Navigating Research in Health Technology
This interactive guide distills a comprehensive report on scientific research methodologies. Explore the core principles, quality frameworks, and practical applications of quantitative, qualitative, and mixed methods approaches, especially within Health Technology Assessment (HTA). Use the navigation above to jump between key concepts and interactive tools.
The Two Pillars: Quantitative vs. Qualitative
At the heart of scientific inquiry are two fundamental approaches to gathering and interpreting evidence. This section provides a direct comparison of their core characteristics. While distinct, they are most powerful when seen as complementary parts of a whole research strategy.
Quantitative Research
Focuses on numerical data and statistical analysis to test hypotheses, identify patterns, and make predictions. It seeks objective, measurable, and generalizable truths.
Qualitative Research
Focuses on non-numerical data like text and observations to understand subjective experiences, meanings, and context. It seeks deep, rich, and exploratory insights.
Bridging the Divide: Mixed Methods
Mixed methods research combines quantitative and qualitative approaches to gain a more complete understanding. This integrated approach allows the strengths of one method to offset the weaknesses of the other. Explore the common designs below.
Sequential Explanatory
Quantitative data is collected first, followed by qualitative data to help explain the initial results.
Convergent Design
Quantitative and qualitative data are collected concurrently and then merged for analysis and comparison.
Embedded Design
One dataset is secondary and embedded within a larger study using the other methodology.
QUANTITATIVE STUDY
Ensuring Rigor and Trustworthiness
Both research paradigms have rigorous standards for ensuring quality. While quantitative research focuses on validity and reliability, qualitative research emphasizes trustworthiness. Evidence is then systematically appraised using frameworks like GRADE.
Quantitative Quality Criteria
- Internal Validity: Can we be sure X caused Y?
- External Validity: Do the findings apply to other people/settings?
- Reliability: Would we get the same results if we did it again?
- Objectivity: Are the results free from researcher bias?
Qualitative Trustworthiness Pillars
- Credibility: Do the findings faithfully represent participant reality?
- Transferability: Are the findings relevant to other contexts?
- Dependability: Is the research process logical and documented?
- Confirmability: Are findings based on participants' words, not researcher bias?
Evidence Appraisal: The GRADE Frameworks
Frameworks like GRADE (for quantitative) and GRADE-CERQual (for qualitative) provide a transparent system to rate the level of confidence we can have in research findings, guiding policy and practice.
Evidence Body
(RCTs, Studies)
Factors to Assess
(Risk of Bias, Coherence, etc.)
Confidence Rating
(High, Moderate, Low)
HTA in Practice: An Interactive SWOT Analysis
How do these methodologies apply to Health Technology Assessment (HTA)? Select a research approach and an HTA domain to explore the specific Strengths, Weaknesses, Opportunities, and Threats of each method in a real-world context.
At a Glance: Method Strengths Across Domains
This radar chart synthesizes the SWOT analysis, visualizing the perceived overall strength of each methodology across the different HTA domains.
The Philosophical Lens: Research Paradigms
Every research study is guided by a paradigm—a fundamental worldview about reality and knowledge. These philosophical assumptions shape every choice a researcher makes. Click on a paradigm to explore its core beliefs.
