Choosing the right methodological approach is one of the most important —and sometimes most challenging— decisions in academic research. Should I use quantitative methods, qualitative methods, or both? Can I combine them? At what stage of the process? These are common questions for those beginning a thesis or research project and lead us to three major approaches: single-method, multi-method, and mixed methods.
This article walks you through the key characteristics of each approach, their advantages, and how to choose the one best suited to the phenomenon you are studying.
Why does the methodological approach matter?
For a long time, academic research was divided between two “camps”: the quantitative approach, which measures and quantifies, and the qualitative approach, which explores and interprets. Over time, however, it became evident that social, educational, and human phenomena are far too complex to be understood from a single perspective.
Often, neither quantitative nor qualitative data alone are sufficient to grasp the full scope of a phenomenon. This has led to the development of more integrative approaches, such as the multi-method approach and mixed methods, which allow for a more comprehensive understanding.
Single-method: Depth from a single perspective
The single-method approach is the most traditional and simplest to apply. It involves using only one type of methodology throughout the entire research process: quantitative (such as surveys or statistical analyses) or qualitative (such as interviews, focus groups, or document analysis). Its main advantage is internal coherence, as the entire design follows a single epistemological and technical logic.
In the social field, a study measuring citizen satisfaction with public services in rural areas through large-scale structured surveys is a typical application of this approach. In education, a study based solely on semi-structured interviews with novice teachers to explore their perceptions of technology use in the classroom allows for in-depth qualitative analysis. In health, the statistical analysis of Type 2 diabetes incidence in a community over the past ten years, using hospital record data, exemplifies a purely quantitative logic.
This approach is particularly recommended when the goal is to delve deeply into one angle of the phenomenon, though it may be limited in addressing complex realities that require multiple levels of analysis.
Multi-method: Diversity of techniques, independence of paradigms
The multi-method approach involves using more than one data collection method, typically combining qualitative and quantitative techniques applied independently. Throughout the research process, each method is conducted separately —either in different stages or with distinct objectives— and the results are compared or triangulated at the end.
In social research, a study on access to housing might first include a statistical analysis of public records to obtain hard data, followed by interviews with community leaders to gather subjective perceptions, without directly merging the sources. In the educational field, a team might use standardized tests to assess academic performance in urban schools and, at the same time, carry out classroom observations to understand teaching dynamics, keeping the analyses separate. In health research, a survey on symptoms and impacts might be conducted in an Indigenous community, while community newsletters are reviewed and health promoters interviewed. These findings are then brought together in the final discussion, though the data were not integrated during earlier phases.
This approach is useful when a phenomenon needs to be examined from different angles, without requiring data integration from the outset.
Mixed methods: Integration from the design stage
Mixed methods represent a more advanced approach, where the integration of qualitative and quantitative data is planned from the beginning of the research design. In this case, both methodologies not only coexist but are intentionally connected throughout the different stages of the process, aiming to enhance the understanding of the phenomenon.
In the social field, a study on youth unemployment might combine surveys conducted with unemployed youth and focus groups that explore their experiences, aspirations, and perceptions, with integrated analysis to explain both the scope and causes of the issue. In education, research might evaluate the impact of project-based learning using standardized tests while also analyzing student portfolios and interviews with teachers, cross-referencing academic results with lived experiences. In health, a study on treatment adherence among patients with hypertension might combine a questionnaire on medication frequency with interviews that explore cultural or economic barriers, analyzing both sources together.
This approach is particularly valuable when it is necessary to understand not only the “how much” or “what,” but also the “why” and “how” of the phenomena, articulating multiple layers of reality.
How do they differ?
| Criterion | Single-method | Multi-method | Mixed methods |
|---|---|---|---|
| Number of methods | One only (either qualitative or quantitative) | Two or more, applied separately | Two or more, integrated from the design |
| Integration point | Not applicable | At the end, during interpretation | Throughout the process: design, data collection, and analysis |
| Epistemological paradigm | A single one | May involve multiple paradigms | Generally aims for a shared epistemological base |
| Complexity | Low | Medium | High |
How to choose the right approach?
It depends on several factors:
- How complex is the phenomenon? If it has many dimensions, integrative approaches are recommended.
- What are your research objectives? If you seek depth in a single aspect, a single-method approach may suffice.
- How much time and resources do you have? Mixed methods typically require more planning and skills.
- What are your strengths as a researcher? Not all approaches fit all people or teams.
Single-method, multi-method, and mixed methods are not rivals, but rather complementary options for addressing different types of research questions. The key is to choose wisely, based on the problem, the goals, and the context. Sometimes, less is more. Other times, integrating multiple methods is the only way to fully grasp the complexity of reality.
