dissertation main aim

• 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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• Knowledge Base
• Dissertation

What Is a Dissertation? | 5 Essential Questions to Get Started

Published on 26 March 2020 by Jack Caulfield . Revised on 5 May 2022.

A dissertation is a large research project undertaken at the end of a degree. It involves in-depth consideration of a problem or question chosen by the student. It is usually the largest (and final) piece of written work produced during a degree.

The length and structure of a dissertation vary widely depending on the level and field of study. However, there are some key questions that can help you understand the requirements and get started on your dissertation project.

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Table of contents

When and why do you have to write a dissertation, who will supervise your dissertation, what type of research will you do, how should your dissertation be structured, what formatting and referencing rules do you have to follow, frequently asked questions about dissertations.

A dissertation, sometimes called a thesis, comes at the end of an undergraduate or postgraduate degree. It is a larger project than the other essays you’ve written, requiring a higher word count and a greater depth of research.

You’ll generally work on your dissertation during the final year of your degree, over a longer period than you would take for a standard essay . For example, the dissertation might be your main focus for the last six months of your degree.

Why is the dissertation important?

The dissertation is a test of your capacity for independent research. You are given a lot of autonomy in writing your dissertation: you come up with your own ideas, conduct your own research, and write and structure the text by yourself.

This means that it is an important preparation for your future, whether you continue in academia or not: it teaches you to manage your own time, generate original ideas, and work independently.

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During the planning and writing of your dissertation, you’ll work with a supervisor from your department. The supervisor’s job is to give you feedback and advice throughout the process.

The dissertation supervisor is often assigned by the department, but you might be allowed to indicate preferences or approach potential supervisors. If so, try to pick someone who is familiar with your chosen topic, whom you get along with on a personal level, and whose feedback you’ve found useful in the past.

How will your supervisor help you?

Your supervisor is there to guide you through the dissertation project, but you’re still working independently. They can give feedback on your ideas, but not come up with ideas for you.

You may need to take the initiative to request an initial meeting with your supervisor. Then you can plan out your future meetings and set reasonable deadlines for things like completion of data collection, a structure outline, a first chapter, a first draft, and so on.

Make sure to prepare in advance for your meetings. Formulate your ideas as fully as you can, and determine where exactly you’re having difficulties so you can ask your supervisor for specific advice.

Your approach to your dissertation will vary depending on your field of study. The first thing to consider is whether you will do empirical research , which involves collecting original data, or non-empirical research , which involves analysing sources.

Empirical dissertations (sciences)

An empirical dissertation focuses on collecting and analysing original data. You’ll usually write this type of dissertation if you are studying a subject in the sciences or social sciences.

• What are airline workers’ attitudes towards the challenges posed for their industry by climate change?
• How effective is cognitive behavioural therapy in treating depression in young adults?
• What are the short-term health effects of switching from smoking cigarettes to e-cigarettes?

There are many different empirical research methods you can use to answer these questions – for example, experiments , observations, surveys , and interviews.

When doing empirical research, you need to consider things like the variables you will investigate, the reliability and validity of your measurements, and your sampling method . The aim is to produce robust, reproducible scientific knowledge.

Non-empirical dissertations (arts and humanities)

A non-empirical dissertation works with existing research or other texts, presenting original analysis, critique and argumentation, but no original data. This approach is typical of arts and humanities subjects.

• What attitudes did commentators in the British press take towards the French Revolution in 1789–1792?
• How do the themes of gender and inheritance intersect in Shakespeare’s Macbeth ?
• How did Plato’s Republic and Thomas More’s Utopia influence nineteenth century utopian socialist thought?

The first steps in this type of dissertation are to decide on your topic and begin collecting your primary and secondary sources .

Primary sources are the direct objects of your research. They give you first-hand evidence about your subject. Examples of primary sources include novels, artworks and historical documents.

Secondary sources provide information that informs your analysis. They describe, interpret, or evaluate information from primary sources. For example, you might consider previous analyses of the novel or author you are working on, or theoretical texts that you plan to apply to your primary sources.

Dissertations are divided into chapters and sections. Empirical dissertations usually follow a standard structure, while non-empirical dissertations are more flexible.

Structure of an empirical dissertation

Empirical dissertations generally include these chapters:

• Introduction : An explanation of your topic and the research question(s) you want to answer.
• Literature review : A survey and evaluation of previous research on your topic.
• Methodology : An explanation of how you collected and analysed your data.
• Results : A brief description of what you found.
• Discussion : Interpretation of what these results reveal.
• Conclusion : Answers to your research question(s) and summary of what your findings contribute to knowledge in your field.

Sometimes the order or naming of chapters might be slightly different, but all of the above information must be included in order to produce thorough, valid scientific research.

Other dissertation structures

If your dissertation doesn’t involve data collection, your structure is more flexible. You can think of it like an extended essay – the text should be logically organised in a way that serves your argument:

• Introduction: An explanation of your topic and the question(s) you want to answer.
• Main body: The development of your analysis, usually divided into 2–4 chapters.
• Conclusion: Answers to your research question(s) and summary of what your analysis contributes to knowledge in your field.

The chapters of the main body can be organised around different themes, time periods, or texts. Below you can see some example structures for dissertations in different subjects.

• Political philosophy

This example, on the topic of the British press’s coverage of the French Revolution, shows how you might structure each chapter around a specific theme.

This example, on the topic of Plato’s and More’s influences on utopian socialist thought, shows a different approach to dividing the chapters by theme.

This example, a master’s dissertation on the topic of how writers respond to persecution, shows how you can also use section headings within each chapter. Each of the three chapters deals with a specific text, while the sections are organised thematically.

Like other academic texts, it’s important that your dissertation follows the formatting guidelines set out by your university. You can lose marks unnecessarily over mistakes, so it’s worth taking the time to get all these elements right.

Formatting guidelines concern things like:

• line spacing
• page numbers
• punctuation
• title pages
• presentation of tables and figures

If you’re unsure about the formatting requirements, check with your supervisor or department. You can lose marks unnecessarily over mistakes, so it’s worth taking the time to get all these elements right.

How will you reference your sources?

Referencing means properly listing the sources you cite and refer to in your dissertation, so that the reader can find them. This avoids plagiarism by acknowledging where you’ve used the work of others.

Keep track of everything you read as you prepare your dissertation. The key information to note down for a reference is:

• The publication date
• Page numbers for the parts you refer to (especially when using direct quotes)

Different referencing styles each have their own specific rules for how to reference. The most commonly used styles in UK universities are listed below.

You can use the free APA Reference Generator to automatically create and store your references.

APA Reference Generator

The words ‘ dissertation ’ and ‘thesis’ both refer to a large written research project undertaken to complete a degree, but they are used differently depending on the country:

• In the UK, you write a dissertation at the end of a bachelor’s or master’s degree, and you write a thesis to complete a PhD.
• In the US, it’s the other way around: you may write a thesis at the end of a bachelor’s or master’s degree, and you write a dissertation to complete a PhD.

The main difference is in terms of scale – a dissertation is usually much longer than the other essays you complete during your degree.

Another key difference is that you are given much more independence when working on a dissertation. You choose your own dissertation topic , and you have to conduct the research and write the dissertation yourself (with some assistance from your supervisor).

Dissertation word counts vary widely across different fields, institutions, and levels of education:

• An undergraduate dissertation is typically 8,000–15,000 words
• A master’s dissertation is typically 12,000–50,000 words
• A PhD thesis is typically book-length: 70,000–100,000 words

However, none of these are strict guidelines – your word count may be lower or higher than the numbers stated here. Always check the guidelines provided by your university to determine how long your own dissertation should be.

At the bachelor’s and master’s levels, the dissertation is usually the main focus of your final year. You might work on it (alongside other classes) for the entirety of the final year, or for the last six months. This includes formulating an idea, doing the research, and writing up.

A PhD thesis takes a longer time, as the thesis is the main focus of the degree. A PhD thesis might be being formulated and worked on for the whole four years of the degree program. The writing process alone can take around 18 months.

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Research Voyage

Research Tips and Infromation

How to Write Aims and Objectives for your Dissertation or Thesis?

Introduction

Understanding aims and objectives, crafting aims, break it down into objectives, developing specific objectives, align with research questions, consider feasibility, review and refine, seek feedback, documenting aims and objectives.

In a PhD or Post Graduate dissertation, the aims and objectives play a crucial role in shaping the research process and ensuring focus. They provide a clear roadmap for your study and serve as the guiding principles that steer your research in the right direction.

Aims represent the broader purpose or the overarching goal of your research. They define what you want to achieve with your dissertation. For example, let’s say you’re conducting a study on renewable energy sources. Your aim could be to analyze the economic viability and environmental impact of solar energy adoption in residential areas.

Objectives, on the other hand, break down the aim into specific, measurable, and achievable targets that help you accomplish your research goal. They outline the specific steps or tasks you need to undertake to fulfill the aim. Continuing with the previous example, some objectives could be:

• Evaluate the current state of solar energy technologies and their efficiency.
• Assess the economic costs and benefits associated with the installation of solar panels in residential areas.
• Analyze the environmental impact of solar energy adoption in terms of carbon emissions reduction.
• Investigate the potential barriers to the widespread adoption of solar energy in residential communities.
• Develop recommendations for policymakers and stakeholders to promote the use of solar energy in residential areas.

These objectives, when combined, address different aspects related to the aim of analyzing the economic viability and environmental impact of solar energy adoption. Each objective guides a specific aspect of the research and contributes to answering the research questions.

By having clear aims and objectives, you establish a solid framework for your study. They help you stay focused on the main purpose of your research and prevent you from getting sidetracked or overwhelmed by tangential topics. Moreover, they provide clarity to both you and your readers, ensuring that your research remains coherent and well-structured.

In summary, clear aims and objectives are instrumental in guiding the research process of a PhD dissertation. They provide a roadmap, define the research goal, and break it down into specific targets. Through the example provided, it is evident how aims and objectives bring focus to a study on renewable energy sources and solar energy adoption in residential areas.

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Aims and objectives play a crucial role in guiding research projects. It’s important to define these terms and differentiate between them to ensure a clear focus in your work.

Aims represent the broader purpose or goal of your study. They define what you aim to achieve through your research project. Aims provide the overarching context and direction for your work, guiding the selection of topics, methodologies, and outcomes.

Example: Suppose you’re working on a PhD dissertation in computer science with a focus on natural language processing. Your aim could be: “To develop an efficient and accurate algorithm for sentiment analysis in social media data.”

In this example, the aim highlights the objective of creating an algorithm specifically for sentiment analysis in social media data, indicating the main objective of your research.

Objectives break down the aim into specific, measurable, and achievable targets that contribute to achieving the overall goal. They are more focused and concrete than aims, outlining the steps or tasks necessary to fulfill the aim. Objectives serve as the building blocks of your research, guiding the implementation and evaluation of your work.

Example: Continuing with the previous aim, let’s define some specific objectives:

• Collect and preprocess a large dataset of social media posts for sentiment analysis.
• Explore and compare existing sentiment analysis techniques to identify their limitations and strengths.
• Design and develop a novel algorithm that addresses the limitations of current approaches.
• Implement the algorithm and evaluate its performance on the collected dataset.
• Analyze the results and compare them with existing state-of-the-art sentiment analysis methods.

These objectives, when combined, address different aspects necessary to fulfill the aim of developing an efficient and accurate sentiment analysis algorithm for social media data. Each objective represents a specific task or milestone that contributes to the overall research goal.

The relationship between aims and objectives is critical in driving research. Objectives are derived from the aim and provide the means to accomplish it. They act as stepping stones, guiding the researcher towards achieving the broader aim.

In summary, aims provide the broader context and goal, while objectives break down the aim into specific tasks and milestones. Together, they ensure focus and direction in your research, guiding the selection of topics, methodologies, and outcomes. The objectives serve as the means to achieve the overall aim, highlighting the relationship between aims and objectives in driving research in the computer science domain.

Formulating the overarching aim of your research is a crucial step in defining the direction and purpose of your dissertation. The aim represents the primary goal or intention of your study, and crafting it effectively is essential for setting the foundation of your research.

Research Topic: Enhancing cybersecurity in cloud computing environments.

In this example, the aim focuses on improving cybersecurity in the context of cloud computing. The aim should be formulated in a concise and focused manner that aligns with the research topic. Here’s an example of how the aim could be crafted effectively:

Aim: Develop an efficient and robust security framework for ensuring data confidentiality, integrity, and availability in cloud computing environments.

The above aim encapsulates the overall goal of the research, which is to develop a security framework for enhancing cybersecurity in cloud computing. It clearly states the intention to address key aspects such as data confidentiality, integrity, and availability. The aim is concise, specific, and directly aligned with the research topic.

The significance of a well-defined aim cannot be overstated. It serves as a guiding beacon throughout your research journey, providing a clear direction and purpose. A well-crafted aim helps you stay focused and ensures that your efforts are aligned with the research’s core objectives. It also helps you communicate the purpose of your study to others, including your advisor, peers, and potential readers of your dissertation.

Additionally, an effective aim sets the stage for the subsequent development of specific objectives and research questions. It serves as a foundation upon which you can break down the aim into smaller, manageable objectives that contribute to achieving the overall research goal. Each objective should align with the aim and work together harmoniously to address the research questions and gaps in the field.

Moreover, a concise and aligned aim allows readers to quickly grasp the essence of your research. It provides them with a clear understanding of the research’s scope and purpose. By stating the aim concisely and aligning it with the research topic, you demonstrate your ability to articulate the core objective of your study in a succinct manner.

In summary, crafting effective aims involves formulating the overarching goal or intention of your research in a concise and focused manner. A well-defined aim sets the direction for your dissertation, guiding your efforts and ensuring alignment with the research topic. It serves as a foundation for the development of specific objectives and research questions. By presenting a clear and aligned aim, you convey the purpose of your study to others and demonstrate your ability to articulate the core objective of your research.

After defining the aim of your research, it’s important to break it down into smaller, manageable objectives. These objectives should address key research questions or subtopics that are necessary to achieve the overall aim. Additionally, objectives should be specific, measurable, and utilize action verbs to describe the intended actions or achievements.

Example: Suppose the aim of your research is to develop a recommendation system for an e-commerce platform. Here are some examples of specific objectives:

• Action Verbs: Analyze, Identify
• Description: Gather and analyze user preferences and historical data from the e-commerce platform to identify patterns in user behavior and item preferences.
• Action Verbs: Design, Implement
• Description: Develop and implement collaborative filtering algorithms, such as user-based or item-based methods, to generate personalized recommendations based on user similarities or item similarities.
• Action Verbs: Incorporate
• Description: Integrate machine learning techniques, such as matrix factorization or deep learning models, into the recommendation system to improve the accuracy and personalization of the recommendations.
• Action Verbs: Evaluate
• Description: Conduct experiments and evaluate the performance of the recommendation system using appropriate evaluation metrics, such as precision, recall, or mean average precision, to assess the effectiveness and efficiency of the system.
• Action Verbs: Optimize
• Description: Identify and implement optimization techniques, such as parallel computing or distributed systems, to enhance the scalability and efficiency of the recommendation algorithm, allowing it to handle large-scale datasets and real-time recommendations.

By breaking down the aim into these specific objectives, you address key components of developing a recommendation system, such as data analysis, algorithm design, evaluation, and optimization. Each objective represents a distinct step that contributes to achieving the overall aim.

Importantly, these objectives are specific and measurable, allowing you to determine whether you have successfully achieved them. For instance, you can measure the accuracy of the recommendation system, evaluate its performance against baseline models, or assess its scalability in terms of handling large datasets.

In summary, when conducting research, breaking down the aim into specific objectives helps in managing the workload and providing a clear roadmap for your research. These objectives should address key research questions or subtopics, be specific and measurable, and use action verbs to describe the intended actions or achievements. By following this approach, you can ensure a systematic and focused research process.

To develop specific objectives for your research, you need to break down the overarching aim into smaller, measurable objectives. These objectives should be clear, specific, and actionable, providing a roadmap for your research and guiding the entire research process.

Aim: Develop a machine learning-based system for automated sentiment analysis in social media data.

Objective 1: Conduct a comprehensive literature review on existing sentiment analysis techniques and methodologies.

• Breakdown: This objective focuses on reviewing the literature in the field of sentiment analysis, specifically examining the various techniques and methodologies that have been developed and applied. It involves gathering and analyzing research papers, books, and other relevant sources to gain a comprehensive understanding of the existing knowledge in sentiment analysis.

Objective 2: Collect a large dataset of social media posts for training and evaluation.

• Breakdown: This objective entails the collection of a substantial amount of social media data that will be used as input for training and evaluating the machine learning model. It involves designing data collection mechanisms, such as web scraping or utilizing available APIs, to gather a diverse set of social media posts from platforms like Twitter or Facebook.

Objective 3: Design and implement a machine learning algorithm capable of accurately detecting sentiment polarity in social media text.

• Breakdown: This objective focuses on the development of a machine learning algorithm tailored for sentiment analysis in social media text. It involves designing and implementing the necessary algorithms, selecting appropriate feature representations, and training a model to accurately classify sentiment polarity (positive, negative, or neutral) of social media posts.

Objective 4: Evaluate the performance of the developed sentiment analysis system against benchmark datasets and compare it with existing state-of-the-art approaches.

• Breakdown: This objective involves assessing the performance of the developed sentiment analysis system by evaluating it against established benchmark datasets. It requires selecting appropriate evaluation metrics and comparing the system’s performance with existing state-of-the-art approaches in sentiment analysis, such as accuracy, precision, recall, or F1 score.

The importance of clear, specific objectives cannot be overstated. These objectives provide a clear roadmap and direction for your research, guiding your efforts and ensuring that you stay on track. They help you structure your research activities, allocate resources effectively, and measure progress along the way.

Using action verbs to articulate objectives effectively is another crucial aspect. Action verbs convey specific actions or achievements that need to be accomplished. They provide clarity and precision, leaving no room for ambiguity. For example:

By using action verbs, you explicitly state what needs to be done or achieved in each objective, making it easier to track progress and assess the completion of objectives.

In summary, developing specific objectives involves breaking down the overarching aim into smaller, measurable objectives. Clear and specific objectives provide a roadmap for your research and guide the entire research process. By using action verbs, you articulate objectives effectively, leaving no room for ambiguity. These objectives help structure your research activities, allocate resources effectively, and measure progress, ultimately leading to the successful completion of your research.

When formulating objectives for your research, it is essential to ensure that they align with the research questions you have formulated. Each objective should contribute to addressing or answering a specific research question, creating a cohesive and focused research framework.

Example: Suppose your research in computer science focuses on developing an automated system for detecting and preventing cybersecurity threats. Here are examples of objectives aligned with research questions:

Research Question: How can machine learning algorithms be utilized to detect and mitigate cybersecurity threats effectively?

Objective 1: Evaluate and compare different machine learning algorithms for cybersecurity threat detection.

• Description: Explore and assess various machine learning algorithms, such as decision trees, random forests, or neural networks, to identify the most suitable approach for detecting cybersecurity threats accurately and efficiently.

Objective 2: Develop a dataset representative of diverse cybersecurity threats.

• Description: Create a comprehensive dataset containing various types of cybersecurity threats, including malware, phishing attacks, and network intrusions, to train and evaluate the machine learning models effectively.

Research Question: What are the key challenges and vulnerabilities in existing cybersecurity systems that need to be addressed?

Objective 3: Conduct a systematic analysis of existing cybersecurity systems and identify vulnerabilities.

• Description: Analyze and evaluate existing cybersecurity systems, such as intrusion detection systems or antivirus software, to identify vulnerabilities, weaknesses, and potential areas of improvement that can inform the development of a more robust automated system.

Objective 4: Propose novel techniques to enhance the resilience of the cybersecurity system.

• Description: Develop innovative approaches, such as anomaly detection algorithms or behavior-based analysis techniques, to enhance the resilience of the automated cybersecurity system and address the identified vulnerabilities.

By aligning the objectives with the research questions, you ensure that each objective contributes to addressing a specific aspect of your research. For example, Objective 1 directly addresses the research question regarding the utilization of machine learning algorithms for cybersecurity threat detection. Objective 3 focuses on analyzing existing systems to identify vulnerabilities, which is in line with the question about challenges and vulnerabilities in existing cybersecurity systems.

The alignment between research questions and objectives helps maintain a clear focus on the research objectives and ensures that your efforts are directed towards addressing the research questions. It also enhances the coherence of your research, as each objective becomes a stepping stone towards answering the research questions and achieving the overall aim of your study.

In summary, aligning objectives with research questions is crucial in research. It ensures that each objective contributes to answering or addressing a specific research question, creating a logical and cohesive framework for your study. By establishing this alignment, you can maintain a clear focus on the research objectives and make meaningful contributions to the field.

When setting objectives for your research, it is important to consider their feasibility. Feasibility refers to the realistic achievability of your objectives within the scope of your PhD research, taking into account available resources, time constraints, and other practical limitations.

Example: Suppose your research focuses on developing a new algorithm for real-time video processing and analysis. Here are examples of objectives that consider feasibility:

Objective 1: Implement the real-time video processing algorithm on a high-performance computing cluster.

• Feasibility Considerations: Before setting this objective, assess whether you have access to a high-performance computing cluster and the necessary resources (e.g., hardware, software, computational power) to support the implementation and testing of the algorithm. If such resources are available within your research environment or institution, this objective is feasible.

Objective 2: Collect and annotate a large-scale video dataset for algorithm training and evaluation.

• Feasibility Considerations: Consider the practical aspects of collecting and annotating a large-scale video dataset. Evaluate the time, manpower, and equipment required for this task. Assess whether you have access to the necessary resources (e.g., cameras, storage, annotation tools) and the capability to manage and process such a dataset. If these resources and capabilities are available within your research context, this objective is feasible.

Objective 3: Collaborate with industry partners to obtain real-world video data for testing and validation.

• Feasibility Considerations: Evaluate the feasibility of establishing collaborations with industry partners to obtain real-world video data. Consider factors such as data sharing agreements, legal and privacy considerations, and the willingness of industry partners to provide access to their data. Assess the potential challenges and limitations that may arise during this collaboration process. If such collaborations are feasible and can be established within the constraints of your research, this objective is feasible.

By considering feasibility, you ensure that your objectives are realistically achievable within the resources, time, and other constraints of your PhD research. It helps you avoid setting objectives that are too ambitious or beyond the scope of what you can reasonably accomplish.

Feasibility assessment is crucial in ensuring the successful completion of your research project. It allows you to allocate resources effectively, manage your time, and avoid potential pitfalls or setbacks that could hinder your progress. By setting feasible objectives, you can maintain a practical and manageable research plan that is more likely to lead to meaningful outcomes within the given constraints.

In summary, considering feasibility when setting objectives in computer science research is essential. Assess the available resources, time constraints, and practical limitations to ensure that your objectives are realistically achievable within the scope of your PhD research. By doing so, you can plan and execute your research effectively, making the most of the resources at your disposal and increasing the likelihood of successful outcomes.

Once you have defined your aims and objectives for your research, it’s important to review and refine them to ensure clarity, coherence, and logical flow. This step allows you to make any necessary revisions to ensure that your aims and objectives accurately reflect the scope and purpose of your research.

Example: Suppose your research in computer science focuses on developing a mobile application for enhancing cybersecurity awareness among smartphone users. Here’s an example of reviewing and refining aims and objectives:

Aim: Develop a mobile application for enhancing cybersecurity awareness among smartphone users.

Objective 1: Conduct a comprehensive literature review on cybersecurity awareness strategies and mobile application design principles.

• Review and Refinement: Upon review, you find that the objective is clear and aligned with the aim. However, you decide to refine it to include specific aspects you intend to cover in the literature review, such as user education techniques, persuasive design elements, and existing cybersecurity awareness mobile applications.

Objective 2: Design and develop a user-friendly mobile application prototype that delivers educational content and interactive features.

• Review and Refinement: During the review, you realize that the objective lacks specificity regarding the educational content and interactive features. You refine it to explicitly mention the inclusion of topics like phishing prevention, password management, and interactive quizzes to reinforce learning.

Objective 3: Conduct usability testing and collect feedback from potential users to evaluate the effectiveness of the mobile application.

• Review and Refinement: While reviewing, you realize that the objective could benefit from additional information. You refine it to include details such as the target user group (e.g., smartphone users aged 18-35), the number of participants you plan to involve in the usability testing, and the specific metrics you will use to evaluate the effectiveness of the application.

By reviewing and refining your aims and objectives, you ensure that they accurately capture the scope and purpose of your research. It helps you identify any gaps, ambiguities, or areas that need further clarification. Through this process, you can enhance the clarity, coherence, and logical flow of your aims and objectives, making them more robust and aligned with your research goals.

Additionally, reviewing and refining your aims and objectives allows you to align them with the current state of knowledge in the field. As you conduct literature reviews and gain more insights into existing research, you may discover the need to make adjustments to your aims and objectives to reflect the most relevant and up-to-date information.

In summary, reviewing and refining aims and objectives in research is essential to ensure clarity, coherence, and logical flow. By carefully reviewing each aim and objective, you can identify areas for improvement, refine them to include specific details, and align them with the current state of knowledge in the field. This process enhances the accuracy and effectiveness of your aims and objectives, providing a strong foundation for your research.

Once you have developed your aims and objectives for your research, it is important to seek feedback from your supervisor or peers. Sharing your aims and objectives with others allows you to gather valuable insights, suggestions, and perspectives that can help refine and improve your objectives, ensuring they are appropriate and aligned with your research.

Imagine you have formulated the following objectives for your computer science research on developing an intelligent tutoring system:

Objective 1: Conduct a literature review on existing intelligent tutoring systems and their effectiveness in enhancing student learning outcomes.

Objective 2: Design and develop an adaptive learning algorithm to personalize the tutoring experience based on individual student needs.

Objective 3: Implement a user-friendly interface for the intelligent tutoring system that provides an intuitive and engaging learning environment.

Objective 4: Evaluate the effectiveness of the developed intelligent tutoring system through a series of user studies and compare it with traditional tutoring methods.

At this stage, it would be beneficial to share your aims and objectives with your supervisor or peers to receive feedback. They can provide valuable insights and suggestions to help you refine and improve your objectives. For example:

• Your supervisor may suggest including a specific research question to further clarify the focus of Objective 1, such as “What are the key features and techniques used in successful intelligent tutoring systems?”
• Peers may provide feedback on the clarity and specificity of Objective 2, suggesting adding details on the specific adaptability mechanisms to be incorporated.
• Your supervisor might suggest considering the inclusion of usability testing as part of Objective 3 to ensure the interface meets the needs and preferences of the target users.
• Peers may offer suggestions on additional evaluation metrics or experimental setups to strengthen Objective 4 and provide more robust comparisons.

By seeking feedback, you open yourself up to constructive criticism and valuable perspectives that can help enhance the quality and effectiveness of your aims and objectives. Feedback from experienced researchers or knowledgeable peers can help you identify any potential gaps or weaknesses in your objectives and provide suggestions for improvement.

Remember that feedback is an iterative process, and it is important to carefully consider the suggestions provided while also critically evaluating them in the context of your research. Incorporating constructive feedback will help you refine your aims and objectives, ensuring they are robust, relevant, and aligned with your research goals.

In summary, seeking feedback on your aims and objectives is a valuable step in the process of developing your research. Sharing your objectives with your supervisor or peers allows you to gather insights, suggestions, and perspectives that can help refine and improve your objectives. Feedback helps ensure that your objectives are appropriate, clear, and aligned with your research goals, ultimately strengthening the overall quality of your research.

When writing your dissertation, it is crucial to properly document and present your aims and objectives. The placement and presentation of aims and objectives play a significant role in providing readers with a clear understanding of the research’s purpose and direction.

Placement: The aims and objectives of your research should be presented early on in your dissertation, typically within the introduction chapter. This allows readers to grasp the overall scope and intent of your research from the beginning. Placing them in the introduction helps set the context and provides a roadmap for the rest of the dissertation.

Presentation: When presenting aims and objectives, it is important to clearly distinguish between the two and articulate their role in driving the research. Here’s an example of how you can document aims and objectives:

Aims: Start by presenting the overarching aim of your research, which represents the primary goal or intention of your study. It should be a concise statement that captures the essence of your research focus.

For example:

Aim: The aim of this research is to develop a machine learning-based system for automated sentiment analysis in social media data.

Objectives: Following the aim, present a list of specific objectives that outline the key steps or milestones required to achieve the aim. Each objective should be clear, specific, and measurable. Here’s an example:

Objectives:

• Analyze existing sentiment analysis techniques and methodologies in the literature to identify their limitations and challenges.
• Collect and preprocess a large dataset of social media posts to serve as the training and evaluation data for the sentiment analysis system.
• Design and implement a machine learning algorithm capable of accurately detecting sentiment polarity in social media text.
• Evaluate the performance of the developed sentiment analysis system against existing state-of-the-art approaches, using appropriate evaluation metrics.
• Optimize the system for scalability and efficiency, allowing it to handle large volumes of real-time social media data.

By clearly documenting the aims and objectives in your dissertation, you provide readers with a clear understanding of the purpose and direction of your research. This enables them to follow your thought process and evaluate the relevance and significance of your study. Aims and objectives serve as guideposts that help readers navigate through your dissertation and understand the specific research questions you seek to address.

Moreover, the well-documented aims and objectives help you maintain focus throughout your research journey and provide a framework for organizing your dissertation. They establish the foundation upon which your methodology, analysis, and conclusions are built.

In summary, when documenting aims and objectives in a dissertation, it is important to place them in the introduction chapter and clearly present their role in guiding the research. Aims and objectives should be distinct, with the aim of capturing the overarching goal and the objectives outlining the specific steps or milestones to achieve it. By effectively documenting aims and objectives, you provide readers with a clear understanding of the research’s purpose and direction, facilitating their engagement with your work.

Crafting clear and well-defined aims and objectives is a critical aspect of writing a PhD or Post Graduate dissertation. These aims and objectives provide a solid foundation for your research, guiding your efforts and ensuring a focused and coherent study. Through this discussion, we have explored the importance of aims and objectives in a PhD dissertation and how they contribute to the research process.

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How to Write a Thesis or Dissertation Introduction

Published on September 7, 2022 by Tegan George and Shona McCombes. Revised on November 21, 2023.

The introduction is the first section of your thesis or dissertation , appearing right after the table of contents . Your introduction draws your reader in, setting the stage for your research with a clear focus, purpose, and direction on a relevant topic .

Your introduction should include:

• Your topic, in context: what does your reader need to know to understand your thesis dissertation?
• Your focus and scope: what specific aspect of the topic will you address?
• The relevance of your research: how does your work fit into existing studies on your topic?
• Your questions and objectives: what does your research aim to find out, and how?
• An overview of your structure: what does each section contribute to the overall aim?

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Table of contents

How to start your introduction, topic and context, focus and scope, relevance and importance, questions and objectives, overview of the structure, thesis introduction example, introduction checklist, other interesting articles, frequently asked questions about introductions.

Although your introduction kicks off your dissertation, it doesn’t have to be the first thing you write — in fact, it’s often one of the very last parts to be completed (just before your abstract ).

It’s a good idea to write a rough draft of your introduction as you begin your research, to help guide you. If you wrote a research proposal , consider using this as a template, as it contains many of the same elements. However, be sure to revise your introduction throughout the writing process, making sure it matches the content of your ensuing sections.

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Begin by introducing your dissertation topic and giving any necessary background information. It’s important to contextualize your research and generate interest. Aim to show why your topic is timely or important. You may want to mention a relevant news item, academic debate, or practical problem.

After a brief introduction to your general area of interest, narrow your focus and define the scope of your research.

You can narrow this down in many ways, such as by:

• Geographical area
• Time period
• Demographics or communities
• Themes or aspects of the topic

It’s essential to share your motivation for doing this research, as well as how it relates to existing work on your topic. Further, you should also mention what new insights you expect it will contribute.

Start by giving a brief overview of the current state of research. You should definitely cite the most relevant literature, but remember that you will conduct a more in-depth survey of relevant sources in the literature review section, so there’s no need to go too in-depth in the introduction.

Depending on your field, the importance of your research might focus on its practical application (e.g., in policy or management) or on advancing scholarly understanding of the topic (e.g., by developing theories or adding new empirical data). In many cases, it will do both.

Ultimately, your introduction should explain how your thesis or dissertation:

• Helps solve a practical or theoretical problem
• Addresses a gap in the literature
• Builds on existing research
• Proposes a new understanding of your topic

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Perhaps the most important part of your introduction is your questions and objectives, as it sets up the expectations for the rest of your thesis or dissertation. How you formulate your research questions and research objectives will depend on your discipline, topic, and focus, but you should always clearly state the central aim of your research.

If your research aims to test hypotheses , you can formulate them here. Your introduction is also a good place for a conceptual framework that suggests relationships between variables .

• Conduct surveys to collect data on students’ levels of knowledge, understanding, and positive/negative perceptions of government policy.
• Determine whether attitudes to climate policy are associated with variables such as age, gender, region, and social class.
• Conduct interviews to gain qualitative insights into students’ perspectives and actions in relation to climate policy.

To help guide your reader, end your introduction with an outline  of the structure of the thesis or dissertation to follow. Share a brief summary of each chapter, clearly showing how each contributes to your central aims. However, be careful to keep this overview concise: 1-2 sentences should be enough.

I. Introduction

Human language consists of a set of vowels and consonants which are combined to form words. During the speech production process, thoughts are converted into spoken utterances to convey a message. The appropriate words and their meanings are selected in the mental lexicon (Dell & Burger, 1997). This pre-verbal message is then grammatically coded, during which a syntactic representation of the utterance is built.

Speech, language, and voice disorders affect the vocal cords, nerves, muscles, and brain structures, which result in a distorted language reception or speech production (Sataloff & Hawkshaw, 2014). The symptoms vary from adding superfluous words and taking pauses to hoarseness of the voice, depending on the type of disorder (Dodd, 2005). However, distortions of the speech may also occur as a result of a disease that seems unrelated to speech, such as multiple sclerosis or chronic obstructive pulmonary disease.

This study aims to determine which acoustic parameters are suitable for the automatic detection of exacerbations in patients suffering from chronic obstructive pulmonary disease (COPD) by investigating which aspects of speech differ between COPD patients and healthy speakers and which aspects differ between COPD patients in exacerbation and stable COPD patients.

Checklist: Introduction

I have introduced my research topic in an engaging way.

I have provided necessary context to help the reader understand my topic.

I have clearly specified the focus of my research.

I have shown the relevance and importance of the dissertation topic .

I have clearly stated the problem or question that my research addresses.

I have outlined the specific objectives of the research .

I have provided an overview of the dissertation’s structure .

You've written a strong introduction for your thesis or dissertation. Use the other checklists to continue improving your dissertation.

If you want to know more about AI for academic writing, AI tools, or research bias, make sure to check out some of our other articles with explanations and examples or go directly to our tools!

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The introduction of a research paper includes several key elements:

• A hook to catch the reader’s interest
• Relevant background on the topic
• Details of your research problem

and your problem statement

• A thesis statement or research question
• Sometimes an overview of the paper

Don’t feel that you have to write the introduction first. The introduction is often one of the last parts of the research paper you’ll write, along with the conclusion.

This is because it can be easier to introduce your paper once you’ve already written the body ; you may not have the clearest idea of your arguments until you’ve written them, and things can change during the writing process .

Research objectives describe what you intend your research project to accomplish.

They summarize the approach and purpose of the project and help to focus your research.

Your objectives should appear in the introduction of your research paper , at the end of your problem statement .

Scope of research is determined at the beginning of your research process , prior to the data collection stage. Sometimes called “scope of study,” your scope delineates what will and will not be covered in your project. It helps you focus your work and your time, ensuring that you’ll be able to achieve your goals and outcomes.

Defining a scope can be very useful in any research project, from a research proposal to a thesis or dissertation . A scope is needed for all types of research: quantitative , qualitative , and mixed methods .

To define your scope of research, consider the following:

• Budget constraints or any specifics of grant funding
• Your proposed timeline and duration
• Specifics about your population of study, your proposed sample size , and the research methodology you’ll pursue
• Any inclusion and exclusion criteria
• Any anticipated control , extraneous , or confounding variables that could bias your research if not accounted for properly.

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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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Dissertation writing in post graduate medical education

Department of Anaesthesiology, Dr. B R Ambedkar Medical College, Bengaluru, Karnataka, India

Mridul M Panditrao

1 Department of Anaesthesiology and Intensive Care, Adesh Institute of Medical Sciences and Research (AIMSR), Bathinda, Punjab, India

2 Department of Anaesthesiology, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India

Sukhminder Jit Singh Bajwa

3 Department of Anaesthesiology and Intensive Care, Gian Sagar Medical College and Hospital, Patiala, Punjab, India

Nishant Sahay

4 Department of Anaesthesiology, All India Institute of Medical Sciences, Patna, Bihar, India

Thrivikrama Padur Tantry

5 Department of Anaesthesiology, A J Institute of Medical Sciences and Research Centre, Kuntikana, Mangalore, Karnataka, India

Associated Data

A dissertation is a practical exercise that educates students about basics of research methodology, promotes scientific writing and encourages critical thinking. The National Medical Commission (India) regulations make assessment of a dissertation by a minimum of three examiners mandatory. The candidate can appear for the final examination only after acceptance of the dissertation. An important role in a dissertation is that of the guide who has to guide his protégés through the process. This manuscript aims to assist students and guides on the basics of conduct of a dissertation and writing the dissertation. For students who will ultimately become researchers, a dissertation serves as an early exercise. Even for people who may never do research after their degree, a dissertation will help them discern the merits of new treatment options available in literature for the benefit of their patients.

INTRODUCTION

The zenith of clinical residency is the completion of the Master's Dissertation, a document formulating the result of research conducted by the student under the guidance of a guide and presenting and publishing the research work. Writing a proper dissertation is most important to present the research findings in an acceptable format. It is also reviewed by the examiners to determine a part of the criteria for the candidate to pass the Masters’ Degree Examination.

The predominant role in a dissertation is that of the guide who has to mentor his protégés through the process by educating them on research methodology, by: (i) identifying a pertinent and topical research question, (ii) formulating the “type” of study and the study design, (iii) selecting the sample population, (iv) collecting and collating the research data accurately, (v) analysing the data, (vi) concluding the research by distilling the outcome, and last but not the least (vii) make the findings known by publication in an acceptable, peer-reviewed journal.[ 1 ] The co-guide could be a co-investigator from another department related to the study topic, and she/he will play an equivalent role in guiding the student.

Research is a creative and systematic work undertaken to increase the stock of knowledge.[ 2 ] This work, known as a study may be broadly classified into two groups in a clinical setting:

• Trials: Here the researcher intervenes to either prevent a disease or to treat it.
• Observational studies: Wherein the investigator makes no active intervention and merely observes the patients or subjects allocated the treatment based on clinical decisions.[ 3 ]

The research which is described in a dissertation needs to be presented under the following headings: Introduction, Aim of the Study, Description of devices if any or pharmacology of drugs, Review of Literature, Material and Methods, Observations and Results, Discussion, Conclusions, Limitations of the study, Bibliography, Proforma, Master chart. Some necessary certificates from the guide and the institute are a requirement in certain universities. The students often add an acknowledgement page before the details of their dissertation proper. It is their expression of gratitude to all of those who they feel have been directly or indirectly helpful in conduct of the study, data analysis, and finally construction of the dissertation.

Framing the research question (RQ)

It is the duty of the teacher to suggest suitable research topics to the residents, based on resources available, feasibility and ease of conduct at the centre. Using the FINER criteria, the acronym for feasibility, topical interest, novelty, ethicality and relevance would be an excellent way to create a correct RQ.[ 4 ]

The PICOT method which describes the patient, intervention, comparison, outcome and time, would help us narrow down to a specific and well-formulated RQ.[ 5 , 6 ] A good RQ leads to the derivation of a research hypothesis, which is an assumption or prediction of the outcome that will be tested by the research. The research topic could be chosen from among the routine clinical work regarding clinical management, use of drugs e.g., vasopressors to prevent hypotension or equipment such as high flow nasal oxygen to avoid ventilation.

Review of literature

To gather this information may be a difficult task for a fresh trainee however, a good review of the available literature is a tool to identify and narrow down a good RQ and generate a hypothesis. Literature sources could be primary (clinical trials, case reports), secondary (reviews, meta-analyses) or tertiary (e.g., reference books, compilations). Methods of searching literature could be manual (journals) or electronic (online databases), by looking up references or listed citations in existing articles. Electronic database searches are made through the various search engines available online e.g., scholar.google.com, National Library of Medicine (NLM) website, clinical key app and many more. Advanced searches options may help narrow down the search results to those that are relevant for the student. This could be based on synthesising keywords from the RQ, or by searching for phrases, Boolean operators, or utilising filters.

After choosing the topic, an apt and accurate title has to be chosen. This should be guided by the use of Medical Subject Headings (MeSH) terminology from the NLM, which is used for indexing, cataloguing, and searching of biomedical and health-related information.[ 7 ] The dissertation requires a detailed title which may include the objective of the study, key words and even the PICOT components. One may add the study design in the title e.g. “a randomised cross over study” or “an observational analytical study” etc.

Aim and the objectives

The Aims and the Objectives of the research study have to be listed clearly, before initiating the study.[ 8 ] “Gaps” or deficiencies in existing knowledge should be clearly cited. The Aim by definition is a statement of the expected outcome, while the Objectives (which might be further classed into primary and secondary based on importance) should be specific, measurable, achievable, realistic or relevant, time-bound and challenging; in short, “SMART!” To simplify, the aim is a statement of intent, in terms of what we hope to achieve at the end of the project. Objectives are specific, positive statements of measurable outcomes, and are a list of steps that will be taken to achieve the outcome.[ 9 ] Aim of a dissertation, for example, could be to know which of two nerve block techniques is better. To realise this aim, comparing the duration of postoperative analgesia after administration of the block by any measurable criteria, could be an objective, such as the time to use of first rescue analgesic drug. Similarly, total postoperative analgesic drug consumption may form a secondary outcome variable as it is also measurable. These will generate data that may be used for analysis to realise the main aim of the study.

Inclusion and exclusions

The important aspect to consider after detailing when and how the objectives will be measured is documenting the eligibility criteria for inclusion of participants. The exclusion criteria must be from among the included population/patients only. e.g., If only American Society of Anesthesiologists (ASA) I and II are included, then ASA III and IV cannot be considered as exclusion criteria, since they were never a part of the study. The protocol must also delineate the setting of the study, locations where data would be collected, and specify duration of conduct of the dissertation. A written informed consent after explaining the aim, objectives and methodology of the study is legally mandatory before embarking upon any human study. The study should explicitly clarify whether it is a retrospective or a prospective study, where the study is conducted and the duration of the study.

Sample size: The sample subjects in the study should be representative of the population upon whom the inference has to be drawn. Sampling is the process of selecting a group of representative people from a larger population and subjecting them for the research.[ 10 ] The sample size represents a number, beyond which the addition of population is unlikely to change the conclusion of the study. The sample size is calculated taking into consideration the primary outcome criteria, confidence interval (CI), power of the study, and the effect size the researcher wishes to observe in the primary objective of the study. Hence a typical sample size statement can be - “Assuming a duration of analgesia of 150 min and standard deviation (SD) of 15 min in first group, keeping power at 80% and CIs at 95% (alpha error at 0.05), a sample of 26 patients would be required to detect a minimum difference (effect size) of 30% in the duration of analgesia between the two groups. Information regarding the different sampling methods and sample size calculations may be found in the Supplementary file 1 .

Any one research question may be answered using a number of research designs.[ 11 ] Research designs are often described as either observational or experimental. The various research designs may be depicted graphically as shown in Figure 1 .

Graphical description of available research designs

The observational studies lack “the three cornerstones of experimentation” – controls, randomisation, and replication. In an experimental study on the other hand, in order to assess the effect of treatment intervention on a participant, it is important to compare it with subjects similar to each other but who have not been given the studied treatment. This group, also called the control group, may help distinguish the effect of the chosen intervention on outcomes from effects caused by other factors, such as the natural history of disease, placebo effects, or observer or patient expectations.

All the proposed dissertations must be submitted to the scientific committee for any suggestion regarding the correct methodology to be followed, before seeking ethical committee approval.

Ethical considerations

Ethical concerns are an important part of the research project, right from selection of the topic to the dissertation writing. It must be remembered, that the purpose of a dissertation given to a post-graduate student is to guide him/her through the process by educating them on the very basics of research methodology. It is therefore not imperative that the protégés undertake a complicated or risky project. If research involves human or animal subjects, drugs or procedures, research ethics guidelines as well as drug control approvals have to be obtained before tabling the proposal to the Institutional Ethics Committee (IEC). The roles, responsibilities and composition of the Ethics Committee has been specified by the Directorate General of Health Services, Government of India. Documented approval of the Ethics committee is mandatory before any subject can be enroled for any dissertation in India. Even retrospective studies require approval from the IEC. Details of this document is available at: https://cdsco.gov.in/opencms/resources/UploadCDSCOWeb/2018/UploadEthicsRegistration/Applmhrcrr.pdf .

The candidate and the guide are called to present their proposal before the committee. The ethical implications, risks and management, subjects’ rights and responsibilities, informed consent, monetary aspects, the research and analysis methods are all discussed. The patient safety is a topmost priority and any doubts of the ethical committee members should be explained in medically layman's terms. The dissertation topics should be listed as “Academic clinical trials” and must involve only those drugs which are already approved by the Drugs Controller General of India. More commonly, the Committee suggests rectifications, and then the researchers have to resubmit the modified proposal after incorporating the suggestions, at the next sitting of the committee or seek online approval, as required. At the conclusion of the research project, the ethics committee has to be updated with the findings and conclusions, as well as when it is submitted for publication. Any deviation from the approved timeline, as well as the research parameters has to be brought to the attention of the IEC immediately, and re-approval sought.

Clinical trial registration

Clinical Trial Registry of India (CTRI) is a free online searchable system for prospective registration of all clinical studies conducted in India. It is owned and managed by the National Institute of Medical Statistics, a division of Indian Council of Medical Research, Government of India. Registration of clinical trials will ensure transparency, accountability and accessibility of trials and their results to all potential beneficiaries.

After the dissertation proposal is passed by the scientific committee and IEC, it may be submitted for approval of trial registration to the CTRI. The student has to create a login at the CTRI website, and submit all the required data with the help of the guides. After submission, CTRI may ask for corrections, clarifications or changes. Subject enrolment and the actual trial should begin only after the CTRI approval.

Randomisation

In an experimental study design, the method of randomisation gives every subject an equal chance to get selected in any group by preventing bias. Primarily, three basic types employed in post-graduate medical dissertations are simple randomisation, block randomisation and stratified randomisation. Simple randomisation is based upon a single sequence of random assignments such as flipping a coin, rolling of dice (above 3 or below 3), shuffling of cards (odd or even) to allocate into two groups. Some students use a random number table found in books or use computer-generated random numbers. There are many random number generators, randomisation programs as well as randomisation services available online too. ( https://www-users.york.ac.uk/~mb55/guide/randsery.htm ).

There are many applications which generate random number sequences and a research student may use such computer-generated random numbers [ Figure 2 ]. Simple randomisation has higher chances of unequal distribution into the two groups, especially when sample sizes are low (<100) and thus block randomisation may be preferred. Details of how to do randomisation along with methods of allocation concealment may be found in Supplementary file 2 .

Figure depicting how to do block randomisation using online resources. (a) generation of a random list (b) transfer of the list to an MS excel file

Allocation concealment

If it is important in a study to generate a random sequence of intervention, it is also important for this sequence to be concealed from all stake-holders to prevent any scope of bias.[ 12 ] Allocation concealment refers to the technique used to implement a random sequence for allocation of intervention, and not to generate it.[ 13 ] In an Indian post-graduate dissertation, the sequentially numbered, opaque, sealed envelopes (SNOSE) technique is commonly used [ Supplementary file 2 ].

To minimise the chances of differential treatment allocation or assessments of outcomes, it is important to blind as many individuals as possible in the trial. Blinding is not an all-or-none phenomenon. Thus, it is very desirable to explicitly state in the dissertation, which individuals were blinded, how they achieved blinding and whether they tested the success of blinding.

Commonly used terms for blinding are

• Single blinding: Masks the participants from knowing which intervention has been given.
• Double blinding: Blinds both the participants as well as researchers to the treatment allocation.
• Triple blinding: By withholding allocation information from the subjects, researchers, as well as data analysts. The specific roles of researchers involved in randomisation, allocation concealment and blinding should be stated clearly in the dissertation.

Data which can be measured as numbers are called quantitative data [ Table 1 ]. Studies which emphasise objective measurements to generate numerical data and then apply statistical and mathematical analysis constitute quantitative research. Qualitative research on the other hand focuses on understanding people's beliefs, experiences, attitudes, behaviours and thus these generate non-numerical data called qualitative data, also known as categorical data, descriptive data or frequency counts. Importance of differentiating data into qualitative and quantitative lies in the fact that statistical analysis as well as the graphical representation may be very different.

Data collection types

In order to obtain data from the outcome variable for the purpose of analysis, we need to design a study which would give us the most valid information. A valid data or measurement tool, is the degree to which the tool measures what it claims to measure. For example, appearance of end tidal carbon dioxide waveform is a more valid measurement to assess correct endotracheal tube placement than auscultation of breath sounds on chest inflation.

The compilation of all data in a ‘Master Chart’ is a necessary step for planning, facilitating and appropriate preparation and processing of the data for analysis. It is a complete set of raw research data arranged in a systematic manner forming a well-structured and formatted, computable data matrix/database of the research to facilitate data analysis. The master chart is prepared as a Microsoft Excel sheet with the appropriate number of columns depicting the variable parameters for each individual subjects/respondents enlisted in the rows.

Statistical analysis

The detailed statistical methodology applied to analyse the data must be stated in the text under the subheading of statistical analysis in the Methods section. The statistician should be involved in the study during the initial planning stage itself. Following four steps have to be addressed while planning, performing and text writing of the statistical analysis part in this section.

Step 1. How many study groups are present? Whether analysis is for an unpaired or paired situation? Whether the recorded data contains repeated measurements? Unpaired or paired situations decide again on the choice of a test. The latter describes before and after situations for collected data (e.g. Heart rate data ‘before’ and ‘after’ spinal anaesthesia for a single group). Further, data should be checked to find out whether they are from repeated measurements (e.g., Mean blood pressure at 0, 1 st , 2 nd , 5 th , 10 th minutes and so on) for a group. Different types of data are commonly encountered in a dissertation [ Supplementary file 3A ].

Step 2. Does the data follow a normal distribution?[ 14 ]

Each study group as well as every parameter has to be checked for distribution analysis. This step will confirm whether the data of a particular group is normally distributed (parametric data) or does not follow the normal distribution (non-parametric data); subsequent statistical test selection mainly depends on the results of the distribution analysis. For example, one may choose the Student's’ test instead of the ‘Mann-Whitney U’ for non-parametric data, which may be incorrect. Each study group as well as every parameter has to be checked for distribution analysis [ Supplementary File 3B ].

Step 3. Calculation of measures of central tendency and measures of variability.

Measures of central tendency mainly include mean, median and mode whereas measures of variability include range, interquartile range (IQR), SD or variance not standard error of mean. Depending on Step 2 findings, one needs to make the appropriate choice. Mean and SD/variance are more often for normally distributed and median with IQR are the best measure for not normal (skewed) distribution. Proportions are used to describe the data whenever the sample size is ≥100. For a small sample size, especially when it is approximately 25-30, describe the data as 5/25 instead of 20%. Software used for statistical analysis automatically calculates the listed step 3 measures and thus makes the job easy.

Step 4. Which statistical test do I choose for necessary analysis?

Choosing a particular test [ Figure 3 ] is based on orderly placed questions which are addressed in the dissertation.[ 15 ]

Chosing a statistical test, (a). to find a difference between the groups of unpaired situations, (b). to find a difference between the groups of paired situations, (c). to find any association between the variables, (d). to find any agreement between the assessment techniques. ANOVA: Analysis of Variance. Reproduced with permission from Editor of Indian Journal of Ophthalmology, and the author, Dr Barun Nayak[ 15 ]

• Is there a difference between the groups of unpaired situations?
• Is there a difference between the groups of paired situations?
• Is there any association between the variables?
• Is there any agreement between the assessment techniques?

Perform necessary analysis using user-friendly software such as GraphPad Prism, Minitab or MedCalc,etc. Once the analysis is complete, appropriate writing in the text form is equally essential. Specific test names used to examine each part of the results have to be described. Simple listing of series of tests should not be done. A typical write-up can be seen in the subsequent sections of the supplementary files [Supplementary files 3C – E ]. One needs to state the level of significance and software details also.

Role of a statistician in dissertation and data analysis

Involving a statistician before planning a study design, prior to data collection, after data have been collected, and while data are analysed is desirable when conducting a dissertation. On the contrary, it is also true that self-learning of statistical analysis reduces the need for statisticians’ help and will improve the quality of research. A statistician is best compared to a mechanic of a car which we drive; he knows each element of the car, but it is we who have to drive it. Sometimes the statisticians may not be available for a student in an institute. Self-learning software tools, user-friendly statistical software for basic statistical analysis thus gain importance for students as well as guides. The statistician will design processes for data collection, gather numerical data, collect, analyse, and interpret data, identify the trends and relationships in data, perform statistical analysis and its interpretation, and finally assist in final conclusion writing.

Results are an important component of the dissertation and should follow clearly from the study objectives. Results (sometimes described as observations that are made by the researcher) should be presented after correct analysis of data, in an appropriate combination of text, charts, tables, graphs or diagrams. Decision has to be taken on each outcome; which outcome has to be presented in what format, at the beginning of writing itself. These should be statistically interpreted, but statistics should not surpass the dissertation results. The observations should always be described accurately and with factual or realistic values in results section, but should not be interpreted in the results section.

While writing, classification and reporting of the Results has to be done under five section paragraphs- population data, data distribution analysis, results of the primary outcome, results of secondary outcomes, any additional observations made such as a rare adverse event or a side effect (intended or unintended) or of any additional analysis that may have been done, such as subgroup analysis.

At each level, one may either encounter qualitative (n/N and %) or quantitative data (mean [SD], median [IQR] and so on.

In the first paragraph of Results while describing the population data, one has to write about included and excluded patients. One needs to cite the Consolidated Standards of Reporting Trials (CONSORT) flow chart to the text, at this stage. Subsequently, highlighting of age, sex, height, body mass index (BMI) and other study characteristics referring to the first table of ‘patients data’ should be considered. It is not desirable to detail all values and their comparison P values in the text again in population data as long as they are presented in a cited table. An example of this pattern can be seen in Supplementary file 3D .

In the second paragraph, one needs to explain how the data is distributed. It should be noted that, this is not a comparison between the study groups but represents data distribution for the individual study groups (Group A or Group B, separately)[ Supplementary file 3E ].

In the subsequent paragraph of Results , focused writing on results of the primary outcomes is very important. It should be attempted to mention most of the data outputs related to the primary outcomes as the study is concluded based on the results of this outcome analysis. The measures of central tendency and dispersion (Mean or median and SD or IQR etc., respectively), alongside the CIs, sample number and P values need to be mentioned. It should be noted that the CIs can be for the mean as well as for the mean difference and should not be interchanged. An example of this pattern can be seen in Supplementary file 3F .

A large number of the dissertations are guided for single primary outcome analysis, and also the results of multiple secondary outcomes are needed to be written. The primary outcome should be presented in detail, and secondary outcomes can be presented in tables or graphs only. This will help in avoiding a possible evaluator's fatigue. An example of this pattern can be seen in Supplementary file 3G .

In the last paragraph of the Results, mention any additional observations, such as a rare adverse event or side effect or describe the unexpected results. The results of any additional analysis (subgroup analysis) then need to be described too. An example of this pattern can be seen in Supplementary file 3H .

The most common error observed in the Results text is duplication of the data and analytical outputs. While using the text for summarising the results, at each level, it should not be forgotten to cite the table or graph but the information presented in a table should not be repeated in the text. Further, results should not be given to a greater degree of accuracy than that of the measurement. For example, mean (SD) age need to be presented as 34.5 (11.3) years instead of 34.5634 (11.349). The latter does not carry any additional information and is unnecessary. The actual P values need to be mentioned. The P value should not be simply stated as ‘ P < 0.05’; P value should be written with the actual numbers, such as ‘ P = 0.021’. The symbol ‘<’ should be used only when actual P value is <0.001 or <0.0001. One should try avoiding % calculations for a small sample especially when n < 100. The sample size calculation is a part of the methodology and should not be mentioned in the Results section.

The use of tables will help present actual data values especially when in large numbers. The data and their relationships can be easily understood by an appropriate table and one should avoid overwriting of results in the text format. All values of sample size, central tendency, dispersions, CIs and P value are to be presented in appropriate columns and rows. Preparing a dummy table for all outcomes on a rough paper before proceeding to Microsoft Excel may be contemplated. Appropriate title heading (e.g., Table 1 . Study Characteristics), Column Headings (e.g., Parameter studied, P values) should be presented. A footnote should be added whenever necessary. For outputs, where statistically significant P values are recorded, the same should be highlighted using an asterisk (*) symbol and the same *symbol should be cited in the footnote describing its value (e.g., * P < 0.001) which is self-explanatory for statistically significance. One should not use abbreviations such as ‘NS’ or ‘Sig’ for describing (non-) significance. Abbreviations should be described for all presented tables. A typical example of a table can be seen in Figure 4 .

Example of presenting a table

Graphical images

Similar to tables, the graphs and diagrams give a bird's-eye view of the entire data and therefore may easily be understood. bar diagrams (simple, multiple or component), pie charts, line diagrams, pictograms and spot maps suit qualitative data more whereas the histograms, frequency polygons, cumulative frequency, polygon scatter diagram, box and whisker plots and correlation diagrams are used to depict quantitative data. Too much presentation of graphs and images, selection of inappropriate or interchanging of graphs, unnecessary representation of three-dimensional graph for one-dimensional graphs, disproportionate sizes of length and width and incorrect scale and labelling of an axis should be avoided. All graphs should contain legends, abbreviation descriptions and a footnote. Appropriate labelling of the x - and the y -axis is also essential. Priori decided scale for axis data should be considered. The ‘error bar’ represents SDs or IQRs in the graphs and should be used irrespective of whether they are bar charts or line graphs. Not showing error bars in a graphical image is a gross mistake. An error bar can be shown on only one side of the line graph to keep it simple. A typical example of a graphical image can be seen in Figure 5 . The number of subjects (sample) is to be mentioned for each time point on the x -axis. An asterisk (*) needs to be put for data comparisons having statistically significant P value in the graph itself and they are self-explanatory with a ‘stand-alone’ graph.

Example of an incorrect (a) and correct (b) image

Once the results have been adequately analysed and described, the next step is to draw conclusions from the data and study. The main goal is to defend the work by staging a constructive debate with the literature.[ 16 ] Generally, the length of the ‘ Discussion ’ section should not exceed the sum of other sections (introduction, material and methods, and results).[ 17 ] Here the interpretation, importance/implications, relevance, limitations of the results are elaborated and should end in recommendations.

It is advisable to start by mentioning the RQ precisely, summarising the main findings without repeating the entire data or results again. The emphasis should be on how the results correlate with the RQ and the implications of these results, with the relevant review of literature (ROL). Do the results coincide with and add anything to the prevalent knowledge? If not, why not? It should justify the differences with plausible explanation. Ultimately it should be made clear, if the study has been successful in making some contribution to the existing evidence. The new results should not be introduced and any exaggerated deductions which cannot be corroborated by the outcomes should not be made.

The discussion should terminate with limitations of the study,[ 17 ] mentioned magnanimously. Indicating limitations of the study reflects objectivity of the authors. It should not enlist any errors, but should acknowledge the constraints and choices in designing, planning methodology or unanticipated challenges that may have cropped up during the actual conduct of the study. However, after listing the limitations, the validity of results pertaining to the RQ may be emphasised again.

This section should convey the precise and concise message as the take home message. The work carried out should be summarised and the answer found to the RQ should be succinctly highlighted. One should not start dwelling on the specific results but mention the overall gain or insights from the observations, especially, whether it fills the gap in the existing knowledge if any. The impact, it may have on the existing knowledge and practices needs to be reiterated.

What to do when we get a negative result?

Sometimes, despite the best research framework, the results obtained are inconclusive or may even challenge a few accepted assumptions.[ 18 ] These are frequently, but inappropriately, termed as negative results and the data as negative data. Students must believe that if the study design is robust and valid, if the confounders have been carefully neutralised and the outcome parameters measure what they are intended to, then no result is a negative result. In fact, such results force us to critically re-evaluate our current understanding of concepts and knowledge thereby helping in better decision making. Studies showing lack of prolongation of the apnoea desaturation safety periods at lower oxygen flows strengthened belief in the difficult airway guidelines which recommend nasal insufflations with at least 15 L/min oxygen.[ 19 , 20 , 21 ]

Publishing the dissertation work

There are many reporting guidelines based upon the design of research. These are a checklist, flow diagram, or structured text to guide authors in reporting a specific type of research, developed using explicit methodology. The CONSORT[ 22 ] and Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) initiatives,[ 23 ] both included in the Enhancing the Quality and Transparency of Health Research (EQUATOR) international network, have elaborated appropriate suggestions to improve the transparency, clarity and completeness of scientific literature [ Figure 6 ].

Equator publishing tree

All authors are advised to follow the CONSORT/STROBE checklist attached as Supplementary file 4 , when writing and reporting their dissertation.

For most dissertations in Anaesthesiology, the CONSORT, STROBE, Standards for Reporting Diagnostic accuracy studies (STARD) or REporting recommendations for tumour MARKer prognostic studies (REMARK) guidelines would suffice.

Abstract and Summary

These two are the essential sections of a dissertation.

It should be at the beginning of the manuscript, after the title page and acknowledgments, but before the table of contents. The preparation varies as per the University guidelines, but generally ranges between 150 to 300 words. Although it comes at the very beginning of the thesis, it is the last part one writes. It must not be a ‘copy-paste job’ from the main manuscript, but well thought out miniaturisation, giving the overview of the entire text. As a rule, there should be no citation of references here.

Logically, it would have four components starting with aims, methods, results, and conclusion. One should begin the abstract with the research question/objectives precisely, avoiding excessive background information. Adjectives like, evaluate, investigate, test, compare raise the curiosity quotient of the reader. This is followed by a brief methodology highlighting only the core steps used. There is no need of mentioning the challenges, corrections, or modifications, if any. Finally, important results, which may be restricted to fulfilment (or not), of the primary objective should be mentioned. Abstracts end with the main conclusion stating whether a specific answer to the RQ was found/not found. Then recommendations as a policy statement or utility may be made taking care that it is implementable.

Keywords may be included in the abstract, as per the recommendations of the concerned university. The keywords are primarily useful as markers for future searches. Lastly, the random reader using any search engine may use these, and the identifiability is increased.

The summary most often, is either the last part of the Discussion or commonly, associated with the conclusions (Summary and Conclusions). Repetition of introduction, whole methodology, and all the results should be avoided. Summary, if individually written, should not be more than 150 to 300 words. It highlights the research question, methods used to investigate it, the outcomes/fallouts of these, and then the conclusion part may start.

References/bibliography

Writing References serves mainly two purposes. It is the tacit acknowledgement of the fact that someone else's written words or their ideas or their intellectual property (IP) are used, in part or in toto , to avoid any blame of plagiarism. It is to emphasise the circumspective and thorough literature search that has been carried out in preparation of the work.

Vancouver style for referencing is commonly used in biomedical dissertation writing. A reference list contains details of the works cited in the text of the document. (e.g. book, journal article, pamphlet, government reports, conference material, internet site). These details must include sufficient details so that others may locate and access those references.[ 24 ]

How much older the references can be cited, depends upon the university protocol. Conventionally accepted rule is anywhere between 5-10 years. About 85% of references should be dispersed in this time range. Remaining 15%, which may include older ones if they deal with theories, historical aspects, and any other factual content. Rather than citing an entire book, it is prudent to concentrate on the chapter or subsection of the text. There are subjective variations between universities on this matter. But, by and large, these are quoted as and when deemed necessary and with correct citation.

Bibliography is a separate list from the reference list and should be arranged alphabetically by writing name of the ‘author or title’ (where no author name is given) in the Vancouver style.

There are different aspects of writing the references.[ 24 ]

Citing the reference in the form of a number in the text. The work of other authors referred in the manuscript should be given a unique number and quoted. This is done in the order of their appearance in the text in chronological order by using Arabic numerals. The multiple publications of same author shall be written individually. If a reference article has more than six authors, all six names should be written, followed by “ et al .” to be used in lieu of other author names. It is desirable to write the names of the journals in abbreviations as per the NLM catalogue. Examples of writing references from the various sources may be found in the Supplementary file 5 .

Both the guide and the student have to work closely while searching the topic initially and also while finalising the submission of the dissertation. But the role of the guide in perusing the document in detail, and guiding the candidate through the required corrections by periodic updates and discussions cannot be over-emphasised.

Assessment of dissertations

Rarely, examiners might reject a dissertation for failure to choose a contemporary topic, a poor review of literature, defective methodology, biased analysis or incorrect conclusions. If these cannot be corrected satisfactorily, it will then be back to the drawing board for the researchers, who would have to start from scratch to redesign the study, keeping the deficiencies in mind this time.

Before submission, dissertation has to be run through “plagiarism detector” software, such as Turnitin or Grammarly to ensure that plagiarism does not happen even unwittingly. Informal guidelines state that the percentage plagiarism picked up by these tools should be <10%.

No work of art is devoid of mistakes/errors. Logically, a dissertation, being no exception, may also have errors. Our aim, is to minimise them.

The dissertation is an integral part in the professional journey of any medical post-graduate student. It is also an important responsibility for a guide to educate his protégé, the basics of research methodology through the process. Searching for a gap in literature and identification of a pertinent research question is the initial step. Careful planning of the study design is a vitally important aspect. After the conduct of study, writing the dissertation is an art for which the student often needs guidance. A good dissertation is a good description of a meticulously conducted study under the different headings described, utilising the various reporting guidelines. By avoiding some common errors as discussed in this manuscript, a good dissertation can result in a very fruitful addition to medical literature.

Financial support and sponsorship

Conflicts of interest.

There are no conflicts of interest.

SUPPLEMENTARY FILES

How To Write A Dissertation Or Thesis

8 straightforward steps to craft an a-grade dissertation.

By: Derek Jansen (MBA) Expert Reviewed By: Dr Eunice Rautenbach | June 2020

Writing a dissertation or thesis is not a simple task. It takes time, energy and a lot of will power to get you across the finish line. It’s not easy – but it doesn’t necessarily need to be a painful process. If you understand the big-picture process of how to write a dissertation or thesis, your research journey will be a lot smoother.  

In this post, I’m going to outline the big-picture process of how to write a high-quality dissertation or thesis, without losing your mind along the way. If you’re just starting your research, this post is perfect for you. Alternatively, if you’ve already submitted your proposal, this article which covers how to structure a dissertation might be more helpful.

How To Write A Dissertation: 8 Steps

• Clearly understand what a dissertation (or thesis) is
• Find a unique and valuable research topic
• Craft a convincing research proposal
• Write up a strong introduction chapter
• Review the existing literature and compile a literature review
• Design a rigorous research strategy and undertake your own research
• Present the findings of your research
• Draw a conclusion and discuss the implications

Step 1: Understand exactly what a dissertation is

This probably sounds like a no-brainer, but all too often, students come to us for help with their research and the underlying issue is that they don’t fully understand what a dissertation (or thesis) actually is.

So, what is a dissertation?

At its simplest, a dissertation or thesis is a formal piece of research , reflecting the standard research process . But what is the standard research process, you ask? The research process involves 4 key steps:

• Ask a very specific, well-articulated question (s) (your research topic)
• See what other researchers have said about it (if they’ve already answered it)
• If they haven’t answered it adequately, undertake your own data collection and analysis in a scientifically rigorous fashion
• Answer your original question(s), based on your analysis findings

In short, the research process is simply about asking and answering questions in a systematic fashion . This probably sounds pretty obvious, but people often think they’ve done “research”, when in fact what they have done is:

• Started with a vague, poorly articulated question
• Not taken the time to see what research has already been done regarding the question
• Collected data and opinions that support their gut and undertaken a flimsy analysis
• Drawn a shaky conclusion, based on that analysis

If you want to see the perfect example of this in action, look out for the next Facebook post where someone claims they’ve done “research”… All too often, people consider reading a few blog posts to constitute research. Its no surprise then that what they end up with is an opinion piece, not research. Okay, okay – I’ll climb off my soapbox now.

The key takeaway here is that a dissertation (or thesis) is a formal piece of research, reflecting the research process. It’s not an opinion piece , nor a place to push your agenda or try to convince someone of your position. Writing a good dissertation involves asking a question and taking a systematic, rigorous approach to answering it.

If you understand this and are comfortable leaving your opinions or preconceived ideas at the door, you’re already off to a good start!

Step 2: Find a unique, valuable research topic

As we saw, the first step of the research process is to ask a specific, well-articulated question. In other words, you need to find a research topic that asks a specific question or set of questions (these are called research questions ). Sounds easy enough, right? All you’ve got to do is identify a question or two and you’ve got a winning research topic. Well, not quite…

A good dissertation or thesis topic has a few important attributes. Specifically, a solid research topic should be:

Let’s take a closer look at these:

Attribute #1: Clear

Your research topic needs to be crystal clear about what you’re planning to research, what you want to know, and within what context. There shouldn’t be any ambiguity or vagueness about what you’ll research.

Here’s an example of a clearly articulated research topic:

An analysis of consumer-based factors influencing organisational trust in British low-cost online equity brokerage firms.

As you can see in the example, its crystal clear what will be analysed (factors impacting organisational trust), amongst who (consumers) and in what context (British low-cost equity brokerage firms, based online).

Need a helping hand?

Attribute #2:   Unique

Your research should be asking a question(s) that hasn’t been asked before, or that hasn’t been asked in a specific context (for example, in a specific country or industry).

For example, sticking organisational trust topic above, it’s quite likely that organisational trust factors in the UK have been investigated before, but the context (online low-cost equity brokerages) could make this research unique. Therefore, the context makes this research original.

One caveat when using context as the basis for originality – you need to have a good reason to suspect that your findings in this context might be different from the existing research – otherwise, there’s no reason to warrant researching it.

Attribute #3: Important

Simply asking a unique or original question is not enough – the question needs to create value. In other words, successfully answering your research questions should provide some value to the field of research or the industry. You can’t research something just to satisfy your curiosity. It needs to make some form of contribution either to research or industry.

For example, researching the factors influencing consumer trust would create value by enabling businesses to tailor their operations and marketing to leverage factors that promote trust. In other words, it would have a clear benefit to industry.

So, how do you go about finding a unique and valuable research topic? We explain that in detail in this video post – How To Find A Research Topic . Yeah, we’ve got you covered 😊

Step 3: Write a convincing research proposal

Once you’ve pinned down a high-quality research topic, the next step is to convince your university to let you research it. No matter how awesome you think your topic is, it still needs to get the rubber stamp before you can move forward with your research. The research proposal is the tool you’ll use for this job.

So, what’s in a research proposal?

The main “job” of a research proposal is to convince your university, advisor or committee that your research topic is worthy of approval. But convince them of what? Well, this varies from university to university, but generally, they want to see that:

• You have a clearly articulated, unique and important topic (this might sound familiar…)
• You’ve done some initial reading of the existing literature relevant to your topic (i.e. a literature review)
• You have a provisional plan in terms of how you will collect data and analyse it (i.e. a methodology)

At the proposal stage, it’s (generally) not expected that you’ve extensively reviewed the existing literature , but you will need to show that you’ve done enough reading to identify a clear gap for original (unique) research. Similarly, they generally don’t expect that you have a rock-solid research methodology mapped out, but you should have an idea of whether you’ll be undertaking qualitative or quantitative analysis , and how you’ll collect your data (we’ll discuss this in more detail later).

Long story short – don’t stress about having every detail of your research meticulously thought out at the proposal stage – this will develop as you progress through your research. However, you do need to show that you’ve “done your homework” and that your research is worthy of approval .

So, how do you go about crafting a high-quality, convincing proposal? We cover that in detail in this video post – How To Write A Top-Class Research Proposal . We’ve also got a video walkthrough of two proposal examples here .

Step 4: Craft a strong introduction chapter

Once your proposal’s been approved, its time to get writing your actual dissertation or thesis! The good news is that if you put the time into crafting a high-quality proposal, you’ve already got a head start on your first three chapters – introduction, literature review and methodology – as you can use your proposal as the basis for these.

Handy sidenote – our free dissertation & thesis template is a great way to speed up your dissertation writing journey.

What’s the introduction chapter all about?

The purpose of the introduction chapter is to set the scene for your research (dare I say, to introduce it…) so that the reader understands what you’ll be researching and why it’s important. In other words, it covers the same ground as the research proposal in that it justifies your research topic.

What goes into the introduction chapter?

This can vary slightly between universities and degrees, but generally, the introduction chapter will include the following:

• A brief background to the study, explaining the overall area of research
• A problem statement , explaining what the problem is with the current state of research (in other words, where the knowledge gap exists)
• Your research questions – in other words, the specific questions your study will seek to answer (based on the knowledge gap)
• The significance of your study – in other words, why it’s important and how its findings will be useful in the world

As you can see, this all about explaining the “what” and the “why” of your research (as opposed to the “how”). So, your introduction chapter is basically the salesman of your study, “selling” your research to the first-time reader and (hopefully) getting them interested to read more.

How do I write the introduction chapter, you ask? We cover that in detail in this post .

Step 5: Undertake an in-depth literature review

As I mentioned earlier, you’ll need to do some initial review of the literature in Steps 2 and 3 to find your research gap and craft a convincing research proposal – but that’s just scratching the surface. Once you reach the literature review stage of your dissertation or thesis, you need to dig a lot deeper into the existing research and write up a comprehensive literature review chapter.

What’s the literature review all about?

There are two main stages in the literature review process:

Literature Review Step 1: Reading up

The first stage is for you to deep dive into the existing literature (journal articles, textbook chapters, industry reports, etc) to gain an in-depth understanding of the current state of research regarding your topic. While you don’t need to read every single article, you do need to ensure that you cover all literature that is related to your core research questions, and create a comprehensive catalogue of that literature , which you’ll use in the next step.

Reading and digesting all the relevant literature is a time consuming and intellectually demanding process. Many students underestimate just how much work goes into this step, so make sure that you allocate a good amount of time for this when planning out your research. Thankfully, there are ways to fast track the process – be sure to check out this article covering how to read journal articles quickly .

Literature Review Step 2: Writing up

Once you’ve worked through the literature and digested it all, you’ll need to write up your literature review chapter. Many students make the mistake of thinking that the literature review chapter is simply a summary of what other researchers have said. While this is partly true, a literature review is much more than just a summary. To pull off a good literature review chapter, you’ll need to achieve at least 3 things:

• You need to synthesise the existing research , not just summarise it. In other words, you need to show how different pieces of theory fit together, what’s agreed on by researchers, what’s not.
• You need to highlight a research gap that your research is going to fill. In other words, you’ve got to outline the problem so that your research topic can provide a solution.
• You need to use the existing research to inform your methodology and approach to your own research design. For example, you might use questions or Likert scales from previous studies in your your own survey design .

As you can see, a good literature review is more than just a summary of the published research. It’s the foundation on which your own research is built, so it deserves a lot of love and attention. Take the time to craft a comprehensive literature review with a suitable structure .

But, how do I actually write the literature review chapter, you ask? We cover that in detail in this video post .

Step 6: Carry out your own research

Once you’ve completed your literature review and have a sound understanding of the existing research, its time to develop your own research (finally!). You’ll design this research specifically so that you can find the answers to your unique research question.

There are two steps here – designing your research strategy and executing on it:

1 – Design your research strategy

The first step is to design your research strategy and craft a methodology chapter . I won’t get into the technicalities of the methodology chapter here, but in simple terms, this chapter is about explaining the “how” of your research. If you recall, the introduction and literature review chapters discussed the “what” and the “why”, so it makes sense that the next point to cover is the “how” –that’s what the methodology chapter is all about.

In this section, you’ll need to make firm decisions about your research design. This includes things like:

• Your research philosophy (e.g. positivism or interpretivism )
• Your overall methodology (e.g. qualitative , quantitative or mixed methods)
• Your data collection strategy (e.g. interviews , focus groups, surveys)
• Your data analysis strategy (e.g. content analysis , correlation analysis, regression)

If these words have got your head spinning, don’t worry! We’ll explain these in plain language in other posts. It’s not essential that you understand the intricacies of research design (yet!). The key takeaway here is that you’ll need to make decisions about how you’ll design your own research, and you’ll need to describe (and justify) your decisions in your methodology chapter.

2 – Execute: Collect and analyse your data

Once you’ve worked out your research design, you’ll put it into action and start collecting your data. This might mean undertaking interviews, hosting an online survey or any other data collection method. Data collection can take quite a bit of time (especially if you host in-person interviews), so be sure to factor sufficient time into your project plan for this. Oftentimes, things don’t go 100% to plan (for example, you don’t get as many survey responses as you hoped for), so bake a little extra time into your budget here.

Once you’ve collected your data, you’ll need to do some data preparation before you can sink your teeth into the analysis. For example:

• If you carry out interviews or focus groups, you’ll need to transcribe your audio data to text (i.e. a Word document).
• If you collect quantitative survey data, you’ll need to clean up your data and get it into the right format for whichever analysis software you use (for example, SPSS, R or STATA).

Once you’ve completed your data prep, you’ll undertake your analysis, using the techniques that you described in your methodology. Depending on what you find in your analysis, you might also do some additional forms of analysis that you hadn’t planned for. For example, you might see something in the data that raises new questions or that requires clarification with further analysis.

The type(s) of analysis that you’ll use depend entirely on the nature of your research and your research questions. For example:

• If your research if exploratory in nature, you’ll often use qualitative analysis techniques .
• If your research is confirmatory in nature, you’ll often use quantitative analysis techniques
• If your research involves a mix of both, you might use a mixed methods approach

Again, if these words have got your head spinning, don’t worry! We’ll explain these concepts and techniques in other posts. The key takeaway is simply that there’s no “one size fits all” for research design and methodology – it all depends on your topic, your research questions and your data. So, don’t be surprised if your study colleagues take a completely different approach to yours.

Step 7: Present your findings

Once you’ve completed your analysis, it’s time to present your findings (finally!). In a dissertation or thesis, you’ll typically present your findings in two chapters – the results chapter and the discussion chapter .

What’s the difference between the results chapter and the discussion chapter?

While these two chapters are similar, the results chapter generally just presents the processed data neatly and clearly without interpretation, while the discussion chapter explains the story the data are telling  – in other words, it provides your interpretation of the results.

For example, if you were researching the factors that influence consumer trust, you might have used a quantitative approach to identify the relationship between potential factors (e.g. perceived integrity and competence of the organisation) and consumer trust. In this case:

• Your results chapter would just present the results of the statistical tests. For example, correlation results or differences between groups. In other words, the processed numbers.
• Your discussion chapter would explain what the numbers mean in relation to your research question(s). For example, Factor 1 has a weak relationship with consumer trust, while Factor 2 has a strong relationship.

Depending on the university and degree, these two chapters (results and discussion) are sometimes merged into one , so be sure to check with your institution what their preference is. Regardless of the chapter structure, this section is about presenting the findings of your research in a clear, easy to understand fashion.

Importantly, your discussion here needs to link back to your research questions (which you outlined in the introduction or literature review chapter). In other words, it needs to answer the key questions you asked (or at least attempt to answer them).

For example, if we look at the sample research topic:

In this case, the discussion section would clearly outline which factors seem to have a noteworthy influence on organisational trust. By doing so, they are answering the overarching question and fulfilling the purpose of the research .

For more information about the results chapter , check out this post for qualitative studies and this post for quantitative studies .

Step 8: The Final Step Draw a conclusion and discuss the implications

Last but not least, you’ll need to wrap up your research with the conclusion chapter . In this chapter, you’ll bring your research full circle by highlighting the key findings of your study and explaining what the implications of these findings are.

What exactly are key findings? The key findings are those findings which directly relate to your original research questions and overall research objectives (which you discussed in your introduction chapter). The implications, on the other hand, explain what your findings mean for industry, or for research in your area.

Sticking with the consumer trust topic example, the conclusion might look something like this:

Key findings

This study set out to identify which factors influence consumer-based trust in British low-cost online equity brokerage firms. The results suggest that the following factors have a large impact on consumer trust:

While the following factors have a very limited impact on consumer trust:

Notably, within the 25-30 age groups, Factors E had a noticeably larger impact, which may be explained by…

Implications

The findings having noteworthy implications for British low-cost online equity brokers. Specifically:

The large impact of Factors X and Y implies that brokers need to consider….

The limited impact of Factor E implies that brokers need to…

As you can see, the conclusion chapter is basically explaining the “what” (what your study found) and the “so what?” (what the findings mean for the industry or research). This brings the study full circle and closes off the document.

Let’s recap – how to write a dissertation or thesis

You’re still with me? Impressive! I know that this post was a long one, but hopefully you’ve learnt a thing or two about how to write a dissertation or thesis, and are now better equipped to start your own research.

To recap, the 8 steps to writing a quality dissertation (or thesis) are as follows:

• Understand what a dissertation (or thesis) is – a research project that follows the research process.
• Find a unique (original) and important research topic
• Craft a convincing dissertation or thesis research proposal
• Write a clear, compelling introduction chapter
• Undertake a thorough review of the existing research and write up a literature review
• Undertake your own research
• Present and interpret your findings

Once you’ve wrapped up the core chapters, all that’s typically left is the abstract , reference list and appendices. As always, be sure to check with your university if they have any additional requirements in terms of structure or content.  

Psst… there’s more (for free)

This post is part of our dissertation mini-course, which covers everything you need to get started with your dissertation, thesis or research project. 

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20 Comments

thankfull >>>this is very useful

Thank you, it was really helpful

unquestionably, this amazing simplified way of teaching. Really , I couldn’t find in the literature words that fully explicit my great thanks to you. However, I could only say thanks a-lot.

Great to hear that – thanks for the feedback. Good luck writing your dissertation/thesis.

This is the most comprehensive explanation of how to write a dissertation. Many thanks for sharing it free of charge.

Very rich presentation. Thank you

Thanks Derek Jansen|GRADCOACH, I find it very useful guide to arrange my activities and proceed to research!

Thank you so much for such a marvelous teaching .I am so convinced that am going to write a comprehensive and a distinct masters dissertation

It is an amazing comprehensive explanation

This was straightforward. Thank you!

I can say that your explanations are simple and enlightening – understanding what you have done here is easy for me. Could you write more about the different types of research methods specific to the three methodologies: quan, qual and MM. I look forward to interacting with this website more in the future.

Thanks for the feedback and suggestions 🙂

Hello, your write ups is quite educative. However, l have challenges in going about my research questions which is below; *Building the enablers of organisational growth through effective governance and purposeful leadership.*

Very educating.

Just listening to the name of the dissertation makes the student nervous. As writing a top-quality dissertation is a difficult task as it is a lengthy topic, requires a lot of research and understanding and is usually around 10,000 to 15000 words. Sometimes due to studies, unbalanced workload or lack of research and writing skill students look for dissertation submission from professional writers.

Thank you 💕😊 very much. I was confused but your comprehensive explanation has cleared my doubts of ever presenting a good thesis. Thank you.

thank you so much, that was so useful

Hi. Where is the excel spread sheet ark?

could you please help me look at your thesis paper to enable me to do the portion that has to do with the specification

my topic is “the impact of domestic revenue mobilization.

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Spatial Variations of the Activity of 137 Cs and the Contents of Heavy Metals and Petroleum Products in the Polluted Soils of the City of Elektrostal

• DEGRADATION, REHABILITATION, AND CONSERVATION OF SOILS
• Open access
• Published: 15 June 2022
• Volume 55 , pages 840–848, ( 2022 )

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• D. N. Lipatov 1 ,
• V. A. Varachenkov 1 ,
• D. V. Manakhov 1 ,
• M. M. Karpukhin 1 &
• S. V. Mamikhin 1  

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The levels of specific activity of 137 Cs and the contents of mobile forms (1 M ammonium acetate extraction) of heavy metals (Zn, Cu, Ni, Co, Cr, Pb) and petroleum products were studied in the upper soil horizon of urban landscapes of the city of Elektrostal under conditions of local radioactive and chemical contamination were studied. In the soils within a short radius (0–100 m) around the heavy engineering plant, the specific activity of 137 Cs and the contents of mobile forms of Pb, Cu, and Zn were increased. The lognormal distribution law of 137 Cs was found in the upper (0–10 cm) soil layer; five years after the radiation accident, the specific activity of 137 Cs varied from 6 to 4238 Bq/kg. The coefficients of variation increased with an increase in the degree of soil contamination in the following sequence: Co < Ni < petroleum products < Cr < 137 Cs < Zn < Pb < Cu ranging from 50 to 435%. Statistically significant direct correlation was found between the specific activity of 137 Cs and the contents of mobile forms of Pb, Cu, and Zn in the upper horizon of urban soils, and this fact indicated the spatial conjugacy of local spots of radioactive and polymetallic contamination in the studied area. It was shown that the specific activity of 137 Cs, as well as the content of heavy metals and petroleum products in the upper layer (0–10 cm) of the soils disturbed in the course of decontamination, earthwork and reclamation is reduced.

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INTRODUCTION

Contaminants migrate and accumulate in urban ecosystems under the impact of both natural and technogenic factors. The processes of technogenic migration of 137 Cs are most pronounced in radioactively contaminated territories. It was found in urboecological studies that the intensity of sedimentation of aerosol particles containing radionuclides and heavy metals is determined by the types of the surfaces of roofs, walls, roads, lawns, and parks and by their position within the urban wind field [ 12 , 26 ]. Traffic in the cities results in significant transport of dust and associated contaminants and radionuclides [ 15 , 24 ]. During decontamination measures in the areas of Chernobyl radioactive trace, not only the decrease in the level of contamination but also the possibility of secondary radioactive contamination because of the transportation of contaminated soil particles by wind or water, or anthropogenic transfer of transferring of ground were observed [ 5 , 6 ]. Rainstorm runoff and hydrological transport of dissolved and colloidal forms of 137 Cs can result in the accumulation of this radionuclide in meso- and microdepressions, where sedimentation takes place [ 10 , 16 ]. Different spatial distribution patterns of 137 Cs in soils of particular urban landscapes were found in the city of Ozersk near the nuclear fuel cycle works [ 17 ]. Natural character of 137 Cs migration in soils of Moscow forest-parks and a decrease in its specific activity in industrial areas have been revealed [ 10 ]. Determination of the mean level and parameters of spatial variations of 137 Cs in soils is one of primary tasks of radioecological monitoring of cities, including both unpolluted (background) and contaminated territories.

Emissions and discharges from numerous sources of contamination can cause the accumulation of a wide range of toxicants in urban soils: heavy metals (HMs), oil products (OPs), polycyclic aromatic hydrocarbons (PAHs), and other chemical substances. Soil contamination by several groups of toxicants is often observed in urban landscapes [ 20 , 23 ] because of the common contamination source or close pathways of the migration of different contaminants. A comprehensive analysis of contamination of urban soils by radionuclides and heavy metals has been performed in some studies [ 21 , 25 ]. The determination of possible spatial interrelationships between radioactive and chemical contaminations in urban soils is an important problem in urban ecology.

A radiation accident took place in the Elektrostal heavy engineering works (EHEW) in April 2013: a capacious source of 137 Cs entered the smelt furnace, and emission of radioactive aerosols from the aerating duct into the urban environment took place. The activity of molten source was estimated at about 1000–7000 Ci [ 14 ]. The area of contamination in the territory of the plant reached 7500 m 2 . However, radioactive aerosols affected a much larger area around the EHEW, including Krasnaya and Pervomaiskaya streets, and reached Lenin Prospect.

Geochemical evaluation of contamination of the upper soil horizon in the city of Elektrostal was carried out in 1989–1991. This survey indicated the anomalies of concentrations of wolfram, nickel, molybdenum, chromium, and other heavy metals related to accumulation of alloying constituent and impurities of non-ferrous metals in the emissions of steelmaking works [ 19 ].

The aim of our work was to determine the levels of specific activity of 137 Cs, concentrations of mobile forms of heavy metals (Zn, Cu, Ni, Co, Cr, and Pb) and oil products in the upper soil horizons in different urban landscapes of the city of Elektrostal under the conditions of local radioactive and chemical contamination.

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D. N. Lipatov, V. A. Varachenkov, D. V. Manakhov, M. M. Karpukhin & S. V. Mamikhin

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Lipatov, D.N., Varachenkov, V.A., Manakhov, D.V. et al. Spatial Variations of the Activity of 137 Cs and the Contents of Heavy Metals and Petroleum Products in the Polluted Soils of the City of Elektrostal. Eurasian Soil Sc. 55 , 840–848 (2022). https://doi.org/10.1134/S1064229322060072

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Received : 21 October 2021

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Published : 15 June 2022

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DOI : https://doi.org/10.1134/S1064229322060072

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Office of graduate and postdoctoral education, 12 grad students named as finalists for 2024 three minute thesis competition.

Mar 26, 2024

After six intense preliminary rounds, twelve exceptional scholars have emerged from a pool of 65 talented candidates, earning their place as finalists in Georgia Tech's highly anticipated annual Three Minute Thesis (3MT) competition. On Friday, April 5, 2024, these finalists will hit the stage, harnessing their research expertise, to deliver compelling presentations in a three-minute format.

Congratulations to the following twelve finalists:

Karina Bhattacharya MID Industrial Design 

Vinodhini Comandur, Ph.D. Aerospace Engineering 

Mo Jarin, Ph.D. Environmental Engineering 

Anamik Jhunjhunwala, Ph.D. Biomedical Engineering 

Valeria Juarez, Ph.D. Biomedical Engineering 

Alexandra Patterson, Ph.D. Bioengineering 

Jeffrey Pattison, Ph.D. Aerospace Engineering 

Kantwon Rogers, Ph.D. Computer Science 

Mallika Senthil, MS Biomedical Engineering 

Wenting Shi, Ph.D. Chemistry and Biochemistry 

Shreyas Srivathsan, Ph.D. Aerospace Engineering 

Raghav Tandon, Ph.D. Machine Learning 

This year’s 3MT competition takes place on Friday, April 5, 2024, at 5:30 p.m. in the Atlantic Theater in the John Lewis Student Center. The entire Georgia Tech community is encouraged to attend the competition, which occurs as the finale of the 2024 Grad Student Appreciation Week. 3MT will also be streamed online and can be viewed at https://gatech.zoom.us/j/98696536715 .  Audience members and online viewers can vote for their favorite presenter to win the People’s Choice Award.  

Ph.D. winners can win up to $2,000 in research travel grants. The master's winner will receive a $1,000 research travel grant.   

Tech’s 3MT competition is coordinated by the Office of Graduate Education in partnership with the Center for Teaching and Learning (CTL), The Naugle Communications Center, and the Language Institute.  

For more information, visit grad.gatech.edu/3mt . 

Brittani Hill | Marketing and Communications Manager 

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How to Write a Dissertation Proposal with Structure & Steps

Published by Anastasia Lois at August 14th, 2021 , Revised On October 26, 2023

“A dissertation proposal is a stepping stone towards writing the final dissertation paper. It’s a unique document  that informs the reader of the aim & objectives of dissertation research and   its course of action.”

The main purpose of a proposal paper is to showcase to your supervisor or dissertation committee members that your dissertation research will add value to existing knowledge in your area of study.

Although the exact structure of a dissertation proposal may vary depending on your academic level, academic subject, and size of the paper, the contents remain pretty much the same.

However, it will still make sense to consult with your supervisor about the proposal formatting and structuring guidelines before working on your dissertation proposal paper.

You may lose out on scoring some important marks if your proposal paper does not follow your department’s specific rules. Here are some tips for you on how to structure a dissertation proposal paper.

Tips on Completing a Dissertation Proposal in Due Time

Consult your supervisor or department to find out how much time you have to  complete your dissertation proposal . Each graduate program is different, so you must adhere to the specific rules to avoid unwelcome surprises.

Depending on the degree program you are enrolled in, you may have to start working on your chosen topic  right away, or you might need to deal with some  assignments  and  exams  first.

You can learn about the rules and timelines concerning your dissertation project on the university’s online portal. If you are still unsure, it will be best to speak with your department’s admin clerk, the program head, or supervisor.

Look for Proposal Structural Requirements in the Guidelines

Most academic institutions will provide precise rules for structuring your dissertation proposal in terms of the document’s content and how to arrange it.  If you have not figured out these requirements, you must speak with your supervisor to find out what they recommend. Typical contents and structure of a dissertation proposal include the following;

• Statement of the Problem
• Background/Rationale
• Introduction (Justifying your Research)
• Research Questions or  Hypothesis  (Research aim and objectives)
• Literature Review
• Proposed Methodology
• Opportunities and Limitations

Project Schedule

Have an unhelpful dissertation project supervisor? Here is some advice to  help you deal with an uncompromising dissertation advisor.

How Long is a Dissertation Proposal?

The length of your dissertation proposal will depend on your degree program and your research topic. PhD-level dissertation proposals are much longer in terms of word count than Bachelors’s and Master’s level proposals.

• Bachelor’s level dissertation proposals are about 5-6 pages long.
• Masters and Ph.D. level proposals’ length varies from 15-25 pages depending on the academic subject and degree program’s specifications.
• If the word count or page length expectation is not mentioned in the dissertation handbook or the guidelines on the university’s website, you should check with your supervisor or program coordinator for a clear understanding of this particular requirement.

The proposals we write have:

• Precision and Clarity
• Zero Plagiarism
• High-level Encryption
• Authentic Sources

Dissertation Proposal Formatting

Formatting your dissertation proposal will also depend on your program’s specific guidelines and your research area. Find the exact guidelines for formatting cover sheets and title pages, referencing style, notes, bibliography, margin sizes, page numbers, and fonts. Again if you are unsure about anything, it is recommended to consult with your project advisor.

Find out About the Approval Criteria

The process of  writing your dissertation proposal paper  and getting acceptance from the committee of members of your supervisor is tricky.

Consult your department’s academic assistant, supervisor, or program chair to learn about all the process stages. Here are a couple of points you will need to be aware of:

• You might be required to have your chosen research topic approved by your academic supervisor or department chair.
• Submit your proposal and have it formally signed and approved so you can continue with your research.

You may find the dissertation proposal writing process perplexing and challenging if this is the first time you are preparing such a document. All the essential elements of a dissertation proposal paper need to be present before submitting it for approval.

Any feedback received from the tutor or the supervising committee should be taken very seriously and incorporated into your planning for dissertation research. Do not start working on your final dissertation paper until your supervisor has accepted the proposal.

To help you organise your dissertation proposal paper correctly, we have detailed guidelines for structuring a dissertation proposal. Irrespective of the degree program you are developing your dissertation proposal for, you will find these guidelines equally important.

Our expert academics can produce a flawless dissertation proposal on your chosen topic. They can also suggest free topics in your area of study if you haven’t selected a topic. Order free topics here or get a quote for our proposal writing service here.

Select a Topic

Selecting an  appropriate topic is the key to having your research work recognised in your field of study. Make sure your chosen topic is relevant, interesting, and manageable.

Ideally, you would want to research a topic that previous researchers have not explored so you can contribute to knowledge on the academic subject.

But even if your topic has been well-researched previously, you can make your study stand out by tweaking the  research design  and  research questions  to add a new dimension to your research.

How to Choose a Suitable Research Topic

Here are some guidelines on how to choose a suitable research topic.

List all the topics that you find interesting and relevant to your area of study. PhD and MaMasters’sevel students are already well aware of their academic interests.

Bachelor students can consider unanswered questions that emerged from their past academic assignments and drove them to conduct a detailed investigation to find answers.

Follow this process, and you’ll be able to choose the most appropriate topic for your research. Not only will this make your dissertation unique, but it also increases the chances of your proposal being accepted in the first attempt.

• Think about all your past academic achievements and associations, such as any research notes you might have written for your classes, any unsettled questions from your previous academic assignments that left you wondering, and the material you learned in classes taught by professors.
• For example , you learned about how natural gas is supplied to households in the UK in one of your coursework assignments and now eagerly wish to know exactly how natural gas is processed at an industrial scale.

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Conduct initial research on your chosen topic(s). This will include reading authentic text material on the topic(s) to familiarise yourself with each potential topic. Doing so will help you figure out whether there really is a need to investigate your selected topics further.

Visit your university’s library or online academic databases such as ProQuest, EBSCO, QuickBase to find articles, journals, books, peer-reviewed articles, and thesis/dissertation papers (by other students) written on your possible research topic .

Ignore all academic sources that you find methodologically flawed or obsolete.  Visit our online research topics library to choose a topic relevant to your interests .

Consult your academic supervisor and show them your list of potential topics. Their advice will be crucial for deciding whether the topic you are interested in is appropriate and meets your degree program requirements.

It is recommended to set up an appointment with your supervisor to see them in person to discuss your potential topics, even though you can do the same in email too.

• If the topics you are interested in are too broad or lack focus, your supervisor will be able to guide you towards academic sources that could help narrow down your research.
• Having several topics in your list of potential topics will mean that you will have something to fall back onto if they don’t approve your first choice.

Narrow the Focus of your Research  – Once a topic has been mutually agreed upon between you and your academic supervisor, it is time to narrow down the focus. Hence, your research explores an aspect of the topic that has not been investigated before.

Spend as much time as possible examining different aspects of the topic to establish a research aim that would truly add value to the existing knowledge.

• For example, you were initially interested in studying the different natural gas process techniques in the UK on an industrial scale. But you noticed that the existing literature doesn’t count for one advanced gas processing method that helps the industry save millions of pounds every year. Hence, you decide to make that the focus of your research.
• Your topic could be too broad as you start your research, but as you dig deep into your research, the topic will continue to narrow and evolve. TIP – It is better to work on a topic that is too broad rather than on something there is not enough text material to work with.

Structure of a Dissertation Proposal

The key elements of a great dissertation proposal are explained in detail under this section ‘structure of a dissertation proposal’. Once you’ve finalised your topic, you need to switch to writing your dissertation proposal paper quickly. As previously mentioned, your proposal paper’s exact structure may vary depending on your university/college requirements.

A good dissertation proposal  title  will give the reader an insight into the aim/idea of your study. Describe the purpose and/or contents of your dissertation proposal paper in the fewest possible words.

A concise and focused title will help you gain the attention of the readers. However, you might need to adjust your title several times as you write the paper because your comprehensive research might continue to add new dimensions to your study.

• Your title must be as categorical as possible. For example, instead of “Natural Gas Processing Techniques in the UK”, use a more specific title like “Investigating various industrial natural gas processing technologies employed in the UK” so the reader can understand exactly what your research is about.

Write a brief executive summary or an abstract of your proposal if you have been asked to do so in the structural guidelines. Generally, the  abstract  is included in the final dissertation paper with a length of around 300-400 words.

If you have to write an abstract for your proposal, here are the key points that it must cover;

• The background to your research.
• Research questions that you wish to address.
• Your proposed methods of research, which will either test the hypothesis or address the research problem.
• The significance of your research as to how it will add value to the scientific or academic community.

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Introduction

This is your first chance to make a strong impression on the reader. Not only your  introduction  section should be engaging, contextually, but it is also supposed to provide a background to the topic and explain the  thesis problem .

Here is what the first paragraph of the introduction section should include:

• Explain your research idea and present a clear understanding as to why you’ve chosen this topic.
• Present a summary of the scope of your research study, taking into account the existing literature.
• Briefly describe the issues and specific problems your research aims to address!

In the next paragraphs, summarise  the statement of the problem . Explain what gap in the existing knowledge your research will fill and how your work will prove significant in your area of study.

For example, the focus of your research could be the stage of carbon monoxide removal from natural gas. Still, other similar studies do not sufficiently explore this aspect of natural gas processing technology.

Here is a comprehensive article on “ How to Write Introduction for Dissertation Paper .”

Aim & Objectives

This is the  most critical section of the proposal paper . List the  research questions  or the research objectives your study will address. When writing this particular section, it will make sense to think of the following questions:

• Are there any specific findings that you are expecting?
• What aspects of the topic have you decided not to investigate and why?
• How will your research contribute to the existing knowledge in your field?

Literature Review

The  literature review section  is your chance to state the key established research trends,  hypotheses , and theories on the subject. Demonstrate to the reader that your research is a unique contribution to your field because it explores the topic from a new angle.

In a dissertation proposal, you won’t be expected to provide an extensive list of all previous research studies on the topic. Still, all the key theories reported by other scholars should be briefly referred to.

Take into consideration the following when writing the literature review section:

• The gaps identified in the previous research studies on the topic which your own research aims to fill. State the limitations of previous studies, whether lacking sufficient evidence, invalid, or too broad.
• The key established research trends, theories, and hypotheses as reported by other researchers.
• Any specific arguments and/or methodologies that previous scholars used when investigating your topic.

Our expert dissertation proposal editors can improve the quality of your proposal paper to the First Class standard. Complete this short and simple order form here so we can get feedback from our writers.

Methodology

A focused and well-defined methodology in a proposal paper can help you explain to your readers  how you plan to conduct your research  and why  your chosen research design  can provide reliable answers to your research questions.

The choice of research design and analytical approach will depend on several factors, including but not limited to your area of study and research constraints.

Depending on your topic and the existing literature, you will need to decide whether your dissertation will be purely descriptive or use primary (quantitative/qualitative data) as part of the research design.

Any research limitations and ethical issues that you expect to deal with should be clearly stated. For example, you might not be able to use a large sample size of respondents due to financial constraints. Small sample size can undermine your research significance.

How to Write a First Class Dissertation Proposal or Research Proposal.

“If you’re unable to pull off a first-class proposal, we’re here to help. We at ResearchProspect make sure that our writers prepare a flawless dissertation proposal for you. Our highly qualified team of writers will also help you choose a relevant topic for your subject area. Get in touch with us today, and let us take care of all your dissertation worries! Learn more about our dissertation proposal writing service.

Some Masters and PhD level degree programs require students to include a project timeline or timetable to give readers an idea of how and when they plan to complete different stages of the project.

Project timeline can be a great planning tool, mainly if your research includes experiments, statistical analysis , designing, and primary data collection. However, it may have to be modified slightly as you progress into your research.

By no means is it a fixed program for carrying out your work. When developing the project timeline in your proposal, always consider the time needed for practical aspects of the research, such as travelling, experiments, and fieldwork.

Referencing and In-Text Citations

Underrated, but referencing is one of the most crucial aspects of preparing a proposal. You can think of your proposal as the first impression of your dissertation.

You would want everything to be perfect and in place, wouldn’t you? Thus, always make sure that your dissertation consists of all the necessary elements.

You will have to cite information and data that you include in your dissertation. So make sure that the references that you include are credible and authentic.

You can use well-known academic journals, official websites, past researches, and concepts presented by renowned authors and writers in the respective field.

The same rule applies to in-text citations. Make sure that you cite references accurately  according to the required referencing style  as mentioned in the guidelines.

References should back statistics, facts, and figures at all times. It is highly recommended to back every 100-200 words written with at least one academic reference. The quantity of references does not matter; however, the quality does.

These are the basic elements of a dissertation proposal. Taking care of all these sections will help you when you are confused about structuring a dissertation proposal. In addition to these steps, look for different  dissertation proposal examples  on your research topic. A  sample dissertation proposal  paper can provide a clear understanding of how to go about the “pro”osal stage” of”the dissertation project.

“If you’re unable to pull off a first-class proposal, we’re here to help. We at ResearchProspect make sure that our writers prepare a flawless dissertation proposal for you. Our highly qualified team of writers will also help you choose a relevant topic for your subject area. Get in touch with us today, and let us take care of all your dissertation worries! Learn more about our dissertation proposal writing service .”

Frequently Asked Questions

What is dissertation proposal in research.

A dissertation proposal in research outlines the planned study. It includes research objectives, methods, scope, and significance. It’s a blueprint that demonstrates the feasibility and value of the research, helping gain approval before proceeding with the full dissertation.

How do you write a dissertation proposal?

A dissertation proposal outlines your research topic, objectives, methodology, and potential significance. Start with a clear title, state your research question, detail the methods you will use to answer it, and highlight the contribution it will make to the field. Ensure it is well-researched, concise, and compelling to gain approval.

How long is a dissertation proposal?

A dissertation proposal’s length varies by field and institution. Typically, it ranges from 10 to 20 pages, but can be longer for complex topics. It includes an introduction, research question, literature review, methodology, and potential significance. Always consult department guidelines or advisors to ensure appropriate length and content.

What are the types of dissertation proposals?

Dissertation proposal types largely depend on the research’s nature and methodology. Common types include empirical (collecting data from the real world), non-empirical (theory or literature-based), and narrative (case studies). Each type dictates a different approach to data collection, analysis, and presentation, tailored to the subject and field of study.

You May Also Like

How to write a hypothesis for dissertation,? A hypothesis is a statement that can be tested with the help of experimental or theoretical research.

Here we explore what is research problem in dissertation with research problem examples to help you understand how and when to write a research problem.

This article is a step-by-step guide to how to write statement of a problem in research. The research problem will be half-solved by defining it correctly.

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Watch CBS News

What caused the Dali to slam into Baltimore's Francis Scott Key Bridge? What we know about what led up to the collapse

By Kerry Breen

Updated on: March 27, 2024 / 7:43 PM EDT / CBS News

Shocking video showed the moment a massive cargo ship collided with Baltimore's Francis Scott Key Bridge early Tuesday morning, sending parts of the decades-old suspension bridge, along with people and vehicles, into the Patapsco River. 

Six people who were on the bridge are missing and presumed dead , officials said late Tuesday. Two others were rescued from the water. All eight were construction workers who were repairing potholes on the bridge, officials said. There were 22 Indian nationals, including two pilots, aboard the cargo ship. 

Investigators and officials are now crafting a timeline of events, including what caused the Singapore-owned vessel , called the Dali, to hit the bridge just minutes after leaving port . Here's what we know so far. 

What caused the Dali to slam into the Francis Scott Key Bridge? 

The Dali, which was chartered by shipping giant Maersk and operated by Synergy Marine Group, hit the Francis Scott Key Bridge shortly after leaving the Port of Baltimore. 

An unclassified memo issued by CISA, the Cybersecurity and Infrastructure Security Agency, said the ship reported losing propulsion . Maryland Gov. Wes Moore said the ship's crew reported a "power issue." A spokesperson for the National Transportation Safety Board, which is investigating the crash, said the agency still needs to verify that the Dali lost power before striking the bridge column. 

Two U.S. officials told CBS News multiple alarms rang out on the ship, alerting pilots and crew to an issue on board. The crew ran several system tests to attempt to remedy the loss of propulsion from the motor, but the tests proved unsuccessful. At that point, the ship's pilots alerted the Maryland Department of Transportation and the Maryland Transit Authority. 

That alert allowed local officials to stop traffic on the bridge and likely saved lives , officials said. 

The ship's crew tried to deploy the anchor, though it remains unclear how much progress was made, multiple officials said. The massive ship is over 900 feet long and was moving at about 8 knots, or just over 9 miles per hour. Authorities said that speed is considered "very rapid." 

Captain Michael Burns, executive director of the Massachusetts Maritime Academy's Maritime Center for Responsible Energy, told CBS Boston  that stopping a cargo ship is difficult, especially in such a short time. 

"It's extremely challenging, and takes years of experience and training in order to be able to do this safely," he said. "It can take up to a mile for some of these ships to get stopped, depending on the circumstances, so we really need to think well out, miles ahead of the ship."

Why did the Dali lose propulsion? 

It's not clear what caused the vessel to lose propulsion, officials said. 

A spokesperson for the NTSB told CBS Baltimore that it had collected the ship's data recorder, and would review and analyze the material there to determine what happened aboard the vessel in the moments before the collision. 

That data recorder will also be used to establish a timeline of events. 

What happens when a ship loses propulsion? 

James Mercante, the president of the New York Board of Pilot Commissioners, told CBS News that a ship that has lost steering and power is essentially "a dead ship just being carried by the current or its own momentum." 

He highlighted a moment in the video of the crash that appears to show a "big, big puff of black, real dark black smoke" which might indicate that the vessel's power was "restored at the last minute" and that the pilot was "attempting to make an emergency maneuver" to avoid hitting the bridge. However, he emphasized that it would be difficult to stop the massive cargo ship, especially in such a short time. 

"It would take quite a while — probably the length of five [or] six football fields — to bring that ship to a stop, even after dropping the anchors, because of its power and momentum," said Mercante. "This is a behemoth." 

• Francis Scott Key Bridge
• Bridge Collapse

Kerry Breen is a reporter and news editor at CBSNews.com. A graduate of New York University's Arthur L. Carter School of Journalism, she previously worked at NBC News' TODAY Digital. She covers current events, breaking news and issues including substance use.

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Second temporary passage clears way for more smaller vessels past Key Bridge collapse site

Transcript: Baltimore Mayor Brandon Scott on "Face the Nation," March 31, 2024

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Fact Sheets Final CY 2025 Part D Redesign Program Instructions Fact Sheet

• Medicare Part D

Today, the Centers for Medicare & Medicaid Services (CMS) released the Final Calendar Year (CY) 2025 Part D Redesign Program Instructions (the Final Program Instructions) concurrently with the CY 2025 Medicare Advantage (MA) Capitation Rates and Part C and Part D Payment Policies (the Rate Announcement). The purpose of the Final Program Instructions is to provide interested parties with guidance for CY 2025 regarding, among other topics, the implementation of section 11201 of the Inflation Reduction Act of 2022 (IRA) (P.L. 117-169), signed into law on August 16, 2022, which made several amendments and additions to the Social Security Act (“the Act”) that affect the structure of the defined standard Part D drug benefit. 

The Final Program Instructions contain a detailed description of, and guidance related to, changes newly in place for CY 2025 made by the IRA, as well as guidance for CY 2023 Medical Loss Ratio (MLR) reporting related to the Inflation Reduction Act Subsidy Amount (IRASA). The Final Program Instructions are published concurrently with the Rate Announcement that, among other things, announces updates to Part D parameters, some of which are impacted by provisions in the Final Program Instructions. 

Following the publication of the CY 2025 Draft Program Instructions, it came to CMS’ attention that the methodology codified at 42 C.F.R. § 423.104(d)(2)(iv)(D)(3) will no longer be valid when the Initial Coverage Limit (ICL) is eliminated in 2025.  As such, CMS has included a new methodology in the Final Program Instructions to determine the specialty tier coinsurance/deductible ranges under the redesigned Part D benefit.  

Overview of Changes to the Part D Benefit: 

In CY 2025, the structure of the Part D benefit is updated to reflect provisions of the IRA that become effective on January 1, 2025. The CY 2025 updates include the following: 

• A newly defined standard Part D benefit design consisting of three phases: annual deductible, initial coverage, and catastrophic coverage; 
• A lower annual out-of-pocket (OOP) threshold of $2,000; 
• The sunset of the Coverage Gap Discount Program (CGDP) and establishment of the Manufacturer Discount Program (Discount Program); and
• Changes to the liability of enrollees, Part D sponsors, manufacturers, and CMS in the newly defined standard Part D benefit design. 

Summary of Key Policies in the Final Program Instructions :

Costs Counted Toward True Out-of-Pocket Costs (TrOOP)

TrOOP is the portion of spending on covered Part D drugs made by the beneficiary or on their behalf by certain third parties. The IRA updates which categories of payments count toward TrOOP spending. TrOOP is the spending that determines when a beneficiary enters the initial coverage phase, becomes an applicable beneficiary for the Discount Program, reaches the annual OOP threshold, and subsequently enters the catastrophic coverage phase. In addition to the third-party arrangements that already count toward TrOOP, the IRA specifically amends the definition of incurred costs that count toward TrOOP for CY 2025 to include payments for previously excluded supplemental benefits provided by Part D sponsors andEmployer Group Waiver Plans (EGWPs) and exclude payments under the new Discount Program. 

Creditable Coverage

Consistent with IRA changes, we are revising the regulatory definition of creditable coverage at § 423.56(b) to reflect that discounts paid under the Manufacturer Discount Program are not taken into account when determining actuarial value. Given various concerns raised by commenters and the significant changes to the Part D benefit for CY 2025 as a result of the redesign, CMS will continue to permit use of the creditable coverage simplified determination methodology, without modification to the existing parameters, for CY 2025 for non-EGWP group health plan sponsors not applying for the retiree drug subsidy under section 1860D-22(a) of the Act. The Final Program Instructions also specify that CMS will re-evaluate the continued use of the existing simplified determination methodology or establish a revised one for CY 2026 in future guidance.   

Policy for Drugs Not Subject to Defined Standard Deductible

In CY 2025, the IRA eliminates the coverage gap phase and the related CGDP and, in its place, establishes the new Discount Program. The IRA also alters the defined standard benefit to exempt certain drugs (certain insulins and vaccines) from the deductible. For CY 2025, if a beneficiary has not satisfied their plan deductible but has incurred sufficient TrOOP-eligible costs to satisfy the defined standard deductible, they will be both an applicable beneficiary under the Discount Program and deemed to have satisfied their plan deductible. If the beneficiary satisfies the plan’s deductible or utilizes a drug not subject to the deductible but is not eligible for the Discount Program because they have not incurred sufficient TrOOP-eligible costs to satisfy the defined standard deductible amount, then the Part D sponsor will be required to cover the portion of costs a manufacturer would have owed had Discount Program discounts begun.

Government Reinsurance Methodology

The IRA changes the government reinsurance calculation methodology for CY 2025 to be dependent on drug type. These changes to the reinsurance payment amount require CMS to revise the Direct and Indirect Remuneration (DIR) allocation methodology. Specifically, since the reinsurance amount must be calculated differently for different types of drugs, the DIR allocation methodology must correspondingly vary for different types of drugs in CY 2025. CMS will calculate the reinsurance subsidy separately for applicable and non-applicable drugs and allocate the share of DIR for applicable and non-applicable drugs based on their respective share of gross covered prescription drug costs that fall in the catastrophic phase.

EGWP Prospective Reinsurance Amount

Because the Part D redesign reduces the government reinsurance percentage in CY 2025, using the existing methodology for Part D Calendar Year EGWP prospective reinsurance payments would result in CMS prospectively paying significantly more than necessary for CY 2025. CMS would then need to recover sizable funds from EGWPs during the Part D payment reconciliation process. Therefore, CMS is updating the methodology to ensure that Part D Calendar Year EGWPs are paid a more appropriate prospective reinsurance amount in CY 2025. CMS will calculate the prospective reinsurance payments to all Part D Calendar Year EGWP sponsors using the weighted average of per-member-per-month (PMPM) prospective reinsurance amounts submitted by Part D sponsors for Enhanced Alternative (EA) plans as part of the Part D bid submissions for the payment year in question (for example, CMS will use CY 2025 Part D bids submitted in June 2024 to calculate prospective reinsurance payments for Calendar Year EGWPs for CY 2025).

Definition of EA Benefit Design

In CY 2025, the Part D benefit redesign provisions under the IRA limit the available options for sponsors to enhance their benefits to offer an EA plan to the following: 

• Coverage of drugs that are specifically excluded from Part D drug coverage; and/or
• Any one or more of the following changes that increase the actuarial value of benefits above the actuarial value of the defined standard prescription drug coverage:
• Reduction (or elimination) of the defined standard deductible
• Reduction of cost sharing in the initial coverage phase.

Because the Part D benefit redesign reduces available options for EA plan design, CMS reconsidered what constitutes a permissible EA benefit design. The Final Program Instructions establish a process for ensuring that individuals receive value relative to the defined standard benefit when they enroll in an EA plan. Specifically, for CY 2025, CMS will use the Part D Out-of-Pocket Costs (OOPC) model to estimate the value of EA plans relative to the value of the defined standard benefit. 

For more details on the updated structure of the defined standard Part D drug benefit, please see the notes and the graphic below. 

• Annual deductible . The enrollee pays 100% of their gross covered prescription drug costs (GCPDC) until the deductible of $590 for CY 2025 is met.
• Initial coverage . The enrollee pays 25% coinsurance for covered Part D drugs. The sponsor typically pays 65% of the cost of applicable drugs and 75% of the cost of all other covered Part D drugs. The manufacturer, through the Discount Program, typically covers 10% of the cost of applicable drugs. This phase ends when the enrollee has reached the annual OOP threshold of $2,000 for CY 2025. 
• Catastrophic. The enrollee pays no cost sharing for covered Part D drugs. Sponsors typically pay 60% of the costs of all covered Part D drugs. The manufacturer pays a discount, typically equal to 20%, for applicable drugs. CMS pays a reinsurance subsidy equal to 20% of the costs of applicable drugs and equivalent to 40% of the costs of all other covered Part D drugs that are not applicable drugs.

Part D Benefit in CY 2025 and Past Years (Non-Low Income Subsidy Beneficiary)

*The Discount Program is phased in for certain drugs of qualifying drug manufacturers during the initial coverage phase from 2025 through 2028 and in the catastrophic phase from 2025 through 2030. For drugs subject to the phase-in, Part D sponsors will be responsible for the additional cost that would have otherwise been covered by the manufacturer discount. 

For more information about topics related to the Part D Benefit Redesign, please go to  https://www.cms.gov/inflation-reduction-act-and-medicare/part-d-improvements .

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CMS News and Media Group Catherine Howden, Director Media Inquiries Form 202-690-6145