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What is Research: Definition, Methods, Types & Examples

The search for knowledge is closely linked to the object of study; that is, to the reconstruction of the facts that will provide an explanation to an observed event and that at first sight can be considered as a problem. It is very human to seek answers and satisfy our curiosity. Let’s talk about research.

Content Index

What is Research?

What are the characteristics of research.

Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, “research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.”

Inductive methods analyze an observed event, while deductive methods verify the observed event. Inductive approaches are associated with qualitative research , and deductive methods are more commonly associated with quantitative analysis .

Research is conducted with a purpose to:

Identify potential and new customers
Understand existing customers
Set pragmatic goals
Develop productive market strategies
Address business challenges
Put together a business expansion plan
Identify new business opportunities
Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
The analysis is based on logical reasoning and involves both inductive and deductive methods.
Real-time data and knowledge is derived from actual observations in natural settings.
There is an in-depth analysis of all data collected so that there are no anomalies associated with it.
It creates a path for generating new questions. Existing data helps create more research opportunities.
It is analytical and uses all the available data so that there is no ambiguity in inference.
Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.

What is the purpose of research?

There are three main purposes:

Exploratory: As the name suggests, researchers conduct exploratory studies to explore a group of questions. The answers and analytics may not offer a conclusion to the perceived problem. It is undertaken to handle new problem areas that haven’t been explored before. This exploratory data analysis process lays the foundation for more conclusive data collection and analysis.

LEARN ABOUT: Descriptive Analysis

Descriptive: It focuses on expanding knowledge on current issues through a process of data collection. Descriptive research describe the behavior of a sample population. Only one variable is required to conduct the study. The three primary purposes of descriptive studies are describing, explaining, and validating the findings. For example, a study conducted to know if top-level management leaders in the 21st century possess the moral right to receive a considerable sum of money from the company profit.

LEARN ABOUT: Best Data Collection Tools

Explanatory: Causal research or explanatory research is conducted to understand the impact of specific changes in existing standard procedures. Running experiments is the most popular form. For example, a study that is conducted to understand the effect of rebranding on customer loyalty.

Here is a comparative analysis chart for a better understanding:

It begins by asking the right questions and choosing an appropriate method to investigate the problem. After collecting answers to your questions, you can analyze the findings or observations to draw reasonable conclusions.

When it comes to customers and market studies, the more thorough your questions, the better the analysis. You get essential insights into brand perception and product needs by thoroughly collecting customer data through surveys and questionnaires . You can use this data to make smart decisions about your marketing strategies to position your business effectively.

To make sense of your study and get insights faster, it helps to use a research repository as a single source of truth in your organization and manage your research data in one centralized data repository .

Types of research methods and Examples

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods.

Qualitative research is a method that collects data using conversational methods, usually open-ended questions . The responses collected are essentially non-numerical. This method helps a researcher understand what participants think and why they think in a particular way.

Types of qualitative methods include:

One-to-one Interview
Focus Groups
Ethnographic studies
Text Analysis

Quantitative methods deal with numbers and measurable forms . It uses a systematic way of investigating events or data. It answers questions to justify relationships with measurable variables to either explain, predict, or control a phenomenon.

Types of quantitative methods include:

Survey research
Descriptive research
Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

Remember, it is only valuable and useful when it is valid, accurate, and reliable. Incorrect results can lead to customer churn and a decrease in sales.

It is essential to ensure that your data is:

Valid – founded, logical, rigorous, and impartial.
Accurate – free of errors and including required details.
Reliable – other people who investigate in the same way can produce similar results.
Timely – current and collected within an appropriate time frame.
Complete – includes all the data you need to support your business decisions.

Gather insights

Identify the main trends and issues, opportunities, and problems you observe. Write a sentence describing each one.
Keep track of the frequency with which each of the main findings appears.
Make a list of your findings from the most common to the least common.
Evaluate a list of the strengths, weaknesses, opportunities, and threats identified in a SWOT analysis .
Prepare conclusions and recommendations about your study.
Act on your strategies
Look for gaps in the information, and consider doing additional inquiry if necessary
Plan to review the results and consider efficient methods to analyze and interpret results.

Review your goals before making any conclusions about your study. Remember how the process you have completed and the data you have gathered help answer your questions. Ask yourself if what your analysis revealed facilitates the identification of your conclusions and recommendations.

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Types of Research – Explained with Examples

By DiscoverPhDs
October 2, 2020

Types of Research

Research is about using established methods to investigate a problem or question in detail with the aim of generating new knowledge about it.

It is a vital tool for scientific advancement because it allows researchers to prove or refute hypotheses based on clearly defined parameters, environments and assumptions. Due to this, it enables us to confidently contribute to knowledge as it allows research to be verified and replicated.

Knowing the types of research and what each of them focuses on will allow you to better plan your project, utilises the most appropriate methodologies and techniques and better communicate your findings to other researchers and supervisors.

Classification of Types of Research

There are various types of research that are classified according to their objective, depth of study, analysed data, time required to study the phenomenon and other factors. It’s important to note that a research project will not be limited to one type of research, but will likely use several.

According to its Purpose

Theoretical research.

Theoretical research, also referred to as pure or basic research, focuses on generating knowledge , regardless of its practical application. Here, data collection is used to generate new general concepts for a better understanding of a particular field or to answer a theoretical research question.

Results of this kind are usually oriented towards the formulation of theories and are usually based on documentary analysis, the development of mathematical formulas and the reflection of high-level researchers.

Applied Research

Here, the goal is to find strategies that can be used to address a specific research problem. Applied research draws on theory to generate practical scientific knowledge, and its use is very common in STEM fields such as engineering, computer science and medicine.

This type of research is subdivided into two types:

Technological applied research : looks towards improving efficiency in a particular productive sector through the improvement of processes or machinery related to said productive processes.
Scientific applied research : has predictive purposes. Through this type of research design, we can measure certain variables to predict behaviours useful to the goods and services sector, such as consumption patterns and viability of commercial projects.

According to your Depth of Scope

Exploratory research.

Exploratory research is used for the preliminary investigation of a subject that is not yet well understood or sufficiently researched. It serves to establish a frame of reference and a hypothesis from which an in-depth study can be developed that will enable conclusive results to be generated.

Because exploratory research is based on the study of little-studied phenomena, it relies less on theory and more on the collection of data to identify patterns that explain these phenomena.

Descriptive Research

The primary objective of descriptive research is to define the characteristics of a particular phenomenon without necessarily investigating the causes that produce it.

In this type of research, the researcher must take particular care not to intervene in the observed object or phenomenon, as its behaviour may change if an external factor is involved.

Explanatory Research

Explanatory research is the most common type of research method and is responsible for establishing cause-and-effect relationships that allow generalisations to be extended to similar realities. It is closely related to descriptive research, although it provides additional information about the observed object and its interactions with the environment.

Correlational Research

The purpose of this type of scientific research is to identify the relationship between two or more variables. A correlational study aims to determine whether a variable changes, how much the other elements of the observed system change.

According to the Type of Data Used

Qualitative research.

Qualitative methods are often used in the social sciences to collect, compare and interpret information, has a linguistic-semiotic basis and is used in techniques such as discourse analysis, interviews, surveys, records and participant observations.

In order to use statistical methods to validate their results, the observations collected must be evaluated numerically. Qualitative research, however, tends to be subjective, since not all data can be fully controlled. Therefore, this type of research design is better suited to extracting meaning from an event or phenomenon (the ‘why’) than its cause (the ‘how’).

Quantitative Research

Quantitative research study delves into a phenomena through quantitative data collection and using mathematical, statistical and computer-aided tools to measure them . This allows generalised conclusions to be projected over time.

According to the Degree of Manipulation of Variables

Experimental research.

It is about designing or replicating a phenomenon whose variables are manipulated under strictly controlled conditions in order to identify or discover its effect on another independent variable or object. The phenomenon to be studied is measured through study and control groups, and according to the guidelines of the scientific method.

Non-Experimental Research

Also known as an observational study, it focuses on the analysis of a phenomenon in its natural context. As such, the researcher does not intervene directly, but limits their involvement to measuring the variables required for the study. Due to its observational nature, it is often used in descriptive research.

Quasi-Experimental Research

It controls only some variables of the phenomenon under investigation and is therefore not entirely experimental. In this case, the study and the focus group cannot be randomly selected, but are chosen from existing groups or populations . This is to ensure the collected data is relevant and that the knowledge, perspectives and opinions of the population can be incorporated into the study.

According to the Type of Inference

Deductive investigation.

In this type of research, reality is explained by general laws that point to certain conclusions; conclusions are expected to be part of the premise of the research problem and considered correct if the premise is valid and the inductive method is applied correctly.

Inductive Research

In this type of research, knowledge is generated from an observation to achieve a generalisation. It is based on the collection of specific data to develop new theories.

Hypothetical-Deductive Investigation

It is based on observing reality to make a hypothesis, then use deduction to obtain a conclusion and finally verify or reject it through experience.

According to the Time in Which it is Carried Out

Longitudinal study (also referred to as diachronic research).

It is the monitoring of the same event, individual or group over a defined period of time. It aims to track changes in a number of variables and see how they evolve over time. It is often used in medical, psychological and social areas .

Cross-Sectional Study (also referred to as Synchronous Research)

Cross-sectional research design is used to observe phenomena, an individual or a group of research subjects at a given time.

According to The Sources of Information

Primary research.

This fundamental research type is defined by the fact that the data is collected directly from the source, that is, it consists of primary, first-hand information.

Secondary research

Unlike primary research, secondary research is developed with information from secondary sources, which are generally based on scientific literature and other documents compiled by another researcher.

According to How the Data is Obtained

Documentary (cabinet).

Documentary research, or secondary sources, is based on a systematic review of existing sources of information on a particular subject. This type of scientific research is commonly used when undertaking literature reviews or producing a case study.

Field research study involves the direct collection of information at the location where the observed phenomenon occurs.

From Laboratory

Laboratory research is carried out in a controlled environment in order to isolate a dependent variable and establish its relationship with other variables through scientific methods.

Mixed-Method: Documentary, Field and/or Laboratory

Mixed research methodologies combine results from both secondary (documentary) sources and primary sources through field or laboratory research.

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Methodology

Research Methods | Definitions, Types, Examples

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 :

Qualitative vs. quantitative : Will your data take the form of words or numbers?
Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

For quantitative data, you can use statistical analysis methods to test relationships between variables.
For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in 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.

Qualitative vs. quantitative data

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 .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

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.

Descriptive vs. experimental data

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.

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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 methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
Using non-probability sampling methods .

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 methods

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:

During an experiment .
Using probability sampling methods .

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.

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.

Chi square test of independence
Statistical power
Descriptive statistics
Degrees of freedom
Pearson correlation
Null hypothesis
Double-blind study
Case-control study
Research ethics
Data collection
Hypothesis testing
Structured interviews

Research bias

Hawthorne effect
Unconscious bias
Recall bias
Halo effect
Self-serving bias
Information 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 .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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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Research methods--quantitative, qualitative, and more: overview.

Quantitative Research
Qualitative Research
Data Science Methods (Machine Learning, AI, Big Data)
Text Mining and Computational Text Analysis
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About Research Methods

This guide provides an overview of research methods, how to choose and use them, and supports and resources at UC Berkeley.

As Patten and Newhart note in the book Understanding Research Methods , "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge. The accumulation of knowledge through research is by its nature a collective endeavor. Each well-designed study provides evidence that may support, amend, refute, or deepen the understanding of existing knowledge...Decisions are important throughout the practice of research and are designed to help researchers collect evidence that includes the full spectrum of the phenomenon under study, to maintain logical rules, and to mitigate or account for possible sources of bias. In many ways, learning research methods is learning how to see and make these decisions."

The choice of methods varies by discipline, by the kind of phenomenon being studied and the data being used to study it, by the technology available, and more. This guide is an introduction, but if you don't see what you need here, always contact your subject librarian, and/or take a look to see if there's a library research guide that will answer your question.

Suggestions for changes and additions to this guide are welcome!

START HERE: SAGE Research Methods

Without question, the most comprehensive resource available from the library is SAGE Research Methods. HERE IS THE ONLINE GUIDE to this one-stop shopping collection, and some helpful links are below:

SAGE Research Methods
Little Green Books (Quantitative Methods)
Little Blue Books (Qualitative Methods)
Dictionaries and Encyclopedias
Case studies of real research projects
Sample datasets for hands-on practice
Streaming video--see methods come to life
Methodspace- -a community for researchers
SAGE Research Methods Course Mapping

Library Data Services at UC Berkeley

Library Data Services Program and Digital Scholarship Services

The LDSP offers a variety of services and tools ! From this link, check out pages for each of the following topics: discovering data, managing data, collecting data, GIS data, text data mining, publishing data, digital scholarship, open science, and the Research Data Management Program.

Be sure also to check out the visual guide to where to seek assistance on campus with any research question you may have!

Library GIS Services

Other Data Services at Berkeley

D-Lab Supports Berkeley faculty, staff, and graduate students with research in data intensive social science, including a wide range of training and workshop offerings Dryad Dryad is a simple self-service tool for researchers to use in publishing their datasets. It provides tools for the effective publication of and access to research data. Geospatial Innovation Facility (GIF) Provides leadership and training across a broad array of integrated mapping technologies on campu Research Data Management A UC Berkeley guide and consulting service for research data management issues

General Research Methods Resources

Here are some general resources for assistance:

Assistance from ICPSR (must create an account to access): Getting Help with Data , and Resources for Students
Wiley Stats Ref for background information on statistics topics
Survey Documentation and Analysis (SDA) . Program for easy web-based analysis of survey data.

Consultants

D-Lab/Data Science Discovery Consultants Request help with your research project from peer consultants.
Research data (RDM) consulting Meet with RDM consultants before designing the data security, storage, and sharing aspects of your qualitative project.
Statistics Department Consulting Services A service in which advanced graduate students, under faculty supervision, are available to consult during specified hours in the Fall and Spring semesters.

Related Resourcex

IRB / CPHS Qualitative research projects with human subjects often require that you go through an ethics review.
OURS (Office of Undergraduate Research and Scholarships) OURS supports undergraduates who want to embark on research projects and assistantships. In particular, check out their "Getting Started in Research" workshops
Sponsored Projects Sponsored projects works with researchers applying for major external grants.
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Last Updated: Apr 3, 2023 3:14 PM
URL: https://guides.lib.berkeley.edu/researchmethods

Research Design 101

Everything You Need To Get Started (With Examples)

By: Derek Jansen (MBA) | Reviewers: Eunice Rautenbach (DTech) & Kerryn Warren (PhD) | April 2023

Research design for qualitative and quantitative studies

Navigating the world of research can be daunting, especially if you’re a first-time researcher. One concept you’re bound to run into fairly early in your research journey is that of “ research design ”. Here, we’ll guide you through the basics using practical examples , so that you can approach your research with confidence.

Overview: Research Design 101

What is research design.

Research design types for quantitative studies
Video explainer : quantitative research design
Research design types for qualitative studies
Video explainer : qualitative research design
How to choose a research design
Key takeaways

Research design refers to the overall plan, structure or strategy that guides a research project , from its conception to the final data analysis. A good research design serves as the blueprint for how you, as the researcher, will collect and analyse data while ensuring consistency, reliability and validity throughout your study.

Understanding different types of research designs is essential as helps ensure that your approach is suitable given your research aims, objectives and questions , as well as the resources you have available to you. Without a clear big-picture view of how you’ll design your research, you run the risk of potentially making misaligned choices in terms of your methodology – especially your sampling , data collection and data analysis decisions.

The problem with defining research design…

One of the reasons students struggle with a clear definition of research design is because the term is used very loosely across the internet, and even within academia.

Some sources claim that the three research design types are qualitative, quantitative and mixed methods , which isn’t quite accurate (these just refer to the type of data that you’ll collect and analyse). Other sources state that research design refers to the sum of all your design choices, suggesting it’s more like a research methodology . Others run off on other less common tangents. No wonder there’s confusion!

In this article, we’ll clear up the confusion. We’ll explain the most common research design types for both qualitative and quantitative research projects, whether that is for a full dissertation or thesis, or a smaller research paper or article.

Research Design: Quantitative Studies

Quantitative research involves collecting and analysing data in a numerical form. Broadly speaking, there are four types of quantitative research designs: descriptive , correlational , experimental , and quasi-experimental .

Descriptive Research Design

As the name suggests, descriptive research design focuses on describing existing conditions, behaviours, or characteristics by systematically gathering information without manipulating any variables. In other words, there is no intervention on the researcher’s part – only data collection.

For example, if you’re studying smartphone addiction among adolescents in your community, you could deploy a survey to a sample of teens asking them to rate their agreement with certain statements that relate to smartphone addiction. The collected data would then provide insight regarding how widespread the issue may be – in other words, it would describe the situation.

The key defining attribute of this type of research design is that it purely describes the situation . In other words, descriptive research design does not explore potential relationships between different variables or the causes that may underlie those relationships. Therefore, descriptive research is useful for generating insight into a research problem by describing its characteristics . By doing so, it can provide valuable insights and is often used as a precursor to other research design types.

Correlational Research Design

Correlational design is a popular choice for researchers aiming to identify and measure the relationship between two or more variables without manipulating them . In other words, this type of research design is useful when you want to know whether a change in one thing tends to be accompanied by a change in another thing.

For example, if you wanted to explore the relationship between exercise frequency and overall health, you could use a correlational design to help you achieve this. In this case, you might gather data on participants’ exercise habits, as well as records of their health indicators like blood pressure, heart rate, or body mass index. Thereafter, you’d use a statistical test to assess whether there’s a relationship between the two variables (exercise frequency and health).

As you can see, correlational research design is useful when you want to explore potential relationships between variables that cannot be manipulated or controlled for ethical, practical, or logistical reasons. It is particularly helpful in terms of developing predictions , and given that it doesn’t involve the manipulation of variables, it can be implemented at a large scale more easily than experimental designs (which will look at next).

That said, it’s important to keep in mind that correlational research design has limitations – most notably that it cannot be used to establish causality . In other words, correlation does not equal causation . To establish causality, you’ll need to move into the realm of experimental design, coming up next…

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Experimental Research Design

Experimental research design is used to determine if there is a causal relationship between two or more variables . With this type of research design, you, as the researcher, manipulate one variable (the independent variable) while controlling others (dependent variables). Doing so allows you to observe the effect of the former on the latter and draw conclusions about potential causality.

For example, if you wanted to measure if/how different types of fertiliser affect plant growth, you could set up several groups of plants, with each group receiving a different type of fertiliser, as well as one with no fertiliser at all. You could then measure how much each plant group grew (on average) over time and compare the results from the different groups to see which fertiliser was most effective.

Overall, experimental research design provides researchers with a powerful way to identify and measure causal relationships (and the direction of causality) between variables. However, developing a rigorous experimental design can be challenging as it’s not always easy to control all the variables in a study. This often results in smaller sample sizes , which can reduce the statistical power and generalisability of the results.

Moreover, experimental research design requires random assignment . This means that the researcher needs to assign participants to different groups or conditions in a way that each participant has an equal chance of being assigned to any group (note that this is not the same as random sampling ). Doing so helps reduce the potential for bias and confounding variables . This need for random assignment can lead to ethics-related issues . For example, withholding a potentially beneficial medical treatment from a control group may be considered unethical in certain situations.

Quasi-Experimental Research Design

Quasi-experimental research design is used when the research aims involve identifying causal relations , but one cannot (or doesn’t want to) randomly assign participants to different groups (for practical or ethical reasons). Instead, with a quasi-experimental research design, the researcher relies on existing groups or pre-existing conditions to form groups for comparison.

For example, if you were studying the effects of a new teaching method on student achievement in a particular school district, you may be unable to randomly assign students to either group and instead have to choose classes or schools that already use different teaching methods. This way, you still achieve separate groups, without having to assign participants to specific groups yourself.

Naturally, quasi-experimental research designs have limitations when compared to experimental designs. Given that participant assignment is not random, it’s more difficult to confidently establish causality between variables, and, as a researcher, you have less control over other variables that may impact findings.

All that said, quasi-experimental designs can still be valuable in research contexts where random assignment is not possible and can often be undertaken on a much larger scale than experimental research, thus increasing the statistical power of the results. What’s important is that you, as the researcher, understand the limitations of the design and conduct your quasi-experiment as rigorously as possible, paying careful attention to any potential confounding variables .

The four most common quantitative research design types are descriptive, correlational, experimental and quasi-experimental.

Research Design: Qualitative Studies

There are many different research design types when it comes to qualitative studies, but here we’ll narrow our focus to explore the “Big 4”. Specifically, we’ll look at phenomenological design, grounded theory design, ethnographic design, and case study design.

Phenomenological Research Design

Phenomenological design involves exploring the meaning of lived experiences and how they are perceived by individuals. This type of research design seeks to understand people’s perspectives , emotions, and behaviours in specific situations. Here, the aim for researchers is to uncover the essence of human experience without making any assumptions or imposing preconceived ideas on their subjects.

For example, you could adopt a phenomenological design to study why cancer survivors have such varied perceptions of their lives after overcoming their disease. This could be achieved by interviewing survivors and then analysing the data using a qualitative analysis method such as thematic analysis to identify commonalities and differences.

Phenomenological research design typically involves in-depth interviews or open-ended questionnaires to collect rich, detailed data about participants’ subjective experiences. This richness is one of the key strengths of phenomenological research design but, naturally, it also has limitations. These include potential biases in data collection and interpretation and the lack of generalisability of findings to broader populations.

Grounded Theory Research Design

Grounded theory (also referred to as “GT”) aims to develop theories by continuously and iteratively analysing and comparing data collected from a relatively large number of participants in a study. It takes an inductive (bottom-up) approach, with a focus on letting the data “speak for itself”, without being influenced by preexisting theories or the researcher’s preconceptions.

As an example, let’s assume your research aims involved understanding how people cope with chronic pain from a specific medical condition, with a view to developing a theory around this. In this case, grounded theory design would allow you to explore this concept thoroughly without preconceptions about what coping mechanisms might exist. You may find that some patients prefer cognitive-behavioural therapy (CBT) while others prefer to rely on herbal remedies. Based on multiple, iterative rounds of analysis, you could then develop a theory in this regard, derived directly from the data (as opposed to other preexisting theories and models).

Grounded theory typically involves collecting data through interviews or observations and then analysing it to identify patterns and themes that emerge from the data. These emerging ideas are then validated by collecting more data until a saturation point is reached (i.e., no new information can be squeezed from the data). From that base, a theory can then be developed .

As you can see, grounded theory is ideally suited to studies where the research aims involve theory generation , especially in under-researched areas. Keep in mind though that this type of research design can be quite time-intensive , given the need for multiple rounds of data collection and analysis.

Ethnographic Research Design

Ethnographic design involves observing and studying a culture-sharing group of people in their natural setting to gain insight into their behaviours, beliefs, and values. The focus here is on observing participants in their natural environment (as opposed to a controlled environment). This typically involves the researcher spending an extended period of time with the participants in their environment, carefully observing and taking field notes .

All of this is not to say that ethnographic research design relies purely on observation. On the contrary, this design typically also involves in-depth interviews to explore participants’ views, beliefs, etc. However, unobtrusive observation is a core component of the ethnographic approach.

As an example, an ethnographer may study how different communities celebrate traditional festivals or how individuals from different generations interact with technology differently. This may involve a lengthy period of observation, combined with in-depth interviews to further explore specific areas of interest that emerge as a result of the observations that the researcher has made.

As you can probably imagine, ethnographic research design has the ability to provide rich, contextually embedded insights into the socio-cultural dynamics of human behaviour within a natural, uncontrived setting. Naturally, however, it does come with its own set of challenges, including researcher bias (since the researcher can become quite immersed in the group), participant confidentiality and, predictably, ethical complexities . All of these need to be carefully managed if you choose to adopt this type of research design.

Case Study Design

With case study research design, you, as the researcher, investigate a single individual (or a single group of individuals) to gain an in-depth understanding of their experiences, behaviours or outcomes. Unlike other research designs that are aimed at larger sample sizes, case studies offer a deep dive into the specific circumstances surrounding a person, group of people, event or phenomenon, generally within a bounded setting or context .

As an example, a case study design could be used to explore the factors influencing the success of a specific small business. This would involve diving deeply into the organisation to explore and understand what makes it tick – from marketing to HR to finance. In terms of data collection, this could include interviews with staff and management, review of policy documents and financial statements, surveying customers, etc.

While the above example is focused squarely on one organisation, it’s worth noting that case study research designs can have different variation s, including single-case, multiple-case and longitudinal designs. As you can see in the example, a single-case design involves intensely examining a single entity to understand its unique characteristics and complexities. Conversely, in a multiple-case design , multiple cases are compared and contrasted to identify patterns and commonalities. Lastly, in a longitudinal case design , a single case or multiple cases are studied over an extended period of time to understand how factors develop over time.

As you can see, a case study research design is particularly useful where a deep and contextualised understanding of a specific phenomenon or issue is desired. However, this strength is also its weakness. In other words, you can’t generalise the findings from a case study to the broader population. So, keep this in mind if you’re considering going the case study route.

Case study design often involves investigating an individual to gain an in-depth understanding of their experiences, behaviours or outcomes.

How To Choose A Research Design

Having worked through all of these potential research designs, you’d be forgiven for feeling a little overwhelmed and wondering, “ But how do I decide which research design to use? ”. While we could write an entire post covering that alone, here are a few factors to consider that will help you choose a suitable research design for your study.

Data type: The first determining factor is naturally the type of data you plan to be collecting – i.e., qualitative or quantitative. This may sound obvious, but we have to be clear about this – don’t try to use a quantitative research design on qualitative data (or vice versa)!

Research aim(s) and question(s): As with all methodological decisions, your research aim and research questions will heavily influence your research design. For example, if your research aims involve developing a theory from qualitative data, grounded theory would be a strong option. Similarly, if your research aims involve identifying and measuring relationships between variables, one of the experimental designs would likely be a better option.

Time: It’s essential that you consider any time constraints you have, as this will impact the type of research design you can choose. For example, if you’ve only got a month to complete your project, a lengthy design such as ethnography wouldn’t be a good fit.

Resources: Take into account the resources realistically available to you, as these need to factor into your research design choice. For example, if you require highly specialised lab equipment to execute an experimental design, you need to be sure that you’ll have access to that before you make a decision.

Keep in mind that when it comes to research, it’s important to manage your risks and play as conservatively as possible. If your entire project relies on you achieving a huge sample, having access to niche equipment or holding interviews with very difficult-to-reach participants, you’re creating risks that could kill your project. So, be sure to think through your choices carefully and make sure that you have backup plans for any existential risks. Remember that a relatively simple methodology executed well generally will typically earn better marks than a highly-complex methodology executed poorly.

Recap: Key Takeaways

We’ve covered a lot of ground here. Let’s recap by looking at the key takeaways:

Research design refers to the overall plan, structure or strategy that guides a research project, from its conception to the final analysis of data.
Research designs for quantitative studies include descriptive , correlational , experimental and quasi-experimenta l designs.
Research designs for qualitative studies include phenomenological , grounded theory , ethnographic and case study designs.
When choosing a research design, you need to consider a variety of factors, including the type of data you’ll be working with, your research aims and questions, your time and the resources available to you.

If you need a helping hand with your research design (or any other aspect of your research), check out our private coaching services .

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Is there any blog article explaining more on Case study research design? Is there a Case study write-up template? Thank you.

Thanks this was quite valuable to clarify such an important concept.

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Thank you for your explanation. I think case study research design and the use of secondary data in researches needs to be talked about more in your videos and articles because there a lot of case studies research design tailored projects out there.

Please is there any template for a case study research design whose data type is a secondary data on your repository?

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Methodology

Research Methods | Definition, Types, Examples

Research methods are specific procedures for collecting and analysing 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 :

Qualitative vs quantitative : Will your data take the form of words or numbers?
Primary vs secondary : Will you collect original data yourself, or will you use data that have already been collected by someone else?
Descriptive vs experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyse the data .

For quantitative data, you can use statistical analysis methods to test relationships between variables.
For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Methods for collecting data, examples of data collection methods, methods for analysing data, examples of data analysis methods, frequently asked questions about methodology.

Data are 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.

Qualitative vs quantitative data

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 .

You can also take a mixed methods approach, where you use both qualitative and quantitative research methods.

Primary vs secondary data

Primary data are any original information that you collect for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary data are information 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 synthesise existing knowledge, analyse historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs experimental data

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 .

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Your data analysis methods will depend on the type of data you collect and how you prepare them for analysis.

Data can often be analysed both quantitatively and qualitatively. For example, survey responses could be analysed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that were collected:

From open-ended survey and interview questions, literature reviews, case studies, and other sources that use text rather than numbers.
Using non-probability sampling methods .

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.

Quantitative analysis methods

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 were collected either:

During an experiment.
Using probability sampling methods .

Because the data are collected and analysed in a statistically valid way, the results of quantitative analysis can be easily standardised and shared among researchers.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

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.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. 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 .

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Research Study Types

There are many different types of research studies, and each has distinct strengths and weaknesses. In general, randomized trials and cohort studies provide the best information when looking at the link between a certain factor (like diet) and a health outcome (like heart disease).

Laboratory and Animal Studies

These are studies done in laboratories on cells, tissue, or animals.

Strengths: Laboratories provide strictly controlled conditions and are often the genesis of scientific ideas that go on to have a broad impact on human health. They can help understand the mechanisms of disease.
Weaknesses: Laboratory and animal studies are only a starting point. Animals or cells are not a substitute for humans.

Cross-Sectional Surveys

These studies examine the incidence of a certain outcome (disease or other health characteristic) in a specific group of people at one point in time. Surveys are often sent to participants to gather data about the outcome of interest.

Strengths: Inexpensive and easy to perform.
Weaknesses: Can only establish an association in that one specific time period.

Case-Control Studies

These studies look at the characteristics of one group of people who already have a certain health outcome (the cases) and compare them with a similar group of people who do not have the outcome (the controls). An example may be looking at a group of people with heart disease and another group without heart disease who are similar in age, sex, and economic status, and comparing their intakes of fruits and vegetables to see if this exposure could be associated with heart disease risk.

Strengths: Case-control studies can be done quickly and relatively cheaply.
Weaknesses: Not ideal for studying diet because they gather information from the past, which can be difficult for most people to recall accurately. Furthermore, people with illnesses often recall past behaviors differently from those without illness. This opens such studies to potential inaccuracy and bias in the information they gather.

Cohort Studies

These are observational studies that follow large groups of people over a long period of time, years or even decades, to find associations of an exposure(s) with disease outcomes. Researchers regularly gather information from the people in the study on several variables (like meat intake, physical activity level, and weight). Once a specified amount of time has elapsed, the characteristics of people in the group are compared to test specific hypotheses (such as a link between high versus low intake of carotenoid-rich foods and glaucoma, or high versus low meat intake and prostate cancer).

Strengths: Participants are not required to change their diets or lifestyle as may be with randomized controlled studies. Study sizes may be larger than other study types. They generally provide more reliable information than case-control studies because they don’t rely on information from the past. Cohort studies gather information from participants at the beginning and throughout the study, long before they may develop the disease being studied. As a group, many of these types of studies have provided valuable information about the link between lifestyle factors and disease.
Weaknesses: A longer duration of following participants make these studies time-consuming and expensive. Results cannot suggest cause-and-effect, only associations. Evaluation of dietary intake is self-reported.

Two of the largest and longest-running cohort studies of diet are the Harvard-based Nurses’ Health Study and the Health Professionals Follow-up Study.

If you follow nutrition news, chances are you have come across findings from a cohort called the Nurses’ Health Study . The Nurses’ Health Study (NHS) began in 1976, spearheaded by researchers from the Channing Laboratory at the Brigham and Women’s Hospital, Harvard Medical School, and the Harvard T.H. Chan School of Public Health, with funding from the National Institutes of Health. It gathered registered nurses ages 30-55 years from across the U.S. to respond to a series of questionnaires. Nurses were specifically chosen because of their ability to complete the health-related, often very technical, questionnaires thoroughly and accurately. They showed motivation to participate in the long-term study that required ongoing questionnaires every two years. Furthermore, the group provided blood, urine, and other samples over the course of the study.

The NHS is a prospective cohort study, meaning a group of people who are followed forward in time to examine lifestyle habits or other characteristics to see if they develop a disease, death, or some other indicated outcome. In comparison, a retrospective cohort study would specify a disease or outcome and look back in time at the group to see if there were common factors leading to the disease or outcome. A benefit of prospective studies over retrospective studies is greater accuracy in reporting details, such as food intake, that is not distorted by the diagnosis of illness.

To date, there are three NHS cohorts: NHS original cohort, NHS II, and NHS 3. Below are some features unique to each cohort.

NHS – Original Cohort

Started in 1976 by Frank Speizer, M.D.
Participants: 121,700 married women, ages 30 to 55 in 1976.
Outcomes studied: Impact of contraceptive methods and smoking on breast cancer; later this was expanded to observe other lifestyle factors and behaviors in relation to 30 diseases.
A food frequency questionnaire was added in 1980 to collect information on dietary intake, and continues to be collected every four years.
Started in 1989 by Walter Willett, M.D., M.P.H., Dr.P.H., and colleagues.
Participants: 116,430 single and married women, ages 25 to 42 in 1989.
Outcomes studied: Impact on women’s health of oral contraceptives initiated during adolescence, diet and physical activity in adolescence, and lifestyle risk factors in a younger population than the NHS Original Cohort. The wide range of diseases examined in the original NHS is now also being studied in NHSII.
The first food frequency questionnaire was collected in 1991, and is collected every four years.
Started in 2010 by Jorge Chavarro, M.D., Sc.M., Sc.D, Walter Willett, M.D., M.P.H., Dr.P.H., Janet Rich-Edwards, Sc.D., M.P.H, and Stacey Missmer, Sc.D.
Participants: Expanded to include not just registered nurses but licensed practical nurses (LPN) and licensed vocational nurses (LVN), ages 19 to 46. Enrollment is currently open.
Inclusion of more diverse population of nurses, including male nurses and nurses from Canada.
Outcomes studied: Dietary patterns, lifestyle, environment, and nursing occupational exposures that may impact men’s and women’s health; the impact of new hormone preparations and fertility/pregnancy on women’s health; relationship of diet in adolescence on breast cancer risk.

From these three cohorts, extensive research has been published regarding the association of diet, smoking, physical activity levels, overweight and obesity, oral contraceptive use, hormone therapy, endogenous hormones, dietary factors, sleep, genetics, and other behaviors and characteristics with various diseases. In 2016, in celebration of the 40 th Anniversary of NHS, the American Journal of Public Health’s September issue was dedicated to featuring the many contributions of the Nurses’ Health Studies to public health.

Growing Up Today Study (GUTS)

In 1996, recruitment began for a new cross-generational cohort called GUTS (Growing Up Today Study) —children of nurses from the NHS II. GUTS is composed of 27,802 girls and boys who were between the ages of 9 and 17 at the time of enrollment. As the entire cohort has entered adulthood, they complete annual questionnaires including information on dietary intake, weight changes, exercise level, substance and alcohol use, body image, and environmental factors. Researchers are looking at conditions more common in young adults such as asthma, skin cancer, eating disorders, and sports injuries.

Randomized Trials

Like cohort studies, these studies follow a group of people over time. However, with randomized trials, the researchers intervene with a specific behavior change or treatment (such as following a specific diet or taking a supplement) to see how it affects a health outcome. They are called “randomized trials” because people in the study are randomly assigned to either receive or not receive the intervention. This randomization helps researchers determine the true effect the intervention has on the health outcome. Those who do not receive the intervention or labelled the “control group,” which means these participants do not change their behavior, or if the study is examining the effects of a vitamin supplement, the control group participants receive a placebo supplement that contains no active ingredients.

Strengths: Considered the “gold standard” and best for determining the effectiveness of an intervention (e.g., dietary pattern, supplement) on an endpoint such as cancer or heart disease. Conducted in a highly controlled setting with limited variables that could affect the outcome. They determine cause-and-effect relationships.
Weaknesses: High cost, potentially low long-term compliance with prescribed diets, and possible ethical issues. Due to expense, the study size may be small.

Meta-Analyses and Systematic Reviews

A meta-analysis collects data from several previous studies on one topic to analyze and combine the results using statistical methods to provide a summary conclusion. Meta-analyses are usually conducted using randomized controlled trials and cohort studies that have higher quality of evidence than other designs. A systematic review also examines past literature related to a specific topic and design, analyzing the quality of studies and results but may not pool the data. Sometimes a systematic review is followed by conducting a meta-analysis if the quality of the studies is good and the data can be combined.

Strengths: Inexpensive and provides a general comprehensive summary of existing research on a topic. This can create an explanation or assumption to be used for further investigation.
Weaknesses: Prone to selection bias, as the authors can choose or exclude certain studies, which can change the resulting outcome. Combining data that includes lower-quality studies can also skew the results.

A primer on systematic review and meta-analysis in diabetes research

The contents of this website are for educational purposes and are not intended to offer personal medical advice. You should seek the advice of your physician or other qualified health provider with any questions you may have regarding a medical condition. Never disregard professional medical advice or delay in seeking it because of something you have read on this website. The Nutrition Source does not recommend or endorse any products.

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Home » Research Methodology – Types, Examples and writing Guide

Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

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.

Structure of Research Methodology

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

Provide an overview of the research problem and the need for a research methodology section
Outline the main research questions and objectives

II. Research Design

Explain the research design chosen and why it is appropriate for the research question(s) and objectives
Discuss any alternative research designs considered and why they were not chosen
Describe the research setting and participants (if applicable)

III. Data Collection Methods

Describe the methods used to collect data (e.g., surveys, interviews, observations)
Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
Detail any procedures or software used for data analysis

V. Ethical Considerations

Discuss any ethical issues that may arise from the research and how they were addressed
Explain how informed consent was obtained (if applicable)
Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

Summarize the key aspects of the research methodology section
Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

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.

Qualitative Research Methodology

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.

Mixed-Methods Research Methodology

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.

Case Study Research Methodology

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.

Action Research Methodology

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.

Experimental Research Methodology

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.

Survey Research Methodology

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.

Grounded Theory Research Methodology

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.

Research Methodology Example

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.

How to Write Research Methodology

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:

Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write 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.

Applications of Research Methodology

Here are some of the applications of research methodology:

To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

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:

Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

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Researcher, Academic Writer, Web developer

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1.9: Types of Research Studies and How To Interpret Them

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Alice Callahan, Heather Leonard, & Tamberly Powell

Alice Callahan, Heather Leonard, & Tamberly Powell
Lane Community College via OpenOregon

The field of nutrition is dynamic, and our understanding and practices are always evolving. Nutrition scientists are continuously conducting new research and publishing their findings in peer-reviewed journals. This adds to scientific knowledge, but it’s also of great interest to the public, so nutrition research often shows up in the news and other media sources. You might be interested in nutrition research to inform your own eating habits, or if you work in a health profession, so that you can give evidence-based advice to others. Making sense of science requires that you understand the types of research studies used and their limitations.

The Hierarchy of Nutrition Evidence

Researchers use many different types of study designs depending on the question they are trying to answer, as well as factors such as time, funding, and ethical considerations. The study design affects how we interpret the results and the strength of the evidence as it relates to real-life nutrition decisions. It can be helpful to think about the types of studies within a pyramid representing a hierarchy of evidence, where the studies at the bottom of the pyramid usually give us the weakest evidence with the least relevance to real-life nutrition decisions, and the studies at the top offer the strongest evidence, with the most relevance to real-life nutrition decisions .

The pyramid also represents a few other general ideas. There tend to be more studies published using the methods at the bottom of the pyramid, because they require less time, money, and other resources. When researchers want to test a new hypothesis , they often start with the study designs at the bottom of the pyramid , such as in vitro, animal, or observational studies. Intervention studies are more expensive and resource-intensive, so there are fewer of these types of studies conducted. But they also give us higher quality evidence, so they’re an important next step if observational and non-human studies have shown promising results. Meta-analyses and systematic reviews combine the results of many studies already conducted, so they help researchers summarize scientific knowledge on a topic.

Non-Human Studies: In Vitro & Animal Studies

The simplest form of nutrition research is an in vitro study . In vitro means “within glass,” (although plastic is used more commonly today) and these experiments are conducted within flasks, dishes, plates, and test tubes. These studies are performed on isolated cells or tissue samples, so they’re less expensive and time-intensive than animal or human studies. In vitro studies are vital for zooming in on biological mechanisms, to see how things work at the cellular or molecular level. However, these studies shouldn’t be used to draw conclusions about how things work in humans (or even animals), because we can’t assume that the results will apply to a whole, living organism.

Two photos representing lab research. At left, a person appearing to be a woman with long dark hair and dark skin handles tiny tubes in a black bucket of ice. More tubes surround the bucket on the table. At right, a white mouse with red eyes peers out of an opening of a cage.

Animal studies are one form of in vivo research, which translates to “within the living.” Rats and mice are the most common animals used in nutrition research. Animals are often used in research that would be unethical to conduct in humans. Another advantage of animal dietary studies is that researchers can control exactly what the animals eat. In human studies, researchers can tell subjects what to eat and even provide them with the food, but they may not stick to the planned diet. People are also not very good at estimating, recording, or reporting what they eat and in what quantities. In addition, animal studies typically do not cost as much as human studies.

There are some important limitations of animal research. First, an animal’s metabolism and physiology are different from humans. Plus, animal models of disease (cancer, cardiovascular disease, etc.), although similar, are different from human diseases. Animal research is considered preliminary, and while it can be very important to the process of building scientific understanding and informing the types of studies that should be conducted in humans, animal studies shouldn’t be considered relevant to real-life decisions about how people eat.

Observational Studies

Observational studies in human nutrition collect information on people’s dietary patterns or nutrient intake and look for associations with health outcomes. Observational studies do not give participants a treatment or intervention; instead, they look at what they’re already doing and see how it relates to their health. These types of study designs can only identify correlations (relationships) between nutrition and health; they can’t show that one factor causes another. (For that, we need intervention studies, which we’ll discuss in a moment.) Observational studies that describe factors correlated with human health are also called epidemiological studies . 1

One example of a nutrition hypothesis that has been investigated using observational studies is that eating a Mediterranean diet reduces the risk of developing cardiovascular disease. (A Mediterranean diet focuses on whole grains, fruits and vegetables, beans and other legumes, nuts, olive oil, herbs, and spices. It includes small amounts of animal protein (mostly fish), dairy, and red wine. 2 ) There are three main types of observational studies, all of which could be used to test hypotheses about the Mediterranean diet:

Cohort studies follow a group of people (a cohort) over time, measuring factors such as diet and health outcomes. A cohort study of the Mediterranean diet would ask a group of people to describe their diet, and then researchers would track them over time to see if those eating a Mediterranean diet had a lower incidence of cardiovascular disease.
Case-control studies compare a group of cases and controls, looking for differences between the two groups that might explain their different health outcomes. For example, researchers might compare a group of people with cardiovascular disease with a group of healthy controls to see whether there were more controls or cases that followed a Mediterranean diet.
Cross-sectional studies collect information about a population of people at one point in time. For example, a cross-sectional study might compare the dietary patterns of people from different countries to see if diet correlates with the prevalence of cardiovascular disease in the different countries.

Prospective cohort studies, which enroll a cohort and follow them into the future, are usually considered the strongest type of observational study design. Retrospective studies look at what happened in the past, and they’re considered weaker because they rely on people’s memory of what they ate or how they felt in the past. There are several well-known examples of prospective cohort studies that have described important correlations between diet and disease:

Framingham Heart Study : Beginning in 1948, this study has followed the residents of Framingham, Massachusetts to identify risk factors for heart disease.
Health Professionals Follow-Up Study : This study started in 1986 and enrolled 51,529 male health professionals (dentists, pharmacists, optometrists, osteopathic physicians, podiatrists, and veterinarians), who complete diet questionnaires every 2 years.
Nurses Health Studies : Beginning in 1976, these studies have enrolled three large cohorts of nurses with a total of 280,000 participants. Participants have completed detailed questionnaires about diet, other lifestyle factors (smoking and exercise, for example), and health outcomes.

Observational studies have the advantage of allowing researchers to study large groups of people in the real world, looking at the frequency and pattern of health outcomes and identifying factors that correlate with them. But even very large observational studies may not apply to the population as a whole. For example, the Health Professionals Follow-Up Study and the Nurses Health Studies include people with above-average knowledge of health. In many ways, this makes them ideal study subjects, because they may be more motivated to be part of the study and to fill out detailed questionnaires for years. However, the findings of these studies may not apply to people with less baseline knowledge of health.

We’ve already mentioned another important limitation of observational studies—that they can only determine correlation, not causation. A prospective cohort study that finds that people eating a Mediterranean diet have a lower incidence of heart disease can only show that the Mediterranean diet is correlated with lowered risk of heart disease. It can’t show that the Mediterranean diet directly prevents heart disease. Why? There are a huge number of factors that determine health outcomes such as heart disease, and other factors might explain a correlation found in an observational study. For example, people who eat a Mediterranean diet might also be the same kind of people who exercise more, sleep more, have higher income (fish and nuts can be expensive!), or be less stressed. These are called confounding factors ; they’re factors that can affect the outcome in question (i.e., heart disease) and also vary with the factor being studied (i.e., Mediterranean diet).

Intervention Studies

Intervention studies , also sometimes called experimental studies or clinical trials, include some type of treatment or change imposed by the researcher. Examples of interventions in nutrition research include asking participants to change their diet, take a supplement, or change the time of day that they eat. Unlike observational studies, intervention studies can provide evidence of cause and effect , so they are higher in the hierarchy of evidence pyramid.

The gold standard for intervention studies is the randomized controlled trial (RCT) . In an RCT, study subjects are recruited to participate in the study. They are then randomly assigned into one of at least two groups, one of which is a control group (this is what makes the study controlled ). In an RCT to study the effects of the Mediterranean diet on cardiovascular disease development, researchers might ask the control group to follow a low-fat diet (typically recommended for heart disease prevention) and the intervention group to eat a Mediterrean diet. The study would continue for a defined period of time (usually years to study an outcome like heart disease), at which point the researchers would analyze their data to see if more people in the control or Mediterranean diet had heart attacks or strokes. Because the treatment and control groups were randomly assigned, they should be alike in every other way except for diet, so differences in heart disease could be attributed to the diet. This eliminates the problem of confounding factors found in observational research, and it’s why RCTs can provide evidence of causation, not just correlation.

Imagine for a moment what would happen if the two groups weren’t randomly assigned. What if the researchers let study participants choose which diet they’d like to adopt for the study? They might, for whatever reason, end up with more overweight people who smoke and have high blood pressure in the low-fat diet group, and more people who exercised regularly and had already been eating lots of olive oil and nuts for years in the Mediterranean diet group. If they found that the Mediterranean diet group had fewer heart attacks by the end of the study, they would have no way of knowing if this was because of the diet or because of the underlying differences in the groups. In other words, without randomization, their results would be compromised by confounding factors, with many of the same limitations as observational studies.

In an RCT of a supplement, the control group would receive a placebo—a “fake” treatment that contains no active ingredients, such as a sugar pill. The use of a placebo is necessary in medical research because of a phenomenon known as the placebo effect. The placebo effect results in a beneficial effect because of a subject’s belief in the treatment, even though there is no treatment actually being administered.

A cartoon depicts the study described in the text. At left is shown the "super duper sports drink" (sports drink plus food coloring) in orange. At right is the regular sports drink in green. A cartoon guy with yellow hair is pictured sprinting. The time with the super duper sports drink is 10.50 seconds, and the time with the regular sports drink is 11.00 seconds. The image reads "the improvement is the placebo effect."

Blinding is a technique to prevent bias in intervention studies. In a study without blinding, the subject and the researchers both know what treatment the subject is receiving. This can lead to bias if the subject or researcher have expectations about the treatment working, so these types of trials are used less frequently. It’s best if a study is double-blind , meaning that neither the researcher nor the subject know what treatment the subject is receiving. It’s relatively simple to double-blind a study where subjects are receiving a placebo or treatment pill, because they could be formulated to look and taste the same. In a single-blind study , either the researcher or the subject knows what treatment they’re receiving, but not both. Studies of diets—such as the Mediterranean diet example—often can’t be double-blinded because the study subjects know whether or not they’re eating a lot of olive oil and nuts. However, the researchers who are checking participants’ blood pressure or evaluating their medical records could be blinded to their treatment group, reducing the chance of bias.

Like all studies, RCTs and other intervention studies do have some limitations. They can be difficult to carry on for long periods of time and require that participants remain compliant with the intervention. They’re also costly and often have smaller sample sizes. Furthermore, it is unethical to study certain interventions. (An example of an unethical intervention would be to advise one group of pregnant mothers to drink alcohol to determine its effects on pregnancy outcomes, because we know that alcohol consumption during pregnancy damages the developing fetus.)

VIDEO: “ Not all scientific studies are created equal ” by David H. Schwartz, YouTube (April 28, 2014), 4:26.

Meta-Analyses and Systematic Reviews

At the top of the hierarchy of evidence pyramid are systematic reviews and meta-analyses . You can think of these as “studies of studies.” They attempt to combine all of the relevant studies that have been conducted on a research question and summarize their overall conclusions. Researchers conducting a systematic review formulate a research question and then systematically and independently identify, select, evaluate, and synthesize all high-quality evidence that relates to the research question. Since systematic reviews combine the results of many studies, they help researchers produce more reliable findings. A meta-analysis is a type of systematic review that goes one step further, combining the data from multiple studies and using statistics to summarize it, as if creating a mega-study from many smaller studies . 4

However, even systematic reviews and meta-analyses aren’t the final word on scientific questions. For one thing, they’re only as good as the studies that they include. The Cochrane Collaboration is an international consortium of researchers who conduct systematic reviews in order to inform evidence-based healthcare, including nutrition, and their reviews are among the most well-regarded and rigorous in science. For the most recent Cochrane review of the Mediterranean diet and cardiovascular disease, two authors independently reviewed studies published on this question. Based on their inclusion criteria, 30 RCTs with a total of 12,461 participants were included in the final analysis. However, after evaluating and combining the data, the authors concluded that “despite the large number of included trials, there is still uncertainty regarding the effects of a Mediterranean‐style diet on cardiovascular disease occurrence and risk factors in people both with and without cardiovascular disease already.” Part of the reason for this uncertainty is that different trials found different results, and the quality of the studies was low to moderate. Some had problems with their randomization procedures, for example, and others were judged to have unreliable data. That doesn’t make them useless, but it adds to the uncertainty about this question, and uncertainty pushes the field forward towards more and better studies. The Cochrane review authors noted that they found seven ongoing trials of the Mediterranean diet, so we can hope that they’ll add more clarity to this question in the future. 5

Science is an ongoing process. It’s often a slow process, and it contains a lot of uncertainty, but it’s our best method of building knowledge of how the world and human life works. Many different types of studies can contribute to scientific knowledge. None are perfect—all have limitations—and a single study is never the final word on a scientific question. Part of what advances science is that researchers are constantly checking each other’s work, asking how it can be improved and what new questions it raises.

Attributions:

“Chapter 1: The Basics” from Lindshield, B. L. Kansas State University Human Nutrition (FNDH 400) Flexbook. goo.gl/vOAnR , CC BY-NC-SA 4.0
“ The Broad Role of Nutritional Science ,” section 1.3 from the book An Introduction to Nutrition (v. 1.0), CC BY-NC-SA 3.0

References:

1 Thiese, M. S. (2014). Observational and interventional study design types; an overview. Biochemia Medica , 24 (2), 199–210. https://doi.org/10.11613/BM.2014.022
2 Harvard T.H. Chan School of Public Health. (2018, January 16). Diet Review: Mediterranean Diet . The Nutrition Source. https://www.hsph.harvard.edu/nutritionsource/healthy-weight/diet-reviews/mediterranean-diet/
3 Ross, R., Gray, C. M., & Gill, J. M. R. (2015). Effects of an Injected Placebo on Endurance Running Performance. Medicine and Science in Sports and Exercise , 47 (8), 1672–1681. https://doi.org/10.1249/MSS.0000000000000584
4 Hooper, A. (n.d.). LibGuides: Systematic Review Resources: Systematic Reviews vs Other Types of Reviews . Retrieved February 7, 2020, from //libguides.sph.uth.tmc.edu/c.php?g=543382&p=5370369
5 Rees, K., Takeda, A., Martin, N., Ellis, L., Wijesekara, D., Vepa, A., Das, A., Hartley, L., & Stranges, S. (2019). Mediterranean‐style diet for the primary and secondary prevention of cardiovascular disease. Cochrane Database of Systematic Reviews , 3 . doi.org/10.1002/14651858.CD009825.pub3
Figure 2.3. The hierarchy of evidence by Alice Callahan, is licensed under CC BY 4.0
Research lab photo by National Cancer Institute on Unsplas h ; mouse photo by vaun0815 on Unsplash
Figure 2.4. “Placebo effect example” by Lindshield, B. L. Kansas State University Human Nutrition (FNDH 400) Flexbook. goo.gl/vOAnR

What is Research Methodology? Definition, Types, and Examples

Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.

The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.

What is research methodology ?

A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.

Why is research methodology important?

Having a good research methodology in place has the following advantages: 3

Helps other researchers who may want to replicate your research; the explanations will be of benefit to them.
You can easily answer any questions about your research if they arise at a later stage.
A research methodology provides a framework and guidelines for researchers to clearly define research questions, hypotheses, and objectives.
It helps researchers identify the most appropriate research design, sampling technique, and data collection and analysis methods.
A sound research methodology helps researchers ensure that their findings are valid and reliable and free from biases and errors.
It also helps ensure that ethical guidelines are followed while conducting research.
A good research methodology helps researchers in planning their research efficiently, by ensuring optimum usage of their time and resources.

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Types of research methodology.

There are three types of research methodology based on the type of research and the data required. 1

Quantitative research methodology focuses on measuring and testing numerical data. This approach is good for reaching a large number of people in a short amount of time. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations.
Qualitative research methodology examines the opinions, behaviors, and experiences of people. It collects and analyzes words and textual data. This research methodology requires fewer participants but is still more time consuming because the time spent per participant is quite large. This method is used in exploratory research where the research problem being investigated is not clearly defined.
Mixed-method research methodology uses the characteristics of both quantitative and qualitative research methodologies in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method.

What are the types of sampling designs in research methodology?

Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.

Probability sampling

In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:

Systematic —sample members are chosen at regular intervals. It requires selecting a starting point for the sample and sample size determination that can be repeated at regular intervals. This type of sampling method has a predefined range; hence, it is the least time consuming.
Stratified —researchers divide the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized, and then a sample can be drawn from each group separately.
Cluster —the population is divided into clusters based on demographic parameters like age, sex, location, etc.
Convenience —selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.
Purposive —participants are selected at the researcher’s discretion. Researchers consider the purpose of the study and the understanding of the target audience.
Snowball —already selected participants use their social networks to refer the researcher to other potential participants.
Quota —while designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.

What are data collection methods?

During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.

Qualitative research 5

One-on-one interviews: Helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event
Document study/literature review/record keeping: Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
Focus groups: Constructive discussions that usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic.
Qualitative observation : Researchers collect data using their five senses (sight, smell, touch, taste, and hearing).

Quantitative research 6

Sampling: The most common type is probability sampling.
Interviews: Commonly telephonic or done in-person.
Observations: Structured observations are most commonly used in quantitative research. In this method, researchers make observations about specific behaviors of individuals in a structured setting.
Document review: Reviewing existing research or documents to collect evidence for supporting the research.
Surveys and questionnaires. Surveys can be administered both online and offline depending on the requirement and sample size.

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What are data analysis methods.

The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.

Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.

Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:

Measures of frequency (count, percent, frequency)
Measures of central tendency (mean, median, mode)
Measures of dispersion or variation (range, variance, standard deviation)
Measure of position (percentile ranks, quartile ranks)

Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:

Correlation: To understand the relationship between two or more variables.
Cross-tabulation: Analyze the relationship between multiple variables.
Regression analysis: Study the impact of independent variables on the dependent variable.
Frequency tables: To understand the frequency of data.
Analysis of variance: To test the degree to which two or more variables differ in an experiment.

Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:

Content analysis: For analyzing documented information from text and images by determining the presence of certain words or concepts in texts.
Narrative analysis: For analyzing content obtained from sources such as interviews, field observations, and surveys. The stories and opinions shared by people are used to answer research questions.
Discourse analysis: For analyzing interactions with people considering the social context, that is, the lifestyle and environment, under which the interaction occurs.
Grounded theory: Involves hypothesis creation by data collection and analysis to explain why a phenomenon occurred.
Thematic analysis: To identify important themes or patterns in data and use these to address an issue.

How to choose a research methodology?

Here are some important factors to consider when choosing a research methodology: 8

Research objectives, aims, and questions —these would help structure the research design.
Review existing literature to identify any gaps in knowledge.
Check the statistical requirements —if data-driven or statistical results are needed then quantitative research is the best. If the research questions can be answered based on people’s opinions and perceptions, then qualitative research is most suitable.
Sample size —sample size can often determine the feasibility of a research methodology. For a large sample, less effort- and time-intensive methods are appropriate.
Constraints —constraints of time, geography, and resources can help define the appropriate methodology.

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How to write a research methodology .

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.
Research method —this can be quantitative, qualitative, or mixed-method.
Reason for selecting a specific methodology —explain why this methodology is the most suitable to answer your research problem.
Research instruments —explain the research instruments you plan to use, mainly referring to the data collection methods such as interviews, surveys, etc. Here as well, a reason should be mentioned for selecting the particular instrument.
Sampling —this involves selecting a representative subset of the population being studied.
Data collection —involves gathering data using several data collection methods, such as surveys, interviews, etc.
Data analysis —describe the data analysis methods you will use once you’ve collected the data.
Research limitations —mention any limitations you foresee while conducting your research.
Validity and reliability —validity helps identify the accuracy and truthfulness of the findings; reliability refers to the consistency and stability of the results over time and across different conditions.
Ethical considerations —research should be conducted ethically. The considerations include obtaining consent from participants, maintaining confidentiality, and addressing conflicts of interest.

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Frequently Asked Questions

Q1. What are the key components of research methodology?

A1. A good research methodology has the following key components:

Research design
Data collection procedures
Data analysis methods
Ethical considerations

Q2. Why is ethical consideration important in research methodology?

A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10

Participants should not be subjected to harm.
Respect for the dignity of participants should be prioritized.
Full consent should be obtained from participants before the study.
Participants’ privacy should be ensured.
Confidentiality of the research data should be ensured.
Anonymity of individuals and organizations participating in the research should be maintained.
The aims and objectives of the research should not be exaggerated.
Affiliations, sources of funding, and any possible conflicts of interest should be declared.
Communication in relation to the research should be honest and transparent.
Misleading information and biased representation of primary data findings should be avoided.

Q3. What is the difference between methodology and method?

A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.

Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.

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Factors to consider while choosing the right research methodology. PhD Monster website. Accessed August 17, 2023. https://www.phdmonster.com/factors-to-consider-while-choosing-the-right-research-methodology/
What is research methodology? Research and writing guides. Accessed August 14, 2023. https://paperpile.com/g/what-is-research-methodology/
Ethical considerations. Business research methodology website. Accessed August 17, 2023. https://research-methodology.net/research-methodology/ethical-considerations/

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Comment: Schools are using research to try to improve children’s learning – but it’s not working

4 April 2024

What is the best practice for using evidence from research studies in schools? Dr Sally Riordan (IOE, UCL's Faculty of Education and Society) argues that we don’t have enough evidence to be confident that it should always be the first port of call in The Conversation.

Evidence is obviously a good thing. We take it for granted that evidence from research can help solve the post-lockdown crises in education – from how to keep teachers in the profession to how to improve behaviour in schools, get children back into school and protect the mental health of a generation.

But my research and that of others shows that incorporating strategies that have evidence backing them into teaching doesn’t always yield the results we want.

The Department for Education encourages school leadership teams to cite evidence from research studies when deciding how to spend school funding. Teachers are more frequently required to conduct their own research as part of their professional training than they were a decade ago. Independent consultancies have sprung up to support schools to bring evidence-based methods into their teaching.

This push for evidence to back up teaching methods has become particularly strong in the past ten years. The movement has been driven by the Education Endowment Foundation (EEF), a charity set up in 2011 with funding from the Conservative-Liberal Democrat coalition government to provide schools with information about which teaching methods and other approaches to education actually work.

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The EEF funds randomised controlled trials – large-scale studies in which students are randomly assigned to an educational initiative or not and then comparisons are then made to see which students perform better. For instance, several of these studies have been carried out in which some children received one-on-one reading sessions with a trained classroom assistant, and their reading progress was compared to children who had not. The cost of one of these trials was around £500,000 over the course of a year.

Trials such as this in education were lobbied for by Ben Goldacre, a doctor and data scientist who wrote a report in 2013 on behalf of the Department for Education. Goldacre suggested that education should follow the lead of medicine in the use of evidence.

Using evidence

In 2023, however, researchers at the University of Warwick pointed out something that should have been obvious for some time but has been very much overlooked – that following the evidence is not resulting in the progress we might expect.

Reading is the most heavily supported area of the EEF’s research, accounting for more than 40% of projects. Most schools have implemented reading programmes with significant amounts of evidence behind them. But, despite this, reading abilities have not changed much in the UK for decades.

This flatlining of test scores is a global phenomenon. If reading programmes worked as the evidence says they do, reading abilities should be better.

And the evidence is coming back with unexpected results. A series of randomised controlled trials, including one looking at how to improve literacy through evidence, have suggested that schools that use methods based on research are not performing better than schools that do not.

In fact, research by a team at Sheffield Hallam University have demonstrated that on average, these kinds of education initiatives have very little to no impact.

My work has shown that when the findings of different research studies are brought together and synthesised, teachers may end up implementing these findings in contradictory ways. Research messages are frequently too vague to be effective because the skills and expertise of teaching are difficult to transfer.

It is also becoming apparent that the gains in education are usually very small, perhaps because learning is the sum total of trillions of interactions. It is possible that the research trials we really need in education would be so vast that they are currently too impractical to do.

It seems that evidence is much harder to tame and to apply sensibly in education than elsewhere. In my view, it was inevitable and necessary that educators had to follow medicine in our search for answers. But we now need to think harder about the peculiarities of how evidence works in education.

Right now, we don’t have enough evidence to be confident that evidence should always be our first port of call.

This article was originally published in The Conversation on 2 April 2024.

Original article in The Conversation
Dr Sally Riordan's academic profile
IOE, Faculty of Education and Society

‘It’s the greatest living experiment’: Pitt Men’s Study marks 40 years of AIDS research

Anthony Silvestre, left, with August Pusateri, contributes to a poster remembering those lost on World AIDS Day in 2015 at Heinz Chapel and sponsored by the Pitt Men’s Study.

PITTSBURGH — In a Pittsburgh hospital in the early 1980s, Charles Rinaldo saw a young, previously healthy gay man critically ill with a virus usually only seen in weakened immune systems.

Around the same time, Jeffrey Toth was hearing terms like “the gay cancer” and “gay related immune deficiency” — and watching players in his gay softball league get mysteriously ill.

“People were dying and we didn’t know why,” said Marc C. E. Wagner. “I knew it was a devastating condition, even early on.”

Through gay bars and picnics, word began to spread about a study at the University of Pittsburgh investigating the disease, and on April 1, 1984, the study officially began recruiting its first participants.

Forty years later, the Pitt Men’s Study is one of the longest-running studies on HIV and AIDS in the country. About 2,000 men have participated since the beginning, coming every six months to give blood samples and answer questionnaires, building a scientific goldmine in the process.

“It’s the greatest living experiment,” said Wagner, an AIDS researcher at Pitt and one of the original study participants. “As one of my mentors, who is no longer with us, once told me, ‘You start in ignorance and you grow in knowledge, and that’s the basis of science.’”

Overall, 1,811 people have participated in the Pitt Men’s Study over the last 40 years, with 438 still-active participants — 201 of those who joined in 1985 or before. Of those who have ever participated in the study, 539 have died from AIDS or other causes.

In 1978, Rinaldo came to Pittsburgh, fresh from completing postdoctoral studies at Massachusetts General Hospital in Boston. His focus was an “opportunistic virus” called cytomegalovirus that attacked people with weakened immune systems, such as organ transplant recipients. Pittsburgh was growing as a transplant center by 1981, boosted by the arrival of transplant pioneer Thomas Starzl.

That same year, Rinaldo remembers seeing a “perplexing case” of a critically ill gay man in his mid-20s with CMV and Pneumocystis pneumonia, another opportunistic virus. Unlike most of the patients that Rinaldo saw with CMV, he had no previous health problems and had not received an organ transplant. Though the disease didn’t have a name yet, the man is now recognized as Pittsburgh’s first known AIDS patient, and later died of the disease.

Shortly afterward, Rinaldo met David Lyter, a Pitt medical student who had recently come out as gay. Lyter had seen the new disease affecting the gay community and approached Rinaldo about putting together a study to investigate it. With no official funding, and with Lyter doing most of the recruiting, they put together a pilot study of about 70 gay men.

At the same time, the country was starting to recognize the virus as well. In June of 1981, the U.S. Centers for Disease Control reported on a cluster of five cases in Los Angeles — all gay men with no known contact with each other, sick with Pneumocystis pneumonia and CMV infections. In September 1982, the CDC used the term AIDS, or acquired immune deficiency syndrome, for the first time. A few months later, the National Institutes of Health put out a request for research proposals for a large study of the new disease.

The study was looking to include one research site in a city that didn’t have as high of an incidence of AIDS as major population centers such as L.A. or New York City. “They thought maybe there was a different cause,” said Rinaldo. “That was one of the hypotheses at the time.”

Rinaldo was decades younger than most of the academic heavyweights vying for funding. But with the support of leaders at the university, he applied.

In the summer of 1983, he received a grant for $4.2 million — which equates to more than $13 million in 2024 — over four years. The study, called the Multicenter AIDS Cohort Study, also included sites in San Francisco, Los Angeles, Baltimore and Chicago, and all except San Francisco are still involved today.

“We were to define the natural history of what was just then being called AIDS,” said Rinaldo. “We did not know the virus that was the cause of this. Part of our intent was to help discover what was causing this mysterious disease.”

But first, Rinaldo needed to find more than 1,000 gay men to come to Pittsburgh to participate in the study — at a time of great fear of the virus and stigma toward homosexuality.

Building the study

“I’m a straight male scientist, never having dealt with the LGBTQ community,” he said. “This is Pittsburgh; it wasn’t San Francisco. That community was not as prominent and accepted as it was in some of the larger cities at the time.”

With Lyter’s help, he enlisted the Tavern Guild — a group of gay bar and bathhouse owners — to spread the word. They recruited at gay bars, putting up posters and handing out napkins with the study’s name and address. Sometimes they took blood specimens right in the bars, using an office or coat check room. Many bars at the time had switched to using plastic utensils, unsure how the virus could spread.

The study also hired Tony Silvestre, a prominent gay leader from Philadelphia, to lead recruiting. An instrumental part of the history of the Pitt Men’s Study, Silvestre died in 2022.

The recruitment was effective, in part because some viewed it as their chance to do something positive about a terrible situation.

Toth heard about the study from a former boss. “HIV was affecting the community — nobody knew what it was, but it was quite scary back then,” he said. “We were younger back then, and we saw some older people just getting very sick. We thought, ‘Oh, we have to do something. It may affect us eventually.’ And it did.”

Because of the fear at the time, the study took immense precautions on secrecy. The clinic was in the Oakland neighborhood of Pittsburgh, not in a university building. Participants were identified only by an ID number; information about their names was kept in a different office in a different building.

Even outside of the building, employees of the study practiced strict confidentiality.

“If you were walking down the street and saw someone and you knew they were part of the study, you just walked right past them,” said Bill Buchanan, who worked for the study from 1988 until he retired in 2022. “Unless you talked to me first, it would be like I never saw you in my life. You have to play that game.”

Even the door to the clinic didn’t fully identify what was going on. “There were no signs on the door that said Pitt Men’s Study. It just said PMS Clinic,” said Buchanan. “Once in a blue moon, you’d get a woman that came in. When she found out that wasn’t what PMS meant, she’d get a little upset.”

At first, visits to the clinic would involve taking all sorts of specimens — blood, saliva, feces, semen — and questionnaires about sexual practices.

“Back then, we took everything,” said Rinaldo. “We didn’t know what we were looking for.”

Evolving testing

In 1985, the FDA approved a test to determine whether antibodies for the virus that caused AIDS were present in a blood test.

All these men who had submitted blood samples could now find out — if they chose to — whether or not they had the virus now known as HIV.

The researchers carefully developed a protocol for how they would let the participants know: They would tell them in person, whether they were positive or negative.

Wagner remembers going in for his session. Though he had no symptoms, he was told that his blood did have the antibodies. Sometime in between his first and second visit to the study, he contracted HIV.

“It was devastating,” he said. “Back then, there were literally no medications. All you were hearing was that it was a death sentence — that in some course of time that you didn’t know yet, you would die.”

In Pittsburgh, about 22% of the participants had antibodies indicating HIV. In some of the other sites in the study, that figure was closer to 50%.

Testing for HIV and AIDS improved further with viral load testing, which not only showed antibodies but also the presence of the virus itself.

One of the Pitt Men’s Study’s most important findings was research on viral loads in the mid-1990s, showing that people who had higher levels of the virus in their blood were much more likely to develop AIDS than people who had lower levels.

“Common sense would dictate it, but we were the first to actually prove it,” said Rinaldo. “To this day, it’s one of the most cited papers in the field.”

Forging community

With so many gay men — both with AIDS and without — regularly visiting the Pitt Men’s Study office, it started to become a de facto clearinghouse of information. Pittsburgh’s gay infrastructure wasn’t as developed as in cities with larger populations, such as San Francisco, and people weren’t sure where else to turn.

“Ultimately, people would turn to the study for all kinds of help — medical help, legal help, I’ve been evicted from my apartment,” said Buchanan. “We were a study, we didn’t have those kinds of resources, and that was the impetus behind creating the Pittsburgh AIDS Task Force.”

The study frequently referred those with AIDS to Jerry Rabinowitz, who was killed in the Squirrel Hill synagogue shooting in 2018. Rabinowitz was one of the first doctors in Pittsburgh willing to treat AIDS patients.

Contributing to the study’s legacy are the larger AIDS services that developed from it. Education programs that stemmed from the study likely prevented many more AIDS cases, said Buchanan.

The study also created a community advisory board that continues to this day, and for years the study led the way locally in commemorating World AIDS Day in Pittsburgh.

Growing understanding — and options

As the AIDS epidemic continued, understanding of the virus grew, as did treatments. In 1987, the FDA approved the first AIDS drug, called AZT. The drug prolonged the lives of some AIDS patients but had serious side effects for some, such as nausea, liver problems and headaches.

For Wagner, the side effects of AZT were unbearable. In what he believed was a choice between quality of life and quantity of life, he stopped taking it.

By 1993, HIV was the leading cause of death among Americans aged 25 to 44. But new and better drugs were on the way. In the mid-1990s, the FDA approved combination therapies that were more effective, but required taking many pills per day. By the late 1990s, those medications were further improved and consolidated into fewer pills.

With medication, Wagner’s viral load is now so low that it is considered undetectable. “I’ve outlived so many of my relatives. If you would have told me at the beginning of this journey that I would still be here and they would be gone, I never would have believed this to be possible. The study gave back to me so much understanding of my own body, peace of mind of knowing what’s going on.”

In some ways, the study has transformed into research on aging with HIV and AIDS, and the effect that the virus has on the body.

With such a large bank of data — and 40 years of specimens in freezers — there are unlimited opportunities for research. Rinaldo is involved in one study that has taken modern understanding of microbiomes and applied it to decades-old stool samples of HIV-positive men, showing differences in the bacteria of those who developed AIDS. Other studies are looking at how HIV affects men who become infected today versus in the early 1980s.

“Forty years later, the specimens that the men gave us are extremely relevant,” said Rinaldo. “I tell my students and postdocs, every time you go into the freezer and take out these specimens, just remember how we got these. Even with all the fancy technology we use now, there’s no way at all we could do all this without these men.”

And to those involved, the study has meant more than just science. For 40 years, they have come to a nondescript building, sharing not just their blood but also friendship, sorrow and camaraderie.

“It’s one of the most dedicated groups of people that I’ve ever seen. Some of the best people in the world walk through that door,” said Buchanan. “I came to love them as friends. Even though I’m retired, there’s a number of them who said, ‘I need your home number, I need to stay in touch.’ Some of them showed up at my mother’s funeral last month.”

Part of the close kinship, of course, comes from tragedy. Toth, one of the original participants and a current data manager for the study, still has a photo from his gay softball team in the early 1980s. “The majority of the team is gone,” he said, “and most of them, sadly, is because of AIDS.”

Later this year, the study will hold events to honor the participants and mark 40 years.

“I don’t call this a celebration: I call this a commemoration,” said Rinaldo. “We won’t be celebrating until we don’t have to do this anymore — until we cure this infection or have a vaccine. We want to keep this going until the study is no longer needed.”

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Industry Payments to US Physicians by Specialty and Product Type

1 Ain Shams University, Faculty of Medicine, Cairo, Egypt
2 Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
3 Baptist Health, Louisville, Kentucky
4 Department of Medicine, Harvard Medical School, Boston, Massachusetts
5 Department of Medicine, Penn State Milton S. Hershey Medical Center, Hershey, Pennsylvania
Research Letter Trends in Industry Payments to Physicians in the United States From 2014 to 2018 Deborah C. Marshall, MD, MAS; Elizabeth S. Tarras, MD; Kenneth Rosenzweig, MD; Deborah Korenstein, MD; Susan Chimonas, PhD JAMA
Research Letter Comparison of Industry Payments to Physicians and Advanced Practice Clinicians Audrey D. Zhang, MD; Timothy S. Anderson, MD, MAS JAMA
Brief Report Trends in Industry Payments to US Oncologists Since the Open Payments Program, 2014 to 2019 Elizabeth S. Tarras, MD; Deborah C. Marshall, MD; Kenneth Rosenzweig, MD; Deborah Korenstein, MD; Susan Chimonas, PhD JAMA Oncology

Despite evidence that financial conflicts of interest may influence physician prescribing and may damage patients’ trust in medical professionals, 1 - 3 such relationships remain pervasive. 4 The Physician Payments Sunshine Act led to the creation of the Open Payments database in August 2013, a repository of industry payments to health care professionals. 5 We examined the distribution of payments within and across specialties and the medical products associated with the largest total payments.

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Small protein plays big role in chronic HIV infection

UC Riverside-led study on innate immune system may lead to new treatments for patients with neuroHIV

NeuroHIV refers to the effects of HIV infection on the brain or central nervous system and, to some extent, the spinal cord and peripheral nervous system. A collection of diseases, including neuropathy and dementia, neuroHIV can cause problems with memory and thinking and compromise our ability to live a normal life.

Using a mouse model of neuroHIV, a research team led by biomedical scientists at the University of California, Riverside, studied the effects of interferon-β (IFNβ), a small protein involved in cell signaling and integral to the body’s natural defense mechanism against viral infections. The researchers found that higher or lower than normal levels of IFNβ affect the brain in a sex-dependent fashion: some changes only occur in females, others only in males.

Marcus Kaul , a professor of biomedical sciences in the School of Medicine who led the study , explained that when infection-induced IFNβ levels become high, the brains of females and males are protected. If IFNβ production in response to infection is absent or too low, HIV can compromise brain function right away in both females and males, he said.

“However, IFNβ also controls other cell and brain functions,” Kaul said. “If IFNβ is absent, females display reduced nerve cell connections called dendrites in the cerebral cortex, while males show diminished ‘presynaptic terminals,’ another type of nerve cell connection, in the hippocampus.”

Dendrites are highly branched structures that increase the receptive surface of neurons.

“Paradoxically, in the hippocampus of females and males, the damage to presynaptic terminals by HIV is diminished when IFNβ is absent but the reduction of injury is more pronounced in males,” Kaul said.

According to the researchers, the work adds to scientists’ understanding of how innate immunity affects the brain during chronic HIV infection.

“Until now, it was not known that normal levels of IFNβ are required for normal memory function and that the absence of IFNβ changes the production of nerve cell components in a sex-dependent fashion,” Kaul said.

The findings, published in the journal Brain, Behavior, and Immunity , are noteworthy because the mouse model of neuroHIV that Kaul and his team used shares key features of brain injury and compromised function, such as impaired memory, with people living with HIV infection, or PLWH.

Almost all cells in the body can produce IFNβ. Kaul explained IFNβ regulates the production of inflammatory factors in neuroHIV and has two major effects: (a) it changes the state of a virally infected cell from ‘normal’ to ‘anti-viral,’ making the cells uncomfortable environments for the virus, even completely shutting down virus production, and (b) IFNβ is released from infected cells as well as specialized cells that, by sensing infected cells, can alert neighboring cells and the entire body of a viral infection.

“This is how neighboring cells adapt to become more resistant to viral infection,” Kaul said. “Some of them will also release additional anti-viral factors and a mixture of other factors that can promote or limit inflammation, such as cytokines called CCL3, CCL4 and CCL5.”

The research was performed in Kaul’s laboratory. The team generated a new variant of an established transgenic mouse model of neuroHIV by crossbreeding this model with mice that lack IFNβ. The team then analyzed memory function and brain tissue of the transgenic mice for injury that usually occurs in neuroHIV.

“HIV and some other viruses have developed mechanisms to reduce or even prevent the production of more than normal levels of IFNβ,” said Hina Singh , an assistant project scientist in Kaul’s lab and the first author of the research paper. “We know little about the role of IFNβ in the human brain beyond that it can reduce inflammation. This is a major reason why IFNβ is used to treat multiple sclerosis, an autoimmune disease that affects more than 2.8 million people worldwide . Currently, we have almost no information about how much IFNβ is present in the brains of PLWH and what it does there.”

Singh said the study underscores the importance of having normal levels of IFNβ during no viral infection and having sufficiently high levels of IFNβ in case of neuroHIV or other viral infections.

“The body’s many anti-viral responses observed in HIV infection are not specific to HIV but also occur with other viral infections,” she said. “But in contrast to most other viral infections, the body cannot get rid of HIV, which diminishes the effectiveness of the natural IFNβ response.”

Next, the team plans to work on confirming the findings of the neuroHIV model in PLWH.

“For this, we will need to investigate tissues of PLWH who consented to donate them for research after death,” Kaul said. “Ultimately, we hope to develop IFNβ into a therapy for patients with neuroHIV.”

The study was funded by grants to Kaul from the National Institutes of Health. Kaul and Singh were joined in the research by scientists at UCR and The Scripps Research Institute in La Jolla, California.

The title of the research paper is “Interferon-β deficiency alters brain response to chronic HIV-1 envelope protein exposure in a transgenic model of NeuroHIV.” The paper is scheduled to appear in print in May 2024.

Second related study

Another study from the Kaul lab is scheduled to appear in print in the May 2024 issue of Brain, Behavior, and Immunity.

“This study adds another important aspect to our understanding of how innate immunity and an inflammatory mechanism affects the brain during chronic HIV infection,” Kaul said.

The study shows that intact HIV and its viral envelope protein gp120 each cause macrophages, a type of white blood cell, to release cysteinyl leukotrienes, or CysLTs, which are pro-inflammatory mediators. The study shows for the first time that the CysLTs are critical components of macrophage neurotoxicity induced by HIV-1 , the most common of the two major types of HIV.

“The potential translational value of our work is the demonstration that an asthma drug approved by the Food and Drug Administration, that inhibits a major receptor for CysLTs also prevents HIV-induced neurotoxicity,” Kaul said.

The research paper is titled “A critical role for Macrophage-derived Cysteinyl-Leukotrienes in HIV-1 induced neuronal injury.” Nina Yuan, a former associate specialist researcher in the Kaul lab, is the paper’s lead author. This study was supported by funds from the National Institute of Health.

Header photo shows Hina Singh (left) and Marcus Kaul. (UCR/Kaul lab)

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

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Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

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EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

EXAMPLE 1. Descriptive research question (quantitative research)
- Presents research variables to be assessed (distinct phenotypes and subphenotypes)
“BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
EXAMPLE 2. Relationship research question (quantitative research)
- Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
“Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
EXAMPLE 3. Comparative research question (quantitative research)
- Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
“BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
EXAMPLE 4. Exploratory research question (qualitative research)
- Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
“Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
EXAMPLE 5. Relationship research question (quantitative research)
- Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
“Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

EXAMPLE 1. Working hypothesis (quantitative research)
- A hypothesis that is initially accepted for further research to produce a feasible theory
“As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
“In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
EXAMPLE 2. Exploratory hypothesis (qualitative research)
- Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
“We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
“Conclusion
Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
“We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
EXAMPLE 4. Statistical hypothesis (quantitative research)
- An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
“Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
“Statistical Analysis
( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

EXAMPLE 1. Background, hypotheses, and aims are provided
“Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
“ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
“This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
EXAMPLE 2. Background, hypotheses, and aims are provided
“We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
“ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
EXAMPLE 3. Background, aim, and hypothesis are provided
“In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
“This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
“ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

Conceptualization: Barroga E, Matanguihan GJ.
Methodology: Barroga E, Matanguihan GJ.
Writing - original draft: Barroga E, Matanguihan GJ.
Writing - review & editing: Barroga E, Matanguihan GJ.

When the Earth, Moon, and Sun line up in space, we can see an eclipse. NASA studies eclipses from the ground, in our atmosphere, and in space, influencing solar, planetary, and Earth science.

A purple Moon with a bright white, wispy solar atmosphere billowing out around it. It fills the red and purple background.

Get ready for the 2024 total solar eclipse!

Against a black background, the Sun shines out around a black circle. The Sun appears as wispy white streams of light.

2024 Total Solar Eclipse

On April 8, 2024, a total solar eclipse will cross North America, passing over Mexico, the United States, and Canada.

How the 2024 Total Solar Eclipse Is Different than the 2017 Eclipse

On April 8, the Moon’s shadow will sweep across the United States, as millions will view a total solar eclipse.…

A map of North America. Sweeping from Oregon to South Carolina is a thin, gray path labeled 2017. Sweeping from Mazatlan, Mexico, through Texas, across the U.S., and entering Canada through Maine is a wider gray path labeled 2024.

About Eclipses

An eclipse is an awe-inspiring celestial event that drastically changes the appearance of the two biggest objects we see in our sky: our Sun and Moon. On Earth, people can experience solar and lunar eclipses when Earth, the Moon, and the Sun line up. Safety is the number one priority when viewing a solar eclipse. Be sure to follow these safety guidelines when viewing a solar eclipse .

Quick Facts

Parts of the U.S. will experience a total eclipse in April 2024.

Two eclipse paths intersecting to make an "X" across the globe.

After the total solar eclipse on April 8, 2024, the next total solar eclipse that can be seen from the contiguous United States will be on Aug. 23, 2044.

A bright flash of white appears at the top of a black circle, showing a solar eclipse. It appears like the diamond on top of a ring.

We can't normally see the corona – the Sun's outer atmosphere – because Sun's surface below it is so much brighter. But during a total solar eclipse, the corona emerges, offering unique opportunities to study it.

sun blocked by moon in total eclipse, with just corona visible

An eclipse season is one of only two periods during each year when the Sun, the Moon and Earth are aligned, allowing eclipses to occur. Each season lasts about 35 days and repeats just short of six months later!

Reflected on a calendar are crescents of the Sun during a solar eclipse.

Citizen Science
Eclipse Types

Eye Safety During an Eclipse

Observing our star, the Sun, can be safe and inspirational.

Except for a specific and brief period of time during a total solar eclipse, you must never look directly at the Sun without proper eye protection, such as safe solar viewing glasses (eclipse glasses). Eclipse glasses are NOT the same as regular sunglasses; regular sunglasses are not safe for viewing the Sun. During a total solar eclipse, you must wear your eclipse glasses (or use other solar filters) to view the Sun directly during the partial eclipse phase. You can only take your glasses off during the short time when the Moon completely obscures the Sun – known as the period of totality. If you don’t have eclipse glasses, you can use an indirect viewing method , such as a pinhole projector, which projects an image of the Sun onto a nearby surface. It is safe to look at the Moon with unprotected eyes or through a telescope during all types and during all stages of a lunar eclipse.

A family wearing eclipse glasses watches the total solar eclipse

Citizen Science Projects

Observing a solar eclipse is one of many ways to get in on the fun of doing science.

You can get involved with NASA science by participating in a number of NASA-funded citizen science projects. Citizen science projects are collaborations between scientists and interested members of the public. Through these collaborations, volunteers (known as citizen scientists) have helped make thousands of important scientific discoveries.

Know your eclipses!

There are four types of solar eclipses: Total, partial, hybrid, and annular.

The type of eclipse that people get to see depends on how the Moon aligns with Earth and the Sun, and how far away the Moon is from Earth. There are three types of lunar eclipses: total, partial, and penumbral. At least two partial lunar eclipses happen every year, but total lunar eclipses are rare. Unlike a solar eclipse, it is always safe to look at a lunar eclipse with the naked eye.

From left to right, this image shows a total solar eclipse, annular solar eclipse, and partial solar eclipse. A hybrid eclipse can appear as either a total or annular eclipse (the left and middle images) depending on the viewer's location.

Science of Eclipses

Eclipses aren’t just beautiful – they’re great for science.

In addition to inspiring artists and musicians, eclipses have driven numerous scientific discoveries. For over a century, solar eclipses helped scientists decipher the Sun’s structure and explosive events, find evidence for the theory of general relativity, discover a new element, and much more. NASA scientists still study eclipses to make new discoveries about the Sun, Earth, and our space environment. Total solar eclipses are particularly important because they allow scientists to see a part of the Sun’s atmosphere – known as the corona – which is too faint to see except when the bright light of the Sun’s surface is blocked.

History of the Eclipse

Eclipses have fascinated humans from the beginning.

Throughout time, humans have had different interpretations of and reactions to these striking celestial events. In fact, historical records of eclipses from scribes in Anyang, China, helped astronomers at NASA’s Jet Propulsion Laboratory to determine how Earth’s rotation has changed over time. Determining exactly when the eclipse was seen and where the Moon's shadow fell on Earth helped the scientists calculate the rate of Earth's spin. The eclipses they used for this research were in 1226 B.C.E., 1198 B.C.E., 1172 B.C.E., 1163 B.C.E., and 1161 B.C.E.

This composite image shows the progression of a partial solar eclipse over Ross Lake, in Northern Cascades National Park, Washington, on Monday, Aug. 21, 2017.

Eclipse Stories

Sun Series: Minisode! Countdown to Total Solar Eclipse 2024

Astronauts Protect Their Eyes with Eclipse Glasses

Eclipse Across North America 2024

Harnessing the 2024 Eclipse for Ionospheric Discovery with HamSCI

The Sun, seen in red with bright orange area, partially covered by black circle coming from the top left – the Moon.

Scientists Pursue the Total Solar Eclipse with NASA Jet Planes

NASA Partnerships Bring 2024 Total Solar Eclipse to Everyone

Artist's concept shows the red-dwarf star, TRAPPIST-1, at the upper left, with two large dots on the face of the disk representing transiting planets; five more planets are shown at varying positions descending toward the lower right as they orbit the star. Artist's concept shows the TRAPPIST-1 planets as they might be seen from Earth using an extremely powerful – and fictional – telescope. Credit: NASA/JPL-Caltech

That Starry Night Sky? It’s Full of Eclipses

A model showing the evolution of the solar corona prediction for April 8, 2024. It shows the solar corona as white light with defined structure encircling a black disk. The structured light ripples and changes throughout the animation, which represents coronal predictions.

Scientists Use NASA Data to Predict Solar Corona Before Eclipse

Eclipses Gallery

Discover More Topics From NASA

Tendrils of hot plasma stream from the Sun.

2024 Total Eclipse

Skywatching

A man looks through a telescope at twilight.

IMAGES

Types of Research
Types of Study
Types of Research by Method
Five Basic Types of Research Studies
Different Types of Research
Types of Research Methodology: Uses, Types & Benefits

VIDEO

TYPES OF RESEARCH REPORTS/BS/A COMPREHENSIVE ANALYSIS/ EASY DESCRIPTION/PROF. SHAMSA KANWAL
Research, Educational research
RESEARCH CRITIQUE: Quantitative Study
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Metho1: What Is Research?
Research Types

COMMENTS

What is Research
Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, "research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.".
What is Research? Definition, Types, Methods and Process
Research is defined as a meticulous and systematic inquiry process designed to explore and unravel specific subjects or issues with precision. This methodical approach encompasses the thorough collection, rigorous analysis, and insightful interpretation of information, aiming to delve deep into the nuances of a chosen field of study.
Types of Research
Classification of Types of Research. There are various types of research that are classified according to their objective, depth of study, analysed data, time required to study the phenomenon and other factors. It's important to note that a research project will not be limited to one type of research, but will likely use several.
Types of Research Designs Compared
Types of research can be categorized based on the research aims, the type of data, and the subjects, timescale, and location of the research. ... But the type of research is only the first step: next, you have to make more concrete decisions about your research methods and the details of the study. Read more about creating a research design ...
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A research design is a strategy for answering your research question using empirical data. Creating a research design means making decisions about: Your overall research objectives and approach. Whether you'll rely on primary research or secondary research. Your sampling methods or criteria for selecting subjects. Your data collection methods.
Study designs: Part 1
Research study design is a framework, or the set of methods and procedures used to collect and analyze data on variables specified in a particular research problem. Research study designs are of many types, each with its advantages and limitations. The type of study design used to answer a particular research question is determined by the ...
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There are various types of scientific studies such as experiments and comparative analyses, observational studies, surveys, or interviews. The choice of study type will mainly depend on the research question being asked. When making decisions, patients and doctors need reliable answers to a number of questions.
Research Methods
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:
Research
Research, in its simplest terms, is searching for knowledge and searching for truth. In a formal sense, it is a systematic study of a problem attacked by a deliberately chosen strategy, which starts with choosing an approach to preparing a blueprint (design) and acting upon it in terms of designing research hypotheses, choosing methods and ...
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Research Methods
To analyse data collected in a statistically valid manner (e.g. from experiments, surveys, and observations). Meta-analysis. Quantitative. To statistically analyse the results of a large collection of studies. Can only be applied to studies that collected data in a statistically valid manner. Thematic analysis.
Research
Research design: Research design refers to the overall plan and structure of the study, including the type of study (e.g., observational, experimental), the sampling strategy, and the data collection and analysis methods. Sampling strategy: Sampling strategy refers to the method used to select a representative sample of participants or units ...
Types of studies and research design
Types of study design. Medical research is classified into primary and secondary research. Clinical/experimental studies are performed in primary research, whereas secondary research consolidates available studies as reviews, systematic reviews and meta-analyses. Three main areas in primary research are basic medical research, clinical research ...
Research Study Types
These are studies done in laboratories on cells, tissue, or animals. Strengths: Laboratories provide strictly controlled conditions and are often the genesis of scientific ideas that go on to have a broad impact on human health. They can help understand the mechanisms of disease. Weaknesses: Laboratory and animal studies are only a starting point.
What Is Research? Types and Methods
Research is the process of examining a hypothesis to make discoveries. Practically every career involves research in one form or another. Accountants research their client's history and financial documents to understand their financial situation, and data scientists perform research to inform data-driven decisions. In this guide, we'll go over:
Research Methods
Research methods are used in various fields to investigate, analyze, and answer research questions. Here are some examples of how research methods are applied in different fields: Psychology: Research methods are widely used in psychology to study human behavior, emotions, and mental processes. For example, researchers may use experiments ...
19 Types of Research (With Definitions and Examples)
Example: A researcher examines if and how employee satisfaction changes in the same employees after one year, three years and five years with the same company. 16. Mixed research. Mixed research includes both qualitative and quantitative data. The results are often presented as a mix of graphs, words and images.
6 Basic Types of Research Studies (Plus Pros and Cons)
Here are six common types of research studies, along with examples that help explain the advantages and disadvantages of each: 1. Meta-analysis. A meta-analysis study helps researchers compile the quantitative data available from previous studies. It's an observational study in which the researchers don't manipulate variables.
Research Methodology
Research Methodology Types. Types of Research Methodology are as follows: Quantitative Research Methodology. 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.
1.9: Types of Research Studies and How To Interpret Them
A meta-analysis is a type of systematic review that goes one step further, combining the data from multiple studies and using statistics to summarize it, as if creating a mega-study from many smaller studies.4. However, even systematic reviews and meta-analyses aren't the final word on scientific questions.
What is Research Methodology? Definition, Types, and Examples
Definition, Types, and Examples. Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of ...
Comment: Schools are using research to try to improve children's
In fact, research by a team at Sheffield Hallam University have demonstrated that on average, these kinds of education initiatives have very little to no impact. My work has shown that when the findings of different research studies are brought together and synthesised, teachers may end up implementing these findings in contradictory ways.
'It's the greatest living experiment': Pitt Men's Study marks 40 years
The study was looking to include one research site in a city that didn't have as high of an incidence of AIDS as major population centers such as L.A. or New York City. "They thought maybe ...
Industry Payments to US Physicians by Specialty and Product Type
Results. From 2013 to 2022, 85 087 744 payments with a total value of $12.13 billion were made by industry to 826 313 of 1 445 944 eligible physicians (% receiving payments, 57.1%; median payment, $48 per physician [IQR, $0-$1015]), and 79 774 940 (93.8%) of these payments were associated with 1 or more marketed medical products.
Small protein plays big role in chronic HIV infection
Using a mouse model of neuroHIV, a research team led by biomedical scientists at the University of California, Riverside, studied the effects of interferon-β (IFNβ), a small protein involved in cell signaling and integral to the body's natural defense mechanism against viral infections. The researchers found that higher or lower than normal ...
A Practical Guide to Writing Quantitative and Qualitative Research
INTRODUCTION. Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses.1,2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results.3,4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the ...
Chasing the eclipse with sounding rockets and high-altitude planes
Scientific teams will use sounding rockets and high-altitude research planes to study the total solar eclipse to better understand the sun and its impact on Earth.
Research TASK Grade 12 2024
Relevant research area identified on a map with an appropriate legend, appropriate labels and use of scale. Study area is well motivated and forms part of the local community and a related geographical issue. Learner has fully described the study area in a paragraph and has provided the appropriate background information relevant to the Hypothesis.
Eclipses
About Eclipses. An eclipse is an awe-inspiring celestial event that drastically changes the appearance of the two biggest objects we see in our sky: our Sun and Moon. On Earth, people can experience solar and lunar eclipses when Earth, the Moon, and the Sun line up. Safety is the number one priority when viewing a solar eclipse.

What is Research: Definition, Methods, Types & Examples

What is Research?

Qualitative methods

What is the purpose of research?

Types of research methods and Examples

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Types of Research – Explained with Examples

Types of Research

Classification of Types of Research

According to its Purpose

Applied Research

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Descriptive Research

Explanatory Research

Correlational Research

According to the Type of Data Used

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According to the Degree of Manipulation of Variables

Non-Experimental Research

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According to the Type of Inference

Inductive Research

Hypothetical-Deductive Investigation

According to the Time in Which it is Carried Out

Cross-Sectional Study (also referred to as Synchronous Research)

According to The Sources of Information

Secondary research

According to How the Data is Obtained

From Laboratory

Mixed-Method: Documentary, Field and/or Laboratory

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