How to conduct a meta analysis example

how to conduct a meta analysis example

How to conduct a qualitative meta-analysis: Tailoring methods to enhance methodological integrity

steps from a published paper on meta analysis and systematic review of the e ectiveness of salt restricted diet on blood pressure control. This paper is a basic introduction to the process of meta-analysis. In subse-quent papers in this series, we will discuss how you can conduct meta analysis of diagnostic and screeningCited by: 3. Feb 24, The write up of the systematic review and meta-analysis requires the use of the PRISMA or theMeta-analysis of Observational Studies in Epidemiology [MOOSE] checklist. This is a checklist for reporting systematic literature reviews and meta-analyses and it outlines what details should be reported in each section of a high-quality systematic review.

Although qualitative research has long been of interest in the field of psychology, meta-analyses of qualitative literatures sometimes called meta-syntheses are still quite rare. Like quantitative meta-analyses, these methods function to aggregate findings and identify patterns across metx studies, but their aims, procedures, meya methodological considerations may vary. Objective: This paper explains the function of qualitative meta-analyses and their methodological development.

Recommendations have broad relevance but are framed with an eye toward their use in psychotherapy research. Rather than arguing for the adoption of any single meta-method, this paper advocates for considering how how to use external sd card as internal memory can best be selected and adapted to enhance a meta-study's conudct integrity.

Method: Through the paper, recommendations are provided to help researchers identify procedures that can best serve their studies' specific goals. Meta-analysts are encouraged to consider the methodological integrity of their studies in relation to central research processes, including identifying a set of primary research studies, transforming primary findings cknduct initial units of data for a meta-analysis, developing hoe or themes, and communicating findings.

Conclusion: The paper provides guidance for researchers who desire to tailor meta-analytic methods to meet their particular goals while enhancing the rigor of their research. Keywords: meta-synthesis; methodological integrity; psychotherapy; qualitative meta-analysis; trustworthiness.

Abstract Although qualitative research has long been of interest in the field of psychology, meta-analyses of qualitative literatures sometimes called meta-syntheses are still quite rare.

Publication types Review.

References

Jun 15, Step-By-Step Guide to conduct your Meta Analysis. Step 1: Identify studies and Employ Inclusion/Exclusion criteria to Titles and Abstracts. Step 2: Exclude Studies that evidently meet the Exclusion Criteria predetermined by you. Step 3: Download and save the full text of the remaining research studies/articles. There are two ways to conceptualise meta-analysis: fixed effects and random effects models3. The fixed-effect model assumes that studies in the meta-analysis are sampled from a population in which the average effect size is fixed. Put another way, sample effect sizes should be homogenous because they come from the same populationFile Size: KB. Meta-analysts are encouraged to consider the methodological integrity of their studies in relation to central research processes, including identifying a set of primary research studies, transforming primary findings into initial units of data for a meta-analysis, developing categories or themes, and communicating likedatingall.com by:

Tropical Medicine and Health volume 47 , Article number: 46 Cite this article. Metrics details. The massive abundance of studies relating to tropical medicine and health has increased strikingly over the last few decades. It is not easy to be done as there are obstacles that could face the researcher. The amount of studies published in the biomedical literature, especially tropical medicine and health, has increased strikingly over the last few decades.

This massive abundance of literature makes clinical medicine increasingly complex, and knowledge from various researches is often needed to inform a particular clinical decision. However, available studies are often heterogeneous with regard to their design, operational quality, and subjects under study and may handle the research question in a different way, which adds to the complexity of evidence and conclusion synthesis [ 1 ].

Differing from a systematic review, unsystematic narrative review tends to be descriptive, in which the authors select frequently articles based on their point of view which leads to its poor quality.

A systematic review, on the other hand, is defined as a review using a systematic method to summarize evidence on questions with a detailed and comprehensive plan of study. Furthermore, despite the increasing guidelines for effectively conducting a systematic review, we found that basic steps often start from framing question, then identifying relevant work which consists of criteria development and search for articles, appraise the quality of included studies, summarize the evidence, and interpret the results [ 2 , 3 ].

However, those simple steps are not easy to be reached in reality. There are many troubles that a researcher could be struggled with which has no detailed indication. To solve those hindrances, we recommend a flow diagram Fig. Detailed flow diagram guideline for systematic review and meta-analysis steps. All the explained methods feature the standards followed internationally, with our compiled experience in the conduct of SR beside it, which we think proved some validity.

This is a SR under conduct by a couple of researchers teaming in a research group, moreover, as the outbreak of Ebola which took place in Africa resulted in a significant mortality and morbidity.

Furthermore, since there are many published and ongoing trials assessing the safety of Ebola vaccines, we thought this would provide a great opportunity to tackle this hotly debated issue. Moreover, Ebola started to fire again and new fatal outbreak appeared in the Democratic Republic of Congo since August , which caused infection to more than people according to the World Health Organization, and people have been killed till now. Hence, it is considered the second worst Ebola outbreak, after the first one in West Africa in , which infected more than 26, and killed about 11, people along outbreak course.

Therefore, a clear, logical, and well-defined research question should be formulated. When we apply this to our assumed research topic, being of qualitative nature, the use of SPIDER approach is more valid. PICO is usually used for systematic review and meta-analysis of clinical trial study. For the observational study without intervention or comparator , in many tropical and epidemiological questions, it is usually enough to use P Patient and O outcome only to formulate a research question.

We must indicate clearly the population P , then intervention I or exposure. Next, it is necessary to compare C the indicated intervention with other interventions, i. Finally, we need to clarify which are our relevant outcomes.

To facilitate comprehension, we choose the Ebola virus disease EVD as an example. Currently, the vaccine for EVD is being developed and under phase I, II, and III clinical trials; we want to know whether this vaccine is safe and can induce sufficient immunogenicity to the subjects. P: healthy subjects human , I: vaccination, C: placebo, O: safety or adverse effects.

We recommend a preliminary search to identify relevant articles, ensure the validity of the proposed idea, avoid duplication of previously addressed questions, and assure that we have enough articles for conducting its analysis. Moreover, themes should focus on relevant and important health-care issues, consider global needs and values, reflect the current science, and be consistent with the adopted review methods.

Gaining familiarity with a deep understanding of the study field through relevant videos and discussions is of paramount importance for better retrieval of results. If we ignore this step, our study could be canceled whenever we find out a similar study published before. This means we are wasting our time to deal with a problem that has been tackled for a long time.

While doing this step, we identify a systematic review and meta-analysis of determinant factors influencing antibody response from vaccination of Ebola vaccine in non-human primate and human [ 7 ], which is a relevant paper to read to get a deeper insight and identify gaps for better formulation of our research question or purpose.

We can still conduct systematic review and meta-analysis of Ebola vaccine because we evaluate safety as a different outcome and different population only human. Eligibility criteria are based on the PICO approach, study design, and date.

Exclusion criteria mostly are unrelated, duplicated, unavailable full texts, or abstract-only papers. These exclusions should be stated in advance to refrain the researcher from bias. The inclusion criteria would be articles with the target patients, investigated interventions, or the comparison between two studied interventions. Briefly, it would be articles which contain information answering our research question.

But the most important is that it should be clear and sufficient information, including positive or negative, to answer the question. For the topic we have chosen, we can make inclusion criteria: 1 any clinical trial evaluating the safety of Ebola vaccine and 2 no restriction regarding country, patient age, race, gender, publication language, and date. Exclusion criteria are as follows: 1 study of Ebola vaccine in non-human subjects or in vitro studies; 2 study with data not reliably extracted, duplicate, or overlapping data; 3 abstract-only papers as preceding papers, conference, editorial, and author response theses and books; 4 articles without available full text available; and 5 case reports, case series, and systematic review studies.

A standard search strategy is used in PubMed, then later it is modified according to each specific database to get the best relevant results. The basic search strategy is built based on the research question formulation i.

Search strategies are constructed to include free-text terms e. Additionally, we advise not to use terms for the Outcomes as their inclusion might hinder the database being searched to retrieve eligible studies because the used outcome is not mentioned obviously in the articles. The improvement of the search term is made while doing a trial search and looking for another relevant term within each concept from retrieved papers. Because the study for this topic is limited, we do not include outcome term safety and immunogenicity in the search term to capture more studies.

Researchers should consider to choose relevant database according to the research topic. Some databases do not support the use of Boolean or quotation; otherwise, there are some databases that have special searching way. Therefore, we need to modify the initial search terms for each database to get appreciated results; therefore, manipulation guides for each online database searches are presented in Additional file 5 : Table S2.

The detailed search strategy for each database is found in Additional file 5 : Table S3. The search term that we created in PubMed needs customization based on a specific characteristic of the database. An example for Google Scholar advanced search for our topic is as follows:. Finally, all records are collected into one Endnote library in order to delete duplicates and then to it export into an excel sheet.

Using remove duplicating function with two options is mandatory. All references which have 1 the same title and author, and published in the same year, and 2 the same title and author, and published in the same journal, would be deleted.

References remaining after this step should be exported to an excel file with essential information for screening. Protocol registration at an early stage guarantees transparency in the research process and protects from duplication problems. It is recommended that researchers send it to the principal investigator PI to revise it, then upload it to registry sites. Decisions to select retrieved articles for further assessment are based on eligibility criteria, to minimize the chance of including non-relevant articles.

According to the Cochrane guidance, two reviewers are a must to do this step, but as for beginners and junior researchers, this might be tiresome; thus, we propose based on our experience that at least three reviewers should work independently to reduce the chance of error, particularly in teams with a large number of authors to add more scrutiny and ensure proper conduct.

Mostly, the quality with three reviewers would be better than two, as two only would have different opinions from each other, so they cannot decide, while the third opinion is crucial. And here are some examples of systematic reviews which we conducted following the same strategy by a different group of researchers in our research group and published successfully, and they feature relevant ideas to tropical medicine and disease [ 9 , 10 , 11 ].

In this step, duplications will be removed manually whenever the reviewers find them out. When there is a doubt about an article decision, the team should be inclusive rather than exclusive, until the main leader or PI makes a decision after discussion and consensus. All excluded records should be given exclusion reasons. Many search engines provide links for free to access full-text articles. In case not found, we can search in some research websites as ResearchGate, which offer an option of direct full-text request from authors.

Additionally, exploring archives of wanted journals, or contacting PI to purchase it if available. Similarly, 23 reviewers work independently to decide about included full texts according to eligibility criteria, with reporting exclusion reasons of articles.

In case any disagreement has occurred, the final decision has to be made by discussion. One has to exhaust all possibilities to reduce bias by performing an explicit hand-searching for retrieval of reports that may have been dropped from first search [ 12 ]. Each of the abovementioned methods can be performed by 23 independent reviewers, and all the possible relevant article must undergo further scrutiny against the inclusion criteria, after following the same records yielded from electronic databases, i.

Similarly, the number of included articles has to be stated before addition to the overall included records. This step entitles data collection from included full-texts in a structured extraction excel sheet, which is previously pilot-tested for extraction using some random studies. We recommend extracting both adjusted and non-adjusted data because it gives the most allowed confounding factor to be used in the analysis by pooling them later [ 13 ].

The process of extraction should be executed by 23 independent reviewers. Mostly, the sheet is classified into the study and patient characteristics, outcomes, and quality assessment QA tool. Data presented in graphs should be extracted by software tools such as Web plot digitizer [ 14 ]. Most of the equations that can be used in extraction prior to analysis and estimation of standard deviation SD from other variables is found inside Additional file 5 : File S2 with their references as Hozo et al.

We recommend that 23 reviewers independently assess the quality of the studies and add to the data extraction form before the inclusion into the analysis to reduce the risk of bias.

In the NIH tool for observational studiescohort and cross-sectionalas in this EBOLA case, to evaluate the risk of bias, reviewers should rate each of the 14 items into dichotomous variables: yes, no, or not applicable. An overall score is calculated by adding all the items scores as yes equals one, while no and NA equals zero. A score will be given for every paper to classify them as poor, fair, or good conducted studies, where a score from 05 was considered poor, 69 as fair, and 1014 as good.

In the EBOLA case example above, authors can extract the following information: name of authors, country of patients, year of publication, study design case report, cohort study, or clinical trial or RCT , sample size, the infected point of time after EBOLA infection, follow-up interval after vaccination time, efficacy, safety, adverse effects after vaccinations, and QA sheet Additional file 6 : Data S1. Due to the expected human error and bias, we recommend a data checking step, in which every included article is compared with its counterpart in an extraction sheet by evidence photos, to detect mistakes in data.

We advise assigning articles to 23 independent reviewers, ideally not the ones who performed the extraction of those articles. When resources are limited, each reviewer is assigned a different article than the one he extracted in the previous stage. Investigators use different methods for combining and summarizing findings of included studies. Before analysis, there is an important step called cleaning of data in the extraction sheet, where the analyst organizes extraction sheet data in a form that can be read by analytical software.

The analysis consists of 2 types namely qualitative and quantitative analysis. Qualitative analysis mostly describes data in SR studies, while quantitative analysis consists of two main types: MA and network meta-analysis NMA. Subgroup, sensitivity, cumulative analyses, and meta-regression are appropriate for testing whether the results are consistent or not and investigating the effect of certain confounders on the outcome and finding the best predictors. Publication bias should be assessed to investigate the presence of missing studies which can affect the summary.

Other Ebola vaccines were not meta-analyzed because of the limited number of studies instead, it will be included for narrative review. The imaginary data for vaccine safety meta-analysis can be accessed in Additional file 7 : Data S2.



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