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Types of research papers

what are the types of research papers

Analytical research paper

Argumentative or persuasive paper, definition paper, compare and contrast paper, cause and effect paper, interpretative paper, experimental research paper, survey research paper, frequently asked questions about the different types of research papers, related articles.

There are multiple different types of research papers. It is important to know which type of research paper is required for your assignment, as each type of research paper requires different preparation. Below is a list of the most common types of research papers.

➡️ Read more:  What is a research paper?

In an analytical research paper you:

  • pose a question
  • collect relevant data from other researchers
  • analyze their different viewpoints

You focus on the findings and conclusions of other researchers and then make a personal conclusion about the topic. It is important to stay neutral and not show your own negative or positive position on the matter.

The argumentative paper presents two sides of a controversial issue in one paper. It is aimed at getting the reader on the side of your point of view.

You should include and cite findings and arguments of different researchers on both sides of the issue, but then favor one side over the other and try to persuade the reader of your side. Your arguments should not be too emotional though, they still need to be supported with logical facts and statistical data.

Tip: Avoid expressing too much emotion in a persuasive paper.

The definition paper solely describes facts or objective arguments without using any personal emotion or opinion of the author. Its only purpose is to provide information. You should include facts from a variety of sources, but leave those facts unanalyzed.

Compare and contrast papers are used to analyze the difference between two:

Make sure to sufficiently describe both sides in the paper, and then move on to comparing and contrasting both thesis and supporting one.

Cause and effect papers are usually the first types of research papers that high school and college students write. They trace probable or expected results from a specific action and answer the main questions "Why?" and "What?", which reflect effects and causes.

In business and education fields, cause and effect papers will help trace a range of results that could arise from a particular action or situation.

An interpretative paper requires you to use knowledge that you have gained from a particular case study, for example a legal situation in law studies. You need to write the paper based on an established theoretical framework and use valid supporting data to back up your statement and conclusion.

This type of research paper basically describes a particular experiment in detail. It is common in fields like:

Experiments are aimed to explain a certain outcome or phenomenon with certain actions. You need to describe your experiment with supporting data and then analyze it sufficiently.

This research paper demands the conduction of a survey that includes asking questions to respondents. The conductor of the survey then collects all the information from the survey and analyzes it to present it in the research paper.

➡️ Ready to start your research paper? Take a look at our guide on how to start a research paper .

In an analytical research paper, you pose a question and then collect relevant data from other researchers to analyze their different viewpoints. You focus on the findings and conclusions of other researchers and then make a personal conclusion about the topic.

The definition paper solely describes facts or objective arguments without using any personal emotion or opinion of the author. Its only purpose is to provide information.

Cause and effect papers are usually the first types of research papers that high school and college students are confronted with. The answer questions like "Why?" and "What?", which reflect effects and causes. In business and education fields, cause and effect papers will help trace a range of results that could arise from a particular action or situation.

This type of research paper describes a particular experiment in detail. It is common in fields like biology, chemistry or physics. Experiments are aimed to explain a certain outcome or phenomenon with certain actions.

what are the types of research papers

What are the Different Types of Research Papers?

types of research papers

There is a diverse array of research papers that one can find in academic writing. Research papers are a rigorous combination of knowledge, thinking, analysis, research, and writing. Early career researchers and students need to know that research papers can be of fundamentally different types. Generally, they combine aspects and elements of multiple strands or frameworks of research. This depends primarily on the aim of the study, the discipline, the critical requirements of research publications and journals and the research topic or area. Specifically, research papers can be differentiated by their primary rationale, structure, and emphasis. The different types of research papers contribute to the universe of knowledge while providing invaluable insights for policy and scope for further advanced research and development. In this article, we will look at various kinds of research papers and understand their underlying principles, objectives, and purposes.  

Different types of research papers

  • Argumentative Research Paper:  In an argumentative paper, the researcher is expected to present facts and findings on both sides of a given topic but make an extended and persuasive argument supporting one side  over  the other. The purpose of such research papers is to provide evidence-based arguments to support the claim or thesis statement taken up by the researcher. Emotions mustn’t inform the building up of the case. Conversely, facts and findings must be objective and logical while presenting both sides of the issue. The position taken up by the researcher must be stated clearly and in a well-defined manner. The evidence supporting the claim must be well-researched and up-to-date, and the paper presents differing views on the topic, even if these do not agree or align with the researcher’s thesis statement. 
  • Analytical Research Paper:  In an analytical research paper, the researcher starts by asking a research question, followed by a collection of appropriate data from a wide range of sources. These include primary and secondary data, which the researcher needs to analyze and interpret closely. Critical and analytical thinking skills are therefore crucial to this process. Rather than presenting a summary of the data, the researcher is expected to analyze the findings and perspectives of each source material before putting forward their critical insights and concluding. Personal biases or positions mustn’t influence or creep into the process of writing an analytical research paper. 
  • Experimental Research Paper:  Experimental research papers provide a detailed report on a particular research experiment undertaken by a researcher and its outcomes or findings. Based on the research experiment, the researcher explains the experimental design and procedure, shows sufficient data, presents analysis, and draws a conclusion. Such research papers are more common in fields such as biology, chemistry, and physics. Experimental research involves conducting experiments in controlled conditions to test specific hypotheses. This not only allows researchers to arrive at particular conclusions but also helps them understand causal relationships. As it lends itself to replicating the findings of the research, it enhances the validity of the research conducted. 

Some more types of research papers

In addition to the above-detailed types of research papers, there are many more types, including review papers, case study papers, comparative research papers and so on.  

  • Review papers   provide a detailed overview and analysis of existing research on a particular topic. The key objective of a review paper is to provide readers with a comprehensive understanding of the latest research findings on a specific subject. 
  • Case study papers  usually focus on a single or small number of cases. This is used in research when the aim is to obtain an in-depth investigation of an issue.  
  • Comparative research papers  involve comparing and contrasting two or more entities or cases that help to identify and arrive at trends or relationships. The objective of relative research papers is to increase knowledge and understand issues in different contexts. 
  • Survey research papers  require that a survey be conducted on a given topic by posing questions to potential respondents. Once the survey has been completed, the researcher analyzes the information and presents it as a research paper. 
  • Interpretative paper s  employ the knowledge or information gained from pursuing a specific issue or research topic in a particular field. It is written around theoretical frameworks and uses data to support the thesis statement and findings.  

Research papers are an essential part of academic writing and contribute significantly to advancing our knowledge and understanding of different subjects. The researcher’s ability to conduct research, analyze data, and present their findings is crucial to producing high-quality research papers. By understanding the different types of research papers and their underlying principles, researchers can contribute to the advancement of knowledge in their respective fields and provide invaluable insights for policy and further research.

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Although research paper assignments may vary widely, there are essentially two basic types of research papers. These are argumentative and analytical .

Argumentative

In an argumentative research paper, a student both states the topic they will be exploring and immediately establishes the position they will argue regarding that topic in a thesis statement . This type of paper hopes to persuade its reader to adopt the view presented.

 Example : a paper that argues the merits of early exposure to reading for children would be an argumentative essay.

An analytical research paper states the topic that the writer will be exploring, usually in the form of a question, initially taking a neutral stance. The body of the paper will present multifaceted information and, ultimately, the writer will state their conclusion, based on the information that has unfolded throughout the course of the essay. This type of paper hopes to offer a well-supported critical analysis without necessarily persuading the reader to any particular way of thinking.

Example : a paper that explores the use of metaphor in one of Shakespeare's sonnets would be an example of an analytical essay.

*Please note that this LibGuide will primarily be concerning itself with argumentative or rhetorical research papers.

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Genre and the Research Paper

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This handout provides detailed information about how to write research papers including discussing research papers as a genre, choosing topics, and finding sources.

Research: What it is.

A research paper is the culmination and final product of an involved process of research, critical thinking, source evaluation, organization, and composition. It is, perhaps, helpful to think of the research paper as a living thing, which grows and changes as the student explores, interprets, and evaluates sources related to a specific topic. Primary and secondary sources are the heart of a research paper, and provide its nourishment; without the support of and interaction with these sources, the research paper would morph into a different genre of writing (e.g., an encyclopedic article). The research paper serves not only to further the field in which it is written, but also to provide the student with an exceptional opportunity to increase her knowledge in that field. It is also possible to identify a research paper by what it is not.

Research: What it is not.

A research paper is not simply an informed summary of a topic by means of primary and secondary sources. It is neither a book report nor an opinion piece nor an expository essay consisting solely of one's interpretation of a text nor an overview of a particular topic. Instead, it is a genre that requires one to spend time investigating and evaluating sources with the intent to offer interpretations of the texts, and not unconscious regurgitations of those sources. The goal of a research paper is not to inform the reader what others have to say about a topic, but to draw on what others have to say about a topic and engage the sources in order to thoughtfully offer a unique perspective on the issue at hand. This is accomplished through two major types of research papers.

Two major types of research papers.

Argumentative research paper:

The argumentative research paper consists of an introduction in which the writer clearly introduces the topic and informs his audience exactly which stance he intends to take; this stance is often identified as the thesis statement . An important goal of the argumentative research paper is persuasion, which means the topic chosen should be debatable or controversial. For example, it would be difficult for a student to successfully argue in favor of the following stance.

Perhaps 25 years ago this topic would have been debatable; however, today, it is assumed that smoking cigarettes is, indeed, harmful to one's health. A better thesis would be the following.

In this sentence, the writer is not challenging the current accepted stance that both firsthand and secondhand cigarette smoke is dangerous; rather, she is positing that the social acceptance of the latter over the former is indicative of a cultural double-standard of sorts. The student would support this thesis throughout her paper by means of both primary and secondary sources, with the intent to persuade her audience that her particular interpretation of the situation is viable.

Analytical research paper:

The analytical research paper often begins with the student asking a question (a.k.a. a research question) on which he has taken no stance. Such a paper is often an exercise in exploration and evaluation. For example, perhaps one is interested in the Old English poem Beowulf . He has read the poem intently and desires to offer a fresh reading of the poem to the academic community. His question may be as follows.

His research may lead him to the following conclusion.

Though his topic may be debatable and controversial, it is not the student's intent to persuade the audience that his ideas are right while those of others are wrong. Instead, his goal is to offer a critical interpretation of primary and secondary sources throughout the paper--sources that should, ultimately, buttress his particular analysis of the topic. The following is an example of what his thesis statement may look like once he has completed his research.

This statement does not negate the traditional readings of Beowulf ; instead, it offers a fresh and detailed reading of the poem that will be supported by the student's research.

It is typically not until the student has begun the writing process that his thesis statement begins to take solid form. In fact, the thesis statement in an analytical paper is often more fluid than the thesis in an argumentative paper. Such is one of the benefits of approaching the topic without a predetermined stance.

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Research Papers

What is a research paper?

A research paper requires you to form an opinion on a topic, research and gain expert knowledge on that topic, and then back up your own opinions and assertions with facts found through your thorough research.

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Types of Research Papers   This guide discusses the different types of research papers that you might encounter in an academic setting.

How to Write a Research Paper  This article provides step-by-step guidance on how to write a research paper.

Argumentative Essays

What is an argumentative essay?

In this paper, you make an argument about a topic or subject and use evidence and analysis to prove your argument. Your main argument is also called a thesis statement .

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How to Write an Argumentative Essay   This article discusses the basics of writing an argumentative paper.

Exploratory Essays

What is an exploratory essay?

An exploratory essay considers a topic or problem and explores possible solutions. This type of paper also sometimes includes background about how you have approached the topic, as well as information about your research process. Whereas other types of essays take a concrete stance on an issue and offer extensive support for that stance, the exploratory essay covers how you arrived at an idea and what research materials and methods you used to explore it.

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How to Write an Exploratory Essay   This article covers the essentials of writing an exploratory essay.

Critical Analysis Essays

What is a critical analysis essay?

A critical analysis examines and evaluates someone else’s work, such as a book, an essay, or an article. It requires two steps: a careful reading of the work and thoughtful analysis of the information presented in the work.

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How to Write a Critical Analysis Essay   This resource discusses the details of critical analysis essays and provides tips for writing one.

Literature Reviews

What is a literature review?

A literature review is an assessment of sources on a chosen topic of research. The  four main objectives  of a literature review are:

  • Studying  the references of your research area
  • Summarizing  the main arguments
  • Identifying  current gaps, stances, and issues
  • Finally,  presenting  all of the above in a text

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How to Write a Literature Review   This guide defines literature reviews and offers strategies for constructing them.

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How To Write A Research Paper

Step-By-Step Tutorial With Examples + FREE Template

By: Derek Jansen (MBA) | Expert Reviewer: Dr Eunice Rautenbach | March 2024

For many students, crafting a strong research paper from scratch can feel like a daunting task – and rightly so! In this post, we’ll unpack what a research paper is, what it needs to do , and how to write one – in three easy steps. 🙂 

Overview: Writing A Research Paper

What (exactly) is a research paper.

  • How to write a research paper
  • Stage 1 : Topic & literature search
  • Stage 2 : Structure & outline
  • Stage 3 : Iterative writing
  • Key takeaways

Let’s start by asking the most important question, “ What is a research paper? ”.

Simply put, a research paper is a scholarly written work where the writer (that’s you!) answers a specific question (this is called a research question ) through evidence-based arguments . Evidence-based is the keyword here. In other words, a research paper is different from an essay or other writing assignments that draw from the writer’s personal opinions or experiences. With a research paper, it’s all about building your arguments based on evidence (we’ll talk more about that evidence a little later).

Now, it’s worth noting that there are many different types of research papers , including analytical papers (the type I just described), argumentative papers, and interpretative papers. Here, we’ll focus on analytical papers , as these are some of the most common – but if you’re keen to learn about other types of research papers, be sure to check out the rest of the blog .

With that basic foundation laid, let’s get down to business and look at how to write a research paper .

Research Paper Template

Overview: The 3-Stage Process

While there are, of course, many potential approaches you can take to write a research paper, there are typically three stages to the writing process. So, in this tutorial, we’ll present a straightforward three-step process that we use when working with students at Grad Coach.

These three steps are:

  • Finding a research topic and reviewing the existing literature
  • Developing a provisional structure and outline for your paper, and
  • Writing up your initial draft and then refining it iteratively

Let’s dig into each of these.

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what are the types of research papers

Step 1: Find a topic and review the literature

As we mentioned earlier, in a research paper, you, as the researcher, will try to answer a question . More specifically, that’s called a research question , and it sets the direction of your entire paper. What’s important to understand though is that you’ll need to answer that research question with the help of high-quality sources – for example, journal articles, government reports, case studies, and so on. We’ll circle back to this in a minute.

The first stage of the research process is deciding on what your research question will be and then reviewing the existing literature (in other words, past studies and papers) to see what they say about that specific research question. In some cases, your professor may provide you with a predetermined research question (or set of questions). However, in many cases, you’ll need to find your own research question within a certain topic area.

Finding a strong research question hinges on identifying a meaningful research gap – in other words, an area that’s lacking in existing research. There’s a lot to unpack here, so if you wanna learn more, check out the plain-language explainer video below.

Once you’ve figured out which question (or questions) you’ll attempt to answer in your research paper, you’ll need to do a deep dive into the existing literature – this is called a “ literature search ”. Again, there are many ways to go about this, but your most likely starting point will be Google Scholar .

If you’re new to Google Scholar, think of it as Google for the academic world. You can start by simply entering a few different keywords that are relevant to your research question and it will then present a host of articles for you to review. What you want to pay close attention to here is the number of citations for each paper – the more citations a paper has, the more credible it is (generally speaking – there are some exceptions, of course).

how to use google scholar

Ideally, what you’re looking for are well-cited papers that are highly relevant to your topic. That said, keep in mind that citations are a cumulative metric , so older papers will often have more citations than newer papers – just because they’ve been around for longer. So, don’t fixate on this metric in isolation – relevance and recency are also very important.

Beyond Google Scholar, you’ll also definitely want to check out academic databases and aggregators such as Science Direct, PubMed, JStor and so on. These will often overlap with the results that you find in Google Scholar, but they can also reveal some hidden gems – so, be sure to check them out.

Once you’ve worked your way through all the literature, you’ll want to catalogue all this information in some sort of spreadsheet so that you can easily recall who said what, when and within what context. If you’d like, we’ve got a free literature spreadsheet that helps you do exactly that.

Don’t fixate on an article’s citation count in isolation - relevance (to your research question) and recency are also very important.

Step 2: Develop a structure and outline

With your research question pinned down and your literature digested and catalogued, it’s time to move on to planning your actual research paper .

It might sound obvious, but it’s really important to have some sort of rough outline in place before you start writing your paper. So often, we see students eagerly rushing into the writing phase, only to land up with a disjointed research paper that rambles on in multiple

Now, the secret here is to not get caught up in the fine details . Realistically, all you need at this stage is a bullet-point list that describes (in broad strokes) what you’ll discuss and in what order. It’s also useful to remember that you’re not glued to this outline – in all likelihood, you’ll chop and change some sections once you start writing, and that’s perfectly okay. What’s important is that you have some sort of roadmap in place from the start.

You need to have a rough outline in place before you start writing your paper - or you’ll end up with a disjointed research paper that rambles on.

At this stage you might be wondering, “ But how should I structure my research paper? ”. Well, there’s no one-size-fits-all solution here, but in general, a research paper will consist of a few relatively standardised components:

  • Introduction
  • Literature review
  • Methodology

Let’s take a look at each of these.

First up is the introduction section . As the name suggests, the purpose of the introduction is to set the scene for your research paper. There are usually (at least) four ingredients that go into this section – these are the background to the topic, the research problem and resultant research question , and the justification or rationale. If you’re interested, the video below unpacks the introduction section in more detail. 

The next section of your research paper will typically be your literature review . Remember all that literature you worked through earlier? Well, this is where you’ll present your interpretation of all that content . You’ll do this by writing about recent trends, developments, and arguments within the literature – but more specifically, those that are relevant to your research question . The literature review can oftentimes seem a little daunting, even to seasoned researchers, so be sure to check out our extensive collection of literature review content here .

With the introduction and lit review out of the way, the next section of your paper is the research methodology . In a nutshell, the methodology section should describe to your reader what you did (beyond just reviewing the existing literature) to answer your research question. For example, what data did you collect, how did you collect that data, how did you analyse that data and so on? For each choice, you’ll also need to justify why you chose to do it that way, and what the strengths and weaknesses of your approach were.

Now, it’s worth mentioning that for some research papers, this aspect of the project may be a lot simpler . For example, you may only need to draw on secondary sources (in other words, existing data sets). In some cases, you may just be asked to draw your conclusions from the literature search itself (in other words, there may be no data analysis at all). But, if you are required to collect and analyse data, you’ll need to pay a lot of attention to the methodology section. The video below provides an example of what the methodology section might look like.

By this stage of your paper, you will have explained what your research question is, what the existing literature has to say about that question, and how you analysed additional data to try to answer your question. So, the natural next step is to present your analysis of that data . This section is usually called the “results” or “analysis” section and this is where you’ll showcase your findings.

Depending on your school’s requirements, you may need to present and interpret the data in one section – or you might split the presentation and the interpretation into two sections. In the latter case, your “results” section will just describe the data, and the “discussion” is where you’ll interpret that data and explicitly link your analysis back to your research question. If you’re not sure which approach to take, check in with your professor or take a look at past papers to see what the norms are for your programme.

Alright – once you’ve presented and discussed your results, it’s time to wrap it up . This usually takes the form of the “ conclusion ” section. In the conclusion, you’ll need to highlight the key takeaways from your study and close the loop by explicitly answering your research question. Again, the exact requirements here will vary depending on your programme (and you may not even need a conclusion section at all) – so be sure to check with your professor if you’re unsure.

Step 3: Write and refine

Finally, it’s time to get writing. All too often though, students hit a brick wall right about here… So, how do you avoid this happening to you?

Well, there’s a lot to be said when it comes to writing a research paper (or any sort of academic piece), but we’ll share three practical tips to help you get started.

First and foremost , it’s essential to approach your writing as an iterative process. In other words, you need to start with a really messy first draft and then polish it over multiple rounds of editing. Don’t waste your time trying to write a perfect research paper in one go. Instead, take the pressure off yourself by adopting an iterative approach.

Secondly , it’s important to always lean towards critical writing , rather than descriptive writing. What does this mean? Well, at the simplest level, descriptive writing focuses on the “ what ”, while critical writing digs into the “ so what ” – in other words, the implications. If you’re not familiar with these two types of writing, don’t worry! You can find a plain-language explanation here.

Last but not least, you’ll need to get your referencing right. Specifically, you’ll need to provide credible, correctly formatted citations for the statements you make. We see students making referencing mistakes all the time and it costs them dearly. The good news is that you can easily avoid this by using a simple reference manager . If you don’t have one, check out our video about Mendeley, an easy (and free) reference management tool that you can start using today.

Recap: Key Takeaways

We’ve covered a lot of ground here. To recap, the three steps to writing a high-quality research paper are:

  • To choose a research question and review the literature
  • To plan your paper structure and draft an outline
  • To take an iterative approach to writing, focusing on critical writing and strong referencing

Remember, this is just a b ig-picture overview of the research paper development process and there’s a lot more nuance to unpack. So, be sure to grab a copy of our free research paper template to learn more about how to write a research paper.

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Types of Research Papers.

Research papers play a crucial role in academia, allowing scholars to explore and contribute to the existing knowledge within their respective fields. However, not all research papers are created equal. There are various types of research papers, each serving a specific purpose and requiring distinct methodologies and writing styles. In this blog post, we will provide a comprehensive overview of the different types of research papers, shedding light on their characteristics, purposes, and key elements.

1. Descriptive Research Papers:  

Descriptive research papers aim to provide a detailed account or description of a particular phenomenon, event, or subject. These papers focus on answering questions related to “what” and “how.” Descriptive research papers often employ observational methods, surveys, or interviews to collect data. They are valuable in establishing a baseline understanding of a topic or providing an overview of existing conditions.

2. Experimental Research Papers: 

Experimental research papers involve conducting controlled experiments to investigate cause-and-effect relationships between variables. Researchers manipulate independent variables, measure dependent variables, and aim to establish causal relationships. These papers typically include sections such as hypothesis formulation, methodology, data analysis, and conclusion. Experimental research papers are common in scientific disciplines.

3. Analytical Research Papers: 

Analytical research papers emphasize critical thinking and analysis. They delve deep into a specific topic or issue, critically examining existing literature, theories, or concepts. These papers often require the author to evaluate different perspectives, present arguments, and provide evidence to support their claims. Analytical research papers contribute to the development of new theories or the refinement of existing ones.

4. Review Research Papers: 

Review research papers provide a comprehensive summary and evaluation of existing literature on a specific topic. They synthesize and analyze multiple sources to identify trends, gaps, or controversies in the field. Review papers help researchers gain a broader understanding of the current state of knowledge and identify areas that require further investigation. They are often published in academic journals and serve as valuable resources for scholars and students.

5. Argumentative Research Papers: 

Argumentative research papers aim to persuade the reader by presenting a clear argument or position on a specific issue. These papers require the author to gather evidence, present logical reasoning, and counter opposing viewpoints. Argumentative research papers are prevalent in disciplines such as philosophy, social sciences, and humanities, where different perspectives and debates are common.

6. Case Study Research Papers:  

Case study research papers provide an in-depth analysis of a particular individual, group, organization, or event. They involve detailed examination and interpretation of qualitative or quantitative data, often collected through interviews, observations, or document analysis. Case studies offer insights into complex phenomena and allow researchers to explore real-life contexts and unique scenarios.

7. Argumentative Research Papers:  

8. comparative research papers:  .

Comparative research papers involve the systematic comparison of two or more entities, such as countries, cultures, policies, or systems. These papers focus on identifying similarities, differences, and patterns to gain insights into the researched subjects. Comparative research papers can be qualitative or quantitative in nature, depending on the research objectives and methodology.

9. Historical Research Papers:  

Historical research papers examine past events, people, or periods to understand their impact on the present. These papers involve extensive archival research, analysis of primary and secondary sources, and interpretation of historical data. Historical research papers contribute to the understanding of historical contexts, social changes, and the evolution of societies.

10. Theoretical or Conceptual Research Papers:  

Theoretical or conceptual research papers aim to develop or refine theories, models, or frameworks within a particular field. These papers often involve proposing new concepts, exploring relationships between existing theories, or providing theoretical explanations for observed phenomena. Theoretical research papers contribute to advancing knowledge and understanding within a specific discipline.

11. Action Research Papers: 

Action research papers focus on addressing practical problems or challenges within a specific context. They involve collaboration between researchers and practitioners to develop and implement interventions, assess their effectiveness, and reflect on the outcomes. Action research papers emphasize the application of research findings to solve real-world problems and bring about positive change.

Conclusion.

Understanding the different types of research papers is essential for researchers and students alike. Each type serves a distinct purpose, requires specific methodologies, and follows unique writing styles. Whether it’s exploring a phenomenon, conducting experiments, analyzing existing literature, or presenting arguments, researchers must select the appropriate type of research paper to effectively communicate their findings and contribute to the knowledge base of their respective fields.

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  • A Research Guide
  • Research Paper Guide

Different Types of Research Papers

  • According to the purpose
  • According to the depth of scope
  • According to the data type
  • According to variables manipulation
  • According to the type of inference
  • According to the time in which it is carried out
  • According to the sources of information
  • According to how the data is obtained
  • According to design
  • Other research paper types

Types of Research Papers

Types of research papers

As a way to make your journey through the research-type paper options a bit easier, let’s divide them by types of work.

According to the purpose:

  • Theoretical. Theoretical research type is one of the most popular types of research paper as it has a clear focus. If you have to work with this type, your main objective is to generate all currently available. Even if it has no practical appliance (like in Engineering or design), you must use it anyway. You must collect data and make sure that your target audience understands what your research is about and what theory it follows. Most of such research papers will relate to theories and basic analytical work.
  • Applied. This research type stands for something that can be approached scientifically based on practice. The aim here is to generate practical skills. It’s essential in Engineering, Healthcare, and Biology. For such types of papers, one can alternate between technological or scientific types of research, depending on your aims. A technological approach will be fitting if you wish to improve some processes. Now, the scientific research type would include prediction as you work with variables and design things.

According to the depth of scope:

  • Exploratory. It is most suitable for research type papers where you have to explore a not-well-known subject. Start with making a hypothesis and developing research. It can be an investigation talking about the role of video games in the development of teenagers.
  • Descriptive. This type of research is where you must describe certain characteristics or discuss specifics of some belief or an event. You may not have to research why something has caused these characteristic traits. You must describe and talk about how some things may change IF this or that takes place.
  • Explanatory. It’s one of the popular research methods since one has to analyze specific methodologies and help the target audience trace the cause-and-effect relations. It is close to descriptive writing by nature. Still, you must create a research environment since your findings may have to be re-created by others.
  • Correlational. This is where you identify the link between two or more variables. You must focus on determining whether certain research variables will be affected and see whether something is systematic regarding these changes (correlational research methodology).

According to the data type:

  • Qualitative . It’s used to collect, evaluate, and explain information based on obtained information. It means you have to approach a linguistic-semiotic method to things as you research. You can turn to analysis, interviews, questionnaires, and personal surveys. This is where statistical data helps! You must ask yourself “why” instead of “how.”
  • Quantitative. Such types of papers to write belong to one of the most challenging cases because quantitative stands for mathematical (think MATLAB) and computer-based software to check things. It also makes it possible to create a prognosis, which is why this type of research is usually met in engineering.
  • Mixed. It’s also possible to use both methodologies if you can support your research type assignment with source information and personal examples. If you are dealing with Psychology or Experimental study, use surveys and aid yourself with AI-based evaluation tools.

According to variables manipulation:

  • Experimental. Contrary to its title, you do not have to experiment per se. It’s about the design or replication of things you research. It means you have to re-create specific research conditions to discover what effects are caused by given variables. It’s where you primarily use case studies and sample groups.
  • Non-experimental. They often call this research type an observational study. It means that you have to provide analysis in its natural environment. You do not have to intervene in the process but consider turning to descriptive writing. This research may include observation of animals in their natural habitat or the use of the noise effect in the urban environment.
  • Quasi-experimental. These types of academic papers are not purely experimental, as you only work with two or three variables. Another aspect of this research is based on randomly chosen variables. It helps to decrease the bias in your study. It also helps to focus on relevant data and allows us to narrow things down.

According to the type of inference:

  • Deductive. It means the research is basically fixed since one has to focus on laws and things that can or cannot be. It helps to come to certain conclusions. As you look at the research problem, you use deduction to create your considerations. If you make assumptions and develop reliable evidence, this work method suits you.
  • Inductive. It’s one of the flexible methods to think about. The reason why it’s flexible is the way inductive research is generated. You conclude by observing and generalizing while different kinds of research occur. You have to collect data over a period, which makes the process less fixed.
  • Hypothetical-deductive approach. You have to make a hypothesis for your research work and use deduction methods to come up with a conclusion. The major difference is that a researcher also takes time to evaluate whether things are correct.

According to the time in which it is carried out:

  • Longitudinal. You might know this type of work as diachronic research. Despite the complex name, it focuses on the same issue or an event where a fixed period is taken. It has to track certain changes based on variables. It’s one of the most popular research papers in Healthcare, Nursing, Sociology, Psychology, and Education.
  • Cross-sectional. Also known as synchronous research, it is the type of work that approaches cross-sectional design. Here, you have to look at some event or a process at a certain point by taking notes. Thus, research can be used both for sample groups or when working with a case study.

According to the sources of information:

  • Primary. Most students are asked to use primary sources. It is exactly why we have a primary research paper method. The data must be collected directly (personal interviews, surveys, questionnaires, a field observation study, etc.) and represent first-hand information. It is perfect for papers in Psychology, Journalism, Healthcare, and subjects where accuracy is vital.
  • Secondary. This research type of work is mainly developed with sources that represent secondary references. These include books in print or found online, scientific journals, peer-reviewed documents, etc. If another expert or a student reviews a study, it is related to secondary research; so will your project.

According to how the data is obtained:

  • Documentary. As the name suggests, documentary research is based on the secondary references you used. It is a systematic review where you turn to secondary sources related to your subject of study. The most prominent types of research projects in this area are writing a literature review or working with a case study. It is one of the most accessible and clear types of research work.
  • Field. It is quite popular research these days as students tend to collect information in the field or at the location where something takes place. Think about researching Fashion Studies where you attend the shows or exploring Environmental Science, where you must observe a phenomenon and take notes.
  • Laboratory. The major difference in laboratory research type is working in a strictly-controlled environment where study notes are taken immediately. You must isolate unnecessary variables and use one or two scientific methods. Therefore, such type of research writing is called laboratory research. If your college professor asks for this assignment, consider keeping up with standards and rules.
  • Survey. This is where you have to work with the primary information or the use of first-hand data you obtain yourself. It is especially helpful when you work with a group to obtain variables. With this research type, you can also come up with certain conclusions to support your hypothesis and thesis statement.

According to design:

  • Fixed. When conducting a fixed research type, narrow things down and focus on temporal aspects. It means you have to discuss how often you will evaluate something, where your research will occur, a sample group, and other fixed variables. Working on fixed types of research reports, creating precise conditions, and follow strict protocols. Such research is related chiefly to lab reports or laboratory works mostly used in Healthcare and/or Law.
  • Flexible. Now, the flexible research type will provide you with a process where certain things will change as you take step after step in your research. The examples may include case studies where you have to observe the changes that may take over time. Another example would relate to Anthropology or Geography, where you have to observe a group of people or deal with a cross-cultural analysis. It can also relate to grounded-theory studies, where you should develop theoretical knowledge based on analysis and your thinking.

Other research paper types:

  • Argumentative. Also known as a persuasive research type paper, you have to persuade your target audience on your side and a point of view. You have to use at least one piece of evidence (references) to prove your point and support your argument. You must talk about different research opinions and show why your side is correct.
  • Analytical. Analytical research papers should always pose a problem and collect relevant information. You can look at another researcher’s works and provide an analysis based on various points of view. The main types of research papers include analysis and must keep the tone analytical and remain neutral without showing your thoughts unless only to guide the reader.
  • Definition. This research type requires describing the facts or arguments without using anything based on your opinion or an emotional constituent. You only have to offer information by including facts, yet let your data remain without analysis or bias.
  • Action-based. This research type assignment must conduct your work based on a process or a certain action causing things. It can also lead to social processes where a person’s actions have led to something. It can be some research about social movements and/or manufacturing processes.
  • Causal. It may relate to cause-and-effect papers where you must focus on the causes. This research type has to address the questions and explore the causes. It can be based on case studies related to business, education, environmental, educational issues, and more.
  • Classification. If you have to classify, compare, and contrast things, this method will be helpful. Start with the standards and the rules by setting your classification type immediately. Once you know it, your research paper will go smoothly.
  • Comparative. As a rule, this research will deal with comparative work where you take a methodology and compare two sample groups, two individuals, different beliefs, or situations. If you have to compare, discuss your objectives and then create two columns to determine differences and similarities.

What research paper type is most suitable for me?

It will always depend on the research paper objectives you wish to achieve. If you need clarification on the research type you must approach, consult your academic advisor or look closely at your grading rubric. If it says that you must develop an analytical study, it will require posing a specific research question or a problem. The next step would be to collect information on a topic and provide an analysis based on various points of view.

Likewise, if your grading rubric has the word “definition” mentioned, your research type paper must focus on the facts or argumentation. In this case, you should not provide your opinion or talk about what some author thinks. Only the definition of an object or belief is necessary.

As you can see, you only have to find out what your research must achieve. Set the purpose and look at the different types of research and possible methods to approach your problem . Once you know it, look at the research type papers and choose the most fitting option!

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  • 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
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  • Further Readings
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  • 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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what are the types of research papers

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Types of Research – Explained with Examples

DiscoverPhDs

  • By DiscoverPhDs
  • October 2, 2020

Types of Research Design

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.

Methodology Research

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.

Types of Research Methodology

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.

Descriptive Research Design

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.

Action Research Methods

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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Types of Research Papers

Jason Burrey

Table of Contents

Writing a research paper requires a special approach, depending on its type. Students associate completing this type of academic assignment with spending long hours on difficult writing. But writing academic work can be less challenging if you know how to distinguish different paper types. You will better understand what aspect to emphasize and how to present the information the right way. The paper type determines the tone of your work.

Let’s find what popular research work types and their main features to make your academic writing journey captivating and flawless are.

different types of research papers

What Is a Research Paper?

Before moving to paper-type details, let’s find out what research work is and how it differs from other written assignments. A research article is a form of academic writing providing analysis, evaluation, or interpretation of a topic based on empirical evidence. Research papers use statistical data and a strict code for citations. The structure of a research paper depends on assignment requirements. However, generally, it consists of:

  • Introduction
  • Literature review
  • Recommendations
  • Limitations
  • Acknowledgements
  • Figures and Tables

The language of your article should be formal, objective, hedged, and responsible. Plan and organize your writing carefully and precisely. It is required to use complex sentence structures and impersonal pronouns. When writing your research work, avoid wordiness, a vague thesis statement, informal language, description without analysis, and not citing sources. Use one style manual (MLA, APA, or Chicago) to cite them consistently.

Features of research articles are clear focus established by the thesis statement, straightforward structure, statements supported by evidence, and impersonal tone. The length of a research paper ranges from 4,000 to 6,000 words. However, depending on the assignment, your work can be 2,000 words or even 10,000 words. Your academic level and the assignment complexity influence the essay length.

Simple Steps for Writing Different Types of Research Papers

There are nine simple steps you should follow if you wonder: “how can I write my research paper ?”

  • Carefully read the assignment guidelines.
  • Select an engaging article topic.
  • Do early research.
  • Create a powerful thesis statement.
  • Find reliable sources.
  • Write a paper outline.
  • Create an essay draft.
  • Follow citation and formatting rules.
  • Thoroughly edit and proofread your work.

When you need research paper help for some reason, you can find a lot of professional writing services and buy research work.

Different Types of Research Article

There are seven main research work types. Explore them to know what approach to take to create a high-quality paper in the future. Here you can find each type’s specifics and differences to prepare for your assignment the best way. If you have some issues with task completion, choose a reliable service and buy a research paper.

#1 Argumentative Research Papers

Creating an argumentative paper requires a writer to present arguments related to the topic from different points of view. They should analyze the two sides and propose their pros and cons. After that, an author should choose one viewpoint and prove its correctness using evidence from primary sources. There is a special argumentative paper structure that is aimed at persuading the reader to support the writer’s opinion. Thus, describe the problem from two different viewpoints, suggest their pros and cons, and give preference to one.

#2 Analytical Research Papers

It may seem challenging to write an analytical work, but once you find its features, structure, and guidelines, there’s nothing to worry about. A writer should analyze in their paper ideas, facts, events, or issues. It requires an objective analysis and critical thinking to provide strong arguments. You should not take any viewpoint and neutrally describe every point supporting them with relevant information. The analytical paper is based on describing multiple points of view, analyzing all points, and drawing a general conclusion.

#3 Cause and Effect Research Papers

These papers are created to find what is the cause of the expected result. Students without much writing experience are generally assigned to complete such research works. In their papers, they have to describe a situation, present effects, and causes, and draw a conclusion. But this paper type is not as simple as it seems at first sight. Depending on your academic level and subject, a professor may ask you to determine the possible result if conditions change.

#4 Problem-Solution Research Papers

Dealing with this paper type, a writer should describe the problem, present their solution to it, and prove why it is correct. Your task is to find a relevant issue that will be interesting to solve and to engage the readers to explore your solution. Provide reliable data to support your opinion. Consider adding some examples, statistics, and data.

#5 Experimental Research Papers

If you study biology, physics, chemistry, or sociology, this paper type is right for you. When creating an experimental work, a writer should describe their experimental process. This paper provides useful experience and relevant data. Conclude the paper proving that your experiment makes a great contribution to the field.

#6 Report Research Papers

A report paper provides a logical and detailed summary of a case study. A researcher outlines what has been done for the research. The paper includes information, data characteristics, and necessary facts to summarize the findings.

#7 An Interpretive Essay

Such essays are assigned to social science and literature students to show their theoretical knowledge of the subject. Interpret someone’s piece of writing and identify their methods. It is required to support the thesis statement and findings with relevant data.

Types of a Research Article

Research articles are often associated with research articles, and there is no difference between them. Some scholars suggest that works are longer and more detailed. So let’s see what six types of research articles are:

  • The original research article is a manuscript for a journal.
  • A review article is a comprehensive research summary consisting of a systematic review, literature review, and meta-analysis.
  • Short communications are a type of research article that provides a summary of research data.
  • A book chapter is a separate section of a book.
  • The book review is a brief report of a book consisting of an introduction, author profile, book format, and content.
  • Conference materials are article types that can be presented as conference abstracts, posters, and presentation extracts.

Research Paper Styles

If you need research work help, check out the main research article styles. Educational institutions worldwide require their students to adhere to one of the following paper formats or styles:

American Medical Association (AMA) Style

AMA style is commonly used in medical publications. It has a special citation format with in-text references cited numerically in consecutive order using Arabic numerals. Double-space and 12-point font are preferable.

Associated Press Style

The AP style is used mainly for writing news. It’s characterized by consistency, logic, and brevity. Writers avoid offensive and stereotypical language in their works. This style is essential for print journalism.

Chicago Manual of Style

Chicago format style is used in history, physical, natural, and social sciences by many writers and scientists. It is crucial to know about this style that the note numbers are placed within the text, and the sources are found at the end of the chapter.

American Psychological Association (APA) Style

This format is one of the most widely used in academic writing. Students benefit from the APA style frequently in the social sciences. It is also easy to read due to its 12-point font. There are many features of this style, but you should remember that it differs by a left-aligned running header with the title of your study on each page.

Modern Language Association (MLA) Style

MLA style is one of two of the most popular article formats. It is widely used for writing papers on humanities, literature, and English. This style is simple and easy; just use double-spaced throughout the paper and a 12-point font.

Can Research Papers Have Opinions?

Giving your opinion on the issue presupposes subjective evaluation, and in the article, we found that a research paper should be written in an impersonal, objective tone. That’s a controversial question, and we’ll try to handle it.

You can include opinions of prominent scholars in the field and give citations and references to their works. An author should show in their work that they have a personal view on the question and can substantiate it by research and literature. Persuade readers in your paper that your opinion is worth considering using arguments.

Besides, there is an opinion research paper type that aims at presenting the writer’s opinion on a specific topic. Here you are welcome to express your viewpoint but support it with reliable sources and documents.

Writing a research paper seems an insurmountable task with many aspects to consider. Determine your paper type, and your writing process will be much easier as you will have special guidelines.

Contact a research paper writer if you require academic assistance.

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What types of studies are there.

Created: June 15, 2016 ; Last Update: September 8, 2016 ; Next update: 2020.

There are various types of scientific studies such as experiments and comparative analyses, observational studies, surveys, or interviews. The choice of study type will mainly depend on the research question being asked.

When making decisions, patients and doctors need reliable answers to a number of questions. Depending on the medical condition and patient's personal situation, the following questions may be asked:

  • What is the cause of the condition?
  • What is the natural course of the disease if left untreated?
  • What will change because of the treatment?
  • How many other people have the same condition?
  • How do other people cope with it?

Each of these questions can best be answered by a different type of study.

In order to get reliable results, a study has to be carefully planned right from the start. One thing that is especially important to consider is which type of study is best suited to the research question. A study protocol should be written and complete documentation of the study's process should also be done. This is vital in order for other scientists to be able to reproduce and check the results afterwards.

The main types of studies are randomized controlled trials (RCTs), cohort studies, case-control studies and qualitative studies.

  • Randomized controlled trials

If you want to know how effective a treatment or diagnostic test is, randomized trials provide the most reliable answers. Because the effect of the treatment is often compared with "no treatment" (or a different treatment), they can also show what happens if you opt to not have the treatment or diagnostic test.

When planning this type of study, a research question is stipulated first. This involves deciding what exactly should be tested and in what group of people. In order to be able to reliably assess how effective the treatment is, the following things also need to be determined before the study is started:

  • How long the study should last
  • How many participants are needed
  • How the effect of the treatment should be measured

For instance, a medication used to treat menopause symptoms needs to be tested on a different group of people than a flu medicine. And a study on treatment for a stuffy nose may be much shorter than a study on a drug taken to prevent strokes.

“Randomized” means divided into groups by chance. In RCTs participants are randomly assigned to one of two or more groups. Then one group receives the new drug A, for example, while the other group receives the conventional drug B or a placebo (dummy drug). Things like the appearance and taste of the drug and the placebo should be as similar as possible. Ideally, the assignment to the various groups is done "double blinded," meaning that neither the participants nor their doctors know who is in which group.

The assignment to groups has to be random in order to make sure that only the effects of the medications are compared, and no other factors influence the results. If doctors decided themselves which patients should receive which treatment, they might – for instance – give the more promising drug to patients who have better chances of recovery. This would distort the results. Random allocation ensures that differences between the results of the two groups at the end of the study are actually due to the treatment and not something else.

Randomized controlled trials provide the best results when trying to find out if there is a cause-and-effect relationship. RCTs can answer questions such as these:

  • Is the new drug A better than the standard treatment for medical condition X?
  • Does regular physical activity speed up recovery after a slipped disk when compared to passive waiting?
  • Cohort studies

A cohort is a group of people who are observed frequently over a period of many years – for instance, to determine how often a certain disease occurs. In a cohort study, two (or more) groups that are exposed to different things are compared with each other: For example, one group might smoke while the other doesn't. Or one group may be exposed to a hazardous substance at work, while the comparison group isn't. The researchers then observe how the health of the people in both groups develops over the course of several years, whether they become ill, and how many of them pass away. Cohort studies often include people who are healthy at the start of the study. Cohort studies can have a prospective (forward-looking) design or a retrospective (backward-looking) design. In a prospective study, the result that the researchers are interested in (such as a specific illness) has not yet occurred by the time the study starts. But the outcomes that they want to measure and other possible influential factors can be precisely defined beforehand. In a retrospective study, the result (the illness) has already occurred before the study starts, and the researchers look at the patient's history to find risk factors.

Cohort studies are especially useful if you want to find out how common a medical condition is and which factors increase the risk of developing it. They can answer questions such as:

  • How does high blood pressure affect heart health?
  • Does smoking increase your risk of lung cancer?

For example, one famous long-term cohort study observed a group of 40,000 British doctors, many of whom smoked. It tracked how many doctors died over the years, and what they died of. The study showed that smoking caused a lot of deaths, and that people who smoked more were more likely to get ill and die.

  • Case-control studies

Case-control studies compare people who have a certain medical condition with people who do not have the medical condition, but who are otherwise as similar as possible, for example in terms of their sex and age. Then the two groups are interviewed, or their medical files are analyzed, to find anything that might be risk factors for the disease. So case-control studies are generally retrospective.

Case-control studies are one way to gain knowledge about rare diseases. They are also not as expensive or time-consuming as RCTs or cohort studies. But it is often difficult to tell which people are the most similar to each other and should therefore be compared with each other. Because the researchers usually ask about past events, they are dependent on the participants’ memories. But the people they interview might no longer remember whether they were, for instance, exposed to certain risk factors in the past.

Still, case-control studies can help to investigate the causes of a specific disease, and answer questions like these:

  • Do HPV infections increase the risk of cervical cancer?
  • Is the risk of sudden infant death syndrome (“cot death”) increased by parents smoking at home?

Cohort studies and case-control studies are types of "observational studies."

  • Cross-sectional studies

Many people will be familiar with this kind of study. The classic type of cross-sectional study is the survey: A representative group of people – usually a random sample – are interviewed or examined in order to find out their opinions or facts. Because this data is collected only once, cross-sectional studies are relatively quick and inexpensive. They can provide information on things like the prevalence of a particular disease (how common it is). But they can't tell us anything about the cause of a disease or what the best treatment might be.

Cross-sectional studies can answer questions such as these:

  • How tall are German men and women at age 20?
  • How many people have cancer screening?
  • Qualitative studies

This type of study helps us understand, for instance, what it is like for people to live with a certain disease. Unlike other kinds of research, qualitative research does not rely on numbers and data. Instead, it is based on information collected by talking to people who have a particular medical condition and people close to them. Written documents and observations are used too. The information that is obtained is then analyzed and interpreted using a number of methods.

Qualitative studies can answer questions such as these:

  • How do women experience a Cesarean section?
  • What aspects of treatment are especially important to men who have prostate cancer?
  • How reliable are the different types of studies?

Each type of study has its advantages and disadvantages. It is always important to find out the following: Did the researchers select a study type that will actually allow them to find the answers they are looking for? You can’t use a survey to find out what is causing a particular disease, for instance.

It is really only possible to draw reliable conclusions about cause and effect by using randomized controlled trials. Other types of studies usually only allow us to establish correlations (relationships where it isn’t clear whether one thing is causing the other). For instance, data from a cohort study may show that people who eat more red meat develop bowel cancer more often than people who don't. This might suggest that eating red meat can increase your risk of getting bowel cancer. But people who eat a lot of red meat might also smoke more, drink more alcohol, or tend to be overweight. The influence of these and other possible risk factors can only be determined by comparing two equal-sized groups made up of randomly assigned participants.

That is why randomized controlled trials are usually the only suitable way to find out how effective a treatment is. Systematic reviews, which summarize multiple RCTs, are even better. In order to be good-quality, though, all studies and systematic reviews need to be designed properly and eliminate as many potential sources of error as possible.

  • German Network for Evidence-based Medicine. Glossar: Qualitative Forschung.  Berlin: DNEbM; 2011. 
  • Greenhalgh T. Einführung in die Evidence-based Medicine: kritische Beurteilung klinischer Studien als Basis einer rationalen Medizin. Bern: Huber; 2003. 
  • Institute for Quality and Efficiency in Health Care (IQWiG, Germany). General methods . Version 5.0. Cologne: IQWiG; 2017.
  • Klug SJ, Bender R, Blettner M, Lange S. Wichtige epidemiologische Studientypen. Dtsch Med Wochenschr 2007; 132:e45-e47. [ PubMed : 17530597 ]
  • Schäfer T. Kritische Bewertung von Studien zur Ätiologie. In: Kunz R, Ollenschläger G, Raspe H, Jonitz G, Donner-Banzhoff N (eds.). Lehrbuch evidenzbasierte Medizin in Klinik und Praxis. Cologne: Deutscher Ärzte-Verlag; 2007.

IQWiG health information is written with the aim of helping people understand the advantages and disadvantages of the main treatment options and health care services.

Because IQWiG is a German institute, some of the information provided here is specific to the German health care system. The suitability of any of the described options in an individual case can be determined by talking to a doctor. We do not offer individual consultations.

Our information is based on the results of good-quality studies. It is written by a team of health care professionals, scientists and editors, and reviewed by external experts. You can find a detailed description of how our health information is produced and updated in our methods.

  • Cite this Page InformedHealth.org [Internet]. Cologne, Germany: Institute for Quality and Efficiency in Health Care (IQWiG); 2006-. What types of studies are there? 2016 Jun 15 [Updated 2016 Sep 8].

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Research Method

Home » Research Methodology – Types, Examples and writing Guide

Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

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

II. Research Design

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

III. Data Collection Methods

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

IV. Data Analysis Methods

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

V. Ethical Considerations

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

VI. Limitations

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

VII. Conclusion

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

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

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

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

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

Purpose of Research Methodology

Research methodology serves several important purposes, including:

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

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

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

Research Methodology Vs Research Methods

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Types of journal articles

It is helpful to familiarise yourself with the different types of articles published by journals. Although it may appear there are a large number of types of articles published due to the wide variety of names they are published under, most articles published are one of the following types; Original Research, Review Articles, Short reports or Letters, Case Studies, Methodologies.

Original Research:

This is the most common type of journal manuscript used to publish full reports of data from research. It may be called an  Original Article, Research Article, Research, or just  Article, depending on the journal. The Original Research format is suitable for many different fields and different types of studies. It includes full Introduction, Methods, Results, and Discussion sections.

Short reports or Letters:

These papers communicate brief reports of data from original research that editors believe will be interesting to many researchers, and that will likely stimulate further research in the field. As they are relatively short the format is useful for scientists with results that are time sensitive (for example, those in highly competitive or quickly-changing disciplines). This format often has strict length limits, so some experimental details may not be published until the authors write a full Original Research manuscript. These papers are also sometimes called Brief communications .

Review Articles:

Review Articles provide a comprehensive summary of research on a certain topic, and a perspective on the state of the field and where it is heading. They are often written by leaders in a particular discipline after invitation from the editors of a journal. Reviews are often widely read (for example, by researchers looking for a full introduction to a field) and highly cited. Reviews commonly cite approximately 100 primary research articles.

TIP: If you would like to write a Review but have not been invited by a journal, be sure to check the journal website as some journals to not consider unsolicited Reviews. If the website does not mention whether Reviews are commissioned it is wise to send a pre-submission enquiry letter to the journal editor to propose your Review manuscript before you spend time writing it.  

Case Studies:

These articles report specific instances of interesting phenomena. A goal of Case Studies is to make other researchers aware of the possibility that a specific phenomenon might occur. This type of study is often used in medicine to report the occurrence of previously unknown or emerging pathologies.

Methodologies or Methods

These articles present a new experimental method, test or procedure. The method described may either be completely new, or may offer a better version of an existing method. The article should describe a demonstrable advance on what is currently available.

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Top 10 research topics for students.

what are the types of research papers

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Is your dissertation just around the corner? Are you spending all day thinking about “research topic ideas for students”? What topic would make you stand out from the crowd? That’s a tough question, but definitely not an impossible one! In this blog, we will help you find research topic examples for students, or give you a direction for it. Let’s begin! 

What is a Research Paper?

In the 21st century, writing a research paper has become one of the most crucial parts of most academic degrees. While it may not be necessary, it is best to write one as your research paper can get you into your dream college sometimes! 

A Research Paper is a kind of academic writing that provides data, interpretation, and analysis of a Research Question. In some universities, writing a research paper is often a part of their academic curriculum, that is often referred to as ‘Dissertation”. 

Why should students write research papers?

You might sometimes wonder how a research paper will help you in life? The truth is, there are many reasons why students should engage in research writing early in their studies. Some of these benefits include:

  • It helps students excel at research writing for their higher studies.
  • Enables students to acquire firsthand knowledge, discover new facts, and even get published.
  • Students get a chance to make useful connections with professors and other researchers.
  • Writing a unique research paper gives students recognition and credits in many universities.

What makes a Research good?

Writing a good research paper requires a lot of effort and critical thinking. But imagine, if a class of 115 students is writing research papers, then whose paper will stand out? There are some factors that make a research paper unique and recognized. Let’s see what they are.

  • Research Topic must be crisp, self-explanatory, and unique.
  • The paper must be reliable and valid.
  • Appropriate research methods must be used as per the topic.
  • The objective of the research must be clearly stated.
  • The collection of data and interpretation must be done in the right manner.

What are some research topics for students?

Choosing a research topic can become a tiring process, especially when you have no idea which direction to go in. In this section of the blog, we will help you with some research title examples for students, and how to choose your choice of research topic. 

To choose a research topic of your choice:

  • Lean into your interest in the topic : For example, if you are interested in studying human psychology, then narrow it down to the field of psychology you would like to research about. 
  • Look for topics : Now suppose, you have narrowed down your choice to Child Psychology. The next step is to look for topics that have enough information for research, and ones that are easily accessible.
  • Guidelines & Ethics : Make sure the topic that you are finalising falls in line with the guidelines that your university/guide/professor has provided. For example, researching “Autism in Children” will not help you if your guidelines clearly state research on adults.

Given below are some Research Topic examples that you can choose for your paper, or get an idea from. Let’s dive in and get you that A+ and your dream university!

  • Religion and Globalization – Students can choose this topic to study if there is any relationship between religion and globalisation, and how religions are making use of global communications.
  • Body Shaming & Its Impact on Mental Wellness and Emotional Expressivity – Many people are victims of body shaming from a very young age. Research on how body shaming impacts a person’s self-worth and other factors can be studied.
  • AI and its impact on various businesses – How is Artificial Intelligence impacting different businesses? Is it a boon or a bane for certain businesses?
  • Relationship between multilingualism and socialization – Can being multilingual boost socialization among people? Do people feel more safe and comfortable around people who speak the same language in a different country?
  • LGBTQ+ – What are the rights of people who are a part of the LGBTQ+ community? How accepting is today’s society towards the community?
  • Impact of Climate Change on Happiness – Can climate change impact a person’s happiness? Does it have a significant impact on how a person feels?
  • Work-Life Balance – What are workplaces doing to maintain work-life balance? Why is it important?
  • Relationship between Technology and Risk Management? – How can technology play a role in Risk management? How does it help?
  • Parenting Styles and its Impact on Children – Different parenting styles can have different impacts on children. Research about the consequences of different styles.
  • Rapid Urbanization and its Social Impact – What are the positive and negative impacts of urbanisation?

Final Words

Finding a perfect research topic often seems impossible, and a very hectic task. But we hope this blog has helped you in finding your research interest, and formulating a topic. Writing a research paper can help students in various ways, such as developing academic writing skills. Moreover, many international universities appreciate and prefer students who have published their own research, as it portrays innovation and leadership skills. So, what are you waiting for? Get started on your research now! And if you still feel stuck deciding the topic, then you can refer to some AI tools as well. To know more about these tools, read this blog on Best AI Tools for Students in 2024 .

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Satellite photo showing a container ship entangled with the wreckage of a bridge.

Baltimore bridge collapse: a bridge engineer explains what happened, and what needs to change

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Associate Professor, Civil Engineering, Monash University

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Colin Caprani receives funding from the Department of Transport (Victoria) and the Level Crossing Removal Project. He is also Chair of the Confidential Reporting Scheme for Safer Structures - Australasia, Chair of the Australian Regional Group of the Institution of Structural Engineers, and Australian National Delegate for the International Association for Bridge and Structural Engineering.

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When the container ship MV Dali, 300 metres long and massing around 100,000 tonnes, lost power and slammed into one of the support piers of the Francis Scott Key Bridge in Baltimore, the bridge collapsed in moments . Six people are presumed dead, several others injured, and the city and region are expecting a months-long logistical nightmare in the absence of a crucial transport link.

It was a shocking event, not only for the public but for bridge engineers like me. We work very hard to ensure bridges are safe, and overall the probability of being injured or worse in a bridge collapse remains even lower than the chance of being struck by lightning.

However, the images from Baltimore are a reminder that safety can’t be taken for granted. We need to remain vigilant.

So why did this bridge collapse? And, just as importantly, how might we make other bridges more safe against such collapse?

A 20th century bridge meets a 21st century ship

The Francis Scott Key Bridge was built through the mid 1970s and opened in 1977. The main structure over the navigation channel is a “continuous truss bridge” in three sections or spans.

The bridge rests on four supports, two of which sit each side of the navigable waterway. It is these two piers that are critical to protect against ship impacts.

And indeed, there were two layers of protection: a so-called “dolphin” structure made from concrete, and a fender. The dolphins are in the water about 100 metres upstream and downstream of the piers. They are intended to be sacrificed in the event of a wayward ship, absorbing its energy and being deformed in the process but keeping the ship from hitting the bridge itself.

Diagram of a bridge

The fender is the last layer of protection. It is a structure made of timber and reinforced concrete placed around the main piers. Again, it is intended to absorb the energy of any impact.

Fenders are not intended to absorb impacts from very large vessels . And so when the MV Dali, weighing more than 100,000 tonnes, made it past the protective dolphins, it was simply far too massive for the fender to withstand.

Read more: I've captained ships into tight ports like Baltimore, and this is how captains like me work with harbor pilots to avoid deadly collisions

Video recordings show a cloud of dust appearing just before the bridge collapsed, which may well have been the fender disintegrating as it was crushed by the ship.

Once the massive ship had made it past both the dolphin and the fender, the pier – one of the bridge’s four main supports – was simply incapable of resisting the impact. Given the size of the vessel and its likely speed of around 8 knots (15 kilometres per hour), the impact force would have been around 20,000 tonnes .

Bridges are getting safer

This was not the first time a ship hit the Francis Scott Bridge. There was another collision in 1980 , damaging a fender badly enough that it had to be replaced.

Around the world, 35 major bridge collapses resulting in fatalities were caused by collisions between 1960 and 2015, according to a 2018 report from the World Association for Waterborne Transport Infrastructure. Collisions between ships and bridges in the 1970s and early 1980s led to a significant improvement in the design rules for protecting bridges from impact.

A greenish book cover with the title Ship Collision With Bridges.

Further impacts in the 1970s and early 1980s instigated significant improvements in the design rules for impact.

The International Association for Bridge and Structural Engineering’s Ship Collision with Bridges guide, published in 1993, and the American Association of State Highway and Transporation Officials’ Guide Specification and Commentary for Vessel Collision Design of Highway Bridges (1991) changed how bridges were designed.

In Australia, the Australian Standard for Bridge Design (published in 2017) requires designers to think about the biggest vessel likely to come along in the next 100 years, and what would happen if it were heading for any bridge pier at full speed. Designers need to consider the result of both head-on collisions and side-on, glancing blows. As a result, many newer bridges protect their piers with entire human-made islands.

Of course, these improvements came too late to influence the design of the Francis Scott Key Bridge itself.

Lessons from disaster

So what are the lessons apparent at this early stage?

First, it’s clear the protection measures in place for this bridge were not enough to handle this ship impact. Today’s cargo ships are much bigger than those of the 1970s, and it seems likely the Francis Scott Key Bridge was not designed with a collision like this in mind.

So one lesson is that we need to consider how the vessels near our bridges are changing. This means we cannot just accept the structure as it was built, but ensure the protection measures around our bridges are evolving alongside the ships around them.

Photo shows US Coast Guard boat sailing towards a container ship entangled in the wreckage of a large bridge.

Second, and more generally, we must remain vigilant in managing our bridges. I’ve written previously about the current level of safety of Australian bridges, but also about how we can do better.

This tragic event only emphasises the need to spend more on maintaining our ageing infrastructure. This is the only way to ensure it remains safe and functional for the demands we put on it today.

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Reservoir engineering for classical nonlinear fields

Benedikt tissot, hugo ribeiro, and florian marquardt, phys. rev. research 6 , 023015 – published 3 april 2024.

  • No Citing Articles
  • INTRODUCTION
  • SYSTEM-RESERVOIR COUPLING WITH PARTICLE…
  • MICROSCOPIC MODEL: THE ANHARMONIC CHAIN
  • CONCLUSIONS
  • ACKNOWLEDGMENTS

Reservoir engineering has become a prominent tool to control quantum systems. Recently, there have been first experiments applying it to many-body systems, especially with a view to engineer particle-conserving dissipation for quantum simulations using bosons. In this paper, we explore the dissipative dynamics of these systems in the classical limit. We derive a general equation of motion capturing the effective nonlinear dissipation introduced by the bath and apply it to the special case of a Bose-Hubbard model, where it leads to an unconventional type of dissipative nonlinear Schrödinger equation. Building on that, we study the dynamics of one and two solitons in such a dissipative classical field theory.

Figure

  • Received 16 November 2023
  • Accepted 5 March 2024

DOI: https://doi.org/10.1103/PhysRevResearch.6.023015

what are the types of research papers

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Open access publication funded by Max Planck Society.

Published by the American Physical Society

Physics Subject Headings (PhySH)

  • Research Areas
  • Physical Systems

Authors & Affiliations

  • 1 Department of Physics, University of Konstanz, D-78457 Konstanz, Germany
  • 2 Department of Physics and Applied Physics, University of Massachusetts Lowell, Lowell, Massachusetts 01854, USA
  • 3 Max Planck Institute for the Science of Light, Staudtstr. 2, 91058 Erlangen, Germany
  • 4 Department of Physics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Staudstr. 7, 91058 Erlangen, Germany
  • * [email protected]
  • [email protected]
  • [email protected]

Article Text

Vol. 6, Iss. 2 — April - June 2024

Subject Areas

  • Atomic and Molecular Physics
  • Nonlinear Dynamics

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(a) The physical scenario of a bosonic system (in the classical limit) coupled to a driven reservoir, in a particle-conserving way. (b) Particular illustrative realization considered in the text, a Bose-Hubbard chain (blue b j ) with sites coupled to driven cavities (orange bosonic modes a j ) with coupling strength χ and to each other with hopping rate J . See main text for details. (c) Spectrum of a dissipative cavity, where the incoming drive can be upscattered in frequency through interaction with the bosonic many-body system, extracting energy. The detuning Δ and the dissipation rate κ determine the properties of this driven reservoir.

Effective parameters as defined in Eqs. ( 5 ) and ( 7 ) as functions of the detuning: The correction of the effective on-site interaction δ g (black solid) as well as the dissipation parameter γ (dashed gray). The dissipation parameter is positive in the red-detuned domain ( Δ < 0 ) and changes sign in the blue-detuned domain ( Δ > 0 ). Both the correction of the on-site interaction, as well as the dissipation parameter scale with the second order of the bath interaction but have different limiting behavior at large detuning Δ .

Comparison of the PCDNSE [Eq. ( 10 )] and the discrete equations of motion (EOM) including the reservoir dynamics, see Eqs. ( 2 ) and ( 3 ). In panel (a) we compare simulations for different array lengths to the PCDNSE and in (b) different cavity parameters leading to the same effective evolution. Only when the continuum limit or weak-coupling limit are not satisfied (small L or Δ = − 2 J , respectively) the discrete dynamics are in disagreement with the dynamics of the PCDNSE. Unless otherwise specified (see legend) we use L = 800 , κ = J , Δ = − 0.1 J , η = J and χ , α such that we get the effective parameters g = − 0.1 J , γ = 0.05 . The distributions are taken after an evolution for J t = 50 ( L / 400 ) 2 of an initial stable soliton [see inset of (b)] with height ψ ( 0 ) = 1 and velocity v ( 0 ) ≈ 0.48 . The PCDNSE uses a length of L = 400 . For the evolution according to the discrete EOM, we assume that the cavities are initially in their unperturbed steady state η / ( κ / 2 − i Δ ) .

Velocity damping rate as a function of g γ ψ 4 ( 0 ) . We see good agreement between the variational approach and numerical results of the particle-conserving dissipative nonlinear Schrödinger equation (PCDNSE). The deviation at the smallest value is due to the soliton breaking up in the simulation, underlined by the datapoint given by the star where the relative and absolute tolerances where decreased to 10 − 13 and 10 − 12 respectively from 10 − 8 for both. The inset shows that the deviation | δ ( J t = 4 ) | = | ψ 2 ( J t = 4 ) / ψ 2 ( 0 ) − 1 | (pentagons, diamonds) as well as d ( J t = 4 ) (triangles) from the stable soliton stays small for the evolution. The PCDNSE simulation is for a stable soliton with ψ ( 0 ) = 1 , x ( 0 ) = L / 8 , v ( 0 ) ≈ 0.49 , and L = 600 and for a duration J t = 4 .

Shape stabilization of ill prepared solitons. The maximal amplitude of the PCDNSE (dashed lines) is compared to the prediction of the collective coordinates (solid lines) in (a) and (b) for the different deviations δ = ψ ( 0 ) / ψ SS − 1 [see legend in (c)]. While for δ = − 0.1 , 0.01 both solutions oscillate around the steady-state amplitude, for δ = 0.3 the soliton shape breaks down and this oscillation is visible in neither solution. The breakout is also visible in the inset of (b), which displays | Ψ ( J t , x − x 0 ) / ψ S S | 2 according to the PCDNSE and where the color corresponds to 0 (darkest purple) to 1.7 (lightest yellow). Therefore, we investigate the dynamics for long times for the smaller δ = − 0.1 , 0.01 [(b)–(d)]. Panel (b) shows the continued oscillation around the steady state amplitude after a prolonged evolution time of J t = 2 × 10 6 and (c) displays the modulo square distribution after this evolution. To quantify the long time dynamics we compare the envelope of the deviation of the maximal amplitude ψ ( t ) deviation from the steady state amplitude ψ SS on a long timescale in these cases (d). To this end, we calculate the envelope as the maximal deviation within a time-window of length 5 × 10 4 . The relaxation process is sketched in the inset of (d). We use g = − 0.1 J , N = 1 , γ = 0.1 , L = 10 w SS , and only deviate from the stable soliton via δ ≠ 0 (i.e., d = 0 ).

Influence of the dissipative dynamics due to the interaction of two stable solitons. The figure depicts the energy of the two solitons compared to the single soliton solution as a function of time during the interaction for different γ (see legend). The inset shows | Ψ ( x , t ) | 2 for γ = 10 − 2 where the values range from 0 (dark) to ≈ 3.62 (light). We use g = − 0.1 J and the initial solitons have ψ ( 0 ) = 1 ( N ≈ 9 ), and | v ( 0 ) | ≈ 0.5 with opposite signs and are placed 5 w ( 0 ) apart on a space of size 20 w ( 0 ) . The figure shows that the interaction of the two solitons can enhance the energy dissipation.

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Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

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

Second, decide how you will analyze the data .

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

Table of contents

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

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

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

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

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

Qualitative analysis methods

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

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

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

  • During an experiment .
  • Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

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

Research bias

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

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

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

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

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

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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

Published on 3.4.2024 in Vol 26 (2024)

Public Discourse, User Reactions, and Conspiracy Theories on the X Platform About HIV Vaccines: Data Mining and Content Analysis

Authors of this article:

Author Orcid Image

Original Paper

  • Jueman M Zhang 1 , PhD   ; 
  • Yi Wang 2 , PhD   ; 
  • Magali Mouton 3   ; 
  • Jixuan Zhang 4   ; 
  • Molu Shi 5 , PhD  

1 Harrington School of Communication and Media, University of Rhode Island, Kingston, RI, United States

2 Department of Communication, University of Louisville, Louisville, KY, United States

3 School of Rehabilitation Sciences, University of Ottawa, Ottawa, ON, Canada

4 Polk School of Communications, Long Island University, Brooklyn, NY, United States

5 College of Business, University of Louisville, Louisville, KY, United States

Corresponding Author:

Jueman M Zhang, PhD

Harrington School of Communication and Media

University of Rhode Island

10 Ranger Road

Kingston, RI, 02881

United States

Phone: 1 401 874 2110

Email: [email protected]

Background: The initiation of clinical trials for messenger RNA (mRNA) HIV vaccines in early 2022 revived public discussion on HIV vaccines after 3 decades of unsuccessful research. These trials followed the success of mRNA technology in COVID-19 vaccines but unfolded amid intense vaccine debates during the COVID-19 pandemic. It is crucial to gain insights into public discourse and reactions about potential new vaccines, and social media platforms such as X (formerly known as Twitter) provide important channels.

Objective: Drawing from infodemiology and infoveillance research, this study investigated the patterns of public discourse and message-level drivers of user reactions on X regarding HIV vaccines by analyzing posts using machine learning algorithms. We examined how users used different post types to contribute to topics and valence and how these topics and valence influenced like and repost counts. In addition, the study identified salient aspects of HIV vaccines related to COVID-19 and prominent anti–HIV vaccine conspiracy theories through manual coding.

Methods: We collected 36,424 English-language original posts about HIV vaccines on the X platform from January 1, 2022, to December 31, 2022. We used topic modeling and sentiment analysis to uncover latent topics and valence, which were subsequently analyzed across post types in cross-tabulation analyses and integrated into linear regression models to predict user reactions, specifically likes and reposts. Furthermore, we manually coded the 1000 most engaged posts about HIV and COVID-19 to uncover salient aspects of HIV vaccines related to COVID-19 and the 1000 most engaged negative posts to identify prominent anti–HIV vaccine conspiracy theories.

Results: Topic modeling revealed 3 topics: HIV and COVID-19, mRNA HIV vaccine trials, and HIV vaccine and immunity. HIV and COVID-19 underscored the connections between HIV vaccines and COVID-19 vaccines, as evidenced by subtopics about their reciprocal impact on development and various comparisons. The overall valence of the posts was marginally positive. Compared to self-composed posts initiating new conversations, there was a higher proportion of HIV and COVID-19–related and negative posts among quote posts and replies, which contribute to existing conversations. The topic of mRNA HIV vaccine trials, most evident in self-composed posts, increased repost counts. Positive valence increased like and repost counts. Prominent anti–HIV vaccine conspiracy theories often falsely linked HIV vaccines to concurrent COVID-19 and other HIV-related events.

Conclusions: The results highlight COVID-19 as a significant context for public discourse and reactions regarding HIV vaccines from both positive and negative perspectives. The success of mRNA COVID-19 vaccines shed a positive light on HIV vaccines. However, COVID-19 also situated HIV vaccines in a negative context, as observed in some anti–HIV vaccine conspiracy theories misleadingly connecting HIV vaccines with COVID-19. These findings have implications for public health communication strategies concerning HIV vaccines.

Introduction

Vaccination has long been recognized as a crucial preventive measure against diseases and infections, but opposition to vaccines has endured [ 1 ]. HIV vaccination has been regarded as a potential preventive measure to help combat the HIV epidemic in the United States, with research and progress dating back to the mid-1980s but without success thus far [ 2 ]. An estimated 1.2 million people were living with HIV in the United States by the end of 2021, with 36,136 new HIV diagnoses reported in 2021 [ 3 ].

On January 27, 2022, the biotechnology company Moderna announced the initiation of clinical trials for an HIV vaccine using messenger RNA (mRNA) technology [ 4 ]. In March 2022, the National Institutes of Health announced the start of clinical trials for 3 mRNA HIV vaccines [ 5 ]. The mRNA technology had previously been used in the Pfizer-BioNTech and Moderna COVID-19 vaccines, which protected individuals against severe symptoms and fatalities during the pandemic [ 6 ]. Following the successes of mRNA COVID-19 vaccines, which led to the Nobel Prize in Physiology or Medicine being awarded to 2 scientists in October 2023 [ 7 ], researchers have been investigating the potential of mRNA vaccines for various other diseases, including HIV [ 8 , 9 ]. The announcements of clinical trials for mRNA HIV vaccines revived public discussion on the prospect of vaccines to combat HIV [ 9 ] despite >3 decades of unsuccessful research [ 2 ]. Meanwhile, these announcements were made against the backdrop of intense vaccine debates during the COVID-19 pandemic, with misinformation and conspiracy theories fueling vaccine hesitancy [ 10 - 12 ].

The X platform, formerly known as Twitter, has been a significant social media platform and a vital source for text-based public discourse. Posts on X have been studied to understand public discourse about vaccines in general [ 13 - 15 ] and about specific vaccines, such as COVID-19 vaccines in recent years [ 12 , 16 , 17 ]. However, there is a dearth of research about public discourse on HIV vaccines on social media. Given the advancement in mRNA technology in COVID-19 vaccines and heated vaccine debates, it has become especially important to gain insights into public discourse and reactions regarding potential new vaccines.

This study is grounded in the growing field of infodemiology and infoveillance, which investigates the “distribution and determinants of information in an electronic medium,” specifically on the web, by analyzing unstructured text with the aim of informing public health practices or serving surveillance objectives [ 18 ]. In recent infodemiology and infoveillance studies, machine learning algorithms have been increasingly used to examine substantial amounts of social media content, such as posts on X related to COVID-19 vaccines [ 12 , 16 , 17 ] and HIV prevention [ 19 ], to extract insights into public discourse and reactions. These algorithms automatically analyze extensive volumes of posts and capture latent textual information such as topics and sentiments. This study aimed to investigate how users used different post types to contribute original content to topics and valence identified through machine learning algorithms and how these topics and valence affected user reactions on X regarding HIV vaccines. In addition, by manually coding the most engaged posts, similar to an approach used in previous infodemiology and infoveillance research [ 20 ], the study intended to identify salient aspects of HIV vaccines related to COVID-19 as well as prominent anti–HIV vaccine conspiracy theories. Analyzing posts on X about HIV vaccines can shed light on public discourse and information diffusion. These findings have implications for shaping public health communication strategies about HIV vaccines [ 18 ]. Furthermore, the findings may help in understanding the acceptability of the HIV vaccine upon its successful development in comparison with adherence to existing HIV prevention measures. Previous infodemiology and infoveillance research effectively increased the forecast accuracy of COVID-19 vaccine uptake by leveraging insights derived from posts on X [ 21 ].

Literature Review

Public discourse about hiv prevention on x.

Social media platforms have become important channels for HIV communication, enabling the dissemination of and engagement with content encompassing a wide array of issues related to HIV prevention, treatment, coping, and available resources [ 22 , 23 ]. An earlier infodemiology study examined 69,197 posts on the X platform containing the hashtag #HIVPrevention between 2014 and 2019 and categorized these posts into 10 identified topics concerning HIV prevention [ 19 ]. Among them, pre-exposure prophylaxis had the highest representation with 13,895 posts, followed by HIV testing; condoms; harm reduction; gender equity and violence against women; voluntary medical male circumcision; sex work; postexposure prophylaxis; elimination of mother-to-child transmission of HIV; and abstinence, which had the lowest representation with 180 posts. Furthermore, that study suggested a consistency between the volume of posts related to specific HIV prevention measures on X over time and the temporal trends in the uptake of those measures [ 19 ]. It is noteworthy that the topic of HIV vaccines was absent, which suggested minimal public discourse on the topic during these years. This may be associated with the extensive history of unsuccessful research in this area [ 2 ].

Despite the availability of current HIV prevention measures, efforts have been made to develop HIV vaccines, which are considered necessary to bridge the gap between the challenges in adhering to existing HIV prevention measures and the ambitious goal set by United Nations member states to end the HIV epidemic by 2030 [ 24 , 25 ]. The surge in public discussion about HIV vaccines, possibly elicited by the clinical trials for mRNA HIV vaccines [ 9 ], presented an optimal opportunity to investigate public discourse and reactions regarding HIV vaccines. To the best of our knowledge, this is the first study to analyze posts on X about HIV vaccines.

Public Discourse and Post Types on X

On the X platform, public discourse featuring original content can be observed through 3 post types: self-composed posts, quote posts, and replies [ 26 ]. X users can compose a post. They can also create a quote post, which entails reposting a post while adding their comments. In addition, they can reply to a post to share their comments [ 26 ]. While self-composed posts initiate new conversations, quote posts and replies enable users to join existing conversations by contributing their own comments [ 27 ]. The Pew Research Center’s analysis of survey respondents’ posts on X from October 2022 to April 2023 revealed the composition of different types of posts. Regarding the 3 types of posts containing original content, replies accounted for the highest proportion at 40%, followed by self-composed posts at 15% and quote posts at 9%. The remaining 35% were reposts [ 28 ].

Machine learning algorithms have been increasingly used in recent years to identify latent message features, including textual topics and sentiment valence, among vast numbers of social media posts, as exemplified by previous research analyzing posts on X about COVID-19 vaccines [ 12 , 16 , 17 ] and HIV prevention [ 19 ]. However, the patterns of public discourse in social media conversations are unclear. Specifically, there is a scarcity of research on how people contribute their original content to topics and valence related to a public health issue. This study aimed to address this gap by examining the relationship between post types and message features, specifically topics and valence uncovered using machine learning algorithms, with a focus on HIV vaccines as the subject matter. The findings will advance our knowledge of user contributions to social media conversations about HIV vaccines.

Message Features Influencing User Reactions on X

Examining message diffusion on social media has been a multifaceted challenge, especially with vaccines being a contentious issue debated fervently during the COVID-19 pandemic [ 16 ]. Another contribution of this study is to advance this research area by using machine learning to investigate the synergistic impact of content and account features on user reactions regarding a potential new vaccine amid the context of intense vaccine debates.

The extent to which a message results in optimal diffusion on social media can be gauged by user reactions [ 16 , 29 - 31 ]. On X, a user can engage with posts—be it a self-composed post, quote post, or reply—in 2 primary 1-click reactions: liking and reposting [ 26 ]. An X user can like a post to show appreciation for it or repost it to share it publicly. Compared to liking, reposting is a more social behavior [ 16 , 32 ]. Unlike X’s old timeline, which mostly displayed posts from accounts that a user followed, its current “For you” timeline also shows posts that those accounts have engaged with along with other posts recommended based on user reactions [ 33 ]. The nature of promoting posts based on user reactions makes it more important to investigate the factors that influence user reactions.

This study investigated 2 categories of message-level features that, according to previous research, can drive user interactions: content features in terms of topics and valence and account features in terms of user verification and follower count. Post topics affect likes and reposts on X [ 16 , 30 , 34 ]. Previous research on COVID-19 vaccine posts on X has indicated that posts containing useful information garner more likes and reposts [ 16 ]. This is likely because information utility fills people’s knowledge gaps and serves their utilitarian needs in the face of health risks [ 16 , 32 , 34 - 36 ]. In addition, previous studies have suggested that the novelty of useful information further facilitates sharing of digital health information [ 32 , 36 ], such as updates about COVID-19 vaccine development [ 12 ]. Given the initial success of mRNA technology in COVID-19 vaccines, mRNA HIV vaccine candidates may possess the inherent features of prospective usefulness and ongoing novelty. As a result, posts presenting pertinent information have the potential to generate more likes and reposts. Meanwhile, the announcements of clinical trials for mRNA HIV vaccines were made amidst intense vaccine debates during the COVID-19 pandemic [ 12 ]. Previous research has shown that perceived controversiality in health information increases viewership but not sharing on social media [ 32 ]. In the context of the heated controversy surrounding vaccines, it is crucial to understand user reactions to new potential vaccines.

In addition to post topics, post valence can play a role in user reactions [ 34 ]. Past research has generally revealed that there are more positive than negative posts on X about vaccines in general [ 13 - 15 ] and, more recently, about COVID-19 vaccines in particular [ 12 , 16 , 17 ]. However, the influence of post valence on user reactions remains unclear. One study on COVID-19 vaccines showed that positive posts on X received more likes but not more reposts [ 16 ]. Another study on vaccines regardless of their type revealed that antivaccine posts garnered more reposts than provaccine posts on X [ 13 ]. A psychological rationale supporting the social transmission of positive content is the motivation of individuals to present themselves positively and shape their self-identity [ 35 , 37 ]. In comparison, social transmission of negative content can be attributed to the idea that certain negative content triggers activation, which drives user reactions [ 35 ].

Furthermore, previous research has shown that account features such as verification status and follower count affect user reactions on social media [ 13 , 16 , 34 ]. Given the vast amounts of information available in the digital age, the authenticity of user accounts becomes crucial in the diffusion of health information. One study revealed that account verification enhanced the number of likes and reposts for posts about COVID-19 vaccines on X [ 16 ]. Another study indicated that follower counts increased the number of reposts for posts about vaccines on X regardless of vaccine type [ 13 ].

Conspiracy Theories

A conspiracy theory refers to the belief that a coalition of powerholders forms secret agreements with malevolent intentions [ 38 , 39 ]. It differs from other types of misinformation by hypothesizing a pattern in which people, objects, or events are interconnected in a causal manner [ 39 ]. Previous research has revealed conspiracy theories as a salient theme in antivaccine discourse on social media, along with other themes such as side effects and inefficacy [ 40 , 41 ]. For HIV vaccines, conspiracy theories are crucial in understanding public discourse against them given the limited information about side effects and inefficacy until future success. An additional contribution of this study is the identification of prominent anti–HIV vaccine conspiracy theories through manual coding of the most engaged with negative posts.

Antivaccine conspiracy theories contribute to vaccine hesitancy [ 42 - 44 ], as observed recently with COVID-19 vaccines [ 10 , 11 ]. Understanding the themes and reasoning behind antivaccine conspiracy theories will provide vital implications for deploying evidence-based and logic-driven strategies to counter them [ 45 - 47 ]. A systematic review of antivaccine discourse on social media from 2015 to 2019 revealed pre–COVID-19 conspiracy theories [ 41 ]. These theories claimed that powerholders promoted vaccines for self-serving interests, including hiding vaccine side effects for financial gain and controlling society and the population [ 40 , 41 ]. During the COVID-19 pandemic, antivaccine conspiracy theories thrived on social media. Some theories claimed that the pandemic was invented for pharmaceutical companies’ profit from vaccines [ 44 ], whereas others linked mRNA COVID-19 vaccines to infertility and population control [ 10 , 11 , 44 , 48 , 49 ]. Another conspiracy theory claimed that Bill Gates and the US government aimed to implant trackable microchips into people through mass vaccination [ 11 , 27 , 49 ]. This aligns with conspiracy theories from earlier years. In particular, the Big Pharma conspiracy theory claims that pharmaceutical companies, together with politicians and other powerholders, conspire against the public interest [ 50 ]. The New World Order conspiracy theory alleges that a power elite with a globalization agenda colludes to rule the world [ 51 ]. Conspiracy theories have also linked other vaccines, such as poliovirus vaccines in the past [ 52 , 53 ] and COVID-19 vaccines in recent years, to HIV infection [ 54 , 55 ]. These conspiracy theories were based on the claims that alleged vaccines contained HIV.

Research Questions

To understand public discourse and reactions surrounding HIV vaccines on the X platform, we put forward the following research questions (RQs):

  • What are the topics of the posts about HIV vaccines? (RQ 1)
  • What is the valence of the posts about HIV vaccines? (RQ 2)
  • How do topics and valence vary across different types of posts? (RQ 3)
  • How do content features (topics and valence) and account features (verification status and follower count) affect 1-click reactions in terms of likes and reposts, respectively? (RQ 4)
  • What are the prominent anti–HIV vaccine conspiracy theories that receive the most reactions? (RQ 5)

Data Source

We collected English-language original posts about HIV vaccines on the X platform from January 1, 2022, to December 31, 2022, using Netlytic [ 56 ]. The selected time frame began in January 2022 with the initiation of mRNA HIV vaccine clinical trials fueling public discussion and concluded in December 2022, a significant month for HIV and AIDS awareness marked by World AIDS Day on the first day of the month. Posts, excluding reposts, that contained both keywords (case insensitive)—“HIV” and “vaccine”—were extracted, resulting in a total of 36,424 posts across 365 days. Posts were collected weekly. Posts published from the last ending time point to at least 24 hours before each collection time point were included in the data set, allowing for a substantial reaction time.

The unit of analysis was a post. For each post, automated extraction produced data for user reactions (the number of likes and reposts) as well as account features (account verification status and follower count). All 36,424 posts underwent topic modeling using latent Dirichlet allocation (LDA) to identify latent topics, as well as sentiment analysis using Valence Aware Dictionary and Sentiment Reasoner (VADER) to access valence. LDA generated topic-specific loadings and identified the dominant topic for each post. VADER generated a valence compound score for each post, which was also categorized as positive, neutral, or negative based on standard VADER classification values.

LDA revealed 3 topics. As the topic of HIV and COVID-19 dominated in a large proportion of posts, we manually coded the 1000 most engaged posts containing the words “HIV” and “COVID” to uncover the salient aspects of HIV vaccines related to COVID-19. To develop coding for subtopics, 2 researchers initially reviewed and coded the top 200 posts with the most reactions. Subtopics were categorized by adapting existing categories from the literature [ 16 , 34 ] and integrating newly identified subtopics from the posts. The Scott π was 0.80 for categorizing subtopics. Subsequently, each researcher independently coded half of the remaining 800 posts.

We then conducted cross-tabulation analyses among all posts to examine the distribution of topics and valence among different types of posts. Furthermore, we conducted linear regression analyses among all posts to assess the influence of content and account features on these 1-click reactions. Of all 36,424 posts, 19,284 (52.94%) received ≥1 like, and 9155 (25.13%) received ≥1 repost. We added a constant value of 1 to all data points for likes and reposts before applying the natural logarithm. This was done to include posts with 0 likes or reposts and to mitigate the skewness of the data distribution.

Of the 28,439 posts that received likes or reposts, 6176 (21.72%) were negative. We manually coded the top 1000 negative posts with the most reactions to uncover prominent anti–HIV vaccine conspiracy theories. To develop coding for conspiracy theories, 2 researchers initially reviewed and coded the top 200 negative posts that received the most reactions. Posts containing conspiracy theories were identified based on expressions of postulated causal connections between people, objects, or events with malevolent intent [ 38 , 39 ]. Conspiracy theories were then classified based on the existing ones from the literature [ 50 , 51 ] and the emerging ones observed in the posts. Coding discrepancies were resolved through a further review of questionable posts and refinement of the conspiracy theories following the approach used in previous social media content analyses [ 40 , 57 ]. The procedure identified conspiracy theories and established intercoder reliability. The Scott π was 0.83 for identifying conspiracy theories and 0.81 for categorizing them. Each researcher then independently coded half of the remaining 800 negative posts.

User Reactions

One-click reactions were measured by the number of likes and reposts, which were automatically extracted. Because a small number of posts garnered significant 1-click reactions, the distribution of likes and reposts was right skewed. To reduce right skewness, we used the natural logarithm of the number of likes and reposts in linear regression analyses, as done in previous research [ 16 , 30 , 34 ].

Post Topics

All posts underwent topic modeling using LDA [ 58 ]. Topic modeling is a commonly used unsupervised learning method that generates a probabilistic model for a corpus of text data [ 59 ]. As a widely used topic model [ 59 ], LDA has been applied to discover topics within rich sources of digital health information, such as electronic health records [ 60 ], reviews on the web [ 61 ], and posts on X [ 16 , 34 ].

LDA relies on 2 matrices to define the underlying topical structure: the word-topic matrix and the document-topic matrix [ 62 ]. In this study, a post was considered a document. The general idea is that a post is represented by a Dirichlet distribution of latent topics, with each latent topic being represented by a Dirichlet distribution of words [ 59 ]. In the word-topic matrix, where the rows represent words and the columns represent topics, each element reveals the conditional probability of a word appearing within a topic [ 62 ]. A topic can be interpreted by examining a list of the most probable words ranked by their frequencies within a given topic using 3 to 30 words [ 63 ]. In the document-topic matrix, where rows represent posts and columns represent topics, each element reveals the conditional probability of a topic underlying a post [ 62 ]. In other words, it reveals the topic-specific loadings for each post.

When interpreting each topic, we reviewed the word-topic matrix as well as sample posts with high topic-specific loadings and significant reactions. LDA generated topic-specific loadings for each post ranging from 0 to 1, with values closer to 1 indicating a higher probability of a topic being associated with a post. Furthermore, LDA determined the dominant topic for each post by selecting the topic with the highest topic-specific loading among all topics. In the cross-tabulation analysis examining the distribution of topics across post types, the dominant topic for each post was entered for analysis. In the linear regression models assessing message-level drivers of user reactions, topic-specific loadings for each post were entered as topic values following previous research [ 16 , 34 ].

Post Valence

We used VADER to analyze the sentiment valence of each post. VADER is a rule-based model specifically attuned for assessing sentiments expressed in social media text [ 64 ]. VADER generated a compound valence score for each post ranging from –1 to 1, with a value of –1 indicating the most negative sentiment and a value of 1 indicating the most positive sentiment [ 65 ]. The standard VADER compound value thresholds for classifying valence categories are as follows: 0.05 to 1 for positive, −0.05 to 0.05 for neutral, and −0.05 to −1 for negative [ 65 ]. In the cross-tabulation analysis examining the distribution of valence among post types, the valence category for each post was entered for analysis. In the linear regression models assessing message-level drivers of user reactions, the VADER compound valence score for each post was used.

This study collected original posts excluding reposts. For each original post, it was automatically extracted whether it was a self-composed post, a quote post with comments, or a reply.

In total, 2 researchers manually coded the top 1000 out of 6176 negative posts with the highest total number of likes and reposts to uncover highly engaged conspiracy theories. They distinguished conspiracy theories from other types of negative information, particularly other types of misinformation, by recognizing the presence of a hypothesized pattern of causal connections between people, objects, or events for malicious intent [ 38 , 39 ]. Conspiracy theories were then categorized based on the existing ones from the literature and the emerging ones observed in the posts.

As an example, consider a post paraphrased as follows:

Image using condoms consistently, only to contract HIV from a COVID vaccine.

It was posted on February 9, 2022, and received 783 likes and 296 reposts. This post was not coded as displaying a conspiracy theory as it only presented misinformation suggesting that COVID-19 vaccines caused HIV. In comparison, another post was paraphrased as follows:

The COVID vaccine contained a spike protein derived from HIV. I was banned from saying this and ridiculed for months. Also, pharmacies stock up HIV self-tests.

It was posted on February 8, 2022, with 147 likes and 48 reposts. This post was coded as displaying a conspiracy theory. It was further classified within the category of conspiracy theories linked to COVID-19 vaccines containing, causing, or increasing HIV. This post suggested a hypothesized pattern of maliciously intended causal connections between the claim that the COVID-19 vaccine contained HIV and the stocking of HIV self-tests in pharmacies. As another example, a post was paraphrased as follows:

Scientists uncover a “highly virulent” strain of HIV in the Netherlands.

It was posted on February 12, 2022, and received 11 likes and 11 reposts. This post conveyed negative information but did not present a conspiracy theory. In comparison, another post was paraphrased as follows:

By coincidence again, the development of a new mRNA HIV vaccine began just before the emergence of the new HIV strain.

It was posted on February 8, 2022, and received 102 likes and 4 reposts. This post was coded as presenting a conspiracy theory and further classified into the category of conspiracy theories linked to the identification of a new highly virulent HIV strain. This post emphasized the speculative timing of the discovery of the new highly virulent HIV strain occurring shortly after the announcement of the development of a new mRNA HIV vaccine.

Account Features

For each post, the posting account’s verification status and follower count were automatically extracted.

Data Analysis

We used cross-tabulation analyses to investigate the distribution of topics and valence across different post types, in which the dominant topic and valence category for each post were entered, respectively, alongside the post type. We used linear regression models to examine the message-level drivers of user reactions among posts that received likes or reposts. In the linear regression models, a constant value of 1 was added to all data points of like and repost counts. The natural log-transformed values for each post were then regressed on 3 topic-specific loadings generated from LDA, the valence compound score generated from VADER, and 2 autoextracted account features—account verification status and follower count. The “plus one” technique was used to include posts that received 0 likes or reposts and to address the skewness of the data distribution.

Ethical Considerations

Following Long Island University’s institutional review board determination process, an institutional review board review was deemed unnecessary for this study, which collected and analyzed publicly available social media data. All referenced posts were paraphrased to avoid association with any particular user on the X platform.

RQ 1 asked about the topics present in all the posts. We trained a topic model using LDA exploring topic numbers ranging from 2 to 20. The optimal number of topics ( k ) was selected considering both the coherence score ( C v ) and the topic model visualization in a Python library called pyLDAvis , as done in previous research [ 16 , 66 ]. C v is a metric that reflects the semantic coherence of topics by evaluating the word co-occurrence likelihood within topics [ 67 ]. A higher C v indicates a better classification achieved by the topic model. In this study, the model with 2 topics ( k =2) yielded the highest C v (0.42), whereas the model with 3 topics ( k =3) yielded the second highest C v (0.35). The pyLDAvis chart depicts each topic as a circle. Overlapping areas between circles suggest similarities in topics. Thus, a chart without overlapping circles is preferable for k . The pyLDAvis chart for this study showed that, when the value of k was 2 or 3, the circles did not overlap. However, when k reached 4, the circles began to overlap, and overlapping circles persisted for values of k ranging from 4 to 20. Between the k values of 2 and 3, we opted for a model comprising 3 topics ( k =3) considering that a smaller number of topics tends to result in overly broad meanings for each topic [ 68 ].

Table 1 summarizes the 3 topics and lists their representative posts. Each topic was interpreted by examining the top 10 probable words ranked by frequency, along with sample posts exhibiting high topic-specific loadings and 1-click reactions. Topic 1 was HIV and COVID-19, covering 78% of the tokens [ 69 ] and dominating in 92.46% (33,678/36,424) of the posts. Topic 2 was mRNA HIV vaccine trials, covering 14% of the tokens and dominating in 5.91% (2151/36,424) of the posts. Topic 3 was HIV vaccine and immunity, covering 8% of the tokens and dominating in 1.63% (595/36,424) of the posts.

Figure 1 illustrates the daily numbers of original posts about HIV vaccines throughout 2022, in total and categorized into 3 topics. Moderna’s announcement of clinical trials for its first mRNA HIV vaccine on January 27, 2022, likely triggered the initial surge, culminating in a daily peak when the number of posts reached 805 on January 29, 2022. The daily number of posts about mRNA HIV vaccine trials (topic 2) in the week following Moderna’s announcement was higher than on other days throughout the year. Nevertheless, even during that week, there were higher daily numbers of posts about HIV and COVID-19 (topic 1), which remained dominant among the 3 topics during the entire year. The year’s second and highest daily peak occurred on February 8, 2022, recording a total of 1603 posts, most of which focused on HIV and COVID-19 (topic 1). This could be attributed to the emergence of new HIV-related events in early February 2022, including the promotion of HIV tests by public figures [ 64 ] and the discovery of a new highly virulent HIV strain [ 65 ]. The third highest daily peak, comprising 1085 posts, occurred on May 18, 2022, which has marked HIV Vaccine Awareness Day since 1998. Most of the posts centered on HIV and COVID-19 (topic 1). The remainder of the year did not reach such high peaks, with the largest daily volume of 205 posts occurring on December 2, 2022, the day following World AIDS Day, observed since 1988. Similar to previous daily peaks, most of the posts revolved around HIV and COVID-19 (topic 1).

The results revealed the dominance of HIV and COVID-19 (topic 1) in 92.46% (33,678/36,424) of the posts, with HIV as the most frequent word and COVID as the fourth most frequent word. To gain a deeper understanding of salient aspects of HIV vaccines related to COVID-19, we manually coded the top 1000 posts with the highest total number of likes and reposts that contained both HIV and COVID . Table 2 summarizes the subtopics and their representative posts with like and repost counts.

The first major subtopic, comprising 24% (240/1000) of the posts, focused on the reciprocal influence of HIV vaccines and COVID-19 vaccines on each other’s development. Years of HIV vaccine research facilitated the rapid development of mRNA COVID-19 vaccines, and the success of COVID-19 vaccines might accelerate the development of mRNA HIV vaccines. The second major subtopic, comprising 17.6% (176/1000) of the posts, involved comparisons between HIV and COVID-19 in various aspects. Specifically, the development speed of HIV vaccines compared to COVID-19 vaccines was a major point of comparison. In addition, some posts questioned whether potential HIV vaccines could be comparable to COVID-19 vaccines in terms of cost and accessibility during rollout. Others raised concerns about efficacy, safety, and inequality for both vaccines. The third major subtopic, comprising 26.5% (265/1000) of the posts, connected COVID-19 vaccines with HIV. One issue discussed was whether COVID-19 vaccines contained, caused, or increased HIV. Another issue raised was distinguishing between HIV symptoms and COVID-19 vaccine side effects, such as a fabricated condition called VAIDS , short for vaccine-acquired immunodeficiency syndrome. The fourth major subtopic, comprising 13.6% (136/1000) of the posts, featured conspiracy theories that presented hypothesized patterns linking COVID-19, HIV, and their vaccines with malicious intent. Prominent conspiracy theories in this subtopic included connecting misinformation that COVID-19 vaccines contain, cause, or increase HIV with the ongoing development of HIV vaccines; associating HIV and AIDS symptoms with side effects of COVID-19 vaccines; and claiming that COVID-19 originated from unsuccessful HIV vaccine research. As this study also manually coded the 1000 most engaged negative posts to identify prominent conspiracy theories, additional results pertaining to conspiracy theories will be discussed further in another subsection. The remaining posts related to HIV and COVID-19 included those that generally mentioned research on them or made connections without specifying details.

a mRNA: messenger RNA.

what are the types of research papers

a The reaction count is the total number of likes and reposts.

b PrEP: pre-exposure prophylaxis.

c VAIDS: vaccine-acquired immunodeficiency syndrome.

d The categories labeled as “other” contain various topics. Thus, no representative post is displayed.

RQ 2 asked about the sentiment valence present in all the posts. According to the standard VADER classification values, valence is categorized by compound scores as follows: positive (0.05 to 1), neutral (−0.05 to 0.05), and negative (−0.05 to −1) [ 65 ]. On average, all posts had a marginally positive score of 0.053. HIV and COVID-19 (topic 1) had a slightly positive average score of 0.055. The mRNA HIV vaccine trials (topic 2) had a neutral average score of 0.040, leaning toward the positive side. HIV vaccine and immunity (topic 3) had a more neutral average score of −0.0008. Moreover, 42.78% (15,584/36,424) of the posts were positive, 25.64% (9338/36,424) of the posts were neutral, and 31.58% (11,502/36,424) of the posts were negative.

Topics and Valence Across Post Types

Of the 36,424 posts, 18,580 (51.01%) were replies, making up over half of the overall count. Self-composed posts totaled 41.6% (15,151/36,424), whereas the remaining 7.39% (2693/36,424) were quote posts. RQ 3 asked about the distribution of topics and valence among the 3 post types. As Table 3 shows, the distribution of topics varied by post type (N=36,424, χ 2 4 =2511.4, P <.001). Of the self-composed posts, 85.36% (12,933/15,151) focused on HIV and COVID-19 (topic 1) and 13.21% (2001/15,151) focused on mRNA HIV vaccine trials (topic 2). In comparison, quote posts and replies exhibited a different pattern, in each case >97% of posts centering on HIV and COVID-19 (topic 1; 2616/2693, 97.14% and 18,129/18,580, 97.57%, respectively).

As Table 4 shows, the distribution of valence also varied by post type (N=36,424, χ 2 4 =911.7, P <.001). The proportion of positive posts was slightly higher among self-composed posts at 44.95% (6810/15,151) compared to replies at 41.09% (7634/18,580) and quote posts at 42.33% (1140/2693). Self-composed posts had a smaller proportion of negative posts at 23.56% (3570/15,151) compared to replies at 37.64% (6994/18,580) and quote posts at 34.83% (938/2693). The proportion of neutral posts was larger for self-composed posts at 31.49% (4771/15,151) compared to quote posts at 22.84% (615/2693) and replies at 21.27% (3952/18,580).

Regarding the distribution of topics and valence among the 3 types of posts, quote posts and replies displayed similarities, whereas self-composed posts diverged. Compared to self-composed posts, which initiate new conversations, there was a higher proportion of HIV and COVID-19-related posts (topic 1) and a greater proportion of negative posts among quote posts and replies, which contribute to existing conversations.

a N=36,424, χ 2 4 =2511.4, P <.001.

b mRNA: messenger RNA.

a N=36,424, X 2 4 =911.7, P <.001.

Content and Account Features Influencing User Reactions

RQ 4 asked about the influence of content and account features on likes and reposts.

Liking is more common than reposting. While 52.94% (19,284/36,424) of posts received an average of 24.83 likes, ranging from 1 to 102,843, a total of 25.13% (9155/36,424) posts received an average of 11.38 reposts, ranging from 1 to 10,572. Table 5 reveals the influence of content features (topics and valence) and account features (verification status and follower count) on the natural log-transformed number of likes and reposts. Both linear regression models were significant at P <.001. The adjusted  R 2 was 0.072 for the like model and 0.090 for the repost model.

Among the 3 topics identified using LDA, HIV and COVID-19 (topic 1) did not affect like counts but decreased repost counts. In comparison, mRNA HIV vaccine trials (topic 2) decreased like counts while increasing repost counts. Positive valence increased like and repost counts. Account verification status and follower count increased like and repost counts.

a The natural logarithm, ln (Y i +1), was calculated on like and repost counts. This transformation was conducted to include posts receiving 0 likes and reposts, as well as to account for the skewness of the data distribution.

b F (model significance): P <.001; adjusted R 2 =0.072.

c F (model significance): P <.001; adjusted R 2 =0.090.

d mRNA: messenger RNA.

e The models excluded topic 3 on HIV vaccine and immunity to address multicollinearity issues arising from its correlations with topics 1 and 2. The reported standard β for topic 3 represents a possible β value if it had been included in the models.

Posts With Most Reactions

Table 6 summarizes posts ranked within the top 5 for the number of likes and reposts presented in chronological order. It is worth noting that all posts in the top 5 for likes and reposts were self-composed. One particular post, which garnered the most likes (n=102,843) and reposts (n=10,572), expressed the incredible feeling of witnessing the development of an HIV vaccine within our lifetimes. It was posted by an unverified account on January 28, 2022, the day after Moderna’s announcement of clinical trials for its first mRNA HIV vaccine.

a Ranks beyond the fifth were not indicated.

Anti–HIV Vaccine Conspiracy Theories

RQ 5 asked about prominent anti–HIV vaccine conspiracy theories. Of the 1000 negative posts that received the most reactions, 227 (22.7%) contained conspiracy theories. As Table 7 shows, we classified these prominent anti–HIV vaccine conspiracy theories into 4 categories and presented their representative posts and the number of reactions.

The first category, comprising 44.9% (102/227) of the posts, formulated conspiracy theories by connecting COVID-19, COVID-19 vaccines, HIV, and HIV vaccines. For instance, 52.9% (54/102) of these posts connected the misinformation regarding COVID-19 vaccines containing, causing, or increasing HIV with the ongoing efforts to develop HIV vaccines. This misinformation may have arisen from past occurrences resurfacing following Moderna’s initiation of its mRNA HIV vaccine trials. One incident occurred at the end of 2020, when an Australian COVID-19 vaccine, which used a small fragment of protein from HIV to clamp SARS-CoV-2’s spike proteins, was abandoned due to false HIV-positive results [ 70 ]. Another incident occurred in October 2020, when 4 researchers sent a letter to a medical journal expressing concerns about the potential increased risk of HIV acquisition among men receiving COVID-19 vaccines using adenovirus type-5 vectors without supporting data from COVID-19 vaccines [ 71 ]. The misinformation typically interpreted the incidents out of context and generally suggested that COVID-19 vaccines contained, caused, or increased HIV without specifying details. In addition, there were conspiracy theories linking HIV and AIDS to COVID-19 vaccine side effects, including a fabricated condition known as VAIDS. VAIDS falsely suggests that COVID-19 vaccines caused immune deficiency [ 72 ]. Furthermore, there were claims that COVID-19 originated from unsuccessful HIV vaccine research.

The second category, comprising 38.3% (87/227) of the posts, suggested that the alignment of concurrent events with Moderna’s start of mRNA HIV vaccine trials in late January 2022 was intentional to manipulate the market for HIV vaccines. These events included the rising HIV discussion and fear; promotion of HIV tests by public figures [ 73 ]; the discovery of a new highly virulent HIV strain [ 74 ]; and the passing away of HIV researchers, including Luc Montagnier, codiscoverer of HIV with an antivaccine stance during the COVID-19 pandemic [ 75 ], all occurring in early February 2022.

The third category, with 11.5% (26/227) of the posts, revealed conspiracy theories based on the distrust of powerholders [ 76 ]. Some posts extended existing conspiracy theories, such as the Big Pharma conspiracy theory [ 50 ] and the New World Order conspiracy theory [ 51 ], into the context of HIV vaccines, emphasizing the intent of powerholders, including major pharmaceutical companies and governments, behind vaccine promotion for financial profits and society control. Other posts created conspiracy theories about the government’s research on HIV vaccines. The remaining posts generally stated that HIV vaccines were a scam. The final category comprised the remaining 5.3% (12/227) of the posts with other conspiracy theories.

It is worth noting that, of the 227 posts containing conspiracy theories, 39 (17.2%) were posted by accounts that had already been suspended at the time of manual coding. For these posts, the X platform displays the following message—“This post is from a suspended account”—and the content of the post is not visible. The X platform suspends accounts that violate its rules [ 77 ]. However, specific details of the violations are not accessible on the platform. The invisibility of these posts halted their spread when the suspension was enacted. For our manual coding of these posts, we used the text obtained during the data collection process.

b The posts were from suspended accounts.

d The categories labeled as “other” contain various conspiracy theories. Thus, no representative post is displayed.

Principal Findings

This study investigated the patterns of public discourse and the message-level drivers of user reactions on the X platform regarding HIV vaccines through the analysis of posts using machine learning algorithms. We examined the distribution of topics and valence across different post types and assessed the influence of content features (topics and valence) and account features (account verification status and follower count) on like and repost counts. In addition, we manually coded the 1000 most engaged posts about HIV and COVID-19 to understand the salient aspects of HIV vaccines related to COVID-19 and the 1000 most engaged negative posts to identify prominent anti–HIV vaccine conspiracy theories.

The results revealed that COVID-19 plays a substantial role as a context for public discourse and reactions regarding HIV vaccines. Of the 3 topics identified using LDA, the leading topic was HIV and COVID-19, covering 78% of tokens and dominating in 92.46% (33,678/36,424) of the posts. Furthermore, on each of the top 4 days with the highest post counts, most of the posts were about HIV and COVID-19. This comprehensive topic included important subtopics that linked HIV vaccines with COVID-19 vaccines, as demonstrated through the manual coding of the 1000 most engaged posts about HIV and COVID-19. These subtopics encompassed the reciprocal influence of HIV vaccines and COVID-19 vaccines in advancing each other’s development; comparisons in their development speed; inquiries about the possible alignment of HIV vaccines with COVID-19 vaccines in terms of cost and accessibility during distribution; and concerns about efficacy, safety, and equality for both vaccines.

COVID-19 positioned HIV vaccines in both a positive and negative context. On the one hand, the success of mRNA technology in COVID-19 vaccines [ 6 ] potentially cast mRNA HIV vaccines in a positive light. The topic of HIV and COVID-19 had a marginally positive valence score of 0.055. Moreover, 3 (60%) out of the 5 most liked posts and 2 (40%) out of the 5 most reposted posts expressed excitement about advancements in HIV vaccines that were based on the experience with COVID-19 vaccines. On the other hand, antivaccine discourse, including conspiracy theories, heated up during the COVID-19 pandemic [ 10 , 11 , 27 , 44 , 48 , 49 ], which posed challenges to HIV vaccines. Of the 1000 most engaged posts about HIV and COVID-19, a total of 136 (13.6%) featured conspiracy theories. Of the 1000 most engaged negative posts, 227 (22.7%) contained conspiracy theories, with 102 (44.9%) of them revolving around HIV and COVID-19. For instance, a prominent conspiracy theory connected the misinformation about COVID-19 vaccines containing, causing, or increasing HIV infection [ 55 ] with the initiation of clinical trials for mRNA HIV vaccines [ 4 , 5 ], implying a malevolent intent behind the deliberate connection. The results indicate that conspiracy theories tend to elicit an approach-oriented response, as evidenced by people engaging in liking and reposting, as opposed to an avoidance-oriented approach [ 39 ]. This underscores the need to intensify efforts to counter conspiracy theories in public health communication about HIV vaccines.

According to a study conducted by the Pew Research Center, irrespective of the subject matter, replies constituted the largest portion of original posts on X, followed by self-composed and quote posts [ 28 ]. Specifically, the number of replies was 3 times greater than that of self-composed posts. In this study, although replies constituted slightly more than half (18,580/36,424, 51.01%) of the posts, it is worth noting that the subject of HIV vaccines elicited a higher proportion of self-composed posts at 41.6% (15,151/36,424). Specifically, the number of replies was 23% higher than that of self-composed posts. Moreover, the topic of mRNA vaccine trials was most evident in self-composed posts compared to replies and quote posts. In comparison, there was a higher proportion of focus on the topic of HIV and COVID-19 and a greater proportion of negative posts among quote posts and replies, which contribute to existing conversations. This suggests that users were more likely to initiate new conversations rather than joining existing conversations about mRNA HIV vaccines. In contrast, they were more likely to join existing conversations rather than starting new conversations about HIV and COVID-19. In addition, users were less likely to initiate new conversations negatively but more likely to contribute negatively to existing ones.

As the primary topic, HIV and COVID-19 had no impact on like counts but had a negative impact on repost counts. In comparison, the topic of mRNA HIV vaccine trials had a negative impact on like counts and a positive impact on repost counts. The results should be interpreted while considering that, as revealed in previous research [ 16 , 34 ] and this study, most posts on the X platform are unlikely to receive likes and even less likely to receive reposts. In this study, among the total of 36,424 posts, approximately half (n=19,284, 52.94%) received likes, and approximately one-quarter (n=9155, 25.13%) received reposts. To include all posts and mitigate the data distribution skewness in the linear regression analysis, we applied the “plus one” technique. This involved adding a constant value of 1 to all like and repost data points before taking the natural logarithm. Although most posts were not liked or reposted, it is noteworthy that the topic of mRNA HIV vaccines led to an increase in repost counts, highlighting its positive influence on social sharing. In addition, 2 (40%) out of the 5 most reposted posts were about mRNA HIV vaccine trials. These results correspond to the findings of previous research that suggested the diffusion of novel useful information [ 12 , 16 , 32 , 36 ].

The overall valence of the posts about HIV vaccines was marginally positive. The positivity aligns with the positive sentiment found in posts on X about vaccines in general [ 13 - 15 ] and COVID-19 vaccines in particular [ 12 , 16 , 17 ]. However, the positivity about HIV vaccines was not apparent as the average score of 0.053 placed it on the edge of the neutral range, which goes from −0.05 to 0.05 according to the standard VADER classification values. Positive sentiment had a favorable impact on like and repost counts, partially consistent with findings of previous research on COVID-19 vaccines [ 16 ]. The post that achieved the most likes conveyed the incredible feeling of witnessing the development of an HIV vaccine in our lifetimes. This could be attributed to the psychological rationale that social transmission of positive content fulfills people’s motivation to present a positive image [ 35 , 37 ]. In alignment with the findings of previous research [ 13 , 16 , 34 ], account verification status and follower count increased like and repost counts.

This study has implications for public health communication related to HIV vaccines and potentially other vaccines. Given the massive scale of the COVID-19 vaccination campaign, it is understandable that people will draw comparisons with other vaccines. Topic modeling identified HIV and COVID-19 as the primary topic, and manual coding revealed various intertwined aspects. Leveraging the advantages observed in the COVID-19 vaccine campaign, such as its widespread accessibility, could be valuable. Furthermore, addressing common concerns such as efficacy, safety, and inequality could also prove beneficial.

In the case of HIV vaccines, it is essential to tackle concerns associated with COVID-19 vaccines, especially those related to HIV vaccines. A major subtopic of HIV and COVID-19 involved suspicions about COVID-19 vaccines containing, causing, or increasing HIV. Another major subtopic was the confusion between HIV symptoms and the alleged side effects of COVID-19 vaccines, such as VAIDS. Misinformation concerning both subtopics has been woven into conspiracy theories, further complicating this situation. To combat misinformation and conspiracies that have these elements, efforts could focus on promoting evidence-based factual information [ 45 - 47 ].

Another notable technique in the conspiracy theories was linking concurrent COVID-19 and other HIV-related events in unsubstantiated relationships to create false perceptions, suggesting that these events were intentional to manipulate the market for HIV vaccines. These HIV-related events included rising HIV discussion and fear, promotion of HIV tests by public figures [ 73 ], the discovery of a new highly virulent HIV strain [ 74 ], and the passing away of HIV researchers, all occurring in early February 2022. These findings suggest that refuting false connections among such concurrent events can be an effective strategy to counter these conspiracy theories [ 45 - 47 ]. These occurrences, frequently entwined within conspiracy theories, could be specifically addressed in public health communication efforts.

Limitations

This study has several limitations. Because we used autoidentified content features (topics and valence) and autoextracted account features (verification status and follower count) in the regression models to predict the autoextracted number of user reactions (likes and reposts), the results were mostly limited to the examined autoidentified and autoextracted factors. For instance, political polarization, which manifested in a wide range of issues, including response to vaccines [ 78 ], could be a factor worth investigating in future studies. Furthermore, manual coding of conspiracy theories revealed a prevalent technique of twisting concurrent events into false relationships. This underscores the significance of refuting unfounded associations among these incidents to counter such conspiracy theories. It will be interesting for future research to assess the impact of this technique on user reactions to conspiracy theories. These findings could provide further insights into public health communication strategies to combat conspiracy theories.

Conclusions

The results highlight COVID-19 as a significant backdrop for public discourse and reactions on the X platform regarding HIV vaccines. COVID-19 situated HIV vaccines in both a positive and negative context. The success of mRNA COVID-19 vaccines shed a positive light on HIV vaccines. However, COVID-19 also situated HIV vaccines in a negative context, as evident in anti–HIV vaccine conspiracy theories falsely linking HIV vaccines to COVID-19. The findings provide implications for public health communication strategies concerning HIV vaccines.

Acknowledgments

This study was supported in part by the College of Arts and Sciences and the Harrington School of Communication and Media at the University of Rhode Island. The authors express their appreciation for the support. The funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report.

Data Availability

The data sets collected and analyzed during this study are available from the corresponding author upon request.

Conflicts of Interest

None declared.

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Abbreviations

Edited by G Eysenbach; submitted 04.10.23; peer-reviewed by X Ma, J Zhang; comments to author 18.10.23; revised version received 08.11.23; accepted 28.02.24; published 03.04.24.

©Jueman M Zhang, Yi Wang, Magali Mouton, Jixuan Zhang, Molu Shi. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 03.04.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

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  1. What are the different types of research papers?

    Experimental research paper. This type of research paper basically describes a particular experiment in detail. It is common in fields like: biology. chemistry. physics. Experiments are aimed to explain a certain outcome or phenomenon with certain actions. You need to describe your experiment with supporting data and then analyze it sufficiently.

  2. What are the Different Types of Research Papers?

    Discover the different types of research papers in academic writing, including argumentative, analytical, experimental, review, case study, comparative, survey, and interpretative research papers. Gain a comprehensive understanding of their underlying principles and objectives.

  3. Types of Research Papers

    Although research paper assignments may vary widely, there are essentially two basic types of research papers. These are argumentative and analytical.. Argumentative. In an argumentative research paper, a student both states the topic they will be exploring and immediately establishes the position they will argue regarding that topic in a thesis statement.

  4. Research Paper

    Definition: Research Paper is a written document that presents the author's original research, analysis, and interpretation of a specific topic or issue. It is typically based on Empirical Evidence, and may involve qualitative or quantitative research methods, or a combination of both. The purpose of a research paper is to contribute new ...

  5. Genre and the Research Paper

    Research: What it is. A research paper is the culmination and final product of an involved process of research, critical thinking, source evaluation, organization, and composition. It is, perhaps, helpful to think of the research paper as a living thing, which grows and changes as the student explores, interprets, and evaluates sources related ...

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    Most research assignments ask you to engage in one of two approaches: Explore and evaluate (present an analysis) Persuade (present an argument) The tabs below will give you more information about each type. Your professor may allow you to choose between these strategies or may ask you to use only one. If you're not sure which type you should ...

  7. Types of Research Designs Compared

    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.

  8. How to Write a Research Paper

    Choose a research paper topic. Conduct preliminary research. Develop a thesis statement. Create a research paper outline. Write a first draft of the research paper. Write the introduction. Write a compelling body of text. Write the conclusion. The second draft.

  9. Research Paper Format

    Formatting a Chicago paper. The main guidelines for writing a paper in Chicago style (also known as Turabian style) are: Use a standard font like 12 pt Times New Roman. Use 1 inch margins or larger. Apply double line spacing. Indent every new paragraph ½ inch. Place page numbers in the top right or bottom center.

  10. LibGuides: Academic Writing: FAQs: Types of Academic Writing

    A research paper requires you to form an opinion on a topic, research and gain expert knowledge on that topic, and then back up your own opinions and assertions with facts found through your thorough research. Types of Research Papers This guide discusses the different types of research papers that you might encounter in an academic setting ...

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    Definition paper. Experimental paper. Interpretative paper. Survey paper. Let us understand each type of research paper in detail. 1. Analytical Research Paper. While writing an analytical paper, the student asks a question, collects relevant data from a variety of sources, and analyzes it. The findings, viewpoints, and conclusions presented in ...

  12. How To Write A Research Paper (FREE Template

    Step 1: Find a topic and review the literature. As we mentioned earlier, in a research paper, you, as the researcher, will try to answer a question.More specifically, that's called a research question, and it sets the direction of your entire paper. What's important to understand though is that you'll need to answer that research question with the help of high-quality sources - for ...

  13. Types of Research Papers.

    Argumentative research papers are prevalent in disciplines such as philosophy, social sciences, and humanities, where different perspectives and debates are common. 6. Case Study Research Papers: Case study research papers provide an in-depth analysis of a particular individual, group, organization, or event.

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    It is perfect for papers in Psychology, Journalism, Healthcare, and subjects where accuracy is vital. Secondary. This research type of work is mainly developed with sources that represent secondary references. These include books in print or found online, scientific journals, peer-reviewed documents, etc.

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    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 ...

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    Research paper format is an essential aspect of academic writing that plays a crucial role in the communication of research findings.The format of a research paper depends on various factors such as the discipline, style guide, and purpose of the research. It includes guidelines for the structure, citation style, referencing, and other elements of the paper that contribute to its overall ...

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    There are various types of research that are classified by objective, depth of study, analysed data and the time required to study the phenomenon etc. ... A concept paper is a short document written by a researcher before starting their research project, explaining what the study is about, why it is needed and the methods that will be used.

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    The length of a research paper ranges from 4,000 to 6,000 words. However, depending on the assignment, your work can be 2,000 words or even 10,000 words. Your academic level and the assignment complexity influence the essay length. Simple Steps for Writing Different Types of Research Papers

  19. What types of studies are there?

    There are various types of scientific studies such as experiments and comparative analyses, observational studies, surveys, or interviews. The choice of study type will mainly depend on the research question being asked. When making decisions, patients and doctors need reliable answers to a number of questions.

  20. What Is a Research Design

    A research design is a strategy for answering your research question using empirical data. Creating a research design means making decisions about: Your overall research objectives and approach. Whether you'll rely on primary research or secondary research. Your sampling methods or criteria for selecting subjects. Your data collection methods.

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    The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

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    Original Research: This is the most common type of journal manuscript used to publish full reports of data from research. It may be called an Original Article, Research Article, Research, or just Article, depending on the journal. The Original Research format is suitable for many different fields and different types of studies.

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    Top 10 Research Topics For Students. Given below are some Research Topic examples that you can choose for your paper, or get an idea from. Let's dive in and get you that A+ and your dream university! Religion and Globalization - Students can choose this topic to study if there is any relationship between religion and globalisation, and how ...

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    In this paper, we explore the dissipative dynamics of these systems in the classical limit. We derive a general equation of motion capturing the effective nonlinear dissipation introduced by the bath and apply it to the special case of a Bose-Hubbard model, where it leads to an unconventional type of dissipative nonlinear Schr\"odinger equation.

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    Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design. When planning your methods, there are two key decisions you will make. First, decide how you will collect data. Your methods depend on what type of data you need to answer your research question:

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    Background: The initiation of clinical trials for messenger RNA (mRNA) HIV vaccines in early 2022 revived public discussion on HIV vaccines after 3 decades of unsuccessful research. These trials followed the success of mRNA technology in COVID-19 vaccines but unfolded amid intense vaccine debates during the COVID-19 pandemic. It is crucial to gain insights into public discourse and reactions ...