Synthesis Research and Review Techniques

Qualitative vs Quantitative Research

Main Types of Questions Answered

• Qualitative: Explores subjective experiences and meanings. Asks Why? (to understand underlying reasons, motivations), How? (to explore processes, mechanisms), Who? (to identify key actors, demographics), When? (to understand timing of events), Where? (to contextualize phenomena).

• Quantitative: Seeks to measure and test objective hypotheses. Asks What? (to identify frequencies, correlations, prevalence, effects).

Participants

• Qualitative: Typically involves a small, purposively recruited population. Participants are selected based on specific characteristics or experiences relevant to the research question, allowing for in-depth exploration and rich data.

• Quantitative: Generally involves a large, randomly-sampled population to ensure generalizability of findings to a broader population. Random sampling aims to minimize bias.

Data Collection Approach

• Qualitative: Employs unstructured or semi-structured methods, allowing for flexibility and emergent themes during data collection. This often involves open-ended conversations or observations.

• Quantitative: Utilizes structured methods, wherein predetermined questions and response options are consistently applied to all participants, ensuring standardization and comparability of data.

Common Data Collection Methods

• Qualitative:

  • Participant observation: Researchers immerse themselves in a setting to observe and understand behaviors and interactions in natural contexts.

  • Interview: In-depth, one-on-one conversations to explore participants' perspectives, experiences, and opinions.

  • Focus Group Discussion: Group interviews facilitating discussion among participants on a specific topic, revealing shared understandings and differing views.

• Quantitative:

  • Questionnaires: Standardized sets of questions administered to a large sample, often using Likert scales or multiple-choice formats.

  • Surveys: Broader data collection instruments often including questionnaires, used to gather information from a large group.

  • Experiments: Controlled studies designed to test causal relationships between variables.

Types of Questions Asked

• Qualitative: Relies on open-ended questions, which encourage detailed, free-form responses, providing rich narrative data and allowing for the discovery of unexpected insights.

• Quantitative: Uses closed-ended questions, offering fixed response options (e.g., yes/no, multiple-choice, rating scales), which are easy to quantify and compare across participants.

Data Collected

• Qualitative: Gathers text data (words, transcripts of interviews, field notes), images, or objects, which provides descriptive and interpretive insights into phenomena.

• Quantitative: Collects numeric data, which can be statistically analyzed to identify patterns, relationships, and differences.

Goal of Data Analysis

• Qualitative: Aims to formulate new theories or generate hypotheses through inductive reasoning, often leading to a deeper understanding of complex social realities.

• Quantitative: Focuses on testing existing hypotheses or theories through deductive reasoning, often involving statistical tests to confirm or refute relationships.

Outcomes Reported

• Qualitative: Presents themes and patterns, offering rich descriptions, in-depth interpretations, and conceptual frameworks derived from the data.

• Quantitative: Reports statistics, including means, frequencies, correlations, and P-values, to describe populations and test hypotheses, often in a generalizable manner.

Synthesis Research

Overview

• Definition: Synthesis research systematically integrates and interprets existing knowledge from previous, independently conducted research projects to gain a broader, more comprehensive understanding of a topic. It does not typically involve collecting new raw data.

• Requirements for Review Articles in Health Sciences: To be considered robust and credible, review articles must adhere to specific standards:

  • Extensive search of the literature: A comprehensive and systematic search strategy is crucial to identify all relevant studies, minimizing publication bias.

  • Extraction of key information from relevant articles: Important data points (e.g., sample size, methods, outcomes) must be systematically extracted and recorded.

  • Clear and concise presentation of this information: Findings should be organized logically and communicated effectively, often using summary tables or narrative synthesis.

Characteristic Descriptions

Common Types of Research (in relation to data use)

• Primary Research: Involves the collection of new data directly from participants or observations to answer a specific research question. This is original research.

• Secondary Research: Utilizes existing data that has already been collected by others (e.g., public datasets, previous studies). Synthesis research, like systematic reviews, falls into this category.

• Tertiary Research: Involves synthesizing or reviewing existing reviews. An example is a 'review of reviews' or an 'umbrella review,' which consolidates findings from multiple systematic reviews on a broader topic.

Types of Studies in Synthesis Research (examples of study designs that can be synthesized)

• Correlational study: Examines the relationship or association between two or more variables, but does not imply causation.

• Case series: Describes the medical history and outcomes of a group of patients with a similar diagnosis or treatment, often used to identify new diseases or adverse effects.

• Cross-sectional study: Observes a defined population at a single point in time to assess the prevalence of disease or exposure.

• Case-control study: Compares individuals with a disease (cases) to individuals without the disease (controls) and looks retrospectively for differences in exposure to risk factors.

• Cohort study: Follows a group of individuals (cohort) over time to observe the incidence of disease and identify risk factors, either prospectively or retrospectively.

• Experimental study: Researchers manipulate one or more variables (interventions) to determine their effect on an outcome, best exemplified by Randomized Controlled Trials (RCTs).

Types of Reviews

Narrative Review

• Description:

  • Provides a unique, often expert-driven perspective on a topic, supported by literature and the author's commentary. It's less systematic and relies heavily on the author's expertise and interpretation.

  • Organized by theme, methodology, chronology, or other logical structures deemed appropriate by the author, allowing for flexibility in presentation.

  • Becoming less common as there is a strong push for more systematic and transparent methods in research synthesis to reduce bias and improve reproducibility.

Systematic Review

• Purpose:

  • Aims to answer a clearly defined primary study question by identifying, appraising, and synthesizing all relevant studies on the topic. It adheres to a rigorous, transparent, and reproducible methodology.

  • Provides a comprehensive summary of evidence, often including a qualitative synthesis of findings, and may also result in a summary statistic if eligible for meta-analysis.

Meta-Analysis

• Description:

  • A statistical technique used in conjunction with a systematic review that combines the statistical results from multiple independent studies to produce a single, more precise numerical estimate of an effect (e.g., treatment efficacy, risk factor association). This is known as a pooled effect size.

Advantages and Considerations

• Narrative Reviews: Are informal, broad in scope, and descriptive. They are often useful for introducing a topic or providing historical context.

  • Limited by the potential for bias, as the selection of literature and its interpretation can be subjective and may not represent the full body of evidence.

• Systematic Reviews: Are structured, transparent, and reproducible, which inherently minimizes bias by following predefined protocols for searching, screening, and data extraction.

• Meta-Analyses: Are statistical extensions of systematic reviews, offering quantitative precision and increased statistical power by combining data.

  • Requires that all studies combined used similar definitions, methods, and populations to ensure valid and meaningful results. Combining heterogeneous studies can lead to misleading conclusions (known as