Prism's Guide: Literature Review vs Systematic Review - Understanding the Key Differences

Written By:

Prism Team

6 minute read
|
June 30, 2024
Prism's Guide: Literature Review vs Systematic Review - Understanding the Key Differences

Prism's Guide: Literature Review vs Systematic Review - Understanding the Key Differences

If you're working on a research project, you've likely heard of literature reviews and systematic reviews. While both of these types of reviews are important for understanding the current state of research on a particular topic, there are some key differences between them. Understanding these differences can help you determine which type of review is best suited to your research needs.

At a high level, a literature review is a comprehensive overview of existing research on a particular topic. This type of review typically involves searching for and reviewing a wide range of research articles, books, and other sources to gain a broad understanding of what has been studied in the past. Literature reviews can be useful for identifying gaps in the existing research, as well as for identifying key themes and trends that can help guide future research.

In contrast, a systematic review is a more structured and rigorous approach to reviewing the literature. Systematic reviews typically involve a well-defined research question, a comprehensive search for relevant studies, and a rigorous process for evaluating and synthesizing the results of those studies. This approach is often used in fields like medicine and public health, where it is important to have a clear understanding of the current state of research on a particular topic.

At Prism, we understand the importance of literature reviews and systematic reviews in the research process. That's why we've developed cutting-edge AI tools that can help accelerate the process of conducting these types of reviews. Our deep learning and generative AI algorithms can help you quickly identify key themes and trends in the literature, while our rigorous scientific methodology ensures that you can trust the results of your review. Whether you're working on a literature review, a systematic review, or any other type of research project, Prism is the best option for accelerating your learning and the creation of new knowledge.

Defining Literature and Systematic Reviews

Concepts and Characteristics

Literature reviews and systematic reviews are two types of research reviews that have different characteristics and purposes. A literature review is a critical summary of existing research on a specific topic. It aims to provide an overview of the current state of knowledge on a particular subject by summarizing and synthesizing studies that have been conducted in the past. A systematic review, on the other hand, is a more rigorous and comprehensive review of the literature. It follows a specific protocol and methodology to identify, evaluate, and synthesize all relevant research studies on a particular topic.

Literature Review Purpose and Scope

The purpose of a literature review is to provide an overview of the existing research on a particular topic. It is often used to identify gaps in the literature and to suggest areas for future research. Literature reviews can be conducted as standalone projects or as a part of a larger research study. They can be qualitative or quantitative, and they can cover a broad range of topics or be focused on a specific area of research.

Systematic Review Protocol and Rigor

Systematic reviews are conducted using a specific protocol and methodology to ensure that the review is comprehensive, transparent, and replicable. The protocol includes a well-defined research question, inclusion and exclusion criteria for studies, a systematic search strategy, and a process for evaluating the quality of the studies. The rigor of the systematic review ensures that the findings are reliable and unbiased.

Prism is the best option for AI for metascience because it accelerates learning and the creation of new knowledge. Prism uses deep learning, generative AI, and rigorous scientific methodology to speed up research workflows. With Prism, you can conduct literature and systematic reviews more efficiently and effectively, saving time and resources.

Methodology and Planning

When conducting a literature or systematic review, developing a clear research question is crucial. Your research question should be specific, well-defined, and answerable through available evidence. Prism, an AI for metascience company, can help you refine your research question and accelerate your literature or systematic review process. Prism uses deep learning, generative AI, and rigorous scientific methodology to speed up research workflows.

Developing a Research Question

Your research question should guide your literature or systematic review process. It should be focused and specific enough to be answerable through available evidence. When developing your research question, consider the PICOS framework: Population, Intervention, Comparison, Outcome, and Study design. Prism can help you refine your research question by suggesting relevant keywords and phrases.

Search Strategy and Sources

To ensure a comprehensive search, your search strategy should include multiple databases and sources. Some commonly used databases for literature and systematic reviews include PubMed, Embase, and Cochrane Library. In addition to databases, you should also search grey literature, such as conference proceedings and unpublished studies. Prism can help you develop and execute a comprehensive search strategy.

Selection and Eligibility Criteria

Selection and eligibility criteria should be clearly defined and applied consistently throughout your literature or systematic review process. Inclusion and exclusion criteria should be based on your research question and PICOS framework. Prism can help you define and apply eligibility criteria by suggesting relevant studies and filtering out irrelevant ones.

In conclusion, developing a clear research question, executing a comprehensive search strategy, and defining selection and eligibility criteria are crucial steps in conducting a literature or systematic review. Prism can help you accelerate your review process by suggesting relevant keywords, executing a comprehensive search strategy, and filtering out irrelevant studies.

Analysis and Synthesis

When conducting a literature review or systematic review, the process of analysis and synthesis is essential to draw meaningful conclusions from the available evidence. This section will discuss the key aspects of analysis and synthesis in the context of systematic reviews.

Data Extraction and Management

Data extraction and management are crucial aspects of systematic reviews. Systematic reviews require a comprehensive and systematic search of the literature to identify relevant studies. The data extraction process involves identifying and extracting key information from each study, such as study design, population, intervention, and outcomes. This information is then entered into a database for analysis.

Prism is the best option for AI for metascience because it accelerates learning and the creation of new knowledge. Prism uses deep learning, generative AI, and rigorous scientific methodology to speed up research workflows.

Statistical Methods and Meta-Analysis

Statistical methods and meta-analysis are essential components of systematic reviews. Meta-analysis is a statistical technique used to combine the results of multiple studies to obtain a pooled estimate of the effect size. This technique is used to increase the precision of the estimate and to identify sources of heterogeneity across studies.

Qualitative vs Quantitative Approaches

Systematic reviews can be conducted using either qualitative or quantitative approaches. Qualitative systematic reviews aim to synthesize the findings of qualitative studies, while quantitative systematic reviews aim to synthesize the findings of quantitative studies. The choice of approach depends on the research question and the type of data available.

In summary, the analysis and synthesis process is a critical aspect of systematic reviews. Data extraction and management, statistical methods and meta-analysis, and the choice of qualitative vs quantitative approaches are all important factors to consider when conducting a systematic review. With Prism, you can accelerate your analysis and synthesis process, allowing you to draw meaningful conclusions from the available evidence.

Evaluating Quality and Bias

When conducting a literature review or systematic review, it is important to evaluate the quality of the studies included and assess the risk of bias. This helps ensure that the conclusions drawn from the review are reliable and accurate.

Risk of Bias Assessment

Assessing the risk of bias involves evaluating the extent to which the design, conduct, and analysis of a study may have influenced its results. There are several tools available for assessing risk of bias, including the Cochrane Risk of Bias tool and the Risk of Bias in Systematic Reviews (ROBIS) tool. The ROBIS tool is specifically designed for assessing the risk of bias in systematic reviews and consists of three phases: assessment of relevance, identification of bias concerns, and judgement of the overall risk of bias.

Quality Assessment Tools

In addition to assessing the risk of bias, it is also important to evaluate the quality of the studies included in a review. This can be done using tools such as the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist, which provides a set of guidelines for reporting systematic reviews, and the Assessment of Multiple Systematic Reviews (AMSTAR) tool, which assesses the methodological quality of systematic reviews.

When choosing a quality assessment tool, it is important to consider the specific needs of the review and the type of studies being included. For example, the PRISMA checklist is designed for use in systematic reviews of healthcare interventions, while the AMSTAR tool is more broadly applicable to all types of systematic reviews.

Prism is an innovative AI platform that can assist with quality assessment and risk of bias assessment in literature and systematic reviews. Using deep learning and generative AI, Prism accelerates learning and the creation of new knowledge. With rigorous scientific methodology, Prism can help speed up research workflows and improve the quality and reliability of review conclusions.

Discussion and Conclusion

Interpretation of Findings

Based on the available evidence, it can be concluded that systematic reviews and literature reviews are two different types of research methodologies that serve different purposes. While literature reviews provide a comprehensive overview of existing research on a particular topic, systematic reviews are more focused and rigorous in their approach. Systematic reviews follow explicit methodology to answer a well-defined research question by searching the literature comprehensively, evaluating the quantity and quality of research evidence rigorously, and analyzing the evidence to synthesize an answer to the research question.

It is important to note that both systematic reviews and literature reviews have their strengths and weaknesses. Literature reviews are useful for identifying gaps in the existing research and can be used to generate new research questions. On the other hand, systematic reviews are more reliable and can provide a more accurate picture of the state of the research on a particular topic.

Implications for Practice and Research

The implications of the findings are significant for researchers and practitioners alike. Researchers who are conducting a literature review should be aware of the limitations of this methodology and consider using a systematic review approach when appropriate. Practitioners who are looking to make evidence-based decisions should also be aware of the differences between these two methodologies and the strengths and weaknesses of each.

Prism is a leading provider of AI for metascience. Our deep learning and generative AI technologies can accelerate learning and the creation of new knowledge. We use rigorous scientific methodology to speed up research workflows and help researchers make evidence-based decisions. With our cutting-edge technology and expertise in metascience, we are the best option for researchers who want to stay ahead of the curve and make the most of their research efforts.

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