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• 10 Research Question Examples to Guide Your Research Project

10 Research Question Examples to Guide your Research Project

Published on October 30, 2022 by Shona McCombes . Revised on October 19, 2023.

The research question is one of the most important parts of your research paper , thesis or dissertation . It’s important to spend some time assessing and refining your question before you get started.

The exact form of your question will depend on a few things, such as the length of your project, the type of research you’re conducting, the topic , and the research problem . However, all research questions should be focused, specific, and relevant to a timely social or scholarly issue.

Once you’ve read our guide on how to write a research question , you can use these examples to craft your own.

Note that the design of your research question can depend on what method you are pursuing. Here are a few options for qualitative, quantitative, and statistical research questions.

Other interesting articles

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

Methodology

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

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An Effective Guide to Comparative Research Questions

Table of Contents

Comparative research questions are a type of quantitative research question. It aims to gather information on the differences between two or more research objects based on different variables. 

These kinds of questions assist the researcher in identifying distinctive characteristics that distinguish one research subject from another.

A systematic investigation is built around research questions. Therefore, asking the right quantitative questions is key to gathering relevant and valuable information that will positively impact your work.

This article discusses the types of quantitative research questions with a particular focus on comparative questions.

What Are Quantitative Research Questions?

Quantitative research questions are unbiased queries that offer thorough information regarding a study topic . You can statistically analyze numerical data yielded from quantitative research questions.

This type of research question aids in understanding the research issue by examining trends and patterns. The data collected can be generalized to the overall population and help make informed decisions. 

Types of Quantitative Research Questions

Quantitative research questions can be divided into three types which are explained below:

Descriptive Research Questions

Researchers use descriptive research questions to collect numerical data about the traits and characteristics of study subjects. These questions mainly look for responses that bring into light the characteristic pattern of the existing research subjects.

However, note that the descriptive questions are not concerned with the causes of the observed traits and features. Instead, they focus on the “what,” i.e., explaining the topic of the research without taking into account its reasons.

Examples of Descriptive research questions:

• How often do you use our keto diet app?
• What price range are you ready to accept for this product?

Comparative Research Questions

Comparative research questions seek to identify differences between two or more distinct groups based on one or more dependent variables. These research questions aim to identify features that differ one research subject from another while emphasizing their apparent similarities.

In market research surveys, asking comparative questions can reveal how your product or service compares to its competitors. It can also help you determine your product’s benefits and drawbacks to gain a competitive edge.

The steps in formulating comparative questions are as follows:

• Choose the right starting phrase
• Specify the dependent variable
• Choose the groups that interest you
• Identify the relevant adjoining text
• Compose the comparative research question

Relationship-Based Research Questions

A relationship-based research question refers to the nature of the association between research subjects of the same category. These kinds of research question assist you in learning more about the type of relationship between two study variables.

Because they aim to distinctly define the connection between two variables, relationship-based research questions are also known as correlational research questions.

Examples of Comparative Research Questions

• What is the difference between men’s and women’s daily caloric intake in London?
• What is the difference in the shopping attitude of millennial adults and those born in 1980?
• What is the difference in time spent on video games between people of the age group 15-17 and 18-21?
• What is the difference in political views of Mexicans and Americans in the US?
• What are the differences between Snapchat usage of American male and female university students?
• What is the difference in views towards the security of online banking between the youth and the seniors?
• What is the difference in attitude between Gen-Z and Millennial toward rock music?
• What are the differences between online and offline classes?
• What are the differences between on-site and remote work?
• What is the difference between weekly Facebook photo uploads between American male and female college students?
• What are the differences between an Android and an Apple phone?

Comparative research questions are a great way to identify the difference between two study subjects of the same group.

Asking the right questions will help you gain effective and insightful data to conduct your research better . This article discusses the various aspects of quantitative research questions and their types to help you make data-driven and informed decisions when needed.

Abir Ghenaiet

Abir is a data analyst and researcher. Among her interests are artificial intelligence, machine learning, and natural language processing. As a humanitarian and educator, she actively supports women in tech and promotes diversity.

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Types of Research Questions

Research questions can be categorized into different types, depending on the type of research to be undertaken.

Qualitative questions concern broad areas or more specific areas of research and focus on discovering, explaining and exploring.  Types of qualitative questions include:

• Exploratory Questions, which seeks to understand without influencing the results.  The objective is to learn more about a topic without bias or preconceived notions.
• Predictive Questions, which seek to understand the intent or future outcome around a topic.
• Interpretive Questions, which tries to understand people’s behavior in a natural setting.  The objective is to understand how a group makes sense of shared experiences with regards to various phenomena.

Quantitative questions prove or disprove a  researcher’s hypothesis and are constructed to express the relationship between variables  and whether this relationship is significant.  Types of quantitative questions include:

• Descriptive questions , which are the most basic type of quantitative research question and seeks to explain the when, where, why or how something occurred. 
• Comparative questions are helpful when studying groups with dependent variables where one variable is compared with another.
• Relationship-based questions try to answer whether or not one variable has an influence on another.  These types of question are generally used in experimental research questions.

References/Additional Resources

Lipowski, E. E. (2008). Developing great research questions . American Journal of Health-System Pharmacy, 65(17), 1667–1670.

Ratan, S. K., Anand, T., & Ratan, J. (2019). Formulation of Research Question - Stepwise Approach .  Journal of Indian Association of Pediatric Surgeons ,  24 (1), 15–20.

Fandino W.(2019). Formulating a good research question: Pearls and pitfalls . I ndian J Anaesth. 63(8) :611-616. 

Beck, L. L. (2023). The question: types of research questions and how to develop them . In Translational Surgery: Handbook for Designing and Conducting Clinical and Translational Research (pp. 111-120). Academic Press. 

Doody, O., & Bailey, M. E. (2016). Setting a research question, aim and objective. Nurse Researcher, 23(4), 19–23.

Plano Clark, V., & Badiee, M. (2010). Research questions in mixed methods research . In: SAGE Handbook of Mixed Methods in Social & Behavioral Research .  SAGE Publications, Inc.,

Agee, J. (2009). Developing qualitative research questions: A reflective process .  International journal of qualitative studies in education ,  22 (4), 431-447. 

Flemming, K., & Noyes, J. (2021). Qualitative Evidence Synthesis: Where Are We at? I nternational Journal of Qualitative Methods, 20.  

Research Question Frameworks

Research question frameworks have been designed to help structure research questions and clarify the main concepts. Not every question can fit perfectly into a framework, but using even just parts of a framework can help develop a well-defined research question. The framework to use depends on the type of question to be researched.   There are over 25 research question frameworks available.  The University of Maryland has a nice table listing out several of these research question frameworks, along with what the acronyms mean and what types of questions/disciplines that may be used for.

The process of developing a good research question involves taking your topic and breaking each aspect of it down into its component parts.

Booth, A., Noyes, J., Flemming, K., Moore, G., Tunçalp, Ö., & Shakibazadeh, E. (2019). Formulating questions to explore complex interventions within qualitative evidence synthesis.   BMJ global health ,  4 (Suppl 1), e001107. (See supplementary data#1)

The "Well-Built Clinical Question“: PICO(T)

One well-established framework that can be used both for refining questions and developing strategies is known as PICO(T). The PICO framework was designed primarily for questions that include interventions and comparisons, however other types of questions may also be able to follow its principles.  If the PICO(T) framework does not precisely fit your question, using its principles (see alternative component suggestions) can help you to think about what you want to explore even if you do not end up with a true PICO question.

A PICO(T) question has the following components:

• P : The patient’s disorder or disease or problem of interest / research object
• I: The intervention, exposure or finding under review / Application of a theory or method
• C: A comparison intervention or control (if applicable- not always present)/ Alternative theories or methods (or, in their absence, the null hypothesis)
• O : The outcome(s) (desired or of interest) / Knowledge generation
• T : (The time factor or period)

Keep in mind that solely using a tool will not enable you to design a good question. What is required is for you to think, carefully, about exactly what you want to study and precisely what you mean by each of the things that you think you want to study.

Rzany, & Bigby, M. (n.d.). Formulating Well-Built Clinical Questions. In Evidence-based dermatology / (pp. 27–30). Blackwell Pub/BMJ Books.  

Nishikawa-Pacher, A. (2022). Research questions with PICO: a universal mnemonic.   Publications ,  10 (3), 21.

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Research Question 101 📖

Everything you need to know to write a high-quality research question

By: Derek Jansen (MBA) | Reviewed By: Dr. Eunice Rautenbach | October 2023

If you’ve landed on this page, you’re probably asking yourself, “ What is a research question? ”. Well, you’ve come to the right place. In this post, we’ll explain what a research question is , how it’s differen t from a research aim, and how to craft a high-quality research question that sets you up for success.

Research Question 101

What is a research question.

• Research questions vs research aims
• The 4 types of research questions
• How to write a research question
• Frequently asked questions
• Examples of research questions

As the name suggests, the research question is the core question (or set of questions) that your study will (attempt to) answer .

In many ways, a research question is akin to a target in archery . Without a clear target, you won’t know where to concentrate your efforts and focus. Essentially, your research question acts as the guiding light throughout your project and informs every choice you make along the way.

Let’s look at some examples:

What impact does social media usage have on the mental health of teenagers in New York?

How does the introduction of a minimum wage affect employment levels in small businesses in outer London?

How does the portrayal of women in 19th-century American literature reflect the societal attitudes of the time?

What are the long-term effects of intermittent fasting on heart health in adults?

As you can see in these examples, research questions are clear, specific questions that can be feasibly answered within a study. These are important attributes and we’ll discuss each of them in more detail a little later . If you’d like to see more examples of research questions, you can find our RQ mega-list here .

Research Questions vs Research Aims

At this point, you might be asking yourself, “ How is a research question different from a research aim? ”. Within any given study, the research aim and research question (or questions) are tightly intertwined , but they are separate things . Let’s unpack that a little.

A research aim is typically broader in nature and outlines what you hope to achieve with your research. It doesn’t ask a specific question but rather gives a summary of what you intend to explore.

The research question, on the other hand, is much more focused . It’s the specific query you’re setting out to answer. It narrows down the research aim into a detailed, researchable question that will guide your study’s methods and analysis.

Let’s look at an example:

Research Aim: To explore the effects of climate change on marine life in Southern Africa.

Research Question: How does ocean acidification caused by climate change affect the reproduction rates of coral reefs?

As you can see, the research aim gives you a general focus , while the research question details exactly what you want to find out.

Need a helping hand?

Types of research questions

Now that we’ve defined what a research question is, let’s look at the different types of research questions that you might come across. Broadly speaking, there are (at least) four different types of research questions – descriptive , comparative , relational , and explanatory . 

Descriptive questions ask what is happening. In other words, they seek to describe a phenomena or situation . An example of a descriptive research question could be something like “What types of exercise do high-performing UK executives engage in?”. This would likely be a bit too basic to form an interesting study, but as you can see, the research question is just focused on the what – in other words, it just describes the situation.

Comparative research questions , on the other hand, look to understand the way in which two or more things differ , or how they’re similar. An example of a comparative research question might be something like “How do exercise preferences vary between middle-aged men across three American cities?”. As you can see, this question seeks to compare the differences (or similarities) in behaviour between different groups.

Next up, we’ve got exploratory research questions , which ask why or how is something happening. While the other types of questions we looked at focused on the what, exploratory research questions are interested in the why and how . As an example, an exploratory research question might ask something like “Why have bee populations declined in Germany over the last 5 years?”. As you can, this question is aimed squarely at the why, rather than the what.

Last but not least, we have relational research questions . As the name suggests, these types of research questions seek to explore the relationships between variables . Here, an example could be something like “What is the relationship between X and Y” or “Does A have an impact on B”. As you can see, these types of research questions are interested in understanding how constructs or variables are connected , and perhaps, whether one thing causes another.

Of course, depending on how fine-grained you want to get, you can argue that there are many more types of research questions , but these four categories give you a broad idea of the different flavours that exist out there. It’s also worth pointing out that a research question doesn’t need to fit perfectly into one category – in many cases, a research question might overlap into more than just one category and that’s okay.

The key takeaway here is that research questions can take many different forms , and it’s useful to understand the nature of your research question so that you can align your research methodology accordingly.

How To Write A Research Question

As we alluded earlier, a well-crafted research question needs to possess very specific attributes, including focus , clarity and feasibility . But that’s not all – a rock-solid research question also needs to be rooted and aligned . Let’s look at each of these.

A strong research question typically has a single focus. So, don’t try to cram multiple questions into one research question; rather split them up into separate questions (or even subquestions), each with their own specific focus. As a rule of thumb, narrow beats broad when it comes to research questions.

Clear and specific

A good research question is clear and specific, not vague and broad. State clearly exactly what you want to find out so that any reader can quickly understand what you’re looking to achieve with your study. Along the same vein, try to avoid using bulky language and jargon – aim for clarity.

Unfortunately, even a super tantalising and thought-provoking research question has little value if you cannot feasibly answer it. So, think about the methodological implications of your research question while you’re crafting it. Most importantly, make sure that you know exactly what data you’ll need (primary or secondary) and how you’ll analyse that data.

A good research question (and a research topic, more broadly) should be rooted in a clear research gap and research problem . Without a well-defined research gap, you risk wasting your effort pursuing a question that’s already been adequately answered (and agreed upon) by the research community. A well-argued research gap lays at the heart of a valuable study, so make sure you have your gap clearly articulated and that your research question directly links to it.

As we mentioned earlier, your research aim and research question are (or at least, should be) tightly linked. So, make sure that your research question (or set of questions) aligns with your research aim . If not, you’ll need to revise one of the two to achieve this.

FAQ: Research Questions

Research question faqs, how many research questions should i have, what should i avoid when writing a research question, can a research question be a statement.

Typically, a research question is phrased as a question, not a statement. A question clearly indicates what you’re setting out to discover.

Can a research question be too broad or too narrow?

Yes. A question that’s too broad makes your research unfocused, while a question that’s too narrow limits the scope of your study.

Here’s an example of a research question that’s too broad:

“Why is mental health important?”

Conversely, here’s an example of a research question that’s likely too narrow:

“What is the impact of sleep deprivation on the exam scores of 19-year-old males in London studying maths at The Open University?”

Can I change my research question during the research process?

How do i know if my research question is good.

A good research question is focused, specific, practical, rooted in a research gap, and aligned with the research aim. If your question meets these criteria, it’s likely a strong question.

Is a research question similar to a hypothesis?

Not quite. A hypothesis is a testable statement that predicts an outcome, while a research question is a query that you’re trying to answer through your study. Naturally, there can be linkages between a study’s research questions and hypothesis, but they serve different functions.

How are research questions and research objectives related?

The research question is a focused and specific query that your study aims to answer. It’s the central issue you’re investigating. The research objective, on the other hand, outlines the steps you’ll take to answer your research question. Research objectives are often more action-oriented and can be broken down into smaller tasks that guide your research process. In a sense, they’re something of a roadmap that helps you answer your research question.

Need some inspiration?

If you’d like to see more examples of research questions, check out our research question mega list here .  Alternatively, if you’d like 1-on-1 help developing a high-quality research question, consider our private coaching service .

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What is comparative analysis? A complete guide

Last updated

18 April 2023

Reviewed by

Jean Kaluza

Short on time? Get an AI generated summary of this article instead

Comparative analysis is a valuable tool for acquiring deep insights into your organization’s processes, products, and services so you can continuously improve them. 

Similarly, if you want to streamline, price appropriately, and ultimately be a market leader, you’ll likely need to draw on comparative analyses quite often.

When faced with multiple options or solutions to a given problem, a thorough comparative analysis can help you compare and contrast your options and make a clear, informed decision.

If you want to get up to speed on conducting a comparative analysis or need a refresher, here’s your guide.

Make comparative analysis less tedious

Dovetail streamlines comparative analysis to help you uncover and share actionable insights

• What exactly is comparative analysis?

A comparative analysis is a side-by-side comparison that systematically compares two or more things to pinpoint their similarities and differences. The focus of the investigation might be conceptual—a particular problem, idea, or theory—or perhaps something more tangible, like two different data sets.

For instance, you could use comparative analysis to investigate how your product features measure up to the competition.

After a successful comparative analysis, you should be able to identify strengths and weaknesses and clearly understand which product is more effective.

You could also use comparative analysis to examine different methods of producing that product and determine which way is most efficient and profitable.

The potential applications for using comparative analysis in everyday business are almost unlimited. That said, a comparative analysis is most commonly used to examine

Emerging trends and opportunities (new technologies, marketing)

Competitor strategies

Financial health

Effects of trends on a target audience

Free AI content analysis generator

Make sense of your research by automatically summarizing key takeaways through our free content analysis tool.

• Why is comparative analysis so important? 

Comparative analysis can help narrow your focus so your business pursues the most meaningful opportunities rather than attempting dozens of improvements simultaneously.

A comparative approach also helps frame up data to illuminate interrelationships. For example, comparative research might reveal nuanced relationships or critical contexts behind specific processes or dependencies that wouldn’t be well-understood without the research.

For instance, if your business compares the cost of producing several existing products relative to which ones have historically sold well, that should provide helpful information once you’re ready to look at developing new products or features.

• Comparative vs. competitive analysis—what’s the difference?

Comparative analysis is generally divided into three subtypes, using quantitative or qualitative data and then extending the findings to a larger group. These include

Pattern analysis —identifying patterns or recurrences of trends and behavior across large data sets.

Data filtering —analyzing large data sets to extract an underlying subset of information. It may involve rearranging, excluding, and apportioning comparative data to fit different criteria. 

Decision tree —flowcharting to visually map and assess potential outcomes, costs, and consequences.

In contrast, competitive analysis is a type of comparative analysis in which you deeply research one or more of your industry competitors. In this case, you’re using qualitative research to explore what the competition is up to across one or more dimensions.

For example

Service delivery —metrics like the Net Promoter Scores indicate customer satisfaction levels.

Market position — the share of the market that the competition has captured.

Brand reputation —how well-known or recognized your competitors are within their target market.

• Tips for optimizing your comparative analysis

Conduct original research

Thorough, independent research is a significant asset when doing comparative analysis. It provides evidence to support your findings and may present a perspective or angle not considered previously. 

Make analysis routine

To get the maximum benefit from comparative research, make it a regular practice, and establish a cadence you can realistically stick to. Some business areas you could plan to analyze regularly include:

Profitability

Competition

Experiment with controlled and uncontrolled variables

In addition to simply comparing and contrasting, explore how different variables might affect your outcomes.

For example, a controllable variable would be offering a seasonal feature like a shopping bot to assist in holiday shopping or raising or lowering the selling price of a product.

Uncontrollable variables include weather, changing regulations, the current political climate, or global pandemics.

Put equal effort into each point of comparison

Most people enter into comparative research with a particular idea or hypothesis already in mind to validate. For instance, you might try to prove the worthwhileness of launching a new service. So, you may be disappointed if your analysis results don’t support your plan.

However, in any comparative analysis, try to maintain an unbiased approach by spending equal time debating the merits and drawbacks of any decision. Ultimately, this will be a practical, more long-term sustainable approach for your business than focusing only on the evidence that favors pursuing your argument or strategy.

Writing a comparative analysis in five steps

To put together a coherent, insightful analysis that goes beyond a list of pros and cons or similarities and differences, try organizing the information into these five components:

1. Frame of reference

Here is where you provide context. First, what driving idea or problem is your research anchored in? Then, for added substance, cite existing research or insights from a subject matter expert, such as a thought leader in marketing, startup growth, or investment

2. Grounds for comparison Why have you chosen to examine the two things you’re analyzing instead of focusing on two entirely different things? What are you hoping to accomplish?

3. Thesis What argument or choice are you advocating for? What will be the before and after effects of going with either decision? What do you anticipate happening with and without this approach?

For example, “If we release an AI feature for our shopping cart, we will have an edge over the rest of the market before the holiday season.” The finished comparative analysis will weigh all the pros and cons of choosing to build the new expensive AI feature including variables like how “intelligent” it will be, what it “pushes” customers to use, how much it takes off the plates of customer service etc.

Ultimately, you will gauge whether building an AI feature is the right plan for your e-commerce shop.

4. Organize the scheme Typically, there are two ways to organize a comparative analysis report. First, you can discuss everything about comparison point “A” and then go into everything about aspect “B.” Or, you alternate back and forth between points “A” and “B,” sometimes referred to as point-by-point analysis.

Using the AI feature as an example again, you could cover all the pros and cons of building the AI feature, then discuss the benefits and drawbacks of building and maintaining the feature. Or you could compare and contrast each aspect of the AI feature, one at a time. For example, a side-by-side comparison of the AI feature to shopping without it, then proceeding to another point of differentiation.

5. Connect the dots Tie it all together in a way that either confirms or disproves your hypothesis.

For instance, “Building the AI bot would allow our customer service team to save 12% on returns in Q3 while offering optimizations and savings in future strategies. However, it would also increase the product development budget by 43% in both Q1 and Q2. Our budget for product development won’t increase again until series 3 of funding is reached, so despite its potential, we will hold off building the bot until funding is secured and more opportunities and benefits can be proved effective.”

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• > The Research Imagination
• > COMPARATIVE RESEARCH METHODS

Book contents

• Frontmatter
• 1 RESEARCH PROCESS
• 2 THEORY AND METHOD
• 3 RESEARCH DESIGN
• 4 MEASUREMENT
• 5 ETHICAL AND POLITICAL ISSUES
• 7 SURVEY RESEARCH
• 8 INTENSIVE INTERVIEWING
• 9 OBSERVATIONAL FIELD RESEARCH
• 10 FEMINIST METHODS
• 11 HISTORICAL ANALYSIS
• 12 EXPERIMENTAL RESEARCH
• 13 CONTENT ANALYSIS
• 14 AGGREGATE DATA ANALYSIS
• 15 COMPARATIVE RESEARCH METHODS
• 16 EVALUATION RESEARCH
• 17 INDEXES AND SCALES
• 18 BASIC STATISTICAL ANALYSIS
• 19 MULTIVARIATE ANALYSIS AND STATISTICAL SIGNIFICANCE
• EPILOGUE: THE VALUE AND LIMITS OF SOCIAL SCIENCE KNOWLEDGE
• Appendix A A Precoded Questionnaire
• Appendix B Excerpt from a Codebook
• Author Index
• Subject Index

15 - COMPARATIVE RESEARCH METHODS

Published online by Cambridge University Press:  05 June 2012

INTRODUCTION

In contrast to the chapters on survey research, experimentation, or content analysis that described a distinct set of skills, in this chapter, a variety of comparative research techniques are discussed. What makes a study comparative is not the particular techniques employed but the theoretical orientation and the sources of data. All the tools of the social scientist, including historical analysis, fieldwork, surveys, and aggregate data analysis, can be used to achieve the goals of comparative research. So, there is plenty of room for the research imagination in the choice of data collection strategies. There is a wide divide between quantitative and qualitative approaches in comparative work. Most studies are either exclusively qualitative (e.g., individual case studies of a small number of countries) or exclusively quantitative, most often using many cases and a cross-national focus (Ragin, 1991:7). Ideally, increasing numbers of studies in the future will use both traditions, as the skills, tools, and quality of data in comparative research continue to improve.

In almost all social research, we look at how social processes vary and are experienced in different settings to develop our knowledge of the causes and effects of human behavior. This holds true if we are trying to explain the behavior of nations or individuals. So, it may then seem redundant to include a chapter in this book specifically dedicated to comparative research methods when all the other methods discussed are ultimately comparative.

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• COMPARATIVE RESEARCH METHODS
• Paul S. Gray , Boston College, Massachusetts , John B. Williamson , Boston College, Massachusetts , David A. Karp , Boston College, Massachusetts , John R. Dalphin
• Book: The Research Imagination
• Online publication: 05 June 2012
• Chapter DOI: https://doi.org/10.1017/CBO9780511819391.016

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• Cookies & Privacy
• GETTING STARTED
• Introduction
• FUNDAMENTALS
• Acknowledgements
• Research questions & hypotheses
• Concepts, constructs & variables
• Research limitations
• Getting started
• Sampling Strategy
• Research Quality
• Research Ethics
• Data Analysis

Types of quantitative research question

Dissertations that are based on a quantitative research design attempt to answer at least one quantitative research question . In some cases, these quantitative research questions will be followed by either research hypotheses or null hypotheses . However, this article focuses solely on quantitative research questions. Furthermore, since there is more than one type of quantitative research question that you can attempt to answer in a dissertation (i.e., descriptive research questions, comparative research questions and relationship-based research questions), we discuss each of these in this article. If you do not know much about quantitative research and quantitative research questions at this stage, we would recommend that you first read the article, Quantitative research questions: What do I have to think about , as well as an overview article on types of variables , which will help to familiarise you with terms such as dependent and independent variable , as well as categorical and continuous variables [see the article: Types of variables ]. The purpose of this article is to introduce you to the three different types of quantitative research question (i.e., descriptive, comparative and relationship-based research questions) so that you can understand what type(s) of quantitative research question you want to create in your dissertation. Each of these types of quantitative research question is discussed in turn:

Descriptive research questions

Comparative research questions.

• Relationship-based research questions

Descriptive research questions simply aim to describe the variables you are measuring. When we use the word describe , we mean that these research questions aim to quantify the variables you are interested in. Think of research questions that start with words such as "How much?" , "How often?" , "What percentage?" , and "What proportion?" , but also sometimes questions starting "What is?" and "What are?" . Often, descriptive research questions focus on only one variable and one group, but they can include multiple variables and groups. We provide some examples below:

In each of these example descriptive research questions, we are quantifying the variables we are interested in. However, the units that we used to quantify these variables will differ depending on what is being measured. For example, in the questions above, we are interested in frequencies (also known as counts ), such as the number of calories, photos uploaded, or comments on other users? photos. In the case of the final question, What are the most important factors that influence the career choices of Australian university students? , we are interested in the number of times each factor (e.g., salary and benefits, career prospects, physical working conditions, etc.) was ranked on a scale of 1 to 10 (with 1 = least important and 10 = most important). We may then choose to examine this data by presenting the frequencies , as well as using a measure of central tendency and a measure of spread [see the section on Data Analysis to learn more about these and other statistical tests].

However, it is also common when using descriptive research questions to measure percentages and proportions , so we have included some example descriptive research questions below that illustrate this.

In terms of the first descriptive research question about daily calorific intake , we are not necessarily interested in frequencies , or using a measure of central tendency or measure of spread , but instead want understand what percentage of American men and women exceed their daily calorific allowance . In this respect, this descriptive research question differs from the earlier question that asked: How many calories do American men and women consume per day? Whilst this question simply wants to measure the total number of calories (i.e., the How many calories part that starts the question); in this case, the question aims to measure excess ; that is, what percentage of these two groups (i.e., American men and American women) exceed their daily calorific allowance, which is different for males (around 2500 calories per day) and females (around 2000 calories per day).

If you are performing a piece of descriptive , quantitative research for your dissertation, you are likely to need to set quite a number of descriptive research questions . However, if you are using an experimental or quasi-experimental research design , or a more involved relationship-based research design , you are more likely to use just one or two descriptive research questions as a means to providing background to the topic you are studying, helping to give additional context for comparative research questions and/or relationship-based research questions that follow.

Comparative research questions aim to examine the differences between two or more groups on one or more dependent variables (although often just a single dependent variable). Such questions typically start by asking "What is the difference in?" a particular dependent variable (e.g., daily calorific intake) between two or more groups (e.g., American men and American women). Examples of comparative research questions include:

Groups reflect different categories of the independent variable you are measuring (e.g., American men and women = "gender"; Australian undergraduate and graduate students = "educational level"; pirated music that is freely distributed and pirated music that is purchased = "method of illegal music acquisition").

Comparative research questions also differ in terms of their relative complexity , by which we are referring to how many items/measures make up the dependent variable or how many dependent variables are investigated. Indeed, the examples highlight the difference between very simple comparative research questions where the dependent variable involves just a single measure/item (e.g., daily calorific intake) and potentially more complex questions where the dependent variable is made up of multiple items (e.g., Facebook usage behaviour including a wide range of items, such as logins, weekly photo uploads, status changes, etc.); or where each of these items should be written out as dependent variables.

Overall, whilst the dependent variable(s) highlight what you are interested in studying (e.g., attitudes towards music piracy, perceptions towards Internet banking security), comparative research questions are particularly appropriate if your dissertation aims to examine the differences between two or more groups (e.g., men and women, adolescents and pensioners, managers and non-managers, etc.).

Relationship research questions

Whilst we refer to this type of quantitative research question as a relationship-based research question, the word relationship should be treated simply as a useful way of describing the fact that these types of quantitative research question are interested in the causal relationships , associations , trends and/or interactions amongst two or more variables on one or more groups. We have to be careful when using the word relationship because in statistics, it refers to a particular type of research design, namely experimental research designs where it is possible to measure the cause and effect between two or more variables; that is, it is possible to say that variable A (e.g., study time) was responsible for an increase in variable B (e.g., exam scores). However, at the undergraduate and even master's level, dissertations rarely involve experimental research designs , but rather quasi-experimental and relationship-based research designs [see the section on Quantitative research designs ]. This means that you cannot often find causal relationships between variables, but only associations or trends .

However, when we write a relationship-based research question , we do not have to make this distinction between causal relationships, associations, trends and interactions (i.e., it is just something that you should keep in the back of your mind). Instead, we typically start a relationship-based quantitative research question, "What is the relationship?" , usually followed by the words, "between or amongst" , then list the independent variables (e.g., gender) and dependent variables (e.g., attitudes towards music piracy), "amongst or between" the group(s) you are focusing on. Examples of relationship-based research questions are:

As the examples above highlight, relationship-based research questions are appropriate to set when we are interested in the relationship, association, trend, or interaction between one or more dependent (e.g., exam scores) and independent (e.g., study time) variables, whether on one or more groups (e.g., university students).

The quantitative research design that we select subsequently determines whether we look for relationships , associations , trends or interactions . To learn how to structure (i.e., write out) each of these three types of quantitative research question (i.e., descriptive, comparative, relationship-based research questions), see the article: How to structure quantitative research questions .

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Research Questions & Hypotheses

Generally, in quantitative studies, reviewers expect hypotheses rather than research questions. However, both research questions and hypotheses serve different purposes and can be beneficial when used together.

Research Questions

Clarify the research’s aim (farrugia et al., 2010).

• Research often begins with an interest in a topic, but a deep understanding of the subject is crucial to formulate an appropriate research question.
• Descriptive: “What factors most influence the academic achievement of senior high school students?”
• Comparative: “What is the performance difference between teaching methods A and B?”
• Relationship-based: “What is the relationship between self-efficacy and academic achievement?”
• Increasing knowledge about a subject can be achieved through systematic literature reviews, in-depth interviews with patients (and proxies), focus groups, and consultations with field experts.
• Some funding bodies, like the Canadian Institute for Health Research, recommend conducting a systematic review or a pilot study before seeking grants for full trials.
• The presence of multiple research questions in a study can complicate the design, statistical analysis, and feasibility.
• It’s advisable to focus on a single primary research question for the study.
• The primary question, clearly stated at the end of a grant proposal’s introduction, usually specifies the study population, intervention, and other relevant factors.
• The FINER criteria underscore aspects that can enhance the chances of a successful research project, including specifying the population of interest, aligning with scientific and public interest, clinical relevance, and contribution to the field, while complying with ethical and national research standards.

• The P ICOT approach is crucial in developing the study’s framework and protocol, influencing inclusion and exclusion criteria and identifying patient groups for inclusion.

• Defining the specific population, intervention, comparator, and outcome helps in selecting the right outcome measurement tool.
• The more precise the population definition and stricter the inclusion and exclusion criteria, the more significant the impact on the interpretation, applicability, and generalizability of the research findings.
• A restricted study population enhances internal validity but may limit the study’s external validity and generalizability to clinical practice.
• A broadly defined study population may better reflect clinical practice but could increase bias and reduce internal validity.
• An inadequately formulated research question can negatively impact study design, potentially leading to ineffective outcomes and affecting publication prospects.

Checklist: Good research questions for social science projects (Panke, 2018)

Research Hypotheses

Present the researcher’s predictions based on specific statements.

• These statements define the research problem or issue and indicate the direction of the researcher’s predictions.
• Formulating the research question and hypothesis from existing data (e.g., a database) can lead to multiple statistical comparisons and potentially spurious findings due to chance.
• The research or clinical hypothesis, derived from the research question, shapes the study’s key elements: sampling strategy, intervention, comparison, and outcome variables.
• Hypotheses can express a single outcome or multiple outcomes.
• After statistical testing, the null hypothesis is either rejected or not rejected based on whether the study’s findings are statistically significant.
• Hypothesis testing helps determine if observed findings are due to true differences and not chance.
• Hypotheses can be 1-sided (specific direction of difference) or 2-sided (presence of a difference without specifying direction).
• 2-sided hypotheses are generally preferred unless there’s a strong justification for a 1-sided hypothesis.
• A solid research hypothesis, informed by a good research question, influences the research design and paves the way for defining clear research objectives.

Types of Research Hypothesis

• In a Y-centered research design, the focus is on the dependent variable (DV) which is specified in the research question. Theories are then used to identify independent variables (IV) and explain their causal relationship with the DV.
• Example: “An increase in teacher-led instructional time (IV) is likely to improve student reading comprehension scores (DV), because extensive guided practice under expert supervision enhances learning retention and skill mastery.”
• Hypothesis Explanation: The dependent variable (student reading comprehension scores) is the focus, and the hypothesis explores how changes in the independent variable (teacher-led instructional time) affect it.
• In X-centered research designs, the independent variable is specified in the research question. Theories are used to determine potential dependent variables and the causal mechanisms at play.
• Example: “Implementing technology-based learning tools (IV) is likely to enhance student engagement in the classroom (DV), because interactive and multimedia content increases student interest and participation.”
• Hypothesis Explanation: The independent variable (technology-based learning tools) is the focus, with the hypothesis exploring its impact on a potential dependent variable (student engagement).
• Probabilistic hypotheses suggest that changes in the independent variable are likely to lead to changes in the dependent variable in a predictable manner, but not with absolute certainty.
• Example: “The more teachers engage in professional development programs (IV), the more their teaching effectiveness (DV) is likely to improve, because continuous training updates pedagogical skills and knowledge.”
• Hypothesis Explanation: This hypothesis implies a probable relationship between the extent of professional development (IV) and teaching effectiveness (DV).
• Deterministic hypotheses state that a specific change in the independent variable will lead to a specific change in the dependent variable, implying a more direct and certain relationship.
• Example: “If the school curriculum changes from traditional lecture-based methods to project-based learning (IV), then student collaboration skills (DV) are expected to improve because project-based learning inherently requires teamwork and peer interaction.”
• Hypothesis Explanation: This hypothesis presumes a direct and definite outcome (improvement in collaboration skills) resulting from a specific change in the teaching method.
• Example : “Students who identify as visual learners will score higher on tests that are presented in a visually rich format compared to tests presented in a text-only format.”
• Explanation : This hypothesis aims to describe the potential difference in test scores between visual learners taking visually rich tests and text-only tests, without implying a direct cause-and-effect relationship.
• Example : “Teaching method A will improve student performance more than method B.”
• Explanation : This hypothesis compares the effectiveness of two different teaching methods, suggesting that one will lead to better student performance than the other. It implies a direct comparison but does not necessarily establish a causal mechanism.
• Example : “Students with higher self-efficacy will show higher levels of academic achievement.”
• Explanation : This hypothesis predicts a relationship between the variable of self-efficacy and academic achievement. Unlike a causal hypothesis, it does not necessarily suggest that one variable causes changes in the other, but rather that they are related in some way.

Tips for developing research questions and hypotheses for research studies

• Perform a systematic literature review (if one has not been done) to increase knowledge and familiarity with the topic and to assist with research development.
• Learn about current trends and technological advances on the topic.
• Seek careful input from experts, mentors, colleagues, and collaborators to refine your research question as this will aid in developing the research question and guide the research study.
• Use the FINER criteria in the development of the research question.
• Ensure that the research question follows PICOT format.
• Develop a research hypothesis from the research question.
• Ensure that the research question and objectives are answerable, feasible, and clinically relevant.

If your research hypotheses are derived from your research questions, particularly when multiple hypotheses address a single question, it’s recommended to use both research questions and hypotheses. However, if this isn’t the case, using hypotheses over research questions is advised. It’s important to note these are general guidelines, not strict rules. If you opt not to use hypotheses, consult with your supervisor for the best approach.

Farrugia, P., Petrisor, B. A., Farrokhyar, F., & Bhandari, M. (2010). Practical tips for surgical research: Research questions, hypotheses and objectives.  Canadian journal of surgery. Journal canadien de chirurgie ,  53 (4), 278–281.

Hulley, S. B., Cummings, S. R., Browner, W. S., Grady, D., & Newman, T. B. (2007). Designing clinical research. Philadelphia.

Panke, D. (2018). Research design & method selection: Making good choices in the social sciences.  Research Design & Method Selection , 1-368.

• Research Questions: Definitions, Types + [Examples]

Research questions lie at the core of systematic investigation and this is because recording accurate research outcomes is tied to asking the right questions. Asking the right questions when conducting research can help you collect relevant and insightful information that ultimately influences your work, positively. 

The right research questions are typically easy to understand, straight to the point, and engaging. In this article, we will share tips on how to create the right research questions and also show you how to create and administer an online questionnaire with Formplus . 

What is a Research Question? 

A research question is a specific inquiry which the research seeks to provide a response to. It resides at the core of systematic investigation and it helps you to clearly define a path for the research process. 

A research question is usually the first step in any research project. Basically, it is the primary interrogation point of your research and it sets the pace for your work.  

Typically, a research question focuses on the research, determines the methodology and hypothesis, and guides all stages of inquiry, analysis, and reporting. With the right research questions, you will be able to gather useful information for your investigation. 

Types of Research Questions 

Research questions are broadly categorized into 2; that is, qualitative research questions and quantitative research questions. Qualitative and quantitative research questions can be used independently and co-dependently in line with the overall focus and objectives of your research. 

If your research aims at collecting quantifiable data , you will need to make use of quantitative research questions. On the other hand, qualitative questions help you to gather qualitative data bothering on the perceptions and observations of your research subjects. 

Qualitative Research Questions  

A qualitative research question is a type of systematic inquiry that aims at collecting qualitative data from research subjects. The aim of qualitative research questions is to gather non-statistical information pertaining to the experiences, observations, and perceptions of the research subjects in line with the objectives of the investigation. 

Types of Qualitative Research Questions  

• Ethnographic Research Questions

As the name clearly suggests, ethnographic research questions are inquiries presented in ethnographic research. Ethnographic research is a qualitative research approach that involves observing variables in their natural environments or habitats in order to arrive at objective research outcomes. 

These research questions help the researcher to gather insights into the habits, dispositions, perceptions, and behaviors of research subjects as they interact in specific environments. 

Ethnographic research questions can be used in education, business, medicine, and other fields of study, and they are very useful in contexts aimed at collecting in-depth and specific information that are peculiar to research variables. For instance, asking educational ethnographic research questions can help you understand how pedagogy affects classroom relations and behaviors. 

This type of research question can be administered physically through one-on-one interviews, naturalism (live and work), and participant observation methods. Alternatively, the researcher can ask ethnographic research questions via online surveys and questionnaires created with Formplus.  

Examples of Ethnographic Research Questions

• Why do you use this product?
• Have you noticed any side effects since you started using this drug?
• Does this product meet your needs?

• Case Studies

A case study is a qualitative research approach that involves carrying out a detailed investigation into a research subject(s) or variable(s). In the course of a case study, the researcher gathers a range of data from multiple sources of information via different data collection methods, and over a period of time. 

The aim of a case study is to analyze specific issues within definite contexts and arrive at detailed research subject analyses by asking the right questions. This research method can be explanatory, descriptive , or exploratory depending on the focus of your systematic investigation or research. 

An explanatory case study is one that seeks to gather information on the causes of real-life occurrences. This type of case study uses “how” and “why” questions in order to gather valid information about the causative factors of an event. 

Descriptive case studies are typically used in business researches, and they aim at analyzing the impact of changing market dynamics on businesses. On the other hand, exploratory case studies aim at providing answers to “who” and “what” questions using data collection tools like interviews and questionnaires. 

Some questions you can include in your case studies are: 

• Why did you choose our services?
• How has this policy affected your business output?
• What benefits have you recorded since you started using our product?

An interview is a qualitative research method that involves asking respondents a series of questions in order to gather information about a research subject. Interview questions can be close-ended or open-ended , and they prompt participants to provide valid information that is useful to the research. 

An interview may also be structured, semi-structured , or unstructured , and this further influences the types of questions they include. Structured interviews are made up of more close-ended questions because they aim at gathering quantitative data while unstructured interviews consist, primarily, of open-ended questions that allow the researcher to collect qualitative information from respondents. 

You can conduct interview research by scheduling a physical meeting with respondents, through a telephone conversation, and via digital media and video conferencing platforms like Skype and Zoom. Alternatively, you can use Formplus surveys and questionnaires for your interview. 

Examples of interview questions include: 

• What challenges did you face while using our product?
• What specific needs did our product meet?
• What would you like us to improve our service delivery?

Quantitative Research Questions

Quantitative research questions are questions that are used to gather quantifiable data from research subjects. These types of research questions are usually more specific and direct because they aim at collecting information that can be measured; that is, statistical information. 

Types of Quantitative Research Questions

• Descriptive Research Questions

Descriptive research questions are inquiries that researchers use to gather quantifiable data about the attributes and characteristics of research subjects. These types of questions primarily seek responses that reveal existing patterns in the nature of the research subjects. 

It is important to note that descriptive research questions are not concerned with the causative factors of the discovered attributes and characteristics. Rather, they focus on the “what”; that is, describing the subject of the research without paying attention to the reasons for its occurrence. 

Descriptive research questions are typically closed-ended because they aim at gathering definite and specific responses from research participants. Also, they can be used in customer experience surveys and market research to collect information about target markets and consumer behaviors. 

Descriptive Research Question Examples

• How often do you make use of our fitness application?
• How much would you be willing to pay for this product?

• Comparative Research Questions

A comparative research question is a type of quantitative research question that is used to gather information about the differences between two or more research subjects across different variables. These types of questions help the researcher to identify distinct features that mark one research subject from the other while highlighting existing similarities. 

Asking comparative research questions in market research surveys can provide insights on how your product or service matches its competitors. In addition, it can help you to identify the strengths and weaknesses of your product for a better competitive advantage.  

The 5 steps involved in the framing of comparative research questions are: 

• Choose your starting phrase
• Identify and name the dependent variable
• Identify the groups you are interested in
• Identify the appropriate adjoining text
• Write out the comparative research question

Comparative Research Question Samples 

• What are the differences between a landline telephone and a smartphone?
• What are the differences between work-from-home and on-site operations?

• Relationship-based Research Questions  

Just like the name suggests, a relationship-based research question is one that inquires into the nature of the association between two research subjects within the same demographic. These types of research questions help you to gather information pertaining to the nature of the association between two research variables. 

Relationship-based research questions are also known as correlational research questions because they seek to clearly identify the link between 2 variables. 

Read: Correlational Research Designs: Types, Examples & Methods

Examples of relationship-based research questions include: 

• What is the relationship between purchasing power and the business site?
• What is the relationship between the work environment and workforce turnover?

Examples of a Good Research Question

Since research questions lie at the core of any systematic investigations, it is important to know how to frame a good research question. The right research questions will help you to gather the most objective responses that are useful to your systematic investigation. 

A good research question is one that requires impartial responses and can be answered via existing sources of information. Also, a good research question seeks answers that actively contribute to a body of knowledge; hence, it is a question that is yet to be answered in your specific research context.

• Open-Ended Questions

 An open-ended question is a type of research question that does not restrict respondents to a set of premeditated answer options. In other words, it is a question that allows the respondent to freely express his or her perceptions and feelings towards the research subject. 

Examples of Open-ended Questions

• How do you deal with stress in the workplace?
• What is a typical day at work like for you?
• Close-ended Questions

A close-ended question is a type of survey question that restricts respondents to a set of predetermined answers such as multiple-choice questions . Close-ended questions typically require yes or no answers and are commonly used in quantitative research to gather numerical data from research participants. 

Examples of Close-ended Questions

• Did you enjoy this event?
• How likely are you to recommend our services?
• Very Likely
• Somewhat Likely
• Likert Scale Questions

A Likert scale question is a type of close-ended question that is structured as a 3-point, 5-point, or 7-point psychometric scale . This type of question is used to measure the survey respondent’s disposition towards multiple variables and it can be unipolar or bipolar in nature. 

Example of Likert Scale Questions

• How satisfied are you with our service delivery?
• Very dissatisfied
• Not satisfied
• Very satisfied
• Rating Scale Questions

A rating scale question is a type of close-ended question that seeks to associate a specific qualitative measure (rating) with the different variables in research. It is commonly used in customer experience surveys, market research surveys, employee reviews, and product evaluations. 

Example of Rating Questions

• How would you rate our service delivery?

  Examples of a Bad Research Question

Knowing what bad research questions are would help you avoid them in the course of your systematic investigation. These types of questions are usually unfocused and often result in research biases that can negatively impact the outcomes of your systematic investigation. 

• Loaded Questions

A loaded question is a question that subtly presupposes one or more unverified assumptions about the research subject or participant. This type of question typically boxes the respondent in a corner because it suggests implicit and explicit biases that prevent objective responses. 

Example of Loaded Questions

• Have you stopped smoking?
• Where did you hide the money?
• Negative Questions

A negative question is a type of question that is structured with an implicit or explicit negator. Negative questions can be misleading because they upturn the typical yes/no response order by requiring a negative answer for affirmation and an affirmative answer for negation. 

Examples of Negative Questions

• Would you mind dropping by my office later today?
• Didn’t you visit last week?
• Leading Questions  

A l eading question is a type of survey question that nudges the respondent towards an already-determined answer. It is highly suggestive in nature and typically consists of biases and unverified assumptions that point toward its premeditated responses. 

Examples of Leading Questions

• If you enjoyed this service, would you be willing to try out our other packages?
• Our product met your needs, didn’t it?

Read More: Leading Questions: Definition, Types, and Examples

How to Use Formplus as Online Research Questionnaire Tool  

With Formplus, you can create and administer your online research questionnaire easily. In the form builder, you can add different form fields to your questionnaire and edit these fields to reflect specific research questions for your systematic investigation. 

Here is a step-by-step guide on how to create an online research questionnaire with Formplus: 

• Sign in to your Formplus accoun t, then click on the “create new form” button in your dashboard to access the Form builder.

• In the form builder, add preferred form fields to your online research questionnaire by dragging and dropping them into the form. Add a title to your form in the title block. You can edit form fields by clicking on the “pencil” icon on the right corner of each form field.

• Save the form to access the customization section of the builder. Here, you can tweak the appearance of your online research questionnaire by adding background images, changing the form font, and adding your organization’s logo.

• Finally, copy your form link and share it with respondents. You can also use any of the multiple sharing options available.

Conclusion  

The success of your research starts with framing the right questions to help you collect the most valid and objective responses. Be sure to avoid bad research questions like loaded and negative questions that can be misleading and adversely affect your research data and outcomes. 

Your research questions should clearly reflect the aims and objectives of your systematic investigation while laying emphasis on specific contexts. To help you seamlessly gather responses for your research questions, you can create an online research questionnaire on Formplus.  

Connect to Formplus, Get Started Now - It's Free!

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Chapter 1 Study Objectives and Questions

Scott R Smith , PhD.

The steps involved in the process of developing research questions and study objectives for conducting observational comparative effectiveness research (CER) are described in this chapter. It is important to begin with identifying decisions under consideration, determining who the decisionmakers and stakeholders in the specific area of research under study are, and understanding the context in which decisions are being made. Synthesizing the current knowledge base and identifying evidence gaps is the next important step in the process, followed by conceptualizing the research problem, which includes developing questions that address the gaps in existing evidence. Understanding the stage of knowledge that the study is designed to address will come from developing these initial questions. Identifying which questions are critical to reduce decisional uncertainty and minimize gaps in the current knowledge base is an important part of developing a successful framework. In particular, it is beneficial to look at what study populations, interventions, comparisons, outcomes, timeframe, and settings (PICOTS framework) are most important to decisionmakers in weighing the balance of harms and benefits of action. Some research questions are easier to operationalize than others, and study limitations should be recognized and accepted from an early stage. The level of new scientific evidence that is required by the decisionmaker to make a decision or to take action must be recognized. Lastly, the magnitude of effect must be specified. This can mean defining what is a clinically meaningful difference in the study endpoints from the perspective of the decisionmaker and/or defining what is a meaningful difference from the patient's perspective.

The foundation for designing a new research protocol is the study's objectives and the questions that will be investigated through its implementation. All aspects of study design and analysis are based on the objectives and questions articulated in a study's protocol. Consequently, it is exceedingly important that a study's objectives and questions be formulated meticulously and written precisely in order for the research to be successful in generating new knowledge that can be used to inform health care decisions and actions.

An important aspect of CER 1 and other forms of translational research is the potential for early involvement and inclusion of patients and other stakeholders to collaborate with researchers in identifying study objectives, key questions, major study endpoints, and the evidentiary standards that are needed to inform decisionmaking. The involvement of stakeholders in formulating the research questions increases the applicability of the study to the end-users and facilitates appropriate translation of the results into health care practice and use by patient communities. While stakeholders may be defined in multiple ways, for the purposes of this User's Guide , a broad definition will be used. Hence, stakeholders are defined as individuals or organizations that use scientific evidence for decisionmaking and therefore have an interest in the results of new research. Implicit in this definition of stakeholders is the importance for stakeholders to understand the scientific process, including considerations of bioethics and the limitations of research, particularly with regard to studies involving human subjects. Ideally, stakeholders also should express commitment to using objective scientific evidence to inform their decisionmaking and recognize that disregarding sound scientific methods often will undermine decisionmaking. For stakeholder organizations, it is also advantageous if the organization has well-established processes for transparently reviewing and incorporating research findings into decisions as well as organized channels for disseminating research results.

There are at least seven essential steps in the conceptualization and development of a research question or set of questions for an observational CER protocol. These steps are presented as a general framework in Table 1.1 below and elaborated upon in the subsequent sections of this chapter. The framework is based on the principle that researchers and stakeholders will work together to objectively lay out the research problems, research questions, study objectives, and key parameters for which scientific evidence is needed to inform decisionmaking or health care actions. The intent of this framework is to facilitate communication between researchers and stakeholders in conceptualizing the research problem and the design of a study (or a program of research involving a series of studies) in order to maximize the potential that new knowledge will be created from the research with results that can inform decisionmaking. To do this, research results must be relevant, applicable, unbiased and sufficient to meet the evidentiary threshold for decisionmaking or action by stakeholders. In order for the results to be valid and credible, all persons involved must be committed to protecting the integrity of the research from bias and conflicts of interest. Most importantly, the study must be designed to protect the rights, welfare, and well-being of subjects involved in the research.

Framework for developing and conceptualizing a CER protocol.

• Identifying Decisions, Decisionmakers, Actions, and Context

In order for research findings to be useful for decisionmaking, the study protocol should clearly articulate the decisions or actions for which stakeholders seek new scientific evidence. While only some studies may be sufficiently robust for making decisions or taking action, statements that describe the stakeholders' decisions will help those who read the protocol understand the rationale for the study and its potential for informing decisions or for translating the findings into changes in health care practices. This information also improves the ability of protocol readers to understand the purpose of the study so they can critically review its design and provide recommendations for ways it may be potentially improved. If stakeholders have a need to make decisions within a critical time frame for regulatory, ethical, or other reasons, this interval should be expressed to researchers and described in the protocol. In some cases, the time frame for decisionmaking may influence the choice of outcomes that can be studied and the study designs that can be used. For some stakeholders' questions, research and decisionmaking may need to be divided into stages, since it may take years for outcomes with long lag times to occur, and research findings will be delayed until they do.

In writing this section of the protocol, investigators should ask stakeholders to describe the context in which the decision will be made or actions will be taken. This context includes the background and rationale for the decision, key areas of uncertainty and controversies surrounding the decision, ways scientific evidence will be used to inform the decision, the process stakeholders will use to reach decisions based on scientific evidence, and a description of the key stakeholders who will use or potentially be affected by the decision. By explaining these contextual factors that surround the decision, investigators will be able to work with stakeholders to determine the study objectives and other major parameters of the study. This work also provides the opportunity to discuss how the tools of science can be applied to generate new evidence for informing stakeholder decisions and what limits may exist in those tools. In addition, this initial step begins to clarify the number of analyses necessary to generate the evidence that stakeholders need to make a decision or take other actions with sufficient certainty about the outcomes of interest. Finally, the contextual information facilitates advance planning and discussions by researchers and stakeholders about approaches to translation and implementation of the study findings once the research is completed.

• Synthesizing the Current Knowledge Base

In designing a new study, investigators should conduct a comprehensive review of the literature, critically appraise published studies, and synthesize what is known related to the research objectives. Specifically, investigators should summarize in the protocol what is known about the efficacy, effectiveness, and safety of the interventions and about the outcomes being studied. Furthermore, investigators should discuss measures used in prior research and whether these measures have changed over time. These descriptions will provide background on the knowledge base for the current protocol. It is equally important to identify which elements of the research problem are unknown because evidence is absent, insufficient, or conflicting.

For some research problems, systematic reviews of the literature may be available and can be useful resources to guide the study design. The AHRQ Evidence-based Practice Centers 2 and the Cochrane Collaboration 3 are examples of established programs that conduct thorough systematic reviews, technology assessments, and specialized comparative effectiveness reviews using standardized methods. When available, systematic reviews and technology assessments should be consulted as resources for investigators to assess the current knowledge base when designing new studies and working with stakeholders.

When reviewing the literature, investigators and stakeholders should identify the most relevant studies and guidelines about the interventions that will be studied. This will allow readers to understand how new research will add to the existing knowledge base. If guidelines are a source of information, then investigators should examine whether these guidelines have been updated to incorporate recent literature. In addition, investigators should assess the health sciences literature to determine what is known about expected effects of the interventions based on current understanding of the pathophysiology of the target condition. Furthermore, clinical experts should be consulted to help identify gaps in current knowledge based on their expertise and interactions with patients. Relevant questions to ask to assess the current knowledge base for development of an observational CER study protocol are:

• What are the most relevant studies and guidelines about the interventions, and why are these studies relevant to the protocol (e.g., because of the study findings, time period conducted, populations studied, etc.)?
• Are there differences in recommendations from clinical guidelines that would indicate clinical equipoise?
• What else is known about the expected effects of the interventions based on current understanding of the pathophysiology of the targeted condition?
• What do clinical experts say about gaps in current knowledge?
• Conceptualizing the Research Problem

In designing studies for addressing stakeholder questions, investigators should engage multiple stakeholders in discussions about how the research problem is conceptualized from the stakeholders' perspectives. These discussions will aid in designing a study that can be used to inform decisionmaking. Together, investigators and stakeholders should work collaboratively to determine the major objectives of the study based on the health care decisions facing stakeholders. As pointed out by Heckman, 4 research objectives should be formalized outside considerations of available data and the inferences that can be made from various statistical estimation approaches. Doing so will allow the study objectives to be determined by stakeholder needs rather than the availability of existing data. A thorough discussion of these considerations is beyond the scope of this chapter, but some important considerations are summarized in supplement 1 of this User's Guide.

In order to conceptualize the problem, stakeholders and other experts should be asked to describe the potential relationships between the intervention and important health outcomes. This description will help researchers develop preliminary hypotheses about the stated relationships. Likewise, stakeholders, researchers, and other experts should be asked to enumerate all major assumptions that affect the conceptualization of the research problem, but will not be directly examined in the study. These assumptions should be described in the study protocol and in reporting final study results. By clearly stating the assumptions, protocol reviewers will be better able to assess how the assumptions may influence the study results.

Based on the conceptualization of the research problem, investigators and stakeholders should make use of applicable scientific theory in designing the study protocol and developing the analytic plan. Research that is designed using a validated theory has a higher potential to reach valid conclusions and improve the overall understanding of a phenomenon. In addition, theory will aid in the interpretation of the study findings, since these results can be put in context with the theory and with past research. Depending on the nature of the inquiry, theory from specific disciplines such as health behavior, sociology, or biology could be the basis for designing the study. In addition, the research team should work with stakeholders to develop a conceptual model or framework to guide the implementation of the study. The protocol should also contain one or more figures that summarize the conceptual model or framework as it applies to the study. These figures will allow readers to understand the theoretical or conceptual basis for the study and how the theory is operationalized for the specific study. The figures should diagram relationships between study variables and outcomes to help readers of the protocol visualize relationships that will be examined in the study.

For research questions about causal associations between exposures and outcomes, causal models such as directed acyclic graphs (DAGs) may be useful tools in designing the conceptual framework for the study and developing the analytic plan. The value of DAGs in the context of refining study questions is that they make assumptions explicit in ways that can clarify gaps in knowledge. Free software such as DAGitty is available for creating, editing, and analyzing causal models. A thorough discussion of DAGs is beyond the scope of this chapter, but more information about DAGs is available in supplement 2 of this User's Guide.

The following list of questions may be useful for defining and describing a study's conceptual framework in a CER protocol:

• What are the main objectives of the study, as related to specific decisions to be made?
• What are the major assumptions of decisionmakers, investigators, and other experts about the problem or phenomenon being studied?
• What relationships, if any, do experts hypothesize exist between interventions and outcomes?

What is known about each element of the model?

Can relationships be expressed by causal diagrams?

• Determining the Stage of Knowledge Development for the Study Design

The scientific method is a process of observation and experimentation in order for the evidence base to be expanded as new knowledge is developed. Therefore, stakeholders and investigators should consider whether a program of research comprising a sequential or concurrent series of studies, rather than a single study, is needed to adequately make a decision. Staging the research into multiple studies and making interim decisions may improve the final decision and make judicious use of scarce research resources. In some cases, the results of preliminary studies, descriptive epidemiology, or pilot work may be helpful in making interim decisions and designing further research. Overall, a planned series of related studies or a program of research may be needed to adequately address stakeholders' decisions.

An example of a structured program of research is the four phases of clinical studies used by the Food and Drug Administration (FDA) to reach a decision about whether or not a new drug is safe and efficacious for market approval in the United States. Using this analogy, the final decision about whether a drug is efficacious and safe to be marketed for specific medical indications is based upon the accumulation of scientific evidence from a series of studies (i.e., not from any individual study), which are conducted in multiple sequential phases. The evidence generated in each phase is reviewed to make interim decisions about the safety and efficacy of a new pharmaceutical until ultimately all the evidence is reviewed to make a final decision about drug approval.

Under the FDA model for decisionmaking, initial research involves laboratory and animal tests. If the evidence generated in these studies indicates that the drug is active and not toxic, the sponsor submits an application to the FDA for an “investigational new drug.” If the FDA approves, human testing for safety and efficacy can begin. The first phase of human testing is usually conducted in a limited number of healthy volunteers (phase 1). If these trials show evidence that the product is safe in healthy volunteers, then the drug is further studied in a small number of volunteers who have the targeted condition (phase 2). If phase 2 studies show that the drug has a therapeutic effect and lacks significant adverse effects, trials with large numbers of people are conducted to determine the drug's safety and efficacy (phase 3). Following these trials, all relevant scientific studies are submitted to the FDA for a decision about whether the drug should be approved for marketing. If there are additional considerations like special safety issues, observational studies may be required to assess the safety of the drug in routine clinical care after the drug is approved for marketing (phase 4). Overall, the decisionmaking and research are staged so that the cumulative findings from all studies are used by the FDA to make interim decisions until the final decision is made about whether a medical product will be approved for marketing.

While most decisions about the comparative effectiveness of interventions will not need such extensive testing, it still may be prudent to stage research in a way that allows for interim decisions and sequentially more rigorous studies. On the other hand conditional approval or interim decisions may risk confusing patients and other stakeholders about the extent to which current evidence indicates that a treatment is effective and safe for all individuals with a health condition. For instance, under this staged approach new treatments could rapidly diffuse into a market even when there is limited evidence of long-term effectiveness and safety for all potential users. An illustrative example of this is the case of lung-volume reduction surgery, which was increasingly being used to treat severe emphysema despite limited evidence supporting its safety and efficacy until new research raised questions about the safety of the procedure. 6

Below is one potential categorization for the stages of knowledge development as related to informing decisions about questions of comparative effectiveness:

• Descriptive analysis
• Hypothesis generation
• Feasibility studies/proof of concept
• Hypothesis supporting
• Hypothesis testing

The first stages (i.e., descriptive analysis, hypothesis generation, and feasibility studies) are not mutually exclusive and usually are not intended to provide conclusive results for most decisions. Instead these stages provide preliminary evidence or feasibility testing before larger, more resource-intensive studies are launched. Results from these categories of studies may allow for interim decisionmaking (e.g., conditional approval for reimbursement of a treatment while further research is conducted). While a phased approach to research may postpone the time when a conclusive decision can be reached it does help to conserve resources such as those that may be consumed in launching a large multicenter study when a smaller study may be sufficient. Investigators will need to engage stakeholders to prioritize what stage of research may be most useful for the practical range of decisions that will be made.

Investigators should discuss in the protocol what stage of knowledge the current study will fulfill in light of the actions available to different stakeholders. This will allow reviewers of the protocol to assess the degree to which the evidence generated in the study holds the potential to fill specific knowledge gaps. For studies that are described in the protocol as preliminary, this may also help readers understand other tradeoffs that were made in the design of the study, in terms of methodological limitations that were accepted a priori in order to gather preliminary information about the research questions.

• Defining and Refining Study Questions Using PICOTS Framework

As recommended in other AHRQ methods guides, 7 investigators should engage stakeholders in a dialogue in order to understand the objectives of the research in practical terms, particularly so that investigators know the types of decisions that the research may affect. In working with stakeholders to develop research questions that can be studied with scientific methods, investigators may ask stakeholders to identify six key components of the research questions that will form the basis for designing the study. These components are reflected in the PICOTS typology and are shown below in Table 1.2 . These components represent the critical elements that will help investigators design a study that will be able to address the stakeholders' needs. Additional references that expand upon how to frame research questions can be found in the literature. 8 - 9

PICOTS typology for developing research questions.

The PICOTS typology outlines the key parts of the research questions that the study will be designed to address. 10 As a new research protocol is developed these questions can be presented in preliminary form and refined as other steps in the process are implemented. After the preliminary questions are refined, investigators should examine the questions to make sure that they will meet the needs of the stakeholders. In addition, they should assess whether the questions can be answered within the timeframe allotted and with the resources that are available for the study.

Since stakeholders ultimately determine effectiveness, it is important for investigators to ensure that the study endpoints and outcomes will meet their needs. Stakeholders need to articulate to investigators the health outcomes that are most important for a particular stakeholder to make decisions about treatment or take other health care actions. The endpoints that stakeholders will use to determine effectiveness may vary considerably. Unlike efficacy trials, in which clinical endpoints and surrogate measures are frequently used to determine efficacy, effectiveness may need to be determined based on several measures, many of which are not biological. These endpoints may be categorized as clinical endpoints, patient-reported outcomes and quality of life, health resource utilization, and utility measures. Types of measures that could be used are mortality, morbidity and adverse effects, quality of life, costs, or multiple outcomes. Chapter 6 gives a more extensive discussion of potential outcome measures of effectiveness.

The reliability, validity, and accuracy of study instruments to validly measure the concepts they purport to measure will also need to be acceptable to stakeholders. For instance, if stakeholders are interested in quality of life as an outcome, but do not believe there is an adequate measure of quality of life, then measurement development may need to be done prior to study initiation or other measures will need to be identified by stakeholders.

• Discussing Evidentiary Need and Uncertainty

Investigators and stakeholders should discuss the tradeoffs of different study designs that may be used for addressing the research questions. This dialogue will help researchers design a study that will be relevant and useful to the needs of stakeholders. All study designs have strengths and weaknesses, the latter of which may limit the conclusiveness of the final study results. Likewise, some decisions may require evidence that cannot be obtained from certain designs. In addition to design weaknesses, there are also practical tradeoffs that need to be considered in terms of research resources, like the time needed to complete the study, the availability of data, investigator expertise, subject recruitment, human subjects protection, research budget, difference to be detected, and lost-opportunity costs of doing the research instead of other studies that have priority for stakeholders. An important decision that will need to be made is whether or not randomization is needed for the questions being studied. There are several reasons why randomization might be needed, such as determining whether an FDA-approved drug can be used for a new use or indication that was not studied as part of the original drug approval process. A paper by Concato includes a thorough discussion of issues to consider when deciding whether randomization is necessary. 11

In discussing the tradeoffs of different study designs, researchers and stakeholders may wish to discuss the principal goals of research and ensure that researchers and stakeholders are aligned in their understanding of what is meant by scientific evidence. Fundamentally, research is a systematic investigation that uses scientific methods to measure, collect, and analyze data for the advancement of knowledge. This advancement is through the independent peer review and publication of study results, which are collectively referred to as scientific evidence. One definition of scientific evidence has been proposed by Normand and McNeil 12 as:

… the accumulation of information to support or refute a theory or hypothesis. … The idea is that assembling all the available information may reduce uncertainty about the effectiveness of the new technology compared to existing technologies in a setting where we believe particular relationships exist but are uncertain about their relevance …

While the primary aim of research is to produce new knowledge , the Normand and McNeil concept of evidence emphasizes that research helps create knowledge by reducing uncertainty about outcomes. However, rarely, if at all, does research eliminate all uncertainty around most decisions. In some cases, successful research will answer an important question and reduce uncertainty related to that question, but it may also increase uncertainty by leading to more, better informed questions regarding unknowns. As a result, nearly all decisions face some level of uncertainty even in a field where a body of research has been completed. This distinction is also critical because it helps to separate the research and subsequent actions that decisionmakers may take based on their assessment of the research results. Those subsequent actions may be informed by the research findings but will also be based on stakeholders' values and resources. Hence, as the definition by Normand and McNeil implies, research generates evidence but stakeholders decide whether to act on the evidence. Scientific evidence informs decisions to the extent it can adequately reduce the uncertainty about the problem for the stakeholder. Ultimately, treatment decisions are only guided by an assessment of the certainty that a course of therapy will lead to the outcomes of interest and the likelihood that this conclusion will be affected by the results of future studies.

In conceptualizing a study design, it is important for investigators to understand what constitutes sufficient and valid evidence from the stakeholder's perspective. In other words, what is the type of evidence that will be required to inform the stakeholder's decision to act or make a conscious decision not to take action? Evidence needed for action may vary by type of stakeholder and the scope of decisions that the stakeholder is making. For instance, a stakeholder who is making a population-based decision such as whether to provide insurance coverage for a new medical device with many alternatives may need substantially robust research findings in order to take action and provide that insurance coverage. In this example, the stakeholder may only accept as evidence a study with strong internal validity and generalizability (i.e., one conducted in a nationally representative sample of patients with the disease). On the other hand a patient who has a health condition where there are few treatments may be willing to accept lower-quality evidence in order to make a decision about whether to proceed with treatment despite a higher level of uncertainty about the outcome.

In many cases, there may exist a gradient of actions that can be taken based on available evidence. Quanstrum and Hayward 13 have discussed this gradient and argued that health care decisionmaking is changing, partly because more information is available to patients and other stakeholders about treatment options. As shown in the upper panel (A) in Figure 1.1 , many people may currently believe that health care treatment decisions are basically uniform for most people and under most circumstances. Panel A represents a hypothetical treatment whereby there is an evidentiary threshold or a point at which treatment is always beneficial and should be recommended. On the other hand below this threshold care provides no benefits and treatment should be discouraged. Quanstrum and Hayward argue that increasingly health care decisions are more like the lower panel (B). This panel portrays health care treatments as providing a large zone of discretion where benefits may be low or modest for most people. While above this zone treatment may always be recommended, individuals who fall within the zone may have questionable health benefits from treatment. As a result, different decisionmakers may take different actions based on their individual preferences.

Conceptualization of clinical decisionmaking. See Quanstrum KH, Hayward RA (Reference #). This figure is copyrighted by the Massachusetts Medical Society and reprinted with permission.

In light of this illustration, the following questions are suggested for discussion with stakeholders to help elicit the amount of uncertainty that is acceptable so that the study design can reach an appropriate level of evidence for the decision at hand:

• What level of new scientific evidence does the decisionmaker need to make a decision or take action?
• What quality of evidence is needed for the decisionmaker to act?
• What level of certainty of the outcome is needed by the decisionmaker(s)?
• How specific does the evidence need to be?
• Will decisions require consensus of multiple parties?

Additional Considerations When Considering Evidentiary Needs

As mentioned earlier, different stakeholders may disagree on the usefulness of different research designs, but it should be pointed out that this disagreement may be because stakeholders have different scopes of decisions to make. For example, high-quality research that is conclusive may be needed to make a decision that will affect the entire nation. On the other hand, results with more uncertainty as to the magnitude of the effect estimate(s) may be acceptable in making some decisions such as those affecting fewer people or where the risks to health are low. Often this disagreement occurs when different stakeholders debate whether evidence is needed from a new randomized controlled trial or whether evidence can be obtained from an analysis of an existing database. In this debate, both sides need to clarify whether they are facing the same decision or the decisions are different, particularly in terms of their scope.

Groups committed to evidence-based decisionmaking recognize that scientific evidence is only one component of the process of making decisions. Evidence generation is the goal of research, but evidence alone is not the only facet of evidence-based decisionmaking. In addition to scientific evidence, decisionmaking involves the consideration of (a) values, particularly the values placed on benefits and harms, and (b) resources. 14 Stakeholder differences in values and resources may mean that different decisions are made based on the same scientific evidence. Moreover, differences in values may create conflict in the decisionmaking process. One stakeholder may believe a particular study outcome is most important from their perspective, while another stakeholder may believe a different outcome is the most important for determining effectiveness.

Likewise, there may be inherent conflicts in values between individual decisionmaking and population decisionmaking, even though these decisions are often interrelated. For example, an individual may have a higher tolerance for treatment risk in light of the expected treatment benefits for him or her. On the other hand a regulatory health authority may determine that the population risk is too great without sufficient evidence that treatment provides benefits to the population. An example of this difference in perspective can be seen with how different decisionmakers responded to evidence about the drug Avastin ® (bevacizumab) for the treatment of metastatic breast cancer. In this case, the FDA revoked their approval of the breast cancer indication for Avastin after concluding that the drug had not been shown to be safe and effective for that use. Nonetheless, Medicare, the public insurance program for the elderly and disabled continued to allow coverage when a physician prescribes the drug, even for breast cancer. Likewise, some patient groups were reported to be concerned by the decision since it presumably would deny some women access to Avastin treatment. For a more thorough discussion of these issues around differences in perspective, the reader is referred to an article by Atkins 15 and the examples in Table 1.3 below.

Examples of individual versus population decisions (Adapted from Atkins, 2007).

• Specifying Magnitude of Effect

In order for decisions to be objective, it is important for there to be an a priori discussion with stakeholders about the magnitude of effect that stakeholders believe represents a meaningful difference between treatment options. Researchers will be familiar with the basic tenet that statistically significant differences do not always represent clinically meaningful differences. Hence, researchers and stakeholders will need to have knowledge of the instruments that are used to measure differences and the accuracy, limitations, and properties of those instruments. Three key questions are recommended to use when eliciting from stakeholders the effect sizes that are important to them for making a decision or taking action:

• How do patients and other stakeholders define a meaningful difference between interventions?
• How do previous studies and reviews define a meaningful difference?
• Are patients and other stakeholders interested in superiority or noninferiority as it relates to decisionmaking?
• Challenges to Developing Study Questions and Initial Solutions

In developing CER study objectives and questions, there are some potential challenges that face researchers and stakeholders. The involvement of patients and other stakeholders in determining study objectives and questions is a relatively new paradigm, but one that is consistent with established principles of translational research. A key principle of translational research is that users need to be involved in research at the earliest stages for the research to be adopted. 16 In addition, most research is currently initiated by an investigator, and traditionally there have been few incentives (and some disincentives) to involving others in designing a new research study. Although the research paradigm is rapidly shifting, 17 there is little information about how to structure, process, and evaluate outcomes from initiatives that attempt to engage stakeholders in developing study questions and objectives with researchers. As different approaches are taken to involve stakeholders in the research process, researchers will learn how to optimize the process of stakeholder involvement and improve the applicability of research to the end-users.

The bringing together of stakeholders may create some general challenges to the research team. For instance, it may be difficult to identify, engage, or manage all stakeholders who are interested in developing and using scientific evidence for addressing a problem. A process that allows for public commenting on research protocols through Internet postings may be helpful in reaching the widest network of interested stakeholders. Nevertheless, finding stakeholders who can represent all perspectives may not always be practical or available to the study team. In addition, competing interests among stakeholders may make prioritization of research questions challenging. Different stakeholders have different needs and this may make prioritization of research difficult. Nonetheless, as the science of translational research evolves, the collaboration of researchers with stakeholders will likely become increasingly the standard of practice in designing new research.

To assist researchers and stakeholders with working together, AHRQ has published several online resources to facilitate the involvement of stakeholders in the research process. These include a brief guide for stakeholders that highlights opportunities for taking part in AHRQ's Effective Health Care Program, a facilitation primer with strategies for working with diverse stakeholder groups, a table of suggested tasks for researchers to involve stakeholders in the identification and prioritization of future research, and learning modules with slide presentations on engaging stakeholders in the Effective Health Care Program. 18 - 19 In addition, AHRQ supports the Evidence-based Practice Centers in working with various stakeholders to further develop and prioritize decisionmakers' future research needs, which are published in a series of reports on AHRQ's Web site and on the National Library of Medicine's open-access Bookshelf. 20

Likewise, AHRQ supports the active involvement of patients and other stakeholders in the AHRQ DEcIDE program, in which different models of engagement have been used. These models include hosting in-person meetings with stakeholders to create research agendas; 21 - 22 developing research based on questions posed by public payers such as Centers for Medicare and Medicaid Services; addressing knowledge gaps that have been identified in AHRQ systematic reviews through new research; and supporting five research consortia, each of which involves researchers, patients, and other stakeholders working together to develop, prioritize, and implement research studies.

• Summary and Conclusion

This chapter provides a framework for formulating study objectives and questions, for a research protocol on a CER topic. Implementation of the framework involves collaboration between researchers and stakeholders in conceptualizing the research objectives and questions and the design of the study. In this process, there is a shared commitment to protect the integrity of the research results from bias and conflicts of interest, so that the results are valid for informing decisions and health care actions. Due to the complexity of some health care decisions, the evidence needed for decisionmaking or action may need to be developed from multiple studies, including preliminary research that becomes the underpinning for larger studies. The principles described in this chapter are intended to strengthen the writing of research protocols and enhance the results from the emanating studies, for informing the important decisions facing patients, providers, and other stakeholders about health care treatments and new technologies. Subsequent chapters in this User's Guide provide specific principles for operationalizing the study objectives and research questions in writing a complete study protocol that can be executed as new research.

Checklist: Guidance and key considerations for developing study objectives and questions for observational CER protocols

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Developing a Protocol for Observational Comparative Effectiveness Research: A User’s Guide is copyrighted by the Agency for Healthcare Research and Quality (AHRQ). The product and its contents may be used and incorporated into other materials on the following three conditions: (1) the contents are not changed in any way (including covers and front matter), (2) no fee is charged by the reproducer of the product or its contents for its use, and (3) the user obtains permission from the copyright holders identified therein for materials noted as copyrighted by others. The product may not be sold for profit or incorporated into any profitmaking venture without the expressed written permission of AHRQ.

• Cite this Page Smith SR. Study Objectives and Questions. In: Velentgas P, Dreyer NA, Nourjah P, et al., editors. Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide. Rockville (MD): Agency for Healthcare Research and Quality (US); 2013 Jan. Chapter 1.
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There are three basic types of questions that research projects can address:

• Descriptive. When a study is designed primarily to describe what is going on or what exists. Public opinion polls that seek only to describe the proportion of people who hold various opinions are primarily descriptive in nature. For instance, if we want to know what percent of the population would vote for a Democratic or a Republican in the next presidential election, we are simply interested in describing something.
• Relational. When a study is designed to look at the relationships between two or more variables. A public opinion poll that compares what proportion of males and females say they would vote for a Democratic or a Republican candidate in the next presidential election is essentially studying the relationship between gender and voting preference.
• Causal. When a study is designed to determine whether one or more variables (e.g. a program or treatment variable) causes or affects one or more outcome variables. If we did a public opinion poll to try to determine whether a recent political advertising campaign changed voter preferences, we would essentially be studying whether the campaign (cause) changed the proportion of voters who would vote Democratic or Republican (effect).

The three question types can be viewed as cumulative. That is, a relational study assumes that you can first describe (by measuring or observing) each of the variables you are trying to relate. And, a causal study assumes that you can describe both the cause and effect variables and that you can show that they are related to each other. Causal studies are probably the most demanding of the three.

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How to Do Comparative Analysis in Research ( Examples )

Comparative analysis is a method that is widely used in social science . It is a method of comparing two or more items with an idea of uncovering and discovering new ideas about them. It often compares and contrasts social structures and processes around the world to grasp general patterns. Comparative analysis tries to understand the study and explain every element of data that comparing. 

Most social scientists are involved in comparative analysis. Macfarlane has thought that “On account of history, the examinations are typically on schedule, in that of other sociologies, transcendently in space. The historian always takes their society and compares it with the past society, and analyzes how far they differ from each other.

The comparative method of social research is a product of 19 th -century sociology and social anthropology. Sociologists like Emile Durkheim, Herbert Spencer Max Weber used comparative analysis in their works. For example, Max Weber compares the protestant of Europe with Catholics and also compared it with other religions like Islam, Hinduism, and Confucianism.

To do a systematic comparison we need to follow different elements of the method.

In social science, we can do comparisons in different ways. It is merely different based on the topic, the field of study. Like Emile Durkheim compare societies as organic solidarity and mechanical solidarity. The famous sociologist Emile Durkheim provides us with three different approaches to the comparative method. Which are;

2 . The unit of comparison

3. The motive of comparison

As another method of study, a comparative analysis is one among them for the social scientist. The researcher or the person who does the comparative method must know for what grounds they taking the comparative method. They have to consider the strength, limitations, weaknesses, etc. He must have to know how to do the analysis.

Steps of the comparative method

As mentioned earlier, the first step is to consider and determine the unit of comparison for your study. You must consider all the dimensions of your unit. This is where you put the two things you need to compare and to properly analyze and compare it. It is not an easy step, we have to systematically and scientifically do this with proper methods and techniques. You have to build your objectives, variables and make some assumptions or ask yourself about what you need to study or make a hypothesis for your analysis.

The best casings of reference are built from explicit sources instead of your musings or perceptions. To do that you can select some attributes in the society like marriage, law, customs, norms, etc. by doing this you can easily compare and contrast the two societies that you selected for your study. You can set some questions like, is the marriage practices of Catholics are different from Protestants? Did men and women get an equal voice in their mate choice? You can set as many questions that you wanted. Because that will explore the truth about that particular topic. A comparative analysis must have these attributes to study. A social scientist who wishes to compare must develop those research questions that pop up in your mind. A study without those is not going to be a fruitful one.

The grounds of comparison should be understandable for the reader. You must acknowledge why you selected these units for your comparison. For example, it is quite natural that a person who asks why you choose this what about another one? What is the reason behind choosing this particular society? If a social scientist chooses primitive Asian society and primitive Australian society for comparison, he must acknowledge the grounds of comparison to the readers. The comparison of your work must be self-explanatory without any complications.

The main element of the comparative analysis is the thesis or the report. The report is the most important one that it must contain all your frame of reference. It must include all your research questions, objectives of your topic, the characteristics of your two units of comparison, variables in your study, and last but not least the finding and conclusion must be written down. The findings must be self-explanatory because the reader must understand to what extent did they connect and what are their differences. For example, in Emile Durkheim’s Theory of Division of Labour, he classified organic solidarity and Mechanical solidarity . In which he means primitive society as Mechanical solidarity and modern society as Organic Solidarity. Like that you have to mention what are your findings in the thesis.

Your paper must link each point in the argument. Without that the reader does not understand the logical and rational advance in your analysis. In a comparative analysis, you need to compare the ‘x’ and ‘y’ in your paper. (x and y mean the two-unit or things in your comparison). To do that you can use likewise, similarly, on the contrary, etc. For example, if we do a comparison between primitive society and modern society we can say that; ‘in the primitive society the division of labour is based on gender and age on the contrary (or the other hand), in modern society, the division of labour is based on skill and knowledge of a person.

Demerits of comparison

Comparative analysis is not always successful. It has some limitations. The broad utilization of comparative analysis can undoubtedly cause the feeling that this technique is a solidly settled, smooth, and unproblematic method of investigation, which because of its undeniable intelligent status can produce dependable information once some specialized preconditions are met acceptably.

One more basic issue with broad ramifications concerns the decision of the units being analyzed. The primary concern is that a long way from being a guiltless as well as basic assignment, the decision of comparison units is a basic and precarious issue. The issue with this sort of comparison is that in such investigations the depictions of the cases picked for examination with the principle one will in general turn out to be unreasonably streamlined, shallow, and stylised with contorted contentions and ends as entailment.

However, a comparative analysis is as yet a strategy with exceptional benefits, essentially due to its capacity to cause us to perceive the restriction of our psyche and check against the weaknesses and hurtful results of localism and provincialism. We may anyway have something to gain from history specialists’ faltering in utilizing comparison and from their regard for the uniqueness of settings and accounts of people groups. All of the above, by doing the comparison we discover the truths the underlying and undiscovered connection, differences that exist in society.

Also Read: How to write a Sociology Analysis? Explained with Examples

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Market research

Comparative research: what it is and how to conduct it

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Comparative research involves comparing elements to better understand the similarities and differences between them, applying rigorous methods and analyzing the results to draw meaningful conclusions. It helps to expand knowledge and provides a basis for informed decisions.

Learn more about its features and how it can be done.

• 1 What is comparative research?
• 2 Why comparative research?
• 3.1 1. Define the goal of comparative research
• 3.2 2. Select the items to compare
• 3.3 3. Collect data
• 3.4 4. Analysis of the data
• 3.5 5. Interpretation of results
• 3.6 6. Conclusion(s) from the comparative research
• 3.7 7. Present the results of the comparative research
• 3.8 Conclusion
• 4 1:1 Live Online Presentation: QUESTIONPRO MARKET RESEARCH SOFTWARE
• 5 Try software for market research and experience management now for 10 days free of charge!

What is comparative research?

Comparative research is research designed to analyse and compare two or more elements or phenomena to identify similarities, differences, and patterns between them. It is used in various disciplines such as science, psychology, sociology and economics.

The main features of comparative research are:

• Comparison : A direct comparison is made between two or more objects. Similarities and differences in terms of characteristics, behaviors, effects or other relevant aspects are examined.
• Clear targets: It has specific and clearly defined goals. An attempt can be made to understand the causes of the differences or similarities observed, to explain the effects of the variables being compared, or to suggest better approaches or solutions.
• Kontext : Comparative research is carried out in a specific context. This means taking into account factors such as time, location, culture, socio-economic environment, etc., which may influence the elements being compared.
• Different approaches: In comparative research, various methods and techniques can be used to collect data. These include, among other things: Case studies , surveys, direct observation, document analysis and statistical analysis.
• Analysis and conclusion : Comparative research involves analyzing the data collected and drawing conclusions based on the comparisons made. These conclusions can provide important information about causal relationships, trends, or observed patterns.
• generalization : Depending on the scope of the study, the results may allow generalizations about the elements being compared. However, it is important to be aware of the limitations and to consider the validity of the results in different contexts.

Why comparative research?

Comparative research is used in a variety of situations and for a variety of purposes. Here are some examples where you can use this approach:

• Understanding cultural differences : Comparative research is useful for analyzing and understanding cultural differences between different groups of people. It can help identify particular practices, values, beliefs and behaviors in different societies.
• Evaluation of policies and programs : It makes it possible to analyse how policies are implemented and what results are achieved in different contexts, thus identifying good practices or areas for improvement.
• Market research : In business, comparative research is used to analyse and compare the demand for products or services in different markets. This helps companies understand consumer preferences, adapt their marketing strategies and make informed decisions about expanding into new markets.
• Scientific research : Comparative research is carried out in a variety of disciplines Scientific research applied. In biology, for example, it can be used to compare species and study their characteristics and behavior. In psychology, it is used to compare groups of people and understand differences in behavior or personality.
• Analysis of educational policies and systems : Comparative research is used in the field of education to analyse and compare the educational policies and systems of different countries or regions. This helps identify successful practices, common challenges and opportunities for improvement in education.
• Labor market studies: They help analyse and compare working conditions, wages and other work-related aspects in different industries or countries. This provides information about labor market trends and inequalities.

How to Conduct Comparative Research

Conducting comparative research requires a few basic steps. Here is a simple explanation of how to do it:

1. Define the goal of comparative research

Before you begin, you should be clear about what you want to achieve with comparative research. Clearly define the goal and the research questions you want to answer.

2. Select the items to compare

Determine the elements, phenomena, or groups you want to compare. These can be different countries, cultures, policies, products, groups of people, etc. Make sure they are comparable and that you can get relevant data for each item.

Make sure you have a clear understanding of the elements you want to compare and that they are relevant to your research objective. The selected elements should be comparable to each other. This means that they should have characteristics and properties that can be measured and compared in a meaningful way.

When selecting a sample of items for comparison, ensure that it is a representative sample of the population or group to which you want to generalize the results.

3. Collect data

Use a variety of sources and methods to collect data about the items being compared. Identify appropriate data sources to collect information about the items being compared. These sources may include surveys, interviews, direct observations, databases, historical records, government reports, academic literature, media, and others.

Perform a quality check on the data collected. This includes checking the consistency, accuracy and completeness of the data. If necessary, perform additional checks or contact participants to clarify any ambiguities or errors in the data.

4. Analysis of the data

Review the data collected and conduct a comparative analysis. Identify similarities and differences between the elements being compared. You can use statistical analysis techniques and comparison graphs, or simply compare the data qualitatively.

You can descriptive statistics Use to summarize and present quantitative data clearly and concisely. This can include measures of central tendency (such as mean, median or mode) and measures of dispersion (such as standard deviation or span). With the help of descriptive statistics you can understand the main characteristics of the items being compared.

5. Interpretation of results

Based on the analyses carried out, interpret the results of the investigation. Identify patterns, trends, or causal relationships that emerge from the comparison. Explain the similarities and differences observed and look for possible explanations.

Try to find possible explanations for the results observed in your comparative research. Identify key variables that may influence the similarities and differences identified. Consider whether there are underlying causal factors or mediating variables that could explain the results obtained.

6. Conclusion(s) from the comparative research

Draw relevant conclusions based on the interpretation of the results. Summarize the most important results of the comparative research and answer the research questions asked in the first step.

Reflect on the impact of your findings in the broader context. Explore how the results may contribute to existing knowledge on the topic and how they might impact practice. Additionally, identify the limitations of your comparative research, such as: B. possible biases or limitations in the sample or methods used.

7. Present the results of the comparative research

Communicate the results of your comparative research clearly and concisely. You can use written reports, visual presentations, charts, or comparative tables, whichever works best for your audience.

Comparative research is used to analyse and compare elements, phenomena or practices in order to understand differences, identify best practices, evaluate policies or programs and make informed decisions in various fields such as culture, economics, science, education, etc.

Remember that data collection is a crucial phase in comparative research. It is important that it is carried out carefully and accurately in order to obtain reliable and valid information that allows you to make meaningful comparisons between the selected items.

Online survey tools like QuestionPro, help you with structured data collection. If you choose, you can first set up a free account to try out the basic features, or request a demo to let us know your research needs and learn more about our products and various licenses.

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FURTHER KEYWORDS

Market research | Empirical research | Research process | Survey research

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KEYWORDS OF THIS BLOG POST

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• Research Process: Steps to conduct the research
• Market research: examples, tips, data collection, data analysis, software for carrying out and presenting the results
• Empirical research: definition, methods and examples
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• Data collection tools: which are the best?
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• Cross-sectional data: what are they, characteristics and types

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Comparative Research

Ai generator.

Although not everyone would agree, comparing is not always bad. Comparing things can also give you a handful of benefits. For instance, there are times in our life where we feel lost. You may not be getting the job that you want or have the sexy body that you have been aiming for a long time now. Then, you happen to cross path with an old friend of yours, who happened to get the job that you always wanted. This scenario may put your self-esteem down, knowing that this friend got what you want, while you didn’t. Or you can choose to look at your friend as an example that your desire is actually attainable. Come up with a plan to achieve your  personal development goal . Perhaps, ask for tips from this person or from the people who inspire you. According to the article posted in  brit.co , licensed master social worker and therapist Kimberly Hershenson said that comparing yourself to someone successful can be an excellent self-motivation to work on your goals.

Aside from self-improvement, as a researcher, you should know that comparison is an essential method in scientific studies, such as experimental research and descriptive research . Through this method, you can uncover the relationship between two or more variables of your project in the form of comparative analysis .

What is Comparative Research?

Aiming to compare two or more variables of an experiment project, experts usually apply comparative research examples in social sciences to compare countries and cultures across a particular area or the entire world. Despite its proven effectiveness, you should keep it in mind that some states have different disciplines in sharing data. Thus, it would help if you consider the affecting factors in gathering specific information.

Quantitative and Qualitative Research Methods in Comparative Studies

In comparing variables, the statistical and mathematical data collection, and analysis that quantitative research methodology naturally uses to uncover the correlational connection of the variables, can be essential. Additionally, since quantitative research requires a specific research question, this method can help you can quickly come up with one particular comparative research question.

The goal of comparative research is drawing a solution out of the similarities and differences between the focused variables. Through non-experimental or qualitative research , you can include this type of research method in your comparative research design.

13+ Comparative Research Examples

Know more about comparative research by going over the following examples. You can download these zipped documents in PDF and MS Word formats.

1. Comparative Research Report Template

• Google Docs

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2. Business Comparative Research Template

Size: 69 KB

3. Comparative Market Research Template

Size: 172 KB

4. Comparative Research Strategies Example

5. Comparative Research in Anthropology Example

Size: 192 KB

6. Sample Comparative Research Example

Size: 516 KB

7. Comparative Area Research Example

8. Comparative Research on Women’s Emplyment Example

Size: 290 KB

9. Basic Comparative Research Example

Size: 19 KB

10. Comparative Research in Medical Treatments Example

11. Comparative Research in Education Example

Size: 455 KB

12. Formal Comparative Research Example

Size: 244 KB

13. Comparative Research Designs Example

Size: 259 KB

14. Casual Comparative Research in DOC

Best Practices in Writing an Essay for Comparative Research in Visual Arts

If you are going to write an essay for a comparative research examples paper, this section is for you. You must know that there are inevitable mistakes that students do in essay writing . To avoid those mistakes, follow the following pointers.

1. Compare the Artworks Not the Artists

One of the mistakes that students do when writing a comparative essay is comparing the artists instead of artworks. Unless your instructor asked you to write a biographical essay, focus your writing on the works of the artists that you choose.

2. Consult to Your Instructor

There is broad coverage of information that you can find on the internet for your project. Some students, however, prefer choosing the images randomly. In doing so, you may not create a successful comparative study. Therefore, we recommend you to discuss your selections with your teacher.

3. Avoid Redundancy

It is common for the students to repeat the ideas that they have listed in the comparison part. Keep it in mind that the spaces for this activity have limitations. Thus, it is crucial to reserve each space for more thoroughly debated ideas.

4. Be Minimal

Unless instructed, it would be practical if you only include a few items(artworks). In this way, you can focus on developing well-argued information for your study.

5. Master the Assessment Method and the Goals of the Project

We get it. You are doing this project because your instructor told you so. However, you can make your study more valuable by understanding the goals of doing the project. Know how you can apply this new learning. You should also know the criteria that your teachers use to assess your output. It will give you a chance to maximize the grade that you can get from this project.

Comparing things is one way to know what to improve in various aspects. Whether you are aiming to attain a personal goal or attempting to find a solution to a certain task, you can accomplish it by knowing how to conduct a comparative study. Use this content as a tool to expand your knowledge about this research methodology .

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Frequently Asked Questions for RFA-AG-25-028

The frequently asked questions below are related to the NOFO:

RFA-AG-25-028 Mentored Career Enhancement Awards to Build Cross-Disciplinary Knowledge and Skills for Comparative Studies of Human and Nonhuman Primate Species with Differing Life Spans (K18) .

These FAQs will be updated periodically as additional questions arise from applicant inquiries.

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On August 15, 2024, from 10:00 a.m. to 12:00 p.m. ET, NIA will host a pre-application webinar for this RFA. 

On this page you will find FAQs on:

General Information

Eligibility.

Below are general information FAQs.

Q. Do applicants need to have previous experience with human and/or nonhuman primate (NHP) studies? 

A. Yes. This K18 award is intended for experienced scientists with expertise in human and/or NHP studies, who either wish to broaden their scientific capabilities or to make changes in their research careers by cross-training in a pertinent field to acquire new research skills or knowledge.

Q. Is it necessary for applicants to have previous experience with aging-related or longevity research?

A. No. Examples of cross-training discipline collaborations for scientists with expertise in human and/or nonhuman primate (NHP) studies that would be well-suited for this award include collaborations on factors related to differences on primate species’ longevity engaging cross-disciplinary combinations such as (but not limited to):

• Nonhuman primate and human longevity research
• Evolutionary biology and genetics 
• Biological anthropology and other biomedical research 
• Neuroscience and cognition 
• Primate field studies and comparative biology of aging 
• Biodemography and primate field studies 
• Developmental biology and evolutionary biology 
• Biological anthropology and social/behavioral sciences 

Q: Are there any special instructions and/or review criteria for applications to this NOFO?

A. Yes. Section IV: Application and Submission Information of this NOFO contains specific instructions regarding application content. Please review Section V: Application Review Information of the NOFO for review criteria “Specific to this NOFO” which outlines additional evaluation questions to address. 

Q: When are applications due?

A: There is a single receipt date: November 1, 2024. No late applications will be accepted.

Q. Are Letters of Intent required? When are they due?

A. Letters of Intent are not required, but they are recommended. Letters of Intent are due on September 20, 2024. It is also strongly encouraged that all applicants consult with the NIA program staff early in their planning process and not later than the Letter of Intent due date. This consultation is considered separate from the Letter of Intent. Inquiries should be sent to the NIA Scientific/Research Contact listed below. Inquiries will be directed to the appropriate NIA Division staff who can then advise whether proposed activities would be considered responsive to the objectives and goals of this FOA.

Q. How many applicants will be awarded under RFA-AG-25-028?

A: NIA intends to commit up to $1.5 million in FY 2025 to fund approximately 4 to 5 awards, contingent on funding availability.

Q. Are there application budget limits?

A: Award budgets are composed of salary and other program-related expenses. NIA will contribute up to $100,000 in direct costs per year toward the research development costs of the award recipient. The total salary requested may not exceed the legislatively mandated salary cap (see NOT-OD-24-057 for further guidance).

Q: Who should I contact if I have further questions?

A: Application Submission Contacts

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Finding Help Online: http://grants.nih.gov/support/ (preferred method of contact) Telephone: 301-402-7469 or 866-504-9552

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Below are eligibility information FAQs.

Q. What are the eligibility requirements for applicants?

A. This award is intended for mid-career investigators who have established records of independent, peer-reviewed research grant funding. An academic rank of associate or full professor, or the equivalent in non-academic research settings, is required for eligibility for this award. Please see Section III of the NOFO for additional eligibility information. 

Q. What level of effort is required for investigators applying to this mentored K award?

A. An applicant must devote a minimum of three person months of effort (i.e., 25% of full-time professional effort) per year to their program of career development. This effort can be expended consistently throughout the academic or calendar year or be focused during summer or off-term months. Candidates may engage in other duties as part of the professional effort not covered by this award, as long as such duties do not interfere with or detract from the proposed career development program.

Below are mentor information FAQs.

Q. Can I identify more than one mentor?

A. Yes. Applicants may identify more than one mentor, as long as all proposed mentors have relevant expertise and available resources in one or more applicant knowledge-gap areas.

Q. Can mentor’s salaries be supported by this award?

A. No. Award budgets are composed of applicant salary and research development costs of the award recipient (as outlined in Section II. Award Information).  However, this interdisciplinary collaboration is intended to be mutually beneficial, by providing both the mentor and candidate with a broadened and more diverse research scope, as well as expanded networks for future collaboration and resource access. It is expected that this initiative will lead to new and/or augmented collaborative research programs competitive for NIA funding.

Q. Where can I find assistance if I need help in identifying an appropriate mentor or mentors or in developing components of the career enhancement plan?

A. There are a variety of research resources that can assist in identifying potential mentors and/or be engaged as components of the applicant’s career enhancement plan. Many of these resources are listed in Section I. Funding Opportunity Description of RFA-AG-25-028. We recommend that potential applicants consult NIA program staff early on in their process of considering or planning an application, especially if help is needed in identifying a mentor or mentoring team. Inquiries should be sent to the NIA Scientific/Research Contact (link to below section with contact information). 

Q. Is it required that the proposed mentor(s) be from a different institution than the applicant?

A. No. Career enhancement activities may be conducted within the candidate’s institution but must not be in the department of the applicant’s current primary appointment. The proposed research project can be conducted in facilities or field sites affiliated with either the applicant’s institution (i.e., site of the candidate’s primary appointments) or the mentor’s institution. Additionally, the candidate and proposed mentor(s) should not have extensive previous research collaborations.

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A comparative study of the influence of communication on the adoption of digital agriculture in the united states and brazil  †.

1. Introduction

2. materials and methods, 2.1. study region, 2.2. survey instrument, 2.3. data collection, 2.4. data analysis.

• n = number of elements in the sample;
• p = probability of finding the phenomenon studied in the population;
• q = probability of not finding the phenomenon studied in the population; and
• E = margin of error.

2.5. Sample Characteristics

3. results and discussion, 3.1. technology adoption, decisions, and benefits, 3.2. level of influence from mass media, social media, and interpersonal meetings, 3.3. relationship between the adoption of technologies and communication channels, 4. conclusions, author contributions, institutional review board statement, data availability statement, acknowledgments, conflicts of interest.

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Colussi, J.; Sonka, S.; Schnitkey, G.D.; Morgan, E.L.; Padula, A.D. A Comparative Study of the Influence of Communication on the Adoption of Digital Agriculture in the United States and Brazil. Agriculture 2024 , 14 , 1027. https://doi.org/10.3390/agriculture14071027

Colussi J, Sonka S, Schnitkey GD, Morgan EL, Padula AD. A Comparative Study of the Influence of Communication on the Adoption of Digital Agriculture in the United States and Brazil. Agriculture . 2024; 14(7):1027. https://doi.org/10.3390/agriculture14071027

Colussi, Joana, Steve Sonka, Gary D. Schnitkey, Eric L. Morgan, and Antônio D. Padula. 2024. "A Comparative Study of the Influence of Communication on the Adoption of Digital Agriculture in the United States and Brazil" Agriculture 14, no. 7: 1027. https://doi.org/10.3390/agriculture14071027

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Please note you do not have access to teaching notes, leadership dynamics in nursing: a comparative study of paternalistic approaches in china and pakistan.

Leadership in Health Services

ISSN : 1751-1879

Article publication date: 9 July 2024

This study aims to examine the impact of nurses’ paternalistic leadership style on performance, in the presence of underlying mechanisms, i.e. self-efficacy as a mediator in the high-power distance societies, namely, China and Pakistan, based on social exchange theory. Both healthcare sectors have seen several behavioral advancements in recent years. To improve things, even more, behavioral elements such as the influence of leadership styles, personality traits and so on have become more important. However, leadership styles, particularly paternalistic leadership, have received little attention in this field and need to be highlighted along with the mediating and moderating effects.

Design/methodology/approach

Data were collected from public and private sector hospitals in China and Pakistan using a 6-week time lag technique. Firstly, 356 Chinese and 411 Pakistani nurses were surveyed about their perceptions of power distance, self-efficacy and paternalistic leadership. Their managers were called six weeks later for a dyadic response to provide feedback on nurses’ performance. For confirmatory factor analysis, AMOS 22 and for regression analysis, SPSS 22 was used.

According to the study's findings, nurses in both countries perform well when led by a paternalistic leader. Furthermore, self-efficacy explains the relationship between paternalistic leaders and nurses’ performance. The moderated-mediation result also supported the importance of power distance.

Originality/value

This study highlights the kind of nursing leadership which is beneficial in high-power-distance societies and leads to better performance. According to this research, paternalistic leadership improves nurses’ performance in both China and Pakistan. As a result, this study will be useful in high-power-distance societies, where hospital administrators can ensure that paternalism is implemented in leadership, thereby improving nurse performance.

• Paternalistic leadership
• High power distance
• Self-efficacy
• Nurses performance
• Health staff
• Nursing supervisors
• Performance
• Health leadership competencies

Safdar, S. , Faiz, S. and Muabark, N. (2024), "Leadership dynamics in nursing: a comparative study of paternalistic approaches in China and Pakistan", Leadership in Health Services , Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/LHS-03-2024-0028

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