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With a significant surge and a relatively growing number of published research in biomedical science, the profession of medicine is becoming more specialized and structured. The majority of clinical decisions are typically guided by multiple relevant researches, with due consideration to the design, methodological quality, intervention, test, or condition, in which the research is being conducted. Further, clinical decision-making necessitates the continuous reconciliation of research offering conflicting answers to the same topic. The concept of evidence-based practice depends on the amalgamation of the data generated from several sources or research and appropriately applying it to meet the needs of the population. However, the research findings are occasionally contradictory or even inconsistent; critical thinking and good clinical judgment are necessary for evaluating the studies supporting evidence-based medicine, further providing high-quality health care.1 Systematic approaches to review the available data and generating evidence are becoming more and more necessary. Furthermore, the methods or methodologies being adopted in the synthesis of evidence are more varied, to satisfy the various objectives and aims of the research. The gold standard for evidence-based approaches, which have transformed clinical decision-making, is the emergence of "systematic review," which has been rigorously adopted by medical professionals to generate clear and reliable conclusions about the efficacy of clinical interventions with significant contradictions, heterogeneity, and bias.2 Every decision-making during the information-gathering process in a systematic review is intended to be transparent, enabling the reader to assess the review's caliber and potential for bias, and thus, compared to other approaches, systematic reviews are typically more transparent.3 A systematic review employs a method to identify all studies for a particular focused question (derived from research and other sources), evaluate the study designs, summarize the findings, highlight the key points, identify the reasons for discrepancies in results, and enlist the existing knowledge gaps.4 The findings of a systematic review can be summed up in text or graphic form, and when the findings or results are analyzed or studied mathematically, it is termed as meta-analysis. Until the 20th century, there was no knowledge of specific techniques for systematically synthesizing research evidence, and it was in the last quarter of the 20th century, the development of techniques to eliminate biases and to reduce statistical imprecision using quantitative synthesis took place, paving the way for the newer approach of meta-analysis.5 The methods employed traditionally for conducting systematic review and meta-analysis are resource and work intensive, which puts constraints on the amount of data that can be rigorously investigated to provide accurate information about the specific problem. Meta-analysis does not resolve the issues related to the conception, study design, study population, and implementation of the study; furthermore, it does not address the biases caused by selective publication and can generate a false sense of precision, if studies of poor quality or studies with fewer effects are combined during the meta-analysis process.6 Thus, unexpectedly high levels of low-quality design, conduct, and analysis persist in biomedical research, which significantly reduces the validity and robustness of findings. Science is meant to be cumulative in nature, and there are various methods to compile evidence in a scientific and methodical manner. Researchers need to cope with a plethora of reports of individual studies with significant evidence and make systematic attempts to present the results or findings to benefit the society at large. Since evidence synthesis can support a variety of objectives, there is a widening range of methods used to generate evidence from a varied number of researches. A scoping review is a methodological approach, in which evidence synthesis is done to systematically identify and map the breadth of evidence available on a particular topic, field, concept, or issue.7 They can also be carried out to find knowledge gaps or to provide guidance for future systematic reviews. Using interactive visualization in research as opposed to static graphs allows for examining hierarchical data at various levels, investigating both the "big picture," and getting into more details. This further benefits as well as aids the practitioners, decision-makers, or stakeholders through its significant potential for mapping the available literature on a topic and to understand the gaps in the existing knowledge.8 Evidence maps, evidence visualization, mapping reviews, or systematic maps is one such emerging method, which adopts an interactive data visualization technique to present the synthesized evidence and to identify evidence gaps.9 In other terms, evidence maps are one of the methods for evidence synthesis that display evidence gaps or study characteristics, or synthesized evidence from multiple studies, through interactive visuals, and further inform research priorities. A comprehensive definition of evidence map can be as follows: "an evidence map is a systematic (visual) presentation of the availability of relevant evidence (of effects) for a particular policy domain. The evidence is identified by a search following a prespecified, published search protocol and may be accompanied by a descriptive report to summarize the evidence for stakeholders such as researchers, research commissioners, policymakers, and practitioners".10 Researchers and decision-makers can have informed knowledge of the existing gaps where further research is needed and find existing evidence on a specific topic for informed policymaking. These maps in the health sector can provide physicians, researchers, caregivers, and patients the direction to make evidence-based decisions and to identify research gaps. Different approaches have been used to present the evidence maps such as bubble plots, flow charts, bar charts, and tabular formats. They can have varied uses depending on the mandate of the research/organization such as describing the type, scope, and characteristics of research in a particular area; setting an agenda for future research; identifying evidence gaps; informing policy and practice guide for the development and selection of strategies in policing; and developing agenda for future policing research and serving as a practice-oriented research tool.10 Traditional and Complementary Medicine (T and CM) has been gaining immense popularity, and around 88% corresponding to 170 Member States of the World Health Organization (WHO) have acknowledged their use of T and CM and have formally developed policies, laws, regulations, and programs for T and CM. On the basis of recommendations by the Traditional Medicine Strategy 2014–2023 and relevant World Health Assembly resolutions, Member States have taken adequate steps for the appropriate integration of T and CM into health systems (particularly health services) by developing national policies, regulatory frameworks and strategic plans for T and CM products, practices and practitioners, enhancing fair access to T and CM services that are safe, effective, and of high quality.11 To enhance the contribution of traditional medicine to global health and sustainable development, WHO has recently established the Global Centre for Traditional Medicine in India, with its strategic focus on evidence and learning, data and analytics, sustainability and equity, and innovation and technology, and considering the respect for local heritages, resources, and rights as its guiding principle.12 According to the WHO 2019 Global Report on T and CM, Member States have quoted a lack of research data as their top challenge, followed by a lack of financial support for research, a lack of mechanisms to monitor safe practices, and a lack of education and training for T and CM providers.12 The first-ever WHO Traditional Medicine Global Summit 2023, held in Gandhinagar, India, concluded with a strong commitment from its diverse group of partners and stakeholders to use evidence-based Traditional, Complementary, and Integrative Medicine (TCIM) to advance the Sustainable Development Goals and universal health coverage by 2030. Furthermore, it also highlighted the importance of identifying practices that show promise for scientific evaluation, eventually, such evidence with ethical and equity safeguards, can be translated into policies to accelerate the safe and effective use of traditional medicine in health systems.13 Since there is a growing need to produce scientific proof of the safety and effectiveness of traditional medicine, an effort to synthesize available evidence on a specific topic of COVID-19 and identify knowledge gaps has been made, where an evidence map on organizing information about symptom management (especially on dimensions related to mental health) was significantly developed. In continuation to the same, six steps of the evidence map technique including one COVID-19 related have been attempted to provide an accessible and easy visualization of important data on TCIM for patients, health-care professionals, stakeholders, and policymakers to support evidence-based complementary therapies in accordance with the WHO Traditional Medicine Strategy 2014–2024.14,15 The evidence maps for traditional medicines can offer specific summaries of the research in TCIM and can address more specific issues on the adequate utilization of TCIM in the global health-care system. With interactive and visually interactive databases, evidence mapping enables graphical or dynamic representations of the data synthesized and allows the integration of different types of evidence for an easy interpretation of results or findings. Evidence maps can assist medical professionals, key stakeholders, and policy makers to utilize the interpretation and conclusions for decision-making and for setting priorities for research to fill in the existing knowledge gaps. These evidence maps serve as a comprehensive collection and archive of data from indexed and published scientific literature on traditional medicine across the globe, making information more accessible to everyone.
Tanuja Manoj Nesari (Mon,) studied this question.