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ObjectivesThe objectives of this study are to assess reporting of evidence-based healthcare (EBHC) e-learning interventions using the Guideline for Reporting Evidence-based practice Educational interventions and Teaching (GREET) checklist and explore factors associated with compliant reporting.DesignMethodological cross-sectional study.MethodsBased on the criteria used in an earlier systematic review, we included studies comparing EBHC e-learning and any other form of EBHC training or no EBHC training. We searched Medline, Embase, ERIC, CINAHL, CENTRAL, SCOPUS, Web of Knowledge, PsycInfo, ProQuest and Best Evidence Medical Education up to 4 January 2023. Screening of titles, abstracts, full-text articles and data extraction was done independently by two authors. For each study, we assessed adherence to each of the 17 GREET items and extracted information on possible predictors. Adequacy of reporting for each item of the GREET checklist was judged with yes (provided complete information), no (provided no information), unclear (when insufficient information was provided), or not applicable, when the item was clearly of no relevance to the intervention described (such as for item 8—details about the instructors—in the studies which used electronic, self-paced intervention, without any tutoring). Studies’ adherence to the GREET checklist was presented as percentages and absolute numbers. We performed univariate analysis to assess the association of potential adherence predictors with the GREET checklist. We summarised results descriptively.ResultsWe included 40 studies, the majority of which assessed e-learning or blended learning and mostly involved medical and other healthcare students. None of the studies fully reported all the GREET items. Overall, the median number of GREET items met (received yes) per study was 8 and third quartile (Q3) of GREET items met per study was 9 (min. 4 max. 14). When we used Q3 of the number of items met as cut-off point, adherence to the GREET reporting checklist was poor with 7 out of 40 studies (17.5%) reporting items of the checklist on acceptable level (adhered to at least 10 items out of 17). None of the studies reported on all 17 GREET items. For 3 items, 80% of included studies well reported information (received yes for these items): item 1 (brief description of intervention), item 4 (evidence-based practice content) and item 6 (educational strategies). Items for which 50% of included studies reported complete information (received yes for these items) included: item 9 (modes of delivery), item 11 (schedule) and 12 (time spent on learning). The items for which 70% or more of included studies did not provide information (received no for these items) included: item 7 (incentives) and item 13 (adaptations; for both items 70% of studies received no for them), item 14 (modifications of educational interventions—95% of studies received no for this item), item 16 (any processes to determine whether the materials and the educational strategies used in the educational intervention were delivered as originally planned—93% of studies received no for this item) and 17 (intervention delivery according to schedule—100% of studies received no for this item). Studies published after September 2016 showed slight improvements in nine reporting items. In the logistic regression models, using the cut-off point of Q3 (10 points or above) the odds of acceptable adherence to GREET guidelines were 7.5 times higher if adherence to other guideline (Consolidated Standards of Reporting Trials, Strengthening the Reporting of Observational Studies in Epidemiology, etc) was reported for a given study type (p=0.039), also higher number of study authors increased the odds of adherence to GREET guidance by 18% (p=0.037).ConclusionsStudies assessing educational interventions on EBHC e-learning still poorly adhere to the GREET checklist. Using other reporting guidelines increased the odds of better GREET reporting. Journals should call for the use of appropriate use of reporting guidelines of future studies on teaching EBHC to increase transparency of reporting, decrease unnecessary research duplication and facilitate uptake of research evidence or result.Study registration numberThe Open Science Framework (https://doi.org/10.17605/OSF.IO/V86FR).

A surprising feature of the SARS-CoV-2 pandemic to date is the low burdens reported in sub-Saharan Africa (SSA) countries relative to other global regions. Potential explanations (for example, warmer environments1, younger populations2–4) have yet to be framed within a comprehensive analysis. We synthesized factors hypothesized to drive the pace and burden of this pandemic in SSA during the period from 25 February to 20 December 2020, encompassing demographic, comorbidity, climatic, healthcare capacity, intervention efforts and human mobility dimensions. Large diversity in the probable drivers indicates a need for caution in interpreting analyses that aggregate data across low- and middle-income settings. Our simulation shows that climatic variation between SSA population centers has little effect on early outbreak trajectories; however, heterogeneity in connectivity, although rarely considered, is likely an important contributor to variance in the pace of viral spread across SSA. Our synthesis points to the potential benefits of context-specific adaptation of surveillance systems during the ongoing pandemic. In particular, characterizing patterns of severity over age will be a priority in settings with high comorbidity burdens and poor access to care. Understanding the spatial extent of outbreaks warrants emphasis in settings where low connectivity could drive prolonged, asynchronous outbreaks resulting in extended stress to health systems.