Systematic literature reviews are a crucial tool in nursing research. They involve a comprehensive analysis of all available research on a specific topic, following a structured protocol to minimize bias. This process ensures a thorough examination of existing evidence to inform clinical practice.

Planning, conducting, and analyzing are key steps in a systematic review. Researchers define criteria, develop a protocol, craft search strategies, and select appropriate sources. They then extract data, assess study quality, and synthesize findings to draw meaningful conclusions for nursing practice.

Planning the Review

Defining Systematic Review and Criteria

• Systematic review involves comprehensive analysis of all available research on a specific topic
• Follows structured, predefined protocol to minimize bias and ensure reproducibility
• Inclusion criteria specify characteristics studies must meet to be included in review
  • May include factors like publication date, study design, population, interventions
• Exclusion criteria outline reasons for rejecting studies from review
  • Can include factors such as language restrictions, small sample sizes, poor methodological quality
• PRISMA statement provides guidelines for conducting and reporting systematic reviews
  • Consists of 27-item checklist and flow diagram to enhance transparency and completeness

Developing a Review Protocol

• Protocol outlines entire review process before it begins
• Includes research question, search strategy, inclusion/exclusion criteria, data extraction methods
• Helps prevent bias by establishing methods prior to knowing study results
• Can be registered with organizations like PROSPERO to increase transparency
• May undergo peer review to ensure quality and comprehensiveness

Conducting the Search

Crafting an Effective Search Strategy

• Search strategy involves developing comprehensive list of relevant search terms
• Includes keywords, subject headings, and synonyms related to research question
• May use controlled vocabulary (MeSH terms) for more precise searching
• Boolean operators (AND, OR, NOT) combine search terms to refine results
  • AND narrows search (diabetes AND exercise)
  • OR broadens search (heart attack OR myocardial infarction)
  • NOT excludes terms (cancer NOT lung)
• Truncation () and wildcards (?) capture variations of terms (nurs for nurse, nursing, nurses)

Selecting Appropriate Information Sources

• Database selection crucial for comprehensive coverage of relevant literature
• Common databases include PubMed, CINAHL, Cochrane Library, Web of Science
• Grey literature encompasses non-commercially published materials
  • Includes conference proceedings, dissertations, government reports
  • Helps reduce publication bias by including unpublished studies
• Hand-searching key journals and reference lists of included studies
• Contacting experts in the field for additional relevant studies or unpublished data

Analyzing the Results

Extracting and Organizing Data

• Data extraction involves systematically collecting relevant information from included studies
• Develop standardized form to ensure consistent data collection across all studies
• Extract key information such as:
  • Study characteristics (authors, publication year, design)
  • Participant demographics
  • Interventions and comparators
  • Outcome measures and results
  • Potential sources of bias
• Use data management software (Excel, RevMan) to organize and store extracted data
• Double data extraction by two independent reviewers reduces errors and bias

Assessing Study Quality and Bias

• Quality assessment evaluates methodological rigor and potential for bias in included studies
• Various tools available depending on study design:
  • Cochrane Risk of Bias tool for randomized controlled trials
  • Newcastle-Ottawa Scale for observational studies
  • CASP checklists for different study types
• Assess factors such as randomization, blinding, allocation concealment, attrition
• Consider how study quality impacts strength of evidence and conclusions drawn
• Use quality assessment results to conduct sensitivity analyses or subgroup analyses
• Narrative synthesis or meta-analysis combines results across studies to draw overall conclusions