proposed strategy research

Writing a Research Strategy

This page is focused on providing practical tips and suggestions for preparing The Research Strategy, the primary component of an application's Research Plan along with the Specific Aims. The guidance on this page is primarily geared towards an R01-style application, however, much of it is useful for other grant types as well.

Developing the Research Strategy

The primary audience for your application is your peer review group. When writing your Research Strategy, your goal is to present a well-organized, visually appealing, and readable description of your proposed project and the rationale for pursuing it. Your writing should be streamlined and organized so your reviewers can readily grasp the information. If it's a key point, repeat it, then repeat it again. Add more emphasis by putting the text in bold , or bold italics . If writing is not your forte, get help.  For more information, please visit  W riting For Reviewers .

How to Organize the Research Strategy Section

How to organize a Research Strategy is largely up to the applicant. Start by following the NIH application instructions and guidelines for formatting attachments such as the research plan section.

It is generally structured as follows:

Significance

For  Preliminary Studies (for new applications) or a Progress Report (for renewal and revision applications).

• You can either include preliminary studies or progress report information as a subsection of Approach or integrate it into any or all of the three main sections.
• If you do the latter, be sure to mark the information clearly, for example, with a bold subhead.

 Helpful tips to consider when formatting:

• Organize using bold headers or an outline or numbering system—or both—that are used consistently throughout.
• Start each section with the appropriate header: Significance, Innovation, or Approach.
• Organize the Approach section around the Specific Aims.

For most applications, you need to address Rigor ous Study Design  by describing the experimental design and methods you propose and how they will achieve robust and unbiased results. See the NIH guidance for elaboration on the 4 major areas of rigor and transparency emphasized in grant review.  These requirements apply to research grant, career development, fellowship, and training applications.

Tips for Drafting Sections of the Research Strategy

Although you will emphasize your project's significance throughout the application, the Significance section should give the most details. The farther removed your reviewers are from your field, the more information you'll need to provide on basic biology, importance of the area, research opportunities, and new findings. Reviewing the potentially relevant study section rosters may give you some ideas as to general reviewer expertise. You will also need to describe the prior and preliminary studies that provide a strong scientific rationale for pursuing the proposed studies, emphasizing the strengths and weaknesses in the rigor and transparency of these key studies.

This section gives you the chance to explain how your application is conceptually and/or technically innovative. Some examples as to how you might do this could include but not limited to:

• Demonstrate the proposed research is new and unique, e.g., explores new scientific avenues, has a novel hypothesis, will create new knowledge.
• Explain how the proposed work can refine, improve, or propose a new application of an existing concept or method.

If your proposal is paradigm-shifting or challenges commonly held beliefs, be sure that you include sufficient evidence in your preliminary data to convince reviewers, including strong rationale, data supporting the approach, and clear feasibility. Your job is to make the reviewers feel confident that the risk is worth taking.

For projects predominantly focused on innovation and outside-the-box research, investigators may wish to consider mechanisms other than R01s for example (e.g., exploratory/developmental research (R21) grants, NIH Director's Pioneer Award Program (DP1), and NIH Director's New Innovator Award Program (DP2).

The Approach section is where the experimental design is described. Expect your assigned reviewers to scrutinize your approach: they will want to know what you plan to do, how you plan to do it, and whether you can do it. NIH data show that of the peer review criteria, approach has the highest correlation with the overall impact score. Importantly, elements of rigorous study design should be addressed in this section, such as plans for minimization of bias (e.g. methods for blinding and treatment randomization) and consideration of relevant biological variables. Likewise, be sure to lay out a plan for alternative experiments and approaches in case you get uninterpretable or surprising results, and also consider limitations of the study and alternative interpretations. Point out any procedures, situations, or materials that may be hazardous to personnel and precautions to be exercised. A full discussion on the use of select agents should appear in the Select Agent Research attachment .  Consider including a timeline demonstrating anticipated completion of the Aims. 

Here are some pointers to consider when organizing your Approach section:

• Enter a bold header for each Specific Aim.
• Under each aim, describe the experiments.
• If you get result X, you will follow pathway X; if you get result Y, you will follow pathway Y.
• Consider illustrating this with a flowchart.

Preliminary Studies

If submitting a new application to a NOFO that allows preliminary data, it is strongly encouraged to include preliminary studies.  Preliminary studies demonstrate competency in the methods and interpretation. Well-designed and robust preliminary studies also serve to provide a strong scientific rationale for the proposed follow-up experiments. Reviewers also use preliminary studies together with the biosketches to assess the investigator review criterion, which reflects the competence of the research team. Provide alternative interpretations to your data to show reviewers you've thought through problems in-depth and are prepared to meet future challenges. As noted above, preliminary data can be put anywhere in the Research Strategy, but just make sure reviewers will be able to distinguish it from the proposed studies. Alternatively, it can be a separate section with its own header.

Progress Reports

If applying for a renewal or a revision (a competing supplement to an existing grant), include a progress report for reviewers.

Create a header so reviewers can easily find it and include the following information:

• Project period beginning and end dates.
• Summary of the importance and robustness of the completed findings in relation to the Specific Aims.
• Account of published and unpublished results, highlighting progress toward achieving your Specific Aims.  

Other Helpful Tips

Referencing publications.

References show breadth of knowledge of the field and provide a scientific foundation for your application. If a critical work is omitted, reviewers may assume the applicant is not aware of it or deliberately ignoring it.

Throughout the application, reference all relevant publications for the concepts underlying your research and your methods. Remember the strengths and weaknesses in the rigor of the key studies you cite for justifying your proposal will need to be discussed in the Significance and/or Approach sections.

Read more about Bibliography and References Cited at Additional Application Elements .

Graphics can illustrate complex information in a small space and add visual interest to your application. Including schematics, tables, illustrations, graphs, and other types of graphics can enhance applications. Consider adding a timetable or flowchart to illustrate your experimental plan, including decision trees with alternative experimental pathways to help your reviewers understand your plans.

Video may enhance your application beyond what graphics alone can achieve. If you plan to send one or more videos, you'll need to meet certain requirements and include key information in your Research Strategy. State in your cover letter that a video will be included in your application (don't attach your files to the application). After you apply and get assignment information from the Commons, ask your assigned Scientific Review Officer (SRO) how your business official should send the files. Your video files are due at least one month before the peer review meeting.

However, you can't count on all reviewers being able to see or hear video, so you'll want to be strategic in how you incorporate it into your application by taking the following steps:

• Caption any narration in the video.
• Include key images from the video
• Write a description of the video, so the text would make sense even without the video.

Tracking for Your Budget

As you design your experiments, keep a running tab of the following essential data:

• Who. A list of people who will help (for the Key Personnel section later).
• What. A list of equipment and supplies for the experiments
• Time. Notes on how long each step takes. Timing directly affects the budget as well as how many Specific Aims can realistically be achieved.

Jotting this information down will help when Creating a Budget  and complete other sections later.

Review and Finalize Your Research Plan

Critically review the research plan through the lens of a reviewer to identify potential questions or weak spots.

Enlist others to review your application with a fresh eye. Include people who aren't familiar with the research to make sure the proposed work is clear to someone outside the field.

When finalizing the details of the Research Strategy, revisit and revise the Specific Aims as needed. Please see Writing Specific Aims . 

comments Want to contact NINDS staff? Please visit our Find Your NINDS Program Officer page to learn more about contacting Program Officer, Grants Management Specialists, Scientific Review Officers, and Health Program Specialists.

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Write Your Research Plan

In this part, we give you detailed information about writing an effective Research Plan. We start with the importance and parameters of significance and innovation.

We then discuss how to focus the Research Plan, relying on the iterative process described in the Iterative Approach to Application Planning Checklist shown at Draft Specific Aims  and give you advice for filling out the forms.

You'll also learn the importance of having a well-organized, visually appealing application that avoids common missteps and the importance of preparing your just-in-time information early.

While this document is geared toward the basic research project grant, the R01, much of it is useful for other grant types.

Table of Contents

Research plan overview and your approach, craft a title, explain your aims, research strategy instructions, advice for a successful research strategy, graphics and video, significance, innovation, and approach, tracking for your budget, preliminary studies or progress report, referencing publications, review and finalize your research plan, abstract and narrative.

Your application's Research Plan has two sections:

• Specific Aims —a one-page statement of your objectives for the project.
• Research Strategy —a description of the rationale for your research and your experiments in 12 pages for an R01.

In your Specific Aims, you note the significance and innovation of your research; then list your two to three concrete objectives, your aims.

Your Research Strategy is the nuts and bolts of your application, where you describe your research rationale and the experiments you will conduct to accomplish each aim. Though how you organize it is largely up to you, NIH expects you to follow these guidelines.

• Organize using bold headers or an outline or numbering system—or both—that you use consistently throughout.
• Start each section with the appropriate header: Significance, Innovation, or Approach.
• Organize the Approach section around your Specific Aims.

Format of Your Research Plan

To write the Research Plan, you don't need the application forms. Write the text in your word processor, turn it into a PDF file, and upload it into the application form when it's final.

Because NIH may return your application if it doesn't meet all requirements, be sure to follow the rules for font, page limits, and more. Read the instructions at NIH’s Format Attachments .

For an R01, the Research Strategy can be up to 12 pages, plus one page for Specific Aims. Don't pad other sections with information that belongs in the Research Plan. NIH is on the lookout and may return your application to you if you try to evade page limits.

Follow Examples

As you read this page, look at our Sample Applications and More  to see some of the different strategies successful PIs use to create an outstanding Research Plan.

Keeping It All In Sync

Writing in a logical sequence will save you time.

Information you put in the Research Plan affects just about every other application part. You'll need to keep everything in sync as your plans evolve during the writing phase.

It's best to consider your writing as an iterative process. As you develop and finalize your experiments, you will go back and check other parts of the application to make sure everything is in sync: the "who, what, when, where, and how (much money)" as well as look again at the scope of your plans.

In that vein, writing in a logical sequence is a good approach that will save you time. We suggest proceeding in the following order:

• Create a provisional title.
• Write a draft of your Specific Aims.
• Start with your Significance and Innovation sections.
• Then draft the Approach section considering the personnel and skills you'll need for each step.
• Evaluate your Specific Aims and methods in light of your expected budget (for a new PI, it should be modest, probably under the $250,000 for NIH's modular budget).
• As you design experiments, reevaluate your hypothesis, aims, and title to make sure they still reflect your plans.
• Prepare your Abstract (a summary of your Specific Aims).
• Complete the other forms.

Even the smaller sections of your application need to be well-organized and readable so reviewers can readily grasp the information. If writing is not your forte, get help.

To view writing strategies for successful applications, see our Sample Applications and More . There are many ways to create a great application, so explore your options.

Within the character limit, include the important information to distinguish your project within the research area, your project's goals, and the research problem.

Giving your project a title at the outset can help you stay focused and avoid a meandering Research Plan. So you may want to launch your writing by creating a well-defined title.

NIH gives you a 200 character limit, but don’t feel obliged to use all of that allotment. Instead, we advise you to keep the title as succinct as possible while including the important information to distinguish your project within the research area. Make your title reflect your project's goals, the problem your project addresses, and possibly your approach to studying it. Make your title specific: saying you are studying lymphocyte trafficking is not informative enough.

For examples of strong titles, see our Sample Applications and More .

After you write a preliminary title, check that

• My title is specific, indicating at least the research area and the goals of my project.
• It is 200 characters or less.
• I use as simple language as possible.
• I state the research problem and, possibly, my approach to studying it.
• I use a different title for each of my applications. (Note: there are exceptions, for example, for a renewal—see Apply for Renewal  for details.)
• My title has appropriate keywords.

Later you may want to change your initial title. That's fine—at this point, it's just an aid to keep your plans focused.

Since all your reviewers read your Specific Aims, you want to excite them about your project.

If testing your hypothesis is the destination for your research, your Research Plan is the map that takes you there.

You'll start by writing the smaller part, the Specific Aims. Think of the one-page Specific Aims as a capsule of your Research Plan. Since all your reviewers read your Specific Aims, you want to excite them about your project.

For more on crafting your Specific Aims, see Draft Specific Aims .

Write a Narrative

Use at least half the page to provide the rationale and significance of your planned research. A good way to start is with a sentence that states your project's goals.

For the rest of the narrative, you will describe the significance of your research, and give your rationale for choosing the project. In some cases, you may want to explain why you did not take an alternative route.

Then, briefly describe your aims, and show how they build on your preliminary studies and your previous research. State your hypothesis.

If it is likely your application will be reviewed by a study section with broad expertise, summarize the status of research in your field and explain how your project fits in.

In the narrative part of the Specific Aims of many outstanding applications, people also used their aims to

• State the technologies they plan to use.
• Note their expertise to do a specific task or that of collaborators.
• Describe past accomplishments related to the project.
• Describe preliminary studies and new and highly relevant findings in the field.
• Explain their area's biology.
• Show how the aims relate to one another.
• Describe expected outcomes for each aim.
• Explain how they plan to interpret data from the aim’s efforts.
• Describe how to address potential pitfalls with contingency plans.

Depending on your situation, decide which items are important for you. For example, a new investigator would likely want to highlight preliminary data and qualifications to do the work.

Many people use bold or italics to emphasize items they want to bring to the reviewers' attention, such as the hypothesis or rationale.

Detail Your Aims

After the narrative, enter your aims as bold bullets, or stand-alone or run-on headers.

• State your plans using strong verbs like identify, define, quantify, establish, determine.
• Describe each aim in one to three sentences.
• Consider adding bullets under each aim to refine your objectives.

How focused should your aims be? Look at the example below.

Spot the Sample

Read the Specific Aims of the Application from Drs. Li and Samulski , "Enhance AAV Liver Transduction with Capsid Immune Evasion."

• Aim 1. Study the effect of adeno-associated virus (AAV) empty particles on AAV capsid antigen cross-presentation in vivo .
• Aim 2. Investigate AAV capsid antigen presentation following administration of AAV mutants and/or proteasome inhibitors for enhanced liver transduction in vivo .
• Aim 3. Isolate AAV chimeric capsids with human hepatocyte tropism and the capacity for cytotoxic T lymphocytes (CTL) evasion.

After finishing the draft Specific Aims, check that

• I keep to the one-page limit.
• Each of my two or three aims is a narrowly focused, concrete objective I can achieve during the grant.
• They give a clear picture of how my project can generate knowledge that may improve human health.
• They show my project's importance to science, how it addresses a critical research opportunity that can move my field forward.
• My text states how my work is innovative.
• I describe the biology to the extent needed for my reviewers.
• I give a rationale for choosing the topic and approach.
• I tie the project to my preliminary data and other new findings in the field.
• I explicitly state my hypothesis and why testing it is important.
• My aims can test my hypothesis and are logical.
• I can design and lead the execution of two or three sets of experiments that will strive to accomplish each aim.
• As much as possible, I use language that an educated person without expertise can understand.
• My text has bullets, bolding, or headers so reviewers can easily spot my aims (and other key items).

For each element listed above, analyze your text and revise it until your Specific Aims hit all the key points you'd like to make.

After the list of aims, some people add a closing paragraph, emphasizing the significance of the work, their collaborators, or whatever else they want to focus reviewers' attention on.

Your Research Strategy is the bigger part of your application's Research Plan (the other part is the Specific Aims—discussed above.)

The Research Strategy is the nuts and bolts of your application, describing the rationale for your research and the experiments you will do to accomplish each aim. It is structured as follows:

• Significance
• You can either include this information as a subsection of Approach or integrate it into any or all of the three main sections.
• If you do the latter, be sure to mark the information clearly, for example, with a bold subhead.
• Possible other sections, for example, human subjects, vertebrate animals, select agents, and others (these do not count toward the page limit).

Though how you organize your application is largely up to you, NIH does want you to follow these guidelines:

• Add bold headers or an outlining or numbering system—or both—that you use consistently throughout.
• Start each of the Research Strategy's sections with a header: Significance, Innovation, and Approach.

For an R01, the Research Strategy is limited to 12 pages for the three main sections and the preliminary studies only. Other items are not included in the page limit.

Find instructions for R01s in the SF 424 Application Guide—go to NIH's SF 424 (R&R) Application and Electronic Submission Information for the generic SF 424 Application Guide or find it in your notice of funding opportunity (NOFO).

For most applications, you need to address Rigor and Reproducibility by describing the experimental design and methods you propose and how they will achieve robust and unbiased results. The requirement applies to research grant, career development, fellowship, and training applications.

If you're responding to an institute-specific program announcement (PA) (not a parent program announcement) or a request for applications (RFA), check the NIH Guide notice, which has additional information you need. Should it differ from the NOFO, go with the NIH Guide .

Also note that your application must meet the initiative's objectives and special requirements. NIAID program staff will check your application, and if it is not responsive to the announcement, your application will be returned to you without a review.

When writing your Research Strategy, your goal is to present a well-organized, visually appealing, and readable description of your proposed project. That means your writing should be streamlined and organized so your reviewers can readily grasp the information. If writing is not your forte, get help.

There are many ways to create an outstanding Research Plan, so explore your options.

What Success Looks Like

Your application's Research Plan is the map that shows your reviewers how you plan to test your hypothesis.

It not only lays out your experiments and expected outcomes, but must also convince your reviewers of your likely success by allaying any doubts that may cross their minds that you will be able to conduct the research.

Notice in the sample applications how the writing keeps reviewers' eyes on the ball by bringing them back to the main points the PIs want to make. Write yourself an insurance policy against human fallibility: if it's a key point, repeat it, then repeat it again.

The Big Three

So as you write, put the big picture squarely in your sights. When reviewers read your application, they'll look for the answers to three basic questions:

• Can your research move your field forward?
• Is the field important—will progress make a difference to human health?
• Can you and your team carry out the work?

Add Emphasis

Savvy PIs create opportunities to drive their main points home. They don't stop at the Significance section to emphasize their project's importance, and they look beyond their biosketches to highlight their team's expertise.

Don't take a chance your reviewer will gloss over that one critical sentence buried somewhere in your Research Strategy or elsewhere. Write yourself an insurance policy against human fallibility: if it's a key point, repeat it, then repeat it again.

Add more emphasis by putting the text in bold, or bold italics (in the modern age, we skip underlining—it's for typewriters).

Here are more strategies from our successful PIs:

• While describing a method in the Approach section, they state their or collaborators' experience with it.
• They point out that they have access to a necessary piece of equipment.
• When explaining their field and the status of current research, they weave in their own work and their preliminary data.
• They delve into the biology of the area to make sure reviewers will grasp the importance of their research and understand their field and how their work fits into it.

You can see many of these principles at work in the Approach section of the Application from Dr. William Faubion , "Inflammatory cascades disrupt Treg function through epigenetic mechanisms."

• Reviewers felt that the experiments described for Aim 1 will yield clear results.
• The plans to translate those findings to gene targets of relevance are well outlined and focused.
• He ties his proposed experiments to the larger picture, including past research and strong preliminary data for the current application. 

Anticipate Reviewer Questions

Our applicants not only wrote with their reviewers in mind they seemed to anticipate their questions. You may think: how can I anticipate all the questions people may have? Of course you can't, but there are some basic items (in addition to the "big three" listed above) that will surely be on your reviewers' minds:

• Will the investigators be able to get the work done within the project period, or is the proposed work over ambitious?
• Did the PI describe potential pitfalls and possible alternatives?
• Will the experiments generate meaningful data?
• Could the resulting data prove the hypothesis?
• Are others already doing the work, or has it been already completed?

Address these questions; then spend time thinking about more potential issues specific to you and your research—and address those too.

For applications, a picture can truly be worth a thousand words. Graphics can illustrate complex information in a small space and add visual interest to your application.

Look at our sample applications to see how the investigators included schematics, tables, illustrations, graphs, and other types of graphics to enhance their applications.

Consider adding a timetable or flowchart to illustrate your experimental plan, including decision trees with alternative experimental pathways to help your reviewers understand your plans.

Plan Ahead for Video

If you plan to send one or more videos, you'll need to meet certain standards and include key information in your Research Strategy now.

To present some concepts or demonstrations, video may enhance your application beyond what graphics alone can achieve. However, you can't count on all reviewers being able to see or hear video, so you'll want to be strategic in how you incorporate it into your application.

Be reviewer-friendly. Help your cause by taking the following steps:

• Caption any narration in the video.
• Choose evocative still images from your video to accompany your summary.
• Write your summary of the video carefully so the text would make sense even without the video.

In addition to those considerations, create your videos to fit NIH’s technical requirements. Learn more in the SF 424 Form Instructions .

Next, as you write your Research Strategy, include key images from the video and a brief description.

Then, state in your cover letter that you plan to send video later. (Don't attach your files to the application.)

After you apply and get assignment information from the Commons, ask your assigned scientific review officer (SRO) how your business official should send the files. Your video files are due at least one month before the peer review meeting.

Know Your Audience's Perspective

The primary audience for your application is your peer review group. Learn how to write for the reviewers who are experts in your field and those who are experts in other fields by reading Know Your Audience .

Be Organized: A B C or 1 2 3?

In the top-notch applications we reviewed, organization ruled but followed few rules. While you want to be organized, how you go about it is up to you.

Nevertheless, here are some principles to follow:

• Start each of the Research Strategy's sections with a header: Significance, Innovation, and Approach—this you must do.

The Research Strategy's page limit—12 for R01s—is for the three main parts: Significance, Innovation, and Approach and your preliminary studies (or a progress report if you're renewing your grant). Other sections, for example, research animals or select agents, do not have a page limit.

Although you will emphasize your project's significance throughout the application, the Significance section should give the most details. Don't skimp—the farther removed your reviewers are from your field, the more information you'll need to provide on basic biology, importance of the area, research opportunities, and new findings.

When you describe your project's significance, put it in the context of 1) the state of your field, 2) your long-term research plans, and 3) your preliminary data.

In our Sample Applications , you can see that both investigators and reviewers made a case for the importance of the research to improving human health as well as to the scientific field.

Look at the Significance section of the Application from Dr. Mengxi Jiang , "Intersection of polyomavirus infection and host cellular responses," to see how these elements combine to make a strong case for significance.

• Dr. Jiang starts with a summary of the field of polyomavirus research, identifying critical knowledge gaps in the field.
• The application ties the lab's previous discoveries and new research plans to filling those gaps, establishing the significance with context.
• Note the use of formatting, whitespace, and sectioning to highlight key points and make it easier for reviewers to read the text.

After conveying the significance of the research in several parts of the application, check that

• In the Significance section, I describe the importance of my hypothesis to the field (especially if my reviewers are not in it) and human disease.
• I also point out the project's significance throughout the application.
• The application shows that I am aware of opportunities, gaps, roadblocks, and research underway in my field.
• I state how my research will advance my field, highlighting knowledge gaps and showing how my project fills one or more of them.
• Based on my scan of the review committee roster, I determine whether I cannot assume my reviewers will know my field and provide some information on basic biology, the importance of the area, knowledge gaps, and new findings.

If you are either a new PI or entering a new area: be cautious about seeming too innovative. Not only is innovation just one of five review criteria, but there might be a paradigm shift in your area of science. A reviewer may take a challenge to the status quo as a challenge to his or her world view.

When you look at our sample applications, you see that both the new and experienced investigators are not generally shifting paradigms. They are using new approaches or models, working in new areas, or testing innovative ideas.

After finishing the draft innovation section, check that

• I show how my proposed research is new and unique, e.g., explores new scientific avenues, has a novel hypothesis, will create new knowledge.
• Most likely, I explain how my project's research can refine, improve, or propose a new application of an existing concept or method.
• Make a very strong case for challenging the existing paradigm.
• Have data to support the innovative approach.
• Have strong evidence that I can do the work.

In your Approach, you spell out a few sets of experiments to address each aim. As we noted above, it's a good idea to restate the key points you've made about your project's significance, its place in your field, and your long-term goals.

You're probably wondering how much detail to include.

If you look at our sample applications as a guide, you can see very different approaches. Though people generally used less detail than you'd see in a scientific paper, they do include some experimental detail.

Expect your assigned reviewers to scrutinize your approach: they will want to know what you plan to do and how you plan to do it.

NIH data show that of the peer review criteria, approach has the highest correlation with the overall impact score.

Look at the Application from Dr. Mengxi Jiang , "Intersection of polyomavirus infection and host cellular responses," to see how a new investigator handled the Approach section.

For an example of an experienced investigator's well-received Approach section, see the Application from Dr. William Faubion , "Inflammatory cascades disrupt Treg function through epigenetic mechanisms."

Especially if you are a new investigator, you need enough detail to convince reviewers that you understand what you are undertaking and can handle the method.

• Cite a publication that shows you can handle the method where you can, but give more details if you and your team don't have a proven record using the method—and state explicitly why you think you will succeed.
• If space is short, you could also focus on experiments that highlight your expertise or are especially interesting. For experiments that are pedestrian or contracted out, just list the method.

Be sure to lay out a plan for alternative experiments and approaches in case you get negative or surprising results. Show reviewers you have a plan for spending the four or five years you will be funded no matter where the experiments lead.

See the Application from Drs. Li and Samulski , "Enhance AAV Liver Transduction with Capsid Immune Evasion," for a strong Approach section covering potential. As an example, see section C.1.3.'s alternative approaches.

Here are some pointers for organizing your Approach:

• Enter a bold header for each Specific Aim.
• Under each aim, describe the first set of experiments.
• If you get result X, you will follow pathway X; if you get result Y, you will follow pathway Y.
• Consider illustrating this with a flowchart.

Trim the fat—omit all information not needed to make your case. If you try to wow reviewers with your knowledge, they'll find flaws and penalize you heavily. Don't give them ammunition by including anything you don't need.

As you design your experiments, keep a running tab of the following essential data on a separate piece of paper:

• Who. A list of people who will help you for your Key Personnel section later.
• What. A list of equipment and supplies for the experiments you plan.
• Time. Notes on how long each step takes. Timing directly affects your budget as well as how many Specific Aims you can realistically achieve.

Jotting this information down will help you Create a Budget and complete other sections later.

After finishing a draft Approach section, check that

• I include enough background and preliminary data to give reviewers the context and significance of my plans.
• They can test the hypothesis (or hypotheses).
• I show alternative experiments and approaches in case I get negative or surprising results.
• My experiments can yield meaningful data to test my hypothesis (or hypotheses).
• As a new investigator, I include enough detail to convince reviewers I understand and can handle a method. I reviewed the sample applications to see how much detail to use.
• If I or my team has experience with a method, I cite it; otherwise I include enough details to convince reviewers we can handle it.
• I describe the results I anticipate and their implications.
• I omit all information not needed to state my case.
• I keep track of and explain who will do what, what they will do, when and where they will do it, how long it will take, and how much money it will cost.
• My timeline shows when I expect to complete my aims.

If you are applying for a new application, include preliminary studies; for a renewal or a revision (a competing supplement to an existing grant), prepare a progress report instead.

Describing Preliminary Studies

Your preliminary studies show that you can handle the methods and interpret results. Here's where you build reviewer confidence that you are headed in the right direction by pursuing research that builds on your accomplishments.

Reviewers use your preliminary studies together with the biosketches to assess the investigator review criterion, which reflects the competence of the research team.

Give alternative interpretations to your data to show reviewers you've thought through problems in-depth and are prepared to meet future challenges. If you don't do this, the reviewers will!

Though you may include other people's publications, focus on your preliminary data or unpublished data from your lab and the labs of your team members as much as you can.

As we noted above, you can put your preliminary data anywhere in the Research Strategy that you feel is appropriate, but just make sure your reviewers will be able to distinguish it. Alternatively, you can create a separate section with its own header.

Including a Progress Report

If you are applying for a renewal or a revision (a competing supplement to an existing grant), prepare a progress report instead of preliminary studies.

Create a header so your program officer can easily find it and include the following information:

• Project period beginning and end dates.
• Summary of the importance of your findings in relation to your Specific Aims.
• Account of published and unpublished results, highlighting your progress toward achieving your Specific Aims.

Note: if you submit a renewal application before the due date of your progress report, you do not need to submit a separate progress report for your grant. However, you will need to submit it, if your renewal is not funded.

After finishing the draft, check that

• I interpret my preliminary results critically.
• There is enough information to show I know what I'm talking about.
• If my project is complex, I give more preliminary studies.
• I show how my previous experience prepared me for the new project.
• It's clear which data are mine and which are not.

References show your breadth of knowledge of the field. If you leave out an important work, reviewers may assume you're not aware of it.

Throughout your application, you will reference all relevant publications for the concepts underlying your research and your methods.

Read more about your Bibliography and References Cited at Add a Bibliography and Appendix .

• Throughout my application I cite the literature thoroughly but not excessively, adding citations for all references important to my work.
• I cite all papers important to my field, including those from potential reviewers.
• I include fewer than 100 citations (if possible).
• My Bibliography and References Cited form lists all my references.
• I refer to unpublished work, including information I learned through personal contacts.
• If I do not describe a method, I add a reference to the literature.

Look over what you've written with a critical eye of a reviewer to identify potential questions or weak spots.

Enlist others to do that too—they can look at your application with a fresh eye. Include people who aren't familiar with your research to make sure you can get your point across to someone outside your field.

As you finalize the details of your Research Strategy, you will also need to return to your Specific Aims to see if you must revise. See Draft Specific Aims .

After you finish your Research Plan, you are ready to write your Abstract (called Project Summary/Abstract) and Project Narrative, which are attachments to the Other Project Information form.

These sections may be small, but they're important.

• All your peer reviewers read your Abstract and narrative.
• Staff and automated systems in NIH's Center for Scientific Review use them to decide where to assign your application, even if you requested an institute and study section.
• They show the importance and health relevance of your research to members of the public and Congress who are interested in what NIH is funding with taxpayer dollars.

Be sure to omit confidential or proprietary information in these sections! When your application is funded, NIH enters your title and Abstract in the public RePORTER database.

Think brief and simple: to the extent that you can, write these sections in lay language, and include appropriate keywords, e.g., immunotherapy, genetic risk factors.

As NIH referral officers use these parts to direct your application to an institute for possible funding, your description can influence the choice they make.

Write a succinct summary of your project that both a scientist and a lay person can understand (to the extent that you can).

• Use your Specific Aims as a template—shorten it and simplify the language.
• In the first sentence, state the significance of your research to your field and relevance to NIAID's mission: to better understand, treat, and prevent infectious, immunologic, and allergic diseases.
• Next state your hypothesis and the innovative potential of your research.
• Then list and briefly describe your Specific Aims and long-term objectives.

In your Project Narrative, you have only a few sentences to drive home your project's potential to improve public health.

Check out these effective Abstracts and Narratives from our R01  Sample Applications :

• Application from Dr. Mengxi Jiang , "Intersection of polyomavirus infection and host cellular responses"
• Application from Dr. William Faubion , "Inflammatory cascades disrupt Treg function through epigenetic mechanisms"
• My Project Summary/Abstract and Project Narrative (and title) are accessible to a broad audience.
• They describe the significance of my research to my field and state my hypothesis, my aims, and the innovative potential of my research.
• My narrative describes my project's potential to improve public health.
• I do not include any confidential or proprietary information.
• I do not use graphs or images.
• My Abstract has keywords that are appropriate and distinct enough to avoid confusion with other terms.
• My title is specific and informative.

Previous Step

Have questions.

A program officer in your area of science can give you application advice, NIAID's perspective on your research, and confirmation that NIAID will accept your application.

Find contacts and instructions at When to Contact an NIAID Program Officer .

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Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

• Your overall aims and approach
• The type of research design you’ll use
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Prevent plagiarism, run a free check.

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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Research Methods in Dentistry pp 87–114 Cite as

Writing a Research Proposal

• Fahimeh Tabatabaei 3 &
• Lobat Tayebi 3  
• First Online: 10 April 2022

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A research proposal is a roadmap that brings the researcher closer to the objectives, takes the research topic from a purely subjective mind, and manifests an objective plan. It shows us what steps we need to take to reach the objective, what questions we should answer, and how much time we need. It is a framework based on which you can perform your research in a well-organized and timely manner. In other words, by writing a research proposal, you get a map that shows the direction to the destination (answering the research question). If the proposal is poorly prepared, after spending a lot of energy and money, you may realize that the result of the research has nothing to do with the initial objective, and the study may end up nowhere. Therefore, writing the proposal shows that the researcher is aware of the proper research and can justify the significance of his/her idea.

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Organizing Your Social Sciences Research Paper

• Types of Research Designs
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Introduction

Before beginning your paper, you need to decide how you plan to design the study .

The research design refers to the overall strategy and analytical approach that you have chosen in order to integrate, in a coherent and logical way, the different components of the study, thus ensuring that the research problem will be thoroughly investigated. It constitutes the blueprint for the collection, measurement, and interpretation of information and data. Note that the research problem determines the type of design you choose, not the other way around!

De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Trochim, William M.K. Research Methods Knowledge Base. 2006.

General Structure and Writing Style

The function of a research design is to ensure that the evidence obtained enables you to effectively address the research problem logically and as unambiguously as possible . In social sciences research, obtaining information relevant to the research problem generally entails specifying the type of evidence needed to test the underlying assumptions of a theory, to evaluate a program, or to accurately describe and assess meaning related to an observable phenomenon.

With this in mind, a common mistake made by researchers is that they begin their investigations before they have thought critically about what information is required to address the research problem. Without attending to these design issues beforehand, the overall research problem will not be adequately addressed and any conclusions drawn will run the risk of being weak and unconvincing. As a consequence, the overall validity of the study will be undermined.

The length and complexity of describing the research design in your paper can vary considerably, but any well-developed description will achieve the following :

• Identify the research problem clearly and justify its selection, particularly in relation to any valid alternative designs that could have been used,
• Review and synthesize previously published literature associated with the research problem,
• Clearly and explicitly specify hypotheses [i.e., research questions] central to the problem,
• Effectively describe the information and/or data which will be necessary for an adequate testing of the hypotheses and explain how such information and/or data will be obtained, and
• Describe the methods of analysis to be applied to the data in determining whether or not the hypotheses are true or false.

The research design is usually incorporated into the introduction of your paper . You can obtain an overall sense of what to do by reviewing studies that have utilized the same research design [e.g., using a case study approach]. This can help you develop an outline to follow for your own paper.

NOTE : Use the SAGE Research Methods Online and Cases and the SAGE Research Methods Videos databases to search for scholarly resources on how to apply specific research designs and methods . The Research Methods Online database contains links to more than 175,000 pages of SAGE publisher's book, journal, and reference content on quantitative, qualitative, and mixed research methodologies. Also included is a collection of case studies of social research projects that can be used to help you better understand abstract or complex methodological concepts. The Research Methods Videos database contains hours of tutorials, interviews, video case studies, and mini-documentaries covering the entire research process.

Creswell, John W. and J. David Creswell. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 5th edition. Thousand Oaks, CA: Sage, 2018; De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Leedy, Paul D. and Jeanne Ellis Ormrod. Practical Research: Planning and Design . Tenth edition. Boston, MA: Pearson, 2013; Vogt, W. Paul, Dianna C. Gardner, and Lynne M. Haeffele. When to Use What Research Design . New York: Guilford, 2012.

Action Research Design

Definition and Purpose

The essentials of action research design follow a characteristic cycle whereby initially an exploratory stance is adopted, where an understanding of a problem is developed and plans are made for some form of interventionary strategy. Then the intervention is carried out [the "action" in action research] during which time, pertinent observations are collected in various forms. The new interventional strategies are carried out, and this cyclic process repeats, continuing until a sufficient understanding of [or a valid implementation solution for] the problem is achieved. The protocol is iterative or cyclical in nature and is intended to foster deeper understanding of a given situation, starting with conceptualizing and particularizing the problem and moving through several interventions and evaluations.

What do these studies tell you ?

• This is a collaborative and adaptive research design that lends itself to use in work or community situations.
• Design focuses on pragmatic and solution-driven research outcomes rather than testing theories.
• When practitioners use action research, it has the potential to increase the amount they learn consciously from their experience; the action research cycle can be regarded as a learning cycle.
• Action research studies often have direct and obvious relevance to improving practice and advocating for change.
• There are no hidden controls or preemption of direction by the researcher.

What these studies don't tell you ?

• It is harder to do than conducting conventional research because the researcher takes on responsibilities of advocating for change as well as for researching the topic.
• Action research is much harder to write up because it is less likely that you can use a standard format to report your findings effectively [i.e., data is often in the form of stories or observation].
• Personal over-involvement of the researcher may bias research results.
• The cyclic nature of action research to achieve its twin outcomes of action [e.g. change] and research [e.g. understanding] is time-consuming and complex to conduct.
• Advocating for change usually requires buy-in from study participants.

Coghlan, David and Mary Brydon-Miller. The Sage Encyclopedia of Action Research . Thousand Oaks, CA:  Sage, 2014; Efron, Sara Efrat and Ruth Ravid. Action Research in Education: A Practical Guide . New York: Guilford, 2013; Gall, Meredith. Educational Research: An Introduction . Chapter 18, Action Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Kemmis, Stephen and Robin McTaggart. “Participatory Action Research.” In Handbook of Qualitative Research . Norman Denzin and Yvonna S. Lincoln, eds. 2nd ed. (Thousand Oaks, CA: SAGE, 2000), pp. 567-605; McNiff, Jean. Writing and Doing Action Research . London: Sage, 2014; Reason, Peter and Hilary Bradbury. Handbook of Action Research: Participative Inquiry and Practice . Thousand Oaks, CA: SAGE, 2001.

Case Study Design

A case study is an in-depth study of a particular research problem rather than a sweeping statistical survey or comprehensive comparative inquiry. It is often used to narrow down a very broad field of research into one or a few easily researchable examples. The case study research design is also useful for testing whether a specific theory and model actually applies to phenomena in the real world. It is a useful design when not much is known about an issue or phenomenon.

• Approach excels at bringing us to an understanding of a complex issue through detailed contextual analysis of a limited number of events or conditions and their relationships.
• A researcher using a case study design can apply a variety of methodologies and rely on a variety of sources to investigate a research problem.
• Design can extend experience or add strength to what is already known through previous research.
• Social scientists, in particular, make wide use of this research design to examine contemporary real-life situations and provide the basis for the application of concepts and theories and the extension of methodologies.
• The design can provide detailed descriptions of specific and rare cases.
• A single or small number of cases offers little basis for establishing reliability or to generalize the findings to a wider population of people, places, or things.
• Intense exposure to the study of a case may bias a researcher's interpretation of the findings.
• Design does not facilitate assessment of cause and effect relationships.
• Vital information may be missing, making the case hard to interpret.
• The case may not be representative or typical of the larger problem being investigated.
• If the criteria for selecting a case is because it represents a very unusual or unique phenomenon or problem for study, then your interpretation of the findings can only apply to that particular case.

Case Studies. Writing@CSU. Colorado State University; Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 4, Flexible Methods: Case Study Design. 2nd ed. New York: Columbia University Press, 1999; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Greenhalgh, Trisha, editor. Case Study Evaluation: Past, Present and Future Challenges . Bingley, UK: Emerald Group Publishing, 2015; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Stake, Robert E. The Art of Case Study Research . Thousand Oaks, CA: SAGE, 1995; Yin, Robert K. Case Study Research: Design and Theory . Applied Social Research Methods Series, no. 5. 3rd ed. Thousand Oaks, CA: SAGE, 2003.

Causal Design

Causality studies may be thought of as understanding a phenomenon in terms of conditional statements in the form, “If X, then Y.” This type of research is used to measure what impact a specific change will have on existing norms and assumptions. Most social scientists seek causal explanations that reflect tests of hypotheses. Causal effect (nomothetic perspective) occurs when variation in one phenomenon, an independent variable, leads to or results, on average, in variation in another phenomenon, the dependent variable.

Conditions necessary for determining causality:

• Empirical association -- a valid conclusion is based on finding an association between the independent variable and the dependent variable.
• Appropriate time order -- to conclude that causation was involved, one must see that cases were exposed to variation in the independent variable before variation in the dependent variable.
• Nonspuriousness -- a relationship between two variables that is not due to variation in a third variable.
• Causality research designs assist researchers in understanding why the world works the way it does through the process of proving a causal link between variables and by the process of eliminating other possibilities.
• Replication is possible.
• There is greater confidence the study has internal validity due to the systematic subject selection and equity of groups being compared.
• Not all relationships are causal! The possibility always exists that, by sheer coincidence, two unrelated events appear to be related [e.g., Punxatawney Phil could accurately predict the duration of Winter for five consecutive years but, the fact remains, he's just a big, furry rodent].
• Conclusions about causal relationships are difficult to determine due to a variety of extraneous and confounding variables that exist in a social environment. This means causality can only be inferred, never proven.
• If two variables are correlated, the cause must come before the effect. However, even though two variables might be causally related, it can sometimes be difficult to determine which variable comes first and, therefore, to establish which variable is the actual cause and which is the  actual effect.

Beach, Derek and Rasmus Brun Pedersen. Causal Case Study Methods: Foundations and Guidelines for Comparing, Matching, and Tracing . Ann Arbor, MI: University of Michigan Press, 2016; Bachman, Ronet. The Practice of Research in Criminology and Criminal Justice . Chapter 5, Causation and Research Designs. 3rd ed. Thousand Oaks, CA: Pine Forge Press, 2007; Brewer, Ernest W. and Jennifer Kubn. “Causal-Comparative Design.” In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 125-132; Causal Research Design: Experimentation. Anonymous SlideShare Presentation; Gall, Meredith. Educational Research: An Introduction . Chapter 11, Nonexperimental Research: Correlational Designs. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Trochim, William M.K. Research Methods Knowledge Base. 2006.

Cohort Design

Often used in the medical sciences, but also found in the applied social sciences, a cohort study generally refers to a study conducted over a period of time involving members of a population which the subject or representative member comes from, and who are united by some commonality or similarity. Using a quantitative framework, a cohort study makes note of statistical occurrence within a specialized subgroup, united by same or similar characteristics that are relevant to the research problem being investigated, rather than studying statistical occurrence within the general population. Using a qualitative framework, cohort studies generally gather data using methods of observation. Cohorts can be either "open" or "closed."

• Open Cohort Studies [dynamic populations, such as the population of Los Angeles] involve a population that is defined just by the state of being a part of the study in question (and being monitored for the outcome). Date of entry and exit from the study is individually defined, therefore, the size of the study population is not constant. In open cohort studies, researchers can only calculate rate based data, such as, incidence rates and variants thereof.
• Closed Cohort Studies [static populations, such as patients entered into a clinical trial] involve participants who enter into the study at one defining point in time and where it is presumed that no new participants can enter the cohort. Given this, the number of study participants remains constant (or can only decrease).
• The use of cohorts is often mandatory because a randomized control study may be unethical. For example, you cannot deliberately expose people to asbestos, you can only study its effects on those who have already been exposed. Research that measures risk factors often relies upon cohort designs.
• Because cohort studies measure potential causes before the outcome has occurred, they can demonstrate that these “causes” preceded the outcome, thereby avoiding the debate as to which is the cause and which is the effect.
• Cohort analysis is highly flexible and can provide insight into effects over time and related to a variety of different types of changes [e.g., social, cultural, political, economic, etc.].
• Either original data or secondary data can be used in this design.
• In cases where a comparative analysis of two cohorts is made [e.g., studying the effects of one group exposed to asbestos and one that has not], a researcher cannot control for all other factors that might differ between the two groups. These factors are known as confounding variables.
• Cohort studies can end up taking a long time to complete if the researcher must wait for the conditions of interest to develop within the group. This also increases the chance that key variables change during the course of the study, potentially impacting the validity of the findings.
• Due to the lack of randominization in the cohort design, its external validity is lower than that of study designs where the researcher randomly assigns participants.

Healy P, Devane D. “Methodological Considerations in Cohort Study Designs.” Nurse Researcher 18 (2011): 32-36; Glenn, Norval D, editor. Cohort Analysis . 2nd edition. Thousand Oaks, CA: Sage, 2005; Levin, Kate Ann. Study Design IV: Cohort Studies. Evidence-Based Dentistry 7 (2003): 51–52; Payne, Geoff. “Cohort Study.” In The SAGE Dictionary of Social Research Methods . Victor Jupp, editor. (Thousand Oaks, CA: Sage, 2006), pp. 31-33; Study Design 101. Himmelfarb Health Sciences Library. George Washington University, November 2011; Cohort Study. Wikipedia.

Cross-Sectional Design

Cross-sectional research designs have three distinctive features: no time dimension; a reliance on existing differences rather than change following intervention; and, groups are selected based on existing differences rather than random allocation. The cross-sectional design can only measure differences between or from among a variety of people, subjects, or phenomena rather than a process of change. As such, researchers using this design can only employ a relatively passive approach to making causal inferences based on findings.

• Cross-sectional studies provide a clear 'snapshot' of the outcome and the characteristics associated with it, at a specific point in time.
• Unlike an experimental design, where there is an active intervention by the researcher to produce and measure change or to create differences, cross-sectional designs focus on studying and drawing inferences from existing differences between people, subjects, or phenomena.
• Entails collecting data at and concerning one point in time. While longitudinal studies involve taking multiple measures over an extended period of time, cross-sectional research is focused on finding relationships between variables at one moment in time.
• Groups identified for study are purposely selected based upon existing differences in the sample rather than seeking random sampling.
• Cross-section studies are capable of using data from a large number of subjects and, unlike observational studies, is not geographically bound.
• Can estimate prevalence of an outcome of interest because the sample is usually taken from the whole population.
• Because cross-sectional designs generally use survey techniques to gather data, they are relatively inexpensive and take up little time to conduct.
• Finding people, subjects, or phenomena to study that are very similar except in one specific variable can be difficult.
• Results are static and time bound and, therefore, give no indication of a sequence of events or reveal historical or temporal contexts.
• Studies cannot be utilized to establish cause and effect relationships.
• This design only provides a snapshot of analysis so there is always the possibility that a study could have differing results if another time-frame had been chosen.
• There is no follow up to the findings.

Bethlehem, Jelke. "7: Cross-sectional Research." In Research Methodology in the Social, Behavioural and Life Sciences . Herman J Adèr and Gideon J Mellenbergh, editors. (London, England: Sage, 1999), pp. 110-43; Bourque, Linda B. “Cross-Sectional Design.” In  The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman, and Tim Futing Liao. (Thousand Oaks, CA: 2004), pp. 230-231; Hall, John. “Cross-Sectional Survey Design.” In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 173-174; Helen Barratt, Maria Kirwan. Cross-Sectional Studies: Design Application, Strengths and Weaknesses of Cross-Sectional Studies. Healthknowledge, 2009. Cross-Sectional Study. Wikipedia.

Descriptive Design

Descriptive research designs help provide answers to the questions of who, what, when, where, and how associated with a particular research problem; a descriptive study cannot conclusively ascertain answers to why. Descriptive research is used to obtain information concerning the current status of the phenomena and to describe "what exists" with respect to variables or conditions in a situation.

• The subject is being observed in a completely natural and unchanged natural environment. True experiments, whilst giving analyzable data, often adversely influence the normal behavior of the subject [a.k.a., the Heisenberg effect whereby measurements of certain systems cannot be made without affecting the systems].
• Descriptive research is often used as a pre-cursor to more quantitative research designs with the general overview giving some valuable pointers as to what variables are worth testing quantitatively.
• If the limitations are understood, they can be a useful tool in developing a more focused study.
• Descriptive studies can yield rich data that lead to important recommendations in practice.
• Appoach collects a large amount of data for detailed analysis.
• The results from a descriptive research cannot be used to discover a definitive answer or to disprove a hypothesis.
• Because descriptive designs often utilize observational methods [as opposed to quantitative methods], the results cannot be replicated.
• The descriptive function of research is heavily dependent on instrumentation for measurement and observation.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 5, Flexible Methods: Descriptive Research. 2nd ed. New York: Columbia University Press, 1999; Given, Lisa M. "Descriptive Research." In Encyclopedia of Measurement and Statistics . Neil J. Salkind and Kristin Rasmussen, editors. (Thousand Oaks, CA: Sage, 2007), pp. 251-254; McNabb, Connie. Descriptive Research Methodologies. Powerpoint Presentation; Shuttleworth, Martyn. Descriptive Research Design, September 26, 2008; Erickson, G. Scott. "Descriptive Research Design." In New Methods of Market Research and Analysis . (Northampton, MA: Edward Elgar Publishing, 2017), pp. 51-77; Sahin, Sagufta, and Jayanta Mete. "A Brief Study on Descriptive Research: Its Nature and Application in Social Science." International Journal of Research and Analysis in Humanities 1 (2021): 11; K. Swatzell and P. Jennings. “Descriptive Research: The Nuts and Bolts.” Journal of the American Academy of Physician Assistants 20 (2007), pp. 55-56; Kane, E. Doing Your Own Research: Basic Descriptive Research in the Social Sciences and Humanities . London: Marion Boyars, 1985.

Experimental Design

A blueprint of the procedure that enables the researcher to maintain control over all factors that may affect the result of an experiment. In doing this, the researcher attempts to determine or predict what may occur. Experimental research is often used where there is time priority in a causal relationship (cause precedes effect), there is consistency in a causal relationship (a cause will always lead to the same effect), and the magnitude of the correlation is great. The classic experimental design specifies an experimental group and a control group. The independent variable is administered to the experimental group and not to the control group, and both groups are measured on the same dependent variable. Subsequent experimental designs have used more groups and more measurements over longer periods. True experiments must have control, randomization, and manipulation.

• Experimental research allows the researcher to control the situation. In so doing, it allows researchers to answer the question, “What causes something to occur?”
• Permits the researcher to identify cause and effect relationships between variables and to distinguish placebo effects from treatment effects.
• Experimental research designs support the ability to limit alternative explanations and to infer direct causal relationships in the study.
• Approach provides the highest level of evidence for single studies.
• The design is artificial, and results may not generalize well to the real world.
• The artificial settings of experiments may alter the behaviors or responses of participants.
• Experimental designs can be costly if special equipment or facilities are needed.
• Some research problems cannot be studied using an experiment because of ethical or technical reasons.
• Difficult to apply ethnographic and other qualitative methods to experimentally designed studies.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 7, Flexible Methods: Experimental Research. 2nd ed. New York: Columbia University Press, 1999; Chapter 2: Research Design, Experimental Designs. School of Psychology, University of New England, 2000; Chow, Siu L. "Experimental Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 448-453; "Experimental Design." In Social Research Methods . Nicholas Walliman, editor. (London, England: Sage, 2006), pp, 101-110; Experimental Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Kirk, Roger E. Experimental Design: Procedures for the Behavioral Sciences . 4th edition. Thousand Oaks, CA: Sage, 2013; Trochim, William M.K. Experimental Design. Research Methods Knowledge Base. 2006; Rasool, Shafqat. Experimental Research. Slideshare presentation.

Exploratory Design

An exploratory design is conducted about a research problem when there are few or no earlier studies to refer to or rely upon to predict an outcome . The focus is on gaining insights and familiarity for later investigation or undertaken when research problems are in a preliminary stage of investigation. Exploratory designs are often used to establish an understanding of how best to proceed in studying an issue or what methodology would effectively apply to gathering information about the issue.

The goals of exploratory research are intended to produce the following possible insights:

• Familiarity with basic details, settings, and concerns.
• Well grounded picture of the situation being developed.
• Generation of new ideas and assumptions.
• Development of tentative theories or hypotheses.
• Determination about whether a study is feasible in the future.
• Issues get refined for more systematic investigation and formulation of new research questions.
• Direction for future research and techniques get developed.
• Design is a useful approach for gaining background information on a particular topic.
• Exploratory research is flexible and can address research questions of all types (what, why, how).
• Provides an opportunity to define new terms and clarify existing concepts.
• Exploratory research is often used to generate formal hypotheses and develop more precise research problems.
• In the policy arena or applied to practice, exploratory studies help establish research priorities and where resources should be allocated.
• Exploratory research generally utilizes small sample sizes and, thus, findings are typically not generalizable to the population at large.
• The exploratory nature of the research inhibits an ability to make definitive conclusions about the findings. They provide insight but not definitive conclusions.
• The research process underpinning exploratory studies is flexible but often unstructured, leading to only tentative results that have limited value to decision-makers.
• Design lacks rigorous standards applied to methods of data gathering and analysis because one of the areas for exploration could be to determine what method or methodologies could best fit the research problem.

Cuthill, Michael. “Exploratory Research: Citizen Participation, Local Government, and Sustainable Development in Australia.” Sustainable Development 10 (2002): 79-89; Streb, Christoph K. "Exploratory Case Study." In Encyclopedia of Case Study Research . Albert J. Mills, Gabrielle Durepos and Eiden Wiebe, editors. (Thousand Oaks, CA: Sage, 2010), pp. 372-374; Taylor, P. J., G. Catalano, and D.R.F. Walker. “Exploratory Analysis of the World City Network.” Urban Studies 39 (December 2002): 2377-2394; Exploratory Research. Wikipedia.

Field Research Design

Sometimes referred to as ethnography or participant observation, designs around field research encompass a variety of interpretative procedures [e.g., observation and interviews] rooted in qualitative approaches to studying people individually or in groups while inhabiting their natural environment as opposed to using survey instruments or other forms of impersonal methods of data gathering. Information acquired from observational research takes the form of “ field notes ” that involves documenting what the researcher actually sees and hears while in the field. Findings do not consist of conclusive statements derived from numbers and statistics because field research involves analysis of words and observations of behavior. Conclusions, therefore, are developed from an interpretation of findings that reveal overriding themes, concepts, and ideas. More information can be found HERE .

• Field research is often necessary to fill gaps in understanding the research problem applied to local conditions or to specific groups of people that cannot be ascertained from existing data.
• The research helps contextualize already known information about a research problem, thereby facilitating ways to assess the origins, scope, and scale of a problem and to gage the causes, consequences, and means to resolve an issue based on deliberate interaction with people in their natural inhabited spaces.
• Enables the researcher to corroborate or confirm data by gathering additional information that supports or refutes findings reported in prior studies of the topic.
• Because the researcher in embedded in the field, they are better able to make observations or ask questions that reflect the specific cultural context of the setting being investigated.
• Observing the local reality offers the opportunity to gain new perspectives or obtain unique data that challenges existing theoretical propositions or long-standing assumptions found in the literature.

What these studies don't tell you

• A field research study requires extensive time and resources to carry out the multiple steps involved with preparing for the gathering of information, including for example, examining background information about the study site, obtaining permission to access the study site, and building trust and rapport with subjects.
• Requires a commitment to staying engaged in the field to ensure that you can adequately document events and behaviors as they unfold.
• The unpredictable nature of fieldwork means that researchers can never fully control the process of data gathering. They must maintain a flexible approach to studying the setting because events and circumstances can change quickly or unexpectedly.
• Findings can be difficult to interpret and verify without access to documents and other source materials that help to enhance the credibility of information obtained from the field  [i.e., the act of triangulating the data].
• Linking the research problem to the selection of study participants inhabiting their natural environment is critical. However, this specificity limits the ability to generalize findings to different situations or in other contexts or to infer courses of action applied to other settings or groups of people.
• The reporting of findings must take into account how the researcher themselves may have inadvertently affected respondents and their behaviors.

Historical Design

The purpose of a historical research design is to collect, verify, and synthesize evidence from the past to establish facts that defend or refute a hypothesis. It uses secondary sources and a variety of primary documentary evidence, such as, diaries, official records, reports, archives, and non-textual information [maps, pictures, audio and visual recordings]. The limitation is that the sources must be both authentic and valid.

• The historical research design is unobtrusive; the act of research does not affect the results of the study.
• The historical approach is well suited for trend analysis.
• Historical records can add important contextual background required to more fully understand and interpret a research problem.
• There is often no possibility of researcher-subject interaction that could affect the findings.
• Historical sources can be used over and over to study different research problems or to replicate a previous study.
• The ability to fulfill the aims of your research are directly related to the amount and quality of documentation available to understand the research problem.
• Since historical research relies on data from the past, there is no way to manipulate it to control for contemporary contexts.
• Interpreting historical sources can be very time consuming.
• The sources of historical materials must be archived consistently to ensure access. This may especially challenging for digital or online-only sources.
• Original authors bring their own perspectives and biases to the interpretation of past events and these biases are more difficult to ascertain in historical resources.
• Due to the lack of control over external variables, historical research is very weak with regard to the demands of internal validity.
• It is rare that the entirety of historical documentation needed to fully address a research problem is available for interpretation, therefore, gaps need to be acknowledged.

Howell, Martha C. and Walter Prevenier. From Reliable Sources: An Introduction to Historical Methods . Ithaca, NY: Cornell University Press, 2001; Lundy, Karen Saucier. "Historical Research." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor. (Thousand Oaks, CA: Sage, 2008), pp. 396-400; Marius, Richard. and Melvin E. Page. A Short Guide to Writing about History . 9th edition. Boston, MA: Pearson, 2015; Savitt, Ronald. “Historical Research in Marketing.” Journal of Marketing 44 (Autumn, 1980): 52-58;  Gall, Meredith. Educational Research: An Introduction . Chapter 16, Historical Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007.

Longitudinal Design

A longitudinal study follows the same sample over time and makes repeated observations. For example, with longitudinal surveys, the same group of people is interviewed at regular intervals, enabling researchers to track changes over time and to relate them to variables that might explain why the changes occur. Longitudinal research designs describe patterns of change and help establish the direction and magnitude of causal relationships. Measurements are taken on each variable over two or more distinct time periods. This allows the researcher to measure change in variables over time. It is a type of observational study sometimes referred to as a panel study.

• Longitudinal data facilitate the analysis of the duration of a particular phenomenon.
• Enables survey researchers to get close to the kinds of causal explanations usually attainable only with experiments.
• The design permits the measurement of differences or change in a variable from one period to another [i.e., the description of patterns of change over time].
• Longitudinal studies facilitate the prediction of future outcomes based upon earlier factors.
• The data collection method may change over time.
• Maintaining the integrity of the original sample can be difficult over an extended period of time.
• It can be difficult to show more than one variable at a time.
• This design often needs qualitative research data to explain fluctuations in the results.
• A longitudinal research design assumes present trends will continue unchanged.
• It can take a long period of time to gather results.
• There is a need to have a large sample size and accurate sampling to reach representativness.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 6, Flexible Methods: Relational and Longitudinal Research. 2nd ed. New York: Columbia University Press, 1999; Forgues, Bernard, and Isabelle Vandangeon-Derumez. "Longitudinal Analyses." In Doing Management Research . Raymond-Alain Thiétart and Samantha Wauchope, editors. (London, England: Sage, 2001), pp. 332-351; Kalaian, Sema A. and Rafa M. Kasim. "Longitudinal Studies." In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 440-441; Menard, Scott, editor. Longitudinal Research . Thousand Oaks, CA: Sage, 2002; Ployhart, Robert E. and Robert J. Vandenberg. "Longitudinal Research: The Theory, Design, and Analysis of Change.” Journal of Management 36 (January 2010): 94-120; Longitudinal Study. Wikipedia.

Meta-Analysis Design

Meta-analysis is an analytical methodology designed to systematically evaluate and summarize the results from a number of individual studies, thereby, increasing the overall sample size and the ability of the researcher to study effects of interest. The purpose is to not simply summarize existing knowledge, but to develop a new understanding of a research problem using synoptic reasoning. The main objectives of meta-analysis include analyzing differences in the results among studies and increasing the precision by which effects are estimated. A well-designed meta-analysis depends upon strict adherence to the criteria used for selecting studies and the availability of information in each study to properly analyze their findings. Lack of information can severely limit the type of analyzes and conclusions that can be reached. In addition, the more dissimilarity there is in the results among individual studies [heterogeneity], the more difficult it is to justify interpretations that govern a valid synopsis of results. A meta-analysis needs to fulfill the following requirements to ensure the validity of your findings:

• Clearly defined description of objectives, including precise definitions of the variables and outcomes that are being evaluated;
• A well-reasoned and well-documented justification for identification and selection of the studies;
• Assessment and explicit acknowledgment of any researcher bias in the identification and selection of those studies;
• Description and evaluation of the degree of heterogeneity among the sample size of studies reviewed; and,
• Justification of the techniques used to evaluate the studies.
• Can be an effective strategy for determining gaps in the literature.
• Provides a means of reviewing research published about a particular topic over an extended period of time and from a variety of sources.
• Is useful in clarifying what policy or programmatic actions can be justified on the basis of analyzing research results from multiple studies.
• Provides a method for overcoming small sample sizes in individual studies that previously may have had little relationship to each other.
• Can be used to generate new hypotheses or highlight research problems for future studies.
• Small violations in defining the criteria used for content analysis can lead to difficult to interpret and/or meaningless findings.
• A large sample size can yield reliable, but not necessarily valid, results.
• A lack of uniformity regarding, for example, the type of literature reviewed, how methods are applied, and how findings are measured within the sample of studies you are analyzing, can make the process of synthesis difficult to perform.
• Depending on the sample size, the process of reviewing and synthesizing multiple studies can be very time consuming.

Beck, Lewis W. "The Synoptic Method." The Journal of Philosophy 36 (1939): 337-345; Cooper, Harris, Larry V. Hedges, and Jeffrey C. Valentine, eds. The Handbook of Research Synthesis and Meta-Analysis . 2nd edition. New York: Russell Sage Foundation, 2009; Guzzo, Richard A., Susan E. Jackson and Raymond A. Katzell. “Meta-Analysis Analysis.” In Research in Organizational Behavior , Volume 9. (Greenwich, CT: JAI Press, 1987), pp 407-442; Lipsey, Mark W. and David B. Wilson. Practical Meta-Analysis . Thousand Oaks, CA: Sage Publications, 2001; Study Design 101. Meta-Analysis. The Himmelfarb Health Sciences Library, George Washington University; Timulak, Ladislav. “Qualitative Meta-Analysis.” In The SAGE Handbook of Qualitative Data Analysis . Uwe Flick, editor. (Los Angeles, CA: Sage, 2013), pp. 481-495; Walker, Esteban, Adrian V. Hernandez, and Micheal W. Kattan. "Meta-Analysis: It's Strengths and Limitations." Cleveland Clinic Journal of Medicine 75 (June 2008): 431-439.

Mixed-Method Design

• Narrative and non-textual information can add meaning to numeric data, while numeric data can add precision to narrative and non-textual information.
• Can utilize existing data while at the same time generating and testing a grounded theory approach to describe and explain the phenomenon under study.
• A broader, more complex research problem can be investigated because the researcher is not constrained by using only one method.
• The strengths of one method can be used to overcome the inherent weaknesses of another method.
• Can provide stronger, more robust evidence to support a conclusion or set of recommendations.
• May generate new knowledge new insights or uncover hidden insights, patterns, or relationships that a single methodological approach might not reveal.
• Produces more complete knowledge and understanding of the research problem that can be used to increase the generalizability of findings applied to theory or practice.
• A researcher must be proficient in understanding how to apply multiple methods to investigating a research problem as well as be proficient in optimizing how to design a study that coherently melds them together.
• Can increase the likelihood of conflicting results or ambiguous findings that inhibit drawing a valid conclusion or setting forth a recommended course of action [e.g., sample interview responses do not support existing statistical data].
• Because the research design can be very complex, reporting the findings requires a well-organized narrative, clear writing style, and precise word choice.
• Design invites collaboration among experts. However, merging different investigative approaches and writing styles requires more attention to the overall research process than studies conducted using only one methodological paradigm.
• Concurrent merging of quantitative and qualitative research requires greater attention to having adequate sample sizes, using comparable samples, and applying a consistent unit of analysis. For sequential designs where one phase of qualitative research builds on the quantitative phase or vice versa, decisions about what results from the first phase to use in the next phase, the choice of samples and estimating reasonable sample sizes for both phases, and the interpretation of results from both phases can be difficult.
• Due to multiple forms of data being collected and analyzed, this design requires extensive time and resources to carry out the multiple steps involved in data gathering and interpretation.

Burch, Patricia and Carolyn J. Heinrich. Mixed Methods for Policy Research and Program Evaluation . Thousand Oaks, CA: Sage, 2016; Creswell, John w. et al. Best Practices for Mixed Methods Research in the Health Sciences . Bethesda, MD: Office of Behavioral and Social Sciences Research, National Institutes of Health, 2010Creswell, John W. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 4th edition. Thousand Oaks, CA: Sage Publications, 2014; Domínguez, Silvia, editor. Mixed Methods Social Networks Research . Cambridge, UK: Cambridge University Press, 2014; Hesse-Biber, Sharlene Nagy. Mixed Methods Research: Merging Theory with Practice . New York: Guilford Press, 2010; Niglas, Katrin. “How the Novice Researcher Can Make Sense of Mixed Methods Designs.” International Journal of Multiple Research Approaches 3 (2009): 34-46; Onwuegbuzie, Anthony J. and Nancy L. Leech. “Linking Research Questions to Mixed Methods Data Analysis Procedures.” The Qualitative Report 11 (September 2006): 474-498; Tashakorri, Abbas and John W. Creswell. “The New Era of Mixed Methods.” Journal of Mixed Methods Research 1 (January 2007): 3-7; Zhanga, Wanqing. “Mixed Methods Application in Health Intervention Research: A Multiple Case Study.” International Journal of Multiple Research Approaches 8 (2014): 24-35 .

Observational Design

This type of research design draws a conclusion by comparing subjects against a control group, in cases where the researcher has no control over the experiment. There are two general types of observational designs. In direct observations, people know that you are watching them. Unobtrusive measures involve any method for studying behavior where individuals do not know they are being observed. An observational study allows a useful insight into a phenomenon and avoids the ethical and practical difficulties of setting up a large and cumbersome research project.

• Observational studies are usually flexible and do not necessarily need to be structured around a hypothesis about what you expect to observe [data is emergent rather than pre-existing].
• The researcher is able to collect in-depth information about a particular behavior.
• Can reveal interrelationships among multifaceted dimensions of group interactions.
• You can generalize your results to real life situations.
• Observational research is useful for discovering what variables may be important before applying other methods like experiments.
• Observation research designs account for the complexity of group behaviors.
• Reliability of data is low because seeing behaviors occur over and over again may be a time consuming task and are difficult to replicate.
• In observational research, findings may only reflect a unique sample population and, thus, cannot be generalized to other groups.
• There can be problems with bias as the researcher may only "see what they want to see."
• There is no possibility to determine "cause and effect" relationships since nothing is manipulated.
• Sources or subjects may not all be equally credible.
• Any group that is knowingly studied is altered to some degree by the presence of the researcher, therefore, potentially skewing any data collected.

Atkinson, Paul and Martyn Hammersley. “Ethnography and Participant Observation.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 248-261; Observational Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Patton Michael Quinn. Qualitiative Research and Evaluation Methods . Chapter 6, Fieldwork Strategies and Observational Methods. 3rd ed. Thousand Oaks, CA: Sage, 2002; Payne, Geoff and Judy Payne. "Observation." In Key Concepts in Social Research . The SAGE Key Concepts series. (London, England: Sage, 2004), pp. 158-162; Rosenbaum, Paul R. Design of Observational Studies . New York: Springer, 2010;Williams, J. Patrick. "Nonparticipant Observation." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor.(Thousand Oaks, CA: Sage, 2008), pp. 562-563.

Philosophical Design

Understood more as an broad approach to examining a research problem than a methodological design, philosophical analysis and argumentation is intended to challenge deeply embedded, often intractable, assumptions underpinning an area of study. This approach uses the tools of argumentation derived from philosophical traditions, concepts, models, and theories to critically explore and challenge, for example, the relevance of logic and evidence in academic debates, to analyze arguments about fundamental issues, or to discuss the root of existing discourse about a research problem. These overarching tools of analysis can be framed in three ways:

• Ontology -- the study that describes the nature of reality; for example, what is real and what is not, what is fundamental and what is derivative?
• Epistemology -- the study that explores the nature of knowledge; for example, by what means does knowledge and understanding depend upon and how can we be certain of what we know?
• Axiology -- the study of values; for example, what values does an individual or group hold and why? How are values related to interest, desire, will, experience, and means-to-end? And, what is the difference between a matter of fact and a matter of value?
• Can provide a basis for applying ethical decision-making to practice.
• Functions as a means of gaining greater self-understanding and self-knowledge about the purposes of research.
• Brings clarity to general guiding practices and principles of an individual or group.
• Philosophy informs methodology.
• Refine concepts and theories that are invoked in relatively unreflective modes of thought and discourse.
• Beyond methodology, philosophy also informs critical thinking about epistemology and the structure of reality (metaphysics).
• Offers clarity and definition to the practical and theoretical uses of terms, concepts, and ideas.
• Limited application to specific research problems [answering the "So What?" question in social science research].
• Analysis can be abstract, argumentative, and limited in its practical application to real-life issues.
• While a philosophical analysis may render problematic that which was once simple or taken-for-granted, the writing can be dense and subject to unnecessary jargon, overstatement, and/or excessive quotation and documentation.
• There are limitations in the use of metaphor as a vehicle of philosophical analysis.
• There can be analytical difficulties in moving from philosophy to advocacy and between abstract thought and application to the phenomenal world.

Burton, Dawn. "Part I, Philosophy of the Social Sciences." In Research Training for Social Scientists . (London, England: Sage, 2000), pp. 1-5; Chapter 4, Research Methodology and Design. Unisa Institutional Repository (UnisaIR), University of South Africa; Jarvie, Ian C., and Jesús Zamora-Bonilla, editors. The SAGE Handbook of the Philosophy of Social Sciences . London: Sage, 2011; Labaree, Robert V. and Ross Scimeca. “The Philosophical Problem of Truth in Librarianship.” The Library Quarterly 78 (January 2008): 43-70; Maykut, Pamela S. Beginning Qualitative Research: A Philosophic and Practical Guide . Washington, DC: Falmer Press, 1994; McLaughlin, Hugh. "The Philosophy of Social Research." In Understanding Social Work Research . 2nd edition. (London: SAGE Publications Ltd., 2012), pp. 24-47; Stanford Encyclopedia of Philosophy . Metaphysics Research Lab, CSLI, Stanford University, 2013.

Sequential Design

• The researcher has a limitless option when it comes to sample size and the sampling schedule.
• Due to the repetitive nature of this research design, minor changes and adjustments can be done during the initial parts of the study to correct and hone the research method.
• This is a useful design for exploratory studies.
• There is very little effort on the part of the researcher when performing this technique. It is generally not expensive, time consuming, or workforce intensive.
• Because the study is conducted serially, the results of one sample are known before the next sample is taken and analyzed. This provides opportunities for continuous improvement of sampling and methods of analysis.
• The sampling method is not representative of the entire population. The only possibility of approaching representativeness is when the researcher chooses to use a very large sample size significant enough to represent a significant portion of the entire population. In this case, moving on to study a second or more specific sample can be difficult.
• The design cannot be used to create conclusions and interpretations that pertain to an entire population because the sampling technique is not randomized. Generalizability from findings is, therefore, limited.
• Difficult to account for and interpret variation from one sample to another over time, particularly when using qualitative methods of data collection.

Betensky, Rebecca. Harvard University, Course Lecture Note slides; Bovaird, James A. and Kevin A. Kupzyk. "Sequential Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 1347-1352; Cresswell, John W. Et al. “Advanced Mixed-Methods Research Designs.” In Handbook of Mixed Methods in Social and Behavioral Research . Abbas Tashakkori and Charles Teddle, eds. (Thousand Oaks, CA: Sage, 2003), pp. 209-240; Henry, Gary T. "Sequential Sampling." In The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman and Tim Futing Liao, editors. (Thousand Oaks, CA: Sage, 2004), pp. 1027-1028; Nataliya V. Ivankova. “Using Mixed-Methods Sequential Explanatory Design: From Theory to Practice.” Field Methods 18 (February 2006): 3-20; Bovaird, James A. and Kevin A. Kupzyk. “Sequential Design.” In Encyclopedia of Research Design . Neil J. Salkind, ed. Thousand Oaks, CA: Sage, 2010; Sequential Analysis. Wikipedia.

Systematic Review

• A systematic review synthesizes the findings of multiple studies related to each other by incorporating strategies of analysis and interpretation intended to reduce biases and random errors.
• The application of critical exploration, evaluation, and synthesis methods separates insignificant, unsound, or redundant research from the most salient and relevant studies worthy of reflection.
• They can be use to identify, justify, and refine hypotheses, recognize and avoid hidden problems in prior studies, and explain data inconsistencies and conflicts in data.
• Systematic reviews can be used to help policy makers formulate evidence-based guidelines and regulations.
• The use of strict, explicit, and pre-determined methods of synthesis, when applied appropriately, provide reliable estimates about the effects of interventions, evaluations, and effects related to the overarching research problem investigated by each study under review.
• Systematic reviews illuminate where knowledge or thorough understanding of a research problem is lacking and, therefore, can then be used to guide future research.
• The accepted inclusion of unpublished studies [i.e., grey literature] ensures the broadest possible way to analyze and interpret research on a topic.
• Results of the synthesis can be generalized and the findings extrapolated into the general population with more validity than most other types of studies .
• Systematic reviews do not create new knowledge per se; they are a method for synthesizing existing studies about a research problem in order to gain new insights and determine gaps in the literature.
• The way researchers have carried out their investigations [e.g., the period of time covered, number of participants, sources of data analyzed, etc.] can make it difficult to effectively synthesize studies.
• The inclusion of unpublished studies can introduce bias into the review because they may not have undergone a rigorous peer-review process prior to publication. Examples may include conference presentations or proceedings, publications from government agencies, white papers, working papers, and internal documents from organizations, and doctoral dissertations and Master's theses.

Denyer, David and David Tranfield. "Producing a Systematic Review." In The Sage Handbook of Organizational Research Methods .  David A. Buchanan and Alan Bryman, editors. ( Thousand Oaks, CA: Sage Publications, 2009), pp. 671-689; Foster, Margaret J. and Sarah T. Jewell, editors. Assembling the Pieces of a Systematic Review: A Guide for Librarians . Lanham, MD: Rowman and Littlefield, 2017; Gough, David, Sandy Oliver, James Thomas, editors. Introduction to Systematic Reviews . 2nd edition. Los Angeles, CA: Sage Publications, 2017; Gopalakrishnan, S. and P. Ganeshkumar. “Systematic Reviews and Meta-analysis: Understanding the Best Evidence in Primary Healthcare.” Journal of Family Medicine and Primary Care 2 (2013): 9-14; Gough, David, James Thomas, and Sandy Oliver. "Clarifying Differences between Review Designs and Methods." Systematic Reviews 1 (2012): 1-9; Khan, Khalid S., Regina Kunz, Jos Kleijnen, and Gerd Antes. “Five Steps to Conducting a Systematic Review.” Journal of the Royal Society of Medicine 96 (2003): 118-121; Mulrow, C. D. “Systematic Reviews: Rationale for Systematic Reviews.” BMJ 309:597 (September 1994); O'Dwyer, Linda C., and Q. Eileen Wafford. "Addressing Challenges with Systematic Review Teams through Effective Communication: A Case Report." Journal of the Medical Library Association 109 (October 2021): 643-647; Okoli, Chitu, and Kira Schabram. "A Guide to Conducting a Systematic Literature Review of Information Systems Research."  Sprouts: Working Papers on Information Systems 10 (2010); Siddaway, Andy P., Alex M. Wood, and Larry V. Hedges. "How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-analyses, and Meta-syntheses." Annual Review of Psychology 70 (2019): 747-770; Torgerson, Carole J. “Publication Bias: The Achilles’ Heel of Systematic Reviews?” British Journal of Educational Studies 54 (March 2006): 89-102; Torgerson, Carole. Systematic Reviews . New York: Continuum, 2003.

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• What Is a Research Methodology? | Steps & Tips

What Is a Research Methodology? | Steps & Tips

Published on August 25, 2022 by Shona McCombes and Tegan George. Revised on November 20, 2023.

Your research methodology discusses and explains the data collection and analysis methods you used in your research. A key part of your thesis, dissertation , or research paper , the methodology chapter explains what you did and how you did it, allowing readers to evaluate the reliability and validity of your research and your dissertation topic .

It should include:

• The type of research you conducted
• How you collected and analyzed your data
• Any tools or materials you used in the research
• How you mitigated or avoided research biases
• Why you chose these methods
• Your methodology section should generally be written in the past tense .
• Academic style guides in your field may provide detailed guidelines on what to include for different types of studies.
• Your citation style might provide guidelines for your methodology section (e.g., an APA Style methods section ).

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Table of contents

How to write a research methodology, why is a methods section important, step 1: explain your methodological approach, step 2: describe your data collection methods, step 3: describe your analysis method, step 4: evaluate and justify the methodological choices you made, tips for writing a strong methodology chapter, other interesting articles, frequently asked questions about methodology.

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Your methods section is your opportunity to share how you conducted your research and why you chose the methods you chose. It’s also the place to show that your research was rigorously conducted and can be replicated .

It gives your research legitimacy and situates it within your field, and also gives your readers a place to refer to if they have any questions or critiques in other sections.

You can start by introducing your overall approach to your research. You have two options here.

Option 1: Start with your “what”

What research problem or question did you investigate?

• Aim to describe the characteristics of something?
• Explore an under-researched topic?
• Establish a causal relationship?

And what type of data did you need to achieve this aim?

• Quantitative data , qualitative data , or a mix of both?
• Primary data collected yourself, or secondary data collected by someone else?
• Experimental data gathered by controlling and manipulating variables, or descriptive data gathered via observations?

Option 2: Start with your “why”

Depending on your discipline, you can also start with a discussion of the rationale and assumptions underpinning your methodology. In other words, why did you choose these methods for your study?

• Why is this the best way to answer your research question?
• Is this a standard methodology in your field, or does it require justification?
• Were there any ethical considerations involved in your choices?
• What are the criteria for validity and reliability in this type of research ? How did you prevent bias from affecting your data?

Once you have introduced your reader to your methodological approach, you should share full details about your data collection methods .

Quantitative methods

In order to be considered generalizable, you should describe quantitative research methods in enough detail for another researcher to replicate your study.

Here, explain how you operationalized your concepts and measured your variables. Discuss your sampling method or inclusion and exclusion criteria , as well as any tools, procedures, and materials you used to gather your data.

Surveys Describe where, when, and how the survey was conducted.

• How did you design the questionnaire?
• What form did your questions take (e.g., multiple choice, Likert scale )?
• Were your surveys conducted in-person or virtually?
• What sampling method did you use to select participants?
• What was your sample size and response rate?

Experiments Share full details of the tools, techniques, and procedures you used to conduct your experiment.

• How did you design the experiment ?
• How did you recruit participants?
• How did you manipulate and measure the variables ?
• What tools did you use?

Existing data Explain how you gathered and selected the material (such as datasets or archival data) that you used in your analysis.

• Where did you source the material?
• How was the data originally produced?
• What criteria did you use to select material (e.g., date range)?

The survey consisted of 5 multiple-choice questions and 10 questions measured on a 7-point Likert scale.

The goal was to collect survey responses from 350 customers visiting the fitness apparel company’s brick-and-mortar location in Boston on July 4–8, 2022, between 11:00 and 15:00.

Here, a customer was defined as a person who had purchased a product from the company on the day they took the survey. Participants were given 5 minutes to fill in the survey anonymously. In total, 408 customers responded, but not all surveys were fully completed. Due to this, 371 survey results were included in the analysis.

• Information bias
• Omitted variable bias
• Regression to the mean
• Survivorship bias
• Undercoverage bias
• Sampling bias

Qualitative methods

In qualitative research , methods are often more flexible and subjective. For this reason, it’s crucial to robustly explain the methodology choices you made.

Be sure to discuss the criteria you used to select your data, the context in which your research was conducted, and the role you played in collecting your data (e.g., were you an active participant, or a passive observer?)

Interviews or focus groups Describe where, when, and how the interviews were conducted.

• How did you find and select participants?
• How many participants took part?
• What form did the interviews take ( structured , semi-structured , or unstructured )?
• How long were the interviews?
• How were they recorded?

Participant observation Describe where, when, and how you conducted the observation or ethnography .

• What group or community did you observe? How long did you spend there?
• How did you gain access to this group? What role did you play in the community?
• How long did you spend conducting the research? Where was it located?
• How did you record your data (e.g., audiovisual recordings, note-taking)?

Existing data Explain how you selected case study materials for your analysis.

• What type of materials did you analyze?
• How did you select them?

In order to gain better insight into possibilities for future improvement of the fitness store’s product range, semi-structured interviews were conducted with 8 returning customers.

Here, a returning customer was defined as someone who usually bought products at least twice a week from the store.

Surveys were used to select participants. Interviews were conducted in a small office next to the cash register and lasted approximately 20 minutes each. Answers were recorded by note-taking, and seven interviews were also filmed with consent. One interviewee preferred not to be filmed.

• The Hawthorne effect
• Observer bias
• The placebo effect
• Response bias and Nonresponse bias
• The Pygmalion effect
• Recall bias
• Social desirability bias
• Self-selection bias

Mixed methods

Mixed methods research combines quantitative and qualitative approaches. If a standalone quantitative or qualitative study is insufficient to answer your research question, mixed methods may be a good fit for you.

Mixed methods are less common than standalone analyses, largely because they require a great deal of effort to pull off successfully. If you choose to pursue mixed methods, it’s especially important to robustly justify your methods.

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Next, you should indicate how you processed and analyzed your data. Avoid going into too much detail: you should not start introducing or discussing any of your results at this stage.

In quantitative research , your analysis will be based on numbers. In your methods section, you can include:

• How you prepared the data before analyzing it (e.g., checking for missing data , removing outliers , transforming variables)
• Which software you used (e.g., SPSS, Stata or R)
• Which statistical tests you used (e.g., two-tailed t test , simple linear regression )

In qualitative research, your analysis will be based on language, images, and observations (often involving some form of textual analysis ).

Specific methods might include:

• Content analysis : Categorizing and discussing the meaning of words, phrases and sentences
• Thematic analysis : Coding and closely examining the data to identify broad themes and patterns
• Discourse analysis : Studying communication and meaning in relation to their social context

Mixed methods combine the above two research methods, integrating both qualitative and quantitative approaches into one coherent analytical process.

Above all, your methodology section should clearly make the case for why you chose the methods you did. This is especially true if you did not take the most standard approach to your topic. In this case, discuss why other methods were not suitable for your objectives, and show how this approach contributes new knowledge or understanding.

In any case, it should be overwhelmingly clear to your reader that you set yourself up for success in terms of your methodology’s design. Show how your methods should lead to results that are valid and reliable, while leaving the analysis of the meaning, importance, and relevance of your results for your discussion section .

• Quantitative: Lab-based experiments cannot always accurately simulate real-life situations and behaviors, but they are effective for testing causal relationships between variables .
• Qualitative: Unstructured interviews usually produce results that cannot be generalized beyond the sample group , but they provide a more in-depth understanding of participants’ perceptions, motivations, and emotions.
• Mixed methods: Despite issues systematically comparing differing types of data, a solely quantitative study would not sufficiently incorporate the lived experience of each participant, while a solely qualitative study would be insufficiently generalizable.

Remember that your aim is not just to describe your methods, but to show how and why you applied them. Again, it’s critical to demonstrate that your research was rigorously conducted and can be replicated.

1. Focus on your objectives and research questions

The methodology section should clearly show why your methods suit your objectives and convince the reader that you chose the best possible approach to answering your problem statement and research questions .

2. Cite relevant sources

Your methodology can be strengthened by referencing existing research in your field. This can help you to:

• Show that you followed established practice for your type of research
• Discuss how you decided on your approach by evaluating existing research
• Present a novel methodological approach to address a gap in the literature

3. Write for your audience

Consider how much information you need to give, and avoid getting too lengthy. If you are using methods that are standard for your discipline, you probably don’t need to give a lot of background or justification.

Regardless, your methodology should be a clear, well-structured text that makes an argument for your approach, not just a list of technical details and procedures.

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

• Normal distribution
• Measures of central tendency
• Chi square tests
• Confidence interval
• Quartiles & Quantiles

Methodology

• Cluster sampling
• Stratified sampling
• Thematic analysis
• Cohort study
• Peer review
• Ethnography

Research bias

• Implicit bias
• Cognitive bias
• Conformity bias
• Hawthorne effect
• Availability heuristic
• Attrition bias

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

In a scientific paper, the methodology always comes after the introduction and before the results , discussion and conclusion . The same basic structure also applies to a thesis, dissertation , or research proposal .

Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.

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

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

Reliability and validity are both about how well a method measures something:

• Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
• Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

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Expert Commentary

Research strategy guide for finding quality, credible sources

Strategies for finding academic studies and other information you need to give your stories authority and depth

Republish this article

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License .

by Keely Wilczek, The Journalist's Resource May 20, 2011

This <a target="_blank" href="https://journalistsresource.org/home/research-strategy-guide/">article</a> first appeared on <a target="_blank" href="https://journalistsresource.org">The Journalist's Resource</a> and is republished here under a Creative Commons license.<img src="https://journalistsresource.org/wp-content/uploads/2020/11/cropped-jr-favicon-150x150.png" style="width:1em;height:1em;margin-left:10px;">

Knowing how to conduct deeper research efficiently and effectively is a critical skill for journalists — especially in the information age. It is, like other facets of the profession such as interviewing, a matter of practice and establishing good habits. And once you find a successful routine for information-gathering, it will pay dividends time and again.

Journalists need to be able to do many kinds of research. This article focuses on creating a research strategy that will help you find academic studies and related scholarly information. These sources can, among other things, give your stories extra authority and depth — and thereby distinguish your work. You can see examples of such studies — and find many relevant ones for your stories — by searching the Journalist’s Resource database . But that is just a representative sample of what exists in the research world.

The first step is to create a plan for seeking the information you need. This requires you to take time initially and to proceed with care, but it will ultimately pay off in better results. The research strategy covered in this article involves the following steps:

Get organized

Articulate your topic, locate background information.

• Identify your information needs

List keywords and concepts for search engines and databases

Consider the scope of your topic, conduct your searches, evaluate the information sources you found, analyze and adjust your research strategy.

Being organized is an essential part of effective research strategy. You should create a record of your strategy and your searches. This will prevent you from repeating searches in the same resources and from continuing to use ineffective terms. It will also help you assess the success or failure of your research strategy as you go through the process. You also may want to consider tracking and organizing citations and links in bibliographic software such as Zotero . (See this helpful resource guide about using Zotero.)

Next, write out your topic in a clear and concise manner. Good research starts with a specific focus.

For example, let’s say you are writing a story about the long-range health effects of the explosion at the Chernobyl Nuclear Power Plant based on a study published in Environmental Health Perspectives titled, “The Chernobyl Accident 20 Years On: An Assessment of the Health Consequences and the International Response.” (The study is summarized in Journalist’s Resource here .)

A statement of your topic might be, “Twenty years after the Chernobyl disaster, scientists are still learning the affects of the accident on the health of those who lived in the surrounding area and their descendants.”

If you have a good understanding of the Chernobyl disaster, proceed to the next step, “Identify the information you need.” If not, it’s time to gather background information. This will supply you with the whos and the whens of the topic. It will also provide you with a broader context as well as the important terminology.

Excellent sources of background information are subject-specific encyclopedias and dictionaries, books, and scholarly articles, and organizations’ websites. You should always consult more than one source so you can compare for accuracy and bias.

For your story about Chernobyl, you might want to consult some of the following sources:

• Frequently Asked Chernobyl Questions , International Atomic Agency
• Chernobyl Accident 1986 , World Nuclear Association
• Chernobyl: Consequences of the Catastrophe for People and the Environment , New York Academy of Sciences, 2009.
• “Chernobyl Disaster,” Encyclopedia Britannica, last updated 2013.

Identify the information you need

What information do you need to write your story? One way to determine this is to turn your overall topic into a list of questions to be answered. This will help you identify the type and level of information you need. Some possible questions on consequences of the Chernobyl accident are:

• What are the proven health effects?
• What are some theorized health effects?
• Is there controversy about any of these studies?
• What geographic area is being studied?
• What are the demographic characteristics of the population being studied?
• Was there anything that could have been done at the time to mitigate these effects?

Looking at these questions, it appears that scientific studies and scholarly articles about those studies, demographic data, disaster response analysis, and government documents and publications from the Soviet Union and Ukraine would be needed.

Now you need to determine what words you will use to enter in the search boxes within resources. One way to begin is to extract the most important words and phrases from the questions produced in the previous step. Next, think about alternative words and phrases that you might use. Always keep in mind that different people may write or talk about the same topic in different ways. Important concepts can referred to differently or be spelled differently depending on country of origin or field of study.

For the Chernobyl health story, some search keyword options are: “Chernobyl,” “Chornobyl”; “disaster,” “catastrophe,” “explosion”; “health,” “disease,” “illness,” “medical conditions”; “genetic mutation,” “gene mutation,” “germ-line mutation,” “hereditary disease.” Used in different combinations, these can unearth a wide variety of resources.

Next you should identify the scope of your topic and any limitations it puts on your searches. Some examples of limitations are language, publication date, and publication type. Every database and search engine will have its own rules so you may need to click on an advanced search option in order to input these limitations.

It is finally time to start looking for information but identifying which resources to use is not always easy to do. First, if you are part of an organization, find out what, if any, resources you have access to through a subscription. Examples of subscription resources are LexisNexis and JSTOR. If your organization does not provide subscription resources, find out if you can get access to these sources through your local library. Should you not have access to any subscription resources appropriate for your topic, look at some of the many useful free resources on the internet.

Here are some examples of sources for free information:

• PLoS , Public Library of Science
• Google Scholar
• SSRN , Social Science Research Network
• FDsys , U.S. Government documents and publications
• World Development Indicators , World Bank
• Pubmed , service of the U.S. National Library of Medicine

More quality sites, and search tips, are here among the other research articles at Journalist’s Resource.

As you only want information from the most reliable and suitable sources, you should always evaluate your results. In doing this, you can apply journalism’s Five W’s (and One H):

• Who : Who is the author and what are his/her credentials in this topic?
• What: Is the material primary or secondary in nature?
• Where: Is the publisher or organization behind the source considered reputable? Does the website appear legitimate?
• When: Is the source current or does it cover the right time period for your topic?
• Why: Is the opinion or bias of the author apparent and can it be taken into account?
• How: Is the source written at the right level for your needs? Is the research well-documented?

Were you able to locate the information you needed? If not, now it is time to analyze why that happened. Perhaps there are better resources or different keywords and concepts you could have tried. Additional background information might supply you with other terminology to use. It is also possible that the information you need is just not available in the way you need it and it may be necessary to consult others for assistance like an expert in the topic or a professional librarian.

Keely Wilczek is a research librarian at the Harvard Kennedy School. Tags: training

About The Author

Keely Wilczek

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• Section 4. Developing Successful Strategies: Planning to Win

Chapter 8 Sections

• Section 1. An Overview of Strategic Planning or "VMOSA" (Vision, Mission, Objectives, Strategies, and Action Plans)
• Section 2. Proclaiming Your Dream: Developing Vision and Mission Statements
• Section 3. Creating Objectives
• Section 5. Developing an Action Plan
• Section 6. Obtaining Feedback from Constituents: What Changes are Important and Feasible?
• Section 7. Identifying Action Steps in Bringing About Community and System Change
• Main Section

What is a strategy?

What are the criteria for developing a good strategy, why develop strategies, when should you develop strategies for your initiative, how do you develop strategies.

A strategy is a way of describing how you are going to get things done. It is less specific than an action plan (which tells the who-what-when); instead, it tries to broadly answer the question, "How do we get there from here?" (Do we want to take the train? Fly? Walk?)

A good strategy will take into account existing barriers and resources (people, money, power, materials, etc.). It will also stay with the overall vision, mission, and objectives of the initiative. Often, an initiative will use many different strategies--providing information, enhancing support, removing barriers, providing resources, etc.--to achieve its goals.

Objectives outline the aims of an initiative--what success would look like in achieving the vision and mission. By contrast, strategies suggest paths to take (and how to move along) on the road to success. That is, strategies help you determine how you will realize your vision and objectives through the nitty-gritty world of action.

Strategies for your community initiative should meet several criteria.

Does the strategy:

• Give overall direction ? A strategy, such as enhancing experience and skill or increasing resources and opportunities, should point out the overall path without dictating a particular narrow approach (e.g., using a specific skills training program).
• Fit resources and opportunities ? A good strategy takes advantage of current resources and assets, such as people's willingness to act or a tradition of self-help and community pride. It also embraces new opportunities such as an emerging public concern for neighborhood safety or parallel economic development efforts in the business community.
• Minimize resistance and barriers ? When initiatives set out to accomplish important things, resistance (even opposition) is inevitable. However, strategies need not provide a reason for opponents to attack the initiative. Good strategies attract allies and deter opponents.
• Reach those affected ? To address the issue or problem, strategies must connect the intervention with those who it should benefit. For example, if the mission of the initiative is to get people into decent jobs, do the strategies (providing education and skills training, creating job opportunities, etc.) reach those currently unemployed?
• Advance the mission ? Taken together, are strategies likely to make a difference on the mission and objectives? If the aim is to reduce a problem such as unemployment, are the strategies enough to make a difference on rates of employment? If the aim is to prevent a problem, such as substance use, have factors contributing to risk (and protection) been changed sufficiently to reduce use of alcohol, tobacco, and other drugs?

Developing strategies is really a way to focus your efforts and figure out how you're going to get things done. By doing so, you can achieve the following advantages:

• Taking advantage of resources and emerging opportunities
• Responding effectively to resistance and barriers
• A more efficient use of time, energy, and resources

Developing strategies is the fourth step in the VMOSA (Vision, Mission, Objectives, Strategies, and Action Plans) process outlined at the beginning of this chapter. Developing strategies is the essential step between figuring out your objectives and making the changes to reach them. Strategies should always be formed in advance of taking action, not deciding how to do something after you have done it. Without a clear idea of the how, your group's actions may waste time and effort and fail to take advantage of emerging opportunities. Strategies should also be updated periodically to meet the needs of a changing environment, including new opportunities and emerging opposition to the group's efforts.

Once again, let's refer back to our friends at the fictional Reducing the Risk (RTR) Coalition that hopes to reduce the risk of teenage pregnancy in its community. We'll walk through the process of developing strategies with this group so as to better explain the who, what, and why of strategies.

As with the process you went through to write your vision and mission statements and to set your objectives, developing strategies involves brainstorming and talking to community members.

Organize a brainstorming meeting with members of your organization and members of the community

Remember, people will work best in a relaxed and welcoming environment. You can help achieve this by:

• One person speaks at a time
• No interrupting each other
• Everyone's ideas are respected
• Bringing fans or heaters (if needed) so people will be comfortable.
• Asking members to escort each other home or to their cars, the subway, or the bus stop if the meeting runs late.
• Providing refreshments. Never underestimate the power of homemade food, drinks, and other treats.

The RTR Coalition held brainstorming sessions among organization members. They invited local teens, parents, teachers, counselors, church members, and other community leaders to participate in listening sessions. These were used to help develop strategies to reduce the risk of teen pregnancy. Homemade cookies, fruit, and coffee helped make participants feel welcome.

Review (identify) the targets and agents of change for your initiative

• Your targets of change include all of the people who experience (or are at risk for) this issue or problem addressed by your initiative. Remember to be inclusive; that is, include everyone who is affected by the problem or issue or whose action or inaction contributes to it. For example, a coalition such the RTR Coalition would want to include all teenagers as potential targets of change, not just adolescents who seem particularly at risk, and parents, peers, and teachers whose actions or inactions might make a difference.
• Your agents of change include everyone who is in a position to help contribute to the solution. With the RTR Coalition, examples of agents of change might include teens, teachers, guidance counselors, parents of teens, lawmakers, and others.

Review your vision, mission, and objectives to keep you on the right track

It is helpful to review your mission, vision, and objectives to ensure that your strategies are all aligned with the goals expressed in your previous work.

Work together to brainstorm the best strategies for your initiative

The following list of questions can be a guide for deciding on the most beneficial strategies for your group:

• What resources and assets exist that can be used to help achieve the vision and mission? How can they be used best?
• What obstacles or resistance exist that could make it difficult to achieve your vision and mission? How can you minimize or get around them?
• What are potential agents of change willing to do to serve the mission?
• Do you want to reduce the existing problem, or does it make more sense to try to prevent (or reduce risk for) problems before they start? For example, if you are trying to reduce teen sexual activity, you might consider gearing some of your strategies to younger children, for whom sex is not yet a personal issue; or, to promote academic success, to work with younger children who still have full potential for learning and school success.
• How will your potential strategies decrease the risk for experiencing the problem (e.g., young girls getting pressure for sex from older men)? How will the strategies increase protective factors (e.g., support from peers; access to contraceptives)?
• What potential strategies will affect the whole population and problem? For example, connecting youth with caring adults might be good for virtually all youth, regardless of income or past experience with the problem. Also, just one strategy, affecting just one part of the community such as schools or youth organizations, often isn't enough to improve the situation. Make sure that your strategies affect the problem or issue as a whole.
• What potential strategies reach those at particular risk for the problem? For example, early screenings might help focus on those at higher risk for heart disease or cancer; past academic failure or history of drug use, for identifying with whom support and other intervention efforts might be focused.

Let's look at the strategies proposed by the members of the RTR Coalition to prevent teen pregnancy.

Example: The strategies of the RTR Coalition We will pursue the following strategies to reach each of our objectives: Assist local churches in implementing parent-child awareness sessions (for example, a series of talks might be given discussing how to talk to your preteen about sex); Include comprehensive sex education in the curriculum of students from kindergarten through grade twelve, including information on abstinence, sexual decision-making skills, and family planning / contraception at age-appropriate times; Incorporate options for teacher-led and peer support programs in the schools; Survey and report on student knowledge, attitudes, and behavior related to sexual issues; Increase access to contraception; Organize a school/community action group to create supervised after-school activities, mentor programs, etc.

Things to note about the RTR strategies:

• They give overall direction (without dictating specifics, such as the particular sexuality education curricula to be used).
• They fit local resources, including a variety of the available agents of change (in this case, peers, parents and guardians, clergy, and teachers).
• Some of the strategies try to change existing situations (such as increased access to contraception); others are geared to stop the problem of teen pregnancy before it starts (for example, assisting local churches to improve early parent-child communication).
• The strategies involve many different parts of the community, including churches and other groups from whom opposition to some strategies (such as access to contraceptives) might be expected.
• The strategies try to decrease some of the probable risk factors for teen pregnancy (lack of information, lack of access to contraceptives, peer pressure), and at the same time, they try to increase some of the possible protective factors (increased parent-child communication, church involvement, education, opportunities for a better future).

Check your proposed strategies for completeness, accuracy, and whether they contribute to the vision, mission, and objectives

Online Resource

Tom Wolff / AHEC/Community Partners. (1993).  Coalition building tip sheets [Resource Sheets]. Amherst, MA

Concerns Report Handbook: Planning for Community Health

Preventing Adolescent Pregnancy: An Action Planning Guide for Community-Based Initiatives

Preventing Adolescent Substance Abuse: An Action Planning Guide for Community-Based Initiatives

Preventing Child Abuse and Neglect: An Action Planning Guide for Community-Based Initiatives

Preventing Youth Violence: An Action Planning Guide for Community-Based Initiatives

Promoting Child Well-Being: An Action Planning Guide for Community-Based Initiatives

Promoting Health for All: Improving Access and Eliminating Disparities in Community Health

Promoting Healthy Living and Preventing Chronic Disease: An Action Planning Guide for Communities

Promoting Urban Neighborhood Development: An Action Planning Guide for Improving Housing, Jobs, Education, Safety and Health

Reducing Risk for Chronic Disease: An Action Planning Guide for Community-Based Initiatives

Work Group Evaluation Handbook

Youth Development: An Action Planning Guide for Community-Based Initiatives

Print Resources

Berkowitz, W. (1982).  Community impact: creating grassroots change in hard times . Cambridge: Schenkman.

Brown, C. (1984).  The art of coalition building: a guide for community leaders . The American Jewish Committee.

Fawcett, S., Francisco, V., Paine, A., Fisher, J., Lewis, R., Williams, E., Richter, K.., Harris, K.., & Berkley, J., with assistance from Oxley, L., Graham, A., & Amawi, L. (1994).  Preventing youth violence: an action planning guide . Lawrence, KS: Work Group on Health Promotion and Community Development, University of Kansas.

Fawcett, S.., Harris, K., Paine- A., Richter, K., Lewis, R., Francisco, V., Arbaje, A., Davis, A., Cheng, H. in collaboration with Johnston, J. (1995).  Reducing risk for chronic disease: an action planning guide for community-based initiatives . Lawrence, KS: Work Group on Health Promotion and Community Development, University of Kansas.

Hawkins, J., & Catalano, R., et al. (1992).  Communities that care . San Francisco, CA.

National Highway Traffic Safety Administration (1996).  Strategic execution plan  (DOT HS 808-377).

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Strategies for effective dissemination of research to United States policymakers: a systematic review

Laura ellen ashcraft.

1 University of Pittsburgh School of Social Work, 2117 Cathedral of Learning, 4200 Fifth Avenue, Pittsburgh, PA 15260 USA

Deirdre A. Quinn

2 Center for Health Equity Research and Promotion (CHERP), VA Pittsburgh Healthcare System, University Drive C, Building 30, Pittsburgh, PA 15240 USA

Ross C. Brownson

3 Prevention Research Center, Brown School, Washington University in St. Louis, One Brookings Drive, Campus Box 1196, St. Louis, MO 63130 USA

4 Department of Surgery, Division of Public Health Sciences, and Alvin J. Siteman Cancer Center, Washington University School of Medicine, 660 South Euclid Avenue, Saint Louis, MO 63110 USA

Associated Data

Raw search results, citations, and abstracts available upon request.

Research has the potential to influence US social policy; however, existing research in this area lacks a coherent message. The Model for Dissemination of Research provides a framework through which to synthesize lessons learned from research to date on the process of translating research to US policymakers.

The peer-reviewed and grey literature was systematically reviewed to understand common strategies for disseminating social policy research to policymakers in the United States. We searched Academic Search Premier, PolicyFile, SocINDEX, Social Work Abstracts, and Web of Science from January 1980 through December 2019. Articles were independently reviewed and thematically analyzed by two investigators and organized using the Model for Dissemination of Research.

The search resulted in 5225 titles and abstracts for inclusion consideration. 303 full-text articles were reviewed with 27 meeting inclusion criteria. Common sources of research dissemination included government, academic researchers, the peer reviewed literature, and independent organizations. The most frequently disseminated research topics were health-related, and legislators and executive branch administrators were the most common target audience. Print materials and personal communication were the most common channels for disseminating research to policymakers. There was variation in dissemination channels by level of government (e.g., a more formal legislative process at the federal level compared with other levesl). Findings from this work suggest that dissemination is most effective when it starts early, galvanizes support, uses champions and brokers, considers contextual factors, is timely, relevant, and accessible, and knows the players and process.

Conclusions

Effective dissemination of research to US policymakers exists; yet, rigorous quantitative evaluation is rare. A number of cross-cutting strategies appear to enhance the translation of research evidence into policy.

Registration

Not registered.

Contributions to the literature

• This is one of the first systematic reviews to synthesize how social policy research evidence is disseminated to US policymakers.
• Print materials and personal communications were the most commonly used channels to disseminate social policy research to policymakers.
• Several cross-cutting strategies (e.g., start early, use evidence “champions,” make research products more timely, relevant, and accessible) were identified that are likely to lead to more effective translate of research evidence into the policy making process in the United States.

In recent years, social scientists have sought to understand how research may influence policy [ 1 , 2 ]. Interest in this area of investigation has grown with the increased availability of funding for policy-specific research (e.g., dissemination and implementation research) [ 3 ]. However, because of variation in the content of public policy, this emerging area of scholarship lacks a coherent message that specifically addresses social policy in the United States (US). While other studies have examined the use of evidence in policymaking globally [ 4 – 7 ], the current review focuses on US social policy; for the purposes of this study, social policy includes policies which focus on antipoverty, economic security, health, education, and social services [ 8 – 10 ].

Significant international research exists on barriers and facilitators to the dissemination and use of research evidence by policymakers [ 4 , 5 ]. Common themes include the importance of personal relationships, the timeliness of evidence, and resource availability [ 4 , 5 ]. Previous work demonstrates the importance of understanding policymakers’ perceptions and how evidence is disseminated. The current review builds on this existing knowledge to examine how research evidence reaches policymakers and to understand what strategies are likely to be effective in overcoming identified barriers.

Theoretical frameworks offer a necessary foundation to identify and assess strategies for disseminating research to policymakers. The Model for Dissemination of Research integrates Diffusion of Innovations Theory and Social Marketing Theory with the Mathematical Theory of Communication [ 11 , 12 ] and the Matrix of Persuasive Communication [ 13 , 14 ] to address the translation gap between research and policy. The purpose of the Model for Dissemination of Research is to highlight the gaps between research and targets audiences (e.g., policymakers) and improve dissemination through the use of a theoretical foundation and review of the literature [ 15 ]. Diffusion of Innovations Theory describes the spread and adoption of novel interventions through an “s-curve,” ordered process, and characteristics of the message and audience [ 16 ]. Additional theoretical contributions for dissemination research come from Social Marketing Theory, which postulates commercial marketing strategies summarized by the four P’s (produce, price, place, and promotion) and the understanding that communication of the message alone will not change behavior [ 17 ].

The Model for Dissemination of Research includes the four key components described by Shannon and Weaver [ 11 , 12 ] and later McGuire [ 13 , 14 ] of the research translation process: the source, message, audience, and channel (Fig. ​ (Fig.1). 1 ). The source includes researchers who generate evidence. The message includes relevant information sent by the source on a policy topic. The audience includes those receiving the message via the channel [ 15 ]. The channel is how the message gets from the source to the audience [ 15 ].

The Model for Dissemination of Research. The Model for Dissemination of Research integrates Diffusion of Innovations Theory, the Mathematical Theory of Communication, and Social Marketing Theory to develop a framework for conceptualizing how information moves from source to audience. Originally published by Brownson et al. in Journal of public health management and practice in 2018

While the Model for Dissemination of Research and its origins (i.e., the Mathematical Theory of Communication and Diffusion of Innovations Theory) appear linear in their presentation, Shannon and Weaver [ 11 , 12 ] and Rogers [ 16 ] clearly acknowledge that the dissemination of information is not a linear process and is effected by the environment within which it occurs. This approach aligns with the system model or knowledge to action approach proposed by Best and Holmes [ 18 ]. The systems model accounts for influence of the environment on a process and accounts for the complexity of the system [ 18 ]. Therefore, while some theoretical depictions appear linear in their presentation; it is important to acknowledge the critical role of systems thinking.

To date, lessons learned from dissemination and implementation science about the ways in which research influences policy are scattered across diverse disciplines and bodies of literature. These disparate lessons highlight the critical need to integrate knowledge across disciplines. The current study aims to make sense of and distill these lessons by conducting a systematic review of scientific literature on the role of research in shaping social policy in the United States. The results of this systematic review are synthesized in a preliminary conceptual model (organized around the Model for Dissemination of Research) with the goal of improving dissemination strategies for the translation of scientific research to policymakers and guiding future research in this area.

This systematic review aims to synthesize existing evidence about how research has been used to influence social policy and is guided by the following research questions:

• What are common strategies for using research to influence social policy in the United States?
• What is the effectiveness of these strategies?

We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-P) model [ 19 , 20 ] to examine and distill existing studies on strategies for using research evidence to influence social policy.

Eligibility criteria

Studies were eligible for this review if they met the following inclusion criteria: (1) occurred in the United States; (2) reported in English; (3) systematically evaluated the impact of research on social policy (this typically excluded studies focusing on policymaker dissemination preferences); (4) discussed domestic social policy (as defined above); and (5) were published in the peer reviewed literature or the grey literature (e.g., think tank research briefs, foundation research publications).

We chose to focus our review on the United States to capture the strengths and challenges of its unique, multi-level policy and political environment. The de-centralized structure of government in the United States allows significant decision-making authority at the state and local levels, with wide variation in capacity and the availability of resources across the country [ 21 ]. For example, some states have full-time legislatures while other states have part-time legislatures. In total, these factors create a fitting and complex environment to examine the dissemination of research to policymakers. The influence of lobbying in the United States also differs from other western countries. In the United States, there is more likely to be a “winner-take-all” process where some advocates (often corporations and trade associations) have disproportionate influence [ 22 ]. In addition, the role of evidence differs in the US compared with other countries, where the US tends to take a narrower focus on intervention impact with less emphasis on system-level issues (e.g., implementation, cost) [ 23 ].

Studies were excluded if they were not in English or occurred outside of the United States. We also excluded non-research sources, such as editorials, opinion pieces, and narrative stories that contain descriptions of dissemination strategies without systematic evaluation. Further, studies were excluded if the results focused on practitioners (e.g., case managers, local health department workers) and/or if results for practitioners could not be parsed from results for policymakers.

To identify studies that systematically evaluated the impact of research on social policy, we reviewed the research questions and results of each study to determine whether or not they examined how research evidence reaches policymakers (as opposed to policymaker preferences for disseminated research). For example, we would not include a research study that only describes different types of policy briefs, without also evaluating how the briefs are used by policymakers to inform policy decisions. We used the Model for Dissemination of Research, as defined above, to see if and how the studies describe and test the channels of dissemination. We built on the Model of Dissemination by also considering passive forms of knowledge, such as peer-reviewed literature or research briefs, as potential sources of knowledge and not just as channels in and of themselves.

Information sources

We took a three-pronged approach to develop a comprehensive understanding of existing knowledge in this area. First, we searched the peer reviewed literature using the following databases: Academic Search Premier, PolicyFile, SocINDEX, Social Work Abstracts, and Web of Science. We expanded the inquiry for evidence by searching the grey literature through PolicyFile, and included recommendations from experts in the field of dissemination of research evidence to policymakers resulting in 137 recommended publications.

Search strategy

Our search strategy included the following terms: [research OR study OR studies OR knowledge] AND [policy OR policies OR law OR laws OR legislation] AND [use OR utilization OR utilisation] OR [disseminate OR dissemination OR disseminating] OR [implementation OR implementing OR implement] OR [translate OR translation OR translating]. Our search was limited to studies in the United States between 1980 and 2019. We selected this timeframe based on historical context: the 1950s through the 1970s saw the development of the modern welfare state, which was (relatively) complete by 1980. However, shifting political agendas in the 1980s saw the demand for evidence increase to provide support for social programs [ 24 ]; we hoped to capture this increase in evidence use in policy.

Selection process

All titles and abstracts were screened by the principal investigator (LEA) with 20% reviewed at random by a co-investigator (DAQ) with total agreement post-training. Studies remaining after abstract screening moved to full text review. The full text of each study was considered for inclusion (LEA and DAQ) with conflicts resolved by consensus. The data abstraction form was developed by the principal investigator (LEA) based on previous research [ 25 , 26 ] and with feedback from co-authors. Data were independently abstracted from each reference in duplicate with conflicts resolved by consensus (LEA and DAQ). We completed reliability checks on 20% of the final studies, selected at random, to ensure accurate data abstraction.

Data synthesis

Abstracted data was qualitatively analyzed using thematic analysis (LEA and DAQ) and guided by the Model for Dissemination of Research. The goal of the preliminary conceptual model was to synthesize components of dissemination for studies that evaluate the dissemination of social policy to policymakers.

Descriptive results

The search of the literature resulted in 5675 articles and 137 articles recommended by content experts for review with 5225 titles and abstracts screened after duplicates removed. Of those articles, 4922 were excluded due to not meeting inclusion criteria. Further, 303 full text articles were reviewed with 276 excluded as they did not meet inclusion criteria. Twenty-seven articles met inclusion criteria (see the Fig. ​ Fig.2 2 for the PRISMA flow diagram).

PRISMA flowchart. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram reports included and excluded articles in the systematic review

Included studies are listed in Table ​ Table1. 1 . The 27 included 6 studies using quantitative methods, 18 that employed qualitative methods, and 3 that used a mixed methods approach. The qualitative studies mostly employed interviews ( n = 10), while others used case studies ( n = 6) or focus groups ( n = 3). Most studies examined state-level policy ( n = 18) and nine studies examined federal-level policy, with some studies looking at multiple levels of government. Included studies focused on the executive and legislative branches with no studies examining the judicial branch.

Included studies

We examined dissemination based on geographic regions and/or political boundaries (i.e., regions or states). Sixteen of the 27 studies (about 59%) used national samples or multiple states and did not provide geographic-specific results [ 27 – 42 ]. Two studies (about 7%) did not specific the geographic region or state in which the study took place [ 43 , 44 ]. Of the remaining studies, four examined policymaking in the Northeastern United States [ 45 – 48 ], four in the Western US [ 49 – 52 ], and one in the South [ 53 ]. The geographic regional groups used similar channels to disseminate evidence to policymakers including publications and presentations.

We also analyzed whether dissemination at different levels of government (i.e., local, state, and federal) used unique channels. Six of included studies (about 22%) examined multiple levels of government and did not separate results based on specific levels of government [ 27 – 31 , 53 ]. One study did not specifically identify the level of government used [ 46 ]. While there is considerable overlap in dissemination channels used at each level of government, there are some unique characteristics.

Five studies (about 18.5%) examined dissemination at the federal level [ 32 – 36 ]. At the federal level, dissemination channels tended to be more formal such as congressional committee hearings [ 36 ] and legislative development [ 35 ]. Twelve studies (about 44%) evaluated dissemination at the state level [ 38 – 44 , 47 , 48 , 50 – 52 ]. State level dissemination heavily relied on printed materials including from mental health care disparity report cards [ 41 ], policy briefs [ 38 ], and effectiveness reports [ 50 ]. Another common channel was in-person communications such as one-on-one meetings [ 44 ] and presentations to stakeholders [ 51 ]. Three studies (about 11%) focused on local-level government. Dissemination channels at the local level had little consistency across the three studies with channels including public education [ 45 ], reports [ 37 ], and print materials [ 49 ].

Roughly half of studies were atheoretical ( n = 13). Four studies used the Weiss Typology [ 29 , 36 , 54 , 55 ], two studies used the operationalization framework [ 45 , 53 ], and two studies used the advocacy coalition framework [ 53 , 56 ].

Model for dissemination of research

We used the Model for Dissemination of Research to summarize the findings from the included studies into the themes of source, message, audience, and channel (i.e., strategies). We integrated themes from the studies into the Model (see Fig. ​ Fig.3 3 ).

A conceptual model for dissemination of research to policymakers. The populated conceptual model builds on the Model for Dissemination of Research by organizing findings from the current systematic review to build an understanding of how research is disseminated to policymakers in the United States

The sources of knowledge varied across studies with some studies including multiple sources of social policy information. The most common sources of knowledge included research, as in peer-reviewed literature ( n = 7) [ 30 , 33 , 38 , 42 , 43 , 49 , 54 ], researchers ( n = 5) [ 27 , 31 , 32 , 34 , 56 ], and research broadly defined ( n = 5) [ 36 , 39 , 47 , 48 , 55 ], the government ( n = 11) [ 29 , 36 , 41 – 44 , 47 , 50 , 54 , 56 , 57 ], and organizations ( n = 7) [ 33 , 36 , 46 , 52 – 54 , 56 ].

The majority of studies focused on health topics ( n = 12) [ 29 , 30 , 33 , 34 , 38 , 41 , 42 , 45 , 47 , 55 , 56 , 58 ] and child and family well-being ( n = 6) [ 27 , 36 , 46 , 49 , 52 , 57 ]. The remaining studies covered the topics of education ( n = 4) [ 39 , 43 , 53 , 54 ], guns [ 56 ], veterans [ 44 ], and general social research ( n = 3) [ 31 , 32 , 48 ]. Multiple studies offered specific recommendations for message framing, suggesting that the packaging of information is as critical as the information itself [ 27 ]. One study piloted multiple styles of policy briefs and found staffers preferred to use and share narrative or story-based briefs while legislators were more likely to use and share statistical, data-based briefs [ 38 ]. This finding was mirrored in two studies that found testimonial or descriptive evidence to be as effective as data-driven research [ 34 , 52 ], particularly in the context of sympathetic populations [ 52 ]. Three studies highlighted the reliance of effective message delivery on the message’s ability to capture audience interest (e.g., what the research means to the policymaker, specifically and if possible, personally) [ 27 , 34 , 41 ]. Finally, two studies emphasized creating a sense of urgency or even shock-value within the message in order to capture policymakers’ interest [ 36 , 57 ].

The audience included executive branch policymakers [ 49 ], administrators ( n = 9) [ 27 , 31 , 38 , 39 , 41 , 43 , 53 , 55 , 57 ], and staff [ 42 ]. Studies which focused on the legislative branch examined legislators ( n = 12) [ 27 , 32 , 36 , 38 , 44 – 47 , 50 , 52 , 53 , 58 ] and staff ( n = 3) [ 32 , 34 , 36 ]. Three studies examined broadly defined policymakers [ 33 , 54 , 56 ] and generalized staff [ 54 ] without indication for specific branch of government.

Included studies examined a variety of channels with many including multiple channels. Print materials was the most commonly used channel, including reports ( n = 10) [ 27 , 30 , 33 , 41 , 46 , 50 , 53 , 55 , 57 , 58 ] and policy briefs ( n = 3) [ 31 , 34 , 38 ]. Researchers examined in-person meetings and communications as a channel to disseminate research ( n = 9) [ 30 , 32 , 33 , 39 , 44 , 48 , 53 , 56 , 57 ]. Research and research summaries were also studied ( n = 7) [ 30 , 31 , 42 , 47 , 49 , 52 , 54 ]. Both traditional ( n = 6) [ 31 , 33 , 47 , 52 – 54 ] and social media ( n = 2) [ 47 , 53 ] were examined as channels to disseminate research to policymakers. Other channels include conferences and presentations ( n = 4) [ 33 , 34 , 49 , 57 ], electronic communication ( n = 2) [ 27 , 57 ], online resources ( n = 3) [ 34 , 49 , 58 ], and personal testimony ( n =2) [ 42 , 52 ].

Effectiveness and lessons learned

The majority of studies employed qualitative research methods (e.g., interviews, case studies, focus groups) to evaluate the impact of scientific research on domestic social policy. Our review of the literature also identified nine quantitative and mixed-methods studies [ 31 , 32 , 38 , 39 , 42 – 44 , 49 , 58 ]. We identified a series of cross-cutting dissemination strategies for engaging policymakers including recommendations for and barriers to research-to-policy (see Table ​ Table2 2 ).

Start early

Four studies highlighted the importance for early and ongoing engagement with policymakers throughout the research process in order to maximize interest and applicability. Researchers are encouraged to take the initiative to contact policymakers as early as possible in the research process. Many policymakers may be interested in accessing and using research but uncertain who or how to make connections in the academic or research community [ 27 ]. Involving policymakers when designing projects and framing initial research questions increases the likelihood that key policy stakeholders will remain invested in the work by allowing their individual research interests to shine [ 34 , 41 ]. Early engagement also ensures that research products (e.g., reports, policy briefs, factsheets) will have strategic usefulness for policymakers [ 30 ].

Drum up support

In addition to early policymaker engagement, three studies highlighted the need for researchers to garner outside support for their work, ideally involving a broad pool of experts and cultivating a broader coalition of supporters than typical academic endeavors [ 47 ]. Often, policymakers appear unwilling or uninterested in considering the application of evidence to their work [ 45 , 53 ]; when researchers can demonstrate the value and relevance of their work [ 58 ], policymakers may be more likely to engage.

Use research evidence “champions” or “brokers”

A common strategy for garnering support (as recommended above) is the use of evidence champions or brokers ; these are intermediary individuals or organizations who connect research suppliers (e.g., individual researchers, academic institutions) to research demand (e.g., policymakers) [ 53 ]. These champions can broker important connections; however, researchers and policymakers alike must remember that these intermediaries are not neutral carriers of information, and may spin research in support of personal agendas [ 45 , 52 , 53 ]. Individual biases may also present a barrier in research-to-policy translation, as individuals or organizations are empowered to select the “best” research evidence to share with policymakers [ 29 ]. One study found that nearly half of state policymakers named professional associations as trusted sources for research information, specifically because the organization is perceived not to have a stake in the final policy outcome [ 58 ].

Two studies specifically addressed the role of intermediary organizations or brokers in the translation of research evidence to policy. Hopkins et al. [ 39 ] explored the exchange of research evidence among state education agency (SEA) leaders, while Massell et al. [ 43 ] examined more broadly the origins of research evidence use in three SEAs. Both studies found that external brokers played a role in connecting SEA policymakers to relevant research, as well as in the conceptualization and development of policy.

Focus on context

Multiple studies stressed the importance of research evidence being contextually relevant to the specific policy audience [ 29 , 54 , 55 , 57 ]. For some policymakers, the needs and interests of local constituents will drive the use of research and the specifics of the policy agenda; for others, discussions that integrate research evidence into the broader sociopolitical context will be more effective [ 45 ]. For state- and local-level policymakers, policies may be most effective when based on the evidence-based understanding of local stakeholders, rather than imposed from the federal level without local contextual details [ 29 ].

Ideology of external advisors and brokers (as discussed above) and policymakers’ own personal beliefs and experiences [ 54 ] and the prevailing political ideology of a particular geographic region [ 55 ] are critical components of context. Ideological beliefs, often deeply held and personal, may create a barrier between researchers and policymakers [ 41 ], though differentiating ideology from other factors that affect individual position-taking is difficult in most situations [ 44 ]. McGinty et al. [ 56 ] suggest that in polarized contexts involving strong ideological beliefs, research may add legitimacy to a particular viewpoint, though as with brokers, that research is likely to be carefully curated to support the desired message. Purtle et al. [ 55 ] concur, reporting that some county health officials were wary of the potential to spin research findings to make a case for certain programs over others and noted the need to avoid the challenge of distorting evidence. Two studies recommend positional neutrality as a researcher’s best approach to handling potential ideological differences, suggesting that presenting research findings as simple fact, rather than making specific recommendations for action, may help avoid conflict and also help researchers gain credibility across the ideological spectrum [ 27 , 50 ].

Make research products timely, relevant, and accessible

As with all research endeavors, timeliness and relevance are paramount. However, the typical timeline for academic research (years) is often too long for policymakers whose window for championing a policy action is much shorter (weeks or months) [ 27 , 52 ]. A frequently reported barrier in research-to-policy translation is the complexity of research and concerns about the quality of research evidence [ 29 , 41 , 56 ]; one strategy for combating this concern is the use of clear, careful language [ 27 ], and tailored, audience-specific products that meet the needs of a diverse population of end users [ 27 , 34 , 58 ]. Research that is presented in commonly used, accessible formats (e.g., briefs, factsheets, videos) [ 48 ] may also be more effective, though one study found that use of these formats was dependent on job type, with legislators and staffers preferring different formats [ 58 ].

Multiple studies engaged with policymakers in an effort to determine how they receive research evidence and what strategies or formats are most desirable or effective [ 38 ]. After piloting four different styles of policy briefs (on the same research topic) with state-level policymakers, Brownson et al. [ 38 ] found that while all styles of brief were considered understandable and credible, opinions on the usefulness of the brief varied by the style of the brief and by the level of policymaker (e.g., legislative staff, legislators, and executive branch administrators). These findings suggest that targeted, audience-specific research evidence materials may be more likely to be used by policymakers than generic research evidence. One study explored the usefulness of electronic vs. printed research material and again found differences by type of policymaker—legislators were more likely to read hard copy printed material, while staffers gave higher ratings to online content. Not surprisingly, the age of the policymaker also played a role in the choice to access electronic or printed material, with younger policymakers much more likely to read electronic copy than were their older peers [ 58 ].

A study on state policymakers’ perceptions of comparative effectiveness research (CER) found that the most useful research is that which is consistent and specific to the needs of the policymakers [ 42 ]. The same study identified related barriers to the use of CER in policy decision-making, citing a lack of relevant high quality or conclusive research [ 42 ].

Finally, two studies described pilot projects focused on the delivery of research evidence directly to policymakers. The first cultivated researchers’ capacity to accelerate the translation of research evidence into useable knowledge for policymakers through a rapid response researcher network [ 32 ]. This model was shown to be effective for both researchers (in mobilizing) and policymakers (in eliciting requests for research evidence to bolster a policy conversation or debate) [ 32 ]. The second implementation study reported on a field experiment in which state legislators randomly received relevant research about pending policy proposals [ 44 ]. Findings from this study suggest that having relevant research information increases policymakers’ co-sponsorship of proposals by 60% and highlights the importance of research access in the policy process [ 44 ].

Know the players and the process

Policymakers are as much experts in their arena as researchers are in their academic fields. In order to build lasting working relationships with a target policymaking audience and maximize the relevance of research products for policy work, researchers must first understand the policy process [ 27 , 30 , 34 ]. One study examined the role of researchers themselves in disseminating findings to policymakers and identified individual- and organizational-level facilitators and barriers to the process [ 31 ]. Researchers’ familiarity with the policy process, the relevance of policy dissemination to individual programs of research, and the expectation of dissemination (from higher institutional or funding bodies) facilitated the research-to-policy exchange, while lack of familiarity with effective dissemination strategies and lack of financial and institutional support for dissemination emerged as primary barriers in the research-to-policy exchange [ 31 ].

Public policy, whether legislative, executive, or judicial, affects all areas of daily life in both obvious and subtle ways. The policy process (i.e., the steps from an idea to policy enactment) does not exist in a vacuum; it is influenced by many factors, including public opinion [ 59 , 60 ], special interest groups [ 61 ], personal narratives [ 62 ], expressed needs of constituents [ 1 ], the media [ 63 – 65 ], and corporations [ 66 , 67 ]. Research may also play a role in shaping policy and has the potential to add objectivity and evidence to these other forces [ 1 , 2 , 68 ]. The current study synthesizes existing knowledge to understand dissemination strategies of social policy research to policymakers in the United States.

Many channels exist to disseminate evidence to policymakers, with the most common being print materials (i.e., reports and policy briefs). This finding is surprising in our current digital age, as print materials are necessarily time-bound and rapidly evolving technology has created more channels (e.g., social media, videos) which may be preferred by policymakers. This shift creates an opportunity to optimize the content of print materials to disseminate in new mediums; it also offers a chance for authors to improve the accessibility of their work for broader audiences (e.g., via more visual presentation formats) [ 15 , 69 – 71 ].

Our review found strategies to increase effectiveness of research dissemination to policymakers includes starting early, drumming-up support, using champions and brokers, understanding the context, ensuring timeliness, relevance, and accessibility of research products, and knowing the players and the process. These themes align with existing knowledge about policymaker preferences including face-to-face engagement [ 72 , 73 ], contextual considerations (e.g., timeliness and budget) [ 2 , 72 ], and existing barriers and facilitators to research evidence use [ 4 , 5 ]. Our study adds to what we already know about policymakers’ desire for research evidence and their varying preferences as to the context and form of that knowledge [ 2 , 72 , 74 ] and supports existing efforts to bridge the gap between researchers and policymakers.

Many of the barriers and facilitators to research dissemination that we identified in this review mirror those cited by policymakers as barriers and facilitators to evidence use; this overlap reasonably suggests that efforts to expand research dissemination may improve the other. Particularly relevant lessons from the evidence use literature that also emerged from our review include emphasis on the benefit of building personal relationships between researchers and policymakers [ 5 , 75 , 76 ], narrowing the perceived gap between the two groups [ 77 , 78 ], and changing the culture of decision making to increase appreciation for the value of research in policy development [ 5 , 75 – 77 ]. Considering the multiple pathways through which research evidence is used in policy, from providing direct evidence of a program’s effectiveness to informing or orienting policy makers about relevant issues [ 23 ], these shared lessons around barriers and facilitators may better inform researchers, policymakers, and staff as to best practices for future communication and collaboration.

Our findings also highlight several unique elements of the US policy landscape, wherein significant power is reserved from the federal-level and afforded to state-level government. In some states, this power is further distributed to county and local governments. This system creates major variation across the country in both policy decisions and in resource availability for social policy implementation. Despite our relatively unique government structure, however, many of the effective strategies for dissemination we identified mirror strategies found in other countries [ 79 , 80 ].

Studies that focused on a specific level of government had some unique characteristics such as formality and reliance on print materials. For example, federal dissemination relied more heavily on formal legislative testimony while state level material relied on written policy materials (e.g., policy briefs, report cards). However, these results are limited by small sample sizes and limited evidence about effectiveness.

A wide range of contextual variables may influence policy dissemination in the US at different levels of government. In the federal legislative context alone, multiple committees and subcommittees of both the U.S. House of Representatives and the U.S. Senate may exercise some control over programs and policies related to a single social policy issue (e.g., child and family services) [ 81 ]. At the federal level, the Congressional Research Service (CRS) provides non-partisan research support to legislators in multiple formats including reports on major policy issues, expert testimony, and responses to individual inquiries; the Domestic Social Policy Division offers Congress interdisciplinary research and analysis on social policy issues [ 82 ]. While there may be fewer decision-makers for each issue on the state level, policymaking is further complicated by the extensive rules and reporting requirements attached to state use of federal funding as well as competing priorities or needs at the local level within each state [ 83 , 84 ]. Another dissemination influence may include geographic proximity; for example, geographical proximity may increase the likelihood of university-industry partnerships [ 85 ].

Infrastructure differences may also represent important differences between the US social policy context and that of other developed nations. Each country has a distinct and perhaps unique policy context given available resources, political rules and regulations, and priorities. While models for infrastructure and dissemination interventions may be shared across policy contexts, it may be difficult to directly compare dissemination strategies in one country with dissemination strategies in another country.

Several examples across western countries contribute to a stronger nexus between research evidence and the policy-making process. In the United States, the Wisconsin Family Impact Seminars ( www.wisfamilyimpact.org ) are an example of long-standing initiatives that provide the opportunity for researchers and policymakers to come together to discuss unbiased policy-relevant evidence [ 86 ]. As exemplified by Friese and Bogenschneider [ 27 ], these forums continue to be perceived as objective, relevant, and useful by policymakers and have succeeded at bringing attention to social policy [ 86 ]. Researchers and policymakers in Canada have sought to bridge the research-to-policy gap. For example, the Canadian Foundation for Healthcare Improvement (formerly the Canadian Health Services Research Foundation), funded by the Canadian federal government, brings together researchers and policymakers early and throughout the research development process to discuss, prioritize, and evaluate opportunities for research and dissemination [ 79 ]. In the UK, infrastructure at the national level includes the National Institute for Health Research Policy Research Programme, which funds health research with the explicit goal of informing national policy decisions in health and social care [ 87 ]. These efforts include open calls for research proposals as well as 15 dedicated Policy Research Units located at leading academic institutions around the country. Another resource is the EPPI-Centre at University College London, which provides policymakers support for finding and using research to inform policy decisions through its Research Advisory Service. This allows researchers to work alongside policymakers to reach their goals in addressing educational needs with evidence-informed policy [ 80 ].

Limitations

The current study has several limitations—these illustrate opportunities for future research. First, we attempted to cast a wide net when searching for studies which examined the influence of research on social policy by including a broad search of the peer-reviewed literature, think tanks, and content experts. However, it is possible we missed some studies which examine how research influences policy. Second, we provide a rationale for focusing on US studies and that our findings may not be generalizable to other countries. Third, we were unable to assess the risk of bias for individual studies as current standards note difficulties in assessing quality and bias in qualitative research [ 88 ]. Fourth, many studies examined multiple channels or strategies for how research influences policy, so the parsing of singular strategies (e.g., policy brief, in-person meeting) as an effective approach should be interpreted with caution. Additional investigation is needed to explore and test causal pathways in how these channels can best influence social policy. Fifth, the majority of studies did not use any theory or framework as a foundation or guide for exploration. This gap may indicate a space to use frameworks such as the Model for Dissemination of Research to guide future research. Finally, the dearth of mixed-methods studies that systematically evaluate the impact of research evidence on domestic social policy (this review identified only 3) presents an opportunity for future work in this field to integrate quantitative and qualitative methodologies.

One significant challenge to increasing the rigor in dissemination research studies is the difficulty in choosing and then measuring an outcome. Many of the studies included in this review are either case studies or descriptive, making it difficult to determine what, if any, impact the given research had on policy. Bogenschneider and Corbett discuss this at length as one of the primary challenges to furthering this research [ 72 ], imploring researchers not to focus solely on the outcome of whether or not a piece or legislation passes but rather to examine whether research influenced one of the proposed policy options [ 72 ]. However, this information can be difficult both to operationalize and to collect. That said, some researchers have already begun to think beyond the passage of legislation, as evidenced by Zelizer [ 44 ] who examined bill co-sponsorship rather than passage. A recent review of health policy implementation measurement found that validated quantitative measures are underutilized and recommends further development and testing of such measures [ 89 ]. Difficulties in identifying robust outcomes and high-quality scales to operationalize them present opportunities for additional exploration in this area.

Dissemination and implementation are often described together; not surprisingly, is overlap in effective strategies for each. The current review identified six dissemination strategies and described their reported effectiveness, while the Expert Recommendations for Implementing Change (ERIC) Project identified 73 implementation strategies [ 90 ]. One such similarity is obvious: the dissemination strategy of using champions and brokers mirrors the ERIC implementation strategy of identifying and preparing champions. The difference between the number of implementation strategies and dissemination strategies is striking and highlights the gap in research. Future work should further explore the degree to which dissemination strategies and implementation strategies either overlap or are distinct.

Finally, the dissemination of research to policymakers may raise certain ethical issues. It is imperative for researchers to critically assess when and how to disseminate research findings to policymakers, keeping in mind that promoting a specific policy agenda may result in a perceived or real loss of objectivity [ 91 ]. Syntheses of policy-relevant evidence can be useful, particularly when researchers work in partnership with non-governmental organizations to inform the policy process.

We summarize strategies and illuminate potential barriers to the research-to-policy dissemination process. Key findings are drawn from multiple disciplines and suggest that lessons learned may cut across both research topics and levels of government. The most frequently referenced channel for dissemination to policymakers was print materials, with personal communication (including both in-person and electronic meetings and individual communications) a close second. Corresponding strategies for effective dissemination to policymakers included starting early, drumming-up support, using champions and brokers, understanding the context, ensuring timeliness, relevance, and accessibility of research products, and knowing the players and the process. A shared feature of these strategies is the distillation of complex research findings into accessible pieces of relevant information that can then be delivered via multiple avenues.

Interdisciplinary collaboration is a common practice in scientific research [ 92 ]. Our findings provide leads on how to more effectively to engage with policymakers, leading to a greater likelihood of translating research evidence into policy action. Engaging policymakers early as contributing members of the research team, maintaining communication during the research process, and presenting relevant findings in a clear, concise manner may empower both researchers and policymakers to further apply scientific evidence to improve social policy in the United States.

Supplementary information

Acknowledgements.

The views expressed herein are those of the authors and do not reflect those of the Department of Veterans Affairs, the Centers for Disease Control and Prevention, or the National Institutes of Health.

Abbreviations

Authors’ contributions.

Review methodology: LEA, DAQ, RCB; eligibility criteria: LEA, DAQ, RCB; search strings and terms: LEA, DAQ; abstract screening: LEA, DAQ; full text screening: LEA, DAQ; pilot extraction: LEA, DAQ; data extraction: LEA, DAQ; data aggregation: LEA, DAQ; writing: LEA, DAQ; editing: LEA, DAQ, RCB. The author(s) read and approved the final manuscript.

LEA is supported by a pre-doctoral Clinical and Translational Science Fellowship (NIH TL1 TR001858 (PI: Kraemer)). DAQ is supported by a postdoctoral fellowship through the Department of Veterans Affairs (VA) Office of Academic Affiliations and the Center for Health Equity Research and Promotion at the VA Pittsburgh Healthcare System. RCB is supported by the National Cancer Institute (P50CA244431) the Centers for Disease Control and Prevention (U48DP006395). The funding entities had no role in the development, data collection, analysis, reporting, or publication of this work. Article processing charges for this article were fully paid by the University Library System, University of Pittsburgh.

Availability of data and materials

Ethics approval and consent to participate.

Not applicable.

Consent for publication

Competing interests.

The authors declare they have no conflicting interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Laura Ellen Ashcraft, Email: ude.ttip@tfarchsanellearual .

Deirdre A. Quinn, Email: [email protected] .

Ross C. Brownson, Email: ude.ltsuw@nosnworbr .

Supplementary information accompanies this paper at 10.1186/s13012-020-01046-3.

A Proposed Strategy for Research Misconduct Policy: A Review on Misconduct Management in Health Research System

Affiliations.

• 1 Deputy of Research and Technology, Ministry of Health and Medical Education, Tehran, Iran; NCD Research Centre, Endocrinology and Metabolism Research Institute, Tehran University of Medical Sciences, Tehran, Iran.
• 2 Deputy of Research and Technology, Ministry of Health and Medical Education, Tehran, Iran; Molecular Microbiology Research Center, Shahed University, Tehran, Iran.
• 3 Department of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
• 4 Deputy of Research and Technology, Ministry of Health and Medical Education, Tehran, Iran.
• PMID: 27512558
• PMCID: PMC4966197
• DOI: 10.4103/2008-7802.186227

Background: Today, with the rapid growth of scientific production, research misconduct has become a worldwide problem. This article is intended to introduce the successful experience on the management of research paper misconducts in the field of health research.

Methods: Our aim was to design and develop the strategy for research misconduct policy. Focusing on the national regulatory system, we developed a hierarchical model for paper misconduct policy in all the medical sciences universities and their affiliated research units.

Results: Through our regulatory policy for paper misconduct management, specific protocol was followed in the field of health research publications through which the capabilities of covering the four main elements of prevention, investigation, punishment, and correction have come together.

Conclusions: Considering the proposed strategy, regarding the strengths and weaknesses, utilization of evaluation tool can be one of the best strategies to achieving the prospective of health research papers by 2025.

Keywords: Health research; Iran; misconduct; policy; strategy.

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Biden-Harris Administration Releases First-Ever National Strategy to Accelerate Deployment of Zero-Emission Infrastructure for Freight Trucks

Landmark Strategy Will Build on New National Electric Vehicle Freight Corridors Designated by the Federal Highway Administration and Advance the President’s Clean Transportation Goal to Decarbonize the Freight Sector to Improve Our Communities, the Environment, and the Economy

FHWA 09-24 Contact: [email protected] Tel: (202) 366-0660

Washington, D.C. – The Biden-Harris Administration today released the National Zero-Emission Freight Corridor Strategy . Developed by the Joint Office of Energy and Transportation and U.S. Department of Energy (DOE), in collaboration with the Department of Transportation (DOT) and the Environmental Protection Agency (EPA), the Strategy will guide the deployment of zero-emission medium- and heavy-duty vehicle (ZE-MHDV) charging and hydrogen fueling infrastructure from 2024 to 2040. The Strategy is designed to meet growing market demands by targeting public investment to amplify private sector momentum, focus utility and regulatory energy planning, align industry activity, and improve air quality in local communities heavily impacted by diesel emissions.

“For over a century, petroleum-fueled freight has transported vital food and resources to American families but at the same time, these vehicles have also contributed to lower public health, especially in densely populated communities,” said U.S. Secretary of Energy Jennifer M. Granholm . “The Biden-Harris Administration is addressing this issue head-on with innovative strategies to transform freight so it not only supports American families and businesses, but also protects the environment for future generations.”

“This is a big move to deliver environmental justice – 75% of heavy truck traffic travels on just 4% of our nation’s roads, jeopardizing the health of our most vulnerable communities,” said President Biden’s National Climate Advisor Ali Zaidi . “President Biden’s historic investments in zero-emission infrastructure on those high-traffic roads and the hubs they connect will rapidly transform freight transport in the U.S. and strengthen American innovation. Through the President’s whole-of-government strategy, this administration is delivering a win-win-win for frontline communities who will benefit from cleaner air, businesses that will save millions on fuel costs, and for our climate.”

“This landmark strategy brings us one step closer to achieving a zero-emission transportation sector that provides clean air for communities, creates market certainty for industries investing in clean technology, and strengthens our supply chains,” said Senator Alex Padilla . “I’m grateful to the Administration for advancing this whole-of-government effort and heeding my calls to launch a national strategy to accelerate the build-out of heavy-duty vehicle infrastructure. This all-hands-on-deck approach from the federal government and industry partners will enable us to realize California’s and the Administration’s zero-emission goals.

Providing ubiquitous and convenient access to electric vehicle (EV) charging and hydrogen refueling along our nation’s freight corridors and at intermodal freight facilities and high-usage ports is key to achieving U.S. goals to promote at least 30 percent ZE-MHDV sales by 2030 and 100 percent sales by 2040 . The goal of the Strategy is to align public policy and investments by prioritizing, sequencing, and accelerating infrastructure along the National Highway Freight Network (NHFN) in four phases. A core objective of the Strategy is to meet freight truck and technology markets where they are today, determine where they are likely to develop next, and set an ambitious pathway that mobilizes actions to achieve decarbonization.

In alignment with the Joint Office’s National Zero-Emission Freight Corridor Strategy, the Federal Highway Administration is announcing the designation of National EV Freight Corridors along the National Highway Freight Network and other key roadways. The designations, which are required by the Bipartisan Infrastructure Law (BIL), are a critical part of the Biden-Harris Administration’s strategy for building out a convenient, reliable, and made-in-America national EV charging network that supports individual drivers and commercial needs.

Battery electric and hydrogen fuel cell vehicle technology along with other zero-emission forms of freight transport have considerable potential to save Americans money on consumer goods thanks to reduced fueling and maintenance costs associated with transport, all while delivering significant health benefits for historically disadvantaged populations that suffer the worst impacts of pollution from freight emissions and helping achieve national climate goals.

“The Federal Highway Administration is pleased to announce these new freight EV corridor designations along our national highways,” said Federal Highway Administrator Shailen Bhatt . “Medium- and heavy-duty trucks in our current freight network contribute approximately 23% of greenhouse gas emissions in the U.S. transportation sector. These new designations and Strategy will help to grow our national EV charging network, encourage clean commerce within the freight community, and support President Biden’s goals of achieving net-zero emissions for the nation by 2050.”

Under President Biden’s leadership, the number of publicly available EV chargers nationwide has increased by more than 80% to more than 173,000, and at least 40 U.S.-based facilities to produce EV chargers have been announced or opened. President Biden’s Investing in America agenda has attracted more than $25 billion of investment in the U.S. EV charging network. Today’s freight corridor designations are expected to crowd in even more investment for EV charging, with a particular focus on the needs of medium- and heavy-duty vehicles.

This is an all-of-government approach to aligning investments and accelerating sustainable and scalable deployment of reliable ZE-MHDV infrastructure. Focusing deployment on areas with substantial freight volume starts deployment in areas with the most opportunity to spark further investment. Deployment factors include corridor segment usage by freight volume, port usage by annual freight tonnage, projected ZE-MHDV volumes, disproportionate environmental and air quality burden from MHDV transportation and non-attainment for criteria air pollutants, states with ZEV deployment-enabling policies, and “on the ground” planning through DOE’s commercial ZEV corridor planning grants.

The National Zero-Emission Freight Corridor Strategy will prioritize, sequence, and accelerate infrastructure along key freight corridors and hubs in four phases. The phases include:

• Establish priority hubs based on freight volumes (2024-2027)
• Connect hubs along critical freight corridors (2027-2030)
• Expand corridor connections initiating network development (2030-2035)
• Achieve national network by linking regional corridors for ubiquitous access (2035-2040)

See the National Zero-Emission Freight Corridor Strategy for additional maps and detail.

'The most important neighborhood." What a new strategy envisions for downtown Louisville

If downtown Louisville is to remain an economic powerhouse for the city and state, it will need to adapt to post-pandemic realities in what the public needs out of its urban center.

That message to evolve is a key part of the 10-year development strategy , “A New Paradigm for Downtown Louisville,” unveiled Thursday.

The blueprint outlines both short- and long-term strategies for moving away from an office-centric downtown to a multi-use destination for entertainment, retail, housing and office use.

Hybrid and remote working trends greatly influenced by the pandemic mean workers have more choice in where and how they want to work, the report outlines. Companies are adjusting their office needs accordingly.

Meanwhile, perception issues linger from the social justice protests of 2020 as to the safety and inclusivity of downtown.

“Downtown must be a place where they want to be, and downtowns must make that choice as compelling as possible,” the report reads. “If people perceive no added value of traveling downtown on a regular basis for work or play, they will not come.”

You may like: More housing, better public spaces: 4 major takeaways from new downtown Louisville strategy

Drawn on feedback from public listening sessions, conversations with national experts, over 70 stakeholder meetings and consultant research, the 10-year blueprint outlines a vision for how downtown can succeed long term.

Among the takeaways:

• Downtown needs to be more than the Central Business District and better connect to its adjacent neighborhoods.
• Downtown needs more uses that generate activity 24/7.
• Downtown should be viewed as a residential neighborhood that’s walkable, pedestrian friendly and connected.
• Public spaces and downtown infrastructure need to go beyond aesthetics to act as an economic development driver. Open spaces should be a “coordinated network of engaging places for people to seek out and enjoy.”
• Developing downtown “districts” to add distinctiveness and unique draws to various parts of downtown, driving activity in each of those areas.  

The report focuses on three main strategies to make downtown thrive: “activating” downtown through increased attractions; growing the number of people who live downtown; and enhancing the “public realm” via more pedestrian friendly streets, more inviting public spaces and better connectivity within downtown and to the areas surrounding it.

“Downtown is the most important neighborhood in our entire city,” Mayor Craig Greenberg said Thursday at the report’s debut event. “It is truly the glue that connects us all.”

Greenberg referenced a $100 million allocation in the Kentucky Senate’s budget over the next two years to downtown-focused projects, including a reimagined Belvedere, repurposed Louisville Gardens , the Louisville Medical & Education and District and mixed-use development in Butchertown around Lynn Family Stadium.

“This has the potential to be transformational for our city,” he said. “We are continuing advocating on a daily basis to make sure that those investments stay in the final budget.”

The report was developed over the last year by the nonprofit Louisville Downtown Partnership, which issues such strategies about every decade. It hired Louisville-based urban planning and strategy firm CityVisions Associates, a subsidiary of development firm Weyland Ventures, to create the report.

The blueprint released Thursday isn’t meant to be a specific master plan for downtown that details projects in great depth and specificity. Instead, it’s meant to outline foundational principles to guide development downtown over the next decade.

Rebecca Fleischaker, executive director of the Louisville Downtown Partnership, touted $1.5 billion of investments across 61 downtown developments underway and announced.

“Economic development is the long game,” she said Thursday. “It requires putting the building blocks down one project at a time, one year at a time that help makes new projects possible.”

She also pointed to challenges the report says need to be addressed to lead to long-term success. These issues include a declining office workforce (downtown office space vacancy is about 21%), public safety concerns, infrastructure maintenance and a loss of public confidence in downtown.

While the report doesn’t spend much time focusing on how to attract and retain businesses in downtown, it reiterates that it “must remain the commercial heart of the region” and called for both public and private strategies to maintain that title.

Among the blueprint’s short-term recommendations:

• Establishing a dedicated LMPD district for downtown with foot, bicycle and horseback patrols.
• Maintaining the expanded downtown ambassador team , which recently doubled to 36 people via the Louisville Downtown Partnership.
• Creating an investment fund for transitional housing, led by the private sector and matched by Louisville Metro Government, that would fund 200-300 transitional housing units.

The report emphasizes connectivity throughout what’s traditionally been considered downtown and surrounding neighborhoods.

Downtown needs to be interesting, attractive and engaging, and efforts to improve the physical landscape need to go beyond cleanliness and aesthetics and instead create real energy and points of interest, the report argues.

Achieving this goal makes it a draw for locals and for workers and businesses looking to relocate to Louisville.

Housing, too, is a big focus of the strategy. The report ties the overall economic health of downtown, in large part, to significantly boosting the number of people living there, saying the residential population remains well below a critical mass.

“This cannot be overstated,” the report reads. “The residential population of downtown will become a major driver of its economy.”

Adding to the housing stock, currently around 6,000 apartments and condo units, can be achieved through repurposing underutilized office buildings and surface parking lots into residences.

The report calls for public-private partnerships to help accomplish some of its visions.

Longer-term proposals include:

• Creating a downtown public art trail that better uses open spaces and places a reimagined Belvedere as its “crown jewel.”
• Reviving the “Whiskey Alley” plans for the 100 block of Washington Street, on the north side of the Whiskey Row block. 
• Creating a “Louisville Creativity Center” downtown to elevate local innovations in bourbon, food, music and design.
• Strengthening Muhammad Ali Boulevard from Fifth to 18th streets via the Old Walnut Street Corridor Plan.
• Developing “residential neighborhood clusters” outside of the Central Business District, from the waterfront, to the east (in the NuLu area), to the west (in the Russell and Portland neighborhoods), and in the South Broadway district, stretching into Old Louisville.
• Embarking on “a sensitive and inclusive redesign” of Jefferson Square , which came to be known as Injustice Square during the social justice protests of 2020.

Reach Growth and Development Reporter Matthew Glowicki at [email protected].

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Statement by Director Sethuraman Panchanathan on the release of the National Strategy for Microelectronics Research

“Microelectronics are essential to the economic and national security of the United States and the importance of this industry is evident through the passage of the ‘ CHIPS and Science Act ’ in 2022,” said U.S. National Science Foundation Director Sethuraman Panchanathan. “The National Strategy on Microelectronics Research is a whole-of-government strategy that provides the framework for federal departments and agencies, academia, industry, nonprofits, and international allies and partners to address key needs to support R&D advances that will shape the semiconductors of the future. This strategy is enabling NSF to work with partners in the public and private sectors to strengthen the global microelectronics innovation ecosystem, secure supply chains and develop, attract, and retain a larger pool of talent in the domestic semiconductor industry through NSF’s  Future of Semiconductors (FuSe) program .”

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