How to Design a Mixed Methods Study by John W. Creswell, Ph.D. and Vicki L. Plano Clark, M.S. University of Nebraska-Lincoln Andrews University, July, 2004

How would you combine two types of data? Qualitative Text Data This is a sample of a text file of words that might be collected on transcripts through interviews, fieldnotes from observations, or from optically-scanned documents. Quantitative Numeric Data 2342543112232132 23322543 3122432432132433 32334441 2222111432143213 22111555 2331432432132433 32135432

Objectives of the workshop: Let’s design a mixed methods study Let’s study how people learn mixed methods research in this room? (or you can work on your own project and follow along at each step) Let’s start with a title. Write a title. What data will we collect?

What are types of quantitative and qualitative data? Quantitative data Close-ended scales Attitudinal/behavioral scales Behavioral checklists Census, attendance records Qualitative data Open-ended responses Semi-structured interviews Semi-structured observations Records/documents Videotapes

Let’s identify our quantitative and qualitative data collection

Now let’s consider some reasons for why we are collecting (and mixing) both forms of data Together quantitative and qualitative data provide both precise measurement and generalizability of quantitative research and the in-depth, complex picture of qualitative research To validate quantitative results with qualitative data We do not have an adequate instrument. Thus, we need to explore views and develop an instrument Our quantitative data provide a general explanation and we need to follow-up with participants and have them explain the quantitative results In our experiment, outcomes to be measured are not enough; they need to be complemented by understanding the process of participants

Let’s identify our reason for mixing

So… There are good reasons for gathering both forms of data But…there are certain requirements for this to work best

Requirement #1: Now let’s consider whether we have the skills, time, and resources? We need minimum skills in both qualitative and quantitative data collection. What do we need? We need time and resources for extensive data collection and analysis. How much time and resources do we need?

Write down the skills, time, and resources we will need

Requirement #2: The audience(s) Does our audience appreciate both numbers and stories? Are they familiar with this design? Do they need to be educated? Are examples of published studies available in our content area?

Let’s identify the audiences

But audiences may not recognize it yet because it is so new Increased use and acceptance of qualitative research from 1990’s to present The complexity of our research problems today requires understanding trends, differences, as well as individual stories, setting Individuals advocating for and writing about mixed methods research as a distinct, new procedure (e.g., books)

They may think that it is analyzing data separately Quantitative Data Qualitative Data Mixing: converging the data or connecting the data

But how do we mix? Converge data: Connect data: Qual Results Quan Qual

Why our audience may recognize it The evidence Books Methodological articles Many published research studies using it Federal agencies Private foundations

Other writings, initiatives on mixed methods research: Research studies reported in journals Methodological articles exploring issues and procedures Website for bringing mixed methods writers together Conference sessions Handbook of Mixed Methods in Social and Behavioral Research Private foundation interest; federal agency interest

NIH Guidelines - Mentioned several approaches for combining qualitative and quantitative research - Considerations for deciding what model to use (literature available, prior studies, realistic design, expertise) - Need to describe each method thoroughly

Quotes: “Combining qualitative and quantitative methods has gained broad appeal in public health research. The key question has become not whether it is acceptable or legitimate to combine methods, but rather how they will be combined to be mutually supportive and how findings achieved through different methods will be integrated.” (NIH, Office of Behavioral and Social Science Research, 1999).

National Academy of Sciences Three major research questions in quality educational research: What is happening? (qualitative designs) Is there a systematic effect? (a quantitative experiment) Why or how it is happening? (a qualitative followup)

But even if they recognize it, they may not appreciate or understand how to design a mixed methods study “We are interested in a randomized control trial with a non-experimental approach embedded within it.” (a private foundation officer) “We accept multi-method studies, but investigators mostly do not sort out the complexity of these projects so that we can understand them.” (a federal projects officer).

We need to define mixed methods research for our audiences Mixed methods research is a design for collecting, analyzing, and mixing both quantitative and qualitative data in a single study or series of studies to understand a research problem. The purpose of this form of research is that both qualitative and quantitative methods, in combination, provide a better understanding of a research problem or issue than either method alone.

Now we could mix within single studies or multiple studies Single Study: Quan Qual Results Multiple Studies (called multimethod research): Quan Qual Qual Quan Study 1 Study 2 Study 3 Study 4

So how do we design a mixed methods study? The model Worldviews, theoretical frameworks, problem and research question, skills, resources Type of mixed methods design Procedures for: designing the title writing the introduction to a study writing the purpose statement and research questions/hypotheses data collection data analysis writing the mixed methods report evaluating the mixed methods research

What is a worldview? Philosophy about your preferences for how you learn about something through research You prefer the quantitative worldview: you are the expert, you decide what needs to be learned, you build in objectivity You prefer the qualitative worldview: participant is the expert, participant helps you build knowledge, you bring personal bias in You prefer both the quantitative and qualitative worldview

The next steps in planning our study Let’s write the overall research question for our study

Then let’s choose a type of mixed methods study to conduct What designs are possible?

Types of mixed methods designs I. Triangulation Mixed Methods Design + QUAN Data and Results QUAL Data and Results Interpretation II. Nested Mixed Methods Design QUAN Pre-test Data and Results QUAN Post-test Data and Results Qual Process

Types of mixed methods designs III. Explanatory Mixed Methods Design qual Data and Results QUAN Data and Results Follow-up IV. Exploratory Mixed Methods Design QUAL Data and Results quan Data and Results Building

Triangulation Design: Characteristics Collecting both quantitative and qualitative data Collecting these data at the same time in the research procedure Analyzing the quantitative and qualitative data separately Comparing or combining the results of the quantitative and qualitative analysis Example: collect survey data (quantitative) and collect individual interviews (qualitative) and then compare the results

Triangulation Design: When is it used? When you want to combine the advantages of quantitative (trends, large numbers, generalization) with qualitative (detail, small numbers, in-depth) When you want to validate your quantitative findings with qualitative data When you want to expand your quantitative findings with some open-ended qualitative data (e.g., survey with closed- and open-ended data)

Nested Design: Characteristics Collecting both quantitative and qualitative data Collecting both types of data at the same time Having ONE form of data play a smaller role in the study than the other form of data Also, Using one form of data to answer one question; the other form another question Collecting one form of data at one level of analysis and another at another level of analysis Example: You conduct an experiment and during the experiment you gather qualitative interview data. The outcomes of the experiment assessed quantitatively address different questions than the process of the experiment explored qualitatively.

Nested Design: When is it used? When you do not have time or resources to commit to extensive quantitative and qualitative data collection When you want to study the process of an experiment as well as the outcomes When you want to examine different levels in an organization

and analysis of qualitative Nested Research Design Experiment Quan Data collection Pre-test Intervention Quan Data collection Post-test Process – collection and analysis of qualitative data

Explanatory Sequential Design: Characteristics Viewing the study as a two-phase project Collecting quantitative data first followed by collecting qualitative data second Typically, a greater emphasis is placed on the quantitative data in the study Example: You first conduct a survey and then follow up with a few individuals who answered positively to the questions through interviews

Explanatory Sequential Design: When do you use it? When you want to explain the quantitative results in more depth with qualitative data (e.g., statistical differences among groups, individuals who scored at extreme levels) When you want to identify appropriate participants to study in more depth qualitatively

Here is an example of an explanatory design: Quant itative Quantitative Case Selection Qualitative Interpretation – based on quan and QUAL results Data Collection (quan) Data Analysis (quan) Data Analysis (QUAL) + Qualitative Data Collection Quantitative Data* Quantitative Analysis Case Selection Qualitative Analysis Interpretation Selected 5 cases maximally varying Identified critical months in which smoking varied Number of cigarettes Graphic plot of CES - Descri ption of each Why did changes in CES - D6 D6 scores over time case smoking occur? for each participant Identification of life Qualitative Data* Graphic plot of events occurring Semi - structured cigarettes/day values during critical over time for each months where interviews, audio recorded and participant smoking increased or decreased transcribed Thematic analysis of life events for each * Data collected 10 times case over the course of a calendar year for 40 Cross - case thematic participants analysis Creswell et al. (in progress)

Exploratory Sequential Design: Characteristics Viewing the study as a two-phase project Qualitative data collection precedes quantitative data collection Typically, greater emphasis is placed on the qualitative data in the study Example: You collect qualitative diary entries, analyze the data for themes, and then develop an instrument based on the themes to measure attitudes on a quantitative survey administered to a large sample.

Exploratory Sequential Design: When do you use it? To develop an instrument when one is not available (first explore, then develop instrument) To develop a classification or typology for testing To identify the most important variables to study quantitatively when these variable are not known

Sequential Exploratory Mixed Methods Design Phase I Qualitative Research - Year 1 Unstructured Interviews - 50 participants 8 observations at the site 16 documents Qualitative Data Collection Qualitative Data Analysis Text Analysis: Using QSR N6 Development of codes and themes for each site Qualitative Findings Phase II Quantitative Research - Year 2 Create approximately a 80-item instrument plus demographics Quantitative Instrument Development Administer survey to 500 individuals Determine factor structure of items and conduct reliability analysis for scales Quantitative Test of the Instrument Quantitative Results Determine how groups differ using ANOVA test Sequential Exploratory Mixed Methods Design

How will we analyze the quantitative and qualitative data (within the design types)? Qualitative analysis Text/image data Coding Themes Description Interrelated themes Types of analysis: Quantitative analysis Numeric data Descriptive trend analysis Hypothesis testing, effect size, interval estimates

Triangulation data analysis QUAN data collection QUAL data collection Separate QUAN and QUAL data analysis QUAN data analysis QUAL data analysis Two options Data transformation (change QUAL to QUAN or QUAN to QUAL) Comparison (keep separate and compare/contrast) Results

Table. Example of Data Transformation of Text Units into Numeric Data Count Adj.Count** Row Pct Column Pct Patients N=2 Physicians N=4 Medical Assistants Themes Familiarity With the Form 13 6.5 41.9 5.8 17 4.25 27.4 3.0 19 4.75 30.7 5.3 49 15.5 100.0 Reactions to the Form 23 11.5 22.2 10.2 100 25.0 48.3 17.4 61 15.3 29.5 16.9 184 51.75 Use for Managing Depression 67 33.5 38.6 29.8 177 44.25 51.0 36 9.0 10.4 10.0 280 86.75 Changes to the Form 115 57.5 37.5 51.1 196 49.0 32.0 34.0 187 46.8 30.5 51.7 498 153.3 Situational Use of the Form 7 3.5 8.9 3.1 86 21.5 54.4 14.9 58 14.5 36.7 16.1 151 39.5 225 112.5 576 144.0 361 90.3

Nested data analysis Quantitative Experiment Intervention Quan Data collection Pre-test Quan Data collection Post-test Qualitative Process Data Analysis Pre-test scores Themes/Codes/ Interrelated Themes Post-test scores or gain scores Compare/Describe Results

Explanatory sequential data analysis Qual data collection (purposeful sampling) Select cases based on s.d. variables Select cases to represent outliers Select cases to represent extreme cases Select cases to make group comparisons QUAN data analysis Statistical results Outlier cases Extreme cases Qual analysis codes themes cases

Exploratory sequential data analysis QUAL data analysis Quotes Codes Themes Quan data analysis instrument development Items on a survey Variables on a survey Scales on a survey

Let’s identify how we will analyze the data

Drawing our Design Let’s draw a picture of our design Identify the type of design Add in data collection Add in data analysis Show the flow of activities Add in “products” for our audiences

Helpful tips for creating this visual: Give a title to the visual model. Choose either horizontal or vertical layout for the model. Draw boxes for quantitative and qualitative stages of data collection, data analysis and interpretation of the study results. Use capitalized (QUAN) or small letters (quan) to designate priority of quantitative and qualitative data collection and analysis. Use single-headed arrows to show the flow of procedures in the design. Specify procedures for each quantitative and qualitative data collection and analysis stage. Specify expected products or outcomes of each quantitative and qualitative data collection and analysis procedure. Make your model simple. Size your model to one page.

Now let’s rework our purpose statement using some scripts

Sample Script for a Concurrent Design (Triangulation or Nested) “The purpose of this concurrent mixed methods study is to better understand a research problem by converging both quantitative (numeric) and qualitative (text or image) data. In this approach, ___________ (quantitative instruments) will be used to measure the relationship between the ________ (independent variables) and __________ (dependent variables). At the same time in the study, the __________ (central phenomenon) will be explored using _____________ (qualitative interviews, documents, observations, visual materials) with _________ (participants) at ____________ (the research site).”

Sample Script for a Sequential Exploratory Design “The purpose of this two-phase, exploratory mixed methods study will be to explore participant views with the intent of using this information to develop and test an instrument with a sample from a population. The first phase will be a qualitative exploration of a _______(central phenomenon) by collecting ___________(data) from ____________ (participants) at _______ (research site). Themes from this qualitative data will then be developed into an instrument (or survey) so that the __________ (theory and research questions/hypotheses) can be tested that ________ (relate, compare) ____________ (independent variable) with __________ (dependent variable) for _________(sample of a population) at _________ (research site).”

Sample Script for a Sequential Explanatory Design “The purpose of this two-phase, explanatory mixed methods study will be to obtain statistical, quantitative results from a sample and then follow-up with a few individuals to probe or explore those results in more depth. In the first phase, quantitative research questions or hypotheses will address the relationship or comparison of __________ (independent) and ________ (dependent) variables with ___________ (participants) at ___________(the research site). In the second phase, qualitative interviews or observations will be used to problem significant _______(quantitative results) by exploring aspects of the ________ (central phenomenon) with _______ (a few participants) at ____________ (research site).”

Criteria for evaluating our plan: Use appropriate terminology for title and design Provide a rationale for mixing and include it early in the study (“when you use…”) Create a mixed methods purpose statement Identify types of qual and quan data to be collected and qual and quan data analysis steps Include a visual/procedural diagram of methods with timeline Use rigorous procedures for the quantitative data collection and analysis

Let’s share our drawings of our mixed methods procedures

How to Design a Mixed Methods Study by John W. Creswell, Ph.D. and Vicki L. Plano Clark, M.S. University of Nebraska-Lincoln Andrews University, July, 2004