Mixed methods research design is a kind of research methodology for conducting research that involves collecting, analyzing and integrating quantitative and qualitative data’s. This type of methodology is adopted for better understanding of the research phenomena when either of each alone can’t help. The main advantageous of conducting mixed methods research is the possibility of triangulation, i.e., the use of several methods, data sources and researchers to examine the same phenomenon [1].

• Quantitative data: these are close-ended information such as that found to measure knowledge (e.g. multiple choice questions), attitudes (e.g., rating scales), practice (e.g., observation checklists), and performance instruments. This data required statistical analysis to interpret the phenomena and to test the
• Qualitative data: these are of open-ended information that the researcher usually gathers through interviews, focus groups and observations. The analysis of these date will be

  in descriptive form by following the path of aggregating the information into categories and presenting diversity of ideas.

• It can be based on either or both
• Research problems can become research questions and/or hypotheses based on prior literature, knowledge, experience, or the research
• Sample sizes may vary based on methods used to investigate.
• Data collection method can involve any technique available to
• Interpretation is continual and it can influence stages in the research

• To validate or corroborate the results obtained from other methods(qualitative research + quantitative research)
• To use one method to inform another method (qualitative research qualitative research)
• To nonstop look at a research question from different angles, and clarify unexpected findings and/or potential contradictions. (qualitative research qualitative research)
• To elaborate, clarify, or build on findings from other methods (qualitative research qualitative research)
• To develop a theory(through qualitative research) about a phenomenon of interest and then test it (through quantitative research)
• To generalize findings from qualitative research. (qualitative research à quantitative research)

• To explain and
• To explore a
• To develop and test a new
• To serve a theoretical
• To complement the strengths and to overcome the weaknesses of a single
• To address a research question at different
• To address a theoretical perspectives of phenomena at different

Deciding the type of mixed method research design is  depends up on over all purpose of the study, research question and strength and weakness of the each design. Figure 1 show 4 major

 types of mixed method research design and table-1 narrates the each design with strength and weaknesses [2].

Figure 1: Types of mixed method research designs.

The following six questions are a useful guide when reading mixed methods research or writing a proposal using mixed methods to answer a research question,

• Does the research question justify the purpose of mixed methods?
• Whether the sequence of method is clearly described, logical in flow and well aligned with study aims?
• Whether the data collection and analysis clearly described and well aligned with study objectives?
• Whether one method dominates the other method or is they equally important?
• Did the use of one method limits or confound the other method?
• When, how and by whom the mixing of data can be achieved?
  

  Table 1: Types, purposes, examples, strength and weaknesses of mixed method research designs.

  Types of MMRD	Purpose	Examples	Strengths	Weaknesses
  Quantitatively                driven approaches/design: in this design the quantitative data is first collected and analyzed followed by the qualitative date is collected and analyzed. The first concern is given to the quantitative data, and the findings are integrated for interpretation.	· To explain, interpret or contextualize quantitative findings. · To                examine unexpected results from a quantitative study in detail.	· The researcher collects data about attitude of nursing students towards chosen profession using a structured questionnaire (survery) and follows up with interviews with a few students who participated in the survey to learn in in detail about their survey responses (e.g. to understand the thought process and perceptions).	· Easy                   to implement stages. · The design is easy to describe · The results easy to report.	· Data collection required more time as it requires two separate phases it is time consuming process.
  Qualitatively                 driven approaches/design: in this design the qualitative data is first collected and analyzed followed by the quantitative date is collected and analyzed. The first concern is given  to  the  qualitative part	· To explore and expand phenomena on             qualitative findings. · To test components of an emergent theory that results	· The researcher explores nursing officer’s attitude regarding chosen profession by starting with interviews and then uses an analysis of the information to develop a survey instrument that is	· Easy                   to implement as the steps are clear and separate · The design is easy to describe · The results easy	· Data collection required more time as it requires two separate phases it is time consuming process. · Some time it is difficult to build subsequent data collection from the
  of the study and the findings are           integrated            for interpretation [3]	from the qualitative research. · To             generalize qualitative findings to different samples · To develop and test a new instruments	administered      later     to     a sample from a population.	to report.	qualitative analysis
  Interactive or equal status designs or concurrent triangulation: Usually, equal priority is given to both  types of research [4] and it involves only one data collection phase were during which quantitative and qualitative data collection and analysis are conducted separately but concurrently. and the findings are integrated for interpretation   Triangulation means using more than one method to  collect data on the same phenomina [5].	· To have a complete understanding of a phenomenon. · To corroborate or cross-validate the findings.	· The researcher uses a survey to assess people’s life style practices and also observes those practices in their natural environment. By comparing the two types of data, the researcher can see if there is a match between what people think they are doing and what they are actually doing in terms of such phenomenon.	·         It provides well-validated findings. ·         It provides substantiated findings. ·         Data collection takes less time.	· Need more effort · Need expertise to adequately use two separate methods at the same time. · Need two types  of analysis (i.e.inferential and descriptive) · Difficult to compare the results analysis using data of different forms. · No clear way to solve the discrepancies that arise while comparing the results. · Results of one method (e.g. Survey) cannot be integrated    in    the  other method (e.g.interview).
  Mixed priority designs: · This type of design only one data collection phase is used, during which a predominant method (quantitative or qualitative) nests or embeds the other less priority method (qualitative or quantitative, respectively). The data collected from the two methods are mixed during the analysis phase of the study [6].	· To obtain in-depth perspectives on a topic. · To balance possible weaknesses inherent to the predominant method. · Nesting mean that the                  embedded method addresses a different question than the dominant method or seeks information from different levels.	· The investigator collects data to assess participant knowledge and risk perceptions about diabetes mellitus by using a survey instrument that mixes qualitative (open-ended) and quantitative (closed-ended) questions, and both forms of data are integrated and analyzed.	· Reduces time and resources     as     2 data        collection done simultaneously. · Study          results from               both quantitative and qualitative     data	· Integrating the data during analysis may be difficult as the data needs to be transformed in some way. · Inequality              between different methods may result in unequal evidence within the study that can interfere with interpreting the results.

  Table 2: Morse and Niehaus (2009) listed eight mixed methods and multi method research designs [7].(2009) listed eight mixed methods and multi method research designs [7].

  Types	Mixed method research design		Multi method research design
  	Inductive	Deductive	Inductive	Deductive
  Simultaneous	QUAL+quan (here the core component is qualitative and the supplemental component is quantitative)	QUAN+qual (here, the core component is quantitative and the supplemental component is qualitative)	QUAL +qual (where both components are qualitative; this is a multimethod design rather than a mixed methods design)	QUAN +quan (here both components are quantitative; this is a multimethod design rather than a mixed methods design
  Sequential	QUALàquan (here the core component is qualitative and the supplemental component is quantitative)	QUANàqual (here the core component is quantitative and the supplemental component is qualitative)	QUAL →qual              (both components are qualitative; this is a multimethod design rather than a mixed methods design)	QUAN →quan               (both components are quantitative; this is a multimethod design rather than a mixed methods design).

  Table 3: Strength and Weaknesses of Mixed Method Research Designs [9-10].

   

  Strengths	Weaknesses
  ·         It balances the weaknesses of both quantitative and qualitative research. (For example when quantitative research design is weak in understanding the very context phenomena like human behavior, the qualitative	·         MMRD is very complex research design. ·         More time consuming ·         More resource consuming ·         It will be difficult to plan and implement one
  research design will makes up for understanding. ·         The strengths of each approach can compensate for the weaknesses of the other. ·         Gives a complete and comprehensive understanding of the research problem than either quantitative or qualitative approaches alone. ·         Provides an approach for developing more context specific instruments. ·         Helps to explain findings or on how causal processes work.	method by drawing on the findings of another. ·         It will be unclear on how to handle discrepancies that occurs in  the interpretation of the findings. ·         Some designs generate unequal evidence. ·         It is difficult to decide when to proceed in sequential designs. ·         Little guidance available on transformative methods.

The integration of quantitative and qualitative data in the form of a mixed methods study has great potential to strengthen the rigor and enrich the analysis and findings. By carefully selecting the mixed method design that best suits the study question, purpose of the study will facilitate deep and more meaningful information of the phenomena of interest.

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