommendations, this overview included literature reviews across diverse treatment areas, investigating the impact of PROM feedback on patient health outcomes (including quality of life, symptoms, or survival) and care process outcomes (including communication, symptom identification, or clinical practice). The methodological quality of the evidence was assessed with a modified version of A Measurement Tool to Assess Systematic Reviews 2, and the potential overlap of primary studies was quantified. Results were narratively synthesized. Forty reviews grouped into 4 categories of treatment areas were included. Overall, their methodological quality was low. The overall overlap of primary studies was 2.2%, reaching up to 15.7% within specific treatment areas. The results indicate that PROM feedback may enhance the quality-of-care processes, whereas its effects on patient health outcomes remained less conclusive. PROM feedback positively influences the interaction between physicians and patients across the included treatment areas. Further research is needed to comprehend the trickle-down effects of PROM feedback and how to enhance its potential in yielding health benefits for patients. • Primary studies, reviews, and overviews of Patient-Reported Outcome Measure (PROM) feedback are already present, but their research focus is often limited, primarily concentrating on specific treatment areas or individual outcomes. • This comprehensive overview assesses the influence of PROM feedback on both "patient health outcomes," such as quality of life, physical or mental symptoms, and "care process outcomes," such as communication or symptom identification across treatment areas, with no restrictions on single outcome parameters. Additionally, it provides a detailed evaluation of the reviews' methodological quality. • The results indicate that PROM feedback may enhance care process outcomes, whereas its effects on patient health outcomes remained less definitive. For a comprehensive evaluation of effects on treatment quality, clinical parameters should also be considered. Future research should clearly identify the feedback characteristics so that beneficial elements of the feedback system can be identified and PROM feedback interventions continuously improved. [ABSTRACT FROM AUTHOR]

One of the guiding ideas in modern environmentalist thought is that we shouldn’t interfere with nature. It’s better to leave it alone. Many of the arguments offered in favor of this presumption against environmental interference are epistemic. One such argument focuses on ineffectiveness. It says that conservation interventions often do not accomplish their goals. A second argument says that well-intentioned interference in nature produces many harmful unintended consequences. I show that these arguments do not justify the presumption against environmental interference. Both arguments depend on stronger claims, such as the claim that conservation interventions do more harm than good overall. Yet, evidence-based conservation studies do not support the idea that conservation interventions generally do not work, or that they do more harm than good. These facts seriously undermine the presumption against environmental interference. [ABSTRACT FROM AUTHOR]

Childhood cancer is an urgent priority in Egypt, owing to a large number of children with cancer, the great need and demand for paediatric oncology services, limited resources/ funds and inferior survival outcomes. Therefore, an overview of the status of childhood cancer care in Egypt and an evidence-based approach towards optimal utilisation of resources/funds to improve this care are needed. This paper summarises key evidence about childhood cancer care and outcomes in Egypt. We conducted a narrative literature review using a structured search strategy of the MEDLINE database through the PubMed interface. All relevant evidence was summarised under five main sub-topics: (1) burden of childhood cancer in Egypt; (2) treatment approaches; (3) health outcomes; (4) costs and cost-effectiveness of treatment; and (5) barriers and facilitators to optimal childhood cancer care. We found high estimates of disease burden of childhood cancer in Egypt. Furthermore, childhood cancer treatment in Egypt is based on either implementing intensity- regulated protocols or adopting international protocols with or without adaptations to local contexts, leading to varying standards of care among the different treating centres. Limited data about the survival outcomes, costs and cost-effectiveness of treatment exist, although high-quality data from retrospective cohort studies were published from a large paediatric oncology centre (Children's Cancer Hospital Egypt--57357). As Egypt joins the WHO Global Initiative for Childhood Cancers as a focus country, it is prepared to move towards streamlining national efforts to implement a national childhood cancer plan to advance care, improve health outcomes and optimise resource use. Through these efforts, Egypt could become a beacon of hope and a role model to other low- and middle-income countries seeking to improve their childhood cancer care. [ABSTRACT FROM AUTHOR]

Robust estimates of the relative efficacies of alternative management interventions are essential for developing evidence‐informed fisheries bycatch policy. Bycatch is a major threat to the conservation of albatrosses and other pelagic seabirds. Branchline weighting is one approach prescribed by regional fisheries management organisations and the Agreement on the Conservation of Albatrosses and Petrels to reduce seabird bycatch in pelagic longline fisheries. We used a Bayesian multilevel network meta‐regression modelling approach to conduct the first synthesis of available evidence to assess the relative efficacies at mitigating seabird bycatch of alternative pelagic longline weighting designs. Unlike conventional pairwise meta‐analysis, network meta‐analysis enables the simultaneous comparison of multiple interventions within a coherent modelling framework. There was a > 97% probability that all weighting designs significantly reduced seabird bycatch compared to a reference design with no weight within 5 m of the hook. Nonetheless, some weighting designs were significantly more effective at reducing seabird bycatch than others—for instance, the 2 designs with weights >60 g and >1 m from the hook performed the best with >93% probability that those 2 designs performed significantly better than 2 more commonly used designs with less weight but attached closer to the hook. These two best performing designs reduced seabird bycatch by ca 89% relative to the reference design. These relative efficacies and rankings, when combined with other performance criteria such as costs to commercial viability and crew safety, support robust evaluations of alternative bycatch management strategies. [ABSTRACT FROM AUTHOR]

Background: Systematic reviews (SRs) are time-consuming and labor-intensive to perform. With the growing number of scientific publications, the SR development process becomes even more laborious. This is problematic because timely SR evidence is essential for decision-making in evidence-based healthcare and policymaking. Numerous methods and tools that accelerate SR development have recently emerged. To date, no scoping review has been conducted to provide a comprehensive summary of methods and ready-to-use tools to improve efficiency in SR production. Objective: To present an overview of primary studies that evaluated the use of ready-to-use applications of tools or review methods to improve efficiency in the review process. Methods: We conducted a scoping review. An information specialist performed a systematic literature search in four databases, supplemented with citation-based and grey literature searching. We included studies reporting the performance of methods and ready-to-use tools for improving efficiency when producing or updating a SR in the health field. We performed dual, independent title and abstract screening, full-text selection, and data extraction. The results were analyzed descriptively and presented narratively. Results: We included 103 studies: 51 studies reported on methods, 54 studies on tools, and 2 studies reported on both methods and tools to make SR production more efficient. A total of 72 studies evaluated the validity (n = 69) or usability (n = 3) of one method (n = 33) or tool (n = 39), and 31 studies performed comparative analyses of different methods (n = 15) or tools (n = 16). 20 studies conducted prospective evaluations in real-time workflows. Most studies evaluated methods or tools that aimed at screening titles and abstracts (n = 42) and literature searching (n = 24), while for other steps of the SR process, only a few studies were found. Regarding the outcomes included, most studies reported on validity outcomes (n = 84), while outcomes such as impact on results (n = 23), time-saving (n = 24), usability (n = 13), and cost-saving (n = 3) were less often evaluated. Conclusion: For title and abstract screening and literature searching, various evaluated methods and tools are available that aim at improving the efficiency of SR production. However, only few studies have addressed the influence of these methods and tools in real-world workflows. Few studies exist that evaluate methods or tools supporting the remaining tasks. Additionally, while validity outcomes are frequently reported, there is a lack of evaluation regarding other outcomes. [ABSTRACT FROM AUTHOR]

Background: Evidence synthesis organisations are trying to meet commissioners' needs for rapid responses to their evidence synthesis commissions. In this project we piloted an intensive process, working to complete evidence syntheses within six-weeks, rather than the standard lead time of 4–6 months. Our objective was to explore how researchers experience working intensively, identify barriers and facilitators, and determine how a more intensive approach to evidence synthesis could be more systematically introduced in the future. Methods: In a pre-planning phase, an intensive work group was established, and two commissions were selected for this pilot project. The evidence synthesis process was divided into two phases: planning and intensive. The planning phase, involved scheduling the intensive phase, exploring new digital tools, and identifying peer reviewers. The intensive phase encompassed the entire evidence synthesis process. Two review teams were formed, each with a team lead supported by a process lead and leadership contact point. Throughout the project, teams engaged in reflective meetings to evaluate and adjust processes as needed. Results: During the planning phase, teams identified significant uncertainties regarding scopes, research questions, and inclusion criteria. To address this, they engaged with commissioners earlier than originally planned, clarified these aspects, and prepared protocols. Despite some minor deviations from the original plan, both reviews were completed on schedule, with one team expanding their scope due to the absence of eligible studies. Teams operated flexibly, held regular meetings, and found the process seamless due to fewer interruptions. Machine learning tools facilitated rapid study selection. The process lead role, created to guide and evaluate the project, proved beneficial, providing structure and support, although clearer role delineation with the leadership contact point could have improved efficiency. Conclusions: Overall, the intensive process fostered focus and productivity, allowing teams to manage short-term deliverables effectively. The researchers preferred working intensively with one evidence synthesis over being involved with many projects at the same time. They felt that time use was more effective, and they were able to complete the tasks in a focused way. However, there are several implications that should be considered before implementing an intensive approach in future evidence syntheses. [ABSTRACT FROM AUTHOR]

Practice-based case studies that describe learning from implementation are a useful source of evidence for policy makers, practitioners and researchers. Despite the value of narratives developed in context as a form of experiential or applied evidence, little is known about appropriate qualitative review and synthesis methods to deal with multiple practice-based case studies. This paper reports on a methodological study to develop and pilot a synthesis method using a sample of community wellbeing case studies focused on interventions to improve community infrastructure. The study was conducted in four interlinked phases: (i) literature review to scope synthesis methods (ii) piloting search and selection methods to identify a sample of relevant practice-based case studies that reported experiential learning (iii) undertaking cross case analysis and qualitative synthesis based on framework analysis methods (iv) review and reflection to produce a summative account of the method and agreed definition. The main output from the study was a staged approach to qualitative synthesis of practice-based case studies based on seven steps, which move from identification of a conceptual framework through to producing a narrative report. The potential transferability of this approach and its application in research and policy are critically discussed. Synthesis of case studies derived from community-based interventions could address knowledge gaps in the formal evidence base. While further methodological development is warranted, it is argued that study results form a credible qualitative framework for synthesising practice-based evidence. [ABSTRACT FROM AUTHOR]

Background: Genome-wide association studies have enabled Mendelian randomization analyses to be performed at an industrial scale. Two-sample summary data Mendelian randomization analyses can be performed using publicly available data by anyone who has access to the internet. While this has led to many insightful papers, it has also fuelled an explosion of poor-quality Mendelian randomization publications, which threatens to undermine the credibility of the whole approach. Findings: We detail five pitfalls in conducting a reliable Mendelian randomization investigation: (1) inappropriate research question, (2) inappropriate choice of variants as instruments, (3) insufficient interrogation of findings, (4) inappropriate interpretation of findings, and (5) lack of engagement with previous work. We have provided a brief checklist of key points to consider when performing a Mendelian randomization investigation; this does not replace previous guidance, but highlights critical analysis choices. Journal editors should be able to identify many low-quality submissions and reject papers without requiring peer review. Peer reviewers should focus initially on key indicators of validity; if a paper does not satisfy these, then the paper may be meaningless even if it is technically flawless. Conclusions: Performing an informative Mendelian randomization investigation requires critical thought and collaboration between different specialties and fields of research. [ABSTRACT FROM AUTHOR]

Aim: In line with the publication of clinical information related to the therapeutic process of repetitive transcranial magnetic stimulation (rTMS) and the updating of relevant treatment guidelines, the present meta-analysis study was designed and conducted to determine the effect of repetitive transcranial magnetic stimulation (rTMS) on the Hamilton Depression Rating Scale-17 (HDRS-17) criterion in patients with major depressive disorder (MDD) without psychotic features. Methods: In this study, a systematic search was conducted in electronic databases such as PubMed [Medline], Scopus, Web of Science, Embase, Ovid, Cochrane Library, and ClinicalTrials. gov using relevant keywords. The search period in this study was from January 2000 to January 2022, which was updated until May 2023. Randomized controlled trials (RCTs) that determined the effect of repetitive transcranial magnetic stimulation (rTMS) on the Hamilton Depression Rating Scale-17 (HDRS-17) criterion in patients with major depressive disorder (MDD) without psychotic features were included in the analysis. The quality of the included RCTs was assessed using the Cochrane Risk of Bias checklist. Statistical analyses were performed using STATA (Version 16) and RevMan (Version 5). Results: Following the combination of results from 16 clinical trial studies in the present meta-analysis, it was found that the mean Hamilton Depression Rating Scale-17 (HDRS-17) in patients with major depressive disorder (MDD) decreases by an average of 1.46 units (SMD: -1.46; % 95 CI: -1.65, -1.27, I square: 45.74%; P heterogeneity: 0.56). Subgroup analysis results indicated that the standardized mean difference of Hamilton Depression Rating Scale-17 (HDRS-17) varied based on the number of treatment sessions: patients receiving 10 or fewer repetitive transcranial magnetic stimulation (rTMS) sessions showed a mean Hamilton Depression Rating Scale-17 (HDRS-17) reduction of 2.60 units (SMD: -2.60; % 95 CI: -2.86, -2.33, I square: 55.12%; P heterogeneity: 0.55), while those receiving 11 to 20 sessions showed a mean Hamilton Depression Rating Scale-17 (HDRS-17) reduction of 0.28 units (SMD: -0.28; % 95 CI: -0.65, -0.09, I square: 39.91%; P heterogeneity: 0.89). Conclusion: In conclusion, our meta-analysis demonstrates the efficacy of repetitive transcranial magnetic stimulation (rTMS) in reducing depressive symptoms in major depressive disorder (MDD) patients. The complex results of subgroup analysis revealed insight on the possible benefits of a more focused strategy with fewer sessions, as well as the impact of treatment session frequency. These findings add to our understanding of repetitive transcranial magnetic stimulation (rTMS) as a therapeutic intervention for the treatment of major depressive illnesses. [ABSTRACT FROM AUTHOR]

Enhancing the reliability of literature reviews and evidence synthesis is crucial for advancing the transformation of agriculture and food (agri-food) systems as well as for informed decisions and policy making. In this perspective, we argue that evidence syntheses in the field of agri-food systems research often suffer from a suite of methodological limitations that substantially increase the risk of bias, i.e., publication and selection bias, resulting in unreliable and potentially flawed conclusions and, consequently, poor decisions (e.g., policy direction, investment, research foci). We assessed 926 articles from the Collaboration for Environmental Evidence Database of Evidence Reviews (CEEDER) and recent examples from agri-food systems research to support our reasoning. The analysis of articles from CEEDER (n = 926) specifically indicates poor quality (Red) in measures to minimize subjectivity during critical appraisal (98% of all reviews), application of the eligibility criteria (97%), cross-checking of extracted data by more than one reviewer (97%), critical appraisal of studies (88%), establishment of an a priori method/protocol (86%), and transparent reporting of eligibility decisions (65%). Additionally, deficiencies (Amber) were found in most articles (>50%) regarding the investigation and discussion of variability in study findings (89%), comprehensiveness of the search (78%), definition of eligibility criteria (72%), search approach (64%), reporting of extracted data for each study (59%), consideration and discussion of the limitations of the synthesis (56%), documentation of data extraction (54%) and regarding the statistical approach (52%). To enhance the quality of evidence synthesis in agri-food science, review authors should use tried-and-tested methodologies and publish peer-reviewed a priori protocols. Training in evidence synthesis methods should be scaled, with universities playing a crucial role. It is the shared duty of research authors, training providers, supervisors, reviewers, and editors to ensure that rigorous and robust evidence syntheses are made available to decision-makers. We argue that all these actors should be cognizant of these common mistakes to avoid publishing unreliable syntheses. Only by thinking as a community can we ensure that reliable evidence is provided to support appropriate decisionmaking in agri-food systems science. [ABSTRACT FROM AUTHOR]

Study Objectives: The Federal Interagency Traumatic Brain Injury Research (FITBIR) Informatics System contains individual-patient-level traumatic brain injury (TBI) data, which when combined, allows for the examination of rates and outcomes for key subpopulations at risk for developing sleep disturbance. Methods: This proof-of-concept study creates a model system for harmonizing data (i.e., combining and standardizing data) across FITBIR studies for participants with and without a history of TBI to estimate rates of sleep disturbance and identify risk factors. Results: Three studies were eligible for harmonization (N = 1753). Sleep disturbance was common among those with a history of mild TBI (63%). Individuals with mild TBI were two to four times more likely to have sleep disturbance compared to those with no history of TBI. Conclusions: This study established methods, harmonization code, and meta-databases that are publicly available on the FITBIR website. We demonstrated how the harmonization of FITBIR studies can answer TBI research questions, showing that associations between TBI and sleep disturbance may be influenced by demographic factors. [ABSTRACT FROM AUTHOR]

There has been recent discussion in Australia and New Zealand concerning the utility of Clinical Practice Guidelines (CPGs) and the role of the Royal Australian and New Zealand College of Psychiatrists (RANZCP) in their development. The College Board therefore established a Steering Group (SG) to oversee an exploration of options and produce recommendations about contemporary approaches to the development of high-quality evidence-based clinical practice guidance for psychiatry. This paper outlines the SG's conclusions and recommendations, as well as the underlying methods and reasoning. In particular, we discuss best practice and recent developments in the synthesis of research evidence. Account has been taken of the opportunities offered by digital technologies, the proliferation of clinical evidence and awareness of the gains to be made by increased inclusion of lived-experience perspectives. It is recommended that the broader concept of best practice resources (BPRs) as now emphasised in so many fields of service is the most appropriate starting point for the College's role in this area especially as the expertise of the College and its fellows lends itself to the development of a range of BPRs. In conclusion, contemporary guidance needs to be tailored to the requirements of the practitioners seeking it, to articulate the real-world needs and experiences of patients, and to be delivered in a contemporary format that is responsive to rapidly emerging evidence. The experience in Australia and New Zealand may have implications elsewhere for the development of CPGs and BPRs more broadly. [ABSTRACT FROM AUTHOR]

Naturalistic body stimuli are necessary for understanding many aspects of human psychology, yet there are no centralized databases of body stimuli. Furthermore, there are a high number of independently developed stimulus sets lacking in standardization and reproducibility potential, and a general lack of organization, contributing to issues of both replicability and generalizability in body-related research. We conducted a comprehensive scoping review to index and explore existing naturalistic whole-body stimuli. Our research questions were as follows: (1) What sets of naturalistic human whole-body stimuli are present in the literature? And (2) On what factors (e.g., demographics, emotion expression) do these stimuli vary? To be included, stimulus sets had to (1) include human bodies as stimuli; (2) be photographs, videos, or other depictions of real human bodies (not computer generated, drawn, etc.); (3) include the whole body (defined as torso, arms, and legs); and (4) could include edited images, but still had to be recognizable as human bodies. We identified a relatively large number of existing stimulus sets (N = 79) which offered relative variability in terms of main manipulated factors and the degree of visual information included (i.e., inclusion of heads and/or faces). However, stimulus sets were demographically homogenous, skewed towards White, young adult, and female bodies. We identified significant issues in reporting and availability practices, posing a challenge to the generalizability, reliability, and reproducibility of body-related research. Accordingly, we urge researchers to adopt transparent and accessible practices and to take steps to diversify body stimuli. [ABSTRACT FROM AUTHOR]

Background: Causal graphs are an important tool for covariate selection but there is limited applied research on how best to create them. Here, we used data from the Coronary Drug Project trial to assess a range of approaches to directed acyclic graph (DAG) creation. We focused on the effect of adherence on mortality in the placebo arm, since the true causal effect is believed with a high degree of certainty. Methods: We created DAGs for the effect of placebo adherence on mortality using different approaches for identifying variables and links to include or exclude. For each DAG, we identified minimal adjustment sets of covariates for estimating our causal effect of interest and applied these to analyses of the Coronary Drug Project data. Results: When we used only baseline covariate values to estimate the cumulative effect of placebo adherence on mortality, all adjustment sets performed similarly. The specific choice of covariates had minimal effect on these (biased) point estimates, but including nonconfounding prognostic factors resulted in smaller variance estimates. When we additionally adjusted for time-varying covariates of adherence using inverse probability weighting, covariates identified from the DAG created by focusing on prognostic factors performed best. Conclusion: Theoretical advice on covariate selection suggests that including prognostic factors that are not exposure predictors can reduce variance without increasing bias. In contrast, for exposure predictors that are not prognostic factors, inclusion may result in less bias control. Our results empirically confirm this advice. We recommend that hand-creating DAGs begin with the identification of all potential outcome prognostic factors. [ABSTRACT FROM AUTHOR]

There is an increasing consensus that climate change undermines human security by exacerbating existing challenges, acting as a "threat multiplier". Bangladesh is a climate hot spot due to its geographical location, dense population and vulnerable socio-economic infrastructure. Although there is an increasing number of studies on the impacts of climate change in Bangladesh, aggregated research that combines this evidence and provides a comprehensive overview is lacking. The aim of this research is to thoroughly investigate the characteristics of the academic literature on the complex pathways through which climate variability affects different components of human security in Bangladesh, allowing for determination of the trends and research gaps, as well as whether they lead to conflict or cooperation. We used a systematic mapping methodology to search and screen 1839 publications in Web of Science, including 320 publications for the final synthesis. We found a predominant research focus on rural areas, especially in the southwestern region, with declining crop yield, economic loss, migration, water shortage, food scarcity and health hazards being the highlighted impacts of climate change for Bangladesh. The impacts on food, economic, environmental, health and water security have been well studied, but we found significant research gaps in some human security components, especially energy security. Women and the economically disadvantaged are disproportionately affected, and the causal pathways between conflict or cooperation and the ever-changing climate lack research efforts, implying a dire need to focus on under-researched areas before they become more complex and difficult to address. Policies and interventions should prioritise climate-resilient agricultural practices and infrastructure in high-risk areas, building local capacities and integrating climate risk assessments into urban planning, considering the high influx of environmental migrants. This systematic map provides a foundation for future longitudinal studies, establishes a baseline for this era for future comparisons and serves as a reliable database for relevant stakeholders and policy makers. [ABSTRACT FROM AUTHOR]

Abstract Background Accurate reporting of outcomes is crucial for interpreting the results of randomized controlled trials (RCTs). However, selectively reporting outcomes in publications to achieve researchers’ anticipated results still occurs frequently. This study aims to investigate the prevalence of selective reporting of outcomes in RCTs on treating acute ischemic stroke (AIS), identify factors contributing to this issue, and assess its potential impact on the degree and direction of intervention effect. Methods A search was conducted in MEDLINE, Embase, and the Cochrane Library to collect interventional RCTs on AIS published from 2020 to 2022. Full texts of RCTs were reviewed, and only those reporting International Clinical Trials Registry Platform primary registry numbers were included. Registration information of the RCTs was extracted from the registry platforms and compared with the publications’ details to assess the selective reporting of outcomes. Bayesian multilevel logistic regression was used to analyze the reasons behind selective reporting. Results Among the total of 159 AIS RCTs identified, 82 (51.6%) were ultimately included, as they reported registration numbers, which encompassed 819 outcomes. Among them, 72 RCTs (87.8%) and 497 outcomes (60.7%) exhibited selective reporting. Omission-type selective reporting (downgrading, omitting, or ambiguously reporting) accounted for 36.4%, while addition-type selective reporting (upgrading, adding, or altering the measurement scope of outcomes) comprised 63.6%. Omission-type selective reporting correlated with negative results (OR: 7.39; 95% CI: 4.08—13.44), whereas addition-type selective reporting correlated with positive results (OR: 2.07; 95% CI: 1.34—3.26) and publication in journals that are not in the top quartile of the Journal Citation Reports (OR: 2.48; 95% CI: 1.15—5.38). Conclusions Registered interventional AIS RCTs still face significant issues regarding selective reporting of outcomes. Therefore, it is necessary to further evaluate the influence of selective reporting bias on the positive results obtained from individual AIS RCTs and the systematic reviews based on these RCTs.

Abstract Background We conducted an NIHR-funded evidence synthesis project, reviewing evidence relating to interventions for perceptual disorders following stroke. This related paper describes how people with lived experience of stroke-related perceptual disorders contributed to and influenced the project, and identifies lessons for future review projects. Methods We planned our patient and public involvement and engagement (PPIE) activities within a study protocol, described according to the domains of the ACTIVE framework; these were founded on principles for good practice in PPIE. Activities occurred across the lifespan of the project, consisting primarily of group discussions and voting to determine if there was consensus. To assess impact and individual experiences, we sought feedback using an evaluation form after each discussion, and conducted an online meeting at the end of the project to allow further reflection. Results We recruited five people to a Lived Experience Group, including two stroke survivors and three carers. Members attended one face-to-face meeting during the development of the review. Subsequent activities were all held online due to the COVID-19 pandemic; with six online meetings, plus email interactions. Positive impacts of the Lived Experience Group on the reviews included clear definitions of key terms, selection of outcome measures, agreement on implications of review findings, and identification of research recommendations. Key challenges identified related to the complexity of the topic and challenges in the use of new online technology as a consequence of the COVID-pandemic. Conclusions A number of lessons were learned during this project. Specific recommendations for future PPIE are to ensure that those involved have an opportunity to get to know one another, and to provide optional sessions to increase familiarity with online meeting software, clear explanations of the purpose of involvement and specific feedback after each activity. These lessons should be considered when planning the PPIE within future reviews.

Meng Zheng,1 Chongfang Meng,2 Qi Zhang,3 Xiang Yan,1 Na Li1 1Dermatology Department of the First Affiliated Hospital of Kunming Medical University, Kunming, Yunan, People’s Republic of China; 2Department of Oncology, First Affiliated Hospital of Kunming Medical University, Kunming, Yunan, People’s Republic of China; 3Nursing Department of Zhongshan Hospital Affiliated to Fudan University, Shanghai, People’s Republic of ChinaCorrespondence: Na Li, Dermatology Department of the First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, Wuhua District, Kunming, Yunnan, People’s Republic of China, Email 4845878@qq.comObjective: This study aims to systematically search, screen, evaluate, and synthesize evidence related to discharge preparation for elderly chemotherapy patients, providing an evidence-based reference for implementing discharge preparation services for this demographic.Methods: Systematic searches were conducted on databases including BMJ Best Clinical Practice, JBI Library, UpToDate Clinical Advisor, Cochrane Library, and relevant guideline websites. The collected literature comprised thematic summaries, clinical practice guidelines, technical reports, expert consensus, and systematic reviews related to discharge preparation for elderly chemotherapy patients. Relevant evaluation tools were selected based on the type of literature to assess methodological quality, and the evidence was extracted, summarized, and organized.Results: Fifteen pieces of evidence were selected according to inclusion and exclusion criteria, including one clinical decision, two expert consensuses, six systematic reviews, two meta-analyses, and four guidelines. Twenty-nine pieces of evidence were summarized across four domains: assessment, planning, implementation, and evaluation.Conclusion: The summarized evidence provides a reliable basis for implementing evidence-based discharge preparation services for elderly chemotherapy patients, laying a foundation for future clinical practice applications. Based on the evidence content and relevant literature, this paper explores the screening and evaluation tools applicable for use in clinical practice.Keywords: elderly, chemotherapy, discharge preparation, evidence-based nursing, evidence synthesis, review

Abstract Background Evidence synthesis organisations are trying to meet commissioners’ needs for rapid responses to their evidence synthesis commissions. In this project we piloted an intensive process, working to complete evidence syntheses within six-weeks, rather than the standard lead time of 4–6 months. Our objective was to explore how researchers experience working intensively, identify barriers and facilitators, and determine how a more intensive approach to evidence synthesis could be more systematically introduced in the future. Methods In a pre-planning phase, an intensive work group was established, and two commissions were selected for this pilot project. The evidence synthesis process was divided into two phases: planning and intensive. The planning phase, involved scheduling the intensive phase, exploring new digital tools, and identifying peer reviewers. The intensive phase encompassed the entire evidence synthesis process. Two review teams were formed, each with a team lead supported by a process lead and leadership contact point. Throughout the project, teams engaged in reflective meetings to evaluate and adjust processes as needed. Results During the planning phase, teams identified significant uncertainties regarding scopes, research questions, and inclusion criteria. To address this, they engaged with commissioners earlier than originally planned, clarified these aspects, and prepared protocols. Despite some minor deviations from the original plan, both reviews were completed on schedule, with one team expanding their scope due to the absence of eligible studies. Teams operated flexibly, held regular meetings, and found the process seamless due to fewer interruptions. Machine learning tools facilitated rapid study selection. The process lead role, created to guide and evaluate the project, proved beneficial, providing structure and support, although clearer role delineation with the leadership contact point could have improved efficiency. Conclusions Overall, the intensive process fostered focus and productivity, allowing teams to manage short-term deliverables effectively. The researchers preferred working intensively with one evidence synthesis over being involved with many projects at the same time. They felt that time use was more effective, and they were able to complete the tasks in a focused way. However, there are several implications that should be considered before implementing an intensive approach in future evidence syntheses.

Abstract Background Systematic reviews (SRs) are time-consuming and labor-intensive to perform. With the growing number of scientific publications, the SR development process becomes even more laborious. This is problematic because timely SR evidence is essential for decision-making in evidence-based healthcare and policymaking. Numerous methods and tools that accelerate SR development have recently emerged. To date, no scoping review has been conducted to provide a comprehensive summary of methods and ready-to-use tools to improve efficiency in SR production. Objective To present an overview of primary studies that evaluated the use of ready-to-use applications of tools or review methods to improve efficiency in the review process. Methods We conducted a scoping review. An information specialist performed a systematic literature search in four databases, supplemented with citation-based and grey literature searching. We included studies reporting the performance of methods and ready-to-use tools for improving efficiency when producing or updating a SR in the health field. We performed dual, independent title and abstract screening, full-text selection, and data extraction. The results were analyzed descriptively and presented narratively. Results We included 103 studies: 51 studies reported on methods, 54 studies on tools, and 2 studies reported on both methods and tools to make SR production more efficient. A total of 72 studies evaluated the validity (n = 69) or usability (n = 3) of one method (n = 33) or tool (n = 39), and 31 studies performed comparative analyses of different methods (n = 15) or tools (n = 16). 20 studies conducted prospective evaluations in real-time workflows. Most studies evaluated methods or tools that aimed at screening titles and abstracts (n = 42) and literature searching (n = 24), while for other steps of the SR process, only a few studies were found. Regarding the outcomes included, most studies reported on validity outcomes (n = 84), while outcomes such as impact on results (n = 23), time-saving (n = 24), usability (n = 13), and cost-saving (n = 3) were less often evaluated. Conclusion For title and abstract screening and literature searching, various evaluated methods and tools are available that aim at improving the efficiency of SR production. However, only few studies have addressed the influence of these methods and tools in real-world workflows. Few studies exist that evaluate methods or tools supporting the remaining tasks. Additionally, while validity outcomes are frequently reported, there is a lack of evaluation regarding other outcomes.

Abstract Background Genome-wide association studies have enabled Mendelian randomization analyses to be performed at an industrial scale. Two-sample summary data Mendelian randomization analyses can be performed using publicly available data by anyone who has access to the internet. While this has led to many insightful papers, it has also fuelled an explosion of poor-quality Mendelian randomization publications, which threatens to undermine the credibility of the whole approach. Findings We detail five pitfalls in conducting a reliable Mendelian randomization investigation: (1) inappropriate research question, (2) inappropriate choice of variants as instruments, (3) insufficient interrogation of findings, (4) inappropriate interpretation of findings, and (5) lack of engagement with previous work. We have provided a brief checklist of key points to consider when performing a Mendelian randomization investigation; this does not replace previous guidance, but highlights critical analysis choices. Journal editors should be able to identify many low-quality submissions and reject papers without requiring peer review. Peer reviewers should focus initially on key indicators of validity; if a paper does not satisfy these, then the paper may be meaningless even if it is technically flawless. Conclusions Performing an informative Mendelian randomization investigation requires critical thought and collaboration between different specialties and fields of research.

Abstract Aim In line with the publication of clinical information related to the therapeutic process of repetitive transcranial magnetic stimulation (rTMS) and the updating of relevant treatment guidelines, the present meta-analysis study was designed and conducted to determine the effect of repetitive transcranial magnetic stimulation (rTMS) on the Hamilton Depression Rating Scale-17 (HDRS-17) criterion in patients with major depressive disorder (MDD) without psychotic features. Methods In this study, a systematic search was conducted in electronic databases such as PubMed [Medline], Scopus, Web of Science, Embase, Ovid, Cochrane Library, and ClinicalTrials. gov using relevant keywords. The search period in this study was from January 2000 to January 2022, which was updated until May 2023. Randomized controlled trials (RCTs) that determined the effect of repetitive transcranial magnetic stimulation (rTMS) on the Hamilton Depression Rating Scale-17 (HDRS-17) criterion in patients with major depressive disorder (MDD) without psychotic features were included in the analysis. The quality of the included RCTs was assessed using the Cochrane Risk of Bias checklist. Statistical analyses were performed using STATA (Version 16) and RevMan (Version 5). Results Following the combination of results from 16 clinical trial studies in the present meta-analysis, it was found that the mean Hamilton Depression Rating Scale-17 (HDRS-17) in patients with major depressive disorder (MDD) decreases by an average of 1.46 units (SMD: -1.46; % 95 CI: -1.65, -1.27, I square: 45.74%; P heterogeneity: 0.56). Subgroup analysis results indicated that the standardized mean difference of Hamilton Depression Rating Scale-17 (HDRS-17) varied based on the number of treatment sessions: patients receiving 10 or fewer repetitive transcranial magnetic stimulation (rTMS) sessions showed a mean Hamilton Depression Rating Scale-17 (HDRS-17) reduction of 2.60 units (SMD: -2.60; % 95 CI: -2.86, -2.33, I square: 55.12%; P heterogeneity: 0.55), while those receiving 11 to 20 sessions showed a mean Hamilton Depression Rating Scale-17 (HDRS-17) reduction of 0.28 units (SMD: -0.28; % 95 CI: -0.65, -0.09, I square: 39.91%; P heterogeneity: 0.89). Conclusion In conclusion, our meta-analysis demonstrates the efficacy of repetitive transcranial magnetic stimulation (rTMS) in reducing depressive symptoms in major depressive disorder (MDD) patients. The complex results of subgroup analysis revealed insight on the possible benefits of a more focused strategy with fewer sessions, as well as the impact of treatment session frequency. These findings add to our understanding of repetitive transcranial magnetic stimulation (rTMS) as a therapeutic intervention for the treatment of major depressive illnesses.

OBJECTIVE: We developed and evaluated a novel one-shot distributed algorithm for evidence synthesis in distributed research networks with rare outcomes. MATERIALS AND METHODS: Fed-Padé, motivated by a classic mathematical tool, Padé approximants, reconstructs the multi-site data likelihood via Padé approximant whose key parameters can be computed distributively. Thanks to the simplicity of [2,2] Padé approximant, Fed-Padé requests an extremely simple task and low communication cost for data partners. Specifically, each data partner only needs to compute and share the log-likelihood and its first 4 gradients evaluated at an initial estimator. We evaluated the performance of our algorithm with extensive simulation studies and four observational healthcare databases. RESULTS: Our simulation studies revealed that a [2,2]-Padé approximant can well reconstruct the multi-site likelihood so that Fed-Padé produces nearly identical estimates to the pooled analysis. Across all simulation scenarios considered, the median of relative bias and rate of instability of our Fed-Padé are both

Abstract Background This meta-analysis aims to establish a more precise association between gestational diabetes mellitus (GDM) incidence and H. pylori infection by amalgamating findings from prior case–control and cohort studies. Methods To identify relevant studies, we conducted a comprehensive search using the Excerpta Medica Database (Embase), PubMed (Medline), Web of Science (ISI), and Scopus from January 1990 to November 2022. The screening process involved reviewing the entire text, abstracts, and titles of retrieved articles. Subsequently, data extraction was performed from the selected articles, and their quality was assessed using the Newcastle–Ottawa Scale checklist. Version 17 of STATA software was utilized for the analysis, with relative risks (RR) calculated along with their 95% confidence intervals (CI) to quantify the impact of the included studies. Results This meta-analysis included eight observational and analytical studies. The combined risk of gestational diabetes mellitus (GDM) in pregnant women with H. pylori infection was found to be 1.97 times higher compared to pregnant women without infection (RR: 1.97; 95% CI 1.57–2.47; I2 = 0.00%; P = 0.84). Conclusion Pregnant women with H. pylori infection are at an increased risk of developing gestational diabetes.

There is a need to create and publish trusted evidence that will inform clinical decisions. Librarians can play an important role in this process, as they can oversee the registration and reporting of primary and secondary studies, take an active part in data synthesis and contribute to increasing the quality, completeness and reliability of existing data.

Abstract Background Standard systematic review can be labor-intensive and time-consuming meaning that it can be difficult to provide timely evidence when there is an urgent public health emergency such as a pandemic. The ClinicalTrials.gov provides a promising way to accelerate evidence production. Methods We conducted a search on PubMed to gather systematic reviews containing a minimum of 5 studies focused on safety aspects derived from randomized controlled trials (RCTs) of pharmacological interventions, aiming to establish a real-world dataset. The registration information of each trial from eligible reviews was further collected and verified. The meta-analytic data were then re-analyzed by using 1) the full meta-analytic data with all trials and 2) emulated rapid data with trials that had been registered and posted results on ClinicalTrials.gov, under the same synthesis methods. The effect estimates of the full meta-analysis and rapid meta-analysis were then compared. Results The real-world dataset comprises 558 meta-analyses. Among them, 56 (10.0%) meta-analyses included RCTs that were not registered in ClinicalTrials.gov. For the remaining 502 meta-analyses, the median percentage of RCTs registered within each meta-analysis is 70.1% (interquartile range: 33.3% to 88.9%). Under a 20% bias threshold, rapid meta-analyses conducted through ClinicalTrials.gov achieved accurate point estimates ranging from 77.4% (using the MH model) to 83.1% (using the GLMM model); 91.0% to 95.3% of these analyses accurately predicted the direction of effects. Conclusions Utilizing the ClinicalTrials.gov platform for safety assessment with a minimum of 5 RCTs holds significant potential for accelerating evidence synthesis to support urgent decision-making.

The evidence-based medicine approach to causal medical inference is the dominant account among medical methodologists. Competing approaches originating in the philosophy of medicine seek to challenge this account. In order to see how successful these challenges are, we need to assess the performance of all approaches in real world medical inference. One important real world problem all approaches could be applied to is the assessment of drugs for approval by drug regulation agencies. This study assesses the success of the status quo against an empirical non-systematically obtained body of evidence and we scrutinise the alternative approaches from the armchair, contemplating how they would fare in the real world. We tentatively conclude that the status quo is regularly not successful at its primary task as it regularly fails to correctly assess effectiveness and safety and suggest that this is due to inherent factors of the “messy real world.” However, while all alternatives hold promise, they are at least as susceptible to the real world issues that beset the status quo. We also make recommendations for changes to current drug approval procedures, identify lacunae to fill in the alternatives, and finally, call for a continuation of the development of alternative approaches to causal medical inference and recommendations for changes to current drug approval procedures.

Abstract Background The demand for high-quality systematic literature reviews (SRs) for evidence-based medical decision-making is growing. SRs are costly and require the scarce resource of highly skilled reviewers. Automation technology has been proposed to save workload and expedite the SR workflow. We aimed to provide a comprehensive overview of SR automation studies indexed in PubMed, focusing on the applicability of these technologies in real world practice. Methods In November 2022, we extracted, combined, and ran an integrated PubMed search for SRs on SR automation. Full-text English peer-reviewed articles were included if they reported studies on SR automation methods (SSAM), or automated SRs (ASR). Bibliographic analyses and knowledge-discovery studies were excluded. Record screening was performed by single reviewers, and the selection of full text papers was performed in duplicate. We summarized the publication details, automated review stages, automation goals, applied tools, data sources, methods, results, and Google Scholar citations of SR automation studies. Results From 5321 records screened by title and abstract, we included 123 full text articles, of which 108 were SSAM and 15 ASR. Automation was applied for search (19/123, 15.4%), record screening (89/123, 72.4%), full-text selection (6/123, 4.9%), data extraction (13/123, 10.6%), risk of bias assessment (9/123, 7.3%), evidence synthesis (2/123, 1.6%), assessment of evidence quality (2/123, 1.6%), and reporting (2/123, 1.6%). Multiple SR stages were automated by 11 (8.9%) studies. The performance of automated record screening varied largely across SR topics. In published ASR, we found examples of automated search, record screening, full-text selection, and data extraction. In some ASRs, automation fully complemented manual reviews to increase sensitivity rather than to save workload. Reporting of automation details was often incomplete in ASRs. Conclusions Automation techniques are being developed for all SR stages, but with limited real-world adoption. Most SR automation tools target single SR stages, with modest time savings for the entire SR process and varying sensitivity and specificity across studies. Therefore, the real-world benefits of SR automation remain uncertain. Standardizing the terminology, reporting, and metrics of study reports could enhance the adoption of SR automation techniques in real-world practice.

Background An abundance of rapidly accumulating scientific evidence presents novel opportunities for researchers and practitioners alike, yet such advantages are often overshadowed by resource demands associated with finding and aggregating a continually expanding body of scientific information. Data extraction activities associated with evidence synthesis have been described as time-consuming to the point of critically limiting the usefulness of research. Across social science disciplines, the use of automation technologies for timely and accurate knowledge synthesis can enhance research translation value, better inform key policy development, and expand the current understanding of human interactions, organizations, and systems. Ongoing developments surrounding automation are highly concentrated in research for evidence-based medicine with limited evidence surrounding tools and techniques applied outside of the clinical research community. The goal of the present study is to extend the automation knowledge base by synthesizing current trends in the application of extraction technologies of key data elements of interest for social scientists. Methods We report the baseline results of a living systematic review of automated data extraction techniques supporting systematic reviews and meta-analyses in the social sciences. This review follows PRISMA standards for reporting systematic reviews. Results The baseline review of social science research yielded 23 relevant studies. Conclusions When considering the process of automating systematic review and meta-analysis information extraction, social science research falls short as compared to clinical research that focuses on automatic processing of information related to the PICO framework. With a few exceptions, most tools were either in the infancy stage and not accessible to applied researchers, were domain specific, or required substantial manual coding of articles before automation could occur. Additionally, few solutions considered extraction of data from tables which is where key data elements reside that social and behavioral scientists analyze.

Background: This meta-analysis aims to establish a more precise association between gestational diabetes mellitus (GDM) incidence and H. pylori infection by amalgamating findings from prior case–control and cohort studies. Methods: To identify relevant studies, we conducted a comprehensive search using the Excerpta Medica Database (Embase), PubMed (Medline), Web of Science (ISI), and Scopus from January 1990 to November 2022. The screening process involved reviewing the entire text, abstracts, and titles of retrieved articles. Subsequently, data extraction was performed from the selected articles, and their quality was assessed using the Newcastle–Ottawa Scale checklist. Version 17 of STATA software was utilized for the analysis, with relative risks (RR) calculated along with their 95% confidence intervals (CI) to quantify the impact of the included studies. Results: This meta-analysis included eight observational and analytical studies. The combined risk of gestational diabetes mellitus (GDM) in pregnant women with H. pylori infection was found to be 1.97 times higher compared to pregnant women without infection (RR: 1.97; 95% CI 1.57–2.47; I2 = 0.00%; P = 0.84). Conclusion: Pregnant women with H. pylori infection are at an increased risk of developing gestational diabetes. [ABSTRACT FROM AUTHOR]

Existing systems for automating the assessment of risk‐of‐bias (RoB) in medical studies are supervised approaches that require substantial training data to work well. However, recent revisions to RoB guidelines have resulted in a scarcity of available training data. In this study, we investigate the effectiveness of generative large language models (LLMs) for assessing RoB. Their application requires little or no training data and, if successful, could serve as a valuable tool to assist human experts during the construction of systematic reviews. Following Cochrane's latest guidelines (RoB2) designed for human reviewers, we prepare instructions that are fed as input to LLMs, which then infer the risk associated with a trial publication. We distinguish between two modelling tasks: directly predicting RoB2 from text; and employing decomposition, in which a RoB2 decision is made after the LLM responds to a series of signalling questions. We curate new testing data sets and evaluate the performance of four general‐ and medical‐domain LLMs. The results fall short of expectations, with LLMs seldom surpassing trivial baselines. On the direct RoB2 prediction test set (n = 5993), LLMs perform akin to the baselines (F1: 0.1–0.2). In the decomposition task setup (n = 28,150), similar F1 scores are observed. Our additional comparative evaluation on RoB1 data also reveals results substantially below those of a supervised system. This testifies to the difficulty of solving this task based on (complex) instructions alone. Using LLMs as an assisting technology for assessing RoB2 thus currently seems beyond their reach. [ABSTRACT FROM AUTHOR]

Network meta-analysis has been used to answer a range of clinical questions about the preferred intervention for a given condition. Although the effectiveness and safety of pharmacological agents depend on the dose administered, network meta-analysis applications typically ignore the role that drugs dosage plays in the results. This leads to more heterogeneity in the network. In this paper, we present a suite of network meta-analysis models that incorporate the dose–effect relationship using restricted cubic splines. We extend existing models into a dose–effect network meta-regression to account for study-level covariates and for groups of agents in a class-effect dose–effect network meta-analysis model. We apply our models to a network of aggregate data about the efficacy of 21 antidepressants and placebo for depression. We find that all antidepressants are more efficacious than placebo after a certain dose. Also, we identify the dose level at which each antidepressant's effect exceeds that of placebo and estimate the dose beyond which the effect of antidepressants no longer increases. When covariates were introduced to the model, we find that studies with small sample size tend to exaggerate antidepressants efficacy for several of the drugs. Our dose–effect network meta-analysis model with restricted cubic splines provides a flexible approach to modelling the dose–effect relationship in multiple interventions. Decision-makers can use our model to inform treatment choice. [ABSTRACT FROM AUTHOR]

Threat mapping is a necessary tool for identifying and abating direct threats to species in the ongoing extinction crisis. There are known gaps in the threat mapping literature for particular threats and geographic locations, and it remains unclear if the distribution of research effort is appropriately targeted relative to conservation need. We aimed to determine the drivers of threat mapping research effort and to quantify gaps that, if filled, could inform actions with the highest potential to reduce species' extinction risk. We used a negative binomial generalized linear model to analyze research effort as a function of threat abatement potential (quantified as the potential reduction in species extinction risk from abating threats), species richness, land area, and human pressure. The model showed that threat mapping research effort increased by 1.1 to 1.2 times per standardized unit change in threat abatement potential. However, species richness and land area were stronger predictors of research effort overall. The greatest areas of mismatch between research effort and threat abatement potential, receiving disproportionately low research effort, were related to the threats to species of agriculture, aquaculture, and biological resource use across the tropical regions of the Americas, Asia, and Madagascar. Conversely, the threat of linear infrastructure (e.g., roads and rails) across regions, the threat of biological resource use (e.g., hunting or collection) in sub‐Saharan Africa, and overall threats in North America and Europe all received disproportionately high research effort. We discuss the range of methodological and sociopolitical factors that may be behind the overall trends and specific areas of mismatch we found. We urge a stronger emphasis on targeting research effort toward those threats and geographic locations where threat abatement activities could make the greatest contribution to reducing global species extinction risk. [ABSTRACT FROM AUTHOR]

Mirroring the patterns of primary research, there is a significant and growing increase in the number of systematic reviews (SRs) in the human–animal interaction (HAI) field. This article describes the content of published SRs and compares their reporting practices against the rigorous, prescribed methodologies associated with quality SRs. This study was designed to describe the characteristics of HAI SRs in terms of publication patterns, human subjects, animal(s) of interest, and outcomes and determine the extent to which they follow recommended practices for transparency and reproducibility. Thirteen bibliographic databases were searched for articles containing both an HAI-related term and an SR term. We screened 766 articles for relevance and coded 110 of them for desired data. The majority of reviews (54.55%) were published between 2019 and 2022. Most (65.45%) did not specify the age of human populations studied, but specified ages included children or adolescents, adults, and older adults. A range of human conditions was studied, including, among others, dementia, autism spectrum disorder, and chronic illness. A slight majority of studies (51.82%) did not specify the animal species to be studied, but those that did included, singly or in combination, dogs, horses, robotic animals, and farm or food animals. The majority of studies (63.63%) referred to PRISMA or other methodological guidelines. Across all studies, 163 different databases were searched, with PubMed, PsycINFO, and CINAHL among the most frequently used. Few studies (18.18%) referred to consultation with an information professional. A slight majority (52.72%) provided a full search strategy for at least one database. Most (67.27%) did not include gray literature searches, and most (72.72%) included an assessment of quality or risk of bias for the studies included in their review. In light of their importance in informing practices and policies, and because they are viewed as the most reliable study type, SR reporting in the HAI field should reflect best practices. There is room for improvement in reporting among HAI SRs. Suggestions are offered for ways HAI educators and journal editors may improve SR methodologies and reporting in the field. [ABSTRACT FROM AUTHOR]

Recently, Ades and colleagues discussed the controversies and advancements in network meta‐analysis (NMA) over the past two decades, discussing its reliability, assumptions, novel approaches, and provided some useful recommendations for the conduction of NMAs. The present discussion paper builds on the insights by Ades and colleagues, providing a roadmap for NMA applications, advancements in software and tools, and approaches designed to facilitate the assessment and interpretation of NMA findings. It also discusses the impact of NMA across disciplines, particularly for policymakers and guideline developers. Despite 20 years of NMA history, challenges remain in understanding and assessing assumptions, communicating and interpreting findings, and applying common approaches like network meta‐regression and NMA involving non‐randomized studies in readily available software. NMA has proven particularly valuable in clinical decision‐making, which highlights the need for additional training and interdisciplinary collaboration of knowledge users, including patient engagement, to enhance its adoption and address real‐world problems. [ABSTRACT FROM AUTHOR]

Background: Standard systematic review can be labor-intensive and time-consuming meaning that it can be difficult to provide timely evidence when there is an urgent public health emergency such as a pandemic. The ClinicalTrials.gov provides a promising way to accelerate evidence production. Methods: We conducted a search on PubMed to gather systematic reviews containing a minimum of 5 studies focused on safety aspects derived from randomized controlled trials (RCTs) of pharmacological interventions, aiming to establish a real-world dataset. The registration information of each trial from eligible reviews was further collected and verified. The meta-analytic data were then re-analyzed by using 1) the full meta-analytic data with all trials and 2) emulated rapid data with trials that had been registered and posted results on ClinicalTrials.gov, under the same synthesis methods. The effect estimates of the full meta-analysis and rapid meta-analysis were then compared. Results: The real-world dataset comprises 558 meta-analyses. Among them, 56 (10.0%) meta-analyses included RCTs that were not registered in ClinicalTrials.gov. For the remaining 502 meta-analyses, the median percentage of RCTs registered within each meta-analysis is 70.1% (interquartile range: 33.3% to 88.9%). Under a 20% bias threshold, rapid meta-analyses conducted through ClinicalTrials.gov achieved accurate point estimates ranging from 77.4% (using the MH model) to 83.1% (using the GLMM model); 91.0% to 95.3% of these analyses accurately predicted the direction of effects. Conclusions: Utilizing the ClinicalTrials.gov platform for safety assessment with a minimum of 5 RCTs holds significant potential for accelerating evidence synthesis to support urgent decision-making. [ABSTRACT FROM AUTHOR]

Background: The demand for high-quality systematic literature reviews (SRs) for evidence-based medical decision-making is growing. SRs are costly and require the scarce resource of highly skilled reviewers. Automation technology has been proposed to save workload and expedite the SR workflow. We aimed to provide a comprehensive overview of SR automation studies indexed in PubMed, focusing on the applicability of these technologies in real world practice. Methods: In November 2022, we extracted, combined, and ran an integrated PubMed search for SRs on SR automation. Full-text English peer-reviewed articles were included if they reported studies on SR automation methods (SSAM), or automated SRs (ASR). Bibliographic analyses and knowledge-discovery studies were excluded. Record screening was performed by single reviewers, and the selection of full text papers was performed in duplicate. We summarized the publication details, automated review stages, automation goals, applied tools, data sources, methods, results, and Google Scholar citations of SR automation studies. Results: From 5321 records screened by title and abstract, we included 123 full text articles, of which 108 were SSAM and 15 ASR. Automation was applied for search (19/123, 15.4%), record screening (89/123, 72.4%), full-text selection (6/123, 4.9%), data extraction (13/123, 10.6%), risk of bias assessment (9/123, 7.3%), evidence synthesis (2/123, 1.6%), assessment of evidence quality (2/123, 1.6%), and reporting (2/123, 1.6%). Multiple SR stages were automated by 11 (8.9%) studies. The performance of automated record screening varied largely across SR topics. In published ASR, we found examples of automated search, record screening, full-text selection, and data extraction. In some ASRs, automation fully complemented manual reviews to increase sensitivity rather than to save workload. Reporting of automation details was often incomplete in ASRs. Conclusions: Automation techniques are being developed for all SR stages, but with limited real-world adoption. Most SR automation tools target single SR stages, with modest time savings for the entire SR process and varying sensitivity and specificity across studies. Therefore, the real-world benefits of SR automation remain uncertain. Standardizing the terminology, reporting, and metrics of study reports could enhance the adoption of SR automation techniques in real-world practice. [ABSTRACT FROM AUTHOR]

Background: There have been numerous studies on NMDA receptors as therapeutic targets for depression. However, so far, there has been no comprehensive scientometric analysis of this field. Thus, we conducted a scientometric analysis with the aim of better elucidating the research hotspots and future trends in this field. Methods: Publications on NMDAR in Depression between 2004 and 2023 were retrieved from the Web of Science Core Collection (WoSCC) database. Then, VOSviewer, CiteSpace, Scimago Graphica, and R-bibliometrix--were used for the scientometric analysis and visualization. Results: 5,092 qualified documents were identified to scientometric analysis. In the past 20 years, there has been an upward trend in the number of annual publications. The United States led the world in terms of international collaborations, publications, and citations. 15 main clusters were identified from the co-cited references analysis with notable modularity (Q-value = 0.7628) and silhouette scores (S-value = 0.9171). According to the keyword and co-cited references analysis, treatment-resistant depression ketamine (an NMDAR antagonist), oxidative stress, synaptic plasticity, neuroplasticity related downstream factors like brain-derived neurotrophic factor were the research hotspots in recent years. Conclusion: As the first scientometric analysis of NMDAR in Depression, this study shed light on the development, trends, and hotspots of research about NMDAR in Depression worldwide. The application and potential mechanisms of ketamine in the treatment of major depressive disorder (MDD) are still a hot research topic at present. However, the side effects of NMDAR antagonist like ketamine have prompted research on new rapid acting antidepressants. [ABSTRACT FROM AUTHOR]

Objective: There is little research available regarding the instructional practices of librarians who support students completing knowledge synthesis projects. This study addresses this research gap by identifying the topics taught, approaches, and resources that academic health sciences librarians employ when teaching students how to conduct comprehensive searches for knowledge synthesis projects in group settings. Methods: This study applies an exploratory-descriptive design using online survey data collection. The final survey instrument included 31 open, closed, and frequency-style questions. Results: The survey received responses from 114 participants, 74 of whom met the target population. Some key results include shared motivations to teach in groups, including student learning and curriculum requirements, as well as popular types of instruction such as single session seminars, and teaching techniques, such as lectures and live demos. Conclusion: This research demonstrates the scope and coverage of librarian-led training in the knowledge synthesis research landscape. Although searching related topics such as Boolean logic were the most frequent, librarians report teaching throughout the review process like methods and reporting. Live demos and lectures were the most reported approaches to teaching, whereas gamification or student-driven learning were used rarely. Our results suggest that librarian's application of formal pedagogical approaches while teaching knowledge synthesis may be under-utilized, as most respondents did not report using any formal instructional framework. [ABSTRACT FROM AUTHOR]

Summary: Aims: The purpose of this systematic review and meta‐analysis was to investigate the effects of family‐based health promotion interventions on child‐level risk factors for type 2 diabetes in vulnerable families. Methods: The Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) checklist for systematic reviews formed the methodological framework. CINAHL, Embase, MEDLINE, PsycINFO, and Web of Science were searched on January 12, 2024. The NTP‐OHAT Risk of Bias Assessment Tool was used to assess the risk of bias in the individual studies, and meta‐analyses were performed. Results: The 4723 studies were identified, and 55 studies met the inclusion criteria. Results showed significant effects on children's body mass index (mean difference [MD], −0.18, 95% CI [−0.33 to −0.03], p = 0.02), body fat percentage (MD, −2.00, 95% CI [−3.31 to −0.69], p = 0.003), daily activity (standardized mean difference [SMD], 0.23, 95% CI [0.01; 0.44], p = 0.04), physical activity self‐efficacy (SMD, 0.73, 95% CI [0.36 to 1.10], p < 0.01), intake of snacks (MD, −0.10, 95% CI [−0.17 to −0.04], p = 0.002), and sugar‐sweetened beverages (SMD, −0.21, 95% CI [−0.42 to −0.01], p = 0.04). Subgroup analyses suggested that interventions aiming to change child and parent behavior simultaneously have larger effect on fasting glucose and nutrition consumption, and that interventions longer than 26 weeks have larger effects on body composition and physical activity behavior than shorter interventions. [ABSTRACT FROM AUTHOR]