examples of mixed research questions

Qualitative Research

• What is Qualitative Research
• PEO for Qualitative Questions
• SPIDER for Mixed Methods Qualitative Research Questions
• Finding Qualitative Research Articles
• Critical Appraisal of Qualitative Research Articles
• Mixed Methods Research
• Qualitative Synthesis

SPIDER: Mixed Methods Qualitative Research Questions

SPIDER  is a search strategy for finding research to answer a mixed-method qualitative research question.

• Sample:  Sample is similar to Patient/Population of PICO. This is the group of people you are interesting in studying qualitatively. For example, in the qualitative research question, "What are the barriers felt by clinicians that lead to the reluctance to use EBP in practice?", S = clinicians  
• Phenomenon of Interest:  The Phenomenon of Interest can be similar to Intervention of PICO. This can be viewed as the topic of the research. For example, in the qualitative research question, "What are the barriers felt by clinicians that lead to the reluctance to use EBP in practice?", PI = Use of EBP  
• Focus Groups
• Observations  
• Evaluation:  Evaluation is similar to Outcomes of PICO. For example, in the qualitative research question, "What are the barriers felt by clinicians that lead to the reluctance to use EBP in practice?", E = Barriers to use of EBP  
• Phenomenology
• Ethnography
• Grounded theory

Using SPIDER for Search Terms

Now that you have your qualitative research questions broken into SPiDER, you can now think about your search strategy and search terms.

For example, in the qualitative research question, " What are the barriers felt by clinicians that lead to the  reluctance to use EBP in practice?"

NOTE: You might not use all these terms in your search.

FINAL BOOLEAN SEARCH:

(clinician* OR health care professional OR health care provider) AND (evidence-based practice OR EBP) AND  ( interview* OR focus group*) AND (barrier* OR hinder* OR resist*) AND phenomenology

Cooke, A., Smith, D., & Booth, A. (2012). Beyond PICO: The SPIDER tool for qualitative evidence  synthesis.  Quality Health Research, 22 (10), 1435-1443. doi: 10.1177/1049732312452938

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• Last Updated: Aug 28, 2023 2:47 PM
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Using mixed methods in health research

Shema tariq.

1 School of Health Sciences, City University London, EC1A 7QN, London, UK

Jenny Woodman

2 MRC Centre of Epidemiology for Child Health, UCL Institute of Child Health, WC1N 1EH, London, UK

Mixed methods research is the use of quantitative and qualitative methods in a single study or series of studies. It is an emergent methodology which is increasingly used by health researchers, especially within health services research. There is a growing literature on the theory, design and critical appraisal of mixed methods research. However, there are few papers that summarize this methodological approach for health practitioners who wish to conduct or critically engage with mixed methods studies. The objective of this paper is to provide an accessible introduction to mixed methods for clinicians and researchers unfamiliar with this approach. We present a synthesis of key methodological literature on mixed methods research, with examples from our own work and that of others, to illustrate the practical applications of this approach within health research. We summarize definitions of mixed methods research, the value of this approach, key aspects of study design and analysis, and discuss the potential challenges of combining quantitative and qualitative methods and data. One of the key challenges within mixed methods research is the successful integration of quantitative and qualitative data during analysis and interpretation. However, the integration of different types of data can generate insights into a research question, resulting in enriched understanding of complex health research problems.

Introduction

Mixed methods research is the use of quantitative and qualitative methods in one study. Research is often dichotomized as quantitative or qualitative. Quantitative research, such as clinical trials or observational studies, generates numerical data. On the other hand qualitative approaches tend to generate non-numerical data, using methods such as semi-structured interviews, focus group discussions and participant observation. Historically, quantitative methods have dominated health research. However, qualitative methods have been increasingly accepted by the health research community in the past two decades, with a rise in publication of qualitative studies. 1 As the value of qualitative approaches has been recognized, there has been a growing interest in combining qualitative and quantitative methods. A recent review of health services research within England has shown an increase in the proportion of studies classified as mixed methods from 17% in the mid-1990s to 30% in the early 2000s. 2 In this paper, we present a synthesis of key literature on mixed methods research, with examples from our own work and that of others to illustrate the practical applications of this approach. This paper is aimed at health researchers and practitioners who are new to the field of mixed methods research and may only have experience of either quantitative or qualitative approaches and methodologies. We wish to provide these readers with an accessible introduction to the increasingly popular methodology of mixed methods research. We hope this will help readers to consider whether their research questions might best be answered by a mixed methods study design, and to engage critically with health research that uses this approach.

The authors each independently carried out a narrative literature review and met to discuss findings. Literature was identified via searches of PubMed, Google and Google Scholar, and hand-searches of the Journal of Mixed Methods Research, with relevant publications selected after discussion. An important consideration was that papers either had a methodological focus or contained a detailed description of their mixed methods design. For PubMed and Google searches, similar terms were used. For example, the PubMed strategy consisted of title and abstract searches for: ((mixed methods) OR ((mixed OR (qualitative AND quantitative)) AND methods)). We also drew upon recommendations from mixed methods conferences and seminars, and reference lists from key publications.

What is mixed methods research?

The most widely accepted definition of mixed methods research is research that ‘focuses on collecting, analysing, and mixing both quantitative and qualitative data in a single study or a series of studies’. 3 Central to the definition is the use of both quantitative and qualitative methods in one study (or a series of connected studies). Separate quantitative and qualitative studies addressing the same research question independently would not be considered ‘mixed methods’ as there would be no integration of approaches at the design, analysis or presentation stage. A recent innovation in mixed methods research is the mixed methods systematic review, which sets out to systematically appraise both quantitative and qualitative literature on a subject area and then synthesize the findings.

Why are mixed methods approaches used?

The underlying assumption of mixed methods research is that it can address some research questions more comprehensively than by using either quantitative or qualitative methods alone. 3 Questions that profit most from a mixed methods design tend to be broad and complex, with multiple facets that may each be best explored by quantitative or qualitative methods. See Boxes 1 and ​ and2 2 for examples from our own work.

Examples of authors’ mixed methods research – JW.

Examples of authors’ mixed methods research – ST.

Usually, quantitative research is associated with a positivist stance and a belief that reality that can be measured and observed objectively. Most commonly, it sets out to test an a priori hypothesis and is therefore conventionally described as ‘deductive’. Strengths of quantitative research include its procedures to minimize confounding and its potential to generate generalizable findings if based on samples that are both large enough and representative. It remains the dominant paradigm in health research. However, this deductive approach is less suited to generating hypotheses about how or why things are happening, or explaining complex social or cultural phenomena.

Qualitative research most often comes from an interpretive framework and is usually informed by the belief that there are multiple realities shaped by personal viewpoints, context and meaning. In-depth qualitative research aims to provide a rich description of views, beliefs and meaning. It also tends to acknowledge the role of researcher and context in shaping and producing the data. Qualitative approaches are described as ‘inductive’ as questions are often open-ended with the analysis allowing hypotheses to emerge from data. High-quality qualitative research can generate robust theory that is applicable to contexts outside of the study area in question, helping to guide practitioners and policy-makers. 8 However, for research that aims to directly impact on policy and practice, the findings of qualitative research can be limited by the small sample sizes that are necessary for in-depth exploratory work and the consequent lack of generalizabilty.

Mixed methods research therefore has the potential to harness the strengths and counterbalance the weaknesses of both approaches and can be especially powerful when addressing complex, multifaceted issues such as health services interventions 9 and living with chronic illness. 10

There are many reasons why researchers choose to combine quantitative and qualitative methods in a study. 11 , 12 We list some common reasons below, using a hypothetical research question about adolescents’ adherence to anticonvulsant medication to illustrate real world applications.

• Complementarity: Using data obtained by one method to illustrate results from another. An example of this would be a survey of adolescents with epilepsy demonstrating poor levels of adherence. Semi-structured interviews with a sub-group of those surveyed may allow us to explore barriers to adherence.
• Development: Using results from one method to develop or inform the use of the other method. A focus group conducted with a group of adolescents with epilepsy may identify mobile phone technology as a potentially important tool in adherence support. We could then develop a mobile phone ‘app’ that reminds patients to take their medication and conduct an intervention study to assess its impact on adherence levels.
• Initiation: Using results from different methods specifically to look for areas of incongruence in order to generate new insights. An illustration of this would be a study exploring the discrepancy between reported adherence in clinic consultations and actual medication adherence. A review of case notes may find adherence levels of over 90% in a clinic population; however, semi-structured interviews with peer researchers may reveal lower levels of adherence and barriers to open discussion with clinicians.
• Expansion: Setting out to examine different aspects of a research question, where each aspect warrants different methods. We may wish to conduct a study that explores adherence more broadly. A large-scale survey of adolescents with epilepsy would provide information on adherence levels and associations whilst interviews and focus groups may allow us to engage with individual experiences of chronic illness and medication in adolescence.
• Triangulation: Using data obtained by both methods to corroborate findings. For example, we could conduct a clinical study measuring drug levels in individuals and documenting self-reported adherence. Qualitative methods such as video diaries may confirm adherence levels.

To this list we would also add political commitment. That is to say, researchers may recognize, and wish to deploy, the strengths of quantitative research in producing generalizable results but may also be committed to representing the voice of participants in their work.

Whatever the reasons for mixing methods, it is important that authors present these explicitly as it allows us to assess if a mixed methods study design is appropriate for answering the research question. 3 , 13

How is mixed methods research conducted?

When embarking on a mixed methods research project it is important to consider:

• the methods that will be used;
• the priority of the methods;
• the sequence in which the methods are to be used.

A wide variety of methods exists by which to collect both quantitative and qualitative data. Both the research question and the data required will be the main determinants of the methods used. To a lesser extent, the choice of methods may be influenced by feasibility, the research team’s skills and experience and time constraints.

Priority of methods relates to the emphasis placed on each method in the study. For instance, the study may be predominantly a quantitative study with a small qualitative component, or vice versa. Alternatively, both quantitative and qualitative methods and data may have equal weighting. The emphasis given to each component of the study will be driven mainly by the research question, the skills of the research team and feasibility.

Finally, researchers must decide when each method is to be used in the study. For instance a team may choose to start with a quantitative phase followed by a qualitative phase, or vice versa. Some studies use both quantitative and qualitative methods concurrently. Again the choice of when to use each method is largely dependent on the research question.

The priority and sequence of mixing methods have been elaborated in a typology of mixed methods research models. See Table 1 for typology and specific examples.

Examples of studies using mixed methods.

How is data analysed in a mixed methods project?

The most important, and perhaps most difficult, aspect of mixed methods research is integrating the qualitative and quantitative data. One approach is to analyse the two data types separately and to then undertake a second stage of analysis where the data and findings from both studies are compared, contrasted and combined. 19 The quantitative and qualitative data are kept analytically distinct and are analysed using techniques usually associated with that type of data; for example, statistical techniques could be used to analyse survey data whilst thematic analysis may be used to analyse interview data. In this approach, the integrity of each data is preserved whilst also capitalizing on the potential for enhanced understanding from combining the two data and sets of findings.

Another approach to mixed methods data analysis is the integrative strategy. 20 Rather than keeping the datasets separate, one type of data may be transformed into another type. That is to say that qualitative data may be turned into quantitative data (‘quantitizing’) or quantitative data may be converted into qualitative data (‘qualitizing’). 21 The former is probably the most common method of this type of integrated analysis. Quantitative transformation is achieved by the numerical coding of qualitative data to create variables that may relate to themes or constructs, allowing statements such as ‘six of 10 participants spoke of the financial barriers to accessing health care’. These data can then be combined with the quantitative dataset and analysed together. Transforming quantitative data into qualitative data is less common. An example of this is the development of narrative psychological ‘types’ from numerical data obtained by questionnaires. 22

Potential challenges in conducting mixed methods research

Despite its considerable strengths as an approach, mixed methods research can present researchers with challenges. 23 , 24

Firstly, combining methodologies has sometimes been seen as problematic because of the view that quantitative and qualitative belong to separate and incompatible paradigms. In this context, paradigms are the set of practices and beliefs held by an academic community at a given point in time. 25 Researchers subscribing to this view argue that it is neither possible nor desirable to combine quantitative and qualitative methods in a study as they represent essentially different and conflicting ways of viewing the world and how we collect information about it. 8 Other researchers take a more pragmatic view, believing that concerns about the incommensurability of worldviews can be set aside if the combination of quantitative and qualitative methods addresses the research question effectively. This pragmatic view informs much applied mixed methods research in health services or policy. 8

Secondly, combining two methods in one study can be time consuming and requires experience and skills in both quantitative and qualitative methods. This can mean, in reality, that a mixed methods project requires a team rather than a lone researcher in order to conduct the study rigorously and within the specified time frame. However, it is important that a team comprising members from different disciplines work well together, rather than becoming compartmentalized. 26 We believe that a project leader with experience in both quantitative and qualitative methods can act as an important bridge in a mixed methods team.

Thirdly, achieving true integration of the different types of data can be difficult. We have suggested various analytic strategies above but this can be hard to achieve as it requires innovative thinking to move between different types of data and make meaningful links between them. It is therefore important to reflect on the results of a study and ask if your understanding has been enriched by the combination of different types of data. If this is not the case then integration may not have occurred sufficiently. 23

Finally, many researchers cite the difficulty in presenting the results of mixed methods study as a barrier to conducting this type of research. 23 Researchers may decide to present their quantitative and qualitative data separately for different audiences. This strategy may involve a decision to publish additional work focusing on the interpretations and conclusions which come from comparing and contrasting findings from the different data types. See Box 1 for an example of this type of publication strategy. Many journals in the medical sciences have a distinct methodological base and relatively restrictive word limits which may preclude the publication of complex, mixed methods studies. However, as the number of mixed methods studies increases in the health research literature we would expect researchers to feel more confident in the presentation of this type of work.

Many of the areas we explore in health are complex and multifaceted. Mixed methods research (combining quantitative and qualitative methods in one study) is an innovative and increasingly popular way of addressing these complexities. Although mixed methods research presents some challenges, in much the same way as every methodology does, this approach provides the research team with a wider range of tools at their disposal in order to answer a question. We believe that the production and integration of different types of data and the combination of skill sets in a team can generate insights into a research question, resulting in enriched understanding.

DECLARATIONS

Competing interests.

None declared

This work was funded by the Medical Research Council (MRC) [grant number: G0701648 to ST], and the MRC with the Economic and Social Research Council (ESRC) [grant number: G0800112 to JW]

Ethical approval

No ethical approval was required for this work

Contributorship

This work was conceived by both ST and JW who each carried out an independent literature review and collaborated on the structure and content of this report. ST wrote the manuscript with revisions and editing done by JW

Acknowledgements

We thank Professors Jonathan Elford and Ruth Gilbert for their comments on draft manuscripts

This article was submitted by the authors and peer reviewed by Geoffrey Harding

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• Mixed methods research: expanding the evidence base
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• Allison Shorten 1 ,
• Joanna Smith 2
• 1 School of Nursing , University of Alabama at Birmingham , USA
• 2 Children's Nursing, School of Healthcare , University of Leeds , UK
• Correspondence to Dr Allison Shorten, School of Nursing, University of Alabama at Birmingham, 1720 2nd Ave South, Birmingham, AL, 35294, USA; [email protected]; ashorten{at}uab.edu

https://doi.org/10.1136/eb-2017-102699

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Introduction

‘Mixed methods’ is a research approach whereby researchers collect and analyse both quantitative and qualitative data within the same study. 1 2 Growth of mixed methods research in nursing and healthcare has occurred at a time of internationally increasing complexity in healthcare delivery. Mixed methods research draws on potential strengths of both qualitative and quantitative methods, 3 allowing researchers to explore diverse perspectives and uncover relationships that exist between the intricate layers of our multifaceted research questions. As providers and policy makers strive to ensure quality and safety for patients and families, researchers can use mixed methods to explore contemporary healthcare trends and practices across increasingly diverse practice settings.

What is mixed methods research?

Mixed methods research requires a purposeful mixing of methods in data collection, data analysis and interpretation of the evidence. The key word is ‘mixed’, as an essential step in the mixed methods approach is data linkage, or integration at an appropriate stage in the research process. 4 Purposeful data integration enables researchers to seek a more panoramic view of their research landscape, viewing phenomena from different viewpoints and through diverse research lenses. For example, in a randomised controlled trial (RCT) evaluating a decision aid for women making choices about birth after caesarean, quantitative data were collected to assess knowledge change, levels of decisional conflict, birth choices and outcomes. 5 Qualitative narrative data were collected to gain insight into women’s decision-making experiences and factors that influenced their choices for mode of birth. 5

In contrast, multimethod research uses a single research paradigm, either quantitative or qualitative. Data are collected and analysed using different methods within the same paradigm. 6 7 For example, in a multimethods qualitative study investigating parent–professional shared decision-making regarding diagnosis of suspected shunt malfunction in children, data collection included audio recordings of admission consultations and interviews 1 week post consultation, with interactions analysed using conversational analysis and the framework approach for the interview data. 8

What are the strengths and challenges in using mixed methods?

Selecting the right research method starts with identifying the research question and study aims. A mixed methods design is appropriate for answering research questions that neither quantitative nor qualitative methods could answer alone. 4 9–11 Mixed methods can be used to gain a better understanding of connections or contradictions between qualitative and quantitative data; they can provide opportunities for participants to have a strong voice and share their experiences across the research process, and they can facilitate different avenues of exploration that enrich the evidence and enable questions to be answered more deeply. 11 Mixed methods can facilitate greater scholarly interaction and enrich the experiences of researchers as different perspectives illuminate the issues being studied. 11

The process of mixing methods within one study, however, can add to the complexity of conducting research. It often requires more resources (time and personnel) and additional research training, as multidisciplinary research teams need to become conversant with alternative research paradigms and different approaches to sample selection, data collection, data analysis and data synthesis or integration. 11

What are the different types of mixed methods designs?

Mixed methods research comprises different types of design categories, including explanatory, exploratory, parallel and nested (embedded) designs. 2   Table 1 summarises the characteristics of each design, the process used and models of connecting or integrating data. For each type of research, an example was created to illustrate how each study design might be applied to address similar but different nursing research aims within the same general nursing research area.

• View inline

Types of mixed methods designs*

What should be considered when evaluating mixed methods research?

When reading mixed methods research or writing a proposal using mixed methods to answer a research question, the six questions below are a useful guide 12 :

Does the research question justify the use of mixed methods?

Is the method sequence clearly described, logical in flow and well aligned with study aims?

Is data collection and analysis clearly described and well aligned with study aims?

Does one method dominate the other or are they equally important?

Did the use of one method limit or confound the other method?

When, how and by whom is data integration (mixing) achieved?

For more detail of the evaluation guide, refer to the McMaster University Mixed Methods Appraisal Tool. 12 The quality checklist for appraising published mixed methods research could also be used as a design checklist when planning mixed methods studies.

• Elliot AE , et al
• Creswell JW ,
• Plano ClarkV L
• Greene JC ,
• Caracelli VJ ,
• Ivankova NV
• Shorten A ,
• Shorten B ,
• Halcomb E ,
• Cheater F ,
• Bekker H , et al
• Tashakkori A ,
• Creswell JW
• 12. ↵ National Collaborating Centre for Methods and Tools . Appraising qualitative, quantitative, and mixed methods studies included in mixed studies reviews: the MMAT . Hamilton, ON : BMJ Publishing Group , 2015 . http://www.nccmt.ca/resources/search/232 (accessed May 2017) .

Competing interests None declared.

Provenance and peer review Commissioned; internally peer reviewed.

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Mixed methods research.

According to the National Institutes of Health , mixed methods strategically integrates or combines rigorous quantitative and qualitative research methods to draw on the strengths of each. Mixed method approaches allow 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 potential resolutions.¹ Mixed methods may be employed to produce a robust description and interpretation of the data, make quantitative results more understandable, or understand broader applicability of small-sample qualitative findings.

Integration

This refers to the ways in which qualitative and quantitative research activities are brought together to achieve greater insight. Mixed methods is not simply having quantitative and qualitative data available or analyzing and presenting data findings separately. The integration process can occur during data collection, analysis, or in the presentation of results.

¹ NIH Office of Behavioral and Social Sciences Research: Best Practices for Mixed Methods Research in the Health Sciences

Basic Mixed Methods Research Designs 

View image description .

Five Key Questions for Getting Started

• What do you want to know?
• What will be the detailed quantitative, qualitative, and mixed methods research questions that you hope to address?
• What quantitative and qualitative data will you collect and analyze?
• Which rigorous methods will you use to collect data and/or engage stakeholders?
• How will you integrate the data in a way that allows you to address the first question?

Rationale for Using Mixed Methods

• Obtain different, multiple perspectives: validation
• Build comprehensive understanding
• Explain statistical results in more depth
• Have better contextualized measures
• Track the process of program or intervention
• Study patient-centered outcomes and stakeholder engagement

Sample Mixed Methods Research Study

The EQUALITY study used an exploratory sequential design to identify the optimal patient-centered approach to collect sexual orientation data in the emergency department.

Qualitative Data Collection and Analysis : Semi-structured interviews with patients of different sexual orientation, age, race/ethnicity, as well as healthcare professionals of different roles, age, and race/ethnicity.

Builds Into : Themes identified in the interviews were used to develop questions for the national survey.

Quantitative Data Collection and Analysis : Representative national survey of patients and healthcare professionals on the topic of reporting gender identity and sexual orientation in healthcare.

Other Resources:

  Introduction to Mixed Methods Research : Harvard Catalyst’s eight-week online course offers an opportunity for investigators who want to understand and apply a mixed methods approach to their research.

Best Practices for Mixed Methods Research in the Health Sciences [PDF] : This guide provides a detailed overview of mixed methods designs, best practices, and application to various types of grants and projects.

Mixed Methods Research Training Program for the Health Sciences (MMRTP ): Selected scholars for this summer training program, hosted by Johns Hopkins’ Bloomberg School of Public Health, have access to webinars, resources, a retreat to discuss their research project with expert faculty, and are matched with mixed methods consultants for ongoing support.

Michigan Mixed Methods : University of Michigan Mixed Methods program offers a variety of resources, including short web videos and recommended reading.

To use a mixed methods approach, you may want to first brush up on your qualitative skills. Below are a few helpful resources specific to qualitative research:

• Qualitative Research Guidelines Project : A comprehensive guide for designing, writing, reviewing and reporting qualitative research.
• Fundamentals of Qualitative Research Methods – What is Qualitative Research : A six-module web video series covering essential topics in qualitative research, including what is qualitative research and how to use the most common methods, in-depth interviews, and focus groups.

View PDF of the above information.

• Examples of good research questions

Last updated

Reviewed by

Tanya Williams

However, developing a good research question is often challenging. But, doing appropriate data analysis or drawing meaningful conclusions from your investigation with a well-defined question make it easier.

So, to get you on the right track, let’s start by defining a research question, what types of research questions are common, and the steps to drafting an excellent research question.

Make research less tedious

Dovetail streamlines research to help you uncover and share actionable insights

• What is a research question?

The definition of a research question might seem fairly obvious.

 At its simplest, a research question is a question you research to find the answer.

Researchers typically start with a problem or an issue and seek to understand why it has occurred, how it can be solved, or other aspects of its nature.

As you'll see, researchers typically start with a broad question that becomes narrower and more specific as the research stages are completed.

In some cases, a study may tackle more than one research question.

• Research question types

Research questions are typically divided into three broad categories: qualitative, quantitative, and mixed-method.

These categories reflect the research type necessary to answer the research question.

Qualitative research

When you conduct qualitative research, you're broadly exploring a subject to analyze its inherent qualities.

There are many types of qualitative research questions, which include:

Descriptive: describing and illuminating little-known or overlooked aspects of a subject

Emancipatory: uncovering data that can serve to emancipate a particular group of people, such as disadvantaged or marginalized communities

Evaluative:  assessing how well a particular research approach or method works

Explanatory: answering “how” or “why” a given phenomenon occurs 

Exploratory:  identifying reasons behind certain behaviors and exploring motivations (also known as generative research because it can generate solutions to problems)

Ideological: researching ideologies or beliefs, such as political affiliation

Interpretive: understanding group perceptions, decision-making, and behavior in a natural setting

Predictive: forecasting a likely outcome or scenario by examining past events 

While it's helpful to understand the differences between these qualitative research question types, writing a good question doesn't start with determining the precise type of research question you'll be asking.

It starts with determining what answers you're seeking.

Quantitative research

Unlike broad, flexible qualitative research questions, quantitative research questions are precise. They also directly link the research question and the proposed methodology.

So, in a quantitative research question, you'll usually find

The study method 

An independent variable (or variables)

A dependent variable

The study population 

Quantitative research questions can also fall into multiple categories, including:

Comparative research questions compare two or more groups according to specific criteria and analyze their similarities and differences.

Descriptive questions measure a population's response to one or more variables.

Relationship (or relationship-based) questions examine how two or more variables interact.

Mixed-methods research

As its name suggests, mixed-methods research questions involve qualitative and quantitative components.

These questions are ideal when the answers require an evaluation of a specific aspect of a phenomenon that you can quantify and a broader understanding of aspects that can't.

• How to write a research question

Writing a good research question can be challenging, even if you're passionate about the subject matter.

A good research question aims to solve a problem that still needs to be answered and can be solved empirically. 

The approach might involve quantitative or qualitative methodology, or a mixture of both. To write a well-developed research question, follow the four steps below:

1. Select a general topic

Start with a broad topic. You may already have one in mind or get one assigned to you. If you don't, think about one you're curious about. 

You can also use common brainstorming techniques , draw on discussions you've had with family and friends, take topics from the news, or use other similar sources of inspiration.

Also, consider a subject that has yet to be studied or addressed. If you're looking to tackle a topic that has already been thoroughly studied, you'll want to examine it from a new angle.

Still, the closer your question, approach, and outcomes are to existing literature, the less value your work will offer. It will also be less publishing-worthy (if that’s your goal).

2. Conduct preliminary research

Next, you'll want to conduct some initial research about your topic. You'll read coverage about your topic in academic journals, the news, and other credible sources at this stage.

You'll familiarize yourself with the terminology commonly used to describe your topic and the current take from subject matter experts and the general public. 

This preliminary review helps you in a few ways. First, you'll find many researchers will discuss challenges they found conducting their research in their "Limitations," "Results," and "Discussion" sections of research papers.

Assessing these sections also helps you avoid choosing the wrong methodological approach to answering your question. Initial research also enables you to avoid focusing on a topic that has already been covered. 

You can generate valuable research questions by tracking topics that have yet to be covered.

3. Consider your audience

Next, you'll want to give some thought to your audience. For example, what kinds of research material are they looking for, and what might they find valuable?

Reflect on why you’re conducting the research. 

What is your team looking to learn if your research is for a work assignment?

How does what they’re asking for from you connect to business goals?

Understanding what your audience is seeking can help you shape the direction of your research so that the final draft connects with your audience.

If you're writing for an academic journal, what types of research do they publish? What kinds of research approaches have they published? And what criteria do they expect submitted manuscripts to meet?

4. Generate potential questions

Take the insights you've gained from your preliminary research and your audience assessment to narrow your topic into a research question. 

Your question should be one that you can answer using the appropriate research methods. Unfortunately, some researchers start with questions they need more resources to answer and then produce studies whose outcomes are limited, limiting the study's value to the broader community. 

Make sure your question is one you can realistically answer.

• Examples of poor research questions

"How do electronics distract teen drivers?"

This question could be better from a researcher's perspective because it is overly broad. For instance, what is “electronics” in this context? Some electronics, like eye-monitoring systems in semi-autonomous vehicles, are designed to keep drivers focused on the road.

Also, how does the question define “teens”? Some states allow you to get a learner's permit as young as 14, while others require you to be 18 to drive. Therefore, conducting a study without further defining the participants' ages is not scientifically sound.

Here's another example of an ineffective research question:

"Why is the sky blue?"

This question has been researched thoroughly and answered. 

A simple online search will turn up hundreds, if not thousands, of pages of resources devoted to this very topic. 

Suppose you spend time conducting original research on a long-answered question; your research won’t be interesting, relevant, or valuable to your audience.

Alternatively, here's an example of a good research question:

"How does using a vehicle’s infotainment touch screen by drivers aged 16 to 18 in the U.S. affect driving habits?"

This question is far more specific than the first bad example. It notes the population of the study, as well as the independent and dependent variables.

And if you're still interested in the sky's color, a better example of a research question might be:

"What color is the sky on Proxima Centauri b, based on existing observations?"

A qualitative research study based on this question could extrapolate what visitors on Proxima Centauri b (a planet in the closest solar system to ours) might see as they look at the sky.

You could approach this by contextualizing our understanding of how the light scatters off the molecules of air resulting in a blue sky, and the likely composition of Proxima Centauri b's atmosphere from data NASA and others have gathered.

• Why the right research question is critical

As you can see from the examples, starting with a poorly-framed research question can make your study difficult or impossible to complete. 

Or it can lead you to duplicate research findings.

Ultimately, developing the right research question sets you up for success. It helps you define a realistic scope for your study, informs the best approach to answer the central question, and conveys its value to your audience. 

That's why you must take the time to get your research question right before you embark on any other part of your project.

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Mixed Methods Research – Different Types & Examples

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Researchers often conduct various types of research in the same study to investigate the different variables in a research project.

Mixed method research is a crucial aspect of research methodology as it combines qualitative and quantitative research approaches, thereby providing a comprehensive understanding of complex phenomena through numerical data and nuanced contextual insights.

Inhaltsverzeichnis

• 1 Mixed methods research – In a Nutshell
• 2 Definition – Mixed methods research
• 3 When to use mixed methods research
• 4 Types of mixed methods research designs
• 5 Advantages of mixed methods research
• 6 Disadvantages of mixed methods research

Mixed methods research – In a Nutshell

• Mixed methods research is a hybrid of quantitative research and qualitative research methodology.
• Researchers use the mixed approach to leverage the benefits of each research method.
• Mixed methods often yield more detailed findings, although they are limited by timelines and inadequate resources.

Definition – Mixed methods research

Mixed methods research incorporates qualitative and quantitative research elements to propose a solution for a research problem . When used together, quantitative and qualitative methods provide more comprehensive findings than the use of each method alone.

Qualitative methods are used to study natural phenomena using observations, interviews, and analysis of text data. Quantitative research involves numerical analysis of quantifiable variables. Mixed methods research is often used in research cases with various variables and data sets such as social and behavioral sciences.

When to use mixed methods research

Mixed methods research is best used when your research displays variables with both qualitative and quantitative characteristics. You can use mixed methods research to formulate generalizable findings, often limited by a standalone quantitative approach.

In addition, using mixed methods research lends credibility to your research findings. By showing how you applied different research methods, your work can hold up under scrutiny since you have covered several aspects. Highlight how your research question will deploy quantitative and qualitative techniques and why it is necessary to use both through mixed methods research.

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Research example

Maybe you want to study road safety on a particular road. You can take a purely quantitative approach if your main metric is the daily average number of road accidents and in which sections they happen. For a qualitative study, you can interview drivers on their thoughts on driving in certain road sections.

A mixed methods research approach seems like the most appropriate way to answer both questions to uncover deeper insights. It can find cause and effect relationships between qualitative and quantitative variables in a detailed study.

For this research problem, a mixed methods research framework may explore whether the sections drivers deem to be more hazardous report more accidents. Note that mixed methods research doesn’t just imply qualitative and quantitative data collection. Both methods should complement each other to answer a common research problem.

Types of mixed methods research designs

There are various mixed methods research designs. The appropriate mixed methods research design choice depends on the research objective, the duration of data collection, and other factors.

We will discuss some designs of mixed methods research. They are used in different contexts to answer different kinds of research problems.

Explanatory sequential

In this type of mixed research, you first collect and analyze quantitative data. This is followed by gathering and analyzing qualitative data. This approach best applies to a research problem where researchers believe the qualitative data will explain the quantitative analysis.

You can estimate the average number of accidents and determine which areas are classified as high risk. From these conclusions, you can interview drivers in these areas and analyze their responses in a qualitative framework.

Based on your qualitative data, you can give possible explanations for why accidents happen in some sections and investigate specific causes.

Exploratory sequential

In this inverse approach, researchers examine qualitative data points and then collect and analyze quantitative data sets.

This approach can be used to formulate research problems and hypotheses. After developing a valid hypothesis, quantitative methods are used to test or validate the qualitative conclusions.

You can begin by talking to drivers or handing out questionnaires to discover hazardous road sections. This is followed by looking at the number of accidents in these sections to compare the statistics with the general drivers’ sentiments.

In a parallel approach, researchers collect both quantitative and qualitative data simultaneously. The findings are analyzed separately, then their respective conclusions are compared to give a general conclusion.

In the analysis of road safety, you can carry out both quantitative and qualitative research as follows:

Qualitative research – You can look at the driver’s comments and issues raised on online platforms such as Twitter.

Quantitative research – You can analyze traffic police reports on the frequency of accidents in various road sections.

The nested approach is also known as the embedded method. In this design, both qualitative and quantitative data are collected concurrently. However, one type of data takes precedence over the other.

Researchers usually adopt a nested approach when there are time restrictions or scarce resources. The nested design is used to support the findings of the main research design.

In the quantitative test, you can investigate if the frequency of the drivers’ concerns about a particular road section corresponds with the frequency of accidents in that section. You can include some qualitative questionnaires to support your quantitative findings.

Advantages of mixed methods research

A win-win scenario – Using both qualitative and quantitative methods takes advantage of the benefits of both research methods. A mixed approach ensures in-depth and generalizable findings.

Versatility in research – Mixed research methods offer more flexibility when formulating research problems. They let researchers break down a research problem into its constituent qualitative and quantitative elements for more comprehensive conclusions.

Expanding the scope of the study – Researchers can expand the subject matter of a research problem using a mixed framework. This often leads to more discoveries beyond the initial research problem.

Disadvantages of mixed methods research

Mismatch of conclusions – Some research designs, such as the parallel design, may yield contrasting results. This poses the problem of generalization as the findings have no similarities.

Lack of sufficient resources – Most research undertakings rely on external funding. Collecting and analyzing both qualitative and quantitative data may consume a lot of time and resources.

Skill gaps – A mixed approach requires skilled qualitative and quantitative analysts. The quantitative field currently has a shortage of skilled personnel due to the complex nature of the quantitative methods available.

What are the key aspects of mixed methods research?

Mixed methods research involves qualitative and quantitative data collection and analysis methods. There are different designs under this approach for various research problems.

When should I use a mixed approach in research?

A mixed approach delivers the best results when the research problem has qualitative and quantitative aspects. Using both methods offers more granular-level insights.

What is the difference between qualitative and quantitative research?

Qualitative is a text analysis of data collected from observation and questionnaires. Quantitative research is a numerical method of collecting and analyzing figures associated with certain research variables.

Which are the 4 mixed research designs?

The main forms of mixed research designs are embedded, parallel, explanatory sequential, and exploratory sequential. They are used in different research proposals to answer research problems.

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• Mixed Methods Research | Definition, Guide, & Examples

Mixed Methods Research | Definition, Guide, & Examples

Published on 4 April 2022 by Tegan George . Revised on 25 October 2022.

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) ?

Table of contents

When to use mixed methods research, mixed methods research designs, benefits of mixed methods research, disadvantages of mixed methods research, frequently asked questions about mixed methods research.

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:

• Generalisability : Qualitative research usually has a smaller sample size , and thus is not generalisable . In mixed methods research, this comparative weakness is mitigated by the comparative strength of ‘large N’, externally valid quantitative research.
• Contextualisation: 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.

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, 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 analyse them separately. After both analyses are complete, compare your results to draw overall conclusions.

• On the qualitative side, you analyse 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 analyse 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 analyse 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 contextualise 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, contextualised insights of qualitative data and the generalisable, 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 generalisable, 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 labour-intensive. Collecting, analysing, and synthesising 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.

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

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

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 organisations.

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 analysed 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 analysed first, followed by qualitative data. You can use this design if you think your qualitative data will explain and contextualise your quantitative findings.
• Exploratory sequential: Qualitative data is collected and analysed 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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6 Common Leadership Styles — and How to Decide Which to Use When

• Rebecca Knight

Being a great leader means recognizing that different circumstances call for different approaches.

Research suggests that the most effective leaders adapt their style to different circumstances — be it a change in setting, a shift in organizational dynamics, or a turn in the business cycle. But what if you feel like you’re not equipped to take on a new and different leadership style — let alone more than one? In this article, the author outlines the six leadership styles Daniel Goleman first introduced in his 2000 HBR article, “Leadership That Gets Results,” and explains when to use each one. The good news is that personality is not destiny. Even if you’re naturally introverted or you tend to be driven by data and analysis rather than emotion, you can still learn how to adapt different leadership styles to organize, motivate, and direct your team.

Much has been written about common leadership styles and how to identify the right style for you, whether it’s transactional or transformational, bureaucratic or laissez-faire. But according to Daniel Goleman, a psychologist best known for his work on emotional intelligence, “Being a great leader means recognizing that different circumstances may call for different approaches.”

• RK Rebecca Knight is a journalist who writes about all things related to the changing nature of careers and the workplace. Her essays and reported stories have been featured in The Boston Globe, Business Insider, The New York Times, BBC, and The Christian Science Monitor. She was shortlisted as a Reuters Institute Fellow at Oxford University in 2023. Earlier in her career, she spent a decade as an editor and reporter at the Financial Times in New York, London, and Boston.

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Americans and affirmative action: How the public sees the consideration of race in college admissions, hiring

The term “affirmative action” has a long history in the United States. One early reference appears in an executive order that President John F. Kennedy signed in 1961 , directing federal contractors to “take affirmative action” to prevent discrimination against job applicants and employees on the basis of race or other factors.

Today, affirmative action generally refers to programs aimed at boosting educational or employment opportunities for racial and ethnic minority groups that historically have faced discrimination. But the idea has sparked many debates in recent years . Some Americans see these programs as an effective way to address past wrongs and increase racial and ethnic diversity in higher education and the workplace. Others view them as discriminatory in their own right.

Here’s a closer look at what recent surveys have found about Americans’ views of affirmative action, both in a broad sense and in specific settings.

Pew Research Center published this backgrounder about affirmative action in the United States because the issue is currently in the news. The U.S. Supreme Court is expected to decide a high-profile case in the weeks ahead about the consideration of race and ethnicity in college admissions decisions.

All public opinion findings cited here come from surveys conducted by the Center or Gallup. Information about the field dates and sample sizes of each survey, as well as additional methodological details, are available by following the links in the text.

For more detailed information about how Americans see the consideration of race and ethnicity in college admissions decisions, read our recent reports: “More Americans Disapprove Than Approve of Colleges Considering Race, Ethnicity in Admissions Decisions” and “Asian Americans Hold Mixed Views Around Affirmative Action.”

How familiar is the public with affirmative action?

In a December 2022 Pew Research Center survey, around eight-in-ten U.S. adults (79%) said they had ever heard the phrase “affirmative action.”

College graduates, those with higher incomes and older people were among the groups most likely have heard the term. For instance, 90% of Americans 65 and older said they had heard the phrase, compared with 65% of those ages 18 to 29. White and Black adults were also more likely than Asian or Hispanic adults to have heard the phrase.

How do Americans feel about affirmative action?

Public attitudes about affirmative action depend on how Americans are asked about it.

Americans who had heard the phrase affirmative action in the Center’s December survey were asked whether they saw it as a good or a bad thing. Among those who had ever heard the term, 36% said affirmative action is a good thing, 29% said it is a bad thing and a third weren’t sure.

By comparison, Gallup has asked U.S. adults whether they “generally favor or oppose affirmative action programs for racial minorities.” In 2021, the last time Gallup asked this question, a 62% majority of Americans favored such programs .

Public attitudes about affirmative action can also vary depending on the specific context in which it is being discussed, such as in higher education or the workplace.

How do Americans view race and ethnicity as a factor in college admissions?

A larger share of Americans disapprove than approve of higher education institutions taking race and ethnicity into account when admitting students, according to several recent Center surveys.

In a survey conducted in spring 2023 , half of U.S. adults said they disapprove of selective colleges and universities taking race and ethnicity into account in admissions decisions in order to increase racial and ethnic diversity. A third of adults approved of this, while 16% were not sure.

In the same survey, 49% of Americans said the consideration of race and ethnicity makes the overall admissions process less fair, while only 20% said it makes the process fairer. Another 17% said it does not affect the fairness of the admissions process, while 13% said they weren’t sure.

Other Center surveys have also found more opposition than support for the consideration of race and ethnicity in college admissions decisions.

In the December 2022 survey, for example, 82% of U.S. adults said colleges should not consider race or ethnicity when deciding which students to accept, while only 17% said colleges should take this into account. Americans were far more likely to say that colleges should consider other factors, particularly high school grades and standardized test scores.

How do Americans view race and ethnicity as a factor in hiring?

Most Americans say companies should not take race and ethnicity into account when hiring or promoting workers, according to a 2019 Center survey .

In that survey, 74% of U.S. adults said that, when making decisions about hiring and promotions, companies and organizations should take only a person’s qualifications into account, even if it results in less diversity. Around a quarter (24%) said companies and organizations should take a person’s race and ethnicity into account – in addition to qualifications – to increase diversity.

While most Americans disapprove of the consideration of race and ethnicity in hiring and promotion decisions, they still see value in a diverse workplace. Three-quarters of adults said in the 2019 survey that it was very or somewhat important for companies and organizations to promote racial and ethnic diversity in their workplace. Around a quarter (24%) said this was not too or not at all important.

How do Americans view recent efforts related to diversity, equity and inclusion (DEI) in the workplace? While public attitudes on DEI efforts in the workplace are much more positive than negative, a sizeable share of Americans say it is neither good nor bad, according to a February 2023 Center survey of employed Americans .

In the survey, 56% of workers said that, in general, focusing on increasing diversity, equity and inclusion at work is mainly a good thing, while far fewer (16%) said it is a bad thing. Another 28% said it is neither good nor bad.

Still, relatively few workers attached a great deal of importance to diversity in their workplace. Only about a third (32%) said it’s extremely or very important to them to work somewhere with a mix of employees of different races and ethnicities.

How do attitudes on these topics vary by race and ethnicity? Racial and ethnic minorities – especially Black Americans – are more likely than White Americans to support the consideration of race and ethnicity in college admissions and hiring decisions.

In the Center’s spring 2023 survey, around half of Black adults (47%) approved of selective colleges considering race and ethnicity in their admissions decisions, compared with 39% of Hispanic adults, 37% of Asian adults and 29% of White adults. In fact, Black adults were the only racial or ethnic group more likely to approve than disapprove of such efforts. Hispanic adults were evenly divided, while Asian and White adults were more likely to disapprove than approve. (These figures refer only to English-speaking Asian adults. For a closer look at views among Asian Americans – including those who do not speak English – read our recent report, “Asian Americans Hold Mixed Views Around Affirmative Action.” )

When it comes to hiring and promotion decisions in the workplace, about four-in-ten Black adults (37%) said in the Center’s 2019 survey that companies and organizations should take a person’s race and ethnicity into account – in addition to their qualifications – in order to increase diversity. Hispanic (27%) and White (21%) adults were less likely to express this view. (There were not enough Asian adults in the survey sample to report their results separately.) Are there partisan differences on these issues?

Yes. Democrats are far more likely than Republicans to approve of colleges and employers considering race and ethnicity.

In the Center’s spring 2023 survey, more than half of Democrats and Democratic-leaning independents (54%) approved of selective colleges and universities taking race and ethnicity into account when making admissions decisions. Roughly three-quarters of Republicans and Republican leaners (74%) disapproved.

There were also wide partisan differences over how the consideration of race and ethnicity affects the college admissions process. Democrats were divided over whether it makes the overall admissions process fairer or less fair (33% and 30%, respectively, held these views). But by a margin of 70% to 7%, Republicans said it makes the process less fair.

In the 2019 survey about hiring and promotion decisions, majorities of Democrats and Republicans alike said companies and organizations should take only a person’s qualifications into account, even if it results in less diversity. But Republicans were far more likely than Democrats to express this view (90% vs. 62%).

• Affirmative Action
• Business & Workplace
• Higher Education

John Gramlich is an associate director at Pew Research Center

Striking findings from 2023

Private, selective colleges are most likely to use race, ethnicity as a factor in admissions decisions, asian americans hold mixed views around affirmative action, more americans disapprove than approve of colleges considering race, ethnicity in admissions decisions, hispanic enrollment reaches new high at four-year colleges in the u.s., but affordability remains an obstacle, most popular.

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