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Chapter 3: Developing a Research Question

3.5 Quantitative, Qualitative, & Mixed Methods Research Approaches

Generally speaking, qualitative and quantitative approaches are the most common methods utilized by researchers. While these two approaches are often presented as a dichotomy, in reality it is much more complicated. Certainly, there are researchers who fall on the more extreme ends of these two approaches, however most recognize the advantages and usefulness of combining both methods (mixed methods). In the following sections we look at quantitative, qualitative, and mixed methodological approaches to undertaking research. Table 2.3 synthesizes the differences between quantitative and qualitative research approaches.

Quantitative Research Approaches

A quantitative approach to research is probably the most familiar approach for the typical research student studying at the introductory level. Arising from the natural sciences, e.g., chemistry and biology), the quantitative approach is framed by the belief that there is one reality or truth that simply requires discovering, known as realism. Therefore, asking the “right” questions is key. Further, this perspective favours observable causes and effects and is therefore outcome-oriented. Typically, aggregate data is used to see patterns and “truth” about the phenomenon under study. True understanding is determined by the ability to predict the phenomenon.

Qualitative Research Approaches

On the other side of research approaches is the qualitative approach. This is generally considered to be the opposite of the quantitative approach. Qualitative researchers are considered phenomenologists, or human-centred researchers. Any research must account for the humanness, i.e., that they have thoughts, feelings, and experiences that they interpret of the participants. Instead of a realist perspective suggesting one reality or truth, qualitative researchers tend to favour the constructionist perspective: knowledge is created, not discovered, and there are multiple realities based on someone’s perspective. Specifically, a researcher needs to understand why, how and to whom a phenomenon applies. These aspects are usually unobservable since they are the thoughts, feelings and experiences of the person. Most importantly, they are a function of their perception of those things rather than what the outside researcher interprets them to be. As a result, there is no such thing as a neutral or objective outsider, as in the quantitative approach. Rather, the approach is generally process-oriented. True understanding, rather than information based on prediction, is based on understanding action and on the interpretive meaning of that action.

Table 3.3 Differences between quantitative and qualitative approaches (from Adjei, n.d).

Note: Researchers in emergency and safety professions are increasingly turning toward qualitative methods. Here is an interesting peer paper related to qualitative research in emergency care.

Qualitative Research in Emergency Care Part I: Research Principles and Common Applications by Choo, Garro, Ranney, Meisel, and Guthrie (2015)

Interview-based Qualitative Research in Emergency Care Part II: Data Collection, Analysis and Results Reporting.

Research Methods for the Social Sciences: An Introduction Copyright © 2020 by Valerie Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Introduction: Considering Qualitative, Quantitative and Mixed Methods Research

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Alistair McBeath 2 &
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In this introduction we will explore some of the differences and similarities between quantitative and qualitative research, and dispel some of the perceived mysteries within research. We will briefly introduce some of the advantages and disadvantages of both approaches. There will also be an introduction to some of the philosophical assumptions that underpin quantitative and qualitative research methods, with specific mention made of ontological and epistemological considerations. These about the nature of existence (ontology) and how we might gain knowledge about the nature of existence (epistemology). We will explore the difference between positivist and interpretivist research, idiographic versus nomothetic, and inductive and deductive perspectives. Finally, we will also distinguish between qualitative, quantitative and mixed method s research, gaining familiarity with attempts to bridge divides between disciplines and research approaches. Throughout this book, the issue of research-supported practice will remain an underlying theme. This chapter aims to support a research-based practice, aided by considering the multiple routes into research. The chapter encourages you to familiarise yourself with approaches ranging from phenomenological experiences to more nomothetic, generalising and comparing foci like outcome measuring and random control trials (RCTs), understood with a basic knowledge of statistics. The book introduces you to a range of research, guided by interest in separate approaches but also inductive—deductive combinations, as in grounded theory together with pluralistic and mixed methods approaches, all with a shared interest in providing support in the field of mental health and emotional wellbeing. Primarily, we hope that the chapter will encourage you to start considering your own research. Enjoy!

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McBeath, A., Bager-Charleson, S. (2020). Introduction: Considering Qualitative, Quantitative and Mixed Methods Research. In: Bager-Charleson, S., McBeath, A. (eds) Enjoying Research in Counselling and Psychotherapy. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-55127-8_1

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Allison Shorten 1 ,
Joanna Smith 2
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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

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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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In This Article Expand or collapse the "in this article" section Qualitative, Quantitative, and Mixed Methods Research Sampling Strategies

Introduction.

Sampling Strategies
Sample Size
Qualitative Design Considerations
Discipline Specific and Special Considerations
Sampling Strategies Unique to Mixed Methods Designs

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Qualitative, Quantitative, and Mixed Methods Research Sampling Strategies by Timothy C. Guetterman LAST MODIFIED: 26 February 2020 DOI: 10.1093/obo/9780199756810-0241

Sampling is a critical, often overlooked aspect of the research process. The importance of sampling extends to the ability to draw accurate inferences, and it is an integral part of qualitative guidelines across research methods. Sampling considerations are important in quantitative and qualitative research when considering a target population and when drawing a sample that will either allow us to generalize (i.e., quantitatively) or go into sufficient depth (i.e., qualitatively). While quantitative research is generally concerned with probability-based approaches, qualitative research typically uses nonprobability purposeful sampling approaches. Scholars generally focus on two major sampling topics: sampling strategies and sample sizes. Or simply, researchers should think about who to include and how many; both of these concerns are key. Mixed methods studies have both qualitative and quantitative sampling considerations. However, mixed methods studies also have unique considerations based on the relationship of quantitative and qualitative research within the study.

Sampling in Qualitative Research

Sampling in qualitative research may be divided into two major areas: overall sampling strategies and issues around sample size. Sampling strategies refers to the process of sampling and how to design a sampling. Qualitative sampling typically follows a nonprobability-based approach, such as purposive or purposeful sampling where participants or other units of analysis are selected intentionally for their ability to provide information to address research questions. Sample size refers to how many participants or other units are needed to address research questions. The methodological literature about sampling tends to fall into these two broad categories, though some articles, chapters, and books cover both concepts. Others have connected sampling to the type of qualitative design that is employed. Additionally, researchers might consider discipline specific sampling issues as much research does tend to operate within disciplinary views and constraints. Scholars in many disciplines have examined sampling around specific topics, research problems, or disciplines and provide guidance to making sampling decisions, such as appropriate strategies and sample size.

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What is mixed methods research?

Last updated

20 February 2023

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Miroslav Damyanov

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

Dovetail streamlines analysis to help you uncover and share actionable insights

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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Methodology

Qualitative vs. Quantitative Research | Differences, Examples & Methods

Qualitative vs. Quantitative Research | Differences, Examples & Methods

Published on April 12, 2019 by Raimo Streefkerk . Revised on June 22, 2023.

When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

Quantitative research is at risk for research biases including information bias , omitted variable bias , sampling bias , or selection bias . Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs. quantitative research, how to analyze qualitative and quantitative data, other interesting articles, frequently asked questions about qualitative and quantitative research.

Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.

Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observational studies or case studies , your data can be represented as numbers (e.g., using rating scales or counting frequencies) or as words (e.g., with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

Surveys : List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
Experiments : Situation in which different types of variables are controlled and manipulated to establish cause-and-effect relationships.
Observations : Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

Interviews : Asking open-ended questions verbally to respondents.
Focus groups : Discussion among a group of people about a topic to gather opinions that can be used for further research.
Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
Literature review : Survey of published works by other authors.

A rule of thumb for deciding whether to use qualitative or quantitative data is:

Use quantitative research if you want to confirm or test something (a theory or hypothesis )
Use qualitative research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Quantitative research approach

You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”

You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.

Qualitative research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data

Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

Average scores ( means )
The number of times a particular answer was given
The correlation or causation between two or more variables
The reliability and validity of the results

Analyzing qualitative data

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing qualitative data include:

Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
Thematic analysis : Closely examining the data to identify the main themes and patterns
Discourse analysis : Studying how communication works in social contexts

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.

Chi square goodness of fit test
Degrees of freedom
Null hypothesis
Discourse analysis
Control groups
Mixed methods research
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 .

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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.

There are various approaches to qualitative data analysis , but they all share five steps in common:

Prepare and organize your data.
Review and explore your data.
Develop a data coding system.
Assign codes to the data.
Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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Quantitative, Qualitative, and Mixed-Methods Research: Home

Quantitative, qualitative, and mixed-methods research.

Depending on the philosophy of the researcher, the nature of the data, and how it is collected, behavioral science can be classified into qualitative, quantitative, or mixed methods research. Below are descriptions of each method.

Quantitative Research

Collects numerical data, such as frequencies or scores to focus on cause-and-effect relationships among variables

Variables and research methodologies are defined in advance by theories and hypotheses derived from other theories. These remain unchanged throughout the research process.

The researcher tries to achieve objectivity by distancing himself or herself from the research, not allowing himself or herself to be emotionally involved.

The researcher mostly studies research in artificial or less than its natural setting, and manipulates behavior as opposed to studying the behavior in its natural context.

The researcher tries to maintain internal validity and focuses on average behavior or thoughts of people in a population

Qualitative Research

Where researchers collect non-numerical information, such as descriptions of behavioral phenomena, how people experience or interpret events, and/or answers to participants' open-ended responses.

The researcher's variables andmethods used come from the researcher's experiences and can be modified as the research progresses.

The researcher is involved and his or her experiences are valuable as well as the participants' experiences.

The researcher studies behavior as it naturally happens in the natural context.

The researcher tries to maximize ecological validity.

The researcher focuses on similarities and differences in experiences and how people interpret them.

Mixed-Methods Research

Involves both quantitative and qualitative components.

The researcher specifies in advance the types of information necessary to accomplish the study's goals.

The researcher needs to carefully consider the order in which the data types will be collected and the selection criteria for participants in the various parts of the study (e.g., which people will participate in the qualitative assessment if a sub-selection of participants will be involved).

Involves development (where the researcher uses one method to inform data collection or analysis with another method) initiation (where unexpected results change protocol in the other method), corroboration (where consistency is evaluated and compared between methods), and elaboration (where one method is used to expand on the results of the other method).

Whitley, B. E. & Kite, M. E. (2013). Principles of research in behavioral science (3rd ed.). Routledge.

Last Updated: Sep 2, 2020 12:29 PM
URL: https://library.divinemercy.edu/research-types

Frontiers in Psychology
Quantitative Psychology and Measurement
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Best Practice Approaches for Mixed Methods Research in Psychological Science - Volume II

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Having started as a small movement in the 1980’s, the study of mixed methods research burst onto the scene around the beginning of the second millennium. After decades of intense dispute between supporters of the qualitative perspective and their quantitative counterparts—with both sides having grown deeply ...

Keywords : Symmetry, Quantitizing, Qualitizing, Record Transformation, Qual-Quan Integration

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College of Education and Human Development

Family Social Science

Methods: mixed methods, quantitative methods

The integration of quantitative and qualitative methods in family science allows researchers to explore the complexity of family life, providing a more comprehensive and nuanced understanding that can inform both theory and practice.

Michelle Pasco Michelle Pasco

Assistant Professor
she/her/hers
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Michelle Pasco received a PhD in Family and Human Development at Arizona State University and before joining the University of Minnesota was a Postdoctoral Research Scholar working on the Arizona Youth Identity Project.

Timothy Piehler Timothy Piehler

Associate Professor
612-301-1484
[email protected]

Advising statement My program of research is focused on developing and evaluating preventive interventions in the areas of youth mental health and substance use.

Xiaoran Sun Xiaoran Sun

[email protected]

Advising statement As a developmental and family psychologist, I conduct research on the interplay between family systems processes and well-being across adolescence and young adulthood, situated in the larger socio-ecological context--including the…

Study Protocol
Open access
Published: 26 March 2024

The effect of a midwifery continuity of care program on clinical competence of midwifery students and delivery outcomes: a mixed-methods protocol

Fatemeh Razavinia ORCID: orcid.org/0000-0002-6827-509X 1 , 2 ,
Parvin Abedi ORCID: orcid.org/0000-0002-6980-0693 3 ,
Mina Iravani ORCID: orcid.org/0000-0002-8854-1738 4 ,
Eesa Mohammadi ORCID: orcid.org/0000-0001-6169-9829 5 ,
Bahman Cheraghian ORCID: orcid.org/0000-0001-5446-6998 6 ,
Shayesteh Jahanfar ORCID: orcid.org/0000-0001-6149-1067 7 &
Mahin Najafian ORCID: orcid.org/0000-0002-6649-3931 8

BMC Medical Education volume 24 , Article number: 338 ( 2024 ) Cite this article

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Metrics details

The midwifery continuity of care model is one of the care models that have not been evaluated well in some countries including Iran. We aimed to assess the effect of a program based on this model on the clinical competence of midwifery students and delivery outcomes in Ahvaz, Iran.

This sequential embedded mixed-methods study will include a quantitative and a qualitative phase. In the first stage, based on the Iranian midwifery curriculum and review of seminal midwifery texts, a questionnaire will be developed to assess midwifery students’ clinical competence. Then, in the second stage, the quantitative phase (randomized clinical trial) will be conducted to see the effect of continuity of care provided by students on maternal and neonatal outcomes. In the third stage, a qualitative study (conventional content analysis) will be carried out to investigate the students’ and mothers’ perception of continuity of care. Finally, the results of the quantitative and qualitative phases will be integrated.

According to the nature of the study, the findings of this research can be effectively used in providing conventional midwifery services in public centers and in midwifery education.

Trial registration

Peer Review reports

Providing quality services to pregnant women has been recommended to all countries to achieve the Millennium Development Goals (MDGs) (Goals 3, 4 and 5) [ 1 ]. There are different care methods to maintain maternal and neonatal health during pregnancy and postpartum [ 1 ]. One of these care models is continuity of care that can be provided by a midwife or an obstetrician.

Midwifery continuity of care is a relationship-based care provided by a midwife who can be supported by one to three more midwives. They provide planned care for a woman during pregnancy, labor, birth, and the early postpartum period up to 6 weeks after delivery [ 2 ].

Continuity of midwifery care has become a global effort to enable women to have access to high-quality maternity care and delivery services [ 3 ]. As a result, many service providers today are transitioning to a continuous care model [ 4 ], and they have considered continuous care to be necessary for realizing women's rights [ 5 ]. Also, continuous midwifery care is known as the gold standard in maternity care to achieve excellent results for women [ 5 , 6 ]. In order to strengthen midwifery services to achieve global health goals in 2015, the World Health Organization (WHO) proposed a midwife-led continuous care model [ 7 ].

Countries use different midwifery care models. In Iran, for example, primary health services that are specific to pregnant mothers are provided in public health centers by midwives working in the network system and in compliance with the level of services and the referral system [ 8 ].

In general, midwifery continuous care not only has an important impact on a wide range of health and clinical outcomes for mothers and neonates but also brings about economic consequences for the health system [ 2 , 9 ]. This care model is useful for healthcare professionals as well [ 10 ], and it has improved the job satisfaction of midwives [ 11 ]. The midwife is the main guide in planning, organizing and providing care to a woman from the beginning of pregnancy to the postpartum period [ 12 ]. In 2011, in order to increase job motivation and satisfaction, promote retention of the midwifery workforce [ 13 ], and alleviate the shortage of workforce at the international level [ 14 ], the Nursing and Midwifery Advisory Center recommended using midwifery students (at the bedside and to perform midwifery work) to overcome this problem.

Providing high quality care requires enhancing the clinical competence of the professionals [ 4 ]. There is a close relationship between the concept of patient care quality and clinical competence. Therefore, clinical competence is of unique importance in midwifery practice [ 15 ]. As a result, in order to achieve quality patient care, midwifery professionals need to train students to become workforce with clinical competence in order to provide quality care in the health system. WHO defined clinical competence as a level of performance that demonstrates the effective application of knowledge, skills, and judgment [ 16 ].

A previous study showed that clinical competence of midwives plays an important role in managing the process of providing care, achieving care goals, and improving the quality of midwifery services [ 17 ]. In other words, the graduates of this field must have an acceptable level of clinical and professional skills in performing midwifery duties so that the health of mothers, children, and ultimately the community can be improved.

In Iran, prenatal care and the care during labor, delivery and postpartum are not continuous, and a new health provider may take the responsibility of care at any stage. This fragmented care may negatively affect the pregnancy outcomes and increase the rate of cesarean section [ 18 ]. Furthermore, the results of some studies in Iran indicate that the clinical competence obtained by midwifery students is far from optimal and that they do not acquire the necessary skills and abilities at the end of their studies [ 19 ]. Farrokhi et al. showed that the performance quality of 70% of midwives is average, and only 18.5% of them have good quality performance [ 20 ]. Several factors play a role in acquiring, maintaining and improving clinical competence [ 21 ]. There are a number of solutions that can increase the clinical competence of midwifery students, and one is the use of different care models such as the continuity of care model. The continuity of care model allows students to develop their midwifery knowledge, skills, and values individually [ 22 ]. Despite the strong foundation of midwifery in Iran, midwifery care models have not yet been tested. Some studies have reported that the quality of services provided during pregnancy, delivery and after delivery in Iran is poor to moderate. Also, these studies emphasize the necessity of a paradigm shift for better quality care and greater satisfaction of mothers, and they consider lack of continuity of care as the reason for the increase in unnecessary cesarean sections [ 23 , 24 , 25 ]. Moreover, the lack of qualified and experienced workforce has led to low quality health services, including midwifery care, and an increase in the economic burden of health. In Iran, no study has yet been conducted to investigate the effect of the midwifery continuity of care model on the students’ clinical competence and pregnancy outcomes. Given the importance of this topic, using a mixed-methods study design, we aimed to assess the effect of a midwifery continuity of care program on the clinical competence of midwifery students and pregnancy outcomes in Ahvaz, Iran.

Specific objectives

To determine the effect of midwifery continuity of care program on the clinical competence of midwifery students.

To determine the effect of a midwifery continuity of care program provided by midwifery students on pregnancy outcomes.

To explain the perception of midwifery students and mothers about the use of the midwifery continuity of care program provided by midwifery students.

Methods/design

Study design.

This sequential embedded mixed-methods study will include a quantitative phase and a qualitative one. A mixed (embedded) experimental design involves the collection and analysis of quantitative and qualitative data by the researcher and the integration of the information into an experimental study or intervention trial. This design adds qualitative data to an experiment or intervention to integrate the personal experience of research participants. Therefore, the qualitative data are converted into a secondary source of data embedded before and after the test. Qualitative data is added to the experiment in differrent ways, including: before the experiment, during the experiment, or after the experiment [ 26 , 27 ]. Embedded mixed-methods studies that are qualitative followed by quantitative are used to understand the rationale for the results and receive feedback from participants (to confirm and support the findings of the quantitative studies) [ 27 ]. In the first stage of this study, a questionnaire for assessing midwifery students’ clinical competence will be created based on the midwifery curriculum of Iran and a review of seminal texts of midwifery. Then, the effect of continuity of care provided by midwifery students on maternal and neonatal outcomes will be assessed in a randomized clinical trial. In the third stage, a qualitative study will be carried out to investigate the perception of students and mothers. Finally, the results of the quantitative and qualitative phases will be integrated (Fig. 1 ).

Sequential and embedded mixed-methods design

First stage: questionnaire development

This questionnaire will be developed based on midwifery curriculum and a comprehensive and systematic search (with no time limit) in English and Persian databases (Web of Science, Embase, Scopus, ProQuest, Google scholar, Magiran, SID).

Tool design

There are four steps in tool development:

Choosing a conceptual model to show aspects of clinical competence in the measurement process

Explaining the purpose of the tool

Designing the route map

Developing the tool (use of methods, classification of objects, rules and procedures for scoring tools) [ 28 ].

Answer to the objects

A 1 to 4-point Likert scale will be used for scoring [ 29 ].

Content validity

To ensure the selection of the most important and correct content (necessity of the case), the content validity will be assessed. Also, to ensure that the instrument items are designed in the best way to measure the content, the content validity index will be calculated [ 30 ].

Reliability

Reliability will be evaluated using internal consistency (Cronbach's alpha coefficient ≥ 0.7) and stability (test-re-test ≥ 0.74) by piloting the questionnaire on 20 midwifery students [ 31 ].

Second stage: quantitative phase

A randomized controlled clinical trial will be conducted in this phase of research to examine the effect of the continuous care program of midwifery students on their clinical competence and pregnancy outcomes.

Sample size

According to the study objective and previous study results [ 32 ] with α = 0.01, β = 0.1, p 1 = 0.51 and p 2 = 0.021, the sample size will be n = 23. Considering a 20% dropout rate, the final sample size will be 58 women (29 women in each group).

Data collection

This phase of the randomized clinical trial will be conducted with the participation of 58 undergraduate midwifery students at their 7th and 8th semesters. The students will be divided randomly to intervention (continuous care) and control (routine care) groups providing care to 58 pregnant women in six health centers and two hospitals (Sina and Razi) in Ahvaz city, southwest of Iran.

The study will begin after receiving the approval of the Ethics Committee of Ahvaz University of Medical Sciences and registering the study in the Iranian Registry for Randomized Clinical Trials. Inclusion criteria will be willingness to participate in the study.

Randomization

To implement the intervention, the students will be divided into two intervention (providing continuous care for pregnant women) and control (providing standard care for pregnant women) groups. Allocating students will be done using permuted block randomization technique with a block size of four and an allocation ratio of 1:1. Five blocks of 4 pieces and 3 blocks of 3 pieces will be extracted randomly using WIN PEPI software. In each block of 4, 2 students will be in control and 2 will be in intervention group. Also, in each block of 3 students, 1 student will be in control and 2 will be in intervention group, and the arrangement of each person is random. To prevent contamination, first the control group will provide routine care, and then the intervention group will conduct continuity of care for pregnant women. Mothers are randomly selected based on the hospital where they will give birth. As a result, Razi Hospital will be the control group and Sina Hospital will be the intervention group.

Intervention

Women who meet the inclusion criteria will be recruited in the study using a non-probability convenience sampling method. Women in the intervention group will be included in the study after their first pregnancy visit (6–10 weeks of gestation) and will receive continuous care by midwifery students. Women in the control group will receive the usual and routine care, and will be included in the study at the time of delivery. They will have a gestational age of more than 37 weeks based on the inclusion criteria of the study. Their delivery will be performed by midwifery students who will follow them up until six weeks after delivery.

At first, the necessary training will be given by the lead researcher (FR) to the students in orientation sessions held for both groups separately. In the intervention group, each midwifery student as the main midwife will be responsible for taking care of two or three pregnant women and will be the back-up midwife for two other pregnant women (under the supervision of other students). The lead researcher will create a group in WhatsApp with the participation of students in the intervention group, and they can communicate with each other and the researcher. Also, the midwifery students will be directly and indirectly under the supervision of a qualified person (lead researcher). Another WhatsApp group will be created for the women of the intervention and control groups (to facilitate communication between the researcher and the women). Two midwifery students will be introduced to each pregnant woman in the intervention group (as a main midwife and a backup midwife). If the main midwife is not available, the woman will be in contact with the backup midwife. The backup student will meet the woman at least once and will be introduced to her.

Instruments

All students and pregnant women participating in this study will complete a demographic questionnaire. A checklist will be provided for collecting data during prenatal care, labor, and delivery.

Also, the midwifery students will complete the clinical competency questionnaire at the beginning and end of the study.

Care will be provided and recorded by the main student according to the pregnancy care protocol. Also, danger signs will be taught to the students according to the national protocol, and emergencies will be handled by the midwifery student under the supervision of the lead researcher. Admission to hospital will be arranged by the student, and all information will be recorded. Pregnancy, labour and delivery, postpartum, and newborn checklist will be completed. Students will complete a demographic and obstetric questionnaire that includes questions about age, education, occupation, gravidity, parity, abortions, live and dead children, last contraceptive method, intended and unintended pregnancies, last menstrual period (LMP), gestational age, date of birth, body mass index (BMI), previous pregnancy and childbirth records, high-risk behavior of the mother and father, current history of special care, test and ultrasound results, and participation in childbirth preparation class. Also, the following data will be recorded in the labor and delivery and post-partum checklist: checking the conditions of labor according to the partograph, length of labor, need for induction and the method used type of delivery, examination of perineal trauma, postpartum bleeding, and examination of the condition of the mother up to 6 weeks after delivery. In addition, the amount of bleeding will be checked visually and by measuring the level of hemoglobin and hematocrit. Apgar score of the newborn will be recorded (in infant checklist) in minutes 1 and 5. Also, the newborn’s hospitalization status, breastfeeding and anthropometric indices will be recorded.

The students in the intervention group will start prenatal care < 20 weeks of gestation. At least five round of prenatal care will be provided by each student according to national guidelines for each pregnant woman. Pregnant women can communicate with their in-charge students in non-emergency cases from 8:00 a.m. to 23:00 p.m. and in emergency cases 24 h a day, all days a week. All reports will be recorded by the students. During labor and delivery, the student and the lead researcher will be present at the mother's bedside. In case of natural vaginal delivery (NVD), delivery will be done by a student midwife under the supervision of the researcher. In case of cesarean delivery (CS), a student will be present at the patient's bedside. Postpartum care will be provided by midwifery students in both groups (intervention and control). Each student will be at the mother's bedside for two hours after delivery. The conditions of labor, delivery, and the neonate will be recorded by the student in the relevant form. Also, the mother will be followed up by telephone for up to 6 weeks after delivery (postpartum). The clinical competency questionnaire will be completed by students before and after the intervention.

Inclusion criteria

Inclusion criteria for midwifery students will be: studying at the seventh and eighth semester and willingness to participate in the study.

Inclusion criteria for service recipients (pregnant women) will be: age 18 – 40 years, Iranian nationality, singleton pregnancy, low risk pregnancy, and gestational age < 20 wks.

Exclusion criteria

Exclusion criteria will be: history of psychiatric disorders, previous caesarean section, use of alcohol and tobacco, or having a disease that requires prenatal care by a specialist.

Primary outcome

Clinical competence of midwifery students.

Secondary outcome

Mode of delivery, length of labor stages, the need to induction, postpartum bleeding first and fifth minute Apgar score, admission of neonate to the neonatal intensive care unit, breastfeeding initiation, and exclusive breastfeeding up to 6 weeks postpartum.

Data analysis

Statistical analyses will be done using SPSS version 26.0 (SPSS, Inc., Chicago, IL, USA). The independent t-test and Chi-square tests will be used for continuous data and categorical data, respectively. ANCOVA test will be used to eliminate the influence of confounding variables. The effect size will be calculated. A 95% confidence interval (CI) and p values will be reported. P -values less than 0.5 will be considered statistically significant.

Third step of research: qualitative study

This phase will be a qualitative study using conventional content analysis.

Purposeful sampling will be used in this study [ 33 ]. Sampling will continue until data saturation [ 34 ], i.e., no new information or data about a class or relationships between classes is revealed.

This phase of the study is a conventional qualitative content analysis [ 35 ] aimed at examining the perceptions of midwifery students and mothers receiving continuous care. The researcher will conduct in-depth, semi-structured interviews with open-ended questions with students and mothers in the group of the continuous care program. All interviews will be done by the lead researcher who is qualified in qualitative research method. The interview will start with a general and open question such as: “Please tell me about your experiences or feelings about participating in the continuous midwifery care program. How did you feel about participating in this program?” Then, in-depth exploratory questions will be asked based on their answers (e.g., what do you mean? Why? Can you elaborate on that? Can you give me an example so I can understand what you mean?). All interviews will be recorded with the participants' consent. Paralinguistic features, such as mood and features of the participants, including tone of voice, facial expressions, and their posture, will be recorded by the researcher during the interview [ 35 ].

The data will be analyzed based on Granheim and Lundman's 2004 content analysis approach [ 36 ].

Interviews will be transcribed at the end of each interview. Data analysis begins with a careful study of all data so that the researcher can immerse herself in the data and gain an overview. Interviews will be transcribed verbatim. Key concepts will be highlighted and codes will be extracted. Then the first interpretations will be made and analyzed. Labels emerge for codes that represent more than one key concept and are usually taken directly from the text and become the initial coding map. Then the codes are placed in the category based on their similarity. Then, definitions will be created for each category, subcategory and code. When reporting findings, examples of each code and data category will be provided [ 35 ].

Inclusion criteria for midwifery students will be: studying at the seventh or eighth semester, willingness to participate in the study.

Inclusion criteria for service recipients (pregnant women) will be: receiving continuous care provided by the student, willingness to participate in the study, and being able to communicate.

The qualitative study and interview data will be analyzed based on the content analysis approach of Granheim and Lundman 2004 [ 36 ] as follows:

Reading and re-reading the interviews after completion of each interview

Selection of the unit of analysis

Determination of semantic units

Classification

Extraction of information content

In the first step, the data is converted into text format. As soon as possible after the interview, the interview will be typed verbatim. Then the whole text will be read several times to get a general understanding of the content of interview. Each meaning unit will be converted into condensed meaning units and then coded. The Codes will be classified into subcategories and categories based on their common characteristics. Finally, the content of the categories will be revealed, taking into account their hidden meaning [ 36 ].

Trustworthiness

Five criteria of will be used to increase data trustworthiness according to Lincoln & Guba [ 37 ]. These include: 1. Credibility, 2. Dependability, 3. Confirmability, 4. Transferability, 5. Authenticity.

Credibility of the data will be ensured by continuous engagement of the researchers with the subject, member checks, and external checks. Dependability will be ensured by relying on the insight of external observers. In order to increase the confirmability, data will be accurately recorded and reported. Also, transferability will be ensured by presenting the research process accurately, clearly and purposefully, which includes purposive sampling and presenting the research results to a number of people with the same profile of the participants who did not participate in the research. Finally, authenticity will be guaranteed by continuous reflection on information, long-term presence of the researcher, interview recording, writing, and reporting of findings.

Combining qualitative and quantitative phases

Data combination will be done using data integration strategies. The integration or combination of data starts from quantitative data analysis. Then qualitative data is collected by interview. In fact, the qualitative study is a secondary source of embedded data in the collection of experimental test data (continuous care) after the quantitative study. In this research, in order to understand the results of the RCT, the views of the participants will be unified in order to get a correct understanding of the intervention (implementation of the continuity of care model by the students) from the mothers' and students' point of view (Fig. 2 ).

Study diagram

Study status

The development of the evaluation tools was made. Also, sampling the quantitative phase of the study and the basic of the program are in process (Table 1 ).

This is the first mixed-methods study to be conducted in Iran investigating the effect of a midwifery continuity of care program on clinical competence of midwifery students and pregnancy outcomes. According to the recommendations of the WHO, midwifery continuity of care should be adopted in order to increase the quality of pregnancy care as well as the satisfaction of pregnant women and service providers [ 7 ]. Contrary to the recommendation of WHO, the continuous care program is neither implemented in Iran's health system nor included in the midwifery curriculum. The results of this study can help health planners and policy makers to implement high quality midwifery care program based on global recommendations.

The study has several strengths. The use of a mixed-methods study design (combination of quantitative and qualitative approaches) in contrast to the separate use of quantitative and qualitative studies provides a better understanding of the research questions [ 38 ]. In embedded design, one type of data collection (quantitative or qualitative) plays a supporting and essential role for another type. As a result, the embedded mixed-methods technique in the qualitative phase after designing the intervention will be used to receive feedback from the participants to confirm and support the findings of quantitative phase [ 39 ]. Also, interviews with mothers and midwifery students in the intervention group can reflect their positive and negative experiences of this program. Considering that Iran's healthcare system lacks continuous midwifery care, the findings of this research can be effectively used in providing conventional midwifery services in public centers and in midwifery education.

Considering that this care model will be implemented for the first time in Iran's midwifery education and healthcare system, there may be two possible limitations in this study: lack of infrastructure and interference with other educational programs.

Availability of data and materials

All the data that will be obtained will be published in the next article after the implementation of the study.

Abbreviations

Body mass index

Cesarean section

Last menstrual period

Millennium Development Goals

Natural vaginal delivery

World Health Organization

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The study was funded by Ahvaz Jundishapur University of Medical Sciences.

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Midwifery Department, Reproductive Health Promotion Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

Fatemeh Razavinia

Midwifery Department, Menopause Andropause Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

Midwifery Department, Menopause Andropause Research Center, Ahvaz Jundisahpur University of Medical Sciences, Golestan BLvd, Ahvaz, Iran

Parvin Abedi

Reproductive Health Promotion Research Center, Midwifery Department, Nursing and Midwifery School, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

Mina Iravani

Department of Nursing, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran

Eesa Mohammadi

Alimentary Tract Research Center, Clinical Sciences Research Institute, Department of Biostatistics and Epidemiology, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

Bahman Cheraghian

MPH Program, Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, USA

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Department of Obstetrics and Gynecology, School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

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FR, PA, MI, EM, BCh, ShJ and MN conceptualized the study. FR will collect the data. FR drafted the protocol. PA revised the manuscript. The authors read and approved the final manuscript.

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Razavinia, F., Abedi, P., Iravani, M. et al. The effect of a midwifery continuity of care program on clinical competence of midwifery students and delivery outcomes: a mixed-methods protocol. BMC Med Educ 24 , 338 (2024). https://doi.org/10.1186/s12909-024-05321-5

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Medical students’ and educators’ opinions of teleconsultation in practice and undergraduate education: a UK-based mixed-methods study

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Introduction: As information and communication technology continues to shape the healthcare landscape, future medical practitioners need to be equipped with skills and competencies that ensure safe, high-quality, and person-centred healthcare in a digitised healthcare system. This study investigated undergraduate medical students’ and medical educators’ opinions of teleconsultation practice in general and their opinions of teleconsultation education. Methods: This study used a cross-sectional, mixed-methods approach, utilising the additional coverage design to sequence and integrate qualitative and quantitative data. An online questionnaire was sent out to all medical schools in the UK, inviting undergraduate medical students and medical educators to participate. Questionnaire participants were given the opportunity to take part in a qualitative semi-structured interview. Descriptive and correlation analyses and a thematic analysis were conducted. Results: A total of 248 participants completed the questionnaire and 23 interviews were conducted. Saving time and the reduced risks of transmitting infectious diseases were identified as common advantages of using teleconsultation. However, concerns about confidentiality and accessibility to services were expressed by students and educators. Eight themes were identified from the thematic analysis. The themes relevant to teleconsultation practice were (1) The benefit of teleconsultations, (2) A second-best option, (3) Patient choice, (4) Teleconsultations differ from in-person interactions, and (5) Impact on the healthcare system. The themes relevant to teleconsultation education were (6) Considerations and reflections on required skills, (7) Learning and teaching content, and (8) The future of teleconsultation education. Discussion: The results of this study have implications for both medical practice and education. Patient confidentiality, safety, respecting patients’ preferences, and accessibility are important considerations for implementing teleconsultations in practice. Education should focus on assessing the appropriateness of teleconsultations, offering accessible and equal care, and developing skills for effective communication and clinical reasoning. High-quality teleconsultation education can influence teleconsultation practice.

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The authors have declared no competing interest.

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Data collection was initiated after the initial ethics approval received from the School of Medicine at the University of St Andrews (approval code MD15263). Additional approval and permission to undertake the research was provided by the UK Medical Schools Council (MSC), and individual UK medical schools upon request.

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Research data underpinning the PhD thesis are available from 9 May 2028 at https://doi.org/10.17630/84eb74f3-e316-4618-a112-19b2f24377ac

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Published: 02 April 2024

Towards universal health coverage in Vietnam: a mixed-method case study of enrolling people with tuberculosis into social health insurance

Rachel Forse ORCID: orcid.org/0000-0002-0716-3342 1 , 2 ,
Clara Akie Yoshino 2 ,
Thanh Thi Nguyen 1 ,
Thi Hoang Yen Phan 3 ,
Luan N. Q. Vo 1 , 2 ,
Andrew J. Codlin 1 , 2 ,
Lan Nguyen 4 ,
Chi Hoang 4 ,
Lopa Basu 5 ,
Minh Pham 5 ,
Hoa Binh Nguyen 6 ,
Luong Van Dinh 6 ,
Maxine Caws 7 , 8 ,
Tom Wingfield 2 , 7 ,
Knut Lönnroth 2 &
Kristi Sidney-Annerstedt 2

Health Research Policy and Systems volume 22 , Article number: 40 ( 2024 ) Cite this article

Metrics details

Vietnam’s primary mechanism of achieving sustainable funding for universal health coverage (UHC) and financial protection has been through its social health insurance (SHI) scheme. Steady progress towards access has been made and by 2020, over 90% of the population were enrolled in SHI. In 2022, as part of a larger transition towards the increased domestic financing of healthcare, tuberculosis (TB) services were integrated into SHI. This change required people with TB to use SHI for treatment at district-level facilities or to pay out of pocket for services. This study was conducted in preparation for this transition. It aimed to understand more about uninsured people with TB, assess the feasibility of enrolling them into SHI, and identify the barriers they faced in this process.

A mixed-method case study was conducted using a convergent parallel design between November 2018 and January 2022 in ten districts of Hanoi and Ho Chi Minh City, Vietnam. Quantitative data were collected through a pilot intervention that aimed to facilitate SHI enrollment for uninsured individuals with TB. Descriptive statistics were calculated. Qualitative interviews were conducted with 34 participants, who were purposively sampled for maximum variation. Qualitative data were analyzed through an inductive approach and themes were identified through framework analysis. Quantitative and qualitative data sources were triangulated.

We attempted to enroll 115 uninsured people with TB into SHI; 76.5% were able to enroll. On average, it took 34.5 days to obtain a SHI card and it cost USD 66 per household. The themes indicated that a lack of knowledge, high costs for annual premiums, and the household-based registration requirement were barriers to SHI enrollment. Participants indicated that alternative enrolment mechanisms and greater procedural flexibility, particularly for undocumented people, is required to achieve full population coverage with SHI in urban centers.

Conclusions

Significant addressable barriers to SHI enrolment for people affected by TB were identified. A quarter of individuals remained unable to enroll after receiving enhanced support due to lack of required documentation. The experience gained during this health financing transition is relevant for other middle-income countries as they address the provision of financial protection for the treatment of infectious diseases.

Peer Review reports

Contributing to universal health coverage (UHC) by improving access to fair and sustainable health financing, of which one mechanism is health insurance, has become a priority among low- and middle-income countries [ 1 , 2 ]. Many countries in the Asia Pacific region have made steady progress towards UHC coverage through sustained political commitments and fiscal policy aligned with their commitment [ 3 ]. By 2020, 27 countries had implemented a social health insurance (SHI) financing mechanism, which typically includes open enrollment for the full population along with partial or full subsidization of healthcare costs for vulnerable groups [ 4 ].

Vietnam’s first SHI scheme was piloted in 1989 and grew through successive pilots and expansions. In 2009 the national-level Health Insurance Law (HIL) went into effect, uniting the existing health insurance programs and schemes for the poor [ 5 ]. Amendments to the HIL effective in 2015 made SHI compulsory for all and pooled risk by re-structuring registration around the household unit [ 4 ]. A household in Vietnam is defined by inclusion in the ‘family book ’, the national system of family and address registration [ 6 ].

Access to SHI in Vietnam increased rapidly, principally through subsidization of premiums. Specific groups were enrolled automatically with full subsidy, including vulnerable populations (e.g., households classified as ‘poor’, children aged < 6, people aged > 80), pensioners and meritorious groups (e.g., veterans). Partial premium subsidization was also available for students, households classified as ‘near-poor’ and some farmers [ 7 ]. More than half of SHI members are entitled to 80% coverage with a 20% co-payment for services [ 8 ]. However, co-payments are reduced to 5% or are eliminated for subsidized groups (e.g., households classified as ‘poor’ and ‘near-poor’, children < 6) [ 4 ].

By 2020, Vietnam recorded a 91% national SHI coverage rate [ 7 ]. Those remaining uninsured mainly consisted of informally employed individuals [ 7 ]. Enrollment rates were highest among low- and high-income groups, leaving the so-called “missing middle” of uninsured [ 5 ].

Vietnam continues to transition to domestic financing of healthcare from donor financing by expanding the breadth of the national SHI. The Ministry of Health and Vietnam Social Security (VSS) have begun to close service gaps and integrate vertical health programs (e.g., those with stand-alone budget allocations and/or direct donor financing) into SHI financing [ 7 ]. The costs for antiretroviral therapy (ART) were transitioned from donor funding to SHI in 2019 [ 9 ], COVID-19 treatments were covered by SHI in 2020, and financing for tuberculosis (TB) care was fully transitioned to SHI in 2022 [ 7 ].

Until this financing transition, anti-TB medications and consultations were provided free of charge in the public sector, funded by a mixture of domestic and international funding [ 10 ]. While first-line TB medications were included in the SHI-reimbursable list of essential medicines, the government network of District TB Units (DTUs) were ineligible for registration with VSS, or reimbursement for services provided. Since July 2022, TB health facilities that met certain conditions could register with VSS and receive reimbursements for TB consultations, diagnostics and anti-TB medications [ 11 ]. The financing for drug-resistant (DR-)TB tests and medications remains largely unchanged, co-financed by the Global Fund and domestic budgets [ 12 ].

This transition of the TB financing model in Vietnam is a large undertaking as the country has the world’s 10th highest TB burden and the SHI benefits package is already considered to be generous, and the sustainability of the SHI fund is a concern [ 4 , 13 ] An estimated 169,000 individuals developed TB in 2021, and the disease killed approximately 14,200 [ 14 ]. A national costing survey of TB-affected households showed that 63% experienced catastrophic costs, spending ≥ 20% of their annual income on TB [ 10 ]. Many face food insecurity and cope with TB-related costs by taking loans, dissavings and informally borrowing money [ 10 , 15 , 16 ].

As Vietnam continues to expand SHI financing for the TB program, it is now vital for people with TB to have SHI. Those without SHI coverage will need to finance their care out of pocket (OOP) or purchase SHI and make co-payments for their care to be subsidized. For these reasons, it is important to understand why certain people with TB are uninsured, the feasibility of enrolling them in insurance when they begin treatment, and the challenges they may face with enrolling in SHI.

We conducted a convergent parallel mixed-method case study [ 17 ]. A case study was selected because it is well-suited to describe a complex issue in a real-life setting [ 18 ]. We used a naturalistic design with theoretical sampling of uninsured persons with TB using an interpretivist approach [ 19 ]. Mixed methods were selected to facilitate comparisons between quantitative and qualitative data and interpretation of the findings. An intervention, assisting TB-affected households to enroll in SHI, was conducted between November 2019 and January 2022, prior to the integration of the TB program into the SHI financing scheme. Quantitative data collection sought to answer questions regarding enrollment success rate, time to enrollment and cost of SHI enrollment for uninsured TB-affected households upon TB treatment initiation. The qualitative data explored barriers to SHI enrollment to explain and contextualize the quantitative findings. The quantitative and qualitative data were weighted equally [ 17 ].

Intervention description

A pilot intervention was conducted to facilitate SHI enrollment for people with TB in ten districts of Ha Noi and Ho Chi Minh City (HCMC). The standard process for first-time enrollment into SHI was mapped and costed from a household’s perspective (Additional file 1 ). Uninsured individuals were identified from the TB treatment register when they were enrolled in drug-susceptible (DS-)TB treatment at DTUs [ 20 ]. Study staff then attempted to facilitate enrollment of the person with TB and up to three household members into SHI.

SHI enrollment support included home visits by study staff to provide detailed information and counseling about the process of SHI enrollment, assistance with SHI application preparation including obtaining photocopies of all required documents, follow-up to obtain missing documentation within the household, accompaniment to the SHI office for application submission, and direct payment of the annual SHI premium for the household. For people who did not have the paperwork certifying temporary residence in Hanoi or Ho Chi Minh City, staff visited the local government office to obtain the information about the process for individual cases to obtain residency certificates and support participants with navigation of the bureaucracy. TB-affected people and their household members were also provided with a hotline number to call and receive support during working hours from the social workers who were employed by the study. Study staff attempted to facilitate the SHI enrollment process throughout the entire 6-month duration of DS-TB treatment. After a TB treatment outcome was recorded by the DTU, study staff stopped assisting with SHI enrollment and participants were recorded as ‘not enrolled in SHI’ in the study’s evaluation.

Quantitative methods

Case-level TB treatment notification data and SHI status were exported from VITIMES, the government-implemented electronic TB register for Vietnam, for all individuals who started TB treatment during the intervention period. The pilot intervention recruited participants from two TB treatment support projects (Project 1, n = 59 and Project 2, n = 56) [ 21 , 22 ] and tracked study forms housed in ONA.io. The sample size was determined by the availability of funding provided by the donor for treatment support service delivery, rather than to measure a specific end point of SHI enrollment. Descriptive statistics summarizing the enrollment cascade and turnaround time of enrollment were calculated using Stata v17 (Stata17 Corp, College Station, USA). To obtain the mean costs for household SHI enrollment, total direct costs for purchasing SHI were summed and divided by the total number of participants. Costs were captured in Vietnamese Dong (VND) and converted to United States Dollars (USD) using the exchange rate from the mid-point of the pilot intervention (1 June 2020) from OANDA.com.

Qualitative methods

Individuals were purposively sampled for maximum variation to ensure representation of all implementation areas and provide gender balance [ 23 ].The concept of information power guided the sample size [ 24 ]. Given the well-defined study aim, high quality in-depth responses from the participants and the authors’ expertise in the subject area, the sample size of 19 individual interviews and three focus group discussions was deemed appropriate. These were conducted in Ha Noi and HCMC. A total of 34 individuals participated in the interviews (Table 1 ).

They included 14 people enrolled in the pilot intervention, five community members who were non-beneficiaries of the treatment support intervention, 13 TB program staff from the national-, provincial- and district-levels and two study staff. Interviews were conducted at two time points: June 2019 and 2020. SHI enrollment barriers were collected as part of a qualitative study on the acceptability of providing cash transfers and SHI enrollment to adults with TB [ 25 ]. During the second round of interviews in 2020, study staff were included due to their in-depth knowledge of the challenges faced by TB-affected households when attempting to enroll in SHI and their ability to suggest programmatic-level solutions to these challenges. These interviews were conducted one-on-one, after the other interviews and focus groups had been conducted to reduce bias. The interviews were conducted at the National Lung Hospital, HCMC Provincial Lung Hospital, study office or DTUs. All interviews were conducted and transcribed in Vietnamese, translated into English, checked and finalized by a lead translator.

The interviews were analyzed through an inductive approach and themes were drawn through a framework analysis [ 26 ] to identify barriers to enrolling in SHI using Dedoose Version 7.0.23 (SocioCultural Research Consultants, Los Angeles, USA).

Data triangulation

Quantitative and qualitative data were collected in parallel. Triangulation of quantitative and qualitative data was conducted to synthesize findings and assess the level of agreement, convergence, and divergence from the findings generated by the different methods [ 17 ].

During the study, 5887 individuals were treated for DS-TB across the 10 intervention districts (Table 2 ). TB registers indicated that 2846 (48.3%) individuals were uninsured upon treatment initiation, or their SHI enrollment status was not recorded. Among 115 uninsured study participants, 88 (76.5%) were successfully enrolled in SHI before the end of their TB treatment. Among those, the household had an average of two members, resulting in a total of 206 individuals living in TB-affected households receiving SHI coverage through the pilot intervention.

The median time between DS-TB treatment initiation and SHI card issuance was 34.5 days (IQR 24–68): 11 days (IQR 5–23) between treatment initiation and pilot enrollment, 7 days (IQR 1–19.5) for SHI application preparation and submission, and 12 days (IQR 9–20) for application processing and SHI card provision.

The qualitative data showed that participants across all participant groups broadly understood that SHI is a system designed to prevent catastrophic OOP medical expenditure. As shown in Table 3 , National and provincial-level TB staff described SHI as a human right and spoke about achieving UHC as a nation; no other participant groups discussed SHI in this way. However, district-level doctors and intervention beneficiaries spoke in greater details about coverage and service gaps, and the practicalities of utilizing SHI. These participant groups expressed that when individuals purchase SHI only after a negative health event, such as a TB diagnosis, then the social safety net is unavailable to provide support until SHI coverage begins. Drawn from these views, the first theme indicated that the optimal time to purchase SHI is prior to a TB diagnosis.

One DTU staff member described how the standard processing time, or delays in processing SHI applications led to periods of high OOP expenditure:

“Unfortunately, claims are not immediately paid upon [SHI registration] submission. They may be handled in about 2 or 3 weeks, or even one month. That is why the insurance is not available at the time that they want to go for an examination and treat their condition using insurance.” (Female, District-level TB staff)

A complementary theme was that perceived lack of knowledge about SHI enrollment procedures prevents or delays enrollment. District-level TB doctors and program staff identified a lack of understanding and knowledge of the SHI enrollment process as a main contributor to lack of insurance or delays in obtaining coverage.

“Actually, for some people [with TB] who do not clearly understand the [enrollment] procedures… it will take a lot of time [to obtain SHI]. It also depends on the staff who handle the files at the commune; some staff are very enthusiastic and they help patients complete forms. There are cases [...] where they [people with TB] are required to fill in all information and write specific codes of each insurance card [from other family members] on a form. Meanwhile some people in their family work far from home and cannot send their insurance cards home in a timely manner.” (Female, program staff)

Participants tended to believe that individuals who lacked information about SHI made up the small minority of uninsured people in Vietnamese society. The above quote illustrated that the complicated administrative process prohibits enrollment; however, a factor potentially facilitating SHI enrollment may be the helpfulness of the person processing the SHI application.

The average cost per household to obtain SHI enrollment for one year (Table 2 ) was VND 1,503,313 (USD 65.52). (For detailed information on the costs of SHI enrollment, see Additional file 1 ). A third theme contextualized this finding and showed that SHI enrollment costs were perceived as prohibitively high for some. Cost was a greater challenge for lower income families, who did not meet the government’s criterion of households classified as ‘poor’ or ‘near-poor’, and were therefore ineligible for premium subsidies and SHI registration with lower co-payment rates. One DTU doctor reported that:

“We think that it is simple to buy health insurance cards, but that is only true for those who have sustainable income - when our income is much higher than the fee for buying health insurance. For some people, buying health insurance is a luxury.” (Male, District-level TB staff)

Twenty-seven people with TB (23.5%) were unable to obtain SHI coverage. The primary reason (70.4%) was missing documentation. In four instances (14.8%) a household member other than the person with TB refused to enroll in SHI. One individual (3.7%) died during the enrollment process. Three individuals (11.1%) did not enroll for other reasons.

SHI refusal by household members was not identified as a barrier to SHI enrollment in the qualitative data. However, a fourth theme confirmed the primary reason for non-enrollment by showing that some individuals do not possess the required documentation to obtain SHI, such as their identity card or ‘family book.’ [See Supplementary File] Even with six months of support from study staff, some TB-affected households were unable to gather the required documents for enrollment. The following quotation by an undocumented, elderly woman with TB illustrates the prolonged challenges she faced with obtaining formal employment, access to government services and SHI:

“I have had problems with my personal papers for a few decades and I cannot adjust my papers because I don’t have the money. […] I searched for my Identity Card and found out that I had lost it. Then I came back there [my hometown] to get the family book, to reissue my ID and to get my CV certified so I could join a company. I was very young at that time, just a little bit more than thirty years old, and I learned that I was cut from the family book.” (Female, pilot beneficiary)

To address challenges with documentation, one DTU officer in HCMC suggested that individuals who had never been insured required a change to the SHI registration requirements to ensure that everyone in Vietnam can access SHI:

“I think we should be flexible with these cases or we can find another way. Normally, the people who really need the support and the insurance or cash support, they are the people who have less information. […] We cannot have the same requirements for these people as for other people. Actually, for those who have [met] all conditions, they already have health insurance cards.” (Male, District-level TB staff)

Participants expressed that the uninsured had often not purchased SHI for a reason, and alternative registration procedures were needed to make SHI accessible for all. A fifth theme was identified indicating that current SHI enrollment procedures may prevent full population coverage.

Beyond the undocumented, some participants reported the enrollment mandate for the entire household (made under the Amendment to the HIL) for first-time enrollees was viewed as prohibitive of SHI coverage.

“Because in the old days, health insurance was sold individually for each person, but now it is sold to households, and many households do not have as good economic [situation]… so they can only afford to buy it for 50% or 60% of the household. Unskilled labor or low-income labor cannot afford to buy it for the whole family. That is to say, it is easier to buy it for each individual and it is difficult to buy for the whole family.” (Male, community member)

Though individual registration would make SHI more accessible to individuals with TB due to lower annual costs, household members with high vulnerability to TB would not be covered if policy promoted individual enrollment solely for TB.

This mixed-methods case study showed that by providing full subsidy and registration assistance, most uninsured people with TB could access SHI. However, the median time to insurance coverage meant that approximately 20% of a person’s DS-TB treatment duration remained uncovered by SHI despite successful enrollment. A substantial number of participants were unable to enroll in SHI and are likely to be perpetually locked out of SHI due to lack of personal documentation. Additional barriers to SHI enrollment were found to be lack of knowledge, the cost of obtaining coverage, and the household-based registration requirement.

The pilot intervention had dedicated staff who facilitated SHI application development and submission, yet it still took a median of 34.5 days for SHI coverage to take effect. In a context where this level of support is not available to all people with TB, it is likely that the turnaround time for SHI coverage is longer due to the complicated bureaucracy involved. This poses a major challenge, as TB-affected households incur the highest cost during the first two months of treatment [ 15 ]. One cost avoidance/mitigation strategy that people with a TB diagnosis may employ following the health financing transition is delaying TB treatment initiation until SHI coverage commences. This will likely lead to worse outcomes and sustained community transmission. The time between diagnosis and treatment should be rigorously monitored to ensure that this coping strategy is not employed, and alternative support should be made available to ensure that people diagnosed with TB are able to receive immediate treatment.

With the TB health financing transition, the uninsured will be asked to pay OOP for TB treatment and most insured individuals must co-pay for TB services which were previously provided free of cost. A national patient cost survey in 2018 found that 63% of TB-affected households experienced catastrophic costs under the previous health financing model [ 10 ]. There is a risk that the proportion of TB-affected households experiencing catastrophic costs could increase with the introduction of fees. This was not found to be the case for people living with HIV (PLHIV) when the costs of ART transitioned to SHI in Vietnam, but a new nationally representative TB costing survey is needed to assess this risk [ 9 ]. Several domestic solutions could ameliorate these challenges. As suggested for the Indian context, domestic revenues allocated by the Ministry of Finance to VSS could be increased to better support TB care [ 27 ]. VSS could also reclassify the category of TB disease and thus ensure that SHI paid for all diagnostics and drugs associated with TB treatment, without the need for a co-payment. A mid-term review of the Global Fund program in Vietnam has also called for a SHI package specifically designed to cover the OOP medical costs of TB care [ 28 ]. There are several potential mechanisms to prevent costs from falling on TB-affected households. A deeper investigation is needed to understand the fiscal space available within the Vietnamese government to cover such costs.

This case study showed that 23.5% of the uninsured people with TB were never able to enroll for the duration of their treatment, primarily due to lack of documentation. Specific provisions need to be made for the undocumented to receive free TB diagnosis, consultations, and medications through routine practice of the TB program. Multi- and bi-lateral funding mechanisms can also play a role in filling gaps by paying for TB tests for the uninsured, purchasing SHI for those diagnosed with TB, subsidizing or reimbursing OOP expenditure in the period before SHI coverage takes effect, and fully financing TB care for the undocumented. Furthermore, longer-term health system strengthening initiatives, such as creating a legal mechanism for the undocumented to obtain SHI, are likely needed to address the challenges faced by the 9% of the general population that remain uninsured. The ILO has called for “determining new strategies, which may include extension of state budget-funded subsidies to further support the participation of workers in the informal economy [ 7 ].” These forms of inclusive initiatives would solve the TB-specific challenges identified in this study and have a large positive impact on society.

We found that addressing the cost of SHI premiums and knowledge gaps in the enrollment procedures may improve SHI coverage. These findings mirror those following the transition of HIV financing to SHI in 2017. A study among PLHIV identified burdensome processes, lack of information about SHI registration procedures, and high SHI premium costs for a household as key barriers to SHI coverage [ 29 ]. However, a cluster randomized control trial which provided education, a 25% premium subsidy, or both to uninsured households found that these interventions had limited effects on SHI enrollment. Yet, “less healthy” individuals had higher SHI enrollment rates [ 30 ]. This suggests that people who have just received a TB diagnosis could be more receptive to interventions promoting SHI enrollment through premium subsidization and education. Vietnam’s National TB Program (NTP) has established a fund to subsidize SHI enrollment costs for TB-affected individuals. The size of the fund could be increased with additional support while access to the fund and the procedures for receiving support could be optimized [ 31 ]. Given the SHI transition, the NTP should also consider providing educational materials about the SHI enrollment process through the DTU network to uninsured persons with TB.

TB registers indicated that 52% of people starting TB treatment in the urban intervention districts had recorded SHI coverage. This rate is lower than other recent SHI coverage reports. A 2018–2022 DS-TB costing survey reported a SHI coverage of 70% [ 32 ], while in a DR-TB costing survey (2020–2022) it was 85% [ 16 ]. All available data sources indicate that SHI coverage among people with TB is lower than the general population, which is indicative of their socioeconomic vulnerability [ 33 ]. However, this large SHI coverage rate discrepancy may be explained by people with TB not revealing they had SHI coverage, or DTU staff could have also inconsistently recorded an individual’s SHI status in the paper TB registers since these data did not have much clinical relevance for TB treatment at the time. Now that DTUs receive financial reimbursements for the TB services from VSS, SHI coverage rates in treatment registers are likely to increase. Further research should be conducted to understand the national SHI coverage rate for people receiving TB treatment, along with the risk factors associated with being uninsured.

Limitations

This case study was conducted in the two largest cities of Vietnam and findings may not be representative of the entire country. Quantitative data were collected in a programmatic setting, and SHI coverage data for all individuals initiating TB treatment in the intervention areas appear to be underreported for reasons described above. Lastly, we were unable to collect SHI enrollment data from a control population, either prospectively during the pilot intervention or retrospectively during the pilot evaluation. As a result, we do not have information on the enrollment status or time to obtain SHI coverage among a population that did not receive assistance from the pilot intervention. However, given the substantial additional support provided by study staff for the enrollment process, we believe it is safe to assume that if left alone, TB-affected households would be slower in the enrollment process and likely enroll in lower rates.

Vietnam is viewed as a leader among Southeast Asian nations in its commitment and progress towards UHC. This mixed-methods case study illustrated the progress that Vietnam has made in its path to greater domestic financing of healthcare through SHI. This study is one of the first to examine the integration of TB services into SHI in Vietnam and define the challenges that people with TB face while attempting to gain access to financial protection after receiving a TB diagnosis. In order to make strides towards UHC in Vietnam and to close population coverage gaps, initiatives are required to specifically address the barriers faced by the uninsured. This study found that the majority of the uninsured were able to gain access to SHI through full subsidization of premiums, enrollment assistance and education. However, initiating TB care and SHI enrollment concomitantly left a significant portion of the 6-month TB treatment duration without financial protection. Additionally, a quarter of the uninsured with TB were unable to gain access to SHI during treatment, primarily due to a lack of documentation. There is great need for official mechanisms to be in place that enable those without sufficient state documents to access the TB program and to address the time-sensitive nature of providing effective financial protection during treatment of an infectious disease. These findings are relevant for other high TB burden, middle-income countries who are on a similar pathway for transitioning away from donor-financed TB programs to ones supported with a higher proportion of domestic resources.

Availability of data and materials

The quantitative dataset used and analyzed during the current study are available from the corresponding author on reasonable request. Seven anonymized transcripts of interviews with the people enrolled in the pilot intervention and non-beneficiaries have been uploaded to the following URL: https://doi.org/ https://doi.org/10.5281/zenodo.7736220 .

Abbreviations

Anti antiretroviral therapy

Drug resistant tuberculosis

Drug susceptible tuberculosis

District TB Unit

Ho Chi Minh City

Health Insurance Law

Human immunodeficiency virus

International Labour Organization

Interquartile range

National Tuberculosis Program

Out of pocket

People Living with HIV

Social Health Insurance

Tuberculosis

Universal Health Coverage

United States Dollar

Vietnamese Dong

Vietnam Social Security

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Acknowledgements

The authors would like to acknowledge the contributions of Hoang Thi My Linh, Chu Thi Hoang Anh, Nguyen Khac Cuong, Nham Thi Yen Ngoc and Tran Thai Hiep for conducting qualitative interviews and assisting with SHI enrollment activities. Special thanks to Dr. Kerri Viney for providing insightful comments on an early draft of this manuscript; they greatly strengthened the final version. This work was graciously supported by the staff of Vietnam’s National TB Program, the Hanoi Lung Hospital, Pham Ngoc Thach Provincial TB Hospital and 10 District TB Units. Lastly, we would like to thank the interview participants who shared their time and insights.

Open access funding provided by Karolinska Institute. The European Commission's Horizon 2020 program supported the provision of SHI and all data collection in 2019 through the IMPACT-TB study under grant agreement number 733174. For the period of 2020–2022, support to implement the pilot and conduct the evaluation was made possible by the generous support of the American people through the USAID under award number 72044020FA00001. TW was supported by grants from: the Wellcome Trust, UK ( Seed Award, grant number 209075/Z/17/Z); the Department of Health and Social Care (DHSC), the Foreign, Commonwealth & Development Office (FCDO), the Medical Research Council (MRC) and Wellcome, UK (Joint Global Health Trials, MR/V004832/1); the Medical Research Council (Public Health Intervention Development Award “PHIND”, APP2293); and the Medical Research Foundation (Dorothy Temple Cross International Collaboration Research Grant, MRF-131–0006-RG-KHOS-C0942). KSA was supported by the ASPECT Trial funded the Swedish Research Council (2022-00727). The contents of this study are the responsibility of the listed authors, and do not necessarily reflect the views of USAID or the United States Government.

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Contributions

This study was conceived of by RF, KSA, TTN, THYP, CAY, AJC, LNQV. The study was administered by RF, YP, TTN, AJC. Support from Vietnam’s National TB program was provided by HBN and LVD. The methodology was developed by RJ, CAY, KV, KL, KSA. The analysis was carried out by RF, CAY, TTN, and THYP. LNQV, AJC, TW, LN, CH, LB, MP, HBN, LVD, MC, KV, KL, and KSA supported the interpretation of findings. The first manuscript was written by RF. All co-authors reviewed and commented on the initial manuscript. The final manuscript was approved and reviewed by all authors.

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Correspondence to Rachel Forse .

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All study procedures were conducted in strict adherence to the Declaration of Helsinki. Ethical approvals were granted by the National Lung Hospital Institutional Review Board (114/19/CT-HĐKH-ĐĐ), the Pham Ngoc Thach Hospital Institutional Review Board (1225/PNT-HĐĐĐ) and Ha Noi University of Public Health Institutional Review Board (300/2020/YTCC-HD3). All participants provided written informed consent and individual-level data were pseudonymized prior to analysis.

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Informed written consent was obtained for all individuals who the study attempted to enroll in SHI, as part of the pilot intervention. It was also obtained for all individuals who participated in the qualitative interviews.

Competing interests

Ten of the authors received salary support from one of the funding agencies to implement the pilot interventions and their evaluation. Two of the authors were employed by United States Agency for International Development (USAID), which funded one of the two pilot interventions. They played no role in the design or implementation of the pilot interventions or their evaluation, but during the development of the manuscript, they provided their insights about the context of the results and Vietnam’s health financing transition as experts in the field.

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Mapping of procedures and costs for first-time enrollment into Vietnam's social health insurance scheme.

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Forse, R., Yoshino, C.A., Nguyen, T.T. et al. Towards universal health coverage in Vietnam: a mixed-method case study of enrolling people with tuberculosis into social health insurance. Health Res Policy Sys 22 , 40 (2024). https://doi.org/10.1186/s12961-024-01132-8

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DOI : https://doi.org/10.1186/s12961-024-01132-8

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Mixed Methods in Nursing Research : An Overview and Practical Examples

Ardith z. doorenbos.

School of Nursing, University of Washington, USA, Box 357266, Seattle, WA 98177

Mixed methods research methodologies are increasingly applied in nursing research to strengthen the depth and breadth of understanding of nursing phenomena. This article describes the background and benefits of using mixed methods research methodologies, and provides two examples of nursing research that used mixed methods. Mixed methods research produces several benefits. The examples provided demonstrate specific benefits in the creation of a culturally congruent picture of chronic pain management for American Indians, and the determination of a way to assess cost for providing chronic pain care.

Introduction

Mixed methods is one of the three major research paradigms: quantitative research, qualitative research, and mixed methods research. Mixed methods research combines elements of qualitative and quantitative research approaches for the broad purpose of increasing the breadth and depth of understanding. The definition of mixed methods, from the first issue of the Journal of Mixed Methods Research, is “research in which the investigator collects and analyzes data, integrates the findings, and draws inferences using both qualitative and quantitative approaches or methods in a single study or program of inquiry” ( Tashakkori & Creswell, 2007 , p.4).

Mixed methods research began among anthropologists and sociologists in the early 1960s. In the late 1970s, the term “triangulation” began to enter methodology conversations. Triangulation was identified as a combination of methodologies in the study of the same phenomenon to decrease the bias inherent in using one particular method ( Morse, 1991 ). Two types of sequencing for mixed methods design have been proposed: simultaneous and sequential. Type of sequencing is one of the key decisions in mixed methods study design. Simultaneous sequencing is postulated to be simultaneous use of qualitative and quantitative methods, where there is limited interaction between the two sources of data during data collection, but the data obtained is used in the data interpretation stage to support each method's findings and to reach a final understanding. Sequential sequencing is postulated to be the use of one method before the other, as when the results of one method are necessary for planning the next method.

Since the 1960s, the use of mixed methods has continued to grow in popularity ( O'Cathain, 2009 ). Currently, although there are numerous designs to consider for mixed methods research, the four major types of mixed methods designs are triangulation design, embedded design, explanatory design, and exploratory design ( Creswell & Plano Clark, 2007 ). The most common and well-known approach to mixed methods research continues to be triangulation design.

There are many benefits to using mixed methods. Quantitative data can support qualitative research components by identifying representative patients or outlying cases, while qualitative data can shed light on quantitative components by helping with development of the conceptual model or instrument. During data collection, quantitative data can provide baseline information to help researchers select patients to interview, while qualitative data can help researchers understand the barriers and facilitators to patient recruitment and retention. During data analysis, qualitative data can assist with interpreting, clarifying, describing, and validating quantitative results.

Four broad types of research situations have been reported as benefiting particularly from mixed methods research. The first situation is when concepts are new and not well understood. Thus, there is a need for qualitative exploration before quantitative methods can be used. The second situation is when findings from one approach can be better understood with a second source of data. The third situation is when neither a qualitative nor a quantitative approach, by itself, is adequate to understanding the concept being studied. Lastly, the fourth situation is when the quantitative results are difficult to interpret, and qualitative data can assist with understanding the results ( Creswell & Plano Clark, 2007 ).

The purpose of this article is to illustrate mixed methods methodology by using examples of research into the chronic pain management experience among American Indians. These examples demonstrate the methodology used to provide (a) a detailed multilevel understanding of the chronic pain care experience for American Indians using triangulation design (multilevel model), and (b) a comparison of cost for two different chronic pain care delivery models, also using triangulation design (data transformation model).

An Example : Understanding the Pain Management Experience Among American Indians

Chronic pain poses unique challenges to the American health care system, including ever-escalating costs, unintentional poisonings and deaths from overdoses of painkillers, and incalculable suffering for patients as well as their families. Approximately 100 million adults in the United States are affected by chronic pain, with treatment costs and losses in productivity totaling $635 billion annually ( Institute of Medicine, 2011 ). Symptoms of pain are the leading reason patients visit health care providers ( Hing, Cherry, & Woodwell, 2006 ).

At the level of the community-based primary care provider, especially in tribal areas of the United States, there is often not enough capacity to manage complex chronic pain cases, and this is often due to lack of access to specialty pain care ( Momper, Delva, Tauiliili, Mueller-Williams, & Goral, 2013 ). The American Indian population in particular is underserved by health care and the most vulnerable to the impact of chronic pain, with high rates of drug poisoning due to opioid analgesics ( Warner, Chen, Makuc, Anderson, & Minino, 2011 ). There are 2.9 million people who report exclusive and an additional 1.6 million who report partial American Indian ancestry in the United States. They are a diverse group, residing in 35 states and organized into 564 federally recognized tribes ( U.S. Census Bureau, 2010 ). However, there is a scarcity of published literature exploring the experience, epidemiology, and management of pain among American Indians ( Haozous, Knobf, & Brant, 2010 ; Haozous & Knobf, 2013 ; Jimenez, Garroutte, Kundu, Morales, & Buchwald, 2011 ).

Using Mixed Methods to Overcome Barriers to Research

Barriers to effective research into chronic pain management among American Indians include the relatively small number of American Indian patients in any circumscribed area or tribe, the limitations of individual databases, and widespread racial misclassification. A mixed methods research approach is needed to understand the complex experience, epidemiology, and management of chronic pain among American Indians and to address the strengths and weaknesses of quantitative methodologies (large sample size, trends, generalizable) with those of qualitative methodologies (small sample size, details, in-depth).

This first example is from an ongoing study that uses triangulation design to provide a better understanding of the phenomenon of chronic pain management among American Indians. The study uses a multilevel model in which quantitative data collected at the national and state levels will be analyzed in parallel with the collection and analysis of the qualitative data at the patient level (see Figure 1 ). This allows the weakness of one approach to be offset by the strengths of the other. The results of the separate level analyses will be compared, contrasted, and blended leading to an overall interpretation of results.

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Role of quantitative data

Previous examination of U.S. national databases has reported a higher prevalence of lower back pain in American Indians than in the general population (35% compared to 26% ; Deyo, Mirza, & Martin, 2002 ). Thus, at level 1, quantitative administrative data sets representing health care received by American Indians, both across the United States and in broad regions, will be used to evaluate macro-level trends in utilization of health care and in basic outcomes, such as opioid-related deaths.

At level 2, more detailed quantitative Washington state tribal clinic data will be used to identify American Indian populations, evaluate breakdowns in the delivery of care, and identify processes that lead to unsuccessful outcomes. For example, in a study conducted with community health practitioners in Alaska, participants reported low levels of knowledge and comfort around discussing cancer pain ( Cueva, Lanier, Dignan, Kuhnley, & Jenkins, 2005 ).

Role of qualitative data

At level 3, qualitative research through focus groups and key informant interviews will provide even more refined information about perceptions of recommended and received care. These interviews will provide insight into selected immediate and proximal factors. These factors include patients' choice and use of services; attitudes, motivations, and perceptions that influence their decisions; interpersonal factors, such as social support; and perceived discrimination. This qualitative data will shed light on potential barriers to care that are not easily recognized in administrative or clinical records, and thereby will provide greater detail about patient views of chronic pain care.

Role of (qualitative) indigenous methodologies

Since the focus of this study is on the chronic pain experience among American Indian patients, it is important that the qualitative work in level 3 be guided by indigenous methodologies, in both data collection and analysis. The phrase “indigenous methodologies” refers to an evolving framework for creating research that places the epistemologies of indigenous participants and communities at the center of the work, while building an equitable and respectful setting for bidirectional learning ( Evans, Hole, Berg, Hutchinson, & Sookraj, 2009 ; Louis, 2007 .; Smith, 2004 ). Although the tenets of indigenous methodologies vary according to the source, there is agreement among sources that research with indigenous populations should be wellness-oriented, holistic, community-oriented, and focused on indigenous knowledge, and should incorporate bidirectional learning ( Louis, 2007 ; Smith, 2004 ).

The ongoing project aligns with these guidelines by building knowledge about the chronic pain experience from the perspective of American Indian patients. The data is being interpreted with the goal of designing a usable and relevant model that will resonate at the American Indian community level. The researchers have conducted focus groups with the needs and priorities of the participants placed at the forefront, to best achieve the goals of learning and building knowledge that reflects the participants' experiences. Specifically, the focus groups were scheduled within three tribes, ensuring high familiarity and social support among group members. These focus groups met either at a tribal community center or in a nearby tribally owned casino in the evening. Each focus group started with a dinner, followed by discussion.

The focus group facilitator was well-known to the community, and although not American Indian, had been an active participant in community events and had provided expert knowledge and consultation to the tribes. Additionally, each focus group was co-facilitated by a tribal elder. The high familiarity among the participants and the research team was an important component of the bidirectional learning: it helped reduce much of the mistrust that has historically prevented medical researchers from obtaining high-quality data in similarly vulnerable populations ( Guadagnolo, Cina, & Helbig, 2009 ).

Benefits of Triangulation Design: Multilevel Model

In summary, only a mixed methods study that included quantitative and qualitative methods could provide the data required for a comprehensive multilevel assessment of the chronic pain experience among American Indians. Although this study is ongoing, the plan is for a nationwide analysis of variations in chronic pain outcomes among American Indians to examine the structure of service delivery and organization. Analysis of the state tribal clinic data will address intermediate factors and will examine community-level variation in pain management and local access to pain specialists. Preliminary analysis of the focus group data has already demonstrated that there is insufficient pain management among American Indians, due in part to lack of knowledge about pain management among providers and lack of access to pain specialists.

An Example; Comparing the Costs of Two Models for Providing Chronic Pain Care to American Indians

Telehealth is one innovative approach to providing access to high-quality interdisciplinary pain care for American Indians. A telehealth model with a unique approach based on provider-to-provider videoconference consultations allows community-based providers to present complex chronic pain cases to a panel of pain specialists through a videoconferencing infrastructure that also incorporates longitudinal outcomes tracking to monitor patient progress. Telehealth is an innovative model of health care delivery, and its use among American Indians has been expanding over the past several years ( Doorenbos et al., 2010 ; Doorenbos et al., 2011a ; 2011b ). Although the use of telehealth for providing chronic pain consultation is still in early stages, the long-term effectiveness of this approach and its impact on increasing capacity for pain management among community providers is being investigated ( Haozous et al., 2012 ; Tauben, Towle, Gordon, Theodore, & Doorenbos, 2013 ). The mixed methods approach for this transaction cost analysis used a unique triangulation design with a data transformation model to build a body of evidence for telehealth pain management.

With ever increasing mandates to reduce the cost and increase the quality of pain management, health care institutions are faced with the challenge of demonstrating that new technologies provide value while maintaining or even improving the quality of care ( Harries & Yellowlees, 2013 ). Transaction cost analysis can provide this evidence by using mixed methods research methodologies to provide comparative evaluation of the costs and consequences of using alternative technologies and the accompanying organizational arrangements for delivering care ( Williamson, 2000 ).

The theory of transaction cost developed from the observation that our structures for governing transactions—the ways in which we organize, manage, support, and carry out exchange — have economic consequences ( Williamson, 1991 ). Though prices matter, this theory recognizes that prices can and do deviate from the cost of production and do not include the cost of transacting ( Coase, 1960 ). Setting aside neoclassical economic conceptions of price, output, demand, and supply, the transaction becomes the unit of analysis ( Williamson, 1985 ).

In transactions, there are typically two parties engaging in the exchange of goods or services, and both exert effort to carry out the transaction, incurring costs in the hope or with the expectation of realizing benefits. Some ways of structuring or supporting a given transaction, such as consultation or treatment for a patient from a health care provider, may be more efficient than others. The analysis examines the actual costs incurred and the related consequences experienced by the parties over time, with the hypothesis that efficiency results from the discriminating alignment of transactions with alternative, more efficient structures of governance ( Williamson, 2002 ).

Specialty health care services participating in the study described here included the University of Washington (UW) Center for Pain Relief and the UW TelePain program. The UW Center for Pain Relief is an outpatient multispecialty consultation and treatment clinic that uses the assembled expertise and skills of physicians and other medical team providers to assist in diagnosis and care for chronic pain, for example for people with painful disorders that have persisted beyond expected duration, or for people who have persistent uncontrolled pain despite appropriate treatment for the underlying medical condition. The clinic also offers pain consultation and treatment for a variety of new-onset or acute problems that may benefit from selective anesthetic procedures, such as nerve blocks or spinal nerve root compression.

The UW TelePain program serves tribal providers in the Washington, Wyoming, Alaska, Montana, and Idaho (WWAMI) region. These tribal providers include primary care physicians, physician assistants, and nurse practitioners. The tribal providers have access to weekly videoconferences both with other community providers and with university-based pain and symptom management experts. During videoconferences, providers manage cases, engage in evidence-based practice activities, and receive peer support. Throughout the process, these community providers are responsible for direct patient care, and they act on recommendations of the consulting pain specialists.

The two care delivery models discussed above — traditional in-clinic consultation at the Center for Pain Relief and telehealth case consultation through TelePain — provided this mixed methods study using triangulation design and a data transformation model with two comparative arrangements for delivering the same transaction: delivery of pain care to patients (see Figure 2 ).

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Qualitative and Quantitative Data Collection Procedures

Participant observation and structured interviews were used to identify and describe two comparable completed transactions for patients with chronic pain. Members of the clinical care teams selected one transaction from each service for which the care could be said to represent the routines and norms of their health care organization. The chosen transactions were carried out with patients of the same gender, similar age, and similar health characteristics. For the study, clinical care teams from each service provided two qualitative on-site interviews documenting clinical work flow and processes (i.e., the steps in the transaction). For the in-clinic transaction, members of the clinical care team interviewed included a nurse care coordinator, pain specialist, medical assistant, patient outcomes assessment coordinator, nurse triage manager, patient support services supervisor, and financial authorization specialist. For the Tele-Pain transaction, team members interviewed included the TelePain nurse care coordinator, two pain specialists, an information technology specialist, and the clinic provider.

The following details the process of the mixed methods analysis. First, individual steps, or discrete tasks, within each transaction (in-clinic versus TelePain) were identified using qualitative interviews and itemized in detail. Details from the qualitative data included a description of each task, the person (s) engaged, the duration of engagement of each person in minutes, the information accrued to the patient's medical record, the technologies employed, and the locations where tasks were conducted and information was transmitted or stored.

The quantitative data collected included date and time, and therefore duration in business days, that accumulated with each step in the transaction. Finally, the costs of each step collected from the qualitative data were identified and transformed into quantitatively estimated data for each transaction. Analysis focused on the primary costs in health care: the value of people's time. These values were limited to labor costs for the in-clinic and telehealth personnel; proxies for the value of time were used with estimates of time for the patient. Costs were estimated as a function of time spent per task and per patient, and the actual wage, including benefits, of personnel engaged in the transaction.

Qualitative and Quantitative Data Analysis

Personal identifiable information was redacted from each patient's medical record, and the records were reviewed for comparability as well as for norms and routines of care for the in-clinic and telehealth organizations. The characteristics of the two patients were similar. Both were first-time patients to their respective organizations, and were referred by their primary care providers for specialized care. The reasons for seeking care and report of conditions potentially related to chronic pain were similar. Both transactions resulted in a consultation recommending referral for additional specialized care or treatment.

Two work flows, one in-clinic and one telehealth, were developed by documenting actual tasks undertaken during the transactions. In follow-up interviews, these work flows were presented to participants for review and comment. These interviews resulted in a complete itemized list of dates, personnel, and time spent per person on discrete steps or tasks. Tables and graphs expressing the steps, with cost accrual over time and in sum, were developed and compared for each transaction, to each other, and with respect to participants' rationales for the tasks in each transaction.

The equation expressing the cost per transaction is as follows, where the total cost of the transaction ( C T ) is the sum of the costs of each discrete task ( k i ) in the transaction, measured per participant ( x, y, z …) on the task, as the product of time ( t ) and wage rate ( w ), or in the case of the patient ( x, y, z …), a proxy for the value of time ( w ) and estimated time ( t ).

In total, 46 discrete steps were taken for the typical in-clinic transaction at the UW Center for Pain Relief (one patient case, reviewed by two pain specialists) versus 27 steps for the typical TelePain transaction (three patient cases, reviewed by six pain specialists). The greater number and types of administrative steps taken to schedule, execute, and follow up the in-clinic consultation resulted in greater duration of time between receipt of initial referral request and completion of the initial consultation with the pain specialists. A total of 153 business days (213 calendar days) elapsed between referral and the completion of the entire in-clinic transaction, versus 4 business days (4 calendar, days) for the TelePain transaction. Importantly, for the transaction at the UW Center for Pain Relief, 72 business days transpired before consultation concluded with a referral for the patient's record; the same conclusion was reached in 4 days in the TelePain transaction. These methods used to determine transaction costs provide an excellent example of mixed methods research, where both qualitative and quantitative data and analysis are needed to provide the transaction cost results.

Mixed methods are increasingly being used in nursing research. We have detailed two studies in which mixed methods research with triangulation design brought a richness to the examination of the phenomenon that a single methodology would not In the two examples described, a major advantage of the triangulation design is its efficiency, because both types of data are collected simultaneously. Each type of data can be collected and analyzed separately and independently, using the techniques traditionally associated with each data type. Both simultaneous and sequential data collection lend themselves to team research, in which the team includes researchers with both quantitative and qualitative expertise.

Challenges include the effort and expertise required due to the simultaneous data collection, and the fact that equal weight is usually given to each data type. Thus this research requires a team, or extensive training in both quantitative and qualitative methodologies, and careful adherence to the methodological rigor required for both methodologies. Nursing researchers may face the possibility of inconsistency in research findings arising from the objectivity of quantitative methods and the subjectivity of qualitative methods. In these cases, additional data collection may be required.

The first example, regarding the pain management experience among American Indians, used triangulation design in a multilevel model format. The multilevel model was useful in designing this study as different methods were needed at different levels to fully understand the complex health care system. In this example, quantitative data is being collected and analyzed at the national and state levels, and qualitative data is being collected at the patient level. Both qualitative and quantitative data are being collected simultaneously. The findings from each level will then be blended into one overall interpretation.

The second example, a transaction cost analysis, also used triangulation design, but the model used was that of data transformation. As in the multilevel model used in the first example, the data transformation model involved the separate but concurrent collection of qualitative and quantitative data. A novel step in this model involves transforming the qualitative data into quantitative data, and then comparing and interrelating the data sets. This required the development of procedures for transforming the qualitative data, related to, time spent on a step and salary of the provider, into quantitative cost data.

The two studies presented as examples demonstrate mixed methods research resulting in the creation of (a) a rich description of the American Indian chronic pain experience, and (b) a way to assess cost for providing chronic pain care via tribal clinics. In both examples, the quantitative data and their subsequent analysis provide a general understanding of the research problem. The qualitative data and their analysis refine and explain the results by exploring participants' views in more depth. Research using a single methodology would not have been able to achieve the same results.

Acknowledgments

Research reported in this paper was supported by the National Institute of Nursing Research of the National Institutes of Health under award number #R01NR012450 and the National Cancer Institute of the National Institutes of Health under award number #R42 CA141875. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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COMMENTS

Combining qualitative and quantitative research within mixed method research designs: A methodological review
Proponents of mixed methods research suggest that the purist view, that quantitative and qualitative approaches cannot be merged, poses a threat to the advancement of science (Onwuegbuzie and Leech, 2005) and that while epistemological and ontological commitments may be associated with certain research methods, the connections are not necessary ...
Mixed Methods Research
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 ...
3.5 Quantitative, Qualitative, & Mixed Methods Research Approaches
3.5 Quantitative, Qualitative, & Mixed Methods Research Approaches Generally speaking, qualitative and quantitative approaches are the most common methods utilized by researchers. While these two approaches are often presented as a dichotomy, in reality it is much more complicated. ... Table 2.3 synthesizes the differences between quantitative ...
How to Construct a Mixed Methods Research Design
Quantitative dominant [or quantitatively driven] mixed methods research is the type of mixed research in which one relies on a quantitative, postpositivist view of the research process, while concurrently recognizing that the addition of qualitative data and approaches are likely to benefit most research projects. (p.
PDF Getting Started with Mixed Methods Research
Mixed methods approaches allows 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 ...
Mixed methods research: what it is and what it could be
Combining methods in social scientific research has recently gained momentum through a research strand called Mixed Methods Research (MMR). This approach, which explicitly aims to offer a framework for combining methods, has rapidly spread through the social and behavioural sciences, and this article offers an analysis of the approach from a field theoretical perspective. After a brief outline ...
Research design: qualitative, quantitative, and mixed methods
This review examines John W. Creswell and David Creswell's sixth edition, which covers the most popular research methods, offering readers a comprehensive understanding and practical guidance in qualitative, quantitative, and mixed methods. The review includes observations on existing drawbacks, gaps, and ideas on potential areas for improvement in the book. The book is an excellent entry ...
PDF Mixed Methods: Integrating Quantitative and Qualitative Data Collection
Mixed methods give a voice to study participants and ensure that study findings are grounded in participants' experiences. Fosters scholarly interaction. Such studies add breadth to multidisciplinary team research by . encouraging the interaction of quantitative, qualitative, and mixed methods scholars. Provides methodological flexibility.
Integrating Quantitative and Qualitative Results in Health Science
METHODS. We searched for empirical articles that included joint displays in 3 journals that publish state-of-the-art mixed methods research. We analyzed each of 19 identified joint displays to extract the type of display, mixed methods design, purpose, rationale, qualitative and quantitative data sources, integration approaches, and analytic strategies.
Introduction: Considering Qualitative, Quantitative and Mixed Methods
Historically, views on the appropriateness of quantitative and qualitative research methods have become polarised and captured by the notion of a 'paradigm war' (Ukpabi et al. 2014). In a mixed methods approach there is no inherent conflict, with quantitative and qualitative research methods able to make their own distinctive contribution.
Current Mixed Methods Practices in Qualitative Research: A Content
Mixed methods research (MMR) has become increasingly popular over the last 25 years (Creswell, 2015).However, collecting qualitative and quantitative data was commonplace in many social sciences throughout the first 60 years of the 20th Century. During the 1980's, MMR re-emerged as a distinct approach, inducing a second wave of popularity (Creswell, 2015; Guest, 2013; Johnson, Onwuegbuzie ...
Mixed methods research: expanding the evidence base
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 ...
Qualitative, Quantitative, and Mixed Methods Research Sampling
However, mixed methods studies also have unique considerations based on the relationship of quantitative and qualitative research within the study. Sampling in Qualitative Research Sampling in qualitative research may be divided into two major areas: overall sampling strategies and issues around sample size.
Qualitative Approaches to Mixed Methods Practice
mixed methods, qualitative approaches, case studies. qualitative approach to research aims to understand how individuals make meaning of their social world. The social world is not something independent of individual percep-tions but is created through social interactions of individuals with the world around them.
Mixed Methods Research Guide With Examples
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 ...
Qualitative vs. Quantitative Research
When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge. Quantitative research. Quantitative research is expressed in numbers and graphs. It is used to test or confirm theories and assumptions.
Quantitative, Qualitative, and Mixed-Methods Research: Home
Qualitative Research. Where researchers collect non-numerical information, such as descriptions of behavioral phenomena, how people experience or interpret events, and/or answers to participants' open-ended responses. The researcher's variables andmethods used come from the researcher's experiences and can be modified as the research progresses.
Mixed Methods Research
The mixed methods research definition is a design that utilizes both quantitative (numeric) and qualitative (descriptive) research elements to gain a conclusion for a study. A mixed methods study ...
Best Practice Approaches for Mixed Methods Research in ...
Having started as a small movement in the 1980's, the study of mixed methods research burst onto the scene around the beginning of the second millennium. After decades of intense dispute between supporters of the qualitative perspective and their quantitative counterparts—with both sides having grown deeply entrenched in their respective views—a complementary approach promising the ...
Research Methods-Quantitative, Qualitative, and Mixed methods
However, research approaches are often classified into quantitative, qualitative, and mixed research (Creswell, 2009). Quantitative research is often presented numerically and tends to be analyzed ...
What is Mixed Methods Research?<br/>
Mixed qualitative and quantitative research methods are less tied to established research paradigms, so they are flexible to use. Mixed methods research allows you to tackle a broad range of research questions. This is because you are not limited to a research method. This approach helps researchers get stronger evidence to collaborate their ...
Methods: mixed methods, quantitative methods
The integration of quantitative and qualitative methods in family science allows researchers to explore the complexity of ... Methods: mixed methods, quantitative methods . ... and Human Development at Arizona State University and before joining the University of Minnesota was a Postdoctoral Research Scholar working on the Arizona Youth ...
The effect of a midwifery continuity of care program on clinical
The use of a mixed-methods study design (combination of quantitative and qualitative approaches) in contrast to the separate use of quantitative and qualitative studies provides a better understanding of the research questions . In embedded design, one type of data collection (quantitative or qualitative) plays a supporting and essential role ...
Medical students' and educators' opinions of teleconsultation in
Methods: This study used a cross-sectional, mixed-methods approach, utilising the additional coverage design to sequence and integrate qualitative and quantitative data. An online questionnaire was sent out to all medical schools in the UK, inviting undergraduate medical students and medical educators to participate.
Towards universal health coverage in Vietnam: a mixed-method case study
We conducted a convergent parallel mixed-method case study [].A case study was selected because it is well-suited to describe a complex issue in a real-life setting [].We used a naturalistic design with theoretical sampling of uninsured persons with TB using an interpretivist approach [].Mixed methods were selected to facilitate comparisons between quantitative and qualitative data and ...
"Not Bad, Just hard:" A Mixed-Methods Investigation of Reactions to
1 There have been discussions among researchers, clinicians, and individuals with lived experience of dissociative identity disorder regarding terminology used to refer to self-states. The term self-states was selected for use in this manuscript based on language used in the Diagnostic and Statistical Manual of Mental Disorders − 5 th edition and that which is used in most research literature.
In This Issue: Inclusive Language to Foster Equity and Diversity, Joint
Their article demonstrates the process of beginning with survey results that included both qualitative and quantitative items and building to the subsequent qualitative phase that is participatory. They include participatory principles in developing prompts to be used for data collection in the qualitative phase. ... Journal of Mixed Methods ...
Mixed Methods in Nursing Research : An Overview and Practical Examples
The definition of mixed methods, from the first issue of the Journal of Mixed Methods Research, is "research in which the investigator collects and analyzes data, integrates the findings, and draws inferences using both qualitative and quantitative approaches or methods in a single study or program of inquiry" ( Tashakkori & Creswell, 2007 ...
Research Design: Qualitative, Quantitative, and Mixed Methods ...
Research Design: Qualitative, Quantitative, and Mixed Methods 5th Edition ISBN13 : 9781506386706 - eBook ****. Get eBook Now<<<. Research Design: Qualitative, Quantitative, and Mixed Methods 5th Edition. Share Add a Comment. Be the first to comment Nobody's responded to this post yet. Add your thoughts and get the conversation going. ...

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