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• Mixed Methods Research | Definition, Guide & Examples

Mixed Methods Research | Definition, Guide & Examples

Published on August 13, 2021 by Tegan George . Revised on June 22, 2023.

Mixed methods research combines elements of quantitative research and qualitative research in order to answer your research question . Mixed methods can help you gain a more complete picture than a standalone quantitative or qualitative study, as it integrates benefits of both methods.

Mixed methods research is often used in the behavioral, health, and social sciences, especially in multidisciplinary settings and complex situational or societal research.

• To what extent does the frequency of traffic accidents ( quantitative ) reflect cyclist perceptions of road safety ( qualitative ) in Amsterdam?
• How do student perceptions of their school environment ( qualitative ) relate to differences in test scores ( quantitative ) ?
• How do interviews about job satisfaction at Company X ( qualitative ) help explain year-over-year sales performance and other KPIs ( quantitative ) ?
• How can voter and non-voter beliefs about democracy ( qualitative ) help explain election turnout patterns ( quantitative ) in Town X?
• How do average hospital salary measurements over time (quantitative) help to explain nurse testimonials about job satisfaction (qualitative) ?

Table of contents

When to use mixed methods research, mixed methods research designs, advantages of mixed methods research, disadvantages of mixed methods research, other interesting articles, frequently asked questions.

Mixed methods research may be the right choice if your research process suggests that quantitative or qualitative data alone will not sufficiently answer your research question. There are several common reasons for using mixed methods research:

• Generalizability : Qualitative research usually has a smaller sample size , and thus is not generalizable. In mixed methods research, this comparative weakness is mitigated by the comparative strength of “large N,” externally valid quantitative research.
• Contextualization: Mixing methods allows you to put findings in context and add richer detail to your conclusions. Using qualitative data to illustrate quantitative findings can help “put meat on the bones” of your analysis.
• Credibility: Using different methods to collect data on the same subject can make your results more credible. If the qualitative and quantitative data converge, this strengthens the validity of your conclusions. This process is called triangulation .

As you formulate your research question , try to directly address how qualitative and quantitative methods will be combined in your study. If your research question can be sufficiently answered via standalone quantitative or qualitative analysis, a mixed methods approach may not be the right fit.

But mixed methods might be a good choice if you want to meaningfully integrate both of these questions in one research study.

Keep in mind that mixed methods research doesn’t just mean collecting both types of data; you need to carefully consider the relationship between the two and how you’ll integrate them into coherent conclusions.

Mixed methods can be very challenging to put into practice, and comes with the same risk of research biases as standalone studies, so it’s a less common choice than standalone qualitative or qualitative research.

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There are different types of mixed methods research designs . The differences between them relate to the aim of the research, the timing of the data collection , and the importance given to each data type.

As you design your mixed methods study, also keep in mind:

• Your research approach ( inductive vs deductive )
• Your research questions
• What kind of data is already available for you to use
• What kind of data you’re able to collect yourself.

Here are a few of the most common mixed methods designs.

Convergent parallel

In a convergent parallel design, you collect quantitative and qualitative data at the same time and analyze them separately. After both analyses are complete, compare your results to draw overall conclusions.

• On the qualitative side, you analyze cyclist complaints via the city’s database and on social media to find out which areas are perceived as dangerous and why.
• On the quantitative side, you analyze accident reports in the city’s database to find out how frequently accidents occur in different areas of the city.

In an embedded design, you collect and analyze both types of data at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other.

This is a good approach to take if you have limited time or resources. You can use an embedded design to strengthen or supplement your conclusions from the primary type of research design.

Explanatory sequential

In an explanatory sequential design, your quantitative data collection and analysis occurs first, followed by qualitative data collection and analysis.

You should use this design if you think your qualitative data will explain and contextualize your quantitative findings.

Exploratory sequential

In an exploratory sequential design, qualitative data collection and analysis occurs first, followed by quantitative data collection and analysis.

You can use this design to first explore initial questions and develop hypotheses . Then you can use the quantitative data to test or confirm your qualitative findings.

“Best of both worlds” analysis

Combining the two types of data means you benefit from both the detailed, contextualized insights of qualitative data and the generalizable , externally valid insights of quantitative data. The strengths of one type of data often mitigate the weaknesses of the other.

For example, solely quantitative studies often struggle to incorporate the lived experiences of your participants, so adding qualitative data deepens and enriches your quantitative results.

Solely qualitative studies are often not very generalizable, only reflecting the experiences of your participants, so adding quantitative data can validate your qualitative findings.

Method flexibility

Mixed methods are less tied to disciplines and established research paradigms. They offer more flexibility in designing your research, allowing you to combine aspects of different types of studies to distill the most informative results.

Mixed methods research can also combine theory generation and hypothesis testing within a single study, which is unusual for standalone qualitative or quantitative studies.

Mixed methods research is very labor-intensive. Collecting, analyzing, and synthesizing two types of data into one research product takes a lot of time and effort, and often involves interdisciplinary teams of researchers rather than individuals. For this reason, mixed methods research has the potential to cost much more than standalone studies.

Differing or conflicting results

If your analysis yields conflicting results, it can be very challenging to know how to interpret them in a mixed methods study. If the quantitative and qualitative results do not agree or you are concerned you may have confounding variables , it can be unclear how to proceed.

Due to the fact that quantitative and qualitative data take two vastly different forms, it can also be difficult to find ways to systematically compare the results, putting your data at risk for bias in the interpretation stage.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question. It’s a research strategy that can help you enhance the validity and credibility of your findings.

Triangulation is mainly used in qualitative research , but it’s also commonly applied in quantitative research . Mixed methods research always uses triangulation.

These are four of the most common mixed methods designs :

• Convergent parallel: Quantitative and qualitative data are collected at the same time and analyzed separately. After both analyses are complete, compare your results to draw overall conclusions. 
• Embedded: Quantitative and qualitative data are collected at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other.
• Explanatory sequential: Quantitative data is collected and analyzed first, followed by qualitative data. You can use this design if you think your qualitative data will explain and contextualize your quantitative findings.
• Exploratory sequential: Qualitative data is collected and analyzed first, followed by quantitative data. You can use this design if you think the quantitative data will confirm or validate your qualitative findings.

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• What is mixed methods research?

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20 February 2023

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By blending both quantitative and qualitative data, mixed methods research allows for a more thorough exploration of a research question. It can answer complex research queries that cannot be solved with either qualitative or quantitative research .

Analyze your mixed methods research

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Mixed methods research combines the elements of two types of research: quantitative and qualitative.

Quantitative data is collected through the use of surveys and experiments, for example, containing numerical measures such as ages, scores, and percentages. 

Qualitative data involves non-numerical measures like beliefs, motivations, attitudes, and experiences, often derived through interviews and focus group research to gain a deeper understanding of a research question or phenomenon.

Mixed methods research is often used in the behavioral, health, and social sciences, as it allows for the collection of numerical and non-numerical data.

• When to use mixed methods research

Mixed methods research is a great choice when quantitative or qualitative data alone will not sufficiently answer a research question. By collecting and analyzing both quantitative and qualitative data in the same study, you can draw more meaningful conclusions. 

There are several reasons why mixed methods research can be beneficial, including generalizability, contextualization, and credibility. 

For example, let's say you are conducting a survey about consumer preferences for a certain product. You could collect only quantitative data, such as how many people prefer each product and their demographics. Or you could supplement your quantitative data with qualitative data, such as interviews and focus groups , to get a better sense of why people prefer one product over another.

It is important to note that mixed methods research does not only mean collecting both types of data. Rather, it also requires carefully considering the relationship between the two and method flexibility.

You may find differing or even conflicting results by combining quantitative and qualitative data . It is up to the researcher to then carefully analyze the results and consider them in the context of the research question to draw meaningful conclusions.

When designing a mixed methods study, it is important to consider your research approach, research questions, and available data. Think about how you can use different techniques to integrate the data to provide an answer to your research question.

• Mixed methods research design

A mixed methods research design  is   an approach to collecting and analyzing both qualitative and quantitative data in a single study.

Mixed methods designs allow for method flexibility and can provide differing and even conflicting results. Examples of mixed methods research designs include convergent parallel, explanatory sequential, and exploratory sequential.

By integrating data from both quantitative and qualitative sources, researchers can gain valuable insights into their research topic . For example, a study looking into the impact of technology on learning could use surveys to measure quantitative data on students' use of technology in the classroom. At the same time, interviews or focus groups can provide qualitative data on students' experiences and opinions.

• Types of mixed method research designs

Researchers often struggle to put mixed methods research into practice, as it is challenging and can lead to research bias. Although mixed methods research can reveal differences or conflicting results between studies, it can also offer method flexibility.

Designing a mixed methods study can be broken down into four types: convergent parallel, embedded, explanatory sequential, and exploratory sequential.

Convergent parallel

The convergent parallel design is when data collection and analysis of both quantitative and qualitative data occur simultaneously and are analyzed separately. This design aims to create mutually exclusive sets of data that inform each other. 

For example, you might interview people who live in a certain neighborhood while also conducting a survey of the same people to determine their satisfaction with the area.

Embedded design

The embedded design is when the quantitative and qualitative data are collected simultaneously, but the qualitative data is embedded within the quantitative data. This design is best used when you want to focus on the quantitative data but still need to understand how the qualitative data further explains it.

For instance, you may survey students about their opinions of an online learning platform and conduct individual interviews to gain further insight into their responses.

Explanatory sequential design

In an explanatory sequential design, quantitative data is collected first, followed by qualitative data. This design is used when you want to further explain a set of quantitative data with additional qualitative information.

An example of this would be if you surveyed employees at a company about their satisfaction with their job and then conducted interviews to gain more information about why they responded the way they did.

Exploratory sequential design

The exploratory sequential design collects qualitative data first, followed by quantitative data. This type of mixed methods research is used when the goal is to explore a topic before collecting any quantitative data.

An example of this could be studying how parents interact with their children by conducting interviews and then using a survey to further explore and measure these interactions.

Integrating data in mixed methods studies can be challenging, but it can be done successfully with careful planning.

No matter which type of design you choose, understanding and applying these principles can help you draw meaningful conclusions from your research.

• Strengths of mixed methods research

Mixed methods research designs combine the strengths of qualitative and quantitative data, deepening and enriching qualitative results with quantitative data and validating quantitative findings with qualitative data. This method offers more flexibility in designing research, combining theory generation and hypothesis testing, and being less tied to disciplines and established research paradigms.

Take the example of a study examining the impact of exercise on mental health. Mixed methods research would allow for a comprehensive look at the issue from different angles. 

Researchers could begin by collecting quantitative data through surveys to get an overall view of the participants' levels of physical activity and mental health. Qualitative interviews would follow this to explore the underlying dynamics of participants' experiences of exercise, physical activity, and mental health in greater detail.

Through a mixed methods approach, researchers could more easily compare and contrast their results to better understand the phenomenon as a whole.  

Additionally, mixed methods research is useful when there are conflicting or differing results in different studies. By combining both quantitative and qualitative data, mixed methods research can offer insights into why those differences exist.

For example, if a quantitative survey yields one result while a qualitative interview yields another, mixed methods research can help identify what factors influence these differences by integrating data from both sources.

Overall, mixed methods research designs offer a range of advantages for studying complex phenomena. They can provide insight into different elements of a phenomenon in ways that are not possible with either qualitative or quantitative data alone. Additionally, they allow researchers to integrate data from multiple sources to gain a deeper understanding of the phenomenon in question.  

• Challenges of mixed methods research

Mixed methods research is labor-intensive and often requires interdisciplinary teams of researchers to collaborate. It also has the potential to cost more than conducting a stand alone qualitative or quantitative study . 

Interpreting the results of mixed methods research can be tricky, as it can involve conflicting or differing results. Researchers must find ways to systematically compare the results from different sources and methods to avoid bias.

For example, imagine a situation where a team of researchers has employed an explanatory sequential design for their mixed methods study. After collecting data from both the quantitative and qualitative stages, the team finds that the two sets of data provide differing results. This could be challenging for the team, as they must now decide how to effectively integrate the two types of data in order to reach meaningful conclusions. The team would need to identify method flexibility and be strategic when integrating data in order to draw meaningful conclusions from the conflicting results.

• Advanced frameworks in mixed methods research

Mixed methods research offers powerful tools for investigating complex processes and systems, such as in health and healthcare.

Besides the three basic mixed method designs—exploratory sequential, explanatory sequential, and convergent parallel—you can use one of the four advanced frameworks to extend mixed methods research designs. These include multistage, intervention, case study , and participatory. 

This framework mixes qualitative and quantitative data collection methods in stages to gather a more nuanced view of the research question. An example of this is a study that first has an online survey to collect initial data and is followed by in-depth interviews to gain further insights.

Intervention

This design involves collecting quantitative data and then taking action, usually in the form of an intervention or intervention program. An example of this could be a research team who collects data from a group of participants, evaluates it, and then implements an intervention program based on their findings .

This utilizes both qualitative and quantitative research methods to analyze a single case. The researcher will examine the specific case in detail to understand the factors influencing it. An example of this could be a study of a specific business organization to understand the organizational dynamics and culture within the organization.

Participatory

This type of research focuses on the involvement of participants in the research process. It involves the active participation of participants in formulating and developing research questions, data collection, and analysis.

An example of this could be a study that involves forming focus groups with participants who actively develop the research questions and then provide feedback during the data collection and analysis stages.

The flexibility of mixed methods research designs means that researchers can choose any combination of the four frameworks outlined above and other methodologies , such as convergent parallel, explanatory sequential, and exploratory sequential, to suit their particular needs.

Through this method's flexibility, researchers can gain multiple perspectives and uncover differing or even conflicting results when integrating data.

When it comes to integration at the methods level, there are four approaches.

Connecting involves collecting both qualitative and quantitative data during different phases of the research.

Building involves the collection of both quantitative and qualitative data within a single phase.

Merging involves the concurrent collection of both qualitative and quantitative data.

Embedding involves including qualitative data within a quantitative study or vice versa.

• Techniques for integrating data in mixed method studies

Integrating data is an important step in mixed methods research designs. It allows researchers to gain further understanding from their research and gives credibility to the integration process. There are three main techniques for integrating data in mixed methods studies: triangulation protocol, following a thread, and the mixed methods matrix.

Triangulation protocol

This integration method combines different methods with differing or conflicting results to generate one unified answer.

For example, if a researcher wanted to know what type of music teenagers enjoy listening to, they might employ a survey of 1,000 teenagers as well as five focus group interviews to investigate this. The results might differ; the survey may find that rap is the most popular genre, whereas the focus groups may suggest rock music is more widely listened to. 

The researcher can then use the triangulation protocol to come up with a unified answer—such as that both rap and rock music are popular genres for teenage listeners. 

Following a thread

This is another method of integration where the researcher follows the same theme or idea from one method of data collection to the next. 

A research design that follows a thread starts by collecting quantitative data on a specific issue, followed by collecting qualitative data to explain the results. This allows whoever is conducting the research to detect any conflicting information and further look into the conflicting information to understand what is really going on.

For example, a researcher who used this research method might collect quantitative data about how satisfied employees are with their jobs at a certain company, followed by qualitative interviews to investigate why job satisfaction levels are low. They could then use the results to explore any conflicting or differing results, allowing them to gain a deeper understanding of job satisfaction at the company. 

By following a thread, the researcher can explore various research topics related to the original issue and gain a more comprehensive view of the issue.

Mixed methods matrix

This technique is a visual representation of the different types of mixed methods research designs and the order in which they should be implemented. It enables researchers to quickly assess their research design and adjust it as needed. 

The matrix consists of four boxes with four different types of mixed methods research designs: convergent parallel, explanatory sequential, exploratory sequential, and method flexibility. 

For example, imagine a researcher who wanted to understand why people don't exercise regularly. To answer this question, they could use a convergent parallel design, collecting both quantitative (e.g., survey responses) and qualitative (e.g., interviews) data simultaneously.

If the researcher found conflicting results, they could switch to an explanatory sequential design and collect quantitative data first, then follow up with qualitative data if needed. This way, the researcher can make adjustments based on their findings and integrate their data more effectively.

Mixed methods research is a powerful tool for understanding complex research topics. Using qualitative and quantitative data in one study allows researchers to understand their subject more deeply. 

Mixed methods research designs such as convergent parallel, explanatory sequential, and exploratory sequential provide method flexibility, enabling researchers to collect both types of data while avoiding the limitations of either approach alone.

However, it's important to remember that mixed methods research can produce differing or even conflicting results, so it's important to be aware of the potential pitfalls and take steps to ensure that data is being correctly integrated. If used effectively, mixed methods research can offer valuable insight into topics that would otherwise remain largely unexplored.

What is an example of mixed methods research?

An example of mixed methods research is a study that combines quantitative and qualitative data. This type of research uses surveys, interviews, and observations to collect data from multiple sources.

Which sampling method is best for mixed methods?

It depends on the research objectives, but a few methods are often used in mixed methods research designs. These include snowball sampling, convenience sampling, and purposive sampling. Each method has its own advantages and disadvantages.

What is the difference between mixed methods and multiple methods?

Mixed methods research combines quantitative and qualitative data in a single study. Multiple methods involve collecting data from different sources, such as surveys and interviews, but not necessarily combining them into one analysis. Mixed methods offer greater flexibility but can lead to differing or conflicting results when integrating data.

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Home » Mixed Methods Research – Types & Analysis

Mixed Methods Research – Types & Analysis

Table of Contents

Mixed Methods Research

Mixed methods research is an approach to research that combines both quantitative and qualitative research methods in a single study or research project. It is a methodological approach that involves collecting and analyzing both numerical (quantitative) and narrative (qualitative) data to gain a more comprehensive understanding of a research problem.

Types of Mixed Research

There are different types of mixed methods research designs that researchers can use, depending on the research question, the available data, and the resources available. Here are some common types:

Convergent Parallel Design

This design involves collecting both qualitative and quantitative data simultaneously, analyzing them separately, and then merging the findings to draw conclusions. The qualitative and quantitative data are given equal weight, and the findings are integrated during the interpretation phase.

Sequential Explanatory Design

In this design, the researcher collects and analyzes quantitative data first, and then uses qualitative data to explain or elaborate on the quantitative findings. The researcher may use the qualitative data to clarify unexpected or contradictory results from the quantitative analysis.

Sequential Exploratory Design

This design involves collecting qualitative data first, analyzing it, and then collecting and analyzing quantitative data to confirm or refute the qualitative findings. Qualitative data are used to generate hypotheses that are tested using quantitative data.

Concurrent Triangulation Design

This design involves collecting both qualitative and quantitative data concurrently and then comparing the results to find areas of agreement and disagreement. The findings are integrated during the interpretation phase to provide a more comprehensive understanding of the research question.

Concurrent Nested Design

This design involves collecting one type of data as the primary method and then using the other type of data to elaborate or clarify the primary data. For example, a researcher may use quantitative data as the primary method and qualitative data as a secondary method to provide more context and detail.

Transformative Design

This design involves using mixed methods research to not only understand the research question but also to bring about social change or transformation. The research is conducted in collaboration with stakeholders and aims to generate knowledge that can be used to improve policies, programs, and practices.

Concurrent Embedded Design

Concurrent embedded design is a type of mixed methods research design in which one type of data is embedded within another type of data. This design involves collecting both quantitative and qualitative data simultaneously, with one type of data being the primary method and the other type of data being the secondary method. The secondary method is embedded within the primary method, meaning that it is used to provide additional information or to clarify the primary data.

Data Collection Methods

Here are some common data collection methods used in mixed methods research:

Surveys are a common quantitative data collection method used in mixed methods research. Surveys involve collecting standardized responses to a set of questions from a sample of participants. Surveys can be conducted online, in person, or over the phone.

Interviews are a qualitative data collection method that involves asking open-ended questions to gather in-depth information about a participant’s experiences, perspectives, and opinions. Interviews can be conducted in person, over the phone, or online.

Focus groups

Focus groups are a qualitative data collection method that involves bringing together a small group of participants to discuss a topic or research question. The group is facilitated by a researcher, and the discussion is recorded and analyzed for themes and patterns.

Observations

Observations are a qualitative data collection method that involves systematically watching and recording behavior in a natural setting. Observations can be structured or unstructured and can be used to gather information about behavior, interactions, and context.

Document Analysis

Document analysis is a qualitative data collection method that involves analyzing existing documents, such as reports, policy documents, or media articles. Document analysis can be used to gather information about trends, policy changes, or public attitudes.

Experimentation

Experimentation is a quantitative data collection method that involves manipulating one or more variables and measuring their effects on an outcome. Experiments can be conducted in a laboratory or in a natural setting.

Data Analysis Methods

Mixed methods research involves using both quantitative and qualitative data analysis methods to analyze data collected through different methods. Here are some common data analysis methods used in mixed methods research:

Quantitative Data Analysis

Quantitative data collected through surveys or experiments can be analyzed using statistical methods. Statistical analysis can be used to identify relationships between variables, test hypotheses, and make predictions. Common statistical methods used in quantitative data analysis include regression analysis, t-tests, ANOVA, and correlation analysis.

Qualitative Data Analysis

Qualitative data collected through interviews, focus groups, or observations can be analyzed using a variety of qualitative data analysis methods. These methods include content analysis, thematic analysis, narrative analysis, and grounded theory. Qualitative data analysis involves identifying themes and patterns in the data, interpreting the meaning of the data, and drawing conclusions based on the findings.

Integration of Data

The integration of quantitative and qualitative data involves combining the results from both types of data analysis to gain a more comprehensive understanding of the research question. Integration can involve either a concurrent or sequential approach. Concurrent integration involves analyzing quantitative and qualitative data at the same time, while sequential integration involves analyzing one type of data first and then using the results to inform the analysis of the other type of data.

Triangulation

Triangulation involves using multiple sources or types of data to validate or corroborate findings. This can involve using both quantitative and qualitative data or multiple qualitative methods. Triangulation can enhance the credibility and validity of the research findings.

Mixed Methods Meta-analysis

Mixed methods meta-analysis involves the systematic review and synthesis of findings from multiple studies that use mixed methods designs. This involves combining quantitative and qualitative data from multiple studies to gain a broader understanding of a research question.

How to conduct Mixed Methods Research

Here are some general steps for conducting mixed methods research:

• Identify the research problem: The first step is to clearly define the research problem and determine if mixed methods research is appropriate for addressing it.
• Design the study: The research design should include both qualitative and quantitative data collection and analysis methods. The specific design will depend on the research question and the purpose of the study.
• Collect data : Data collection involves collecting both qualitative and quantitative data through various methods such as surveys, interviews, observations, and document analysis.
• Analyze data: Both qualitative and quantitative data need to be analyzed separately and then integrated. Analysis methods may include coding, statistical analysis, and thematic analysis.
• Interpret results: The results of the analysis should be interpreted, taking into account both the quantitative and qualitative findings. This involves integrating the results and identifying any patterns, themes, or discrepancies.
• Draw conclusions : Based on the interpretation of the results, conclusions should be drawn that address the research question and objectives.
• Report findings: Finally, the findings should be reported in a clear and concise manner, using both quantitative and qualitative data to support the conclusions.

Applications of Mixed Methods Research

Mixed methods research can be applied to a wide range of research fields and topics, including:

• Education : Mixed methods research can be used to evaluate educational programs, assess the effectiveness of teaching methods, and investigate student learning experiences.
• Health and social sciences: Mixed methods research can be used to study health interventions, understand the experiences of patients and their families, and assess the effectiveness of social programs.
• Business and management: Mixed methods research can be used to investigate customer satisfaction, assess the impact of marketing campaigns, and analyze the effectiveness of management strategies.
• Psychology : Mixed methods research can be used to explore the experiences and perspectives of individuals with mental health issues, investigate the impact of psychological interventions, and assess the effectiveness of therapy.
• Sociology : Mixed methods research can be used to study social phenomena, investigate the experiences and perspectives of marginalized groups, and assess the impact of social policies.
• Environmental studies: Mixed methods research can be used to assess the impact of environmental policies, investigate public perceptions of environmental issues, and analyze the effectiveness of conservation strategies.

Examples of Mixed Methods Research

Here are some examples of Mixed-Methods research:

• Evaluating a school-based mental health program: A researcher might use a concurrent embedded design to evaluate a school-based mental health program. The researcher might collect quantitative data through surveys and qualitative data through interviews with students and teachers. The quantitative data might be analyzed using statistical methods, while the qualitative data might be analyzed using thematic analysis. The results of the two types of data analysis could be integrated to provide a comprehensive evaluation of the program’s effectiveness.
• Understanding patient experiences of chronic illness: A researcher might use a sequential explanatory design to investigate patient experiences of chronic illness. The researcher might collect quantitative data through surveys and then use the results of the survey to inform the selection of participants for qualitative interviews. The qualitative data might be analyzed using content analysis to identify common themes in the patients’ experiences.
• Assessing the impact of a new public transportation system : A researcher might use a concurrent triangulation design to assess the impact of a new public transportation system. The researcher might collect quantitative data through surveys and qualitative data through focus groups with community members. The results of the two types of data analysis could be triangulated to provide a more comprehensive understanding of the impact of the new transportation system on the community.
• Exploring teacher perceptions of technology integration in the classroom: A researcher might use a sequential exploratory design to investigate teacher perceptions of technology integration in the classroom. The researcher might collect qualitative data through in-depth interviews with teachers and then use the results of the interviews to develop a survey. The quantitative data might be analyzed using descriptive statistics to identify trends in teacher perceptions.

When to use Mixed Methods Research

Mixed methods research is typically used when a research question cannot be fully answered by using only quantitative or qualitative methods. Here are some common situations where mixed methods research is appropriate:

• When the research question requires a more comprehensive understanding than can be achieved by using only quantitative or qualitative methods.
• When the research question requires both an exploration of individuals’ experiences, perspectives, and attitudes, as well as the measurement of objective outcomes and variables.
• When the research question requires the examination of a phenomenon in its natural setting and context, which can be achieved by collecting rich qualitative data, as well as the generalization of findings to a larger population, which can be achieved through the use of quantitative methods.
• When the research question requires the integration of different types of data or perspectives, such as combining data collected from participants with data collected from stakeholders or experts.
• When the research question requires the validation of findings obtained through one method by using another method.
• When the research question involves studying a complex phenomenon that cannot be understood by using only one method, such as studying the impact of a policy on a community’s well-being.
• When the research question involves studying a topic that has not been well-researched, and using mixed methods can help provide a more comprehensive understanding of the topic.

Purpose of Mixed Methods Research

The purpose of mixed methods research is to provide a more comprehensive understanding of a research problem than can be obtained through either quantitative or qualitative methods alone.

Mixed methods research is particularly useful when the research problem is complex and requires a deep understanding of the context and subjective experiences of participants, as well as the ability to generalize findings to a larger population. By combining both qualitative and quantitative methods, researchers can obtain a more complete picture of the research problem and its underlying mechanisms, as well as test hypotheses and identify patterns that may not be apparent with only one method.

Overall, mixed methods research aims to provide a more holistic and nuanced understanding of the research problem, allowing researchers to draw more valid and reliable conclusions, make more informed decisions, and develop more effective interventions and policies.

Advantages of Mixed Methods Research

Mixed methods research offers several advantages over using only qualitative or quantitative research methods. Here are some of the main advantages of mixed methods research:

• Comprehensive understanding: Mixed methods research provides a more comprehensive understanding of the research problem by combining both qualitative and quantitative data, which allows for a more nuanced interpretation of the data.
• Triangulation : Mixed methods research allows for triangulation, which is the use of multiple sources of data to verify findings. This improves the validity and reliability of the research.
• Addressing limitations: Mixed methods research can address the limitations of qualitative or quantitative research by compensating for the weaknesses of each method.
• Flexibility : Mixed methods research is flexible, allowing researchers to adapt the research design and methods as needed to best address the research question.
• Validity : Mixed methods research can increase the validity of the research by using multiple methods to measure the same concept.
• Generalizability : Mixed methods research can improve the generalizability of the findings by using quantitative data to test the applicability of qualitative findings to a larger population.
• Practical applications: Mixed methods research is useful for developing practical applications, such as interventions or policies, as it provides a more comprehensive understanding of the research problem.

Limitations of Mixed Methods Research

Here are some of the main limitations of mixed methods research:

• Time-consuming: Mixed methods research can be time-consuming and may require more resources than using only one research method.
• Complex data analysis: Integrating qualitative and quantitative data can be challenging and requires specialized skills for data analysis.
• Sampling bias: Mixed methods research can be subject to sampling bias, particularly if the sampling strategies for the qualitative and quantitative components are not aligned.
• Validity and reliability: Mixed methods research requires careful attention to the validity and reliability of both the qualitative and quantitative data, as well as the integration of the two data types.
• Difficulty in balancing the two methods: Mixed methods research can be difficult to balance the qualitative and quantitative methods effectively, particularly if one method dominates the other.
• Theoretical and philosophical issues: Mixed methods research raises theoretical and philosophical questions about the compatibility of qualitative and quantitative research methods and the underlying assumptions about the nature of reality and knowledge.

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• Volume 20, Issue 3
• Mixed methods research: expanding the evidence base
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• Allison Shorten 1 ,
• Joanna Smith 2
• 1 School of Nursing , University of Alabama at Birmingham , USA
• 2 Children's Nursing, School of Healthcare , University of Leeds , UK
• Correspondence to Dr Allison Shorten, School of Nursing, University of Alabama at Birmingham, 1720 2nd Ave South, Birmingham, AL, 35294, USA; [email protected]; ashorten{at}uab.edu

https://doi.org/10.1136/eb-2017-102699

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Introduction

‘Mixed methods’ is a research approach whereby researchers collect and analyse both quantitative and qualitative data within the same study. 1 2 Growth of mixed methods research in nursing and healthcare has occurred at a time of internationally increasing complexity in healthcare delivery. Mixed methods research draws on potential strengths of both qualitative and quantitative methods, 3 allowing researchers to explore diverse perspectives and uncover relationships that exist between the intricate layers of our multifaceted research questions. As providers and policy makers strive to ensure quality and safety for patients and families, researchers can use mixed methods to explore contemporary healthcare trends and practices across increasingly diverse practice settings.

What is mixed methods research?

Mixed methods research requires a purposeful mixing of methods in data collection, data analysis and interpretation of the evidence. The key word is ‘mixed’, as an essential step in the mixed methods approach is data linkage, or integration at an appropriate stage in the research process. 4 Purposeful data integration enables researchers to seek a more panoramic view of their research landscape, viewing phenomena from different viewpoints and through diverse research lenses. For example, in a randomised controlled trial (RCT) evaluating a decision aid for women making choices about birth after caesarean, quantitative data were collected to assess knowledge change, levels of decisional conflict, birth choices and outcomes. 5 Qualitative narrative data were collected to gain insight into women’s decision-making experiences and factors that influenced their choices for mode of birth. 5

In contrast, multimethod research uses a single research paradigm, either quantitative or qualitative. Data are collected and analysed using different methods within the same paradigm. 6 7 For example, in a multimethods qualitative study investigating parent–professional shared decision-making regarding diagnosis of suspected shunt malfunction in children, data collection included audio recordings of admission consultations and interviews 1 week post consultation, with interactions analysed using conversational analysis and the framework approach for the interview data. 8

What are the strengths and challenges in using mixed methods?

Selecting the right research method starts with identifying the research question and study aims. A mixed methods design is appropriate for answering research questions that neither quantitative nor qualitative methods could answer alone. 4 9–11 Mixed methods can be used to gain a better understanding of connections or contradictions between qualitative and quantitative data; they can provide opportunities for participants to have a strong voice and share their experiences across the research process, and they can facilitate different avenues of exploration that enrich the evidence and enable questions to be answered more deeply. 11 Mixed methods can facilitate greater scholarly interaction and enrich the experiences of researchers as different perspectives illuminate the issues being studied. 11

The process of mixing methods within one study, however, can add to the complexity of conducting research. It often requires more resources (time and personnel) and additional research training, as multidisciplinary research teams need to become conversant with alternative research paradigms and different approaches to sample selection, data collection, data analysis and data synthesis or integration. 11

What are the different types of mixed methods designs?

Mixed methods research comprises different types of design categories, including explanatory, exploratory, parallel and nested (embedded) designs. 2   Table 1 summarises the characteristics of each design, the process used and models of connecting or integrating data. For each type of research, an example was created to illustrate how each study design might be applied to address similar but different nursing research aims within the same general nursing research area.

• View inline

Types of mixed methods designs*

What should be considered when evaluating mixed methods research?

When reading mixed methods research or writing a proposal using mixed methods to answer a research question, the six questions below are a useful guide 12 :

Does the research question justify the use of mixed methods?

Is the method sequence clearly described, logical in flow and well aligned with study aims?

Is data collection and analysis clearly described and well aligned with study aims?

Does one method dominate the other or are they equally important?

Did the use of one method limit or confound the other method?

When, how and by whom is data integration (mixing) achieved?

For more detail of the evaluation guide, refer to the McMaster University Mixed Methods Appraisal Tool. 12 The quality checklist for appraising published mixed methods research could also be used as a design checklist when planning mixed methods studies.

• Elliot AE , et al
• Creswell JW ,
• Plano ClarkV L
• Greene JC ,
• Caracelli VJ ,
• Ivankova NV
• Shorten A ,
• Shorten B ,
• Halcomb E ,
• Cheater F ,
• Bekker H , et al
• Tashakkori A ,
• Creswell JW
• 12. ↵ National Collaborating Centre for Methods and Tools . Appraising qualitative, quantitative, and mixed methods studies included in mixed studies reviews: the MMAT . Hamilton, ON : BMJ Publishing Group , 2015 . http://www.nccmt.ca/resources/search/232 (accessed May 2017) .

Competing interests None declared.

Provenance and peer review Commissioned; internally peer reviewed.

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5.5 Mixed Methods Study Designs

There are diverse reasons why researchers undertake mixed methods research. 10 When researchers commence their study with a quantitative phase before a qualitative phase, often the aim is to use the initial information gathered to identify the best participants who may be recruited in the follow-up qualitative phase or to explain the mechanism behind the quantitative results. 10 For research studies where the quantitative phase follows the qualitative phase, the researcher may develop either a survey instrument, an intervention, or a program informed by the qualitative findings/ evidence. The choice of a mixed methods design should be informed by theoretical and/ or conceptual frameworks that support the study aims/ objectives. 9

The following mixed methods designs listed below are not exhaustive but only highlight common designs used in health care. Convergent, sequential and embedded are the basic designs, while multiphase goes beyond these basic designs but has been included here for your knowledge. 25 It is important to note that there are more complex designs, and the research question drives them.

Convergent (parallel or concurrent) design : A mixed methods design in which quantitative and qualitative data are collected simultaneously but analyzed separately, and the results are merged or integrated (Figure 5.2). 25 This type of design allows for the collection of rich, detailed data and provides a comprehensive understanding of the research problem. 2 5 An example of a concurrent mixed method design is the study by Rosenkranz, Wang and Hu., 2015 which aimed to explore, identify and explain what motivates and demotivates medical students to do research. The study used a convergent parallel mixed methods study where quantitative data were collected via a survey and qualitative data via semi-structured interviews. Data were analysed separately, and the results were compared and merged. 26 

The benefit of the convergent mixed methods design used in the study by Rosenkranz et al., 26 is that it allowed for a more comprehensive and nuanced understanding of what motivates and demotivates medical students to do research by drawing on both types of data. The survey results showed that students who had experienced exposure to the uncertainties of clinical practice through clerkships and supported compulsory research activities, were more likely to view future research activities positively. The semi-structured interviews revealed that these activities were particularly important because they helped the students to see research as a social activity which has clinical relevance and builds confidence. Overall, the study design provided evidence for the motivating effects of Competence and Relatedness in relation to medical students doing research.  In this particular study, the researchers were able to not only identify the factors that motivate and demotivate medical students to do research but also gain an in-depth understanding of why those factors were important. The study design also increased the validity of the research as the limitations of the survey data were addressed by using qualitative data to provide a more in-depth understanding of the research question.

Sequential (exploratory or explanatory) designs: In this type of mixed methods design, the aim is to use the results of one method to develop or build another method. These designs may begin with a qualitative method followed by a quantitative approach (exploratory) or a quantitative investigation followed up with a qualitative enquiry (explanatory). 25

Exploratory sequential design : This technique involves the initial collection of qualitative data, and the findings are used to guide the design and development of quantitative data collection tools. 25 The quantitative and qualitative data results are then integrated to provide a more comprehensive understanding of the phenomenon (Figure 5.3). This method is useful when developing and testing a new instrument. An example is the study by Jafer et al., 2020 which investigated dental patients’ behaviour, thoughts, opinions and needs for oral cancer information, and dentists’ behaviour regarding the prevention and examination of oral cancer. 27 The qualitative methodology was utilised to discover the emerging patterns in the patient’s thoughts, opinions and expectations regarding oral cancer. Following the qualitative investigation, a descriptive quantitative observational study was conducted on a larger sample of dental patients to analyse and quantify oral cancer-related features. 27

The benefit of using an exploratory sequential design in the study by Jafer et al., 27 is that it allowed for an in-depth exploration of the dental patients’ thoughts, opinions, and needs for oral cancer information, and dentists’ behaviour regarding the prevention and examination of oral cancer. By using qualitative methods to explore the emerging patterns in the patients’ views and needs, the researchers were able to identify key themes and issues that would have been missed in a purely quantitative study. The subsequent quantitative study, which involved a larger sample of dental patients, allowed the researchers to test and confirm their findings from the qualitative study in a more representative sample. By combining both qualitative and quantitative methods, the researchers were able to gain a more comprehensive understanding of the research problem and provide more nuanced and insightful recommendations for improving oral cancer prevention and examination practices in dental settings.

Explanatory sequential design: this method is characterised by the collection and analysis of quantitative data, followed by the collection and analysis of qualitative data. 25 The goal is to use the qualitative findings to explain and interpret the quantitative results (Figure 5.4). This method is popular in health research. 25 An example of explanatory sequential design is the study by Albert et al., 2022 which explored the views of General Practitioners (GPs) and Exercise Physiologists (EPs) as key stakeholders for optimizing patient care and efficiency of physical activity referral schemes (PARS). 28 

The authors used quantitative methods to investigate these health professionals’ knowledge, beliefs, and attitudes towards PARS in the first phase of the study. This initial phase provided an overall understanding of the topic, indicated that the participants valued PARS and the findings guided the development of the interview guide and participant selection for the second (qualitative) phase. In the second phase, the authors used semi-structured interviews to gather in-depth information on participants’ perceptions about care coordination through PARS. The qualitative data allowed for a more nuanced understanding of the research question and helped the researchers to identify the key factors that influence the success of PARS. This design helped the authors to develop a robust and accurate understanding of a complex phenomenon and provided insights that can inform the development of interventions and policies to improve patient care and the efficiency of PARS.

Embedded design : This design is also known as nested design. 25 It involves embedding one research design into another to generate new insights (Figure 5.5). Embedded designs may be convergent or sequential. 25 As an illustration, this technique could embed qualitative research within a broader quantitative study. 25 The quantitative study is used to offer a larger understanding of the research problem, whereas the qualitative study provides a more in-depth understanding of specific parts of the research topic. 25 An example is the study by Yue et al., 2022 which aimed to investigate nurses’ perceptions and experiences with the transition to a new nursing information system (Care Direct) 2 years after its first introduction. The study used an embedded design in which qualitative data and quantitative data were collected concurrently with the qualitative data given priority. 29

The embedded mixed methods design allowed the authors to explore both the prevalence of certain attitudes or behaviors and to gain insight into why these attitudes and behaviors were present. The use of qualitative data as a priority in the study allowed the researchers to explore the complexity and richness of the nurses’ experiences with the new system. This approach is particularly useful when trying to understand the factors that contribute to or impede successful implementation of new technologies. Additionally, the qualitative data was used to develop a theoretical framework that informed the development of the quantitative survey instrument. This strategy ensured that the quantitative data collected was grounded in the context of the nurses’ experiences with the new system, thereby enhancing the quality and relevance of the research findings.

Multiphase design: In this approach, multiple projects with a common goal are conducted. 25 This method requires multiple designs to be conducted over time with linkages in place to ensure that each phase builds on the previous one. 25 A project could start with a qualitative design and proceed to a quantitative design, then return to a qualitative design, and so on (Figure 5.6). The design may contain convergent or sequential elements. 25 For example, Lee et al., 2018 , conducted a study that sought to evaluate an intervention program – The Prevention and Wellness Trust Fund (PWTF). 30 The program was designed to address hypertension, paediatric asthma, falls among older adults, and tobacco use in Massachusetts. The aim was to improve health outcomes through prevention and disease management strategies and reduce healthcare costs. 30 A multi-phase, explanatory sequential mixed methods design (qualitative to quantitative to qualitative) was used to gain a more comprehensive understanding of the implementation of the Prevention and Wellness Trust Fund interventions. 30

The multi-phase, explanatory sequential mixed methods design used in this study enabled the researchers to provide a more holistic, comprehensive, and actionable evaluation of the PWTF intervention program. The findings from the study can help program developers and policymakers to identify the most effective strategies for addressing the target health issues and design programs that are sustainable and cost-effective.

An Introduction to Research Methods for Undergraduate Health Profession Students Copyright © 2023 by Faith Alele and Bunmi Malau-Aduli is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

• What Is Mixed Methods Research? Definition, Guide & Examples

As the world continues to evolve, we face increasingly complex problems,  from climate change to global health disparities. These issues are becoming increasingly difficult to address through conventional research methods.

Mixed methods research offers a new way to tackle these challenges, by providing us with a deeper understanding of the underlying causes and effects of complex topics.

In this article, we’ll explore how mixed-method research works, and how it helps us solve real-world problems.

The Foundation of Mixed Methods Research

Mixed methods research is an effective approach to understanding complex phenomena. It combines the strengths of quantitative and qualitative methods to provide a more comprehensive and nuanced perspective.

Here is a breakdown of the pioneers of mixed-method research and how it has evolved over the years:

A. Historical Development of Mixed Methods

Mixed methods research dates back to the early 1900s , but it didn’t become widely adopted until the late 1980s. Before that, people thought that quantitative and qualitative methods were two different concepts.

Quantitative research focuses on numbers and facts, while qualitative research focuses on people’s experiences and meanings. Combining these two using mixed-method research gives you a more accurate understanding of complex concepts.

Today, Mixed methods research is widely used across different industries, such as education, health science, social science, business, etc. This is because it gives a holistic view of research findings, making them easily reproducible and accurate.

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B. Key Figures and Contributions in the Field

• Abbas Tashakkori

Tashakkori is one of the leading experts in mixed-methods research with his work has provided a valuable framework for understanding and conducting mixed-methods research. 

He has published several books and papers on mixed methods research, including the “Foundation of mixed methods” and “Mixed Methodology: combining quantitative and qualitative research approaches.” 

• John W. Creswell

Creswell has established himself as a leading authority on mixed methods research. He has published several books and papers on the subject, including the groundbreaking textbook “Qualitative Inquiry: Choosing Between Five Traditions”. 

Creswell’s work has contributed to the legitimization of mixed-method research as a robust and scientifically sound research approach.

• Charles Teddlie

Another big name in mixed methods research is Charles Teddlie. He’s co-authored several books and journals about mixed methods, including the textbook, “Foundations of Mixed Methods Research: Integrating Quantitative and Qualitative Approaches in the Social and Behavioral Sciences.” His work has helped make mixed methods research better understood and practiced across different fields.

C. Paradigms and Philosophies Underlying Mixed Methods Research

Mixed methods research is grounded in several paradigms and philosophies, each of which offers unique insights into why mixed methods should be adopted for research processes. 

Some of the most common paradigms and philosophies underlying mixed methods research include:

• Pragmatism 

Pragmatism on the practical implications of things. This approach focuses on researching concepts to see how they help solve real-world problems.

Mixed methods research is compatible with pragmatism because it gives researchers the freedom to use different methods so they can determine the most effective way to solve research problems.

• Triangulation

Triangulation uses multiple techniques to collect data on the same subject to improve the validity and robustness of the research results. Mixed methods research frequently uses triangulation to gather and analyze data from quantitative and qualitative sources.

• Integration

Integration is the process of combining quantitative and qualitative data to provide a more comprehensive understanding of a phenomenon. 

The purpose of mixed methods research is to bring quantitative and qualitative information together in a meaningful manner, rather than just combining them. Integration methods such as data transformation, mixed methods convergence analysis, and mixed methods modeling help you do this seamlessly.

Understanding the Components of Mixed Methods Research

The following are the key elements that make up mixed-method research:

• Quantitative Research

Quantitative research focuses on collecting and analyzing numerical data. It helps you to collect numerical data test hypotheses, identify patterns and trends, and make predictions.

It’s like taking a photograph of a crowd: you can see who’s there and how many are there, but you can’t see what they’re thinking or how they feel.

You can perform quantitative research using surveys, questionnaires, experiments, and observations. The most common methods of analyzing quantitative analysis findings are statistical analysis, regression analysis, and factor analysis.

• Qualitative Research

Qualitative research focuses on gathering and analyzing non-structural data, such as text, pictures, and audio. It looks at complex phenomena by focusing on people’s experiences and opinions.

Think of qualitative research as talking to the people in a crowd. It allows you to capture their individual experiences and points of view. 

The most common methods for collecting qualitative data collection methods include interviews, focus groups, ethnography, and document analysis. You can analyze your findings using thematic analysis, discourse analysis, and grounded theory.

The Advantages of Mixed Methods Research

A. comprehensive understanding of research questions.

Quantitative research is good at identifying patterns and trends, while qualitative research is good at providing depth and understanding. Mixed method research combines these features to gain a more complete understanding of the research topic.

For example, a mixed-method study on the impact of a new teaching approach on student learning outcomes would use quantitative methods (academic performance) to measure student improvement. It would also use qualitative data (interviews and questionnaires) to gain insight into why a teaching approach is doing well or poorly.

B. Increased Validity and Reliability

Mixed methods research often employs triangulation which uses multiple methods to collect data on the same phenomenon. This reduces the risk of bias and ensures that the research findings are accurate and reliable.

For example, a mixed-method study on the challenges people with chronic illnesses face would track symptoms and interview their caregivers to get a better idea of what they’re going through and what they’re facing.

C. Enhanced Triangulation

Mixed methods research provides several opportunities for triangulation by combining multiple techniques, sources, and viewpoints to collect and analyze data. This helps improve the accuracy and completeness of research results.

For example, in a study about student performance you can triangulate quantitative and qualitative data, data from different sources (e.g., surveys, interviews, observations), and data from different perspectives (e.g., students, teachers, parents).

D. Addressing Research Bias

Research bias is a potential problem in all types of research, but it can be particularly challenging to address in qualitative research. Mixed methods research can help to address research bias by combining quantitative and qualitative data.

For example, you can use a survey to gather data on demographic factors prone to bias, like race, gender, and income. Then, you for control bias by analyzing the data using qualitative data such as focus groups and interviews.

E. Opportunities for Exploration and Discovery

Mixed-method research allows you to collect and analyze data from various perspectives and methods. This allows you to gain new insights and understandings that would not be possible with either quantitative or qualitative research alone.

For instance, a mixed-method study on the school experience of students with disabilities could collect quantitative data on student performance such as grades, standardized test results, and school attendance. Combining this data with qualitative data from the students, their teachers, and their parents would give you a deeper understanding of the unique challenges and experiences of students with disabilities in school.

Designing a Mixed Methods Study

You need a proper design to successfully execute your mixed-method research. Here is the list of steps that will get you there:

A. Research Questions and Hypotheses

Start by clearly defining your research questions and hypotheses. This will help you to choose the appropriate research design and data collection methods.

Also, ensure the research questions are specific, measurable, and relevant to your research goals.

B. Choosing the Appropriate Research Design

There are three main types of mixed methods research designs: concurrent, sequential, and exploratory.

• Concurrent designs collect and analyze quantitative and qualitative data simultaneously. This helps you explore complex phenomena in detail and to develop new theories.
• Sequential design is all about collecting and analyzing data one after the other, not simultaneously like concurrent design. It’s usually used to test hypotheses and build on existing studies.
• Exploratory design is the process of coming up with new concepts and ideas. This is the most suitable research method if you are working on a new topic that there’s little to no understanding of.

C. Sampling Strategies

Sampling is the process of selecting a subset of a population to represent the entire population. When designing a mixed methods study, you have to sample both quantitatively and qualitatively.

In qualitative sampling, participants are selected based on their likelihood of providing high-quality and meaningful data.  However, in quantitative sampling, participants are randomly selected or stratified to ensure that the sample is representative of the population.

D. Data Collection and Instrumentation

You have to choose your data collection instruments; these are the tools that allow you to collect research data. Quantitative research typically uses surveys, questionnaires, and tests, while qualitative uses interviews, focus groups, and observation guides to collect data.

E. Data Analysis

Data analysis is the process of organizing, summarizing, and interpreting data. 

Statistical and regression analysis are the most common ways of analyzing quantitative data. Qualitative research uses different analysis methods including, thematic analysis, discourse analysis, and grounded theories.

F, Integration of Findings

Integration of findings is the final step in the mixed methods research process. This involves combining the quantitative and qualitative findings in a meaningful way to answer the research questions and hypotheses.

Here are the most common methods of integrating findings in mixed-method research:

• Triangulation matrix : it uses a table to compare and contrast the quantitative and qualitative findings.
• Convergence analysis : this is a statistical analysis method that helps you determine the relationship between quantitative and qualitative results, by looking at their similarities and differences.

Real-World Applications of Mixed Methods Research

Mixed methods research allows you to gain better insights into complex topics across different industries including:

• Education : You can use mixed methods research to study a variety of topics in education, such as the effectiveness of new teaching methods, the impact of school policies on student achievement, or determining the optimal courseload for students.
• Healthcare : Mixed methods also allow you to effectively investigate healthcare topics, such as the effectiveness of new medical treatments, the impact of public health interventions on population health, etc.
• Social sciences: Mixed methods research helps you to explore social science topics like what influences crime rate in different regions, how policies affect social well-being, etc.
• Business and marketing : You can also use mixed-method research to determine the effectiveness of new marketing campaigns, the impact of customer satisfaction on business performance, etc.

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B. Impact of Mixed Methods Research on Policy Development and Decision-Making

Mixed methods research helps policymakers develop more effective policies and programs by giving them a deeper understanding of different topics.

For example, the findings of the mixed methods study on the effectiveness of the public health intervention on childhood obesity could be used to inform the development of other public health interventions to reduce obesity rates.

Challenges and Limitations of Mixed Methods Research

While mixed-method research is an effective approach to solving complex problems, it’s not without its limitations. Here are common mixed-method research limitations and challenges:

A. Integration Challenges

One of the most difficult aspects of mixed methods research is the integration of qualitative and quantitative data. This is because qualitative and quantitative data are very different in content and format.

You can integrate by using data transformation to convert qualitative data into quantitative data. You could also use convergence analysis to identify patterns and trends in both the quantitative and qualitative data.

B. Resource-Intensive Nature

Mixed methods studies involve collecting and analyzing both quantitative and qualitative data. This requires significant time, money, and personnel resources.

You can overcome this challenge by carefully planning the mixed methods studies by ensuring you have all the resources you need. You could also look for funding from outside sources, like the government or private foundations.

C. Potential for Researcher Bias

All types of research are susceptible to researcher bias, but this can be a particular challenge in mixed-methods research. This is because mixed methods research often involves collecting and analyzing data from multiple perspectives.

You can use strategies such as triangulation, peer review, and member checking to pinpoint your biases and mitigate them.

D. Complexity in Data Interpretation

Mixed methods studies often produce a large amount of data from multiple sources, making it difficult to interpret. 

One of the simplest ways to mitigate this difficulty is to use data visualization techniques such as graphs, maps, charts, and more. This makes it easier for you to identify trends and patterns in the data.

Best Practices for Conducting Mixed Methods Research

Here are some best practices to ensure you have an effective mixed-method research:

A. Establishing a Clear Research Plan

Start your research by outlining your research questions, hypotheses, research design, data collection methods, data analysis methods, and integration strategies.

Also, ensure you are very specific in your research plan. This will help you to stay on track throughout the research process and to ensure that your study is rigorous and well-structured.

B. Collaborative Research Teams

Mixed method research is a very rigorous and resource-intensive research method, so having a team of researchers on board makes sure you’re collecting and analyzing data thoroughly without the same amount of stress if you were doing it alone.  Having a collaborative research team also helps reduce researcher bias and generate stronger results.

C. Ongoing Reflexivity and Transparency

Being reflexive means being aware of your own biases and limitations, while transparency means honestly reporting your research methods and findings.

One way to be more reflexive and transparent is to keep a research journal. This allows you to document your thoughts and feelings about the research process, as well as any challenges or obstacles that you encounter.

You can also seek feedback from others on your research design, data collection methods, data analysis methods, and integration strategies.

D. Reporting Mixed Methods Research Findings

Clearly and honestly document your research by providing detailed descriptions of your data collection methods, data analysis methods, and integration strategies. 

You can do this by using a mixed-methods research reporting template. This ensures you have a structure for reporting your results and avoid leaving out important information.

Dive into Experimental Research Designs: Exploring Types, Examples, and Methods

Mixed method research enables you to get a better grasp on topics that would be hard to understand using just one research method. This allows you to make accurate data-driven decisions, and it works across different fields.

However, like any other research method, mixed-method research is not without its challenges and limitations. Ensure you use the best practices in this guide to get quality data and achieve your mixed-method research goals.

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• Mixed Methods Research
• qualitative research
• quantitative research
• research design
• Research Plan
• Sampling Strategies
• Moradeke Owa

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Mixed methods research design (JARS–Mixed)

APA Style JARS for Mixed Methods Research (JARS–Mixed) include both quantitative and qualitative research designs.

JARS–Mixed, developed in 2018, mark the first time APA Style has included mixed methods standards. They outline what should be reported in mixed methods research manuscripts to make the review process easier.

The seventh edition of the Publication Manual also includes content on mixed methods studies such as standards for journal article reporting, considerations for presenting the sequence of quantitative and qualitative studies, and recommendations for describing the integration of quantitative and qualitative aspects of the research throughout a paper.

• Mixed Methods Design Reporting Standards (JARS–Mixed) (PDF, 126KB) Used in conjunction with all relevant jars –Qual and jars –Quant guidelines

For more information on how these standards were created, read Journal Article Reporting Standards for Qualitative Primary, Qualitative Meta-Analytic, and Mixed Methods Research in Psychology .

• Quantitative design standards
• Qualitative design standards
• Race, Ethnicity, and Culture standards

Return to Journal Article Reporting Standards homepage

Jars resources

• History of APA’s journal article reporting standards
• APA Style JARS supplemental glossary
• Supplemental resource on the ethic of transparency in JARS
• Frequently asked questions
• JARS-Quant Decision Flowchart (PDF, 98KB)
• JARS-Quant Participant Flowchart (PDF, 98KB)

Jars articles

• Jars –Quant article
• Jars –Qual / Mixed article
• Jars – rec executive summary

Questions / feedback

Email an APA Style Expert if you have questions, feedback, or suggestions for modules to be included in future JARS updates.

APA resources

• APA Databases and Electronic Resources
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Mixed methods research.

According to the National Institutes of Health , mixed methods strategically integrates or combines rigorous quantitative and qualitative research methods to draw on the strengths of each. Mixed method approaches allow researchers to use a diversity of methods, combining inductive and deductive thinking, and offsetting limitations of exclusively quantitative and qualitative research through a complementary approach that maximizes strengths of each data type and facilitates a more comprehensive understanding of health issues and potential resolutions.¹ Mixed methods may be employed to produce a robust description and interpretation of the data, make quantitative results more understandable, or understand broader applicability of small-sample qualitative findings.

Integration

This refers to the ways in which qualitative and quantitative research activities are brought together to achieve greater insight. Mixed methods is not simply having quantitative and qualitative data available or analyzing and presenting data findings separately. The integration process can occur during data collection, analysis, or in the presentation of results.

¹ NIH Office of Behavioral and Social Sciences Research: Best Practices for Mixed Methods Research in the Health Sciences

Basic Mixed Methods Research Designs 

View image description .

Five Key Questions for Getting Started

• What do you want to know?
• What will be the detailed quantitative, qualitative, and mixed methods research questions that you hope to address?
• What quantitative and qualitative data will you collect and analyze?
• Which rigorous methods will you use to collect data and/or engage stakeholders?
• How will you integrate the data in a way that allows you to address the first question?

Rationale for Using Mixed Methods

• Obtain different, multiple perspectives: validation
• Build comprehensive understanding
• Explain statistical results in more depth
• Have better contextualized measures
• Track the process of program or intervention
• Study patient-centered outcomes and stakeholder engagement

Sample Mixed Methods Research Study

The EQUALITY study used an exploratory sequential design to identify the optimal patient-centered approach to collect sexual orientation data in the emergency department.

Qualitative Data Collection and Analysis : Semi-structured interviews with patients of different sexual orientation, age, race/ethnicity, as well as healthcare professionals of different roles, age, and race/ethnicity.

Builds Into : Themes identified in the interviews were used to develop questions for the national survey.

Quantitative Data Collection and Analysis : Representative national survey of patients and healthcare professionals on the topic of reporting gender identity and sexual orientation in healthcare.

Other Resources:

  Introduction to Mixed Methods Research : Harvard Catalyst’s eight-week online course offers an opportunity for investigators who want to understand and apply a mixed methods approach to their research.

Best Practices for Mixed Methods Research in the Health Sciences [PDF] : This guide provides a detailed overview of mixed methods designs, best practices, and application to various types of grants and projects.

Mixed Methods Research Training Program for the Health Sciences (MMRTP ): Selected scholars for this summer training program, hosted by Johns Hopkins’ Bloomberg School of Public Health, have access to webinars, resources, a retreat to discuss their research project with expert faculty, and are matched with mixed methods consultants for ongoing support.

Michigan Mixed Methods : University of Michigan Mixed Methods program offers a variety of resources, including short web videos and recommended reading.

To use a mixed methods approach, you may want to first brush up on your qualitative skills. Below are a few helpful resources specific to qualitative research:

• Qualitative Research Guidelines Project : A comprehensive guide for designing, writing, reviewing and reporting qualitative research.
• Fundamentals of Qualitative Research Methods – What is Qualitative Research : A six-module web video series covering essential topics in qualitative research, including what is qualitative research and how to use the most common methods, in-depth interviews, and focus groups.

View PDF of the above information.

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• Nepal J Epidemiol
• v.12(1); 2022 Mar

The Growing Importance of Mixed-Methods Research in Health

Sharada prasad wasti.

1,2 School of Human and Health Sciences, University of Huddersfield, United Kingdom

Padam Simkhada

3 Centre for Midwifery, Maternal and Perinatal Health, Bournemouth University, Bournemouth, United Kingdom

Edwin R. van Teijlingen

Brijesh sathian.

4 Geriatrics and long term care Department, Rumailah Hospital, Hamad Medical Corporation, Doha, Qatar

Indrajit Banerjee

5 Sir Seewoosagur Ramgoolam Medical College, Belle Rive, Mauritius

All authors have made substantial contributions to all of the following: (1) the conception and design of the study (2) drafting the article or revising it critically for important intellectual content, (3) final approval of the version to be submitted

There is no conflict of interest for any author of this manuscript.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sector.

This paper illustrates the growing importance of mixed-methods research to many health disciplines ranging from nursing to epidemiology. Mixed-methods approaches requires not only the skills of the individual quantitative and qualitative methods but also a skill set to bring two methods/datasets/findings together in the most appropriate way. Health researchers need to pay careful attention to the ‘best’ approach to designing, implementing, analysing, integrating both quantitative (number) and qualitative (word) information and writing this up in a way offers greater insights and enhances its applicability. This paper highlights the strengths and weaknesses of mixed-methods approaches as well as some of the common mistakes made by researchers applying mixed-methods for the first time.

Quantitative and qualitative research methods each address different types of questions, collect different kinds of data and deliver different kinds of answers. Each set of methods has its own inherent strengths and weaknesses, and each offers a particular approach to address specific types of research questions (and agendas). Health disciplines such as dentistry, nursing, speech and language therapy, and physiotherapy often use either quantitative or qualitative research methods on their own. However, there is a steadily growing literature showing the advantages of mixed-methods research is used in the health care and health service field [ 1-2 ]. Although we have advocated the use of mixed-methods in this journal eight years ago [ 3 ], there is still not enough mixed-methods research training in the health research field, particularly for health care practitioners, such as nurses, physiotherapists, midwives, and doctors, wanting to do research. Mixed-methods research has been popular in the social sciences since the twentieth century [ 4 ], and it has been growing in popularity among healthcare professionals [ 5 ], although it is still underdeveloped in disciplines such nursing and midwifery [ 6 , 7 ].

Underpinning philosophies

To help understand that mixed-methods research is not simply employing two different methods in the same study, one needs to consider their underpinning research philosophies (also called paradigms). First, quantitative research is usually underpinned by positivism. This includes most epidemiological studies; such research is typically based on the assumption that there is one single real world out there that can be measured. For example, quantitative research would address the question “What proportion of the population of India drinks coffee?” Secondly, qualitative research is more likely to be based on interpretivism. This includes research based on interviews and focus groups, research which us is typically based on the assumption that we all experience the world differently. Since we all live in a slightly different world in our heads the task of qualitative research is to analyse the interpretations of the people in the sample. For example, qualitative research would address the question “How do people experience drinking coffee in India?”, and “What does drinking coffee mean to them?”

Mixed-methods research brings together questions from two different philosophies in what is being referred to as the third path [ 8 ], third research paradigm [ 9 , 10 ], the third methodology movement [ 11 , 12 ] and pragmatism [ 5 ]. The two paradigms differ in key underlying assumptions that ultimately lead to choices in research methodology and methods and often give a breadth by answering more complicated research questions [ 4 ]. The roles of mixed-methods are clear in an understanding of the situation (the what), meaning, norms, values (the why or how) within a single research question which combine the strength of two different method and offer multiple ways of looking at the research question [ 13 ]. Epidemiology sits strongly in the quantitative research corner, with a strong emphasis on large data sets and sophisticated statistical analysis. Although the use of mixed methods in health research has been discussed widely researchers raised concerns about the explanation of why and how mixed methods are used in a single research question [ 5 ].

The relevance of mixed-methods in health research

The overall goal of the mixed-methods research design is to provide a better and deeper understanding, by providing a fuller picture that can enhance description and understanding of the phenomena [ 4 ]. Mixed-methods research has become popular because it uses quantitative and qualitative data in one single study which provides stronger inference than using either approach on its own [ 4 ]. In other words, a mixed-methods paper helps to understand the holistic picture from meanings obtained from interviews or observation to the prevalence of traits in a population obtained from surveys, which add depth and breadth to the study. For example, a survey questionnaire will include a limited number of structured questions, adding qualitative methods can capture other unanticipated facets of the topic that may be relevant to the research problem and help in the interpretation of the quantitative data. A good example of a mixed-methods study, it one conducted in Australia to understand the nursing care in public hospitals and also explore what factors influence adherence to nursing care [ 14 ]. Another example is a mixed-methods study that explores the relationship between nursing care practices and patient satisfaction. This study started with a quantitative survey to understand the general nursing services followed by qualitative interviews. A logistic regression analysis was performed to quantify the associations between general nursing practice variables supplemented with a thematic analysis of the interviews [ 15 ]. These research questions could not be answered if the researchers had used either qualitative or quantitative alone. Overall, this fits well with the development of evidence-based practice.

Despite the strengths of mixed-methods research but there is not much of it in nursing and other fields [ 7 ]. A recent review paper shows that the prevalence of mixed-methods studies in nursing was only 1.9% [ 7 ]. Similarly, a systematic review synthesised a total of 20 papers [ 16 ], and 16 papers [ 17 ] on nursing-related research paper among these only one mixed-methods paper was identified. Worse, a further two mixed-methods review recently revealed that out of 48 [ 18 , 19 ] synthesised nursing research papers, not one single mixed-methods paper was identified. This clearly depicts that mixed-methods research is still in its infancy stage in nursing but we can say there is huge scope to implement it to understand research questions on both sides of coin [ 4 ]. Therefore, there is a great need for mixed-methods training to enhance the evidence-based decision making in health and nursing practices.

Strengths and weaknesses of mixed-methods

There are several challenges in identifying expertise of both methods and in working with a multidisciplinary, interdisciplinary, or transdisciplinary team [ 20 ]. It increases costs and resources, takes longer to complete as mixed-methods design often involves multiple stages of data collection and separate data analysis [ 4 , 5 ]. Moreover, conducting mixed-methods research does not necessarily guarantee an improvement in the quality of health research. Therefore, mixed-methods research is only appropriate when there are appropriate research questions [ 4 , 6 ].

Identifying an appropriate mixed-methods journal can also be challenging when writing mixed-methods papers [ 21 ]. Mixed-methods papers need considerably more words than single-methods papers as well as sympathetic editors who understand the underlying philosophy of a mixed-methods approach. Such papers, simply require more words. The mixed-methods researcher must be reporting two separate methods with their own characteristics, different samples, and ways of analysing, therefore needs more words to describe both methods as well as both sets of findings. Researcher needs to find a journal that accepts longer articles to help broaden existing evidence-based practice and promote its applicability in the nursing field [ 22 ].

Common mistakes in applying mixed-methods

Not all applied researchers have insight into the underlying philosophy and/or the skills to apply each set of methods appropriately. Younas and colleagues’ review identified that around one-third (29%) of mixed-methods studies did not provide an explicit label of the study design and 95% of studies did not identify the research paradigm [ 7 ]. Whilst several mixed-methods publications did not provide clear research questions covering both quantitative and qualitative approaches. Another common issue is how to collect data either concurrent or sequential and the priority is given to each approach within the study where equal or dominant which are not clearly stated in writing which is important to mention while writing in the methods section. Similarly, a commonly overlooked aspect is how to integrate both findings in a paper. The responsibility lies with the researcher to ensure that findings are sufficiently plausible and credible [ 4 ]. Therefore, intensive mixed-methods research training is required for nursing and other health practitioners to ensure its appropriate.

The way forward

Despite the recognised strengths and benefits of doing mixed-methods research, there is still only a limited number of nursing and related-health research publications using such this approach. Researchers need training in how to design, conduct, analyse, synthesise and disseminate mixed-methods research. Most importantly, they need to consider appropriate research questions that can be addressed using a mixed methods approach to add to our knowledge in evidence-based practice. In short, we need more training on mixed-methods research for a range of health researchers and health professionals.

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Research design : qualitative, quantitative, and mixed methods approaches

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