Systematic Review in Research

Systematic Reviews

• Definition: A comprehensive and systematic approach to identify, evaluate, and synthesize all relevant studies on a specific research question.
• Characteristics:
  • Comprehensive search strategy
  • Explicit inclusion and exclusion criteria
  • Critical appraisal of study quality
  • Data extraction and synthesis
• Types:
  • Narrative review: Qualitative summary of existing literature
  • Quantitative review: Statistical analysis of data from multiple studies
• Steps:
  1. Formulate research question
  2. Conduct comprehensive literature search
  3. Select studies based on inclusion and exclusion criteria
  4. Critically appraise study quality
  5. Extract and synthesize data
  6. Draw conclusions and make recommendations

Mixed-Methods Research

• Definition: A research design that combines quantitative and qualitative methods to study a research question.
• Characteristics:
  • Integration of both quantitative and qualitative data
  • Use of multiple methods to achieve a more comprehensive understanding
• Types:
  • Concurrent mixed-methods: Quantitative and qualitative data collected simultaneously
  • Sequential mixed-methods: Quantitative data informs qualitative data collection or vice versa
• Advantages:
  • Provides a more comprehensive understanding of the research question
  • Increases validity and reliability of findings
  • Allows for triangulation of data
• Challenges:
  • Integrating different data types and methods
  • Managing and analyzing large datasets

Content Analysis

• Definition: A research method that involves the systematic analysis of texts, images, or other media to identify patterns and themes.
• Characteristics:
  • Focus on textual or visual data
  • Coding and categorization of data
  • Identification of patterns and themes
• Types:
  • Quantitative content analysis: Focus on frequency and statistical analysis
  • Qualitative content analysis: Focus on interpretation and meaning
• Steps:
  1. Define research question and objectives
  2. Select data collection method (e.g., texts, images)
  3. Develop coding scheme and categorization system
  4. Code and analyze data
  5. Identify patterns and themes
  6. Draw conclusions and make recommendations

Meta-Analysis

• Definition: A statistical method that combines the results of multiple studies to draw more general conclusions.
• Characteristics:
  • Combines data from multiple studies
  • Uses statistical methods to calculate a weighted average of effect sizes
• Types:
  • Fixed-effects model: Assumes a single true effect size
  • Random-effects model: Accounts for variation in effect sizes between studies
• Steps:
  1. Identify research question and inclusion criteria
  2. Conduct comprehensive literature search
  3. Select studies based on inclusion criteria
  4. Extract and convert data into a common metric (e.g., effect size)
  5. Calculate weighted average of effect sizes
  6. Draw conclusions and make recommendations

Systematic Reviews

• Comprehensive and systematic approach to identify, evaluate, and synthesize all relevant studies on a specific research question
• Characteristics: comprehensive search strategy, explicit inclusion and exclusion criteria, critical appraisal of study quality, and data extraction and synthesis
• Types: narrative review (qualitative summary of existing literature) and quantitative review (statistical analysis of data from multiple studies)
• Steps: formulate research question, conduct comprehensive literature search, select studies based on inclusion and exclusion criteria, critically appraise study quality, extract and synthesize data, and draw conclusions and make recommendations

Mixed-Methods Research

• Research design that combines quantitative and qualitative methods to study a research question
• Characteristics: integration of both quantitative and qualitative data, and use of multiple methods to achieve a more comprehensive understanding
• Types: concurrent mixed-methods (quantitative and qualitative data collected simultaneously) and sequential mixed-methods (quantitative data informs qualitative data collection or vice versa)
• Advantages: provides a more comprehensive understanding of the research question, increases validity and reliability of findings, and allows for triangulation of data
• Challenges: integrating different data types and methods, and managing and analyzing large datasets

Content Analysis

• Research method that involves the systematic analysis of texts, images, or other media to identify patterns and themes
• Characteristics: focus on textual or visual data, coding and categorization of data, and identification of patterns and themes
• Types: quantitative content analysis (focus on frequency and statistical analysis) and qualitative content analysis (focus on interpretation and meaning)
• Steps: define research question and objectives, select data collection method, develop coding scheme and categorization system, code and analyze data, identify patterns and themes, and draw conclusions and make recommendations

Meta-Analysis

• Statistical method that combines the results of multiple studies to draw more general conclusions
• Characteristics: combines data from multiple studies, uses statistical methods to calculate a weighted average of effect sizes
• Types: fixed-effects model (assumes a single true effect size) and random-effects model (accounts for variation in effect sizes between studies)
• Steps: identify research question and inclusion criteria, conduct comprehensive literature search, select studies based on inclusion criteria, extract and convert data into a common metric, calculate weighted average of effect sizes, and draw conclusions and make recommendations