purpose of research article

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11.1 The Purpose of Research Writing

Learning objectives.

Identify reasons to research writing projects.
Outline the steps of the research writing process.

Why was the Great Wall of China built? What have scientists learned about the possibility of life on Mars? What roles did women play in the American Revolution? How does the human brain create, store, and retrieve memories? Who invented the game of football, and how has it changed over the years?

You may know the answers to these questions off the top of your head. If you are like most people, however, you find answers to tough questions like these by searching the Internet, visiting the library, or asking others for information. To put it simply, you perform research.

Whether you are a scientist, an artist, a paralegal, or a parent, you probably perform research in your everyday life. When your boss, your instructor, or a family member asks you a question that you do not know the answer to, you locate relevant information, analyze your findings, and share your results. Locating, analyzing, and sharing information are key steps in the research process, and in this chapter, you will learn more about each step. By developing your research writing skills, you will prepare yourself to answer any question no matter how challenging.

Reasons for Research

When you perform research, you are essentially trying to solve a mystery—you want to know how something works or why something happened. In other words, you want to answer a question that you (and other people) have about the world. This is one of the most basic reasons for performing research.

But the research process does not end when you have solved your mystery. Imagine what would happen if a detective collected enough evidence to solve a criminal case, but she never shared her solution with the authorities. Presenting what you have learned from research can be just as important as performing the research. Research results can be presented in a variety of ways, but one of the most popular—and effective—presentation forms is the research paper . A research paper presents an original thesis, or purpose statement, about a topic and develops that thesis with information gathered from a variety of sources.

If you are curious about the possibility of life on Mars, for example, you might choose to research the topic. What will you do, though, when your research is complete? You will need a way to put your thoughts together in a logical, coherent manner. You may want to use the facts you have learned to create a narrative or to support an argument. And you may want to show the results of your research to your friends, your teachers, or even the editors of magazines and journals. Writing a research paper is an ideal way to organize thoughts, craft narratives or make arguments based on research, and share your newfound knowledge with the world.

Write a paragraph about a time when you used research in your everyday life. Did you look for the cheapest way to travel from Houston to Denver? Did you search for a way to remove gum from the bottom of your shoe? In your paragraph, explain what you wanted to research, how you performed the research, and what you learned as a result.

Research Writing and the Academic Paper

No matter what field of study you are interested in, you will most likely be asked to write a research paper during your academic career. For example, a student in an art history course might write a research paper about an artist’s work. Similarly, a student in a psychology course might write a research paper about current findings in childhood development.

Having to write a research paper may feel intimidating at first. After all, researching and writing a long paper requires a lot of time, effort, and organization. However, writing a research paper can also be a great opportunity to explore a topic that is particularly interesting to you. The research process allows you to gain expertise on a topic of your choice, and the writing process helps you remember what you have learned and understand it on a deeper level.

Research Writing at Work

Knowing how to write a good research paper is a valuable skill that will serve you well throughout your career. Whether you are developing a new product, studying the best way to perform a procedure, or learning about challenges and opportunities in your field of employment, you will use research techniques to guide your exploration. You may even need to create a written report of your findings. And because effective communication is essential to any company, employers seek to hire people who can write clearly and professionally.

Writing at Work

Take a few minutes to think about each of the following careers. How might each of these professionals use researching and research writing skills on the job?

Medical laboratory technician
Small business owner
Information technology professional
Freelance magazine writer

A medical laboratory technician or information technology professional might do research to learn about the latest technological developments in either of these fields. A small business owner might conduct research to learn about the latest trends in his or her industry. A freelance magazine writer may need to research a given topic to write an informed, up-to-date article.

Think about the job of your dreams. How might you use research writing skills to perform that job? Create a list of ways in which strong researching, organizing, writing, and critical thinking skills could help you succeed at your dream job. How might these skills help you obtain that job?

Steps of the Research Writing Process

How does a research paper grow from a folder of brainstormed notes to a polished final draft? No two projects are identical, but most projects follow a series of six basic steps.

These are the steps in the research writing process:

Choose a topic.
Plan and schedule time to research and write.
Conduct research.
Organize research and ideas.
Draft your paper.
Revise and edit your paper.

Each of these steps will be discussed in more detail later in this chapter. For now, though, we will take a brief look at what each step involves.

Step 1: Choosing a Topic

As you may recall from Chapter 8 “The Writing Process: How Do I Begin?” , to narrow the focus of your topic, you may try freewriting exercises, such as brainstorming. You may also need to ask a specific research question —a broad, open-ended question that will guide your research—as well as propose a possible answer, or a working thesis . You may use your research question and your working thesis to create a research proposal . In a research proposal, you present your main research question, any related subquestions you plan to explore, and your working thesis.

Step 2: Planning and Scheduling

Before you start researching your topic, take time to plan your researching and writing schedule. Research projects can take days, weeks, or even months to complete. Creating a schedule is a good way to ensure that you do not end up being overwhelmed by all the work you have to do as the deadline approaches.

During this step of the process, it is also a good idea to plan the resources and organizational tools you will use to keep yourself on track throughout the project. Flowcharts, calendars, and checklists can all help you stick to your schedule. See Chapter 11 “Writing from Research: What Will I Learn?” , Section 11.2 “Steps in Developing a Research Proposal” for an example of a research schedule.

Step 3: Conducting Research

When going about your research, you will likely use a variety of sources—anything from books and periodicals to video presentations and in-person interviews.

Your sources will include both primary sources and secondary sources . Primary sources provide firsthand information or raw data. For example, surveys, in-person interviews, and historical documents are primary sources. Secondary sources, such as biographies, literary reviews, or magazine articles, include some analysis or interpretation of the information presented. As you conduct research, you will take detailed, careful notes about your discoveries. You will also evaluate the reliability of each source you find.

Step 4: Organizing Research and the Writer’s Ideas

When your research is complete, you will organize your findings and decide which sources to cite in your paper. You will also have an opportunity to evaluate the evidence you have collected and determine whether it supports your thesis, or the focus of your paper. You may decide to adjust your thesis or conduct additional research to ensure that your thesis is well supported.

Remember, your working thesis is not set in stone. You can and should change your working thesis throughout the research writing process if the evidence you find does not support your original thesis. Never try to force evidence to fit your argument. For example, your working thesis is “Mars cannot support life-forms.” Yet, a week into researching your topic, you find an article in the New York Times detailing new findings of bacteria under the Martian surface. Instead of trying to argue that bacteria are not life forms, you might instead alter your thesis to “Mars cannot support complex life-forms.”

Step 5: Drafting Your Paper

Now you are ready to combine your research findings with your critical analysis of the results in a rough draft. You will incorporate source materials into your paper and discuss each source thoughtfully in relation to your thesis or purpose statement.

When you cite your reference sources, it is important to pay close attention to standard conventions for citing sources in order to avoid plagiarism , or the practice of using someone else’s words without acknowledging the source. Later in this chapter, you will learn how to incorporate sources in your paper and avoid some of the most common pitfalls of attributing information.

Step 6: Revising and Editing Your Paper

In the final step of the research writing process, you will revise and polish your paper. You might reorganize your paper’s structure or revise for unity and cohesion, ensuring that each element in your paper flows into the next logically and naturally. You will also make sure that your paper uses an appropriate and consistent tone.

Once you feel confident in the strength of your writing, you will edit your paper for proper spelling, grammar, punctuation, mechanics, and formatting. When you complete this final step, you will have transformed a simple idea or question into a thoroughly researched and well-written paper you can be proud of!

Review the steps of the research writing process. Then answer the questions on your own sheet of paper.

In which steps of the research writing process are you allowed to change your thesis?
In step 2, which types of information should you include in your project schedule?
What might happen if you eliminated step 4 from the research writing process?

Key Takeaways

People undertake research projects throughout their academic and professional careers in order to answer specific questions, share their findings with others, increase their understanding of challenging topics, and strengthen their researching, writing, and analytical skills.
The research writing process generally comprises six steps: choosing a topic, scheduling and planning time for research and writing, conducting research, organizing research and ideas, drafting a paper, and revising and editing the paper.

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Article Contents

Primacy of the research question, structure of the paper, writing a research article: advice to beginners.

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Thomas V. Perneger, Patricia M. Hudelson, Writing a research article: advice to beginners, International Journal for Quality in Health Care , Volume 16, Issue 3, June 2004, Pages 191–192, https://doi.org/10.1093/intqhc/mzh053

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Writing research papers does not come naturally to most of us. The typical research paper is a highly codified rhetorical form [ 1 , 2 ]. Knowledge of the rules—some explicit, others implied—goes a long way toward writing a paper that will get accepted in a peer-reviewed journal.

A good research paper addresses a specific research question. The research question—or study objective or main research hypothesis—is the central organizing principle of the paper. Whatever relates to the research question belongs in the paper; the rest doesn’t. This is perhaps obvious when the paper reports on a well planned research project. However, in applied domains such as quality improvement, some papers are written based on projects that were undertaken for operational reasons, and not with the primary aim of producing new knowledge. In such cases, authors should define the main research question a posteriori and design the paper around it.

Generally, only one main research question should be addressed in a paper (secondary but related questions are allowed). If a project allows you to explore several distinct research questions, write several papers. For instance, if you measured the impact of obtaining written consent on patient satisfaction at a specialized clinic using a newly developed questionnaire, you may want to write one paper on the questionnaire development and validation, and another on the impact of the intervention. The idea is not to split results into ‘least publishable units’, a practice that is rightly decried, but rather into ‘optimally publishable units’.

What is a good research question? The key attributes are: (i) specificity; (ii) originality or novelty; and (iii) general relevance to a broad scientific community. The research question should be precise and not merely identify a general area of inquiry. It can often (but not always) be expressed in terms of a possible association between X and Y in a population Z, for example ‘we examined whether providing patients about to be discharged from the hospital with written information about their medications would improve their compliance with the treatment 1 month later’. A study does not necessarily have to break completely new ground, but it should extend previous knowledge in a useful way, or alternatively refute existing knowledge. Finally, the question should be of interest to others who work in the same scientific area. The latter requirement is more challenging for those who work in applied science than for basic scientists. While it may safely be assumed that the human genome is the same worldwide, whether the results of a local quality improvement project have wider relevance requires careful consideration and argument.

Once the research question is clearly defined, writing the paper becomes considerably easier. The paper will ask the question, then answer it. The key to successful scientific writing is getting the structure of the paper right. The basic structure of a typical research paper is the sequence of Introduction, Methods, Results, and Discussion (sometimes abbreviated as IMRAD). Each section addresses a different objective. The authors state: (i) the problem they intend to address—in other terms, the research question—in the Introduction; (ii) what they did to answer the question in the Methods section; (iii) what they observed in the Results section; and (iv) what they think the results mean in the Discussion.

In turn, each basic section addresses several topics, and may be divided into subsections (Table 1 ). In the Introduction, the authors should explain the rationale and background to the study. What is the research question, and why is it important to ask it? While it is neither necessary nor desirable to provide a full-blown review of the literature as a prelude to the study, it is helpful to situate the study within some larger field of enquiry. The research question should always be spelled out, and not merely left for the reader to guess.

Typical structure of a research paper

The Methods section should provide the readers with sufficient detail about the study methods to be able to reproduce the study if so desired. Thus, this section should be specific, concrete, technical, and fairly detailed. The study setting, the sampling strategy used, instruments, data collection methods, and analysis strategies should be described. In the case of qualitative research studies, it is also useful to tell the reader which research tradition the study utilizes and to link the choice of methodological strategies with the research goals [ 3 ].

The Results section is typically fairly straightforward and factual. All results that relate to the research question should be given in detail, including simple counts and percentages. Resist the temptation to demonstrate analytic ability and the richness of the dataset by providing numerous tables of non-essential results.

The Discussion section allows the most freedom. This is why the Discussion is the most difficult to write, and is often the weakest part of a paper. Structured Discussion sections have been proposed by some journal editors [ 4 ]. While strict adherence to such rules may not be necessary, following a plan such as that proposed in Table 1 may help the novice writer stay on track.

References should be used wisely. Key assertions should be referenced, as well as the methods and instruments used. However, unless the paper is a comprehensive review of a topic, there is no need to be exhaustive. Also, references to unpublished work, to documents in the grey literature (technical reports), or to any source that the reader will have difficulty finding or understanding should be avoided.

Having the structure of the paper in place is a good start. However, there are many details that have to be attended to while writing. An obvious recommendation is to read, and follow, the instructions to authors published by the journal (typically found on the journal’s website). Another concerns non-native writers of English: do have a native speaker edit the manuscript. A paper usually goes through several drafts before it is submitted. When revising a paper, it is useful to keep an eye out for the most common mistakes (Table 2 ). If you avoid all those, your paper should be in good shape.

Common mistakes seen in manuscripts submitted to this journal

Huth EJ . How to Write and Publish Papers in the Medical Sciences , 2nd edition. Baltimore, MD: Williams & Wilkins, 1990 .

Browner WS . Publishing and Presenting Clinical Research . Baltimore, MD: Lippincott, Williams & Wilkins, 1999 .

Devers KJ , Frankel RM. Getting qualitative research published. Educ Health 2001 ; 14 : 109 –117.

Docherty M , Smith R. The case for structuring the discussion of scientific papers. Br Med J 1999 ; 318 : 1224 –1225.

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What is Research? – Purpose of Research

By DiscoverPhDs
September 10, 2020

The purpose of research is to enhance society by advancing knowledge through the development of scientific theories, concepts and ideas. A research purpose is met through forming hypotheses, collecting data, analysing results, forming conclusions, implementing findings into real-life applications and forming new research questions.

What is Research

Simply put, research is the process of discovering new knowledge. This knowledge can be either the development of new concepts or the advancement of existing knowledge and theories, leading to a new understanding that was not previously known.

As a more formal definition of research, the following has been extracted from the Code of Federal Regulations :

While research can be carried out by anyone and in any field, most research is usually done to broaden knowledge in the physical, biological, and social worlds. This can range from learning why certain materials behave the way they do, to asking why certain people are more resilient than others when faced with the same challenges.

The use of ‘systematic investigation’ in the formal definition represents how research is normally conducted – a hypothesis is formed, appropriate research methods are designed, data is collected and analysed, and research results are summarised into one or more ‘research conclusions’. These research conclusions are then shared with the rest of the scientific community to add to the existing knowledge and serve as evidence to form additional questions that can be investigated. It is this cyclical process that enables scientific research to make continuous progress over the years; the true purpose of research.

What is the Purpose of Research

From weather forecasts to the discovery of antibiotics, researchers are constantly trying to find new ways to understand the world and how things work – with the ultimate goal of improving our lives.

The purpose of research is therefore to find out what is known, what is not and what we can develop further. In this way, scientists can develop new theories, ideas and products that shape our society and our everyday lives.

Although research can take many forms, there are three main purposes of research:

Exploratory: Exploratory research is the first research to be conducted around a problem that has not yet been clearly defined. Exploration research therefore aims to gain a better understanding of the exact nature of the problem and not to provide a conclusive answer to the problem itself. This enables us to conduct more in-depth research later on.
Descriptive: Descriptive research expands knowledge of a research problem or phenomenon by describing it according to its characteristics and population. Descriptive research focuses on the ‘how’ and ‘what’, but not on the ‘why’.
Explanatory: Explanatory research, also referred to as casual research, is conducted to determine how variables interact, i.e. to identify cause-and-effect relationships. Explanatory research deals with the ‘why’ of research questions and is therefore often based on experiments.

Characteristics of Research

There are 8 core characteristics that all research projects should have. These are:

Empirical – based on proven scientific methods derived from real-life observations and experiments.
Logical – follows sequential procedures based on valid principles.
Cyclic – research begins with a question and ends with a question, i.e. research should lead to a new line of questioning.
Controlled – vigorous measures put into place to keep all variables constant, except those under investigation.
Hypothesis-based – the research design generates data that sufficiently meets the research objectives and can prove or disprove the hypothesis. It makes the research study repeatable and gives credibility to the results.
Analytical – data is generated, recorded and analysed using proven techniques to ensure high accuracy and repeatability while minimising potential errors and anomalies.
Objective – sound judgement is used by the researcher to ensure that the research findings are valid.
Statistical treatment – statistical treatment is used to transform the available data into something more meaningful from which knowledge can be gained.

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Types of Research

Research can be divided into two main types: basic research (also known as pure research) and applied research.

Basic Research

Basic research, also known as pure research, is an original investigation into the reasons behind a process, phenomenon or particular event. It focuses on generating knowledge around existing basic principles.

Basic research is generally considered ‘non-commercial research’ because it does not focus on solving practical problems, and has no immediate benefit or ways it can be applied.

While basic research may not have direct applications, it usually provides new insights that can later be used in applied research.

Applied Research

Applied research investigates well-known theories and principles in order to enhance knowledge around a practical aim. Because of this, applied research focuses on solving real-life problems by deriving knowledge which has an immediate application.

Methods of Research

Research methods for data collection fall into one of two categories: inductive methods or deductive methods.

Inductive research methods focus on the analysis of an observation and are usually associated with qualitative research. Deductive research methods focus on the verification of an observation and are typically associated with quantitative research.

Qualitative Research

Qualitative research is a method that enables non-numerical data collection through open-ended methods such as interviews, case studies and focus groups .

It enables researchers to collect data on personal experiences, feelings or behaviours, as well as the reasons behind them. Because of this, qualitative research is often used in fields such as social science, psychology and philosophy and other areas where it is useful to know the connection between what has occurred and why it has occurred.

Quantitative Research

Quantitative research is a method that collects and analyses numerical data through statistical analysis.

It allows us to quantify variables, uncover relationships, and make generalisations across a larger population. As a result, quantitative research is often used in the natural and physical sciences such as engineering, biology, chemistry, physics, computer science, finance, and medical research, etc.

What does Research Involve?

Research often follows a systematic approach known as a Scientific Method, which is carried out using an hourglass model.

A research project first starts with a problem statement, or rather, the research purpose for engaging in the study. This can take the form of the ‘ scope of the study ’ or ‘ aims and objectives ’ of your research topic.

Subsequently, a literature review is carried out and a hypothesis is formed. The researcher then creates a research methodology and collects the data.

The data is then analysed using various statistical methods and the null hypothesis is either accepted or rejected.

In both cases, the study and its conclusion are officially written up as a report or research paper, and the researcher may also recommend lines of further questioning. The report or research paper is then shared with the wider research community, and the cycle begins all over again.

Although these steps outline the overall research process, keep in mind that research projects are highly dynamic and are therefore considered an iterative process with continued refinements and not a series of fixed stages.

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The scope of the study is defined at the start of the study. It is used by researchers to set the boundaries and limitations within which the research study will be performed.

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The Purpose of Research Writing

Learning Objectives
Identify reasons to research writing projects.
Outline the steps of the research writing process.

Reasons for Research

But the research process does not end when you have solved your mystery. Imagine what would happen if a detective collected enough evidence to solve a criminal case, but she never shared her solution with the authorities. Presenting what you have learned from research can be just as important as performing the research. Research results can be presented in a variety of ways, but one of the most popular—and effective—presentation forms is the research paper. A research paper presents an original thesis, or purpose statement, about a topic and develops that thesis with information gathered from a variety of sources.

Exercise 1
Write a paragraph about a time when you used research in your everyday life. Did you look for the cheapest way to travel from Houston to Denver? Did you search for a way to remove gum from the bottom of your shoe? In your paragraph, explain what you wanted to research, how you performed the research, and what you learned as a result.

Research Writing and the Academic Paper

Research Writing at Work

Writing at Work

Take a few minutes to think about each of the following careers. How might each of these professionals use researching and research writing skills on the job?

Medical laboratory technician
Small business owner
Information technology professional
Freelance magazine writer

Steps of the Research Writing Process

How does a research paper grow from a folder of brainstormed notes to a polished final draft? No two projects are identical, but most projects follow a series of six basic steps.

These are the steps in the research writing process:

Choose a topic.
Plan and schedule time to research and write.
Conduct research.
Organize research and ideas.
Draft your paper.
Revise and edit your paper.

Each of these steps will be discussed in more detail later in this chapter. For now, though, we will take a brief look at what each step involves.

Step 1: Choosing a Topic

To narrow the focus of your topic, you may try freewriting exercises, such as brainstorming. You may also need to ask a specific research question —a broad, open-ended question that will guide your research—as well as propose a possible answer, or a working thesis. You may use your research question and your working thesis to create a research proposal . In a research proposal, you present your main research question, any related subquestions you plan to explore, and your working thesis.

Step 2: Planning and Scheduling

Step 3: Conducting Research

When going about your research, you will likely use a variety of sources—anything from books and periodicals to video presentations and in-person interviews.

Step 4: Organizing Research and the Writer’s Ideas

Tip Remember, your working thesis is not set in stone. You can and should change your working thesis throughout the research writing process if the evidence you find does not support your original thesis. Never try to force evidence to fit your argument. For example, your working thesis is “Mars cannot support life-forms.” Yet, a week into researching your topic, you find an article in the New York Times detailing new findings of bacteria under the Martian surface. Instead of trying to argue that bacteria are not life forms, you might instead alter your thesis to “Mars cannot support complex life-forms.”

Step 5: Drafting Your Paper

Step 6: Revising and Editing Your Paper

Review the steps of the research writing process. Then answer the questions on your own sheet of paper.

In which steps of the research writing process are you allowed to change your thesis?
In step 2, which types of information should you include in your project schedule?
What might happen if you eliminated step 4 from the research writing process?

Key Takeaways

People undertake research projects throughout their academic and professional careers in order to answer specific questions, share their findings with others, increase their understanding of challenging topics, and strengthen their researching, writing, and analytical skills.

The research writing process generally comprises six steps: choosing a topic, scheduling and planning time for research and writing, conducting research, organizing research and ideas, drafting a paper, and revising and editing the paper.

This material comes from Writing for Success, by University of Minnesota, which is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted. You are free to use, adapt, and/or share this material as long as you properly attribute. Please keep this information on materials you use, adapt, and/or share for attribution purposes.

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Research paper

How to Write a Research Paper | A Beginner's Guide

A research paper is a piece of academic writing that provides analysis, interpretation, and argument based on in-depth independent research.

Research papers are similar to academic essays , but they are usually longer and more detailed assignments, designed to assess not only your writing skills but also your skills in scholarly research. Writing a research paper requires you to demonstrate a strong knowledge of your topic, engage with a variety of sources, and make an original contribution to the debate.

This step-by-step guide takes you through the entire writing process, from understanding your assignment to proofreading your final draft.

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Understand the assignment, 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, the revision process, research paper checklist, free lecture slides.

Completing a research paper successfully means accomplishing the specific tasks set out for you. Before you start, make sure you thoroughly understanding the assignment task sheet:

Read it carefully, looking for anything confusing you might need to clarify with your professor.
Identify the assignment goal, deadline, length specifications, formatting, and submission method.
Make a bulleted list of the key points, then go back and cross completed items off as you’re writing.

Carefully consider your timeframe and word limit: be realistic, and plan enough time to research, write, and edit.

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There are many ways to generate an idea for a research paper, from brainstorming with pen and paper to talking it through with a fellow student or professor.

You can try free writing, which involves taking a broad topic and writing continuously for two or three minutes to identify absolutely anything relevant that could be interesting.

You can also gain inspiration from other research. The discussion or recommendations sections of research papers often include ideas for other specific topics that require further examination.

Once you have a broad subject area, narrow it down to choose a topic that interests you, m eets the criteria of your assignment, and i s possible to research. Aim for ideas that are both original and specific:

A paper following the chronology of World War II would not be original or specific enough.
A paper on the experience of Danish citizens living close to the German border during World War II would be specific and could be original enough.

Note any discussions that seem important to the topic, and try to find an issue that you can focus your paper around. Use a variety of sources , including journals, books, and reliable websites, to ensure you do not miss anything glaring.

Do not only verify the ideas you have in mind, but look for sources that contradict your point of view.

Is there anything people seem to overlook in the sources you research?
Are there any heated debates you can address?
Do you have a unique take on your topic?
Have there been some recent developments that build on the extant research?

In this stage, you might find it helpful to formulate some research questions to help guide you. To write research questions, try to finish the following sentence: “I want to know how/what/why…”

A thesis statement is a statement of your central argument — it establishes the purpose and position of your paper. If you started with a research question, the thesis statement should answer it. It should also show what evidence and reasoning you’ll use to support that answer.

The thesis statement should be concise, contentious, and coherent. That means it should briefly summarize your argument in a sentence or two, make a claim that requires further evidence or analysis, and make a coherent point that relates to every part of the paper.

You will probably revise and refine the thesis statement as you do more research, but it can serve as a guide throughout the writing process. Every paragraph should aim to support and develop this central claim.

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A research paper outline is essentially a list of the key topics, arguments, and evidence you want to include, divided into sections with headings so that you know roughly what the paper will look like before you start writing.

A structure outline can help make the writing process much more efficient, so it’s worth dedicating some time to create one.

Your first draft won’t be perfect — you can polish later on. Your priorities at this stage are as follows:

Maintaining forward momentum — write now, perfect later.
Paying attention to clear organization and logical ordering of paragraphs and sentences, which will help when you come to the second draft.
Expressing your ideas as clearly as possible, so you know what you were trying to say when you come back to the text.

You do not need to start by writing the introduction. Begin where it feels most natural for you — some prefer to finish the most difficult sections first, while others choose to start with the easiest part. If you created an outline, use it as a map while you work.

Do not delete large sections of text. If you begin to dislike something you have written or find it doesn’t quite fit, move it to a different document, but don’t lose it completely — you never know if it might come in useful later.

Paragraph structure

Paragraphs are the basic building blocks of research papers. Each one should focus on a single claim or idea that helps to establish the overall argument or purpose of the paper.

Example paragraph

George Orwell’s 1946 essay “Politics and the English Language” has had an enduring impact on thought about the relationship between politics and language. This impact is particularly obvious in light of the various critical review articles that have recently referenced the essay. For example, consider Mark Falcoff’s 2009 article in The National Review Online, “The Perversion of Language; or, Orwell Revisited,” in which he analyzes several common words (“activist,” “civil-rights leader,” “diversity,” and more). Falcoff’s close analysis of the ambiguity built into political language intentionally mirrors Orwell’s own point-by-point analysis of the political language of his day. Even 63 years after its publication, Orwell’s essay is emulated by contemporary thinkers.

Citing sources

It’s also important to keep track of citations at this stage to avoid accidental plagiarism . Each time you use a source, make sure to take note of where the information came from.

You can use our free citation generators to automatically create citations and save your reference list as you go.

APA Citation Generator MLA Citation Generator

The research paper introduction should address three questions: What, why, and how? After finishing the introduction, the reader should know what the paper is about, why it is worth reading, and how you’ll build your arguments.

What? Be specific about the topic of the paper, introduce the background, and define key terms or concepts.

Why? This is the most important, but also the most difficult, part of the introduction. Try to provide brief answers to the following questions: What new material or insight are you offering? What important issues does your essay help define or answer?

How? To let the reader know what to expect from the rest of the paper, the introduction should include a “map” of what will be discussed, briefly presenting the key elements of the paper in chronological order.

The major struggle faced by most writers is how to organize the information presented in the paper, which is one reason an outline is so useful. However, remember that the outline is only a guide and, when writing, you can be flexible with the order in which the information and arguments are presented.

One way to stay on track is to use your thesis statement and topic sentences . Check:

topic sentences against the thesis statement;
topic sentences against each other, for similarities and logical ordering;
and each sentence against the topic sentence of that paragraph.

Be aware of paragraphs that seem to cover the same things. If two paragraphs discuss something similar, they must approach that topic in different ways. Aim to create smooth transitions between sentences, paragraphs, and sections.

The research paper conclusion is designed to help your reader out of the paper’s argument, giving them a sense of finality.

Trace the course of the paper, emphasizing how it all comes together to prove your thesis statement. Give the paper a sense of finality by making sure the reader understands how you’ve settled the issues raised in the introduction.

You might also discuss the more general consequences of the argument, outline what the paper offers to future students of the topic, and suggest any questions the paper’s argument raises but cannot or does not try to answer.

You should not :

Offer new arguments or essential information
Take up any more space than necessary
Begin with stock phrases that signal you are ending the paper (e.g. “In conclusion”)

There are four main considerations when it comes to the second draft.

Check how your vision of the paper lines up with the first draft and, more importantly, that your paper still answers the assignment.
Identify any assumptions that might require (more substantial) justification, keeping your reader’s perspective foremost in mind. Remove these points if you cannot substantiate them further.
Be open to rearranging your ideas. Check whether any sections feel out of place and whether your ideas could be better organized.
If you find that old ideas do not fit as well as you anticipated, you should cut them out or condense them. You might also find that new and well-suited ideas occurred to you during the writing of the first draft — now is the time to make them part of the paper.

The goal during the revision and proofreading process is to ensure you have completed all the necessary tasks and that the paper is as well-articulated as possible. You can speed up the proofreading process by using the AI proofreader .

Global concerns

Confirm that your paper completes every task specified in your assignment sheet.
Check for logical organization and flow of paragraphs.
Check paragraphs against the introduction and thesis statement.

Fine-grained details

Check the content of each paragraph, making sure that:

each sentence helps support the topic sentence.
no unnecessary or irrelevant information is present.
all technical terms your audience might not know are identified.

Next, think about sentence structure , grammatical errors, and formatting . Check that you have correctly used transition words and phrases to show the connections between your ideas. Look for typos, cut unnecessary words, and check for consistency in aspects such as heading formatting and spellings .

Finally, you need to make sure your paper is correctly formatted according to the rules of the citation style you are using. For example, you might need to include an MLA heading or create an APA title page .

Scribbr’s professional editors can help with the revision process with our award-winning proofreading services.

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Checklist: Research paper

I have followed all instructions in the assignment sheet.

My introduction presents my topic in an engaging way and provides necessary background information.

My introduction presents a clear, focused research problem and/or thesis statement .

My paper is logically organized using paragraphs and (if relevant) section headings .

Each paragraph is clearly focused on one central idea, expressed in a clear topic sentence .

Each paragraph is relevant to my research problem or thesis statement.

I have used appropriate transitions to clarify the connections between sections, paragraphs, and sentences.

My conclusion provides a concise answer to the research question or emphasizes how the thesis has been supported.

My conclusion shows how my research has contributed to knowledge or understanding of my topic.

My conclusion does not present any new points or information essential to my argument.

I have provided an in-text citation every time I refer to ideas or information from a source.

I have included a reference list at the end of my paper, consistently formatted according to a specific citation style .

I have thoroughly revised my paper and addressed any feedback from my professor or supervisor.

I have followed all formatting guidelines (page numbers, headers, spacing, etc.).

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Research Writing and Analysis

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Step 1: Seek Out Evidence
Step 2: Explain
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How to Synthesize and Analyze
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Problem Statement
Purpose Statement
Quantitative Research Questions
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Analysis and Coding Example- Qualitative Data
Thematic Data Analysis in Qualitative Design
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Purpose statement overview.

The purpose statement succinctly explains (on no more than 1 page) the objectives of the research study. These objectives must directly address the problem and help close the stated gap. Expressed as a formula:

Good purpose statements:

Flow from the problem statement and actually address the proposed problem
Are concise and clear
Answer the question ‘Why are you doing this research?’
Match the methodology (similar to research questions)
Have a ‘hook’ to get the reader’s attention
Set the stage by clearly stating, “The purpose of this (qualitative or quantitative) study is to ...

In PhD studies, the purpose usually involves applying a theory to solve the problem. In other words, the purpose tells the reader what the goal of the study is, and what your study will accomplish, through which theoretical lens. The purpose statement also includes brief information about direction, scope, and where the data will come from.

A problem and gap in combination can lead to different research objectives, and hence, different purpose statements. In the example from above where the problem was severe underrepresentation of female CEOs in Fortune 500 companies and the identified gap related to lack of research of male-dominated boards; one purpose might be to explore implicit biases in male-dominated boards through the lens of feminist theory. Another purpose may be to determine how board members rated female and male candidates on scales of competency, professionalism, and experience to predict which candidate will be selected for the CEO position. The first purpose may involve a qualitative ethnographic study in which the researcher observes board meetings and hiring interviews; the second may involve a quantitative regression analysis. The outcomes will be very different, so it’s important that you find out exactly how you want to address a problem and help close a gap!

The purpose of the study must not only align with the problem and address a gap; it must also align with the chosen research method. In fact, the DP/DM template requires you to name the research method at the very beginning of the purpose statement. The research verb must match the chosen method. In general, quantitative studies involve “closed-ended” research verbs such as determine , measure , correlate , explain , compare , validate , identify , or examine ; whereas qualitative studies involve “open-ended” research verbs such as explore , understand , narrate , articulate [meanings], discover , or develop .

A qualitative purpose statement following the color-coded problem statement (assumed here to be low well-being among financial sector employees) + gap (lack of research on followers of mid-level managers), might start like this:

In response to declining levels of employee well-being, the purpose of the qualitative phenomenology was to explore and understand the lived experiences related to the well-being of the followers of novice mid-level managers in the financial services industry. The levels of follower well-being have been shown to correlate to employee morale, turnover intention, and customer orientation (Eren et al., 2013). A combined framework of Leader-Member Exchange (LMX) Theory and the employee well-being concept informed the research questions and supported the inquiry, analysis, and interpretation of the experiences of followers of novice managers in the financial services industry.

A quantitative purpose statement for the same problem and gap might start like this:

In response to declining levels of employee well-being, the purpose of the quantitative correlational study was to determine which leadership factors predict employee well-being of the followers of novice mid-level managers in the financial services industry. Leadership factors were measured by the Leader-Member Exchange (LMX) assessment framework by Mantlekow (2015), and employee well-being was conceptualized as a compound variable consisting of self-reported turnover-intent and psychological test scores from the Mental Health Survey (MHS) developed by Johns Hopkins University researchers.

Both of these purpose statements reflect viable research strategies and both align with the problem and gap so it’s up to the researcher to design a study in a manner that reflects personal preferences and desired study outcomes. Note that the quantitative research purpose incorporates operationalized concepts or variables ; that reflect the way the researcher intends to measure the key concepts under study; whereas the qualitative purpose statement isn’t about translating the concepts under study as variables but instead aim to explore and understand the core research phenomenon.

Best Practices for Writing your Purpose Statement

Always keep in mind that the dissertation process is iterative, and your writing, over time, will be refined as clarity is gradually achieved. Most of the time, greater clarity for the purpose statement and other components of the Dissertation is the result of a growing understanding of the literature in the field. As you increasingly master the literature you will also increasingly clarify the purpose of your study.

The purpose statement should flow directly from the problem statement. There should be clear and obvious alignment between the two and that alignment will get tighter and more pronounced as your work progresses.

The purpose statement should specifically address the reason for conducting the study, with emphasis on the word specifically. There should not be any doubt in your readers’ minds as to the purpose of your study. To achieve this level of clarity you will need to also insure there is no doubt in your mind as to the purpose of your study.

Many researchers benefit from stopping your work during the research process when insight strikes you and write about it while it is still fresh in your mind. This can help you clarify all aspects of a dissertation, including clarifying its purpose.

Your Chair and your committee members can help you to clarify your study’s purpose so carefully attend to any feedback they offer.

The purpose statement should reflect the research questions and vice versa. The chain of alignment that began with the research problem description and continues on to the research purpose, research questions, and methodology must be respected at all times during dissertation development. You are to succinctly describe the overarching goal of the study that reflects the research questions. Each research question narrows and focuses the purpose statement. Conversely, the purpose statement encompasses all of the research questions.

Identify in the purpose statement the research method as quantitative, qualitative or mixed (i.e., “The purpose of this [qualitative/quantitative/mixed] study is to ...)

Avoid the use of the phrase “research study” since the two words together are redundant.

Follow the initial declaration of purpose with a brief overview of how, with what instruments/data, with whom and where (as applicable) the study will be conducted. Identify variables/constructs and/or phenomenon/concept/idea. Since this section is to be a concise paragraph, emphasis must be placed on the word brief. However, adding these details will give your readers a very clear picture of the purpose of your research.

Developing the purpose section of your dissertation is usually not achieved in a single flash of insight. The process involves a great deal of reading to find out what other scholars have done to address the research topic and problem you have identified. The purpose section of your dissertation could well be the most important paragraph you write during your academic career, and every word should be carefully selected. Think of it as the DNA of your dissertation. Everything else you write should emerge directly and clearly from your purpose statement. In turn, your purpose statement should emerge directly and clearly from your research problem description. It is good practice to print out your problem statement and purpose statement and keep them in front of you as you work on each part of your dissertation in order to insure alignment.

It is helpful to collect several dissertations similar to the one you envision creating. Extract the problem descriptions and purpose statements of other dissertation authors and compare them in order to sharpen your thinking about your own work. Comparing how other dissertation authors have handled the many challenges you are facing can be an invaluable exercise. Keep in mind that individual universities use their own tailored protocols for presenting key components of the dissertation so your review of these purpose statements should focus on content rather than form.

Once your purpose statement is set it must be consistently presented throughout the dissertation. This may require some recursive editing because the way you articulate your purpose may evolve as you work on various aspects of your dissertation. Whenever you make an adjustment to your purpose statement you should carefully follow up on the editing and conceptual ramifications throughout the entire document.

In establishing your purpose you should NOT advocate for a particular outcome. Research should be done to answer questions not prove a point. As a researcher, you are to inquire with an open mind, and even when you come to the work with clear assumptions, your job is to prove the validity of the conclusions reached. For example, you would not say the purpose of your research project is to demonstrate that there is a relationship between two variables. Such a statement presupposes you know the answer before your research is conducted and promotes or supports (advocates on behalf of) a particular outcome. A more appropriate purpose statement would be to examine or explore the relationship between two variables.

Your purpose statement should not imply that you are going to prove something. You may be surprised to learn that we cannot prove anything in scholarly research for two reasons. First, in quantitative analyses, statistical tests calculate the probability that something is true rather than establishing it as true. Second, in qualitative research, the study can only purport to describe what is occurring from the perspective of the participants. Whether or not the phenomenon they are describing is true in a larger context is not knowable. We cannot observe the phenomenon in all settings and in all circumstances.

Writing your Purpose Statement

It is important to distinguish in your mind the differences between the Problem Statement and Purpose Statement.

The Problem Statement is why I am doing the research

The Purpose Statement is what type of research I am doing to fit or address the problem

The Purpose Statement includes:

Method of Study
Specific Population

Remember, as you are contemplating what to include in your purpose statement and then when you are writing it, the purpose statement is a concise paragraph that describes the intent of the study, and it should flow directly from the problem statement. It should specifically address the reason for conducting the study, and reflect the research questions. Further, it should identify the research method as qualitative, quantitative, or mixed. Then provide a brief overview of how the study will be conducted, with what instruments/data collection methods, and with whom (subjects) and where (as applicable). Finally, you should identify variables/constructs and/or phenomenon/concept/idea.

Qualitative Purpose Statement

Creswell (2002) suggested for writing purpose statements in qualitative research include using deliberate phrasing to alert the reader to the purpose statement. Verbs that indicate what will take place in the research and the use of non-directional language that do not suggest an outcome are key. A purpose statement should focus on a single idea or concept, with a broad definition of the idea or concept. How the concept was investigated should also be included, as well as participants in the study and locations for the research to give the reader a sense of with whom and where the study took place.

Creswell (2003) advised the following script for purpose statements in qualitative research:

“The purpose of this qualitative_________________ (strategy of inquiry, such as ethnography, case study, or other type) study is (was? will be?) to ________________ (understand? describe? develop? discover?) the _________________(central phenomenon being studied) for ______________ (the participants, such as the individual, groups, organization) at __________(research site). At this stage in the research, the __________ (central phenomenon being studied) will be generally defined as ___________________ (provide a general definition)” (pg. 90).

Quantitative Purpose Statement

Creswell (2003) offers vast differences between the purpose statements written for qualitative research and those written for quantitative research, particularly with respect to language and the inclusion of variables. The comparison of variables is often a focus of quantitative research, with the variables distinguishable by either the temporal order or how they are measured. As with qualitative research purpose statements, Creswell (2003) recommends the use of deliberate language to alert the reader to the purpose of the study, but quantitative purpose statements also include the theory or conceptual framework guiding the study and the variables that are being studied and how they are related.

Creswell (2003) suggests the following script for drafting purpose statements in quantitative research:

“The purpose of this _____________________ (experiment? survey?) study is (was? will be?) to test the theory of _________________that _________________ (compares? relates?) the ___________(independent variable) to _________________________(dependent variable), controlling for _______________________ (control variables) for ___________________ (participants) at _________________________ (the research site). The independent variable(s) _____________________ will be generally defined as _______________________ (provide a general definition). The dependent variable(s) will be generally defined as _____________________ (provide a general definition), and the control and intervening variables(s), _________________ (identify the control and intervening variables) will be statistically controlled in this study” (pg. 97).

Sample Purpose Statements

The purpose of this qualitative study was to determine how participation in service-learning in an alternative school impacted students academically, civically, and personally. There is ample evidence demonstrating the failure of schools for students at-risk; however, there is still a need to demonstrate why these students are successful in non-traditional educational programs like the service-learning model used at TDS. This study was unique in that it examined one alternative school’s approach to service-learning in a setting where students not only serve, but faculty serve as volunteer teachers. The use of a constructivist approach in service-learning in an alternative school setting was examined in an effort to determine whether service-learning participation contributes positively to academic, personal, and civic gain for students, and to examine student and teacher views regarding the overall outcomes of service-learning. This study was completed using an ethnographic approach that included observations, content analysis, and interviews with teachers at The David School.
The purpose of this quantitative non-experimental cross-sectional linear multiple regression design was to investigate the relationship among early childhood teachers’ self-reported assessment of multicultural awareness as measured by responses from the Teacher Multicultural Attitude Survey (TMAS) and supervisors’ observed assessment of teachers’ multicultural competency skills as measured by the Multicultural Teaching Competency Scale (MTCS) survey. Demographic data such as number of multicultural training hours, years teaching in Dubai, curriculum program at current school, and age were also examined and their relationship to multicultural teaching competency. The study took place in the emirate of Dubai where there were 14,333 expatriate teachers employed in private schools (KHDA, 2013b).
The purpose of this quantitative, non-experimental study is to examine the degree to which stages of change, gender, acculturation level and trauma types predicts the reluctance of Arab refugees, aged 18 and over, in the Dearborn, MI area, to seek professional help for their mental health needs. This study will utilize four instruments to measure these variables: University of Rhode Island Change Assessment (URICA: DiClemente & Hughes, 1990); Cumulative Trauma Scale (Kira, 2012); Acculturation Rating Scale for Arabic Americans-II Arabic and English (ARSAA-IIA, ARSAA-IIE: Jadalla & Lee, 2013), and a demographic survey. This study will examine 1) the relationship between stages of change, gender, acculturation levels, and trauma types and Arab refugees’ help-seeking behavior, 2) the degree to which any of these variables can predict Arab refugee help-seeking behavior. Additionally, the outcome of this study could provide researchers and clinicians with a stage-based model, TTM, for measuring Arab refugees’ help-seeking behavior and lay a foundation for how TTM can help target the clinical needs of Arab refugees. Lastly, this attempt to apply the TTM model to Arab refugees’ condition could lay the foundation for future research to investigate the application of TTM to clinical work among refugee populations.
The purpose of this qualitative, phenomenological study is to describe the lived experiences of LLM for 10 EFL learners in rural Guatemala and to utilize that data to determine how it conforms to, or possibly challenges, current theoretical conceptions of LLM. In accordance with Morse’s (1994) suggestion that a phenomenological study should utilize at least six participants, this study utilized semi-structured interviews with 10 EFL learners to explore why and how they have experienced the motivation to learn English throughout their lives. The methodology of horizontalization was used to break the interview protocols into individual units of meaning before analyzing these units to extract the overarching themes (Moustakas, 1994). These themes were then interpreted into a detailed description of LLM as experienced by EFL students in this context. Finally, the resulting description was analyzed to discover how these learners’ lived experiences with LLM conformed with and/or diverged from current theories of LLM.
The purpose of this qualitative, embedded, multiple case study was to examine how both parent-child attachment relationships are impacted by the quality of the paternal and maternal caregiver-child interactions that occur throughout a maternal deployment, within the context of dual-military couples. In order to examine this phenomenon, an embedded, multiple case study was conducted, utilizing an attachment systems metatheory perspective. The study included four dual-military couples who experienced a maternal deployment to Operation Iraqi Freedom (OIF) or Operation Enduring Freedom (OEF) when they had at least one child between 8 weeks-old to 5 years-old. Each member of the couple participated in an individual, semi-structured interview with the researcher and completed the Parenting Relationship Questionnaire (PRQ). “The PRQ is designed to capture a parent’s perspective on the parent-child relationship” (Pearson, 2012, para. 1) and was used within the proposed study for this purpose. The PRQ was utilized to triangulate the data (Bekhet & Zauszniewski, 2012) as well as to provide some additional information on the parents’ perspective of the quality of the parent-child attachment relationship in regards to communication, discipline, parenting confidence, relationship satisfaction, and time spent together (Pearson, 2012). The researcher utilized the semi-structured interview to collect information regarding the parents' perspectives of the quality of their parental caregiver behaviors during the deployment cycle, the mother's parent-child interactions while deployed, the behavior of the child or children at time of reunification, and the strategies or behaviors the parents believe may have contributed to their child's behavior at the time of reunification. The results of this study may be utilized by the military, and by civilian providers, to develop proactive and preventive measures that both providers and parents can implement, to address any potential adverse effects on the parent-child attachment relationship, identified through the proposed study. The results of this study may also be utilized to further refine and understand the integration of attachment theory and systems theory, in both clinical and research settings, within the field of marriage and family therapy.

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Research Guides

Reading for Research: Social Sciences

Structure of a research article.

Structural Read

Guide Acknowledgements

How to Read a Scholarly Article from the Howard Tilton Memorial Library at Tulane University

Strategic Reading for Research from the Howard Tilton Memorial Library at Tulane University

Bridging the Gap between Faculty Expectation and the Student Experience: Teaching Students toAnnotate and Synthesize Sources

Librarian for Sociology, Environmental Sociology, MHS and Public Policy Studies

Academic writing has features that vary only slightly across the different disciplines. Knowing these elements and the purpose of each serves help you to read and understand academic texts efficiently and effectively, and then apply what you read to your paper or project.

Social Science (and Science) original research articles generally follow IMRD: Introduction- Methods-Results-Discussion

Introduction

Introduces topic of article
Presents the "Research Gap"/Statement of Problem article will address
How research presented in the article will solve the problem presented in research gap.
Literature Review. presenting and evaluating previous scholarship on a topic. Sometimes, this is separate section of the article.

Method & Results

How research was done, including analysis and measurements.
Sometimes labeled as "Research Design"
What answers were found
Interpretation of Results (What Does It Mean? Why is it important?)
Implications for the Field, how the study contributes to the existing field of knowledge
Suggestions for further research
Sometimes called Conclusion

You might also see IBC: Introduction - Body - Conclusion

Identify the subject
State the thesis
Describe why thesis is important to the field (this may be in the form of a literature review or general prose)

Body

Presents Evidence/Counter Evidence
Integrate other writings (i.e. evidence) to support argument
Discuss why others may disagree (counter-evidence) and why argument is still valid
Summary of argument
Evaluation of argument by pointing out its implications and/or limitations
Anticipate and address possible counter-claims
Suggest future directions of research
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Doing Research in Education: Theory and Practice

Student resources, 1. the purpose of research: why do we do it.

Select SAGE Journal articles are available to give you even more insight into chapter topics. These are also an ideal resource to help support your literature reviews, dissertations and assignments.

Click on the following links which will open in a new window.

Brace, M., Herriotts, P., Mccullagh, A. and Nzegwu, F. (2007) ‘Why research — what research should be done?: Report of a collaborative workshop in the UK to discuss social research priorities on visual impairment’, British Journal of Visual Impairment , 25(2): 178–189.

Hannah, D.R. and Lautsch, B.A. (2010) ‘Counting in Qualitative Research: Why to Conduct it, When to Avoid it, and When to Closet it’, in Journal of Management Inquiry , 20(1): 14–22.

TechBullion

Academic writing: understanding the purpose of research articles.

Academic writing can often feel like a daunting task, with its formal language and dense research articles. But fear not! In this blog post, we will demystify the purpose of research articles and show you how they are essential tools for advancing knowledge in your field.

Introduction

In the world of academia, research articles are considered to be the backbone of academic writing. They form an integral part of scholarly communication and play a crucial role in advancing knowledge and understanding in various fields of study. A research article is a written piece that reports on original research or findings, experiments, concepts, theories, or methodologies in a specific area of study. It undergoes a rigorous process of peer review before being published in reputable academic journals.

Research articles serve multiple purposes and have several important functions within the realm of academic writing. Firstly, they contribute to the body of knowledge by presenting new findings or perspectives on a particular topic. This helps to build upon existing research and add to the collective understanding within a field.

Moreover, research articles also provide evidence-based support for arguments made by scholars and researchers. By citing relevant studies and data from research articles, writers can strengthen their claims and lend credibility to their work. This not only adds depth and validity to academic writing but also encourages critical thinking among readers.

Definition of Research Articles:

A research article can be defined as a document that presents original research on a particular topic or problem. It is usually written by researchers, scholars, or scientists who have conducted extensive studies or experiments on a subject matter. Research articles undergo rigorous peer-review processes before they are published in reputable academic journals.

Understanding the Purpose of Research Articles:

The main purpose of research articles is to contribute to the existing body of knowledge in a particular area by presenting new findings or perspectives. They aim to advance understanding and stimulate further research within the academic community. By sharing their work through research articles, researchers not only gain recognition but also contribute to the progress and development of their respective fields.

Another important purpose of research articles is to provide evidence-based information for decision-making processes. The findings presented in these articles can help policymakers and practitioners make informed decisions that can drive positive change in society.

Format of Research Articles:

Research articles typically follow a standard format with sections such as abstract, introduction, literature review, methodology, results and findings, discussion and analysis, conclusion and implications, and references and bibliography. Each section serves a unique purpose in conveying information effectively to readers.

The abstract gives an overview of the entire article, including its key points and conclusions. The introduction provides background information on the topic under study and explains why it is significant. The literature review summarizes existing knowledge on the topic while identifying gaps that need further exploration.

The methodology section outlines how the study was conducted, including details about participants and sample size, data collection methods and tools used, and data analysis techniques. The results section presents the findings of the study in a clear and organized manner, often using tables, charts, and graphs.

The discussion/analysis section interprets the results in relation to the research question and objectives. It also discusses implications, limitations, and future directions for research. The conclusion summarizes the main points of the article while highlighting its significance.

Research articles are an important medium for communicating new knowledge and ideas within the academic community. They serve to advance understanding, inform decision-making processes, and contribute to societal progress. Understanding their purpose and format is crucial for both readers and writers of these valuable pieces of literature.

Key Components of a Research Article:

A research article is a vital form of academic writing that serves to present the findings and outcomes of an in-depth study or investigation. It is typically written by scholars, researchers, and scientists from various fields of study and is published in academic journals to contribute to the existing body of knowledge in their respective disciplines. However, understanding the structure and purpose of a research article can be daunting for those new to academic writing. In this section, we will discuss the key components of a research article: the abstract, introduction, methodology, results, and discussion/conclusion.

1) Abstract: The abstract is a concise summary of the entire research article. It provides readers with an overview of the study’s objectives, methods used, major findings, and conclusions. The typical length of an abstract is anywhere between 100 and 300 words, depending on the journal’s guidelines. A well-written abstract should be able to stand alone, as it may be read independently by readers who are interested in only specific aspects of the study.

2) Introduction: The introduction sets the tone for your research article by providing background information on the topic and outlining its significance in relation to previous studies. This section should also clearly state your research question or hypothesis that you aim to answer through your study. Furthermore, it should provide a brief overview of your methodology and highlight any key terms or concepts that will be used throughout your paper.

3) Methodology: The methodology section outlines how you conducted your study. It includes details such as sample size, data collection techniques (interviews, questionnaires, and observations), data analysis methods (qualitative and quantitative), and any limitations or ethical considerations that may have impacted your study’s results.

4) Results: The results section presents all relevant findings obtained from analyzing the collected data using statistical tools or qualitative analysis techniques. This section often includes tables, graphs, or figures to help visualize complex data sets better. The results should be presented objectively, without interpretation or bias.

5) Discussion/Conclusion: The discussion section is where you interpret and analyze your results in light of your research question or hypothesis. This section allows you to compare your findings with previous studies and explain any discrepancies. Additionally, it should include the significance of your study’s results and how they contribute to the existing body of knowledge. The conclusion summarizes the key points discussed in the article and provides a final statement on whether your research question or hypothesis has been supported or not.

Importance of Proper Citation and Referencing in Research Articles

Proper citation and referencing are essential components of academic writing, especially in research articles. This section will discuss the importance of these elements and how they contribute to the overall quality and credibility of a research article.

Firstly, proper citation and referencing give credit where credit is due. In other words, it acknowledges the work of others that has been used as evidence or support for the arguments presented in the article. Without proper citation, it can be considered plagiarism, which is a serious offense in the academic world. Plagiarism not only undermines the integrity of the writer but also devalues their work.

Moreover, accurate citation and referencing allow readers to easily locate and access the sources used by the author. This helps to build upon existing knowledge and encourages further research on the topic at hand. Additionally, it allows readers to verify and evaluate the credibility of the information provided by examining its original source.

Proper citation and referencing enhance transparency in research articles. By citing sources accurately, authors demonstrate their commitment to transparency by providing evidence for their claims rather than relying solely on personal opinions or beliefs. This adds validity to their arguments and strengthens their stance in the eyes of readers.

In addition to enhancing transparency, proper citation and referencing also contribute significantly to maintaining consistency within a field of study. Citations create connections between different studies on a similar topic by acknowledging previous findings while building upon them with new insights or perspectives. This creates a cohesive body of literature that allows researchers to understand a subject more comprehensively.

Proper citation and referencing are vital aspects of academic writing, specifically in research articles. It not only gives credit to the original authors but also contributes to the overall credibility and transparency of the article. By acknowledging previous research and maintaining consistency within a field, writers can create a reliable body of knowledge that advances their area of study. Therefore, it is crucial for researchers to understand the importance of citation and referencing and use them accurately in their writing.

Research articles are a significant medium for sharing new insights and expanding knowledge in various disciplines. Proper citation and referencing play a crucial role in maintaining the integrity, credibility, and transparency of these articles. By acknowledging the work of others and building upon it with new findings, writers contribute to the advancement of their field of study. Therefore, it is essential for researchers to understand the importance of proper citation and referencing and use them accurately in their writing.

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What Is Research, and Why Do People Do It?

Open Access
First Online: 03 December 2022

Cite this chapter

You have full access to this open access chapter

James Hiebert 6 ,
Jinfa Cai 7 ,
Stephen Hwang 7 ,
Anne K Morris 6 &
Charles Hohensee 6

Part of the book series: Research in Mathematics Education ((RME))

15k Accesses

Abstractspiepr Abs1

Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain, and by its commitment to learn from everyone else seriously engaged in research. We call this kind of research scientific inquiry and define it as “formulating, testing, and revising hypotheses.” By “hypotheses” we do not mean the hypotheses you encounter in statistics courses. We mean predictions about what you expect to find and rationales for why you made these predictions. Throughout this and the remaining chapters we make clear that the process of scientific inquiry applies to all kinds of research studies and data, both qualitative and quantitative.

You have full access to this open access chapter, Download chapter PDF

Part I. What Is Research?

Have you ever studied something carefully because you wanted to know more about it? Maybe you wanted to know more about your grandmother’s life when she was younger so you asked her to tell you stories from her childhood, or maybe you wanted to know more about a fertilizer you were about to use in your garden so you read the ingredients on the package and looked them up online. According to the dictionary definition, you were doing research.

Recall your high school assignments asking you to “research” a topic. The assignment likely included consulting a variety of sources that discussed the topic, perhaps including some “original” sources. Often, the teacher referred to your product as a “research paper.”

Were you conducting research when you interviewed your grandmother or wrote high school papers reviewing a particular topic? Our view is that you were engaged in part of the research process, but only a small part. In this book, we reserve the word “research” for what it means in the scientific world, that is, for scientific research or, more pointedly, for scientific inquiry .

Exercise 1.1

Before you read any further, write a definition of what you think scientific inquiry is. Keep it short—Two to three sentences. You will periodically update this definition as you read this chapter and the remainder of the book.

This book is about scientific inquiry—what it is and how to do it. For starters, scientific inquiry is a process, a particular way of finding out about something that involves a number of phases. Each phase of the process constitutes one aspect of scientific inquiry. You are doing scientific inquiry as you engage in each phase, but you have not done scientific inquiry until you complete the full process. Each phase is necessary but not sufficient.

In this chapter, we set the stage by defining scientific inquiry—describing what it is and what it is not—and by discussing what it is good for and why people do it. The remaining chapters build directly on the ideas presented in this chapter.

A first thing to know is that scientific inquiry is not all or nothing. “Scientificness” is a continuum. Inquiries can be more scientific or less scientific. What makes an inquiry more scientific? You might be surprised there is no universally agreed upon answer to this question. None of the descriptors we know of are sufficient by themselves to define scientific inquiry. But all of them give you a way of thinking about some aspects of the process of scientific inquiry. Each one gives you different insights.

An image of the book's description with the words like research, science, and inquiry and what the word research meant in the scientific world.

Exercise 1.2

As you read about each descriptor below, think about what would make an inquiry more or less scientific. If you think a descriptor is important, use it to revise your definition of scientific inquiry.

Creating an Image of Scientific Inquiry

We will present three descriptors of scientific inquiry. Each provides a different perspective and emphasizes a different aspect of scientific inquiry. We will draw on all three descriptors to compose our definition of scientific inquiry.

Descriptor 1. Experience Carefully Planned in Advance

Sir Ronald Fisher, often called the father of modern statistical design, once referred to research as “experience carefully planned in advance” (1935, p. 8). He said that humans are always learning from experience, from interacting with the world around them. Usually, this learning is haphazard rather than the result of a deliberate process carried out over an extended period of time. Research, Fisher said, was learning from experience, but experience carefully planned in advance.

This phrase can be fully appreciated by looking at each word. The fact that scientific inquiry is based on experience means that it is based on interacting with the world. These interactions could be thought of as the stuff of scientific inquiry. In addition, it is not just any experience that counts. The experience must be carefully planned . The interactions with the world must be conducted with an explicit, describable purpose, and steps must be taken to make the intended learning as likely as possible. This planning is an integral part of scientific inquiry; it is not just a preparation phase. It is one of the things that distinguishes scientific inquiry from many everyday learning experiences. Finally, these steps must be taken beforehand and the purpose of the inquiry must be articulated in advance of the experience. Clearly, scientific inquiry does not happen by accident, by just stumbling into something. Stumbling into something unexpected and interesting can happen while engaged in scientific inquiry, but learning does not depend on it and serendipity does not make the inquiry scientific.

Descriptor 2. Observing Something and Trying to Explain Why It Is the Way It Is

When we were writing this chapter and googled “scientific inquiry,” the first entry was: “Scientific inquiry refers to the diverse ways in which scientists study the natural world and propose explanations based on the evidence derived from their work.” The emphasis is on studying, or observing, and then explaining . This descriptor takes the image of scientific inquiry beyond carefully planned experience and includes explaining what was experienced.

According to the Merriam-Webster dictionary, “explain” means “(a) to make known, (b) to make plain or understandable, (c) to give the reason or cause of, and (d) to show the logical development or relations of” (Merriam-Webster, n.d. ). We will use all these definitions. Taken together, they suggest that to explain an observation means to understand it by finding reasons (or causes) for why it is as it is. In this sense of scientific inquiry, the following are synonyms: explaining why, understanding why, and reasoning about causes and effects. Our image of scientific inquiry now includes planning, observing, and explaining why.

An image represents the observation required in the scientific inquiry including planning and explaining.

We need to add a final note about this descriptor. We have phrased it in a way that suggests “observing something” means you are observing something in real time—observing the way things are or the way things are changing. This is often true. But, observing could mean observing data that already have been collected, maybe by someone else making the original observations (e.g., secondary analysis of NAEP data or analysis of existing video recordings of classroom instruction). We will address secondary analyses more fully in Chap. 4 . For now, what is important is that the process requires explaining why the data look like they do.

We must note that for us, the term “data” is not limited to numerical or quantitative data such as test scores. Data can also take many nonquantitative forms, including written survey responses, interview transcripts, journal entries, video recordings of students, teachers, and classrooms, text messages, and so forth.

An image represents the data explanation as it is not limited and takes numerous non-quantitative forms including an interview, journal entries, etc.

Exercise 1.3

What are the implications of the statement that just “observing” is not enough to count as scientific inquiry? Does this mean that a detailed description of a phenomenon is not scientific inquiry?

Find sources that define research in education that differ with our position, that say description alone, without explanation, counts as scientific research. Identify the precise points where the opinions differ. What are the best arguments for each of the positions? Which do you prefer? Why?

Descriptor 3. Updating Everyone’s Thinking in Response to More and Better Information

This descriptor focuses on a third aspect of scientific inquiry: updating and advancing the field’s understanding of phenomena that are investigated. This descriptor foregrounds a powerful characteristic of scientific inquiry: the reliability (or trustworthiness) of what is learned and the ultimate inevitability of this learning to advance human understanding of phenomena. Humans might choose not to learn from scientific inquiry, but history suggests that scientific inquiry always has the potential to advance understanding and that, eventually, humans take advantage of these new understandings.

Before exploring these bold claims a bit further, note that this descriptor uses “information” in the same way the previous two descriptors used “experience” and “observations.” These are the stuff of scientific inquiry and we will use them often, sometimes interchangeably. Frequently, we will use the term “data” to stand for all these terms.

An overriding goal of scientific inquiry is for everyone to learn from what one scientist does. Much of this book is about the methods you need to use so others have faith in what you report and can learn the same things you learned. This aspect of scientific inquiry has many implications.

One implication is that scientific inquiry is not a private practice. It is a public practice available for others to see and learn from. Notice how different this is from everyday learning. When you happen to learn something from your everyday experience, often only you gain from the experience. The fact that research is a public practice means it is also a social one. It is best conducted by interacting with others along the way: soliciting feedback at each phase, taking opportunities to present work-in-progress, and benefitting from the advice of others.

A second implication is that you, as the researcher, must be committed to sharing what you are doing and what you are learning in an open and transparent way. This allows all phases of your work to be scrutinized and critiqued. This is what gives your work credibility. The reliability or trustworthiness of your findings depends on your colleagues recognizing that you have used all appropriate methods to maximize the chances that your claims are justified by the data.

A third implication of viewing scientific inquiry as a collective enterprise is the reverse of the second—you must be committed to receiving comments from others. You must treat your colleagues as fair and honest critics even though it might sometimes feel otherwise. You must appreciate their job, which is to remain skeptical while scrutinizing what you have done in considerable detail. To provide the best help to you, they must remain skeptical about your conclusions (when, for example, the data are difficult for them to interpret) until you offer a convincing logical argument based on the information you share. A rather harsh but good-to-remember statement of the role of your friendly critics was voiced by Karl Popper, a well-known twentieth century philosopher of science: “. . . if you are interested in the problem which I tried to solve by my tentative assertion, you may help me by criticizing it as severely as you can” (Popper, 1968, p. 27).

A final implication of this third descriptor is that, as someone engaged in scientific inquiry, you have no choice but to update your thinking when the data support a different conclusion. This applies to your own data as well as to those of others. When data clearly point to a specific claim, even one that is quite different than you expected, you must reconsider your position. If the outcome is replicated multiple times, you need to adjust your thinking accordingly. Scientific inquiry does not let you pick and choose which data to believe; it mandates that everyone update their thinking when the data warrant an update.

Doing Scientific Inquiry

We define scientific inquiry in an operational sense—what does it mean to do scientific inquiry? What kind of process would satisfy all three descriptors: carefully planning an experience in advance; observing and trying to explain what you see; and, contributing to updating everyone’s thinking about an important phenomenon?

We define scientific inquiry as formulating , testing , and revising hypotheses about phenomena of interest.

Of course, we are not the only ones who define it in this way. The definition for the scientific method posted by the editors of Britannica is: “a researcher develops a hypothesis, tests it through various means, and then modifies the hypothesis on the basis of the outcome of the tests and experiments” (Britannica, n.d. ).

An image represents the scientific inquiry definition given by the editors of Britannica and also defines the hypothesis on the basis of the experiments.

Notice how defining scientific inquiry this way satisfies each of the descriptors. “Carefully planning an experience in advance” is exactly what happens when formulating a hypothesis about a phenomenon of interest and thinking about how to test it. “ Observing a phenomenon” occurs when testing a hypothesis, and “ explaining ” what is found is required when revising a hypothesis based on the data. Finally, “updating everyone’s thinking” comes from comparing publicly the original with the revised hypothesis.

Doing scientific inquiry, as we have defined it, underscores the value of accumulating knowledge rather than generating random bits of knowledge. Formulating, testing, and revising hypotheses is an ongoing process, with each revised hypothesis begging for another test, whether by the same researcher or by new researchers. The editors of Britannica signaled this cyclic process by adding the following phrase to their definition of the scientific method: “The modified hypothesis is then retested, further modified, and tested again.” Scientific inquiry creates a process that encourages each study to build on the studies that have gone before. Through collective engagement in this process of building study on top of study, the scientific community works together to update its thinking.

Before exploring more fully the meaning of “formulating, testing, and revising hypotheses,” we need to acknowledge that this is not the only way researchers define research. Some researchers prefer a less formal definition, one that includes more serendipity, less planning, less explanation. You might have come across more open definitions such as “research is finding out about something.” We prefer the tighter hypothesis formulation, testing, and revision definition because we believe it provides a single, coherent map for conducting research that addresses many of the thorny problems educational researchers encounter. We believe it is the most useful orientation toward research and the most helpful to learn as a beginning researcher.

A final clarification of our definition is that it applies equally to qualitative and quantitative research. This is a familiar distinction in education that has generated much discussion. You might think our definition favors quantitative methods over qualitative methods because the language of hypothesis formulation and testing is often associated with quantitative methods. In fact, we do not favor one method over another. In Chap. 4 , we will illustrate how our definition fits research using a range of quantitative and qualitative methods.

Exercise 1.4

Look for ways to extend what the field knows in an area that has already received attention by other researchers. Specifically, you can search for a program of research carried out by more experienced researchers that has some revised hypotheses that remain untested. Identify a revised hypothesis that you might like to test.

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

To get a full sense of the definition of scientific inquiry we will use throughout this book, it is helpful to spend a little time with each of the key terms.

We first want to make clear that we use the term “hypothesis” as it is defined in most dictionaries and as it used in many scientific fields rather than as it is usually defined in educational statistics courses. By “hypothesis,” we do not mean a null hypothesis that is accepted or rejected by statistical analysis. Rather, we use “hypothesis” in the sense conveyed by the following definitions: “An idea or explanation for something that is based on known facts but has not yet been proved” (Cambridge University Press, n.d. ), and “An unproved theory, proposition, or supposition, tentatively accepted to explain certain facts and to provide a basis for further investigation or argument” (Agnes & Guralnik, 2008 ).

We distinguish two parts to “hypotheses.” Hypotheses consist of predictions and rationales . Predictions are statements about what you expect to find when you inquire about something. Rationales are explanations for why you made the predictions you did, why you believe your predictions are correct. So, for us “formulating hypotheses” means making explicit predictions and developing rationales for the predictions.

“Testing hypotheses” means making observations that allow you to assess in what ways your predictions were correct and in what ways they were incorrect. In education research, it is rarely useful to think of your predictions as either right or wrong. Because of the complexity of most issues you will investigate, most predictions will be right in some ways and wrong in others.

By studying the observations you make (data you collect) to test your hypotheses, you can revise your hypotheses to better align with the observations. This means revising your predictions plus revising your rationales to justify your adjusted predictions. Even though you might not run another test, formulating revised hypotheses is an essential part of conducting a research study. Comparing your original and revised hypotheses informs everyone of what you learned by conducting your study. In addition, a revised hypothesis sets the stage for you or someone else to extend your study and accumulate more knowledge of the phenomenon.

We should note that not everyone makes a clear distinction between predictions and rationales as two aspects of hypotheses. In fact, common, non-scientific uses of the word “hypothesis” may limit it to only a prediction or only an explanation (or rationale). We choose to explicitly include both prediction and rationale in our definition of hypothesis, not because we assert this should be the universal definition, but because we want to foreground the importance of both parts acting in concert. Using “hypothesis” to represent both prediction and rationale could hide the two aspects, but we make them explicit because they provide different kinds of information. It is usually easier to make predictions than develop rationales because predictions can be guesses, hunches, or gut feelings about which you have little confidence. Developing a compelling rationale requires careful thought plus reading what other researchers have found plus talking with your colleagues. Often, while you are developing your rationale you will find good reasons to change your predictions. Developing good rationales is the engine that drives scientific inquiry. Rationales are essentially descriptions of how much you know about the phenomenon you are studying. Throughout this guide, we will elaborate on how developing good rationales drives scientific inquiry. For now, we simply note that it can sharpen your predictions and help you to interpret your data as you test your hypotheses.

An image represents the rationale and the prediction for the scientific inquiry and different types of information provided by the terms.

Hypotheses in education research take a variety of forms or types. This is because there are a variety of phenomena that can be investigated. Investigating educational phenomena is sometimes best done using qualitative methods, sometimes using quantitative methods, and most often using mixed methods (e.g., Hay, 2016 ; Weis et al. 2019a ; Weisner, 2005 ). This means that, given our definition, hypotheses are equally applicable to qualitative and quantitative investigations.

Hypotheses take different forms when they are used to investigate different kinds of phenomena. Two very different activities in education could be labeled conducting experiments and descriptions. In an experiment, a hypothesis makes a prediction about anticipated changes, say the changes that occur when a treatment or intervention is applied. You might investigate how students’ thinking changes during a particular kind of instruction.

A second type of hypothesis, relevant for descriptive research, makes a prediction about what you will find when you investigate and describe the nature of a situation. The goal is to understand a situation as it exists rather than to understand a change from one situation to another. In this case, your prediction is what you expect to observe. Your rationale is the set of reasons for making this prediction; it is your current explanation for why the situation will look like it does.

You will probably read, if you have not already, that some researchers say you do not need a prediction to conduct a descriptive study. We will discuss this point of view in Chap. 2 . For now, we simply claim that scientific inquiry, as we have defined it, applies to all kinds of research studies. Descriptive studies, like others, not only benefit from formulating, testing, and revising hypotheses, but also need hypothesis formulating, testing, and revising.

One reason we define research as formulating, testing, and revising hypotheses is that if you think of research in this way you are less likely to go wrong. It is a useful guide for the entire process, as we will describe in detail in the chapters ahead. For example, as you build the rationale for your predictions, you are constructing the theoretical framework for your study (Chap. 3 ). As you work out the methods you will use to test your hypothesis, every decision you make will be based on asking, “Will this help me formulate or test or revise my hypothesis?” (Chap. 4 ). As you interpret the results of testing your predictions, you will compare them to what you predicted and examine the differences, focusing on how you must revise your hypotheses (Chap. 5 ). By anchoring the process to formulating, testing, and revising hypotheses, you will make smart decisions that yield a coherent and well-designed study.

Exercise 1.5

Compare the concept of formulating, testing, and revising hypotheses with the descriptions of scientific inquiry contained in Scientific Research in Education (NRC, 2002 ). How are they similar or different?

Exercise 1.6

Provide an example to illustrate and emphasize the differences between everyday learning/thinking and scientific inquiry.

Learning from Doing Scientific Inquiry

We noted earlier that a measure of what you have learned by conducting a research study is found in the differences between your original hypothesis and your revised hypothesis based on the data you collected to test your hypothesis. We will elaborate this statement in later chapters, but we preview our argument here.

Even before collecting data, scientific inquiry requires cycles of making a prediction, developing a rationale, refining your predictions, reading and studying more to strengthen your rationale, refining your predictions again, and so forth. And, even if you have run through several such cycles, you still will likely find that when you test your prediction you will be partly right and partly wrong. The results will support some parts of your predictions but not others, or the results will “kind of” support your predictions. A critical part of scientific inquiry is making sense of your results by interpreting them against your predictions. Carefully describing what aspects of your data supported your predictions, what aspects did not, and what data fell outside of any predictions is not an easy task, but you cannot learn from your study without doing this analysis.

An image represents the cycle of events that take place before making predictions, developing the rationale, and studying the prediction and rationale multiple times.

Analyzing the matches and mismatches between your predictions and your data allows you to formulate different rationales that would have accounted for more of the data. The best revised rationale is the one that accounts for the most data. Once you have revised your rationales, you can think about the predictions they best justify or explain. It is by comparing your original rationales to your new rationales that you can sort out what you learned from your study.

Suppose your study was an experiment. Maybe you were investigating the effects of a new instructional intervention on students’ learning. Your original rationale was your explanation for why the intervention would change the learning outcomes in a particular way. Your revised rationale explained why the changes that you observed occurred like they did and why your revised predictions are better. Maybe your original rationale focused on the potential of the activities if they were implemented in ideal ways and your revised rationale included the factors that are likely to affect how teachers implement them. By comparing the before and after rationales, you are describing what you learned—what you can explain now that you could not before. Another way of saying this is that you are describing how much more you understand now than before you conducted your study.

Revised predictions based on carefully planned and collected data usually exhibit some of the following features compared with the originals: more precision, more completeness, and broader scope. Revised rationales have more explanatory power and become more complete, more aligned with the new predictions, sharper, and overall more convincing.

Part II. Why Do Educators Do Research?

Doing scientific inquiry is a lot of work. Each phase of the process takes time, and you will often cycle back to improve earlier phases as you engage in later phases. Because of the significant effort required, you should make sure your study is worth it. So, from the beginning, you should think about the purpose of your study. Why do you want to do it? And, because research is a social practice, you should also think about whether the results of your study are likely to be important and significant to the education community.

If you are doing research in the way we have described—as scientific inquiry—then one purpose of your study is to understand , not just to describe or evaluate or report. As we noted earlier, when you formulate hypotheses, you are developing rationales that explain why things might be like they are. In our view, trying to understand and explain is what separates research from other kinds of activities, like evaluating or describing.

One reason understanding is so important is that it allows researchers to see how or why something works like it does. When you see how something works, you are better able to predict how it might work in other contexts, under other conditions. And, because conditions, or contextual factors, matter a lot in education, gaining insights into applying your findings to other contexts increases the contributions of your work and its importance to the broader education community.

Consequently, the purposes of research studies in education often include the more specific aim of identifying and understanding the conditions under which the phenomena being studied work like the observations suggest. A classic example of this kind of study in mathematics education was reported by William Brownell and Harold Moser in 1949 . They were trying to establish which method of subtracting whole numbers could be taught most effectively—the regrouping method or the equal additions method. However, they realized that effectiveness might depend on the conditions under which the methods were taught—“meaningfully” versus “mechanically.” So, they designed a study that crossed the two instructional approaches with the two different methods (regrouping and equal additions). Among other results, they found that these conditions did matter. The regrouping method was more effective under the meaningful condition than the mechanical condition, but the same was not true for the equal additions algorithm.

What do education researchers want to understand? In our view, the ultimate goal of education is to offer all students the best possible learning opportunities. So, we believe the ultimate purpose of scientific inquiry in education is to develop understanding that supports the improvement of learning opportunities for all students. We say “ultimate” because there are lots of issues that must be understood to improve learning opportunities for all students. Hypotheses about many aspects of education are connected, ultimately, to students’ learning. For example, formulating and testing a hypothesis that preservice teachers need to engage in particular kinds of activities in their coursework in order to teach particular topics well is, ultimately, connected to improving students’ learning opportunities. So is hypothesizing that school districts often devote relatively few resources to instructional leadership training or hypothesizing that positioning mathematics as a tool students can use to combat social injustice can help students see the relevance of mathematics to their lives.

We do not exclude the importance of research on educational issues more removed from improving students’ learning opportunities, but we do think the argument for their importance will be more difficult to make. If there is no way to imagine a connection between your hypothesis and improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Notice that we said the ultimate goal of education is to offer all students the best possible learning opportunities. For too long, educators have been satisfied with a goal of offering rich learning opportunities for lots of students, sometimes even for just the majority of students, but not necessarily for all students. Evaluations of success often are based on outcomes that show high averages. In other words, if many students have learned something, or even a smaller number have learned a lot, educators may have been satisfied. The problem is that there is usually a pattern in the groups of students who receive lower quality opportunities—students of color and students who live in poor areas, urban and rural. This is not acceptable. Consequently, we emphasize the premise that the purpose of education research is to offer rich learning opportunities to all students.

One way to make sure you will be able to convince others of the importance of your study is to consider investigating some aspect of teachers’ shared instructional problems. Historically, researchers in education have set their own research agendas, regardless of the problems teachers are facing in schools. It is increasingly recognized that teachers have had trouble applying to their own classrooms what researchers find. To address this problem, a researcher could partner with a teacher—better yet, a small group of teachers—and talk with them about instructional problems they all share. These discussions can create a rich pool of problems researchers can consider. If researchers pursued one of these problems (preferably alongside teachers), the connection to improving learning opportunities for all students could be direct and immediate. “Grounding a research question in instructional problems that are experienced across multiple teachers’ classrooms helps to ensure that the answer to the question will be of sufficient scope to be relevant and significant beyond the local context” (Cai et al., 2019b , p. 115).

As a beginning researcher, determining the relevance and importance of a research problem is especially challenging. We recommend talking with advisors, other experienced researchers, and peers to test the educational importance of possible research problems and topics of study. You will also learn much more about the issue of research importance when you read Chap. 5 .

Exercise 1.7

Identify a problem in education that is closely connected to improving learning opportunities and a problem that has a less close connection. For each problem, write a brief argument (like a logical sequence of if-then statements) that connects the problem to all students’ learning opportunities.

Part III. Conducting Research as a Practice of Failing Productively

Scientific inquiry involves formulating hypotheses about phenomena that are not fully understood—by you or anyone else. Even if you are able to inform your hypotheses with lots of knowledge that has already been accumulated, you are likely to find that your prediction is not entirely accurate. This is normal. Remember, scientific inquiry is a process of constantly updating your thinking. More and better information means revising your thinking, again, and again, and again. Because you never fully understand a complicated phenomenon and your hypotheses never produce completely accurate predictions, it is easy to believe you are somehow failing.

The trick is to fail upward, to fail to predict accurately in ways that inform your next hypothesis so you can make a better prediction. Some of the best-known researchers in education have been open and honest about the many times their predictions were wrong and, based on the results of their studies and those of others, they continuously updated their thinking and changed their hypotheses.

A striking example of publicly revising (actually reversing) hypotheses due to incorrect predictions is found in the work of Lee J. Cronbach, one of the most distinguished educational psychologists of the twentieth century. In 1955, Cronbach delivered his presidential address to the American Psychological Association. Titling it “Two Disciplines of Scientific Psychology,” Cronbach proposed a rapprochement between two research approaches—correlational studies that focused on individual differences and experimental studies that focused on instructional treatments controlling for individual differences. (We will examine different research approaches in Chap. 4 ). If these approaches could be brought together, reasoned Cronbach ( 1957 ), researchers could find interactions between individual characteristics and treatments (aptitude-treatment interactions or ATIs), fitting the best treatments to different individuals.

In 1975, after years of research by many researchers looking for ATIs, Cronbach acknowledged the evidence for simple, useful ATIs had not been found. Even when trying to find interactions between a few variables that could provide instructional guidance, the analysis, said Cronbach, creates “a hall of mirrors that extends to infinity, tormenting even the boldest investigators and defeating even ambitious designs” (Cronbach, 1975 , p. 119).

As he was reflecting back on his work, Cronbach ( 1986 ) recommended moving away from documenting instructional effects through statistical inference (an approach he had championed for much of his career) and toward approaches that probe the reasons for these effects, approaches that provide a “full account of events in a time, place, and context” (Cronbach, 1986 , p. 104). This is a remarkable change in hypotheses, a change based on data and made fully transparent. Cronbach understood the value of failing productively.

Closer to home, in a less dramatic example, one of us began a line of scientific inquiry into how to prepare elementary preservice teachers to teach early algebra. Teaching early algebra meant engaging elementary students in early forms of algebraic reasoning. Such reasoning should help them transition from arithmetic to algebra. To begin this line of inquiry, a set of activities for preservice teachers were developed. Even though the activities were based on well-supported hypotheses, they largely failed to engage preservice teachers as predicted because of unanticipated challenges the preservice teachers faced. To capitalize on this failure, follow-up studies were conducted, first to better understand elementary preservice teachers’ challenges with preparing to teach early algebra, and then to better support preservice teachers in navigating these challenges. In this example, the initial failure was a necessary step in the researchers’ scientific inquiry and furthered the researchers’ understanding of this issue.

We present another example of failing productively in Chap. 2 . That example emerges from recounting the history of a well-known research program in mathematics education.

Making mistakes is an inherent part of doing scientific research. Conducting a study is rarely a smooth path from beginning to end. We recommend that you keep the following things in mind as you begin a career of conducting research in education.

First, do not get discouraged when you make mistakes; do not fall into the trap of feeling like you are not capable of doing research because you make too many errors.

Second, learn from your mistakes. Do not ignore your mistakes or treat them as errors that you simply need to forget and move past. Mistakes are rich sites for learning—in research just as in other fields of study.

Third, by reflecting on your mistakes, you can learn to make better mistakes, mistakes that inform you about a productive next step. You will not be able to eliminate your mistakes, but you can set a goal of making better and better mistakes.

Exercise 1.8

How does scientific inquiry differ from everyday learning in giving you the tools to fail upward? You may find helpful perspectives on this question in other resources on science and scientific inquiry (e.g., Failure: Why Science is So Successful by Firestein, 2015).

Exercise 1.9

Use what you have learned in this chapter to write a new definition of scientific inquiry. Compare this definition with the one you wrote before reading this chapter. If you are reading this book as part of a course, compare your definition with your colleagues’ definitions. Develop a consensus definition with everyone in the course.

Part IV. Preview of Chap. 2

Now that you have a good idea of what research is, at least of what we believe research is, the next step is to think about how to actually begin doing research. This means how to begin formulating, testing, and revising hypotheses. As for all phases of scientific inquiry, there are lots of things to think about. Because it is critical to start well, we devote Chap. 2 to getting started with formulating hypotheses.

Agnes, M., & Guralnik, D. B. (Eds.). (2008). Hypothesis. In Webster’s new world college dictionary (4th ed.). Wiley.

Google Scholar

Britannica. (n.d.). Scientific method. In Encyclopaedia Britannica . Retrieved July 15, 2022 from https://www.britannica.com/science/scientific-method

Brownell, W. A., & Moser, H. E. (1949). Meaningful vs. mechanical learning: A study in grade III subtraction . Duke University Press..

Cai, J., Morris, A., Hohensee, C., Hwang, S., Robison, V., Cirillo, M., Kramer, S. L., & Hiebert, J. (2019b). Posing significant research questions. Journal for Research in Mathematics Education, 50 (2), 114–120. https://doi.org/10.5951/jresematheduc.50.2.0114

Article Google Scholar

Cambridge University Press. (n.d.). Hypothesis. In Cambridge dictionary . Retrieved July 15, 2022 from https://dictionary.cambridge.org/us/dictionary/english/hypothesis

Cronbach, J. L. (1957). The two disciplines of scientific psychology. American Psychologist, 12 , 671–684.

Cronbach, L. J. (1975). Beyond the two disciplines of scientific psychology. American Psychologist, 30 , 116–127.

Cronbach, L. J. (1986). Social inquiry by and for earthlings. In D. W. Fiske & R. A. Shweder (Eds.), Metatheory in social science: Pluralisms and subjectivities (pp. 83–107). University of Chicago Press.

Hay, C. M. (Ed.). (2016). Methods that matter: Integrating mixed methods for more effective social science research . University of Chicago Press.

Merriam-Webster. (n.d.). Explain. In Merriam-Webster.com dictionary . Retrieved July 15, 2022, from https://www.merriam-webster.com/dictionary/explain

National Research Council. (2002). Scientific research in education . National Academy Press.

Weis, L., Eisenhart, M., Duncan, G. J., Albro, E., Bueschel, A. C., Cobb, P., Eccles, J., Mendenhall, R., Moss, P., Penuel, W., Ream, R. K., Rumbaut, R. G., Sloane, F., Weisner, T. S., & Wilson, J. (2019a). Mixed methods for studies that address broad and enduring issues in education research. Teachers College Record, 121 , 100307.

Weisner, T. S. (Ed.). (2005). Discovering successful pathways in children’s development: Mixed methods in the study of childhood and family life . University of Chicago Press.

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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). What Is Research, and Why Do People Do It?. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_1

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5.1: The Purpose of Research Writing

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Lynne Bost, Barbara Hall, Michelle Kassorla, Karen McKinney-Holley, Kirk Swenson, and Rebecca Weaver (Managing Editor)

Lynne Bost, Barbara Hall, Michelle Kassorla, Karen McKinney-Holley, Kirk Swenson, and Rebecca Weaver (Managing Editor)
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The Purpose of Research Writing

Screen Shot 2019-11-27 at 10.10.04 AM.png

Who has written poetry about exile?
What roles did women play in the American Revolution?
Where do cicadas go during their off years?
Should big-time college athletes be paid?
When did bookmakers start using movable type?
Why was the Great Wall of China built?
How does the human brain create, store, and retrieve memories?

You may know the answers to these questions off the top of your head. If you are like most people, however, you find answers to tough questions like these by searching the Internet, visiting a library, or asking others for information. To put it simply, you perform research.

Whether or not you realize it, you probably already perform research in your everyday life.

When your boss, your instructor, or a family member asks you a question that you don’t know the answer to, you locate relevant information, analyze your findings, and share your results. Locating, analyzing, and sharing information are key steps in the research process. In this chapter, you will learn more about each step. By developing your research writing skills, you will prepare yourself to answer challenging questions.

Sometimes you perform research simply to satisfy your own curiosity. Once you find the answer to your research question, your search may be over, or it may lead to more in-depth research about that topic or about another topic.

Other times, you want to communicate what you have learned to your peers, your family, your teachers, or even the editors of magazines, newspapers, or journals. In your personal life, you might simply discuss the topic with your friends. In more formal situations, such as in business and school, you communicate your findings in writing or in a presentation.

There are differences between a report and research:

A report may simply relay the results of your research in an organized manner. In contrast, a research project presents a research question and answers that question through the sources which led you to that answer.

In a research paper, you use facts, interpretations, and opinions you encounter in your research to create a narrative and support an argument (an answer to your research question) about your topic.

A student in an art history course might write a research paper about an artist's work or an aesthetic movement. A student in a psychology course might present on findings about current research in childhood development.

No matter what field of study you pursue, you will most likely be asked to compose a research project in your college degree program and to apply the skills of research and writing in your career. For similar reasons as professionals, students do research to answer specific questions, to share their findings with others, to increase their understanding of challenging topics, and to strengthen their analytical skills.

Having to complete a research project may feel intimidating at first. After all, researching and composing a large project requires a lot of time, effort, and organization. However, its challenges have rewards. The research process allows you to gain expertise on a topic of your choice.

The writing process helps you to remember what you learned, to understand it on a deeper level, and to develop expertise. Thus writing a research paper can be a great opportunity to explore a question and topic that particularly interests you and to grow as a person.

Screen Shot 2019-11-27 at 10.11.55 AM.png

Exercise: Free Writing about Research

Screen Shot 2019-11-27 at 10.14.09 AM.png

Identify the job of your dreams.
Now, freewrite about ways in which strong researching, organizing, writing, and critical thinking skills could help you succeed at your dream job.
Finally, share some of your ideas with a partner or in class discussion. Are there more ways to apply research to that job than you had thought of initially?

Process Overview

Screen Shot 2019-11-27 at 10.16.17 AM.png

How does a research paper grow from a folder of notes to a polished final draft? No two projects are identical, and no two paths to completion are identical. That said, most research projects go through a set of stages, often repeating stages such a prewriting, drafting, writing from sources, and revising, in a recursive pattern.

Here is an example of what that pattern often looks like in a real-life research project, with the stages described in detail the infographic below:

The Recursive Process

Screen Shot 2019-11-27 at 10.17.14 AM.png

You probably noticed that the process started repeating and fell out of order, right? Well, that's research (and writing in general)! It's a messy, sometimes confusing, but almost always rewarding journey, and if you dive into the process with an open mind, you'll probably end up with some great and interesting results.

Defining a Topic

Depending on your specific professor's assignment directions, you may get to choose your topic completely, you may get to choose a topic within a frame, or you may get to choose a topic from a list provided by the professor.

To narrow the focus of your topic, brainstorm using prewriting techniques, as well as any guidance or texts given by your instructor. Once you're sure of your topic, formulate a specific research question (a broad, open-ended question) or set of questions that will guide your research. Your research will help you answer the question or answer another question that you realize is more interesting or useful.

Planning and Scheduling

Conducting Research: Determining and Gathering the Right Kinds of Research

When going about your research, you will likely use a variety of sources, anything from books and periodicals to video presentations and in-person interviews. However, you should pay close attention to instructions; instructors often specify what kinds of sources they require for research papers.

Many will instruct you to only use academic / scholarly (peer-reviewed) sources, as those are the sources most valued in academia. For some assignments, your sources might include primary, secondary, and tertiary sources.

Primary sources provide firsthand information or raw data. For example, surveys, in-person interviews, historical documents, works of art, and works of literature are primary sources.
Secondary sources -- such as biographies, literary reviews, or news articles--include some analysis or interpretation of the information presented.
Tertiary sources --such as dictionaries, sourcebooks, encyclopedias, and some textbooks--repackage, reorganize, abstract, or compile information. They are usually not referenced to a specific author.

As you conduct research, you should take detailed, careful notes about your discoveries. This is writing, and it's an important part of the process, even if it's just notes at this point. Remember: you understand what you're reading by engaging with the material. You need to read predatorily and take notes strategically. You should also evaluate the reliability of each source you find, especially sources that are not peer-reviewed. Just because it exists doesn't mean it's a good source.

Organizing Your Research and Ideas, Abstracting From Materials, Writing

As you're beginning to learn about your topic, you'll likely feel overwhelmed by all of the information. That's normal. Here is what will help: writing as you're researching. This doesn't have to be polished writing. What's important is that you write throughout the process, constantly cycling through the recursive process.

When your research is complete, you will therefore have more material than you need, and you'll then be able to organize your findings and decide which sources to cite in your paper. You will also have an opportunity to evaluate the evidence you have collected and determine whether it supports your thesis, or the focus of your paper.

You may decide to adjust your thesis or conduct additional research to ensure that your thesis is well supported. The steps of a research project often overlap and repeat. They are not sequential or separate from each other.

Drafting Your Project

Now you are ready to compile your research findings, your notes, and other research with your critical analysis of the results in a first rough draft. This will likely be a messy draft, and that's OK.

The idea at this stage is to start to draw all of your thoughts and new-found expertise into a somewhat cohesive whole. You can always revise later. Your goal in almost any research project is to find out the answer to your research question. You will incorporate source materials into your paper and discuss each source thoughtfully in relation to your thesis (the answer to that question) or purpose statement.

It is important to pay close attention to standard conventions for citing sources in order to avoid plagiarism, which is the practice of using someone else's words without acknowledging the source. Later in this chapter, you will learn how to incorporate sources in your project and avoid some of the most common pitfalls of attributing information.

Revising and Editing Your Project

If you commit to the process of drafting a little every day and drafting as you research, you'll find that the project will get less messy as you begin to understand how the new information you know helps you understand the topic and your questions about it.

You might reorganize your paper's structure or revise for unity and cohesion, ensuring that each element in your paper smoothly and logically flows into the next. You will also make sure that your paper uses an appropriate and consistent tone.

Once you feel confident in the strength of your writing, you will edit your paper for proper spelling, grammar, punctuation, mechanics, and formatting.

When you complete this final step, you will have transformed a simple idea or question into a thoroughly researched and well-written project of which you can be proud.

A Final Note

Writing a good research project takes time, thought, and effort. Although this assignment is challenging, it is manageable if you commit to the process: write to understand what you want to know (answer your research questions), write as you learn more (understand your research), and write to share what you know (share that expertise with your audience). This will help you develop a thoughtful, informative, well-supported research project.

Why your students don't do the readings

Dr Sandris Zeivots

Most higher education students do not engage with course readings, but new research suggests that can be fixed by rethinking how and why they are assigned.

Published in the Academy of Management Learning and Education , the research proposes six aspects to consider when seeking meaningful student engagement with readings: usefulness, enjoyment, quantity, access, intent and integration with the course.

Dr Sandris Zeivots said the research was inspired by his work in course co-design at the University of Sydney Business School .

“ Existing research suggests 70 to 80 percent of students do not engage with course readings. That’s for a whole host of reasons, from time constraints and language barriers to a lack of understanding of the purpose of readings,” Dr Zeivots said.

“Anecdotally, lecturers know most students don’t comply with the system, but we act as though the fault is with the students. This research started by flipping that assumption and asking: what are we trying to achieve with readings? And, how can we better design them so that students will want to engage?”

Dr Zeivots worked with International Business course coordinator Professor Vikas Kumar to redesign the readings in the popular Master of Commerce subject at the Business School.

After examining the existing literature and developing their framework, Dr Zeivots and his co-author Ms Courtney Shalavin worked with Professor Kumar, tutors and students over the course of three consecutive semesters – a process that led to half the readings being changed.

They introduced one to two ‘must-read’ pages for each reading that contained the key points, and an unmarked online discussion question to guide students’ approach to each reading and to engage their critical thinking.

Surveys revealed just over half (54 percent) of students reported reading the must-read pages, and engagement with readings increased slightly over the semester, rather than decreased with student fatigue.

Professor Kumar said the discussion questions allowed tutors to engage students on the concepts raised by the readings without the pressure of a grade.

“Involving students in the co-design process produced invaluable feedback. For example, we learned students wanted to learn more about fintech, so we introduced more fintech case studies that aligned with our core teaching concepts.”

Declaration

This research was conducted as part of the Connected Learning at Scale project at the University of Sydney Business School. The authors declare no conflicts of interest.

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Advice for the Unmotivated

Robin Abrahams
Boris Groysberg

How to reignite your enthusiasm for work

Employee disengagement is rampant in the workplace. We’ve all experienced it as customers encountering unhelpful retail clerks and as colleagues dealing with apathetic teammates. But what happens when you yourself feel dead at work?

This article describes what you as an individual can do to sustain your motivation or recover it, even in the most stultifying of jobs. After synthesizing research on this challenge and experimenting with various strategies, the authors have developed a process for recharging yourself called DEAR.

The first step is to detach and objectively analyze your situation so that you can make wise choices about it, instead of reacting in a fight-or-flight way. At day’s end, review what went well at your job and then mentally disconnect from it to give yourself a break. Meditation and exercise can help you do that and will improve your mood and cognitive function. Next, show empathy. Practice self-care, make friends, recognize the accomplishments of others, seek their views, and help them. Research shows that this combats burnout. Third, take action: achieve small wins, invest in rewarding outside activities, redefine your responsibilities, and turn uninteresting tasks into games. Ask yourself how someone you admire would behave in your situation, and dress in a way that projects confidence. Last, reframe your thinking: Focus on the informal roles you enjoy at work, your job’s higher-order purpose, and how others benefit from your work. All these techniques will improve your mental health and increase the energy you bring to your job—even if it is not what you’d like it to be.

In virtually everyone’s career, there comes a time when motivation and interest vanish. The usual tasks feel tedious. It’s hard to muster the energy for new projects. Though we go through the motions of being good employees or managers, we’re not really “there.” We become ghosts or zombies: the working dead.

Robin Abrahams is a research associate at Harvard Business School.
BG Boris Groysberg is a professor of business administration in the Organizational Behavior unit at Harvard Business School and a faculty affiliate at the school’s Race, Gender & Equity Initiative. He is the coauthor, with Colleen Ammerman, of Glass Half-Broken: Shattering the Barriers That Still Hold Women Back at Work (Harvard Business Review Press, 2021). bgroysberg

Partner Center

The rise of the inclusive consumer

The American consumer is undeniably becoming more inclusive. Responding to our survey 1 McKinsey Inclusive Consumer Survey, October 2021. in October 2021, two out of three Americans told us their social values now shape their shopping choices. And 45 percent—likely representing well over a hundred million shoppers 2 Extrapolated data: 45 percent of 270 million US residents over 18 years old would be about 120 million. —believe retailers should actively support Black-owned businesses and brands. This 45 percent represents the inclusive consumer.

About the authors

This article is a collaborative effort by Pamela Brown, Tiffany Burns , Tyler Harris, Charlotte Lucas, and Israe Zizaoui, representing views from McKinsey’s Retail Practice.

Large consumer and retail players from Nordstrom to Yelp are moving quickly to serve this group of influential customers. Indeed, while inclusive consumers tend to be younger, female, and more racially diverse, they include men and women across ethnic backgrounds, income levels, and age groups. Given this diverse and ubiquitous representation, the inclusive consumer holds the unique power to influence all demographic groups (Exhibit 1).

The inclusive consumer is more likely than other shoppers to buy Black-owned brands out of a desire to support diverse entrepreneurs on their growth journeys and small businesses in general (Exhibit 2). Like many other consumers today, they base their shopping choices less on traditional advertising and more on social media, friends’ recommendations, and the stories of those who founded the brands they admire. They are also more likely than other shoppers to care about sustainability and quality. 3 McKinsey Inclusive Consumer Survey, October 2021.

Where the inclusive consumer may be headed

Inclusive consumers are a large and influential population, and they want to spend more on Black-owned brands, which they know are underrepresented on store shelves. However, finding the brands and the products remains a barrier. Indeed, one in five inclusive consumers cited not finding the products they wanted as a reason for not buying from Black-owned brands. This plays out in the bigger picture of US retail spending as well. While about 14 percent of the US population identifies as Black, 4 “Quick facts,” United States Census Bureau, July 1, 2019. Black-owned brands rang up only about $83 billion in sales in 2020 5 Estimated with consumer-reported proportion of holiday shopping with Black-owned brands and National Retail Federation data on 2020 holiday spending of $790 billion. —less than 1.5 percent of $5.4 trillion 6 “Sales for U.S. retail trade sector over $5,411.0 billion,” United States Census Bureau, January 28, 2021. of retail spending. In our survey, about 21 percent of inclusive consumers said they had pledged to devote at least 15 percent of their retail spending to Black-owned brands in an effort to turn the tides. 7 McKinsey Inclusive Consumer Survey, October 2021.

Most retailers will need to make changes to meet the needs of inclusive consumers. Fewer than half of these shoppers say they know which products on retail shelves are from Black-owned brands, and a third don’t know where to go to purchase Black-owned brands. 8 McKinsey Inclusive Consumer Survey, October 2021. About 45 percent of the inclusive consumers we surveyed said they would value relevant labeling on store shelves and the ability to filter website results to find Black-owned brands. About a third would value additional sources of information, such as curated lists of products, a database of Black-owned brands, and recommendations from influencers.

Major retailers are now joining social influencers and other stakeholders to spread the word. Growing support for Black-owned brands is evident in social media and traditional media: a wide range of publications, from New York magazine and GQ to Harper’s Bazaar 9 “The 42 best gifts to shop from Black-owned businesses now and forever,” Harper’s Bazaar , November 17, 2021. and whowhatwear.com, published a curated holiday list of products from Black-owned brands in November 2021. In the same month, Oprah’s “favorite things” list 10 “Oprah’s favorite things 2021 list is here!,” Oprah Daily, November 23, 2021. focused on products from small businesses, many of which are owned by women and people of color.

How retailers could attract the inclusive consumer

In a marketplace being transformed by digitization, social change, and a global pandemic, leading retailers and brand managers know that they must keep meeting evolving consumer preferences to stay relevant. Major retailers are now reviewing how they work—from operations and merchandising to hiring and HR practices—and starting to move the needle. Retailers should consider actions in five main areas to bring the inclusive consumer through their doors and onto their websites.

Action 1: Reshape shelves. Retailers can first and foremost demonstrate a commitment to the inclusive consumer by evaluating and reimagining the brands on their shelves. Many are already taking strong action, reimagining their merchandising mix to make shelves and the brands that sit on them more representative. For example, more than 28 national retailers, including Gap, Macy’s, and Sephora, have signed the Fifteen Percent Pledge’s call for 15 percent of retail shelf space to be dedicated to Black-owned brands. Some of these retailers have doubled their assortments of Black-owned brands in just a year, opening their doors to almost 400 brands. 11 Elizabeth Segran, “In one year, the 15% Pledge got 385 Black-owned brands on the shelves of Macy’s, Gap, Sephora, and more,” Fast Company , July 7, 2021. In addition to introducing Black-owned brands, retailers could also review their planograms and product placement: for example, Ulta Beauty is intentional about placing Black-owned brands in prime locations in stores and creates dedicated efforts to increase Black-owned brands’ features in circular advertising and email marketing. 12 Liz Flora, “Camille Rose expands to Ulta Beauty as retailer makes Black-owned brand push,” Glossy, April 12, 2021.

Retailers can first and foremost demonstrate a commitment to the inclusive consumer by evaluating and reimagining the brands on their shelves.

Action 2: Switch up sourcing. Retailers, especially those who are vertically integrated, could also demonstrate commitment to the inclusive consumer by doubling down on diversity in their supply chain. For example, Best Buy has committed to spending at least $1.2 billion with businesses owned by members of the Black, Indigenous, and people of color (BIPOC) community and other diverse businesses by 2025. 13 “Best Buy commits to spending $1.2 billion with BIPOC and diverse businesses by 2025,” Business Wire, June 24, 2021. The commitment includes plans to increase all forms of spending with businesses from nearly every corner of the company—from how it brings goods and services to stores to where and how it advertises. Supplier diversity is not limited to retailers and can also be considered broadly by most brands and companies. For example, in 2020, the Coca-Cola Company committed to spending an additional $500 million over five years with Black-owned suppliers, more than doubling the company’s previous commitment. 14 “Coca-Cola Company commits $500 million in additional spending with Black-owned suppliers,” Coca-Cola Company, October 10, 2020. These actions show an increasing commitment to diversity across the supply chain, and these types of commitments will likely grow in future years as consumers begin calling for similar levels of diversity in the supply chain as they are calling for on shelves.

Action 3: Map it out. Inclusive consumers consistently say that not knowing which brands are Black-owned or where to shop for them are barriers to spending as much as they would like on brands from diverse founders. And wayfinding is their resounding answer. Retailers could help consumers identify Black-owned brands with clear labeling on shelves and websites, the ability to filter website search results, and curated lists of products, for example.

Sephora responded to these needs by creating a dedicated tab on its website to share Black-owned brands’ stories and products and by enhancing its online site, which features Black-owned brands on its browsing pane, provides a filter for shoppers looking for Black- and BIPOC-owned brands, and provides curated lists of recommended products, including a “Sephora Favorites” bundle in Black-owned beauty. 15 Kori Hale, “Sephora’s planning to double down on Black-owned brands,” Forbes , January 25, 2021. Google is also actively working on multiple initiatives to support Black-owned brands, including a tool that allows Black-owned businesses to identify themselves in maps, listings, and Google business-profile searches. 16 Keyword , “Standing with the Black community,” blog entry by Sundar Pichai, Google, June 3, 2020; “Supporting Black-owned businesses,” Google for Small Business, 2021. Additionally, Google has launched the ByBlack platform, which consists of both a national Black business directory (powered by the US Black Chambers) and a national certification as a Black-owned business (in partnership with American Express). This tool provides Black entrepreneurs access to a community with valuable business resources (including Google trainings) and a way to help reach new customers.

Action 4: Share the stories. Inclusive consumers care about what is on shelves, but they want more. They want to learn about founders’ stories, for example, and support the missions of small businesses. Further, our research shows that inclusive consumers are more likely than other shoppers to buy Black-owned brands based on recommendations from friends, and retailers that incorporate founder stories into marketing and digital placements are more likely than those that don’t to attract the inclusive consumer’s eye. Nordstrom, for example, introduced “Concept 012: Black_Space,” which includes a dedicated shop developed, designed, and curated by Black voices to amplify Black representation through in-store buildouts and merchandising. The concept is further supported with an online site experience that includes video content created by Black curators to represent their perspectives. 17 “New Concepts @Nordstrom launches Concept 012: Black_Space,” Nordstrom, February 22, 2021.

Action 5: Ditch the big-brand playbook. Introducing and cultivating smaller brands takes different capabilities and mindsets than retailers may be accustomed to when working with larger, more established brands. Unlike big brands, small brands come with more variability in experience and know-how, as well as growing pains as they enter the bigger retail stage. Retailers that are committed to fostering smaller brands will need to work differently, creating teams that understand how these brands operate. For example, those with experience working with small brands know that everyday requirements from retailers, such as buy sizes and inventory systems, can have large-scale repercussions on small brands with limited working capital or team capacity to meet these terms. A retailer that seeks to help smaller brands can boost the odds of success by adapting its playbook and its teams to suit their needs.

The time is now

In the years ahead, millions more consumers will likely join the ranks of inclusive consumers, rewarding businesses that pursue inclusion and avoiding those that don’t.

Businesses that meet the needs of inclusive consumers will likely do more than raise revenues and loyalty—they may also earn dividends in other areas of the business, including attracting and retaining talent. About 70 percent of the US-based employees we surveyed in August 2020 said their sense of purpose is largely defined by work, and nearly two-thirds said COVID-19 had caused them to reflect on their purpose in life, and nearly half were reconsidering the kind of work they do. (For more on this topic, please see Naina Dhingra, Andrew Samo, Bill Schaninger, and Matt Schrimper “ Help your employees find purpose—or watch them leave .”)

Whether employees or customers, the inclusive consumer is changing the imperative for retail. The evidence is overwhelming: the inclusive consumer is leading the pack, influencing consumers across demographics, and voting with their pocketbooks for retailers that support diverse entrepreneurs and their products. (For more on this topic, please see “ The Black unicorn: Changing the game for inclusivity in retail .”)

Pamela Brown is a partner in McKinsey’s New Jersey office, where Charlotte Lucas and Israe Zizaoui are consultants; Tiffany Burns is a partner in the Atlanta office; and Tyler Harris is an associate partner in the Washington, DC, office.

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Behav Anal Pract
v.8(2); 2015 Oct

The Importance of Research—A Student Perspective

Rachel arena.

grid.252546.20000000122978753Department of Psychology, Auburn University, Magnolia Street and Duncan Drive and West Thatch Ave, Auburn, AL 36849 USA

Sheridan Chambers

Angelyn rhames, katherine donahoe.

As students, we will focus on the importance of an objective ranking system, research, and mentorship to an applicant. We will address points raised in the (Behavior Analysis In Practice 8(1):7–15, 2015) article as well as debate the usefulness of proposed standards of objective ranking.

A Student’s Perspective on Research

A little more than a year ago each of us was madly scrambling to negotiate the process of graduate program admissions. Like many people who go to graduate school, each of us had some history of viewing academic efforts through the lens of “too much is never enough,” and we applied our obsessive habits to the challenge of gathering information about graduate programs. We pored over Web sites and printed brochures. We stalked program faculty at conferences, via email and phone, and during campus visits. We talked to trusted mentors about the programs they respected. When in professional settings, we tried to find out where people who impressed us had attended graduate school, and we sometimes eavesdropped on strangers’ conversations for potentially valuable tidbits about the graduate programs they were considering.

Based on this chaotic and exhausting experience, we agree with Dixon et al. ( 2015 ) that consumers in our field need standardized information about the relative merits of graduate programs in applied behavior analysis (ABA). When we began the process of screening graduate programs, we knew that we were uninformed but we were less sure about what we needed to learn to become better consumers. We suspect that, like us, most college seniors find it difficult to know what aspects of a graduate program are crucial to the training of highly qualified ABA practitioners. To us, the most important contribution of Dixon et al. ( 2015 ) was to emphasize that our field should not abandon students to an uncertain process of self-education.

We agree with Dixon et al. ( 2015 ) that our field is better equipped than outside bodies (e.g., U.S. News & World Report ) to determine what constitutes top-quality graduate training. We were aware that the Behavior Analysis Certification Board publishes the rates at which graduates of various programs pass its certification exam, and we considered this information during our respective searches. Even as undergraduates, however, we knew that there is more to being a capable practitioner than simply passing the certification exam, and we would have appreciated much more guidance from our field than we received.

In the absence of standardized, objective information about graduate programs, prospective graduate students have to rely heavily on hearsay. As we gathered information on program reputations from mentors and colleagues, it occurred to us that this information sometimes says as much about the person providing it as about graduate programs themselves. We learned that some people are impressed by graduate programs that have a reputation for highly selective admissions, but we were not sure how or whether this predicted the quality of training that we could hope to receive. We learned that certain mentors thought highly of certain programs, but different people thought highly of different programs, and it was not always obvious how these opinions related to specific features of the training offered by the programs. We weren’t always sure whether the opinions were generic or had been offered with our individual needs and interests in mind.

Among the features of graduate programs that interested us was the type and degree of emphasis on research. Here, a few words of explanation will provide context for our perspective. As undergraduates, we learned to value evidence-based practices, data-based case management, and the science-based critical thinking that should guide clinical case management. But each of us decided to seek graduate training not just to apply current best practices; we also wanted to contribute to clinical innovation (e.g., Critchfield 2015 ). For various reasons, none of us wished to conduct research for a living, and we chose our program at Auburn University in part because its accelerated, 12-month, non-thesis curriculum would get us swiftly into the workplace where we knew, from past field experiences, our main reinforcers are to be found. Still, program research emphasis was important to us.

Unfortunately, far too much time and effort was required for us to understand that different programs have different types of research emphases. “Research training” comprises not a single repertoire but many. One involves conducting research. Another involves locating and consuming available research on a topic of interest. Yet, another involves translating from research findings in order to develop innovative interventions (Critchfield 2015 ; Critchfield & Reed, 2005 ). It is here that we would quibble with the position of Dixon et al. ( 2015 ), which suggests a one-size-fits-all approach to assessing the research climate at ABA graduate programs.

In order to gain insight about the research environment in graduate programs, undergraduates often compare their own research interests to those of faculty as described on program web sites and as illustrated in published articles. This comparison is most relevant to students who seek to become independent researchers. Our own goal is to become life-long consumers of research. It may not be the full-time job of Masters-level practitioners to conduct research, but in a field that is growing quickly it is pivotal that people like us not be limited to the state of our field’s knowledge at the time we take a certification exam. We need skills for tracking scholarly developments across the full breath of our careers.

We agree with Dixon et al. ( 2015 ) that it is helpful for ABA program faculty to maintain active research programs, but our concern is with what program graduates are able to do with the fruits of research, not how many articles a faculty member can publish. It has been suggested that the process of developing effective and transportable interventions from research findings requires a skill set that is independent of either conducting research or implementing existing interventions (e.g., Critchfield 2015 ; Critchfield and Reed, 2005 ). No skill set seems more relevant to our lifelong professional development.

Yes, we want to learn how to read and critically evaluate research, but we want to learn to do this from faculty who know how to translate and who care about helping us to become translators. Our ideal ABA program faculty member will have the time and inclination to focus on this. We want mentors who can conduct research, but more importantly who will discuss research with us on a regular basis and explore with us how research findings relate to the behavioral processes operating in practice settings. We want mentors whose skills and schedules allow them to provide on-site clinical supervision through which the connections between research and practice can be drawn explicitly.

While we applaud the efforts of Dixon et al. ( 2015 ) to rank ABA graduate programs in terms of program research climate, we stress that this climate has multiple facets. We represent a category of consumer who cares very much about our field’s research foundations, but we wish to harness rather than add to those foundations. Faculty publication counts may not be the best measure of a program’s ability to help us to this. Unfortunately, the program attributes that we particularly value are hard to quantify and thus will be difficult to incorporate into an objective system for ranking programs. Yet, if the purpose of rankings is to assist consumers (Dixon et al., 2015 ), then the needs of consumers like us should not be ignored.

Contributor Information

Rachel Arena, Email: ude.nrubua@0200azr .

Sheridan Chambers, Email: ude.nrubua@5400cms .

Angelyn Rhames, Email: ude.nrubua@7400rza .

Katherine Donahoe, Email: ude.nrubua@4200drk .

Critchfield TS. What counts as high-quality practitioner training in applied behavior analysis? Behavior Analysis In Practice. 2015; 8 (1):3–6. doi: 10.1007/s40617-015-0049-0. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
Critchfield TS, Reed DD. Conduits of translation in behavior-science bridge research. In: Burgos JE, Ribes E, editors. Theory, basic and applied research, and technological applications in behavior science: Conceptual and methodological issues. Guadalajara, Mexico: University of Guadalajara Press; 2005. pp. 45–84. [ Google Scholar ]
Dixon MR, Reed DD, Smith T, Belisle J, Jackson RE. Research rankings of behavior analytic graduate training programs and their faculty. Behavior Analysis In Practice. 2015; 8 (1):7–15. doi: 10.1007/s40617-015-0057-0. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

On Purpose: Collectively Defining Our Team’s Mission Statement

How the Firefox User Research team crafted our mission statement

Firefox illustration by UX designer Gabrielle Lussier

Like many people who work at Mozilla, I’m inspired by the organization’s mission : to ensure the Internet is a global public resource, open and accessible to all . In thinking about the team I belong to, though, what’s our piece of this bigger puzzle?

The Firefox User Research team tackled this question early last year. We gathered in person for a week of team-focused activities; defining a team mission statement was on the agenda. As someone who enjoys workshop creation and strategic planning, I was on point to develop the workshop. The end goal? A team-backed statement that communicated our unique purpose and value.

Mission statement development was new territory for me. I read up on approaches for creating them and landed on a workshop design (adapted from MITRE’s Innovation Toolkit ) that would enable the team to participate in a process of collectively reflecting on our work and defining our shared purpose.

To my delight, the workshop was fruitful and engaging. Not only did it lead us to a statement that resonates, but it also sparked meaningful discussion along the way.

Here, I outline the five workshop activities that guided us there.

1) Discuss the value of a good mission statement

We kicked off the workshop by discussing the value of a well-crafted statement. Why were we aiming to define one in the first place? Benefits include: fostering alignment between the team’s activities and objectives, communicating the team’s purpose, and helping the team to cohere around a shared direction. In contrast to a vision statement, which describes future conditions in aspirational language, a mission statement describes present conditions in concrete terms.

In our case, the team had recently grown in size to thirteen people. We had a fairly new leadership team, along with a few new members of the team. With a mix of longer tenure and newer members, and quantitative and mixed methods researchers (which at one point in the past had been on separate teams), we wanted to inspire team alignment around our shared goals and build bridges between team members.

2) Individually answer a set of questions about our team’s work

Large sheets of paper were set up around the room with the following questions:

A. What do we, as a user research team, do?

B. How do we do what we do?

C. What value do we bring?

D. Who benefits from our work?

E. Why does our team exist?

Markers in hand, team members dispersed around the room, spending a few minutes writing answers to each question until we had cycled through them all.

Team members during the workshop

3) Highlight keywords and work in groups to create draft statements

Small groups were formed and were tasked with highlighting keywords from the answers provided in the previous step. These keywords served as the foundation for drafting statements, with the following format provided as a helpful guide:

Our mission is to (A — what we do ) by (B — how we do it ).

We (C — the value we bring ) so that (D — who benefits from our work ) can (E — why we exist ).

One group’s draft statement from Step 3

4) Review and discuss resulting statements

Draft statements emerged remarkably fluidly from the activities in Steps 2 and 3. Common elements were easy to identify (we develop insights and shape product decisions), while the differences sparked worthwhile discussions. For example: How well does the term ‘human-centered’ capture the work of our quantitative researchers? Is creating empathy for our users a core part of our purpose? How does our value extend beyond impacting product decisions?

As a group, we reviewed and discussed the statements, crossing out any jargony terms and underlining favoured actions and words. After this step, we knew we were close to a final statement. We concluded the workshop, with a plan to revisit the statements when we were back to work the following week.

5) Refine and share for feedback

The following week, we refined our work and shared the outcome with the lead of our Content Design practice for review. Her sharp feedback included encouraging us to change the phrase ‘ informing strategic decisions’ to ‘ influencing strategic decisions’ to articulate our role as less passive — a change we were glad to make. After another round of editing, we arrived at our final mission statement:

Our mission is to influence strategic decisions through systematic, qualitative, and quantitative research. We develop insights that uncover opportunities for Mozilla to build an open and healthy internet for all.

Closing thoughts

If you’re considering involving your team in defining a team mission statement, it makes for a rewarding workshop activity. The five steps presented in this article give team members the opportunity to reflect on important foundational questions (what value do we bring?), while deepening mutual understanding.

Crafting a team mission statement was much less of an exercise in wordsmithing than I might have assumed. Instead, it was an exercise in aligning on the bigger questions of why we exist and who benefits from our work. I walked away with a better understanding of the value our team brings to Mozilla, a clearer way to articulate how our work ladders up to the organization’s mission, and a deeper appreciation for the individual perspectives of our team members.

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

Published on 16.4.2024 in Vol 26 (2024)

Adverse Event Signal Detection Using Patients’ Concerns in Pharmaceutical Care Records: Evaluation of Deep Learning Models

Authors of this article:

Original Paper

Satoshi Nishioka 1 , PhD ;
Satoshi Watabe 1 , BSc ;
Yuki Yanagisawa 1 , PhD ;
Kyoko Sayama 1 , MSc ;
Hayato Kizaki 1 , MSc ;
Shungo Imai 1 , PhD ;
Mitsuhiro Someya 2 , BSc ;
Ryoo Taniguchi 2 , PhD ;
Shuntaro Yada 3 , PhD ;
Eiji Aramaki 3 , PhD ;
Satoko Hori 1 , PhD

1 Division of Drug Informatics, Keio University Faculty of Pharmacy, Tokyo, Japan

2 Nakajima Pharmacy, Hokkaido, Japan

3 Nara Institute of Science and Technology, Nara, Japan

Corresponding Author:

Satoko Hori, PhD

Division of Drug Informatics

Keio University Faculty of Pharmacy

1-5-30 Shibakoen

Tokyo, 105-8512

Phone: 81 3 5400 2650

Email: [email protected]

Background: Early detection of adverse events and their management are crucial to improving anticancer treatment outcomes, and listening to patients’ subjective opinions (patients’ voices) can make a major contribution to improving safety management. Recent progress in deep learning technologies has enabled various new approaches for the evaluation of safety-related events based on patient-generated text data, but few studies have focused on the improvement of real-time safety monitoring for individual patients. In addition, no study has yet been performed to validate deep learning models for screening patients’ narratives for clinically important adverse event signals that require medical intervention. In our previous work, novel deep learning models have been developed to detect adverse event signals for hand-foot syndrome or adverse events limiting patients’ daily lives from the authored narratives of patients with cancer, aiming ultimately to use them as safety monitoring support tools for individual patients.

Objective: This study was designed to evaluate whether our deep learning models can screen clinically important adverse event signals that require intervention by health care professionals. The applicability of our deep learning models to data on patients’ concerns at pharmacies was also assessed.

Methods: Pharmaceutical care records at community pharmacies were used for the evaluation of our deep learning models. The records followed the SOAP format, consisting of subjective (S), objective (O), assessment (A), and plan (P) columns. Because of the unique combination of patients’ concerns in the S column and the professional records of the pharmacists, this was considered a suitable data for the present purpose. Our deep learning models were applied to the S records of patients with cancer, and the extracted adverse event signals were assessed in relation to medical actions and prescribed drugs.

Results: From 30,784 S records of 2479 patients with at least 1 prescription of anticancer drugs, our deep learning models extracted true adverse event signals with more than 80% accuracy for both hand-foot syndrome (n=152, 91%) and adverse events limiting patients’ daily lives (n=157, 80.1%). The deep learning models were also able to screen adverse event signals that require medical intervention by health care providers. The extracted adverse event signals could reflect the side effects of anticancer drugs used by the patients based on analysis of prescribed anticancer drugs. “Pain or numbness” (n=57, 36.3%), “fever” (n=46, 29.3%), and “nausea” (n=40, 25.5%) were common symptoms out of the true adverse event signals identified by the model for adverse events limiting patients’ daily lives.

Conclusions: Our deep learning models were able to screen clinically important adverse event signals that require intervention for symptoms. It was also confirmed that these deep learning models could be applied to patients’ subjective information recorded in pharmaceutical care records accumulated during pharmacists’ daily work.

Introduction

Increasing numbers of people are expected to develop cancers in our aging society [ 1 - 3 ]. Thus, there is increasing interest in how to detect and manage the side effects of anticancer therapies in order to improve treatment regimens and patients’ quality of life [ 4 - 8 ]. The primary approaches for side effect management are “early signal detection and early intervention” [ 9 - 11 ]. Thus, more efficient approaches for this purpose are needed.

It has been recognized that patients’ voices concerning adverse events represent an important source of information. Several studies have indicated that the number, severity, and time of occurrence of adverse events might be underevaluated by physicians [ 12 - 15 ]. Thus, patient-reported outcomes (PROs) have recently received more attention in the drug evaluation process, reflecting patients’ real voices. Various kinds of PRO measures have been developed and investigated in different disease populations [ 16 , 17 ]. Health care authorities have also encouraged the pharmaceutical industry to use PROs for drug evaluation [ 18 , 19 ], and it is becoming more common to take PRO assessment results into consideration for drug marketing approval [ 20 , 21 ]. Similar trends can be seen in the clinical management of individual patients. Thus, health care professionals have an interest in understanding how to appropriately gather patients’ concerns in order to improve safety management and clinical decisions [ 22 - 24 ].

The applications of deep learning for natural language processing have expanded dramatically in recent years [ 25 ]. Since the development of a high-performance deep learning model in 2018 [ 26 ], attempts to apply cutting-edge deep learning models to various kinds of patient-generated text data for the evaluation of safety events or the analysis of unscalable subjective information from patients have been accelerating [ 27 - 31 ]. Most studies have been conducted to use patients’ narrative data for pharmacovigilance [ 27 , 32 - 35 ], while few have been aimed at improvement of real-time safety monitoring for individual patients. In addition, there have been some studies on adverse event severity grading based on health care records [ 36 - 39 ], but none has yet aimed to extract clinically important adverse event signals that require medical intervention from patients’ narratives. It is important to know whether deep learning models could contribute to the detection of such important adverse event signals from concern texts generated by individual patients.

To address this question, we have developed deep learning models to detect adverse event signals from individual patients with cancer based on patients’ blog articles in online communities, following other types of natural language processing–related previous work [ 40 , 41 ]. One deep learning model focused on the specific symptom of hand-foot syndrome (HFS), which is one of the typical side effects of anticancer treatments [ 42 ], and another focused on a broad range of adverse events that impact patients’ activities of daily living [ 43 ]. We showed that our models can provide good performance scores in targeting adverse event signals. However, the evaluation relied on patients’ narratives from the patients’ blog data used for deep learning model training, so further evaluation is needed to ensure the validity and applicability of the models to other texts regarding patients’ concerns. In addition, the blog data source did not contain medical information, so it was not feasible to assess whether the models could contribute to the extraction of clinically important adverse event signals.

To address these challenges, we focused on pharmaceutical care records written by pharmacists at community pharmacies. The gold standard format for pharmaceutical care records in Japan is the SOAP (subjective, objective, assessment, plan)-based document that follows the “problem-oriented system” concept proposed by Weed [ 44 ] in 1968. Pharmacists track patients’ subjective concerns in the S column, provide objective information or observations in the O column, give their assessment from the pharmacist perspective in the A column, and suggest a plan for moving forward in the P column [ 45 , 46 ]. We considered that SOAP-based pharmaceutical care records could be a unique data source suitable for further evaluation of our deep learning models because they contain both patients’ concerns and professional health care records by pharmacists, including the medication prescription history with time stamps. Therefore, this study was designed to assess whether our deep learning models could extract clinically important adverse event signals that require intervention by medical professionals from these records. We also aimed to evaluate the characteristics of the models when applied to patients’ subjective information noted in the pharmaceutical care records, as there have been only a few studies on the application of deep learning models to patients’ concerns recorded during pharmacists’ daily work [ 47 - 49 ].

Here, we report the results of applying our deep learning models to patients’ concern text data in pharmaceutical care records, focusing on patients receiving anticancer treatment.

Data Source

The original data source was 2,276,494 pharmaceutical care records for 303,179 patients, created from April 2020 to December 2021 at community pharmacies belonging to the Nakajima Pharmacy Group in Japan [ 50 ]. To focus on patients with cancer, records of patients with at least 1 prescription for an anticancer drug were retrieved by sorting individual drug codes (YJ codes) used in Japan (YJ codes starting with 42 refer to anticancer drugs). Records in the S column (ie, S records) were collected from the patients with cancer as the text data of patients’ concerns for deep learning model analysis.

Deep Learning Models

The deep learning models used for this research were those that we constructed based on patients’ narratives in blog articles posted in an online community and that showed the best performance score in each task in our previous work (ie, a Bidirectional Encoder Representations From Transformers [BERT]–based model for HFS signal extraction [ 42 ] and a T5-based model for adverse event signal extraction [ 43 ]). BERT [ 26 ] and T5 [ 51 ] both belong to a type of deep learning model that has recently shown high performance in several studies [ 29 , 52 ]. Hereafter, we refer to the deep learning model for HFS signals as the HFS model, the model for any adverse event signals as All AE (ie, all or any adverse events) model, and the model for adverse event signals limited to patients’ activities of daily living as the AE-L (adverse events limiting patients’ daily lives) model. It was also confirmed that these deep learning models showed similar or higher performance scores for the HFS, All AE, or AE-L identification tasks using 1000 S records randomly extracted from the data source of this study compared to the values obtained in our previous work [ 42 , 43 ] (the performance scores of sentence-level tasks from our previous work are comparable, as the mean number of words in the sentences in the data source in our previous work was 32.7 [SD 33.9], which is close to that of the S records used in this study, 38.8 [SD 29.4]). The method and results of the performance-level check are described in detail in Multimedia Appendix 1 [ 42 , 43 ]. We applied the deep learning models to all text data in this study without any adjustment in setting parameters from those used in constructing them based on patient-authored texts in our previous work [ 42 , 43 ].

Evaluation of Extracted S Records by the Deep Learning Models

In this study, we focused on the evaluation of S records that our deep learning models extracted as HFS or AE-L positive. Each positive S record was assessed as if it was a true adverse event signal, a sort of adverse event symptom, whether or not an intervention was made by health care professionals. We also investigated the kind of anticancer treatment prescription in connection with each adverse event signal identified in S records.

To assess whether an extracted positive S record was a true adverse event signal, we used the same annotation guidelines as in our previous work [ 43 ]. In brief, each S record was treated as an “adverse event signal” if any untoward medical occurrence happened to the patient, regardless of the cause. For the AE-L model only, if a positive S record was confirmed as an adverse event signal, it was further categorized into 1 or more of the following adverse event symptoms: “fatigue,” “nausea,” “vomiting,” “diarrhea,” “constipation,” “appetite loss,” “pain or numbness,” “rash or itchy,” “hair loss,” “menstrual irregularity,” “fever,” “taste disorder,” “dizziness,” “sleep disorder,” “edema,” or “others.”

For the assessment of interventions by health care professionals and anticancer treatment prescriptions, information from the O, A, and P columns and drug prescription history in the data source were investigated for the extracted positive S records. The interventions by health care professionals were categorized in any of the following: “adding symptomatic treatment for the adverse event signal,” “dose reduction or discontinuation of causative anticancer treatment,” “consultation with physician,” “others,” or “no intervention (ie, just following up the adverse event signal).” The actions categorized in “others” were further evaluated individually. For this assessment, we also randomly extracted 200 S records and evaluated them in the same way for comparison with the results from the deep learning model. Prescription history of anticancer treatment was analyzed by primary category of mechanism of action (MoA) with subcategories if applicable (eg, target molecule for kinase inhibitors).

Applicability Check to Other Text Data Including Patients’ Concerns

To check the applicability of our deep learning models to data from a different source, interview transcripts from patients with cancer were also evaluated. The interview transcripts were created by the Database of Individual Patient Experiences-Japan (DIPEx-Japan) [ 53 ]. DIPEx-Japan divides the interview transcripts into sections for each topic, such as “onset of disease” and “treatment,” and posts the processed texts on its website. Processing is conducted by accredited researchers based on qualitative research methods established by the University of Oxford [ 54 ]. In this study, interview text data created from interviews with 52 patients with breast cancer conducted from January 2008 to October 2018 were used to assess whether our deep learning models can extract adverse event signals from this source. In total, 508 interview transcripts were included with the approval of DIPEx-Japan.

Ethical Considerations

This study was conducted with anonymized data following approval by the ethics committee of the Keio University Faculty of Pharmacy (210914-1 and 230217-1) and in accordance with relevant guidelines and regulations and the Declaration of Helsinki. Informed consent specific to this study was waived due to the retrospective observational design of the study with the approval of the ethics committee of the Keio University Faculty of Pharmacy. To respect the will of each individual stakeholder, however, we provided patients and pharmacists of the pharmacy group with an opportunity to refuse the sharing of their pharmaceutical care records by posting an overview of this study at each pharmacy store or on their web page regarding the analysis using pharmaceutical care records. Interview transcripts from DIPEx-Japan were provided through a data sharing arrangement for using narrative data for research and education. Consent for interview transcription and its sharing from DIPEx-Japan was obtained from the participants when the interviews were recorded.

From the original data source of 2,180,902 pharmaceutical care records for 291,150 patients, S records written by pharmacists for patients with a history of at least 1 prescription of an anticancer drug were extracted. This yielded 30,784 S records for 2479 patients with cancer ( Table 1 ). The mean and median number of words in the S records were 38.8 (SD 29.4) and 32 (IQR 20-50), respectively. We applied our deep learning models, HFS, All AE, and AE-L, to these 30,784 S records for the evaluation of the deep learning models for adverse event signal detection.

For interview transcripts created by DIPEx-Japan, the mean and median number of words were 428.9 (SD 160.9) and 416 (IQR 308-526), respectively, in the 508 transcripts for 52 patients with breast cancer.

a SOAP: subjective, objective, assessment, plan.

b S: subjective.

Application of the HFS Model

First, we applied the HFS model to the S records for patients with cancer. The BERT-based model was used for this research as it showed the best performance score in our previous work [ 42 ].

S Records Extracted as HFS Positive

The S records extracted as HFS positive by the HFS model ( Table 2 ) amounted to 167 (0.5%) records for 119 (4.8%) patients. A majority of the patients had 1 HFS-positive record in their S records (n=91, 76.5%), while 2 patients had as many as 6 (1.7%) HFS-positive records. When we examined whether the extracted S records were true adverse event signals or not, 152 records were confirmed to be adverse event signals, while the other 15 records were false-positives. All the false-positive S records were descriptions about the absence of symptoms or confirmation of improving condition (eg, “no diarrhea, mouth ulcers, or limb pain so far” or “the skin on the soles of my feet has calmed down a lot with this ointment”). Some examples of S records that were predicted as HFS positive by the model are shown in Table S1 in Multimedia Appendix 2 .

The same examination was conducted with interview transcripts from DIPEx-Japan. Only 1 (0.2%) transcript was extracted as HFS positive by the HFS model, and it was a true adverse event signal (100%). The actual transcript extracted as HFS positive is shown in Table S2 in Multimedia Appendix 2 .

a S: subjective.

b HFS: hand-foot syndrome.

c All false-positive S records were denial of symptoms or confirmation of improving condition.

Interventions by Health Care Professionals

The 167 S records extracted as HFS positive as well as 200 randomly selected records were checked for interventions by health care professionals ( Figure 1 ). The proportion showing any action by health care professionals was 64.1% for 167 HFS-positive S records compared to 13% for the 200 random S records. Among the actions taken for HFS positives, “adding symptomatic treatment” was the most common, accounting for around half (n=79, 47.3%), followed by “other” (n=18, 10.8%). Most “other” actions were educational guidance from pharmacists, such as instructions on moisturizing, nail care, or application of ointment and advice on daily living (eg, “avoid tight socks”).

Anticancer Drugs Prescribed

The types of anticancer drugs prescribed for HFS-positive patients are summarized based on the prescription histories in Table 3 . For the 152 adverse event signals identified by the HFS model in the previous section, the most common MoA class of anticancer drugs used for the patients was antimetabolite (n=62, 40.8%), specifically fluoropyrimidines (n=59, 38.8%). Kinase inhibitors were next (n=49, 32.2%), with epidermal growth factor receptor (EGFR) inhibitors and multikinase inhibitors as major subgroups (n=28, 18.4% and n=14, 9.2%, respectively). The third and fourth most common MoAs were aromatase inhibitors (n=24, 15.8%) and antiandrogen or estrogen drugs (n=7, 4.6% each) for hormone therapy.

a EGFR: epidermal growth factor receptor.

b VEGF: vascular endothelial growth factor.

c HER2: human epidermal growth factor receptor-2.

d CDK4/6: cyclin-dependent kinase 4/6.

Application of the All AE or AE-L model

The All AE and AE-L models were also applied to the same S records for patients with cancer. The T5-based model was used for this research as it gave the best performance score in our previous work [ 43 ].

S Records Extracted as All AE or AE-L positive

The numbers of S records extracted as positive were 7604 (24.7%) for 1797 patients and 196 (0.6%) for 142 patients for All AE and AE-L, respectively. In the case of All AE, patients tended to have multiple adverse event positives in their S records (n=1315, 73.2% of patients had at least 2 positives). In the case of AE-L, most patients had only 1 AE-L positive (n=104, 73.2%), and the largest number of AE-L positives for 1 patient was 4 (2.8%; Table 4 ).

We focused on AE-L evaluation due to its greater importance from a medical viewpoint and lower workload for manual assessment, considering the number of positive S records. Of the 197 AE-L–positive S records, it was confirmed that 157 (80.1%) records accurately extracted adverse event signals, while 39 (19.9%) records were false-positives that did not include any adverse event signals ( Table 4 ). The contents of the 39 false-positives were all descriptions about the absence of symptoms or confirmation of improving condition, showing a similar tendency to the HFS false-positives (eg, “The diarrhea has calmed down so far. Symptoms in hands and feet are currently fine” and “No symptoms for the following: upset in stomach, diarrhea, nausea, abdominal pain, abdominal pain or stomach cramps, constipation”). Examples of S records that were predicted as AE-L positive are shown in Table S3 in Multimedia Appendix 2 .

The deep learning models were also applied to interview transcripts from DIPEx-Japan in the same manner. The deep learning models identified 84 (16.5%) and 18 (3.5%) transcripts as All AE or AE-L positive, respectively. Of the 84 All AE–positive transcripts, 73 (86.9%) were true adverse event signals. The false-positives of All AE (n=11, 13.1%) were categorized into any of the following 3 types: explanations about the disease or its prognosis, stories when their cancer was discovered, or emotional changes that did not include clear adverse event mentions. With regard to AE-L, all the 18 (100%) positives were true adverse event signals (Table S4 in Multimedia Appendix 2 ). Examples of actual transcripts extracted as All AE or AE-L positive are shown in Table S5 in Multimedia Appendix 2 .

b All AE: all (or any of) adverse event.

c AE-L: adverse events limiting patients’ daily lives.

d All false-positive S records were denial of symptoms or confirmation of improving condition.

Whether or not interventions were made by health care professionals was investigated for the 196 AE-L–positive S records. As in the HFS model evaluation, data from 200 randomly selected S records were used for comparison ( Figure 2 ). In total, 91 (46.4%) records in the 196 AE-L–positive records were accompanied by an intervention, while the corresponding figure in the 200 random records was 26 (13%) records. The most common action in response to adverse event signals identified by the AE-L model was “adding symptomatic treatment” (n=71, 36.2%), followed by “other” (n=11, 5.6%). “Other” included educational guidance from pharmacists, inquiries from pharmacists to physicians, or recommendations for patients to visit a doctor.

The types of anticancer drugs prescribed for patients with adverse event signals identified by the AE-L model were summarized based on the prescription histories ( Table 5 ). In connection with the 157 adverse event signals, the most common MoA of the prescribed anticancer drug was antimetabolite (n=62, 39.5%) and fluoropyrimidine (n=53, 33.8%), which accounted for the majority. Kinase inhibitor (n=31, 19.7%) was the next largest category with multikinase inhibitor (n=14, 8.9%) as the major subgroup. These were followed by antiandrogen (n=27, 17.2%), antiestrogen (n=10, 6.4%), and aromatase inhibitor (n=10, 6.4%) for hormone therapy.

b JAK: janus kinase.

c VEGF: vascular endothelial growth factor.

d BTK: bruton tyrosine kinase.

e FLT3: FMS-like tyrosine kinase-3.

f PARP: poly-ADP ribose polymerase.

g CDK4/6: cyclin-dependent kinase 4/6.

h CD20: cluster of differentiation 20.

Adverse Event Symptoms

For the 157 adverse event signals identified by the AE-L model, the symptoms were categorized according to the predefined guideline in our previous work [ 43 ]. “Pain or numbness” (n=57, 36.3%) accounted for the largest proportion followed by “fever” (n=46, 29.3%) and “nausea” (n=40, 25.5%; Table 6 ). Symptoms classified as “others” included chills, tinnitus, running tears, dry or peeling skin, and frequent urination. When comparing the proportion of the symptoms associated with or without interventions by health care professionals, a trend toward a greater proportion of interventions was observed in “fever,” “nausea,” “diarrhea,” “constipation,” “vomiting,” and “edema” ( Figure 3 , black boxes). On the other hand, a smaller proportion was observed in “pain or numbness,” “fatigue,” “appetite loss,” “rash or itchy,” “taste disorder,” and “dizziness” ( Figure 3 , gray boxes).

This study was designed to evaluate our deep learning models, previously constructed based on patient-authored texts posted in an online community, by applying them to pharmaceutical care records that contain both patients’ subjective concerns and medical information created by pharmacists. Based on the results, we discuss whether these deep learning models can extract clinically important adverse event signals that require medical intervention, and what characteristics they show when applied to data on patients’ concerns in pharmaceutical care records.

Performance for Adverse Event Signal Extraction

The first requirement for the deep learning models is to extract adverse event signals from patients’ narratives precisely. In this study, we evaluated the proportion of true adverse event signals in positive S records extracted by the HFS or AE-L model. True adverse event signals amounted to 152 (91%) and 157 (80.1%) for the HFS and AE-L models, respectively ( Tables 2 and 4 ). Given that the proportion of true adverse event signals in 200 randomly extracted S records without deep learning models was 54 (27%; categories other than “no adverse event” in Figures 1 and 2 ), the HFS and AE-L models were able to concentrate S records with adverse event mentions. Although 15 (9%) for the HFS model and 39 (19.9%) for the AE-L model were false-positives, it was confirmed all of the false-positive records described a lack of symptoms or confirmation of improving condition. We considered that such false-positives are due to the unique feature of pharmaceutical care records, where pharmacists might proactively interview patients about potential side effects of their medications. As the data set of blog articles we used to construct the deep learning models included few such cases (especially comments on lack of symptoms), our models seemed unable to exclude them correctly. Even though we confirmed that the proportion of true “adverse event” signals extracted from the S records by the HFS or AE-L model was more than 80%, the performance scores to extract true “HFS” or “AE-L” signals were not so high based on the performance check using 1000 randomly extracted S records ( F 1 -scores were 0.50 and 0.22 for true HFS and AE-L signals, respectively; Table S1 in Multimedia Appendix 1 ). It is considered that the performance to extract true HFS and AE-L signals was relatively low due to the short length of texts in the S records, providing less context to judge the impact on patients’ daily lives, especially for the AE-L model (the mean word number of the S records was 38.8 [SD 29.4; Table 1 ], similar to the sentence-level tasks in our previous work [ 42 , 43 ]). However, we consider a true adverse event signal proportion of more than 80% in this study represents a promising outcome, as this is the first attempt to apply our deep learning models to a different source of patients’ concern data, and the extracted positive cases would be worthy of evaluation by a medical professional, as the potential adverse events could be caused by drugs taken by the patients.

When the deep learning models were applied to DIPEx-Japan interview transcripts, including patients’ concerns, the proportion of true adverse event signals was also more than 80% (for All AE: n=73, 86.9% and for HFS and AE-L: n=18, 100%). The difference in the results between pharmaceutical care S records and DIPEx-Japan interview transcripts was the features of false-positives, descriptions about lack of symptoms or confirmation of improving condition in S records versus explanations about disease or its prognosis, stories about when their cancer was discovered, or emotional changes in interview transcripts. This is considered due to the difference in the nature of the data source; the pharmaceutical care records were generated in a real-time manner by pharmacists through their daily work, where adverse event signals are proactively monitored, while the interview transcripts were purely based on patients’ retrospective memories. Our deep learning models were able to extract true adverse event signals with an accuracy of more than 80% from both text data sources in spite of the difference in their nature. When looking at future implementation of the deep learning models in society (discussed in the Potential for Deep Learning Model Implementation in Society section), it may be desirable to further adjust deep learning models to reduce false-positives depending upon the features of the data source.

Identification of Important Adverse Events Requiring Medical Intervention

To assess whether the models could extract clinically important adverse event signals, we investigated interventions by health care professionals connected with the adverse event signals that are identified by our deep learning models. In the 200 randomly extracted S records, only 26 (13%) consisted of adverse event signals, leading to any intervention by health care professionals. On the other hand, the proportion of signals associated with interventions was increased to 107 (64.1%) and 91 (46.4%) in the S records extracted as positive by the HFS and AE-L models, respectively ( Figures 1 and 2 ). These results suggest that both deep learning models can screen clinically important adverse event signals that require intervention from health care professionals. The performance level in screening adverse event signals requiring medical intervention was higher in the HFS model than in the AE-L model (n=107, 64.1% vs n=91, 46.4%; Figures 1 and 2 ). Since the target events were specific and adverse event signals of HFS were narrowly defined, which is one of the typical side effects of some anticancer drugs, we consider that health care providers paid special attention to HFS-related signals and took action proactively. In both deep learning models, similar trends were observed in actions taken by health care professionals in response to extracted adverse event signals; common actions were attempts to manage adverse event symptoms by symptomatic treatment or other mild interventions, including educational guidance from pharmacists or recommendations for patients to visit a doctor. More direct interventions focused on the causative drugs (ie, “dose reduction or discontinuation of anticancer treatment”) amounted to less than 5%; 7 (4.2%) for the HFS model and 6 (3.1%) for the AE-L model ( Figures 1 and 2 ). Thus, it appears that our deep learning models can contribute to screening mild to moderate adverse event signals that require preventive actions such as symptomatic treatments or professional advice from health care providers, especially for patients with less sensitivity to adverse event signals or who have few opportunities to visit clinics and pharmacies.

Ability to Catch Real Side Effect Signals of Anticancer Drugs

Based on the drug prescription history associated with S records extracted as HFS or AE-L positive, the type and duration of anticancer drugs taken by patients experiencing the adverse event signals were investigated. For the HFS model, the most common MoA of anticancer drug was antimetabolite (fluoropyrimidine: n=59, 38.8%), followed by kinase inhibitors (n=49, 32.2%, of which EGFR inhibitors and multikinase inhibitors accounted for n=28, 18.4% and n=14, 9.2%, respectively) and aromatase inhibitors (n=24, 15.8%; Table 3 ). It is known that fluoropyrimidine and multikinase inhibitors are typical HFS-inducing drugs [ 55 - 58 ], suggesting that the HFS model accurately extracted HFS side effect signals derived from these drugs. Note that symptoms such as acneiform rash, xerosis, eczema, paronychia, changes in the nails, arthralgia, or stiffness of limb joints, which are common side effects of EGFR inhibitors or aromatase inhibitors [ 59 , 60 ], might be extracted as closely related expressions to those of HFS signals. When looking at the MoA of anticancer drugs for patients with adverse event signals identified by the AE-L model, antimetabolite (fluoropyrimidine) was the most common one (n=53, 33.8%), as in the case of those identified by the HFS model, followed by kinase inhibitors (n=31, 19.7%) and antiandrogens (n=27, 17.2%; Table 5 ). Since the AE-L model targets a broad range of adverse event symptoms, it is difficult to rationalize the relationship between the adverse event signals and types of anticancer drugs. However, the type of anticancer drugs would presumably closely correspond to the standard treatments of the cancer types of the patients. Based on the prescribed anticancer drugs, we can infer that a large percentage of the patients had breast or lung cancer, indicating that our study results were based on data from such a population. Thus, a possible direction for the expansion of this research would be adjusting the deep learning models by additional training with expressions for typical side effects associated with standard treatments of other cancer types. To interpret these results correctly, it should be noted that we could not investigate anticancer treatments conducted outside of the pharmacies (eg, the time-course relationship with intravenously administered drugs would be missed, as the administration will be done at hospitals). To further evaluate how useful this model is in side effect signal monitoring for patients with cancer, comprehensive medical information for the eligible patients would be required.

Suitability of the Deep Learning Models for Specific Adverse Event Symptoms

Among the adverse event signals identified by the AE-L model, the type of symptom was categorized according to a predefined annotation guideline that we previously developed [ 43 ]. The most frequently recorded adverse event signals identified by the AE-L model were “pain or numbness” (n=57, 36.3%), “fever” (n=46, 29.3%), and “nausea” (n=40, 25.5%; Table 6 ). Since the pharmaceutical care records had information about interventions by health care professionals, the frequency of the presence or absence of the interventions for each symptom was examined. A trend toward a greater proportion of interventions was observed in “fever,” “nausea,” “diarrhea,” “constipation,” “vomiting,” and “edema” ( Figure 3 , black boxes). There seem to be 2 possible explanations for this: these symptoms are of high importance and require early medical intervention or effective symptomatic treatments are available for these symptoms in clinical practice so that medical intervention is an easy option. On the other hand, a trend for a smaller proportion of adverse event signals to result in interventions was observed for “pain or numbness,” “fatigue,” “appetite loss,” “rash or itchy,” “taste disorder,” and “dizziness” ( Figure 3 , gray boxes). The reason for this may be the lack of effective symptomatic treatments or the difficulty of judging whether the severity of these symptoms justifies medical intervention by health care providers. In either case, there may be room for improvement in the quality of medical care for these symptoms. We expect that our research will contribute to a quality improvement in safety monitoring in clinical practice by supporting adverse event signal detection in a cost-effective manner.

Potential for Deep Learning Model Implementation in Society

Although we evaluated our deep learning models using pharmaceutical care records in this study, the main target of future implementation of our deep learning models in society would be narrative texts that patients directly write to record their daily experiences. For example, the application of these deep learning models to electronic media where patients record their daily experiences in their lives with disease (eg, health care–related e-communities and disease diary applications) could enable information about adverse event signal onset that patients experience to be provided to health care providers in a timely manner. Adverse event signals can automatically be identified and shared with health care providers based on the concern texts that patients post to any platform. This system will have the advantage that health care providers can efficiently grasp safety-related events that patients experience outside of clinic visits so that they can conduct more focused or personalized interactions with patients at their clinic visits. However, consideration should be given to avoid an excessive burden on health care providers. For instance, limiting the sharing of adverse event signals to those of high severity or summarizing adverse event signals over a week rather than sharing each one in a real-time manner may be reasonable approaches for medical staff. We also need to think about how to encourage patients to record their daily experiences using electronic tools. Not only technical progress and support but also the establishment of an ecosystem where both patients and medical staff can feel benefit will be required. Prospective studies with deep learning models to follow up patients in the long term and evaluate outcomes will be needed. We primarily looked at patient-authored texts as targets of implementation, but our deep learning models may also be worth using medical data including patients’ subjective concerns, such as pharmaceutical care S records. As this study confirmed that our deep learning models are applicable to patients’ concern texts tracked by pharmacists, it should be possible to use them to analyze other “patient voice-like” medical text data that have not been actively investigated so far.

Limitations

First, the major limitation of this study was that we were not able to collect complete medical information of the patients. Although we designed this study to analyze patients’ concerns extracted by the deep learning models and their relationship with medical information contained in the pharmaceutical care records, some information could not be tracked (eg, missing history of medical interventions or anticancer treatment at hospitals as well as diagnosis of patients’ primary cancers). Second, there might be a data creation bias in S records for patients’ concerns by pharmacists. For example, symptoms that have little impact on intervention decisions might less likely be recorded by them. It should be also noted that the characteristics of S records may not be consistent at different community pharmacies.

Conclusions

Our deep learning models were able to screen clinically important adverse event signals that require intervention by health care professionals from patients’ concerns in pharmaceutical care records. Thus, these models have the potential to support real-time adverse event monitoring of individual patients taking anticancer treatments in an efficient manner. We also confirmed that these deep learning models constructed based on patient-authored texts could be applied to patients’ subjective information recorded by pharmacists through their daily work. Further research may help to expand the applicability of the deep learning models for implementation in society or for analysis of data on patients’ concerns accumulated in professional records at pharmacies or hospitals.

Acknowledgments

This work was supported by Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research (KAKENHI; grant 21H03170) and Japan Science and Technology Agency, Core Research for Evolutional Science and Technology (CREST; grant JPMJCR22N1), Japan. Mr Yuki Yokokawa and Ms Sakura Yokoyama at our laboratory advised SN about the structure of pharmaceutical care records. This study would not have been feasible without the high quality of pharmaceutical care records created by many individual pharmacists at Nakajima Pharmacy Group through their daily work.

Data Availability

The data sets generated and analyzed during this study are available from the corresponding author on reasonable request.

Authors' Contributions

SN and SH designed the study. SN retrieved the subjective records of patients with cancer from the data source for the application of deep learning models and organized other data for subsequent evaluations. SN ran the deep learning models with the support of SW. SN, YY, and KS checked the adverse event signals for each subjective record that was extracted as positive by the models for hand-foot syndrome or adverse events limiting patients’ daily lives and evaluated the adverse event signal symptoms, details of interventions taken by health care professionals, and types of anticancer drugs prescribed for patients based on available data from the data source. HK and SI advised on the study concept and process. MS and RT provided pharmaceutical records at their community pharmacies along with advice on how to use and interpret them. SY and EA supervised the natural language processing research as specialists. SH supervised the study overall. SN drafted and finalized the paper. All authors reviewed and approved the paper.

Conflicts of Interest

SN is an employee of Daiichi Sankyo Co, Ltd. All other authors declare no conflicts of interest.

Performance evaluation of deep learning models.

Examples of S records and sample interview transcripts.

Global cancer observatory: cancer over time. World Health Organization. URL: https://gco.iarc.fr/overtime/en [accessed 2023-07-02]
Mattiuzzi C, Lippi G. Current cancer epidemiology. J Epidemiol Glob Health. 2019;9(4):217-222. [ FREE Full text ] [ CrossRef ] [ Medline ]
Montazeri F, Komaki H, Mohebi F, Mohajer B, Mansournia MA, Shahraz S, et al. Editorial: disparities in cancer prevention and epidemiology. Front Oncol. 2022;12:872051. [ FREE Full text ] [ CrossRef ] [ Medline ]
Lasala R, Santoleri F. Association between adherence to oral therapies in cancer patients and clinical outcome: a systematic review of the literature. Br J Clin Pharmacol. 2022;88(5):1999-2018. [ FREE Full text ] [ CrossRef ] [ Medline ]
Pudkasam S, Polman R, Pitcher M, Fisher M, Chinlumprasert N, Stojanovska L, et al. Physical activity and breast cancer survivors: importance of adherence, motivational interviewing and psychological health. Maturitas. 2018;116:66-72. [ FREE Full text ] [ CrossRef ] [ Medline ]
Markman M. Chemotherapy-associated neurotoxicity: an important side effect-impacting on quality, rather than quantity, of life. J Cancer Res Clin Oncol. 1996;122(9):511-512. [ CrossRef ] [ Medline ]
Jitender S, Mahajan R, Rathore V, Choudhary R. Quality of life of cancer patients. J Exp Ther Oncol. 2018;12(3):217-221. [ Medline ]
Di Nardo P, Lisanti C, Garutti M, Buriolla S, Alberti M, Mazzeo R, et al. Chemotherapy in patients with early breast cancer: clinical overview and management of long-term side effects. Expert Opin Drug Saf. 2022;21(11):1341-1355. [ FREE Full text ] [ CrossRef ] [ Medline ]
Cuomo RE. Improving cancer patient outcomes and cost-effectiveness: a Markov simulation of improved early detection, side effect management, and palliative care. Cancer Invest. 2023;41(10):858-862. [ CrossRef ] [ Medline ]
Pulito C, Cristaudo A, La Porta C, Zapperi S, Blandino G, Morrone A, et al. Oral mucositis: the hidden side of cancer therapy. J Exp Clin Cancer Res. 2020;39(1):210. [ FREE Full text ] [ CrossRef ] [ Medline ]
Bartal A, Mátrai Z, Szûcs A, Liszkay G. Main treatment and preventive measures for hand-foot syndrome, a dermatologic side effect of cancer therapy. Magy Onkol. 2011;55(2):91-98. [ FREE Full text ] [ Medline ]
Basch E, Jia X, Heller G, Barz A, Sit L, Fruscione M, et al. Adverse symptom event reporting by patients vs clinicians: relationships with clinical outcomes. J Natl Cancer Inst. 2009;101(23):1624-1632. [ FREE Full text ] [ CrossRef ] [ Medline ]
Basch E. The missing voice of patients in drug-safety reporting. N Engl J Med. 2010;362(10):865-869. [ FREE Full text ] [ CrossRef ] [ Medline ]
Fromme EK, Eilers KM, Mori M, Hsieh YC, Beer TM. How accurate is clinician reporting of chemotherapy adverse effects? A comparison with patient-reported symptoms from the Quality-of-Life Questionnaire C30. J Clin Oncol. 2004;22(17):3485-3490. [ FREE Full text ] [ CrossRef ] [ Medline ]
Liu L, Suo T, Shen Y, Geng C, Song Z, Liu F, et al. Clinicians versus patients subjective adverse events assessment: based on patient-reported outcomes version of the common terminology criteria for adverse events (PRO-CTCAE). Qual Life Res. 2020;29(11):3009-3015. [ CrossRef ] [ Medline ]
Churruca K, Pomare C, Ellis LA, Long JC, Henderson SB, Murphy LED, et al. Patient-reported outcome measures (PROMs): a review of generic and condition-specific measures and a discussion of trends and issues. Health Expect. 2021;24(4):1015-1024. [ FREE Full text ] [ CrossRef ] [ Medline ]
Pérez-Alfonso KE, Sánchez-Martínez V. Electronic patient-reported outcome measures evaluating cancer symptoms: a systematic review. Semin Oncol Nurs. 2021;37(2):151145. [ FREE Full text ] [ CrossRef ] [ Medline ]
Patient-reported outcome measures: use in medical product development to support labeling claims. U.S. Food & Drug Administration. 2009. URL: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/patient-reported-outcome-measures-use-medical-product-development-support-labeling-claims [accessed 2023-11-26]
Appendix 2 to the guideline on the evaluation of anticancer medicinal products in man—the use of patient-reported outcome (PRO) measures in oncology studies—scientific guideline. European Medicines Agency. 2016. URL: https://www.ema.europa.eu/en/appendix-2-guideline-evaluation-anticancer-medicinal-products-man-use-patient-reported-outcome-pro [accessed 2023-11-26]
Weber SC. The evolution and use of patient-reported outcomes in regulatory decision making. RF Q. 2023;3(1):4-9. [ FREE Full text ]
Teixeira MM, Borges FC, Ferreira PS, Rocha J, Sepodes B, Torre C. A review of patient-reported outcomes used for regulatory approval of oncology medicinal products in the European Union between 2017 and 2020. Front Med (Lausanne). 2022;9:968272. [ FREE Full text ] [ CrossRef ] [ Medline ]
Newell S, Jordan Z. The patient experience of patient-centered communication with nurses in the hospital setting: a qualitative systematic review protocol. JBI Database System Rev Implement Rep. 2015;13(1):76-87. [ FREE Full text ] [ CrossRef ] [ Medline ]
Yagasaki K, Takahashi H, Ouchi T, Yamagami J, Hamamoto Y, Amagai M, et al. Patient voice on management of facial dermatological adverse events with targeted therapies: a qualitative study. J Patient Rep Outcomes. 2019;3(1):27. [ FREE Full text ] [ CrossRef ] [ Medline ]
Giardina TD, Korukonda S, Shahid U, Vaghani V, Upadhyay DK, Burke GF, et al. Use of patient complaints to identify diagnosis-related safety concerns: a mixed-method evaluation. BMJ Qual Saf. 2021;30(12):996-1001. [ FREE Full text ] [ CrossRef ] [ Medline ]
Lauriola I, Lavelli A, Aiolli F. An introduction to deep learning in natural language processing: models, techniques, and tools. Neurocomputing. 2022;470:443-456. [ CrossRef ]
Devlin J, Chang MW, Lee K, Toutanova K. BERT: pre-training of deep bidirectional transformers for language understanding. 2019. Presented at: 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies; June 2-7, 2019;4171-4186; Minneapolis, MN, USA.
Dreisbach C, Koleck TA, Bourne PE, Bakken S. A systematic review of natural language processing and text mining of symptoms from electronic patient-authored text data. Int J Med Inform. 2019;125:37-46. [ FREE Full text ] [ CrossRef ] [ Medline ]
Sim JA, Huang X, Horan MR, Stewart CM, Robison LL, Hudson MM, et al. Natural language processing with machine learning methods to analyze unstructured patient-reported outcomes derived from electronic health records: a systematic review. Artif Intell Med. 2023;146:102701. [ CrossRef ] [ Medline ]
Weissenbacher D, Banda JM, Davydova V, Estrada-Zavala D, Gascó Sánchez L, Ge Y, et al. Overview of the seventh social media mining for health applications (#SMM4H) shared tasks at COLING 2022. 2022. Presented at: Proceedings of the Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task; October 12-17, 2022;221-241; Gyeongju, Republic of Korea. URL: https://aclanthology.org/2022.smm4h-1.54/
Matsuda S, Ohtomo T, Okuyama M, Miyake H, Aoki K. Estimating patient satisfaction through a language processing model: model development and evaluation. JMIR Form Res. 2023;7(1):e48534. [ FREE Full text ] [ CrossRef ] [ Medline ]
Yu D, Vydiswaran VGV. An assessment of mentions of adverse drug events on social media with natural language processing: model development and analysis. JMIR Med Inform. 2022;10(9):e38140. [ FREE Full text ] [ CrossRef ] [ Medline ]
Liu X, Chen H. A research framework for pharmacovigilance in health social media: identification and evaluation of patient adverse drug event reports. J Biomed Inform. 2015;58:268-279. [ FREE Full text ] [ CrossRef ] [ Medline ]
Nikfarjam A, Sarker A, O'Connor K, Ginn R, Gonzalez G. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features. J Am Med Inform Assoc. 2015;22(3):671-681. [ FREE Full text ] [ CrossRef ] [ Medline ]
Kakalou C, Dimitsaki S, Dimitriadis VK, Natsiavas P. Exploiting social media for active pharmacovigilance: the PVClinical social media workspace. Stud Health Technol Inform. 2022;290:739-743. [ CrossRef ] [ Medline ]
Bousquet C, Dahamna B, Guillemin-Lanne S, Darmoni SJ, Faviez C, Huot C, et al. The adverse drug reactions from patient reports in social media project: five major challenges to overcome to operationalize analysis and efficiently support pharmacovigilance process. JMIR Res Protoc. 2017;6(9):e179. [ FREE Full text ] [ CrossRef ] [ Medline ]
Young IJB, Luz S, Lone N. A systematic review of natural language processing for classification tasks in the field of incident reporting and adverse event analysis. Int J Med Inform. 2019;132:103971. [ CrossRef ] [ Medline ]
Jacobsson R, Bergvall T, Sandberg L, Ellenius J. Extraction of adverse event severity information from clinical narratives using natural language processing. Pharmacoepidemiol Drug Saf. 2017;26(S2):37. [ FREE Full text ]
Liang C, Gong Y. Predicting harm scores from patient safety event reports. Stud Health Technol Inform. 2017;245:1075-1079. [ CrossRef ] [ Medline ]
Jiang G, Wang L, Liu H, Solbrig HR, Chute CG. Building a knowledge base of severe adverse drug events based on AERS reporting data using semantic web technologies. Stud Health Technol Inform. 2013;192(1-2):496-500. [ CrossRef ] [ Medline ]
Usui M, Aramaki E, Iwao T, Wakamiya S, Sakamoto T, Mochizuki M. Extraction and standardization of patient complaints from electronic medication histories for pharmacovigilance: natural language processing analysis in Japanese. JMIR Med Inform. 2018;6(3):e11021. [ FREE Full text ] [ CrossRef ] [ Medline ]
Watanabe T, Yada S, Aramaki E, Yajima H, Kizaki H, Hori S. Extracting multiple worries from breast cancer patient blogs using multilabel classification with the natural language processing model bidirectional encoder representations from transformers: infodemiology study of blogs. JMIR Cancer. 2022;8(2):e37840. [ FREE Full text ] [ CrossRef ] [ Medline ]
Nishioka S, Watanabe T, Asano M, Yamamoto T, Kawakami K, Yada S, et al. Identification of hand-foot syndrome from cancer patients' blog posts: BERT-based deep-learning approach to detect potential adverse drug reaction symptoms. PLoS One. 2022;17(5):e0267901. [ FREE Full text ] [ CrossRef ] [ Medline ]
Nishioka S, Asano M, Yada S, Aramaki E, Yajima H, Yanagisawa Y, et al. Adverse event signal extraction from cancer patients' narratives focusing on impact on their daily-life activities. Sci Rep. 2023;13(1):15516. [ FREE Full text ] [ CrossRef ] [ Medline ]
Weed LL. Medical records that guide and teach. N Engl J Med. 1968;278(11):593-600. [ CrossRef ] [ Medline ]
Podder V, Lew V, Ghassemzadeh S. SOAP Notes. Treasure Island, FL. StatPearls Publishing; 2023.
Shenavar Masooleh I, Ramezanzadeh E, Yaseri M, Sahere Mortazavi Khatibani S, Sadat Fayazi H, Ali Balou H, et al. The effectiveness of training on daily progress note writing by medical interns. J Adv Med Educ Prof. 2021;9(3):168-175. [ FREE Full text ] [ CrossRef ] [ Medline ]
Grothen AE, Tennant B, Wang C, Torres A, Sheppard BB, Abastillas G, et al. Application of artificial intelligence methods to pharmacy data for cancer surveillance and epidemiology research: a systematic review. JCO Clin Cancer Inform. 2020;4:1051-1058. [ FREE Full text ] [ CrossRef ] [ Medline ]
Ohno Y, Kato R, Ishikawa H, Nishiyama T, Isawa M, Mochizuki M, et al. Using the natural language processing system MedNER-J to analyze pharmaceutical care records. medRxiv. Preprint posted online on October 2, 2023. [ CrossRef ]
Ranchon F, Chanoine S, Lambert-Lacroix S, Bosson JL, Moreau-Gaudry A, Bedouch P. Development of artificial intelligence powered apps and tools for clinical pharmacy services: a systematic review. Int J Med Inform. 2023;172:104983. [ CrossRef ] [ Medline ]
Nakajima Pharmacy. URL: https://www.nakajima-phar.co.jp/ [accessed 2023-12-07]
Raffel C, Shazeer N, Roberts A, Lee K, Narang S, Matena M, et al. Exploring the limits of transfer learning with a unified text-to-text transformer. J Mach Learn Res. 2020;21(140):1-67. [ FREE Full text ]
Pathak A. Comparative analysis of transformer based language models. Comput Sci Inf Technol. 2021.:165-176. [ FREE Full text ] [ CrossRef ]
DIPEx Japan. URL: https://www.dipex-j.org/ [accessed 2024-02-04]
Herxheimer A, McPherson A, Miller R, Shepperd S, Yaphe J, Ziebland S. Database of patients' experiences (DIPEx): a multi-media approach to sharing experiences and information. Lancet. 2000;355(9214):1540-1543. [ CrossRef ] [ Medline ]
Lara PE, Muiño CB, de Spéville BD, Reyes JJ. Hand-foot skin reaction to regorafenib. Actas Dermosifiliogr. 2016;107(1):71-73. [ CrossRef ]
Zaiem A, Hammamia SB, Aouinti I, Charfi O, Ladhari W, Kastalli S, et al. Hand-foot syndrome induced by chemotherapy drug: case series study and literature review. Indian J Pharmacol. 2022;54(3):208-215. [ FREE Full text ] [ CrossRef ] [ Medline ]
McLellan B, Ciardiello F, Lacouture ME, Segaert S, Van Cutsem E. Regorafenib-associated hand-foot skin reaction: practical advice on diagnosis, prevention, and management. Ann Oncol. 2015;26(10):2017-2026. [ FREE Full text ] [ CrossRef ] [ Medline ]
Ai L, Xu Z, Yang B, He Q, Luo P. Sorafenib-associated hand-foot skin reaction: practical advice on diagnosis, mechanism, prevention, and management. Expert Rev Clin Pharmacol. 2019;12(12):1121-1127. [ CrossRef ] [ Medline ]
Tenti S, Correale P, Cheleschi S, Fioravanti A, Pirtoli L. Aromatase inhibitors-induced musculoskeletal disorders: current knowledge on clinical and molecular aspects. Int J Mol Sci. 2020;21(16):5625. [ FREE Full text ] [ CrossRef ] [ Medline ]
Lacouture ME, Melosky BL. Cutaneous reactions to anticancer agents targeting the epidermal growth factor receptor: a dermatology-oncology perspective. Skin Therapy Lett. 2007;12(6):1-5. [ FREE Full text ] [ Medline ]

Abbreviations

Edited by G Eysenbach; submitted 25.12.23; peer-reviewed by CY Wang, L Guo; comments to author 24.01.24; revised version received 14.02.24; accepted 09.03.24; published 16.04.24.

©Satoshi Nishioka, Satoshi Watabe, Yuki Yanagisawa, Kyoko Sayama, Hayato Kizaki, Shungo Imai, Mitsuhiro Someya, Ryoo Taniguchi, Shuntaro Yada, Eiji Aramaki, Satoko Hori. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 16.04.2024.

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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11.1 The Purpose of Research Writing
Step 4: Organizing Research and the Writer's Ideas. When your research is complete, you will organize your findings and decide which sources to cite in your paper. You will also have an opportunity to evaluate the evidence you have collected and determine whether it supports your thesis, or the focus of your paper.
Writing a research article: advice to beginners
The typical research paper is a highly codified rhetorical form [1, 2]. Knowledge of the rules—some explicit, others implied—goes a long way toward writing a paper that will get accepted in a peer-reviewed journal. Primacy of the research question. A good research paper addresses a specific research question.
What is Research?
The purpose of research is to further understand the world and to learn how this knowledge can be applied to better everyday life. It is an integral part of problem solving. Although research can take many forms, there are three main purposes of research: Exploratory: Exploratory research is the first research to be conducted around a problem ...
A Practical Guide to Writing Quantitative and Qualitative Research
The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge ...
Writing for publication: Structure, form, content, and journal
This article provides an overview of writing for publication in peer-reviewed journals. While the main focus is on writing a research article, it also provides guidance on factors influencing journal selection, including journal scope, intended audience for the findings, open access requirements, and journal citation metrics.
7.1: The Purpose of Research Writing
For similar reasons as professionals, students do research to answer specific questions, to share their findings with others, to increase their understanding of challenging topics, and to strengthen their analytical skills. Having to write a research paper may feel intimidating at first. After all, researching and writing a long paper requires ...
14.1: The Purpose of Research Writing
You will need a way to put your thoughts together in a logical, coherent manner. You may want to use the facts you have learned to create a narrative or to support an argument. You may want to show the results of your research to your friends, your teachers, or even the editors of magazines and journals. Writing a research paper is an ideal way ...
The Purpose of Research Writing
Step 4: Organizing Research and the Writer's Ideas. When your research is complete, you will organize your findings and decide which sources to cite in your paper. You will also have an opportunity to evaluate the evidence you have collected and determine whether it supports your thesis, or the focus of your paper.
Purpose of Research
The purpose of research can vary depending on the field of study, the research question, and the intended audience. In general, research can be used to: Generate new knowledge and theories. Test existing theories or hypotheses. Identify trends or patterns. Gather information for decision-making. Evaluate the effectiveness of programs, policies ...
How to Write a Research Paper
To write research questions, try to finish the following sentence: "I want to know how/what/why…" Develop a thesis statement. A thesis statement is a statement of your central argument — it establishes the purpose and position of your paper. If you started with a research question, the thesis statement should answer it.
LibGuides: Research Writing and Analysis: Purpose Statement
In PhD studies, the purpose usually involves applying a theory to solve the problem. In other words, the purpose tells the reader what the goal of the study is, and what your study will accomplish, through which theoretical lens. The purpose statement also includes brief information about direction, scope, and where the data will come from.
Structure of a Research Article
Knowing these elements and the purpose of each serves help you to read and understand academic texts efficiently and effectively, and then apply what you read to your paper or project. Social Science (and Science) original research articles generally follow IMRD: Introduction- Methods-Results-Discussion. Introduction. Introduces topic of article.
What is Scientific Research and How Can it be Done?
Research conducted for the purpose of contributing towards science by the systematic collection, interpretation and evaluation of data and that, too, in a planned manner is called scientific research: a researcher is the one who conducts this research. The results obtained from a small group through scientific studies are socialised, and new ...
1. The Purpose of Research: Why do we do it?
by Ioanna Palaiologou, David Needham and Trevor Male. 1. The Purpose of Research: Why do we do it? Select SAGE Journal articles are available to give you even more insight into chapter topics. These are also an ideal resource to help support your literature reviews, dissertations and assignments. Click on the following links which will open in ...
Quality in Research: Asking the Right Question
The purpose of a research question is to define what will be studied, with enough specificity that there will be no ambiguity or confusion about exactly what variables (quantitative research) or phenomena (qualitative research) the researcher is seeking to study. Additionally, in quantitative studies, the variables being measured must be ...
Academic Writing: Understanding the Purpose of Research Articles
The main purpose of research articles is to contribute to the existing body of knowledge in a particular area by presenting new findings or perspectives. They aim to advance understanding and stimulate further research within the academic community. By sharing their work through research articles, researchers not only gain recognition but also ...
What Is Research, and Why Do People Do It?
Abstractspiepr Abs1. Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain ...
7.3: The Purpose of Research Writing
The research process allows you to gain expertise on a topic of your choice. The writing process helps you to remember what you learned and to understand it on a deeper level. Thus writing a research paper can be a great opportunity to explore a topic that particularly interests you and to grow as a person.
Definition, Purposes, and Dimensions of Research
Smith's definition also refers to the fact that the research must stand on its own merit, not the status of the researcher or the eloquence of the writing. Purposes of Research Research has 2 general purposes: (1) increasing knowledge within rhe discipline and (2) increasing knowledge within oneself as a professional consumer of research in ...
5.1: The Purpose of Research Writing
The research process allows you to gain expertise on a topic of your choice. The writing process helps you to remember what you learned, to understand it on a deeper level, and to develop expertise. Thus writing a research paper can be a great opportunity to explore a question and topic that particularly interests you and to grow as a person.
Why should I do research? Is it a waste of time?
Nevertheless, the purpose of research is more than that. It is time to reframe the way research is done and rewarded, leaving profits in second place. We need to remind ourselves about the real purpose of scientific research. Moreover, we need to decide what research is needed and what impact it is likely to have.
Preliminary Development of Items for a Nurses' Physical Environmental
To develop the preliminary environmental assessment tool, an exploratory sequential methodology was used. The approach consisted of three distinct phases, including (a) a qualitative content analysis of existing focus group data, (b) a qualitative content analysis of pertinent literature related to environmental assessment tools in a healthcare context, and (c) the development and refinement ...
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Advice for the Unmotivated
Next, show empathy. Practice self-care, make friends, recognize the accomplishments of others, seek their views, and help them. Research shows that this combats burnout. Third, take action ...
Peer Review in Scientific Publications: Benefits, Critiques, & A
The peer review process begins when a scientist completes a research study and writes a manuscript that describes the purpose, experimental design, results, and conclusions of the study. The scientist then submits this paper to a suitable journal that specializes in a relevant research field, a step referred to as pre-submission.
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The American consumer is undeniably becoming more inclusive. Responding to our survey 1 McKinsey Inclusive Consumer Survey, October 2021. in October 2021, two out of three Americans told us their social values now shape their shopping choices. And 45 percent—likely representing well over a hundred million shoppers 2 Extrapolated data: 45 percent of 270 million US residents over 18 years old ...
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Abstract. As students, we will focus on the importance of an objective ranking system, research, and mentorship to an applicant. We will address points raised in the (Behavior Analysis In Practice 8 (1):7-15, 2015) article as well as debate the usefulness of proposed standards of objective ranking. Keywords: Graduate school, Graduate training ...
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Journal of Medical Internet Research
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11.1 The Purpose of Research Writing

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Step 1: Choosing a Topic

Step 2: Planning and Scheduling

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Step 5: Drafting Your Paper

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The Purpose of Research Writing

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