how to do a systematic literature review in nursing a step by step guide pdf

How to do a systematic literature review in nursing: A step-by-step guide

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How to do a Systematic Literature Review in Nursing: A step-by-step guide (2nd Edition)

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• Literature Review Arts & Humanities 100%
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T1 - How to do a Systematic Literature Review in Nursing: A step-by-step guide (2nd Edition)

AU - Bettany-Saltikov, Josette

AU - McSherry, Robert

PY - 2016/4

Y1 - 2016/4

N2 - This is a step-by-step guide to doing a literature review in nursing, or related healthcare professions, that takes you through every step of the process from start to finish. From writing your review question to writing up your review, this practical book is the perfect workbook companion if you are doing your first literature review for study or clinical practice improvement. The book features sample review case studies to help identify good practice as well as the pitfalls to avoid, and the practical explanations will be invaluable at every stage.

AB - This is a step-by-step guide to doing a literature review in nursing, or related healthcare professions, that takes you through every step of the process from start to finish. From writing your review question to writing up your review, this practical book is the perfect workbook companion if you are doing your first literature review for study or clinical practice improvement. The book features sample review case studies to help identify good practice as well as the pitfalls to avoid, and the practical explanations will be invaluable at every stage.

SN - 9780335263806

BT - How to do a Systematic Literature Review in Nursing: A step-by-step guide (2nd Edition)

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How-to conduct a systematic literature review: A quick guide for computer science research

Angela carrera-rivera.

a Faculty of Engineering, Mondragon University

William Ochoa

Felix larrinaga.

b Design Innovation Center(DBZ), Mondragon University

Associated Data

• No data was used for the research described in the article.

Performing a literature review is a critical first step in research to understanding the state-of-the-art and identifying gaps and challenges in the field. A systematic literature review is a method which sets out a series of steps to methodically organize the review. In this paper, we present a guide designed for researchers and in particular early-stage researchers in the computer-science field. The contribution of the article is the following:

• • Clearly defined strategies to follow for a systematic literature review in computer science research, and
• • Algorithmic method to tackle a systematic literature review.

Graphical abstract

Specifications table

Method details

A Systematic Literature Review (SLR) is a research methodology to collect, identify, and critically analyze the available research studies (e.g., articles, conference proceedings, books, dissertations) through a systematic procedure [12] . An SLR updates the reader with current literature about a subject [6] . The goal is to review critical points of current knowledge on a topic about research questions to suggest areas for further examination [5] . Defining an “Initial Idea” or interest in a subject to be studied is the first step before starting the SLR. An early search of the relevant literature can help determine whether the topic is too broad to adequately cover in the time frame and whether it is necessary to narrow the focus. Reading some articles can assist in setting the direction for a formal review., and formulating a potential research question (e.g., how is semantics involved in Industry 4.0?) can further facilitate this process. Once the focus has been established, an SLR can be undertaken to find more specific studies related to the variables in this question. Although there are multiple approaches for performing an SLR ( [5] , [26] , [27] ), this work aims to provide a step-by-step and practical guide while citing useful examples for computer-science research. The methodology presented in this paper comprises two main phases: “Planning” described in section 2, and “Conducting” described in section 3, following the depiction of the graphical abstract.

Defining the protocol is the first step of an SLR since it describes the procedures involved in the review and acts as a log of the activities to be performed. Obtaining opinions from peers while developing the protocol, is encouraged to ensure the review's consistency and validity, and helps identify when modifications are necessary [20] . One final goal of the protocol is to ensure the replicability of the review.

Define PICOC and synonyms

The PICOC (Population, Intervention, Comparison, Outcome, and Context) criteria break down the SLR's objectives into searchable keywords and help formulate research questions [ 27 ]. PICOC is widely used in the medical and social sciences fields to encourage researchers to consider the components of the research questions [14] . Kitchenham & Charters [6] compiled the list of PICOC elements and their corresponding terms in computer science, as presented in Table 1 , which includes keywords derived from the PICOC elements. From that point on, it is essential to think of synonyms or “alike” terms that later can be used for building queries in the selected digital libraries. For instance, the keyword “context awareness” can also be linked to “context-aware”.

Planning Step 1 “Defining PICOC keywords and synonyms”.

Formulate research questions

Clearly defined research question(s) are the key elements which set the focus for study identification and data extraction [21] . These questions are formulated based on the PICOC criteria as presented in the example in Table 2 (PICOC keywords are underlined).

Research questions examples.

Select digital library sources

The validity of a study will depend on the proper selection of a database since it must adequately cover the area under investigation [19] . The Web of Science (WoS) is an international and multidisciplinary tool for accessing literature in science, technology, biomedicine, and other disciplines. Scopus is a database that today indexes 40,562 peer-reviewed journals, compared to 24,831 for WoS. Thus, Scopus is currently the largest existing multidisciplinary database. However, it may also be necessary to include sources relevant to computer science, such as EI Compendex, IEEE Xplore, and ACM. Table 3 compares the area of expertise of a selection of databases.

Planning Step 3 “Select digital libraries”. Description of digital libraries in computer science and software engineering.

Define inclusion and exclusion criteria

Authors should define the inclusion and exclusion criteria before conducting the review to prevent bias, although these can be adjusted later, if necessary. The selection of primary studies will depend on these criteria. Articles are included or excluded in this first selection based on abstract and primary bibliographic data. When unsure, the article is skimmed to further decide the relevance for the review. Table 4 sets out some criteria types with descriptions and examples.

Planning Step 4 “Define inclusion and exclusion criteria”. Examples of criteria type.

Define the Quality Assessment (QA) checklist

Assessing the quality of an article requires an artifact which describes how to perform a detailed assessment. A typical quality assessment is a checklist that contains multiple factors to evaluate. A numerical scale is used to assess the criteria and quantify the QA [22] . Zhou et al. [25] presented a detailed description of assessment criteria in software engineering, classified into four main aspects of study quality: Reporting, Rigor, Credibility, and Relevance. Each of these criteria can be evaluated using, for instance, a Likert-type scale [17] , as shown in Table 5 . It is essential to select the same scale for all criteria established on the quality assessment.

Planning Step 5 “Define QA assessment checklist”. Examples of QA scales and questions.

Define the “Data Extraction” form

The data extraction form represents the information necessary to answer the research questions established for the review. Synthesizing the articles is a crucial step when conducting research. Ramesh et al. [15] presented a classification scheme for computer science research, based on topics, research methods, and levels of analysis that can be used to categorize the articles selected. Classification methods and fields to consider when conducting a review are presented in Table 6 .

Planning Step 6 “Define data extraction form”. Examples of fields.

The data extraction must be relevant to the research questions, and the relationship to each of the questions should be included in the form. Kitchenham & Charters [6] presented more pertinent data that can be captured, such as conclusions, recommendations, strengths, and weaknesses. Although the data extraction form can be updated if more information is needed, this should be treated with caution since it can be time-consuming. It can therefore be helpful to first have a general background in the research topic to determine better data extraction criteria.

After defining the protocol, conducting the review requires following each of the steps previously described. Using tools can help simplify the performance of this task. Standard tools such as Excel or Google sheets allow multiple researchers to work collaboratively. Another online tool specifically designed for performing SLRs is Parsif.al 1 . This tool allows researchers, especially in the context of software engineering, to define goals and objectives, import articles using BibTeX files, eliminate duplicates, define selection criteria, and generate reports.

Build digital library search strings

Search strings are built considering the PICOC elements and synonyms to execute the search in each database library. A search string should separate the synonyms with the boolean operator OR. In comparison, the PICOC elements are separated with parentheses and the boolean operator AND. An example is presented next:

(“Smart Manufacturing” OR “Digital Manufacturing” OR “Smart Factory”) AND (“Business Process Management” OR “BPEL” OR “BPM” OR “BPMN”) AND (“Semantic Web” OR “Ontology” OR “Semantic” OR “Semantic Web Service”) AND (“Framework” OR “Extension” OR “Plugin” OR “Tool”

Gather studies

Databases that feature advanced searches enable researchers to perform search queries based on titles, abstracts, and keywords, as well as for years or areas of research. Fig. 1 presents the example of an advanced search in Scopus, using titles, abstracts, and keywords (TITLE-ABS-KEY). Most of the databases allow the use of logical operators (i.e., AND, OR). In the example, the search is for “BIG DATA” and “USER EXPERIENCE” or “UX” as a synonym.

Example of Advanced search on Scopus.

In general, bibliometric data of articles can be exported from the databases as a comma-separated-value file (CSV) or BibTeX file, which is helpful for data extraction and quantitative and qualitative analysis. In addition, researchers should take advantage of reference-management software such as Zotero, Mendeley, Endnote, or Jabref, which import bibliographic information onto the software easily.

Study Selection and Refinement

The first step in this stage is to identify any duplicates that appear in the different searches in the selected databases. Some automatic procedures, tools like Excel formulas, or programming languages (i.e., Python) can be convenient here.

In the second step, articles are included or excluded according to the selection criteria, mainly by reading titles and abstracts. Finally, the quality is assessed using the predefined scale. Fig. 2 shows an example of an article QA evaluation in Parsif.al, using a simple scale. In this scenario, the scoring procedure is the following YES= 1, PARTIALLY= 0.5, and NO or UNKNOWN = 0 . A cut-off score should be defined to filter those articles that do not pass the QA. The QA will require a light review of the full text of the article.

Performing quality assessment (QA) in Parsif.al.

Data extraction

Those articles that pass the study selection are then thoroughly and critically read. Next, the researcher completes the information required using the “data extraction” form, as illustrated in Fig. 3 , in this scenario using Parsif.al tool.

Example of data extraction form using Parsif.al.

The information required (study characteristics and findings) from each included study must be acquired and documented through careful reading. Data extraction is valuable, especially if the data requires manipulation or assumptions and inferences. Thus, information can be synthesized from the extracted data for qualitative or quantitative analysis [16] . This documentation supports clarity, precise reporting, and the ability to scrutinize and replicate the examination.

Analysis and Report

The analysis phase examines the synthesized data and extracts meaningful information from the selected articles [10] . There are two main goals in this phase.

The first goal is to analyze the literature in terms of leading authors, journals, countries, and organizations. Furthermore, it helps identify correlations among topic s . Even when not mandatory, this activity can be constructive for researchers to position their work, find trends, and find collaboration opportunities. Next, data from the selected articles can be analyzed using bibliometric analysis (BA). BA summarizes large amounts of bibliometric data to present the state of intellectual structure and emerging trends in a topic or field of research [4] . Table 7 sets out some of the most common bibliometric analysis representations.

Techniques for bibliometric analysis and examples.

Several tools can perform this type of analysis, such as Excel and Google Sheets for statistical graphs or using programming languages such as Python that has available multiple  data visualization libraries (i.e. Matplotlib, Seaborn). Cluster maps based on bibliographic data(i.e keywords, authors) can be developed in VosViewer which makes it easy to identify clusters of related items [18] . In Fig. 4 , node size is representative of the number of papers related to the keyword, and lines represent the links among keyword terms.

[1] Keyword co-relationship analysis using clusterization in vos viewer.

This second and most important goal is to answer the formulated research questions, which should include a quantitative and qualitative analysis. The quantitative analysis can make use of data categorized, labelled, or coded in the extraction form (see Section 1.6). This data can be transformed into numerical values to perform statistical analysis. One of the most widely employed method is frequency analysis, which shows the recurrence of an event, and can also represent the percental distribution of the population (i.e., percentage by technology type, frequency of use of different frameworks, etc.). Q ualitative analysis includes the narration of the results, the discussion indicating the way forward in future research work, and inferring a conclusion.

Finally, the literature review report should state the protocol to ensure others researchers can replicate the process and understand how the analysis was performed. In the protocol, it is essential to present the inclusion and exclusion criteria, quality assessment, and rationality beyond these aspects.

The presentation and reporting of results will depend on the structure of the review given by the researchers conducting the SLR, there is no one answer. This structure should tie the studies together into key themes, characteristics, or subgroups [ 28 ].

SLR can be an extensive and demanding task, however the results are beneficial in providing a comprehensive overview of the available evidence on a given topic. For this reason, researchers should keep in mind that the entire process of the SLR is tailored to answer the research question(s). This article has detailed a practical guide with the essential steps to conducting an SLR in the context of computer science and software engineering while citing multiple helpful examples and tools. It is envisaged that this method will assist researchers, and particularly early-stage researchers, in following an algorithmic approach to fulfill this task. Finally, a quick checklist is presented in Appendix A as a companion of this article.

CRediT author statement

Angela Carrera-Rivera: Conceptualization, Methodology, Writing-Original. William Ochoa-Agurto : Methodology, Writing-Original. Felix Larrinaga : Reviewing and Supervision Ganix Lasa: Reviewing and Supervision.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

Funding : This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant No. 814078.

Carrera-Rivera, A., Larrinaga, F., & Lasa, G. (2022). Context-awareness for the design of Smart-product service systems: Literature review. Computers in Industry, 142, 103730.

1 https://parsif.al/

Data Availability

Handbook of Research Methods in Health Social Sciences pp 805–826 Cite as

Conducting a Systematic Review: A Practical Guide

• Freya MacMillan 2 ,
• Kate A. McBride 3 ,
• Emma S. George 4 &
• Genevieve Z. Steiner 5  
• Reference work entry
• First Online: 13 January 2019

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1 Citations

It can be challenging to conduct a systematic review with limited experience and skills in undertaking such a task. This chapter provides a practical guide to undertaking a systematic review, providing step-by-step instructions to guide the individual through the process from start to finish. The chapter begins with defining what a systematic review is, reviewing its various components, turning a research question into a search strategy, developing a systematic review protocol, followed by searching for relevant literature and managing citations. Next, the chapter focuses on documenting the characteristics of included studies and summarizing findings, extracting data, methods for assessing risk of bias and considering heterogeneity, and undertaking meta-analyses. Last, the chapter explores creating a narrative and interpreting findings. Practical tips and examples from existing literature are utilized throughout the chapter to assist readers in their learning. By the end of this chapter, the reader will have the knowledge to conduct their own systematic review.

• Systematic review
• Search strategy
• Risk of bias
• Heterogeneity
• Meta-analysis
• Forest plot
• Funnel plot
• Meta-synthesis

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How-To Create an Orthopaedic Systematic Review: A Step-by-Step Guide Part I: Study Design

Affiliations.

• 1 Maimonides Medical Center, Department of Orthopaedic Surgery, Brooklyn, NY.
• 2 Sinai Hospital of Baltimore, Rubin Institute for Advanced Orthopedics, Baltimore, Maryland.
• 3 Cleveland Clinic Foundation, Department of Orthopaedic Surgery, Cleveland, OH.
• 4 Sinai Hospital of Baltimore, Rubin Institute for Advanced Orthopedics, Baltimore, Maryland; Northwell Health Orthopaedics, Lenox Hill Hospital, New York, NY. Electronic address: [email protected].
• PMID: 38552865
• DOI: 10.1016/j.arth.2024.03.059

Systematic reviews are conducted through a consistent and reproducible method to search, appraise, and summarize information. Within the evidence-based pyramid, systematic reviews can be at the apex when incorporating high-quality studies, presenting the strongest form of evidence given their synthesis of results from multiple primary studies to level IV evidence, depending on the studies they incorporate. When combined and supplemented with a meta-analysis using statistical methods to pool the results of three or more studies, systematic reviews are powerful tools to help answer research questions. The aim of this review is to serve as a guide on how to: 1) design; 2) execute; and 3) publish an orthopaedic arthroplasty systematic review and meta-analysis. In Part I, we discuss how to develop an appropriate research question as well as source and screen databases. To date, commonly used databases to source studies include PubMed/MEDLINE, Embase, Cochrane Library, Scopus, and Web of Science. Although not all-encompassing, this paper serves as a starting point for those interested in performing and/or critically reviewing lower extremity arthroplasty systematic reviews and meta-analyses.

Keywords: Arthroplasty research; Clinical orthopaedic research; Meta-analysis; Study design; Systematic review.

Copyright © 2024. Published by Elsevier Inc.