research relevant findings

• Affiliate Program

• UNITED STATES
• 台灣 (TAIWAN)
• TÜRKIYE (TURKEY)
• Academic Editing Services
• - Research Paper
• - Journal Manuscript
• - Dissertation
• - College & University Assignments
• Admissions Editing Services
• - Application Essay
• - Personal Statement
• - Recommendation Letter
• - Cover Letter
• - CV/Resume
• Business Editing Services
• - Business Documents
• - Report & Brochure
• - Website & Blog
• Writer Editing Services
• - Script & Screenplay
• Our Editors
• Client Reviews
• Editing & Proofreading Prices
• Wordvice Points
• Partner Discount
• Plagiarism Checker
• APA Citation Generator
• MLA Citation Generator
• Chicago Citation Generator
• Vancouver Citation Generator
• - APA Style
• - MLA Style
• - Chicago Style
• - Vancouver Style
• Writing & Editing Guide
• Academic Resources
• Admissions Resources

How to Write the Results/Findings Section in Research

What is the research paper Results section and what does it do?

The Results section of a scientific research paper represents the core findings of a study derived from the methods applied to gather and analyze information. It presents these findings in a logical sequence without bias or interpretation from the author, setting up the reader for later interpretation and evaluation in the Discussion section. A major purpose of the Results section is to break down the data into sentences that show its significance to the research question(s).

The Results section appears third in the section sequence in most scientific papers. It follows the presentation of the Methods and Materials and is presented before the Discussion section —although the Results and Discussion are presented together in many journals. This section answers the basic question “What did you find in your research?”

What is included in the Results section?

The Results section should include the findings of your study and ONLY the findings of your study. The findings include:

• Data presented in tables, charts, graphs, and other figures (may be placed into the text or on separate pages at the end of the manuscript)
• A contextual analysis of this data explaining its meaning in sentence form
• All data that corresponds to the central research question(s)
• All secondary findings (secondary outcomes, subgroup analyses, etc.)

If the scope of the study is broad, or if you studied a variety of variables, or if the methodology used yields a wide range of different results, the author should present only those results that are most relevant to the research question stated in the Introduction section .

As a general rule, any information that does not present the direct findings or outcome of the study should be left out of this section. Unless the journal requests that authors combine the Results and Discussion sections, explanations and interpretations should be omitted from the Results.

How are the results organized?

The best way to organize your Results section is “logically.” One logical and clear method of organizing research results is to provide them alongside the research questions—within each research question, present the type of data that addresses that research question.

Let’s look at an example. Your research question is based on a survey among patients who were treated at a hospital and received postoperative care. Let’s say your first research question is:

“What do hospital patients over age 55 think about postoperative care?”

This can actually be represented as a heading within your Results section, though it might be presented as a statement rather than a question:

Attitudes towards postoperative care in patients over the age of 55

Now present the results that address this specific research question first. In this case, perhaps a table illustrating data from a survey. Likert items can be included in this example. Tables can also present standard deviations, probabilities, correlation matrices, etc.

Following this, present a content analysis, in words, of one end of the spectrum of the survey or data table. In our example case, start with the POSITIVE survey responses regarding postoperative care, using descriptive phrases. For example:

“Sixty-five percent of patients over 55 responded positively to the question “ Are you satisfied with your hospital’s postoperative care ?” (Fig. 2)

Include other results such as subcategory analyses. The amount of textual description used will depend on how much interpretation of tables and figures is necessary and how many examples the reader needs in order to understand the significance of your research findings.

Next, present a content analysis of another part of the spectrum of the same research question, perhaps the NEGATIVE or NEUTRAL responses to the survey. For instance:

  “As Figure 1 shows, 15 out of 60 patients in Group A responded negatively to Question 2.”

After you have assessed the data in one figure and explained it sufficiently, move on to your next research question. For example:

  “How does patient satisfaction correspond to in-hospital improvements made to postoperative care?”

This kind of data may be presented through a figure or set of figures (for instance, a paired T-test table).

Explain the data you present, here in a table, with a concise content analysis:

“The p-value for the comparison between the before and after groups of patients was .03% (Fig. 2), indicating that the greater the dissatisfaction among patients, the more frequent the improvements that were made to postoperative care.”

Let’s examine another example of a Results section from a study on plant tolerance to heavy metal stress . In the Introduction section, the aims of the study are presented as “determining the physiological and morphological responses of Allium cepa L. towards increased cadmium toxicity” and “evaluating its potential to accumulate the metal and its associated environmental consequences.” The Results section presents data showing how these aims are achieved in tables alongside a content analysis, beginning with an overview of the findings:

“Cadmium caused inhibition of root and leave elongation, with increasing effects at higher exposure doses (Fig. 1a-c).”

The figure containing this data is cited in parentheses. Note that this author has combined three graphs into one single figure. Separating the data into separate graphs focusing on specific aspects makes it easier for the reader to assess the findings, and consolidating this information into one figure saves space and makes it easy to locate the most relevant results.

Following this overall summary, the relevant data in the tables is broken down into greater detail in text form in the Results section.

• “Results on the bio-accumulation of cadmium were found to be the highest (17.5 mg kgG1) in the bulb, when the concentration of cadmium in the solution was 1×10G2 M and lowest (0.11 mg kgG1) in the leaves when the concentration was 1×10G3 M.”

Captioning and Referencing Tables and Figures

Tables and figures are central components of your Results section and you need to carefully think about the most effective way to use graphs and tables to present your findings . Therefore, it is crucial to know how to write strong figure captions and to refer to them within the text of the Results section.

The most important advice one can give here as well as throughout the paper is to check the requirements and standards of the journal to which you are submitting your work. Every journal has its own design and layout standards, which you can find in the author instructions on the target journal’s website. Perusing a journal’s published articles will also give you an idea of the proper number, size, and complexity of your figures.

Regardless of which format you use, the figures should be placed in the order they are referenced in the Results section and be as clear and easy to understand as possible. If there are multiple variables being considered (within one or more research questions), it can be a good idea to split these up into separate figures. Subsequently, these can be referenced and analyzed under separate headings and paragraphs in the text.

To create a caption, consider the research question being asked and change it into a phrase. For instance, if one question is “Which color did participants choose?”, the caption might be “Color choice by participant group.” Or in our last research paper example, where the question was “What is the concentration of cadmium in different parts of the onion after 14 days?” the caption reads:

 “Fig. 1(a-c): Mean concentration of Cd determined in (a) bulbs, (b) leaves, and (c) roots of onions after a 14-day period.”

Steps for Composing the Results Section

Because each study is unique, there is no one-size-fits-all approach when it comes to designing a strategy for structuring and writing the section of a research paper where findings are presented. The content and layout of this section will be determined by the specific area of research, the design of the study and its particular methodologies, and the guidelines of the target journal and its editors. However, the following steps can be used to compose the results of most scientific research studies and are essential for researchers who are new to preparing a manuscript for publication or who need a reminder of how to construct the Results section.

Step 1 : Consult the guidelines or instructions that the target journal or publisher provides authors and read research papers it has published, especially those with similar topics, methods, or results to your study.

• The guidelines will generally outline specific requirements for the results or findings section, and the published articles will provide sound examples of successful approaches.
• Note length limitations on restrictions on content. For instance, while many journals require the Results and Discussion sections to be separate, others do not—qualitative research papers often include results and interpretations in the same section (“Results and Discussion”).
• Reading the aims and scope in the journal’s “ guide for authors ” section and understanding the interests of its readers will be invaluable in preparing to write the Results section.

Step 2 : Consider your research results in relation to the journal’s requirements and catalogue your results.

• Focus on experimental results and other findings that are especially relevant to your research questions and objectives and include them even if they are unexpected or do not support your ideas and hypotheses.
• Catalogue your findings—use subheadings to streamline and clarify your report. This will help you avoid excessive and peripheral details as you write and also help your reader understand and remember your findings. Create appendices that might interest specialists but prove too long or distracting for other readers.
• Decide how you will structure of your results. You might match the order of the research questions and hypotheses to your results, or you could arrange them according to the order presented in the Methods section. A chronological order or even a hierarchy of importance or meaningful grouping of main themes or categories might prove effective. Consider your audience, evidence, and most importantly, the objectives of your research when choosing a structure for presenting your findings.

Step 3 : Design figures and tables to present and illustrate your data.

• Tables and figures should be numbered according to the order in which they are mentioned in the main text of the paper.
• Information in figures should be relatively self-explanatory (with the aid of captions), and their design should include all definitions and other information necessary for readers to understand the findings without reading all of the text.
• Use tables and figures as a focal point to tell a clear and informative story about your research and avoid repeating information. But remember that while figures clarify and enhance the text, they cannot replace it.

Step 4 : Draft your Results section using the findings and figures you have organized.

• The goal is to communicate this complex information as clearly and precisely as possible; precise and compact phrases and sentences are most effective.
• In the opening paragraph of this section, restate your research questions or aims to focus the reader’s attention to what the results are trying to show. It is also a good idea to summarize key findings at the end of this section to create a logical transition to the interpretation and discussion that follows.
• Try to write in the past tense and the active voice to relay the findings since the research has already been done and the agent is usually clear. This will ensure that your explanations are also clear and logical.
• Make sure that any specialized terminology or abbreviation you have used here has been defined and clarified in the  Introduction section .

Step 5 : Review your draft; edit and revise until it reports results exactly as you would like to have them reported to your readers.

• Double-check the accuracy and consistency of all the data, as well as all of the visual elements included.
• Read your draft aloud to catch language errors (grammar, spelling, and mechanics), awkward phrases, and missing transitions.
• Ensure that your results are presented in the best order to focus on objectives and prepare readers for interpretations, valuations, and recommendations in the Discussion section . Look back over the paper’s Introduction and background while anticipating the Discussion and Conclusion sections to ensure that the presentation of your results is consistent and effective.
• Consider seeking additional guidance on your paper. Find additional readers to look over your Results section and see if it can be improved in any way. Peers, professors, or qualified experts can provide valuable insights.

One excellent option is to use a professional English proofreading and editing service  such as Wordvice, including our paper editing service . With hundreds of qualified editors from dozens of scientific fields, Wordvice has helped thousands of authors revise their manuscripts and get accepted into their target journals. Read more about the  proofreading and editing process  before proceeding with getting academic editing services and manuscript editing services for your manuscript.

As the representation of your study’s data output, the Results section presents the core information in your research paper. By writing with clarity and conciseness and by highlighting and explaining the crucial findings of their study, authors increase the impact and effectiveness of their research manuscripts.

For more articles and videos on writing your research manuscript, visit Wordvice’s Resources page.

Wordvice Resources

• How to Write a Research Paper Introduction 
• Which Verb Tenses to Use in a Research Paper
• How to Write an Abstract for a Research Paper
• How to Write a Research Paper Title
• Useful Phrases for Academic Writing
• Common Transition Terms in Academic Papers
• Active and Passive Voice in Research Papers
• 100+ Verbs That Will Make Your Research Writing Amazing
• Tips for Paraphrasing in Research Papers

• How it works

How to Write the Dissertation Findings or Results – Steps & Tips

Published by Grace Graffin at August 11th, 2021 , Revised On October 9, 2023

Each  part of the dissertation is unique, and some general and specific rules must be followed. The dissertation’s findings section presents the key results of your research without interpreting their meaning .

Theoretically, this is an exciting section of a dissertation because it involves writing what you have observed and found. However, it can be a little tricky if there is too much information to confuse the readers.

The goal is to include only the essential and relevant findings in this section. The results must be presented in an orderly sequence to provide clarity to the readers.

This section of the dissertation should be easy for the readers to follow, so you should avoid going into a lengthy debate over the interpretation of the results.

It is vitally important to focus only on clear and precise observations. The findings chapter of the  dissertation  is theoretically the easiest to write.

It includes  statistical analysis and a brief write-up about whether or not the results emerging from the analysis are significant. This segment should be written in the past sentence as you describe what you have done in the past.

This article will provide detailed information about  how to   write the findings of a dissertation .

When to Write Dissertation Findings Chapter

As soon as you have gathered and analysed your data, you can start to write up the findings chapter of your dissertation paper. Remember that it is your chance to report the most notable findings of your research work and relate them to the research hypothesis  or  research questions set out in  the introduction chapter of the dissertation .

You will be required to separately report your study’s findings before moving on to the discussion chapter  if your dissertation is based on the  collection of primary data  or experimental work.

However, you may not be required to have an independent findings chapter if your dissertation is purely descriptive and focuses on the analysis of case studies or interpretation of texts.

• Always report the findings of your research in the past tense.
• The dissertation findings chapter varies from one project to another, depending on the data collected and analyzed.
• Avoid reporting results that are not relevant to your research questions or research hypothesis.

Does your Dissertation Have the Following?

• Great Research/Sources
• Perfect Language
• Accurate Sources

If not, we can help. Our panel of experts makes sure to keep the 3 pillars of the Dissertation strong.

1. Reporting Quantitative Findings

The best way to present your quantitative findings is to structure them around the research  hypothesis or  questions you intend to address as part of your dissertation project.

Report the relevant findings for each research question or hypothesis, focusing on how you analyzed them.

Analysis of your findings will help you determine how they relate to the different research questions and whether they support the hypothesis you formulated.

While you must highlight meaningful relationships, variances, and tendencies, it is important not to guess their interpretations and implications because this is something to save for the discussion  and  conclusion  chapters.

Any findings not directly relevant to your research questions or explanations concerning the data collection process  should be added to the dissertation paper’s appendix section.

Use of Figures and Tables in Dissertation Findings

Suppose your dissertation is based on quantitative research. In that case, it is important to include charts, graphs, tables, and other visual elements to help your readers understand the emerging trends and relationships in your findings.

Repeating information will give the impression that you are short on ideas. Refer to all charts, illustrations, and tables in your writing but avoid recurrence.

The text should be used only to elaborate and summarize certain parts of your results. On the other hand, illustrations and tables are used to present multifaceted data.

It is recommended to give descriptive labels and captions to all illustrations used so the readers can figure out what each refers to.

How to Report Quantitative Findings

Here is an example of how to report quantitative results in your dissertation findings chapter;

Two hundred seventeen participants completed both the pretest and post-test and a Pairwise T-test was used for the analysis. The quantitative data analysis reveals a statistically significant difference between the mean scores of the pretest and posttest scales from the Teachers Discovering Computers course. The pretest mean was 29.00 with a standard deviation of 7.65, while the posttest mean was 26.50 with a standard deviation of 9.74 (Table 1). These results yield a significance level of .000, indicating a strong treatment effect (see Table 3). With the correlation between the scores being .448, the little relationship is seen between the pretest and posttest scores (Table 2). This leads the researcher to conclude that the impact of the course on the educators’ perception and integration of technology into the curriculum is dramatic.

Paired Samples

Paired samples correlation, paired samples test.

Also Read: How to Write the Abstract for the Dissertation.

2. Reporting Qualitative Findings

A notable issue with reporting qualitative findings is that not all results directly relate to your research questions or hypothesis.

The best way to present the results of qualitative research is to frame your findings around the most critical areas or themes you obtained after you examined the data.

In-depth data analysis will help you observe what the data shows for each theme. Any developments, relationships, patterns, and independent responses directly relevant to your research question or hypothesis should be mentioned to the readers.

Additional information not directly relevant to your research can be included in the appendix .

How to Report Qualitative Findings

Here is an example of how to report qualitative results in your dissertation findings chapter;

How do I report quantitative findings?

The best way to present your quantitative findings is to structure them around the  research hypothesis  or  research questions  you intended to address as part of your dissertation project. Report the relevant findings for each of the research questions or hypotheses, focusing on how you analyzed them.

How do I report qualitative findings?

The best way to present the  qualitative research  results is to frame your findings around the most important areas or themes that you obtained after examining the data.

An in-depth analysis of the data will help you observe what the data is showing for each theme. Any developments, relationships, patterns, and independent responses that are directly relevant to your  research question  or  hypothesis  should be clearly mentioned for the readers.

Can I use interpretive phrases like ‘it confirms’ in the finding chapter?

No, It is highly advisable to avoid using interpretive and subjective phrases in the finding chapter. These terms are more suitable for the  discussion chapter , where you will be expected to provide your interpretation of the results in detail.

Can I report the results from other research papers in my findings chapter?

NO, you must not be presenting results from other research studies in your findings.

You May Also Like

Dissertation discussion is where you explore the relevance and significance of results. Here are guidelines to help you write the perfect discussion chapter.

Table of contents is an essential part of dissertation paper. Here is all you need to know about how to create the best table of contents for dissertation.

Here are the steps to make a theoretical framework for dissertation. You can define, discuss and evaluate theories relevant to the research problem.

USEFUL LINKS

LEARNING RESOURCES

COMPANY DETAILS

• How It Works

The Ultimate Guide to Crafting Impactful Recommendations in Research

Are you ready to take your research to the next level? Crafting impactful recommendations is the key to unlocking the full potential of your study. By providing clear, actionable suggestions based on your findings, you can bridge the gap between research and real-world application.

In this ultimate guide, we'll show you how to write recommendations that make a difference in your research report or paper.

You'll learn how to craft specific, actionable recommendations that connect seamlessly with your research findings. Whether you're a student, writer, teacher, or journalist, this guide will help you master the art of writing recommendations in research. Let's get started and make your research count!

Understanding the Purpose of Recommendations

Recommendations in research serve as a vital bridge between your findings and their real-world applications. They provide specific, action-oriented suggestions to guide future studies and decision-making processes. Let's dive into the key purposes of crafting effective recommendations:

Guiding Future Research

Research recommendations play a crucial role in steering scholars and researchers towards promising avenues of exploration. By highlighting gaps in current knowledge and proposing new research questions, recommendations help advance the field and drive innovation.

Influencing Decision-Making

Well-crafted recommendations have the power to shape policies, programs, and strategies across various domains, such as:

• Policy-making
• Product development
• Marketing strategies
• Medical practice

By providing clear, evidence-based suggestions, recommendations facilitate informed decision-making and improve outcomes.

Connecting Research to Practice

Recommendations act as a conduit for transferring knowledge from researchers to practitioners, policymakers, and stakeholders. They bridge the gap between academic findings and their practical applications, ensuring that research insights are effectively translated into real-world solutions.

Enhancing Research Impact

By crafting impactful recommendations, you can amplify the reach and influence of your research, attracting attention from peers, funding agencies, and decision-makers.

Addressing Limitations

Recommendations provide an opportunity to acknowledge and address the limitations of your study. By suggesting concrete and actionable possibilities for future research, you demonstrate a thorough understanding of your work's scope and potential areas for improvement.

Identifying Areas for Future Research

Discovering research gaps is a crucial step in crafting impactful recommendations. It involves reviewing existing studies and identifying unanswered questions or problems that warrant further investigation. Here are some strategies to help you identify areas for future research:

Explore Research Limitations

Take a close look at the limitations section of relevant studies. These limitations often provide valuable insights into potential areas for future research. Consider how addressing these limitations could enhance our understanding of the topic at hand.

Critically Analyze Discussion and Future Research Sections

When reading articles, pay special attention to the discussion and future research sections. These sections often highlight gaps in the current knowledge base and propose avenues for further exploration. Take note of any recurring themes or unanswered questions that emerge across multiple studies.

Utilize Targeted Search Terms

To streamline your search for research gaps, use targeted search terms such as "literature gap" or "future research" in combination with your subject keywords. This approach can help you quickly identify articles that explicitly discuss areas for future investigation.

Seek Guidance from Experts

Don't hesitate to reach out to your research advisor or other experts in your field. Their wealth of knowledge and experience can provide valuable insights into potential research gaps and emerging trends.

By employing these strategies, you'll be well-equipped to identify research gaps and craft recommendations that push the boundaries of current knowledge. Remember, the goal is to refine your research questions and focus your efforts on areas where more understanding is needed.

Structuring Your Recommendations

When it comes to structuring your recommendations, it's essential to keep them concise, organized, and tailored to your audience. Here are some key tips to help you craft impactful recommendations:

Prioritize and Organize

• Limit your recommendations to the most relevant and targeted suggestions for your peers or colleagues in the field.
• Place your recommendations at the end of the report, as they are often top of mind for readers.
• Write your recommendations in order of priority, with the most important ones for decision-makers coming first.

Use a Clear and Actionable Format

• Write recommendations in a clear, concise manner using actionable words derived from the data analyzed in your research.
• Use bullet points instead of long paragraphs for clarity and readability.
• Ensure that your recommendations are specific, measurable, attainable, relevant, and timely (SMART).

Connect Recommendations to Research

By following this simple formula, you can ensure that your recommendations are directly connected to your research and supported by a clear rationale.

Tailor to Your Audience

• Consider the needs and interests of your target audience when crafting your recommendations.
• Explain how your recommendations can solve the issues explored in your research.
• Acknowledge any limitations or constraints of your study that may impact the implementation of your recommendations.

Avoid Common Pitfalls

• Don't undermine your own work by suggesting incomplete or unnecessary recommendations.
• Avoid using recommendations as a place for self-criticism or introducing new information not covered in your research.
• Ensure that your recommendations are achievable and comprehensive, offering practical solutions for the issues considered in your paper.

By structuring your recommendations effectively, you can enhance the reliability and validity of your research findings, provide valuable strategies and suggestions for future research, and deliver impactful solutions to real-world problems.

Crafting Actionable and Specific Recommendations

Crafting actionable and specific recommendations is the key to ensuring your research findings have a real-world impact. Here are some essential tips to keep in mind:

Embrace Flexibility and Feasibility

Your recommendations should be open to discussion and new information, rather than being set in stone. Consider the following:

• Be realistic and considerate of your team's capabilities when making recommendations.
• Prioritize recommendations based on impact and reach, but be prepared to adjust based on team effort levels.
• Focus on solutions that require the fewest changes first, adopting an MVP (Minimum Viable Product) approach.

Provide Detailed and Justified Recommendations

To avoid vagueness and misinterpretation, ensure your recommendations are:

• Detailed, including photos, videos, or screenshots whenever possible.
• Justified based on research findings, providing alternatives when findings don't align with expectations or business goals.

Use this formula when writing recommendations:

Observed problem/pain point/unmet need + consequence + potential solution

Adopt a Solution-Oriented Approach

Foster collaboration and participation.

• Promote staff education on current research and create strategies to encourage adoption of promising clinical protocols.
• Include representatives from the treatment community in the development of the research initiative and the review of proposals.
• Require active, early, and permanent participation of treatment staff in the development, implementation, and interpretation of the study.

Tailor Recommendations to the Opportunity

When writing recommendations for a specific opportunity or program:

• Highlight the strengths and qualifications of the researcher.
• Provide specific examples of their work and accomplishments.
• Explain how their research has contributed to the field.
• Emphasize the researcher's potential for future success and their unique contributions.

By following these guidelines, you'll craft actionable and specific recommendations that drive meaningful change and showcase the value of your research.

Connecting Recommendations with Research Findings

Connecting your recommendations with research findings is crucial for ensuring the credibility and impact of your suggestions. Here's how you can seamlessly link your recommendations to the evidence uncovered in your study:

Grounding Recommendations in Research

Your recommendations should be firmly rooted in the data and insights gathered during your research process. Avoid including measures or suggestions that were not discussed or supported by your study findings. This approach ensures that your recommendations are evidence-based and directly relevant to the research at hand.

Highlighting the Significance of Collaboration

Research collaborations offer a wealth of benefits that can enhance an agency's competitive position. Consider the following factors when discussing the importance of collaboration in your recommendations:

• Organizational Development: Participation in research collaborations depends on an agency's stage of development, compatibility with its mission and culture, and financial stability.
• Trust-Building: Long-term collaboration success often hinges on a history of increasing involvement and trust between partners.
• Infrastructure: A permanent infrastructure that facilitates long-term development is key to successful collaborative programs.

Emphasizing Commitment and Participation

Fostering quality improvement and organizational learning.

In your recommendations, highlight the importance of enhancing quality improvement strategies and fostering organizational learning. Show sensitivity to the needs and constraints of community-based programs, as this understanding is crucial for effective collaboration and implementation.

Addressing Limitations and Implications

If not already addressed in the discussion section, your recommendations should mention the limitations of the study and their implications. Examples of limitations include:

• Sample size or composition
• Participant attrition
• Study duration

By acknowledging these limitations, you demonstrate a comprehensive understanding of your research and its potential impact.

By connecting your recommendations with research findings, you provide a solid foundation for your suggestions, emphasize the significance of collaboration, and showcase the potential for future research and practical applications.

Crafting impactful recommendations is a vital skill for any researcher looking to bridge the gap between their findings and real-world applications. By understanding the purpose of recommendations, identifying areas for future research, structuring your suggestions effectively, and connecting them to your research findings, you can unlock the full potential of your study. Remember to prioritize actionable, specific, and evidence-based recommendations that foster collaboration and drive meaningful change.

As you embark on your research journey, embrace the power of well-crafted recommendations to amplify the impact of your work. By following the guidelines outlined in this ultimate guide, you'll be well-equipped to write recommendations that resonate with your audience, inspire further investigation, and contribute to the advancement of your field. So go forth, make your research count, and let your recommendations be the catalyst for positive change.

Q: What are the steps to formulating recommendations in research? A: To formulate recommendations in research, you should first gain a thorough understanding of the research question. Review the existing literature to inform your recommendations and consider the research methods that were used. Identify which data collection techniques were employed and propose suitable data analysis methods. It's also essential to consider any limitations and ethical considerations of your research. Justify your recommendations clearly and finally, provide a summary of your recommendations.

Q: Why are recommendations significant in research studies? A: Recommendations play a crucial role in research as they form a key part of the analysis phase. They provide specific suggestions for interventions or strategies that address the problems and limitations discovered during the study. Recommendations are a direct response to the main findings derived from data collection and analysis, and they can guide future actions or research.

Q: Can you outline the seven steps involved in writing a research paper? A: Certainly. The seven steps to writing an excellent research paper include:

• Allowing yourself sufficient time to complete the paper.
• Defining the scope of your essay and crafting a clear thesis statement.
• Conducting a thorough yet focused search for relevant research materials.
• Reading the research materials carefully and taking detailed notes.
• Writing your paper based on the information you've gathered and analyzed.
• Editing your paper to ensure clarity, coherence, and correctness.
• Submitting your paper following the guidelines provided.

Q: What tips can help make a research paper more effective? A: To enhance the effectiveness of a research paper, plan for the extensive process ahead and understand your audience. Decide on the structure your research writing will take and describe your methodology clearly. Write in a straightforward and clear manner, avoiding the use of clichés or overly complex language.

Sign up for more like this.

• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

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

The purpose of the discussion section is to interpret and describe the significance of your findings in relation to what was already known about the research problem being investigated and to explain any new understanding or insights that emerged as a result of your research. The discussion will always connect to the introduction by way of the research questions or hypotheses you posed and the literature you reviewed, but the discussion does not simply repeat or rearrange the first parts of your paper; the discussion clearly explains how your study advanced the reader's understanding of the research problem from where you left them at the end of your review of prior research.

Annesley, Thomas M. “The Discussion Section: Your Closing Argument.” Clinical Chemistry 56 (November 2010): 1671-1674; Peacock, Matthew. “Communicative Moves in the Discussion Section of Research Articles.” System 30 (December 2002): 479-497.

Importance of a Good Discussion

The discussion section is often considered the most important part of your research paper because it:

• Most effectively demonstrates your ability as a researcher to think critically about an issue, to develop creative solutions to problems based upon a logical synthesis of the findings, and to formulate a deeper, more profound understanding of the research problem under investigation;
• Presents the underlying meaning of your research, notes possible implications in other areas of study, and explores possible improvements that can be made in order to further develop the concerns of your research;
• Highlights the importance of your study and how it can contribute to understanding the research problem within the field of study;
• Presents how the findings from your study revealed and helped fill gaps in the literature that had not been previously exposed or adequately described; and,
• Engages the reader in thinking critically about issues based on an evidence-based interpretation of findings; it is not governed strictly by objective reporting of information.

Annesley Thomas M. “The Discussion Section: Your Closing Argument.” Clinical Chemistry 56 (November 2010): 1671-1674; Bitchener, John and Helen Basturkmen. “Perceptions of the Difficulties of Postgraduate L2 Thesis Students Writing the Discussion Section.” Journal of English for Academic Purposes 5 (January 2006): 4-18; Kretchmer, Paul. Fourteen Steps to Writing an Effective Discussion Section. San Francisco Edit, 2003-2008.

Structure and Writing Style

I.  General Rules

These are the general rules you should adopt when composing your discussion of the results :

• Do not be verbose or repetitive; be concise and make your points clearly
• Avoid the use of jargon or undefined technical language
• Follow a logical stream of thought; in general, interpret and discuss the significance of your findings in the same sequence you described them in your results section [a notable exception is to begin by highlighting an unexpected result or a finding that can grab the reader's attention]
• Use the present verb tense, especially for established facts; however, refer to specific works or prior studies in the past tense
• If needed, use subheadings to help organize your discussion or to categorize your interpretations into themes

II.  The Content

The content of the discussion section of your paper most often includes :

• Explanation of results : Comment on whether or not the results were expected for each set of findings; go into greater depth to explain findings that were unexpected or especially profound. If appropriate, note any unusual or unanticipated patterns or trends that emerged from your results and explain their meaning in relation to the research problem.
• References to previous research : Either compare your results with the findings from other studies or use the studies to support a claim. This can include re-visiting key sources already cited in your literature review section, or, save them to cite later in the discussion section if they are more important to compare with your results instead of being a part of the general literature review of prior research used to provide context and background information. Note that you can make this decision to highlight specific studies after you have begun writing the discussion section.
• Deduction : A claim for how the results can be applied more generally. For example, describing lessons learned, proposing recommendations that can help improve a situation, or highlighting best practices.
• Hypothesis : A more general claim or possible conclusion arising from the results [which may be proved or disproved in subsequent research]. This can be framed as new research questions that emerged as a consequence of your analysis.

III.  Organization and Structure

Keep the following sequential points in mind as you organize and write the discussion section of your paper:

• Think of your discussion as an inverted pyramid. Organize the discussion from the general to the specific, linking your findings to the literature, then to theory, then to practice [if appropriate].
• Use the same key terms, narrative style, and verb tense [present] that you used when describing the research problem in your introduction.
• Begin by briefly re-stating the research problem you were investigating and answer all of the research questions underpinning the problem that you posed in the introduction.
• Describe the patterns, principles, and relationships shown by each major findings and place them in proper perspective. The sequence of this information is important; first state the answer, then the relevant results, then cite the work of others. If appropriate, refer the reader to a figure or table to help enhance the interpretation of the data [either within the text or as an appendix].
• Regardless of where it's mentioned, a good discussion section includes analysis of any unexpected findings. This part of the discussion should begin with a description of the unanticipated finding, followed by a brief interpretation as to why you believe it appeared and, if necessary, its possible significance in relation to the overall study. If more than one unexpected finding emerged during the study, describe each of them in the order they appeared as you gathered or analyzed the data. As noted, the exception to discussing findings in the same order you described them in the results section would be to begin by highlighting the implications of a particularly unexpected or significant finding that emerged from the study, followed by a discussion of the remaining findings.
• Before concluding the discussion, identify potential limitations and weaknesses if you do not plan to do so in the conclusion of the paper. Comment on their relative importance in relation to your overall interpretation of the results and, if necessary, note how they may affect the validity of your findings. Avoid using an apologetic tone; however, be honest and self-critical [e.g., in retrospect, had you included a particular question in a survey instrument, additional data could have been revealed].
• The discussion section should end with a concise summary of the principal implications of the findings regardless of their significance. Give a brief explanation about why you believe the findings and conclusions of your study are important and how they support broader knowledge or understanding of the research problem. This can be followed by any recommendations for further research. However, do not offer recommendations which could have been easily addressed within the study. This would demonstrate to the reader that you have inadequately examined and interpreted the data.

IV.  Overall Objectives

The objectives of your discussion section should include the following: I.  Reiterate the Research Problem/State the Major Findings

Briefly reiterate the research problem or problems you are investigating and the methods you used to investigate them, then move quickly to describe the major findings of the study. You should write a direct, declarative, and succinct proclamation of the study results, usually in one paragraph.

II.  Explain the Meaning of the Findings and Why They are Important

No one has thought as long and hard about your study as you have. Systematically explain the underlying meaning of your findings and state why you believe they are significant. After reading the discussion section, you want the reader to think critically about the results and why they are important. You don’t want to force the reader to go through the paper multiple times to figure out what it all means. If applicable, begin this part of the section by repeating what you consider to be your most significant or unanticipated finding first, then systematically review each finding. Otherwise, follow the general order you reported the findings presented in the results section.

III.  Relate the Findings to Similar Studies

No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your results to those found in other studies, particularly if questions raised from prior studies served as the motivation for your research. This is important because comparing and contrasting the findings of other studies helps to support the overall importance of your results and it highlights how and in what ways your study differs from other research about the topic. Note that any significant or unanticipated finding is often because there was no prior research to indicate the finding could occur. If there is prior research to indicate this, you need to explain why it was significant or unanticipated. IV.  Consider Alternative Explanations of the Findings

It is important to remember that the purpose of research in the social sciences is to discover and not to prove . When writing the discussion section, you should carefully consider all possible explanations for the study results, rather than just those that fit your hypothesis or prior assumptions and biases. This is especially important when describing the discovery of significant or unanticipated findings.

V.  Acknowledge the Study’s Limitations

It is far better for you to identify and acknowledge your study’s limitations than to have them pointed out by your professor! Note any unanswered questions or issues your study could not address and describe the generalizability of your results to other situations. If a limitation is applicable to the method chosen to gather information, then describe in detail the problems you encountered and why. VI.  Make Suggestions for Further Research

You may choose to conclude the discussion section by making suggestions for further research [as opposed to offering suggestions in the conclusion of your paper]. Although your study can offer important insights about the research problem, this is where you can address other questions related to the problem that remain unanswered or highlight hidden issues that were revealed as a result of conducting your research. You should frame your suggestions by linking the need for further research to the limitations of your study [e.g., in future studies, the survey instrument should include more questions that ask..."] or linking to critical issues revealed from the data that were not considered initially in your research.

NOTE: Besides the literature review section, the preponderance of references to sources is usually found in the discussion section . A few historical references may be helpful for perspective, but most of the references should be relatively recent and included to aid in the interpretation of your results, to support the significance of a finding, and/or to place a finding within a particular context. If a study that you cited does not support your findings, don't ignore it--clearly explain why your research findings differ from theirs.

V.  Problems to Avoid

• Do not waste time restating your results . Should you need to remind the reader of a finding to be discussed, use "bridge sentences" that relate the result to the interpretation. An example would be: “In the case of determining available housing to single women with children in rural areas of Texas, the findings suggest that access to good schools is important...," then move on to further explaining this finding and its implications.
• As noted, recommendations for further research can be included in either the discussion or conclusion of your paper, but do not repeat your recommendations in the both sections. Think about the overall narrative flow of your paper to determine where best to locate this information. However, if your findings raise a lot of new questions or issues, consider including suggestions for further research in the discussion section.
• Do not introduce new results in the discussion section. Be wary of mistaking the reiteration of a specific finding for an interpretation because it may confuse the reader. The description of findings [results section] and the interpretation of their significance [discussion section] should be distinct parts of your paper. If you choose to combine the results section and the discussion section into a single narrative, you must be clear in how you report the information discovered and your own interpretation of each finding. This approach is not recommended if you lack experience writing college-level research papers.
• Use of the first person pronoun is generally acceptable. Using first person singular pronouns can help emphasize a point or illustrate a contrasting finding. However, keep in mind that too much use of the first person can actually distract the reader from the main points [i.e., I know you're telling me this--just tell me!].

Analyzing vs. Summarizing. Department of English Writing Guide. George Mason University; Discussion. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Hess, Dean R. "How to Write an Effective Discussion." Respiratory Care 49 (October 2004); Kretchmer, Paul. Fourteen Steps to Writing to Writing an Effective Discussion Section. San Francisco Edit, 2003-2008; The Lab Report. University College Writing Centre. University of Toronto; Sauaia, A. et al. "The Anatomy of an Article: The Discussion Section: "How Does the Article I Read Today Change What I Will Recommend to my Patients Tomorrow?” The Journal of Trauma and Acute Care Surgery 74 (June 2013): 1599-1602; Research Limitations & Future Research . Lund Research Ltd., 2012; Summary: Using it Wisely. The Writing Center. University of North Carolina; Schafer, Mickey S. Writing the Discussion. Writing in Psychology course syllabus. University of Florida; Yellin, Linda L. A Sociology Writer's Guide . Boston, MA: Allyn and Bacon, 2009.

Writing Tip

Don’t Over-Interpret the Results!

Interpretation is a subjective exercise. As such, you should always approach the selection and interpretation of your findings introspectively and to think critically about the possibility of judgmental biases unintentionally entering into discussions about the significance of your work. With this in mind, be careful that you do not read more into the findings than can be supported by the evidence you have gathered. Remember that the data are the data: nothing more, nothing less.

MacCoun, Robert J. "Biases in the Interpretation and Use of Research Results." Annual Review of Psychology 49 (February 1998): 259-287; Ward, Paulet al, editors. The Oxford Handbook of Expertise . Oxford, UK: Oxford University Press, 2018.

Another Writing Tip

Don't Write Two Results Sections!

One of the most common mistakes that you can make when discussing the results of your study is to present a superficial interpretation of the findings that more or less re-states the results section of your paper. Obviously, you must refer to your results when discussing them, but focus on the interpretation of those results and their significance in relation to the research problem, not the data itself.

Azar, Beth. "Discussing Your Findings."  American Psychological Association gradPSYCH Magazine (January 2006).

Yet Another Writing Tip

Avoid Unwarranted Speculation!

The discussion section should remain focused on the findings of your study. For example, if the purpose of your research was to measure the impact of foreign aid on increasing access to education among disadvantaged children in Bangladesh, it would not be appropriate to speculate about how your findings might apply to populations in other countries without drawing from existing studies to support your claim or if analysis of other countries was not a part of your original research design. If you feel compelled to speculate, do so in the form of describing possible implications or explaining possible impacts. Be certain that you clearly identify your comments as speculation or as a suggestion for where further research is needed. Sometimes your professor will encourage you to expand your discussion of the results in this way, while others don’t care what your opinion is beyond your effort to interpret the data in relation to the research problem.

• << Previous: Using Non-Textual Elements
• Next: Limitations of the Study >>
• Last Updated: May 9, 2024 11:05 AM
• URL: https://libguides.usc.edu/writingguide

Finding Relevant Scholarly Research for Literature Review: How can we be systematic?

On an average, it takes 15 clicks for a researcher to find an article (which may or may not be related to their research topic) online. This time is not productive because it does not help them gain any knowledge and it could potentially be spent doing something more vital in fostering research and development. Moreover, as most researchers rely on two to three databases to find information for their literature review , the time to find relevant scholarly research data also increases.

Table of Contents

Navigating Through Multiple Scholarly Databases—Is it even necessary?

The Internet has revolutionized the way we access information. Websites and online resources within and outside of academic bibliography are significant resources of literature. However, the challenge in searching and managing the results is undeniable.

Considering the exponential growth in scholarly research data and literature, finding relevant information and reporting your research sooner is imperative. While Open Science has been a positive reform of information access, not all data is available at a click, let alone the relevant one. Researchers fear the possibility of missing out on critical information related to their research topic or accidentally committing plagiarism. Hence, they spend time in toggling through multiple scholarly databases.

In this process of searching for literature on multiple databases, researchers tend to download irrelevant information too. Furthermore, the probability of finding similar resources on multiple databases is higher if the resource is on an Open Access platform. These downloaded papers not only occupy the space in reference managers but also make researchers spend a lot of time deciding whether the paper is worth reading or not.

5 Major Challenges Faced on Multiple Scholarly Databases—How to overcome them?

Finding scholarly research data involves navigating through institutional login pages, subscriptions, and paywalls. Apart from the time, effort, and money spent there are several other challenges that researchers encounter while searching literature on multiple scholarly databases.

Here we discuss 5 major challenges faced by researchers while using multiple scholarly databases:

1. Identifying and Deciding the Resources to Search

The Internet provides information in numerous formats, viz. journal articles, preprints, video recordings, podcasts, infographics, conference proceedings, etc. This wide pool of knowledge gets deeper with advances in scholarly research and literature. Hence, while finding research data on multiple scholarly databases in multiple formats, it becomes difficult to identify and decide the resources to download based on their relevance to the research topic. However, these resources can be easily traced if they all are on a single platform.

2. Search or Navigate Resources Correctly

Researchers use keywords and questions to find scholarly data related to their topic of interest. Databases search for the exact words and phrases. Hence, if researchers use a different word or a synonym that describes the concept, the search results are not relevant. If a single database with optimized keywords is used to access billions of scholarly resources, it not only avoids information overload but also allows navigation of relevant information.

3. Assessing Obtained Search Results

Information overload makes it difficult for researchers to assess every discovered resource. One cannot decide the relevancy of search results based on the research paper ’s title. And reading all sections of all papers—abstract, introduction, results, and/or conclusion—will be extremely time consuming. Furthermore, spending time reading these sections of papers to later find out that it’s not related to your research topic will not help anyone. So, what if there was a tool that could search results beyond keywords using research ideas, questions, etc., and also could summarize the key aspects of each downloaded resource? Definitely something to ponder about.

4. Deciding Which Literature to Select and Cite

Scientists are often overwhelmed with the scholarly research data they find online. It is a never-ending task to decide which literature to select and cite. Thus, it is essential to download only relevant data and assess them based on their relevance to the research topic. Furthermore, citing the literature accurately by following journal-specific guidelines and writing style guides will avoid accidental plagiarism. Such cumbersome tasks can be handled with accuracy using an AI-based tool particularly designed to make academic research and publishing easier.

5. Retrieving Relevant Literature in an Accessible and Editable Format

The inability of some software to save, process, and/or retrieve data in all formats is displeasing in this age of digitization. Hence, scientists prefer software that allows accessing, downloading, managing, and editing research data files in all formats.

How to Find Scholarly Research Data with a Systematic Approach? – 7 simple steps

Given the amount of intelligence on the internet, it is only wise to resort to a reliable system. One which is smart, efficient, precise, accessible, and affordable to integrate the scattered information, help researchers through every step of research reporting and publishing, and save time, effort, and money.

A simple 7-step systematic approach to find relevant scholarly research data

• Search literature based on research ideas, keywords, conference talks, author details, etc.
• Assess the found resources based on their key aspects and findings.
• Search, save, manage, read, and annotate relevant literature on a single platform.
• Use easily accessible and editable formats.
• Cite the literature to avoid plagiarism.
• Follow journal guidelines and format the research paper.
• Connect with co-authors and share your work with them for insights and edits.

An extensive and accurate literature search is the key to performing, reporting, and publishing authentic research. A systematic single-platform search database provides a much better comprehension of insights of the research topic. It helps draw comparisons faster as all results are saved and managed in one place! Moreover, it helps researchers to stimulate the interpretation of ideas, analyze shortcomings, and recognize opportunities of future research.

With advances in technology, this process can be simplified without compromising the quality of the final product. As Artificial Intelligence takes over other realms of society, it’s about time researchers leverage these advances to further streamline research publishing.

What are your ways of literature search? How many databases do you have to use simultaneously? Wouldn’t you want to have all your work on one platform without remembering several login IDs and passwords? This sounds like the future of publishing! What do you think?

Rate this article Cancel Reply

Your email address will not be published.

Enago Academy's Most Popular Articles

• Industry News
• Publishing News

Unified AI Guidelines Crucial as Academic Writing Embraces Generative Tools

As generative artificial intelligence (AI) tools like ChatGPT are advancing at an accelerating pace, their…

• Promoting Research
• Thought Leadership
• Trending Now

How Enago Academy Contributes to Sustainable Development Goals (SDGs) Through Empowering Researchers

The United Nations Sustainable Development Goals (SDGs) are a universal call to action to end…

• AI in Academia

Using AI for Journal Selection — Simplifying your academic publishing journey in the smart way

Strategic journal selection plays a pivotal role in maximizing the impact of one’s scholarly work.…

• Old Webinars
• Webinar Mobile App

Using AI for Plagiarism Prevention and AI-Content Detection in Academic Writing

Watch Now   In today’s digital age, where information is readily accessible and content creation…

Authenticating AI-Generated Scholarly Outputs: Practical approaches to take

The rapid advancements in artificial intelligence (AI) have given rise to a new era of…

AI for Accuracy in Research and Academic Writing

Upholding Academic Integrity in the Age of AI: Challenges and solutions

AI Assistance in Academia for Searching Credible Scholarly Sources

Call for Responsible Use of Generative AI in Academia: The battle between rising…

Sign-up to read more

Subscribe for free to get unrestricted access to all our resources on research writing and academic publishing including:

• 2000+ blog articles
• 50+ Webinars
• 10+ Expert podcasts
• 50+ Infographics
• 10+ Checklists
• Research Guides

We hate spam too. We promise to protect your privacy and never spam you.

I am looking for Editing/ Proofreading services for my manuscript Tentative date of next journal submission:

As a researcher, what do you consider most when choosing an image manipulation detector?

• Privacy Policy

Home » Research Report – Example, Writing Guide and Types

Research Report – Example, Writing Guide and Types

Table of Contents

Research Report

Definition:

Research Report is a written document that presents the results of a research project or study, including the research question, methodology, results, and conclusions, in a clear and objective manner.

The purpose of a research report is to communicate the findings of the research to the intended audience, which could be other researchers, stakeholders, or the general public.

Components of Research Report

Components of Research Report are as follows:

Introduction

The introduction sets the stage for the research report and provides a brief overview of the research question or problem being investigated. It should include a clear statement of the purpose of the study and its significance or relevance to the field of research. It may also provide background information or a literature review to help contextualize the research.

Literature Review

The literature review provides a critical analysis and synthesis of the existing research and scholarship relevant to the research question or problem. It should identify the gaps, inconsistencies, and contradictions in the literature and show how the current study addresses these issues. The literature review also establishes the theoretical framework or conceptual model that guides the research.

Methodology

The methodology section describes the research design, methods, and procedures used to collect and analyze data. It should include information on the sample or participants, data collection instruments, data collection procedures, and data analysis techniques. The methodology should be clear and detailed enough to allow other researchers to replicate the study.

The results section presents the findings of the study in a clear and objective manner. It should provide a detailed description of the data and statistics used to answer the research question or test the hypothesis. Tables, graphs, and figures may be included to help visualize the data and illustrate the key findings.

The discussion section interprets the results of the study and explains their significance or relevance to the research question or problem. It should also compare the current findings with those of previous studies and identify the implications for future research or practice. The discussion should be based on the results presented in the previous section and should avoid speculation or unfounded conclusions.

The conclusion summarizes the key findings of the study and restates the main argument or thesis presented in the introduction. It should also provide a brief overview of the contributions of the study to the field of research and the implications for practice or policy.

The references section lists all the sources cited in the research report, following a specific citation style, such as APA or MLA.

The appendices section includes any additional material, such as data tables, figures, or instruments used in the study, that could not be included in the main text due to space limitations.

Types of Research Report

Types of Research Report are as follows:

Thesis is a type of research report. A thesis is a long-form research document that presents the findings and conclusions of an original research study conducted by a student as part of a graduate or postgraduate program. It is typically written by a student pursuing a higher degree, such as a Master’s or Doctoral degree, although it can also be written by researchers or scholars in other fields.

Research Paper

Research paper is a type of research report. A research paper is a document that presents the results of a research study or investigation. Research papers can be written in a variety of fields, including science, social science, humanities, and business. They typically follow a standard format that includes an introduction, literature review, methodology, results, discussion, and conclusion sections.

Technical Report

A technical report is a detailed report that provides information about a specific technical or scientific problem or project. Technical reports are often used in engineering, science, and other technical fields to document research and development work.

Progress Report

A progress report provides an update on the progress of a research project or program over a specific period of time. Progress reports are typically used to communicate the status of a project to stakeholders, funders, or project managers.

Feasibility Report

A feasibility report assesses the feasibility of a proposed project or plan, providing an analysis of the potential risks, benefits, and costs associated with the project. Feasibility reports are often used in business, engineering, and other fields to determine the viability of a project before it is undertaken.

Field Report

A field report documents observations and findings from fieldwork, which is research conducted in the natural environment or setting. Field reports are often used in anthropology, ecology, and other social and natural sciences.

Experimental Report

An experimental report documents the results of a scientific experiment, including the hypothesis, methods, results, and conclusions. Experimental reports are often used in biology, chemistry, and other sciences to communicate the results of laboratory experiments.

Case Study Report

A case study report provides an in-depth analysis of a specific case or situation, often used in psychology, social work, and other fields to document and understand complex cases or phenomena.

Literature Review Report

A literature review report synthesizes and summarizes existing research on a specific topic, providing an overview of the current state of knowledge on the subject. Literature review reports are often used in social sciences, education, and other fields to identify gaps in the literature and guide future research.

Research Report Example

Following is a Research Report Example sample for Students:

Title: The Impact of Social Media on Academic Performance among High School Students

This study aims to investigate the relationship between social media use and academic performance among high school students. The study utilized a quantitative research design, which involved a survey questionnaire administered to a sample of 200 high school students. The findings indicate that there is a negative correlation between social media use and academic performance, suggesting that excessive social media use can lead to poor academic performance among high school students. The results of this study have important implications for educators, parents, and policymakers, as they highlight the need for strategies that can help students balance their social media use and academic responsibilities.

Introduction:

Social media has become an integral part of the lives of high school students. With the widespread use of social media platforms such as Facebook, Twitter, Instagram, and Snapchat, students can connect with friends, share photos and videos, and engage in discussions on a range of topics. While social media offers many benefits, concerns have been raised about its impact on academic performance. Many studies have found a negative correlation between social media use and academic performance among high school students (Kirschner & Karpinski, 2010; Paul, Baker, & Cochran, 2012).

Given the growing importance of social media in the lives of high school students, it is important to investigate its impact on academic performance. This study aims to address this gap by examining the relationship between social media use and academic performance among high school students.

Methodology:

The study utilized a quantitative research design, which involved a survey questionnaire administered to a sample of 200 high school students. The questionnaire was developed based on previous studies and was designed to measure the frequency and duration of social media use, as well as academic performance.

The participants were selected using a convenience sampling technique, and the survey questionnaire was distributed in the classroom during regular school hours. The data collected were analyzed using descriptive statistics and correlation analysis.

The findings indicate that the majority of high school students use social media platforms on a daily basis, with Facebook being the most popular platform. The results also show a negative correlation between social media use and academic performance, suggesting that excessive social media use can lead to poor academic performance among high school students.

Discussion:

The results of this study have important implications for educators, parents, and policymakers. The negative correlation between social media use and academic performance suggests that strategies should be put in place to help students balance their social media use and academic responsibilities. For example, educators could incorporate social media into their teaching strategies to engage students and enhance learning. Parents could limit their children’s social media use and encourage them to prioritize their academic responsibilities. Policymakers could develop guidelines and policies to regulate social media use among high school students.

Conclusion:

In conclusion, this study provides evidence of the negative impact of social media on academic performance among high school students. The findings highlight the need for strategies that can help students balance their social media use and academic responsibilities. Further research is needed to explore the specific mechanisms by which social media use affects academic performance and to develop effective strategies for addressing this issue.

Limitations:

One limitation of this study is the use of convenience sampling, which limits the generalizability of the findings to other populations. Future studies should use random sampling techniques to increase the representativeness of the sample. Another limitation is the use of self-reported measures, which may be subject to social desirability bias. Future studies could use objective measures of social media use and academic performance, such as tracking software and school records.

Implications:

The findings of this study have important implications for educators, parents, and policymakers. Educators could incorporate social media into their teaching strategies to engage students and enhance learning. For example, teachers could use social media platforms to share relevant educational resources and facilitate online discussions. Parents could limit their children’s social media use and encourage them to prioritize their academic responsibilities. They could also engage in open communication with their children to understand their social media use and its impact on their academic performance. Policymakers could develop guidelines and policies to regulate social media use among high school students. For example, schools could implement social media policies that restrict access during class time and encourage responsible use.

References:

• Kirschner, P. A., & Karpinski, A. C. (2010). Facebook® and academic performance. Computers in Human Behavior, 26(6), 1237-1245.
• Paul, J. A., Baker, H. M., & Cochran, J. D. (2012). Effect of online social networking on student academic performance. Journal of the Research Center for Educational Technology, 8(1), 1-19.
• Pantic, I. (2014). Online social networking and mental health. Cyberpsychology, Behavior, and Social Networking, 17(10), 652-657.
• Rosen, L. D., Carrier, L. M., & Cheever, N. A. (2013). Facebook and texting made me do it: Media-induced task-switching while studying. Computers in Human Behavior, 29(3), 948-958.

Note*: Above mention, Example is just a sample for the students’ guide. Do not directly copy and paste as your College or University assignment. Kindly do some research and Write your own.

Applications of Research Report

Research reports have many applications, including:

• Communicating research findings: The primary application of a research report is to communicate the results of a study to other researchers, stakeholders, or the general public. The report serves as a way to share new knowledge, insights, and discoveries with others in the field.
• Informing policy and practice : Research reports can inform policy and practice by providing evidence-based recommendations for decision-makers. For example, a research report on the effectiveness of a new drug could inform regulatory agencies in their decision-making process.
• Supporting further research: Research reports can provide a foundation for further research in a particular area. Other researchers may use the findings and methodology of a report to develop new research questions or to build on existing research.
• Evaluating programs and interventions : Research reports can be used to evaluate the effectiveness of programs and interventions in achieving their intended outcomes. For example, a research report on a new educational program could provide evidence of its impact on student performance.
• Demonstrating impact : Research reports can be used to demonstrate the impact of research funding or to evaluate the success of research projects. By presenting the findings and outcomes of a study, research reports can show the value of research to funders and stakeholders.
• Enhancing professional development : Research reports can be used to enhance professional development by providing a source of information and learning for researchers and practitioners in a particular field. For example, a research report on a new teaching methodology could provide insights and ideas for educators to incorporate into their own practice.

How to write Research Report

Here are some steps you can follow to write a research report:

• Identify the research question: The first step in writing a research report is to identify your research question. This will help you focus your research and organize your findings.
• Conduct research : Once you have identified your research question, you will need to conduct research to gather relevant data and information. This can involve conducting experiments, reviewing literature, or analyzing data.
• Organize your findings: Once you have gathered all of your data, you will need to organize your findings in a way that is clear and understandable. This can involve creating tables, graphs, or charts to illustrate your results.
• Write the report: Once you have organized your findings, you can begin writing the report. Start with an introduction that provides background information and explains the purpose of your research. Next, provide a detailed description of your research methods and findings. Finally, summarize your results and draw conclusions based on your findings.
• Proofread and edit: After you have written your report, be sure to proofread and edit it carefully. Check for grammar and spelling errors, and make sure that your report is well-organized and easy to read.
• Include a reference list: Be sure to include a list of references that you used in your research. This will give credit to your sources and allow readers to further explore the topic if they choose.
• Format your report: Finally, format your report according to the guidelines provided by your instructor or organization. This may include formatting requirements for headings, margins, fonts, and spacing.

Purpose of Research Report

The purpose of a research report is to communicate the results of a research study to a specific audience, such as peers in the same field, stakeholders, or the general public. The report provides a detailed description of the research methods, findings, and conclusions.

Some common purposes of a research report include:

• Sharing knowledge: A research report allows researchers to share their findings and knowledge with others in their field. This helps to advance the field and improve the understanding of a particular topic.
• Identifying trends: A research report can identify trends and patterns in data, which can help guide future research and inform decision-making.
• Addressing problems: A research report can provide insights into problems or issues and suggest solutions or recommendations for addressing them.
• Evaluating programs or interventions : A research report can evaluate the effectiveness of programs or interventions, which can inform decision-making about whether to continue, modify, or discontinue them.
• Meeting regulatory requirements: In some fields, research reports are required to meet regulatory requirements, such as in the case of drug trials or environmental impact studies.

When to Write Research Report

A research report should be written after completing the research study. This includes collecting data, analyzing the results, and drawing conclusions based on the findings. Once the research is complete, the report should be written in a timely manner while the information is still fresh in the researcher’s mind.

In academic settings, research reports are often required as part of coursework or as part of a thesis or dissertation. In this case, the report should be written according to the guidelines provided by the instructor or institution.

In other settings, such as in industry or government, research reports may be required to inform decision-making or to comply with regulatory requirements. In these cases, the report should be written as soon as possible after the research is completed in order to inform decision-making in a timely manner.

Overall, the timing of when to write a research report depends on the purpose of the research, the expectations of the audience, and any regulatory requirements that need to be met. However, it is important to complete the report in a timely manner while the information is still fresh in the researcher’s mind.

Characteristics of Research Report

There are several characteristics of a research report that distinguish it from other types of writing. These characteristics include:

• Objective: A research report should be written in an objective and unbiased manner. It should present the facts and findings of the research study without any personal opinions or biases.
• Systematic: A research report should be written in a systematic manner. It should follow a clear and logical structure, and the information should be presented in a way that is easy to understand and follow.
• Detailed: A research report should be detailed and comprehensive. It should provide a thorough description of the research methods, results, and conclusions.
• Accurate : A research report should be accurate and based on sound research methods. The findings and conclusions should be supported by data and evidence.
• Organized: A research report should be well-organized. It should include headings and subheadings to help the reader navigate the report and understand the main points.
• Clear and concise: A research report should be written in clear and concise language. The information should be presented in a way that is easy to understand, and unnecessary jargon should be avoided.
• Citations and references: A research report should include citations and references to support the findings and conclusions. This helps to give credit to other researchers and to provide readers with the opportunity to further explore the topic.

Advantages of Research Report

Research reports have several advantages, including:

• Communicating research findings: Research reports allow researchers to communicate their findings to a wider audience, including other researchers, stakeholders, and the general public. This helps to disseminate knowledge and advance the understanding of a particular topic.
• Providing evidence for decision-making : Research reports can provide evidence to inform decision-making, such as in the case of policy-making, program planning, or product development. The findings and conclusions can help guide decisions and improve outcomes.
• Supporting further research: Research reports can provide a foundation for further research on a particular topic. Other researchers can build on the findings and conclusions of the report, which can lead to further discoveries and advancements in the field.
• Demonstrating expertise: Research reports can demonstrate the expertise of the researchers and their ability to conduct rigorous and high-quality research. This can be important for securing funding, promotions, and other professional opportunities.
• Meeting regulatory requirements: In some fields, research reports are required to meet regulatory requirements, such as in the case of drug trials or environmental impact studies. Producing a high-quality research report can help ensure compliance with these requirements.

Limitations of Research Report

Despite their advantages, research reports also have some limitations, including:

• Time-consuming: Conducting research and writing a report can be a time-consuming process, particularly for large-scale studies. This can limit the frequency and speed of producing research reports.
• Expensive: Conducting research and producing a report can be expensive, particularly for studies that require specialized equipment, personnel, or data. This can limit the scope and feasibility of some research studies.
• Limited generalizability: Research studies often focus on a specific population or context, which can limit the generalizability of the findings to other populations or contexts.
• Potential bias : Researchers may have biases or conflicts of interest that can influence the findings and conclusions of the research study. Additionally, participants may also have biases or may not be representative of the larger population, which can limit the validity and reliability of the findings.
• Accessibility: Research reports may be written in technical or academic language, which can limit their accessibility to a wider audience. Additionally, some research may be behind paywalls or require specialized access, which can limit the ability of others to read and use the findings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

Data Collection – Methods Types and Examples

Delimitations in Research – Types, Examples and...

Research Process – Steps, Examples and Tips

Research Design – Types, Methods and Examples

Institutional Review Board – Application Sample...

Evaluating Research – Process, Examples and...

How the brain is flexible enough for a complex world (without being thrown into chaos)

Many neurons exhibit “mixed selectivity,” meaning they can integrate multiple inputs and participate in multiple computations. Mechanisms such as oscillations and neuromodulators recruit their participation and tune them to focus on the relevant information.

Every day our brains strive to optimize a trade-off: With lots of things happening around us even as we also harbor many internal drives and memories, somehow our thoughts must be flexible yet focused enough to guide everything we have to do. In a new paper in Neuron, a team of neuroscientists describes how the brain achieves the cognitive capacity to incorporate all the information that’s relevant without becoming overwhelmed by what’s not.

The authors argue that the flexibility arises from a key property observed in many neurons: “mixed selectivity.” While many neuroscientists used to think each cell had just one dedicated function, more recent evidence has shown that many neurons can instead participate in a variety of computational ensembles, each working in parallel. In other words, when a rabbit considers nibbling on some lettuce in a garden, a single neuron might be involved in not only assessing how hungry it feels but also whether it can hear a hawk overhead or smell a coyote in the trees and how far away the lettuce is.

The brain does not multitask, said paper co-author Earl K. Miller , Picower Professor in The Picower Institute for Learning and Memory at MIT and a pioneer of the mixed selectivity idea, but many cells do have the capacity to be roped into multiple computational efforts (essentially “thoughts”). In the new paper the authors describe specific mechanisms the brain employs to recruit neurons into different computations and to ensure that those neurons represent the right number of dimensions of a complex task.

“These neurons wear multiple hats,” Miller said. “With mixed selectivity you can have a representational space that’s as complex as it needs to be and no more complex. That’s what flexible cognition is all about.”

Co-author Kay Tye , Professor at The Salk Institute and the University of California at San Diego, said mixed selectivity among neurons particularly in the medial prefrontal cortex is key to enabling many mental abilities.

"The mPFC is like a hum of whispers that represents so much information through highly flexible and dynamic ensembles," Tye said. “Mixed selectivity is the property that endows us with our flexibility, cognitive capacity, and ability to be creative.  It is the secret to maximizing computational power which is essentially the underpinnings of intelligence."

Origins of an idea

The idea of mixed selectivity germinated in 2000 when Miller and colleague John Duncan defended a surprising result from a study of cognition in Miller’s lab. As animals sorted images into categories, about 30 percent of the neurons in the prefrontal cortex of the brain seemed to be involved. Skeptics who believed that every neuron had a dedicated function scoffed that the brain would devote so many cells to just one task. Miller and Duncan’s answer was that perhaps cells had the flexibility to be involved in many computations. The ability to serve on one cerebral task force, as it were, did not preclude them from being able to serve many others.

But what benefit does mixed selectivity convey? In 2013 Miller teamed up with two co-authors of the new paper, Mattia Rigotti of IBM Research and Stefano Fusi of Columbia University, to show how mixed selectivity endows the brain with powerful computational flexibility. Essentially, an ensemble of neurons with mixed selectivity can accommodate many more dimensions of information about a task than a population of neurons with invariant functions.

“Since our original work, we've made progress understanding the theory of mixed selectivity through the lens of classical machine learning ideas,” Rigotti said. “On the other hand, questions dear to experimentalists about the mechanisms implementing it at a cellular level had been comparatively under-explored. This collaboration and this new paper set out to fill that gap.”

In the new paper the authors imagine a mouse who is considering whether to eat a berry. It might smell delicious (that’s one dimension). It might be poisonous (that’s another). Yet another dimension or two of the problem could come in the form of a social cue. If the mouse smells the berry scent on a fellow mouse’s breath, then the berry is probably OK to eat (depending on the apparent health of the fellow mouse). A neural ensemble with mixed selectivity would be able to integrate all that.

Recruiting neurons

While mixed selectivity has the backing of copious evidence—it has been observed across the cortex and in other brain areas such as the hippocampus and amygdala—there are still open questions. For instance, how are neurons recruited to tasks and how do neurons that are so “open-minded” remain tuned only to what really matters to the mission?

In the new study, the researchers who also include Marcus Benna of UC San Diego and Felix Taschbach of The Salk Institute, define the forms of mixed selectivity that researchers have observed, and argue that when oscillations (also known as “brain waves”) and neuromodulators (chemicals such as serotonin or dopamine that influence neural function) recruit neurons into computational ensembles, they also help them “gate” what’s important for that purpose.

To be sure, some neurons are dedicated to a specific input, but the authors note they are an exception rather than the rule. The authors say these cells have “pure selectivity.” They only care if the rabbit sees lettuce. Some neurons exhibit “linear mixed selectivity,” which means their response predictably depends on multiple inputs adding up (the rabbit sees lettuce and feels hungry). The neurons that add the most dimensional flexibility are the “nonlinear mixed selectivity” ones that can account for multiple independent variables without necessarily summing them. Instead they might weigh a whole set of independent conditions (e.g. there’s lettuce, I’m hungry, I hear no hawks, I smell no coyotes, but the lettuce is far and I see a pretty sturdy fence).

So what brings neurons into the fold to focus on the salient factors, however many there are? One mechanism is oscillations, which are produced in the brain when many neurons all maintain their electrical activity at the same rhythm. This coordinated activity enables information sharing, essentially tuning them together like a bunch of cars all playing the same radio station (maybe the broadcast is about a hawk circling overhead). Another mechanism the authors highlight is neuromodulators. These are chemicals that upon reaching receptors within cells can influence their activity as well. A burst of acetylcholine, for instance, might similarly attune neurons with the right receptors to certain activity or information (like maybe that feeling of hunger).

“These two mechanisms likely work together to dynamically form functional networks,” the authors write.

Understanding mixed selectivity, they continue, is critical to understanding cognition.

“Mixed selectivity is ubiquitous,” they conclude. “It is present across species and across functions from high-level cognition to ‘automatic’ sensorimotor processes such as object recognition. The widespread presence of mixed selectivity underscores its fundamental role in providing the brain with the scalable processing power needed for complex thought and action.”

Related Articles

In the brain, bursts of beta rhythms implement cognitive control.

Paper: To understand cognition—and its dysfunction—neuroscientists must learn its rhythms

Study reveals a universal pattern of brain wave frequencies

Anesthesia blocks sensation by cutting off communication within the cortex

Consulting Research  

Research consultants have research expertise and an outside perspective to help you make informed business decisions.  

Home > Research Glossary > Consulting Research

What is consulting research?  

Consulting research is often done by an outside party to help businesses gather information about the industry, market trends, or opposing entities to help them understand the current market landscape.

Consulting research involves various methods of data collection, including examining public records, analyzing media coverage, conducting interviews, surveys, and online research. It plays a crucial role in informing decision-making processes and enabling businesses to gain a competitive edge in the market. 

What is a research consultant? 

A research consultant is a professional who specializes in conducting consulting research or competitive intelligence for businesses, organizations, or individuals. They possess expertise in data collection, analysis, and interpretation to provide valuable insights and recommendations to their clients.  

Research consultants often use various methodologies and tools to gather relevant information, analyze market trends, assess competitors, and identify opportunities for their clients. 

Why to work with a research consultant?  

Using a research consultant offers several advantages to businesses and organizations:  

• Expertise: Research consultants have specialized knowledge and experience in conducting effective research to make informed recommendations, ensuring that the research is thorough, accurate, and unbiased.
• Time and resource efficiency: Outsourcing research to a consultant allows businesses to focus on their core activities while leaving the research process to the experts.
• Access to data and tools: Research consultants have access to a wide range of data sources, databases, and research tools, enabling them to gather comprehensive and up-to-date information efficiently.
• Objective insights: Research consultants provide an impartial perspective, helping businesses make informed decisions without bias.
• Actionable recommendations: Based on the research findings, consultants can offer actionable recommendations to help businesses improve their strategies, operations, and market positioning. 

Types of consulting research 

Consulting research encompasses various types of research based on the specific needs and objectives of businesses and organizations. Some common types of consulting research include: 

• Market research: Analyzing market trends , customer preferences, and competitive landscape to inform marketing strategies and product development.
• Competitor analysis: Examining the strengths and weaknesses of competitors to identify opportunities and threats in the market.
• Feasibility studies: Assessing the viability of a business venture, project, or initiative to determine its potential success.
• Customer satisfaction surveys: Gathering feedback from customers to measure satisfaction levels and identify areas for improvement.
• Industry analysis: Examining the overall industry landscape , growth prospects, and key players to make informed business decisions. 

Ethical considerations of consulting research  

While consulting research is a legitimate practice, it is important to adhere to ethical guidelines . The collection of information should comply with applicable laws and regulations, respect privacy rights, and avoid engaging in illegal or unethical activities.  

How LexisNexis supports consulting research  

LexisNexis offers solutions to streamline your consulting research with verifiable and accurate information. With Nexis ® Research Solutions , you can explore relevant data in easy-to-filter formats, so you have a more direct path to profound insights and informed conclusions. Access over 36,000 licensed sources and 45,000 total resources in over 37 different languages for complete data.  

Furthermore, LexisNexis provides monitoring and alert services that notify you of any new developments related to your opposition. You can set up customized alerts to stay informed about news articles, legal cases, or other relevant information as it happens, ensuring you never miss important updates. 

With LexisNexis, you have access to the tools and resources you need to conduct thorough and effective consulting research, enabling you to make informed decisions and stay ahead of the competition. 

START A FREE TRIAL

You may also be interested in

Research and development .

Research and Development is invaluable for enhancing your business.

Market Research

Valid business information and market data as the basis of market intelligence. 

Have Questions?

Connect with an expert to discuss your Research needs. Complete the form below or call us at 1-888-46-NEXIS .

• Open access
• Published: 30 April 2024

The cost of keeping patients waiting: retrospective treatment-control study of additional healthcare utilisation for UK patients awaiting elective treatment

• Charlotte James 1 , 2 , 3 , 4 ,
• Rachel Denholm 1 , 3 , 5 &
• Richard Wood 4 , 6  

BMC Health Services Research volume  24 , Article number:  556 ( 2024 ) Cite this article

285 Accesses

Metrics details

Long waiting times for elective hospital treatments are common in many countries. This study seeks to address a deficit in the literature concerning the effect of long waits on the wider consumption of healthcare resources.

We carried out a retrospective treatment-control study in a healthcare system in South West England from 15 June 2021 to 15 December 2021. We compared weekly contacts with health services of patients waiting over 18 weeks for treatment (‘Treatments’) and people not on a waiting list (‘Controls’). Controls were matched to Treatments based on age, sex, deprivation and multimorbidity. Treatments were stratified by the clinical specialty of the awaited hospital treatment, with healthcare usage assessed over various healthcare settings. Wilcoxon signed-rank tests assessed whether there was an increase in healthcare utilisation and bootstrap resampling was used to estimate the magnitude of any differences.

A total of 44,616 patients were waiting over 18 weeks (the constitutional target in England) for treatment during the study period. There was an increase ( p  < 0.0004) in healthcare utilisation for all specialties. Patients in the Cardiothoracic Surgery specialty had the largest increase, with 17.9 [interquartile-range: 4.3, 33.8] additional contacts with secondary care and 17.3 [-1.1, 34.1] additional prescriptions per year.

People waiting for treatment consume higher levels of healthcare than comparable individuals not on a waiting list. These findings are relevant for clinicians and managers in better understanding patient need and reducing harm. Results also highlight the possible ‘false economy’ in failing to promptly resolve long elective waits.

Peer Review reports

In the United Kingdom (UK), rising demand for healthcare has led to consistent increases in the size of waiting lists since 2014. As elective procedures were postponed during the pandemic, COVID-19 has accelerated this growth resulting in a substantial backlog of patients awaiting treatment. In July 2023, there were 7.7 million people in the UK waiting for treatment, an increase of over 50% compared to March 2020 [ 1 ].

The UK government announced an additional £8 billion over 3 years (2022–2025), allocated to the National Health Service (NHS) to tackle this backlog [ 2 , 3 ]. For the purpose of decreasing waiting list size, this additional resource could be invested in: alternative methods for prioritising patients waiting for treatment [ 4 ]; pooling patients into larger surgical regions [ 5 ]; increasing capacity via improving surgical schedules, recruitment or use of the private sector [ 6 , 7 ].

Alongside waiting list size, the median waiting time increased by more than 3 weeks during the COVID-19 pandemic [ 1 ]. In the UK there is an 18-week referral-to-treatment target [ 8 ]. Pre COVID, this target was being met for 86% of patients, however by March 2022 this had dropped to 62% [ 1 ]. For NHS services to optimise the value of interventions for tackling the waiting list backlog, not only does the resourcing of procedures need to be considered but also the additional resources consumed by people waiting for treatment.

The objective of this study is to quantify the difference in healthcare utilisation of people waiting over 18 weeks for treatment compared to a matched population not on a waiting list. Our results represent a first step in quantifying the hidden costs of keeping people waiting for treatment which is needed for determining care needs, minimising harm, and supporting future strategic planning.

Setting, design and population

We conducted a retrospective observational cohort study in Bristol, North Somerset and South Gloucestershire (BNSSG) Integrated Care System (ICS), which serves an approximate one million resident population in South West England across a mixture of urban, rural and coastal communities, with an overall age profile similar to that of England. The treatment group consisted of patients registered with a GP practice in BNSSG that were waiting over 18 weeks for treatment at any point in the period 15th June 2021 to 15th December 2021.

Referral to treatment

Referral to Treatment (RTT) data was obtained from NHS Digital via BNSSG ICS as a Commissioning Data Set [ 9 , 10 ]. Since 2007, this data has been submitted by healthcare providers to NHS Digital Secondary Uses Service (SUS) each month. SUS are responsible for collating the data which is used by health care providers and commissioners for service planning and evaluation [ 9 ].

The RTT data represents all patients referred for consultant-led elective care to 18 main specialties: General Surgery; Urology; Trauma and Orthopaedic; Ear Nose and Throat; Ophthalmology; Oral Surgery; Neurosurgical; Plastic Surgery; Cardiothoracic Surgery; General Internal Medicine; Gastroenterology; Cardiology; Dermatology; Respiratory Medicine; Neurology; Rheumatology; Elderly Medicine and Gynaecology. Referrals to specialties outside of these 18 are grouped under ‘Other’ and not included in this analysis. The data includes date of referral, specialty, pathway status (open or closed) and date treatment started for each patient pathway. In the context of RTT data, treatment starting is the first appointment with a specialist consultant.

Attributes and activity

Patient level data was obtained from the BNSSG System Wide Dataset (SWD) [ 11 ]. This dataset, which provides linkable data for 98.3% of the 1.07 million population of BNSSG, has been available since 2019. It contains two tables. The attributes table, generated from primary care data, is updated monthly and contains each person’s current demographic, socio-economic and clinical characteristics. The activity table contains information for all discrete patient contacts over the range of healthcare (points of delivery) within BNSSG ICS: Primary Care; Secondary Care; Helpline calls (the NHS 111 service); Emergency calls (the NHS 999 service); Community Services; Mental Health. Information is linked and pseudonymised by a third party, the NHS Commissioning Support Unit. Person Attributes and Activity are linkable through a unique patient identifier; a pseudonymised version of the NHS number. Data sources and descriptions are outlined in Table  1 .

Study covariates were obtained from the attributes table and included age, sex, socioeconomic status, and presence of chronic conditions. Socioeconomic status was measured using the Index of Multiple Deprivation (IMD). IMD quantifies the relative deprivation of geographical areas in England. In the SWD, the IMD of a person corresponds to the IMD of the area they live in. Presence of chronic conditions was measured using the Quality and Outcomes Framework (QOF) indicators. These indicators include 20 conditions that lead to a person requiring higher levels of healthcare: atrial fibrillation; coronary heart disease; heart failure; hypertension; peripheral arterial disease; stroke; asthma; chronic obstructive pulmonary disease; obesity; cancer; chronic kidney disease; diabetes; palliative care; dementia; depression; epilepsy; learning disabilities; mental health conditions; osteoporosis; arthritis.

For each person on one of the 18 waiting lists during the study period, a pool of controls was obtained from the SWD. Controls were randomly selected from the general population and matched to those on a waiting list, based on sex, 5-year age band, IMD quantile and individual QOF indicators (see above). Controls were excluded if they were on any waiting list during the study period.

For the treatment group, an individual study period was derived for each patient based on the time of referral and start of treatment (closed pathways). For the treatment group, follow up began at time of referral + 18 weeks, or study start date if already waiting > 18 weeks, and censored at date treatment started or end of the study period.

Mean activity per week, stratified by point of delivery, was determined for each participant. Activity was defined as a contact with each point of delivery, for example a GP appointment, a helpline call, etc. For the treatment group, activity directly associated with the referral, namely the GP appointment on the date of referral and the first outpatient appointment, i.e. the appointment associated with treatment starting, was not included in the analysis.

Patients in the treatment group can have more than one referral to a waiting list and be on waiting lists for multiple specialties. Where a patient had multiple referrals to one specialty, the first referral to a wait list was used, and start of treatment was defined as when all referrals were closed (i.e. the patient was no longer on the waiting list for that specialty). Specialities were analysed separately, as one patient could be on more than one waiting list.

Statistical analysis

Is there a difference in healthcare utilisation.

A one-sided Wilcoxon signed-rank test was used to determine whether there was a difference in mean activity between the treatment and control groups. Given the many control candidates for each patient on a waiting list (and the desire to avoid reliance on a single selection), repeat bootstrap sampling (1,000 times, with replacement) was used to produce a multitude of treatment-control pairs for each analysis. The Wilcoxon signed-rank test was performed to compare the mean weekly activity of the treatment with the control group. For each of the 18 services and 7 points of delivery this yielded 1,000 p-values. A median p-value of less than 0.0004 provided strong evidence of a difference in the mean weekly activity of treatments compared to controls. This threshold was obtained by applying the Bonferroni correction for 126 statistical tests to a p-value of 0.05. A 95% confidence interval was obtained by taking the 2.5% and 97.5% percentiles of the 1,000 calculated p-values.

What is the difference in healthcare utilisation?

To quantify the amount of additional healthcare utilisation we estimated the average difference in mean weekly healthcare contacts between the treatment and control group. We used repeat bootstrap sampling (1,000 times, with replacement). During each iteration we found the difference in mean weekly activity of each patient on the waiting list and a matched control. The median and inter-quartile range (IQR) of the distribution of differences was found for all treatment-control pairs, for each point of delivery and each specialty. Repeating this process 1,000 times resulted in distributions of median and IQR values. To summarise the amount of additional healthcare utilisation we reported the means of these distributions.

Population characteristics

Treatment group.

Of the 49,692 patients waiting over 18 weeks for treatment during the study period, 5076 had no matched controls and were excluded from the analysis. These patients had higher levels of multimorbidity, as measured by number of QOF conditions (Figure S1 ).

The final population consisted of 44,616 treatments across 18 specialties. Treatment characteristics for each speciality are shown in Table  2 . The number of patients on each waiting list varies from 29 for Cardiothoracic Surgery to 6,889 for Trauma and Orthopaedic.

Most services have an approximately equal number of male and female treatments, however there are some exceptions: Gynaecology and Rheumatology are predominantly female whereas the Urology Service is predominantly male (100%, 71% and 30% female respectively). The mean age of the treatment groups is 53 +/- 5 (mean +/- standard deviation) years for all services apart from Oral Surgery and Gynaecology where patients tend to be younger (31 +/- 21 and 42 +/- 15 years respectively) and Elderly Medicine which has a mean age of 77 +/- 8 years. Dermatology had the lowest percentage of patients who were from a low socio-economic background (IMD < 4 = 7.9%), whilst oral surgery had the highest (33.8%). The mean number of QOF conditions is lowest for Oral Surgery (0.51 +/- 0.86) and highest for Elderly Medicine (1.67 +/- 1.34) reflecting the age difference of treatments across specialties. The number of controls per treatment is also reflective of this age difference, with Oral Surgery having the greatest (756.32 +/- 387.53) and Elderly Medicine having the least (200.38 +/- 334.82).

Healthcare utilisation

Across the 7 points of delivery, healthcare utilisation in the treatment group is greatest for primary care, prescriptions, and secondary care (Table  3 ). Patients waiting for Cardiothoracic Surgery have the greatest utilisation with a median of 3 [IQR: 1, 7.5] contacts with primary care, 15 [3, 33.5] prescriptions and 5.5 [2.25, 9] contacts with secondary care. For community services, mental health, helpline calls and emergency calls, the overall number of contacts during a treatment’s individual study period were very low: the median number of contacts is 0 for all four points of delivery (Table  3 ). Controls had lower healthcare utilisation during the study periods, with prescriptions being the only point of delivery where the median number of contacts is non-zero (Table  3 ).

There is evidence of a difference in the healthcare utilisation of patients waiting over 18 weeks for treatment compared to matched controls (Table S1 ). On average, patients waiting for treatment have more contacts with primary care, secondary care, helpline calls and prescriptions compared to those not waiting for treatment ( p  < 0.0004, ‘All Specialties’, Table S1 ). In all specialties, the secondary care utilisation of patients waiting for treatment is greater than matched controls ( p  < 0.0004). Cardiothoracic Surgery and Elderly Medicine are the only specialties for which there is little evidence of an increased use of primary care across the two groups ( p  = 0.0321 [0.0011, 0.2519] and p  = 0.0024 [0.0001, 0.0463] respectively). There is strong evidence that patients waiting for the General Surgery, Urology, Neurology and Gastroenterology services show increased utilisation across all points of delivery ( p  < 0.0004), compared to controls. In contrast, patients waiting for Cardiothoracic Surgery show an increased utilisation in secondary care only.

Patients waiting over 18 weeks for treatment demonstrate higher levels of healthcare utilisation than patients not waiting for treatment (Fig.  1 , Table S2 ). The additional healthcare utilisation is greatest for primary care prescriptions, followed by secondary care. Patients waiting for the Cardiothoracic Surgery service have a median of 17.9 [4.3, 33.8] additional contacts with secondary care and 17.3 [-1.1, 34.1] additional prescriptions per year compared to matched controls not waiting for treatment. Patients waiting for this service also show the largest median increase in the number of GP appointments (‘primary care contact’) (5.5 [-0.3, 15.9]), however in this point of delivery at least 25% of people waiting for Cardiothoracic Surgery show no increase in utilisation (25th percentile < 0). Of the 18 specialties, patients waiting for the Oral Surgery, Ophthalmology, Gynaecology and Dermatology services had median increases of 0.0 across all points of delivery: at least 50% of patients waiting for these services had no additional healthcare utilisation in all points of delivery (Table S2 ). The helpline calls, emergency calls, community and mental health services show the smallest increases in healthcare utilisation (Table S2 ), with these services not used at all by more than 75% of patients in both groups. This suggests that the increased utilisation for some of these services ( p  < 0.0004) can be attributed to less than 25% of the people waiting for treatment.

Additional yearly contacts with primary care, primary care prescriptions, and secondary care for patients waiting for treatment (treatments) compared to matched controls. Additional contacts per person per year were obtained by bootstrap sampling controls for each treatment 1000 times, resulting in 1000 distributions. Black dots represent the median additional contacts per person per year, obtained by averaging the median values of the 1000 distributions. Red lines represent the mean 25th percentile and 75th percentile (interquartile range) of the 1000 distributions of additional contacts, per person, per year. For specialties where there was no evidence of a difference in utilisation ( p  > 0.0004), results are displayed in grey

Our study marks an initial step in quantifying the hidden cost of increases in waiting list size and waiting times. Using a retrospective cohort study design we have demonstrated that the healthcare utilisation of patients waiting over 18 weeks for treatment is greater than a matched population not waiting for treatment. We found evidence of increases in healthcare utilisation in each specialty and across all points of delivery, however the size of the differences varied: patients waiting for the Cardiothoracic Surgery service showed the greatest increase, while at least 50% of patients waiting for the Oral Surgery, Ophthalmology, Gynaecology and Dermatology services had no additional healthcare utilisation. The largest increases were seen across primary care prescriptions and secondary care. Mental health services, emergency calls and helpline calls had the smallest differences. Our results demonstrate the burden of increasing waiting times on both patients and health services.

We selected our control group as people not waiting for treatment, to quantify the additional healthcare utilisation due to patients not being seen within the NHS 18-week target. Our rationale for this choice of control group is that, if a patient starts treatment within the 18-week target, their healthcare need is being met. Once treatment is completed a patient’s healthcare need should be comparable to a similar person (in terms of our matching criteria) that hadn’t required treatment. In contrast, when a patient is waiting longer than the 18-week target, their need is not being met. By comparing the healthcare utilisation of people waiting over 18 weeks for treatment to people not waiting for treatment, we are estimating the additional burden on health services due to the inability to meet the 18-week target for many patients.

Treatments were matched to controls based on sex, 5-year age band, IMD quantile and twenty long-term conditions (QOF indicators). QOF indicators were included in the matching criteria to control for differences in baseline healthcare need between treatments and controls; many of these conditions require long-term management, the nature of which will vary between indicators, but will be evident in a patient’s health service utilisation. Although these matching criteria are stringent, it is not possible to conclude with certainty that the differences in health service utilisation seen in this study are caused by waiting over 18-weeks for treatment. In terms of comorbidities, the twenty QOF indicators included are not exhaustive, and patients waiting for treatment may have additional comorbidities that are not accounted for in the matching. In addition, the QOF indicators themselves may introduce confounding; although QOF indicators mark the presence of a diagnosis, they do not measure the severity of the underlying condition. Severity may be considered a confounder in our study; if patients are waiting for a treatment in relation to a QOF condition, this condition is likely to be more severe, and require greater levels of long-term management. However, had such a patient received treatment within the 18-week target, we would expect the difference in healthcare utilisation to be lower.

Our study population shows that the number of people waiting over 18 weeks for treatment varies between specialties (Table  2 ). This variation is likely due to differences in both demand and capacity across the specialties. As our analysis has been carried out in each specialty independently, these differences in population size need to be considered when comparing results between specialties. For example, patients waiting for Cardiothoracic Surgery show the greatest increase in secondary care utilisation (median 17.9 additional contacts per year, Table S2 ), however this specialty also has the smallest sample size (29 patients, Table  2 ), therefore in total this corresponds to approximately 520 additional contacts with secondary care per year. In contrast, patients waiting for Respiratory Medicine have, on average, fewer additional contacts with secondary care (median 5.9, Table S2 ) but as this population is larger (1342 patients, Table  2 ), this represents a higher burden on secondary care in this healthcare system: approximately 7900 additional contacts over the course of a year.

A consequence of the differences in population size across specialties is that, for some specialties, the population may represent low priority, less urgent referrals, who are waiting longer due to the prioritisation of more urgent cases. In contrast, for other specialties, the population may contain a mix of both urgent and non-urgent referrals, who are waiting over 18-weeks due to increased demand, reduced capacity, or both. This is a limitation of our study: we have not controlled for referral priority within the treatment groups, and more urgent cases are likely to have a higher healthcare need while waiting for treatment to start. However, although this affects comparisons between specialties, it should not affect specialty level results: within each specialty the population waiting over 18-weeks for treatment represents how wait lists are managed for that specialty, therefore our results represent what is typical for each specialty within the locality.

Our study period covers the six months immediately following the easing of restrictions in the UK that were in place due to the COVID-19 pandemic, and a time when UK policy was focussed on the recovery of elective services. Throughout the study period there were no further restrictions in place, however during the study period healthcare utilisation may still have been impacted by the pandemic; an analysis of private healthcare utilisation in the UK from January 2018 to August 2020 found, at the end of this period, utilisation had not returned to pre-pandemic levels [ 12 ]. On the one hand this may be seen as a limitation of our study; if healthcare utilisation had not returned to pre-pandemic levels during our study period, our results may overestimate the difference in activity between treatment and controls. However, by comparing activity differences of treatments and controls over weekly time-windows, our study design reduces the effect of longitudinal, population-level, changes in healthcare utilisation, therefore our estimates are unlikely to be impacted by changes in utilisation due to covid.

This is one of the first studies to consider the wider implications of long waiting times for patients and health services. From a value-based perspective, knowledge of the amount of extra resource being spent on patients while waiting for treatment is crucial to optimising the cost-effectiveness of any intervention to reduce waiting list size. The objective of our study was to determine whether there was an increase in healthcare utilisation when waiting for treatment. By quantifying the magnitude of this increase, our results will assist strategic planners in assigning a cost to waiting times and waiting list size.

The additional service utilisation of patients waiting over 18 weeks for treatment should be considered as an example of failure-demand within the health service: if patients received treatment earlier, they would not be requiring additional support over a prolonged period. Previous work has demonstrated how failure-demand generated by one component of a health system results in demand being deflected to other components [ 13 , 14 ]. The consequence is an increase in pressure elsewhere in the system and a negative impact on patient experience [ 13 ]. In combination with our results, this highlights the need for a whole-system approach to tackling the waiting list backlog: a thorough evaluation of interventions, such as increasing surgical capacity and revising existing methods for prioritising patients, requires consideration of the impact on the health service as a whole.

We have provided evidence that patients waiting for treatment in the UK have higher levels of healthcare utilisation than people not waiting for treatment. Our results can be used to evaluate the cost-effectiveness of interventions to reduce the waiting list backlog. The evidence of increased healthcare utilisation highlights the need for a whole-system approach to tackling the waiting list backlog.

Data availability

Data analysed during this study cannot be made available due to local restrictions on public sharing of patient-level information.

Abbreviations

United Kingdom

National Health Service

Bristol, North Somerset and South Gloucestershire

Integrated Care System

Referral to Treatment

Secondary Uses Service

System Wide Dataset

Index of Multiple Deprivation

Quality and Outcomes Framework

Inter-quartile range

Statistics » Consultant-. led Referral to Treatment Waiting Times [Internet]. [cited 2022 May 27]. https://www.england.nhs.uk/statistics/statistical-work-areas/rtt-waiting-times/ .

Build Back Better. Our Plan for Health and Social Care [Internet]. GOV.UK. [cited 2022 May 27]. https://www.gov.uk/government/publications/build-back-better-our-plan-for-health-and-social-care/build-back-better-our-plan-for-health-and-social-care .

Mahase E. NHS gets £5.9bn funding boost in autumn budget to tackle waiting lists in England. BMJ. 2021;375:n2637.

Article   PubMed   Google Scholar  

Rathnayake D, Clarke M, Jayasinghe V. Patient prioritisation methods to shorten waiting times for elective surgery: a systematic review of how to improve access to surgery. PLoS ONE. 2021;16(8):e0256578.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Clarke J, Murray A, Markar SR, Barahona M, Kinross J, PanSurg C. New geographic model of care to manage the post-COVID-19 elective surgery aftershock in England: a retrospective observational study. BMJ Open. 2020;10(10):e042392.

Oussedik S, MacIntyre S, Gray J, McMeekin P, Clement ND, Deehan DJ. Elective orthopaedic cancellations due to the COVID-19 pandemic: where are we now, and where are we heading? Bone Jt Open. 2021;2(2):103–10.

Article   PubMed   PubMed Central   Google Scholar  

Macdonald N, Clements C, Sobti A, Rossiter D, Unnithan A, Bosanquet N. Tackling the elective treatment backlog generated by Covid-19: the scale of the problem and solutions. J Public Health (Oxf). 2020;42(4):712–6.

Consultant-led treatment. right to start within 18 weeks [Internet]. GOV.UK. [cited 2022 May 27]. https://www.gov.uk/government/publications/right-to-start-consultant-led-treatment-within-18-weeks .

Commissioning Data Sets Introduction [Internet]. [cited 2022 Sep 6]. https://www.datadictionary.nhs.uk/supporting_information/commissioning_data_sets_introduction.html .

Changes to the NHS Data Dictionary to support the measurement of 18 week referral to treatment periods (DSCN 18/2006) [Internet]. [cited 2022 Sep 6]. https://webarchive.nationalarchives.gov.uk/ukgwa/+/http://www.isb.nhs.uk/library_old/dscn//dscn2006/182006.pdf .

Population Health Management [Internet]. Healthier Together. [cited 2022 Sep 6]. https://bnssghealthiertogether.org.uk/population-health-management/ .

Howarth A, Munro M, Theodorou A, et al. Trends in healthcare utilisation during COVID-19: a longitudinal study from the UK. BMJ Open. 2021;11:e048151. https://doi.org/10.1136/bmjopen-2020-048151 .

Walley P, Found P, Williams S. Failure demand: a concept evaluation in UK primary care. Int J Health Care Qual Assur. 2019;32(1):21–33. https://doi.org/10.1108/IJHCQA-08-2017-0159 . PMID: 30859878.

Abbasi AA, Khan S, Ameh V, Muhammad I. The impact of GP referrals on overcrowding in emergency departments and acute medicine. Br J Healthc Manage. 2021;27(2):1–6.

Article   Google Scholar  

Download references

Acknowledgements

This research was supported by the National Institute for Health and Care Research Applied Research Collaboration West (NIHR ARC West). The views expressed in this article are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.

CJ and RD are funded by NIHR Bristol BRC (BRC-1215-20011). CJ is funded by National Institute for Health and Care Research Applied Research Collaboration West (NIHR ARC West) and NIHR Research Capability Funding (RCF 21/22 − 4.2). RD is funded by HDR UK South West CFC0129.

Author information

Authors and affiliations.

The National Institute for Health and Care Research Bristol Biomedical Research Centre (NIHR Bristol BRC), University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, Bristol, UK

Charlotte James & Rachel Denholm

The National Institute for Health and Care Research Applied Research Collaboration West (NIHR ARC West) at University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK

Charlotte James

Population Health Sciences, Bristol Medical School, Bristol, UK

Modelling and Analytics, UK National Health Service (BNSSG ICB), Bristol, UK

Charlotte James & Richard Wood

Health Data Research UK South West, Bristol, UK

Rachel Denholm

Centre for Healthcare Innovation and Improvement (CHI2), School of Management, University of Bath, Bath, UK

Richard Wood

You can also search for this author in PubMed   Google Scholar

Contributions

All authors contributed to the design of the study. CJ acquired the data, carried out the modelling and analysis and drafted the manuscript. All authors contributed to the final version of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Charlotte James .

Ethics declarations

Ethics approval and consent to participate.

Informed consent for this study was waived by Yorkshire & The Humber Leeds East Research Ethics Committee, who granted NHS HRA Research Database approval for the Bristol, North Somerset, and South Gloucestershire (BNSSG) system-wide database in 2020 (REC Reference Number: 20/YH/0185, date: 28 July 2020). Ethical approval is given for processing of personal data by the research database team for research conducted on COVID-19-related priority areas identified by the wider health and care system (in accordance with the Health Service Control of Patient Information Regulations 2002 (COPI) directive for COVID-19-related analyses). Under General Data Protection Regulation (GDPR), the data controller was BNSSG Clinical Commissioning Group. The data from general practice electronic medical records were extracted according to existing data sharing agreements and in line with GDPR and Caldicott principles under pandemic conditions and in accordance with government guidelines and the COPI directive.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

James, C., Denholm, R. & Wood, R. The cost of keeping patients waiting: retrospective treatment-control study of additional healthcare utilisation for UK patients awaiting elective treatment. BMC Health Serv Res 24 , 556 (2024). https://doi.org/10.1186/s12913-024-10931-2

Download citation

Received : 10 October 2023

Accepted : 29 March 2024

Published : 30 April 2024

DOI : https://doi.org/10.1186/s12913-024-10931-2

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Elective recovery
• Waiting times
• Utilisation
• Failure-demand

BMC Health Services Research

ISSN: 1472-6963

• General enquiries: [email protected]

Numbers, Facts and Trends Shaping Your World

Read our research on:

Full Topic List

Regions & Countries

• Publications
• Our Methods
• Short Reads
• Tools & Resources

Read Our Research On:

• Americans Remain Critical of China

Many see China as increasingly influential and consider limiting its power a top priority

Table of contents.

• Unfavorable views of China prevail
• China’s role in the world
• China’s territorial disputes
• Americans lack confidence in Xi Jinping
• Americans increasingly see China as an enemy
• Limiting China’s power and influence
• China’s economic influence on the U.S.
• Acknowledgments
• The American Trends Panel survey methodology

Pew Research Center conducted this study to understand Americans’ opinions of China, its role in the world and its impact on the U.S. economy. For this analysis, we surveyed 3,600 U.S. adults from April 1 to April 7, 2024. Everyone who took part in this survey is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology .

Here are the questions used for this analysis, along with responses, and its methodology .

For the fifth year in a row, about eight-in-ten Americans report an unfavorable view of China, according to a new Pew Research Center survey. Today, 81% of U.S. adults see the country unfavorably, including 43% who hold a very unfavorable opinion. Chinese President Xi Jinping receives similarly negative ratings.

Still, many Americans agree that China’s influence in the world has been getting stronger in recent years (71%). This sense is accompanied by concern about how China interacts with other nations: 61% of Americans are at least somewhat concerned about China’s territorial disputes with neighboring countries. (For more U.S. views of China’s role in the world, go to Chapter 1 .)

When it comes to China’s relationship with the United States, few see China as a partner (6%) and most Americans instead label it a competitor (50%) or an enemy (42%) of the U.S. They are likewise critical of China’s impact on the U.S. economy, describing its influence as large and negative. Roughly half of Americans think limiting China’s power and influence should be a top U.S. foreign policy priority, and another 42% think this should be given some priority. (For more assessments of China’s relationship with the U.S., go to Chapter 2 .)

According to the Center survey, which was conducted April 1-7, 2024, among 3,600 U.S. adults, Republicans are more wary of China than Democrats are.

Republicans and Republican-leaning independents are about twice as likely as Democrats and Democratic leaners to hold a very unfavorable view of China and to consider China an enemy of the U.S. They are also more likely to say that China has recently become more influential.

Republicans also have wider ideological differences within their party, and conservative Republicans stand out on many measures :

• Conservative Republicans are 25 percentage points more likely than moderate and liberal Republicans to express a very unfavorable view of China (68% vs. 43%). There is no difference between liberal Democrats and moderate and conservative Democrats on this question.
• Conservative Republicans are also 31 points more likely than moderate and liberal Republicans to see China as an enemy of the U.S. No ideological difference is present among Democrats.
• While 83% of conservative Republicans say China’s influence in the world has been getting stronger in recent years, 68% of moderate and liberal Republicans say the same. The latter is similar to the shares of moderate and conservative Democrats (67%) and liberal Democrats (69%) who hold this view.

Older Americans are generally more critical of China. A 61% majority of adults ages 65 and older have a very unfavorable view of China, compared with 27% of adults under 30. Adults ages 65 and older are also more than twice as likely as those ages 18 to 29 to see China as an enemy of the U.S. For their part, younger adults are more likely than older ones to label China as a competitor and as a partner.

Older Americans also perceive more growth in China’s international influence. Roughly three-quarters of adults ages 65 and older say China’s influence has been getting stronger in recent years, while about two-thirds of adults under 30 say the same.

Americans with a sour view of the U.S. economy have more critical opinions of China. Those who say the current U.S. economic situation is bad are more likely to hold an unfavorable opinion of China and to say China has a great deal or fair amount of negative influence on the U.S. economy. They are also more likely to see China as an enemy when compared with those who see the economy positively.

Sign up for our weekly newsletter

Fresh data delivery Saturday mornings

Sign up for The Briefing

Weekly updates on the world of news & information

• China Global Image
• Global Balance of Power
• Global Economy & Trade
• International Affairs

How people in Hong Kong view mainland China and their own identity

In east asia, many people see china’s power and influence as a major threat, u.s.-germany relationship remains solid, but underlying policy differences begin to show, how views of the u.s., china and their leaders have changed over time, comparing views of the u.s. and china in 24 countries, most popular, report materials.

1615 L St. NW, Suite 800 Washington, DC 20036 USA (+1) 202-419-4300 | Main (+1) 202-857-8562 | Fax (+1) 202-419-4372 |  Media Inquiries

Research Topics

• Age & Generations
• Coronavirus (COVID-19)
• Economy & Work
• Family & Relationships
• Gender & LGBTQ
• Immigration & Migration
• Internet & Technology
• Methodological Research
• News Habits & Media
• Non-U.S. Governments
• Other Topics
• Politics & Policy
• Race & Ethnicity
• Email Newsletters

ABOUT PEW RESEARCH CENTER  Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of  The Pew Charitable Trusts .

Copyright 2024 Pew Research Center

Terms & Conditions

Privacy Policy

Cookie Settings

Reprints, Permissions & Use Policy

Study Shows How Higher Education Supports Asian American, Native Hawaiian, and Pacific Islander Students Through Culturally Relevant Courses, Programs, and Research

Analysis of minority-serving institutions on the East and West Coasts demonstrates layered processes to build students’ capacities

The model minority myth paints a picture of Asian Americans as a monolithic group with unparalleled success in academics. A new NYU study unpacks this myth, exploring the needs of Asian American, Native Hawaiian, and Pacific Islander students and how higher education institutions support these populations.

In 2007, Congress established a federal designation for higher education institutions that enroll at least 10 percent of undergraduate Asian American, Native Hawaiian, and Pacific Islander (AA&NHPI) students, and who enroll a significant proportion of students from low socioeconomic backgrounds. This designation as an Asian American and Native American Pacific Islander Serving Institution (AANAPISI) was among one of the newest categories of minority-serving institutions that receive federal funding to advance educational equity and support for ethnic and racial minorities.

In a two-site case study, Mike Hoa Nguyen , assistant professor of education at NYU Steinhardt, collected data from interviews, internal and public university documents, and observations of activities, courses, and meetings to determine the process in which AANAPISI programs expand students’ capacities through culturally relevant coursework, mentorship, research, and civic engagement. His findings are published in The Review of Higher Education .

“AANAPISIs demonstrate a federal commitment to supporting the unique educational needs of AA&NHPI students, which are too often obscured by the model minority myth,” said Nguyen. “This myth dangerously asserts that Asian American students, and Native Hawaiian and Pacific Islander students by association, are universally successful and unparalleled in their academic achievements. AANAPISIs play a major role in addressing this problem, and in doing so, provide critical resources to uplift the students they serve. This study documents the process in which these colleges and universities engage in this important work.”

Nguyen's study centered on a large, public community college on the West Coast and a large, urban, regional public university on the East Coast. Nguyen’s findings related to the experiences of students in these programs.

He uncovered a five-tiered process that the two institutions use to build opportunities for learning, practice, and engagement:

AA&NHPI Focused Coursework At both institutions, courses focused on these populations are offered through the institutions’ Asian American Studies programs, where students are exposed to concepts connected to their racial and ethnic identities. One student shared her experience with a course, Asian Women in the United States, “Through my experience with that class I learned…for the first time, issues that affected my community. Specifically, me as an Asian American woman, specifically Vietnamese American…”

Teaching and Mentoring Students who had previously taken AA&NHPI coursework provided tutoring and mentoring to support new students with classwork, programs, books, and scholarship applications.  According to one mentor, “Cambodian Americans fall through the cracks, we’re just not in higher ed…It’s not a supportive space for us…[the AANAPISI faculty] understand…from their own community work, from being on campus, and [from] teaching for so long that…when they find students who fit these demographics it makes sense for them to mentor them.”

Advanced AA&NHPI Focused Coursework After serving as mentors, students often take more advanced courses focused on theoretical, historical, and contemporary issues regarding the AA&NHPI experience to continue their academics while gaining tools to make larger contributions toward their communities. 

Academic and Research Development Students who complete advanced coursework are provided opportunities to engage in academic projects and research with faculty and staff, presenting research at conferences or publishing in peer-reviewed journals. 

Professional and Community Experience The final step in the process offers opportunities for students to engage in community-based projects, internships, and employment with partner organizations, government offices, or other schools. A student shared that his research experience led to the creation of a Vietnamese American organizing and training program. “[Researchers] found out that Vietnamese Americans in [the neighborhood] don't participate in civics or politics…they basically feel disenfranchised, like their vote doesn’t matter…So, the research showed that there needs to be an organization to help push and provide opportunities to talk about politics in a Vietnamese American progressive context…”

“AANAPISIs are the backbone for AA&NHPI students in higher education. These institutions account for six percent of all colleges and universities, yet enroll over 40 percent of all AA&NHPI undergraduates,” said Nguyen. “This study offers new understandings of the critical role that AANAPISIs play to expand educational opportunity and enrich learning experiences—which can be adopted beyond AANAPISIs and for other students—as well as inform the work of policymakers as they seek new solutions to refine and regulate the administration of minority-serving institutions.”

Funding for this study was provided by the UCLA Institute of American Cultures and the UCLA Asian American Studies Center. 

Press Contact

share this!

May 8, 2024

This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:

fact-checked

peer-reviewed publication

trusted source

Marine bacteria team up to produce a vital vitamin

by University of Oldenburg

A German-American research team led by microbiologist Dr. Gerrit Wienhausen from the University of Oldenburg (Germany) has come an important step closer to a better understanding of highly complex interactions between marine microorganisms. The researchers conducted various experiments to analyze the interaction between two species of marine bacteria from the North Sea in the synthesis of vitamin B12, and published their findings in the journal Nature .

Vitamin B12 is a vital but scarce commodity in the sea (and elsewhere). It is essential not only for the metabolism of the two bacteria investigated in this study, but for many other marine organisms. "Half of all algal species cannot survive without this vitamin," Wienhausen explains. Yet like humans, algae cannot produce B12 themselves. So the researchers from the University of Oldenburg and the Scripps Institution of Oceanography in San Diego (U.S.) were eager to take a closer look at B12 synthesis in marine bacteria.

While certain bacterial strains are known as vitamin B12 producers, this research project focused on two strains of the Roseovarius and Colwellia genera that each produce just one of the two building blocks of vitamin B12, meaning that they can only synthesize the substance in cooperation with each other.

"It's fascinating how complex the interactions between bacteria can be," emphasizes Wienhausen with reference to the new study, which was conducted as part of the Roseobacter Collaborative Research Center headed by Oldenburg microbiologist Prof. Dr. Meinhard Simon, who also co-authored the current publication.

Complex interactions between two strains of bacteria

Using complex lab experiments and cutting-edge analytical tools, the researchers were able to explore the interactions between the two bacterial strains in detail. According to their findings, bacteria of the Colwellia strain M166 synthesize the smaller building block for vitamin B12 and release it into the surrounding water. For their part, the bacteria of the Roseovarius strain M141 not only produce the larger building block—which is the main component—but are also able to synthesize the B12 that both bacterial strains require from the combination of the two building blocks.

However, the Roseovarius strain doesn't release the vitamin on its own, but only once Colwellia activates a virus encoded in the bacterial genome of its co-producer and the virus multiplies. The resulting viral infection causes some of the affected Roseovarius bacteria to burst, and vitamin B12 is released alongside the virus, thus becoming available to Colwellia (and possibly other marine organisms, too).

"This fine-tuned cross-feeding of metabolic building blocks and products may not only be relevant in marine microbial communities but also in other ecosystems," the researchers from the Oldenburg Institute for Chemistry and Biology of the Marine Environment (ICBM) and the Scripps Institution of Oceanography report.

"We were able to demonstrate for the first time that two bacteria only synthesize B12 in cooperation with each other," says Wienhausen. "Such a complex form of interaction between bacteria was previously unknown."

More than 60 researchers from Oldenburg, Braunschweig, Göttingen and Bonn investigated the bacteria of the Roseobacter group over the past 13 years within the Transregional Collaborative Research Center (CRC) Roseobacter.

These bacteria are found in all marine habitats—from the tropics to the polar seas and from the sea surface to the deep sea. Among other achievements, the researchers have discovered many new strains and described their distribution and functional biogeography in the world's oceans for the first time. More than 280 scientific articles based on research conducted within the context of the CRC have been published to date.

Journal information: Nature

Provided by University of Oldenburg

Explore further

Feedback to editors

New phononics materials may lead to smaller, more powerful wireless devices

8 hours ago

New 'forever chemical' cleanup strategy discovered

9 hours ago

TESS discovers a rocky planet that glows with molten lava as it's squeezed by its neighbors

Ultrasound experiment identifies new superconductor

10 hours ago

Quantum breakthrough sheds light on perplexing high-temperature superconductors

How climate change will affect malaria transmission

11 hours ago

Topological phonons: Where vibrations find their twist

Looking for life on Enceladus: What questions should we ask?

Analysis of millions of posts shows that users seek out echo chambers on social media

NASA images help explain eating habits of massive black hole

Relevant physicsforums posts, who chooses official designations for individual dolphins, such as fb15, f153, f286.

17 hours ago

Is it usual for vaccine injection site to hurt again during infection?

The cass report (uk).

May 1, 2024

Is 5 milliamps at 240 volts dangerous?

Apr 29, 2024

Major Evolution in Action

Apr 22, 2024

If theres a 15% probability each month of getting a woman pregnant...

Apr 19, 2024

More from Biology and Medical

Related Stories

Study shows diatoms provide an attractive habitat for bacteria

Apr 19, 2023

Vitamin B12 adaptability in Antarctic algae has implications for climate change, life in the Southern Ocean

Feb 5, 2024

Bacteria can boost fitness of their host

Sep 27, 2021

Study reveals how marine bacteria combat algae

Sep 27, 2023

New species of marine bacteria isolated from a deep-sea cold seep

Aug 29, 2023

A new cholera strain replaced older strains during the seventh cholera pandemic

Jan 7, 2022

Recommended for you

AlphaFold 3 upgrade enables the prediction of other types of biomolecular systems

16 hours ago

For sustainable aviation fuel, researchers engineer a promising microorganism for precursor production

14 hours ago

Changes in pig farming in the 20th century spread antibiotic-resistant Salmonella around the world, finds study

New rhizobia-diatom symbiosis solves long-standing marine mystery

How aging clocks tick: New study points to stochastic changes in cells

15 hours ago

Let us know if there is a problem with our content

Use this form if you have come across a typo, inaccuracy or would like to send an edit request for the content on this page. For general inquiries, please use our contact form . For general feedback, use the public comments section below (please adhere to guidelines ).

Please select the most appropriate category to facilitate processing of your request

Thank you for taking time to provide your feedback to the editors.

Your feedback is important to us. However, we do not guarantee individual replies due to the high volume of messages.

E-mail the story

Your email address is used only to let the recipient know who sent the email. Neither your address nor the recipient's address will be used for any other purpose. The information you enter will appear in your e-mail message and is not retained by Phys.org in any form.

Newsletter sign up

Get weekly and/or daily updates delivered to your inbox. You can unsubscribe at any time and we'll never share your details to third parties.

More information Privacy policy

Donate and enjoy an ad-free experience

We keep our content available to everyone. Consider supporting Science X's mission by getting a premium account.

E-mail newsletter

• Global (EN)
• Albania (en)
• Algeria (fr)
• Argentina (es)
• Armenia (en)
• Australia (en)
• Austria (de)
• Austria (en)
• Azerbaijan (en)
• Bahamas (en)
• Bahrain (en)
• Bangladesh (en)
• Barbados (en)
• Belgium (en)
• Belgium (nl)
• Bermuda (en)
• Bosnia and Herzegovina (en)
• Brasil (pt)
• Brazil (en)
• British Virgin Islands (en)
• Bulgaria (en)
• Cambodia (en)
• Cameroon (fr)
• Canada (en)
• Canada (fr)
• Cayman Islands (en)
• Channel Islands (en)
• Colombia (es)
• Costa Rica (es)
• Croatia (en)
• Cyprus (en)
• Czech Republic (cs)
• Czech Republic (en)
• DR Congo (fr)
• Denmark (da)
• Denmark (en)
• Ecuador (es)
• Estonia (en)
• Estonia (et)
• Finland (fi)
• France (fr)
• Georgia (en)
• Germany (de)
• Germany (en)
• Gibraltar (en)
• Greece (el)
• Greece (en)
• Hong Kong SAR (en)
• Hungary (en)
• Hungary (hu)
• Iceland (is)
• Indonesia (en)
• Ireland (en)
• Isle of Man (en)
• Israel (en)
• Ivory Coast (fr)
• Jamaica (en)
• Jordan (en)
• Kazakhstan (en)
• Kazakhstan (kk)
• Kazakhstan (ru)
• Kuwait (en)
• Latvia (en)
• Latvia (lv)
• Lebanon (en)
• Lithuania (en)
• Lithuania (lt)
• Luxembourg (en)
• Macau SAR (en)
• Malaysia (en)
• Mauritius (en)
• Mexico (es)
• Moldova (en)
• Monaco (en)
• Monaco (fr)
• Mongolia (en)
• Montenegro (en)
• Mozambique (en)
• Myanmar (en)
• Namibia (en)
• Netherlands (en)
• Netherlands (nl)
• New Zealand (en)
• Nigeria (en)
• North Macedonia (en)
• Norway (nb)
• Pakistan (en)
• Panama (es)
• Philippines (en)
• Poland (en)
• Poland (pl)
• Portugal (en)
• Portugal (pt)
• Romania (en)
• Romania (ro)
• Saudi Arabia (en)
• Serbia (en)
• Singapore (en)
• Slovakia (en)
• Slovakia (sk)
• Slovenia (en)
• South Africa (en)
• Sri Lanka (en)
• Sweden (sv)
• Switzerland (de)
• Switzerland (en)
• Switzerland (fr)
• Taiwan (en)
• Taiwan (zh)
• Thailand (en)
• Trinidad and Tobago (en)
• Tunisia (en)
• Tunisia (fr)
• Turkey (en)
• Turkey (tr)
• Ukraine (en)
• Ukraine (ru)
• Ukraine (uk)
• United Arab Emirates (en)
• United Kingdom (en)
• United States (en)
• Uruguay (es)
• Uzbekistan (en)
• Uzbekistan (ru)
• Venezuela (es)
• Vietnam (en)
• Vietnam (vi)
• Zambia (en)
• Zimbabwe (en)
• Financial Reporting View
• Women's Leadership
• Corporate Finance
• Board Leadership
• Executive Education

Fresh thinking and actionable insights that address critical issues your organization faces.

• Insights by Industry
• Insights by Topic

KPMG's multi-disciplinary approach and deep, practical industry knowledge help clients meet challenges and respond to opportunities.

• Advisory Services
• Audit Services
• Tax Services

Services to meet your business goals

Technology Alliances

KPMG has market-leading alliances with many of the world's leading software and services vendors.

Helping clients meet their business challenges begins with an in-depth understanding of the industries in which they work. That’s why KPMG LLP established its industry-driven structure. In fact, KPMG LLP was the first of the Big Four firms to organize itself along the same industry lines as clients.

• Our Industries

How We Work

We bring together passionate problem-solvers, innovative technologies, and full-service capabilities to create opportunity with every insight.

• What sets us apart

Careers & Culture

What is culture? Culture is how we do things around here. It is the combination of a predominant mindset, actions (both big and small) that we all commit to every day, and the underlying processes, programs and systems supporting how work gets done.

Relevant Results

Sorry, there are no results matching your search..

• KPMG Corporate Communications
• Multimedia Resources
• News about KPMG

Navigating The AI Era In Financial Reporting

Opportunities, Risks, and Investments Trends to Enhance Trust through Technology 

• In the next three years, 100% of U.S. financial reporting leaders report they will be either piloting or using AI in financial reporting, up from 71% today.
• As for generative AI, 97% will be either piloting or using the technology in financial reporting in three years, up from 46% today. In fact, GenAI is the most prioritized technology among U.S. financial reporting leaders in the coming year.
• Survey finds the top five benefits of AI in financial reporting are real-time insights into risks, fraud, and control weaknesses (70%); lower costs (58%), ability to predict trends and impacts (57%), increased data accuracy and reliability (57%), and better data-enabled decisions (53%).
• In 2023, 61% of financial reporting leaders said that it was important for auditors to utilize AI in performing their analyses; today that number is 83%. Businesses expect their auditors to conduct a more detailed review of the control environment (66%) and assess their AI governance maturity (61%).

New York, May 8, 2024 – All U.S. financial reporting leaders surveyed report they expect to be piloting or using artificial intelligence (“AI”) in financial reporting within three years, and 97% expect to be doing the same with generative AI (“GenAI”), according to a new survey released today by KPMG LLP, the U.S. audit, tax, and advisory firm.

This new survey finds U.S. businesses will continue to invest more of their IT budget in AI-related activities, with GenAI being the top priority next year. Meanwhile, financial reporting leaders are focused on navigating risks by becoming AI ready and expect their external auditor to not only use AI and GenAI in the audit, but also use professional judgement to evaluate control environments. This includes conducting third-party attestation over companies' use of AI as well as providing insights on a company’s AI governance maturity.

“It’s clear that financial reporting leaders are rapidly accelerating investments to use AI and GenAI to not just gain efficiencies but create more value for their organizations by predicting trends and identifying emerging risks," said Scott Flynn, KPMG U.S. Vice Chair - Audit . “Understanding the range of complementary investments in cloud, data, and governance is critical for both financial reporting leaders and external auditors to mitigate risks from this rapid transformation.”

The findings come from KPMG’s latest survey, published in the report AI in Financial Reporting and Audit: Navigating the New Era . The survey was conducted among 1,800 companies across ten major markets. Key perspectives and findings from 300 U.S. respondents are highlighted below. They expand upon the findings from the October 2023 U.S. survey, AI’s Role in Enhancing Trust in Financial Reporting and the Capital Markets . 

Key takeaways from the survey are highlighted below.

The use of ai and genai in financial reporting will be ubiquitous in the coming years..

FLYNN : “The potential benefits of AI are driving every conversation with financial reporting leaders. In the next year or two, the fear of missing out on AI will be replaced with just missing out.”

• As for GenAI, 97% of financial reporting leaders will be either piloting or using GenAI in financial reporting in the next three years, up from 46% today.
• In the previous survey, 18% of leaders said they do not use AI in financial reporting with 10% specifying no specific time for rolling out AI solutions.
• Additionally, in the survey from last year, 10% said they were “not using or considering” GenAI in financial reporting.

GenAI is the #1 technology priority for financial reporting leaders in the coming years, with companies focusing on complementary technologies today.

FLYNN : “The depth of AI and GenAI’s capabilities certainly surprised many, and it’s clear companies are focusing on investing in the technologies that will better enable the use of AI, such as cloud, data, and ERP.”

• 19% of U.S. financial reporting leaders are going beyond planning and piloting, and using AI this year, behind cloud technology (77%), data and analytics (55%), and Enterprise Resource Planning (54%).
• Next year, however, U.S. financial reporting leaders will be prioritizing GenAI (58%) the most among all technologies, followed by process mining technology (45%).

U.S. companies are investing more of their IT budgets on AI-related activities than other countries, on average, and those investments are expected to rise in the coming years.

“The benefits of AI compound as companies organize their data, move to the cloud, and integrate AI across processes. In that context, how companies invest over the next few years will shape competitive positioning and the role of finance functions in business strategy,” said Thomas Mackenzie,   KPMG U.S. and Global Audit Chief Technology Officer .

• On average, U.S. companies are spending 10.1% of their IT budgets on AI-related activities today, compared with 9.9% across all countries studied. U.S. companies intend to boost their overall AI budgets by 16.9% next year, and by 24.6% over the next three years.
• Some are moving faster: 30% plan to ramp up their AI budgets by between 25% and 74% over the next three years. 

Relative to all companies, AI Leaders [1] are investing more in AI-enabling technologies and processes, taking more action to mitigate risk, and – most importantly – reporting more benefits.

FLYNN : “In the era of compound volatility , companies are navigating a multitude of risks, but the value that AI can deliver financial reporting teams demands prioritization.”

• AI Leaders in the U.S. spend nearly 12% of IT budgets on AI-related activities today and expect to increase that investment 25% next year and nearly 28% in the next three years.
• Boards of Directors for AI Leaders are more likely to have established mechanisms to monitor and/or measure AI impacts (71% of AI Leaders vs. 45% of other U.S. companies), met with management to understand AI activities and plans (61% vs. 48%), and set up policies and governance aligned with ESG (Environmental, Social, Governance) goals (79% vs. 69%).
• AI Leaders are also more likely to have developed principles for using AI, ensured tech leadership is involved in systems integration discussions, piloted AI initiatives to validate ROI (Return on Investment), and more.
• AI Leaders are more AI-ready from a technology perspective due to greater progress on implementing key enabling technologies and processes. These include cloud migration (94% of AI Leaders are at mid or full implementation vs. 72% of other U.S. companies), standardization of workflows (89% vs. 70%), establishment of common data basis or single source of truth (84% vs. 70%), and standardization of system landscape (60% vs. 48%).
• Most importantly, compared to those just beginning to use AI, Al Leaders are far more likely to report a host of benefits from AI-enabled reporting, including enhanced staff skills due to AI assistants (42% of Leaders vs. 30% of Beginners), ability to predict trends and impacts (62% vs. 51%), and greater ability to identify data outliers and anomalies (31% vs. 21%).

The landscape is evolving as companies seek to overcome barriers, mitigate risks, and realize benefits from an AI-enabled financial reporting process.

FLYNN: "As companies engage more with AI and GenAI in financial reporting processes, new barriers and challenges are driving critical thinking on risk mitigation strategies. Education is paramount, but a more holistic approach to responsible AI use is critical to building and preserving trust.”

• Across all U.S. companies, top benefits expected in three years include real-time insights into risks, fraud, control weaknesses (73%), increased data accuracy and reliability (67%), and lower costs (62%). In addition, 60% expect greater ability to predict trends and impacts.
• Despite industry concerns that AI will disrupt the workforce, some believe it will act as a magnet for talent and innovation. 34% expect AI to attract talent, while 26% believe AI will help fill staff shortages. 37% believe AI assistants will enhance staff skills.
• Thirty-one percent of financial reporting leaders indicated ethical concerns, such as bias or misinformation is a barrier to adoption, down from 48% last year.
• Keeping up with regulatory changes has also fallen to 41% from 49%.
• Risks from using algorithms without human oversight fell from nearly half to 35%.
• Meanwhile, 56% of respondents identified data security and privacy concerns as the biggest barriers to companies’ adoption of AI, compared to just 32% of respondents last year. Other barriers include limited skills and talent (46%), difficulty gathering relevant and consistent data (44%), and inadequate funding and investment levels (43%).
• U.S. financial reporting leaders noted the most effective practices for mitigating GenAI risks include regular audits and monitoring (50%), education and training (50%), ethical frameworks (47%), and human oversight (42%). Other important actions include collaboration and regulation adherence, third-party reviews, privacy measures, and disclosures. 

Today, financial reporting leaders expect auditors to use AI in their audit approach and evaluate companies’ use of AI within financial reporting.

FLYNN: “AI is fundamentally transforming the audit. We expect to deliver more real-time auditing with greater insights into anomalies and trends supported by deep evaluation of the control environment governing the use of AI in financial reporting.”

• In 2023, 61% of financial reporting leaders said that it was important for auditors to utilize AI in performing their analysis; today that number is 83%.
• Last year, 47% said they thought that GenAI would become a common practice among auditors in one to two years, and 46% foresaw it happening in three to five years. Now, 73% of financial reporting leaders expect the use of GenAI to become the norm over the next two years, and 23% believe it will happen in two to three years.
• Top areas that auditors should prioritize include risk/anomaly identification (65%), data analysis and quality management (65%), risk mitigation and internal controls (62%), and fraud detection (58%).
• Financial reporting leaders’ expectations of auditors in the future are highest in two areas: 66% expect their auditors will conduct a more detailed review of the control environment (slightly up from 64% last year), and 61% expect them to assess their AI governance maturity (considerably up from 53% last year).
• In addition, 33% expect their external auditor to provide third-party attestation over the use of AI technology. 

[1]  Leaders are defined as companies in the top 25 th percentile for AI readiness, based on responses to survey questions around AI adoption and governance in financial reporting. Beginners are in the bottom 25 th percentile.

About KPMG LLP

KPMG LLP is the U.S. firm of the KPMG global organization of independent professional services firms providing audit, tax and advisory services. The KPMG global organization operates in 143 countries and territories and has more than 273,000 people working in member firms around the world. Each KPMG firm is a legally distinct and separate entity and describes itself as such. KPMG International Limited is a private English company limited by guarantee. KPMG International Limited and its related entities do not provide services to clients.

KPMG is widely recognized for being a great place to work and build a career. Our people share a sense of purpose in the work we do, and a strong commitment to community service, inclusion and diversity and eradicating childhood illiteracy. Learn more at www.kpmg.com/us .

Additional Resources

Hannah Gould

Sr Assoc Corporate Communications

Explore more

AI's Role in Enhancing Trust in Financial Reporting & Capital Markets

AI is set to revolutionize financial reporting and audit, with many financial reporting functions adopting AI and generative AI.

The 2024 KPMG U.S. CEO Outlook Pulse Survey

CEOs are tackling risks to growth including geopolitics, cyber and structural changes such as tight labor market and new regulations, according to KPMG's latest survey.

KPMG Announces Google Cloud Center of Excellence to Advance Responsible Adoption of Generative AI

KPMG will bring Google Cloud technology to its workforce and build trusted GenAI solutions that accelerate business transformation for clients

Thank you for contacting KPMG. We will respond to you as soon as possible.

Contact KPMG

By submitting, you agree that KPMG LLP may process any personal information you provide pursuant to KPMG LLP's Privacy Statement .

Job seekers

Visit our careers section or search our jobs database.

Use the RFP submission form to detail the services KPMG can help assist you with.

Office locations

International hotline

You can confidentially report concerns to the KPMG International hotline

Press contacts

Do you need to speak with our Press Office? Here's how to get in touch.

An official website of the United States government

Here’s how you know

Official websites use .gov A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS A lock ( Lock A locked padlock ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

COVID-19 Vaccination Public Education Campaign Saved Thousands of Lives, Billions of Dollars

Study found vaccine campaign saved $90 for every $1 spent 

The U.S. Department of Health and Human Services’ (HHS) COVID-19 Vaccination Public Education Campaign, We Can Do This, resulted in an estimated$731.9 billion in societal benefits due to averted illness and related costs, resulting in a nearly $90 return in societal benefits for every $1 spent, according to research published today in the American Journal of Preventive Medicine .

“At the height of the pandemic, we launched one of the largest public health education campaigns in U.S. history to encourage and educate Americans on the steps they could take to get and stay healthy. We now have research to confirm the COVID-19 Public Education Campaign, We Can Do This, was an indispensable part of efforts to vaccinate people and protect them from COVID-19, saving thousands of lives and billions of dollars in the process,” said HHS Secretary Xavier Becerra. “HHS is responsible for protecting the health and well-being of all Americans. As stewards of the public’s money, we wanted to deliver impact for the American people in the most efficient and effective ways. This confirms we did exactly that. We will no doubt use what we learned in this campaign to further improve our public health efforts in the future.”

The study showed the Campaign encouraged 22.3 million people to complete their primary COVID-19 vaccination series between April 2021 and March 2022, preventing nearly 2.6 million SARS-CoV-2 infections, the virus that causes COVID-19, including nearly 244,000 hospitalizations, during the time period that the highly contagious Delta and Omicron virus variants were spreading.

Preventing these outcomes resulted in societal benefits to the U.S. of $740.2 billion, accounting for such factors as medical expenses, wages, and other costs that people and institutions would have incurred in the absence of the Campaign. In comparison, the Campaign cost $377 million, with an additional $7.9 billion spent to vaccinate 22.3 million people in that time period.

According to the study, from April 2021 to March 2022, the net benefit of the Campaign—how much money these efforts saved minus how much they cost—came to $731.9 billion, translating to a return on investment of $89.54 for every $1 spent.

In April 2021, HHS launched the We Can Do This Public Education Campaign to increase COVID-19 vaccine confidence and uptake in the U.S. The Campaign, one of the largest public health education efforts in U.S. history, promoted COVID-19 vaccine uptake using integrated, multichannel, research-based strategies. It aimed to reach 90% of adults in the United States at least once per quarter, with even more intense outreach to high-risk communities. The Campaign featured more than 7,000 ads in 14 languages, with many culturally tailored and geographically targeted to specific minority, racial, and ethnic audiences. A multimedia approach bolstered widespread engagement with trusted messengers, partner organizations, and influencers who delivered persuasive, accurate, and culturally relevant information to vaccine-hesitant populations.

The benefit-cost study of We Can Do This is the only research study to date that looked at the contributions of a media campaign to encourage people to get COVID-19 vaccines during the pandemic emergency period. The newly published study is unique in that it demonstrates that the nationwide media Campaign was an indispensable component of the nation’s efforts to vaccinate people and protect them from COVID-19. It also adds to the body of evidence that shows the Campaign’s impact on behavior change.

“This research confirms the benefits of public health campaigns as part of a multi-layered response to a public health crisis and to the effort to provide accurate information to the American public,” said May Malik, Senior Advisor for Public Education Campaigns at HHS.

To evaluate the benefits and costs of the national Campaign, researchers used real-world data from multiple sources, such as data on COVID-19 outcomes, uptake of COVID-19 vaccines, and vaccine effectiveness, from the U.S. Centers for Disease Control and Prevention (CDC), along with survey data collected to measure the Campaign’s effects on vaccination behaviors over time.

The findings can help inform the Federal response to future public health threats. As part of a multipronged approach to addressing public health crises, this study demonstrates the return on investment possible from public education campaigns given their effectiveness in building vaccine confidence and supporting healthy behavior change.

The study, Benefit-Cost Analysis of the HHS COVID-19 Campaign: April 2021–March 2022 , was conducted by researchers from HHS Office of the Assistant Secretary for Public Affairs and Fors Marsh in Arlington, Virginia.

Sign Up for Email Updates

Receive the latest updates from the Secretary, Blogs, and News Releases

Subscribe to RSS

Receive latest updates

Related News Releases

Hhs, dhs, and fema announce completion of multi-year review of state efforts to provide language access during the covid-19 public health emergency, readout of hhs secretary becerra’s meeting with pharmacy ceos on covid-19 therapeutics commercialization, readout of hhs meeting with health care providers on covid-19 therapeutics commercialization, related blog posts.

Calling innovators! HHS Long COVID Healthathon launches with $25K in prizes

Reflections from the deputy director of the hhs office of long covid research and practice.

Driving Long COVID Innovation with Health+ Human-Centered Design

Media inquiries.

For general media inquiries, please contact  [email protected] .