Research methodology vs. research methods
The research methodology or design is the overall strategy and rationale that you used to carry out the research. Whereas, research methods are the specific tools and processes you use to gather and understand the data you need to test your hypothesis.
To further understand research methodology, let’s explore some examples of research methodology:
a. Qualitative research methodology example: A study exploring the impact of author branding on author popularity might utilize in-depth interviews to gather personal experiences and perspectives.
b. Quantitative research methodology example: A research project investigating the effects of a book promotion technique on book sales could employ a statistical analysis of profit margins and sales before and after the implementation of the method.
c. Mixed-Methods research methodology example: A study examining the relationship between social media use and academic performance might combine both qualitative and quantitative approaches. It could include surveys to quantitatively assess the frequency of social media usage and its correlation with grades, alongside focus groups or interviews to qualitatively explore students’ perceptions and experiences regarding how social media affects their study habits and academic engagement.
These examples highlight the meaning of methodology in research and how it guides the research process, from data collection to analysis, ensuring the study’s objectives are met efficiently.
When it comes to writing your study, the methodology in research papers or a dissertation plays a pivotal role. A well-crafted methodology section of a research paper or thesis not only enhances the credibility of your research but also provides a roadmap for others to replicate or build upon your work.
Wondering how to write the research methodology section? Follow these steps to create a strong methods chapter:
At the start of a research paper , you would have provided the background of your research and stated your hypothesis or research problem. In this section, you will elaborate on your research strategy.
Begin by restating your research question and proceed to explain what type of research you opted for to test it. Depending on your research, here are some questions you can consider:
a. Did you use qualitative or quantitative data to test the hypothesis?
b. Did you perform an experiment where you collected data or are you writing a dissertation that is descriptive/theoretical without data collection?
c. Did you use primary data that you collected or analyze secondary research data or existing data as part of your study?
These questions will help you establish the rationale for your study on a broader level, which you will follow by elaborating on the specific methods you used to collect and understand your data.
Now that you have told your reader what type of research you’ve undertaken for the dissertation, it’s time to dig into specifics. State what specific methods you used and explain the conditions and variables involved. Explain what the theoretical framework behind the method was, what samples you used for testing it, and what tools and materials you used to collect the data.
Once you have explained the data collection process, explain how you analyzed and studied the data. Here, your focus is simply to explain the methods of analysis rather than the results of the study.
Here are some questions you can answer at this stage:
a. What tools or software did you use to analyze your results?
b. What parameters or variables did you consider while understanding and studying the data you’ve collected?
c. Was your analysis based on a theoretical framework?
Your mode of analysis will change depending on whether you used a quantitative or qualitative research methodology in your study. If you’re working within the hard sciences or physical sciences, you are likely to use a quantitative research methodology (relying on numbers and hard data). If you’re doing a qualitative study, in the social sciences or humanities, your analysis may rely on understanding language and socio-political contexts around your topic. This is why it’s important to establish what kind of study you’re undertaking at the onset.
Now that you have gone through your research process in detail, you’ll also have to make a case for it. Justify your choice of methodology and methods, explaining why it is the best choice for your research question. This is especially important if you have chosen an unconventional approach or you’ve simply chosen to study an existing research problem from a different perspective. Compare it with other methodologies, especially ones attempted by previous researchers, and discuss what contributions using your methodology makes.
No matter how thorough a methodology is, it doesn’t come without its hurdles. This is a natural part of scientific research that is important to document so that your peers and future researchers are aware of it. Writing in a research paper about this aspect of your research process also tells your evaluator that you have actively worked to overcome the pitfalls that came your way and you have refined the research process.
1. Remember who you are writing for. Keeping sight of the reader/evaluator will help you know what to elaborate on and what information they are already likely to have. You’re condensing months’ work of research in just a few pages, so you should omit basic definitions and information about general phenomena people already know.
2. Do not give an overly elaborate explanation of every single condition in your study.
3. Skip details and findings irrelevant to the results.
4. Cite references that back your claim and choice of methodology.
5. Consistently emphasize the relationship between your research question and the methodology you adopted to study it.
To sum it up, what is methodology in research? It’s the blueprint of your research, essential for ensuring that your study is systematic, rigorous, and credible. Whether your focus is on qualitative research methodology, quantitative research methodology, or a combination of both, understanding and clearly defining your methodology is key to the success of your research.
Once you write the research methodology and complete writing the entire research paper, the next step is to edit your paper. As experts in research paper editing and proofreading services , we’d love to help you perfect your paper!
Here are some other articles that you might find useful:
What does research methodology mean, what types of research methodologies are there, what is qualitative research methodology, how to determine sample size in research methodology, what is action research methodology.
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This is very simplified and direct. Very helpful to understand the research methodology section of a dissertation
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Home » Research Methodology – Types, Examples and writing Guide
Table of Contents
Definition:
Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.
Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:
I. Introduction
II. Research Design
III. Data Collection Methods
IV. Data Analysis Methods
V. Ethical Considerations
VI. Limitations
VII. Conclusion
Types of Research Methodology are as follows:
This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.
This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.
This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.
This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.
This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.
This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.
This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.
This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.
An Example of Research Methodology could be the following:
Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults
Introduction:
The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.
Research Design:
The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.
Participants:
Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.
Intervention :
The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.
Data Collection:
Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.
Data Analysis:
Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.
Ethical Considerations:
This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.
Data Management:
All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.
Limitations:
One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.
Conclusion:
This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.
Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:
Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.
The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.
The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.
Here are some of the applications of research methodology:
Research methodology serves several important purposes, including:
Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:
Research Methodology | Research Methods |
---|---|
Research methodology refers to the philosophical and theoretical frameworks that guide the research process. | refer to the techniques and procedures used to collect and analyze data. |
It is concerned with the underlying principles and assumptions of research. | It is concerned with the practical aspects of research. |
It provides a rationale for why certain research methods are used. | It determines the specific steps that will be taken to conduct research. |
It is broader in scope and involves understanding the overall approach to research. | It is narrower in scope and focuses on specific techniques and tools used in research. |
It is concerned with identifying research questions, defining the research problem, and formulating hypotheses. | It is concerned with collecting data, analyzing data, and interpreting results. |
It is concerned with the validity and reliability of research. | It is concerned with the accuracy and precision of data. |
It is concerned with the ethical considerations of research. | It is concerned with the practical considerations of research. |
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Methodology
Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.
First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :
Second, decide how you will analyze the data .
Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.
Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.
Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.
For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .
If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .
Qualitative | to broader populations. . | |
---|---|---|
Quantitative | . |
You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.
Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).
If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.
Primary | . | methods. |
---|---|---|
Secondary |
In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .
In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .
To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.
Descriptive | . . | |
---|---|---|
Experimental |
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Research method | Primary or secondary? | Qualitative or quantitative? | When to use |
---|---|---|---|
Primary | Quantitative | To test cause-and-effect relationships. | |
Primary | Quantitative | To understand general characteristics of a population. | |
Interview/focus group | Primary | Qualitative | To gain more in-depth understanding of a topic. |
Observation | Primary | Either | To understand how something occurs in its natural setting. |
Secondary | Either | To situate your research in an existing body of work, or to evaluate trends within a research topic. | |
Either | Either | To gain an in-depth understanding of a specific group or context, or when you don’t have the resources for a large study. |
Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.
Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.
Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:
Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .
Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).
You can use quantitative analysis to interpret data that was collected either:
Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.
Research method | Qualitative or quantitative? | When to use |
---|---|---|
Quantitative | To analyze data collected in a statistically valid manner (e.g. from experiments, surveys, and observations). | |
Meta-analysis | Quantitative | To statistically analyze the results of a large collection of studies. Can only be applied to studies that collected data in a statistically valid manner. |
Qualitative | To analyze data collected from interviews, , or textual sources. To understand general themes in the data and how they are communicated. | |
Either | To analyze large volumes of textual or visual data collected from surveys, literature reviews, or other sources. Can be quantitative (i.e. frequencies of words) or qualitative (i.e. meanings of words). |
If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.
Research bias
Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.
In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .
A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.
In statistics, sampling allows you to test a hypothesis about the characteristics of a population.
The research methods you use depend on the type of data you need to answer your research question .
Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.
Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).
In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .
In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.
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Why do you need a research methodology, what needs to be included, why do you need to document your research method, what are the different types of research instruments, qualitative / quantitative / mixed research methodologies, how do you choose the best research methodology for you, frequently asked questions about research methodology, related articles.
When you’re working on your first piece of academic research, there are many different things to focus on, and it can be overwhelming to stay on top of everything. This is especially true of budding or inexperienced researchers.
If you’ve never put together a research proposal before or find yourself in a position where you need to explain your research methodology decisions, there are a few things you need to be aware of.
Once you understand the ins and outs, handling academic research in the future will be less intimidating. We break down the basics below:
A research methodology encompasses the way in which you intend to carry out your research. This includes how you plan to tackle things like collection methods, statistical analysis, participant observations, and more.
You can think of your research methodology as being a formula. One part will be how you plan on putting your research into practice, and another will be why you feel this is the best way to approach it. Your research methodology is ultimately a methodological and systematic plan to resolve your research problem.
In short, you are explaining how you will take your idea and turn it into a study, which in turn will produce valid and reliable results that are in accordance with the aims and objectives of your research. This is true whether your paper plans to make use of qualitative methods or quantitative methods.
The purpose of a research methodology is to explain the reasoning behind your approach to your research - you'll need to support your collection methods, methods of analysis, and other key points of your work.
Think of it like writing a plan or an outline for you what you intend to do.
When carrying out research, it can be easy to go off-track or depart from your standard methodology.
Tip: Having a methodology keeps you accountable and on track with your original aims and objectives, and gives you a suitable and sound plan to keep your project manageable, smooth, and effective.
With all that said, how do you write out your standard approach to a research methodology?
As a general plan, your methodology should include the following information:
In any dissertation, thesis, or academic journal, you will always find a chapter dedicated to explaining the research methodology of the person who carried out the study, also referred to as the methodology section of the work.
A good research methodology will explain what you are going to do and why, while a poor methodology will lead to a messy or disorganized approach.
You should also be able to justify in this section your reasoning for why you intend to carry out your research in a particular way, especially if it might be a particularly unique method.
Having a sound methodology in place can also help you with the following:
A research instrument is a tool you will use to help you collect, measure and analyze the data you use as part of your research.
The choice of research instrument will usually be yours to make as the researcher and will be whichever best suits your methodology.
There are many different research instruments you can use in collecting data for your research.
Generally, they can be grouped as follows:
These are the most common ways of carrying out research, but it is really dependent on your needs as a researcher and what approach you think is best to take.
It is also possible to combine a number of research instruments if this is necessary and appropriate in answering your research problem.
There are three different types of methodologies, and they are distinguished by whether they focus on words, numbers, or both.
Data type | What is it? | Methodology |
---|---|---|
Quantitative | This methodology focuses more on measuring and testing numerical data. What is the aim of quantitative research? | Surveys, tests, existing databases. |
Qualitative | Qualitative research is a process of collecting and analyzing both words and textual data. | Observations, interviews, focus groups. |
Mixed-method | A mixed-method approach combines both of the above approaches. | Where you can use a mixed method of research, this can produce some incredibly interesting results. This is due to testing in a way that provides data that is both proven to be exact while also being exploratory at the same time. |
➡️ Want to learn more about the differences between qualitative and quantitative research, and how to use both methods? Check out our guide for that!
If you've done your due diligence, you'll have an idea of which methodology approach is best suited to your research.
It’s likely that you will have carried out considerable reading and homework before you reach this point and you may have taken inspiration from other similar studies that have yielded good results.
Still, it is important to consider different options before setting your research in stone. Exploring different options available will help you to explain why the choice you ultimately make is preferable to other methods.
If proving your research problem requires you to gather large volumes of numerical data to test hypotheses, a quantitative research method is likely to provide you with the most usable results.
If instead you’re looking to try and learn more about people, and their perception of events, your methodology is more exploratory in nature and would therefore probably be better served using a qualitative research methodology.
It helps to always bring things back to the question: what do I want to achieve with my research?
Once you have conducted your research, you need to analyze it. Here are some helpful guides for qualitative data analysis:
➡️ How to do a content analysis
➡️ How to do a thematic analysis
➡️ How to do a rhetorical analysis
Research methodology refers to the techniques used to find and analyze information for a study, ensuring that the results are valid, reliable and that they address the research objective.
Data can typically be organized into four different categories or methods: observational, experimental, simulation, and derived.
Writing a methodology section is a process of introducing your methods and instruments, discussing your analysis, providing more background information, addressing your research limitations, and more.
Your research methodology section will need a clear research question and proposed research approach. You'll need to add a background, introduce your research question, write your methodology and add the works you cited during your data collecting phase.
The research methodology section of your study will indicate how valid your findings are and how well-informed your paper is. It also assists future researchers planning to use the same methodology, who want to cite your study or replicate it.
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Research methodology is a crucial aspect of any investigative process, serving as the blueprint for the entire research journey. If you are stuck in the methodology section of your research paper , then this blog will guide you on what is a research methodology, its types and how to successfully conduct one.
Table of Contents
Research methodology can be defined as the systematic framework that guides researchers in designing, conducting, and analyzing their investigations. It encompasses a structured set of processes, techniques, and tools employed to gather and interpret data, ensuring the reliability and validity of the research findings.
Research methodology is not confined to a singular approach; rather, it encapsulates a diverse range of methods tailored to the specific requirements of the research objectives.
Here is why Research methodology is important in academic and professional settings.
Research methodology forms the backbone of rigorous inquiry. It provides a structured approach that aids researchers in formulating precise thesis statements , selecting appropriate methodologies, and executing systematic investigations. This, in turn, enhances the quality and credibility of the research outcomes.
In both academic and professional contexts, the ability to reproduce research outcomes is paramount. A well-defined research methodology establishes clear procedures, making it possible for others to replicate the study. This not only validates the findings but also contributes to the cumulative nature of knowledge.
In professional settings, decisions often hinge on reliable data and insights. Research methodology equips professionals with the tools to gather pertinent information, analyze it rigorously, and derive meaningful conclusions.
This informed decision-making is instrumental in achieving organizational goals and staying ahead in competitive environments.
For academic researchers, adherence to robust research methodology is a hallmark of excellence. Institutions value research that adheres to high standards of methodology, fostering a culture of academic rigour and intellectual integrity. Furthermore, it prepares students with critical skills applicable beyond academia.
Research methodology instills a problem-solving mindset by encouraging researchers to approach challenges systematically. It equips individuals with the skills to dissect complex issues, formulate hypotheses , and devise effective strategies for investigation.
In the pursuit of knowledge and discovery, understanding the fundamentals of research methodology is paramount.
Research, in its essence, is a systematic and organized process of inquiry aimed at expanding our understanding of a particular subject or phenomenon. It involves the exploration of existing knowledge, the formulation of hypotheses, and the collection and analysis of data to draw meaningful conclusions.
Research is a dynamic and iterative process that contributes to the continuous evolution of knowledge in various disciplines.
Research takes on various forms, each tailored to the nature of the inquiry. Broadly classified, research can be categorized into two main types:
To conduct effective research, one must go through the different components of research methodology. These components form the scaffolding that supports the entire research process, ensuring its coherence and validity.
Research design serves as the blueprint for the entire research project. It outlines the overall structure and strategy for conducting the study. The three primary types of research design are:
Choosing the right data collection methods is crucial for obtaining reliable and relevant information. Common methods include:
Once data is collected, analysis becomes imperative to derive meaningful conclusions. Different methodologies exist for quantitative and qualitative data:
Selecting an appropriate research method is a critical decision in the research process. It determines the approach, tools, and techniques that will be used to answer the research questions.
Quantitative research involves the collection and analysis of numerical data, providing a structured and objective approach to understanding and explaining phenomena.
Experimental research involves manipulating variables to observe the effect on another variable under controlled conditions. It aims to establish cause-and-effect relationships.
Key Characteristics:
Applications: Commonly used in scientific studies and psychology to test hypotheses and identify causal relationships.
Survey research gathers information from a sample of individuals through standardized questionnaires or interviews. It aims to collect data on opinions, attitudes, and behaviours.
Applications: Widely employed in social sciences, marketing, and public opinion research to understand trends and preferences.
Descriptive research seeks to portray an accurate profile of a situation or phenomenon. It focuses on answering the ‘what,’ ‘who,’ ‘where,’ and ‘when’ questions.
Applications: Useful in situations where researchers want to understand and describe a phenomenon without altering it, common in social sciences and education.
Qualitative research emphasizes exploring and understanding the depth and complexity of phenomena through non-numerical data.
A case study is an in-depth exploration of a particular person, group, event, or situation. It involves detailed, context-rich analysis.
Applications: Common in social sciences, psychology, and business to investigate complex and specific instances.
Ethnography involves immersing the researcher in the culture or community being studied to gain a deep understanding of their behaviours, beliefs, and practices.
Applications: Widely used in anthropology, sociology, and cultural studies to explore and document cultural practices.
Grounded theory aims to develop theories grounded in the data itself. It involves systematic data collection and analysis to construct theories from the ground up.
Applications: Commonly applied in sociology, nursing, and management studies to generate theories from empirical data.
Research design is the structural framework that outlines the systematic process and plan for conducting a study. It serves as the blueprint, guiding researchers on how to collect, analyze, and interpret data.
Exploratory design.
Exploratory research design is employed when a researcher aims to explore a relatively unknown subject or gain insights into a complex phenomenon.
Applications: Valuable in the early stages of investigation, especially when the researcher seeks a deeper understanding of a subject before formalizing research questions.
Descriptive research design focuses on portraying an accurate profile of a situation, group, or phenomenon.
Applications: Widely used in social sciences, marketing, and educational research to provide detailed and objective descriptions.
Explanatory research design aims to identify the causes and effects of a phenomenon, explaining the ‘why’ and ‘how’ behind observed relationships.
Applications: Commonly employed in scientific studies and social sciences to delve into the underlying reasons behind observed patterns.
Cross-sectional design.
Cross-sectional designs collect data from participants at a single point in time.
Applications: Suitable for studying characteristics or behaviours that are stable or not expected to change rapidly.
Longitudinal designs involve the collection of data from the same participants over an extended period.
Applications: Ideal for studying developmental processes, trends, or the impact of interventions over time.
Experimental design.
Experimental designs involve manipulating variables under controlled conditions to observe the effect on another variable.
Applications: Commonly used in scientific studies, psychology, and medical research to establish causal relationships.
Non-experimental designs observe and describe phenomena without manipulating variables.
Applications: Suitable for studying complex phenomena in real-world settings where manipulation may not be ethical or feasible.
Effective data collection is fundamental to the success of any research endeavour.
Objective Design:
Structured Format:
Pilot Testing:
Sampling Strategy:
Establishing Rapport:
Open-Ended Questions:
Active Listening:
Ethical Considerations:
1. participant observation.
Immersive Participation:
Field Notes:
Ethical Awareness:
Objective Observation:
Data Reliability:
Contextual Understanding:
1. using existing data.
Identifying Relevant Archives:
Data Verification:
Ethical Use:
Incomplete or Inaccurate Archives:
Temporal Bias:
Access Limitations:
Conducting research is a complex and dynamic process, often accompanied by a myriad of challenges. Addressing these challenges is crucial to ensure the reliability and validity of research findings.
Sampling bias:.
Measurement error:.
Timeline pressures:.
Selection bias:.
Conducting successful research relies not only on the application of sound methodologies but also on strategic planning and effective collaboration. Here are some tips to enhance the success of your research methodology:
Well-defined research objectives guide the entire research process. Clearly articulate the purpose of your study, outlining specific research questions or hypotheses.
A thorough literature review provides a foundation for understanding existing knowledge and identifying gaps. Invest time in reviewing relevant literature to inform your research design and methodology.
A detailed plan serves as a roadmap, ensuring all aspects of the research are systematically addressed. Develop a detailed research plan outlining timelines, milestones, and tasks.
Ethical practices are fundamental to maintaining the integrity of research. Address ethical considerations early, obtain necessary approvals, and ensure participant rights are safeguarded.
Research methodologies evolve, and staying updated is essential for employing the most effective techniques. Engage in continuous learning by attending workshops, conferences, and reading recent publications.
Unforeseen challenges may arise during research, necessitating adaptability in methods. Be flexible and willing to modify your approach when needed, ensuring the integrity of the study.
Research is often an iterative process, and refining methods based on ongoing findings enhance the study’s robustness. Regularly review and refine your research design and methods as the study progresses.
What is the research methodology.
Research methodology is the systematic process of planning, executing, and evaluating scientific investigation. It encompasses the techniques, tools, and procedures used to collect, analyze, and interpret data, ensuring the reliability and validity of research findings.
Research methodologies include qualitative and quantitative approaches. Qualitative methods involve in-depth exploration of non-numerical data, while quantitative methods use statistical analysis to examine numerical data. Mixed methods combine both approaches for a comprehensive understanding of research questions.
To write a research methodology, clearly outline the study’s design, data collection, and analysis procedures. Specify research tools, participants, and sampling methods. Justify choices and discuss limitations. Ensure clarity, coherence, and alignment with research objectives for a robust methodology section.
In the methodology section of a research paper, describe the study’s design, data collection, and analysis methods. Detail procedures, tools, participants, and sampling. Justify choices, address ethical considerations, and explain how the methodology aligns with research objectives, ensuring clarity and rigour.
Mixed research methodology combines both qualitative and quantitative research approaches within a single study. This approach aims to enhance the details and depth of research findings by providing a more comprehensive understanding of the research problem or question.
A preliminary literature review is an initial exploration of existing research on a topic, setting the foundation for in-depth study.
Explore the essential elements in choosing effective control variables for robust and valid research outcomes.
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The methods section describes actions taken to investigate a research problem and the rationale for the application of specific procedures or techniques used to identify, select, process, and analyze information applied to understanding the problem, thereby, allowing the reader to critically evaluate a study’s overall validity and reliability. The methodology section of a research paper answers two main questions: How was the data collected or generated? And, how was it analyzed? The writing should be direct and precise and always written in the past tense.
Kallet, Richard H. "How to Write the Methods Section of a Research Paper." Respiratory Care 49 (October 2004): 1229-1232.
You must explain how you obtained and analyzed your results for the following reasons:
Bem, Daryl J. Writing the Empirical Journal Article. Psychology Writing Center. University of Washington; Denscombe, Martyn. The Good Research Guide: For Small-Scale Social Research Projects . 5th edition. Buckingham, UK: Open University Press, 2014; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008.
I. Groups of Research Methods
There are two main groups of research methods in the social sciences:
II. Content
The introduction to your methodology section should begin by restating the research problem and underlying assumptions underpinning your study. This is followed by situating the methods you used to gather, analyze, and process information within the overall “tradition” of your field of study and within the particular research design you have chosen to study the problem. If the method you choose lies outside of the tradition of your field [i.e., your review of the literature demonstrates that the method is not commonly used], provide a justification for how your choice of methods specifically addresses the research problem in ways that have not been utilized in prior studies.
The remainder of your methodology section should describe the following:
In addition, an effectively written methodology section should:
NOTE: Once you have written all of the elements of the methods section, subsequent revisions should focus on how to present those elements as clearly and as logically as possibly. The description of how you prepared to study the research problem, how you gathered the data, and the protocol for analyzing the data should be organized chronologically. For clarity, when a large amount of detail must be presented, information should be presented in sub-sections according to topic. If necessary, consider using appendices for raw data.
ANOTHER NOTE: If you are conducting a qualitative analysis of a research problem , the methodology section generally requires a more elaborate description of the methods used as well as an explanation of the processes applied to gathering and analyzing of data than is generally required for studies using quantitative methods. Because you are the primary instrument for generating the data [e.g., through interviews or observations], the process for collecting that data has a significantly greater impact on producing the findings. Therefore, qualitative research requires a more detailed description of the methods used.
YET ANOTHER NOTE: If your study involves interviews, observations, or other qualitative techniques involving human subjects , you may be required to obtain approval from the university's Office for the Protection of Research Subjects before beginning your research. This is not a common procedure for most undergraduate level student research assignments. However, i f your professor states you need approval, you must include a statement in your methods section that you received official endorsement and adequate informed consent from the office and that there was a clear assessment and minimization of risks to participants and to the university. This statement informs the reader that your study was conducted in an ethical and responsible manner. In some cases, the approval notice is included as an appendix to your paper.
III. Problems to Avoid
Irrelevant Detail The methodology section of your paper should be thorough but concise. Do not provide any background information that does not directly help the reader understand why a particular method was chosen, how the data was gathered or obtained, and how the data was analyzed in relation to the research problem [note: analyzed, not interpreted! Save how you interpreted the findings for the discussion section]. With this in mind, the page length of your methods section will generally be less than any other section of your paper except the conclusion.
Unnecessary Explanation of Basic Procedures Remember that you are not writing a how-to guide about a particular method. You should make the assumption that readers possess a basic understanding of how to investigate the research problem on their own and, therefore, you do not have to go into great detail about specific methodological procedures. The focus should be on how you applied a method , not on the mechanics of doing a method. An exception to this rule is if you select an unconventional methodological approach; if this is the case, be sure to explain why this approach was chosen and how it enhances the overall process of discovery.
Problem Blindness It is almost a given that you will encounter problems when collecting or generating your data, or, gaps will exist in existing data or archival materials. Do not ignore these problems or pretend they did not occur. Often, documenting how you overcame obstacles can form an interesting part of the methodology. It demonstrates to the reader that you can provide a cogent rationale for the decisions you made to minimize the impact of any problems that arose.
Literature Review Just as the literature review section of your paper provides an overview of sources you have examined while researching a particular topic, the methodology section should cite any sources that informed your choice and application of a particular method [i.e., the choice of a survey should include any citations to the works you used to help construct the survey].
It’s More than Sources of Information! A description of a research study's method should not be confused with a description of the sources of information. Such a list of sources is useful in and of itself, especially if it is accompanied by an explanation about the selection and use of the sources. The description of the project's methodology complements a list of sources in that it sets forth the organization and interpretation of information emanating from those sources.
Azevedo, L.F. et al. "How to Write a Scientific Paper: Writing the Methods Section." Revista Portuguesa de Pneumologia 17 (2011): 232-238; Blair Lorrie. “Choosing a Methodology.” In Writing a Graduate Thesis or Dissertation , Teaching Writing Series. (Rotterdam: Sense Publishers 2016), pp. 49-72; Butin, Dan W. The Education Dissertation A Guide for Practitioner Scholars . Thousand Oaks, CA: Corwin, 2010; Carter, Susan. Structuring Your Research Thesis . New York: Palgrave Macmillan, 2012; Kallet, Richard H. “How to Write the Methods Section of a Research Paper.” Respiratory Care 49 (October 2004):1229-1232; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008. Methods Section. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Rudestam, Kjell Erik and Rae R. Newton. “The Method Chapter: Describing Your Research Plan.” In Surviving Your Dissertation: A Comprehensive Guide to Content and Process . (Thousand Oaks, Sage Publications, 2015), pp. 87-115; What is Interpretive Research. Institute of Public and International Affairs, University of Utah; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University; Methods and Materials. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College.
Statistical Designs and Tests? Do Not Fear Them!
Don't avoid using a quantitative approach to analyzing your research problem just because you fear the idea of applying statistical designs and tests. A qualitative approach, such as conducting interviews or content analysis of archival texts, can yield exciting new insights about a research problem, but it should not be undertaken simply because you have a disdain for running a simple regression. A well designed quantitative research study can often be accomplished in very clear and direct ways, whereas, a similar study of a qualitative nature usually requires considerable time to analyze large volumes of data and a tremendous burden to create new paths for analysis where previously no path associated with your research problem had existed.
To locate data and statistics, GO HERE .
Knowing the Relationship Between Theories and Methods
There can be multiple meaning associated with the term "theories" and the term "methods" in social sciences research. A helpful way to delineate between them is to understand "theories" as representing different ways of characterizing the social world when you research it and "methods" as representing different ways of generating and analyzing data about that social world. Framed in this way, all empirical social sciences research involves theories and methods, whether they are stated explicitly or not. However, while theories and methods are often related, it is important that, as a researcher, you deliberately separate them in order to avoid your theories playing a disproportionate role in shaping what outcomes your chosen methods produce.
Introspectively engage in an ongoing dialectic between the application of theories and methods to help enable you to use the outcomes from your methods to interrogate and develop new theories, or ways of framing conceptually the research problem. This is how scholarship grows and branches out into new intellectual territory.
Reynolds, R. Larry. Ways of Knowing. Alternative Microeconomics . Part 1, Chapter 3. Boise State University; The Theory-Method Relationship. S-Cool Revision. United Kingdom.
Methods and the Methodology
Do not confuse the terms "methods" and "methodology." As Schneider notes, a method refers to the technical steps taken to do research . Descriptions of methods usually include defining and stating why you have chosen specific techniques to investigate a research problem, followed by an outline of the procedures you used to systematically select, gather, and process the data [remember to always save the interpretation of data for the discussion section of your paper].
The methodology refers to a discussion of the underlying reasoning why particular methods were used . This discussion includes describing the theoretical concepts that inform the choice of methods to be applied, placing the choice of methods within the more general nature of academic work, and reviewing its relevance to examining the research problem. The methodology section also includes a thorough review of the methods other scholars have used to study the topic.
Bryman, Alan. "Of Methods and Methodology." Qualitative Research in Organizations and Management: An International Journal 3 (2008): 159-168; Schneider, Florian. “What's in a Methodology: The Difference between Method, Methodology, and Theory…and How to Get the Balance Right?” PoliticsEastAsia.com. Chinese Department, University of Leiden, Netherlands.
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The research methodology section of any academic research paper gives you the opportunity to convince your readers that your research is useful and will contribute to your field of study. An effective research methodology is grounded in your overall approach – whether qualitative or quantitative – and adequately describes the methods you used. Justify why you chose those methods over others, then explain how those methods will provide answers to your research questions. [1] X Research source
To write a research methodology, start with a section that outlines the problems or questions you'll be studying, including your hypotheses or whatever it is you're setting out to prove. Then, briefly explain why you chose to use either a qualitative or quantitative approach for your study. Next, go over when and where you conducted your research and what parameters you used to ensure you were objective. Finally, cite any sources you used to decide on the methodology for your research. To learn how to justify your choice of methods in your research methodology, scroll down! Did this summary help you? Yes No
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Research methodology is the backbone of any successful study, providing a structured approach to collecting and analysing data. It encompasses a broad spectrum of methods, each with specific processes and applications, tailored to answer distinct research questions.
This article will explore various types of research methodologies, delve into their processes, and illustrate with examples how they are applied in real-world research.
Understanding these methodologies is essential for any researcher aiming to conduct thorough and impactful studies.
Research methodology contains various strategies and approaches to conduct scientific research, each tailored to specific types of questions and data.
Think of research methodology as the master plan for your study. It guides you on why and how to gather and analyse data, ensuring your approach aligns perfectly with your research question.
This methodology includes deciding between qualitative research, which explores topics in depth through interviews or focus groups, or quantitative research, which quantifies data through surveys and statistical analysis.
There is even an option to mix both, and approach called the mixed method.
If you’re analysing the lived experiences of individuals in a specific setting, qualitative methodologies allow you to capture the nuances of human emotions and behaviours through detailed narratives.
Quantitative methodologies would enable you to measure and compare these experiences in a more structured, numerical format.
Choosing a robust methodology not only provides the rationale for the methods you choose but also highlights the research limitations and ethical considerations, keeping your study transparent and grounded.
It’s a thoughtful composition that gives research its direction and purpose, much like how an architect’s plan is essential before the actual construction begins.
Qualitative research dives deep into the social context of a topic. It collects words and textual data rather than numerical data.
Within the family, qualitative research methodologies can be broken down into several approaches:
Ethnography: Deeply rooted in the traditions of anthropology, you immerse yourself in the community or social setting you’re studying when conducting an ethnography study.
Case Study Research: Here, you explore the complexity of a single case in detail. This could be an institution, a group, or an individual. You might look into interviews, documents, and reports, to build a comprehensive picture of the subject.
Grounded Theory: Here, you try to generate theories from the data itself rather than testing existing hypotheses. You might start with a research question but allow your theories to develop as you gather more data.
Narrative Research: You explore the stories people tell about their lives and personal experiences in their own words. Through techniques like in-depth interviews or life story collections, you analyse the narrative to understand the individual’s experiences.
Discourse Analysis: You analyse written or spoken words to understand the social norms and power structures that underlie the language used. This method can reveal a lot about the social context and the dynamics of power in communication.
These methods help to uncover patterns in how people think and interact. For example, in exploring consumer attitudes toward a new product, you would likely conduct focus groups or participant observations to gather qualitative data.
This method helps you understand the motivations and feelings behind consumer choices.
Quantitative research relies on numerical data to find patterns and test hypotheses. This methodology uses statistical analysis to quantify data and uncover relationships between variables.
There are several approaches in quantitative research:
Experimental Research: This is the gold standard when you aim to determine causality. By manipulating one variable and controlling others, you observe changes in the dependent variables.
Survey Research: A popular approach, because of its efficiency in collecting data from a large sample of participants. By using standardised questions, you can gather data that are easy to analyse statistically.
Correlational Research: This approach tries to identify relationships between two or more variables without establishing a causal link. The strength and direction of these relationships are quantified, albeit without confirming one variable causes another.
Longitudinal Studies: You track variables over time, providing a dynamic view of how situations evolve. This approach requires commitment and can be resource-intensive, but the depth of data they provide is unparalleled.
Cross-sectional Studies: Offers a snapshot of a population at a single point in time. They are quicker and cheaper than longitudinal studies.
Mixed methods research combines both approaches to benefit from the depth of qualitative data and the breadth of quantitative analysis.
You might start with qualitative interviews to develop hypotheses about health behaviours in a community. Then, you could conduct a large-scale survey to test these hypotheses quantitatively.
This approach is particularly useful when you want to explore a new area where previous data may not exist, giving you a comprehensive insight into both the empirical and social dimensions of a research problem.
When you dive into a research project, choosing the right methodology is akin to selecting the best tools for building a house.
It shapes how you approach the research question, gather data, and interpret the results. Here are a couple of crucial factors to keep in mind.
The type of research question you pose can heavily influence the methodology you choose. Qualitative methodologies are superb for exploratory research where you aim to understand concepts, perceptions, and experiences.
If you’re exploring how patients feel about a new healthcare policy, interviews and focus groups would be instrumental.
Quantitative methods are your go-to for questions that require measurable and statistical data, like assessing the prevalence of a medical condition across different regions.
Consider what data is necessary to address your research question effectively. Qualitative data can provide depth and detail through:
This makes qualitative method ideal for understanding complex social interactions or historical contexts.
Quantitative data, however, offers the breadth and is often numerical, allowing for a broad analysis of patterns and correlations.
If your study aims to investigate both the breadth and depth, a mixed methods approach might be necessary, enabling you to draw on the strengths of both qualitative and quantitative data.
While deciding on research methodology, you must evaluate the resources available, including:
Quantitative research often requires larger samples and hence, might be more costly and time-consuming.
Qualitative research, while generally less resource-intensive, demands substantial time for data collection and analysis, especially if you conduct lengthy interviews or detailed content analysis.
If resources are limited, adapting your methodology to fit these constraints without compromising the integrity of your research is crucial.
Your familiarity and comfort level with various research methodologies will significantly affect your choice.
Conducting sophisticated statistical analyses requires a different skill set than carrying out in-depth qualitative interviews.
If your background is in social science, you might find qualitative methods more within your wheelhouse; whereas, a postgraduate student in epidemiology might be more adept at quantitative methods.
It’s also worth considering the availability of workshops, courses, or collaborators who could complement your skills.
Different methodologies raise different ethical concerns.
In qualitative research, maintaining anonymity and dealing with sensitive information can be challenging, especially when using direct quotes or detailed descriptions from participants.
Quantitative research might involve considerations around participant consent for large surveys or experiments.
Practically, you need to think about the sampling design to ensure it is representative of the population studied. Non-probability sampling might be quicker and cheaper but can introduce bias, limiting the generalisability of your findings.
By meticulously considering these factors, you tailor your research design to not just answer the research questions effectively but also to reflect the realities of your operational environment.
This thoughtful approach helps ensure that your research is not only robust but also practical and ethical, standing up to both academic scrutiny and real-world application.
Research methodology is a crucial framework that guides the entire research process. It involves choosing between various qualitative and quantitative approaches, each tailored to specific research questions and objectives.
Your chosen methodology shapes how data is gathered, analysed, and interpreted, ultimately influencing the reliability and validity of your research findings.
Understanding these methodologies ensures that researchers can effectively write research proposal, address their study’s aims and contribute valuable insights to their field.
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Table of Contents
Choosing an optimal research methodology is crucial for the success of any research project. The methodology you select will determine the type of data you collect, how you collect it, and how you analyse it. Understanding the different types of research methods available along with their strengths and weaknesses, is thus imperative to make an informed decision.
There are several research methods available depending on the type of study you are conducting, i.e., whether it is laboratory-based, clinical, epidemiological, or survey based . Some common methodologies include qualitative research, quantitative research, experimental research, survey-based research, and action research. Each method can be opted for and modified, depending on the type of research hypotheses and objectives.
When deciding on a research methodology, one of the key factors to consider is whether your research will be qualitative or quantitative. Qualitative research is used to understand people’s experiences, concepts, thoughts, or behaviours . Quantitative research, on the contrary, deals with numbers, graphs, and charts, and is used to test or confirm hypotheses, assumptions, and theories.
Qualitative research is often used to examine issues that are not well understood, and to gather additional insights on these topics. Qualitative research methods include open-ended survey questions, observations of behaviours described through words, and reviews of literature that has explored similar theories and ideas. These methods are used to understand how language is used in real-world situations, identify common themes or overarching ideas, and describe and interpret various texts. Data analysis for qualitative research typically includes discourse analysis, thematic analysis, and textual analysis.
The goal of quantitative research is to test hypotheses, confirm assumptions and theories, and determine cause-and-effect relationships. Quantitative research methods include experiments, close-ended survey questions, and countable and numbered observations. Data analysis for quantitative research relies heavily on statistical methods.
The methods used for data analysis also differ for qualitative and quantitative research. As mentioned earlier, quantitative data is generally analysed using statistical methods and does not leave much room for speculation. It is more structured and follows a predetermined plan. In quantitative research, the researcher starts with a hypothesis and uses statistical methods to test it. Contrarily, methods used for qualitative data analysis can identify patterns and themes within the data, rather than provide statistical measures of the data. It is an iterative process, where the researcher goes back and forth trying to gauge the larger implications of the data through different perspectives and revising the analysis if required.
The choice between qualitative and quantitative research will depend on the gap that the research project aims to address, and specific objectives of the study. If the goal is to establish facts about a subject or topic, quantitative research is an appropriate choice. However, if the goal is to understand people’s experiences or perspectives, qualitative research may be more suitable.
In conclusion, an understanding of the different research methods available, their applicability, advantages, and disadvantages is essential for making an informed decision on the best methodology for your project. If you need any additional guidance on which research methodology to opt for, you can head over to Elsevier Author Services (EAS). EAS experts will guide you throughout the process and help you choose the perfect methodology for your research goals.
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Quantitative research methodologies, qualitative research methodologies, mixed method methodologies, selecting a methodology.
According to Dawson (2019),a research methodology is the primary principle that will guide your research. It becomes the general approach in conducting research on your topic and determines what research method you will use. A research methodology is different from a research method because research methods are the tools you use to gather your data (Dawson, 2019). You must consider several issues when it comes to selecting the most appropriate methodology for your topic. Issues might include research limitations and ethical dilemmas that might impact the quality of your research. Descriptions of each type of methodology are included below.
Quantitative research methodologies are meant to create numeric statistics by using survey research to gather data (Dawson, 2019). This approach tends to reach a larger amount of people in a shorter amount of time. According to Labaree (2020), there are three parts that make up a quantitative research methodology:
Once you decide on a methodology, you can consider the method to which you will apply your methodology.
Qualitative research methodologies examine the behaviors, opinions, and experiences of individuals through methods of examination (Dawson, 2019). This type of approach typically requires less participants, but more time with each participant. It gives research subjects the opportunity to provide their own opinion on a certain topic.
Examples of Qualitative Research Methodologies
A mixed methodology allows you to implement the strengths of both qualitative and quantitative research methods. In some cases, you may find that your research project would benefit from this. This approach is beneficial because it allows each methodology to counteract the weaknesses of the other (Dawson, 2019). You should consider this option carefully, as it can make your research complicated if not planned correctly.
What should you do to decide on a research methodology? The most logical way to determine your methodology is to decide whether you plan on conducting qualitative or qualitative research. You also have the option to implement a mixed methods approach. Looking back on Dawson's (2019) five "W's" on the previous page , may help you with this process. You should also look for key words that indicate a specific type of research methodology in your hypothesis or proposal. Some words may lean more towards one methodology over another.
Quantitative Research Key Words
Qualitative Research Key Words
This article is part of an ongoing series on academic writing help of scholarly articles. Previous parts explored how to write an introduction for a research paper and a literature review outline and format .
The Methodology section portrays the reasoning for the application of certain techniques and methods in the context of the study.
For your academic article, when you describe and explain your chosen methods it is very important to correlate them to your research questions and/or hypotheses. The description of the methods used should include enough details so that the study can be replicated by other Researchers, or at least repeated in a similar situation or framework.
Every stage of your research needs to be explained and justified with clear information on why you chose those particular methods, and how they help you answer your research question or purpose.
As the Authors, in this section you get to explain the rationale of your article for other Researchers. You should focus on answering the following questions:
The responses to these questions should be clear and precise, and the answers should be written in past tense.
First off, let’s establish the differences between research methods and research methodology.
As an Academic and Author of valuable research papers, it’s important not to confuse these two terms.
Research Methodology refers the discussion regarding the specific methods chosen and used in a research paper. This discussion also encompasses the theoretical concepts that further provide information about the methods selection and application.
In other words, you should highlight how these theoretical concepts are connected with these methods in a larger knowledge framework and explain their relevance in examining the purpose, problem and questions of your study. Thus, the discussion that forms your academic article’s research methodology also incorporates an extensive literature review about similar methods, used by other Authors to examine a certain research subject.
A Research Method represents the technical steps involved in conducting the research. Details about the methods focus on characterizing and defining them, but also explaining your chosen techniques, and providing a full account on the procedures used for selecting, collecting and analyzing the data.
The methodology section is very important for the credibility of your article and for a professional academic writing style.
Readers, academics and other researchers need to know how the information used in your academic article was collected. The research methods used for collecting or generating data will influence the discoveries and, by extension, how you will interpret them and explain their contribution to general knowledge.
The most basic methods for data collection are:
Secondary data are data that have been previously collected or gathered for other purposes than the aim of the academic article’s study. This type of data is already available, in different forms, from a variety of sources.
Secondary data collection could lead to Internal or External secondary data research.
Primary data represent data originated for the specific purpose of the study, with its research questions. The methods vary on how Authors and Researchers conduct an experiment, survey or study, but, in general, it uses a particular scientific method.
Primary data collection could lead to Quantitative and Qualitative research.
Readers need to understand how the information was gathered or generated in a way that is consistent with research practices in a field of study . For instance, if you are using a multiple choice survey, the readers need to know which questionnaire items you have examined in your primary quantitative research. Similarly, if your academic article involves secondary data from FED or Eurostat it is important to mention the variables used in your study, their values, and their time-frame.
For primary research, that involve surveys, experiments or observations, for a valuable academic article, Authors should provide information about:
Establishing the main premises of methodology is pivotal for any research because a method or technique that is not reliable for a certain study context will lead to unreliable results, and the outcomes’ interpretation (and overall academic article) will not be valuable.
In most cases, there is a wide variety of methods and procedures that you can use to explore a research topic in your academic article. The methods section should fully explain the reasons for choosing a specific methodology or technique .
Also, it’s essential that you describe the specific research methods of data collection you are going to use , whether they are primary or secondary data collection.
For primary research methods, describe the surveys, interviews, observation methods, etc.
For secondary research methods, describe how the data was originally created, gathered and which institution created and published it.
For this aspect that characterizes a good research methodology, indicate how the research approach fits with the general study , considering the literature review outline and format , and the following sections.
The methods you choose should have a clear connection with the overall research approach and you need to explain the reasons for choosing the research techniques in your study, and how they help you towards understanding your study’s purpose.
This section should also focus on information on how you intend to analyze your results .
Describe how you plan and intend to achieve an accurate assessment of the hypotheses, relationships, patterns, trends, distributions associated with your data and research purpose.
The data type, how it was measured, and which statistical tests were conducted and performed, should be detailed and reported in an accurate manner.
For explaining the data analysis methods, you should aim to answer questions, such as:
There are certain aspects that you need to pay extra attention in relation to your research methodology section. The most common issues to avoid are:
You may also like, related policies and links, responsibilities of the publisher in the relationship with journal editors, general duties of publisher.
Table of Contents
Before conducting a study, a research proposal should be created that outlines researchers’ plans and methodology and is submitted to the concerned evaluating organization or person. Creating a research proposal is an important step to ensure that researchers are on track and are moving forward as intended. A research proposal can be defined as a detailed plan or blueprint for the proposed research that you intend to undertake. It provides readers with a snapshot of your project by describing what you will investigate, why it is needed, and how you will conduct the research.
Your research proposal should aim to explain to the readers why your research is relevant and original, that you understand the context and current scenario in the field, have the appropriate resources to conduct the research, and that the research is feasible given the usual constraints.
This article will describe in detail the purpose and typical structure of a research proposal , along with examples and templates to help you ace this step in your research journey.
A research proposal¹ ,² can be defined as a formal report that describes your proposed research, its objectives, methodology, implications, and other important details. Research proposals are the framework of your research and are used to obtain approvals or grants to conduct the study from various committees or organizations. Consequently, research proposals should convince readers of your study’s credibility, accuracy, achievability, practicality, and reproducibility.
With research proposals , researchers usually aim to persuade the readers, funding agencies, educational institutions, and supervisors to approve the proposal. To achieve this, the report should be well structured with the objectives written in clear, understandable language devoid of jargon. A well-organized research proposal conveys to the readers or evaluators that the writer has thought out the research plan meticulously and has the resources to ensure timely completion.
A research proposal is a sales pitch and therefore should be detailed enough to convince your readers, who could be supervisors, ethics committees, universities, etc., that what you’re proposing has merit and is feasible . Research proposals can help students discuss their dissertation with their faculty or fulfill course requirements and also help researchers obtain funding. A well-structured proposal instills confidence among readers about your ability to conduct and complete the study as proposed.
Research proposals can be written for several reasons:³
Research proposals should aim to answer the three basic questions—what, why, and how.
The What question should be answered by describing the specific subject being researched. It should typically include the objectives, the cohort details, and the location or setting.
The Why question should be answered by describing the existing scenario of the subject, listing unanswered questions, identifying gaps in the existing research, and describing how your study can address these gaps, along with the implications and significance.
The How question should be answered by describing the proposed research methodology, data analysis tools expected to be used, and other details to describe your proposed methodology.
Here is a research proposal sample template (with examples) from the University of Rochester Medical Center. 4 The sections in all research proposals are essentially the same although different terminology and other specific sections may be used depending on the subject.
If you want to know how to make a research proposal impactful, include the following components:¹
1. Introduction
This section provides a background of the study, including the research topic, what is already known about it and the gaps, and the significance of the proposed research.
2. Literature review
This section contains descriptions of all the previous relevant studies pertaining to the research topic. Every study cited should be described in a few sentences, starting with the general studies to the more specific ones. This section builds on the understanding gained by readers in the Introduction section and supports it by citing relevant prior literature, indicating to readers that you have thoroughly researched your subject.
3. Objectives
Once the background and gaps in the research topic have been established, authors must now state the aims of the research clearly. Hypotheses should be mentioned here. This section further helps readers understand what your study’s specific goals are.
4. Research design and methodology
Here, authors should clearly describe the methods they intend to use to achieve their proposed objectives. Important components of this section include the population and sample size, data collection and analysis methods and duration, statistical analysis software, measures to avoid bias (randomization, blinding), etc.
5. Ethical considerations
This refers to the protection of participants’ rights, such as the right to privacy, right to confidentiality, etc. Researchers need to obtain informed consent and institutional review approval by the required authorities and mention this clearly for transparency.
6. Budget/funding
Researchers should prepare their budget and include all expected expenditures. An additional allowance for contingencies such as delays should also be factored in.
7. Appendices
This section typically includes information that supports the research proposal and may include informed consent forms, questionnaires, participant information, measurement tools, etc.
8. Citations
Writing a research proposal begins much before the actual task of writing. Planning the research proposal structure and content is an important stage, which if done efficiently, can help you seamlessly transition into the writing stage. 3,5
Key Takeaways
Here’s a summary of the main points about research proposals discussed in the previous sections:
Q1. How is a research proposal evaluated?
A1. In general, most evaluators, including universities, broadly use the following criteria to evaluate research proposals . 6
Q2. What is the difference between the Introduction and Literature Review sections in a research proposal ?
A2. The Introduction or Background section in a research proposal sets the context of the study by describing the current scenario of the subject and identifying the gaps and need for the research. A Literature Review, on the other hand, provides references to all prior relevant literature to help corroborate the gaps identified and the research need.
Q3. How long should a research proposal be?
A3. Research proposal lengths vary with the evaluating authority like universities or committees and also the subject. Here’s a table that lists the typical research proposal lengths for a few universities.
Arts programs | 1,000-1,500 | |
University of Birmingham | Law School programs | 2,500 |
PhD | 2,500 | |
2,000 | ||
Research degrees | 2,000-3,500 |
Q4. What are the common mistakes to avoid in a research proposal ?
A4. Here are a few common mistakes that you must avoid while writing a research proposal . 7
Thus, a research proposal is an essential document that can help you promote your research and secure funds and grants for conducting your research. Consequently, it should be well written in clear language and include all essential details to convince the evaluators of your ability to conduct the research as proposed.
This article has described all the important components of a research proposal and has also provided tips to improve your writing style. We hope all these tips will help you write a well-structured research proposal to ensure receipt of grants or any other purpose.
References
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How to write a phd research proposal.
The future of academia: how ai tools are changing the way we do research, you may also like, dissertation printing and binding | types & comparison , what is a dissertation preface definition and examples , how to write your research paper in apa..., how to choose a dissertation topic, how to write an academic paragraph (step-by-step guide), maintaining academic integrity with paperpal’s generative ai writing..., research funding basics: what should a grant proposal..., how to write an abstract in research papers..., how to write dissertation acknowledgements.
Published: August 08, 2024
One of the most underrated skills you can have as a marketer is marketing research — which is great news for this unapologetic cyber sleuth.
From brand design and product development to buyer personas and competitive analysis, I’ve researched a number of initiatives in my decade-long marketing career.
And let me tell you: having the right marketing research methods in your toolbox is a must.
Market research is the secret to crafting a strategy that will truly help you accomplish your goals. The good news is there is no shortage of options.
Thanks to the Internet, we have more marketing research (or market research) methods at our fingertips than ever, but they’re not all created equal. Let’s quickly go over how to choose the right one.
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What are you researching? Do you need to understand your audience better? How about your competition? Or maybe you want to know more about your customer’s feelings about a specific product.
Before starting your research, take some time to identify precisely what you’re looking for. This could be a goal you want to reach, a problem you need to solve, or a question you need to answer.
For example, an objective may be as foundational as understanding your ideal customer better to create new buyer personas for your marketing agency (pause for flashbacks to my former life).
Or if you’re an organic sode company, it could be trying to learn what flavors people are craving.
Next, determine what data type will best answer the problems or questions you identified. There are primarily two types: qualitative and quantitative. (Sound familiar, right?)
Understanding the differences between qualitative and quantitative data will help you pinpoint which research methods will yield the desired results.
For instance, thinking of our earlier examples, qualitative data would usually be best suited for buyer personas, while quantitative data is more useful for the soda flavors.
However, truth be told, the two really work together.
Qualitative conclusions are usually drawn from quantitative, numerical data. So, you’ll likely need both to get the complete picture of your subject.
For example, if your quantitative data says 70% of people are Team Black and only 30% are Team Green — Shout out to my fellow House of the Dragon fans — your qualitative data will say people support Black more than Green.
(As they should.)
You’ll also want to understand the difference between primary and secondary research.
Primary research involves collecting new, original data directly from the source (say, your target market). In other words, it’s information gathered first-hand that wasn’t found elsewhere.
Some examples include conducting experiments, surveys, interviews, observations, or focus groups.
Meanwhile, secondary research is the analysis and interpretation of existing data collected from others. Think of this like what we used to do for school projects: We would read a book, scour the internet, or pull insights from others to work from.
So, which is better?
Personally, I say any research is good research, but if you have the time and resources, primary research is hard to top. With it, you don’t have to worry about your source's credibility or how relevant it is to your specific objective.
You are in full control and best equipped to get the reliable information you need.
Once you know your objective and what kind of data you want, you’re ready to select your marketing research method.
For instance, let’s say you’re a restaurant trying to see how attendees felt about the Speed Dating event you hosted last week.
You shouldn’t run a field experiment or download a third-party report on speed dating events; those would be useless to you. You need to conduct a survey that allows you to ask pointed questions about the event.
This would yield both qualitative and quantitative data you can use to improve and bring together more love birds next time around.
Now that you know what you’re looking for in a marketing research method, let’s dive into the best options.
Note: According to HubSpot’s 2024 State of Marketing report, understanding customers and their needs is one of the biggest challenges facing marketers today. The options we discuss are great consumer research methodologies , but they can also be used for other areas.
1. interviews.
Interviews are a form of primary research where you ask people specific questions about a topic or theme. They typically deliver qualitative information.
I’ve conducted many interviews for marketing purposes, but I’ve also done many for journalistic purposes, like this profile on comedian Zarna Garg . There’s no better way to gather candid, open-ended insights in my book, but that doesn’t mean they’re a cure-all.
What I like: Real-time conversations allow you to ask different questions if you’re not getting the information you need. They also push interviewees to respond quickly, which can result in more authentic answers.
What I dislike: They can be time-consuming and harder to measure (read: get quantitative data) unless you ask pointed yes or no questions.
Best for: Creating buyer personas or getting feedback on customer experience, a product, or content.
Focus groups are similar to conducting interviews but on a larger scale.
In marketing and business, this typically means getting a small group together in a room (or Zoom), asking them questions about various topics you are researching. You record and/or observe their responses to then take action.
They are ideal for collecting long-form, open-ended feedback, and subjective opinions.
One well-known focus group you may remember was run by Domino’s Pizza in 2009 .
After poor ratings and dropping over $100 million in revenue, the brand conducted focus groups with real customers to learn where they could have done better.
It was met with comments like “worst excuse for pizza I’ve ever had” and “the crust tastes like cardboard.” But rather than running from the tough love, it took the hit and completely overhauled its recipes.
The team admitted their missteps and returned to the market with better food and a campaign detailing their “Pizza Turn Around.”
The result? The brand won a ton of praise for its willingness to take feedback, efforts to do right by its consumers, and clever campaign. But, most importantly, revenue for Domino’s rose by 14.3% over the previous year.
The brand continues to conduct focus groups and share real footage from them in its promotion:
What I like: Similar to interviewing, you can dig deeper and pivot as needed due to the real-time nature. They’re personal and detailed.
What I dislike: Once again, they can be time-consuming and make it difficult to get quantitative data. There is also a chance some participants may overshadow others.
Best for: Product research or development
Pro tip: Need help planning your focus group? Our free Market Research Kit includes a handy template to start organizing your thoughts in addition to a SWOT Analysis Template, Survey Template, Focus Group Template, Presentation Template, Five Forces Industry Analysis Template, and an instructional guide for all of them. Download yours here now.
Surveys are a form of primary research where individuals are asked a collection of questions. It can take many different forms.
They could be in person, over the phone or video call, by email, via an online form, or even on social media. Questions can be also open-ended or closed to deliver qualitative or quantitative information.
A great example of a close-ended survey is HubSpot’s annual State of Marketing .
In the State of Marketing, HubSpot asks marketing professionals from around the world a series of multiple-choice questions to gather data on the state of the marketing industry and to identify trends.
The survey covers various topics related to marketing strategies, tactics, tools, and challenges that marketers face. It aims to provide benchmarks to help you make informed decisions about your marketing.
It also helps us understand where our customers’ heads are so we can better evolve our products to meet their needs.
Apple is no stranger to surveys, either.
In 2011, the tech giant launched Apple Customer Pulse , which it described as “an online community of Apple product users who provide input on a variety of subjects and issues concerning Apple.”
"For example, we did a large voluntary survey of email subscribers and top readers a few years back."
While these readers gave us a long list of topics, formats, or content types they wanted to see, they sometimes engaged more with content types they didn’t select or favor as much on the surveys when we ran follow-up ‘in the wild’ tests, like A/B testing.”
Pepsi saw similar results when it ran its iconic field experiment, “The Pepsi Challenge” for the first time in 1975.
The beverage brand set up tables at malls, beaches, and other public locations and ran a blindfolded taste test. Shoppers were given two cups of soda, one containing Pepsi, the other Coca-Cola (Pepsi’s biggest competitor). They were then asked to taste both and report which they preferred.
People overwhelmingly preferred Pepsi, and the brand has repeated the experiment multiple times over the years to the same results.
What I like: It yields qualitative and quantitative data and can make for engaging marketing content, especially in the digital age.
What I dislike: It can be very time-consuming. And, if you’re not careful, there is a high risk for scientific error.
Best for: Product testing and competitive analysis
Pro tip: " Don’t make critical business decisions off of just one data set," advises Pamela Bump. "Use the survey, competitive intelligence, external data, or even a focus group to give you one layer of ideas or a short-list for improvements or solutions to test. Then gather your own fresh data to test in an experiment or trial and better refine your data-backed strategy."
8. public domain or third-party research.
While original data is always a plus, there are plenty of external resources you can access online and even at a library when you’re limited on time or resources.
Some reputable resources you can use include:
It’s also smart to turn to reputable organizations that are specific to your industry or field. For instance, if you’re a gardening or landscaping company, you may want to pull statistics from the Environmental Protection Agency (EPA).
If you’re a digital marketing agency, you could look to Google Research or HubSpot Research . (Hey, I know them!)
What I like: You can save time on gathering data and spend more time on analyzing. You can also rest assured the data is from a source you trust.
What I dislike: You may not find data specific to your needs.
Best for: Companies under a time or resource crunch, adding factual support to content
Pro tip: Fellow HubSpotter Iskiev suggests using third-party data to inspire your original research. “Sometimes, I use public third-party data for ideas and inspiration. Once I have written my survey and gotten all my ideas out, I read similar reports from other sources and usually end up with useful additions for my own research.”
If the data you need isn’t available publicly and you can’t do your own market research, you can also buy some. There are many reputable analytics companies that offer subscriptions to access their data. Statista is one of my favorites, but there’s also Euromonitor , Mintel , and BCC Research .
What I like: Same as public domain research
What I dislike: You may not find data specific to your needs. It also adds to your expenses.
Best for: Companies under a time or resource crunch or adding factual support to content
You’re not going to like my answer, but “it depends.” The best marketing research method for you will depend on your objective and data needs, but also your budget and timeline.
My advice? Aim for a mix of quantitative and qualitative data. If you can do your own original research, awesome. But if not, don’t beat yourself up. Lean into free or low-cost tools . You could do primary research for qualitative data, then tap public sources for quantitative data. Or perhaps the reverse is best for you.
Whatever your marketing research method mix, take the time to think it through and ensure you’re left with information that will truly help you achieve your goals.
Related articles.
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5 Time-Saving Tips & Tools
By: David Phair (PhD) and Amy Murdock (PhD) | July 2022
The methodology chapter is a crucial part of your dissertation or thesis – it’s where you provide context and justification for your study’s design. This in turn demonstrates your understanding of research theory, which is what earns you marks .
Over the years, we’ve helped thousands of students navigate this tricky section of the research process. In this post, we’ll share 5 time-saving tips to help you effectively write up your research methodology chapter .
The first thing to keep in mind when writing your methodology chapter (and the rest of your dissertation) is that it’s always a good idea to sketch out a rough outline of what you are going to write about before you start writing . This will ensure that you stay focused and have a clear structural logic – thereby making the writing process simpler and faster.
An easy method of finding a structure for this chapter is to use frameworks that already exist, such as Saunder’s “ research onion ” as an example. Alternatively, there are many free methodology chapter templates for you to use as a starting point, so don’t feel like you have to create a new one from scratch.
Next, you’ll want to consider what your research approach is , and how you can break it down from a top-down angle, i.e., from the philosophical down to the concrete/tactical level. For example, you’ll need to articulate the following:
Keep these questions front of mind to ensure that you have a clear, well-aligned line of argument that will maintain your chapter’s internal and external consistency.
Remember, it’s okay if you feel overwhelmed when you first start the methodology chapter. Nobody is born with an innate knowledge of how to do this, so be prepared for the learning curve associated with new research projects. It’s no small task to write up a dissertation or thesis, so be kind to yourself!
Generally, there are plenty of existing journal articles that will share similar methodological approaches to your study. With any luck, there will also be existing dissertations and theses that adopt a similar methodological approach and topic. So, consider taking inspiration from these studies to help curate the contents of your methodology chapter.
Students often find it difficult to choose what content to include in the methodology chapter and what to leave for the appendix. By reviewing other studies with similar approaches, you will get a clearer sense of your discipline’s norms and characteristics . This will help you, especially in terms of deciding on the structure and depth of discussion.
While you can draw inspiration from other studies, remember that it’s vital to pay close attention to your university’s specific guidelines, so you can anticipate departmental expectations of this section’s layout and content (and make it easier to work with your supervisor). Doing this is also a great way to figure out how in-depth your discussion should be. For example, word-count guidelines can help you decide whether to include or omit certain information.
The golden rule of the methodology chapter is that you need to justify each and every design choice that you make, no matter how small or inconsequential it may seem. We often see that students merely state what they did instead of why they did what they did – and this costs them marks.
Keep in mind that you need to illustrate the strength of your study’s methodological foundation. By discussing the “what”, “why” and “how” of your choices, you demonstrate your understanding of research design and simultaneously justify the relevancy and efficacy of your methodology – both of which will earn you marks.
It’s never an easy task to conduct research. So, it’s seldom the case that you’ll be able to use the very best possible methodology for your research (e.g. due to time or budgetary constraints ). That’s okay – but make sure that you explain and justify your use of an alternate methodology to help justify your approach.
Ultimately, if you don’t justify and explain the logic behind each of your choices, your marker will have to assume that you simply didn’t know any better . So, make sure that you justify every choice, especially when it is a subpar choice (due to a practical constraint, for example). You can see an example of how this is done here.
We often see a tendency in students to mistakenly give more of an overview of their methodology instead of a step-by-step breakdown . Since the methodology chapter needs to be detailed enough for another researcher to replicate your study, your chapter should be particularly granular in terms of detail.
Whether you’re doing a qualitative or quantitative study, it’s crucial to convey rigor in your research. You can do this by being especially detailed when you discuss your data, so be absolutely clear about your:
As you will likely face an extensive period of editing at your supervisor/reviewer’s direction, you’ll make it much easier for yourself if you have more information than you’d need. Some supervisors expect extensive detail around a certain aspect of your dissertation (like your research philosophy), while others may not expect it at all.
Remember, it’s quicker and easier to remove/ trim down information than it is to add information after the fact, so take the time to show your supervisor that you know what you’re talking about (methodologically) and you’re doing your best to be rigorous in your research.
Related to the issue of poor justification (tip #3), it’s important include high-quality academic citations to support the justification of your design choices. In other words, it’s not enough to simply explain why you chose a specific approach – you need to support each justification with reference to academic material.
Simply put, you should avoid thinking of your methodology chapter as a citation-less section in your dissertation. As with your literature review, your methods section must include citations for every decision you make, since you are building on prior research. You must show that you are making decisions based on methods that are proven to be effective, and not just because you “feel” that they are effective.
When considering the source of your citations, you should stick to peer-reviewed academic papers and journals and avoid using websites or blog posts (like us, hehe). Doing this will demonstrate that you are familiar with the literature and that you are factoring in what credible academics have to say about your methodology.
As a final tip, it’s always a good idea to cite as you go . If you leave this for the end, then you’ll end up spending a lot of precious time retracing your steps to find your citations and risk losing track of them entirely. So, be proactive and drop in those citations as you write up . You’ll thank yourself later!
In this post, we covered 5 time-saving tips for writing up the methodology chapter:
If you’ve got any questions relating to the methodology chapter, feel free to drop a comment below. Alternatively, if you’re interested in getting 1-on-1 help with your thesis or dissertation, be sure to check out our private coaching service .
This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...
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A title page is required for all APA Style papers. There are both student and professional versions of the title page. Students should use the student version of the title page unless their instructor or institution has requested they use the professional version. APA provides a student title page guide (PDF, 199KB) to assist students in creating their title pages.
The student title page includes the paper title, author names (the byline), author affiliation, course number and name for which the paper is being submitted, instructor name, assignment due date, and page number, as shown in this example.
Title page setup is covered in the seventh edition APA Style manuals in the Publication Manual Section 2.3 and the Concise Guide Section 1.6
Student papers do not include a running head unless requested by the instructor or institution.
Follow the guidelines described next to format each element of the student title page.
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Paper title | Place the title three to four lines down from the top of the title page. Center it and type it in bold font. Capitalize of the title. Place the main title and any subtitle on separate double-spaced lines if desired. There is no maximum length for titles; however, keep titles focused and include key terms. |
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Author names | Place one double-spaced blank line between the paper title and the author names. Center author names on their own line. If there are two authors, use the word “and” between authors; if there are three or more authors, place a comma between author names and use the word “and” before the final author name. | Cecily J. Sinclair and Adam Gonzaga |
Author affiliation | For a student paper, the affiliation is the institution where the student attends school. Include both the name of any department and the name of the college, university, or other institution, separated by a comma. Center the affiliation on the next double-spaced line after the author name(s). | Department of Psychology, University of Georgia |
Course number and name | Provide the course number as shown on instructional materials, followed by a colon and the course name. Center the course number and name on the next double-spaced line after the author affiliation. | PSY 201: Introduction to Psychology |
Instructor name | Provide the name of the instructor for the course using the format shown on instructional materials. Center the instructor name on the next double-spaced line after the course number and name. | Dr. Rowan J. Estes |
Assignment due date | Provide the due date for the assignment. Center the due date on the next double-spaced line after the instructor name. Use the date format commonly used in your country. | October 18, 2020 |
| Use the page number 1 on the title page. Use the automatic page-numbering function of your word processing program to insert page numbers in the top right corner of the page header. | 1 |
The professional title page includes the paper title, author names (the byline), author affiliation(s), author note, running head, and page number, as shown in the following example.
Follow the guidelines described next to format each element of the professional title page.
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Paper title | Place the title three to four lines down from the top of the title page. Center it and type it in bold font. Capitalize of the title. Place the main title and any subtitle on separate double-spaced lines if desired. There is no maximum length for titles; however, keep titles focused and include key terms. |
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Author names
| Place one double-spaced blank line between the paper title and the author names. Center author names on their own line. If there are two authors, use the word “and” between authors; if there are three or more authors, place a comma between author names and use the word “and” before the final author name. | Francesca Humboldt |
When different authors have different affiliations, use superscript numerals after author names to connect the names to the appropriate affiliation(s). If all authors have the same affiliation, superscript numerals are not used (see Section 2.3 of the for more on how to set up bylines and affiliations). | Tracy Reuter , Arielle Borovsky , and Casey Lew-Williams | |
Author affiliation
| For a professional paper, the affiliation is the institution at which the research was conducted. Include both the name of any department and the name of the college, university, or other institution, separated by a comma. Center the affiliation on the next double-spaced line after the author names; when there are multiple affiliations, center each affiliation on its own line.
| Department of Nursing, Morrigan University |
When different authors have different affiliations, use superscript numerals before affiliations to connect the affiliations to the appropriate author(s). Do not use superscript numerals if all authors share the same affiliations (see Section 2.3 of the for more). | Department of Psychology, Princeton University | |
Author note | Place the author note in the bottom half of the title page. Center and bold the label “Author Note.” Align the paragraphs of the author note to the left. For further information on the contents of the author note, see Section 2.7 of the . | n/a |
| The running head appears in all-capital letters in the page header of all pages, including the title page. Align the running head to the left margin. Do not use the label “Running head:” before the running head. | Prediction errors support children’s word learning |
| Use the page number 1 on the title page. Use the automatic page-numbering function of your word processing program to insert page numbers in the top right corner of the page header. | 1 |
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npj Parkinson's Disease volume 10 , Article number: 160 ( 2024 ) Cite this article
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Human disease-associated gene data are accessible through databases, including the Open Targets Platform, DisGeNET, miRTex, RNADisease, and PubChem. However, missing data entries in such databases are anticipated because of curational errors, biases, and text-mining failures. Additionally, the extensive research on human diseases has led to challenges in registering comprehensive data. The lack of essential data in databases hinders knowledge sharing and should be addressed. Therefore, we propose an analysis pipeline to explore missing entries of unexploited genes in the human disease-associated gene databases. Using this pipeline for genes in Parkinson’s disease with oxidative stress revealed two unexploited genes: nuclear protein 1 ( NUPR1) and ubiquitin-like with PHD and ring finger domains 2 ( UHRF2) . This methodology enhances the identification of underrepresented disease-associated genes, facilitating easier access to potential human disease-related functional genes. This study aims to identify unexploited genes for further research and does not include independent experimental validation.
Introduction.
Human disease research is a significant area in biology. For example, querying “parkinson disease” [All Fields] in the PubMed literature database yields 94,062 literatures (11 February 2024). Subsequently, research findings are curated by experts or extracted through text-mining methodologies to register in databases that facilitate collective intelligence. For instance, the Clinical Genome Resource (ClinGen) 1 , developed by the National Institutes of Health (NIH), curates, assesses, and disseminates aggregated genetic and disease associations as public data. The GWAS Catalog 2 compiles genome-wide association data, including single-nucleotide polymorphisms (SNPs) with associated disease risks. Open Targets Platform 3 integrates data from ClinGen and GWAS Catalog, and other public human disease-related databases, including CRISPRBrain 4 , Open Targets Genetics 5 , Gene Burden 6 , 7 , and Europe PMC 8 , 9 . Additional databases, including DisGeNET (expert-curated integrated gene-disease associations until March 2021) 10 , miRTex (specialized in text-mining approach-extracted microRNA) 11 , RNADisease (specialized in collecting non-coding RNAs with integrated approaches of curating and text-mining) 12 , and PubChem (specialized in extracted data from PubMed) 13 offer complementary insights. They use various combinations of integration of data and specific text-mining methods and focus on RNA-disease links, capturing disease-gene associations that may not be included in the Open Targets Platform. These five databases offer comprehensive access to the latest human genes that have been implicated as functionally related to the disease.
As previously mentioned, PubMed database contained 94,062 studies related to PD. With these publications and accompanying data, missing data entries for disease-related functional genes are anticipated in databases 14 . Factors that contribute to missing disease-related genes may include challenges in computationally accessing biomedical statement contexts and supplementary data in the literature, oversights or biases by curators, and text-mining failures. These unexploited genes, which can be referred to as false-negative genes in current gene-disease association databases, represent incomplete dissemination of prior knowledge, potentially hindering research advancement and the development of disease prevention and treatment strategies. The manual identification of missing data entries across the literature databases requires substantial human resources and time expenditures. Therefore, we propose an approach to identify unexploited genes, which are missing data entries in five relevant databases. Based on our previous research on oxidative stress (OS) 15 , 16 , we selected PD, which exhibits pathological associations with OS, to demonstrate the efficacy of our methodology for identifying unexploited genes.
PD is a neurodegenerative disorder affecting over 6 million patients worldwide 17 . The primary symptoms observed in patients with PD include unilateral rigidity, bradykinesia, tremors, and non-motor symptoms, such as cognitive dysfunction 18 , 19 , 20 . The defining characteristics of PD include disordered α-synuclein aggregation, Lewy body formation, and significant loss of dopaminergic (DA) neurons in the substantia nigra, resulting in depleted dopamine levels, causing motor and cognitive deficits 18 , 20 , 21 , 22 , 23 . PD has been considered to be closely associated with the biological phenomenon, OS, wherein reactive oxygen species (ROS) and nucleophiles both contribute to and are generated by aggregating α-synuclein, Lewy bodies, and DA neuron loss 24 . Because OS is characterized by an imbalance between ROS levels and antioxidant defenses, substantial evidence has implicated it in PD pathogenesis 24 . As current therapies focus on symptomatic treatment, such as dopamine replacement, rather than root-cause therapy, understanding the molecular mechanisms of PD symptoms associated with OS is crucial for developing more effective therapies or biomarkers 25 . Querying “parkinson disease” [All Fields] AND “oxidative stress” [All Fields] in PubMed database yields 4061 publications (as of 15 February 2024), and manually reviewing all 4061 articles to sequentially identify unexploited genes would be labor-intensive. Therefore, the discovery of unexploited genes as candidates for the field of PD and OS research is necessary to further understand their underlying mechanisms.
To identify unexploited genes, we developed an analytical pipeline consisting of four significant stages. First, we curated a candidate gene set based on disease-relevant gene expression data. Second, we classified candidate genes based on the presence or absence of disease associations in the five applicable databases. Third, we refined the genes likely to be functional, leveraging data from transcriptome meta-analysis and transcriptome-wide association studies (TWAS). Finally, we manually searched the refined gene list to identify the unexploited genes with documented disease associations in the literature, but no links in the five databases. To identify genes related to OS in PD, we discovered two unexploited PD genes: nuclear protein 1 ( NUPR1) , and ubiquitin-like with PHD and ring finger domains 2 ( UHRF2) . The proposed approach and its findings will facilitate the identification of unexploited genes missing from databases, thereby advancing future research on human diseases.
Our stepwise methodology entailed the following: (1) Transcriptomic meta-analysis and literature mining were independently conducted to identify differentially expressed genes (DEGs) associated with OS and Parkinson’s disease (PD) in the human brain [Fig. 1a ]. These outputs were compared to extract the dysregulated genes in both OS and PD (OS-PD-DEGs, n = 168) [Fig. 1a ]. (2) The 168 candidate genes in OS-PD-DEGs were categorized into two subsets based on their associations with PD according to relevant databases (Open Targets Platform 3 , DisGeNET 10 , miRTex 11 , RNADisease 12 , and PubChem 13 ). Each database collects information on the relationship between gene and disease in its unique way. Genes were categorized as “PD-linked-genes” if any database showed a connection to PD, and as “PD-unlinked-genes” if no databases showed such a connection. As a result, 116 genes were classified as PD-unlinked-genes [Fig. 1b ], whereas the remaining 52 genes exhibited PD associations and classified as PD-linked-genes. (3) To identify genes with functions, we filtered PD-unlinked-genes using data from the PD transcriptome meta-analysis and TWAS, with 12 genes (unexploited candidate genes) remaining for the last step. 4) Finally, two unexploited genes (NUPR1 and UHRF2 ) were discovered by manually searching PubMed Central for data on unexploited candidate genes [Fig. 1c ]. The source data for identifying DEGs and the thresholds for the meta-analysis are potential confounders in this pipeline. However, to enhance the robustness and ensure the quality of identifying unexploited genes, we implemented two strategies: manual search and verification of unexploited genes at the end of the pipeline, and manual data curation for identifying candidate genes at the beginning of the pipeline.
a Transcriptome meta-analysis to retrieve differentially expressed genes (DEGs) in both oxidative stress (OS) and Parkinson’s disease (PD) ( n = 168). b Gene-disease-linker (see Methods) filters the 168 candidate genes into PD-unlinked-genes based on gene-PD association with evidence studies. c PD-unlinked genes are further filtered using transcriptome-wide association studies (TWAS) and PD meta-analysis results to obtain unexploited candidate genes. A manual search of unexploited candidate genes revealed two unexploited genes.
A transcriptomic meta-analysis was conducted on 122 paired RNA-sequencing (RNA-seq) datasets 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 from cultured human cells related to the brain to identify DEGs associated with OS. Each pair comprised an OS sample and a matched normal condition sample from the same original study. Specifically, the transcriptomes of neurons, astrocytes, and neural progenitor cells [Supplementary Table 1 ] 34 under OS or normal conditions were compiled from the Gene Expression Omnibus (GEO) database 35 . Oxidative stressors included radiation, hydrogen peroxide, rotenone, 1-methyl-4-phenylpyridinium (MPP + ), paraquat, 6-hydroxydopamine (oxidopamine), methyl mercury chloride, and zinc [Table 1 ] [Supplementary Table 1 ] 34 . A total of 3114 genes (5% of all genes whose expression was quantified, termed OS-DEGs), were collected as DEGs, consisting of 1557 most upregulated and downregulated genes [Fig. 1a ] with an ON_score of 1.5. Of the 357 genes in “GO:0006979: response to oxidative stress”, 37 possessed Ensembl IDs annotated to were included in OS-DEGs ( p value: 2.671*e −5 ).
Because existing meta-analyses have delineated DEGs associated with PD, we curated and compiled PD-DEG sets from three relevant studies 36 , 37 , 38 [Table 2 ]. These studies performed meta-analyses of PD transcriptomic data to derive robust gene expression signatures for the disease. Additionally, PD-associated genes identified through TWAS in the brain tissue were obtained from the TWAS-Atlas database 39 and incorporated. In total, the PD-DEG comprised 2895 unique genes (1378 from PMID:27611585 36 , 585 from PMID: 33390883 37 , 989 from PMID: 37347276 38 , and 196 from the TWAS-Atlas) [Fig. 2 ]. Gene set enrichment analysis (GSEA) confirmed the signature of the PD-DEG compilation, with the most enriched term as “has05012: Parkinson disease” [Fig. 3a ]. Collating PD-DEG lists from multiple large-scale omics studies and databases generated an extensive catalog of genes dysregulated in PD for subsequent analyses.
Venn diagram visualizing overlaps of PD-DEGs ( n = 2895) among the studies. PMID represents PubMed ID. Transcriptome-wide association studies (TWAS) represents gene sets acquired from the TWAS-Atlas.
a Results of GSEA of the PD-DEGs ( n = 2763, unrecognized genes by Metascape, which are unstudied genes lacking NCBI gene IDs). b Results of GSEA of the differentially expressed genes (DEGs) commonly dysregulated in both oxidative stress (OS) and Parkinson’s disease (PD) ( n = 168).
Comparative analysis of the 3114 OS-DEGs and 2895 Parkinson’s disease (PD-DEGs) revealed 168 genes dysregulated in both conditions (termed as OS-PD-DEGs) [Fig. 1a ]. Of these, 132 were protein-coding, and 36 were non-coding RNA/pseudogene/small nucleolar RNA or unknown. GSEA of the 168-DEGs overlapping genes exhibited significant enrichment for “GO:0009636: response to toxic substance” and “GO:0000302: response to reactive oxygen species” [Fig. 3b ], confirming their relevance to these biological processes. Mining of PD associations using the gene-disease-linker 40 tool identified 52 OS-PD-DEGs with previously reported PD associations (PD-linked genes). The remaining 116 genes lacking known PD connections were termed PD-unlinked-genes [Fig. 1c ]. The results of the gene-disease-linker using OS-PD-DEGs are listed in Supplementary Table 2 34 . The columns in Supplementary Table 2 are described as follows: ENSG: Ensemble gene ID, PD_log2(fold change)_PMID: Log 2 fold change based on the original papers with PMID specified in the column name, TWAS: whether a gene was indicated in the TWAS, availability of associations: indicates if the gene exhibits association with PD (yes) or not (no), Evidence: databases providing evidence for an association between the given gene and the PD, NU_PMIDs_PD: Number of studies indicating an association between the given gene and PD, NU_PMIDs_NCBI: Number of studies associated with the given gene based on gene2pubmed 41 , PMIDs_PD: PubMed IDs for studies indicating an association between the given gene and PD, and PMIDs_NCBI: PubMed IDs for studies associated with the given gene based on gene2pubmed.
Among the 116 PD-unlinked genes, six were identified with TWAS Z scores in the supplementary data of two studies with TWAS [Table 3 , column: original TWAS]. Five of these genes were part of a set of 711 genes suggested to confer PD risk in the supplementary data of PMID: 33523105 42 . However, the main texts of the study (PMID: 33523105) lacked mention of these five genes. MEI1 was one of the 44 genes implicated in dorsolateral prefrontal cortex PD associations in the TWAS from PMID: 30824768 43 , again lacking textual descriptions of MEI1 within the study (PMID: 30824768). As these six genes were indicated to contribute to PD based on the TWAS results, we presumed them as suitable candidates for assessing the evidence or implications of their involvement in PD molecular mechanisms in the subsequent study mining step of our pipeline.
Among the three PD gene expression meta-analyses examined, seven genes were suggested as PD-DEGs in more than two studies [Table 3 , column: PD_log2(fold change)]. Notably, NUPR1 , in addition to appearing in the supplementary data of the TWAS-based study, was also selected as a PD-DEG in two PD gene expression meta-analyses, indicating dysregulated expression of NUPR1 in PD across three studies. Additionally, these seven genes were unexploited candidate genes in the subsequent step. A total of 12 genes [Table 3 ] have not been previously mentioned in their molecular association with PD as textual description in the main texts of studies; however, the sequence data indicated an association. These 12 genes were selected as unexploited candidate genes for the subsequent step, searching the full-text literature for molecular mechanistic evidence or hypotheses associated with them.
We searched the biomedical full-text literature database PubMed Central with the query “GENE_NAME[All Fields] AND parkinson[All Fields]” to look for unexploited genes (See Methods). Among the 12 genes examined, NUPR1 , and UHRF2 were identified as unexploited based on statements in the literature indicating their involvement in PD molecular mechanisms [Table 4 ]. For NUPR1 , the PMCID: PMC10734959 44 was used to determine the gene as unexploited. NUPR1 was identified as one of the top five ferroptosis-related hub genes in PD by the methodology using random forest and support vector machine models. Additionally, the association between NUPR1 and alterations of the immune microenvironment of PD patients was indicated by a correlation analysis of NUPR1 and immune characteristics. It was mentioned that “The present study also suggests that NUPR1 is involved in PD, is positively correlated with PD, and is most likely involved in PD pathogenic mechanisms through ferroptosis and OS”. For UHRF2 , the PMCID: PMC9775085 45 was used to determine the gene as unexploited. This review article integrates prior knowledge and proposes that UHRF2 dysregulation contributes to PD progression. It was specifically mentioned as follows; “Altogether, it could be assumed that the dysregulation of CPNE8 , CADPS2 , or UHRF2 contributes to PD progression via ERK activation induced by the LRRK2 G2019S mutation”. Table 4 provides the PubMed Central query dates by the author, query results, evidentiary publications (PubMed Central IDs), and quoted text supporting the unexploited status of each gene (evidence statements in the research paper).
In this study, we developed a pipeline to identify unexploited genes, that correspond to false-negative genes for a given disease against five databases that provide gene-disease associations. Additionally, it was used to treat PD associated with OS. Through integrated analysis of curated datasets, including transcriptomics and transcriptome-wide association results, we filtered the 62,266 genes down to 168 genes (OS-PD-DEGs) that exhibited dysregulation of gene expression in both PD and OS contexts. We subsequently classified OS-PD-DEGs into PD-unlinked and PD-linked genes based on existing evidence of their involvement in PD. We have further narrowed down the PD-unlinked genes to 12 unexploited candidate genes. Following a manual search of these 12 genes, NUPR1 , and UHRF2 were identified as unexploited genes that were absent from the current gene-disease associations databases. These unexploited genes are described as functionally associated with PMC9775085 and PMC10734949, yet they are not captured in public gene-disease association databases. Although not the focus of this study due to not meeting the criteria to judge PD unexploited genes, several studies 46 , 47 have reported dysregulated expression due to PD, which enhances the reliability of the association to PD. Thus, this pipeline effectively discovers such overlooked unexploited genes, aiding in the identification of experimental candidate genes.
Although it is challenging to conclusively determine the reasons for missing these entries from databases, three potential explanatory factors have been hypothesized as outlined in the Introduction. First, the databases may not have been recently updated. Two evidentiary publications on unexploited genes were recent (published in 2022 and 2023). Therefore, the absence of registrations may be possible without updates. Although the Open Targets Platform notes bi-monthly updates, the source database update frequencies vary, potentially explaining the omissions. Second, text-mining extraction failures are possible. For example, text-mining from the Europe PMC relies on co-occurrences at the sentence level with several filtering rules to reduce noise 9 . Their extraction methodology excludes articles other than research articles and filters out associations that appear only once in the body of an article but not in the article’s title or abstract. Therefore, the UHRF2 -PD association was excluded from the Open Targets Platform because the review article PMC9775085 was filtered out by the extraction system. Third, certain databases rely on expert manual curation for new data entry, which may be pending or induce human errors or biases. Using our analytical pipeline to identify unexploited genes helps mitigate these database limitations.
Additionally, the two unexploited genes identified were associated with OS. NUPR1 acts as a key inhibitor of ferroptosis by regulating lipocalin-2 (LCN2) expression to reduce iron accumulation and subsequent oxidative damage 48 . For UHRF2 , a gene set involved in ROS, UV response, and oxidative phosphorylation was induced in the retinal tissue of Uhrf2-deficient mice 49 . Among the 52 PD-linked genes, the majority have established associations with PD and OS (for instance, SLC18A2 50 , 51 , TXNIP 52 , NEFL 53 , 54 , MPO 55 , 56 , 57 , 58 , LINC00938 59 , 60 ). Therefore, the 168 OS-PD-DEGs are suggested to include not only well-known OS in PD research candidates, but also novel candidates.
Moreover, PD-linked genes with limited evidentiary publications may harbor false positives (genes that are flagged as disease-associated in a database containing evidence with inappropriate evidence). For example, we identified superoxide dismutase 3 ( SOD3) as a false-positive result. SOD3 was linked to PD through the Open Targets Platform with a single literature annotation, which, on closer inspection turns out that the contents in the literature claim the opposite, that no significant SNP-PD risk association are found for SOD 3 61 . This example demonstrates that our pipeline has the potential to reveal false positive entries in the database.
Finally, we outline four limitations of the analysis pipeline used in this study. First, several pipeline steps require time-consuming manual efforts. The curation of RNA-seq data is required for gene expression analysis in the first step. Following the refinement of the unexploited candidate genes, PMC was manually searched to assess the status of each gene. These manual steps render the methodology unsuitable for the comprehensive identification of numerous unexploited genes. The second limitation is the potential error of extracting false-positive genes, which may appear disease-associated but have weak actual relevance. This is particularly possible in RNAdisease and DisGeNET, where genes are searched based on threshold scores indicating association strength. However, such false-positive genes can be manually verified by reviewing the associated supporting literature as outlined in the Discussion. Furthermore, since the aim of this study is to identify false negatives, false-positive genes are not expected to hinder this objective and, therefore, are not considered a significant issue. The third limitation is the potential for confounders to prevent the identification of unexploited genes. In this study, we selected the candidate gene sets, OS-PD-DEGs, from various meta-analysis results. Changing potential confounders, such as the type and quantity of RNA-seq data selected or the thresholds used in the meta-analysis, could alter the OS-PD-DEGs and, subsequently, the unexploited genes. Therefore, when using this pipeline, it is necessary to curate as many suitable samples as possible and test various thresholds. Lastly, the referenced gene-disease databases are not static but will evolve with database research progress. We selected five databases to maximize the disease-gene coverage presently. However, novel databases are likely to emerge and be integrated over time. Therefore, appropriate database selection based on contemporary availability is necessary.
To collect OS RNA-sequencing data, relevant datasets were manually curated from the GEO 35 repository based on five criteria: (1) total RNA or polyA-enriched sequencing, (2) samples under conditions related to the definition of OS, (3) samples under conditions related to increased ROS levels, (4) availability of paired normal-state samples as a control, and (5) cell cultures with brain relevance (neurons, astrocytes, and progenitors). This resulted in 122 matched OS-normal sample pairs from 10 research groups for analysis as a result of curating started from August 2023 to 31 October 2023. Comprehensive details of the public datasets used in this study are listed in Supplementary Table 1 34 .
To compile DEGs in PD, we conducted a manual survey searching the PubMed database. Meta-analyses of three published studies were found, and we extracted all reported DEGs. Additionally, genes queried for PD in the TWAS-Atlas database 39 were incorporated into the PD-DEG list for downstream analysis. This curation was conducted from August 2023 to 31 October 2023. Comprehensive details regarding all the public datasets used in this study are listed in Table 2 .
For RNA-seq data retrieval, processing, and quantification, we used Ikra 62 , an automated pipeline program for RNA-seq data of Homo sapiens and Mus musculus . The following pipeline comprised fasterq-dump (version.3.0.1) 63 , trim-galore (version.0.6.7) 64 , and salmon (version.1.4.0) 65 processes, with reference transcript sets in GENCODE Release 44 (GRCh38.p14). The transcript IDs were converted into the gene IDs using tximport ( http://bioconductor.org/packages/tximport/ ) [Supplementary Table 2 ] 34 . To retrieve DEGs across 122 paired RNA-seq, we devised an oxidative stress-normal-state score (ON-score) based on these datasets. Initially, the ON-ratio was calculated for each gene, representing the expression ratio between OS and normal states across all sample pairs (Eq. 1 ). Subsequently, genes were then categorized as upregulated, downregulated, or unchanged based on the ON-ratio exceeding a ±1.5-fold threshold. Furthermore, the ON-score for each gene was calculated using Eq. 2 , which involved subtracting the number of downregulated samples from the number of upregulated samples. This scoring methodology was detailed extensively in a previous study 15 . The ON score measured how many of the 122 pairs of samples dysregulate the expression of each gene.
To assess the statistical validity of the meta-analysis method, we compared its results with those obtained using DESeq2 (package version:1.44.0), a widely used tool in bioinformatics research. Setting the threshold at log2FoldChange ≧ |1| and a p value adjusted by the false discovery rate <0.05, 352 genes were identified. The overlap between the 3114 genes identified by meta-analysis and the 352 genes identified by DESeq2 was 89. We conducted Fisher’s exact test to determine whether there is a statistically significant correlation between the gene sets obtained by meta-analysis and DESeq2. The sample size of genes was 62,266, with 3114 genes from the meta-analysis, 352 genes from DESeq2, and an overlap of 89 genes. The calculation yielded a p value of 1.52e-37 at a significant level of 0.05. This indicates that the probability of such an overlap occurring by chance is extremely low, demonstrating a statistically significant correlation between the gene sets obtained by the meta-analysis and DESeq2 methods. The DESeq2 output [Supplementary Table 4 ], the list of 352 genes [Supplementary Table 4 ], the list of overlapped 89 genes [Supplementary Table 4 ], and the script for calculating the fisher’s exact test [Supplementary Data 5 ] are available in the Figshare repository 34 .
To classify genes based on prior evidence linking them to a disease, we originally developed the tool called gene-disease-linker 40 [Fig. 4 ]. The basic functionality of gene-disease-linker is to efficiently search five public gene-disease association databases, perform ID conversions, and organize search results. Using this tool, genes can be efficiently categorized as “linked” or “unlinked” for a specific disease by searching five public databases (accessed on 8 February 2024)—Open Targets Platform 3 , RNAdisease 12 , miRTex 11 , DisGeNET 10 , and PubChem 13 - for gene-disease relationships. As this categorization relies on these five databases, it is crucial that they comprehensively cover disease-gene associations as much as possible. We investigated as many public databases as possible from August 2023 to February 2024, requiring each gene-disease association to include supporting references. As a result, we selected these five public databases.
Overview of gene-disease-linker collecting information about gene-disease associations based on the relevant five databases.
The detailed description of gene-disease-linker is as follows: By inputting a text file of genes list and configuration file into gene-disease-linker, it outputs the search results from these five databases, thereby enabling the determination of whether there is a gene-disease association for each gene in the list regarding a specific disease. In cases a gene exhibiting an association with the disease, it also concurrently outputs the supporting literature with PubMed ID. In contrast, no gene-disease association is indicated if there is no supporting literature annotated to a gene. In this study, a gene-disease-linker was used to classify genes as either PD-linked (existing literature linking the gene to PD) or PD-unlinked (no evidence found) (executed on 8 February 2024). The source codes and usage of gene-disease-linker are available in the GitHub repository. The text file of the genes list and configuration file we used in this study are available in the GitHub repository (168genes.txt and config.yml, respectively). Also, all intermediate and output files from running the gene-disease-linker in this study are available in the results folder on GitHub.
We searched gene names in PubMed Central, a full-text literature database, with the following query: “GENE_NAME[All Fields] AND Parkinson[All Fields]”. Within the retrieved articles, we analyzed the surrounding textual context of gene mentions to identify descriptions indicating or suggesting molecular functional relationships with PD. Only genes with mechanistic evidence or relationships reported in the literature were judged unexploited. Genes only listed among the DEGs without any statements related to functional implications were excluded from the unexploited.
GSEA was performed using the web-based tool Metascape 66 . Shared genes among the various gene sets were visualized using a publicly available web-based Venn diagram generator ( https://bioinformatics.psb.ugent.be/webtools/Venn/ ).
The datasets curated, generated, and analyzed during this study are available in the figshare repository 34 .
The underlying code for the current study is available at gene-disease-linker 40 .
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This research was supported by the Center of Innovation for Bio-Digital Transformation (BioDX), the open innovation platform for industry-academia co-creation (COI-NEXT), the Japan Science and Technology Agency (JST, COI-NEXT, JPMJPF2010), and the ROIS-DS-JOINT (007RP2023). This work was also supported by the JST, which established university fellowships for the creation of science and technology innovation (Grant Number JPMJFS2129). Computations were performed on the computers at Hiroshima University Genome Editing Innovation Center. We also would like to thank all laboratory members at Hiroshima University and the Database Center of Life Science (DBCLS) for their valuable comments.
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Takayuki Suzuki & Hidemasa Bono
Genome Editing Innovation Center, Hiroshima University, 3-10-23 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-0046, Japan
Hidemasa Bono
Database Center for Life Science (DBCLS), Joint Support-Center for Data Science Research, Research Organization of Information and Systems (ROIS), 178-4-4 Wakashiba, Kashiwa, Chiba, 277-0871, Japan
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T.S. was responsible for data curation, software development, pipeline analysis, draft of the original manuscript. T.S. and H.B were responsible for the study design, conceptualization, methodology manuscript review and editing. H.B. was responsible for the project administration, funding acquisition. All authors read and approved the final manuscript.
Correspondence to Hidemasa Bono .
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Suzuki, T., Bono, H. A systematic exploration of unexploited genes for oxidative stress in Parkinson’s disease. npj Parkinsons Dis. 10 , 160 (2024). https://doi.org/10.1038/s41531-024-00776-1
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Step 1: Explain your methodological approach. Step 2: Describe your data collection methods. Step 3: Describe your analysis method. Step 4: Evaluate and justify the methodological choices you made. Tips for writing a strong methodology chapter. Other interesting articles.
Your research methodology discusses and explains the data collection and analysis methods you used in your research. A key part of your thesis, dissertation, or research paper, the methodology chapter explains what you did and how you did it, allowing readers to evaluate the reliability and validity of your research. It should include:
Research methodology is the set of procedures and techniques used to collect, analyze, and interpret data to understand and solve a research problem. ... It could include surveys to quantitatively assess the frequency of social media usage and its correlation with grades, alongside focus groups or interviews to qualitatively explore students ...
The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.
Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design. When planning your methods, there are two key decisions you will make. First, decide how you will collect data. Your methods depend on what type of data you need to answer your research question:
As we mentioned, research methodology refers to the collection of practical decisions regarding what data you'll collect, from who, how you'll collect it and how you'll analyse it. Research design, on the other hand, is more about the overall strategy you'll adopt in your study. For example, whether you'll use an experimental design ...
A research methodology encompasses the way in which you intend to carry out your research. This includes how you plan to tackle things like collection methods, statistical analysis, participant observations, and more. You can think of your research methodology as being a formula. One part will be how you plan on putting your research into ...
Research methodology can be defined as the systematic framework that guides researchers in designing, conducting, and analyzing their investigations. It encompasses a structured set of processes, techniques, and tools employed to gather and interpret data, ensuring the reliability and validity of the research findings.
As Schneider notes, a method refers to the technical steps taken to do research. Descriptions of methods usually include defining and stating why you have chosen specific techniques to investigate a research problem, followed by an outline of the procedures you used to systematically select, gather, and process the data [remember to always save ...
Restate your research problem. Begin your research methodology section by listing the problems or questions you intend to study. Include your hypotheses, if applicable, or what you are setting out to prove through your research. In your restatement, include any underlying assumptions that you're making or conditions that you're taking for granted.
Methodology in research is defined as the systematic method to resolve a research problem through data gathering using various techniques, providing an interpretation of data gathered and drawing conclusions about the research data. Essentially, a research methodology is the blueprint of a research or study (Murthy & Bhojanna, 2009, p. 32).
Do yourself a favour and start with the end in mind. Section 1 - Introduction. As with all chapters in your dissertation or thesis, the methodology chapter should have a brief introduction. In this section, you should remind your readers what the focus of your study is, especially the research aims. As we've discussed many times on the blog ...
Learn how to write a strong methodology chapter that allows readers to evaluate the reliability and validity of the research. A good methodology chapter incl...
1. Understanding the options. Before we jump into the question of how to choose a research methodology, it's useful to take a step back to understand the three overarching types of research - qualitative, quantitative and mixed methods -based research. Each of these options takes a different methodological approach.
A research methodology should include the following components: 3,9. Research design—should be selected based on the research question and the data required. Common research designs include experimental, quasi-experimental, correlational, descriptive, and exploratory.
Your Methods Section contextualizes the results of your study, giving editors, reviewers and readers alike the information they need to understand and interpret your work. Your methods are key to establishing the credibility of your study, along with your data and the results themselves. A complete methods section should provide enough detail ...
Research methodology is a crucial framework that guides the entire research process. It involves choosing between various qualitative and quantitative approaches, each tailored to specific research questions and objectives. Your chosen methodology shapes how data is gathered, analysed, and interpreted, ultimately influencing the reliability and ...
Qualitative research methodology: Qualitative research is often used to examine issues that are not well understood, and to gather additional insights on these topics. Qualitative research methods include open-ended survey questions, observations of behaviours described through words, and reviews of literature that has explored similar theories ...
Here are the steps to follow when writing a methodology: 1. Restate your thesis or research problem. The first part of your methodology is a restatement of the problem your research investigates. This allows your reader to follow your methodology step by step, from beginning to end. Restating your thesis also provides you an opportunity to ...
A research methodology gives research legitimacy and provides scientifically sound findings. It also provides a detailed plan that helps to keep researchers on track, making the process smooth, effective and manageable. A researcher's methodology allows the reader to understand the approach and methods used to reach conclusions.
A research methodology is different from a research method because research methods are the tools you use to gather your data (Dawson, 2019). You must consider several issues when it comes to selecting the most appropriate methodology for your topic. Issues might include research limitations and ethical dilemmas that might impact the quality of ...
The Methodology section portrays the reasoning for the application of certain techniques and methods in the context of the study. For your academic article, when you describe and explain your chosen methods it is very important to correlate them to your research questions and/or hypotheses. The description of the methods used should include ...
Before conducting a study, a research proposal should be created that outlines researchers' plans and methodology and is submitted to the concerned evaluating organization or person. Creating a research proposal is an important step to ensure that researchers are on track and are moving forward as intended. A research proposal can be defined as a detailed plan or blueprint for the proposed ...
From brand design and product development to buyer personas and competitive analysis, I've researched a number of initiatives in my decade-long marketing career.. And let me tell you: having the right marketing research methods in your toolbox is a must. Market research is the secret to crafting a strategy that will truly help you accomplish your goals.
Simply put, you should avoid thinking of your methodology chapter as a citation-less section in your dissertation. As with your literature review, your methods section must include citations for every decision you make, since you are building on prior research. You must show that you are making decisions based on methods that are proven to be ...
For a professional paper, the affiliation is the institution at which the research was conducted. Include both the name of any department and the name of the college, university, or other institution, separated by a comma. Center the affiliation on the next double-spaced line after the author names; when there are multiple affiliations, center ...
To assess the statistical validity of the meta-analysis method, we compared its results with those obtained using DESeq2 (package version:1.44.0), a widely used tool in bioinformatics research.
According to MDWFP officials, the most successful methods of studying black bears include trapping and collaring. (Courtesy: MDWFP) According to MDWFP officials, the most successful methods of ...
The interpersonal consequences of cultural stigma attached to obesity include unfair treatment and judgment based on one's body weight. Americans who are categorized as obese more often report experiencing behaviors toward them that may arise out of people's implicit or explicit biases against extra weight, a bias known as "weightism."
According to Gallup research, 76% of full-time hybrid workers in the U.S. most often cite improved work-life balance as a top advantage of hybrid work. This sentiment is even clearer among ...