this research aims to

• Aims and Objectives – A Guide for Academic Writing
• Doing a PhD

One of the most important aspects of a thesis, dissertation or research paper is the correct formulation of the aims and objectives. This is because your aims and objectives will establish the scope, depth and direction that your research will ultimately take. An effective set of aims and objectives will give your research focus and your reader clarity, with your aims indicating what is to be achieved, and your objectives indicating how it will be achieved.

Introduction

There is no getting away from the importance of the aims and objectives in determining the success of your research project. Unfortunately, however, it is an aspect that many students struggle with, and ultimately end up doing poorly. Given their importance, if you suspect that there is even the smallest possibility that you belong to this group of students, we strongly recommend you read this page in full.

This page describes what research aims and objectives are, how they differ from each other, how to write them correctly, and the common mistakes students make and how to avoid them. An example of a good aim and objectives from a past thesis has also been deconstructed to help your understanding.

What Are Aims and Objectives?

Research aims.

A research aim describes the main goal or the overarching purpose of your research project.

In doing so, it acts as a focal point for your research and provides your readers with clarity as to what your study is all about. Because of this, research aims are almost always located within its own subsection under the introduction section of a research document, regardless of whether it’s a thesis , a dissertation, or a research paper .

A research aim is usually formulated as a broad statement of the main goal of the research and can range in length from a single sentence to a short paragraph. Although the exact format may vary according to preference, they should all describe why your research is needed (i.e. the context), what it sets out to accomplish (the actual aim) and, briefly, how it intends to accomplish it (overview of your objectives).

To give an example, we have extracted the following research aim from a real PhD thesis:

Example of a Research Aim

The role of diametrical cup deformation as a factor to unsatisfactory implant performance has not been widely reported. The aim of this thesis was to gain an understanding of the diametrical deformation behaviour of acetabular cups and shells following impaction into the reamed acetabulum. The influence of a range of factors on deformation was investigated to ascertain if cup and shell deformation may be high enough to potentially contribute to early failure and high wear rates in metal-on-metal implants.

Note: Extracted with permission from thesis titled “T he Impact And Deformation Of Press-Fit Metal Acetabular Components ” produced by Dr H Hothi of previously Queen Mary University of London.

Research Objectives

Where a research aim specifies what your study will answer, research objectives specify how your study will answer it.

They divide your research aim into several smaller parts, each of which represents a key section of your research project. As a result, almost all research objectives take the form of a numbered list, with each item usually receiving its own chapter in a dissertation or thesis.

Following the example of the research aim shared above, here are it’s real research objectives as an example:

Example of a Research Objective

• Develop finite element models using explicit dynamics to mimic mallet blows during cup/shell insertion, initially using simplified experimentally validated foam models to represent the acetabulum.
• Investigate the number, velocity and position of impacts needed to insert a cup.
• Determine the relationship between the size of interference between the cup and cavity and deformation for different cup types.
• Investigate the influence of non-uniform cup support and varying the orientation of the component in the cavity on deformation.
• Examine the influence of errors during reaming of the acetabulum which introduce ovality to the cavity.
• Determine the relationship between changes in the geometry of the component and deformation for different cup designs.
• Develop three dimensional pelvis models with non-uniform bone material properties from a range of patients with varying bone quality.
• Use the key parameters that influence deformation, as identified in the foam models to determine the range of deformations that may occur clinically using the anatomic models and if these deformations are clinically significant.

It’s worth noting that researchers sometimes use research questions instead of research objectives, or in other cases both. From a high-level perspective, research questions and research objectives make the same statements, but just in different formats.

Taking the first three research objectives as an example, they can be restructured into research questions as follows:

Restructuring Research Objectives as Research Questions

• Can finite element models using simplified experimentally validated foam models to represent the acetabulum together with explicit dynamics be used to mimic mallet blows during cup/shell insertion?
• What is the number, velocity and position of impacts needed to insert a cup?
• What is the relationship between the size of interference between the cup and cavity and deformation for different cup types?

Difference Between Aims and Objectives

Hopefully the above explanations make clear the differences between aims and objectives, but to clarify:

• The research aim focus on what the research project is intended to achieve; research objectives focus on how the aim will be achieved.
• Research aims are relatively broad; research objectives are specific.
• Research aims focus on a project’s long-term outcomes; research objectives focus on its immediate, short-term outcomes.
• A research aim can be written in a single sentence or short paragraph; research objectives should be written as a numbered list.

How to Write Aims and Objectives

Before we discuss how to write a clear set of research aims and objectives, we should make it clear that there is no single way they must be written. Each researcher will approach their aims and objectives slightly differently, and often your supervisor will influence the formulation of yours on the basis of their own preferences.

Regardless, there are some basic principles that you should observe for good practice; these principles are described below.

Your aim should be made up of three parts that answer the below questions:

• Why is this research required?
• What is this research about?
• How are you going to do it?

The easiest way to achieve this would be to address each question in its own sentence, although it does not matter whether you combine them or write multiple sentences for each, the key is to address each one.

The first question, why , provides context to your research project, the second question, what , describes the aim of your research, and the last question, how , acts as an introduction to your objectives which will immediately follow.

Scroll through the image set below to see the ‘why, what and how’ associated with our research aim example.

Note: Your research aims need not be limited to one. Some individuals per to define one broad ‘overarching aim’ of a project and then adopt two or three specific research aims for their thesis or dissertation. Remember, however, that in order for your assessors to consider your research project complete, you will need to prove you have fulfilled all of the aims you set out to achieve. Therefore, while having more than one research aim is not necessarily disadvantageous, consider whether a single overarching one will do.

Research Objectives

Each of your research objectives should be SMART :

• Specific – is there any ambiguity in the action you are going to undertake, or is it focused and well-defined?
• Measurable – how will you measure progress and determine when you have achieved the action?
• Achievable – do you have the support, resources and facilities required to carry out the action?
• Relevant – is the action essential to the achievement of your research aim?
• Timebound – can you realistically complete the action in the available time alongside your other research tasks?

In addition to being SMART, your research objectives should start with a verb that helps communicate your intent. Common research verbs include:

Table of Research Verbs to Use in Aims and Objectives

Last, format your objectives into a numbered list. This is because when you write your thesis or dissertation, you will at times need to make reference to a specific research objective; structuring your research objectives in a numbered list will provide a clear way of doing this.

To bring all this together, let’s compare the first research objective in the previous example with the above guidance:

Checking Research Objective Example Against Recommended Approach

Research Objective:

1. Develop finite element models using explicit dynamics to mimic mallet blows during cup/shell insertion, initially using simplified experimentally validated foam models to represent the acetabulum.

Checking Against Recommended Approach:

Q: Is it specific? A: Yes, it is clear what the student intends to do (produce a finite element model), why they intend to do it (mimic cup/shell blows) and their parameters have been well-defined ( using simplified experimentally validated foam models to represent the acetabulum ).

Q: Is it measurable? A: Yes, it is clear that the research objective will be achieved once the finite element model is complete.

Q: Is it achievable? A: Yes, provided the student has access to a computer lab, modelling software and laboratory data.

Q: Is it relevant? A: Yes, mimicking impacts to a cup/shell is fundamental to the overall aim of understanding how they deform when impacted upon.

Q: Is it timebound? A: Yes, it is possible to create a limited-scope finite element model in a relatively short time, especially if you already have experience in modelling.

Q: Does it start with a verb? A: Yes, it starts with ‘develop’, which makes the intent of the objective immediately clear.

Q: Is it a numbered list? A: Yes, it is the first research objective in a list of eight.

Mistakes in Writing Research Aims and Objectives

1. making your research aim too broad.

Having a research aim too broad becomes very difficult to achieve. Normally, this occurs when a student develops their research aim before they have a good understanding of what they want to research. Remember that at the end of your project and during your viva defence , you will have to prove that you have achieved your research aims; if they are too broad, this will be an almost impossible task. In the early stages of your research project, your priority should be to narrow your study to a specific area. A good way to do this is to take the time to study existing literature, question their current approaches, findings and limitations, and consider whether there are any recurring gaps that could be investigated .

Note: Achieving a set of aims does not necessarily mean proving or disproving a theory or hypothesis, even if your research aim was to, but having done enough work to provide a useful and original insight into the principles that underlie your research aim.

2. Making Your Research Objectives Too Ambitious

Be realistic about what you can achieve in the time you have available. It is natural to want to set ambitious research objectives that require sophisticated data collection and analysis, but only completing this with six months before the end of your PhD registration period is not a worthwhile trade-off.

3. Formulating Repetitive Research Objectives

Each research objective should have its own purpose and distinct measurable outcome. To this effect, a common mistake is to form research objectives which have large amounts of overlap. This makes it difficult to determine when an objective is truly complete, and also presents challenges in estimating the duration of objectives when creating your project timeline. It also makes it difficult to structure your thesis into unique chapters, making it more challenging for you to write and for your audience to read.

Fortunately, this oversight can be easily avoided by using SMART objectives.

Hopefully, you now have a good idea of how to create an effective set of aims and objectives for your research project, whether it be a thesis, dissertation or research paper. While it may be tempting to dive directly into your research, spending time on getting your aims and objectives right will give your research clear direction. This won’t only reduce the likelihood of problems arising later down the line, but will also lead to a more thorough and coherent research project.

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Formulating Research Aims and Objectives

Formulating research aim and objectives in an appropriate manner is one of the most important aspects of your thesis. This is because research aim and objectives determine the scope, depth and the overall direction of the research. Research question is the central question of the study that has to be answered on the basis of research findings.

Research aim emphasizes what needs to be achieved within the scope of the research, by the end of the research process. Achievement of research aim provides answer to the research question.

Research objectives divide research aim into several parts and address each part separately. Research aim specifies WHAT needs to be studied and research objectives comprise a number of steps that address HOW research aim will be achieved.

As a rule of dumb, there would be one research aim and several research objectives. Achievement of each research objective will lead to the achievement of the research aim.

Consider the following as an example:

Research title: Effects of organizational culture on business profitability: a case study of Virgin Atlantic

Research aim: To assess the effects of Virgin Atlantic organizational culture on business profitability

Following research objectives would facilitate the achievement of this aim:

• Analyzing the nature of organizational culture at Virgin Atlantic by September 1, 2022
• Identifying factors impacting Virgin Atlantic organizational culture by September 16, 2022
• Analyzing impacts of Virgin Atlantic organizational culture on employee performances by September 30, 2022
• Providing recommendations to Virgin Atlantic strategic level management in terms of increasing the level of effectiveness of organizational culture by October 5, 2022

Figure below illustrates additional examples in formulating research aims and objectives:

Formulation of research question, aim and objectives

Common mistakes in the formulation of research aim relate to the following:

1. Choosing the topic too broadly . This is the most common mistake. For example, a research title of “an analysis of leadership practices” can be classified as too broad because the title fails to answer the following questions:

a) Which aspects of leadership practices? Leadership has many aspects such as employee motivation, ethical behaviour, strategic planning, change management etc. An attempt to cover all of these aspects of organizational leadership within a single research will result in an unfocused and poor work.

b) An analysis of leadership practices in which country? Leadership practices tend to be different in various countries due to cross-cultural differences, legislations and a range of other region-specific factors. Therefore, a study of leadership practices needs to be country-specific.

c) Analysis of leadership practices in which company or industry? Similar to the point above, analysis of leadership practices needs to take into account industry-specific and/or company-specific differences, and there is no way to conduct a leadership research that relates to all industries and organizations in an equal manner.

Accordingly, as an example “a study into the impacts of ethical behaviour of a leader on the level of employee motivation in US healthcare sector” would be a more appropriate title than simply “An analysis of leadership practices”.

2. Setting an unrealistic aim . Formulation of a research aim that involves in-depth interviews with Apple strategic level management by an undergraduate level student can be specified as a bit over-ambitious. This is because securing an interview with Apple CEO Tim Cook or members of Apple Board of Directors might not be easy. This is an extreme example of course, but you got the idea. Instead, you may aim to interview the manager of your local Apple store and adopt a more feasible strategy to get your dissertation completed.

3. Choosing research methods incompatible with the timeframe available . Conducting interviews with 20 sample group members and collecting primary data through 2 focus groups when only three months left until submission of your dissertation can be very difficult, if not impossible. Accordingly, timeframe available need to be taken into account when formulating research aims and objectives and selecting research methods.

Moreover, research objectives need to be formulated according to SMART principle,

 where the abbreviation stands for specific, measurable, achievable, realistic, and time-bound.

Examples of SMART research objectives

At the conclusion part of your research project you will need to reflect on the level of achievement of research aims and objectives. In case your research aims and objectives are not fully achieved by the end of the study, you will need to discuss the reasons. These may include initial inappropriate formulation of research aims and objectives, effects of other variables that were not considered at the beginning of the research or changes in some circumstances during the research process.

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A Complete Guide to Write Research Aims and Objectives

The importance of making a good quality aim and objectives of a research is paramount in the success of the research.

In this post, you will learn:

• What is research aim?
• What are research objectives?
• How to differentiate between research aim and research objective
• Examples of research aims and objectives
• Key points to remember while writing research aim and objectives
• Do’s and Don’ts

What Is Research Aim?

The research aim is the primary focus of the research and determines what the research serves to do. It defines the purpose of the research and tells the audience what the research aims to achieve.

Because research aims are so important for the study, a sun heading in the introductory chapter is usually dedicated to them. They are written in a paragraph form and define the main purpose of conducting the research on a topic.

Example of a good quality research aim

Research about the effects of climate change on the mental health of young adults can be worded as follows:

“The effects of climate change information on the minds of young adults are under researched. This research aims to find the effects that climate change information has on the mental health of young adults. By studying the effects of the intensity and frequency of the consumption of climate change news and forecasts among young adults, this study aims to see how climate change information is influencing their mental health.”

The above research aim is focused and clear and presents the reader with a clear understanding of the purpose of the research.

What Is Research Objective?

Research aims are related to research objectives. The research aim determines the overall purpose of the study, and the objectives determine in what ways that purpose will be achieved. The purpose of the research aim is separated into subsections. However, If any you need to order IT Research Paper help services then you have to take a survey on the net. These subsections are smaller steps that define the objectives of the research.

Research objectives are usually written in the form of a list. These small bits of steps can be checked off as the research progresses. They are written in chronological order, starting with the first objective that needs to be achieved and ending with the final one.

Example of research objectives

Taking the example of the research aim above, we can divide it into smaller sections to create specific aims of the research.

• Understand the concepts of climate change and mental health
• Understand the relationship between climate change and mental health
• Determine the frequency and intensity of climate change news consumption among young adults
• Determine the frequency and intensity of news affects the mental health of young adults
• Develop recommendations for clinical practice in the field

From this example, you can see how the research aim was broken down into smaller, specific objectives that were then listed down.

Differentiate Research Between Aims & Objectives

Although the two concepts are related, they are not the same. The differences between research aim and research objectives are:

• The way they are worded are different: Research aim is worded in a wide scoped way, while research objectives are worded as specific, narrowed down tasks.
• The focus of the two are different: research aim focuses on the overall purpose while research objectives focus on how to achieve that purpose.
• The purpose of the two are different: research aims are concerned with the overall findings of a research, which are long-term, while research objectives serve to define the short term aims of the research.
• The way they are presented are different: research aims are written in a small paragraph form while the objectives are written in the form of a list.

3 Key Points To Remember While Drafting Research Aim

The ways of writing a research aim varies with the researcher, but there are certain points to keep in mind to write a good quality research aim:

1. Answer the “why” question of the research: A research aim needs to provide an answer for why the study is being conducted. It needs to describe, in a small sentence or phares, why the research is important to conduct.

Taking the example of the research aim above, we can see that it answers the why question:

“The effects of climate change information on the minds of young adults are under researched”.

2. Answer the “what” question of the research: this is the main purpose of the research aim, as it signifies the main aim of the research.

From the example above, the “what” question is answered as follows:

“This research aims to find the effects that climate change information has on the mental health of young adults.”

3. Lastly, the research aim needs to answer the “how” question. In a simple sentence or a few phrases, it should outline the main way in which you are planning to achieve the aim.

From the example above, the “how” question is answered as follows:

“By studying the effects of the intensity and frequency of the consumption of climate change news and forecasts among young adults, this study aims to see how climate change information is influencing their mental health.”

Checklist of research aim:

• Tells the purpose of research
• Tells why the research is important
• Tells how the aim will be achieved
• Is clear and concise

5 Key Points To Remember While Drafting Research Objective

An easy way to determine the quality of your research objectives is to apply the SMART method to them:

• You need to make sure that the objectives are worded as specific tasks you need to achieve. They should not be vague.
• You should ensure that the objectives are measurable, meaning that they allow you to see how much of them have been achieved and how much are left to work on.
• The objectives need to be achievable, meaning you should have the resources to work on them.
• They need to be relevant to getting to your research aim.
• They need to be achievable in the time you have available for your research project.

In the example above the objectives follow the above mentioned criteria. While making your own objectives, make sure to evaluate them using the points above to ensure your objectives are good quality.

Checklist of research objectives

Do’s and Don’ts of research aims and objectives

What to do and what to avoid in writing aims and objectives

The Takeaway

• The research aim is the primary focus of the research.
• Research aims are related to research objectives
• The objectives determine in what ways that purpose will be achieved.
• Research aim needs to answer the “what”, “why” and “how” questions of the research.
• Research objectives need to be SMART.

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Research Aims and Objectives: The dynamic duo for successful research

Picture yourself on a road trip without a destination in mind — driving aimlessly, not knowing where you’re headed or how to get there. Similarly, your research is navigated by well-defined research aims and objectives. Research aims and objectives are the foundation of any research project. They provide a clear direction and purpose for the study, ensuring that you stay focused and on track throughout the process. They are your trusted navigational tools, leading you to success.

Understanding the relationship between research objectives and aims is crucial to any research project’s success, and we’re here to break it down for you in this article. Here, we’ll explore the importance of research aims and objectives, understand their differences, and delve into the impact they have on the quality of research.

Understanding the Difference between Research Aims and Objectives

In research, aims and objectives are two important components but are often used interchangeably. Though they may sound similar, they are distinct and serve different purposes.

Research Aims:

Research aims are broad statements that describe the overall purpose of your study. They provide a general direction for your study and indicate the intended achievements of your research. Aims are usually written in a general and abstract manner describing the ultimate goal of the research.

Research Objectives:

Research objectives are specific, measurable, and achievable goals that you aim to accomplish within a specified timeframe. They break down the research aims into smaller, more manageable components and provide a clear picture of what you want to achieve and how you plan to achieve it.

In the example, the objectives provide specific targets that must be achieved to reach the aim. Essentially, aims provide the overall direction for the research while objectives provide specific targets that must be achieved to accomplish the aims. Aims provide a broad context for the research, while the objectives provide smaller steps that the researcher must take to accomplish the overall research goals. To illustrate, when planning a road trip, your research aim is the destination you want to reach, and your research objectives are the specific routes you need to take to get there.

Aims and objectives are interconnected. Objectives play a key role in defining the research methodology, providing a roadmap for how you’ll collect and analyze data, while aim is the final destination, which represents the ultimate goal of your research. By setting specific goals, you’ll be able to design a research plan that helps you achieve your objectives and, ultimately, your research aim.

Importance of Well-defined Aims and Objectives

The impact of clear research aims and objectives on the quality of research cannot be understated. But it’s not enough to simply have aims and objectives. Well-defined research aims and objectives are important for several reasons:

• Provides direction: Clear aims and well-defined objectives provide a specific direction for your research study, ensuring that the research stays focused on a specific topic or problem. This helps to prevent the research from becoming too broad or unfocused, and ensures that the study remains relevant and meaningful.
• Guides research design: The research aim and objectives help guide the research design and methodology, ensuring that your study is designed in a way that will answer the research questions and achieve the research objectives.
• Helps with resource allocation: Clear research aims and objectives helps you to allocate resources effectively , including time, financial resources, human resources, and other required materials. With a well-defined aim and objectives, you can identify the resources required to conduct the research, and allocate them in a way that maximizes efficiency and productivity.
• Assists in evaluation: Clearly specified research aims and objectives allow for effective evaluation of your research project’s success. You can assess whether the research has achieved its objectives, and whether the aim has been met. This evaluation process can help to identify areas of the research project that may require further attention or modification.
• Enhances communication: Well-defined research aims and objectives help to enhance communication among the research team, stakeholders, funding agencies, and other interested parties. Clear aims and objectives ensure that everyone involved in your research project understands the purpose and goals of the study. This can help to foster collaboration and ensure that everyone is working towards the same end goal.

How to Formulate Research Aims and Objectives

Formulating effective research aims and objectives involves a systematic process to ensure that they are clear, specific, achievable, and relevant. Start by asking yourself what you want to achieve through your research. What impact do you want your research to have? Once you have a clear understanding of your aims, you can then break them down into specific, achievable objectives. Here are some steps you can follow when developing research aims and objectives:

• Identify the research question : Clearly identify the questions you want to answer through your research. This will help you define the scope of your research. Understanding the characteristics of a good research question will help you generate clearer aims and objectives.
• Conduct literature review : When defining your research aim and objectives, it’s important to conduct a literature review to identify key concepts, theories, and methods related to your research problem or question. Conducting a thorough literature review can help you understand what research has been done in the area and what gaps exist in the literature.
• Identify the research aim: Develop a research aim that summarizes the overarching goal of your research. The research aim should be broad and concise.
• Develop research objectives: Based on your research questions and research aim, develop specific research objectives that outline what you intend to achieve through your research. These objectives should be specific, measurable, achievable, relevant, and time-bound (SMART).
• Use action verbs: Use action verbs such as “investigate,” “examine,” “analyze,” and “compare” to describe your research aims and objectives. This makes them more specific and measurable.
• Ensure alignment with research question: Ensure that the research aim and objectives are aligned with the research question. This helps to ensure that the research remains focused and that the objectives are specific enough to answer your research question.
• Refine and revise: Once the research aim and objectives have been developed, refine and revise them as needed. Seek feedback from your colleagues, mentors, or supervisors to ensure that they are clear, concise, and achievable within the given resources and timeframe.
• Communicate: After finalizing the research aim and objectives, they should be communicated to the research team, stakeholders, and other interested parties. This helps to ensure that everyone is working towards the same end goal and understands the purpose of the study.

Common Pitfalls to Avoid While Formulating Aims and Objectives

There are several common mistakes that researchers can make when writing research aims and objectives. These include:

• Being too broad or vague: Aims and objectives that are too general or unclear can lead to confusion and lack of focus. It is important to ensure that the aims and objectives are concise and clear.
• Being too narrow or specific: On the other hand, aims and objectives that are too narrow or specific may limit the scope of the research and make it difficult to draw meaningful conclusions or implications.
• Being too ambitious: While it is important to aim high, being too ambitious with the aims and objectives can lead to unrealistic expectations and can be difficult to achieve within the constraints of the research project.
• Lack of alignment: The aims and objectives should be directly linked to the research questions being investigated. Otherwise, this will lead to a lack of coherence in the research project.
• Lack of feasibility: The aims and objectives should be achievable within the constraints of the research project, including time, budget, and resources. Failing to consider feasibility may cause compromise of the research quality.
• Failing to consider ethical considerations: The aims and objectives should take into account any ethical considerations, such as ensuring the safety and well-being of study participants.
• Failing to involve all stakeholders: It’s important to involve all relevant stakeholders, such as participants, supervisors, and funding agencies, in the development of the aims and objectives to ensure they are appropriate and relevant.

To avoid these common pitfalls, it is important to be specific, clear, relevant, and realistic when writing research aims and objectives. Seek feedback from colleagues or supervisors to ensure that the aims and objectives are aligned with the research problem , questions, and methodology, and are achievable within the constraints of the research project. It’s important to continually refine your aims and objectives as you go. As you progress in your research, it’s not uncommon for research aims and objectives to evolve slightly, but it’s important that they remain consistent with the study conducted and the research topic.

In summary, research aims and objectives are the backbone of any successful research project. They give you the ability to cut through the noise and hone in on what really matters. By setting clear goals and aligning them with your research questions and methodology, you can ensure that your research is relevant, impactful, and of the highest quality. So, before you hit the road on your research journey, make sure you have a clear destination and steps to get there. Let us know in the comments section below the challenges you faced and the strategies you followed while fomulating research aims and objectives! Also, feel free to reach out to us at any stage of your research or publication by using #AskEnago  and tagging @EnagoAcademy on Twitter , Facebook , and Quora . Happy researching!

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Home » Research Objectives – Types, Examples and Writing Guide

Research Objectives – Types, Examples and Writing Guide

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Research Objectives

Research objectives refer to the specific goals or aims of a research study. They provide a clear and concise description of what the researcher hopes to achieve by conducting the research . The objectives are typically based on the research questions and hypotheses formulated at the beginning of the study and are used to guide the research process.

Types of Research Objectives

Here are the different types of research objectives in research:

• Exploratory Objectives: These objectives are used to explore a topic, issue, or phenomenon that has not been studied in-depth before. The aim of exploratory research is to gain a better understanding of the subject matter and generate new ideas and hypotheses .
• Descriptive Objectives: These objectives aim to describe the characteristics, features, or attributes of a particular population, group, or phenomenon. Descriptive research answers the “what” questions and provides a snapshot of the subject matter.
• Explanatory Objectives : These objectives aim to explain the relationships between variables or factors. Explanatory research seeks to identify the cause-and-effect relationships between different phenomena.
• Predictive Objectives: These objectives aim to predict future events or outcomes based on existing data or trends. Predictive research uses statistical models to forecast future trends or outcomes.
• Evaluative Objectives : These objectives aim to evaluate the effectiveness or impact of a program, intervention, or policy. Evaluative research seeks to assess the outcomes or results of a particular intervention or program.
• Prescriptive Objectives: These objectives aim to provide recommendations or solutions to a particular problem or issue. Prescriptive research identifies the best course of action based on the results of the study.
• Diagnostic Objectives : These objectives aim to identify the causes or factors contributing to a particular problem or issue. Diagnostic research seeks to uncover the underlying reasons for a particular phenomenon.
• Comparative Objectives: These objectives aim to compare two or more groups, populations, or phenomena to identify similarities and differences. Comparative research is used to determine which group or approach is more effective or has better outcomes.
• Historical Objectives: These objectives aim to examine past events, trends, or phenomena to gain a better understanding of their significance and impact. Historical research uses archival data, documents, and records to study past events.
• Ethnographic Objectives : These objectives aim to understand the culture, beliefs, and practices of a particular group or community. Ethnographic research involves immersive fieldwork and observation to gain an insider’s perspective of the group being studied.
• Action-oriented Objectives: These objectives aim to bring about social or organizational change. Action-oriented research seeks to identify practical solutions to social problems and to promote positive change in society.
• Conceptual Objectives: These objectives aim to develop new theories, models, or frameworks to explain a particular phenomenon or set of phenomena. Conceptual research seeks to provide a deeper understanding of the subject matter by developing new theoretical perspectives.
• Methodological Objectives: These objectives aim to develop and improve research methods and techniques. Methodological research seeks to advance the field of research by improving the validity, reliability, and accuracy of research methods and tools.
• Theoretical Objectives : These objectives aim to test and refine existing theories or to develop new theoretical perspectives. Theoretical research seeks to advance the field of knowledge by testing and refining existing theories or by developing new theoretical frameworks.
• Measurement Objectives : These objectives aim to develop and validate measurement instruments, such as surveys, questionnaires, and tests. Measurement research seeks to improve the quality and reliability of data collection and analysis by developing and testing new measurement tools.
• Design Objectives : These objectives aim to develop and refine research designs, such as experimental, quasi-experimental, and observational designs. Design research seeks to improve the quality and validity of research by developing and testing new research designs.
• Sampling Objectives: These objectives aim to develop and refine sampling techniques, such as probability and non-probability sampling methods. Sampling research seeks to improve the representativeness and generalizability of research findings by developing and testing new sampling techniques.

How to Write Research Objectives

Writing clear and concise research objectives is an important part of any research project, as it helps to guide the study and ensure that it is focused and relevant. Here are some steps to follow when writing research objectives:

• Identify the research problem : Before you can write research objectives, you need to identify the research problem you are trying to address. This should be a clear and specific problem that can be addressed through research.
• Define the research questions : Based on the research problem, define the research questions you want to answer. These questions should be specific and should guide the research process.
• Identify the variables : Identify the key variables that you will be studying in your research. These are the factors that you will be measuring, manipulating, or analyzing to answer your research questions.
• Write specific objectives: Write specific, measurable objectives that will help you answer your research questions. These objectives should be clear and concise and should indicate what you hope to achieve through your research.
• Use the SMART criteria: To ensure that your research objectives are well-defined and achievable, use the SMART criteria. This means that your objectives should be Specific, Measurable, Achievable, Relevant, and Time-bound.
• Revise and refine: Once you have written your research objectives, revise and refine them to ensure that they are clear, concise, and achievable. Make sure that they align with your research questions and variables, and that they will help you answer your research problem.

Example of Research Objectives

Examples of research objectives Could be:

Research Objectives for the topic of “The Impact of Artificial Intelligence on Employment”:

• To investigate the effects of the adoption of AI on employment trends across various industries and occupations.
• To explore the potential for AI to create new job opportunities and transform existing roles in the workforce.
• To examine the social and economic implications of the widespread use of AI for employment, including issues such as income inequality and access to education and training.
• To identify the skills and competencies that will be required for individuals to thrive in an AI-driven workplace, and to explore the role of education and training in developing these skills.
• To evaluate the ethical and legal considerations surrounding the use of AI for employment, including issues such as bias, privacy, and the responsibility of employers and policymakers to protect workers’ rights.

When to Write Research Objectives

• At the beginning of a research project : Research objectives should be identified and written down before starting a research project. This helps to ensure that the project is focused and that data collection and analysis efforts are aligned with the intended purpose of the research.
• When refining research questions: Writing research objectives can help to clarify and refine research questions. Objectives provide a more concrete and specific framework for addressing research questions, which can improve the overall quality and direction of a research project.
• After conducting a literature review : Conducting a literature review can help to identify gaps in knowledge and areas that require further research. Writing research objectives can help to define and focus the research effort in these areas.
• When developing a research proposal: Research objectives are an important component of a research proposal. They help to articulate the purpose and scope of the research, and provide a clear and concise summary of the expected outcomes and contributions of the research.
• When seeking funding for research: Funding agencies often require a detailed description of research objectives as part of a funding proposal. Writing clear and specific research objectives can help to demonstrate the significance and potential impact of a research project, and increase the chances of securing funding.
• When designing a research study : Research objectives guide the design and implementation of a research study. They help to identify the appropriate research methods, sampling strategies, data collection and analysis techniques, and other relevant aspects of the study design.
• When communicating research findings: Research objectives provide a clear and concise summary of the main research questions and outcomes. They are often included in research reports and publications, and can help to ensure that the research findings are communicated effectively and accurately to a wide range of audiences.
• When evaluating research outcomes : Research objectives provide a basis for evaluating the success of a research project. They help to measure the degree to which research questions have been answered and the extent to which research outcomes have been achieved.
• When conducting research in a team : Writing research objectives can facilitate communication and collaboration within a research team. Objectives provide a shared understanding of the research purpose and goals, and can help to ensure that team members are working towards a common objective.

Purpose of Research Objectives

Some of the main purposes of research objectives include:

• To clarify the research question or problem : Research objectives help to define the specific aspects of the research question or problem that the study aims to address. This makes it easier to design a study that is focused and relevant.
• To guide the research design: Research objectives help to determine the research design, including the research methods, data collection techniques, and sampling strategy. This ensures that the study is structured and efficient.
• To measure progress : Research objectives provide a way to measure progress throughout the research process. They help the researcher to evaluate whether they are on track and meeting their goals.
• To communicate the research goals : Research objectives provide a clear and concise description of the research goals. This helps to communicate the purpose of the study to other researchers, stakeholders, and the general public.

Advantages of Research Objectives

Here are some advantages of having well-defined research objectives:

• Focus : Research objectives help to focus the research effort on specific areas of inquiry. By identifying clear research questions, the researcher can narrow down the scope of the study and avoid getting sidetracked by irrelevant information.
• Clarity : Clearly stated research objectives provide a roadmap for the research study. They provide a clear direction for the research, making it easier for the researcher to stay on track and achieve their goals.
• Measurability : Well-defined research objectives provide measurable outcomes that can be used to evaluate the success of the research project. This helps to ensure that the research is effective and that the research goals are achieved.
• Feasibility : Research objectives help to ensure that the research project is feasible. By clearly defining the research goals, the researcher can identify the resources required to achieve those goals and determine whether those resources are available.
• Relevance : Research objectives help to ensure that the research study is relevant and meaningful. By identifying specific research questions, the researcher can ensure that the study addresses important issues and contributes to the existing body of knowledge.

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How to Write the Dissertation Aims and Objectives – Guide & Examples

Published by Grace Graffin at January 27th, 2023 , Revised On October 9, 2023

Aims and objectives are among the essential aspects of a dissertation. If you write aims and objectives effectively, they can act as a foundation to give your research clarity and focus.

This article will provide you with all the necessary information regarding aims and objectives, their differences, writing tips , and the common mistakes you should avoid while writing them.

The aim is often a single sentence or a short paragraph that describes your dissertation’s main goal and intent. It tells what you hope to achieve at the end. You should write the aim so that it becomes identifiable when it is achieved with the completion of your dissertation .

The aim is written in a subsection of the introduction to clarify the overall purpose of the dissertation .

Example: It is often observed that employees in culturally diverse workplaces struggle to work effectively in a team. A probable cause of this issue is bullying at the workplace. This research investigates the impact of bullying on employee job satisfaction at culturally diverse workplaces and the resulting loss of employee productivity. This research will use surveys and case study analysis to analyze the impact of bullying on employees.

The objectives in a dissertation describe the ways through which you intend to achieve the research aim. They are specific statements that break down the aim into several smaller key sections of the overall research. Suitable objectives can help you stay focused and conduct research in the direction of your aim.

The number of objectives should be realistic; usually, between three to six, and each one should be possible to achieve. The following example shows the objectives for the previously-mentioned dissertation aim.

1. identification of the behaviors that are considered as bullying 2. exploring the factors that cause bullying at a culturally diverse workplace 3. analyzing the relationship between bullying and job satisfaction of employees 4. providing suitable recommendations on minimizing the bullying at the workplace

The objectives of a dissertation should be SMART.

• Specific: should be precise, focused, and well-defined
• Measurable: the progress should be measurable, and you should be able to determine when you have achieved an objective.
• Achievable: you should be able to carry out the required action within your available resources
• Relevant: should be related to the dissertation aim
• Time-bound: should be possible within the available time

Differences between aims and objectives

Aims and objectives are often mixed, but there are clear differences between them.

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How to write aims and objectives?

There is no particular way or standard to write the aims and objectives. Different researchers have different writing styles, and often it can be influenced by your research supervisor. However, you should follow certain basic principles while writing aims and objectives in a dissertation.

Writing the aim statement

The aim statement should cover the following essential elements.

• Why is the research necessary? (covers the underlying problem on which the study is to be conducted)
• What is the research about? (description of the research title)
• How are you going to conduct it? (a brief statement of intended research methods)

An appropriate aim clearly defines the research purpose without confusing the reader. If you struggle to explain your research and its importance in simpler terms, you should consider refining your research to clarify it further.

Writing objectives

The objectives describe how you would achieve your research aim. You can do this through the following steps,

• The first one to two objectives can be applied to the literature review . (Verbs to be used: investigate, examine, study)
• One objective can be applied to the methodology portion. (Verbs to be used: collect, select, demonstrate, estimate)
• Two to three objectives can cover the critical evaluation or discussion chapters (Verbs to be used: analyze, compare, evaluate)
• The final objective will cover the conclusion or recommendation portion. (Verbs to be used: conclude, recommend)

Instead of writing like a paragraph, the objectives should be written as a numbered list to give them more clarity.

How many aims and objectives should be there?

It depends upon the topic of your research and mainly upon your supervisor’s requirements. Generally, a dissertation has a single broad statement as the research aim. However, it is acceptable to include a main aim along with two to three subsidiary aims.

Similarly, the number of objectives should be realistic and sufficient to measure the progress regarding the achievement of the research aim. Their number can generally vary from three to six depending upon the aim.

Common mistakes to avoid while writing research aims and objectives

• Writing a broad research aim

Writing a broad research aim is a common mistake, and it often becomes difficult to achieve. It may create a problem when you are asked to prove how you have achieved your aims during your  viva defense . It would be best to narrow your study to a specific area in the early stages of the dissertation.

• Formulating overlapping research objectives

The objectives should be written such that they are measurable and distinct from each other. If they overlap, it makes it difficult to structure your dissertation properly in specific chapters.

• Setting unrealistic aims

Students often get over-ambitious while describing the research aim and face problems afterward in achieving those aims. You should avoid this mistake and be realistic about what you can achieve in the available time and resources.

Aims and objectives are the sections that require significant time and attention to avoid future hassles while conducting research and writing your dissertation.

Frequently Asked Questions

How to set dissertation aims and objectives.

To set dissertation aims and objectives, define your research goals clearly. Aims state what you want to achieve, while objectives outline specific, measurable steps to reach those goals. Ensure they align with your research question and contribute to your study’s significance.

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A dissertation is part of a Master’s or Bachelor’s course, whereas PHD thesis is frequently applied to a doctorate programme.

Not familiar with how to proofread and edit your dissertation? Find out the best tips and do’s and don’ts of proofreading and editing a dissertation here.

Not all doctorates require a dissertation. Many focus on practice and use projects instead. Learn more in this blog.

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• Write Your Specific Aims Page

The specific aims page, especially the aims themselves, are the crux of your grant application. Use the following tips to write a strong, clear specific aims page. Use the Specific Aims Page Checklist to assess your writing and to ensure that you have included all of the necessary components.

Create a ‘Funnel Shape’ Conceptually

Create a focused lead paragraph that has a "funnel shape" conceptually. Lead the reader from the general to the specific, so that by the time your specific aims appear, it's clear what gap in the literature you're addressing and how this new knowledge will fit into the field. This introduction should also indicate how this proposal builds upon your previous data.

Example: "The mechanism by which cirrhosis of the liver occurs in a subset of patients with Cystic Fibrosis is unknown. Our data over the past 3 years has demonstrated that gene X is a candidate modifier gene by crossing Cystic Fibrosis knockout mice with gene X deficient mice. This proposal will build upon these results and test the hypothesis that Gene X is a modifier gene through its fibrogenic activation properties."

Write a Clear, Testable Hypothesis

Strive to create one clear hypothesis first that will be tested through your specific aims . Know the difference between specific aims and long-term goals .

Note: Depending on the grant you are seeking, this rule may not be possible or desirable. For example, if you are applying for an R01 grant in health services/outcomes research, the typical grant in this area has a data collection project at its core that often addresses more than one goal . Therefore, the nature of the project is often briefly described in the last sentence of the introduction, rather than in the specific aims.

Example: "We will conduct a multi-center, prospective, longitudinal study of 1000 patients undergoing bone marrow transplantation for hematologic malignancies in order to..."

Do: "Three cloves of garlic per day cure colon cancer through activation of the caspase death pathway in tumor cells."

Don't: "There are various chemicals within garlic that have different effects on all cells including tumor cells."

Tips on Writing Specific Aims

• Make Aims Concise and Highly Focused
• Ensure Clear Results
• Write Aims that Test Single Hypothesis
• Indicate Why, What and How
• Avoid Sub-Aims

Your specific aims  is the crux of your proposal so make sure they are concise and highly focused. Get them critiqued, and rewrite until the aims are solid and provide a foundation for the rest of your proposal.

Ensure that your specific aims will provide clear results and that they test your hypothesis . Do: Hypothesis: "Three cloves of garlic per day cure colon cancer through activation of the caspase death pathway in tumor cells." Specific Aims: "1. Test in vitro in T84 colon cancer cells and in vivo in a mouse model of colon cancer that garlic activates the caspase death pathway. 2. Activation of this caspase pathway leads to tumor regression."

Don't: Hypothesis: "There are various chemicals within garlic that have different effects on all cells including tumor cells." Specific aims: "1. We will explore whether incubating different cell types in vitro with garlic affects cell survival. 2. Garlic proteins will be extracted and analyzed by mass spectroscopy."

Write specific aims that test a single, overarching hypothesis , and not individual aims connected to their own hypotheses. Note: Depending on the grant you are seeking, this rule may not be possible or desirable. For example, if you are applying for an R01 grant in health services/outcomes research, the typical grant in this area has a data collection project at its core that often addresses more than one goal . Therefore, the nature of the project is often briefly described in the last sentence of the introduction, rather than in the specific aims.

Example: "We will conduct a multi-center prospective, longitudinal study of 1000 patients undergoing bone marrow transplantation for hematologic malignancies in order to..."  

Convey specific aims that indicate why you want to do the work, what you want to do, and how you will do it.

Include no more than three aims and no sub-aims , if possible. Generally, you should not have four or more aims with sub-aims and/or their own hypotheses .

NIH K GRANT SPECIFIC AIMS PAGE RUBRIC

The rubric below provides recommendations for a Specific Aims page of a NIH K grant application . In addition to overall considerations, this rubric is broken up into four parts that correspond to the four sections of a Specific Aims page: the introduction paragraph, the body paragraph(s), the specific aims themselves, and the closing, or impact paragraph.

Use this rubric after you’ve completed a Specific Aims page draft to ensure that you have included all the necessary components. Review the completed rubric and carefully note any unchecked boxes. Review the resources linked throughout this document and use them to improve your Specific Aims page.

Please Note:  While this rubric is meant to be a comprehensive resource, we acknowledge that there is no singular correct way to write a grant application and in some cases, deviation from this rubric may be warranted.

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How to use and assess qualitative research methods

Loraine busetto.

1 Department of Neurology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany

Wolfgang Wick

2 Clinical Cooperation Unit Neuro-Oncology, German Cancer Research Center, Heidelberg, Germany

Christoph Gumbinger

Associated data.

Not applicable.

This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions, and focussing on intervention improvement. The most common methods of data collection are document study, (non-) participant observations, semi-structured interviews and focus groups. For data analysis, field-notes and audio-recordings are transcribed into protocols and transcripts, and coded using qualitative data management software. Criteria such as checklists, reflexivity, sampling strategies, piloting, co-coding, member-checking and stakeholder involvement can be used to enhance and assess the quality of the research conducted. Using qualitative in addition to quantitative designs will equip us with better tools to address a greater range of research problems, and to fill in blind spots in current neurological research and practice.

The aim of this paper is to provide an overview of qualitative research methods, including hands-on information on how they can be used, reported and assessed. This article is intended for beginning qualitative researchers in the health sciences as well as experienced quantitative researchers who wish to broaden their understanding of qualitative research.

What is qualitative research?

Qualitative research is defined as “the study of the nature of phenomena”, including “their quality, different manifestations, the context in which they appear or the perspectives from which they can be perceived” , but excluding “their range, frequency and place in an objectively determined chain of cause and effect” [ 1 ]. This formal definition can be complemented with a more pragmatic rule of thumb: qualitative research generally includes data in form of words rather than numbers [ 2 ].

Why conduct qualitative research?

Because some research questions cannot be answered using (only) quantitative methods. For example, one Australian study addressed the issue of why patients from Aboriginal communities often present late or not at all to specialist services offered by tertiary care hospitals. Using qualitative interviews with patients and staff, it found one of the most significant access barriers to be transportation problems, including some towns and communities simply not having a bus service to the hospital [ 3 ]. A quantitative study could have measured the number of patients over time or even looked at possible explanatory factors – but only those previously known or suspected to be of relevance. To discover reasons for observed patterns, especially the invisible or surprising ones, qualitative designs are needed.

While qualitative research is common in other fields, it is still relatively underrepresented in health services research. The latter field is more traditionally rooted in the evidence-based-medicine paradigm, as seen in " research that involves testing the effectiveness of various strategies to achieve changes in clinical practice, preferably applying randomised controlled trial study designs (...) " [ 4 ]. This focus on quantitative research and specifically randomised controlled trials (RCT) is visible in the idea of a hierarchy of research evidence which assumes that some research designs are objectively better than others, and that choosing a "lesser" design is only acceptable when the better ones are not practically or ethically feasible [ 5 , 6 ]. Others, however, argue that an objective hierarchy does not exist, and that, instead, the research design and methods should be chosen to fit the specific research question at hand – "questions before methods" [ 2 , 7 – 9 ]. This means that even when an RCT is possible, some research problems require a different design that is better suited to addressing them. Arguing in JAMA, Berwick uses the example of rapid response teams in hospitals, which he describes as " a complex, multicomponent intervention – essentially a process of social change" susceptible to a range of different context factors including leadership or organisation history. According to him, "[in] such complex terrain, the RCT is an impoverished way to learn. Critics who use it as a truth standard in this context are incorrect" [ 8 ] . Instead of limiting oneself to RCTs, Berwick recommends embracing a wider range of methods , including qualitative ones, which for "these specific applications, (...) are not compromises in learning how to improve; they are superior" [ 8 ].

Research problems that can be approached particularly well using qualitative methods include assessing complex multi-component interventions or systems (of change), addressing questions beyond “what works”, towards “what works for whom when, how and why”, and focussing on intervention improvement rather than accreditation [ 7 , 9 – 12 ]. Using qualitative methods can also help shed light on the “softer” side of medical treatment. For example, while quantitative trials can measure the costs and benefits of neuro-oncological treatment in terms of survival rates or adverse effects, qualitative research can help provide a better understanding of patient or caregiver stress, visibility of illness or out-of-pocket expenses.

How to conduct qualitative research?

Given that qualitative research is characterised by flexibility, openness and responsivity to context, the steps of data collection and analysis are not as separate and consecutive as they tend to be in quantitative research [ 13 , 14 ]. As Fossey puts it : “sampling, data collection, analysis and interpretation are related to each other in a cyclical (iterative) manner, rather than following one after another in a stepwise approach” [ 15 ]. The researcher can make educated decisions with regard to the choice of method, how they are implemented, and to which and how many units they are applied [ 13 ]. As shown in Fig.  1 , this can involve several back-and-forth steps between data collection and analysis where new insights and experiences can lead to adaption and expansion of the original plan. Some insights may also necessitate a revision of the research question and/or the research design as a whole. The process ends when saturation is achieved, i.e. when no relevant new information can be found (see also below: sampling and saturation). For reasons of transparency, it is essential for all decisions as well as the underlying reasoning to be well-documented.

Iterative research process

While it is not always explicitly addressed, qualitative methods reflect a different underlying research paradigm than quantitative research (e.g. constructivism or interpretivism as opposed to positivism). The choice of methods can be based on the respective underlying substantive theory or theoretical framework used by the researcher [ 2 ].

Data collection

The methods of qualitative data collection most commonly used in health research are document study, observations, semi-structured interviews and focus groups [ 1 , 14 , 16 , 17 ].

Document study

Document study (also called document analysis) refers to the review by the researcher of written materials [ 14 ]. These can include personal and non-personal documents such as archives, annual reports, guidelines, policy documents, diaries or letters.

Observations

Observations are particularly useful to gain insights into a certain setting and actual behaviour – as opposed to reported behaviour or opinions [ 13 ]. Qualitative observations can be either participant or non-participant in nature. In participant observations, the observer is part of the observed setting, for example a nurse working in an intensive care unit [ 18 ]. In non-participant observations, the observer is “on the outside looking in”, i.e. present in but not part of the situation, trying not to influence the setting by their presence. Observations can be planned (e.g. for 3 h during the day or night shift) or ad hoc (e.g. as soon as a stroke patient arrives at the emergency room). During the observation, the observer takes notes on everything or certain pre-determined parts of what is happening around them, for example focusing on physician-patient interactions or communication between different professional groups. Written notes can be taken during or after the observations, depending on feasibility (which is usually lower during participant observations) and acceptability (e.g. when the observer is perceived to be judging the observed). Afterwards, these field notes are transcribed into observation protocols. If more than one observer was involved, field notes are taken independently, but notes can be consolidated into one protocol after discussions. Advantages of conducting observations include minimising the distance between the researcher and the researched, the potential discovery of topics that the researcher did not realise were relevant and gaining deeper insights into the real-world dimensions of the research problem at hand [ 18 ].

Semi-structured interviews

Hijmans & Kuyper describe qualitative interviews as “an exchange with an informal character, a conversation with a goal” [ 19 ]. Interviews are used to gain insights into a person’s subjective experiences, opinions and motivations – as opposed to facts or behaviours [ 13 ]. Interviews can be distinguished by the degree to which they are structured (i.e. a questionnaire), open (e.g. free conversation or autobiographical interviews) or semi-structured [ 2 , 13 ]. Semi-structured interviews are characterized by open-ended questions and the use of an interview guide (or topic guide/list) in which the broad areas of interest, sometimes including sub-questions, are defined [ 19 ]. The pre-defined topics in the interview guide can be derived from the literature, previous research or a preliminary method of data collection, e.g. document study or observations. The topic list is usually adapted and improved at the start of the data collection process as the interviewer learns more about the field [ 20 ]. Across interviews the focus on the different (blocks of) questions may differ and some questions may be skipped altogether (e.g. if the interviewee is not able or willing to answer the questions or for concerns about the total length of the interview) [ 20 ]. Qualitative interviews are usually not conducted in written format as it impedes on the interactive component of the method [ 20 ]. In comparison to written surveys, qualitative interviews have the advantage of being interactive and allowing for unexpected topics to emerge and to be taken up by the researcher. This can also help overcome a provider or researcher-centred bias often found in written surveys, which by nature, can only measure what is already known or expected to be of relevance to the researcher. Interviews can be audio- or video-taped; but sometimes it is only feasible or acceptable for the interviewer to take written notes [ 14 , 16 , 20 ].

Focus groups

Focus groups are group interviews to explore participants’ expertise and experiences, including explorations of how and why people behave in certain ways [ 1 ]. Focus groups usually consist of 6–8 people and are led by an experienced moderator following a topic guide or “script” [ 21 ]. They can involve an observer who takes note of the non-verbal aspects of the situation, possibly using an observation guide [ 21 ]. Depending on researchers’ and participants’ preferences, the discussions can be audio- or video-taped and transcribed afterwards [ 21 ]. Focus groups are useful for bringing together homogeneous (to a lesser extent heterogeneous) groups of participants with relevant expertise and experience on a given topic on which they can share detailed information [ 21 ]. Focus groups are a relatively easy, fast and inexpensive method to gain access to information on interactions in a given group, i.e. “the sharing and comparing” among participants [ 21 ]. Disadvantages include less control over the process and a lesser extent to which each individual may participate. Moreover, focus group moderators need experience, as do those tasked with the analysis of the resulting data. Focus groups can be less appropriate for discussing sensitive topics that participants might be reluctant to disclose in a group setting [ 13 ]. Moreover, attention must be paid to the emergence of “groupthink” as well as possible power dynamics within the group, e.g. when patients are awed or intimidated by health professionals.

Choosing the “right” method

As explained above, the school of thought underlying qualitative research assumes no objective hierarchy of evidence and methods. This means that each choice of single or combined methods has to be based on the research question that needs to be answered and a critical assessment with regard to whether or to what extent the chosen method can accomplish this – i.e. the “fit” between question and method [ 14 ]. It is necessary for these decisions to be documented when they are being made, and to be critically discussed when reporting methods and results.

Let us assume that our research aim is to examine the (clinical) processes around acute endovascular treatment (EVT), from the patient’s arrival at the emergency room to recanalization, with the aim to identify possible causes for delay and/or other causes for sub-optimal treatment outcome. As a first step, we could conduct a document study of the relevant standard operating procedures (SOPs) for this phase of care – are they up-to-date and in line with current guidelines? Do they contain any mistakes, irregularities or uncertainties that could cause delays or other problems? Regardless of the answers to these questions, the results have to be interpreted based on what they are: a written outline of what care processes in this hospital should look like. If we want to know what they actually look like in practice, we can conduct observations of the processes described in the SOPs. These results can (and should) be analysed in themselves, but also in comparison to the results of the document analysis, especially as regards relevant discrepancies. Do the SOPs outline specific tests for which no equipment can be observed or tasks to be performed by specialized nurses who are not present during the observation? It might also be possible that the written SOP is outdated, but the actual care provided is in line with current best practice. In order to find out why these discrepancies exist, it can be useful to conduct interviews. Are the physicians simply not aware of the SOPs (because their existence is limited to the hospital’s intranet) or do they actively disagree with them or does the infrastructure make it impossible to provide the care as described? Another rationale for adding interviews is that some situations (or all of their possible variations for different patient groups or the day, night or weekend shift) cannot practically or ethically be observed. In this case, it is possible to ask those involved to report on their actions – being aware that this is not the same as the actual observation. A senior physician’s or hospital manager’s description of certain situations might differ from a nurse’s or junior physician’s one, maybe because they intentionally misrepresent facts or maybe because different aspects of the process are visible or important to them. In some cases, it can also be relevant to consider to whom the interviewee is disclosing this information – someone they trust, someone they are otherwise not connected to, or someone they suspect or are aware of being in a potentially “dangerous” power relationship to them. Lastly, a focus group could be conducted with representatives of the relevant professional groups to explore how and why exactly they provide care around EVT. The discussion might reveal discrepancies (between SOPs and actual care or between different physicians) and motivations to the researchers as well as to the focus group members that they might not have been aware of themselves. For the focus group to deliver relevant information, attention has to be paid to its composition and conduct, for example, to make sure that all participants feel safe to disclose sensitive or potentially problematic information or that the discussion is not dominated by (senior) physicians only. The resulting combination of data collection methods is shown in Fig.  2 .

Possible combination of data collection methods

Attributions for icons: “Book” by Serhii Smirnov, “Interview” by Adrien Coquet, FR, “Magnifying Glass” by anggun, ID, “Business communication” by Vectors Market; all from the Noun Project

The combination of multiple data source as described for this example can be referred to as “triangulation”, in which multiple measurements are carried out from different angles to achieve a more comprehensive understanding of the phenomenon under study [ 22 , 23 ].

Data analysis

To analyse the data collected through observations, interviews and focus groups these need to be transcribed into protocols and transcripts (see Fig.  3 ). Interviews and focus groups can be transcribed verbatim , with or without annotations for behaviour (e.g. laughing, crying, pausing) and with or without phonetic transcription of dialects and filler words, depending on what is expected or known to be relevant for the analysis. In the next step, the protocols and transcripts are coded , that is, marked (or tagged, labelled) with one or more short descriptors of the content of a sentence or paragraph [ 2 , 15 , 23 ]. Jansen describes coding as “connecting the raw data with “theoretical” terms” [ 20 ]. In a more practical sense, coding makes raw data sortable. This makes it possible to extract and examine all segments describing, say, a tele-neurology consultation from multiple data sources (e.g. SOPs, emergency room observations, staff and patient interview). In a process of synthesis and abstraction, the codes are then grouped, summarised and/or categorised [ 15 , 20 ]. The end product of the coding or analysis process is a descriptive theory of the behavioural pattern under investigation [ 20 ]. The coding process is performed using qualitative data management software, the most common ones being InVivo, MaxQDA and Atlas.ti. It should be noted that these are data management tools which support the analysis performed by the researcher(s) [ 14 ].

From data collection to data analysis

Attributions for icons: see Fig. ​ Fig.2, 2 , also “Speech to text” by Trevor Dsouza, “Field Notes” by Mike O’Brien, US, “Voice Record” by ProSymbols, US, “Inspection” by Made, AU, and “Cloud” by Graphic Tigers; all from the Noun Project

How to report qualitative research?

Protocols of qualitative research can be published separately and in advance of the study results. However, the aim is not the same as in RCT protocols, i.e. to pre-define and set in stone the research questions and primary or secondary endpoints. Rather, it is a way to describe the research methods in detail, which might not be possible in the results paper given journals’ word limits. Qualitative research papers are usually longer than their quantitative counterparts to allow for deep understanding and so-called “thick description”. In the methods section, the focus is on transparency of the methods used, including why, how and by whom they were implemented in the specific study setting, so as to enable a discussion of whether and how this may have influenced data collection, analysis and interpretation. The results section usually starts with a paragraph outlining the main findings, followed by more detailed descriptions of, for example, the commonalities, discrepancies or exceptions per category [ 20 ]. Here it is important to support main findings by relevant quotations, which may add information, context, emphasis or real-life examples [ 20 , 23 ]. It is subject to debate in the field whether it is relevant to state the exact number or percentage of respondents supporting a certain statement (e.g. “Five interviewees expressed negative feelings towards XYZ”) [ 21 ].

How to combine qualitative with quantitative research?

Qualitative methods can be combined with other methods in multi- or mixed methods designs, which “[employ] two or more different methods [ …] within the same study or research program rather than confining the research to one single method” [ 24 ]. Reasons for combining methods can be diverse, including triangulation for corroboration of findings, complementarity for illustration and clarification of results, expansion to extend the breadth and range of the study, explanation of (unexpected) results generated with one method with the help of another, or offsetting the weakness of one method with the strength of another [ 1 , 17 , 24 – 26 ]. The resulting designs can be classified according to when, why and how the different quantitative and/or qualitative data strands are combined. The three most common types of mixed method designs are the convergent parallel design , the explanatory sequential design and the exploratory sequential design. The designs with examples are shown in Fig.  4 .

Three common mixed methods designs

In the convergent parallel design, a qualitative study is conducted in parallel to and independently of a quantitative study, and the results of both studies are compared and combined at the stage of interpretation of results. Using the above example of EVT provision, this could entail setting up a quantitative EVT registry to measure process times and patient outcomes in parallel to conducting the qualitative research outlined above, and then comparing results. Amongst other things, this would make it possible to assess whether interview respondents’ subjective impressions of patients receiving good care match modified Rankin Scores at follow-up, or whether observed delays in care provision are exceptions or the rule when compared to door-to-needle times as documented in the registry. In the explanatory sequential design, a quantitative study is carried out first, followed by a qualitative study to help explain the results from the quantitative study. This would be an appropriate design if the registry alone had revealed relevant delays in door-to-needle times and the qualitative study would be used to understand where and why these occurred, and how they could be improved. In the exploratory design, the qualitative study is carried out first and its results help informing and building the quantitative study in the next step [ 26 ]. If the qualitative study around EVT provision had shown a high level of dissatisfaction among the staff members involved, a quantitative questionnaire investigating staff satisfaction could be set up in the next step, informed by the qualitative study on which topics dissatisfaction had been expressed. Amongst other things, the questionnaire design would make it possible to widen the reach of the research to more respondents from different (types of) hospitals, regions, countries or settings, and to conduct sub-group analyses for different professional groups.

How to assess qualitative research?

A variety of assessment criteria and lists have been developed for qualitative research, ranging in their focus and comprehensiveness [ 14 , 17 , 27 ]. However, none of these has been elevated to the “gold standard” in the field. In the following, we therefore focus on a set of commonly used assessment criteria that, from a practical standpoint, a researcher can look for when assessing a qualitative research report or paper.

Assessors should check the authors’ use of and adherence to the relevant reporting checklists (e.g. Standards for Reporting Qualitative Research (SRQR)) to make sure all items that are relevant for this type of research are addressed [ 23 , 28 ]. Discussions of quantitative measures in addition to or instead of these qualitative measures can be a sign of lower quality of the research (paper). Providing and adhering to a checklist for qualitative research contributes to an important quality criterion for qualitative research, namely transparency [ 15 , 17 , 23 ].

Reflexivity

While methodological transparency and complete reporting is relevant for all types of research, some additional criteria must be taken into account for qualitative research. This includes what is called reflexivity, i.e. sensitivity to the relationship between the researcher and the researched, including how contact was established and maintained, or the background and experience of the researcher(s) involved in data collection and analysis. Depending on the research question and population to be researched this can be limited to professional experience, but it may also include gender, age or ethnicity [ 17 , 27 ]. These details are relevant because in qualitative research, as opposed to quantitative research, the researcher as a person cannot be isolated from the research process [ 23 ]. It may influence the conversation when an interviewed patient speaks to an interviewer who is a physician, or when an interviewee is asked to discuss a gynaecological procedure with a male interviewer, and therefore the reader must be made aware of these details [ 19 ].

Sampling and saturation

The aim of qualitative sampling is for all variants of the objects of observation that are deemed relevant for the study to be present in the sample “ to see the issue and its meanings from as many angles as possible” [ 1 , 16 , 19 , 20 , 27 ] , and to ensure “information-richness [ 15 ]. An iterative sampling approach is advised, in which data collection (e.g. five interviews) is followed by data analysis, followed by more data collection to find variants that are lacking in the current sample. This process continues until no new (relevant) information can be found and further sampling becomes redundant – which is called saturation [ 1 , 15 ] . In other words: qualitative data collection finds its end point not a priori , but when the research team determines that saturation has been reached [ 29 , 30 ].

This is also the reason why most qualitative studies use deliberate instead of random sampling strategies. This is generally referred to as “ purposive sampling” , in which researchers pre-define which types of participants or cases they need to include so as to cover all variations that are expected to be of relevance, based on the literature, previous experience or theory (i.e. theoretical sampling) [ 14 , 20 ]. Other types of purposive sampling include (but are not limited to) maximum variation sampling, critical case sampling or extreme or deviant case sampling [ 2 ]. In the above EVT example, a purposive sample could include all relevant professional groups and/or all relevant stakeholders (patients, relatives) and/or all relevant times of observation (day, night and weekend shift).

Assessors of qualitative research should check whether the considerations underlying the sampling strategy were sound and whether or how researchers tried to adapt and improve their strategies in stepwise or cyclical approaches between data collection and analysis to achieve saturation [ 14 ].

Good qualitative research is iterative in nature, i.e. it goes back and forth between data collection and analysis, revising and improving the approach where necessary. One example of this are pilot interviews, where different aspects of the interview (especially the interview guide, but also, for example, the site of the interview or whether the interview can be audio-recorded) are tested with a small number of respondents, evaluated and revised [ 19 ]. In doing so, the interviewer learns which wording or types of questions work best, or which is the best length of an interview with patients who have trouble concentrating for an extended time. Of course, the same reasoning applies to observations or focus groups which can also be piloted.

Ideally, coding should be performed by at least two researchers, especially at the beginning of the coding process when a common approach must be defined, including the establishment of a useful coding list (or tree), and when a common meaning of individual codes must be established [ 23 ]. An initial sub-set or all transcripts can be coded independently by the coders and then compared and consolidated after regular discussions in the research team. This is to make sure that codes are applied consistently to the research data.

Member checking

Member checking, also called respondent validation , refers to the practice of checking back with study respondents to see if the research is in line with their views [ 14 , 27 ]. This can happen after data collection or analysis or when first results are available [ 23 ]. For example, interviewees can be provided with (summaries of) their transcripts and asked whether they believe this to be a complete representation of their views or whether they would like to clarify or elaborate on their responses [ 17 ]. Respondents’ feedback on these issues then becomes part of the data collection and analysis [ 27 ].

Stakeholder involvement

In those niches where qualitative approaches have been able to evolve and grow, a new trend has seen the inclusion of patients and their representatives not only as study participants (i.e. “members”, see above) but as consultants to and active participants in the broader research process [ 31 – 33 ]. The underlying assumption is that patients and other stakeholders hold unique perspectives and experiences that add value beyond their own single story, making the research more relevant and beneficial to researchers, study participants and (future) patients alike [ 34 , 35 ]. Using the example of patients on or nearing dialysis, a recent scoping review found that 80% of clinical research did not address the top 10 research priorities identified by patients and caregivers [ 32 , 36 ]. In this sense, the involvement of the relevant stakeholders, especially patients and relatives, is increasingly being seen as a quality indicator in and of itself.

How not to assess qualitative research

The above overview does not include certain items that are routine in assessments of quantitative research. What follows is a non-exhaustive, non-representative, experience-based list of the quantitative criteria often applied to the assessment of qualitative research, as well as an explanation of the limited usefulness of these endeavours.

Protocol adherence

Given the openness and flexibility of qualitative research, it should not be assessed by how well it adheres to pre-determined and fixed strategies – in other words: its rigidity. Instead, the assessor should look for signs of adaptation and refinement based on lessons learned from earlier steps in the research process.

Sample size

For the reasons explained above, qualitative research does not require specific sample sizes, nor does it require that the sample size be determined a priori [ 1 , 14 , 27 , 37 – 39 ]. Sample size can only be a useful quality indicator when related to the research purpose, the chosen methodology and the composition of the sample, i.e. who was included and why.

Randomisation

While some authors argue that randomisation can be used in qualitative research, this is not commonly the case, as neither its feasibility nor its necessity or usefulness has been convincingly established for qualitative research [ 13 , 27 ]. Relevant disadvantages include the negative impact of a too large sample size as well as the possibility (or probability) of selecting “ quiet, uncooperative or inarticulate individuals ” [ 17 ]. Qualitative studies do not use control groups, either.

Interrater reliability, variability and other “objectivity checks”

The concept of “interrater reliability” is sometimes used in qualitative research to assess to which extent the coding approach overlaps between the two co-coders. However, it is not clear what this measure tells us about the quality of the analysis [ 23 ]. This means that these scores can be included in qualitative research reports, preferably with some additional information on what the score means for the analysis, but it is not a requirement. Relatedly, it is not relevant for the quality or “objectivity” of qualitative research to separate those who recruited the study participants and collected and analysed the data. Experiences even show that it might be better to have the same person or team perform all of these tasks [ 20 ]. First, when researchers introduce themselves during recruitment this can enhance trust when the interview takes place days or weeks later with the same researcher. Second, when the audio-recording is transcribed for analysis, the researcher conducting the interviews will usually remember the interviewee and the specific interview situation during data analysis. This might be helpful in providing additional context information for interpretation of data, e.g. on whether something might have been meant as a joke [ 18 ].

Not being quantitative research

Being qualitative research instead of quantitative research should not be used as an assessment criterion if it is used irrespectively of the research problem at hand. Similarly, qualitative research should not be required to be combined with quantitative research per se – unless mixed methods research is judged as inherently better than single-method research. In this case, the same criterion should be applied for quantitative studies without a qualitative component.

The main take-away points of this paper are summarised in Table ​ Table1. 1 . We aimed to show that, if conducted well, qualitative research can answer specific research questions that cannot to be adequately answered using (only) quantitative designs. Seeing qualitative and quantitative methods as equal will help us become more aware and critical of the “fit” between the research problem and our chosen methods: I can conduct an RCT to determine the reasons for transportation delays of acute stroke patients – but should I? It also provides us with a greater range of tools to tackle a greater range of research problems more appropriately and successfully, filling in the blind spots on one half of the methodological spectrum to better address the whole complexity of neurological research and practice.

Take-away-points

Acknowledgements

Abbreviations, authors’ contributions.

LB drafted the manuscript; WW and CG revised the manuscript; all authors approved the final versions.

no external funding.

Availability of data and materials

Ethics approval and consent to participate, consent for publication, competing interests.

The authors declare no competing interests.

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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 .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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To Protect Human Health, We Must Protect the Earth’s Health

“The Earth crisis now represents a humanitarian crisis,” says Sam Myers. But there are solutions that serve both people and the planet.

Public Health On Call

Human activities have transformed and degraded Earth’s natural systems. But it’s not just the planet that endures the harms of things like pollution and climate change. Changes like rising ocean temperatures and CO2 levels have cascading effects that threaten the future of humans.

In this Q&A, adapted from the  April 22 episode of Public Health On Call ,  Joshua Sharfstein , MD, talks with  Sam Myers , MD, faculty director of the new  Johns Hopkins Institute for Planetary Health and founding director of the  Planetary Health Alliance , about this interdisciplinary approach to understanding how the state of the planet impacts human health and well-being.

What is planetary health?

Planetary health is a cross-disciplinary field that has emerged in the last eight or nine years. It focuses on how our transformation of nature—our degradation and alteration of all of our planet's natural systems—is coming back to affect our health.

Climate change, biodiversity loss, global-scale pollution of air, water, and soil, changes in land use and land cover—all driven by human activity—are resulting in increased burdens of disease and impacting all dimensions of human health. We want to understand what those dynamics are and how we can address them.

What are some examples of changes impacting human health?

We know that ocean warming is changing the size of both fish and fisheries. It’s also changing where the fisheries are located, moving them away from the tropics and toward the poles. We did a study to determine how many people depend on wild-harvested fish for critical nutrients and live close to a threshold of insufficient intake of those nutrients—what we define as the vulnerable population to these changes. We found that over a billion people fall into this category.

We’ve also found that crops like rice, wheat, and maize—foods that provide most of the calories in the global diet—tend to lose essential nutrients when grown at elevated concentrations of carbon dioxide like the ones we expect to see by about the middle of this century.

In our  free air carbon dioxide enrichment (FACE) experiments , we grew 41 cultivars of those kinds of crops in seven locations across three continents over 10 years. We found that growing these staple food crops at high CO2 levels significantly reduces the amount of iron, zinc, and protein they contain. We then modeled what these findings would mean for populations in 150 countries and found that the CO2 effect alone would cause around 150-200 million people to be pushed into nutritional insufficiency of these nutrients.

Other research has shown that growing different cultivars of rice at elevated CO2 resulted in B vitamins being reduced by almost 30%. We used that data to model what that might mean for the risk of things like neural tube defects, and we found really large impacts.

What other environmental factors does planetary health consider?

Changing levels of CO2 in the atmosphere is just one very specific biophysical change, but we're changing all the biophysical conditions that our entire food production system has been developed to be optimized for: temperature, precipitation, amount of arable land, pollinators, and pest and pathogen relationships. All of those things are now changing in response to human activity in ways that usually represent headwinds for global food production, in terms of both quality and quantity.

How does planetary health address the extreme scale of the changes humans are causing the environment and the consequences of those?

The field of planetary health has emerged out of a recognition that the pace and scale at which we're transforming all our natural systems has become a global health crisis.

The global health impacts of the Earth crisis are kind of a silent pandemic, and there are parallels to the COVID pandemic we've just come out of. The COVID pandemic required massive mobilization of new technologies, investments in economic stimulus and foreign assistance, respect for science, and urgent global behavior change. This silent pandemic is probably much more impactful to human health. It could be addressed in a very similar way, but we’re doing very little.

You can't respond to a crisis until you recognize that there is a crisis. As you are trying to raise concern over planetary health, how is that warning signal being received?

The field is growing very quickly. We started the  Planetary Health Alliance about eight years ago, and we now have more than 400 organizations involved in more than 70 countries. There's been a very rapid proliferation of new courses, degree programs, and journals in planetary health. We’re also seeing government agencies adopting planetary health as a frame, including the European Union, certain national governments, and the UN system.

There has been a rapid understanding and recognition of the global health urgency related to the Earth crisis, but it's a drop in the bucket of what is really needed to fully mobilize and address the crisis.

Are there solutions that can address multiple problems at once?

Yes. From a policy standpoint, the goal is to find opportunities to both optimize human health and well-being and reduce our ecological footprint. In order to protect and regenerate the Earth’s natural life support systems, we have to change the way we’re living. The good news is there are a lot of ways we can do this, and many of these changes also have major co-benefits.

For example, switching to clean, renewable energy is important to addressing climate change. Doing so also reduces the amount of air pollution, which drives something like 9 million deaths every year. Greening our cities and designing them to be walkable and bikeable not only reduces greenhouse gasses and increases biodiversity; these changes also provide major mental and physical health benefits.

What is the Planetary Health Alliance and what does it do?

Contrary to what it sounds like, the Planetary Health Alliance doesn’t fight for the planet’s health—they’re fighting for human health and the health of other species.

It’s a recognition that the well-being of all life on earth depends on stable natural life support systems. Things like degradation of biodiversity, pollution, and land use change all interact with each other in very complex ways that affect these foundational conditions for all life on Earth:

• The quality of air that we breathe.
• The quality of water that we consume.
• The quality and quantity of food we can produce.
• Exposure to infectious disease and extreme weather events.

And these impacts are driving an urgent set of health problems.

The Alliance functions as sort of the backbone organization for this growing global field. That includes curating new knowledge, writing the  first textbook for the field , developing core competencies for education, creating a  platform to support educators and planetary health around the world, organizing an  annual meeting , and putting out  a newsletter .

One half of the Alliance’s focus is to create and support a global community of practice. The other half is what we call “mainstreaming planetary health,” which means taking that community of practice, the new knowledge, and conceptual frameworks out of the field and connecting them to action.

We’re working to ensure that policymakers, the private sector, and the general public are aware that the Earth crisis now represents a humanitarian crisis and that there are a variety of solutions that benefit both people and the planet.

Tell us about the Planetary Health Institute you've started at Johns Hopkins.

The Institute is the first example of a major university using planetary health as a lens to bring faculty and students together across all of its schools and centers. The Institute is bringing together people in the arts and humanities, engineers, natural scientists, and people in government, law, and policy around this central project of planetary health. We’ll focus on research, education, policy, practice, and clinical  programs . And already, there are all kinds of interesting interdisciplinary initiatives at Hopkins that are focused on planetary health: One on planetary health cities, one on Indigenous health, and another one on food systems, just to name a few.  

This interview was edited for length and clarity by Aliza Rosen.

• Healthy Planet, Healthy People
• New Johns Hopkins Institute Aims to Safeguard Human Health on a Rapidly Changing Planet (JHU Hub)
• Planetary Health: Thinking About the Earth Crisis as a Humanitarian Crisis (podcast)

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Marine Cloud Brightening Program

The Marine Cloud Brightening Program is an open collaboration of atmospheric scientists and other experts to study how clouds respond to particles — also called aerosols — in the atmosphere.

This research aims to further our understanding of how interactions between aerosols and clouds impact our climate system, and to investigate the feasibility and potential impacts of reducing climate warming by intentionally increasing the reflection of sunlight from marine clouds. An overarching goal of the research is to provide open, objective scientific information to help improve society’s ability to understand the climate system and to address near-term climate risks.

Why study how particles (aerosols) affect clouds?

Clouds reflect sunlight back to space, which cools temperatures locally and across the planet. Sustained small changes in cloud cover or in the amount of sunlight reflected by clouds have the potential to change climate both locally and globally.

When aerosol particles in the atmosphere from both natural sources (such as biological emissions and sea spray) and human activities (such as from burning fossil fuels, wood and vegetation) mix into low clouds, particularly over the ocean, they can cause the clouds to brighten and thus reflect even more sunlight back into space. This has a cooling effect on the Earth’s climate.

Importantly, this role of aerosols in affecting sunlight reflection is changing. At the same time that humans are continuing to release climate-warming greenhouse gases into the atmosphere, expanding air quality regulations are leading to declines in the concentration of atmospheric aerosol particles. This is beneficial for public health and local ecosystems — at the same time, because most of these particles have a cooling effect on our climate, removing them generally adds to climate warming.

Atmospheric scientists are still not certain just how much of a cooling effect these aerosol particles have on the climate overall. Scientists estimate that aerosols from human emissions are offsetting 0.5℃ of global warming from greenhouse gases, but they could be cooling as little as 0.2 ℃ or as much as 1.0 ℃ ( Forster et al., 2021 ) . The uncertainty in this number leads to uncertainty about how much warming to expect in the coming decades.

If the effect of aerosols on clouds is large, reducing aerosol pollution might significantly accelerate climate warming in the very near term. One recent paper concluded that there has already been an acceleration in global warming due to the decline in atmospheric aerosols since 2010, and projects that between now and 2040 the rate of warming may double due to this effect ( Hansen et al., 2023 ). Recent steep reductions in particulate pollution emissions from ships that coincided with record ocean surface and global temperatures have increased interest in understanding and quantifying these effects.

What is marine cloud brightening?

Scientific studies indicate that aerosols of the right size and concentration could significantly increase the reflectivity of specific types of clouds. This phenomenon is visible in satellite images of clouds brightened by ship emissions (known as “ship tracks”). Observations of ship tracks led scientists to the idea of using particles of salt from sea water, a natural source of cloud-forming aerosol particles, to brighten clouds over parts of the ocean in order to reduce climate warming.

In this approach, sea salt particles from the ocean would be sprayed from ships into areas of low-lying clouds. Once emitted, the particles would remain in the atmosphere for only a few days, within localized areas.

There are specific regions of the ocean with clouds that could be more favorable for brightening in this way, though it is still uncertain how much brightening could be achieved in different regions. If marine cloud brightening (MCB) were ever to be used, which areas are brightened, and by how much, would determine how much climate cooling could be produced, how climate changes would be affected by different implementations of MCB, and how MCB would affect climate impacts and risks.

Changes in clouds over broad regions affect the circulation of the atmosphere, weather and precipitation. Both MCB and pollution aerosols, by changing clouds, therefore will affect regions both near and far from the location of brightening. A critical aspect of understanding MCB and aerosol effects more broadly is improving the ability to project these long-distance effects and risks.

Our research

As humans consider making changes to our aerosol emissions — either reducing them via regulation and technology, or pursuing intentional marine cloud brightening as a climate intervention — we need a stronger scientific understanding of these processes in order to both advance positive effects and limit unintended effects.

The Marine Cloud Brightening Program is a scientific program, led by atmospheric scientists, that aims to simultaneously:

• Better understand the present-day effects of pollution aerosols on clouds
• Investigate whether aerosol particles made from sea salt could be used to intentionally reduce near-term climate warming while greenhouse gas concentrations are brought down to safer levels
• Understand the benefits, risks and efficacy of the intentional use of aerosols to reduce warming through different implementations of marine cloud brightening

The MCB Program includes multiple parallel research efforts in different areas to help achieve this, including:

• Improving the representation of aerosol-cloud interactions and marine cloud brightening in global computer models used to understand how these aerosol effects impact climate
• Studying how the climate is altered by changes in cloud brightness and cloud amount in different regions of the globe
• Using observations of real-world phenomena — such as ship emissions — that are already causing marine cloud brightening to better quantify aerosol-cloud interactions
• Conducting detailed simulations of aerosol-cloud interactions and testing these simulations against observations
• Exploring leading-edge analytical approaches, such as machine learning, to study the potential efficacy and effects of different marine cloud brightening approaches
• Conducting small-scale field studies of the interactions between aerosols and clouds, using the controlled addition of sea salt aerosols to the clouds, in order to test current understanding of the processes driving these interactions
• Developing a new cloud-aerosol research instrument for use in small-scale field studies.  This new research instrument generates controlled volumes and sizes of tiny, sub-micrometer seawater particles in sufficient numbers to increase the local brightness of low clouds in a marine environment

Our approach

In addition to advancing its scientific goals, the MCB Program’s intent is to serve as an exemplary model for open, public-interest research and field studies of clouds and aerosols, and as a resource for scientists, regulators, stakeholders and the public for understanding and engaging with cloud-aerosol and marine cloud brightening research. Appreciating the importance of engagement with international, climate-vulnerable, youth and historically underserved partners, the program supports and fosters diverse and inclusive engagement and input.

The MCB Program’s open science, governance and stakeholder engagement efforts include:

• Open datasets and peer-reviewed publications
• Collaboration and engagement with US federal agencies and US and international scientific assessment processes
• International scientific collaborators
• Scientific and environmental expert review of field studies
• Engagement with Global South and Indigenous Peoples on field science
• Youth partners and forward development of STEM education programs
• Provision of a facility for scientific research, engagement and learning

Read more about our governance, engagement and the CAARE facility here .

The MCB Program is led by atmospheric scientists Robert Wood and Sarah Doherty  at the University of Washington, and is comprised of over 35 interdisciplinary experts from the UW, SRI International (formerly the Palo Alto Research Center) and SilverLining . The Program also collaborates with researchers at a range of other institutions, including the Pacific Northwest National Laboratory , University of Victoria (Canada), the Desert Research Institute , and the University of Exeter (UK).

The University of Washington’s Marine Cloud Brightening Program is funded by SilverLining’s Safe Climate Research Initiative and the generous support of a growing consortium of individual and foundation donors.

Read more about our team, partners and funders here .

• Governance, engagement and the CAARE facility
• Our team, partners and funders
• Studies of cloud-aerosol interactions
• Small-scale field studies
• Generating aerosols for cloud-aerosol research
• Publications

AI Index Report

Welcome to the seventh edition of the AI Index report. The 2024 Index is our most comprehensive to date and arrives at an important moment when AI’s influence on society has never been more pronounced. This year, we have broadened our scope to more extensively cover essential trends such as technical advancements in AI, public perceptions of the technology, and the geopolitical dynamics surrounding its development. Featuring more original data than ever before, this edition introduces new estimates on AI training costs, detailed analyses of the responsible AI landscape, and an entirely new chapter dedicated to AI’s impact on science and medicine.

Read the 2024 AI Index Report

The AI Index report tracks, collates, distills, and visualizes data related to artificial intelligence (AI). Our mission is to provide unbiased, rigorously vetted, broadly sourced data in order for policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI.

The AI Index is recognized globally as one of the most credible and authoritative sources for data and insights on artificial intelligence. Previous editions have been cited in major newspapers, including the The New York Times, Bloomberg, and The Guardian, have amassed hundreds of academic citations, and been referenced by high-level policymakers in the United States, the United Kingdom, and the European Union, among other places. This year’s edition surpasses all previous ones in size, scale, and scope, reflecting the growing significance that AI is coming to hold in all of our lives.

Steering Committee Co-Directors

Ray Perrault

Steering committee members.

Erik Brynjolfsson

John Etchemendy

Katrina Ligett

Terah Lyons

James Manyika

Juan Carlos Niebles

Vanessa Parli

Yoav Shoham

Russell Wald

Staff members.

Loredana Fattorini

Nestor Maslej

Letter from the co-directors.

A decade ago, the best AI systems in the world were unable to classify objects in images at a human level. AI struggled with language comprehension and could not solve math problems. Today, AI systems routinely exceed human performance on standard benchmarks.

Progress accelerated in 2023. New state-of-the-art systems like GPT-4, Gemini, and Claude 3 are impressively multimodal: They can generate fluent text in dozens of languages, process audio, and even explain memes. As AI has improved, it has increasingly forced its way into our lives. Companies are racing to build AI-based products, and AI is increasingly being used by the general public. But current AI technology still has significant problems. It cannot reliably deal with facts, perform complex reasoning, or explain its conclusions.

AI faces two interrelated futures. First, technology continues to improve and is increasingly used, having major consequences for productivity and employment. It can be put to both good and bad uses. In the second future, the adoption of AI is constrained by the limitations of the technology. Regardless of which future unfolds, governments are increasingly concerned. They are stepping in to encourage the upside, such as funding university R&D and incentivizing private investment. Governments are also aiming to manage the potential downsides, such as impacts on employment, privacy concerns, misinformation, and intellectual property rights.

As AI rapidly evolves, the AI Index aims to help the AI community, policymakers, business leaders, journalists, and the general public navigate this complex landscape. It provides ongoing, objective snapshots tracking several key areas: technical progress in AI capabilities, the community and investments driving AI development and deployment, public opinion on current and potential future impacts, and policy measures taken to stimulate AI innovation while managing its risks and challenges. By comprehensively monitoring the AI ecosystem, the Index serves as an important resource for understanding this transformative technological force.

On the technical front, this year’s AI Index reports that the number of new large language models released worldwide in 2023 doubled over the previous year. Two-thirds were open-source, but the highest-performing models came from industry players with closed systems. Gemini Ultra became the first LLM to reach human-level performance on the Massive Multitask Language Understanding (MMLU) benchmark; performance on the benchmark has improved by 15 percentage points since last year. Additionally, GPT-4 achieved an impressive 0.97 mean win rate score on the comprehensive Holistic Evaluation of Language Models (HELM) benchmark, which includes MMLU among other evaluations.

Although global private investment in AI decreased for the second consecutive year, investment in generative AI skyrocketed. More Fortune 500 earnings calls mentioned AI than ever before, and new studies show that AI tangibly boosts worker productivity. On the policymaking front, global mentions of AI in legislative proceedings have never been higher. U.S. regulators passed more AI-related regulations in 2023 than ever before. Still, many expressed concerns about AI’s ability to generate deepfakes and impact elections. The public became more aware of AI, and studies suggest that they responded with nervousness.

Ray Perrault Co-director, AI Index

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New microplastics research hub aims to unravel health impact in changing climate

Rit professor christy tyler is a co-director of the center supported by a $7.3 million grant.

Vera Kuttelvaserova/stock.adobe.com

The Lake Ontario Center for Microplastics and Human Health in a Changing Environment will study the lifecycle of microplastics through the Great Lakes freshwater ecosystem. RIT professor Christy Tyler is co-director of the new research center supported by a $7.3 million grant.

A new Rochester-based research center will study the lifecycle of microplastics, including its origin as plastic waste, distribution, and movement in the Great Lakes freshwater ecosystem. The research will also focus on how climate change could intensify the environmental and health threats posed by microplastics.

The Lake Ontario Center for Microplastics and Human Health in a Changing Environment is a collaboration between Rochester Institute of Technology and the University of Rochester, and supported by a $7.3 million grant from the National Institute of Environmental Health Sciences (NIEHS) and the National Science Foundation (NSF) under the federal Oceans and Human Health program.

“This funding gives us the opportunity to bring together environmental and health sciences researchers to tackle a truly global crisis”, said Christy Tyler , professor in the Thomas H. Gosnell School of Life Sciences at RIT and co-director of the center with Katrina Korfmacher, a professor of Environmental Medicine at the University of Rochester Medical Center (URMC). “We plan to combine research on the quantity and characteristics of plastic in the places where people are most likely to encounter it, with research on how these particles impact our health. And as a result, we’ll be able to come up with a more holistic understanding of the potential harm of plastic pollution, and how we can develop targeted strategies to minimize it.”

Microplastics, particles less than 5 mm in size, are produced from plastic waste, which over time is broken down into microscopic fragments that move easily through the food chain. Common sources of plastic pollution include food wrappers, plastic bottles, plastic bottle caps, plastic bags, plastic straws, cigarette butts, tire-wear particles, and synthetic clothing. Plastic waste enters the environment via urban stormwater and agricultural runoff, and wastewater. Microplastics are ubiquitous, frequently difficult to detect and mitigate, and research has found the particles in human blood, heart, liver, and lung tissue, placenta, and breast milk. However, little is known about their long-term impact on human health.

Christy Tyler conducts research on microplastics in Lake Ontario. She is a co-director of the newly announced Lake Ontario Center for Microplastics and Human Health in a Changing Environment.

The Great Lakes hold more than 20 percent of global surface freshwater and are a source of drinking water, irrigation, fisheries, and recreation for more than 30 million people. While progress has been made in recent decades to improve the environmental health of the lakes, these gains are threatened by rising plastic pollution.

The new center will undertake research projects that aim to understand how environmental changes may affect the movement and characteristics of microplastics in Lake Ontario, how microplastics interact with other contaminants, and the impact on inflammation and immune response in model biological systems. The goal is to develop and promote solutions that inform future research, community actions, and policy changes that will lessen the health effects associated with microplastics.

One project builds on several years of collaborative work at RIT to understanding the input, transport, and ecological risk of plastic pollution in the Lake Ontario basin. The interdisciplinary team, which will be led by Tyler, and includes Matthew Hoffman , professor in the School of Mathematics and Statistics ;  Nathan Eddingsaas , associate professor in the School of Chemistry and Materials Science ;  Steven Day , professor and head of the Department of Biomedical Engineering ; and André Hudson , professor and dean, College of Science . They will examine how climate-related factors, namely warmer weather and more severe storms, will increase the delivery of post-consumer plastic to Lake Ontario.

Tyler, Hoffman, and a group of other RIT scientists have been working with National Oceanic and Atmospheric Administration funding to lead interdisciplinary projects examining plastic waste entering the Great Lakes, and how to prevent and remove it. RIT’s collaborations with the Rochester Museum and Science Center, Seneca Park Zoo, Monroe County, the city of Rochester, and other local institutions continue to provide a joint effort in combating environmental concerns.

A project by the University of Rochester will employ nanomembrane technologies to identify ultrafine microplastics in the water and air that can be more easily ingested into blood and tissue. Another will use frogs as models to study how waterborne microplastics enter, move about, and accumulate in the body at different water temperatures anticipated due to global warming. All research projects will be supported by a materials core led by University of Rochester with participation by Iris Rivero , a professor of industrial and systems engineering at RIT. The center will also engage with community partners through involving residents in efforts to monitor debris flows, and developing, evaluating, and disseminating outreach materials for audiences including youth, educators, community groups, and policy makers in both urban and rural settings.

“This partnership between universities shows how local researchers can work together to address questions of global significance,” said Ryne Raffaelle , vice president for Research at RIT. “How microplastics, combined with climate change, impact the ways in which we live and overall human health is something we need to investigate. This new center will be key to understanding, and hopefully mitigating, the convolution of these environmental impacts and their potential deleterious effects.”

Funding for the center was provided by NIEHS award number P01 ES035526 and NSF award number OCE-2418255.

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New Research Aims to Curb Illegal Sand Mining with Data-Driven Mapping Tools

You may have heard of deforestation and/or water extraction, but have you heard of sand mining? Described as “one of the greatest sustainability challenges in the 21st century” by the United Nations Environment Programme, sand mining refers to the often illegal extraction of construction-grade sand from rivers and beaches to create concrete, asphalt, and glass. In recent years, urbanization and economic growth have led to the demand for sand to skyrocket, resulting in environmental and social crises in river basins across the world.

A group of scholars from the School of Information are tackling this issue with the help of a grant from the Mozilla Technology Foundation (MTF) and collaborators from India. Ph.D. students Suraj Nair and Ando Shah, alongside Professor Joshua Blumenstock, are spearheading the creation of  Sand Mining Watch , a set of open-source tools to enable the production of high-resolution maps of sand-mining activity around the world. 

“By combining deep learning methods and freely available satellite imagery, we hope to automate the process of detecting sand mining activity at scale,” said Nair and Ando (who prefers to go by his first name).

“We both saw a large gap in the academic literature as well as a lack of practical ways to monitor this huge problem…We decided to use our experience with using computational tools for social and environmental monitoring to tackle this problem.” — Ando Shah and Suraj Nair

“We both saw a large gap in the academic literature as well as a lack of practical ways to monitor this huge problem…We decided to use our experience with using computational tools for social and environmental monitoring to tackle this problem.”

For now, the team is setting its sights on India, a country with fertile lands and large sediment loads. Both Nair and Ando grew up in the country and witnessed the pervasiveness of sand mining throughout their time there, especially in rural areas. Their familiarity with the culture and geography made India the perfect place to pilot this project.

“The problem of sand mining is particularly acute in India where a very powerful sand mafia has emerged to control this important resource,” Ando explained. “India also has the largest construction industry in the world with a very aggressive infrastructure development program, all of which needs copious amounts of sand for building bridges, roads, dams, high rises, hospitals and almost every other kind of infrastructure.”

They partnered with the  Veditum Foundation , a non-profit research, media, and action-oriented organization based in India, to pilot and evaluate the performance of their deep learning models in the region. They hope these models will be able to detect sand mining activity in river basins and catalyze policy action, improve the monitoring and regulation of illegal mining activity, and help everyday people better understand the socio-economic and environmental impacts of sand mining.

The team is supported by the Mozilla Technology Foundation’s  AI for Environmental Justice program , which provided the group with $50,000 and one year of mentorship. 

“We are very excited to be included in the Mozilla Technology Foundation’s 2024 cohort of awardees! It’s a great opportunity to interact and learn from researchers and practitioners who are building open-source AI tools to address some of the pressing environmental challenges facing the planet today,” Nair noted. “The MTF grant has allowed us to conduct fieldwork in India which has been crucial to this work, as well as acquire additional computers and help make the project sustainable.”  

“For the research community, this project helps illustrate how AI algorithms can be applied to novel sources of data in order to learn about the lasting consequences of environmental degradation.” — Joshua Blumenstock

Professor Blumenstock added, “I think this project has the potential to impact both policy and research. The team is working closely with local Indian organizations trying to put a stop to illegal sand mining, and this work can help front line organizations more quickly and efficiently identify areas being mined. For the research community, this project helps illustrate how AI algorithms can be applied to novel sources of data in order to learn about the lasting consequences of environmental degradation.”

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New Group Joins the Political Fight Over Disinformation Online

The group intends to fight what its leader, Nina Jankowicz, and others have described as a coordinated campaign by conservatives and their allies to undermine researchers who study disinformation.

By Steven Lee Myers and Jim Rutenberg

Two years ago, Nina Jankowicz briefly led an agency at the Department of Homeland Security created to fight disinformation — the establishment of which provoked a political and legal battle over the government’s role in policing lies and other harmful content online that continues to reverberate.

Now she has re-entered the fray with a new nonprofit organization intended to fight what she and others have described as a coordinated campaign by conservatives and others to undermine researchers, like her, who study the sources of disinformation.

Already a lightning rod for critics of her work on the subject, Ms. Jankowicz inaugurated the organization with a letter accusing three Republican committee chairmen in the House of Representatives of abusing their subpoena powers to silence think tanks and universities that expose the sources of disinformation.

“These tactics echo the dark days of McCarthyism, but with a frightening 21st-century twist,” she wrote in the letter on Monday with the organization’s co-founder Carlos Álvarez-Aranyos, a public-relations consultant who in 2020 was involved in efforts to defend the integrity of the American voting system.

The inception of the group, the American Sunlight Project, reflects how divisive the issue of identifying and combating disinformation has become as the 2024 presidential election approaches. It also represents a tacit admission that the informal networks formed at major universities and research organizations to address the explosion of disinformation online have failed to mount a substantial defense against a campaign, waged largely on the right, depicting their work as part of an effort to silence conservatives.

Taking place in the courts, in conservative media and on the Republican-led House Judiciary Select Subcommittee on the Weaponization of the Federal Government, the campaign has largely succeeded in eviscerating efforts to monitor disinformation, especially around the integrity of the American election system.

Many of the nation’s most prominent researchers, facing lawsuits, subpoenas and physical threats, have pulled back.

“More and more researchers were getting swept up by this, and their institutions weren’t either allowing them to respond or responding in a way that really just was not rising to meet the moment,” Ms. Jankowicz said in an interview. “And the problem with that, obviously, is that if we don’t push back on these campaigns, then that’s the prevailing narrative.”

That narrative is prevailing at a time when social media companies have abandoned or cut back efforts to enforce their own policies against certain types of content.

Many experts have warned that the problem of false or misleading content is only going to increase with the advent of artificial intelligence.

“Disinformation will remain an issue as long as the strategic gains of engaging in it, promoting it and profiting from it outweigh consequences for spreading it,” Common Cause, the nonpartisan public interest group, wrote in a report published last week that warned of a new wave of disinformation around this year’s vote.

Ms. Jankowicz said her group would run advertisements about the broad threats and effects of disinformation and produce investigative reports on the backgrounds and financing of groups conducting disinformation campaigns — including those targeting the researchers.

She has joined with two veteran political strategists: Mr. Álvarez-Aranyos, formerly a communications strategist for Protect Democracy, a nonpartisan group that seeks to counter domestic authoritarian threats, and Eddie Vale, formerly of American Bridge, a liberal group devoted to gathering opposition research into Republicans.

The organization’s advisory board includes Katie Harbath, a former Facebook executive who was previously a top digital strategist for Senate Republicans; Ineke Mushovic, a founder of the Movement Advancement Project , a think tank that tracks threats to democracy and gay, lesbian and transgender issues; and Benjamin Wittes, a national security legal expert at the Brookings Institution and editor in chief of Lawfare .

“We need to be a little bit more aggressive about how we think about defending the research community,” Mr. Wittes said in an interview, portraying the attacks against it as part of “a coordinated assault on those who have sought to counter disinformation and election interference.”

In the letter to congressional Republicans, Ms. Jankowicz noted the appearance of a fake robocall in President Biden’s voice discouraging voters in New Hampshire from voting in the state’s primary and artificially generated images of former President Donald J. Trump with Black supporters, as well as renewed efforts by China and Russia to spread disinformation to American audiences.

The American Sunlight Project has been established as a nonprofit under the section of the Internal Revenue Code that allows it greater leeway to lobby than tax-exempt charities known as 501(c)(3)s. It also does not have to disclose its donors, which Ms. Jankowicz declined to do, though she said the project had initial commitments of $1 million in donations.

The budget pales in comparison with those behind the counteroffensive like America First Legal, the Trump-aligned group that, with a war chest in the tens of millions of dollars, has sued researchers at Stanford and the University of Washington over their collaboration with government officials to combat misinformation about voting and Covid-19.

The Supreme Court is expected to rule soon in a federal lawsuit filed by the attorneys general of Missouri and Louisiana accusing government agencies of using the researchers as proxies to pressure social media platforms to take down or restrict the reach of accounts.

The idea for the American Sunlight Project grew out of Ms. Jankowicz’s experience in 2022 when she was appointed executive director of a newly created Disinformation Governance Board at the Department of Homeland Security.

From the instant the board became public, it faced fierce criticism portraying it as an Orwellian Ministry of Truth that would censor dissenting voices in violation of the First Amendment, though in reality it had only an advisory role and no enforcement authority.

Ms. Jankowicz, an expert on Russian disinformation who once served as an adviser to Ukraine’s Ministry of Foreign Affairs, stepped down shortly after her appointment. Even then, she faced such a torrent of personal threats online that she hired a security consultant. The board was suspended and then, after a short review, abolished.

“I think we’re existing in an information environment where it is very easy to weaponize information and to make it seem sinister,” Mr. Álvarez-Aranyos said. “And I think we’re looking for transparency. I mean, this is sunlight in the very literal sense.”

Ms. Jankowicz said that she was aware that her involvement with the new group would draw out her critics, but that she was well positioned to lead it because she had already “gone through the worst of it.”

Steven Lee Myers covers misinformation and disinformation from San Francisco. Since joining The Times in 1989, he has reported from around the world, including Moscow, Baghdad, Beijing and Seoul. More about Steven Lee Myers

Jim Rutenberg is a writer at large for The Times and The New York Times Magazine and writes most often about media and politics. More about Jim Rutenberg

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8 facts about Black Lives Matter

In the 10 years since the #BlackLivesMatter hashtag was first used on social media, it has appeared in more than 44 million tweets, according to  a recent Pew Research Center report . On a typical (median) day, #BlackLivesMatter appears in about 3,000 tweets as users discuss topics such as racism, violence and the criminal justice system.

Use of the hashtag has often surged around specific acts of violence against Black Americans. The hashtag first appeared in July 2013, after George Zimmerman was acquitted in the 2012 shooting death of 17-year-old Trayvon Martin in Florida. Its use peaked at over 1.2 million tweets per day after Minneapolis police officer Derek Chauvin murdered George Floyd in May 2020.

As we mark 10 years since the hashtag originated, here are eight facts about the Black Lives Matter movement.

Pew Research Center sought to explore the impact and reach of the Black Lives Matter movement 10 years after the #BlackLivesMatter hashtag originated on Twitter. This post includes survey findings from Center studies conducted from 2021 to 2023, as well as a Center analysis of Twitter activity from July 2013 to March 2023. Links to the methodology for each publication, including the questions asked in each survey, can be found in the text of this analysis.

About half of adults in the United States (51%) say they support the Black Lives Matter movement, according to a 2023 Center survey . This includes 22% who strongly support it and 29% who somewhat support it.

There are significant differences in opinion by race and ethnicity, political party, and age. About eight-in-ten Black Americans (81%) support the movement, compared with 63% of Asian, 61% of Hispanic and 42% of White Americans. Democrats and those who lean toward the Democratic Party are about five times as likely as Republicans and Republican leaners to support Black Lives Matter (84% vs. 17%). And whereas most adults ages 18 to 29 (64%) support the movement, 41% of those ages 65 and older do.

Support for Black Lives Matter has decreased significantly among U.S. adults since June 2020, the same Center survey shows. Two-thirds of adults strongly or somewhat supported the movement in June 2020 – shortly after Floyd was murdered – but that share fell to 56% in March 2022 and 51% in April 2023.

The decline is largely due to a smaller share of White adults supporting the movement. In June 2020, 60% of White adults said they supported Black Lives Matter, but that share fell to 50% in 2022 and 42% this year. Support among Asian and Hispanic adults has also fallen since 2020, but not as sharply as it has among White adults. In contrast, about 80% or more of Black adults have expressed support for the movement every year since 2020.

Most teenagers support the Black Lives Matter movement, according to a separate Center survey conducted in 2022 . Seven-in-ten Americans ages 13 to 17 said they strongly or somewhat support the movement.

Black and Democratic teenagers were especially likely to support the movement. Some 92% of Black teenagers said they support it, compared with 82% of Hispanic and 57% of White teenagers. (There were not enough Asian teens in the sample to allow for separate analysis.) And 94% of Democratic teens said they support Black Lives Matter – more than twice the share of Republican teens who said the same (42%).

Among U.S. adults, 7% say they have ever attended a Black Lives Matter protest, according to the 2023 Center report . Even among the demographic groups that are most likely to support Black Lives Matter, the shares of people who have attended a protest are low.

Some 15% of Black adults say they have attended a Black Lives Matter protest; they are more likely than Hispanic, Asian or White adults to say they have done so. Similarly, adults ages 18 to 29 are about twice as likely as those 30 to 49 and five times as likely as those 50 and older to have attended a Black Lives Matter protest. And Democrats are four times as likely as Republicans to have done this.

Many Black adults in the U.S. say Black Lives Matter has done the most to help Black people in recent years. About four-in-ten Black adults (39%) said this in a 2021 Center survey . That far exceeded the share of Black adults who said the same about any other entity asked about in the survey, including the NAACP, Black churches or other religious organizations, the Congressional Black Caucus and the National Urban League. (This survey did not specify whether Black Lives Matter referred to an organization or the broader movement.)

The public is divided on how effective the Black Lives Matter movement has been at bringing attention to racism against Black people in the U.S. About a third of adults (32%) say the movement has been extremely or very effective at this. Some 35% say it has been somewhat effective, while 30% say it has been not too or not at all effective, according to the 2023 Center survey .

Black and Asian adults are more likely than other racial and ethnic groups to say the movement has been extremely or very effective at bringing attention to racism in the country. Some 48% of Black adults and 46% of Asian adults say this, compared with 33% of Hispanic and 27% of White adults.

The public gives the Black Lives Matter movement lower marks on some other questions. Only 14% of U.S. adults say the movement has been extremely or very effective at increasing police accountability; 8% say it has been effective at improving the lives of Black people; and 7% say it has improved race relations.

A large majority of social media users in the U.S. (77%) say they have seen content on social media related to Black Lives Matter, but far fewer report having ever posted or shared something about this topic, according to the 2023 Center report . Some 24% of social media users say they have posted or shared content supporting Black Lives Matter, while 10% have shared content opposing it.

Black social media users are particularly likely to have posted in support of Black Lives Matter: 52% have done so, compared with 24% of Hispanic, 22% of Asian and 18% of White users. Younger users are also more likely than older users to have posted or shared something in support of Black Lives Matter, as are Democrats when compared with Republicans.

On Twitter specifically, millions of people first engaged with the #BlackLivesMatter hashtag following Floyd’s murder. Between May and September 2020, 5.8 million distinct users shared a tweet that contained the hashtag for the first time.

A majority of social media posts that use the #BlackLivesMatter hashtag are supportive, the same report finds. Between July 2013 and March 2023, about seven-in-ten publicly available tweets that used the hashtag (72%) were positive toward the movement. Another 17% were neutral and 11% were negative.

Supportive tweets commonly include words such as together , justice , change , brutality and murder , whereas negative tweets often use words such as riot , assault , criminal and violent .

• Black Americans
• Racial Bias & Discrimination

Jenn Hatfield is a writer/editor at Pew Research Center

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