objectives in a research example

21 Research Objectives Examples (Copy and Paste)

Research objectives refer to the definitive statements made by researchers at the beginning of a research project detailing exactly what a research project aims to achieve.

These objectives are explicit goals clearly and concisely projected by the researcher to present a clear intention or course of action for his or her qualitative or quantitative study. 

Research objectives are typically nested under one overarching research aim. The objectives are the steps you’ll need to take in order to achieve the aim (see the examples below, for example, which demonstrate an aim followed by 3 objectives, which is what I recommend to my research students).

Research Objectives vs Research Aims

Research aim and research objectives are fundamental constituents of any study, fitting together like two pieces of the same puzzle.

The ‘research aim’ describes the overarching goal or purpose of the study (Kumar, 2019). This is usually a broad, high-level purpose statement, summing up the central question that the research intends to answer.

Example of an Overarching Research Aim:

“The aim of this study is to explore the impact of climate change on crop productivity.” 

Comparatively, ‘research objectives’ are concrete goals that underpin the research aim, providing stepwise actions to achieve the aim.

Objectives break the primary aim into manageable, focused pieces, and are usually characterized as being more specific, measurable, achievable, relevant, and time-bound (SMART).

Examples of Specific Research Objectives:

1. “To examine the effects of rising temperatures on the yield of rice crops during the upcoming growth season.” 2. “To assess changes in rainfall patterns in major agricultural regions over the first decade of the twenty-first century (2000-2010).” 3. “To analyze the impact of changing weather patterns on crop diseases within the same timeframe.”

The distinction between these two terms, though subtle, is significant for successfully conducting a study. The research aim provides the study with direction, while the research objectives set the path to achieving this aim, thereby ensuring the study’s efficiency and effectiveness.

How to Write Research Objectives

I usually recommend to my students that they use the SMART framework to create their research objectives.

SMART is an acronym standing for Specific, Measurable, Achievable, Relevant, and Time-bound. It provides a clear method of defining solid research objectives and helps students know where to start in writing their objectives (Locke & Latham, 2013).

Each element of this acronym adds a distinct dimension to the framework, aiding in the creation of comprehensive, well-delineated objectives.

Here is each step:

• Specific : We need to avoid ambiguity in our objectives. They need to be clear and precise (Doran, 1981). For instance, rather than stating the objective as “to study the effects of social media,” a more focused detail would be “to examine the effects of social media use (Facebook, Instagram, and Twitter) on the academic performance of college students.”
• Measurable: The measurable attribute provides a clear criterion to determine if the objective has been met (Locke & Latham, 2013). A quantifiable element, such as a percentage or a number, adds a measurable quality. For example, “to increase response rate to the annual customer survey by 10%,” makes it easier to ascertain achievement.
• Achievable: The achievable aspect encourages researchers to craft realistic objectives, resembling a self-check mechanism to ensure the objectives align with the scope and resources at disposal (Doran, 1981). For example, “to interview 25 participants selected randomly from a population of 100” is an attainable objective as long as the researcher has access to these participants.
• Relevance : Relevance, the fourth element, compels the researcher to tailor the objectives in alignment with overarching goals of the study (Locke & Latham, 2013). This is extremely important – each objective must help you meet your overall one-sentence ‘aim’ in your study.
• Time-Bound: Lastly, the time-bound element fosters a sense of urgency and prioritization, preventing procrastination and enhancing productivity (Doran, 1981). “To analyze the effect of laptop use in lectures on student engagement over the course of two semesters this year” expresses a clear deadline, thus serving as a motivator for timely completion.

You’re not expected to fit every single element of the SMART framework in one objective, but across your objectives, try to touch on each of the five components.

Research Objectives Examples

1. Field: Psychology

Aim: To explore the impact of sleep deprivation on cognitive performance in college students.

• Objective 1: To compare cognitive test scores of students with less than six hours of sleep and those with 8 or more hours of sleep.
• Objective 2: To investigate the relationship between class grades and reported sleep duration.
• Objective 3: To survey student perceptions and experiences on how sleep deprivation affects their cognitive capabilities.

2. Field: Environmental Science

Aim: To understand the effects of urban green spaces on human well-being in a metropolitan city.

• Objective 1: To assess the physical and mental health benefits of regular exposure to urban green spaces.
• Objective 2: To evaluate the social impacts of urban green spaces on community interactions.
• Objective 3: To examine patterns of use for different types of urban green spaces. 

3. Field: Technology

Aim: To investigate the influence of using social media on productivity in the workplace.

• Objective 1: To measure the amount of time spent on social media during work hours.
• Objective 2: To evaluate the perceived impact of social media use on task completion and work efficiency.
• Objective 3: To explore whether company policies on social media usage correlate with different patterns of productivity.

4. Field: Education

Aim: To examine the effectiveness of online vs traditional face-to-face learning on student engagement and achievement.

• Objective 1: To compare student grades between the groups exposed to online and traditional face-to-face learning.
• Objective 2: To assess student engagement levels in both learning environments.
• Objective 3: To collate student perceptions and preferences regarding both learning methods.

5. Field: Health

Aim: To determine the impact of a Mediterranean diet on cardiac health among adults over 50.

• Objective 1: To assess changes in cardiovascular health metrics after following a Mediterranean diet for six months.
• Objective 2: To compare these health metrics with a similar group who follow their regular diet.
• Objective 3: To document participants’ experiences and adherence to the Mediterranean diet.

6. Field: Environmental Science

Aim: To analyze the impact of urban farming on community sustainability.

• Objective 1: To document the types and quantity of food produced through urban farming initiatives.
• Objective 2: To assess the effect of urban farming on local communities’ access to fresh produce.
• Objective 3: To examine the social dynamics and cooperative relationships in the creating and maintaining of urban farms.

7. Field: Sociology

Aim: To investigate the influence of home offices on work-life balance during remote work.

• Objective 1: To survey remote workers on their perceptions of work-life balance since setting up home offices.
• Objective 2: To conduct an observational study of daily work routines and family interactions in a home office setting.
• Objective 3: To assess the correlation, if any, between physical boundaries of workspaces and mental boundaries for work in the home setting.

8. Field: Economics

Aim: To evaluate the effects of minimum wage increases on small businesses.

• Objective 1: To analyze cost structures, pricing changes, and profitability of small businesses before and after minimum wage increases.
• Objective 2: To survey small business owners on the strategies they employ to navigate minimum wage increases.
• Objective 3: To examine employment trends in small businesses in response to wage increase legislation.

9. Field: Education

Aim: To explore the role of extracurricular activities in promoting soft skills among high school students.

• Objective 1: To assess the variety of soft skills developed through different types of extracurricular activities.
• Objective 2: To compare self-reported soft skills between students who participate in extracurricular activities and those who do not.
• Objective 3: To investigate the teachers’ perspectives on the contribution of extracurricular activities to students’ skill development.

10. Field: Technology

Aim: To assess the impact of virtual reality (VR) technology on the tourism industry.

• Objective 1: To document the types and popularity of VR experiences available in the tourism market.
• Objective 2: To survey tourists on their interest levels and satisfaction rates with VR tourism experiences.
• Objective 3: To determine whether VR tourism experiences correlate with increased interest in real-life travel to the simulated destinations.

11. Field: Biochemistry

Aim: To examine the role of antioxidants in preventing cellular damage.

• Objective 1: To identify the types and quantities of antioxidants in common fruits and vegetables.
• Objective 2: To determine the effects of various antioxidants on free radical neutralization in controlled lab tests.
• Objective 3: To investigate potential beneficial impacts of antioxidant-rich diets on long-term cellular health.

12. Field: Linguistics

Aim: To determine the influence of early exposure to multiple languages on cognitive development in children.

• Objective 1: To assess cognitive development milestones in monolingual and multilingual children.
• Objective 2: To document the number and intensity of language exposures for each group in the study.
• Objective 3: To investigate the specific cognitive advantages, if any, enjoyed by multilingual children.

13. Field: Art History

Aim: To explore the impact of the Renaissance period on modern-day art trends.

• Objective 1: To identify key characteristics and styles of Renaissance art.
• Objective 2: To analyze modern art pieces for the influence of the Renaissance style.
• Objective 3: To survey modern-day artists for their inspirations and the influence of historical art movements on their work.

14. Field: Cybersecurity

Aim: To assess the effectiveness of two-factor authentication (2FA) in preventing unauthorized system access.

• Objective 1: To measure the frequency of unauthorized access attempts before and after the introduction of 2FA.
• Objective 2: To survey users about their experiences and challenges with 2FA implementation.
• Objective 3: To evaluate the efficacy of different types of 2FA (SMS-based, authenticator apps, biometrics, etc.).

15. Field: Cultural Studies

Aim: To analyze the role of music in cultural identity formation among ethnic minorities.

• Objective 1: To document the types and frequency of traditional music practices within selected ethnic minority communities.
• Objective 2: To survey community members on the role of music in their personal and communal identity.
• Objective 3: To explore the resilience and transmission of traditional music practices in contemporary society.

16. Field: Astronomy

Aim: To explore the impact of solar activity on satellite communication.

• Objective 1: To categorize different types of solar activities and their frequencies of occurrence.
• Objective 2: To ascertain how variations in solar activity may influence satellite communication.
• Objective 3: To investigate preventative and damage-control measures currently in place during periods of high solar activity.

17. Field: Literature

Aim: To examine narrative techniques in contemporary graphic novels.

• Objective 1: To identify a range of narrative techniques employed in this genre.
• Objective 2: To analyze the ways in which these narrative techniques engage readers and affect story interpretation.
• Objective 3: To compare narrative techniques in graphic novels to those found in traditional printed novels.

18. Field: Renewable Energy

Aim: To investigate the feasibility of solar energy as a primary renewable resource within urban areas.

• Objective 1: To quantify the average sunlight hours across urban areas in different climatic zones. 
• Objective 2: To calculate the potential solar energy that could be harnessed within these areas.
• Objective 3: To identify barriers or challenges to widespread solar energy implementation in urban settings and potential solutions.

19. Field: Sports Science

Aim: To evaluate the role of pre-game rituals in athlete performance.

• Objective 1: To identify the variety and frequency of pre-game rituals among professional athletes in several sports.
• Objective 2: To measure the impact of pre-game rituals on individual athletes’ performance metrics.
• Objective 3: To examine the psychological mechanisms that might explain the effects (if any) of pre-game ritual on performance.

20. Field: Ecology

Aim: To investigate the effects of urban noise pollution on bird populations.

• Objective 1: To record and quantify urban noise levels in various bird habitats.
• Objective 2: To measure bird population densities in relation to noise levels.
• Objective 3: To determine any changes in bird behavior or vocalization linked to noise levels.

21. Field: Food Science

Aim: To examine the influence of cooking methods on the nutritional value of vegetables.

• Objective 1: To identify the nutrient content of various vegetables both raw and after different cooking processes.
• Objective 2: To compare the effect of various cooking methods on the nutrient retention of these vegetables.
• Objective 3: To propose cooking strategies that optimize nutrient retention.

The Importance of Research Objectives

The importance of research objectives cannot be overstated. In essence, these guideposts articulate what the researcher aims to discover, understand, or examine (Kothari, 2014).

When drafting research objectives, it’s essential to make them simple and comprehensible, specific to the point of being quantifiable where possible, achievable in a practical sense, relevant to the chosen research question, and time-constrained to ensure efficient progress (Kumar, 2019). 

Remember that a good research objective is integral to the success of your project, offering a clear path forward for setting out a research design , and serving as the bedrock of your study plan. Each objective must distinctly address a different dimension of your research question or problem (Kothari, 2014). Always bear in mind that the ultimate purpose of your research objectives is to succinctly encapsulate your aims in the clearest way possible, facilitating a coherent, comprehensive and rational approach to your planned study, and furnishing a scientific roadmap for your journey into the depths of knowledge and research (Kumar, 2019). 

Kothari, C.R (2014). Research Methodology: Methods and Techniques . New Delhi: New Age International.

Kumar, R. (2019). Research Methodology: A Step-by-Step Guide for Beginners .New York: SAGE Publications.

Doran, G. T. (1981). There’s a S.M.A.R.T. way to write management’s goals and objectives. Management review, 70 (11), 35-36.

Locke, E. A., & Latham, G. P. (2013). New Developments in Goal Setting and Task Performance . New York: Routledge.

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Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 5 Top Tips for Succeeding at University
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Research Aims, Objectives & Questions

The “Golden Thread” Explained Simply (+ Examples)

By: David Phair (PhD) and Alexandra Shaeffer (PhD) | June 2022

The research aims , objectives and research questions (collectively called the “golden thread”) are arguably the most important thing you need to get right when you’re crafting a research proposal , dissertation or thesis . We receive questions almost every day about this “holy trinity” of research and there’s certainly a lot of confusion out there, so we’ve crafted this post to help you navigate your way through the fog.

Overview: The Golden Thread

• What is the golden thread
• What are research aims ( examples )
• What are research objectives ( examples )
• What are research questions ( examples )
• The importance of alignment in the golden thread

What is the “golden thread”?  

The golden thread simply refers to the collective research aims , research objectives , and research questions for any given project (i.e., a dissertation, thesis, or research paper ). These three elements are bundled together because it’s extremely important that they align with each other, and that the entire research project aligns with them.

Importantly, the golden thread needs to weave its way through the entirety of any research project , from start to end. In other words, it needs to be very clearly defined right at the beginning of the project (the topic ideation and proposal stage) and it needs to inform almost every decision throughout the rest of the project. For example, your research design and methodology will be heavily influenced by the golden thread (we’ll explain this in more detail later), as well as your literature review.

The research aims, objectives and research questions (the golden thread) define the focus and scope ( the delimitations ) of your research project. In other words, they help ringfence your dissertation or thesis to a relatively narrow domain, so that you can “go deep” and really dig into a specific problem or opportunity. They also help keep you on track , as they act as a litmus test for relevance. In other words, if you’re ever unsure whether to include something in your document, simply ask yourself the question, “does this contribute toward my research aims, objectives or questions?”. If it doesn’t, chances are you can drop it.

Alright, enough of the fluffy, conceptual stuff. Let’s get down to business and look at what exactly the research aims, objectives and questions are and outline a few examples to bring these concepts to life.

Research Aims: What are they?

Simply put, the research aim(s) is a statement that reflects the broad overarching goal (s) of the research project. Research aims are fairly high-level (low resolution) as they outline the general direction of the research and what it’s trying to achieve .

Research Aims: Examples  

True to the name, research aims usually start with the wording “this research aims to…”, “this research seeks to…”, and so on. For example:

“This research aims to explore employee experiences of digital transformation in retail HR.”   “This study sets out to assess the interaction between student support and self-care on well-being in engineering graduate students”  

As you can see, these research aims provide a high-level description of what the study is about and what it seeks to achieve. They’re not hyper-specific or action-oriented, but they’re clear about what the study’s focus is and what is being investigated.

Need a helping hand?

Research Objectives: What are they?

The research objectives take the research aims and make them more practical and actionable . In other words, the research objectives showcase the steps that the researcher will take to achieve the research aims.

The research objectives need to be far more specific (higher resolution) and actionable than the research aims. In fact, it’s always a good idea to craft your research objectives using the “SMART” criteria. In other words, they should be specific, measurable, achievable, relevant and time-bound”.

Research Objectives: Examples  

Let’s look at two examples of research objectives. We’ll stick with the topic and research aims we mentioned previously.  

For the digital transformation topic:

To observe the retail HR employees throughout the digital transformation. To assess employee perceptions of digital transformation in retail HR. To identify the barriers and facilitators of digital transformation in retail HR.

And for the student wellness topic:

To determine whether student self-care predicts the well-being score of engineering graduate students. To determine whether student support predicts the well-being score of engineering students. To assess the interaction between student self-care and student support when predicting well-being in engineering graduate students.

  As you can see, these research objectives clearly align with the previously mentioned research aims and effectively translate the low-resolution aims into (comparatively) higher-resolution objectives and action points . They give the research project a clear focus and present something that resembles a research-based “to-do” list.

Research Questions: What are they?

Finally, we arrive at the all-important research questions. The research questions are, as the name suggests, the key questions that your study will seek to answer . Simply put, they are the core purpose of your dissertation, thesis, or research project. You’ll present them at the beginning of your document (either in the introduction chapter or literature review chapter) and you’ll answer them at the end of your document (typically in the discussion and conclusion chapters).  

The research questions will be the driving force throughout the research process. For example, in the literature review chapter, you’ll assess the relevance of any given resource based on whether it helps you move towards answering your research questions. Similarly, your methodology and research design will be heavily influenced by the nature of your research questions. For instance, research questions that are exploratory in nature will usually make use of a qualitative approach, whereas questions that relate to measurement or relationship testing will make use of a quantitative approach.  

Let’s look at some examples of research questions to make this more tangible.

Research Questions: Examples  

Again, we’ll stick with the research aims and research objectives we mentioned previously.  

For the digital transformation topic (which would be qualitative in nature):

How do employees perceive digital transformation in retail HR? What are the barriers and facilitators of digital transformation in retail HR?  

And for the student wellness topic (which would be quantitative in nature):

Does student self-care predict the well-being scores of engineering graduate students? Does student support predict the well-being scores of engineering students? Do student self-care and student support interact when predicting well-being in engineering graduate students?  

You’ll probably notice that there’s quite a formulaic approach to this. In other words, the research questions are basically the research objectives “converted” into question format. While that is true most of the time, it’s not always the case. For example, the first research objective for the digital transformation topic was more or less a step on the path toward the other objectives, and as such, it didn’t warrant its own research question.  

So, don’t rush your research questions and sloppily reword your objectives as questions. Carefully think about what exactly you’re trying to achieve (i.e. your research aim) and the objectives you’ve set out, then craft a set of well-aligned research questions . Also, keep in mind that this can be a somewhat iterative process , where you go back and tweak research objectives and aims to ensure tight alignment throughout the golden thread.

The importance of strong alignment 

Alignment is the keyword here and we have to stress its importance . Simply put, you need to make sure that there is a very tight alignment between all three pieces of the golden thread. If your research aims and research questions don’t align, for example, your project will be pulling in different directions and will lack focus . This is a common problem students face and can cause many headaches (and tears), so be warned.

Take the time to carefully craft your research aims, objectives and research questions before you run off down the research path. Ideally, get your research supervisor/advisor to review and comment on your golden thread before you invest significant time into your project, and certainly before you start collecting data .  

Recap: The golden thread

In this post, we unpacked the golden thread of research, consisting of the research aims , research objectives and research questions . You can jump back to any section using the links below.

As always, feel free to leave a comment below – we always love to hear from you. Also, if you’re interested in 1-on-1 support, take a look at our private coaching service here.

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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37 Comments

Thank you very much for your great effort put. As an Undergraduate taking Demographic Research & Methodology, I’ve been trying so hard to understand clearly what is a Research Question, Research Aim and the Objectives in a research and the relationship between them etc. But as for now I’m thankful that you’ve solved my problem.

Well appreciated. This has helped me greatly in doing my dissertation.

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I am very happy to have carefully gone through this well researched article.

Infact,I used to be phobia about anything research, because of my poor understanding of the concepts.

Now,I get to know that my research question is the same as my research objective(s) rephrased in question format.

I please I would need a follow up on the subject,as I intends to join the team of researchers. Thanks once again.

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i found this document so useful towards my study in research methods. thanks so much.

This is my 2nd read topic in your course and I should commend the simplified explanations of each part. I’m beginning to understand and absorb the use of each part of a dissertation/thesis. I’ll keep on reading your free course and might be able to avail the training course! Kudos!

Thank you! Better put that my lecture and helped to easily understand the basics which I feel often get brushed over when beginning dissertation work.

This is quite helpful. I like how the Golden thread has been explained and the needed alignment.

This is quite helpful. I really appreciate!

The article made it simple for researcher students to differentiate between three concepts.

Very innovative and educational in approach to conducting research.

I am very impressed with all these terminology, as I am a fresh student for post graduate, I am highly guided and I promised to continue making consultation when the need arise. Thanks a lot.

A very helpful piece. thanks, I really appreciate it .

Very well explained, and it might be helpful to many people like me.

Wish i had found this (and other) resource(s) at the beginning of my PhD journey… not in my writing up year… 😩 Anyways… just a quick question as i’m having some issues ordering my “golden thread”…. does it matter in what order you mention them? i.e., is it always first aims, then objectives, and finally the questions? or can you first mention the research questions and then the aims and objectives?

Thank you for a very simple explanation that builds upon the concepts in a very logical manner. Just prior to this, I read the research hypothesis article, which was equally very good. This met my primary objective.

My secondary objective was to understand the difference between research questions and research hypothesis, and in which context to use which one. However, I am still not clear on this. Can you kindly please guide?

In research, a research question is a clear and specific inquiry that the researcher wants to answer, while a research hypothesis is a tentative statement or prediction about the relationship between variables or the expected outcome of the study. Research questions are broader and guide the overall study, while hypotheses are specific and testable statements used in quantitative research. Research questions identify the problem, while hypotheses provide a focus for testing in the study.

Exactly what I need in this research journey, I look forward to more of your coaching videos.

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What data source in writing dissertation/Thesis requires?

What is data source covers when writing dessertation/thesis

This is quite useful thanks

I’m excited and thankful. I got so much value which will help me progress in my thesis.

where are the locations of the reserch statement, research objective and research question in a reserach paper? Can you write an ouline that defines their places in the researh paper?

Very helpful and important tips on Aims, Objectives and Questions.

Thank you so much for making research aim, research objectives and research question so clear. This will be helpful to me as i continue with my thesis.

Thanks much for this content. I learned a lot. And I am inspired to learn more. I am still struggling with my preparation for dissertation outline/proposal. But I consistently follow contents and tutorials and the new FB of GRAD Coach. Hope to really become confident in writing my dissertation and successfully defend it.

As a researcher and lecturer, I find splitting research goals into research aims, objectives, and questions is unnecessarily bureaucratic and confusing for students. For most biomedical research projects, including ‘real research’, 1-3 research questions will suffice (numbers may differ by discipline).

Awesome! Very important resources and presented in an informative way to easily understand the golden thread. Indeed, thank you so much.

Well explained

The blog article on research aims, objectives, and questions by Grad Coach is a clear and insightful guide that aligns with my experiences in academic research. The article effectively breaks down the often complex concepts of research aims and objectives, providing a straightforward and accessible explanation. Drawing from my own research endeavors, I appreciate the practical tips offered, such as the need for specificity and clarity when formulating research questions. The article serves as a valuable resource for students and researchers, offering a concise roadmap for crafting well-defined research goals and objectives. Whether you’re a novice or an experienced researcher, this article provides practical insights that contribute to the foundational aspects of a successful research endeavor.

A great thanks for you. it is really amazing explanation. I grasp a lot and one step up to research knowledge.

I really found these tips helpful. Thank you very much Grad Coach.

I found this article helpful. Thanks for sharing this.

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Home » Research Objectives – Types, Examples and Writing Guide

Research Objectives – Types, Examples and Writing Guide

Table of Contents

Research Objectives

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

Types of Research Objectives

Here are the different types of research objectives in research:

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

How to Write Research Objectives

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

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

Example of Research Objectives

Examples of research objectives Could be:

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

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

When to Write Research Objectives

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

Purpose of Research Objectives

Some of the main purposes of research objectives include:

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

Advantages of Research Objectives

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

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

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• 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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Writing the Research Objectives: 5 Straightforward Examples

The research objective of a research proposal or scientific article defines the direction or content of a research investigation. Without the research objectives, the proposal or research paper is in disarray. It is like a fisherman riding on a boat without any purpose and with no destination in sight. Therefore, at the beginning of any research venture, the researcher must be clear about what he or she intends to do or achieve in conducting a study.

How do you define the objectives of a study? What are the uses of the research objective? How would a researcher write this essential part of the research? This article aims to provide answers to these questions.

Table of Contents

Definition of a research objective.

A research objective describes, in a few words, the result of the research project after its implementation. It answers the question,

“ What does the researcher want or hope to achieve at the end of the research project.”  

The research objective provides direction to the performance of the study.

What are the Uses of the Research Objective?

The uses of the research objective are enumerated below:

• serves as the researcher’s guide in identifying the appropriate research design,
• identifies the variables of the study, and
• specifies the data collection procedure and the corresponding analysis for the data generated.

The research design serves as the “blueprint” for the research investigation. The University of Southern California describes the different types of research design extensively. It details the data to be gathered, data collection procedure, data measurement, and statistical tests to use in the analysis.

The variables of the study include those factors that the researcher wants to evaluate in the study. These variables narrow down the research to several manageable components to see differences or correlations between them.

Specifying the data collection procedure ensures data accuracy and integrity . Thus, the probability of error is minimized. Generalizations or conclusions based on valid arguments founded on reliable data strengthens research findings on particular issues and problems.

In data mining activities where large data sets are involved, the research objective plays a crucial role. Without a clear objective to guide the machine learning process, the desired outcomes will not be met.

How is the Research Objective Written?

A research objective must be achievable, i.e., it must be framed keeping in mind the available time, infrastructure required for research, and other resources.

Before forming a research objective, you should read about all the developments in your area of research and find gaps in knowledge that need to be addressed. Readings will help you come up with suitable objectives for your research project.

5 Examples of Research Objectives

The following examples of research objectives based on several published studies on various topics demonstrate how the research objectives are written:

• This study aims to find out if there is a difference in quiz scores between students exposed to direct instruction and flipped classrooms (Webb and Doman, 2016).
• This study seeks to examine the extent, range, and method of coral reef rehabilitation projects in five shallow reef areas adjacent to popular tourist destinations in the Philippines (Yeemin et al ., 2006).
• This study aims to investigate species richness of mammal communities in five protected areas over the past 20 years (Evans et al ., 2006).
• This study aims to clarify the demographic, epidemiological, clinical, and radiological features of 2019-nCoV patients with other causes of pneumonia (Zhao et al ., 2020).
• This research aims to assess species extinction risks for sample regions that cover some 20% of the Earth’s terrestrial surface.

Finally, writing the research objectives requires constant practice, experience, and knowledge about the topic investigated. Clearly written objectives save time, money, and effort.

Once you have a clear idea of your research objectives, you can now develop your conceptual framework which is a crucial element of your research paper as it guides the flow of your research. The conceptual framework will help you develop your methodology and statistical tests.

I wrote a detailed, step-by-step guide on how to develop a conceptual framework with illustration in my post titled “ Conceptual Framework: A Step by Step Guide on How to Make One. “

Evans, K. L., Rodrigues, A. S., Chown, S. L., & Gaston, K. J. (2006). Protected areas and regional avian species richness in South Africa.  Biology letters ,  2 (2), 184-188.

Thomas, C. D., Cameron, A., Green, R. E., Bakkenes, M., Beaumont, L. J., Collingham, Y. C., … & Hughes, L. (2004). Extinction risk from climate change. Nature, 427(6970), 145-148.

Webb, M., & Doman, E. (2016). Does the Flipped Classroom Lead to Increased Gains on Learning Outcomes in ESL/EFL Contexts?. CATESOL Journal, 28(1), 39-67.

Yeemin, T., Sutthacheep, M., & Pettongma, R. (2006). Coral reef restoration projects in Thailand.  Ocean & Coastal Management ,  49 (9-10), 562-575.

Zhao, D., Yao, F., Wang, L., Zheng, L., Gao, Y., Ye, J., Guo, F., Zhao, H. & Gao, R. (2020). A comparative study on the clinical features of COVID-19 pneumonia to other pneumonias, Clinical Infectious Diseases , ciaa247, https://doi.org/10.1093/cid/ciaa247

© 2020 March 23 P. A. Regoniel Updated 17 November 2020 | Updated 18 January 2024

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About the author, patrick regoniel.

Dr. Regoniel, a faculty member of the graduate school, served as consultant to various environmental research and development projects covering issues and concerns on climate change, coral reef resources and management, economic valuation of environmental and natural resources, mining, and waste management and pollution. He has extensive experience on applied statistics, systems modelling and analysis, an avid practitioner of LaTeX, and a multidisciplinary web developer. He leverages pioneering AI-powered content creation tools to produce unique and comprehensive articles in this website.

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Writing Effective Research Aims and Objectives

• By: Margaret-Anne Houston , Marissa McDonagh Edited by: Margaret-Anne Houston
• Product: Sage Research Methods: Business
• Publisher: SAGE Publications Ltd
• Publication year: 2023
• Online pub date: March 21, 2023
• Discipline: Business and Management
• Methods: Research questions , Writing research , Research design
• DOI: https:// doi. org/10.4135/9781529668216
• Keywords: fuel poverty , social media Show all Show less
• Academic Level: Advanced Undergraduate Online ISBN: 9781529668216 More information Less information

The writing of effective research aims and objectives can cause confusion and concern to new and experienced researchers and learners. This step in your research journey is usually the first written method used to convey your research idea to your tutor. Therefore, aims and objectives should clearly convey your topic, academic foundation, and research design. In order to write effective research aims and objectives, researchers should consider all aspects of their proposed work. For example, the sample(s) to be approached for participation in the primary data collection. Identifying research objectives that are SMART is key to ensuring key aspects of the work are considered prior to any data collection. This includes consideration of access to samples and the ethics of researching the topic and research design. Finally, seeing your work as others will read it, can be an effective evaluation tool to ensure your own research objectives adequately capture and reflect your intended study. Therefore, this guide encourages you to consider common issues with identifying and writing research aims and objectives through consideration of examples.

Learning Outcomes

By the end of this guide, readers should be able to:

• Identify the meaning and purpose of a research aim within business research
• Understand the link between an effective research aim and the wider topic and literature/secondary sources, where appropriate
• Understand how to identify and write Specific, Measurable, Achievable, Realistic and Timely (SMART) Research objectives, research questions, and consideration of research hypothesis
• Recognize the link between writing an effective research aim and the research design. Write own research aim and objectives

Introduction

The writing of effective research aims and objectives can cause confusion and concern to new (and experienced!) researchers and learners. Attempting to identify the scope and focus of a project within a few specific statements, can take time and consideration of all aspects of your research design. If you are still unsure of your approach to your topic, or even the boundaries of the topic itself, this uncertainty can make the framing of an effective research aim seem like an uphill task.

However, even if this is your first time trying to convey your research idea within a few concise and precise statements, there are steps to take to ensure your work clearly communicates your meaning to your audience. This how-to-guide draws on examples of business topic research aims and objectives and explores techniques for reviewing their meaning. This active learning approach will enable you to grow confidence in framing and communicating your own research.

The importance of ensuring the research aim and objectives are not only reflective of the topic choice but are also achievable can be a fluid process, which in itself, can result in anxious researchers. Seeing your work as others will read it, can be an effective evaluation tool to ensure your own research objectives adequately capture and reflect your intended study. Therefore, this guide encourages you to consider common issues with identifying and writing research aims and objectives through consideration of examples.

Identify the Meaning and Purpose of a Research Aim with Business Research

Writing an effective research aim is an integral part of the research process. A research aim is a statement of intent. It should communicate your research goal clearly and should provide a focus for your work from the offset. It is important to differentiate between a research aim and the objectives. If a research aim tells the reader what you plan to achieve, then the research objectives should state how you would reach that goal. Often the objectives will provide a road map of the steps you will take in order to meet the research aim. Therefore, a research aim in business-related topics is typically a single sentence or even two, which conveys the overall purpose of the research-the end goal!

The terminology you use when writing your research aim is important. Note the following example aims from Business related topics:

• 1. This research aims to evaluate the lasting effects of lockdown and ‘work from home’ initiatives on productiveness in the financial service industry.
• 2. This research aims to establish a link between innovations in Artificial Intelligence (AI) and recruitment processes for The Royal Bank of Scotland.
• 3. This research aims to investigate to what extent Corporate Social Responsibility (CSR) initiatives can influence consumer behavior. A case study of Aldi UK.
• 4. This research aims to assess the effectiveness of technology companies’ risk management of cyber and information risks measured on the basis of supply chain resilience.
• 5. This research aims to explore the impact of Government funded initiatives to encourage social entrepreneurship in Scotland.

As evidenced above all of the aims stated contain verbs, these highlight how the research will be undertaken. Words such as to assess, to establish, to explore or to evaluate all reflect research analysis. This conveys your intention clearly to the reader and whilst it may not fully demonstrate exactly how the project will be undertaken, the verbs show what the goal is.

The objectives, which follow the aim, can help to show the exact ways the aim will be achieved, highlighting the research methods. It is important to think carefully about whether you plan to or will be to, come to a clear conclusion. Often it is not possible and this can be due to many factors such as the time or scope of the issue. For example, in the aims stated above number 2 is the only one that states it will ‘establish a link.’ This is because the aim is specific and measurable. The objectives should identify the specific processes it will examine and link to effective recruitment practices that are more effective than prior to AI being used.

However, for the other aims it is more appropriate to explore or investigate the topics, as opposed to ‘establishing’ or to ‘evidence an impact.’

Abbreviations are a useful way of shortening words or phrases and they can give writing a more coherent flow. It is worth noting that all abbreviations like AI or CSR should only be used when they are spelled out initially and if they appear frequently throughout your writing.

It is important to always check with your supervisor or course Handbook but typically, you should have a research question, a research aim, and objectives. The research question should capture what the issue is, often it will help to explain your research aim by offering a critical perspective. For example, if your research is to evaluate the effect of something then your question may be to what extent is that something works?

Finally, it is important to remember that the wording of your research aim may change slightly as your research progresses. Often students will modify the words to reflect what they are undertaking as the process develops.

Section Summary

• An effective research aim should clearly set out the goal of a project.
• Carefully consider the terminology you use at this stage, and ensure it reflects the outcome of the study.
• Remember a research aim can be fluid and the exact wording is likely to change as you progress through your research journey.

Understand the Link Between an Effective Research Aim and the Wider Topic and Literature/secondary Sources, Where Appropriate

When developing the research aim it is important to be engaged with the wider topic and associated literature and secondary sources from the offset. These sources will be crucial in helping you to tackle the topic successfully.

Identifying an idea for a research project can sometimes be a relatively simple first step in the research process. It is often narrowing the idea down to a research aim, which can be more difficult. A good way to start is to brainstorm ideas, think about what interests you the most about your studies, and note down keywords which can then be used as search terms. Researchers, at all levels of research and study, should consider information-seeking as a process through which they engage with the primary literature and secondary sources concerning their topic area. This will develop self-confidence in your ability to define the terms of reference of your work and studies. An inquiring mind and openness to a degree of flexibility of approach in these early stages of research, can be key to ensuring initial topic ideas can be molded into achievable research aims and objectives.

Research could be considered to be cyclical, not a one-off process. Therefore, in order to ensure a definable and achievable research topic, many projects use a mixture of sources. This requires a degree of confidence on the part of the researcher; to identify the relevant resources they require, a strategy for how to find them and also, a process for information management.

Many researchers will start with an online search for both academic and non-academic sources. The short-term success of this first step can be dictated by the choice of keywords and phrases. That is, those terms that the researcher believes are most relevant for, and most likely to come up with links to their research topic. However, caution should be employed in this initial task of online searching - this is an important opportunity to consider how we identify these specific keywords. A limited understanding of the area will be enhanced through further reading. It can allow the researcher to access previous studies in the same topic area and identify effective research methods. An informed research aim should be underpinned by reading and evaluating sources in relation to the research idea.

Using the research aims below as examples, note the sources required and some issues to consider for each source. By strategically linking your research aim to the wider area you will ensure your research is robust from the start.

• Reading combined with ongoing critical appraisal of associated sources can help to refine and focus your research aim and objectives.
• Think of your research as an ongoing process. Reading associated sources should be embedded in every stage of your research journey.
• Ensure you are acknowledging the wider research area and associated sources from the offset as this will help to refine and focus your research aim and objectives.

Understanding How to Identify SMART Research Objectives, Research Questions, and Consideration of Research Hypothesis

First-time final year undergraduates are normally expected to identify a research topic and research design that are realistic and achievable. Not only should they be realistic as topics but also achievable within a short time period when most learners have never undertaken such work previously. A common pitfall of many initial research topics is identifying an area that is too wide in scope. A simple step is to consider how to express and convey the work within a series of research objectives. Careful consideration of the content of these statements can help narrow the topic focus, and ensure the research design is relevant to the work to be undertaken. Therefore, writing your objectives should be viewed as a process and not a one-off exercise. Remember, they convey your work to an audience and set out the initial boundaries of the research to be undertaken.

Therefore, research aims and objectives should provide focus and direction for the research topic. Many business research methods texts will introduce the writing of research aims and objectives as a specific skill required to ensure they are Specific, Measurable, Achievable, Realistic and Timely (SMART). By following the SMART guidelines and analyzing examples of common issues within aims and objectives, learners can build confidence and ensure their aims and objectives are strong. Together with these five criteria, the language used can convey the depth of the inquiry. By way of explanation, consider the following topic submitted for consideration as a final-year project:

The research aim is to evaluate consumer perceptions of the impact of social media advertising on their car purchasing decisions. The fieldwork will examine consumer attitudes toward social media advertising and the benefits of this approach. This will be explored through the following research objectives:

• 1. Examine relevant literature concerning advertising, and trends in social media within the car industry;
• 2. Identify the attitudes of key players and stakeholders within the advertising industry toward the use of social media;
• 3. Discuss the effects of new technology on social media and advertising trends;
• 4. Evaluate how consumers relate to new technology with a view to making recommendations for improvement in the use of social media within online advertising.

S pecific – the research objectives reflect the terminology also used within the research aim.

M easureable – this does not necessarily mean that the work will involve quantitative data. Consider that the objectives identify the issues and samples and so the target of the work.

A chievable – does the work appear to be a piece of research that could be undertaken and completed within the confines of the undergraduate program? It could be achievable on the basis that the work does not appear to require a long time period to complete and the samples should be accessible. Achievability is also a consideration of university ethical consideration processes. For example, although a researcher is able to identify a sample of participants who are experiencing fuel poverty, consideration must be given to the possible ethical issues that surround requesting their participation. It may be deemed that the research could in some manner cause harm to the participants, such as stress through talking about their lived experiences. This stress could also be felt by the researcher who may not be trained to deal with such emotional situations. In both of these examples, the university ethics process could decide this work is unachievable.

R ealistic – the issue of social media advertising is realistic within the stated industry. The samples identified also appear linked to the topic. Furthermore, the academic foundation of the work is also identified – advertising. The work also appears to be realistic in terms of the resources required to complete it. The ethical use of data gathered from social media could also be relevant to determining if this topic is realistic. As with Achievability above, issues such as how the data was originally gathered and how it will then be used by the researcher, would be scrutinized by the Ethics process. Again, the principle of ‘do no harm’ would be applied to determine if the work is realistic.

T imely – although the work does not offer a specific timeframe, the use of social media for advertising is evident within the car industry. Therefore, this could be said to be timely.

Furthermore, the terminology is important. If you choose words that are descriptive, they will convey work that is also descriptive. So, try to use words such as ‘describe,’ ‘understand,’ or ‘gain an insight into’ only where they adequately reflect that your research is not an in-depth study. Consider using terms to evidence how you will approach each objective including: evaluate; critique; critically discuss and examine. All infer the research will go beyond a surface inquiry.

Now, at this stage, consider if the research wished to study the possible relationships between variables such as the impact on consumers of exposure to social media advertising on car sales decision-making. As with the approach to the similar topic above, this could be explored using qualitative data by gathering the experiences of consumers and/or people within the car industry. However, research that specifically wishes to explore possible links between issues and/or specific variables, could sometimes be better framed using a research hypothesis. This is a statement that identifies possible c ause and effect ’ relationships between variables. Therefore, the focus of the above topic could be reconsidered to identify the impact of social media advertising within the car industry. The new research question and hypothesis could be thus:

The research question: Do consumers perceive the impact of social media advertising on their car purchasing decisions?

Null Hypothesis: There is no difference in car purchasing decisions between those consumers who are exposed to social media advertising of cars compared to those who are not.

Alternative Hypothesis: There is a relationship between whether or not a consumer has been exposed to social media advertising and their car purchasing decision.

In order to address the hypothesis, some form of statistical testing would be required which is not covered in this guide. However, as a researcher, you should always consider what it is specifically that you wish to research when framing your work. This topic consideration could identify specific issues and/or variables which you wish to explore further to test if there are statistical relationships. In this situation, you could consider including hypothesis testing within your research design. As can be viewed above, related topics may be presented in different ways, with the inclusion or exclusion of a research hypothesis. The existence of possible relationships may be explored through research that seeks perceptions of advertising. However, research which seeks statistical evidence would be best represented with hypothesis testing.

• Research aim and objectives convey to your audience the topic and possible boundaries of your work. Therefore, ensuring they are presented as SMART, allows others to assess your work in the way you intended.
• Research ethics should be considered when writing research aims and objectives, including the potential impact of participation on individuals. Research should do no harm to the individuals involved, including the sample and researchers themselves.
• Research does not always necessitate consideration of the research hypothesis. However, in some circumstances, a well-considered hypothesis could offer statistical weight to your findings.

Recognizing the Link Between Writing an Effective Research Aim and the Research Design

The research aim and objectives should be written in a way that conveys the specific area or problem to be researched. This should allow anyone reading your research aim to understand the main focus of the work. For example, your work may aim to examine the lived experiences of individuals living with fuel poverty within a specific geographic area or demographic. In this example, you can clearly identify the topic – lived experiences of fuel poverty – and the focus – individuals within the chosen geographical area/demographic . To a more experienced researcher, it can also offer insight into the research design which may be reasonably expected. So, studies of ‘lived experiences’ can involve the gathering and/or analysis of qualitative data from individuals/communities as the researcher seek to gather the first-hand experiences of participants (individuals).

Clearly written research aim and objectives should allow the reader to consider the following information:

• 1. Wider academic area(s) within which the topic falls (for example, accountancy; marketing; management);
• 2. The main areas of the literature identified within the aim and/or objectives;
• 3. The data which would be expected to be gathered to in order to meet/address the research objectives;
• 4. The data collection methods which could be deemed relevant to the research aim and,
• 5. Overall, if the research aim and objectives are SMART (see above).

Consider the wording in the example below:

The research aim of this dissertation is to examine the lived experiences of people living with fuel poverty and their attitudes towards support services within a local council area. This research aim will be addressed through the following research objectives:

• 1. Critically review previous literature and evaluate the origins and purpose of different definitions of ‘fuel poverty.’
• 2. Explore the attitudes of individuals currently experiencing fuel poverty towards support agencies and other stakeholders.
• 3. Analyze the opportunities and barriers to support agencies and related stakeholders within a local council area with specific regard to supporting those experiencing fuel poverty.
• 4. Compare and contrast the lived experiences of individuals experiencing fuel poverty with those of the support agencies to identify potential service gaps.

Looking closely at the work above, it could be reasonable to make the following assumptions about the research:

The academic area(s) within which the topic falls (for example, accountancy; marketing; management; social sciences; economics). This can be researched and explored by keyword searching the research aim. In this example, there appear to be multiple academic roots to the work:

• ‘lived experiences of people living with fuel poverty’ – this could be viewed as a social science/economics topic or even an engineering area. Either would depend on the specific view taken to investigate fuel poverty, i.e., real-world examples of lived experiences, specially such as narratives about their daily life. Alternatively, this aim could encapsulate studies within engineering areas that seek to understand the impact of construction and design decisions on the daily life of individuals.
• ‘…and their attitudes towards support services within a local council area’ – by adding a focus for the study as being specific to support services, this work is now narrowed to more reflect the social sciences area.
• If the work was indeed to study any issues such as building construction, this would be expected to appear within the research aim to convey the topic clearly and precisely.

Therefore, it could be expected that if the research draws on wider academic areas, this should be evident from the terminology within the research objectives. A consistent use of terminology ensures the academic foundation of the work is identifiable throughout. It could also be reasonably presumed that the relevant issues of each sample (individuals within fuel poverty, the support services, and stakeholders), would be refined to include specific factors to ensure the work is focused on specific issues.

Next, consider the type of data you would expect to gather to in order to meet/address the research objectives. The following options appear to be linked to the wording of the objectives:

• Secondary Data: The objectives identify the need for literature in the first stages of work in order to address objectives 1, 2, and 3. As the research is based on lived experiences, this could include not only academic work but also charity and government reports. Given that this is a real-world issue, examples could also be identified from reputable news agencies. All of these sources could help identify possible issues that may be identified by research participants during the data gathering. If these issues are not identified by the participants, they could be used to form a critical discussion around opportunities or barriers (objective 3).
• Primary Data: Given the focus on lived experiences related to support services, the research may be presumed to include a qualitative study. A qualitative study would allow participants to use their own voices and language to explain their lived experiences. Whereas a quantitative study, by its nature, could explore the issues already known to the researcher when the instrument was written, e.g., survey. Qualitative data could perhaps encourage more personal issues to be identified by the individual participants, and also offer some context for their position.

Subsequently, consider which data collection methods you would expect to be used to address the research aim.

• Quantitative data gathering tools: Could quantitative data gathering explore the lived experiences of this sample? Many areas could be effectively explored however lived experiences tend to be personal to the individual and so qualitative could offer more depth and richness to the data.
• As both the research aim and objectives identify specific samples, the research could be considered to have a boundary around those to be invited to participate. Therefore, secondary data may identify the definitions of fuel poverty and offer reasons for any differences. It could also allow the identification of the roles and remits of support services and stakeholders. However, it will not offer specific lived experience details that can come from the sample of individuals.

If specific organizational sectors or companies were identified, the use of quantitative data-gathering tools, such as a survey, may allow more specific information to be gathered. Remember, the research aim identifies that the focus is the individuals who experience fuel poverty. Therefore, a survey could address issues such as knowledge and understanding of these service providers. However, it could then miss hearing about the informal networks used by individuals for support, which could come to light during a qualitative study.

Finally, if in doubt, show your research aim and objectives to a colleague and ask them to tell you , what they think your research is about. This simple exercise will enable you to realize what other people understand from your work and so, allow you to tweak where necessary. This should ensure your research is not only accessible to different audiences but ultimately, is a fair reflection of your topic choice.

• Clearly written research aims and objectives can effectively convey information about your work. This allows a reader to consider the key aspects of your topic and sets expectations about the contents of your report/dissertation/thesis.
• Always ensure that the language used to write a research aim and objectives, adequately convey the meaning and depth of your research. It should be specific to your topic but also accessible to the intended audience(s).
• SMART research objectives can convey your understanding of research design. This should be apparent from the layering of issues and identification of relevant samples.

In conclusion, this guide has offered practical steps through example-based exercises to help you format your idea into an effective research aim and objectives. Having progressed through the exercises, you will have considered issues such as the importance of understanding how a research aim can help you refine your idea. It is also the mechanism to convey your research intention to your audience. Through exploring the importance of linking your research aim to the wider research area this will give you the confidence to develop SMART objectives. Following this, your work will reflect key areas of your research design through the use of relevant research methods terminology.

Therefore, by following the steps in this guide you should now be confident to take your idea and form it into robust research aims and objectives.

Multiple-Choice Quiz Questions

1. The purpose of a research aim is to ______.

Incorrect Answer

Feedback: This is not the correct answer. The correct answer is C.

Correct Answer

Feedback: Well done, correct answer

2. It is important to understand the link between the research aim and the wider topic because ______.

Feedback: This is not the correct answer. The correct answer is B.

3. How many research objectives are necessary to ensure a successful final-year project?

4. Research objectives reflect ______

5. Research design can be reflected in the research aim and objectives by ______.

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• Writing Tips

How to Write Research Objectives

3-minute read

• 22nd November 2021

Writing a research paper, thesis, or dissertation ? If so, you’ll want to state your research objectives in the introduction of your paper to make it clear to your readers what you’re trying to accomplish. But how do you write effective research objectives? In this post, we’ll look at two key topics to help you do this:

• How to use your research aims as a basis for developing objectives.
• How to use SMART criteria to refine your research objectives.

For more advice on how to write strong research objectives, see below.

Research Aims and Objectives

There is an important difference between research aims and research objectives:

• A research aim defines the main purpose of your research. As such, you can think of your research aim as answering the question “What are you doing?”
• Research objectives (as most studies will have more than one) are the steps you will take to fulfil your aims. As such, your objectives should answer the question “How are you conducting your research?”

For instance, an example research aim could be:

This study will investigate the link between dehydration and the incidence of urinary tract infections (UTIs) in intensive care patients in Australia.

To develop a set of research objectives, you would then break down the various steps involved in meeting said aim. For example:

This study will investigate the link between dehydration and the incidence of urinary tract infections (UTIs) in intensive care patients in Australia. To achieve this, the study objectives w ill include:

• Replicat ing a small Singaporean study into the role of dehydration in UTIs in hospital patients (Sepe, 2018) in a larger Australian cohort.
• Trialing the use of intravenous fluids for intensive care patients to prevent dehydration.
• Assessing the relationship between the age of patients and quantities of intravenous fluids needed to counter dehydration.

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Note that the objectives don’t go into any great detail here. The key is to briefly summarize each component of your study. You can save details for how you will conduct the research for the methodology section of your paper.

Make Your Research Objectives SMART

A great way to refine your research objectives is to use SMART criteria . Borrowed from the world of project management, there are many versions of this system. However, we’re going to focus on developing specific, measurable, achievable, relevant, and timebound objectives.

In other words, a good research objective should be all of the following:

• S pecific – Is the objective clear and well-defined?
• M easurable – How will you know when the objective has been achieved? Is there a way to measure the thing you’re seeking to do?
• A chievable – Do you have the support and resources necessary to undertake this action? Are you being overly ambitious with this objective?
• R elevant – Is this objective vital for fulfilling your research aim?
• T imebound – Can this action be realistically undertaken in the time you have?

If you follow this system, your research objectives will be much stronger.

Expert Research Proofreading

Whatever your research aims and objectives, make sure to have your academic writing proofread by the experts!

Our academic editors can help you with research papers and proposals , as well as any other scholarly document you need checking. And this will help to ensure that your academic writing is always clear, concise, and precise.

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• Defining Research Objectives: How To  Write Them

Almost all industries use research for growth and development. Research objectives are how researchers ensure that their study has direction and makes a significant contribution to growing an industry or niche.

Research objectives provide a clear and concise statement of what the researcher wants to find out. As a researcher, you need to clearly outline and define research objectives to guide the research process and ensure that the study is relevant and generates the impact you want.

In this article, we will explore research objectives and how to leverage them to achieve successful research studies.

What Are Research Objectives?

Research objectives are what you want to achieve through your research study. They guide your research process and help you focus on the most important aspects of your topic.

You can also define the scope of your study and set realistic and attainable study goals with research objectives. For example, with clear research objectives, your study focuses on the specific goals you want to achieve and prevents you from spending time and resources collecting unnecessary data.

However, sticking to research objectives isn’t always easy, especially in broad or unconventional research. This is why most researchers follow the SMART criteria when defining their research objectives.

Understanding SMART Criteria in Research

Think of research objectives as a roadmap to achieving your research goals, with the SMART criteria as your navigator on the map.

SMART stands for Specific, Measurable, Achievable, Relevant, and Time-bound. These criteria help you ensure that your research objectives are clear, specific, realistic, meaningful, and time-bound.

Here’s a breakdown of the SMART Criteria:

Specific : Your research objectives should be clear: what do you want to achieve, why do you want to achieve it, and how do you plan to achieve it? Avoid vague or broad statements that don’t provide enough direction for your research.

Measurable : Your research objectives should have metrics that help you track your progress and measure your results. Also, ensure the metrics are measurable with data to verify them.

Achievable : Your research objectives should be within your research scope, timeframe, and budget. Also, set goals that are challenging but not impossible.

Relevant: Your research objectives should be in line with the goal and significance of your study. Also, ensure that the objectives address a specific issue or knowledge gap that is interesting and relevant to your industry or niche.

Time-bound : Your research objectives should have a specific deadline or timeframe for completion. This will help you carefully set a schedule for your research activities and milestones and monitor your study progress.

Characteristics of Effective Research Objectives

Clarity : Your objectives should be clear and unambiguous so that anyone who reads them can understand what you intend to do. Avoid vague or general terms that could be taken out of context.

Specificity : Your objectives should be specific and address the research questions that you have formulated. Do not use broad or narrow objectives as they may restrict your field of research or make your research irrelevant.

Measurability : Define your metrics with indicators or metrics that help you determine if you’ve accomplished your goals or not. This will ensure you are tracking the research progress and making interventions when needed.

Also, do use objectives that are subjective or based on personal opinions, as they may be difficult to accurately verify and measure.

Achievability : Your objectives should be realistic and attainable, given the resources and time available for your research project. You should set objectives that match your skills and capabilities, they can be difficult but not so hard that they are realistically unachievable.

For example, setting very difficult make you lose confidence, and abandon your research. Also, setting very simple objectives could demotivate you and prevent you from closing the knowledge gap or making significant contributions to your field with your research.

Relevance : Your objectives should be relevant to your research topic and contribute to the existing knowledge in your field. Avoid objectives that are unrelated or insignificant, as they may waste your time or resources.

Time-bound : Your objectives should be time-bound and specify when you will complete them. Have a realistic and flexible timeframe for achieving your objectives, and track your progress with it. 

Steps to Writing Research Objectives

Identify the research questions.

The first step in writing effective research objectives is to identify the research questions that you are trying to answer. Research questions help you narrow down your topic and identify the gaps or problems that you want to address with your research.

For example, if you are interested in the impact of technology on children’s development, your research questions could be:

• What is the relationship between technology use and academic performance among children?
• Are children who use technology more likely to do better in school than those who do not?
• What is the social and psychological impact of technology use on children?

Brainstorm Objectives

Once you have your research questions, you can brainstorm possible objectives that relate to them. Objectives are more specific than research questions, and they tell you what you want to achieve or learn in your research.

You can use verbs such as analyze, compare, evaluate, explore, investigate, etc. to express your objectives. Also, try to generate as many objectives as possible, without worrying about their quality or feasibility at this stage.

Prioritize Objectives

Once you’ve brainstormed your objectives, you’ll need to prioritize them based on their relevance and feasibility. Relevance is how relevant the objective is to your research topic and how well it fits into your overall research objective.

Feasibility is how realistic and feasible the objective is compared to the time, money, and expertise you have. You can create a matrix or ranking system to organize your objectives and pick the ones that matter the most.

Refine Objectives

The next step is to refine and revise your objectives to ensure clarity and specificity. Start by ensuring that your objectives are consistent and coherent with each other and with your research questions. 

Make Objectives SMART

A useful way to refine your objectives is to make them SMART, which stands for specific, measurable, achievable, relevant, and time-bound. 

• Specific : Objectives should clearly state what you hope to achieve.
• Measurable : They should be able to be quantified or evaluated.
• Achievable : realistic and within the scope of the research study.
• Relevant : They should be directly related to the research questions.
• Time-bound : specific timeframe for research completion.

Review and Finalize Objectives

The final step is to review your objectives for coherence and alignment with your research questions and aim. Ensure your objectives are logically connected and consistent with each other and with the purpose of your study.

You also need to check that your objectives are not too broad or too narrow, too easy or too hard, too many or too few. You can use a checklist or a rubric to evaluate your objectives and make modifications.

Examples of Well-Written Research Objectives

Example 1- Psychology

Research question: What are the effects of social media use on teenagers’ mental health?

Objective : To determine the relationship between the amount of time teenagers in the US spend on social media and their levels of anxiety and depression before and after using social media.

What Makes the Research Objective SMART?

The research objective is specific because it clearly states what the researcher hopes to achieve. It is measurable because it can be quantified by measuring the levels of anxiety and depression in teenagers. 

Also, the objective is achievable because the researcher can collect enough data to answer the research question. It is relevant because it is directly related to the research question. It is time-bound because it has a specific deadline for completion.

Example 2- Marketing

Research question : How can a company increase its brand awareness by 10%?

Objective : To develop a marketing strategy that will increase the company’s sales by 10% within the next quarter.

How Is this Research Objective SMART?

The research states what the researcher hopes to achieve ( Specific ). You can also measure the company’s reach before and after the marketing plan is implemented ( Measurable ).

The research objective is also achievable because you can develop a marketing plan that will increase awareness by 10% within the timeframe. The objective is directly related to the research question ( Relevant ). It is also time-bound because it has a specific deadline for completion.

Research objectives are a well-designed roadmap to completing and achieving your overall research goal. 

However, research goals are only effective if they are well-defined and backed up with the best practices such as the SMART criteria. Properly defining research objectives will help you plan and conduct your research project effectively and efficiently.

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• research goals
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• SMART research objectives
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• A Research Guide
• Research Paper Guide

How to Write Research Objectives

• What are research objectives
• Step-by-step writing guide
• Helpful tips
• Research objectives examples

What are research objectives, and why are they important?

Step-by-step research objectives writing guide, step 1: provide the major background of your research, step 2: mention several objectives from the most to least important aspects, step 3: follow your resources and do not promise too much, step 4: keep your objectives and limitations mentioned, step 5: provide action verbs and tone, helpful tips for writing research objectives.

• Keep your content specific! It is necessary to narrow things down and leave no space for double meanings or confusion. If some idea cannot be supported with a piece of evidence, it’s better to avoid it in your objectives.
• Objectives must be measurable! It is crucial to make it possible to replicate your work in further research. Creating an outline as you strive for your goals and set the purpose is necessary.
• Keeping things relevant! Your research objectives should be related to your thesis statement and the subject that you have chosen to work with. It will help to avoid introducing ideas that are not related to your work.
• Temporal factor! Set deadlines to track your progress and provide a setting for your research if it is relevant. It will help your target audience to see your limitations and specifics.

Research objectives example

Research objective 1: The study aims to explore the origins and evolution of the youth movements in the Flemish provinces in Belgium, namely Chiro and KSA. This research evaluates the major differences during the post-WW2 period and the social factors that created differences between the movements. 

Research objective 2: This paper implements surveys and personal interviews to determine first-hand feedback from the youth members and the team leaders. 

Research objective 3: Aiming to compare and contrast, this study determines the positive outcomes of the unity project work between the branches of the youth movement in Belgium, aiming for statistical data to support it. 

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How to Write Objectives in a Research Proposal

Last Updated: May 19, 2023 Fact Checked

This article was co-authored by Felipe Corredor . Felipe is a Senior College Admissions Consultant at American College Counselors with over seven years of experience. He specializes in helping clients from all around the world gain admission into America's top universities through private, one-on-one consulting. He helps guide clients through the entire college admissions process and perfect every aspect of their college applications. Felipe earned a Bachelor's Degree from the University of Chicago and recently received his MBA. There are 10 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 124,296 times.

A research proposal is a detailed outline for a significant research project. They’re common for class assignments, capstone papers, grant applications, and even job applications in some fields, so it's possible you'll have to prepare one at some point. The objectives are a very important part of a research proposal because they outline where the project is headed and what it will accomplish. Developing objectives can be a little tricky, so take some time to consider them. Then work on wording them carefully so your readers understand your goals. With clear objectives, your research proposal will be much stronger.

Brainstorming Your Objectives

• For example, your research question might be “What is the effect of prolonged TV-watching on children?” You can then use that question to build your study around.
• Narrow down your research topic if it’s too broad. A broad research topic makes breaking the objectives down much more difficult. A research question like “How can we save the environment?” is a huge question. Something like “What safety measures would prevent ocean pollution?” is more specific and attainable. [2] X Research source

• Remember that in most cases, you shouldn’t state that your study will prove or disprove something exactly since you haven’t done the work yet. Don’t say “This study proves that honey is not an effective treatment for acne.” Instead, make it something like “This study will demonstrate whether or not honey is an effective treatment for acne.”

• If your research question was “What is the effect of prolonged TV-watching on children?” then there are a few categories you could look at. Objectives wrapped up within that question might be: 1) the incidence of eyestrain among children who watch a lot of TV, 2) their muscular development, 3) their level of socialization with other children. Design your objectives around answering these questions.

• You could always state in your research proposal that you plan to design future experiments or studies to answer additional questions. Most experiments leave unanswered questions and subsequent studies try to tackle them.

• A general objective might be "Establish the effect of diet on mental health." Some specific goals in that project could be 1) Determine if processed foods make depression worse, 2) Identify foods that improve mood, 3) Measure if portion sizes have an impact on mood.
• Not all research proposals want you to divide between general and specific goals. Remember to follow the instructions for the proposal you're writing.

• The best goals align with each letter in the SMART acronym. The weaker ones are missing some letters. For example, you might come up with a topic that’s specific, measurable, and time-bound, but not realistic or attainable. This is a weak objective because you probably can’t achieve it.
• Think about the resources at your disposal. Some objectives might be doable with the right equipment, but if you don’t have that equipment, then you can’t achieve that goal. For example, you might want to map DNA structures, but you can’t view DNA without an electron microscope.
• Ask the same question for your entire project. Is it attainable overall? You don’t want to try to achieve too much and overwhelm yourself.
• The specific words in this acronym sometimes change, but the sentiment is the same. Your objectives should overall be clear and specific, measurable, feasible, and limited by time.

Using the Right Language

• Verbs like use, understand, or study is vague and weak. Instead, choose words like calculate, compare, and assess.
• Your objective list might read like this: 1) Compare the muscle development of children who play video games to children who don’t, 2) Assess whether or not video games cause eyestrain, 3) Determine if videogames inhibit a child’s socialization skills.
• Some proposals use the infinitive form of verbs, like “to measure” or “to determine.” This is also fine but refer to the proposal instructions to see if this is correct.

• You can further explain your objectives further in the research proposal. No need to elaborate a lot when you’re just listing them.
• If you’re having trouble shortening an objective to 1 sentence, then you probably need to split it into 2 objectives. It might also be too complicated for this project.

• For example, “Determine if sunlight is harmful” is too vague. Instead, state the objective as “Determine if prolonged sun exposure increases subjects’ risk of skin cancer.”
• It’s helpful to let someone else read your proposal and see if they understand the objectives. If they’re confused, then you need to be more specific.

• For example, don’t say “Measure the effect of radiation on living tissue.” Instead, say “Determine what level of radiation is dangerous to living tissue.”
• Remember, don’t state the objectives as you’ve already done the experiments. They’re still not answered.

Writing the Objectives

• This is a common format for research proposals, but not universal. Always follow the format that the instructions provided.
• Depending on how long your introduction has to be, you might also list the objectives there. This depends on whether or not you have room.

• At the very least, the abstract should list the general objective. This tells the readers what your study is working towards.

• In some research projects, the general objective is called a long-term goal instead. Adjust your language to the proposal requirements.
• Some proposals directions may just want the specific objectives rather than a division between the general and specific ones. Don’t divide them if the instructions tell you not to.

• Your introduction may be as follows: "My long-term objective with this project is determining whether or not prolonged video-game playing is harmful to children under 5. I will accomplish this aim by meeting the following objectives: 1) Compare the muscle development of children who play videogames to children who don’t 2) Assess whether or not videogames cause eyestrain 3) Determine if videogames inhibit a child’s socialization skills"
• The specific objectives are usually listed as a bullet or numbered points. However, follow the instructions given.

Research Proposal Templates

Expert Q&A

• It’s always a good idea to let someone else read your research proposals and make sure they’re clear. Thanks Helpful 0 Not Helpful 0
• Proofread! A great proposal could be ruined by typos and errors. Thanks Helpful 2 Not Helpful 0

• Some proposal instructions are very specific, and applicants that don’t follow the format are eliminated. Always follow the instructions given to stay within the requirements. Thanks Helpful 3 Not Helpful 0

You Might Also Like

• ↑ https://uk.sagepub.com/sites/default/files/upm-assets/15490_book_item_15490.pdf
• ↑ https://research-methodology.net/research-methodology/research-aims-and-objectives/
• ↑ https://www.uh.edu/~lsong5/documents/A%20sample%20proposal%20with%20comment.pdf
• ↑ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3282423/
• ↑ https://www.cdc.gov/healthyyouth/evaluation/pdf/brief3b.pdf
• ↑ https://www.open.edu/openlearncreate/mod/oucontent/view.php?id=231&section=8.6.2
• ↑ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6398294/
• ↑ https://arxiv.org/pdf/physics/0601009.pdf
• ↑ https://www.bpcc.edu/institutional-advancement-grants/how-to-write-goals-and-objectives-for-grant-proposals
• ↑ https://guides.library.illinois.edu/c.php?g=504643&p=3454882

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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.

John Dudovskiy

Research Aims and Objectives: The dynamic duo for successful research

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

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

Understanding the Difference between Research Aims and Objectives

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

Research Aims:

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

Research Objectives:

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

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

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

Importance of Well-defined Aims and Objectives

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

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

How to Formulate Research Aims and Objectives

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

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

Common Pitfalls to Avoid While Formulating Aims and Objectives

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

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

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

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

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The Importance Of Research Objectives

Imagine you’re a student planning a vacation in a foreign country. You’re on a tight budget and need to draw…

Imagine you’re a student planning a vacation in a foreign country. You’re on a tight budget and need to draw up a pocket-friendly plan. Where do you begin? The first step is to do your research.

Before that, you make a mental list of your objectives—finding reasonably-priced hotels, traveling safely and finding ways of communicating with someone back home. These objectives help you focus sharply during your research and be aware of the finer details of your trip.

More often than not, research is a part of our daily lives. Whether it’s to pick a restaurant for your next birthday dinner or to prepare a presentation at work, good research is the foundation of effective learning. Read on to understand the meaning, importance and examples of research objectives.

Why Do We Need Research?

What are the objectives of research, what goes into a research plan.

Research is a careful and detailed study of a particular problem or concern, using scientific methods. An in-depth analysis of information creates space for generating new questions, concepts and understandings. The main objective of research is to explore the unknown and unlock new possibilities. It’s an essential component of success.

Over the years, businesses have started emphasizing the need for research. You’ve probably noticed organizations hiring research managers and analysts. The primary purpose of business research is to determine the goals and opportunities of an organization. It’s critical in making business decisions and appropriately allocating available resources.

Here are a few benefits of research that’ll explain why it is a vital aspect of our professional lives:

Expands Your Knowledge Base

One of the greatest benefits of research is to learn and gain a deeper understanding. The deeper you dig into a topic, the more well-versed you are. Furthermore, research has the power to help you build on any personal experience you have on the subject.

Keeps You Up To Date

Research encourages you to discover the most recent information available. Updated information prevents you from falling behind and helps you present accurate information. You’re better equipped to develop ideas or talk about a topic when you’re armed with the latest inputs.

Builds Your Credibility

Research provides you with a good foundation upon which you can develop your thoughts and ideas. People take you more seriously when your suggestions are backed by research. You can speak with greater confidence because you know that the information is accurate.

Sparks Connections

Take any leading nonprofit organization, you’ll see how they have a strong research arm supported by real-life stories. Research also becomes the base upon which real-life connections and impact can be made. It even helps you communicate better with others and conveys why you’re pursuing something.

Encourages Curiosity

As we’ve already established, research is mostly about using existing information to create new ideas and opinions. In the process, it sparks curiosity as you’re encouraged to explore and gain deeper insights into a subject. Curiosity leads to higher levels of positivity and lower levels of anxiety.

Well-defined objectives of research are an essential component of successful research engagement. If you want to drive all aspects of your research methodology such as data collection, design, analysis and recommendation, you need to lay down the objectives of research methodology. In other words, the objectives of research should address the underlying purpose of investigation and analysis. It should outline the steps you’d take to achieve desirable outcomes. Research objectives help you stay focused and adjust your expectations as you progress.

The objectives of research should be closely related to the problem statement, giving way to specific and achievable goals. Here are the four types of research objectives for you to explore:

General Objective

Also known as secondary objectives, general objectives provide a detailed view of the aim of a study. In other words, you get a general overview of what you want to achieve by the end of your study. For example, if you want to study an organization’s contribution to environmental sustainability, your general objective could be: a study of sustainable practices and the use of renewable energy by the organization.

Specific Objectives

Specific objectives define the primary aim of the study. Typically, general objectives provide the foundation for identifying specific objectives. In other words, when general objectives are broken down into smaller and logically connected objectives, they’re known as specific objectives. They help define the who, what, why, when and how aspects of your project. Once you identify the main objective of research, it’s easier to develop and pursue a plan of action.

Let’s take the example of ‘a study of an organization’s contribution to environmental sustainability’ again. The specific objectives will look like this:

To determine through history how the organization has changed its practices and adopted new solutions

To assess how the new practices, technology and strategies will contribute to the overall effectiveness

Once you’ve identified the objectives of research, it’s time to organize your thoughts and streamline your research goals. Here are a few effective tips to develop a powerful research plan and improve your business performance.

Set SMART Goals

Your research objectives should be SMART—Specific, Measurable, Achievable, Realistic and Time-constrained. When you focus on utilizing available resources and setting realistic timeframes and milestones, it’s easier to prioritize objectives. Continuously track your progress and check whether you need to revise your expectations or targets. This way, you’re in greater control over the process.

Create A Plan

Create a plan that’ll help you select appropriate methods to collect accurate information. A well-structured plan allows you to use logical and creative approaches towards problem-solving. The complexity of information and your skills are bound to influence your plan, which is why you need to make room for flexibility. The availability of resources will also play a big role in influencing your decisions.

Collect And Collate

After you’ve created a plan for the research process, make a list of the data you’re going to collect and the methods you’ll use. Not only will it help make sense of your insights but also keep track of your approach. The information you collect should be:

Logical, rigorous and objective

Can be reproduced by other people working on the same subject

Free of errors and highlighting necessary details

Current and updated

Includes everything required to support your argument/suggestions

Analyze And Keep Ready

Data analysis is the most crucial part of the process and there are many ways in which the information can be utilized. Four types of data analysis are often seen in a professional environment. While they may be divided into separate categories, they’re linked to each other.

Descriptive Analysis:

The most commonly used data analysis, descriptive analysis simply summarizes past data. For example, Key Performance Indicators (KPIs) use descriptive analysis. It establishes certain benchmarks after studying how someone has been performing in the past.

Diagnostic Analysis:

The next step is to identify why something happened. Diagnostic analysis uses the information gathered through descriptive analysis and helps find the underlying causes of an outcome. For example, if a marketing initiative was successful, you deep-dive into the strategies that worked.

Predictive Analysis:

It attempts to answer ‘what’s likely to happen’. Predictive analysis makes use of past data to predict future outcomes. However, the accuracy of predictions depends on the quality of the data provided. Risk assessment is an ideal example of using predictive analysis.

Prescriptive Analysis: 

The most sought-after type of data analysis, prescriptive analysis combines the insights of all of the previous analyses. It’s a huge organizational commitment as it requires plenty of effort and resources. A great example of prescriptive analysis is Artificial Intelligence (AI), which consumes large amounts of data. You need to be prepared to commit to this type of analysis.

Review And Interpret

Once you’ve collected and collated your data, it’s time to review it and draw accurate conclusions. Here are a few ways to improve the review process:

Identify the fundamental issues, opportunities and problems and make note of recurring trends if any

Make a list of your insights and check which is the most or the least common. In short, keep track of the frequency of each insight

Conduct a SWOT analysis and identify the strengths, weaknesses, opportunities and threats

Write down your conclusions and recommendations of the research

When we think about research, we often associate it with academicians and students. but the truth is research is for everybody who is willing to learn and enhance their knowledge. If you want to master the art of strategically upgrading your knowledge, Harappa Education’s Learning Expertly course has all the answers. Not only will it help you look at things from a fresh perspective but also show you how to acquire new information with greater efficiency. The Growth Mindset framework will teach you how to believe in your abilities to grow and improve. The Learning Transfer framework will help you apply your learnings from one context to another. Begin the journey of tactful learning and self-improvement today!

Explore Harappa Diaries to learn more about topics related to the THINK Habit such as  Learning From Experience ,  Critical Thinking  & What is  Brainstorming  to think clearly and rationally.

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Writing SMART objectives for natural resource and environmental management

• In natural resource and environmental management, well-written objectives are critical for effective decision-making and the achievement of desired outcomes. This article aims to improve practitioners' ability to identify and write SMART (Specific, Measurable, Achievable, Relevant, Time-bound) objectives for natural resource and environmental management.
• We differentiate between research and management objectives, define each SMART criterion, and introduce a template to help write management objectives. We demonstrate the use of the SMART management objectives template with a hypothetical example and two recent applications.
• The template simplifies the process of writing SMART management objectives. It is applicable to popular management frameworks like management by objectives and structured decision making.
• The implementation of SMART criteria and the provided template can lead to better outcomes in natural resource and environmental management, benefiting current and future generations.

Citation Information

Related content, mike colvin, phd, research ecologist.

This paper is in the following e-collection/theme issue:

Published on 28.3.2024 in Vol 26 (2024)

Development and External Validation of Machine Learning Models for Diabetic Microvascular Complications: Cross-Sectional Study With Metabolites

Authors of this article:

Original Paper

• Feng He 1, 2 , MSc   ; 
• Clarissa Ng Yin Ling 1 , MD   ; 
• Simon Nusinovici 1, 3 , PhD   ; 
• Ching-Yu Cheng 1, 3 , PhD   ; 
• Tien Yin Wong 1, 3 , PhD   ; 
• Jialiang Li 2 * , PhD   ; 
• Charumathi Sabanayagam 1, 3 * , PhD  

1 Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore

2 Department of Statistics and Data Science, National University of Singapore, Singapore, Singapore

3 Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore

*these authors contributed equally

Corresponding Author:

Charumathi Sabanayagam, PhD

Singapore Eye Research Institute

Singapore National Eye Centre

The Academia, 20 College Road, Discovery Tower Level 6

Singapore, 169856

Phone: 65 6576 7286

Fax:65 6225 2568

Email: [email protected]

Background: Diabetic kidney disease (DKD) and diabetic retinopathy (DR) are major diabetic microvascular complications, contributing significantly to morbidity, disability, and mortality worldwide. The kidney and the eye, having similar microvascular structures and physiological and pathogenic features, may experience similar metabolic changes in diabetes.

Objective: This study aimed to use machine learning (ML) methods integrated with metabolic data to identify biomarkers associated with DKD and DR in a multiethnic Asian population with diabetes, as well as to improve the performance of DKD and DR detection models beyond traditional risk factors.

Methods: We used ML algorithms (logistic regression [LR] with Least Absolute Shrinkage and Selection Operator and gradient-boosting decision tree) to analyze 2772 adults with diabetes from the Singapore Epidemiology of Eye Diseases study, a population-based cross-sectional study conducted in Singapore (2004-2011). From 220 circulating metabolites and 19 risk factors, we selected the most important variables associated with DKD (defined as an estimated glomerular filtration rate <60 mL/min/1.73 m 2 ) and DR (defined as an Early Treatment Diabetic Retinopathy Study severity level ≥20). DKD and DR detection models were developed based on the variable selection results and externally validated on a sample of 5843 participants with diabetes from the UK biobank (2007-2010). Machine-learned model performance (area under the receiver operating characteristic curve [AUC] with 95% CI, sensitivity, and specificity) was compared to that of traditional LR adjusted for age, sex, diabetes duration, hemoglobin A 1c , systolic blood pressure, and BMI.

Results: Singapore Epidemiology of Eye Diseases participants had a median age of 61.7 (IQR 53.5-69.4) years, with 49.1% (1361/2772) being women, 20.2% (555/2753) having DKD, and 25.4% (685/2693) having DR. UK biobank participants had a median age of 61.0 (IQR 55.0-65.0) years, with 35.8% (2090/5843) being women, 6.7% (374/5570) having DKD, and 6.1% (355/5843) having DR. The ML algorithms identified diabetes duration, insulin usage, age, and tyrosine as the most important factors of both DKD and DR. DKD was additionally associated with cardiovascular disease history, antihypertensive medication use, and 3 metabolites (lactate, citrate, and cholesterol esters to total lipids ratio in intermediate-density lipoprotein), while DR was additionally associated with hemoglobin A 1c , blood glucose, pulse pressure, and alanine. Machine-learned models for DKD and DR detection outperformed traditional LR models in both internal (AUC 0.838 vs 0.743 for DKD and 0.790 vs 0.764 for DR) and external validation (AUC 0.791 vs 0.691 for DKD and 0.778 vs 0.760 for DR).

Conclusions: This study highlighted diabetes duration, insulin usage, age, and circulating tyrosine as important factors in detecting DKD and DR. The integration of ML with biomedical big data enables biomarker discovery and improves disease detection beyond traditional risk factors.

Introduction

Diabetes is a complex metabolic disorder and a major global health problem of our time. In 2021, it affected 536.6 million adults worldwide, with a projected surge to 783.2 million by 2045 [ 1 ]. With the rapidly growing population with diabetes and the greater longevity over time, the burden of associated complications is expected to increase in parallel [ 2 ]. Among these, diabetic kidney disease (DKD) was estimated to develop in around 40% of the population with diabetes [ 3 ], while diabetic retinopathy (DR) would manifest in approximately 35% [ 4 ]. Left undetected and untreated, these microvascular complications could substantially elevate the risk of cardiovascular disease (CVD), end-stage renal disease, and permanent vision loss, resulting in compromised quality of life and shortened life expectancy [ 2 , 5 , 6 ]. Yet, timely and accurate diagnosis of DKD and DR remains a challenge because of their asymptomatic progression in the early stages [ 7 ]. Although factors such as age, sex, diabetes duration, hemoglobin A 1c (HbA 1c ) %, systolic blood pressure (SBP), and BMI have been identified as the risk contributors for DKD and DR, they offer only partial insights into the variability of risk among individuals.

To enable risk prediction and exploration of the underlying metabolic pathways, metabolomics has been increasingly used for biomarker discovery in diabetes and its complications [ 7 - 10 ]. Abnormalities in amino acids and lipids metabolism have been linked to both DKD and DR [ 7 ]. Given the similar microvascular structure, physiology, and pathogenic features of the kidney and the eye, these common metabolic traits may indicate biochemical pathways shared by the 2 complications, or both being manifestations of a latent systematic condition [ 11 ]. However, to the best of our knowledge, investigations into the commonalities and differences between DKD and DR in terms of their metabolic basis have been somewhat scarce [ 7 , 12 ]. Moreover, prior research was often limited by inadequate sample sizes, lack of replication, and restricted data analysis methods [ 13 ].

In this study, we aimed to fill these gaps by analyzing 220 circulating metabolites and 19 established risk factors as predictors of prevalent DKD and DR in a retrospective Asian adult population with diabetes. We used 2 machine learning (ML) algorithms, logistic regression (LR) with Least Absolute Shrinkage and Selection Operator (LASSO [ 14 ]), and a gradient-boosting decision tree (GBDT [ 15 ]). Compared with traditional statistical methods, these ML algorithms excel in handling high-dimensional data with complex relationships and can quantify the relative contribution of individual variables through variable importance scores. Based on these scores, we selected the top variables to develop ML models for DKD and DR detection and validated them externally in UK biobank (UKBB [ 16 ]) data. Additionally, we developed reference models using LR adjusted for traditional risk factors. All models were evaluated using the area under the receiver operating characteristic curve (AUC) with 95% CI, sensitivity, and specificity. Finally, we discussed the potential role of the selected metabolites in DKD and DR with reference to previous studies.

We derived this study’s data from the Singapore Epidemiology of Eye Diseases study (SEED [ 17 ]), a population-based cross-sectional study conducted in Singapore from 2004 to 2011. Detailed methodology has been reported elsewhere [ 17 ]. In brief, we recruited 10,033 adults aged 40-80 years using age-stratified random sampling. Participants completed interviewer-administered questionnaires, underwent ocular examinations, and provided samples for biochemical laboratory tests. The cohort included 3280 Malay (2004-2006, response rate 78.7%), 3400 Indian (2007-2009, response rate 75.6%), and 3353 Chinese (2009-2011, response rate 72.8%) individuals.

For external validation, we used data from UKBB, an open-access resource of prospective data set collected in the UK from 2007 to 2010, with over 500,000 participants recruited between the ages of 40 to 69 [ 16 ].

Ethical Considerations

Both SEED and UKBB studies were conducted per the Declaration of Helsinki. Ethical approval was obtained from the SingHealth Institutional Review Board for SEED (2018/2717, 2018/2921, 2018/2006, 2018/2594, 2018/2570, 2015/2279, and 2012/487/A) and from North West Multi-centre Research Ethics Committee for UKBB (21/NW/0157). Written informed consent was provided by all participants during the primary data collection. Due to the retrospective nature of our study and the use of deidentified health information, the SingHealth Institutional Review Board approved this study without requiring additional patient consent.

Definition of Outcome and Variables

In SEED, diabetes was defined as meeting any of the following criteria: HbA 1c % >6.5, random blood glucose >11.1 mmol/L, self-reported physician-diagnosed diabetes, or the use of antidiabetic medication including insulin. In UKBB, we applied the same definition but additionally included individuals with DR if the aforementioned variables were missing.

DKD was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73m 2 in people with diabetes. The eGFR values were calculated from blood creatinine concentrations using the chronic kidney disease epidemiology collaboration equation [ 18 ].

For SEED participants with diabetes, DR severity in each eye was graded from fundus photographs by certified ophthalmic graders according to the standard protocol of Early Treatment Diabetic Retinopathy Study (ETDRS) [ 2 , 19 ] with 6 stages: no DR (level 10-20), minimal (level 20), mild (level 35), moderate (levels 43 to 47), severe (level 53), and proliferative DR (levels >60). We defined the DR outcome as having an ETDRS level ≥20 in at least one eye (ie, any DR). In UKBB, DR severity was not graded. Therefore, we identified DR cases based on the International Classification of Diseases, Tenth Revision (ICD-10) code “H36.0” in their health-related outcomes (UKBB Data-Field: 41270) [ 16 ]. Supplementary analysis in SEED also considered moderate or worse DR (level >43 in at least one eye) as an additional outcome.

We considered a total of 239 variables for biomarker selection ( Multimedia Appendix 1 ). Among these, 19 variables were identified through a literature review, comprising 6 traditional risk factors (age, sex, duration of diabetes, HbA 1c %, SBP, and BMI), and 13 extended risk factors related to lifestyle (alcohol consumption and smoking), medication use (insulin, anticholesterol, and antihypertensive medication), clinic or biochemistry (diastolic blood pressure [DBP], pulse pressure [PP], random blood glucose, total cholesterol, high-density lipoprotein [HDL] cholesterol, and low-density lipoprotein cholesterol), and comorbidity conditions (hypertension and history of CVD). Hypertension in both cohorts was defined as self-reported physician-diagnosed hypertension, SBP >140 mm Hg, DBP >80 mm Hg, or the use of antihypertensive medication.

Using nuclear magnetic resonance techniques (Nightingale Health), we quantified the concentration of 228 circulating metabolites from patients’ blood samples. Of these, glycerol, pyruvate, and glutamine were not available for Malay individuals, creatinine was used in eGFR calculation and DKD outcome definition, while 4 metabolites (total, HDL, low-density lipoprotein cholesterols, and random blood glucose) were duplicated with those measured in biochemistry tests. Therefore, these variables were excluded from the analysis, leaving us with 220 metabolites from 15 categories (amino acids, apolipoproteins, cholesterol, cholesterol esters, fatty acids, fluid balance, free cholesterols, glycolysis-related metabolites, inflammation, ketone bodies, triglycerides, lipoprotein particle sizes, lipoprotein subclasses, lipoprotein lipid ratios, and other lipids).

Statistical Analysis

Inclusion and exclusion criteria.

From the initial SEED data set of 10,033 participants, we excluded those free of diabetes (n=7069), missing metabolomics profiles (n=179), or missing more than 10% (n=13) of the data, to obtain a final study population of 2772 individuals. Similarly, we identified 5843 UKBB participants eligible for external validation after data cleaning ( Figure 1 ).

Descriptive Statistics

We categorized SEED participants into 4 groups based on their DKD and DR status, and summarized group characteristics as number (%), mean (SD), or median (IQR) as appropriate for each variable. Differences among groups were assessed using 2-sided P values derived from Pearson χ 2 tests or Fisher exact test for categorical variables, and Kruskal-Wallis rank sum tests for numeric variables. We also evaluated the interpopulation differences between SEED and UKBB using Pearson χ 2 tests and Mann-Whitney U tests as appropriate for each variable. Some subcategories may not add up due to the presence of missing data.

ML Algorithms

We used LASSO [ 14 ] and GBDT [ 15 ] to identify the key biomarkers and develop disease detection models for DR and DKD. LASSO is an extension of traditional LR that does not require the independence of variables. Therefore, LASSO is suitable for high-dimensional data sets where issues such as multicollinearity often arise. During parameter optimization, LASSO automatically shrinks the coefficients of the less-important variables to zero, while retaining nonzero coefficients for the important ones to achieve biomarker selection. Its strengths include relatively straightforward computation and parameter tuning compared to other ML algorithms. However, its scope is limited to examining only the linear associations between continuous variables and the log-odds. To account for possible nonlinear effects and variable interactions, we additionally implemented the GBDT algorithm, which constructs a sequence of interdependent decision trees to collectively make a decision. During the process, the algorithm assesses each variable’s contribution to minimizing prediction errors, returning a score for its relative influence. We then applied a predefined threshold to select the most influential variables for disease detection based on their scores in each selection round. GBDT is known for its adaptability to various data distributions with generally strong performances, yet its hyper-parameter tuning and computation can be rather time-consuming, with a higher chance of overfitting, and less transparency compared to LASSO.

Model Development and Validation

In SEED, we handled missing data by excluding variables and participants with high levels of missing information, yielding a final data set with each variable containing less than 6% (161/2772) missing data and a participant-level missing data percentage of 10% or less (23/239, Multimedia Appendix 2 ). Following this, missing data imputation was carried out by using mean values for numeric variables, and modes for categorical variables as appropriate. To mitigate selection bias arising from data division into training and validation sets, we averaged the results over 200 random repeats of 5-fold cross-validation. In each repeat, the imputed SEED data set was randomly divided into 5 subsets (ie, folds) of equal sample size by stratified sampling to ensure consistent case rates. Each fold (553/2772, 20% of data) took its turn as the validation set, while the remaining 4 folds (2219/2772, 80% of data) were used for model training and variable selection. From 200 replicates we generated 1000 sets of variable selection results, based on which we quantified each variable’s contribution to the model’s performance by calculating a variable importance score, as the variable’s selection frequency during the repeated cross-validation process.

Next, we arranged the variables in descending order of their selection frequencies and included only those selected 990 times or more (ie, selection frequency 0.990) in the final model. To evaluate the performance of these new models, we performed another 200 random repeats of 5-fold cross-validation but used only the complete cases (ie, no missing data imputation). The final machine-learned models were compared with the multivariate LR models adjusted for the 6 established risk factors including age, sex, diabetes duration, HbA 1c %, SBP, and BMI. The performance of these models was evaluated in internal and external validation using AUC with 95% CI, sensitivity, and specificity. We reported sensitivity and specificity at the optimal threshold, where sensitivity equals specificity. Additionally, in the context of DR and DKD detection, where the cost of false negatives is generally higher than that of false positives, we prioritized higher sensitivity over higher specificity by setting the probability threshold at 0.8 sensitivity to compare the specificity. The AUC difference between machine-learned models and the traditional model was evaluated using the test by DeLong et al [ 20 ]. For the supplementary analysis, we examined the importance of the top machine-learned variables within nested models, to check for any marginal increase in AUC with additional variables. We also calculated the AUC for ML models with all the variables.

Metabolites Selection

Finally, we focused on the metabolites that were consistently selected by both ML algorithms. We quantified their associations with DKD and DR respectively, using odds ratios (OR) per SD increment with 95% CI, and P values from multivariate LR models adjusted for age, sex, diabetes duration, insulin use, HbA 1c %, PP, BMI, cholesterol, and HDL cholesterol.

We conducted all the analyses in R version 4.0.2. (R Foundation) and defined statistical significance as P <.05.

Population Characteristics

Figure 1 illustrates the data cleaning and analysis workflow. In the SEED population with diabetes, 2674 people had information on both disease outcomes ( Multimedia Appendix 3 ). Of these, 1657 (62%) had neither DKD nor DR, 338 (12.6%) had DKD but not DR, 496 (18.5%) had DR but not DKD, and 183 (6.8%) had both DKD and DR. People with DKD, regardless of their DR status, tended to be older, with higher PP, higher SBP, and lower DBP. They also had higher levels of HDL cholesterol, more history of hypertension and CVD, and were more likely to have used anticholesterol medication and antihypertensive medication. However, they had a lower smoking rate and reported less alcohol consumption than those without DKD. People with DR, regardless of their DKD status, tended to have a longer duration of diabetes, with the use of antidiabetic medication and insulin, higher HbA 1c %, and random blood glucose levels. They also had a lower BMI and lower total cholesterol levels. For people with both complications, the abovementioned characteristics further differed from those with neither complication. However, in terms of sex distribution, no significant difference was observed ( P =.09).

We also found differences between SEED and UKBB in terms of demographics, lifestyle factors, biochemical laboratory results, and medical history ( Multimedia Appendix 4 ). In particular, UKBB participants had a lower prevalence of both DKD (374/5570, 6.7%) and DR (355/5843, 6.1%) as compared to SEED (DKD prevalence: 555/2753, 20.2%, and DR prevalence: 685/2693, 25.4%), with only 0.7% (41/5570) having both complications. SEED had a median age of 61.7 (IQR 53.5-69.4) years and 49.1% (1361/2772) women, whereas UKBB had a median age of 61.0 (IQR 55.0-65.0) years and 35.8% (2090/5843) women. SEED was a multiethnic sample based in Singapore with 36.8% (1020/2772) Malay, 45.5% (1262/2772) Indian, and 17.7% (490/2772) Chinese individuals. In contrast, over 81.8% (4778/5843) of the UKBB participants were British, with the rest being Indian (217/5843, 3.7%), Irish (132/5843, 2.3%), Caribbean (93/5843, 1.6%), African (85/5843, 1.5%), or other ethnicities (538/5843, 9.2%).

Figure 2 shows the top 50 variables arranged in descending orders of their variable importance. For DKD detection, LASSO identified 15 variables with a frequency exceeding the cutoff, while GBDT identified 13, so we used the top 15 for deriving the corresponding DKD models; then for DR, LASSO identified 10 variables, while GBDT identified 6, so we used the top 10 for DR.

In the internal validation, GBDT models performed the best with an AUC of 0.838 for DKD and 0.790 for DR, followed by LASSO with AUC values of 0.832 and 0.779, respectively. In contrast, LR only achieved AUC scores of 0.743 for DKD, and 0.764 for DR. In the external validation using UKBB data, LASSO models exhibited the best performance with AUC values of 0.791 for DKD, and 0.778 for DR. GBDT models achieved AUC scores of 0.738 and 0.778, respectively, while LR resulted in AUC values of 0.691 and 0.760 ( Figure 3 ).

Further tests confirmed that the AUC scores of ML models were significantly higher than those obtained using traditional LR (2-sided P <.001). In terms of sensitivity and specificity at the optimal threshold (where sensitivity=specificity), LASSO and GBDT achieved comparable performance in internal validation (for DKD, 0.757 by LASSO vs 0.751 by GBDT; for DR, 0.708 by LASSO vs 0.709 by GBDT), and both were superior to LR (0.674 for DKD and 0.696 for DR). In external validation, LASSO performed the best, with 0.723 for DKD and 0.716 for DR. At 0.8 sensitivity, LASSO achieved 0.636 specificity for DKD detection in UKBB, and 0.617 for DR, outperforming the other 2 models ( Table 1 ).

a AUC: area under the receiver operating characteristic curve.

b SN: sensitivity.

c SP: specificity.

d Final sample size after variable selection and missing data removal.

e DKD: diabetic kidney disease.

f SEED: Singapore Epidemiology of Eye Diseases.

g LR: logistic regression.

h LASSO: Least Absolute Shrinkage and Selection Operator.

i GBDT: gradient-boosting decision tree.

j UKBB: UK biobank.

k DR: diabetic retinopathy.

In the sensitivity analysis, we evaluated the potential improvement in AUC by introducing additional variables in nested models ( Multimedia Appendix 5 ). The results supported the effectiveness of using the top 10 variables for detecting DR in SEED. In line with this, using all 239 variables did not improve beyond what was achieved with the top 10 in both internal validation (LASSO 0.776 and GBDT 0.783) and external validation (LASSO 0.754 and GBDT 0.774). Yet for DKD, incorporating additional variables beyond the top 15 resulted in improved AUC in SEED. Specifically, using all 239 variables yielded higher AUC values of 0.859 for LASSO and 0.842 for GBDT. However, this increase may be attributed to overfitting, as a similar pattern was not observed in external validation. Further, using all available variables resulted in lower AUC values for both LASSO (0.694) and GBDT (0.721) in the UKBB cohort. Consequently, we decided to maintain the DKD model with the top 15 variables for its simplicity and effectiveness.

For DKD, both LASSO and GBDT selected 5 risk factors (duration of diabetes, history of CVD, antihypertensive medication use, age, and insulin use) and 4 metabolites (tyrosine, lactate, cholesterol esters to total lipid ratio in intermediate-density lipoprotein particles [IDL-CE%], and citrate). For any DR, both algorithms identified 6 risk factors (insulin use, HbA 1c %, duration of diabetes, random blood glucose, age, and PP) and 2 metabolites (tyrosine and alanine). In the supplementary analysis, tyrosine was again selected for moderate or worse DR detection ( Multimedia Appendix 6 ).

Table 2 shows the association of the machine-learned metabolites with DKD and DR in multivariable LR models. We found tyrosine to be negatively associated with both DKD (OR 0.65, 95% CI 0.58-0.73; P <.001) and DR (OR 0.90, 95% CI 0.81-1.00; P =.047). High levels of alanine were associated with increased DR prevalence (OR 1.31, 95% CI 1.18-1.45; P <.001), but with decreased DKD prevalence (OR 0.72, 95% CI 0.64-0.80; P <.001). Similarly, a high level of lactate was linked to higher DR prevalence (OR 1.16, 95% CI 1.05-1.28; P =.004) but with lower DKD prevalence (OR 0.71, 95% CI 0.63-0.80; P <.001). Finally, a high level of citrate was associated with increased DKD prevalence (OR 1.90, 95% CI 1.70-2.12; P <.001), while high IDL-CE% was linked to decreased DKD prevalence (OR 0.46, 95% CI 0.40-0.53; P <.001).

a DKD: diabetic kidney disease.

b DR: diabetic retinopathy.

c OR: odds ratio.

d IDL-CE%: cholesterol esters to total lipid ratio in intermediate-density lipoprotein particles.

Principal Findings

ML selected age, use of insulin, duration of diabetes, and circulating tyrosine as the most important markers for DKD and DR detection in the SEED population with diabetes. Additionally, DKD was associated with the use of antihypertensive medications, CVD history, and 3 metabolites (lactate, citrate, and IDL-CE%), whereas DR was additionally linked to HbA 1c , random blood glucose, PP, and alanine.

The ML models developed in the SEED cohort with diabetes were externally validated using UKBB data. In both cohorts, ML models outperformed the traditional LR in terms of AUC, sensitivity, and specificity, demonstrating their potential to discover novel biomarkers and enable disease screening when integrated with health care and metabolite data.

Comparison With Prior Work

Our main data set included a comprehensive set of 19 risk factors and 220 circulating metabolites measured in 2772 individuals. The detailed patient profiling with a robust sample size allowed an opportunity to identify the markers most relevant to DKD and DR, offering insights into the systematic alteration of metabolism and underlying pathways.

In line with the previous literature [ 4 , 13 ], ML consistently identified 3 key factors—diabetes duration, age, and the use of insulin—as the top risk factors for both DKD and DR. However, ML also revealed novel aspects concerning some established risk factors for these conditions. For instance, our ML models exhibited a notable preference for PP over SBP and DBP in DR detection, supporting the study by Yamamoto et al [ 21 ] that PP, as a surrogate marker of arterial stiffness, reflected both the SBP elevation and DBP reduction, thereby carrying more predictive information for DR than other blood pressure metrics. Another example was assessing the relative importance of glycemia control indicators, where HbA 1c % consistently received a higher selection frequency in our ML models compared to random blood glucose levels. This was probably because HbA 1c % was averaged to reflect a mean shift with much less random noise, while random blood glucose data might carry more noise from life cycle changes and interindividual variability [ 22 ]. Interestingly, some well-established risk factors usually included such as sex did not appear in the top-ranking lists by ML, although this variable had been selected by traditional LR models on the same population in previous studies [ 23 ]. This could be because sex is an intrinsic component of other phenotypes. For instance, male sex was associated with CVD [ 24 ], a condition well-known to be linked to DKD and DR [ 2 ].

We noted high levels of tyrosine, an aromatic amino acid, to be negatively associated with the prevalence of DKD and DR, supporting the ADVANCE trial where increased tyrosine concentration was linked to a decreased risk of diabetic microvascular events (hazard ratio 0.78, 95% CI 0.67-0.91) [ 12 ]. Tyrosine is mainly synthesized from phenylalanine hydroxylation in the liver and kidney; impaired kidney function is therefore associated with reduced phenylalanine hydroxylase activity characterized by low blood tyrosine levels [ 12 ]. Additionally, tyrosine serves as a precursor to catecholamine neurotransmitters (dopamine, norepinephrine, and epinephrine), and plays a pivotal role in central nervous system functions and activities [ 25 ]. In metabolic disorders such as diabetes, reduced blood tyrosine can affect its uptake into the brain and also the synthesis and release of transmitters, thereby altering hormonal function, affective state, and blood pressure [ 25 ], potentially linked to higher microvascular risks.

Another amino acid selected by ML was alanine, and its higher concentration in blood was associated with higher DR prevalence, but lower DKD prevalence. In the ADVANCE trial, a negative association was reported between circulating alanine and an aggregated microvascular outcome, defined as new or worsening nephropathy or retinopathy (hazard ratio 0.86, 95% CI 0.76-0.98) [ 12 ]. In other research, high levels of blood amino acids such as alanine have been linked to inhibited insulin signaling to glucose transport, phosphorylation, and glycogen synthesis, causing insulin resistance, which impairs hepatic mitochondrial function in patients with diabetes and contributes to diabetes microvascular complications such as DR [ 26 , 27 ].

Among the ML-selected metabolites for DKD, high levels of lactate were found to be associated with lower DKD prevalence. However, another study conducted in the DKD population suggested an accumulation of acid due to abnormal lactate metabolism causing fibrosis and mitochondrial abnormalities, leading to further kidney damage [ 28 ]. Nevertheless, further investigations are required to understand the complex association between circulating lactate and DKD. Another metabolite identified was citrate, which showed a positive association with DKD in SEED. In people with DKD, an elevated plasma citrate level has been linked to reduced organic anion transport and dysregulated mitochondrial functions of the kidney tissues [ 8 ]. Our study also highlighted the significance of IDL-CE% in diabetic microvascular complications, revealing its inverse association with prevalent DKD in the SEED population with diabetes. Aberrations in lipoprotein composition have been reported to be indicative of insulin resistance and impaired glucose tolerance in the general population, known to cause future diabetes [ 9 , 27 ]. In people with type 1 DKD, abnormality in lipoproteins clearance was further linked to impaired kidney function [ 29 ].

For biomarker discovery, traditional studies often relied on LR models to examine metabolites one by one separately [ 12 , 30 ], with stringent model assumptions and multiple testing corrections [ 9 , 31 ]. Herein, our ML approach was more efficient in the sense that it simultaneously examines all variables for potential associations. While LASSO was limited to detecting linear associations, we implemented GBDT as a complementary model to additionally assess nonlinear terms and high-order interactions. As was shown in Figure 2 , DR-related variables in GBDT had higher selection frequencies than in LASSO, suggesting the existence of such complex associations. Still, LASSO models achieved superior performance in external validation, indicating a prominent contribution of linear associations to DKD and DR detection. Another highlight of our methodology was the repeated cross-validation, which reduced the influence of potential outliers and ensured the randomness of sampling, thereby generating results more robust than those relying on a fixed training set. This approach also allowed us to quantify individual contributions of variables based on their selection frequencies. However, alternative definitions of variable importance scores [ 32 ] may be considered in a future study to potentially refine the variable selection process.

Globally, three-quarters of those with diabetes live in low- and middle-income countries, particularly India and China [ 33 ]. While the risk profile of Asian patients with diabetes differs from that in high-income “Western” societies in terms of age, BMI, lifestyle, diet, and many other aspects [ 33 ], there has been limited discussion on Asian populations with diabetes. Our study, conducted in Asian populations (Malay, Indian, and Chinese), may contribute to the topic by allowing an opportunity to identify the commonalities and differences between DKD and DR in terms of circulating metabolic traits, offering insights into the systematic alteration of metabolism in diabetes.

Limitations

In total, 1 limitation of this study was that we did not separate study subjects by diabetes type. Since around 95% of the SEED population with diabetes had type 2 diabetes, our results would mainly reflect the variable associations with type 2 diabetes. While these associations hold potential for hypothesis generation and disease detection, the cross-sectional nature of our study highlights the need for caution in drawing causal inferences. Future longitudinal studies are warranted to establish temporal associations based on our current findings.

Another issue was data availability—albuminuria, an important indicator of kidney disease [ 13 ], and 3 metabolites (pyruvate, glycerol, and glutamine) were missing in Malay individuals of the SEED population. Hence, these variables were excluded from the analysis. Certain diabetic medications were reported to potentially interfere with circulating metabolite levels [ 12 , 34 , 35 ]. However, we could only account for the use of insulin due to limited data availability on UKBB medication profiles. Furthermore, we noted a difference in defining DR between our development data set (SEED), which used the standard ETDRS classification system, and the external test set (UKBB), where DR cases were identified using ICD-10 codes. This variance in outcome definition might have introduced some degree of misclassification in UKBB. Additionally, due to the absence of ETDRS-based severity scores in UKBB, validation of the supplementary model for moderate or worse DR in supplementary analysis was not feasible. Nevertheless, it was noteworthy that the features identified in SEED remained relevant for enhancing DR detection in the UKBB data set. However, we acknowledge that the discrepancy in DR definition underscores the need for caution when interpreting results, particularly in the context of clinical or practical applications. Future research may benefit from adopting a uniform approach to DR classification to minimize such limitations and enhance result validity.

Conclusions

In conclusion, current ML models developed using the SEED population with diabetes and subsequently validated in UKBB showed superior performance compared to traditional LR for DKD and DR detection. ML highlighted age, use of insulin, diabetes duration, and tyrosine as the most influential factors in DKD and DR. Additionally, DKD was associated with high levels of citrate, low levels of lactate, and low IDL-CE%; while DR was linked to higher levels of alanine. The integration of ML with health care data and metabolomics could facilitate biomarker selection and enable disease screening.

Acknowledgments

We thank all the participants of Singapore Epidemiology of Eye Diseases (SEED) and UK biobank (UKBB) for contributing their health profiles to support our research. ChatGPT (OpenAI) [ 36 ] was used solely for proofreading purposes, focusing on grammar and spelling corrections. All such revisions were reviewed and validated by human coauthors. This study was supported by the Singapore Ministry of Health’s National Medical Research Council (NMRC/StaR/016/2013, NMRC/CIRG/1371/2013, NMRC/CIRG/1417/2015, and OFLCG/001/2017). The funders had no role in study design; data collection, management, analysis, and interpretation; preparation, and review of this paper; or decision to publish.

Data Availability

As the Singapore Epidemiology of Eye Diseases (SEED) study involves human participants, the data cannot be made freely available in this paper, the supplemental files, or a public repository due to ethical restrictions. Nevertheless, the data are available from the Singapore Eye Research Institutional Ethics Committee for researchers who meet the criteria for access to confidential data. Interested researchers can send data access requests to the Singapore Eye Research Institute. The UK biobank (UKBB) test data set was obtained from the UKBB (application 45925). Data cannot be shared publicly due to the violation of patient privacy and the absence of informed consent for data sharing.

Authors' Contributions

All authors contributed to the intellectual development of this paper. JL and CS designed this study and supervised data analysis. FH and CNYL wrote the initial draft. FH performed the statistical analyses. SN, CC, TYW, JL, and CS assisted in the interpretation of the analyzed data and provided critical corrections to this paper. CS is the guarantor of this work and as such had full access to all the data in this study and takes responsibility for the integrity of the data and accuracy of the data analysis. The final version of this paper has been seen and approved by all the authors.

Conflicts of Interest

None declared.

List of 239 Singapore Epidemiology of Eye Diseases (SEED) variables included for machine learning feature selection.

Distribution of missing data in Singapore Epidemiology of Eye Diseases (SEED), column-wise and row-wise histograms.

Population characteristics of Singapore Epidemiology of Eye Diseases (SEED) stratified by diabetic kidney disease (DKD) and diabetic retinopathy (DR) status.

Comparative analysis of population characteristics: Singapore Epidemiology of Eye Diseases (SEED) vs UK biobank.

Area under the receiver operating characteristic curve performance of nested models in internal validation with varying numbers of machine-learned variables.

Top-50 machine-learned variables for moderate or worse diabetic retinopathy (DR) detection.

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Abbreviations

Edited by A Mavragani; submitted 18.01.23; peer-reviewed by KH Hung, G Lim; comments to author 25.09.23; revised version received 12.10.23; accepted 19.12.23; published 28.03.24.

©Feng He, Clarissa Ng Yin Ling, Simon Nusinovici, Ching-Yu Cheng, Tien Yin Wong, Jialiang Li, Charumathi Sabanayagam. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 28.03.2024.

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