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Mixing Methods: Qualitative and Quantitative Research

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This book focuses on a key issue in the methodology of the social and behavioural sciences: the mixing of different research methods. The extent to which qualitative and quantitative research differ from one another has long been a subject of debate. Although many methodologists have concluded that the two approaches are not mutually exclusive, there are few books on either the theory or the practice of mixing methods. Mixing Methods: Qualitative and Quantitative Research presents a comprehensive discussion of the theoretical, methodological and practical issues. It also covers a number of case studies of research which have successfully combined qualitative and quantitative approaches. Contributors include sociologists who have written extensively on the methodology of the social sciences and researchers who have concerned themselves with important social policy issues in the fields of further education, community services and household finances.

Part i | 78 pages, considerations using multi-methods, chapter 1 | 35 pages, combining qualitative and quantitative approaches: an overview, chapter 2 | 17 pages, deconstructing the qualitative-quantitative divide 1, chapter 3 | 22 pages, quantitative and qualitative research: further reflections on their integration, part ii | 90 pages, studies using multi-methods, chapter 4 | 19 pages, the relationships between quantitative and qualitative approaches in social policy research, chapter 5 | 25 pages, integrating methods in applied research in social policy: a case study of carers, chapter 6 | 17 pages, combining quantitative and qualitative methods: a case study of the implementation of the open college policy, chapter 7 | 24 pages, multiple methods in the study of household resource allocation.

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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).

Tests hypotheses that the researcher generates	Discovers and encapsulates meanings once the researcher becomes immersed in the data.
Concepts are in the form of distinct variables.	Concepts tend to be in the form of themes, motifs, generalizations, and taxonomies. However, the objective is still to generate concepts.
Measures are systematically created before data collection and are standardized as far as possible; e.g. measures of job satisfaction	Measures are more specific and may be specific to the individual setting or researcher; e.g. a specific scheme of values.
Data are in the form of numbers from precise measurement	Data are in the form of words from documents, observations, and transcripts. However, quantification is still used in qualitative research
Theory is largely causal and is deductive.	Theory can be causal or non-causal and is often inductive
Procedures are standard, and replication is assumed.	Research procedures are particular and replication is difficult.
Analysis proceeds by using statistics, tables, or charts and discussing how they relate to hypotheses.	Analysis proceeds by extracting themes or generalizations from evidence and organizing data to present a coherent, consistent picture. These generalizations can then be used to generate hypotheses

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 (two parts).

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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Methodology

Mixed Methods Research | Definition, Guide & Examples

Mixed Methods Research | Definition, Guide & Examples

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Convergent parallel

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

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

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

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

Explanatory sequential

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

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

Exploratory sequential

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

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

“Best of both worlds” analysis

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

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

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

Method flexibility

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

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

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

Differing or conflicting results

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

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

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

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

Research bias

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

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

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

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

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

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

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

These are four of the most common mixed methods designs :

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

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Three techniques for integrating data in mixed methods studies

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Peer review
Alicia O’Cathain , professor 1 ,
Elizabeth Murphy , professor 2 ,
Jon Nicholl , professor 1
1 Medical Care Research Unit, School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
2 University of Leicester, Leicester, UK
Correspondence to: A O’Cathain a.ocathain{at}sheffield.ac.uk
Accepted 8 June 2010

Techniques designed to combine the results of qualitative and quantitative studies can provide researchers with more knowledge than separate analysis

Health researchers are increasingly using designs that combine qualitative and quantitative methods, and this is often called mixed methods research. 1 Integration—the interaction or conversation between the qualitative and quantitative components of a study—is an important aspect of mixed methods research, and, indeed, is essential to some definitions. 2 Recent empirical studies of mixed methods research in health show, however, a lack of integration between components, 3 4 which limits the amount of knowledge that these types of studies generate. Without integration, the knowledge yield is equivalent to that from a qualitative study and a quantitative study undertaken independently, rather than achieving a “whole greater than the sum of the parts.” 5

Barriers to integration have been identified in both health and social research. 6 7 One barrier is the absence of formal education in mixed methods research. Fortunately, literature is rapidly expanding to fill this educational gap, including descriptions of how to integrate data and findings from qualitative and quantitative methods. 8 9 In this article we outline three techniques that may help health researchers to integrate data or findings in their mixed methods studies and show how these might enhance knowledge generated from this approach.

Triangulation protocol

Researchers will often use qualitative and quantitative methods to examine different aspects of an overall research question. For example, they might use a randomised controlled trial to assess the effectiveness of a healthcare intervention and semistructured interviews with patients and health professionals to consider the way in which the intervention was used in the real world. Alternatively, they might use a survey of service users to measure satisfaction with a service and focus groups to explore views of care in more depth. Data are collected and analysed separately for each component to produce two sets of findings. Researchers will then attempt to combine these findings, sometimes calling this process triangulation. The term triangulation can be confusing because it has two meanings. 10 It can be used to describe corroboration between two sets of findings or to describe a process of studying a problem using different methods to gain a more complete picture. The latter meaning is commonly used in mixed methods research and is the meaning used here.

The process of triangulating findings from different methods takes place at the interpretation stage of a study when both data sets have been analysed separately (figure ⇓ ). Several techniques have been described for triangulating findings. They require researchers to list the findings from each component of a study on the same page and consider where findings from each method agree (convergence), offer complementary information on the same issue (complementarity), or appear to contradict each other (discrepancy or dissonance). 11 12 13 Explicitly looking for disagreements between findings from different methods is an important part of this process. Disagreement is not a sign that something is wrong with a study. Exploration of any apparent “inter-method discrepancy” may lead to a better understanding of the research question, 14 and a range of approaches have been used within health services research to explore inter-method discrepancy. 15

Point of application for three techniques for integrating data in mixed methods research

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The most detailed description of how to carry out triangulation is the triangulation protocol, 11 which although developed for multiple qualitative methods, is relevant to mixed methods studies. This technique involves producing a “convergence coding matrix” to display findings emerging from each component of a study on the same page. This is followed by consideration of where there is agreement, partial agreement, silence, or dissonance between findings from different components. This technique for triangulation is the only one to include silence—where a theme or finding arises from one data set and not another. Silence might be expected because of the strengths of different methods to examine different aspects of a phenomenon, but surprise silences might also arise that help to increase understanding or lead to further investigations.

The triangulation protocol moves researchers from thinking about the findings related to each method, to what Farmer and colleagues call meta-themes that cut across the findings from different methods. 11 They show a worked example of triangulation protocol, but we could find no other published example. However, similar principles were used in an iterative mixed methods study to understand patient and carer satisfaction with a new primary angioplasty service. 16 Researchers conducted semistructured interviews with 16 users and carers to explore their experiences and views of the new service. These were used to develop a questionnaire for a survey of 595 patients (and 418 of their carers) receiving either the new service or usual care. Finally, 17 of the patients who expressed dissatisfaction with aftercare and rehabilitation were followed up to explore this further in semistructured interviews. A shift of thinking to meta-themes led the researchers away from reporting the findings from the interviews, survey, and follow-up interviews sequentially to consider the meta-themes of speed and efficiency, convenience of care, and discharge and after care. The survey identified that a higher percentage of carers of patients using the new service rated the convenience of visiting the hospital as poor than those using usual care. The interviews supported this concern about the new service, but also identified that the weight carers gave to this concern was low in the context of their family member’s life being saved.

Morgan describes this move as the “third effort” because it occurs after analysis of the qualitative and the quantitative components. 17 It requires time and energy that must be planned into the study timetable. It is also useful to consider who will carry out the integration process. Farmer and colleagues require two researchers to work together during triangulation, which can be particularly important in mixed methods studies if different researchers take responsibility for the qualitative and quantitative components. 11

Following a thread

Moran-Ellis and colleagues describe a different technique for integrating the findings from the qualitative and quantitative components of a study, called following a thread. 18 They state that this takes place at the analysis stage of the research process (figure ⇑ ). It begins with an initial analysis of each component to identify key themes and questions requiring further exploration. Then the researchers select a question or theme from one component and follow it across the other components—they call this the thread. The authors do not specify steps in this technique but offer a visual model for working between datasets. An approach similar to this has been undertaken in health services research, although the researchers did not label it as such, probably because the technique has not been used frequently in the literature (box)

An example of following a thread 19

Adamson and colleagues explored the effect of patient views on the appropriate use of services and help seeking using a survey of people registered at a general practice and semistructured interviews. The qualitative (22 interviews) and quantitative components (survey with 911 respondents) took place concurrently.

The researchers describe what they call an iterative or cyclical approach to analysis. Firstly, the preliminary findings from the interviews generated a hypothesis for testing in the survey data. A key theme from the interviews concerned the self rationing of services as a responsible way of using scarce health care. This theme was then explored in the survey data by testing the hypothesis that people’s views of the appropriate use of services would explain their help seeking behaviour. However, there was no support for this hypothesis in the quantitative analysis because the half of survey respondents who felt that health services were used inappropriately were as likely to report help seeking for a series of symptoms presented in standardised vignettes as were respondents who thought that services were not used inappropriately. The researchers then followed the thread back to the interview data to help interpret this finding.

After further analysis of the interview data the researchers understood that people considered the help seeking of other people to be inappropriate, rather than their own. They also noted that feeling anxious about symptoms was considered to be a good justification for seeking care. The researchers followed this thread back into the survey data and tested whether anxiety levels about the symptoms in the standardised vignettes predicted help seeking behaviour. This second hypothesis was supported by the survey data. Following a thread led the researchers to conclude that patients who seek health care for seemingly minor problems have exceeded their thresholds for the trade-off between not using services inappropriately and any anxiety caused by their symptoms.

Mixed methods matrix

A unique aspect of some mixed methods studies is the availability of both qualitative and quantitative data on the same cases. Data from the qualitative and quantitative components can be integrated at the analysis stage of a mixed methods study (figure ⇑ ). For example, in-depth interviews might be carried out with a sample of survey respondents, creating a subset of cases for which there is both a completed questionnaire and a transcript. Cases may be individuals, groups, organisations, or geographical areas. 9 All the data collected on a single case can be studied together, focusing attention on cases, rather than variables or themes, within a study. The data can be examined in detail for each case—for example, comparing people’s responses to a questionnaire with their interview transcript. Alternatively, data on each case can be summarised and displayed in a matrix 8 9 20 along the lines of Miles and Huberman’s meta-matrix. 21 Within a mixed methods matrix, the rows represent the cases for which there is both qualitative and quantitative data, and the columns display different data collected on each case. This allows researchers to pay attention to surprises and paradoxes between types of data on a single case and then look for patterns across all cases 20 in a qualitative cross case analysis. 21

We used a mixed methods matrix to study the relation between types of team working and the extent of integration in mixed methods studies in health services research (table ⇓ ). 22 Quantitative data were extracted from the proposals, reports, and peer reviewed publications of 75 mixed methods studies, and these were analysed to describe the proportion of studies with integrated outputs such as mixed methods journal articles. Two key variables in the quantitative component were whether the study was assessed as attempting to integrate qualitative or quantitative data or findings and the type of publications produced. We conducted qualitative interviews with 20 researchers who had worked on some of these studies to explore how mixed methods research was practised, including how the team worked together.

Example of a mixed methods matrix for a study exploring the relationship between types of teams and integration between qualitative and quantitative components of studies* 22

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The shared cases between the qualitative and quantitative components were 21 mixed methods studies (because one interviewee had worked on two studies in the quantitative component). A matrix was formed with each of the 21 studies as a row. The first column of the matrix contained the study identification, the second column indicated whether integration had occurred in that project, and the third column the score for integration of publications emerging from the study. The rows were then ordered to show the most integrated cases first. This ordering of rows helped us to see patterns across rows.

The next columns were themes from the qualitative interview with a researcher from that project. For example, the first theme was about the expertise in qualitative research within the team and whether the interviewee reported this as adequate for the study. The matrix was then used in the context of the qualitative analysis to explore the issues that affected integration. In particular, it helped to identify negative cases (when someone in the analysis doesn’t fit with the conclusions the analysis is coming to) within the qualitative analysis to facilitate understanding. Interviewees reported the need for experienced qualitative researchers on mixed methods studies to ensure that the qualitative component was published, yet two cases showed that this was neither necessary nor sufficient. This pushed us to explore other factors in a research team that helped generate outputs, and integrated outputs, from a mixed methods study.

Themes from a qualitative study can be summarised to the point where they are coded into quantitative data. In the matrix (table ⇑ ), the interviewee’s perception of the adequacy of qualitative expertise on the team could have been coded as adequate=1 or not=2. This is called “quantitising” of qualitative data 23 ; coded data can then be analysed with data from the quantitative component. This technique has been used to great effect in healthcare research to identify the discrepancy between health improvement assessed using quantitative measures and with in-depth interviews in a randomised controlled trial. 24

We have presented three techniques for integration in mixed methods research in the hope that they will inspire researchers to explore what can be learnt from bringing together data from the qualitative and quantitative components of their studies. Using these techniques may give the process of integration credibility rather than leaving researchers feeling that they have “made things up.” It may also encourage researchers to describe their approaches to integration, allowing them to be transparent and helping them to develop, critique, and improve on these techniques. Most importantly, we believe it may help researchers to generate further understanding from their research.

We have presented integration as unproblematic, but it is not. It may be easier for single researchers to use these techniques than a large research team. Large teams will need to pay attention to team dynamics, considering who will take responsibility for integration and who will be taking part in the process. In addition, we have taken a technical stance here rather than paying attention to different philosophical beliefs that may shape approaches to integration. We consider that these techniques would work in the context of a pragmatic or subtle realist stance adopted by some mixed methods researchers. 25 Finally, it is important to remember that these techniques are aids to integration and are helpful only when applied with expertise.

Summary points

Health researchers are increasingly using designs which combine qualitative and quantitative methods

However, there is often lack of integration between methods

Three techniques are described that can help researchers to integrate data from different components of a study: triangulation protocol, following a thread, and the mixed methods matrix

Use of these methods will allow researchers to learn more from the information they have collected

Cite this as: BMJ 2010;341:c4587

Funding: Medical Research Council grant reference G106/1116

Competing interests: All authors have completed the unified competing interest form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare financial support for the submitted work from the Medical Research Council; no financial relationships with commercial entities that might have an interest in the submitted work; no spouses, partners, or children with relationships with commercial entities that might have an interest in the submitted work; and no non-financial interests that may be relevant to the submitted work.

Contributors: AOC wrote the paper. JN and EM contributed to drafts and all authors agreed the final version. AOC is guarantor.

Provenance and peer review: Not commissioned; externally peer reviewed.

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Introduction: Considering Qualitative, Quantitative and Mixed Methods Research

First Online: 24 December 2020

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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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An Introduction to Qualitative and Mixed Methods Study Designs in Health Research

The Nature of Mixed Methods Research

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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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The Growing Importance of Mixed-Methods Research in Health

Sharada prasad wasti.

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

Padam Simkhada

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

Edwin R. van Teijlingen

Brijesh sathian.

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

Indrajit Banerjee

5 Sir Seewoosagur Ramgoolam Medical College, Belle Rive, Mauritius

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

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

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

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

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

Underpinning philosophies

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

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

The relevance of mixed-methods in health research

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

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

Strengths and weaknesses of mixed-methods

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

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

Common mistakes in applying mixed-methods

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

The way forward

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

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Combining qualitative and quantitative research within mixed method research designs: a methodological review

Affiliation.

1 Division of Nursing, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden. [email protected]
PMID: 21084086
PMCID: PMC7094322
DOI: 10.1016/j.ijnurstu.2010.10.005

Objectives: It has been argued that mixed methods research can be useful in nursing and health science because of the complexity of the phenomena studied. However, the integration of qualitative and quantitative approaches continues to be one of much debate and there is a need for a rigorous framework for designing and interpreting mixed methods research. This paper explores the analytical approaches (i.e. parallel, concurrent or sequential) used in mixed methods studies within healthcare and exemplifies the use of triangulation as a methodological metaphor for drawing inferences from qualitative and quantitative findings originating from such analyses.

Design: This review of the literature used systematic principles in searching CINAHL, Medline and PsycINFO for healthcare research studies which employed a mixed methods approach and were published in the English language between January 1999 and September 2009.

Results: In total, 168 studies were included in the results. Most studies originated in the United States of America (USA), the United Kingdom (UK) and Canada. The analytic approach most widely used was parallel data analysis. A number of studies used sequential data analysis; far fewer studies employed concurrent data analysis. Very few of these studies clearly articulated the purpose for using a mixed methods design. The use of the methodological metaphor of triangulation on convergent, complementary, and divergent results from mixed methods studies is exemplified and an example of developing theory from such data is provided.

Conclusion: A trend for conducting parallel data analysis on quantitative and qualitative data in mixed methods healthcare research has been identified in the studies included in this review. Using triangulation as a methodological metaphor can facilitate the integration of qualitative and quantitative findings, help researchers to clarify their theoretical propositions and the basis of their results. This can offer a better understanding of the links between theory and empirical findings, challenge theoretical assumptions and develop new theory.

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Forum: Qualitative Social Research / Forum Qualitative Sozialforschung

The Fundamental Difference Between Qualitative and Quantitative Data in Mixed Methods Research

Judith Schoonenboom University of Vienna

Mixed methods research is commonly defined as the combination and integration of qualitative and quantitative data. However, defining these two data types has proven difficult. In this article, I argue that qualitative and quantitative data are fundamentally different, and this difference is not about words and numbers but about condensation and structure. As qualitative data are analyzed with qualitative methods and quantitative data with quantitative methods, we cannot analyze one type of data with the other type of method. Quantitative data analysis can reveal new patterns, but these are always related to the existing variables, whereas qualitative data analysis can reveal new aspects that are hidden in the data. To consider data as quantitative or qualitative, we should judge these data as end products, not in terms of the process through which they come into being. Thus, quantitizing qualitative data results in quantitative data and the analysis thereof is quantitative, not mixed, data analysis. For mixed data analysis, both real , non-quantitized qualitative data and quantitative data are needed. As these quantitative data may be quantitized qualitative data, the implication is that, contrary to a common view, mixed methods research does not necessarily involve quantitative data collection.

Author Biography

Judith schoonenboom, university of vienna.

Judith SCHOONENBOOM is professor of empirical pedagogy at the University of Vienna, Austria. She has extensive experience in designing and evaluating innovations in education, especially those involving educational technology. Her research interests include mixed methods design and the foundations of mixed methods research. Judith is an associate editor of the Journal of Mixed Methods Research and a past president (2020-2021) of the Mixed Methods International Research Association (MMIRA).

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http://orcid.org/0000-0002-4570-6686 Ramya Kumar 1 , 2 ,
http://orcid.org/0000-0003-4076-0170 Deepa Rao 3 ,
http://orcid.org/0000-0002-8189-0732 Anjali Sharma 1 ,
Jamia Phiri 1 ,
Martin Zimba 4 ,
Maureen Phiri 4 ,
Ruth Zyambo 5 ,
Gwen Mulenga Kalo 5 ,
Louise Chilembo 5 ,
Phidelina Milambo Kunda 6 ,
Chama Mulubwa 1 ,
Benard Ngosa 1 ,
http://orcid.org/0000-0001-5208-7468 Kenneth K Mugwanya 7 ,
Wendy E Barrington 8 ,
http://orcid.org/0000-0002-3629-3867 Michael E Herce 1 , 9 ,
http://orcid.org/0000-0001-9968-7540 Maurice Musheke 1
1 Centre for Infectious Disease Research in Zambia , Lusaka , Zambia
2 Epidemiology , University of Washington School of Public Health , Seattle , Washington , USA
3 University of Washington School of Public Health , Seattle , Washington , USA
4 Zambia Sex Workers Alliance , Lusaka , Zambia
5 Tithandizeni Umoyo Network , Lusaka , Zambia
6 Lusaka District Health Office , Zambia Ministry of Health , Lusaka , Zambia
7 Epidemiology, Global Health , University of Washington School of Public Health , Seattle , Washington , USA
8 Epidemiology; Child, Family, and Population Health Nursing; Health Systems and Population Health , University of Washington School of Public Health , Seattle , Washington , USA
9 Institute for Global Health and Infectious Diseases , University of North Carolina at Chapel Hill , Chapel Hill , North Carolina , USA
Correspondence to Dr Ramya Kumar; ramya.kumar.mlk{at}gmail.com

Introduction Women engaging in sex work (WESW) have 21 times the risk of HIV acquisition compared with the general population. However, accessing HIV pre-exposure prophylaxis (PrEP) remains challenging, and PrEP initiation and persistence are low due to stigma and related psychosocial factors. The WiSSPr (Women in Sex work, Stigma and PrEP) study aims to (1) estimate the effect of multiple stigmas on PrEP initiation and persistence and (2) qualitatively explore the enablers and barriers to PrEP use for WESW in Lusaka, Zambia.

Methods and analysis WiSSPr is a prospective observational cohort study grounded in community-based participatory research principles with a community advisory board (CAB) of key population (KP) civil society organi sations (KP-CSOs) and the Ministry of Health (MoH). We will administer a one-time psychosocial survey vetted by the CAB and follow 300 WESW in the electronic medical record for three months to measure PrEP initiation (#/% ever taking PrEP) and persistence (immediate discontinuation and a medication possession ratio). We will conduct in-depth interviews with a purposive sample of 18 women, including 12 WESW and 6 peer navigators who support routine HIV screening and PrEP delivery, in two community hubs serving KPs since October 2021. We seek to value KP communities as equal contributors to the knowledge production process by actively engaging KP-CSOs throughout the research process. Expected outcomes include quantitative measures of PrEP initiation and persistence among WESW, and qualitative insights into the enablers and barriers to PrEP use informed by participants’ lived experiences.

Ethics and dissemination WiSSPr was approved by the Institutional Review Boards of the University of Zambia (#3650-2023) and University of North Carolina (#22-3147). Participants must give written informed consent. Findings will be disseminated to the CAB, who will determine how to relay them to the community and stakeholders.

MENTAL HEALTH
HIV & AIDS
EPIDEMIOLOGIC STUDIES
Health Equity
QUALITATIVE RESEARCH
SOCIAL MEDICINE

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2023-080218

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STRENGTHS AND LIMITATIONS OF THIS STUDY

The Women in Sex work, Stigma and PrEP (WiSSPr) study uses a mixed-methods approach which is ideal for intersectional stigma research because it allows quantitative research to be grounded in the lived experiences of people, while ensuring that aspects of stigma that emerge at the intersections of identities are measured in testable ways.

Qualitative aim enrolls peer navigators to capture the perspectives of women who are at the unique interface of recipients of care as sex workers themselves, and supporters of health service delivery.

Uses core principles of community-based participatory research which value key populations as equal contributors to the knowledge production process.

Limitations include an inability to longitudinally assess the alignment of pre-exposure prophylaxis (PrEP) adherence and persistence with HIV risk, and limitations in measuring PrEP adherence by self-report and pharmacy dispensations instead of by drug biomarkers.

Introduction

Women engaging in sex work (WESW) are a key population (KP) that experiences an unacceptably high risk of HIV infection. In 2019, the Joint United Nations Programme on HIV/AIDS (UNAIDS) estimate WESW have 21 times the risk of HIV acquisition compared with the general population of adults aged 15 – 49 years old. 1 In Southern and East Africa, KPs and their sexual partners account for 25% of all new HIV infections. 2 To reduce the burden of HIV in Africa, HIV prevention strategies tailored to the unique needs of WESW are critical to safeguarding their health, as well as the health of people in their sexual networks. 3 4

While HIV pre-exposure prophylaxis (PrEP) is highly effective in preventing HIV infection, its real-world efficacy is closely linked to adherence, which is a complex process for WESW. A systematic review of PrEP usage and adherence among WESW reveals complex interrelationships between individual perceptions of HIV risk, social support and fear of healthcare provider stigma. 5 WESW may experience multiple stigmatised identities, conditions or behaviours, such as participating in sex work, having a substance use disorder, and taking HIV prevention medication. 6

Zambia has a generalised HIV epidemic, and the capital city of Lusaka is a major regional transit hub attracting WESW from the region. Approximately 3,396 live in Lusaka with over half (53%) living with HIV, underscoring the need to urgently tailor prevention strategies for this population. 7 WESW in Zambia are subject to violence and discrimination in the form of verbal, physical and sexual abuse from strangers, acquaintances, clients, intimate partners and even law enforcement. 8 Surveys among WESW in Zambia have identified healthcare provider stigma and discrimination, as well as a lack of confidential care as main barriers to HIV prevention services at public health facilities. 7 9 Therefore, a better understanding of the multiple stigmas that WESW experience is a critical first step to designing interventions to meet their HIV prevention needs.

In recent years, Zambia has made significant progress in reaching WESW and providing them with comprehensive HIV prevention services. Since May 2019, the PEPFAR-funded Key Population Investment Fund (KPIF) has been successfully engaging with KP in Lusaka Province and providing them with community-based HIV prevention and treatment services. KPIF is implemented by the Centre for Infectious Disease Research in Zambia (CIDRZ) in partnership with the Zambian Ministry of Health (MoH), US Centers for Disease Control and Prevention and importantly, key population civil society organisations (KP-CSOs). A key objective of the KPIF programme is to improve PrEP initiation, persistence and adherence for HIV-negative WESW. For this study, we propose to leverage existing KPIF infrastructure to enhance study feasibility and ensure its real-world relevance to achieving this key objective.

Although PrEP initiations are high in the KPIF programme, they may not accurately reflect PrEP effectiveness. 10 A systematic review of 41 studies found high discontinuation rates at 1 month. 11 Despite WHO recommendations and national PrEP guidelines for regular HIV testing and follow-up visits, maintaining client engagement with PrEP has been challenging. 12 13 This has resulted in a lack of data on short-term PrEP persistence among WESW in Zambia. Assessing the percentage of clients who do not return for their first follow-up visit is crucial for determining PrEP effectiveness. Current prevention strategies do not adequately address the multiple stigmas and psychosocial stress that hinder PrEP persistence.

Specific objectives

The Women in Sex work, Stigma and PrEP (WiSSPr) mixed-methods study aims to (1) measure the association between multiple stigmas on PrEP initiation and persistence among HIV-negative adult WESW and (2) qualitatively explore the enablers and barriers (interpersonal, psychosocial and structural) to initiating and persisting on PrEP. The qualitative aim will complement and contextualise 14–16 findings from the quantitative results. We hypothesize that WESW with high levels of any type of stigma will be less likely to initiate and persist on PrEP.

Conceptual framework

Interview guides will be informed by the Community, Opportunity, Motivation – Behaviour (COM-B) framework to assess how these components drive engagement with PrEP services. 17 18 The COM-B model is commonly used in HIV prevention because it offers a framework to guide the development and implementation of targeted interventions, thereby enhancing the efficacy and reach of HIV prevention programmes. 19 This framework will guide us to identify deficits in knowledge or skills (Capability), environmental and social contexts (Opportunity), and personal motivations and attitudes (Motivation). This integrated approach ensures that all relevant aspects of behaviour change are considered, leading to more effective and sustainable health outcomes.

Directed acyclic graph

Directed acyclic graphs (DAG) visually synthesise a priori knowledge about the hypothesised relationships between variables of interest, helping to identify causal pathways and potential confounders that could bias the results. We propose confounders based on their known association with stigmas and PrEP persistence, using evidence from published studies addressing similar questions. Controlling for the following variables will be sufficient to block any unconditionally open, non-causal backdoor paths that could lead to confounding: age, community hub, duration of sex work, and education ( figure 1 ).

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Directed acyclic graph illustrating the causal effect of stigma on PrEP persistence. PrEP, pre-exposure prophylaxis.

Methods and analysis

Study design.

We will use a prospective observational cohort study design with mixed methods to characterise PrEP outcomes for HIV-negative WESW in Lusaka, Zambia. Trained research assistants will administer a one-time, 75-item psychosocial survey to participants and follow them prospectively in the electronic medical record. For the qualitative aim, we will conduct in-depth interviews (IDIs) with WESW to get perspectives of prevention services with peer navigators who are both recipients of care and supporters of health service delivery.

Mixed-methods integration

We will use the NIH ‘Best Practices for Mixed Methods’ guidelines to design, analyse and interpret qualitative and quantitative data in mixed-methods research. 20 Specifically, we will employ a convergent parallel design that collects both qualitative and quantitative data concurrently and separately, prioritising both the quantitative and qualitative strands equally but keeping them independent during analysis. We will interpret the extent to which the two sets of results converge, diverge, relate to each other and/or combine to create a better understanding in response to the study’s overall purpose. 20

Study setting

The study population is composed of adult WESW who are living or working within the catchment areas of two community hubs located within urban Lusaka. Based on CIDRZ’s prior published work, we anticipate that the study population will be comprised largely (63%) of younger women (18 – 29 years old). 10

Study exposures and outcomes

Table 1 identifies the primary outcomes of PrEP initiation and persistence from pharmacy dispensations records in the last 90 days for survey participants. Several studies have accessed this data from the national electronic medical record system SmartCare. 21 22 CIDRZ is a key Smartcare implementing partner and routinely leveraging this data to optimise service delivery for KP in KPIF in order to better understand outcomes for HIV treatment and prevention in the national HIV programme. 23–28 Table 2 identifies the independent variables of interest including sociodemographic history, intersectional stigma (everyday discrimination scale), 29 substance use (ASSIST), 30 depressive symptoms (Patient Health Questionnaire, PHQ), 31 as well as sex work, HIV and PrEP-related stigmas and resulting discrimination using established questionnaires. 32–34 The qualitative outcomes are insights into the enablers and barriers to PrEP use informed by participants’ lived experiences according to the COM-B model.

View inline

WiSSPr study outcomes

WiSSPr study independent variables

Sample size

We determined the minimum sample size using Demidenko’s method for logistic regression with binary interactions, informed by effect size and variance data from Witte et al ’s study on PrEP acceptability among women in Uganda. 35–37 Sample size considerations are based on our primary outcome of PrEP initiation and informed by preliminary programmatic data that formed assumptions about baseline HIV prevalence and estimated PrEP initiations. Each site tests an average of 200 WESW per month, which will allow an estimated 800 women to be tested during the 2-month enrolment period. We project approximately 56% (448) will test HIV-negative, and of these, we estimate 403 (90%) will be eligible, and 350 (87%) will agree to initiate PrEP. Due to time and resource limitations, we seek to enroll a sample of 300 eligible WESW. Assuming 5% of participant medical records cannot be found, a total cohort of 285 PrEP users would allow us to estimate the prevalence ratio of stigma on PrEP initiation of 1.98 or higher (positive association), or 0.50 or lower (negative association) at 80% power with a significance level of 0.05. We aim to recruit 18 participants for IDIs, based on prior research with this population and qualitative methodology guidelines suggesting that 6 – 10 interviews per subgroup are sufficient to reach thematic saturation 14 20

Participant recruitment

The study will start in July 2023. WiSSPr will recruit 300 participants from a convenience sample of WESW who are receiving HIV services from two community-based hubs which have been functioning as MoH drop-in wellness centres since October 2021. All HIV testing and prevention services at these community hubs are led by teams of KP and MoH staff. Outreach activities take place in venues where WESW socialise, such as brothels, bars, or the home of a KP. Recruitment activities will take place during these outreach activities. KPIF programming leverages KP social networks to mobilise WESW for recruitment into the study. A total of 18 participants, including 6 peer navigators, 6 WESW who discontinue PrEP after initiation, and 6 WESW who continue on PrEP, will be purposively sampled for IDIs, or until we achieve thematic saturation. 38 Qualitative data collection will take place at least 30 days after the quantitative recruitment begins, in order to sample women who initiate a 30 day supply of PrEP but do not return to pick up another refill. Figure 2 outlines the WiSSPr study recruitment process.

The WiSSPr study flow diagram summarises the stages of participant recruitment and follow-up. PrEP, pre-exposure prophylaxis; WiSSPr, Women in Sex work, Stigma and PrEP.

Recruitment will end when 300 participants have been enrolled for the survey and 18 participants enrolled for interviews. PrEP event data will be abstracted from SmartCare approximately 3 months after the final participant’s enrollment. Study activities, including qualitative data collection, data quality control and assurance, and data analysis, are anticipated to continue until the planned end of the study in September 2024.

We will engage the community advisory board (CAB) in collaborative decision-making on: (1) how best to conduct outreach to venues that WESW frequent, (2) how to engage leaders in the sex work community to inform them about this study, and (3) to encourage WESW participation in a way that minimises social harms. Box 1 identifies the inclusion and exclusion criteria for the study. Written informed consent in English or local languages (ChiNyanja or IchiBemba) will be obtained before enrollment. As an added measure of protection for this marginalised population, participants must complete an informed consent quiz to ensure that they understand the potential risks of study participation. Participants will receive the Zambia Kwacha equivalent of US$5 per survey and interview as compensation for their time.

Inclusion and exclusion criteria

Cohort inclusion and exclusion criteria are as follows:

Inclusion criteria: (1) identify as a cis-gendered or transgendered woman, (2) age ≥ 18 years, (3) earns a significant amount of income from exchanging sex for money or goods in the last 3 months, (4) HIV-negative status and eligible for PrEP according to national guidelines, (5) not planning to transfer care to another site within the next 30 days, (6) speaks English or ChiNyanja or IchiBemba and (7) willing and able to provide written informed consent

Exclusion criteria: (1) do not identify as a woman, (2) age < 18 years old, (3) has not earned a significant amount of income from exchanging sex for money or goods or has earned for < 3 months, (4) HIV-positive status or status is unknown or ineligible for PrEP, (5) planning to transfer care to another site within the next 30 days, (6) unable to speak English or ChiNyanja or IchiBemba and (7) not willing or able to provide written informed consent

In-depth interviews will be conducted with cohort members, as well as peer navigators. The inclusions and exclusion criteria for peer navigators is as follows:

Inclusion criteria: (1) age ≥ 18 years old, (2) history working as a peer health navigator, (3) history of providing HIV services to women engaging in sex work, (4) speaks English or ChiNyanja or IchiBemba and (5) willing and able to provide written informed consent.

Exclusion criteria: (1) age < 18 years, (2) does not have a history working as a peer health navigator, (3) does not have a history of providing HIV services to women engaging in sex work, (4) unable to speak English or ChiNyanja or IchiBemba and (5) not willing or able to provide written informed consent.

Quantitative data collection

A team of 3–5 trained research assistants will administer a tablet-based survey ( online supplemental file 1 ) for quicker data entry, real-time quality control and logic checks to reduce data entry errors and immediate data backup compared with paper. Surveys, estimated to take 60 min each, will be conducted in English, ChiNyanja or IchiBemba, based on participant preference. The survey tool will be piloted with CAB members and peer navigators. Patient medical records are routinely entered by KPIF programme staff into a secure, standardised electronic data capture system, from which we will extract relevant deidentified data using the participants’ SmartCare ID numbers.

Supplemental material

Qualitative data collection.

We will use a semi-structured interview guide ( online supplemental file 1 ) with open-ended questions and probes to explore specific themes related to HIV prevention and intersectional stigma. This guide allows some flexibility for participants to follow topics of interest to them. The themes we will explore are informed by the COM-B conceptual framework which include perceived and enacted stigma, the impact of intersectional stigmas on health service utilisation service needs, enablers such as psychosocial support or the trustworthiness of the healthcare system. The guide also includes modules on PrEP where the interviewer will explain oral and long-acting injectable PrEP and assess participants perceptions of the advantages and disadvantages and willingness to use these different PrEP options. Participants will be asked about their own perceptions as well as their perceived opinions of their peers, as this approach has yielded richer responses in previous studies. 39 Interviews are estimated to take 60 minutes and will be conducted in English, ChiNyanja, or IchiBemba in a private location at a community safe space or other similarly secure location determined by participant preference. We will request permission to audio record interviews for transcription and translation. All interviews will be conducted by a single trained interviewer. The interview guides will be piloted with CAB members before implementation.

Data management

SmartCare serves as a repository of clinical data for WESW accessing KPIF services. A secure server will be used to store encrypted study data, including the study database. Quantitative data collected on tablets will be transmitted to the server at the end of each day. To ensure data safety, there will be daily backups, and data will also be stored on secure drives.

All IDIs will be audio recorded. Audio recordings will be transcribed verbatim and then translated into English in a single step by qualified research staff. The audio recordings will not be marked with any identifying information. Instead, interviewers will use unique participant codes to label the audio recordings. No personal identifiers will be used, and any identifiers inadvertently mentioned during interviews will be purged from the transcripts prior to analysis.

All medical records that contain participant identities are treated as confidential in accordance with the Zambian Data Protection Act. All study documents related to the participants will only include an assigned participant code. Only research staff will have access to linkable information, which will be kept strictly confidential. All records will be archived in a secure storage facility for 3 years after the completion of the study per local regulatory guidelines, after which time all electronic data will be deleted from project servers and hard drives, and all paper-based records will be disposed of.

Quantitative data analysis

We will conduct univariable analyses to examine whether there are differences in the levels of stigma, discrimination, depressive symptoms and substance use disorders among those who initiate PrEP versus those who do not, stratified by community hub. We will report the prevalences of HIV and PrEP stigmas, discrimination due to intersectional stigma identified by the Everyday Discrimination scale, depression and suicidal ideation identified by PHQ, and substance use disorders identified by ASSIST. We will sum all items within a screener to a total score before collapsing data into categorical variables. For cases where missing data are more limited (approximately < 5%), for single items and measures, we will use mean imputation to derive a score. If there is substantial missingness (> 10%) then we will use missing data methods such as multiple imputation.

A PHQ-9 score ≥ 10 is commonly used in primary care settings as a cut-off for probable major depression. 40 PHQ-9 cut-off scores of 5, 10, 15 and 20 will be categorised as mild, moderate, moderately severe and severe depression, respectively. The ASSIST gives 10 risk scores for tobacco, alcohol, cannabis, cocaine, amphetamine-type stimulants, inhalants, sedatives, hallucinogens, opioids and other drugs. The score is higher the more frequently the participant reports using substances. For alcohol use, we will use cut-offs of 11 and 27 for moderate and high risk of substance use disorder. For all other substances cut-offs of 4, and 27 for moderate and high risk. 30

PrEP initiation will be calculated using the total number of individuals initiated on PrEP over the total number of HIV-negative individuals who were enrolled and eligible for PrEP. We refer to the complement of discontinuation as PrEP persistence. 41 We define immediate discontinuation for those who initiate a 30 day supply of PrEP and do not return for any refills over the 108 day observation period in alignment with national antiretroviral therapy (ART) programme guidelines on continuity of care and management of missed appointments. 21 42 We will calculate a medication possession ratio (MPR) of total days with medication in patient possession to the observation period, as a measure of engagement in services and report both the MPR and IQR ( table 1 ).

We will use Stata (V.16.1, StataCorp) for analysis, reporting descriptive statistics to characterise the study population and bivariate associations between key exposures and immediate discontinuation with Pearson’s χ 2 statistics. We will fit Poisson regression models, which will estimate prevalence ratios of discrimination, PrEP stigma and HIV stigma on immediate discontinuation of PrEP over a 3-month follow-up period, controlling for confounders identified by the DAG. Adjusted prevalence ratio estimates will be reported with 95% CIs and p-values at the alpha = 0.05 significance level.

Qualitative data analysis

We will analyse the qualitative data using established analytical software (NVivo, QSR International, Melbourne, Australia) through deductive reasoning based on our conceptual model and inductive reasoning to identify major and minor themes emerging from audio recordings and transcripts. The process of eliciting themes will involve familiarisation with interview transcripts and noting emergent themes, adapting our conceptual framework as necessary, performing open coding, developing a codebook, performing data reduction, data display using matrices and/or tables, and interpretation to map out relationships in the data. Two coders will review these data, independently identify emergent themes, and confer to agree on final coding and findings. We will apply established qualitative research principles in our analyses, including negative case analysis and respondent validation. 43 44

Participant attitudes and preferences relating to elements of future stigma-reduction intervention, psychosocial support provision and long-acting injectable PrEP will be described qualitatively. We will strive for critical reflexivity by outlining our point of view in relation to the interviewees of the study during data collection and will state how positionality and context may have affected the findings. The credibility and trustworthiness of qualitative data will be assured through member-checking by participants themselves. 45

Ethics and dissemination

WiSSPr was approved by the Institutional Review Boards of the University of Zambia (#3650 -2023) and University of North Carolina, the Zambia National Health Research Authority and the Lusaka Provincial and District Health Offices. A final study notification will be sent on completion of the study, or in the event of early termination. Participants are free to withdraw from the study at any time without affecting their right to medical care.

The study findings will be disseminated to KP community members, providers, researchers and policy-makers. The CAB will review preliminary results and advise on meaningful dissemination to the KP community, National AIDS Council, National HIV and Mental Health Technical Working Groups, investigators and stakeholders. The information will be presented at conferences or published in peer-reviewed journals. Participants’ personal information will not be included in any publications.

Patient and public involvement

We will use principles of community-based participatory research (CBPR) to ensure patient and public involvement in this study. CBPR is a research paradigm that focuses on relationships between academic and community partners, with principles of co-learning, mutual benefit and long-term commitment. 46 CBPR incorporates community theories, participation, and practices into the research efforts and plays a role in expanding the reach of implementation science to influence practice and policies for eliminating health disparities. 46 47

To collaboratively develop this study with clients and the public, we will use CBPR principles and create a CAB with Lusaka District Health Office and two KP-CSOs working in the study sites: Zambia Sex Workers Alliance and Tithandizeni Umoyo Network. As a study team, our first priority is to develop trust with people engaging in sex work. Trust development is a construct of CBPR and has also emerged as a synthesising theory. 48 49 Trust types are ordered along a relative continuum from least (trust deficit) to most (critical reflective) trust which reflects an ability to discuss and move on after a misstep. 48 Given the historical marginalisation and stigmatisation of WESW in Zambia, we anticipate a trust deficit and have allocated time and budget to nurture and develop trust along this continuum. We will build trust through ‘role-based trust’ as researchers, ‘proxy trust’ from the reputation of CIDRZ and KP CSO team members’ work with KPs in Zambia, and ultimately aim to establish ‘critical reflective’ trust.

The research questions and outcome measures were developed in collaboration with the CAB, ensuring they reflect the priorities, experiences and preferences of the sex worker community. Input from the CAB helped tailor the study to address the most pressing issues identified by the community. The study team will work with the CAB to adapt the study within complex systems of organisational and cultural context and knowledge. Collaborative decision-making will occur prior to the study launch, throughout the recruitment period, and during dissemination. The CAB will provide feedback on the potential burden of the intervention and the time required for participation, so that the study minimises inconvenience and respected participants’ time constraints. All partners will decide what it means to have a ‘collaborative, equitable partnership’ and how to make that happen. 50 The CAB will advise on which community hub to recruit from first, and how to work with community leaders to adapt study standard operating procedures to not disrupt service implementation at study sites. They will also advise on how to minimise potential risks to participants, including ways to reduce emotional distress and ensure physical safety. Participants experiencing emotional distress will be referred for psychosocial support with evidence-based mental health therapy specialised for those with depression and substance abuse, with the KPIF providing transportation and a peer navigator accompanying them to the facility providing these services. The CAB will be actively involved in planning the dissemination of study results to participants and the wider community, helping decide what information to share, the timing of the dissemination and the most appropriate formats for communicating the findings.

The WiSSPr study is significant as it addresses the limitations of HIV interventions that focus solely on HIV-related stigma, without considering co-occurring stigmas linked to other identities or conditions. This study will inform the design of PrEP service delivery programmes for WESW in Zambia and the region. Understanding stigmas and related psychosocial factors is crucial for developing effective, evidence-based stigma-reduction interventions for WESW in Africa. Our long-term goal is to optimise person-centred HIV prevention by implementing inclusive, affirming practices for individuals facing multiple barriers.

Strengths of this study include (1) a mixed-methods approach which grounds quantitative research in the lived experiences of people and measures aspects of stigma that emerge at the intersections of identities, (2) qualitative data from peer navigators capturing perspectives of women at the unique interface of being recipients of care as sex workers as well as direct supporters of health service delivery, and (3) incorporation of core principles of CBPR which value KP-CSOs as equal contributors to the knowledge production process.

Several methodological limitations are also inherent in the study. First, we are unable to longitudinally assess the alignment of PrEP adherence and persistence with HIV risk. We will be limited to measuring PrEP adherence by self-report and pharmacy dispensations instead of by biomarkers of tenofovir use. Secondly, recruitment might fall short at some sites, necessitating expansion to additional community outreach venues leveraging our network of KPs. Lastly, cohort studies may have bias, due to recall and social desirability bias of self-reported measures, and missing data.

Ethics statements

Patient consent for publication.

Not applicable.

Acknowledgments

The authors would like to acknowledge the infrastructure support provided by the Centre for Infectious Disease Research in Zambia (CIDRZ) and the Key Populations Investment Fund (KPIF) programme. The authors would also like to thank peer navigators and leaders in the sex work community for their assistance in developing the study approach and recruiting study participants.

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Williams DR ,
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Palinkas LA ,
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Dhiman VK , et al
Wallerstein NB ,
Wallerstein N ,
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Minkler M ,
Wallerstein N

MEH and MM are joint senior authors.

X @idlidosa2, @kenmugwanya, @webarrington

Contributors RK, DR, AS, MM, MH, KKM and WB conceived and designed the study. RK, DR, AS, MM, MH, JP, MZ, MP, RZ, GMK, LC, PMK, CM and BN created the interview guides and survey. All authors revised drafts and gave final approval for publication. MM is the guarantor of the study and accepts full responsibility for the finished work and the conduct of the study, had access to the data and controlled the decision to publish.

Funding The study is being supported by the NIH Fogarty Global Health Fellowship awarded by the NIH Fogarty International Center Grant #D43TW009340.

Competing interests None declared.

Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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Journal Article Reporting Standards (JARS)

APA Style Journal Article Reporting Standards offer guidance on what information should be included in all manuscript sections for quantitative, qualitative, and mixed methods research and include how to best discuss race, ethnicity, and culture.

Introducing APA Style Journal Article Reporting Standards for Race, Ethnicity, and Culture

Introducing Journal Article Reporting Standards for Race, Ethnicity, and Culture (JARS–REC)

JARS–REC were created to develop best practices related to the manner in which race, ethnicity, and culture are discussed within scientific manuscripts in psychological science.

Quantitative research

Use JARS–Quant when you collect your study data in numerical form or report them through statistical analyses.

Qualitative research

Use JARS–Qual when you collect your study data in the form of natural language and expression.

Mixed methods research

Use JARS–Mixed when your study combines both quantitative and qualitative methods.

Race, ethnicity, culture

Use JARS–REC for all studies for guidance on how to discuss race, ethnicity, and culture.

What are APA Style JARS?

APA Style Journal Article Reporting Standards (APA Style Jars ) are a set of standards designed for journal authors, reviewers, and editors to enhance scientific rigor in peer-reviewed journal articles. Educators and students can use APA Style JARS as teaching and learning tools for conducting high quality research and determining what information to report in scholarly papers.

The standards include information on what should be included in all manuscript sections for:

Quantitative research ( Jars –Quant)
Qualitative research ( Jars –Qual)
Mixed methods research ( Jars –Mixed)

Additionally, the APA Style Journal Article Reporting Standards for Race, Ethnicity, and Culture ( Jars – Rec ) provide guidance on how to discuss race, ethnicity, and culture in scientific manuscripts. Jars – Rec should be applied to all research, whether it is quantitative, qualitative, or mixed methods.

Race, Ethnicity, and Culture ( Jars – Rec )

Using these standards will make your research clearer and more accurate as well as more transparent for readers. For quantitative research, using the standards will increase the reproducibility of science. For qualitative research, using the standards will increase the methodological integrity of research.

Jars –Quant should be used in research where findings are reported numerically (quantitative research). Jars –Qual should be used in research where findings are reported using nonnumerical descriptive data (qualitative research). Jars –Mixed should be applied to research that includes both quantitative and qualitative research (mixed methods research). JARS–REC should be applied to all research, whether it is quantitative, qualitative, or mixed methods.

For more information on APA Style JARS:

Read Editorial: Journal Article Reporting Standards
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Many aspects of research methodology warrant a close look, and journal editors can promote better methods if we encourage authors to take responsibility to report their work in clear, understandable ways. —Nelson Cowan, Editor, Journal of Experimental Psychology: General

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This video describes and discusses the updated APA Style Journal Article Reporting Standards.

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History of APA’s journal article reporting standards
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From the APA Style blog

Introducing APA Style Journal Article Reporting Standards for Race, Ethnicity, and Culture

These standards are for all authors, reviewers, and editors seeking to improve manuscript quality by encouraging more racially and ethnically conscious and culturally responsive journal reporting standards for empirical studies in psychological science.

APA Style JARS for high school students

In this post, we provide an overview of APA Style JARS and resources that can be shared with high school students who want to learn more about effective communication in scholarly research.

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Happy 2022, APA Stylers!

This blog post is dedicated to our awesome APA Style users. You can use the many resources on our website to help you master APA Style and improve your scholarly writing.

APA Style JARS on the EQUATOR Network

The APA Style Journal Article Reporting Standards (APA Style JARS) have been added to the EQUATOR Network. The network aims to promote accuracy and quality in reporting of research.

APA Style JARS: Resources for instructors and students

APA Style Journal Article Reporting Standards (APA Style JARS) are a set of guidelines for papers reporting quantitative, qualitative, and mixed methods research that can be used by instructors, students, and all others reading and writing research papers.

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Advantages and Disadvantages of Qualitative and Quantitative Research Methods

Learn the advantages and disadvantages of qualitative and quantitative research methods, and find out which approach is best suited to your research goals.

Introduction

In the realm of research, qualitative and quantitative methods are two primary approaches, each offering distinct strengths and weaknesses. These methods differ in their focus, design, data collection, and analysis. While qualitative research excels in capturing in-depth insights and personal experiences, quantitative research provides a broader, more generalizable understanding of phenomena. Choosing between the two, or opting for a mixed-methods approach, depends on the research question and the desired outcomes.

Qualitative Research Methods

Advantages of Qualitative Methods :

Provides detailed and in-depth information : Qualitative research offers rich and nuanced insights into complex phenomena, providing a deep understanding of participants’ experiences and perspectives.
Addresses complex issues with flexible structures : The flexible nature of qualitative methods allows researchers to explore multifaceted issues, accommodating diverse viewpoints and evolving research paths.
Explores individuals’ experiences historically : Qualitative research captures the historical context of personal experiences, providing a comprehensive view of how experiences evolve over time.
Allows interaction with participants : Researchers engage directly with participants, often through interviews or focus groups, fostering a closer connection and deeper understanding of their perspectives.
Methods and frameworks can be shared : Qualitative methods often provide transferable frameworks that can be adapted to different contexts, though they are less standardized than quantitative methods.

Disadvantages of Qualitative Methods :

Lack of focus on contextual sensitivities : While qualitative research delves deep into individual experiences, it may neglect broader societal or contextual influences.
Relies on phenomenological methods : Subjectivity can become an issue as qualitative analysis often relies on interpretation, making findings more susceptible to bias.
Low credibility in certain fields : In fields like policy-making, where numerical data is often preferred, qualitative research may be viewed as less reliable or impactful.
Findings are not generalizable : Due to typically smaller sample sizes, the insights gained from qualitative research may not be applicable to larger populations.
Complex interpretation and analysis : The analysis of qualitative data can be labor-intensive, as it often involves interpreting subjective narratives and identifying patterns.

Quantitative Research Methods

Advantages of Quantitative Methods:

Results can be generalized : Quantitative research, with its large sample sizes, enables researchers to generalize their findings to broader populations, increasing external validity.
Findings represent the population : The use of statistical tools ensures that the results accurately reflect the population’s characteristics, adding credibility to the conclusions.
Studies can be replicated over time : The standardized nature of quantitative methods allows for replication, making it easier to verify and validate findings in subsequent studies.
Time-efficient : Data collection and analysis in quantitative research are often more structured and time-efficient, making it suitable for large-scale studies.
Provides snapshots of phenomena : Quantitative research captures data at a specific point in time, offering clear and concise summaries of trends or relationships.

Disadvantages of Quantitative Methods:

Lacks dynamic analysis : Quantitative research often provides a static view of phenomena, capturing data at one point in time, making it difficult to observe changes or processes over time.
Limited insights into individual feelings and actions : Quantitative data often lacks the depth to explore the motivations and emotions behind human behavior, which qualitative research provides.
Time-consuming sampling processes : Ensuring a representative sample in quantitative research can be resource-intensive, requiring careful planning and execution.
Limited in detailed explanations : While quantitative methods provide clear statistical findings, they may not fully explain complex phenomena or answer “why” and “how” questions.

Type of Research	Advantages	Disadvantages
	Qualitative methods allow researchers to delve deeply into the nuances of phenomena. They provide rich descriptions and insights.	Qualitative research may sometimes prioritize individual experiences and meanings over broader contextual factors.
	Qualitative methods offer flexibility in exploring complex phenomena, accommodating participants’ diverse perspectives.	Qualitative research often relies on interpretative approaches, which may introduce subjectivity into the analysis.
	Qualitative methods can capture the historical context of experiences. This allows for a deeper understanding of their evolution over time.	In fields like policy making, qualitative research findings may be perceived as less credible. They are often compared to quantitative data.
	Qualitative researchers can interact with participants during data collection, fostering a deeper understanding of their perspectives.	Findings may not apply to larger populations. This is due to the small sample sizes typically used in qualitative research.
	Quantitative studies often use standardized methods. This makes sharing and replicating research findings across different contexts easier.	Analyzing qualitative data can be time-consuming and challenging due to the subjective nature of the data.
	Quantitative research allows for the generalization of findings to the broader population. This enhances the study’s external validity.	Quantitative methods may overlook the deeper motivations and emotions underlying individuals’ behavior.
	With large sample sizes, quantitative research ensures accuracy in representing the population. This study reflects the population’s characteristics.	Obtaining a representative sample in quantitative research can be time-intensive and resource-demanding.
	lack the depth needed to explain complex phenomena.	Quantitative methods may provide statistical summaries but lack the depth needed to explain complex phenomena.
	Standardized methods in quantitative research facilitate replication studies. This allows for the validation of findings across different time periods.	Quantitative data collection and analysis processes are often more efficient. This efficiency makes them suitable for large-scale studies.
	Quantitative data collection and analysis processes are often more efficient. This efficiency makes them suitable for large-scale studies. Compared to qualitative methods, they are more efficient.	Quantitative research often provides a snapshot view of phenomena at a specific point in time. It limits its ability to capture dynamic processes.

Both qualitative and quantitative research methods play crucial roles in the world of research. Qualitative methods excel in providing deep, contextual insights, while quantitative methods offer generalizability and efficiency. The choice between these methods depends on the research objectives and the nature of the question being investigated. A mixed-methods approach, which combines both, can provide the best of both worlds—combining depth and breadth to answer complex questions comprehensively.

Forensic Analyst by Profession. With Simplyforensic.com striving to provide a one-stop-all-in-one platform with accessible, reliable, and media-rich content related to forensic science. Education background in B.Sc.Biotechnology and Master of Science in forensic science.

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Preventing trauma and grief in emergency and critical care units: a mixed methods study on a psycho-educational defusing intervention.

1. Introduction

2. materials and methods, 2.1. psycho-educational-defusing training, 2.2. evaluating the intervention: mixed methods, 2.3. participants and procedure, 2.4. instruments, 2.5. analytical strategy, 2.6. ethical considerations, 3.1. retrospective: quantitative, 3.2. retrospective: qualitative, 3.3. prospective: quantitative, 4. discussion, 4.1. limitations and future research, 4.2. practical implications, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

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Tommasi, F.; Tommasi, P.; Panato, M.; Cordioli, D.; Sartori, R. Preventing Trauma and Grief in Emergency and Critical Care Units: A Mixed Methods Study on a Psycho-Educational Defusing Intervention. Healthcare 2024 , 12 , 1800. https://doi.org/10.3390/healthcare12171800

Tommasi F, Tommasi P, Panato M, Cordioli D, Sartori R. Preventing Trauma and Grief in Emergency and Critical Care Units: A Mixed Methods Study on a Psycho-Educational Defusing Intervention. Healthcare . 2024; 12(17):1800. https://doi.org/10.3390/healthcare12171800

Tommasi, Francesco, Paolo Tommasi, Marco Panato, Davide Cordioli, and Riccardo Sartori. 2024. "Preventing Trauma and Grief in Emergency and Critical Care Units: A Mixed Methods Study on a Psycho-Educational Defusing Intervention" Healthcare 12, no. 17: 1800. https://doi.org/10.3390/healthcare12171800

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Qualitative and quantitative research methodologies (qqrm) - online certificate course.

Research is a core area in development and humanitarian programming. Some of the research activities normally undertaken by various programs to promote evidence-based planning include assessments, surveys and evaluations. These activities employ qualitative and quantitative research methodologies. Qualitative research aims at generating an in-depth understanding of a specific program activity or event, rather than surface description of a large sample of a population. On the other hand, quantitative research focuses on gathering, analyzing and presenting numerical data and generalizing it across groups of people to explain a particular phenomenon.

Given the great significance of research in development and humanitarian work, IDEAL Public Health and Development Consultancy (IPHDC) has planned a training on Qualitative and Quantitative Research Methodologies (QQRM) . The training aims at equipping participants with current knowledge, skills and best practices on research to improve the quality of their overall programming.

When is the training?

30th September to 4th October 2024

Who should attend this training?

UN, Government and NGO staff including but not limited to program coordinators, project managers and officers.

What are the key aspects of the training?

Introduction to Qualitative and Quantitative Research Methodologies (QQRM);
Hypothesis setting;
Research study design including sampling methods;
Questionnaire development;
Interviewing techniques;
Observation techniques and tools;
Participatory research techniques;
Focus group discussion (FGD) techniques and tools;
Key informant interview (KII) techniques and tools;
Note-taking and coding;
Qualitative and quantitative data analysis (Using SPSS, Nvivo and Ms Excel);
Presentation of findings.

What is the main training objective?

This course aims at building the knowledge and competencies of participants on qualitative and quantitative research methodologies.

What learning approach and language will be used in the training?

The training delivery method includes interactive webinar sessions, PowerPoint presentations, articles, videos, quizzes and assessments.

The entire training will be facilitated in English.

Fee information

How to register.

Interested individuals should complete our Course Application Form before Sunday 29th September 2024.

For more information on our courses you can visit our training page .

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Relationship between quantitative, qualitative and mixed-methods
Mixing Methods: Qualitative and Quantitative Research: : 9781859721162
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Qualitative V/S Quantitative Research Method: Which One Is Better?
Mixing Methods Qualitative and Quantitative Research, First Edition
Qualitative vs. Quantitative vs. Mixed Methods in UX Research

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research methodology (quantitative, qualitative, mixed methods)
Differences between QUALITATIVE & QUANTITATIVE Research Methods
Unit 0 Part 4 Types of Research Methods
Quantitative, Qualitative, and Mixed Methods Research: What's the difference?
Exploring Qualitative and Quantitative Research Methods and why you should use them
Exploring Mixed Methods Research Designs: Types and Applications

COMMENTS

Mixing Methods: Qualitative and Quantitative Research
The extent to which qualitative and quantitative research differ from one another has long been a subject of debate. Although many methodologists have concluded that the two approaches are not mutually exclusive, there are few books on either the theory or the practice of mixing methods. Mixing Methods: Qualitative and Quantitative Research ...
Combining qualitative and quantitative research within mixed method
Combining qualitative and quantitative research within ...
(PDF) Mixing quantitative and qualitative research
ChapterPDF Available. Mixing quantitative and qualitative research. November 2015. In book: Handbook of Innovative Qualitative Research Methods: Pathways to Cool Ideas and Interesting Papers ...
3.5 Quantitative, Qualitative, & Mixed Methods Research Approaches
3.5 Quantitative, Qualitative, & Mixed Methods Research ...
Mixed Methods Research
Mixed Methods Research | Definition, Guide & Examples
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 ...
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 ...
Three techniques for integrating data in mixed methods studies
Health researchers are increasingly using designs that combine qualitative and quantitative methods, and this is often called mixed methods research.1 Integration—the interaction or conversation between the qualitative and quantitative components of a study—is an important aspect of mixed methods research, and, indeed, is essential to some definitions.2 Recent empirical studies of mixed ...
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.
How to … do mixed‐methods research
How to … do mixed‐methods research - PMC
(PDF) Mixing Methods: The Entry of Qualitative and Quantitative
The study used a mixed method of qualitative and quantitative data collection and analysis. 5 point-likert scale questionnaire was used for field survey in addition to semi structured interviews ...
Mixing Methods: The Entry of Qualitative and Quantitative Approaches
The Case for Separation and the Case for Convergence. The case for separate paradigms is that qualitative and quantitative researchers hold different epistemological assumptions, belong to different research cultures and have different researcher biographies that work against convergence (Brannen, Citation 1992).Indeed qualitative researchers are embracing even greater reflexivity, for example ...
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.
Qualitative, quantitative, or mixed methods? A quick guide to ...
Qualitative, quantitative, or mixed methods? A quick guide to ...
Mixing Methods : Qualitative and Quantitative Research
This book focuses on the key issue in the theory and methodology of the social and behavioural sciences: the mixing of different research methods within a single piece of research. Despite the long debate about the different philosophical traditions which are said to underlie quantitative and qualitative research, there are few books on either the theory or the practice of combining different ...
The Growing Importance of Mixed-Methods Research in Health
The Growing Importance of Mixed-Methods Research in ...
Combining qualitative and quantitative research within mixed method
Objectives: It has been argued that mixed methods research can be useful in nursing and health science because of the complexity of the phenomena studied. However, the integration of qualitative and quantitative approaches continues to be one of much debate and there is a need for a rigorous framework for designing and interpreting mixed methods research.
Mixing Methods : Qualitative and Quantitative Research
This book focuses on a key issue in the methodology of the social and behavioural sciences: the mixing of different research methods. The extent to which qualitative and quantitative research differ from one another has long been a subject of debate. Although many methodologists have concluded that the two approaches are not mutually exclusive, there are few books on either the theory or the ...
Mixing Methods: Qualitative and Quantitative Research
This book focuses on a key issue in the methodology of the social and behavioural sciences: the mixing of different research methods. The extent to which qualitative and quantitative research differ from one another has long been a subject of debate. Although many methodologists have concluded that the two approaches are not mutually exclusive, there are few books on either the theory or the ...
PDF Chapter 2: Quantitative, Qualitative, and Mixed Research
This chapter is our introduction to the three major research methodology paradigms. A paradigm is a perspective based on a set of assumptions, concepts, and values that are held and practiced by a community of researchers. For the most of the 20th century the quantitative paradigm was dominant. During the 1980s, the qualitative paradigm came of ...
The Fundamental Difference Between Qualitative and Quantitative Data in
Mixed methods research is commonly defined as the combination and integration of qualitative and quantitative data. However, defining these two data types has proven difficult. In this article, I argue that qualitative and quantitative data are fundamentally different, and this difference is not about words and numbers but about condensation ...
Mixing Quantitative and Qualitative Research
Abstract. This chapter offers several models of ways that scholars can usefully integrate qualitative and quantitative research in both single works and broader research programs: using qualitative methods to identify constructs or hypotheses that can subsequently be examined in quantitative studies; using quantitative studies to identify patterns that can be explored in qualitative work; and ...
Balancing Qualitative and Quantitative Research Methods: Insights and
An examination of the research methods and research designs employed suggests that on the quantitative side structured interview and questionnaire research within a cross-sectional design tends to ...
Facilitators and barriers to policy implementation: A mixed-method
Following this, the quantitative online survey solely examines the practice-level perspective of policy implementation. The mixed-method study's findings are ultimately presented using a triangulation approach to combine the results from the qualitative and quantitative perspectives and address the research questions in a holistic matter.
Mixed-methods protocol for the WiSSPr study: Women in Sex work, Stigma
Strengths of this study include (1) a mixed-methods approach which grounds quantitative research in the lived experiences of people and measures aspects of stigma that emerge at the intersections of identities, (2) qualitative data from peer navigators capturing perspectives of women at the unique interface of being recipients of care as sex ...
Journal Article Reporting Standards (JARS)
Mixed methods research (Jars -Mixed) Additionally, the APA Style Journal Article Reporting Standards for Race, Ethnicity, and Culture (Jars - Rec) provide guidance on how to discuss race, ethnicity, and culture in scientific manuscripts. Jars - Rec should be applied to all research, whether it is quantitative, qualitative, or mixed methods.
Advantages and Disadvantages of Qualitative and Quantitative Research
Type of Research Advantages Disadvantages; Qualitative: Provides detailed and in-depth information: Qualitative methods allow researchers to delve deeply into the nuances of phenomena. They provide rich descriptions and insights. Lack of focus on contextual sensitivities: Qualitative research may sometimes prioritize individual experiences and meanings over broader contextual factors.
Healthcare
Our mixed methods projects are theoretically driven by a deductive approach. As depicted in Figure 1, the first and the second study where represent the retrospective chart, i.e., the psychological status of the staff. In this, quantitative and qualitative data were collected concurrently but analyzed independently.
Implementing a treatment for people with serious mental illness in jail
As part of a larger implementation-effectiveness hybrid study, we gathered mixed-methods data from stakeholders (treatment recipients and jail administrators) on the feasibility and acceptability of the intervention's implementation. ... We found qualitative and quantitative support for the use of this intervention in jail from both sets of ...
Qualitative and Quantitative Research Methodologies (QQRM)
These activities employ qualitative and quantitative research methodologies. Qualitative research aims at generating an in-depth understanding of a specific program activity or event, rather than ...

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TABLE OF CONTENTS

3.5 Quantitative, Qualitative, & Mixed Methods Research Approaches

Quantitative Research Approaches

Qualitative Research Approaches

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Introduction: Considering Qualitative, Quantitative and Mixed Methods Research

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An Introduction to Qualitative and Mixed Methods Study Designs in Health Research

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The Growing Importance of Mixed-Methods Research in Health

Padam Simkhada

Edwin R. van Teijlingen

Indrajit Banerjee

Underpinning philosophies

The relevance of mixed-methods in health research

Strengths and weaknesses of mixed-methods

Common mistakes in applying mixed-methods

The way forward

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Combining qualitative and quantitative research within mixed method research designs: a methodological review

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