Formulating research questions – A systematic review attempts to gather all available empirical research by using clearly defined, systematic methods to obtain answers to a specific question. A meta-analysis is the statistical process of analyzing and combining results from several similar studies.
Here, the definition of the word “similar” is not made clear, but when selecting a topic for the meta-analysis, it is essential to ensure that the different studies present data that can be combined. If the studies contain data on the same topic that can be combined, a meta-analysis can even be performed using data from only two studies.
However, study selection via a systematic review is a precondition for performing a meta-analysis, and it is important to clearly define the Population, Intervention, Comparison, Outcomes (PICO) parameters that are central to evidence-based research.
Is meta synthesis and systematic review the same?
Background – Metasynthesis—the systematic review and integration of findings from qualitative studies—is an emerging technique in medical research that can use many different methods. Nevertheless, the method must be appropriate to the specific scientific field in which it is used.
Is systematic review and meta-analysis qualitative or quantitative?
Meta-analysis is a quantitative method that uses and synthesizes data from multiple individual studies to arrive at one or more conclusions.
What are the weaknesses of systematic review and meta-analysis?
Abstract – Systematic reviews systematically evaluate and summarize current knowledge and have many advantages over narrative reviews. Meta-analyses provide a more reliable and enhanced precision of effect estimate than do individual studies. Systematic reviews are invaluable for defining the methods used in subsequent studies, but, as retrospective research projects, they are subject to bias.
Rigorous research methods are essential, and the quality depends on the extent to which scientific review methods are used. Systematic reviews can be misleading, unhelpful, or even harmful when data are inappropriately handled; meta-analyses can be misused when the difference between a patient seen in the clinic and those included in the meta-analysis is not considered.
Furthermore, systematic reviews cannot answer all clinically relevant questions, and their conclusions may be difficult to incorporate into practice. They should be reviewed on an ongoing basis. As clinicians, we need proper methodological training to perform good systematic reviews and must ask the appropriate questions before we can properly interpret such a review and apply its conclusions to our patients.
What are the disadvantages of systematic reviews and meta-analyses?
These may include risks of bias, such as selection bias, inadequate blinding, attrition bias, and selective outcome reporting; inconsistency that includes clinical or statistical heterogeneity; and imprecision that can lead to Type I and Type II errors.
What are the three main types of literature review?
Over the years, numerous types of literature reviews have emerged, but the four main types are traditional or narrative, systematic, meta-analysis and meta-synthesis.
What is the first step in systematic review?
STEP 1: FRAMING THE QUESTION – The research question may initially be stated as a query in free form but reviewers prefer to pose it in a structured and explicit way. The relations between various components of the question and the structure of the research design are shown in Figure 1, This paper focuses only on the question of safety related to the outcomes described below. Structured questions for systematic reviews and relations between question components in a comparative study Box 1 The steps in a systematic review
Step 1: Framing questions for a review The problems to be addressed by the review should be specified in the form of clear, unambiguous and structured questions before beginning the review work. Once the review questions have been set, modifications to the protocol should be allowed only if alternative ways of defining the populations, interventions, outcomes or study designs become apparent Step 2: Identifying relevant work The search for studies should be extensive. Multiple resources (both computerized and printed) should be searched without language restrictions. The study selection criteria should flow directly from the review questions and be specified a priori, Reasons for inclusion and exclusion should be recorded Step 3: Assessing the quality of studies Study quality assessment is relevant to every step of a review. Question formulation (Step 1) and study selection criteria (Step 2) should describe the minimum acceptable level of design. Selected studies should be subjected to a more refined quality assessment by use of general critical appraisal guides and design-based quality checklists (Step 3). These detailed quality assessments will be used for exploring heterogeneity and informing decisions regarding suitability of meta-analysis (Step 4). In addition they help in assessing the strength of inferences and making recommendations for future research (Step 5) Step 4: Summarizing the evidence Data synthesis consists of tabulation of study characteristics, quality and effects as well as use of statistical methods for exploring differences between studies and combining their effects (meta-analysis). Exploration of heterogeneity and its sources should be planned in advance (Step 3). If an overall meta-analysis cannot be done, subgroup meta-analysis may be feasible Step 5: Interpreting the findings The issues highlighted in each of the four steps above should be met. The risk of publication bias and related biases should be explored. Exploration for heterogeneity should help determine whether the overall summary can be trusted, and, if not, the effects observed in high-quality studies should be used for generating inferences. Any recommendations should be graded by reference to the strengths and weaknesses of the evidence
How many studies do you need for a meta-analysis?
Two studies is a sufficient number to perform a meta-analysis, provided that those two studies can be meaningfully pooled and provided their results are sufficiently ‘similar’.