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• Types of Research Designs Compared | Guide & Examples

Types of Research Designs Compared | Guide & Examples

Published on June 20, 2019 by Shona McCombes . Revised on June 22, 2023.

When you start planning a research project, developing research questions and creating a  research design , you will have to make various decisions about the type of research you want to do.

There are many ways to categorize different types of research. The words you use to describe your research depend on your discipline and field. In general, though, the form your research design takes will be shaped by:

• The type of knowledge you aim to produce
• The type of data you will collect and analyze
• The sampling methods , timescale and location of the research

This article takes a look at some common distinctions made between different types of research and outlines the key differences between them.

Table of contents

Types of research aims, types of research data, types of sampling, timescale, and location, other interesting articles.

The first thing to consider is what kind of knowledge your research aims to contribute.

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The next thing to consider is what type of data you will collect. Each kind of data is associated with a range of specific research methods and procedures.

Finally, you have to consider three closely related questions: how will you select the subjects or participants of the research? When and how often will you collect data from your subjects? And where will the research take place?

Keep in mind that the methods that you choose bring with them different risk factors and types of research bias . Biases aren’t completely avoidable, but can heavily impact the validity and reliability of your findings if left unchecked.

Choosing between all these different research types is part of the process of creating your research design , which determines exactly how your research will be conducted. 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

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.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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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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Research Design 101

Everything You Need To Get Started (With Examples)

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

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 .

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.

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?

This post is very clear, comprehensive and has been very helpful to me. It has cleared the confusion I had in regard to research design and methodology.

This post is helpful, easy to understand, and deconstructs what a research design is. Thanks

how to cite this page

Thank you very much for the post. It is wonderful and has cleared many worries in my mind regarding research designs. I really appreciate .

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Types of Research – Tips and Examples

Published by Carmen Troy at August 16th, 2021 , Revised On October 26, 2023

“Research is an investigation conducted to seek knowledge and find solutions to scientific and social problems.”

It includes the collection of information from various sources. New research can contribute to existing knowledge.

The types of research can be categorised from the following perspectives;

• Application of the study
• Aim of the research
• Mode of inquiry
• Research approach

Types of Research According to the Application Perspective

The different types of research, according to the application perspective, include the following.

Basic Research

Primary research is conducted to increase knowledge. It is also known as theoretical research, pure research, and fundamental research. It provides in-depth knowledge about the scientific and logical explanations and their conclusions.

The results of the primary research are used as the base of applied research. It is based on  experiments  and observation. The results of basic research are published in peer-reviewed journals.

• What is global warming?
• How did the Universe begin?
• What do humans get stress?

Applied Research

Applied research is conducted to find solutions for practical problems. It uses the outcomes of basic research as its base. The results of applied research are applied immediately. It includes case studies, experimental research.

Example: Finding the solution to control air pollution.

Descriptive Research

Descriptive research  is carried out to describe current issues, programs, and provides information about the issue through  surveys  and various fact-finding methods.

It includes co-relational and comparative methods of research. It follows the Ex post facto research, which predicts the possible reasons behind the situation that has already occurred.

A researcher cannot control its variables and can report only about the current situation and its occurring.

Example: The widespread contaminated diseases in a specific area of the town. Investigation reveals that there is no trash removal system in that area. A researcher can hypothesise the reason that the improper trash removal system leads to the widespread of contaminated disease.

Analytical Research

In analytical research, a researcher can use the existing data, facts, and knowledge and critically analyses and evaluates the sources and material. It attempts to describe why a specific situation exists.

Example: Impact of video games on teenagers.

Explanatory

Explanatory research is conducted to know why and how two or more variables are interrelated. Researchers usually conduct experiments to know the effect of specific changes among two or more variables.

Example: A study to identify the impact of a nutritious diet on pregnant women.

Exploratory

Exploratory research is conducted to understand the nature of the problem. It does not focus on finding evidence or a conclusion of the problem. It studies the problem to explore the research in-depth and covers such topics which have not been studied before.

Example:  An investigation about the growing crimes against women in India.

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Types of Research According to the Mode of Inquiry

Qualitative research.

Qualitative research  is based on quality, and it looks in-depth at non-numerical data. It enables us to understand the comprehensive details of the problem. The researcher prepares open-ended questions to gather as much information as possible.

• Stress level among men and women.
• The obesity rate among teenagers.

Quantitative Research

Quantitative research is associated with the aspects of measurement, quantity, and extent. It follows the statistical, mathematical, and computational techniques in the form of numerical data such as percentages and statistics. The research is conducted on a large group of population.

• Find out the weight of students of the fifth standard
• Studying in government schools.

Types of Research According to the Research Approach

Longitudinal research.

Researchers collect the information at multiple points in time. Usually, a specific group of participants is selected and examined numerous times at various periods.

Example: If a researcher experiments on a group of women to find out the impact of a low carb diet within six months. The women’s weight and a health check-up will be done multiple times to get the evidence of the study.

Cross-Sectional Research

Cross-sectional research  gathers and compares the information from various groups of the population at the same point. It may not provide the exact reason and relationship between the subjects but gives a broad picture to study multiple groups at the same time.

Example: If a researcher wants to know the number of students studying in a school, he will get to know about the age groups, height, weight, and gender of the students at the same time.

Conceptual Research

It is associated with the concept and theory that describes the hypothesis being studied. It is based on  the inductive  approach of reasoning. It does not follow practical experiments. Philosophers, thinkers, logicians, and theorists use such research to discover new concepts and understand the existing knowledge.

Example: discoveries of Sir Isaac Newton and Einstein.

Empirical Research

It is also known as experimental research, which depends on observation and experience. It is based on the  deductive  approach of reasoning . A researcher focuses on gathering information about the facts, their sources and investigating the existing knowledge. Example: Is intermittent fasting the healthy weight loss option for women?

The researcher can come up with the result that a certain number of women lost their weight, and it improved their health. On the other hand, a certain number of women suffering from low blood pressure and diabetes didn’t lose weight, and they faced negative impacts of intermittent fasting on their health.

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Mixed Methods of Research

When you combine quantitative and qualitative methods of research, the resulting approach becomes mixed methods of research.

Over the last few decades, much of the research in the world of academia has been conducted using mixed methods. Due to its greater legitimacy, this particular technique has gained for several reasons, including the feeling that combining the two types of research can provide holistic and more dependable results.

Here is what mixed methods of research involve:

• Interpreting and investigating the information gathered through quantitative and qualitative techniques.
• There could be more than one stage of research. Depending on the topic of research, occasionally, it would be more appropriate to perform qualitative research in the first stage to figure out and investigate a problem to unveil key themes; and conduct quantitative research in stage two of the process for measuring relationships between the themes.

 Tips for Choosing the Right Type of Research

Choosing the right type of research is essential for producing relevant and actionable insights. The choice depends on your objectives, available resources, and the nature of the problem. Here are some tips to help you make the right decision:

Define your Research Objectives Clearly

• Descriptive Research: To describe the characteristics of certain phenomena.
• Exploratory Research: To explore a problem that hasn’t been studied in depth.
• Explanatory (or Causal) Research: To explain patterns of cause and effect.
• Predictive Research: To forecast future outcomes based on patterns.

Understand the Research Methods

• Quantitative Research: Employs structured data collection (e.g., surveys) to generate statistical data.
• Qualitative Research: Uses unstructured or semi-structured data collection methods (e.g., interviews, observations) to understand behaviour, motivations, etc.

Consider the Time Dimension

• Cross-sectional Studies: Capture data at a single point in time.
• Longitudinal Studies: Collect data over extended periods to observe changes.

Evaluate Available Resources

• Budget: Some research methods, like experimental research, may require more funding.
• Time: Exploratory or ethnographic studies may take longer than surveys.
• Expertise: Ensure you or your team possess the skills needed for your chosen research method.

Consider the Nature of the Problem

Complex problems may require mixed-methods research (a combination of qualitative and quantitative).

Review Existing Literature

Review existing literature before settling on a type to see what methodologies were previously employed for similar questions.

Think about Data Collection

Consider the best method to gather data: surveys, interviews, experiments, observations, etc. Your choice affects the research type.

Ethical Considerations:

Ensure your chosen method abides by ethical standards, especially when human subjects are involved.

Generalisability Vs. Depth

Quantitative methods often allow for generalizability, while qualitative methods provide depth and detail.

Pilot Testing

If unsure, run a pilot study to test your chosen method’s feasibility and utility.

Stay Open to Adaptation

Sometimes, initial research can lead to unforeseen insights or complexities. Be prepared to adjust your approach if needed.

Seek Feedback

Discuss your research approach with colleagues, mentors, or experts in the field. They might offer valuable insights or identify potential pitfalls.

Stay Updated

Research methods evolve. Stay updated with the latest techniques, tools, and best practices in your field.

Frequently Asked Questions

What is research.

Research is a systematic inquiry aimed at discovering, interpreting, and revising knowledge about specific phenomena. It involves formulating hypotheses, collecting data, and analysing results to generate new insights or validate existing theories. Conducted in various fields, research can be empirical, theoretical, or experimental and is fundamental for informed decision-making.

What are the different Types of Research?

Different types of research include:

• Descriptive: Describe and analyze phenomena.
• Experimental: Manipulate variables to establish causation.
• Correlational: Examine relationships between variables.
• Qualitative: Gather insights and understanding.
• Quantitative: Use numerical data for analysis.
• Case study, survey, ethnography, and more.

What is research design?

Research design is a structured blueprint for conducting a study, outlining how data will be collected, analysed, and interpreted. It determines the overall strategy and approach to obtain valid, accurate, and reliable results. Research design encompasses choices about type (e.g., experimental, observational), method (qualitative, quantitative), and data collection procedures.

What is survey?

A survey is a research method used to gather data from a predefined group by asking specific questions. Surveys can be conducted using various mediums, such as face-to-face interviews, phone calls, or online questionnaires. They are valuable for collecting descriptive, quantitative, or qualitative information and gauging public opinion or behaviours.

What is research method?

A research method is a systematic approach used by researchers to gather, analyse, and interpret data relevant to their study. It dictates how information is collected and evaluated to answer specific research questions. Methods can be qualitative, quantitative, or mixed and include techniques like surveys, experiments, case studies, and interviews.

What is exploratory research?

Exploratory research is an initial study designed to clarify and define the nature of a problem. It’s used when researchers have a limited understanding of the topic. Instead of seeking definitive answers, it aims to identify patterns, ideas, or hypotheses. Methods often include literature reviews, qualitative interviews, and observational studies.

What is the purpose of research?

The purpose of research is to discover, interpret, or revise knowledge on specific topics or phenomena. It seeks to answer questions, validate theories, or find solutions to problems. Research enhances understanding, informs decision-making, guides policies, drives innovation, and contributes to academic, scientific, and societal advancement. It’s fundamental for evidence-based practices.

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A case study is a detailed analysis of a situation concerning organizations, industries, and markets. The case study generally aims at identifying the weak areas.

Content analysis is used to identify specific words, patterns, concepts, themes, phrases, or sentences within the content in the recorded communication.

Baffled by the concept of reliability and validity? Reliability refers to the consistency of measurement. Validity refers to the accuracy of measurement.

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

• Quantitative Research
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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.
• Next: Quantitative Research >>
• Last Updated: Apr 3, 2023 3:14 PM
• URL: https://guides.lib.berkeley.edu/researchmethods

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Neag School of Education

Educational Research Basics by Del Siegle

Types of Research

How do we know something exists? There are a numbers of ways of knowing…

• -Sensory Experience
• -Agreement with others
• -Expert Opinion
• -Scientific Method (we’re using this one)

The Scientific Process (replicable)

• Identify a problem
• Clarify the problem
• Determine what data would help solve the problem
• Organize the data
• Interpret the results

General Types of Educational Research

• Descriptive — survey, historical, content analysis, qualitative (ethnographic, narrative, phenomenological, grounded theory, and case study)
• Associational — correlational, causal-comparative
• Intervention — experimental, quasi-experimental, action research (sort of)

Researchers Sometimes Have a Category Called Group Comparison

• Ex Post Facto (Causal-Comparative): GROUPS ARE ALREADY FORMED
• Experimental: RANDOM ASSIGNMENT OF INDIVIDUALS
• Quasi-Experimental: RANDOM ASSIGNMENT OF GROUPS (oversimplified, but fine for now)

General Format of a Research Publication

• Background of the Problem (ending with a problem statement) — Why is this important to study? What is the problem being investigated?
• Review of Literature — What do we already know about this problem or situation?
• Methodology (participants, instruments, procedures) — How was the study conducted? Who were the participants? What data were collected and how?
• Analysis — What are the results? What did the data indicate?
• Results — What are the implications of these results? How do they agree or disagree with previous research? What do we still need to learn? What are the limitations of this study?

Del Siegle, PhD [email protected]

Last modified 6/18/2019

• USC Libraries
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Organizing Your Social Sciences Research Paper

• Types of Research Designs
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
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• Primary Sources
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• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
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• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
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• USC Libraries Tutorials and Other Guides
• Bibliography

Introduction

Before beginning your paper, you need to decide how you plan to design the study .

The research design refers to the overall strategy and analytical approach that you have chosen in order to integrate, in a coherent and logical way, the different components of the study, thus ensuring that the research problem will be thoroughly investigated. It constitutes the blueprint for the collection, measurement, and interpretation of information and data. Note that the research problem determines the type of design you choose, not the other way around!

De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Trochim, William M.K. Research Methods Knowledge Base. 2006.

General Structure and Writing Style

The function of a research design is to ensure that the evidence obtained enables you to effectively address the research problem logically and as unambiguously as possible . In social sciences research, obtaining information relevant to the research problem generally entails specifying the type of evidence needed to test the underlying assumptions of a theory, to evaluate a program, or to accurately describe and assess meaning related to an observable phenomenon.

With this in mind, a common mistake made by researchers is that they begin their investigations before they have thought critically about what information is required to address the research problem. Without attending to these design issues beforehand, the overall research problem will not be adequately addressed and any conclusions drawn will run the risk of being weak and unconvincing. As a consequence, the overall validity of the study will be undermined.

The length and complexity of describing the research design in your paper can vary considerably, but any well-developed description will achieve the following :

• Identify the research problem clearly and justify its selection, particularly in relation to any valid alternative designs that could have been used,
• Review and synthesize previously published literature associated with the research problem,
• Clearly and explicitly specify hypotheses [i.e., research questions] central to the problem,
• Effectively describe the information and/or data which will be necessary for an adequate testing of the hypotheses and explain how such information and/or data will be obtained, and
• Describe the methods of analysis to be applied to the data in determining whether or not the hypotheses are true or false.

The research design is usually incorporated into the introduction of your paper . You can obtain an overall sense of what to do by reviewing studies that have utilized the same research design [e.g., using a case study approach]. This can help you develop an outline to follow for your own paper.

NOTE : Use the SAGE Research Methods Online and Cases and the SAGE Research Methods Videos databases to search for scholarly resources on how to apply specific research designs and methods . The Research Methods Online database contains links to more than 175,000 pages of SAGE publisher's book, journal, and reference content on quantitative, qualitative, and mixed research methodologies. Also included is a collection of case studies of social research projects that can be used to help you better understand abstract or complex methodological concepts. The Research Methods Videos database contains hours of tutorials, interviews, video case studies, and mini-documentaries covering the entire research process.

Creswell, John W. and J. David Creswell. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 5th edition. Thousand Oaks, CA: Sage, 2018; De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Leedy, Paul D. and Jeanne Ellis Ormrod. Practical Research: Planning and Design . Tenth edition. Boston, MA: Pearson, 2013; Vogt, W. Paul, Dianna C. Gardner, and Lynne M. Haeffele. When to Use What Research Design . New York: Guilford, 2012.

Action Research Design

Definition and Purpose

The essentials of action research design follow a characteristic cycle whereby initially an exploratory stance is adopted, where an understanding of a problem is developed and plans are made for some form of interventionary strategy. Then the intervention is carried out [the "action" in action research] during which time, pertinent observations are collected in various forms. The new interventional strategies are carried out, and this cyclic process repeats, continuing until a sufficient understanding of [or a valid implementation solution for] the problem is achieved. The protocol is iterative or cyclical in nature and is intended to foster deeper understanding of a given situation, starting with conceptualizing and particularizing the problem and moving through several interventions and evaluations.

What do these studies tell you ?

• This is a collaborative and adaptive research design that lends itself to use in work or community situations.
• Design focuses on pragmatic and solution-driven research outcomes rather than testing theories.
• When practitioners use action research, it has the potential to increase the amount they learn consciously from their experience; the action research cycle can be regarded as a learning cycle.
• Action research studies often have direct and obvious relevance to improving practice and advocating for change.
• There are no hidden controls or preemption of direction by the researcher.

What these studies don't tell you ?

• It is harder to do than conducting conventional research because the researcher takes on responsibilities of advocating for change as well as for researching the topic.
• Action research is much harder to write up because it is less likely that you can use a standard format to report your findings effectively [i.e., data is often in the form of stories or observation].
• Personal over-involvement of the researcher may bias research results.
• The cyclic nature of action research to achieve its twin outcomes of action [e.g. change] and research [e.g. understanding] is time-consuming and complex to conduct.
• Advocating for change usually requires buy-in from study participants.

Coghlan, David and Mary Brydon-Miller. The Sage Encyclopedia of Action Research . Thousand Oaks, CA:  Sage, 2014; Efron, Sara Efrat and Ruth Ravid. Action Research in Education: A Practical Guide . New York: Guilford, 2013; Gall, Meredith. Educational Research: An Introduction . Chapter 18, Action Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Kemmis, Stephen and Robin McTaggart. “Participatory Action Research.” In Handbook of Qualitative Research . Norman Denzin and Yvonna S. Lincoln, eds. 2nd ed. (Thousand Oaks, CA: SAGE, 2000), pp. 567-605; McNiff, Jean. Writing and Doing Action Research . London: Sage, 2014; Reason, Peter and Hilary Bradbury. Handbook of Action Research: Participative Inquiry and Practice . Thousand Oaks, CA: SAGE, 2001.

Case Study Design

A case study is an in-depth study of a particular research problem rather than a sweeping statistical survey or comprehensive comparative inquiry. It is often used to narrow down a very broad field of research into one or a few easily researchable examples. The case study research design is also useful for testing whether a specific theory and model actually applies to phenomena in the real world. It is a useful design when not much is known about an issue or phenomenon.

• Approach excels at bringing us to an understanding of a complex issue through detailed contextual analysis of a limited number of events or conditions and their relationships.
• A researcher using a case study design can apply a variety of methodologies and rely on a variety of sources to investigate a research problem.
• Design can extend experience or add strength to what is already known through previous research.
• Social scientists, in particular, make wide use of this research design to examine contemporary real-life situations and provide the basis for the application of concepts and theories and the extension of methodologies.
• The design can provide detailed descriptions of specific and rare cases.
• A single or small number of cases offers little basis for establishing reliability or to generalize the findings to a wider population of people, places, or things.
• Intense exposure to the study of a case may bias a researcher's interpretation of the findings.
• Design does not facilitate assessment of cause and effect relationships.
• Vital information may be missing, making the case hard to interpret.
• The case may not be representative or typical of the larger problem being investigated.
• If the criteria for selecting a case is because it represents a very unusual or unique phenomenon or problem for study, then your interpretation of the findings can only apply to that particular case.

Case Studies. Writing@CSU. Colorado State University; Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 4, Flexible Methods: Case Study Design. 2nd ed. New York: Columbia University Press, 1999; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Greenhalgh, Trisha, editor. Case Study Evaluation: Past, Present and Future Challenges . Bingley, UK: Emerald Group Publishing, 2015; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Stake, Robert E. The Art of Case Study Research . Thousand Oaks, CA: SAGE, 1995; Yin, Robert K. Case Study Research: Design and Theory . Applied Social Research Methods Series, no. 5. 3rd ed. Thousand Oaks, CA: SAGE, 2003.

Causal Design

Causality studies may be thought of as understanding a phenomenon in terms of conditional statements in the form, “If X, then Y.” This type of research is used to measure what impact a specific change will have on existing norms and assumptions. Most social scientists seek causal explanations that reflect tests of hypotheses. Causal effect (nomothetic perspective) occurs when variation in one phenomenon, an independent variable, leads to or results, on average, in variation in another phenomenon, the dependent variable.

Conditions necessary for determining causality:

• Empirical association -- a valid conclusion is based on finding an association between the independent variable and the dependent variable.
• Appropriate time order -- to conclude that causation was involved, one must see that cases were exposed to variation in the independent variable before variation in the dependent variable.
• Nonspuriousness -- a relationship between two variables that is not due to variation in a third variable.
• Causality research designs assist researchers in understanding why the world works the way it does through the process of proving a causal link between variables and by the process of eliminating other possibilities.
• Replication is possible.
• There is greater confidence the study has internal validity due to the systematic subject selection and equity of groups being compared.
• Not all relationships are causal! The possibility always exists that, by sheer coincidence, two unrelated events appear to be related [e.g., Punxatawney Phil could accurately predict the duration of Winter for five consecutive years but, the fact remains, he's just a big, furry rodent].
• Conclusions about causal relationships are difficult to determine due to a variety of extraneous and confounding variables that exist in a social environment. This means causality can only be inferred, never proven.
• If two variables are correlated, the cause must come before the effect. However, even though two variables might be causally related, it can sometimes be difficult to determine which variable comes first and, therefore, to establish which variable is the actual cause and which is the  actual effect.

Beach, Derek and Rasmus Brun Pedersen. Causal Case Study Methods: Foundations and Guidelines for Comparing, Matching, and Tracing . Ann Arbor, MI: University of Michigan Press, 2016; Bachman, Ronet. The Practice of Research in Criminology and Criminal Justice . Chapter 5, Causation and Research Designs. 3rd ed. Thousand Oaks, CA: Pine Forge Press, 2007; Brewer, Ernest W. and Jennifer Kubn. “Causal-Comparative Design.” In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 125-132; Causal Research Design: Experimentation. Anonymous SlideShare Presentation; Gall, Meredith. Educational Research: An Introduction . Chapter 11, Nonexperimental Research: Correlational Designs. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Trochim, William M.K. Research Methods Knowledge Base. 2006.

Cohort Design

Often used in the medical sciences, but also found in the applied social sciences, a cohort study generally refers to a study conducted over a period of time involving members of a population which the subject or representative member comes from, and who are united by some commonality or similarity. Using a quantitative framework, a cohort study makes note of statistical occurrence within a specialized subgroup, united by same or similar characteristics that are relevant to the research problem being investigated, rather than studying statistical occurrence within the general population. Using a qualitative framework, cohort studies generally gather data using methods of observation. Cohorts can be either "open" or "closed."

• Open Cohort Studies [dynamic populations, such as the population of Los Angeles] involve a population that is defined just by the state of being a part of the study in question (and being monitored for the outcome). Date of entry and exit from the study is individually defined, therefore, the size of the study population is not constant. In open cohort studies, researchers can only calculate rate based data, such as, incidence rates and variants thereof.
• Closed Cohort Studies [static populations, such as patients entered into a clinical trial] involve participants who enter into the study at one defining point in time and where it is presumed that no new participants can enter the cohort. Given this, the number of study participants remains constant (or can only decrease).
• The use of cohorts is often mandatory because a randomized control study may be unethical. For example, you cannot deliberately expose people to asbestos, you can only study its effects on those who have already been exposed. Research that measures risk factors often relies upon cohort designs.
• Because cohort studies measure potential causes before the outcome has occurred, they can demonstrate that these “causes” preceded the outcome, thereby avoiding the debate as to which is the cause and which is the effect.
• Cohort analysis is highly flexible and can provide insight into effects over time and related to a variety of different types of changes [e.g., social, cultural, political, economic, etc.].
• Either original data or secondary data can be used in this design.
• In cases where a comparative analysis of two cohorts is made [e.g., studying the effects of one group exposed to asbestos and one that has not], a researcher cannot control for all other factors that might differ between the two groups. These factors are known as confounding variables.
• Cohort studies can end up taking a long time to complete if the researcher must wait for the conditions of interest to develop within the group. This also increases the chance that key variables change during the course of the study, potentially impacting the validity of the findings.
• Due to the lack of randominization in the cohort design, its external validity is lower than that of study designs where the researcher randomly assigns participants.

Healy P, Devane D. “Methodological Considerations in Cohort Study Designs.” Nurse Researcher 18 (2011): 32-36; Glenn, Norval D, editor. Cohort Analysis . 2nd edition. Thousand Oaks, CA: Sage, 2005; Levin, Kate Ann. Study Design IV: Cohort Studies. Evidence-Based Dentistry 7 (2003): 51–52; Payne, Geoff. “Cohort Study.” In The SAGE Dictionary of Social Research Methods . Victor Jupp, editor. (Thousand Oaks, CA: Sage, 2006), pp. 31-33; Study Design 101. Himmelfarb Health Sciences Library. George Washington University, November 2011; Cohort Study. Wikipedia.

Cross-Sectional Design

Cross-sectional research designs have three distinctive features: no time dimension; a reliance on existing differences rather than change following intervention; and, groups are selected based on existing differences rather than random allocation. The cross-sectional design can only measure differences between or from among a variety of people, subjects, or phenomena rather than a process of change. As such, researchers using this design can only employ a relatively passive approach to making causal inferences based on findings.

• Cross-sectional studies provide a clear 'snapshot' of the outcome and the characteristics associated with it, at a specific point in time.
• Unlike an experimental design, where there is an active intervention by the researcher to produce and measure change or to create differences, cross-sectional designs focus on studying and drawing inferences from existing differences between people, subjects, or phenomena.
• Entails collecting data at and concerning one point in time. While longitudinal studies involve taking multiple measures over an extended period of time, cross-sectional research is focused on finding relationships between variables at one moment in time.
• Groups identified for study are purposely selected based upon existing differences in the sample rather than seeking random sampling.
• Cross-section studies are capable of using data from a large number of subjects and, unlike observational studies, is not geographically bound.
• Can estimate prevalence of an outcome of interest because the sample is usually taken from the whole population.
• Because cross-sectional designs generally use survey techniques to gather data, they are relatively inexpensive and take up little time to conduct.
• Finding people, subjects, or phenomena to study that are very similar except in one specific variable can be difficult.
• Results are static and time bound and, therefore, give no indication of a sequence of events or reveal historical or temporal contexts.
• Studies cannot be utilized to establish cause and effect relationships.
• This design only provides a snapshot of analysis so there is always the possibility that a study could have differing results if another time-frame had been chosen.
• There is no follow up to the findings.

Bethlehem, Jelke. "7: Cross-sectional Research." In Research Methodology in the Social, Behavioural and Life Sciences . Herman J Adèr and Gideon J Mellenbergh, editors. (London, England: Sage, 1999), pp. 110-43; Bourque, Linda B. “Cross-Sectional Design.” In  The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman, and Tim Futing Liao. (Thousand Oaks, CA: 2004), pp. 230-231; Hall, John. “Cross-Sectional Survey Design.” In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 173-174; Helen Barratt, Maria Kirwan. Cross-Sectional Studies: Design Application, Strengths and Weaknesses of Cross-Sectional Studies. Healthknowledge, 2009. Cross-Sectional Study. Wikipedia.

Descriptive Design

Descriptive research designs help provide answers to the questions of who, what, when, where, and how associated with a particular research problem; a descriptive study cannot conclusively ascertain answers to why. Descriptive research is used to obtain information concerning the current status of the phenomena and to describe "what exists" with respect to variables or conditions in a situation.

• The subject is being observed in a completely natural and unchanged natural environment. True experiments, whilst giving analyzable data, often adversely influence the normal behavior of the subject [a.k.a., the Heisenberg effect whereby measurements of certain systems cannot be made without affecting the systems].
• Descriptive research is often used as a pre-cursor to more quantitative research designs with the general overview giving some valuable pointers as to what variables are worth testing quantitatively.
• If the limitations are understood, they can be a useful tool in developing a more focused study.
• Descriptive studies can yield rich data that lead to important recommendations in practice.
• Appoach collects a large amount of data for detailed analysis.
• The results from a descriptive research cannot be used to discover a definitive answer or to disprove a hypothesis.
• Because descriptive designs often utilize observational methods [as opposed to quantitative methods], the results cannot be replicated.
• The descriptive function of research is heavily dependent on instrumentation for measurement and observation.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 5, Flexible Methods: Descriptive Research. 2nd ed. New York: Columbia University Press, 1999; Given, Lisa M. "Descriptive Research." In Encyclopedia of Measurement and Statistics . Neil J. Salkind and Kristin Rasmussen, editors. (Thousand Oaks, CA: Sage, 2007), pp. 251-254; McNabb, Connie. Descriptive Research Methodologies. Powerpoint Presentation; Shuttleworth, Martyn. Descriptive Research Design, September 26, 2008; Erickson, G. Scott. "Descriptive Research Design." In New Methods of Market Research and Analysis . (Northampton, MA: Edward Elgar Publishing, 2017), pp. 51-77; Sahin, Sagufta, and Jayanta Mete. "A Brief Study on Descriptive Research: Its Nature and Application in Social Science." International Journal of Research and Analysis in Humanities 1 (2021): 11; K. Swatzell and P. Jennings. “Descriptive Research: The Nuts and Bolts.” Journal of the American Academy of Physician Assistants 20 (2007), pp. 55-56; Kane, E. Doing Your Own Research: Basic Descriptive Research in the Social Sciences and Humanities . London: Marion Boyars, 1985.

Experimental Design

A blueprint of the procedure that enables the researcher to maintain control over all factors that may affect the result of an experiment. In doing this, the researcher attempts to determine or predict what may occur. Experimental research is often used where there is time priority in a causal relationship (cause precedes effect), there is consistency in a causal relationship (a cause will always lead to the same effect), and the magnitude of the correlation is great. The classic experimental design specifies an experimental group and a control group. The independent variable is administered to the experimental group and not to the control group, and both groups are measured on the same dependent variable. Subsequent experimental designs have used more groups and more measurements over longer periods. True experiments must have control, randomization, and manipulation.

• Experimental research allows the researcher to control the situation. In so doing, it allows researchers to answer the question, “What causes something to occur?”
• Permits the researcher to identify cause and effect relationships between variables and to distinguish placebo effects from treatment effects.
• Experimental research designs support the ability to limit alternative explanations and to infer direct causal relationships in the study.
• Approach provides the highest level of evidence for single studies.
• The design is artificial, and results may not generalize well to the real world.
• The artificial settings of experiments may alter the behaviors or responses of participants.
• Experimental designs can be costly if special equipment or facilities are needed.
• Some research problems cannot be studied using an experiment because of ethical or technical reasons.
• Difficult to apply ethnographic and other qualitative methods to experimentally designed studies.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 7, Flexible Methods: Experimental Research. 2nd ed. New York: Columbia University Press, 1999; Chapter 2: Research Design, Experimental Designs. School of Psychology, University of New England, 2000; Chow, Siu L. "Experimental Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 448-453; "Experimental Design." In Social Research Methods . Nicholas Walliman, editor. (London, England: Sage, 2006), pp, 101-110; Experimental Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Kirk, Roger E. Experimental Design: Procedures for the Behavioral Sciences . 4th edition. Thousand Oaks, CA: Sage, 2013; Trochim, William M.K. Experimental Design. Research Methods Knowledge Base. 2006; Rasool, Shafqat. Experimental Research. Slideshare presentation.

Exploratory Design

An exploratory design is conducted about a research problem when there are few or no earlier studies to refer to or rely upon to predict an outcome . The focus is on gaining insights and familiarity for later investigation or undertaken when research problems are in a preliminary stage of investigation. Exploratory designs are often used to establish an understanding of how best to proceed in studying an issue or what methodology would effectively apply to gathering information about the issue.

The goals of exploratory research are intended to produce the following possible insights:

• Familiarity with basic details, settings, and concerns.
• Well grounded picture of the situation being developed.
• Generation of new ideas and assumptions.
• Development of tentative theories or hypotheses.
• Determination about whether a study is feasible in the future.
• Issues get refined for more systematic investigation and formulation of new research questions.
• Direction for future research and techniques get developed.
• Design is a useful approach for gaining background information on a particular topic.
• Exploratory research is flexible and can address research questions of all types (what, why, how).
• Provides an opportunity to define new terms and clarify existing concepts.
• Exploratory research is often used to generate formal hypotheses and develop more precise research problems.
• In the policy arena or applied to practice, exploratory studies help establish research priorities and where resources should be allocated.
• Exploratory research generally utilizes small sample sizes and, thus, findings are typically not generalizable to the population at large.
• The exploratory nature of the research inhibits an ability to make definitive conclusions about the findings. They provide insight but not definitive conclusions.
• The research process underpinning exploratory studies is flexible but often unstructured, leading to only tentative results that have limited value to decision-makers.
• Design lacks rigorous standards applied to methods of data gathering and analysis because one of the areas for exploration could be to determine what method or methodologies could best fit the research problem.

Cuthill, Michael. “Exploratory Research: Citizen Participation, Local Government, and Sustainable Development in Australia.” Sustainable Development 10 (2002): 79-89; Streb, Christoph K. "Exploratory Case Study." In Encyclopedia of Case Study Research . Albert J. Mills, Gabrielle Durepos and Eiden Wiebe, editors. (Thousand Oaks, CA: Sage, 2010), pp. 372-374; Taylor, P. J., G. Catalano, and D.R.F. Walker. “Exploratory Analysis of the World City Network.” Urban Studies 39 (December 2002): 2377-2394; Exploratory Research. Wikipedia.

Field Research Design

Sometimes referred to as ethnography or participant observation, designs around field research encompass a variety of interpretative procedures [e.g., observation and interviews] rooted in qualitative approaches to studying people individually or in groups while inhabiting their natural environment as opposed to using survey instruments or other forms of impersonal methods of data gathering. Information acquired from observational research takes the form of “ field notes ” that involves documenting what the researcher actually sees and hears while in the field. Findings do not consist of conclusive statements derived from numbers and statistics because field research involves analysis of words and observations of behavior. Conclusions, therefore, are developed from an interpretation of findings that reveal overriding themes, concepts, and ideas. More information can be found HERE .

• Field research is often necessary to fill gaps in understanding the research problem applied to local conditions or to specific groups of people that cannot be ascertained from existing data.
• The research helps contextualize already known information about a research problem, thereby facilitating ways to assess the origins, scope, and scale of a problem and to gage the causes, consequences, and means to resolve an issue based on deliberate interaction with people in their natural inhabited spaces.
• Enables the researcher to corroborate or confirm data by gathering additional information that supports or refutes findings reported in prior studies of the topic.
• Because the researcher in embedded in the field, they are better able to make observations or ask questions that reflect the specific cultural context of the setting being investigated.
• Observing the local reality offers the opportunity to gain new perspectives or obtain unique data that challenges existing theoretical propositions or long-standing assumptions found in the literature.

What these studies don't tell you

• A field research study requires extensive time and resources to carry out the multiple steps involved with preparing for the gathering of information, including for example, examining background information about the study site, obtaining permission to access the study site, and building trust and rapport with subjects.
• Requires a commitment to staying engaged in the field to ensure that you can adequately document events and behaviors as they unfold.
• The unpredictable nature of fieldwork means that researchers can never fully control the process of data gathering. They must maintain a flexible approach to studying the setting because events and circumstances can change quickly or unexpectedly.
• Findings can be difficult to interpret and verify without access to documents and other source materials that help to enhance the credibility of information obtained from the field  [i.e., the act of triangulating the data].
• Linking the research problem to the selection of study participants inhabiting their natural environment is critical. However, this specificity limits the ability to generalize findings to different situations or in other contexts or to infer courses of action applied to other settings or groups of people.
• The reporting of findings must take into account how the researcher themselves may have inadvertently affected respondents and their behaviors.

Historical Design

The purpose of a historical research design is to collect, verify, and synthesize evidence from the past to establish facts that defend or refute a hypothesis. It uses secondary sources and a variety of primary documentary evidence, such as, diaries, official records, reports, archives, and non-textual information [maps, pictures, audio and visual recordings]. The limitation is that the sources must be both authentic and valid.

• The historical research design is unobtrusive; the act of research does not affect the results of the study.
• The historical approach is well suited for trend analysis.
• Historical records can add important contextual background required to more fully understand and interpret a research problem.
• There is often no possibility of researcher-subject interaction that could affect the findings.
• Historical sources can be used over and over to study different research problems or to replicate a previous study.
• The ability to fulfill the aims of your research are directly related to the amount and quality of documentation available to understand the research problem.
• Since historical research relies on data from the past, there is no way to manipulate it to control for contemporary contexts.
• Interpreting historical sources can be very time consuming.
• The sources of historical materials must be archived consistently to ensure access. This may especially challenging for digital or online-only sources.
• Original authors bring their own perspectives and biases to the interpretation of past events and these biases are more difficult to ascertain in historical resources.
• Due to the lack of control over external variables, historical research is very weak with regard to the demands of internal validity.
• It is rare that the entirety of historical documentation needed to fully address a research problem is available for interpretation, therefore, gaps need to be acknowledged.

Howell, Martha C. and Walter Prevenier. From Reliable Sources: An Introduction to Historical Methods . Ithaca, NY: Cornell University Press, 2001; Lundy, Karen Saucier. "Historical Research." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor. (Thousand Oaks, CA: Sage, 2008), pp. 396-400; Marius, Richard. and Melvin E. Page. A Short Guide to Writing about History . 9th edition. Boston, MA: Pearson, 2015; Savitt, Ronald. “Historical Research in Marketing.” Journal of Marketing 44 (Autumn, 1980): 52-58;  Gall, Meredith. Educational Research: An Introduction . Chapter 16, Historical Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007.

Longitudinal Design

A longitudinal study follows the same sample over time and makes repeated observations. For example, with longitudinal surveys, the same group of people is interviewed at regular intervals, enabling researchers to track changes over time and to relate them to variables that might explain why the changes occur. Longitudinal research designs describe patterns of change and help establish the direction and magnitude of causal relationships. Measurements are taken on each variable over two or more distinct time periods. This allows the researcher to measure change in variables over time. It is a type of observational study sometimes referred to as a panel study.

• Longitudinal data facilitate the analysis of the duration of a particular phenomenon.
• Enables survey researchers to get close to the kinds of causal explanations usually attainable only with experiments.
• The design permits the measurement of differences or change in a variable from one period to another [i.e., the description of patterns of change over time].
• Longitudinal studies facilitate the prediction of future outcomes based upon earlier factors.
• The data collection method may change over time.
• Maintaining the integrity of the original sample can be difficult over an extended period of time.
• It can be difficult to show more than one variable at a time.
• This design often needs qualitative research data to explain fluctuations in the results.
• A longitudinal research design assumes present trends will continue unchanged.
• It can take a long period of time to gather results.
• There is a need to have a large sample size and accurate sampling to reach representativness.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 6, Flexible Methods: Relational and Longitudinal Research. 2nd ed. New York: Columbia University Press, 1999; Forgues, Bernard, and Isabelle Vandangeon-Derumez. "Longitudinal Analyses." In Doing Management Research . Raymond-Alain Thiétart and Samantha Wauchope, editors. (London, England: Sage, 2001), pp. 332-351; Kalaian, Sema A. and Rafa M. Kasim. "Longitudinal Studies." In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 440-441; Menard, Scott, editor. Longitudinal Research . Thousand Oaks, CA: Sage, 2002; Ployhart, Robert E. and Robert J. Vandenberg. "Longitudinal Research: The Theory, Design, and Analysis of Change.” Journal of Management 36 (January 2010): 94-120; Longitudinal Study. Wikipedia.

Meta-Analysis Design

Meta-analysis is an analytical methodology designed to systematically evaluate and summarize the results from a number of individual studies, thereby, increasing the overall sample size and the ability of the researcher to study effects of interest. The purpose is to not simply summarize existing knowledge, but to develop a new understanding of a research problem using synoptic reasoning. The main objectives of meta-analysis include analyzing differences in the results among studies and increasing the precision by which effects are estimated. A well-designed meta-analysis depends upon strict adherence to the criteria used for selecting studies and the availability of information in each study to properly analyze their findings. Lack of information can severely limit the type of analyzes and conclusions that can be reached. In addition, the more dissimilarity there is in the results among individual studies [heterogeneity], the more difficult it is to justify interpretations that govern a valid synopsis of results. A meta-analysis needs to fulfill the following requirements to ensure the validity of your findings:

• Clearly defined description of objectives, including precise definitions of the variables and outcomes that are being evaluated;
• A well-reasoned and well-documented justification for identification and selection of the studies;
• Assessment and explicit acknowledgment of any researcher bias in the identification and selection of those studies;
• Description and evaluation of the degree of heterogeneity among the sample size of studies reviewed; and,
• Justification of the techniques used to evaluate the studies.
• Can be an effective strategy for determining gaps in the literature.
• Provides a means of reviewing research published about a particular topic over an extended period of time and from a variety of sources.
• Is useful in clarifying what policy or programmatic actions can be justified on the basis of analyzing research results from multiple studies.
• Provides a method for overcoming small sample sizes in individual studies that previously may have had little relationship to each other.
• Can be used to generate new hypotheses or highlight research problems for future studies.
• Small violations in defining the criteria used for content analysis can lead to difficult to interpret and/or meaningless findings.
• A large sample size can yield reliable, but not necessarily valid, results.
• A lack of uniformity regarding, for example, the type of literature reviewed, how methods are applied, and how findings are measured within the sample of studies you are analyzing, can make the process of synthesis difficult to perform.
• Depending on the sample size, the process of reviewing and synthesizing multiple studies can be very time consuming.

Beck, Lewis W. "The Synoptic Method." The Journal of Philosophy 36 (1939): 337-345; Cooper, Harris, Larry V. Hedges, and Jeffrey C. Valentine, eds. The Handbook of Research Synthesis and Meta-Analysis . 2nd edition. New York: Russell Sage Foundation, 2009; Guzzo, Richard A., Susan E. Jackson and Raymond A. Katzell. “Meta-Analysis Analysis.” In Research in Organizational Behavior , Volume 9. (Greenwich, CT: JAI Press, 1987), pp 407-442; Lipsey, Mark W. and David B. Wilson. Practical Meta-Analysis . Thousand Oaks, CA: Sage Publications, 2001; Study Design 101. Meta-Analysis. The Himmelfarb Health Sciences Library, George Washington University; Timulak, Ladislav. “Qualitative Meta-Analysis.” In The SAGE Handbook of Qualitative Data Analysis . Uwe Flick, editor. (Los Angeles, CA: Sage, 2013), pp. 481-495; Walker, Esteban, Adrian V. Hernandez, and Micheal W. Kattan. "Meta-Analysis: It's Strengths and Limitations." Cleveland Clinic Journal of Medicine 75 (June 2008): 431-439.

Mixed-Method Design

• Narrative and non-textual information can add meaning to numeric data, while numeric data can add precision to narrative and non-textual information.
• Can utilize existing data while at the same time generating and testing a grounded theory approach to describe and explain the phenomenon under study.
• A broader, more complex research problem can be investigated because the researcher is not constrained by using only one method.
• The strengths of one method can be used to overcome the inherent weaknesses of another method.
• Can provide stronger, more robust evidence to support a conclusion or set of recommendations.
• May generate new knowledge new insights or uncover hidden insights, patterns, or relationships that a single methodological approach might not reveal.
• Produces more complete knowledge and understanding of the research problem that can be used to increase the generalizability of findings applied to theory or practice.
• A researcher must be proficient in understanding how to apply multiple methods to investigating a research problem as well as be proficient in optimizing how to design a study that coherently melds them together.
• Can increase the likelihood of conflicting results or ambiguous findings that inhibit drawing a valid conclusion or setting forth a recommended course of action [e.g., sample interview responses do not support existing statistical data].
• Because the research design can be very complex, reporting the findings requires a well-organized narrative, clear writing style, and precise word choice.
• Design invites collaboration among experts. However, merging different investigative approaches and writing styles requires more attention to the overall research process than studies conducted using only one methodological paradigm.
• Concurrent merging of quantitative and qualitative research requires greater attention to having adequate sample sizes, using comparable samples, and applying a consistent unit of analysis. For sequential designs where one phase of qualitative research builds on the quantitative phase or vice versa, decisions about what results from the first phase to use in the next phase, the choice of samples and estimating reasonable sample sizes for both phases, and the interpretation of results from both phases can be difficult.
• Due to multiple forms of data being collected and analyzed, this design requires extensive time and resources to carry out the multiple steps involved in data gathering and interpretation.

Burch, Patricia and Carolyn J. Heinrich. Mixed Methods for Policy Research and Program Evaluation . Thousand Oaks, CA: Sage, 2016; Creswell, John w. et al. Best Practices for Mixed Methods Research in the Health Sciences . Bethesda, MD: Office of Behavioral and Social Sciences Research, National Institutes of Health, 2010Creswell, John W. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 4th edition. Thousand Oaks, CA: Sage Publications, 2014; Domínguez, Silvia, editor. Mixed Methods Social Networks Research . Cambridge, UK: Cambridge University Press, 2014; Hesse-Biber, Sharlene Nagy. Mixed Methods Research: Merging Theory with Practice . New York: Guilford Press, 2010; Niglas, Katrin. “How the Novice Researcher Can Make Sense of Mixed Methods Designs.” International Journal of Multiple Research Approaches 3 (2009): 34-46; Onwuegbuzie, Anthony J. and Nancy L. Leech. “Linking Research Questions to Mixed Methods Data Analysis Procedures.” The Qualitative Report 11 (September 2006): 474-498; Tashakorri, Abbas and John W. Creswell. “The New Era of Mixed Methods.” Journal of Mixed Methods Research 1 (January 2007): 3-7; Zhanga, Wanqing. “Mixed Methods Application in Health Intervention Research: A Multiple Case Study.” International Journal of Multiple Research Approaches 8 (2014): 24-35 .

Observational Design

This type of research design draws a conclusion by comparing subjects against a control group, in cases where the researcher has no control over the experiment. There are two general types of observational designs. In direct observations, people know that you are watching them. Unobtrusive measures involve any method for studying behavior where individuals do not know they are being observed. An observational study allows a useful insight into a phenomenon and avoids the ethical and practical difficulties of setting up a large and cumbersome research project.

• Observational studies are usually flexible and do not necessarily need to be structured around a hypothesis about what you expect to observe [data is emergent rather than pre-existing].
• The researcher is able to collect in-depth information about a particular behavior.
• Can reveal interrelationships among multifaceted dimensions of group interactions.
• You can generalize your results to real life situations.
• Observational research is useful for discovering what variables may be important before applying other methods like experiments.
• Observation research designs account for the complexity of group behaviors.
• Reliability of data is low because seeing behaviors occur over and over again may be a time consuming task and are difficult to replicate.
• In observational research, findings may only reflect a unique sample population and, thus, cannot be generalized to other groups.
• There can be problems with bias as the researcher may only "see what they want to see."
• There is no possibility to determine "cause and effect" relationships since nothing is manipulated.
• Sources or subjects may not all be equally credible.
• Any group that is knowingly studied is altered to some degree by the presence of the researcher, therefore, potentially skewing any data collected.

Atkinson, Paul and Martyn Hammersley. “Ethnography and Participant Observation.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 248-261; Observational Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Patton Michael Quinn. Qualitiative Research and Evaluation Methods . Chapter 6, Fieldwork Strategies and Observational Methods. 3rd ed. Thousand Oaks, CA: Sage, 2002; Payne, Geoff and Judy Payne. "Observation." In Key Concepts in Social Research . The SAGE Key Concepts series. (London, England: Sage, 2004), pp. 158-162; Rosenbaum, Paul R. Design of Observational Studies . New York: Springer, 2010;Williams, J. Patrick. "Nonparticipant Observation." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor.(Thousand Oaks, CA: Sage, 2008), pp. 562-563.

Philosophical Design

Understood more as an broad approach to examining a research problem than a methodological design, philosophical analysis and argumentation is intended to challenge deeply embedded, often intractable, assumptions underpinning an area of study. This approach uses the tools of argumentation derived from philosophical traditions, concepts, models, and theories to critically explore and challenge, for example, the relevance of logic and evidence in academic debates, to analyze arguments about fundamental issues, or to discuss the root of existing discourse about a research problem. These overarching tools of analysis can be framed in three ways:

• Ontology -- the study that describes the nature of reality; for example, what is real and what is not, what is fundamental and what is derivative?
• Epistemology -- the study that explores the nature of knowledge; for example, by what means does knowledge and understanding depend upon and how can we be certain of what we know?
• Axiology -- the study of values; for example, what values does an individual or group hold and why? How are values related to interest, desire, will, experience, and means-to-end? And, what is the difference between a matter of fact and a matter of value?
• Can provide a basis for applying ethical decision-making to practice.
• Functions as a means of gaining greater self-understanding and self-knowledge about the purposes of research.
• Brings clarity to general guiding practices and principles of an individual or group.
• Philosophy informs methodology.
• Refine concepts and theories that are invoked in relatively unreflective modes of thought and discourse.
• Beyond methodology, philosophy also informs critical thinking about epistemology and the structure of reality (metaphysics).
• Offers clarity and definition to the practical and theoretical uses of terms, concepts, and ideas.
• Limited application to specific research problems [answering the "So What?" question in social science research].
• Analysis can be abstract, argumentative, and limited in its practical application to real-life issues.
• While a philosophical analysis may render problematic that which was once simple or taken-for-granted, the writing can be dense and subject to unnecessary jargon, overstatement, and/or excessive quotation and documentation.
• There are limitations in the use of metaphor as a vehicle of philosophical analysis.
• There can be analytical difficulties in moving from philosophy to advocacy and between abstract thought and application to the phenomenal world.

Burton, Dawn. "Part I, Philosophy of the Social Sciences." In Research Training for Social Scientists . (London, England: Sage, 2000), pp. 1-5; Chapter 4, Research Methodology and Design. Unisa Institutional Repository (UnisaIR), University of South Africa; Jarvie, Ian C., and Jesús Zamora-Bonilla, editors. The SAGE Handbook of the Philosophy of Social Sciences . London: Sage, 2011; Labaree, Robert V. and Ross Scimeca. “The Philosophical Problem of Truth in Librarianship.” The Library Quarterly 78 (January 2008): 43-70; Maykut, Pamela S. Beginning Qualitative Research: A Philosophic and Practical Guide . Washington, DC: Falmer Press, 1994; McLaughlin, Hugh. "The Philosophy of Social Research." In Understanding Social Work Research . 2nd edition. (London: SAGE Publications Ltd., 2012), pp. 24-47; Stanford Encyclopedia of Philosophy . Metaphysics Research Lab, CSLI, Stanford University, 2013.

Sequential Design

• The researcher has a limitless option when it comes to sample size and the sampling schedule.
• Due to the repetitive nature of this research design, minor changes and adjustments can be done during the initial parts of the study to correct and hone the research method.
• This is a useful design for exploratory studies.
• There is very little effort on the part of the researcher when performing this technique. It is generally not expensive, time consuming, or workforce intensive.
• Because the study is conducted serially, the results of one sample are known before the next sample is taken and analyzed. This provides opportunities for continuous improvement of sampling and methods of analysis.
• The sampling method is not representative of the entire population. The only possibility of approaching representativeness is when the researcher chooses to use a very large sample size significant enough to represent a significant portion of the entire population. In this case, moving on to study a second or more specific sample can be difficult.
• The design cannot be used to create conclusions and interpretations that pertain to an entire population because the sampling technique is not randomized. Generalizability from findings is, therefore, limited.
• Difficult to account for and interpret variation from one sample to another over time, particularly when using qualitative methods of data collection.

Betensky, Rebecca. Harvard University, Course Lecture Note slides; Bovaird, James A. and Kevin A. Kupzyk. "Sequential Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 1347-1352; Cresswell, John W. Et al. “Advanced Mixed-Methods Research Designs.” In Handbook of Mixed Methods in Social and Behavioral Research . Abbas Tashakkori and Charles Teddle, eds. (Thousand Oaks, CA: Sage, 2003), pp. 209-240; Henry, Gary T. "Sequential Sampling." In The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman and Tim Futing Liao, editors. (Thousand Oaks, CA: Sage, 2004), pp. 1027-1028; Nataliya V. Ivankova. “Using Mixed-Methods Sequential Explanatory Design: From Theory to Practice.” Field Methods 18 (February 2006): 3-20; Bovaird, James A. and Kevin A. Kupzyk. “Sequential Design.” In Encyclopedia of Research Design . Neil J. Salkind, ed. Thousand Oaks, CA: Sage, 2010; Sequential Analysis. Wikipedia.

Systematic Review

• A systematic review synthesizes the findings of multiple studies related to each other by incorporating strategies of analysis and interpretation intended to reduce biases and random errors.
• The application of critical exploration, evaluation, and synthesis methods separates insignificant, unsound, or redundant research from the most salient and relevant studies worthy of reflection.
• They can be use to identify, justify, and refine hypotheses, recognize and avoid hidden problems in prior studies, and explain data inconsistencies and conflicts in data.
• Systematic reviews can be used to help policy makers formulate evidence-based guidelines and regulations.
• The use of strict, explicit, and pre-determined methods of synthesis, when applied appropriately, provide reliable estimates about the effects of interventions, evaluations, and effects related to the overarching research problem investigated by each study under review.
• Systematic reviews illuminate where knowledge or thorough understanding of a research problem is lacking and, therefore, can then be used to guide future research.
• The accepted inclusion of unpublished studies [i.e., grey literature] ensures the broadest possible way to analyze and interpret research on a topic.
• Results of the synthesis can be generalized and the findings extrapolated into the general population with more validity than most other types of studies .
• Systematic reviews do not create new knowledge per se; they are a method for synthesizing existing studies about a research problem in order to gain new insights and determine gaps in the literature.
• The way researchers have carried out their investigations [e.g., the period of time covered, number of participants, sources of data analyzed, etc.] can make it difficult to effectively synthesize studies.
• The inclusion of unpublished studies can introduce bias into the review because they may not have undergone a rigorous peer-review process prior to publication. Examples may include conference presentations or proceedings, publications from government agencies, white papers, working papers, and internal documents from organizations, and doctoral dissertations and Master's theses.

Denyer, David and David Tranfield. "Producing a Systematic Review." In The Sage Handbook of Organizational Research Methods .  David A. Buchanan and Alan Bryman, editors. ( Thousand Oaks, CA: Sage Publications, 2009), pp. 671-689; Foster, Margaret J. and Sarah T. Jewell, editors. Assembling the Pieces of a Systematic Review: A Guide for Librarians . Lanham, MD: Rowman and Littlefield, 2017; Gough, David, Sandy Oliver, James Thomas, editors. Introduction to Systematic Reviews . 2nd edition. Los Angeles, CA: Sage Publications, 2017; Gopalakrishnan, S. and P. Ganeshkumar. “Systematic Reviews and Meta-analysis: Understanding the Best Evidence in Primary Healthcare.” Journal of Family Medicine and Primary Care 2 (2013): 9-14; Gough, David, James Thomas, and Sandy Oliver. "Clarifying Differences between Review Designs and Methods." Systematic Reviews 1 (2012): 1-9; Khan, Khalid S., Regina Kunz, Jos Kleijnen, and Gerd Antes. “Five Steps to Conducting a Systematic Review.” Journal of the Royal Society of Medicine 96 (2003): 118-121; Mulrow, C. D. “Systematic Reviews: Rationale for Systematic Reviews.” BMJ 309:597 (September 1994); O'Dwyer, Linda C., and Q. Eileen Wafford. "Addressing Challenges with Systematic Review Teams through Effective Communication: A Case Report." Journal of the Medical Library Association 109 (October 2021): 643-647; Okoli, Chitu, and Kira Schabram. "A Guide to Conducting a Systematic Literature Review of Information Systems Research."  Sprouts: Working Papers on Information Systems 10 (2010); Siddaway, Andy P., Alex M. Wood, and Larry V. Hedges. "How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-analyses, and Meta-syntheses." Annual Review of Psychology 70 (2019): 747-770; Torgerson, Carole J. “Publication Bias: The Achilles’ Heel of Systematic Reviews?” British Journal of Educational Studies 54 (March 2006): 89-102; Torgerson, Carole. Systematic Reviews . New York: Continuum, 2003.

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Home Market Research

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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Introduction to Research Methods

3 types of research.

In the last chapter we talked about the ways that research is all around us. You do it yourself almost every day in small and big ways, but we’re not really here to help you become more rigorous in your search for the best tacos in town. Looking at yelp is research, it’s just not really the type of research we’re going to talk about today. In the first section of this chapter we’ll talk about different types of research. Then we’ll describe different fields of research within social sciences, and finally we’ll discuss the steps of doing research.

I’m going to break types of research into three categories, which probably don’t match the way they’re described in other textbooks.

A lot of the research you do in your daily life could probably be called secondary research . You have a question (“where are the best tacos?”, “when did the Civil War start?”, “is coffee bad for my heart?”) and so you seek an answer. That’s still research, it just doesn’t involve the collection of new data or a lot of detailed steps. Google and other search engines are incredible tools that will direct you towards an answer to your questions. What you’re doing there is secondary research, using the research of others to answer your question. Your collecting, reviewing, or synthesizing existing research, not creating new data to answer a question.

You can be better at secondary research by identifying reputable sources, accessing multiple opinions, and understanding how they produced their findings. That’s part of the research we’re talking about in this class, but only a small part. We’ll return to secondary research in a later chapter, because in order to be really good at it you have to understand how to do the original research yourself. Secondary research thus involves reviewing the research of others and is motivated by getting an answer to a question.

You can only do secondary research if someone has already researched the question you have. Another type of research people do is what could be called applied research, or research that is intended for immediate public dissemination. The idea of applied research is that there is a very clear connection between the research question and the importance of the research. Imagine you’re in a sorority and you’re planning dinner for the new pledges, so you poll everyone to ask which of three options they’d pick. You gather the data and you get an answer – the most common answer is tacos. Why do you care about the answer? Because you needed to know where to go for dinner.

Would people be open to changing the colors on the United States flag? I don’t know, and based on a quick Google search no one has answered the question. No one has polled Americans to find out whether they think red white and blue is a little dated (or maybe just too similar to France). I don’t know why we’d want to change the colors, maybe so everyone has to go buy a new flag. I can’t get an answer to that question based on secondary research though. I have to collect original data if I want an answer.

Polls are a great example of applied research. Who is currently winning the race for president? How do people feel about policies designed to slow climate change? How much trust do citizens have in their government? Those are all questions you can find written about in wonky news sources like the [NY Times], Vox, 538, or others. Why do we care? Because we want to know who is winning the race, or peoples views towards certain policies.

Take another example. A radio station wants to know the demographics of its listeners so that it can make sure the commercials they run are matched to who listens. There isn’t an esoteric question to answer, but they need to collect data to improve their business operations.

The research question and the importance are very directly linked. Thus, applied research involves original research, not just reviewing what others have done, but like secondary research it is motivated to get an answer.

The third type is the least common, but is also generally the focus of a textbook like this. Academic research is the type of research that your professors do most of the time. What differentiates public research from academic research? Public research is concerned with providing new facts, academic research is concerned with testing theories and seeking explanations.

I could spend thousands of dollars to run a new poll with a very rigorous research design to understand exactly what percentage of Americans would support new taxes. If I did that research I might be able to get it published in popular sources like the New York Times, but I could never get it published in an academic journal – and those are the papers that get professors tenure.

Why? Good polls tell us something about the world at this moment, but sciences goal, both the social and hard sciences, is to tell us something about the world beyond this moment. More accurately, it’s concerned with explaining the causes of the phenomena we see. Scientists weren’t just concerned with tracking that rocks fell from buildings, but wanted to identify the force that explained why that occurred (gravity). Similarly, social scientists aren’t just concerned with knowing what percentage of people are in poverty (although that is important) they want to identify the cause of poverty so that those conditions can be changed.

My poll might find that 46% of Americans plan to vote. What academic research is concerned with is the ‘why?’ Why did 46% say that, why did one person say yes and the other no, what does that help us to understand about the society? What we want to understand is the causes of the phenomena we see every day so that we can better understand the world of tomorrow.

Let’s say we did a study and found that 32% of elementary age children are significantly overweight. That’s good to know, it gives everyone an idea of the status of the health of children at this moment. What would be more important to know is why. If we know why 32% of children are significantly overweight and the other 68% aren’t, we can make changes that affect the future. Is it a lack of recess in schools, do children not have enough access to fruits and vegetable, are the foods they’re eating changing – understanding why is just as important as knowing the what, so that we know where to make changes.

Change is the only constant. I do most of my research on urban policy, which sort of means I study cities and the changes they undergo. If I looked at data on all of the neighborhoods in a city a decade ago and look again a decade later some would have gotten richer and others would have gotten poorer.

Change in Income in Nashville 2000 to 2018

That map might look interesting, and it might be important for people living in those communities to know. But unless we can provide an explanation for the change, we haven’t really learned anything. Neighborhoods change. People change. Demographics change. Everything changes. Are the neighborhoods shaded darker going to keep getting richer, or will there be a return to the mean and they’ll get poorer in the next decade? Did something happen that changed the fate of those neighborhoods, or was it just random decisions by a lot of different actors that lead to a new geography of the city? Those questions might seem unnecessary. Some neighborhoods are getting poorer, they need more support! Who cares about the why!? But if we’re going to try and figure out what neighborhoods will get poorer in the future, or want to change the future, we have to understand the underlying causes of those changes. That’s what academic research is trying to untangle. Not just what’s going on, but why, so that we can try to get more control of the future. Thus, academic research involves original research, like applied research, but is focused on developing theories as much as it is getting an answer to a question.

3.2 What’s theory got to do with it?

Let’s first define theory , because the way it’s used in science and the way it’s used in everyday conversation are slightly different. In everyday conversation you might hear the word theory used as the equivalent of “hunch” or “idea”: “oh, that’s just your theory”. In the sciences it means a bit more. A theory in the sciences is a well-substantiated explanation for a set of observations. A law is accepted as true by scientists, it is confirmed fact. A theory is on its way to becoming a law, it just needs more observations to be fully accepted.

The social sciences have plenty of theories, and fewer explanations that can be accepted as laws because as we discussed in the previous chapter humans just make it hard to get consistent findings.

For instance, researchers in in political science and public administration often use:

• elite theory which posits that a small minority of elites be they the wealthy or those that drive the creation of policy, holds most of the power in society even within democratic systems.
• democratic peace theory argues that democracies generally do not go to war or have armed conflicts with other democracies
• representative bureaucracy argues that governing bodies throughout society should be representative of the community they serve or govern.

Those theories and others get applied in different studies to continue testing them and refining them. For instance, I might want to study whether counties with growing Latinx/Latino/Latina populations see changes in who is elected for county wide offices. If I just do that research and report the results it could just be applied research. The public has an interest in knowing who their elected representatives are. If I use the research to test representative bureaucracy as a way of explaining my results, my research is now venturing into academic territory. The theoretical argument is all about explaining whatever I find, whether representation changes in those counties or not.

3.3 Inputs to research

The most difficult thing to accept and internalize in developing a research project is that it is iterative, not linear. We like linear processes like following a recipe. You can follow those steps and you get the end and then you have cookies. Following the research recipe isn’t that clean. It will be a lot of one step forward two steps back, which is progress, but can be frustrating.

Research values novelty. One should not spend a lot of time gathering original data in order to answer a question that has already been answered. So in order to develop a research question worth researching, it is really important to understand what has already been studied on that topic. I’ve learned this from experience, both in my own research and teaching, but you really can’t develop a good research question without doing a lot of reading.

If you’re starting to develop a research project, start with the things you care about. You’re going to spend a lot of time studying it and reading about the subject – it should be something you enjoy. Think about the things you observe in the world, the odd processes or changes you see around you. And think about the things you know a lot about. Whatever your interests are, whether they’re video games or hiking or reading, try to embed that interest in the research.

But again, you have to do a lot of reading. If I was walking down the street and someone stopped me and forced me to come up with a research question in sociology I would surely stumble and I might eventually stammer something out like “why do people leave online communities?” I don’t know much about that, it sounds kind of interesting. And online communities are a somewhat recent development (in comparison to say churches) so maybe the research will be interesting. Almost certainly not. I can guarantee a lot of research has been done on that question. That doesn’t mean I have to abandon the idea, it just means I need to start by reading all the research that has been done, and continue to refine my question. As I read thorough the literature on online group membership I’ll probably find answers to questions that never occurred to me, and as I read I might find questions that haven’t been answered yet.

A similar pattern occurred as I began my PhD. I wanted to study big important questions, and when I got to my program I was given a lot of freedom to decide what I would do research on. I decided I’d start by answering a question I constantly heard debated by policymakers: do sports stadiums create economic activity. I was going to be the researcher that answered the question. But pretty immediately I discovered that, actually, about 100 other researchers had already answered that question (it’s a definitive no, stadiums don’t create any economic activity, they’re a really bad deal for cities). The fact that the public didn’t regard it as a settled question doesn’t mean that researchers hadn’t already answered it. Did I give up? No, I kept reading the literature and I started to uncover related questions that hadn’t been answered yet. I ended up doing my dissertation on minor league baseball stadiums and their impact on the neighborhoods where they are located, which wasn’t the most important question ever but it hadn’t been answered before.

One recommendation I would make as you start reading the literature in a given area is to keep an annotated bibliography . As you read new articles to down a few sentences summarizing them - those few sentences can often be gleaned just from the abstract of the article. That way you’ll have a record of what you read, and as the project changes you can go back and wont have to search through the literature over and over. As your project begins to gain focus, you can pull the relevant articles from your annotated bibliography and begin to build out your paper. I would also recommend using a computer program like Zotero where you can save the details of articles and generate the bibliography of papers later. I don’t know the difference between MLA or APA or any system, because I make the computer do it for me. In the video below I walk through these things with a brief demonstration for anyone starting out a new research project.

One problem you will face in reading about your topic is accessing the articles that are relevant to your topic. If you go to a journals webpage, you’ll see that you can buy the article for probably $30. $30! That’s as much as a book, and you probably won’t even be sure if the article is good before buying it. There have been a lot of arguments made against these paywalls particularly given that taxpayers fund most of the research that is then sent to these journals. Researchers aren’t paid directly for the researcher they publish, which we give the copyright over to journals because it helps us to get tenure; journals then charge for people to read the research, and universities pay subscription fees so their researchers have access. It’s a circular economy, with me working for free, and journals making out like bandits. When you find an article you want to read see if you can access it through your library, but you can also check a few different websites where people post articles in order to “free” them. You can also just reach out to the author of the article and request a copy. Authors generally have the right to share the article even though they’ve given the journal the copyright over its contents, and most researchers are just happy to see someone engage with their work.

Once you’ve got a research question that’s worth studying and hasn’t been answered before, it’s time to answer it yourself. That’ll mean collecting data though, to answer that question. I should probably start by trying to figure out if data already exists that was collected by someone else first. You can do a lot of research in political science based on surveys that are posted online by Gallup or Pew. It’ll be easier to do the research if I can find the data from the start. If I can’t find the data, I’ll be faced with the choice of changing my research question to match the data that’s available or collecting my own data. Collecting your own data can be expensive and difficult, but if you’re interested in breaking new ground in your research it might be necessary.

The two steps are thus iterative. Knowing the literature on a topic will help you to develop new questions and lead you towards data necessary to answer them. But looking at data may help you to generate new questions and lead you back to the literature to understand how it can be used.

As you settle on a research question, and begin to look around for data to answer it, it is good to be explicit about your unit of analysis . The unit of analysis is whatever entity of body you wish to be able to answer your question about at the end of your study. Related, there is also the unit of observation , which is whatever unit you are measuring phenomena at. The unit of analysis and observation can be the same (they often are), but they can also be different.

Your unit of analysis (and observation) can be nations, cities, neighborhoods, individuals, or any other such grouping. Let’s use a few examples. If our research question is ‘why are some nations rich?’ we can answer that by collecting data for different nations, or we could use survey data about the individuals within different countries to make a comparison. Our unit of analysis is the same (countries), but our unit of observation (countries in the first, individuals in the second) can change.

Often we can study similar subjects using different units of observation or analysis. If I want to broadly study volunteering, I could collect data to understand volunteering rates for individuals, cities, states, or countries. The unit of observation will all depend upon what data I either collect or is available. And the unit of analysis can change as well, because I might want to study predictors of why some individuals volunteer and others don’t, or I may want to understand why different countries have different rates of volunteering. Which is all to say that it’ll depend on what you’re actually studying, but you should be explicit from the start about who you are studying.

3.5 Writing research

This is sort of where I get frustrated with myself as a teacher, or more specifically frustrated at myself for you. I just laid out three types of research. One you definitely do, which is secondary research. The second, applied research, is something you’ll see in the world all around you, and there’s some chance you might end up doing in your professional life. And the third, academic research, is generally inaccessible, uncommon, and probably not something you’ll ever do in your life. And yet, here we are, in a class on research, about to start talking about how to write a highly structure research paper using a format you’ll never use again.

Why? Why am I going to do that? In part it’s so that you can better understand the field you’re studying. It’s important to understand what it means not just to be curious about politics or sociology, but to understand what it means to study that field.

Beyond that, the best way to learn something new is to break it apart. This will be a bit like learning to drive by first building a car from parts. You could just move straight to secondary research or driving the car, but for you to really understand why things are working or where a breakdown might be, you have to understand the underlying parts. Each part of your car is important for getting you from point A to B, and each step that goes into research is important to getting you from your question to the right answer.

So when you see a headline in the future like

You’ll be able to better understand how that headline was made. The people that wrote that headline were using some academic research that is being translated to the public to use as secondary research. Where did it come from though, what did the researchers do to know that was the right answer? If it’s good research, they probably followed a process like what we’re about to lay out.

3.5.1 Introduction

If you look at published research in an academic journal it will typically follow a basic structure with 5 sections. The introduction explains the subject of your research and clearly identifies your research question. It provides a bit of background about the subject the current relevancy of it or maybe recent events that heightened its importance.

A good introduction thus has two purposes. First, it should explain to the reader what the paper is about. The thing you learn as you continue to write is the value of being clear in the introduction. Tell the reader what you do in the paper, the order of information you’re going to present, and what they takeaway is going to be. There shouldn’t be any surprise endings or twists. Just give them everything up front.

You can see that is done in the article excerpted and annotated below. This is from an article I published in 2020 Evaluating the impact of short-term rental regulations on Airbnb in New Orleans . The title should generally give you an idea of what the paper is about. It’s not the best paper I’ve ever written, but it’s short and so it’s easy to identify the structure of what I’m describing there. Read the complete introduction below to see how I describe the purpose of the paper in a direct manner with some background to prepare the reader.

3.5.2 Literature Review

There are two themes that should be described in any literature review . The two aren’t separate sections, they’re both intertwined.

• What has been done in the area of your research before
• What I need to know as a reader to understand what you’re going to do.

You want to prove to the reader that you’re aware of what’s been done in the area of your research before so they’ll believe your research is informed and new. The worst feedback you can get from a reviewer is that someone has already done the same study you’re attempting to publish. With any research question you identify you’ll find that a lot has been done before, and that’s fine. But describe what has been done so that I can better understand what makes yours different or unique.

And you’re also trying to make sure I can understand the background of your topic. What are the key words you’re going to be using? How have other people studied the issue? It’s all the background I need to understand your new contribution. Imagine you’re explaining a movie to someone so that they can see the sequel with you. Who are the main characters, what was the story, where did it leave off? Get them excited to see the sequel because you’re going to finally answer the question that was left lingering by all those past researchers!

You’ll want to use the literature you review to build hypotheses for your article. A hypothesis is a statement of what you expect to find. Hypothesis: toddlers that drink milk will be taller as adults.

That statement about toddlers and milk might be right or wrong, and that’s okay! That’s what the paper is building towards, proving whether the hypothesis is correct or not. Because right or wrong, if that hypothesis hasn’t been tested before we’re learning something new. But the hypothesis will be a lot better and more reasonable if it’s based on existing literature. Why would I think milk would help toddlers grow? I’d want to base that prediction on studies about milks effect on the bodies and what non-milk drinkers might consume and anything else that would be relevant.

The literature review for the paper below is 10 paragraphs in all, but I want to just pull out two. What the literature review is trying to do is just get the reader ready. Again, it’s the “previously on…” intro to your favorite show.

3.5.3 Methodology

The introduction and literature review are all used to set up your new study. Now you can explain how you’ll do whatever new and impressive thing you’re about to do in the methodology section. Describe the data you collected and how you’ll analyze it. Essentially you want to draw the reader a road map so they can understand exactly how to redo your study. It’s similar to the chain of custody in evidence for criminal cases. How did you find this information, where did it come from, why should we trust that this data is good? You don’t just wake up and find data on the side of the road, it had be collected somehow and the way it’s collected could impact whether we trust it or not.

One of the big concerns in science is replicability. We’ll talk about that later, but the study design section is a nod towards it. If I wanted to redesign your study, recreate the experiment with similar subjects in a similar setting, how would I do that? In science, we don’t just trust your word for how you generated your results. Tell us how you generated them, so that we can consider whether there were any potential problems present.

You can start writing the methodology section as you begin the research. As you start you should have a design in mind at the beginning of any project, including what data you are going to collect, how will you collect it, and how you will analyze it. Answers to those questions might evolve as you conduct the research, but you can begin by setting it out as a research design , describing your reserach plan, and then revise it as you write the paper. Regardless, your collection and analysis should be guided by a research design, whether formally written or just a mental plan.

Where did you get the data, and what are you gonna do with it now that you have it? What’s written below may or may not make sense at this stage, but I’m including it just to illustrate the way that researchers attempt to write clearly and directly in describing their studies.

3.6 Results

Once you’ve explained how you conducted your study, you can go ahead and tell the reader what you found in the results section. Exactly what you’ll say here will differ based on what you studied, but there isn’t a lot more to say at this stage.

3.6.1 Discussion

The paper then concludes with a discussion of the significance of the results and their implications. You found something, why do we care? How does that change the field? Should policymakers react? Should scientists react? You’ll often start with an overview of what the paper found, before launching into some of the more specific takeaways you want readers to get.

3.7 Summary

This chapter has covered some of the different ways we do research, and one way (a formal paper) that we report our research. It might seem a little overwhelming to think about how to write up your research results before you even know how to do research. And that’s fine, this is something of getting a fly over of the forest before we start to look more closely at the trees. It’s good to have an idea of what your final paper might look like, before we get started. Now we can begin to get a little more detailed about how we fill in all those words between the title and the final period on a research paper.

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Home » Research Methods – Types, Examples and Guide

Research Methods – Types, Examples and Guide

Table of Contents

Research Methods

Definition:

Research Methods refer to the techniques, procedures, and processes used by researchers to collect , analyze, and interpret data in order to answer research questions or test hypotheses. The methods used in research can vary depending on the research questions, the type of data that is being collected, and the research design.

Types of Research Methods

Types of Research Methods are as follows:

Qualitative research Method

Qualitative research methods are used to collect and analyze non-numerical data. This type of research is useful when the objective is to explore the meaning of phenomena, understand the experiences of individuals, or gain insights into complex social processes. Qualitative research methods include interviews, focus groups, ethnography, and content analysis.

Quantitative Research Method

Quantitative research methods are used to collect and analyze numerical data. This type of research is useful when the objective is to test a hypothesis, determine cause-and-effect relationships, and measure the prevalence of certain phenomena. Quantitative research methods include surveys, experiments, and secondary data analysis.

Mixed Method Research

Mixed Method Research refers to the combination of both qualitative and quantitative research methods in a single study. This approach aims to overcome the limitations of each individual method and to provide a more comprehensive understanding of the research topic. This approach allows researchers to gather both quantitative data, which is often used to test hypotheses and make generalizations about a population, and qualitative data, which provides a more in-depth understanding of the experiences and perspectives of individuals.

Key Differences Between Research Methods

The following Table shows the key differences between Quantitative, Qualitative and Mixed Research Methods

Examples of Research Methods

Examples of Research Methods are as follows:

Qualitative Research Example:

A researcher wants to study the experience of cancer patients during their treatment. They conduct in-depth interviews with patients to gather data on their emotional state, coping mechanisms, and support systems.

Quantitative Research Example:

A company wants to determine the effectiveness of a new advertisement campaign. They survey a large group of people, asking them to rate their awareness of the product and their likelihood of purchasing it.

Mixed Research Example:

A university wants to evaluate the effectiveness of a new teaching method in improving student performance. They collect both quantitative data (such as test scores) and qualitative data (such as feedback from students and teachers) to get a complete picture of the impact of the new method.

Applications of 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, surveys, and observational studies to understand how people behave in different situations, how they respond to different stimuli, and how their brains process information.
• Sociology : Sociologists use research methods to study social phenomena, such as social inequality, social change, and social relationships. Researchers may use surveys, interviews, and observational studies to collect data on social attitudes, beliefs, and behaviors.
• Medicine : Research methods are essential in medical research to study diseases, test new treatments, and evaluate their effectiveness. Researchers may use clinical trials, case studies, and laboratory experiments to collect data on the efficacy and safety of different medical treatments.
• Education : Research methods are used in education to understand how students learn, how teachers teach, and how educational policies affect student outcomes. Researchers may use surveys, experiments, and observational studies to collect data on student performance, teacher effectiveness, and educational programs.
• Business : Research methods are used in business to understand consumer behavior, market trends, and business strategies. Researchers may use surveys, focus groups, and observational studies to collect data on consumer preferences, market trends, and industry competition.
• Environmental science : Research methods are used in environmental science to study the natural world and its ecosystems. Researchers may use field studies, laboratory experiments, and observational studies to collect data on environmental factors, such as air and water quality, and the impact of human activities on the environment.
• Political science : Research methods are used in political science to study political systems, institutions, and behavior. Researchers may use surveys, experiments, and observational studies to collect data on political attitudes, voting behavior, and the impact of policies on society.

Purpose of Research Methods

Research methods serve several purposes, including:

• Identify research problems: Research methods are used to identify research problems or questions that need to be addressed through empirical investigation.
• Develop hypotheses: Research methods help researchers develop hypotheses, which are tentative explanations for the observed phenomenon or relationship.
• Collect data: Research methods enable researchers to collect data in a systematic and objective way, which is necessary to test hypotheses and draw meaningful conclusions.
• Analyze data: Research methods provide tools and techniques for analyzing data, such as statistical analysis, content analysis, and discourse analysis.
• Test hypotheses: Research methods allow researchers to test hypotheses by examining the relationships between variables in a systematic and controlled manner.
• Draw conclusions : Research methods facilitate the drawing of conclusions based on empirical evidence and help researchers make generalizations about a population based on their sample data.
• Enhance understanding: Research methods contribute to the development of knowledge and enhance our understanding of various phenomena and relationships, which can inform policy, practice, and theory.

When to Use Research Methods

Research methods are used when you need to gather information or data to answer a question or to gain insights into a particular phenomenon.

Here are some situations when research methods may be appropriate:

• To investigate a problem : Research methods can be used to investigate a problem or a research question in a particular field. This can help in identifying the root cause of the problem and developing solutions.
• To gather data: Research methods can be used to collect data on a particular subject. This can be done through surveys, interviews, observations, experiments, and more.
• To evaluate programs : Research methods can be used to evaluate the effectiveness of a program, intervention, or policy. This can help in determining whether the program is meeting its goals and objectives.
• To explore new areas : Research methods can be used to explore new areas of inquiry or to test new hypotheses. This can help in advancing knowledge in a particular field.
• To make informed decisions : Research methods can be used to gather information and data to support informed decision-making. This can be useful in various fields such as healthcare, business, and education.

Advantages of Research Methods

Research methods provide several advantages, including:

• Objectivity : Research methods enable researchers to gather data in a systematic and objective manner, minimizing personal biases and subjectivity. This leads to more reliable and valid results.
• Replicability : A key advantage of research methods is that they allow for replication of studies by other researchers. This helps to confirm the validity of the findings and ensures that the results are not specific to the particular research team.
• Generalizability : Research methods enable researchers to gather data from a representative sample of the population, allowing for generalizability of the findings to a larger population. This increases the external validity of the research.
• Precision : Research methods enable researchers to gather data using standardized procedures, ensuring that the data is accurate and precise. This allows researchers to make accurate predictions and draw meaningful conclusions.
• Efficiency : Research methods enable researchers to gather data efficiently, saving time and resources. This is especially important when studying large populations or complex phenomena.
• Innovation : Research methods enable researchers to develop new techniques and tools for data collection and analysis, leading to innovation and advancement in the field.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

StatPearls [Internet].

Human subjects research design.

Marlon L. Bayot ; Grace D. Brannan ; Janelle M. Brannan ; Steven Tenny .

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Last Update: August 14, 2023 .

• Definition/Introduction

Human subjects research is a heavily regulated type of research, hence this paper will start with two critical definitions. The US Department of Health and Human Services (HHS) Code of Federal Regulations, 45 CFR 46, provides the following definitions: [1]  “A living individual about whom an investigator (whether professional or student) conducting research:

• Obtains information or biospecimens through intervention or interaction with the individual, and uses, studies, or analyzes the information or biospecimens; or
• Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens."

Research means “a systematic investigation, including research development, testing and evaluation, designed to develop or contribute to generalizable knowledge.” Human subjects research is at the intersection of these two federal definitions and must obtain Institutional Review Board approval before starting, regardless of the type of design involved. The topic of a human research study varies and can include building a theory or hypothesis, determining patient satisfaction, or testing a medication, tool, device, process, or health intervention, to name a few. 

Research studies are classified into a qualitative study, a quantitative study, or a combination of both, called a mixed-methods study. [2] [3]  Qualitative studies gather non-numerical data, whereas quantitative research involves collecting numerical data. Other classifications of research studies exist depending on the purpose and utility of the study, [4]  examples include health systems research and operational research. [5] This review will be limited to the most common quantitative and qualitative research designs.

Quantitative Research

A research study can be done to describe variables and/or to determine the association of test and outcome variables regarding the research topic. [1] Quantitative research studies also subdivide into either interventional studies or non-interventional (observational) studies.  For interventional research studies, the researcher performs some intervention or manipulation of one or more groups in the research study and compares the outcomes to the other groups to help analyze the variables of interest. It may or may not be randomized, although a randomized controlled trial is considered a gold standard, as randomization of patients into the treatment groups reduce bias. Interventional studies apply to medical drugs, biologics, and devices.

For observational or non-interventional research studies, the investigator gathers data for identified variables of interest without any intervention or outside influence by the investigator on the groups under study. Cohort, cross-sectional, and case-control are the common types. [2]

A cohort study involves longitudinally following a group or groups of population with certain known exposures to determine who develops certain diseases or illnesses. This type of study could establish causal relationships between exposure and outcomes such as illness. [2] A cross-sectional study deals with a population at a given point in time as opposed to longitudinally and could provide information such as prevalence. Case-control studies compare populations with and without the exposure to determine if an illness will develop and at what rate in either group. A classic example is comparing smokers and non-smokers to determine which group develops lung cancer.

Qualitative Research

Qualitative research aims to answer the more open-ended questions that arise during the research process. Rather than trying to answer quantitative ‘how much’ or ‘how many’-type questions, qualitative research seeks to answer ‘how’ and ‘why’ questions. [3] Qualitative research often aims to understand and explain why or how a phenomenon is the way it is in order to provide insights and explanations of real-life problems and experiences. [4] Qualitative research can be used alone, in conjunction with quantitative research in mixed methods research, or as a way to explain the findings of a quantitative study because a quantitative study might show that there is a correlation between two things, but a qualitative study could then tell why that correlation exists, and not just that it does indeed exist.

There are many approaches used for qualitative research. Some of the most common are ethnography, grounded theory, phenomenology, and narrative research. [3] Ethnography is an approach that involves the researcher to be immersed in their participant’s environment, and through this immersion, collect insight into the actions, behaviors, and events that could aid them in their research. [4]  Grounded theory is an approach where the researcher observes the population of interest in order to develop a theory that explains the topic of interest. [3] Phenomenology as an approach emphasizes the importance of the ‘lived experience’ for explaining phenomena. [4] Grounded theory and phenomenology are similar, but grounded theory focuses on observation as a whole to create a theory, whereas phenomenology focuses on the perspective of participants themselves to explain why or how something happens. Lastly, narrative research showcases one of qualitative research’s strengths, the ability to tell a story. When research includes the perspective of the individuals involved, it can create robust theory-building because it takes into account the real-life implications and impacts of phenomena in a way that quantitative research often lacks. Data for qualitative research is collected in many ways, including interviews, focus groups, case studies, and medical record reviews.

Mixed Methods Research

In some cases, a combination of both qualitative and quantitative methods, or what is called a mixed-methods research is performed. Mixed methods approaches that combine qualitative and quantitative research can allow for hypothesis generation and hypothesis testing to help try to answer questions in a more well-rounded way. This is usually done to get the benefits of both numerical and non-numerical information to answer the research questions on hand. For example, a cross-sectional study found that young teens are vaping at a high rate. For further elucidation of the reasons why these teens vape, a subsequent focus group could be performed. 

• Issues of Concern

One of the primary concerns in doing research is the identification and formulation of the research problem (i.e., research question). [5]  The research problem should be ethical, researchable, significant, and feasible. In medicine, the goal of the research is not only to add relevant findings to the scientific body of knowledge but also to provide a beneficial, useful contribution to stakeholders, particularly the patients.

The second area of concern for research studies is selecting the correct research study to perform.  Many times descriptive and qualitative research must first take place to produce a robust, significant, and feasible research hypothesis for later quantitative research methods. [6]   Additionally, different research study types have different levels of strength and risk of bias as delineated in the hierarchy of research study designs. [7]  

• Clinical Significance

The significance of research studies and its findings collectively support both clinical and public health needs. The discovery of new medicines and new treatment modalities for specific diseases is possible using randomized clinical (control) trials, more commonly termed as RCTs. [8] Public health, both as medical and social science, can choose from a wide range of qualitative studies, descriptive, analytic, community-based trials [9] , and operations researches, among others, to explore and describe the characteristics of certain groups of populations and its associations to the disease process or a particular health intervention, yielding findings that will inform policymakers and stakeholders.

In clinical settings, case studies and case series can be used by clinicians, surgeons, and other clinical specialists to scientifically document and describe the occurrence of rare diseases. [10]  Researchers can perform studies to determine the association of exposure variables or risk factors in rare diseases or cohort studies to investigate rare exposure variables present in the study population. Meanwhile, studies such as meta-analysis and systematic review are good choices for researchers who want to summarize the results of previous research findings, in quantitative and qualitative means, respectively. [11] [12] Mixed methods are employed to combine and exhaust the utility of the research type or study design combinations (e.g., quantitative and qualitative studies). [13]

Research studies can be both simple and complex; thus, they can be performed in several ways, which must be consistently systematic and scientific. The acquisition of new research findings will eventually find utility in the application of evidence-based medicine (EBM). [14] Research studies must be carried out within the walls of medical ethics, free of bias, and primarily geared towards the welfare of our patients rather than just merely the expedition of science. [15]

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Disclosure: Marlon Bayot declares no relevant financial relationships with ineligible companies.

Disclosure: Grace Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Janelle Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Bayot ML, Brannan GD, Brannan JM, et al. Human Subjects Research Design. [Updated 2023 Aug 14]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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Types of Research – Methods Explained with Examples

In the ever-evolving world of academia and professional inquiry, understanding the various types of research is crucial for anyone looking to delve into a new study or project. Research, a systematic investigation aimed at discovering and interpreting facts, plays a pivotal role in expanding our knowledge across various fields.

From qualitative research , known for its in-depth analysis of non-numerical data, to quantitative research , which focuses on numerical data and statistical approaches, the spectrum of research types is broad and diverse. We also explore descriptive research , which aims to accurately and systematically describe a population, situation, or phenomenon, and analytical research, which goes a step further to understand the ‘why’ and ‘how’ of a subject.

What is Research?

Research is the process of studying a subject in detail to discover new information or understand it better. This can be anything from studying plants or animals, to learning how people think and behave, to finding new ways to cure diseases. People do research by asking questions, collecting information, and then looking at that information to find answers or learn new things.

Types of Researches Glance

This table provides a quick reference to understand the key aspects of each research type.

Types of Researches Methodology

1. qualitative.

Qualitative research is a methodological approach primarily used in fields like social sciences, anthropology, and psychology. It’s aimed at understanding human behavior and the motivations behind it. Unlike quantitative research that focuses on numbers and statistics, qualitative research delves into the nature of phenomena through detailed, in-depth exploration. Here’s a more detailed explanation:

Definition and Approach: Qualitative research focuses on understanding human behavior and the reasons that govern such behavior. It involves in-depth analysis of non-numerical data like texts, videos, or audio recordings.

Key Features:

• Emphasis on exploring complex phenomena
• Involves interviews, focus groups , and observations
• Generates rich, detailed data that are often subjective

Applications: Widely used in social sciences, marketing, and user experience research.

2. Quantitative Research

Quantitative research is a systematic approach used in various scientific fields to quantify data and generalize findings from a sample to a larger population. This type of research is fundamentally different from qualitative research in several ways:

Definition and Approach: Quantitative research is centered around quantifying data and generalizing results from a sample to the population of interest. It involves statistical analysis and numerical data .

• Relies on structured data collection instruments
• Large sample sizes for generalizability
• Statistical methods to establish relationships between variables

Applications: Common in natural sciences, economics, and market research.

3. Descriptive Research

Definition and Approach: This research type aims to accurately describe characteristics of a particular phenomenon or population.

• Provides detailed insights without explaining why or how something happens
• Involves surveys and observations
• Often used as a preliminary research method

Applications: Used in demographic studies, census, and organizational reporting.

4. Analytical Research

Definition and Approach: Analytical research goes beyond description to understand the underlying reasons or causes.

• Involves comparing data and facts to make evaluations
• Critical thinking is a key component
• Often hypothesis-driven

Applications: Useful in scientific research, policy analysis, and business strategy.

5. Applied Research

Definition and Approach: Applied research focuses on finding solutions to practical problems.

• Direct practical application
• Often collaborative , involving stakeholders
• Results are immediately applicable

Applications: Used in healthcare, engineering, and technology development.

6. Fundamental Research

Definition and Approach: Also known as basic or pure research, it aims to expand knowledge without a direct application in mind.

• Theoretical framework
• Focus on understanding fundamental principles
• Long-term in nature

Applications: Foundational in fields like physics, mathematics, and social sciences.

7. Exploratory Research

Definition and Approach: This type of research is conducted for a problem that has not been clearly defined.

• Flexible and unstructured
• Used to identify potential hypotheses
• Relies on secondary research like reviewing available literature

Applications: Often the first step in social science research and product development.

8. Conclusive Research

Definition and Approach: Conclusive research is designed to provide information that is useful in decision-making.

• Structured and methodical
• Aims to test hypotheses
• Involves experiments, surveys, and testing

Applications: Used in market research, clinical trials, and policy evaluations.

Difference between Qualitative And Quantitative Research

Here is detailed difference between the qualitative and quantitative research –

Understanding the different types of research is crucial for anyone embarking on a research project. Each type has its unique approach, methodology, and application area, making it essential to choose the right type for your specific research question or problem. This guide serves as a starting point for researchers to explore and select the most suitable research method for their needs, ensuring effective and reliable outcomes.

Types of Research – FAQs

What are the 4 main types of research.

There are four main types of Quantitative research:  Descriptive, Correlational, Causal-Comparative/Quasi-Experimental, and Experimental Research . attempts to establish cause- effect relationships among the variables. These types of design are very similar to true experiments, but with some key differences.

What are the types of research PDF?

APPLIED RESEARCH BASIC RESEARCH CORRELATIONAL RESEARCH DESCRIPTIVE RESEARCH ETHNOGRAPHIC RESEARCH EXPERIMENTAL RESEARCH. EXPLORATORY RESEARCH

What are the 5 main purpose of research?

The primary purposes of basic research (as opposed to applied research) are  documentation, discovery, interpretation, and the research and development (R&D) of methods and systems for the advancement of human knowledge .

Can I be sure that my assignment paper will be plagiarism-free?

You can be 100% sure about the content of your assignment when done by a professional and genuine assignment maker. Most companies focus on providing the best and unique content so that they can attract more returning customers.

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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.

Read More About

Sayed A , Ross JS , Mandrola J , Lehmann LS , Foy AJ. Industry Payments to US Physicians by Specialty and Product Type. JAMA. Published online March 28, 2024. doi:10.1001/jama.2024.1989

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New Research Says This Type of Exercise Can Offer Relief for Chronic Back Pain

A lthough it’s often characterized as an annoyance, chronic lower back pain can bring serious repercussions—in fact, the World Health Organization (WHO) notes it’s the single leading cause of disability worldwide. Prevalence increases with age, but the WHO reports that lower back pain can be experienced at any age, and the highest number of cases occur between the age of 50 to 55 years.

A new study in the Journal of Orthopaedic Research suggests there may be one non-pharmaceutical approach to consider: a regular yoga practice.

Researchers in Italy looked at how eight sessions of yoga done over four weeks affected 10 women with chronic lower back pain , and 11 women without the issue. At the end of the series, those in the back pain group showed significant reductions in self-reported pain intensity.

All the participants showed improvements in spinal flexion, but that boost was particularly notable among those with chronic pain, since they tended to have less mobility in the spine at the start of the yoga practice, according to lead author Alessandro de Sire , M.D., researcher at the University of Catanzaro in Italy.

Given the small number of participants and limited timeframe, he tells Bicycling that more research needs to be done to assess yoga’s long-term effects on lower back pain. However, he adds that the results are intriguing because they represent a potential option in the management of chronic back pain .

Even doing yoga remotely—at home, doing an online class, or using videos—may have that effect, he says. In the recent study, participants did only one class in person, and the rest were done online.

While the movements themselves are useful, he adds that aspects unique to yoga likely contributed to the results as well. The breathing exercises and mindfulness practices incorporated in yoga can also influence pain perception and spinal flexion, the researchers noted in the study.

“Both deep diaphragmatic breathing techniques and mindfulness practices might enhance pain coping strategies, decrease pain catastrophizing, and improve overall psychological wellbeing,” says de Sire.

Yoga Poses for Back Pain Relief

Although numerous yoga poses may be helpful for easing muscle tightness throughout the body, some may be particularly useful for targeting lower-back tension, according to Rachel Hirsch , registered yoga instructor and founder of Empowered Yoga in Los Angeles. She tells Bicycling these four are especially beneficial, and they were also part of the yoga sequence used in the recent study.

Why it works: “This is a great movement for those with back pain, since it improves blood flow, as well as increases mobility and flexibility in the spine,” says Hirsch. “We often spend a lot of time sitting, which can compress the low back; this can serve as a counterbalance.”

How to do it:

• Start in tabletop position, on hands and knees, shoulders over wrists and hips over knees.
• Inhale to lift gaze and arch spine.
• On exhale, round back, tuck tailbone and move chin to chest.
• Move through these two postures, articulating the spine, for 10 full breaths.

2. Bridge Pose

Why it works: This pose strengthens the back, glutes , and hamstrings while also stretching the front of the body, according to Hirsch. “Mindfully strengthening your back muscles in this way will allow you to relieve tension and improve posture ,” she says. “Similar to cat cow, bridge pose may also improve flexibility in the spine.”

• Lay faceup, knees bent, and feet hip-width apart. Arms at sides, palms flat on the ground.
• On an inhale, press into arms, hands, and feet to lift hips. Keep the gaze up.
• Hold top position for 3 full breaths.
• Slowly lower down.
• Repeat. Do 3 reps.

3. Spinal Twist

Why it works: Any kind of gentle twist in yoga can help with back health, and by lying down, you can feel more supported. “This will help to relieve back pain and can encourage increased spinal mobility, which will also assist with relieving pain over time,” says Hirsch.

• Lay faceup, knees bent and feet on the floor. Bring arms out to a T-shape, with palms up.
• Let legs fall over to the left, as far as they can go before right shoulder comes off the ground.
• Hold for 5 breaths.
• Repeat on the other side.

4. Child’s Pose

Why it works: “This pose gently stretches the spine, potentially decreasing back and shoulder pain,” said Hirsch. “It also helps to relieve stiffness in your hips and pelvis, which can contribute to low back pain.”

• From tabletop position, bring knees apart and feet together so big toes are touching.
• Gently sit back toward feet, and reach arms straight in front of you. Alternately, you can stack the arms and rest forehead on hands.

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Computational Toxicology and Exposure Communities of Practice - Linkages between AOP key events with in vitro DNT assays: Examples of GABAergic and Glutamatergic modes of action

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Who:   Emily Pitzer, EPA ORD Center for Public Health and Environmental Assessment

When:  May 2, 11 – 12 p.m. ET

Where:  Please register via  Zoom .  Don't forget to download the calendar hold which contains your personalized Zoom link. You will need this link to join the webinar. 

Topic overview:

Neurodevelopment is a period vulnerable to various insults, including those produced by environmental compounds, and an understanding of these effects continues to be needed. Although in vitro New Approach Methodologies (NAMs) are being developed to foster efficient screening for both neurotoxicity (NT) and developmental neurotoxicity (DNT), reliability of these methods for regulatory purposes is necessary. Currently there is indication of alignment of DNT NAMs with terms used in NT/DNT Adverse Outcome Pathways (AOPs) found on the Wiki site, as seen in key events such as “cell injury/death”, “decreased synaptogenesis”, or “decreased neuronal network function”. Here we aim to assess the unique protein signatures following developmental or acute exposures to known neurotoxicants in Long Evans rats, which can then be applied to an AOP framework as biological key events and further work to develop and show reliability of in vitro NAMs.

• Chemical Safety Research Home
• Chemical Evaluation & Characterization
• Complex Systems Science
• Translation, Training, & Tools
• New Approach Methodologies Research
• Chemical Research to Inform Decision Making
• Collaborative Agreements