Mixed Methods Research Overview

Study Notes

Mixed methods research combines qualitative and quantitative data collection and analysis within a single study or series.
Qualitative methods are preferred when a deeper understanding of a phenomenon is needed, or when the richness and context of lived experiences are important.
Quantitative methods are useful for quantifying data, exploring large numbers of variables, and testing hypotheses.
Mixed methods research provides a more complete picture of a phenomenon compared to a single method. This allows for the answers to questions which cannot be answered by one method alone.

Qualitative methods are used when detailed understanding is desired, including lived experiences and contexts.
Quantitative methods are useful when generalizability and specific quantification of data are needed.

Qualitative: Results may not generalize beyond participants, and rigor/validity/reliability may be hard to maintain. Interpretation of findings may be subjective and influenced by the researcher, and researcher biases may not be accounted for.
Quantitative: Limited context or lack of a broader understanding of the participants experience. The researcher's voice may not be heard, or may be perceived as an outsider.

Research questions guide method choice
Offers more complete understanding of phenomena by answering questions that cannot be answered with a single method.
Provides triangulation, increasing the validity of findings through corroboration between data sources.

Inductive Approach: Qualitative data is prioritized, and quantitative data supplements or supports the findings generated through the qualitative data collection.
Deductive Approach: Quantitative data is prioritized and qualitative data provides context, confirms findings, or elucidates findings when unexpected or unexplained deviations occur.

Controversy: There is debate about the appropriateness of combining qualitative and quantitative methods, sometimes viewed as a "trojan horse" for positivism.
Pragmatism: Method selection should be driven by the research question, not the paradigm.
Methodology: Mix methods, but do not mix paradigms
Mixed Method Studies: Conducted across one study or a program. Provides richer perspectives, and answers questions which a single method cannot address. Time and resource usage for mixed method design can be efficient to improve completion rates of studies.

Developing Instruments: Qualitative data to develop instrument validation.
Designing Interventions: Using qualitative data to develop promising interventions, then using quantitative data to rigorously examine efficacy.
Generating Hypotheses: Using qualitative data to explore a phenomenon and quantitatively testing these hypotheses.
Constructing Theories: Qualitative data supports and refines theoretical construction, offering evidence that the theory can be corroborated quantitatively.

QUAL and QUAN; Simultaneous: One method is dominant and the other supports.
QUAL > QUAN; Sequential: Inductive drive, qualitative is dominant; then quantitative.
QUAL and QUAN; Simultaneous: Inductive and deductive forms are used simultaneously.
QUAL > QUAN; Sequential: Inductive drive, qualitative is followed by quantitative.
QUAN and QUAL; Simultaneous: Deductive drive, quantitative is dominant and supported by qualitative data.
QUAN > QUAL; Sequential: Deductive drive, quantitative is dominant; then qualitative.
Examples of Real World Applications:
Medication errors in nursing.