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Scoping reviews, mapping reviews, and evidence map methodologies are increasingly used by researchers. The objective of this article is to outline the main difference between these types of evidence synthesis to improve their conduct. This article summarizes the key issues facing reviewers, who conduct scoping reviews, mapping reviews, and evidence maps and those who use the results and may engage in consultations during their development. Several differences exist between the methodologies, and these are in their protocol development, scope, inclusion criteria, data extraction, reporting, and use. Mapping reviews are mainly driven by questions of effectiveness of a particular intervention and hence they use the Participant Intervention Comparator Outcome Study type format similar to systematic reviews of effectiveness. Scoping reviews mostly use the Participant, context, concept (PCC) format, where they map a concept of interest relevant to a particular population in a specific setting and context. Data extraction is limited by only coding of studies and intervention characteristics in evidence maps. The results of the mapping reviews can be used inform research priorities and research funding, whereas, scoping reviews result may be used to inform policy development by clarifying key concepts and methods, and further research. We recommend authors who are planning to undertake scoping reviews confirm that their research question can be appropriately answered using a scoping review methodology, however, for broader research questions without the need for an in-depth analysis of the information, we recommend authors to consider mapping reviews.

The body of research on acupuncture as a treatment strategy for fibromyalgia (FM) is steadily growing. This evidence map identifies, describes, and summarizes the current status of studies conducted to evaluate the efficacy of acupuncture for FM, identify research gaps, and provide information that could guide the design of future studies. Seven electronic databases–Cochrane Library, PubMed, Embase, China Biomedical Literature Database, VIP, Wanfang Database, and Chinese National Knowledge Infrastructure–were searched for relevant articles on acupuncture for FM. The search period was from the dates of inception of the databases to December 19, 2022. Original clinical studies and systematic reviews on the use of acupuncture-related modalities for the treatment of FM were included. The basic information, quality assessments, and evidence maps of the included studies are presented as charts and bubble plots. The quality assessment tools used for evaluating the different types of studies included in the present study were Cochrane Collaboration's tool, Canadian Institute of Health Economics quality appraisal tool, and A MeaSurement Tool to Assess systematic Reviews 2. Fifty studies were included in this study. Of these, 39 (78.00%) were randomized controlled trials (RCTs), 6 (12.0%) were case series, and 5 (10.0%) were systematic reviews. The included studies focused on manual acupuncture and conventional treatment in the treatment and control groups, respectively. The outcomes analyzed in the RCTs included pain (94.9%), sleep quality (46.2%), depression (46.2%), physical function (46.2%), stiffness (35.9%), well-being (35.9%), work status (35.9%), anxiety (33.3%), fatigue (33.3%), quality of life (17.9%), and overall effective rate (10.3%). The methodological quality of most of the studies was low or critically low regardless of the study design. In most studies, the therapeutic effect of acupuncture was significantly superior to that of the comparator. This evidence map suggests that acupuncture-related modalities may be promising options for FM management. However, various studies on this topic have a high risk of bias or are of low quality. Further evidence-based research should be conducted to rigorously examine the efficacy of acupuncture for FM and promote generalizability of the findings.

Ozone therapy (OT), a medical procedure, has been showing good results during the coronavirus disease (COVID-19). We aimed to build an evidence and gaps map (EGM) of OT in the COVID-19 ranking the articles found according to levels of evidence and outcomes. The EGM brings bubbles of different sizes and different colors according to the articles. The OT intervention used was major or minor autohemotherapy, rectal insufflation and ozonized saline solution. EGM was based on 13 clinical studies using OT for COVID-19 involving a total of 271 patients. We found 30 outcomes related to OT in COVID-19. Our EGM divided the outcomes into six groups: 1-clinical improvement; 2-hospitalization; 3-inflammatory, thromboembolic, infectious, or metabolic markers; 4-radiological aspects, 5-viral infection and 6-adverse events. Major autohemotherapy was present in 19 outcomes, followed by rectal insufflation. Improvement in clinical symptoms of COVID-19, improvement of respiratory function, improvement of oxygen saturation, reduction in hospital internment, decrease in C-reactive protein, decrease in ferritin, decrease in lactate dehydrogenase, decrease in interleukin 6, decrease in D-dimer, radiological improvement of lung lesions and absence of reported adverse events were related in the papers. The most commonly used concentrations of OT in major autohemotherapy and in rectal insufflation were 40 μg/mL and 35 μg/mL, respectively. Here, we bring the first EGM showing the efficacy and safety of OT in the treatment of COVID-19. OT can be used as integrative medical therapy in COVID-19 at a low cost and improve the health conditions of the patients.

Background Interactive evidence maps typically visualise characteristics of research evidence, and gaps in evidence, in a particular field. Aims, Materials & Methods Here we present an example of an evidence map on digital drug and alcohol interventions in which the research evidence is supplemented with information about interventions in use (or available for use) in England. We used systematic review methods to identify systematic reviews of intervention effectiveness and an online survey to identify interventions in England. Results Eighteen reviews and 40 interventions were included in the online map. Discussion & Conclusion To our knowledge, this is the first map to juxtapose research and practice in this way. By extending evidence maps to include data on service provision, it becomes easier to see whether research and practice are aligned and where gaps in either evidence or practice (or both) exist.

Background The need for systematic methods for reviewing evidence is continuously increasing. Evidence mapping is one emerging method. There are no authoritative recommendations for what constitutes an evidence map or what methods should be used, and anecdotal evidence suggests heterogeneity in both. Our objectives are to identify published evidence maps and to compare and contrast the presented definitions of evidence mapping, the domains used to classify data in evidence maps, and the form the evidence map takes. Methods We conducted a systematic review of publications that presented results with a process termed “evidence mapping” or included a figure called an “evidence map.” We identified publications from searches of ten databases through 8/21/2015, reference mining, and consulting topic experts. We abstracted the research question, the unit of analysis, the search methods and search period covered, and the country of origin. Data were narratively synthesized. Results Thirty-nine publications met inclusion criteria. Published evidence maps varied in their definition and the form of the evidence map. Of the 31 definitions provided, 67 % described the purpose as identification of gaps and 58 % referenced a stakeholder engagement process or user-friendly product. All evidence maps explicitly used a systematic approach to evidence synthesis. Twenty-six publications referred to a figure or table explicitly called an “evidence map,” eight referred to an online database as the evidence map, and five stated they used a mapping methodology but did not present a visual depiction of the evidence. Conclusions The principal conclusion of our evaluation of studies that call themselves “evidence maps” is that the implied definition of what constitutes an evidence map is a systematic search of a broad field to identify gaps in knowledge and/or future research needs that presents results in a user-friendly format, often a visual figure or graph, or a searchable database. Foundational work is needed to better standardize the methods and products of an evidence map so that researchers and policymakers will know what to expect of this new type of evidence review. Systematic review registration Although an a priori protocol was developed, no registration was completed; this review did not fit the PROSPERO format.

The WHO Classification of Tumours (WCT) guides cancer diagnosis, treatment, and research. However, research evidence in pathology continuously changes, and new evidence emerges. Correct assessment of evidence in the WCT 5th edition (WCT-5) and identification of high level of evidence (LOE) studies based on study design are needed to improve future editions. We aimed at producing exploratory evidence maps for WCT-5 Thoracic Tumours, specifically lung and thymus tumors. We extracted citations from WCT-5, and imported and coded them in EPPI-Reviewer. The maps were plotted using EPPI-Mapper. Maps displayed tumor types (columns), descriptors (rows), and LOE (bubbles using a four-color code). We included 1434 studies addressing 51 lung, and 677 studies addressing 25 thymus tumor types from WCT-5 thoracic tumours volume. Overall, 87.7% (n = 1257) and 80.8% (n = 547) references were low, and 4.1% (n = 59) and 2.2% (n = 15) high LOE for lung and thymus tumors, respectively. Invasive non-mucinous adenocarcinoma of the lung (n = 215; 15.0%) and squamous cell carcinoma of the thymus (n = 93; 13.7%) presented the highest number of references. High LOE was observed for colloid adenocarcinoma of the lung (n = 11; 18.2%) and type AB thymoma (n = 4; 1.4%). Tumor descriptors with the highest number of citations were prognosis and prediction (n = 273; 19.0%) for lung, and epidemiology (n = 186; 28.0%) for thymus tumors. LOE was generally low for lung and thymus tumors. This study represents an initial step in the WCT Evidence Gap Map (WCT-EVI-MAP) project for mapping references in WCT-5 for all tumor types to inform future WCT editions.

Digital technology has become a central aspect of higher education, inherently affecting all aspects of the student experience. It has also been linked to an increase in behavioural, affective and cognitive student engagement, the facilitation of which is a central concern of educators. In order to delineate the complex nexus of technology and student engagement, this article systematically maps research from 243 studies published between 2007 and 2016. Research within the corpus was predominantly undertaken within the United States and the United Kingdom, with only limited research undertaken in the Global South, and largely focused on the fields of Arts & Humanities, Education, and Natural Sciences, Mathematics & Statistics. Studies most often used quantitative methods, followed by mixed methods, with little qualitative research methods employed. Few studies provided a definition of student engagement, and less than half were guided by a theoretical framework. The courses investigated used blended learning and text-based tools (e.g. discussion forums) most often, with undergraduate students as the primary target group. Stemming from the use of educational technology, behavioural engagement was by far the most often identified dimension, followed by affective and cognitive engagement. This mapping article provides the grounds for further exploration into discipline-specific use of technology to foster student engagement.

Urbanization is restructuring ecosystems at an unprecedented pace, with complex and profound consequences for life on Earth. One of the hypothesized trajectories of urban ecosystems and species communities is biotic homogenization, possibly leading to very similar species assemblages in cities across the globe. Urbanization can, however, also have the opposite effect: biotic diversification, with cities, at least at the local scale, becoming biologically more diverse, mainly as a consequence of high species introduction rates and habitat diversification. Applying the hierarchy-of-hypotheses approach, we systematically map and structure the comprehensive body of literature on the urban biotic homogenization (UBH) hypothesis, comprising 225 individual studies (i.e., tests of the hypothesis) retrieved from 145 publications. The UBH hypothesis is studied at multiple levels with a multitude of approaches and underlying assumptions. We show that UBH is generally used with two very different connotations: about half of the studies investigated a potential increase in community similarity across cities, whereas the other half investigated biotic homogenization within cities, the latter being supported more frequently. We also found strong research biases: (1) a taxonomic bias towards birds and plants, (2) a bias towards small and medium distances (<5000 km) in comparisons across cities, (3) a dominance of studies substituting space for time versus true temporal studies, (4) a strong focus on terrestrial versus aquatic systems, (5) more extraurban (including periurban) areas than natural or rural ecosystems for comparison to urban systems, (6) a bias towards taxonomic versus functional, phylogenetic, and temporal homogenization, and (7) more studies undertaken in Europe and North America than in other continents. The overall level of empirical support for the UBH hypothesis was mixed, with 55% of the studies reporting supporting evidence. Results significantly differed when a natural/nature reserve, an extraurban, or rural/agricultural area served as reference to infer biotic homogenization, with homogenization being detected least frequently when urban systems were compared to agricultural, i.e., other anthropogenically influenced, study sites. We provide an evidence map and a bibliographic network and identify key references on UBH with the goal to enhance accessibility and orientation for future research on this topic.

The scientific literature on climate change adaptation has become too large to assess manually. Beyond standard scientometrics, questions about if and how the field is progressing thus remain largely unanswered. Here we provide a novel, inquisitive, computer-assisted evidence mapping methodology that combines expert interviews ( n = 26) and structural topic modelling to evaluate open-ended research questions on progress in the field. We apply this to 62 191 adaptation-relevant scientific publications (1988–2020), selected through supervised machine learning from a comprehensive climate change query. Comparing the literature to key benchmarks of mature adaptation research, our findings align with trends in the adaptation literature observed by most experts: the field is maturing, growing rapidly, and diversifying, with social science and implementation topics arising next to the still-dominant natural sciences and impacts-focused research. Formally assessing the representativeness of IPCC citations, we find evidence of a delay effect for fast-growing areas of research like adaptation strategies and governance. Similarly, we show significant topic biases by geographic location: especially disaster and development-related topics are often studied in Southern countries by authors from the North, while Northern countries dominate governance topics. Moreover, there is a general paucity of research in some highly vulnerable countries. Experts lastly signal a need for meaningful stakeholder involvement. Expanding on the methods presented here would aid the comprehensive and transparent monitoring of adaptation research. For the evidence synthesis community, our methodology provides an example of how to move beyond the descriptive towards the inquisitive and formally evaluating research questions.

The Living Evidence Map Project at the Norwegian Institute of Public Health (NIPH) gives an updated overview of research results and publications. As part of NIPH's mandate to inform evidence-based infection prevention, control and treatment, a large group of experts are continously monitoring, assessing, coding and summarising new COVID-19 publications. Screening tools, coding practice and workflow are incrementally improved, but remain largely manual. This paper describes how deep learning methods have been employed to learn classification and coding from the steadily growing NIPH COVID-19 dashboard data, so as to aid manual classification, screening and preprocessing of the rapidly growing influx of new papers on the subject. Our main objective is to make manual screening scalable through semi-automation, while ensuring high-quality Evidence Map content. We report early results on classifying publication topic and type from titles and abstracts, showing that even simple neural network architectures and text representations can yield acceptable performance.