ABSTRACT Policymakers have little time left to prevent the worst impacts of climate change and limit global warming to well below two degrees. However, a systematic assessment of the available scientific evidence—that is up to date—is not always available to understand what climate policies work, to what extent, in what context, why, and for whom. This is also true for demand‐side policies, including those that use behavioral change to reduce energy demand and the related carbon emissions. There is an ever‐burgeoning literature on policy interventions that target behavioral change among households, with new insights and evidence of their efficacy in different contexts. This living systematic review (LSR) and network meta‐analysis (NMA) synthesizes this evidence to provide timely, rigorous and up‐to‐date insights on this topic. Our LSR and NMA integrate the evidence available from multiple disciplines to answer the following questions: (1) to what extent can information, behavioral (including feedback, social comparison and motivation), and monetary based interventions reduce energy consumption of households; (2) what the relative effectiveness of interventions is; and (3) how effective are the combinations of different interventions. In doing so, we also pilot an LSR for climate policy solutions and share learnings with the community. To fulfill these objectives, we searched the academic and gray literature for experimental and quasi‐experimental studies that quantitatively assessed the impact of either behavioral, monetary, or information interventions (or a combination of these) on energy consumption (including electricity and heat) of the households in residential buildings. We searched the relevant databases: Web of Science Core Collections Citation Indexes, Scopus, JSTOR, RePec, Google Scholar, and gray literature repository Policy Commons to retrieve over 109,000 potentially relevant article abstracts and apply machine learning algorithms to identify the most likely relevant papers. Note that with this update, that includes the relevant literature published till end of December 2024, we added roughly 53,000 potentially relevant documents to the previously existing pool of potentially relevant literature from Khanna et al. (2021). A team of four reviewers screened the titles and abstracts of studies identified as being potentially relevant by the machine learning algorithm, with full‐text assessments and double‐coded data collection following for a set of included studies. The effect sizes reported by different studies were harmonized to Cohen's d for synthesis. We used a multilevel random effects model and NMA for calculating the average intervention effect. We adjust our estimates for possible small‐study effects (publication bias). The NMA allows us to visualize the relative efficacy of the interventions through rankograms and cumulative ranking probability plots. Unlike previous meta‐analyses in this field of research, this study also implements a comprehensive risk of bias criteria for assessing the quality of each study using a modified version of the framework recommended by the Center for Environmental Evidence. We identified 213 relevant studies and conducted meta‐analyses on 192 studies that provide quantitative estimates of the relationship between behavioral, monetary, and information incentives and reduction in energy consumption of households. The studies together represent evidence from 40 countries and 6,528,923 households (average total sample size of 33,216). The studies were of varying quality, with the presence of methodological weaknesses across the included studies. We find an overall average effect size of Cohen's d = 0.22 or 0.13 after adjusting for potential small‐study bias across. Such an effect corresponds to approximately a 4%–6% reduction in energy consumption. Monetary incentives have the largest average effect, followed by some behavioral (motivation) and information interventions. Combining interventions can also increase effectiveness; for example, combining information, social, and behavioral (motivation) interventions has high average effects. Our analysis finds that behavioral, monetary and information interventions taken together on average have a small‐moderate effect on energy consumption of households. Some intervention combinations yield substantially larger impacts—especially when considered at scale. However, the practical consequences of the average effect sizes reported in this review depend on at least three factors: how often a person makes decisions that could be influenced by the interventions under investigation, the scalability and cost of interventions, and the welfare consequences of the interventions. The fast‐growing literature on behavioral, information, and monetary interventions in household energy consumption makes this field a fitting case study for a “living” review assessment. Of the 663 effect sizes used for synthesis, about half come from studies produced after 2020 that were not included in previous reviews on the topic. However, there are significant challenges with consistently updating a review, most importantly, in terms of maintaining consistency in the identification and coding of studies, given resource constraints and changing personnel. Applying machine learning algorithms during abstract‐level document screening helped us significantly reduce the manual effort involved in identifying the relevant literature.

ABSTRACTThe explosion of scientific literature has made the efficient and accurate extraction of structured data a critical component for advancing scientific knowledge and supporting evidence‐based decision‐making. However, existing tools often struggle to extract and structure multimodal, varied, and inconsistent information across documents into standardized formats. We introduce SciDaSynth, a novel interactive system powered by large language models that automatically generates structured data tables according to users' queries by integrating information from diverse sources, including text, tables, and figures. Furthermore, SciDaSynth supports efficient table data validation and refinement, featuring multi‐faceted visual summaries and semantic grouping capabilities to resolve cross‐document data inconsistencies. A within‐subjects study with nutrition and NLP researchers demonstrates SciDaSynth's effectiveness in producing high‐quality structured data more efficiently than baseline methods. We discuss design implications for human–AI collaborative systems supporting data extraction tasks.

ABSTRACTAddressing the climate change and biodiversity loss crises while ensuring livelihoods are not negatively affected is a matter that requires urgent action. A recently published Evidence Gap Map (EGM) identified no recent systematic reviews on land management interventions. Drawing from this EGM, the review aims to examine and synthesise the latest evidence on what works, how, and at what cost to improve environmental and human welfare outcomes in land management in low‐ and middle‐income countries. We will address the following research questions: (1) What are the effects of protected areas, land rights and decentralisation interventions on environmental and poverty outcomes? Do effects vary by population, location, or other factors? (2) What are the barriers and enablers that impact the effectiveness of these interventions? (3) What is the cost‐effectiveness of these interventions? The set of interventions will be based on the studies identified in the EGM, and we will search, appraise and synthesise additional evidence on influencing factors and cost data.

ABSTRACTSchool exclusion—commonly referred to as suspension—is a disciplinary response employed by school authorities to address student misbehaviour. Typically, it involves temporary removal from regular teaching or, in more serious cases, complete removal from the school premises. A substantial body of research has associated exclusion with adverse developmental outcomes. In response, various school‐based interventions have been developed to reduce exclusion rates. While some programmes have shown promising effects, the evidence on their effectiveness remains inconclusive. This mixed‐methods systematic review and multi‐level meta‐analysis updates the previous review by Valdebenito et al. (2018), which included literature published between 1980 and 2015. The present update extends the evidence base by including studies until 2022. The primary aim of this review was to assess the effectiveness of school‐based interventions in reducing disciplinary exclusions, with secondary aims focused on related behavioural outcomes including conduct problems, delinquency, and substance use. Systematic searches conducted between November and December 2022 yielded over 11,000 references for quantitative studies. Following title and abstract screening, 777 records were reviewed at full text by two independent coders. Thirty‐two studies met the inclusion criteria for meta‐analysis, comprising 2765 effect sizes from 67 primary evaluations (1980–2022) and representing approximately 394,242 students. Meta‐analysis was conducted using a multilevel random‐effects model with robust variance estimation to account for the nested structure of the data. Quantitative impact evaluations were eligible if they used a randomised controlled or quasi‐experimental design, included both a control group and pre/post‐test data, and used statistical methods to minimise selection bias (e.g., propensity score matching or matched cohort design). Studies were excluded if they exhibited substantial baseline differences between treatment and control groups. The qualitative synthesis explored implementation barriers and facilitators based on nine UK‐based process evaluations, identified through searches completed in September 2023. Process evaluations were included if they focused on the perceptions of stakeholders—teachers, students, or school leadership—within UK schools. Data collection followed two stages: initial selection based on titles, abstracts, and keywords, followed by full‐text review. Two independent coders applied inclusion criteria, extracted data, and resolved discrepancies with the principal investigators. All steps were documented to inform the PRISMA flow chart. To evaluate interventions reducing school exclusions, we conducted a multilevel meta‐analysis using robust variance estimation. We explored heterogeneity via meta‐regression (e.g., gender, intervention type), conducted sensitivity analyses for outliers and correlation structures, and assessed quality data using the EPOC, ROBIN‐I and CASP checklist for methodological quality. Findings indicated that school‐based interventions were associated with a small but statistically significant reduction in school exclusion (standardised mean difference [SMD] = 0.104; 95% CI: 0.04 to 0.17; p < 0.001). Compared with the original 2018 review, which reported a slightly larger effect size, this update benefits from a broader evidence base and more advanced statistical modelling. However, the results for secondary behavioural outcomes were more limited: effects on conduct problems and delinquency were negligible or non‐significant, and the impact on substance use was small and not statistically significant. Risk of bias was assessed using the Cochrane EPOC 2 tool (Higgins and Green 2011) for randomised controlled trials and ROBINS‐I (Sterne et al. 2016) for quasi‐experimental designs. Randomised studies generally exhibited lower risk of bias, while quasi‐experimental studies showed greater variability in quality. Four major themes emerged from the analysis. First, intervention format mattered: flexible, collaborative, and well‐structured interventions facilitated implementation, while outdated materials or content misaligned with local context impeded delivery. Second, consistency in school policies and practice enabled smoother implementation, whereas inconsistency acted as a barrier. Third, staff buy‐in—particularly among senior leaders—was essential for successful implementation, although resistance from more experienced staff was noted. Finally, perceived effectiveness played a motivational role: visible improvements in pupil behaviour supported continued engagement with the intervention. In summary, the updated review finds that school‐based interventions can modestly but significantly reduce school exclusions. While more serious disciplinary sanctions such as permanent exclusions and out‐of‐school suspensions appear less responsive, in‐school exclusion shows greater potential for reduction. Impacts on other behavioural outcomes remain limited. These findings suggest that targeted, context‐sensitive interventions supported by strong implementation strategies and whole‐school engagement are most likely to achieve sustained reductions in school exclusion.

ABSTRACTRelocation processes are increasingly considered local adaptations to flooding. While relocation can offer many benefits, it also leads to socio‐economic and socio‐psychological consequences. Moreover, it tends to place greater pressure on populations experiencing socio‐territorial inequities compared to other households. It is therefore important to assess the direct and indirect impacts of relocation to consider its application from a more just and equitable perspective. The objective of this scoping review is to document the impacts of flood‐induced residential relocation processes on populations facing socio‐territorial inequities in North America and Europe. It also seeks to categorize the challenges faced by planners in relocation processes. This will help us better assess the relevance of relocation as an adaptation measure to climate change for populations facing socio‐territorial inequities. This scoping review will be conducted in accordance with the methodological guide JBI Manual for Evidence Synthesis (Aromataris and Munn 2020). A systematic search will first be developed in collaboration with an expert librarian. Five databases will be searched: Erudit, Cairn, Web of Science, GreenFILE (EBSCO), and GeoBase (Engineering Village). Gray literature will be collected from Policy Commons, Open Access Theses and Dissertations, Google Scholar, Google, and relevant governmental websites. A screening of the studies and documents obtained will then be carried out by two independent reviewers to retain the relevant documents for the scoping review. If needed, the involvement of a third reviewer will be solicited. The data relevant to our question will then be extracted, using a tool created by the authors, and then analyzed and presented in narrative and tabular formats. The results of this scoping review will be used to discuss and share insights and lessons learned. It will allow us to draw conclusions on the impacts of residential relocation processes on populations facing socio‐territorial inequities and to identify best practices for land‐use planning in the context of climate change.

Emerging evidence suggests that coronavirus disease 2019 (COVID-19) infection may cause diabetes mellitus in patients without a prior history of the condition. This review aims to determine the incidence of new-onset diabetes mellitus in COVID-19 patients compared to individuals without COVID-19, including rates of diabetic ketoacidosis, hyperglycaemia, mortality, and intensive care unit admission. Subgroup analyses will investigate patients receiving corticosteroid therapy for COVID-19, patients admitted to hospital due to COVID-19, and the incidence of new-onset diabetes mellitus in relation to diabetes mellitus worldwide. The incidence of new-onset diabetes mellitus post-infection after a 6-12-month follow-up will also be reported. This protocol follows the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines and is registered in PROSPERO (CRD42023457569). Eligible studies will include published and peer-reviewed cohort studies in English, after 1 December 2019. PubMed, Medline, Embase, and Scopus will be systematically searched. Included studies should compare new-onset diabetes mellitus incidence in COVID-19 patients against a control group without COVID-19. Two independent reviewers will extract data from included studies and assess risk of bias using the Newcastle-Ottawa quality assessment scale. A random-effects meta-analysis will compare the relative risk of new-onset diabetes mellitus post COVID-19 infection compared to non-infected individuals. The findings of this review will contribute to understanding the bidirectional relationship between COVID-19 and diabetes mellitus and inform clinical management strategies for patients at risk. PROSPERO CRD42023457569.

ABSTRACTThis is the protocol for a Campbell systematic review. The objectives are as follows: (1) What qualitative themes and sub‐themes characterize the experience of parenting and addiction recovery in parents who self‐identify as being in recovery or who are identified by the study authors as a sample in recovery (e.g., in the process/have resolved a SUD as indicated by stopping use of substances)? To what extent do these themes reveal how parents incorporate parenting and recovery identities as a core characteristic of oneself? (2) In what ways does gender shape the thematic evidence on how parenting identities intersect with recovery identities? (3) What are the barriers and facilitators for parents in accessing and utilizing addiction recovery services?

ABSTRACTAn equitable and accessible informed consent process is needed to support agency and mutual decision‐making. This systematic review aims to gather and characterise the evidence supporting methods that enhance inclusion and accessibility in informed consent practice for people with vision and/or hearing support needs. It will address the research question: what strategies are being used to enhance inclusive consent practice for people with vision impairment, people who are d/Deaf or hard of hearing, and people who are d/Deafblind. Additionally, the review aims to generate recommendations to facilitate the uptake of accessibility practices within informed consent procedures. This systematic review will build on current evidence for the positive impact of intentional actions to support accessible communication and information exchange. It may guide future work on intervention development and primary research in improving equity in clinical care and research.

[This corrects the article DOI: 10.1002/cl2.70008.].