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Mixed methods research MMR has found an increased interest in the field of health outcomes research. Consideration for both qualitative and quantitative perspectives has become key to contextualising patient experiences in a clinically meaningful measurement framework. The purpose of this paper is to outline a process for incorporating MMR in health outcomes research to guide stakeholders in their understanding of the essence of mixed methods inquiry. In addition, this paper will outline the benefits and challenges of MMR and describe the types of support needed for designing and conducting robust MMR measurement studies.
MMR involves the application of a well-defined and pre-specified research design that articulates purposely and prospectively, qualitative and quantitative components to generate an integrated set of evidence addressing a single research question.
Various methodological design options are possible depending on the research question. MMR designs allow a research question to be studied thoroughly from different perspectives. When applied, it allows the strengths of one approach to complement the restrictions of another. Among other applications, MMR can be used to enhance the creation of conceptual models and development of new instruments, to interpret the meaningfulness of outcomes in a clinical study from the patient perspective, and inform health care policy.
Robust MMR requires research teams with experience in both qualitative and quantitative research. Moreover, a thorough understanding of the underlying principles of MMR is recommended at the point of study conception all the way through to implementation and knowledge dissemination. The framework outlined in this paper is designed to encourage health outcomes researchers to apply MMR to their research and to facilitate innovative, patient-centred methodological solutions to address the complex challenges of the field.
This highlights a clear application for MMR to combining qualitative and quantitative methods in health research to ensure a focus on patient-identified priorities, scientific rigour, and improved patient outcomes. In this issue, MMR was described as an approach to inform the content validity of PROs within the early development phase. With this position paper, we aim to provide a framework for MMR in health outcomes by outlining the characteristics of this methodology, what can be expected and where caution should be exercised.
In this framework, not only should both qualitative and quantitative strands be used by the researcher, but they should be complemented in a relevant research design that is set a priori. They may address distinct, specific research questions but they contribute to the same overall end purpose of the MMR.
Once the overall purpose, and the specific research questions of the qualitative and quantitative strands, are well-defined and procedures are outlined, a clear plan for interaction between the qualitative and quantitative research components is needed.
This point relates to the notion of meta-inference that requires qualitative and quantitative evidence not be considered independently, but interpreted together as a single body of evidence [ 3 ]. Importantly, the importance of the specification relates to the research design, and especially the articulation of the qualitative and quantitative strands, but it obviously does not necessary apply within the research strands, as, in many instances, in particular for qualitative research, a full prespecification may not be appropriate, the research being of exploratory nature.
The characterization of MMR is driven neither by the data collection process, nor by the analysis technique. In MMR, it is not necessary that the qualitative and quantitative streams involve data collected with the same respondents.
A well-designed MMR study may combine qualitative and quantitative data from different samples of individuals to address a single research question, combining rigorous qualitative and quantitative evidence.
Conversely, the collection of qualitative and quantitative data for the same individuals does not necessarily allow for a proper MMR solution as it may be done to address different research questions or without considering both data sets in an integrated approach. Many options are available to the health outcomes researcher looking to utilize MMR, depending on the research question and design. We assert that MMR should not be restricted to any specific research design or methodology, but rather the design that is best suited to answer the research question posed.
The articulation of the qualitative and quantitative elements can be performed in various designs that are well described in the methodological literature e. The choice of the appropriate design and analysis technique qualitative and quantitative remains the responsibility of the researcher who should be guided by the principles outlined above.
MMR allows a research question to be studied from different perspectives. For example, one can combine the rich, subjective insights on complex realities from qualitative inquiry, with the standardized, generalizable data generated through quantitative research. When applied, MMR allows respective strengths and weaknesses of each approach to complement each other.
Since its conception in , the Mixed Methods SIG of ISOQOL has identified and discussed many different applications of MMR in the health outcomes field: exploration of patient experiences to support the development of conceptual models with group concept mapping [ 9 — 11 ]; development of new clinical outcome assessment instruments with integrated qualitative and early quantitative analyses with Rasch model [ 12 — 15 ]; quantitatization of qualitative data to support conceptual saturation analyses [ 16 , 17 ]; use of qualitative information to support the interpretation of quantitative patient-reported outcomes results [ 18 , 19 ], to name but a few.
These examples show that MMR can help us to address common questions in the health outcomes field. This is typified by the inductive and iterative process characteristic of the development of new PROs. It also allows for flexibility and the ability to make the most of small samples. MMR enables a pragmatic path forward to conduct health outcomes measurement research in rare disease populations [ 20 ] or populations that are often difficult to recruit for research purposes e.
In a clinical research context, the versatility of MMR makes it a method of choice for hypothesis generation on PRO endpoints, especially in phase II trials.
Finally, a critical strength of MMR approaches is that they typically capitalize on data reflecting individual lived experiences in the qualitative strand. This ensures that the results are considered from the patient-perspective. Incorporating the patient voice in MMR helps ensure that the research is focused on the needs and priorities of patients.
In this context, it appears clearly that MMR is a strong option to leverage effective patient engagement and support ongoing research focused on patient-identified priorities and the improvement of patient outcomes [ 21 ]. Despite some clear benefits, the application of MMR in the health outcomes research does not come without challenges. One major hurdle is that MMR is demanding in terms of methodological skillsets.
MMR requires a team of researchers who are experienced in both qualitative and quantitative research, and in MMR designs. Indeed, as with traditional qualitative or quantitative methodologies, best practices should be applied rigorously across the multiple methods, but also in the way the quantitative and qualitative strands are articulated.
A particularly critical issue in this context is that of meta-inference, in which the qualitative and quantitative strands connect. Meta-inference should be carefully specified, and researchers should be aware of the challenges of interpreting conflicting results.
The application of MMR can also raise practical considerations, particularly as the integration of both qualitative and quantitative data can require additional resources and time.
However, it should be noted that this additional burden can often be offset against the potential benefits of MMR, particularly where multiple insights support the investigation of complex research questions or small populations. Such challenges stem from differences in the underlying ontological and epistemological positions of positivism that a single objective reality exists and constructivism that reality is a subjective construct and therefore multiple realities exist.
Even though the MMR paradigm goes beyond simply mixing the quantitative and qualitative paradigms and builds a third path, some purists continue to question this third paradigm, considering the very nature of the qualitative and quantitative paradigms irreconcilable. However, as Maxwell and Mittapalli argue [ 22 ], there is an alternative position to positivism and constructivism — critical realism. Critical realists deny that we have any objective or certain knowledge of the world, and accept the possibility of alternative valid accounts of any phenomenon.
They argue that all theories about the world are grounded in a particular perspective and worldview, and all knowledge is partial, incomplete, and fallible. As such, critical realism provides a philosophical stance that is compatible with MMR in that it acknowledges the methodological characteristics of both qualitative and quantitative research, and can facilitate communication and cooperation between the two.
Against the background of this ongoing debate, it is clear from the growing literature that the acceptance of MMR is increasing as the health outcomes research community continues to promote and celebrate methodological diversity.
Two conditions appear critical for the continued development of credible and robust MMR. First, health outcomes researchers have the potential to learn about the different MMR methodologies and outline how MMR can be used to more thoroughly answer health outcomes research questions.
This may include increasing knowledge about the underlying philosophy and history of MMR, examples of MMR research designs and principles, and the pros and cons of this approach above a purely qualitative or quantitative inquiry. To support this journey we provide a list of recommended texts which can form a starting point for the curious researcher. Second, an open dialogue and collaboration between health outcome researchers with positivist or interpretivist leanings should be encouraged to prepare the ground for robust MMR.
In this context, it will be possible to design health outcomes research studies in which the whole is greater than the sum of its parts and allow the research community to further the science through providing innovative solutions to our research challenges.
All reviewed and approved the final version. AR is an employee of Modus Outcomes. TW and SB declare that they have no conflict of interest. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. National Center for Biotechnology Information , U. J Patient Rep Outcomes.
Published online Apr Tom Willgoss 2 Roche Products Ltd. Author information Article notes Copyright and License information Disclaimer. Corresponding author. Received Dec 8; Accepted Apr 3. This article has been cited by other articles in PMC. Abstract Mixed methods research MMR has found an increased interest in the field of health outcomes research.
Table 1 Defining features of the mixed methods research framework. The quantitative and qualitative components are articulated purposely and prospectively in a well-defined, pre-specified research design 3. The response to the research questions is supported by an integrated set of evidence generated from both the qualitative and quantitative component of the research meta-inference. Open in a separate window. Benefits and challenges of mixed methods research Benefits MMR allows a research question to be studied from different perspectives.
Challenges Despite some clear benefits, the application of MMR in the health outcomes research does not come without challenges. Conclusions and recommended reading Two conditions appear critical for the continued development of credible and robust MMR. Notes Ethics approval and consent to participate NA. Competing interests AR is an employee of Modus Outcomes.
Denzin Norman K. Moments, Mixed Methods, and Paradigm Dialogs. Qualitative Inquiry. Conducting mixed methods research. Tashakkori A, Teddlie C. Handbook of mixed Methods in social behavioral research. Teddlie C, Tashakkori A. Foundations of mixed methods research. Patient involvement in the development of patient-reported outcome measures: A scoping review. Health Expect. The new era of mixed methods. Journal of Mixed Methods Research. The use of concept mapping in measurement development and evaluation: Application and future directions.
Eval Program Plann. Willgoss T.
Mixed methods research MMR has found an increased interest in the field of health outcomes research. Consideration for both qualitative and quantitative perspectives has become key to contextualising patient experiences in a clinically meaningful measurement framework. The purpose of this paper is to outline a process for incorporating MMR in health outcomes research to guide stakeholders in their understanding of the essence of mixed methods inquiry. In addition, this paper will outline the benefits and challenges of MMR and describe the types of support needed for designing and conducting robust MMR measurement studies. MMR involves the application of a well-defined and pre-specified research design that articulates purposely and prospectively, qualitative and quantitative components to generate an integrated set of evidence addressing a single research question.
Mixed methods. When to use mixed methods. The benefits of using a mixed methods approach--quantitative with qualitative--to identify client satisfaction and unmet needs in an HIV healthcare centre. AIDS Care 22 4 : Tags: public health qualitative methods research research design.
Qualitative and quantitative are widely used research methods that act as powerful sources of insight for marketers. Generally speaking, qualitative research explores what people think, feel and do while quantitative gives a measure of how many people think, feel or behave in a certain way. One is typically based on the opinions and thoughts of a small sample; the other is normally based on the reported behaviours of a much larger and representative sample.
Quantitative approaches to research include hard numbers and provable results, such as experiments and surveys. Qualitative research is more subjective, often including observation and interpretation of data via ethnography and personal interviews. Recent approaches to research design include using both qualitative and quantitative research -- a mixed-methodology research design.
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Jump to main content. Download PDF Version. This brief focuses on using mixed methods to evaluate patient-centered medical home PCMH models. The series is designed to expand the toolbox of methods used to evaluate and refine PCMH models.
The purpose of this paper is first, to discuss the theoretical assumptions, qualities, problems and myopia of the dominating quantitative and qualitative approaches; second, to describe the methodological lessons that the authors learned while conducting a series of longitudinal studies on the use and usefulness of a specialized balanced scorecard; and third, to encourage researchers to actually use multiple methods and sources of data to address the very many accounting phenomena that are not fully understood. This paper is an opinion piece based on the authors' experience conducting a series of longitudinal mixed method studies. The authors suggest that in many studies, using a mixed method approach provides the best opportunity for addressing research questions. This paper provides encouragement to those who may wish to bridge the authors' ideological gaps and to those who are actively trying to do so. Malina, M. Emerald Group Publishing Limited. Report bugs here.
The aim of this article is to acquaint the beginner researchers with the pros and cons of mixed methods research which has an immense.
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