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IMRAD (Introduction, Methods, Results and Discussion)

Academic research papers in STEM disciplines typically follow a well-defined I-M-R-A-D structure: Introduction, Methods, Results And Discussion (Wu, 2011). Although not included in the IMRAD name, these papers often include a Conclusion.

Introduction

The Introduction typically provides everything your reader needs to know in order to understand the scope and purpose of your research. This section should provide:

  • Context for your research (for example, the nature and scope of your topic)
  • A summary of how relevant scholars have approached your research topic to date, and a description of how your research makes a contribution to the scholarly conversation
  • An argument or hypothesis that relates to the scholarly conversation
  • A brief explanation of your methodological approach and a justification for this approach (in other words, a brief discussion of how you gather your data and why this is an appropriate choice for your contribution)
  • The main conclusions of your paper (or the “so what”)
  • A roadmap, or a brief description of how the rest of your paper proceeds

The Methods section describes exactly what you did to gather the data that you use in your paper. This should expand on the brief methodology discussion in the introduction and provide readers with enough detail to, if necessary, reproduce your experiment, design, or method for obtaining data; it should also help readers to anticipate your results. The more specific, the better!  These details might include:

  • An overview of the methodology at the beginning of the section
  • A chronological description of what you did in the order you did it
  • Descriptions of the materials used, the time taken, and the precise step-by-step process you followed
  • An explanation of software used for statistical calculations (if necessary)
  • Justifications for any choices or decisions made when designing your methods

Because the methods section describes what was done to gather data, there are two things to consider when writing. First, this section is usually written in the past tense (for example, we poured 250ml of distilled water into the 1000ml glass beaker). Second, this section should not be written as a set of instructions or commands but as descriptions of actions taken. This usually involves writing in the active voice (for example, we poured 250ml of distilled water into the 1000ml glass beaker), but some readers prefer the passive voice (for example, 250ml of distilled water was poured into the 1000ml beaker). It’s important to consider the audience when making this choice, so be sure to ask your instructor which they prefer.

The Results section outlines the data gathered through the methods described above and explains what the data show. This usually involves a combination of tables and/or figures and prose. In other words, the results section gives your reader context for interpreting the data. The results section usually includes:

  • A presentation of the data obtained through the means described in the methods section in the form of tables and/or figures
  • Statements that summarize or explain what the data show
  • Highlights of the most important results

Tables should be as succinct as possible, including only vital information (often summarized) and figures should be easy to interpret and be visually engaging. When adding your written explanation to accompany these visual aids, try to refer your readers to these in such a way that they provide an additional descriptive element, rather than simply telling people to look at them. This can be especially helpful for readers who find it hard to see patterns in data.

The Discussion section explains why the results described in the previous section are meaningful in relation to previous scholarly work and the specific research question your paper explores. This section usually includes:

  • Engagement with sources that are relevant to your work (you should compare and contrast your results to those of similar researchers)
  • An explanation of the results that you found, and why these results are important and/or interesting

Some papers have separate Results and Discussion sections, while others combine them into one section, Results and Discussion. There are benefits to both. By presenting these as separate sections, you’re able to discuss all of your results before moving onto the implications. By presenting these as one section, you’re able to discuss specific results and move onto their significance before introducing another set of results.

The Conclusion section of a paper should include a brief summary of the main ideas or key takeaways of the paper and their implications for future research. This section usually includes:

  • A brief overview of the main claims and/or key ideas put forth in the paper
  • A brief discussion of potential limitations of the study (if relevant)
  • Some suggestions for future research (these should be clearly related to the content of your paper)

Sample Research Article

Resource Download

Wu, Jianguo. “Improving the writing of research papers: IMRAD and beyond.” Landscape Ecology 26, no. 10 (November 2011): 1345–1349. http://dx.doi.org/10.1007/s10980-011-9674-3.

Further reading:

  • Organization of a Research Paper: The IMRAD Format by P. K. Ramachandran Nair and Vimala D. Nair
  • George Mason University Writing Centre’s guide on Writing a Scientific Research Report (IMRAD)
  • University of Wisconsin Writing Centre’s guide on Formatting Science Reports

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Structure of a Research Paper

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Structure of a Research Paper: IMRaD Format

I. The Title Page

  • Title: Tells the reader what to expect in the paper.
  • Author(s): Most papers are written by one or two primary authors. The remaining authors have reviewed the work and/or aided in study design or data analysis (International Committee of Medical Editors, 1997). Check the Instructions to Authors for the target journal for specifics about authorship.
  • Keywords [according to the journal]
  • Corresponding Author: Full name and affiliation for the primary contact author for persons who have questions about the research.
  • Financial & Equipment Support [if needed]: Specific information about organizations, agencies, or companies that supported the research.
  • Conflicts of Interest [if needed]: List and explain any conflicts of interest.

II. Abstract: “Structured abstract” has become the standard for research papers (introduction, objective, methods, results and conclusions), while reviews, case reports and other articles have non-structured abstracts. The abstract should be a summary/synopsis of the paper.

III. Introduction: The “why did you do the study”; setting the scene or laying the foundation or background for the paper.

IV. Methods: The “how did you do the study.” Describe the --

  • Context and setting of the study
  • Specify the study design
  • Population (patients, etc. if applicable)
  • Sampling strategy
  • Intervention (if applicable)
  • Identify the main study variables
  • Data collection instruments and procedures
  • Outline analysis methods

V. Results: The “what did you find” --

  • Report on data collection and/or recruitment
  • Participants (demographic, clinical condition, etc.)
  • Present key findings with respect to the central research question
  • Secondary findings (secondary outcomes, subgroup analyses, etc.)

VI. Discussion: Place for interpreting the results

  • Main findings of the study
  • Discuss the main results with reference to previous research
  • Policy and practice implications of the results
  • Strengths and limitations of the study

VII. Conclusions: [occasionally optional or not required]. Do not reiterate the data or discussion. Can state hunches, inferences or speculations. Offer perspectives for future work.

VIII. Acknowledgements: Names people who contributed to the work, but did not contribute sufficiently to earn authorship. You must have permission from any individuals mentioned in the acknowledgements sections. 

IX. References:  Complete citations for any articles or other materials referenced in the text of the article.

  • IMRD Cheatsheet (Carnegie Mellon) pdf.
  • Adewasi, D. (2021 June 14).  What Is IMRaD? IMRaD Format in Simple Terms! . Scientific-editing.info. 
  • Nair, P.K.R., Nair, V.D. (2014). Organization of a Research Paper: The IMRAD Format. In: Scientific Writing and Communication in Agriculture and Natural Resources. Springer, Cham. https://doi.org/10.1007/978-3-319-03101-9_2
  • Sollaci, L. B., & Pereira, M. G. (2004). The introduction, methods, results, and discussion (IMRAD) structure: a fifty-year survey.   Journal of the Medical Library Association : JMLA ,  92 (3), 364–367.
  • Cuschieri, S., Grech, V., & Savona-Ventura, C. (2019). WASP (Write a Scientific Paper): Structuring a scientific paper.   Early human development ,  128 , 114–117. https://doi.org/10.1016/j.earlhumdev.2018.09.011

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How to Organize a Paper: The IMRaD Format

IMRaD Format

What is the IMRaD Format?

The IMRaD (often pronounced “im-rad”) format is a scientific writing structure that includes four or five major sections: introduction (I); research methods (M); results (R); analysis (a); and discussion (D). The IMRaD format is the most commonly used format in scientific article and journal writing and is used widely across most scientific and research fields.

When Do I Use the IMRaD Format?

If you are writing a paper where you are conducting objective research in order answer a specific question, the IMRaD format will most likely serve your purposes best. The IMRaD format is especially useful if you are conducting primary research (such as experimentation, questionnaires, focus groups, observations, interviews, and so forth), but it can be applied even if you only conduct secondary research (which is research you gather from reading sources like books, magazines, journal articles, and so forth.)

The goal of using the IMRaD format is to present facts objectively, demonstrating a genuine interest and care in developing new understanding about a topic; when using this format, you don’t explicitly state an argument or opinion, but rather, you rely on collected data and previously researched information in order to make a claim.

While there are nuances and adjustments that would be made to the following document types, the IMRaD format is the foundational structure many research-driven documents:

  • Recommendation reports
  • Plans (such as an integrated marketing plan or project management plan)

How Does the IMRaD Format Work?

As mentioned above, the IMRaD format includes four or five major sections. The little “a” has had multiple interpretations over the years; some would suggest it means nothing other than “and,” as in “Introduction, Methods, Results, and Discussion,” but others have argued that the “a” should be viewed as “Analysis” in papers where the “Results” section may not be immediately clear and a section that analyzes the results is important for reader comprehension. Either way, the “a” often remains in lower-case to indicate that, while it’s often important, it isn’t always necessary. Below, we’ll review the five major sections, with “a” given equal weight to the other sections.

Note that these five sections should  always  go in the order listed below:

  • Statement of the topic you are about to address
  • Current state of the field of understanding (often, we call this a literature review and it may even merit having its own section)
  • Problem or gap in knowledge (what don’t we know yet or need to know? what does the field still need to understand? what’s been left out of previous research? is this a new issue that needs some direction?)
  • Forecast statement that explains, very briefly, what the rest of the paper will entail, including a possible quick explanation of the type of research that needs to be conducted
  • Separate each type of research you conducted (interviews, focus groups, experiments, etc.) into sub-sections and only discuss one research method in each sub-section (for clarity and organization, it’s important to not talk about multiple methods at once)
  • Be very detailed about your process. If you interviewed people, for example, we need to know how many people you interviewed, what you asked them, what you hoped to learn by interviewing them, why chose to interview over other methods, why you interviewed those people specifically (including providing they demographic information if it’s relevant), and so forth. For other types of data collection, we need to know what your methods were–how long you observed; how frequently you tested; how you coded qualitative data; and so forth.
  • Don’t discuss what the research means. You’ll use the next two sections–Analysis and Discussion–to talk about what the research means. To stay organized, simply discuss your research methods. This is the single biggest mistake when writing research papers, so don’t fall into that trap.
  • Results:  The results section is critical for your audience to understand what the research showed. Use this section to show tables, charts, graphs, quotes, etc. from your research. At this point, you are building your reader towards drawn conclusions, but you are not yet providing a full analysis. You’re simply showing what the data says. Follow the same order as the Methods section–if you put interviews first, then focus groups second, do the same in this section. Be sure, when you include graphics and images, that you label and title every table or graphic (“ Table 3: Interview Results “) and that you introduce them in the body of your text (“As you can see in  Figure 1 , seventy-nine percent of respondents…”)
  • Analysis:  The analysis section details what you and others may learn from the data. While some researchers like to combine this section with the Discussion section, many writers and researchers find it useful to analyze the data separately. In the analysis section, spend time connecting the dots for the reader. What do the interviews say about the way employers think about their employees? What do the observations say about how employees respond to workplace criticism? Can any connections be made between the two research types? It’s important in the Analysis section that you don’t draw conclusions that the research findings don’t suggest.  Always  stick to what the research says.
  • Discussion:  Finally, you conclude this paper by suggesting what new knowledge this provides to the field. You’ll often want to note the limitations of your study and what further research still needs to be done. If something alarming or important was discovered, this is where you highlight that information. If you use the IMRaD format to write other types of papers (like a recommendation report or a plan), this is where you put the recommendations or the detailed plan.

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What is IMRaD?

IMRaD is an acronym for Introduction , Methods , Results , and Discussion . It describes the format for the sections of a research report. The IMRaD (or IMRD) format is often used in the social sciences, as well as in the STEM fields.

Credit: IMRD: The Parts of a Research Paper by Wordvice Editing Service on YouTube

Outline of Scholarly Writing

With some variation among the different disciplines, most scholarly articles of original research follow the IMRD model, which consists of the following components:

Introduction

  • Statement of Problem (i.e. "the Gap")
  • Plan to Solve the Problem

Method & Results

  • How Research was Done
  • What Answers were Found
  • Interpretation of Results (What Does It Mean?)
  • Implications for the Field

This form is most obvious in scientific studies, where the methods are clearly defined and described, and data is often presented in tables or graphs for analysis.

In other fields, such as history, the method and results may be embedded in a narrative, perhaps describing and interpreting events from archival sources. In this case, the method is the selection of archival sources and how they were interpreted, while the results are the interpretation and resultant story.

In full-length books, you might see this general pattern followed over the entire book, within each chapter, or both.

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  • v.92(3); 2004 Jul

The introduction, methods, results, and discussion (IMRAD) structure: a fifty-year survey

Luciana b. sollaci.

1 William Enneking Library Sarah Network of Hospitals Brasilia, Federal District 70335-901 Brazil

Mauricio G. Pereira

2 University of Brasilia Department of Health Sciences Brasilia, Federal District 70919-900 Brazil

3 Catholic University of BrasiliaFaculty of MedicineBrasilia, Federal District 71966-700Brazil

Background: The scientific article in the health sciences evolved from the letter form and purely descriptive style in the seventeenth century to a very standardized structure in the twentieth century known as introduction, methods, results, and discussion (IMRAD). The pace in which this structure began to be used and when it became the most used standard of today's scientific discourse in the health sciences is not well established.

Purpose: The purpose of this study is to point out the period in time during which the IMRAD structure was definitively and widely adopted in medical scientific writing.

Methods: In a cross-sectional study, the frequency of articles written under the IMRAD structure was measured from 1935 to 1985 in a randomly selected sample of articles published in four leading journals in internal medicine: the British Medical Journal, JAMA, The Lancet, and the New England Journal of Medicine.

Results: The IMRAD structure, in those journals, began to be used in the 1940s. In the 1970s, it reached 80% and, in the 1980s, was the only pattern adopted in original papers.

Conclusions: Although recommended since the beginning of the twentieth century, the IMRAD structure was adopted as a majority only in the 1970s. The influence of other disciplines and the recommendations of editors are among the facts that contributed to authors adhering to it.

Since its origin in 1665, the scientific paper has been through many changes. Although during the first two centuries its form and style were not standardized, the letter form and the experimental report coexisted. The letter was usually single authored, written in a polite style, and addressed several subjects at the same time [ 1 ]. The experimental report was purely descriptive, and events were often presented in chronological order. It evolved to a more structured form in which methods and results were incipiently described and interpreted, while the letter form disappeared [ 2 ]. Method description increasingly developed during the second half of the nineteenth century [ 3 ], and an overall organization known as “theory—experiment—discussion” appeared [ 4 , 5 ]. In the early twentieth century, contemporary norms began to be standardized with a decreasing use of the literary style. Gradually, in the course of the twentieth century, the formal established introduction, methods, results, and discussion (IMRAD) structure was adopted [ 6 ].

However, neither the rate at which the use of this format increased nor the point at which it became the standard for today's medical scientific writing is well established. The main objective of this investigation is to discover when this format was definitively adopted. Also, to have a global idea of the articles published during the studied period, articles written without the IMRAD structure will be briefly described.

In a cross-sectional study, the frequency of articles using the IMRAD structure was measured at 5-year intervals, during the 50-year period from 1935 to 1985. Data collection began at 1960, moving forward and backward from that year until the frequency of IMRAD articles reached 100% and none respectively. A sample of 1 in every 10 issues of 4 leading medical journals in internal medicine was systematically selected to evaluate the articles published in these years. A total of 1,297 original articles—all those from each selected issue—were examined: 341 from the British Medical Journal, 328 from Journal of the American Medical Association (JAMA), 401 from The Lancet, and 227 from the New England Journal of Medicine. These journals were chosen based on their similarities in target audience, frequency, and lifespan. The journals had to be currently published at the beginning of the 20th century and show no interruptions during the studied period.

The criteria used by the journal for an original article were accepted. Therefore, if an article was labeled original by the journal, it was regarded as such, even though nowadays it might not be considered so. An article was considered to be written using the IMRAD structure only when the headings “methods, results, and discussion,” or synonyms for these headings, were all included and clearly printed. The introduction section had to be present but not necessarily accompanied by a heading. Articles that did not follow this structure were considered non-IMRAD. They could be generally grouped as: (1) continuous text, (2) articles that used headings other than the IMRAD, (3) case reports, and (4) articles that partially adopted the IMRAD structure.

One of the authors (Sollaci) collected the data. In a randomly selected subsample of forty-eight articles, the data collection was independently repeated after six months. A high agreement was found ( Kappa = 0.95; CI 95%:0.88; 1.0).

The frequency of articles written using the IMRAD structure increased over time. In 1935, no IMRAD article could be found. In 1950, the proportion of articles presented in this modern form surpassed 10% in all journals. Thereafter, a pronounced increase can be observed until the 1970s, when it reached over 80%. During the first 20 years, from 1935 to 1955, the pace of IMRAD increments was slow, from none to 20%. However, during the following 20 years, 1955 to 1975, the frequency of these articles more than quadrupled ( Figure 1 ).

An external file that holds a picture, illustration, etc.
Object name is i0025-7338-092-03-0364-f01.jpg

Proportion of introduction, methods, results, and discussion (IMRAD) adoption in articles published in the British Medical Journal, JAMA, The Lancet, and the New England Journal of Medicine, 1935–1985 (n = 1,297)

All four journals presented a similar trend: the New England Journal of Medicine fully adopted the structure in 1975, followed by the British Medical Journal in 1980, and JAMA and The Lancet in 1985.

Regarding the non-IMRAD articles, the evolution and variations of text organization for all journals can be delineated. In the British Medical Journal and The Lancet, articles that used non-IMRAD headings prevailed from 1935 to 1945. A shift to articles that partially adopted the IMRAD structure occurred from 1950 to 1960. From 1965 and beyond, the full structure tends to predominate. Until 1960, texts with different headings and partial IMRAD headings shared the lead in JAMA. From 1965 onward, the complete format is the most used. The New England Journal of Medicine had a slightly different pattern. Until 1955, continuous text, non-IMRAD headings, and case reports predominated. After 1960, the IMRAD structure takes the lead.

As an example, Figure 2 shows the text organization in the British Medical Journal from 1935 to 1985. The ascending curve represents the IMRAD articles. It is the same as shown in Figure 1 , and the descending curves represent all other forms of text organization. A similar tendency was observed for The Lancet, JAMA, and the New England Journal of Medicine.

An external file that holds a picture, illustration, etc.
Object name is i0025-7338-092-03-0364-f02.jpg

Text organization of published articles in the British Medical Journal from 1935 to 1985 (n = 341)

One interesting finding is that during the initial period of our study, the order of the IMRAD headings did not follow today's convention; results could be presented before methods or discussion before results, and, although a few articles followed the IMRAD structure in the 1940s, they were not the same as articles written with the IMRAD structure in the 1980s. Information, which today is highly standardized in one section, would be absent, repeated, or dispersed among sections in earlier articles.

Gradually and progressively, the IMRAD structure was adopted by the studied journals. Until 1945, articles were organized in a manner more similar to a book chapter, mainly with headings associated with the subject, and did not follow the IMRAD structure. From 1950 to 1960, the IMRAD structure was partially adopted, and, after 1965, it began to predominate, attaining absolute leadership in the 1980s.

The authors did not find definite reasons explaining the leadership of the IMRAD structure in the literature. It is possible that sciences other than medicine might have influenced the growing use of this structure. The field of physics, for example, had already adopted it extensively in the 1950s [ 7 ].

This structure was already considered the ideal outline for scientific writing in the first quarter of the 20th century [ 8 , 9 ]; however, it was not used by authors [ 10 ]. After World War II, international conferences on scientific publishing recommended this format [ 11 ], culminating with the guidelines set by the International Committee of Medical Journal Editors, formerly known as the Vancouver Group, first published in the late 1970s [ 12 ]. According to Huth [ 13 ], the wide use of the IMRAD structure may be largely credited to editors, who insisted on papers being clearly formatted to benefit readers and to facilitate the process of peer review.

According to Meadows [ 14 ], development and changes in the internal organization of the scientific article is simply an answer to the constant growth of information. The IMRAD structure facilitates modular reading, because readers usually do not read in a linear way but browse in each section of the article, looking for specific information, which is normally found in preestablished areas of the paper [ 15 ].

Four major leading journals of internal medicine were examined. It might be assumed that patterns set by these journals would be followed by others; nevertheless, caution should be taken in extrapolating these findings to other journals.

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What is IMRAD?

When writing reports that require a structured abstract, your work will contain the following headings, at minimum, to organize your work:  I ntroduction,  M ethods,  R esults, and  D iscussion. While you will likely utilize additional headings and subheadings, these aforementioned headings should provide the overarching structure of your work. The IMRAD format is commonly used for reports written in the medical, health, biological, chemical, engineering, and computer sciences.  

As you read journal articles, notice that scientific publications also follow the IMRAD format. In this example , the authors structure their work around the headings: background, methods, results, conclusions. 

Using IMRAD

Introduction- Why is this research important?

  • The introduction of your paper should provide the reader with context for your work.  Additionally, the introduction should state your study's objective(s), hypothesis, or research questions. To this end, you should describe how and why your objective(s), hypothesis, or research questions were developed and why your research is important. If your research addresses a "gap" in the literature, discuss the current state of scholarship available and how your research is a solution or aid to this gap. The introduction is usually 2-3 paragraphs in length, or 150 words. See section 2.8 the AMA Manual for more information about developing an introduction. 

Methods- How did you conduct your research? 

  • The methods section informs readers of how you conducted your research. As section 2.8 of the AMA Manual describes, methods sections should contain a description of your study design or type of analysis, sample, methods, equipment, interventions or exposures, and statistical analysis methods, among others. A "gold standard" methods section provides enough detail and specificity that it would enable readers to duplicate your study. 

Results- What are the results of your research? 

  • Present only the findings from your research study. As section  2.8 of the AMA Manual enumerates, the results section should explicitly address the data and information collected that relates to your research hypothesis or study question. Results sections are commonly written in the past tense. If your study contains any tables or figures, include these data sources here. Figures and tables are numbered separately. Captions are provided above tables and beneath figures. 

Discussion- What do your research findings mean? 

  • Now that you have presented your "raw" data, research, and findings in the results section, contextualize your findings for the reader. As the AMA Manual encourages , the discussion section should be a formal consideration, critical examination, and critique of your study and collected data. You should discuss your research question and hypothesis in light of your study's results, and in conversation with the larger body of literature that relates to your area of study. 

Abstract- Summarize your entire research study.  

  • Design, Setting, Participants
  • Main Outcome and Measures 
  • Results 
  • Conclusion 
  • Section 2.5 of AMA Manual provides additional details on structured abstracts. Further instructions on structured abstracts for reports of original data are provided in section 2.5.1.1 of the AMA Manual.  

Common Weaknesses in IMRAD Reports

Weak Abstract

  • Does not provide a clear statement of the study's importance, objectives, main outcome, or results. 

Unclear Introduction

  • Does not provide context for the research study, nor is the study's objective(s), aim(s), hypothesis, or research question clearly stated. 

Wanting Methods Section

  • Methods section lacks detail or is disorganized. 

Unfocused  Results Section 

  • Results section contains comments, explanations, and other digressions rather than only reporting results. 
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The introduction, methods, results and discussion (IMRAD) structure: a Survey of its use in different authoring partnerships in a students' journal

  • Loraine Oriokot 1 ,
  • William Buwembo 2 ,
  • Ian G Munabi 2 &
  • Stephen C Kijjambu 3  

BMC Research Notes volume  4 , Article number:  250 ( 2011 ) Cite this article

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Globally, the role of universities as providers of research education in addition to leading in main - stream research is gaining more importance with demand for evidence based practices. This paper describes the effect of various students and faculty authoring partnerships on the use of the IMRAD style of writing for a university student journal.

This was an audit of the Makerere University Students' Journal publications over an 18-year period. Details of the authors' affiliation, year of publication, composition of the authoring teams and use of IMRAD formatting were noted. Data analysis gave results summarised as frequencies and, effect sizes from correlations and the non parametric test. There were 209 articles found with the earliest from 1990 to latest in 2007 of which 48.3% were authored by faculty only teams, 41.1% were authored by student only teams, 6.2% were authored by students and faculty teams, and 4.3% had no contribution from the above mentioned teams. There were significant correlations between the different teams and the years of the publication ( r s = -0. 338 p < 0.01 one tailed). Use of the IMRAD formatting was significantly affected by the composition of the teams (Χ 2 (2df) = 25.621, p < 0.01) especially when comparing the student only teams to the faculty only teams. (U = 3165 r = - 0.289). There was a significant trend towards student only teams over the years sampled. ( z = -4.764, r = -0.34).

Conclusions

In the surveyed publications, there was evidence of reduced faculty student authoring teams as evidenced by the trends towards students only authoring teams and reduced use of IMRAD formatting in articles published in the students' journal. Since the university is expected to lead in teaching of research, there is need for increased support for undergraduate research, as a starting point for research education.

Globally there is an increasing awareness of the importance of research for developing guidelines to direct social and economic interventions [ 1 , 2 ]. Research involves the critical analysis of each and every solution to a problem using the scientific method to identify the best evidence based solution for action at the time. Research is thus the foundation of evidence based practice [ 3 , 4 ]. Society expects universities to lead both the teaching and carrying out of research. This expectation has led to various policy recommendations and initiatives to promote research and innovation. An example of such a policy recommendation can be found in United States of America, where Gonzalez (2001) identifies the 1998 Boyer commission report encouraging universities to place more emphasis on undergraduate research experiences [ 5 ]. According to Laskowitz et al (2010), Stanford and Duke Universities have been running undergraduate research programmes for the last 40 years that instil in students an appreciation for rigorous research in academic medicine [ 6 ]. In Australia, students picked life skills like time management so long as they dealt with authentic science and had good supervision [ 7 ]. In Africa the demand for high quality research at undergraduate level of education, is yet to be met [ 8 ].

Research and innovation are critical for national social and economic development [ 2 ]. In response to the drive for more economic development, universities are redefining their roles and interactions with society by going from being the traditional storehouses of knowledge to becoming interactive knowledge hubs [ 9 ]. One way of ensuring that the Universities actually act as knowledge hubs is through promoting institutional visibility by encouraging research publication by students and faculty using internationally recognised scientific writing formats like Introduction, Methods, Results and Discussion, [IMRAD] [ 5 , 9 , 10 ]. In addition to visibility, the adoption of high quality international standards benefits the university by the creation of a pool of individuals who are conversant with scientific writing. Having such a pool of people supports Gonzales (2001) recognition that research takes place anywhere, and the "teaching of research is a role that is increasingly becoming the preserve of the university" [ 5 ]. This role of how research is taught is further extended with Gonzales (2001) arguing that undergraduate research is actually the beginning of a "five stage continuum of research education that ends with a post-doctoral experience" [ 5 ]. Research education promotes the uniform conduction, interpretation and response to research findings reported using familiar standard formats of scientific writing. Finally according to Aravamudhan and Frantsve (2009) research education and adoption of uniform formats of scientific writing promotes evidence based practice by improving information awareness, seeking and eventual application of new practices [ 3 ]. The rapid increase in the volume of very advanced knowledge and equally rapid changes in the working environment make it increasingly important to equip students with key research skills like scientific writing to keep abreast [ 3 , 4 ].

This paper looks at work done on the Makerere Medical Journal (MMJ), one of the students' journals at Makerere University. MMJ is run for and by the health professional student body at the former Faculty of Medicine (FoM) that with the School of Public Health became Makerere University College of Health Sciences (MakCHS) in 2008, [ 11 – 13 ] one of the Colleges of Makerere University (one of the oldest universities in Sub-Saharan Africa). With the University's Vision to become a leader in research in Africa, there is a high demand for research and scientific writing currently focusing on graduate research [ 14 ]. The effect of student faculty partnerships on undergraduate scientific writing to our knowledge is not well documented. The paper describes the role of student faculty partnerships in determining the formatting of the MMJ articles over an 18 year (1990-2007) period in the journal's existence.

This was a retrospective audit of the Medical Journal MMJ, a publication of the health professional student body. The MMJ is a peer-reviewed publication that provides a platform for students to: share and exchange medical knowledge; develop writing and analytical abilities; promote awareness of students' contributions to health care; provide continuing medical education and foster valuable leadership and editorial skills. MMJ is published bi-annually and has been in existence from the early 1960's. The journal publishes: original articles, reviews, reports, letters to the editor, case reports, includes sections like: educational quizzes and cross word puzzles.

A hand search was made for complete journal volumes from various sources that included the Sir Albert Cook Library which is the main MakCHS library, personal collections and the journal editorial teams' files. For each article found, the following information was captured; the articles' authors and their affiliations, the use of the IMRAD format of writing papers, the composition of the authoring teams and the year of the publication. The data was analyzed using the Statistical Package for Social Sciences Inc. (version 12.0 for Windows, Chicago, Illinois) with the calculation of odd ratios and trend analysis being made with the aid of online Open Epi programme version 2.3.1 http://www.openepi.com  [ 15 ]. The results were summarised as frequencies and presented in bar graphs and tables with calculation of odds ratios, effect sizes and trend analysis. Additional inferences were made with the aid of spearman's correlations and non parametric tests with the level of significance set as P value of less than 0.05.

Permission to use the data for this study was obtained from the editorial team for the journal. None of the authors' identification details were used during the analysis and the preparation of the paper.

Two hundred and nine (209) journal articles were found during the survey. The earliest publication was of the year 1990 and the most recent from 2007 from 13 volumes of the journal. Of the 209 articles 101/209 (48.3%) were authored by faculty only teams, 86/209 (41.1%) were authored by student only teams, 13/209 (6.2%) were authored by student faculty teams, and 9/209 (4.3%) had no affiliation indicated thus not classified into any of the above mentioned teams. Examination of the paper formatting revealed that only 70/209 (33.5%) of the papers were written using the IMRAD format. The number of articles found by year are summarised in Table 1 , with the highest number of 33 in 2007 and lowest number of 5 seen in 1990. There was no significant change in the odds for IMRAD use over the years. (Mantel Hertz chi square for trend = 1.71 p value 0.1906). There were significant correlations between the different teams and the years of the publication r s = - 0.338 (p < 0.01 one tailed) and for teams and use of IMRAD formatting r s = - 0.265 (p < 0.01 one tailed).

Use of the IMRAD formatting was significantly affected by the composition of the teams Χ 2 (2df) = 25.621, p < 0.001 using the Kruskal Wallis test. Post hoc Mann-Whitney team pair specific tests whose level of significance set at 0.025 showed that the use of IMRAD was not significant when comparing the mixed students-faculty with faculty only teams (U = 444, r = - 0.21), but, was significantly different when comparing the students only to faculty only teams (U = 3165, r = -0.289). Jonkheere's test revealed no trend in the use of IMRAD over the years sampled J = 10100, z = 0.211, r = 0.086. However there was a significant trend to more students only teams over the years sampled J = 6802, z = -4.764, r = -0.34.

The analysis of the data reveals that there is an increase in the number of students only teams submitting articles to the journal. This can be seen in the number of articles submitted which was highest at 33 in the 2007 journal. The increased interest in publication could be the result of a more aggressive editorial team or represent an increasing interest on the part of the student body in the value of research. Increase in undergraduate students interest in research is supported by the observation that globally there is increased interest in research at the undergraduate level as the beginning of research education [ 5 ]. The other factor that could support increased interest in research is the adoption of adult learning approaches to curriculum delivery by the FoM in 2003 [ 16 ].

Sadly the increased student interest in research is also accompanied by a significant trend towards reduced faculty engagement with students in research ( r = - 0.34). Reduced faculty engagement also manifests in two other ways as seen in no change in the use of IMRAD over time ( J = 10100, z = 0.211, r = 0.086) and the observation that the students only teams use IMRAD less than the faculty teams (U = 3165, r = -0.289). Even where the journal article had mixed student faculty teams there was no significant increase in the use of IMRAD when compared to faculty only teams (U = 444, r = - 0.21). Reduced engagement could also point to a different trend developing over time, there seems to be little support for undergraduate research in both the curricula and in extracurricular activities. This seems to have been going on for quite some time considering that most of the faculty were once students at this same university. Examining global trends as described by Gonzales (2001), research education has moved from being the premise of graduate students to a continuum that begins in undergraduate education [ 5 ]. Active support for undergraduate research is happening in more developed settings as is seen in the example of Duke and Stanford universities [ 6 ]. According to Lappato (2007) in undergraduate research experiences students' learn by being positively influenced by the process of investigation, and learning or from modelling higher order methods of thinking as they test and later communicate their research findings [ 17 ]. This makes the undergraduate research experiences a powerful tool for quickly increasing the number of high calibre researchers [ 18 ]. If one assumed that the use of the IMRAD format is a measure of scientific writing skill transfer then the deductions from the analysis of the data obtained from the student journal articles, suggests that for this population research is undergoing a slow but sure decline. This trend has been observed by other researchers concerning the African continent [ 8 ].

Given the powerful nature of the undergraduate research experiences as tools for grooming the next generation of scientists, it is important to look at other factors like the need for extra effort and time of faculty to transfer scholarly writing skills to students [ 19 ]. There is need for urgently exploration of mentoring undergraduates in research in line with global research education trends [ 5 ]. Some other interventions for consideration include using a training or mentoring programme each new MMJ editorial team [ 20 ], and use of the student assessment process as is done at the graduate level [ 8 ]. Using student assessment to promote scientific writing requires clear documentation of the different roles of the various participants and subsequent supervision, [ 21 ] in addition to the creation of an enabling environment using an institution wide research governance framework[ 22 ]. Given that individuals who participate in research as students will more likely continue to participate in research as faculty, it is important that all efforts are made to ensure that the students develop these vital scientific writing skills [ 19 , 23 ].

Study limitations

This retrospective study of the MMJ had some limitations like: the poor journal publication record keeping, annual turnover of the volunteer student editorial board and use of abbreviated names made it difficult to identify some of the author details. Despite this, it was possible to obtain an adequate sample of the journal's publication for detailed analysis.

This survey demonstrates that in the surveyed university population, faculty student partnerships are not producing the desired level of undergraduate research mentoring as evidenced by the reduced use of the IMRAD formatting in articles published in the MMJ. Given that the use of IMRAD is one of the core competencies for one to be an active member of the scientific community, inability to transfer this skill could help explain some of the identified gaps related to scientific writing in this university and Africa at large [ 8 ]. There is need to support undergraduate research in Africa using active mentoring programmes, providing training support for student journal editorial teams and use of innovative pro-scientific writing curricula. Such support could result in the quicker uptake and promotion of scientific writing and the reading of scientific literature in Africa over time.

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Acknowledgements

The authors express their gratitude to the faculty in the Albert Cook Library, members of the editorial team who participated in searching for the various past volumes of the journal, the journal's reviewers who provided many insightful comments and to Ms Evelyn Bakengesa for the time she set aside to proof read the final draft of the paper.

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Former Editor Makerere Medical Students Journal, Makerere University College of Health Sciences, New Mulago Hospital Complex, Kampala Uganda

Loraine Oriokot

Department of Human Anatomy, School of Biomedical Sciences, Makerere University College of Health Sciences, New Mulago Hospital Complex, Kampala Uganda

William Buwembo & Ian G Munabi

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Correspondence to Ian G Munabi .

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Authors' contributions

All the authors read and approved the final manuscript. LO: Participated in the conceptualisation, data collection and write up of the final paper. WB: Participated in all phases of the papers write up from conceptualisation, analysis to the final write up IGM: Participated in all phases of the study; conceptualization, data collection, analysis and write up. SCK: participated in the conceptualisation of the paper and review of the various drafts of the paper prior to submission.

Loraine Oriokot, William Buwembo and Stephen C Kijjambu contributed equally to this work.

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Oriokot, L., Buwembo, W., Munabi, I.G. et al. The introduction, methods, results and discussion (IMRAD) structure: a Survey of its use in different authoring partnerships in a students' journal. BMC Res Notes 4 , 250 (2011). https://doi.org/10.1186/1756-0500-4-250

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research paper using imrad format example

Improving the writing of research papers: IMRAD and beyond

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Publishing in peer-reviewed journals is essential to scientific research. “A scientific experiment, no matter how spectacular the results, is not completed until the results are published” (Day and Gastel 2006 ). Advances in science depend on the rigorous process of scientific publishing. Justified or not, journal impact factors and article citations have become the buzzwords in today’s academic world, and have been used increasingly as metrics to evaluate the performance of research projects, journals, scientists, and institutions. As scientific journals and published articles continue to proliferate, we as editors, reviewers, and scientists all are faced with increasing challenges to communicate science more effectively and efficiently.

In this series of editorials, we focus on the question: How can we improve our writing of research papers for Landscape Ecology and other professional journals to increase their readability and facilitate the process of their evaluation? Obviously, this is not a new question; nor do we promise to have revolutionary answers. Experts have written numerous books and journal articles addressing this very topic. The main goal here is to discuss several key issues on the organization of research papers—particularly on the structure of IMRAD (introduction-methods-results-and-discussion)—the predominant format of scientific writing. I hope that our editors, reviewers, and authors will benefit from this discussion.

IMRAD as an outcome of the evolution of scientific publishing

Everyone in science may know something about IMRAD—the introduction-methods-results-and-discussion structure (Fig.  1 ). But its history is rather brief when compared to that of scientific writing as a whole. The first scientific journals appeared in the 17th century, when articles were published mainly in the form of descriptive letters and narratives structured chronologically (Meadows 1985 ; Day 1989 ). For more than two centuries, scientific papers were published without a generally accepted format. During this period of time, however, the idiosyncrasy in scientific publishing gradually withered as both the journals and the papers in them became increasingly formalized by developing some form of organization in structure (Meadows 1985 ). Day ( 1989 ) argued that it was Louis Pasteur who invented the first IMRAD-like writing structure in his classic book, Etudes sur la Biere (studies on fermentation), originally published in 1876. Pasteur’s book had identifiable sections of “introduction”, “methods”, and “discussion”—although such headings were not explicitly used (Day 1989 ). However, IMRAD did not become the “standard” until the 1970s, when the American national standard for the preparation of scientific papers for written or oral presentation (ANSI Z39.16-1972) was published in 1972 and again 1979 (Day 1989 ; Day and Gastel 2006 ).

Diagrammatic representation of the IMRAD structure of research papers (modified from a diagram at http://www.services.unimelb.edu.au/asu/writing/ ). The basic structure of IMRAD has only four sections: introduction (I), methods (M), results (R), and discussion (D). Most original research papers today have 6–10 sections, with those in dotted-lined boxes being optional. The shape of each section is meaningful as it suggests how that section should proceed in terms of specificity (focusing on your study) and generality (relating to studies by others). The size of each box is roughly proportional to the relative length of each section. The text with arrows indicates what main questions each section should address

IMRAD began to be adopted by scientific journals around the 1940s, and quickly became the dominant format for research papers in a majority of leading scientific journals by the late 1970s. For example, for leading journals in medical research IMRAD was adopted in the 1950s, became predominant in the 1960s, and has been the standard since the 1980s (Sollaci and Pereira 2004 ). In physics, IMRAD was already employed extensively in the 1950s (Bazerman 1984 ). Research papers in two of the most prominent ecological journals, Journal of Ecology (published by British Ecological Society since 1913) and Ecology (published by Ecological Society of America since 1920), began to adopt IMRAD in the 1950s. For instance, Lindeman’s ( 1942 ) seminal article on trophic dynamics in Ecology was organized by topics, but the classic paper on vegetation continuum by Curtis and McIntosh ( 1951 ) in the same journal clearly was IMRAD-structured. In Journal of Ecology, Watt’s ( 1947 ) masterpiece on pattern and process in plant communities was also organized with topical headings, but Pielou’s ( 1957 ) paper—one of the earliest about scale effects on characterizing spatial patterns—had the appearance of IMRAD. Today, IMRAD is the standard for all major journals in ecology, including this one—Landscape Ecology.

Why has IMRAD been adopted by almost all research journals so widely and quickly, with no sign of being abandoned anytime soon? According to Meadows ( 1985 , 1998 ), changing the internal organization of research papers is one way for the scientific community to respond to the exponential growth of scientific information, and thus IMRAD is a result of that evolutionary process. Most, if not all, editors and scientists agree that IMRAD provides a consistent framework that guides the author to address several questions essential to understanding a scientific study (Fig.  1 ): Introduction—Why did you do it in the first place? Methods—How did you do it exactly? Results—What did you find? Discussion—What does it mean after all and so what? According to experts who specialize in the history and practice of scientific writing, IMRAD offers several benefits (Meadows 1998 ; Sollaci and Pereira 2004 ; Day and Gastel 2006 ). The modular structure of IMRAD helps the author to organize ideas and remember critical elements; it makes easier for the editor and the reviewer to evaluate manuscripts; and it improves the efficiency of the scientist to locate specific information without going through the entire paper.

IMRAD as an adaptable structure for research papers

IMRAD is primarily for original research articles, and has little relevance to other types of papers commonly seen in scientific journals, such as reviews, perspectives, and editorials. Even for research papers, IMRAD is silent about several other components of a modern research paper: title, abstract, acknowledgments, and references. It does not even say anything about how the sections of I, M, R, and D should each be constructed. So, IMRAD is not really a straightjacket. It has plenty of room for creativity and innovation.

Dozens of books and hundreds of articles have been published on scientific writing, and most if not all of them offer advice on what each element of IMRAD ought to include. One problem to new writers, however, is that these different guides seem to differ in the details. After handling hundreds of manuscripts for Landscape Ecology, I observed that a considerable portion of them had various structural problems. Two of them are major. One is the lack of clearly identified research problems and questions in the introduction (or elsewhere). The other is the lack of organization within each section (particularly results and discussion)—the reader needs to see a building, not a pile of bricks! I have seen manuscripts with an introduction section running several pages long without mentioning the research question of the study, and a discussion section of more than 3 pages without any headings.

How should one resolve the above-mentioned problems? There is no panacea, but I have two suggestions for improvements. First, I find the diagrammatic representation of IMRAD (Fig.  1 ) quite useful because it captures the essence of the structure. The shape and the size of each section are heuristic and easy to remember. My second suggestion is to consult a good writing guide for specifics of each section, from the title to the references. Every experienced author may have a favorite, and mine is Day and Gastel ( 2006 ). Another excellent guide is Gustavii ( 2008 ), which is a comprehensive yet succinct account of the essentials of scientific writing (particularly helpful to authors whose native language is not English). Also, for those who prefer more detailed instructions about key elements within each section, Hartley’s ( 1999 ) “modest proposal”—IMRAD nested with topical headings/subheading in each section—should be helpful. In addition, being precise and concise in language is quintessential in scientific writing. This is a tall order. To get help, a must-have reference is the timeless “little book”—The Elements of Style (Strunk and White 2000 ).

Don’t try to read every guide that you can find. Don’t read it and rest it. Keep it handy, and consult it frequently while writing.

IMRAD as an evolutionary process

As discussed above, the format of scientific papers has evolved during the past several centuries, and will continue to evolve. The evolution of the article format is more than just a way of coping with the ever-increasing kinds and amount of information. As Meadows ( 1985 ) stated:

“The construction of an acceptable research paper reflects the agreed view of the scientific community on what constitutes science. A study of the way papers are constructed at any point in time therefore tells us something about the scientific community at that time.”

As science and information technology continue to advance, IMRAD will undoubtedly evolve as well. In fact, changes have already taken place. For example, abstract, keywords, acknowledgments, and references have become common parts of the IMRAD structure. Even the sequential order of the sections is altered in some journals (e.g., Nature places the methods section, in smaller font size, at the end of a research paper).

Since the early 1990s, structured abstracts—which are organized into several sections with headings or sequential numbers—have become increasingly common in scientific journals. A common format of structured abstracts is: Abstract [background, aims (or objectives), methods, results, conclusions (or synthesis)]. Many leading journals in medical and physical sciences now have them. Some ecology journals have also jumped on this bandwagon, such as those of British Ecological Society. Studies have shown that structured abstracts have several advantages for both authors and readers. For example, Hartley ( 2003 ) found that structured abstracts tend to be significantly more informative, more readable, and clearer than unstructured, traditional abstracts. Hartley and Betts ( 2007 ) concluded that “… spatial organization, together with the greater amount of information normally provided in structured abstracts, explains why structured abstracts are generally judged to be superior to traditional ones.” This should make immediate sense to landscape ecologists—isn’t this another example of pattern affecting process?

A good abstract should be complete, concise, and clear. That is, an abstract should have all the components necessary for a short but complete story. A condensed version of IMRAD, with greater emphasis on results and discussion, is commonly assumed in an abstract. While being complete, an abstract must also be succinct because most journals require that it be no longer than 250–300 words. In addition, a good abstract must have a clear message—what’s the story and so what? Assuming it is a solid study, the abstract should not be difficult to write after all sections of the paper are completed. In reality, however, it is too easy to find abstracts that are either empty in contents or devoid of any recognizable organization. I think that structured abstracts can help improve upon these problems. The structured format guides the author to tell a complete story in a nutshell, and facilitates a faster search for relevant information by either a human reader or a computerized search engine. A useful message for authors is this: always write your abstract following the logical order of structured abstracts even if your target journal does not require a structured abstract.

There are certainly other ways to improve the adaptive application of IMRAD. A number of experts in linguistics and scientific writing have done a great deal of research on this subject. For example, Hartley ( 1999 ) proposed to go “from structured abstracts to structured articles” with a more elaborated IMRAD organization. Sharp ( 2002 ) advised the application of the six W’s (what, why, when, how, where, and who) in each section of IMRAD as a way of providing more structuring.

More relevant to the readers of this journal, Gustafson ( 2011 ) made several thought-provoking suggestions for improving scientific writing in landscape ecology. The 7-section structure that he proposed may be considered a modification to the traditional IMRAD. The headings and subheadings in the 7 sections can fit into the IMRAD structure and provide more organization in a way similar to Hartley ( 1999 ). As discussed earlier, structuring scientific writing helps avoid missing important elements and facilitates fast retrieval of information. As Riitters ( 2011 ) warned, however, too much structuring may hinder the creative process of writing. In addition, because spatiotemporal patterns are central to most landscape ecological studies, graphical communication and metadata documentation are critically important to scientific publishing in our field. Henebry ( 2011 ) provided a brief but resourceful guide to improving the quality of graphs (particularly maps) and ensuring valuable metadata to persist. I highly recommend writers to bear his advice in mind: “Structure your story around the graphs and enable the captions to capture the key points of your paper.”

Concluding remarks

Peter Medawar, the British biologist and a Nobel Laureate in Physiology/Medicine, famously said that the scientific paper is a fraud “because it misrepresents the processes of thought that accompanied or gave rise to the work that is described in the paper” (Medawar 1964 ). He argued that discussion in an IMRAD-structured paper should be placed at the beginning, which then is followed by results and methods. Meadows ( 1985 ) disagreed, and argued that the scientific paper is an archaeological artifact indicative of how scientists generally view their science at a particular time.

It is true that IMRAD does not always represent the order of actual research activities, but that alone does not make the scientific paper fraudulent. While IMRAD seems reflective of the currently dominant view of what is scientific, the format of the scientific paper may be influenced increasingly by technological advances in information processing and publishing as well as the pace of knowledge production. For now, IMRAD still rules, and modifications will continue.

Riitters ( 2011 ) had a great line: “creativity abhors prescription and well-documented junk is still junk.” While this statement is fundamentally correct, I believe that scientific writing should be disciplined and structured for all the reasons that I have discussed earlier. I also believe that it has been, and will continue to be, true that “the best papers combine the science …… with the art of writing” (Southgate 1995 ). Properly using IMRAD improves the art of writing as well as the communication of the science. No, “Good prose cannot correct bad work” (Sharp 2002 ), but good prose can make good work better—sometimes, so dramatically better!

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Wu, J. Improving the writing of research papers: IMRAD and beyond. Landscape Ecol 26 , 1345–1349 (2011). https://doi.org/10.1007/s10980-011-9674-3

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research paper using imrad format example

IMRAD Format For Research Papers: The Complete Guide

research paper using imrad format example

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Writing a strong research paper is key to succeeding in academia, but it can be overwhelming to know where to start. That’s where the IMRAD format comes in. IMRAD provides a clear structure to help you organize and present your research logically and coherently. In this comprehensive guide, we’ll explain the IMRAD format, why it’s so important for research writing, and how to use it effectively. Follow along to learn the ins and outs of crafting papers in the gold-standard IMRAD structure. In this article, I’ll walk you through the IMRAD format step-by-step. I’ll explain each section, how to write it, and what to avoid. By the end of this article, you’ll be able to write a research paper that is clear, concise, and well-organized.

What is IMRAD Format?

IMRAD stands for Introduction, Methods, Results, and Discussion . It’s a way of organizing a scientific paper to make the information flow logically and help readers easily find key details. The IMRAD structure originated in medical journals but is now the standard format for many scientific fields.

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Here’s a quick overview of each section’s purpose:

Introduction : Summary of prior research and objective of your study

Methods : How you carried out the study

Results : Key findings and analysis

Discussion : Interpretation of results and implications

Most papers also include an abstract at the beginning and a conclusion at the end to summarize the entire report.

Why is the IMRAD Format Important?

Using the IMRAD structure has several key advantages:

It’s conventional and familiar. Since I MRAD is so widely used , it helps ensure editors, reviewers, and readers can easily find the details they need. This enhances clarity and comprehension.

It emphasizes scientific rigor. The methods and results sections encourage thorough reporting of how you conducted the research. This supports transparency, credibility, and reproducibility.

It encourages precision. The structure necessitates concise writing focused only on the core aims and findings. This avoids rambling or repetition.

It enables efficient reading. Readers can quickly skim to the sections most relevant to them, like only reading the methods. IMRAD facilitates this selective reading.

In short, the IMRAD format ensures your writing is clear, precise, rigorous, and accessible – crucial qualities in scientific communication.

When Should You Use IMRAD Format?

The IMRAD structure is ideal for:

Primary research papers that report new data and findings

Review papers that comprehensively summarize prior research

Grant proposals requesting funding for research

IMRAD is not typically used for other paper types like:

Editorials and opinion pieces

Popular science articles for general audiences

Essays analyzing a topic rather than presenting new data

So, if you are writing a scholarly scientific paper based on experiments, investigations, or observational studies, the IMRAD format is likely expected. Embrace this conventional structure to help communicate your exciting discoveries.

Now that we’ve covered the key basics let’s dive into how to write each section of an IMRAD paper.

The abstract is a succinct summary of your entire paper, typically around 200 words. Many readers will only read the abstract, so craft it carefully to function as a standalone piece highlighting your most important points.

Elements to include:

Research problem, question, or objectives

Methods and design

Major findings or developments

Conclusions and implications

While written first, refine the abstract last to accurately encapsulate your final paper. A clear precise abstract can help attract readers and set the tone for your work. Take a look at our complete guide to abstract writing here !

INTRODUCTION

The Introduction provides the necessary background context and sets up the rationale for your research. Start by briefly summarizing the core findings from previous studies related to your topic to orient readers to the field. Provide more detail on the specific gaps, inconsistencies, or unanswered questions in the research your study aims to address. Then, clearly state your research questions, objectives, experimental hypotheses, and overall purpose or anticipated contributions. The Introduction establishes why your research is needed and clarifies your specific aims. Strive for a concise yet comprehensive overview that lets readers learn more about your fascinating study. Writing a good introduction is like writing a good mini-literature review on a subject. Take a look at our complete guide to literature review writing here!

research paper using imrad format example

The methods section is the nuts and bolts, where you comprehensively describe how you carried out the research. Sufficient detail is crucial so others can assess your work and reproduce the study. Take a look at our complete guide to writing an informative and tight literature review here!

Research Design

Start by explaining the overall design and approach. Specify:

Research types like experimental, survey, observational, etc.

Study duration

Sample size

Control vs experimental groups

Clarify the variables, treatments, and factors involved.

Participants

Provide relevant characteristics of the study population or sample, such as:

Health status

Geographic location

For human studies, include recruitment strategies and consent procedures.

List any instruments, tests, assays, chemicals, or other materials utilized. Include details like manufacturers and catalog numbers.

Chronologically explain each step of the experimental methods. Be precise and thorough to enable replication. Use past tense and passive voice.

Data Analysis

Describe any statistical tests, data processing, or software used to analyze the data.

The methods section provides the roadmap of your research journey. Strive for clarity and completeness. Now we’re ready for the fun part – the results!

This section shares the key findings and data from your study without interpretation. The results should mirror the methods used.

Report Findings Concisely

Use text, figures, and tables to present the core results:

Focus only on key data directly related to your objectives

Avoid lengthy explanations and extraneous details

Highlight the most groundbreaking findings

Use Visuals to Present Complex Data

research paper using imrad format example

Tables and figures efficiently communicate more complex data:

Tables organize detailed numerical or textual data

Figures vividly depict relationships like graphs, diagrams, photos

Include clear captions explaining what is shown

Refer to each visual in the text

Reporting your results objectively lays the groundwork for the next section – making sense of it all through discussion.

Here, you interpret the data, explain the implications, acknowledge limitations, and make recommendations for future research. The discussion allows you to show the greater meaning of your study.

Interpret the Findings

Analyze the results in the context of your initial hypothesis and prior studies:

How do your findings compare to past research? Are they consistent or contradictory?

What conclusions can you draw from the data?

What theories or mechanisms could explain the outcomes?

Discuss the Implications

Address the impact and applications of the research:

How do the findings advance scientific understanding or technical capability?

Can the results improve processes, design, or policies in related fields?

What innovations or new research directions do they enable?

Identify Limitations and Future Directions

No study is perfect, so discuss potential weaknesses and areas for improvement:

Were there any methodological limitations that could influence the results?

Can the research be expanded by testing new variables or conditions?

How could future studies build on your work? What questions remain unanswered?

A thoughtful discussion emphasizes the meaningful contributions of your research.

The conclusion recaps the significance of your study and key takeaways. Like the abstract, many readers may only read your opening and closing, so ensure the conclusion packs a punch.

Elements to cover:

Restate the research problem and objectives

Summarize the major findings and main points

Emphasize broader implications and applications

The conclusion provides the perfect opportunity to drive home the importance of your work. End on a high note that resonates with readers.

The IMRAD format organizes research papers into logical sections that improve scientific communication. By following the Introduction-Methods-Results-and-Discussion structure, you can craft clear, credible, and impactful manuscripts. Use IMRAD to empower readers to comprehend and assess your exciting discoveries efficiently. With this gold-standard format under your belt, your next great paper is within reach.

research paper using imrad format example

Ready for more?

How To Write an Abstract for Any Subject and Publication (With Examples)

How To Write an Abstract for Any Subject and Publication (With Examples)

Table of contents

research paper using imrad format example

Christian Rigg

An abstract is a short summary of a longer work, such as a study or research paper. The goal is to provide readers with an overview of the purpose, methodology, results, conclusion, and importance of this text.

As a writing coach and part-time academic editor and translator, I’ve read hundreds of abstracts and helped authors draft and refine dozens more. I’ve found that, when writing an abstract, the greatest difficulty lies in balancing brevity, detail, and accessibility.

Fortunately, there’s a simple formula you can use to write a solid abstract for publication, regardless of the subject. What’s more, you can leverage AI to help you write a clear, concise abstract — without losing your voice or sounding unprofessional.

Below you’ll find step-by-step instructions, best practices, examples, and a helpful checklist. 

Key Takeaways

  • An abstract offers a succinct overview of the aims, results, and importance of your research.
  • Check submission guidelines, write clearly and concisely, and use language to “guide” readers through your abstract. 
  • The IMRaD (Introduction, Methodology, Results, and Discussion) approach is simple and effective. 
  • More and more authors are using AI to do the heavy lifting. With the right prompts, AI can save you time and create a cohesive abstract.

Writing an abstract: First steps and best practices

Keep the following in mind as you write your abstract:

  • If you’re submitting to a publication , check for specific guidelines regarding overall length, format, keywords, and the presence or absence of section headings (e.g. “Purpose”). Follow these guidelines exactly.
  • Write concisely and clearly . If you struggle to write concisely, consider using an AI-writing assistant like Wordtune . Simply select text to receive suggestions on how to write a sentence or paragraph more concisely without losing any value.
  • Make your abstract self-contained . Don’t refer to passages in your article or research. If you must include terms that your audience may not be familiar with, such as highly technical jargon or concepts borrowed from another field, offer a brief definition.
  • Use connecting phrases like “for this reason,” “as a result,” and “this led us” to “guide” the reader through your abstract and help them see the connections between your research goal, methodology, results, and conclusions. ‍
  • Read abstracts on similar studies . This gives you a good benchmark and can help you get started. If you’re submitting your abstract to a particular publication, it also gives you a good idea of the type of language and structure they prefer.

Wordtune offers suggestions to make your text clear and concise.

Get Wordtune for free > Get Wordtune for free >

How to write an abstract: The IMRaD Structure

IMRaD stands for Introduction, Methodology, Results, and Discussion (or Conclusion). 

It’s the most common way to structure a research paper and a very simple way to approach your abstract. In some cases, authors even include these section headings in their abstracts. 

Step One: Introduction

Length : About 25% of your abstract

Purpose : Provide context for your research and describe your research objectives. 

Start by introducing your topic. There are two main parts to this:

  • Your research question stated simply and straightforwardly (what missing knowledge does your study aim to answer?). You can use words like “investigate,” “review,” “test,” “analyze,” “study,” and “evaluate” to make it clear how your work relates to the context.
  • A brief overview of the academic, historical, social, or scientific context. This helps the reader understand the importance and relevance of your work. In many cases, starting with context before your research question makes more sense, so feel free to write in that order. 

Regarding context, consider the following: 

research paper using imrad format example

For example:

Psychologists and neuroscientists have long studied the role of sleep in the formation of new memories. Previous research into how sleep affects memory has often struggled because it’s difficult to measure the quality, stages, and overall impact of sleep accurately. As a result, there’s ongoing debate in the scientific community , and recent research suggests sleep may not be as important as researchers once thought. In this study, we review the evidence and offer a novel conclusion : the same mechanisms thought to mediate sleep-related memory formation also operate during waking hours, particularly quiet wakefulness. 

In this example, several contextual cues are offered: it’s a long-standing topic in the literature; previous research is limited due to a specific issue , and there is active scientific debate . The section closes with the research aims: to review the evidence and offer a new conclusion. 

Step Two: Methodology

Purpose : Clearly describe what you did and highlight novelty. 

In this section, provide a clear description of your research methodology. While it’s important to be concise, make sure you’re not being vague. Mention specific frameworks and tools. 

‍ To explore the impact of social media on political engagement, we conducted a study with 200 participants, divided into two groups. The first was exposed to curated political content on social media, while the control group received a neutral feed. Our mixed-method approach combined quantitative engagement metrics analysis and qualitative interviews to assess changes in political participation.

There’s no need to provide an in-depth justification of your approach, although if it’s a novel one, it’s worth highlighting this and explaining what makes it appropriate. For example, " We chose this approach because it offers a clearer image of the structure of proteins involved in the transfer of electrons during cellular respiration ."

Finally, you can omit methodological limitations; we’ll cover these later. 

Step Three: Results

Length : About 35% of your abstract

Purpose : Provide a clear, specific account of your results. 

This section is arguably the most important (and interesting) part of your abstract.

Explain the results of your analysis in a specific and detailed fashion. This isn’t the time to be vague or bury the lead. For example:

“Our survey indicates a marked shift in sedimentary rock composition. In three locations, we observed significant erosion, and mineralogical analysis revealed a high concentration of quartz. Further analysis suggests two major events in the past 200 years, correlating with disturbances in the region.”
"Our survey of the Redstone Canyon region identified a marked shift in sedimentary rock composition from predominantly sandstone to shale, particularly evident in the lower strata. Quantitative analysis showed a 40% increase in shale content compared to previous surveys. In three distinct locations, we observed significant erosion, with up to two meters of topsoil displacement, primarily due to water runoff. Mineralogical analysis revealed an unexpectedly high concentration of quartz (up to 22%) in these eroded areas. Additionally, our seismic retrogression analysis suggests two major seismic events in the past 200 years, correlating with the observed stratification disturbances."

Incidentally, you don’t need to include all of your findings here, only those that will help the reader to understand the next section: your discussion and conclusion (i.e., what the results mean). This will help you keep the results section concise and relevant. 

Step Four: Discussion/Conclusion

Length : About 15%

Purpose : Present what new knowledge you’ve found and why it matters.

Bearing in mind your research question, give a clear account of your conclusions. What new knowledge has been gained? 

The simplest way to do this is in the present tense: “We conclude that…”

You should also briefly explain why this matters. What are the implications of your findings? Be specific and avoid making claims that aren’t directly supported by your research. 

If there are any important limitations (such as population or control group size), you can mention them now. This helps readers assess the credibility and generalizability of your findings. 

You can use these samples for inspiration.

They are divided into introduction , methodology , results , and conclusion.

The rising urbanization rate poses challenges to mental health, an issue garnering increasing attention in recent years. This study aims to analyze the impact of urban green spaces on the mental health of city dwellers. The focus is on how access to parks and natural environments within urban settings contributes to psychological well-being . For this purpose, we employed a cross-sectional survey methodology, targeting residents in three major cities with varying levels of green space availability. We used a combination of GIS mapping to determine green space distribution and structured questionnaires to assess mental health indicators among 1,000 participants . Our results show a clear correlation between access to green spaces and improved mental health outcomes. Residents with frequent access to parks reported 30% lower stress levels and a 25% reduction in symptoms related to anxiety and depression, compared to those with limited access. Additionally, our analysis revealed that green spaces in dense urban areas had a more significant impact than those in less populated districts . We conclude that urban green spaces play a crucial role in enhancing mental health. This underscores the importance of urban planning policies that prioritize green space development as a public health strategy. These findings have significant implications for city planning and public health policy, advocating for the integration of green spaces in urban development to foster mental well-being .

The phenomenon of antibiotic resistance is a growing concern in medical science. This study investigates the effectiveness of novel synthetic peptides as potential antibiotics against multi-drug resistant bacteria. The research specifically examines the impact of these peptides on the cellular integrity and replication processes of resistant bacterial strains . Our methodology involved in vitro testing of three newly synthesized peptides against a panel of bacteria known for high resistance to conventional antibiotics. The bacterial strains included methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE). We used a combination of microbiological assays and electron microscopy to evaluate the antibacterial activity and the cellular changes induced by the peptides . The results were promising, showing that two of the three peptides effectively inhibited the growth of MRSA and VRE at low concentrations. Electron microscopy revealed significant disruption of bacterial cell walls and membranes, leading to cell lysis. These peptides also demonstrated low toxicity in preliminary mammalian cell culture tests, suggesting a high therapeutic index . Our study provides promising evidence for the use of synthetic peptides in combating antibiotic-resistant bacteria. These findings open new avenues for developing effective treatments against infections caused by drug-resistant pathogens and highlight the potential of peptide-based therapies in future pharmaceutical applications .

The integration of artificial intelligence (AI) in education is a rapidly evolving area of study. This research explores the effectiveness of AI-driven personalized learning systems in enhancing student performance in high school mathematics. The study focuses on understanding how AI customization impacts learning outcomes compared to traditional teaching methods . We conducted a randomized controlled trial involving 500 high school students from five schools, divided into two groups. The experimental group used an AI-based learning platform that adapted to each student's learning pace and style, while the control group continued with standard classroom instruction. The study measured improvements in mathematical understanding and problem-solving skills over a six-month period . The results indicated a significant improvement in the AI group, with a 40% increase in test scores and a 35% rise in problem-solving abilities compared to the control group. Additionally, students using the AI system reported higher levels of engagement and satisfaction with the learning process . In conclusion, the use of AI-driven personalized learning systems shows considerable promise in enhancing educational outcomes in mathematics. This study suggests that AI personalization can be a valuable tool in modern educational strategies, potentially revolutionizing how subjects are taught and learned in schools .

What is the main objective of an abstract?

The goal of an abstract is to provide readers with a concise overview of the purpose, methodology, results, conclusion, and importance of a longer work, such as a research paper or study. 

How long should an abstract be?

Depending on the publication, an abstract should be anywhere from 150 to 250 words. 

What should an abstract include?

An abstract should include an introduction (context + research question), the methodology, the results, and a conclusion (what you found and why it matters).

IMRaD is a simple formula you can follow to write a great abstract for any topic and publication type. Simply follow the instructions above to write each section: Introduction, Methodology, Results, and Discussion/Conclusion.

Be careful to balance detail with brevity, as abstracts are meant to be a short overview of your study. If you struggle with writing concisely and clearly, consider using a writing aid like Wordtune to handle some of the heavy lifting. 

Want to learn more key writing tips? Check out these articles:

  • How to Write Concisely and Effectively (+Examples)
  • Transition Word Examples and How to Use Them Effectively
  • How to Write a Research Paper (+Free AI Research Paper Writer)

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Much prior work has studied generative modeling of video data using a variety of methods, including recurrent networks, [^1] [^2] [^3] generative adversarial networks, [^4] [^5] [^6] [^7] autoregressive transformers, [^8] [^9] and diffusion models. [^10] [^11] [^12] These works often focus on a narrow category of visual data, on shorter videos, or on videos of a fixed size. Sora is a generalist model of visual data—it can generate videos and images spanning diverse durations, aspect ratios and resolutions, up to a full minute of high definition video.

Turning visual data into patches

We take inspiration from large language models which acquire generalist capabilities by training on internet-scale data. [^13] [^14] The success of the LLM paradigm is enabled in part by the use of tokens that elegantly unify diverse modalities of text—code, math and various natural languages. In this work, we consider how generative models of visual data can inherit such benefits. Whereas LLMs have text tokens, Sora has visual patches . Patches have previously been shown to be an effective representation for models of visual data. [^15] [^16] [^17] [^18] We find that patches are a highly-scalable and effective representation for training generative models on diverse types of videos and images.

Figure Patches

At a high level, we turn videos into patches by first compressing videos into a lower-dimensional latent space, [^19] and subsequently decomposing the representation into spacetime patches.

Video compression network

We train a network that reduces the dimensionality of visual data. [^20] This network takes raw video as input and outputs a latent representation that is compressed both temporally and spatially. Sora is trained on and subsequently generates videos within this compressed latent space. We also train a corresponding decoder model that maps generated latents back to pixel space.

Spacetime Latent Patches

Given a compressed input video, we extract a sequence of spacetime patches which act as transformer tokens. This scheme works for images too since images are just videos with a single frame. Our patch-based representation enables Sora to train on videos and images of variable resolutions, durations and aspect ratios. At inference time, we can control the size of generated videos by arranging randomly-initialized patches in an appropriately-sized grid.

Scaling transformers for video generation

Sora is a diffusion model [^21] [^22] [^23] [^24] [^25] ; given input noisy patches (and conditioning information like text prompts), it’s trained to predict the original “clean” patches. Importantly, Sora is a diffusion transformer . [^26] Transformers have demonstrated remarkable scaling properties across a variety of domains, including language modeling, [^13] [^14] computer vision, [^15] [^16] [^17] [^18] and image generation. [^27] [^28] [^29]

Figure Diffusion

In this work, we find that diffusion transformers scale effectively as video models as well. Below, we show a comparison of video samples with fixed seeds and inputs as training progresses. Sample quality improves markedly as training compute increases.

Variable durations, resolutions, aspect ratios

Past approaches to image and video generation typically resize, crop or trim videos to a standard size – e.g., 4 second videos at 256x256 resolution. We find that instead training on data at its native size provides several benefits.

Sampling flexibility

Sora can sample widescreen 1920x1080p videos, vertical 1080x1920 videos and everything inbetween. This lets Sora create content for different devices directly at their native aspect ratios. It also lets us quickly prototype content at lower sizes before generating at full resolution—all with the same model.

Improved framing and composition

We empirically find that training on videos at their native aspect ratios improves composition and framing. We compare Sora against a version of our model that crops all training videos to be square, which is common practice when training generative models. The model  trained on square crops (left) sometimes generates videos where the subject is only partially in view. In comparison, videos from Sora (right)s have improved framing.

Language understanding

Training text-to-video generation systems requires a large amount of videos with corresponding text captions. We apply the re-captioning technique introduced in DALL·E 3 [^30] to videos. We first train a highly descriptive captioner model and then use it to produce text captions for all videos in our training set. We find that training on highly descriptive video captions improves text fidelity as well as the overall quality of videos.

Similar to DALL·E 3, we also leverage GPT to turn short user prompts into longer detailed captions that are sent to the video model. This enables Sora to generate high quality videos that accurately follow user prompts.

Prompting with images and videos

All of the results above and in our landing page show text-to-video samples. But Sora can also be prompted with other inputs, such as pre-existing images or video. This capability enables Sora to perform a wide range of image and video editing tasks—creating perfectly looping video, animating static images, extending videos forwards or backwards in time, etc.

Animating DALL·E images

Sora is capable of generating videos provided an image and prompt as input. Below we show example videos generated based on DALL·E 2 [^31] and DALL·E 3 [^30] images.

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Extending generated videos

Sora is also capable of extending videos, either forward or backward in time. Below are four videos that were all extended backward in time starting from a segment of a generated video. As a result, each of the four videos starts different from the others, yet all four videos lead to the same ending.

We can use this method to extend a video both forward and backward to produce a seamless infinite loop.

Video-to-video editing

Diffusion models have enabled a plethora of methods for editing images and videos from text prompts. Below we apply one of these methods, SDEdit, [^32] to Sora. This technique enables Sora to transform  the styles and environments of input videos zero-shot.

Connecting videos

We can also use Sora to gradually interpolate between two input videos, creating seamless transitions between videos with entirely different subjects and scene compositions. In the examples below, the videos in the center interpolate between the corresponding videos on the left and right.

Image generation capabilities

Sora is also capable of generating images. We do this by arranging patches of Gaussian noise in a spatial grid with a temporal extent of one frame. The model can generate images of variable sizes—up to 2048x2048 resolution.

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Emerging simulation capabilities

We find that video models exhibit a number of interesting emergent capabilities when trained at scale. These capabilities enable Sora to simulate some aspects of people, animals and environments from the physical world. These properties emerge without any explicit inductive biases for 3D, objects, etc.—they are purely phenomena of scale.

3D consistency. Sora can generate videos with dynamic camera motion. As the camera shifts and rotates, people and scene elements move consistently through three-dimensional space.

Long-range coherence and object permanence. A significant challenge for video generation systems has been maintaining temporal consistency when sampling long videos. We find that Sora is often, though not always, able to effectively model both short- and long-range dependencies. For example, our model can persist people, animals and objects even when they are occluded or leave the frame. Likewise, it can generate multiple shots of the same character in a single sample, maintaining their appearance throughout the video.

Interacting with the world. Sora can sometimes simulate actions that affect the state of the world in simple ways. For example, a painter can leave new strokes along a canvas that persist over time, or a man can eat a burger and leave bite marks.

Simulating digital worlds. Sora is also able to simulate artificial processes–one example is video games. Sora can simultaneously control the player in Minecraft with a basic policy while also rendering the world and its dynamics in high fidelity. These capabilities can be elicited zero-shot by prompting Sora with captions mentioning “Minecraft.”

These capabilities suggest that continued scaling of video models is a promising path towards the development of highly-capable simulators of the physical and digital world, and the objects, animals and people that live within them.

Sora currently exhibits numerous limitations as a simulator. For example, it does not accurately model the physics of many basic interactions, like glass shattering. Other interactions, like eating food, do not always yield correct changes in object state. We enumerate other common failure modes of the model—such as incoherencies that develop in long duration samples or spontaneous appearances of objects—in our landing page .

We believe the capabilities Sora has today demonstrate that continued scaling of video models is a promising path towards the development of capable simulators of the physical and digital world, and the objects, animals and people that live within them.

  • Bill Peebles
  • Connor Holmes
  • David Schnurr
  • Troy Luhman
  • Eric Luhman
  • Clarence Wing Yin Ng
  • Aditya Ramesh

Acknowledgments

Please cite as OpenAI et al., and use the following bibtex for citation:  https://openai.com/bibtex/videoworldsimulators2024.bib

  • Newsletters

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

  • Will Douglas Heaven archive page

OpenAI has built a striking new generative video model called Sora that can take a short text description and turn it into a detailed, high-definition film clip up to a minute long.

Based on four sample videos that OpenAI shared with MIT Technology Review ahead of today’s announcement, the San Francisco–based firm has pushed the envelope of what’s possible with text-to-video generation (a hot new research direction that we flagged as a trend to watch in 2024 ).

“We think building models that can understand video, and understand all these very complex interactions of our world, is an important step for all future AI systems,” says Tim Brooks, a scientist at OpenAI.

But there’s a disclaimer. OpenAI gave us a preview of Sora (which means sky in Japanese) under conditions of strict secrecy. In an unusual move, the firm would only share information about Sora if we agreed to wait until after news of the model was made public to seek the opinions of outside experts. [Editor’s note: We’ve updated this story with outside comment below.] OpenAI has not released a technical report or demonstrated the model actually working. And it says it won’t be releasing Sora anytime soon.

The first generative models that could produce video from snippets of text appeared in late 2022. But early examples from Meta , Google, and a startup called Runway were glitchy and grainy. Since then, the tech has been getting better fast. Runway’s gen-2 model, released last year, can produce short clips that come close to matching big-studio animation in their quality. But most of these examples are still only a few seconds long.  

The sample videos from OpenAI’s Sora are high-definition and full of detail. OpenAI also says it can generate videos up to a minute long. One video of a Tokyo street scene shows that Sora has learned how objects fit together in 3D: the camera swoops into the scene to follow a couple as they walk past a row of shops.

OpenAI also claims that Sora handles occlusion well. One problem with existing models is that they can fail to keep track of objects when they drop out of view. For example, if a truck passes in front of a street sign, the sign might not reappear afterward.  

In a video of a papercraft underwater scene, Sora has added what look like cuts between different pieces of footage, and the model has maintained a consistent style between them.

It’s not perfect. In the Tokyo video, cars to the left look smaller than the people walking beside them. They also pop in and out between the tree branches. “There’s definitely some work to be done in terms of long-term coherence,” says Brooks. “For example, if someone goes out of view for a long time, they won’t come back. The model kind of forgets that they were supposed to be there.”

Impressive as they are, the sample videos shown here were no doubt cherry-picked to show Sora at its best. Without more information, it is hard to know how representative they are of the model’s typical output.   

It may be some time before we find out. OpenAI’s announcement of Sora today is a tech tease, and the company says it has no current plans to release it to the public. Instead, OpenAI will today begin sharing the model with third-party safety testers for the first time.

In particular, the firm is worried about the potential misuses of fake but photorealistic video . “We’re being careful about deployment here and making sure we have all our bases covered before we put this in the hands of the general public,” says Aditya Ramesh, a scientist at OpenAI, who created the firm’s text-to-image model DALL-E .

But OpenAI is eyeing a product launch sometime in the future. As well as safety testers, the company is also sharing the model with a select group of video makers and artists to get feedback on how to make Sora as useful as possible to creative professionals. “The other goal is to show everyone what is on the horizon, to give a preview of what these models will be capable of,” says Ramesh.

To build Sora, the team adapted the tech behind DALL-E 3, the latest version of OpenAI’s flagship text-to-image model. Like most text-to-image models, DALL-E 3 uses what’s known as a diffusion model. These are trained to turn a fuzz of random pixels into a picture.

Sora takes this approach and applies it to videos rather than still images. But the researchers also added another technique to the mix. Unlike DALL-E or most other generative video models, Sora combines its diffusion model with a type of neural network called a transformer.

Transformers are great at processing long sequences of data, like words. That has made them the special sauce inside large language models like OpenAI’s GPT-4 and Google DeepMind’s Gemini . But videos are not made of words. Instead, the researchers had to find a way to cut videos into chunks that could be treated as if they were. The approach they came up with was to dice videos up across both space and time. “It’s like if you were to have a stack of all the video frames and you cut little cubes from it,” says Brooks.

The transformer inside Sora can then process these chunks of video data in much the same way that the transformer inside a large language model processes words in a block of text. The researchers say that this let them train Sora on many more types of video than other text-to-video models, varied in terms of resolution, duration, aspect ratio, and orientation. “It really helps the model,” says Brooks. “That is something that we’re not aware of any existing work on.”

“From a technical perspective it seems like a very significant leap forward,” says Sam Gregory, executive director at Witness, a human rights organization that specializes in the use and misuse of video technology. “But there are two sides to the coin,” he says. “The expressive capabilities offer the potential for many more people to be storytellers using video. And there are also real potential avenues for misuse.” 

OpenAI is well aware of the risks that come with a generative video model. We are already seeing the large-scale misuse of deepfake images . Photorealistic video takes this to another level.

Gregory notes that you could use technology like this to misinform people about conflict zones or protests. The range of styles is also interesting, he says. If you could generate shaky footage that looked like something shot with a phone, it would come across as more authentic.

The tech is not there yet, but generative video has gone from zero to Sora in just 18 months. “We’re going to be entering a universe where there will be fully synthetic content, human-generated content and a mix of the two,” says Gregory.

The OpenAI team plans to draw on the safety testing it did last year for DALL-E 3. Sora already includes a filter that runs on all prompts sent to the model that will block requests for violent, sexual, or hateful images, as well as images of known people. Another filter will look at frames of generated videos and block material that violates OpenAI’s safety policies.

OpenAI says it is also adapting a fake-image detector developed for DALL-E 3 to use with Sora. And the company will embed industry-standard C2PA tags , metadata that states how an image was generated, into all of Sora’s output. But these steps are far from foolproof. Fake-image detectors are hit-or-miss. Metadata is easy to remove, and most social media sites strip it from uploaded images by default.  

“We’ll definitely need to get more feedback and learn more about the types of risks that need to be addressed with video before it would make sense for us to release this,” says Ramesh.

Brooks agrees. “Part of the reason that we’re talking about this research now is so that we can start getting the input that we need to do the work necessary to figure out how it could be safely deployed,” he says.

Update 2/15: Comments from Sam Gregory were added .

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