future research implications

Research Implications & Recommendations

A Plain-Language Explainer With Examples + FREE Template

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

The research implications and recommendations are closely related but distinctly different concepts that often trip students up. Here, we’ll unpack them using plain language and loads of examples , so that you can approach your project with confidence.

Overview: Implications & Recommendations

• What are research implications ?
• What are research recommendations ?
• Examples of implications and recommendations
• The “ Big 3 ” categories
• How to write the implications and recommendations
• Template sentences for both sections
• Key takeaways

Implications & Recommendations 101

Let’s start with the basics and define our terms.

At the simplest level, research implications refer to the possible effects or outcomes of a study’s findings. More specifically, they answer the question, “ What do these findings mean?” . In other words, the implications section is where you discuss the broader impact of your study’s findings on theory, practice and future research.

This discussion leads us to the recommendations section , which is where you’ll propose specific actions based on your study’s findings and answer the question, “ What should be done next?” . In other words, the recommendations are practical steps that stakeholders can take to address the key issues identified by your study.

In a nutshell, then, the research implications discuss the broader impact and significance of a study’s findings, while recommendations provide specific actions to take, based on those findings. So, while both of these components are deeply rooted in the findings of the study, they serve different functions within the write up.

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Examples: Implications & Recommendations

The distinction between research implications and research recommendations might still feel a bit conceptual, so let’s look at one or two practical examples:

Let’s assume that your study finds that interactive learning methods significantly improve student engagement compared to traditional lectures. In this case, one of your recommendations could be that schools incorporate more interactive learning techniques into their curriculums to enhance student engagement.

Let’s imagine that your study finds that patients who receive personalised care plans have better health outcomes than those with standard care plans. One of your recommendations might be that healthcare providers develop and implement personalised care plans for their patients.

Now, these are admittedly quite simplistic examples, but they demonstrate the difference (and connection ) between the research implications and the recommendations. Simply put, the implications are about the impact of the findings, while the recommendations are about proposed actions, based on the findings.

The “Big 3” Categories

Now that we’ve defined our terms, let’s dig a little deeper into the implications – specifically, the different types or categories of research implications that exist.

Broadly speaking, implications can be divided into three categories – theoretical implications, practical implications and implications for future research .

Theoretical implications relate to how your study’s findings contribute to or challenge existing theories. For example, if a study on social behaviour uncovers new patterns, it might suggest that modifications to current psychological theories are necessary.

Practical implications , on the other hand, focus on how your study’s findings can be applied in real-world settings. For example, if your study demonstrated the effectiveness of a new teaching method, this would imply that educators should consider adopting this method to improve learning outcomes.

Practical implications can also involve policy reconsiderations . For example, if a study reveals significant health benefits from a particular diet, an implication might be that public health guidelines be re-evaluated.

Last but not least, there are the implications for future research . As the name suggests, this category of implications highlights the research gaps or new questions raised by your study. For example, if your study finds mixed results regarding a relationship between two variables, it might imply the need for further investigation to clarify these findings.

To recap then, the three types of implications are the theoretical, the practical and the implications on future research. Regardless of the category, these implications feed into and shape the recommendations , laying the foundation for the actions you’ll propose.

How To Write The  Sections

Now that we’ve laid the foundations, it’s time to explore how to write up the implications and recommendations sections respectively.

Let’s start with the “ where ” before digging into the “ how ”. Typically, the implications will feature in the discussion section of your document, while the recommendations will be located in the conclusion . That said, layouts can vary between disciplines and institutions, so be sure to check with your university what their preferences are.

For the implications section, a common approach is to structure the write-up based on the three categories we looked at earlier – theoretical, practical and future research implications. In practical terms, this discussion will usually follow a fairly formulaic sentence structure – for example:

This research provides new insights into [theoretical aspect], indicating that…

The study’s outcomes highlight the potential benefits of adopting [specific practice] in..

This study raises several questions that warrant further investigation, such as…

Moving onto the recommendations section, you could again structure your recommendations using the three categories. Alternatively, you could structure the discussion per stakeholder group – for example, policymakers, organisations, researchers, etc.

Again, you’ll likely use a fairly formulaic sentence structure for this section. Here are some examples for your inspiration: 

Based on the findings, [specific group] should consider adopting [new method] to improve…

To address the issues identified, it is recommended that legislation should be introduced to…

Researchers should consider examining [specific variable] to build on the current study’s findings.

Remember, you can grab a copy of our tried and tested templates for both the discussion and conclusion sections over on the Grad Coach blog. You can find the links to those, as well as loads of other free resources, in the description 🙂

FAQs: Implications & Recommendations

How do i determine the implications of my study.

To do this, you’ll need to consider how your findings address gaps in the existing literature, how they could influence theory, practice, or policy, and the potential societal or economic impacts.

When thinking about your findings, it’s also a good idea to revisit your introduction chapter, where you would have discussed the potential significance of your study more broadly. This section can help spark some additional ideas about what your findings mean in relation to your original research aims. 

Should I discuss both positive and negative implications?

Absolutely. You’ll need to discuss both the positive and negative implications to provide a balanced view of how your findings affect the field and any limitations or potential downsides.

Can my research implications be speculative?

Yes and no. While implications are somewhat more speculative than recommendations and can suggest potential future outcomes, they should be grounded in your data and analysis. So, be careful to avoid overly speculative claims.

How do I formulate recommendations?

Ideally, you should base your recommendations on the limitations and implications of your study’s findings. So, consider what further research is needed, how policies could be adapted, or how practices could be improved – and make proposals in this respect.

How specific should my recommendations be?

Your recommendations should be as specific as possible, providing clear guidance on what actions or research should be taken next. As mentioned earlier, the implications can be relatively broad, but the recommendations should be very specific and actionable. Ideally, you should apply the SMART framework to your recommendations.

Can I recommend future research in my recommendations?

Absolutely. Highlighting areas where further research is needed is a key aspect of the recommendations section. Naturally, these recommendations should link to the respective section of your implications (i.e., implications for future research).

Wrapping Up: Key Takeaways

We’ve covered quite a bit of ground here, so let’s quickly recap.

• Research implications refer to the possible effects or outcomes of a study’s findings.
• The recommendations section, on the other hand, is where you’ll propose specific actions based on those findings.
• You can structure your implications section based on the three overarching categories – theoretical, practical and future research implications.
• You can carry this structure through to the recommendations as well, or you can group your recommendations by stakeholder.

Remember to grab a copy of our tried and tested free dissertation template, which covers both the implications and recommendations sections. If you’d like 1:1 help with your research project, be sure to check out our private coaching service, where we hold your hand throughout the research journey, step by step.

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• Writing Tips

How to Write an “Implications of Research” Section

4-minute read

• 24th October 2022

When writing research papers , theses, journal articles, or dissertations, one cannot ignore the importance of research. You’re not only the writer of your paper but also the researcher ! Moreover, it’s not just about researching your topic, filling your paper with abundant citations, and topping it off with a reference list. You need to dig deep into your research and provide related literature on your topic. You must also discuss the implications of your research.

Interested in learning more about implications of research? Read on! This post will define these implications, why they’re essential, and most importantly, how to write them. If you’re a visual learner, you might enjoy this video .

What Are Implications of Research?

Implications are potential questions from your research that justify further exploration. They state how your research findings could affect policies, theories, and/or practices.

Implications can either be practical or theoretical. The former is the direct impact of your findings on related practices, whereas the latter is the impact on the theories you have chosen in your study.

Example of a practical implication: If you’re researching a teaching method, the implication would be how teachers can use that method based on your findings.

Example of a theoretical implication: You added a new variable to Theory A so that it could cover a broader perspective.

Finally, implications aren’t the same as recommendations, and it’s important to know the difference between them .

Questions you should consider when developing the implications section:

●  What is the significance of your findings?

●  How do the findings of your study fit with or contradict existing research on this topic?

●  Do your results support or challenge existing theories? If they support them, what new information do they contribute? If they challenge them, why do you think that is?

Why Are Implications Important?

You need implications for the following reasons:

● To reflect on what you set out to accomplish in the first place

● To see if there’s a change to the initial perspective, now that you’ve collected the data

● To inform your audience, who might be curious about the impact of your research

How to Write an Implications Section

Usually, you write your research implications in the discussion section of your paper. This is the section before the conclusion when you discuss all the hard work you did. Additionally, you’ll write the implications section before making recommendations for future research.

Implications should begin with what you discovered in your study, which differs from what previous studies found, and then you can discuss the implications of your findings.

Your implications need to be specific, meaning you should show the exact contributions of your research and why they’re essential. They should also begin with a specific sentence structure.

Examples of starting implication sentences:

●  These results build on existing evidence of…

●  These findings suggest that…

●  These results should be considered when…

●  While previous research has focused on x , these results show that y …

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You should write your implications after you’ve stated the results of your research. In other words, summarize your findings and put them into context.

The result : One study found that young learners enjoy short activities when learning a foreign language.

The implications : This result suggests that foreign language teachers use short activities when teaching young learners, as they positively affect learning.

 Example 2

The result : One study found that people who listen to calming music just before going to bed sleep better than those who watch TV.

The implications : These findings suggest that listening to calming music aids sleep quality, whereas watching TV does not.

To summarize, remember these key pointers:

●  Implications are the impact of your findings on the field of study.

●  They serve as a reflection of the research you’ve conducted.              

●  They show the specific contributions of your findings and why the audience should care.

●  They can be practical or theoretical.

●  They aren’t the same as recommendations.

●  You write them in the discussion section of the paper.

●  State the results first, and then state their implications.

Are you currently working on a thesis or dissertation? Once you’ve finished your paper (implications included), our proofreading team can help ensure that your spelling, punctuation, and grammar are perfect. Consider submitting a 500-word document for free.

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Implications in research: A quick guide

Last updated

11 January 2024

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Short on time? Get an AI generated summary of this article instead

Implications are a bridge between data and action, giving insight into the effects of the research and what it means. It's a chance for researchers to explain the  why  behind the research. 

When writing a research paper , reviewers will want to see you clearly state the implications of your research. If it's missing, they’ll likely reject your article. 

Let's explore what research implications are, why they matter, and how to include them in your next article or research paper. 

• What are implications in research?

Research implications are the consequences of research findings. They go beyond results and explore your research’s ramifications. 

Researchers can connect their research to the real-world impact by identifying the implications. These can inform further research, shape policy, or spark new solutions to old problems. 

Always clearly state your implications so they’re obvious to the reader. Never leave the reader to guess why your research matters. While it might seem obvious to you, it may not be evident to someone who isn't a subject matter expert. 

For example, you may do important sociological research with political implications. If a policymaker can't understand or connect those implications logically with your research, it reduces your impact.

• What are the key features of implications?

When writing your implications, ensure they have these key features: 

Implications should be clear, concise, and easily understood by a broad audience. You'll want to avoid overly technical language or jargon. Clearly stating your implications increases their impact and accessibility. 

Implications should link to specific results within your research to ensure they’re grounded in reality. You want them to demonstrate an impact on a particular field or research topic . 

Evidence-based

Give your implications a solid foundation of evidence. They need to be rational and based on data from your research, not conjecture. An evidence-based approach to implications will lend credibility and validity to your work.

Implications should take a balanced approach, considering the research's potential positive and negative consequences. A balanced perspective acknowledges the challenges and limitations of research and their impact on stakeholders. 

Future-oriented

Don't confine your implications to their immediate outcomes. You can explore the long-term effects of the research, including the impact on future research, policy decisions, and societal changes. Looking beyond the immediate adds more relevance to your research. 

When your implications capture these key characteristics, your research becomes more meaningful, impactful, and engaging. 

• Types of implications in research

The implications of your research will largely depend on what you are researching. 

However, we can broadly categorize the implications of research into two types: 

Practical: These implications focus on real-world applications and could improve policies and practices.

Theoretical: These implications are broader and might suggest changes to existing theories of models of the world. 

You'll first consider your research's implications in these two broad categories. Will your key findings have a real-world impact? Or are they challenging existing theories? 

Once you've established whether the implications are theoretical or practical, you can break your implication into more specific types. This might include: 

Political implications: How findings influence governance, policies, or political decisions

Social implications: Effects on societal norms, behaviors, or cultural practices

Technological implications: Impact on technological advancements or innovation

Clinical implications: Effects on healthcare, treatments, or medical practices

Commercial or business-relevant implications: Possible strategic paths or actions

Implications for future research: Guidance for future research, such as new avenues of study or refining the study methods

When thinking about the implications of your research, keep them clear and relevant. Consider the limitations and context of your research. 

For example, if your study focuses on a specific population in South America, you may not be able to claim the research has the same impact on the global population. The implication may be that we need further research on other population groups. 

• Understanding recommendations vs. implications

While "recommendations" and "implications" may be interchangeable, they have distinct roles within research.

Recommendations suggest action. They are specific, actionable suggestions you could take based on the research. Recommendations may be a part of the larger implication. 

Implications explain consequences. They are broader statements about how the research impacts specific fields, industries, institutions, or societies. 

Within a paper, you should always identify your implications before making recommendations. 

While every good research paper will include implications of research, it's not always necessary to include recommendations. Some research could have an extraordinary impact without real-world recommendations. 

• How to write implications in research

Including implications of research in your article or journal submission is essential. You need to clearly state your implications to tell the reviewer or reader why your research matters. 

Because implications are so important, writing them can feel overwhelming.

Here’s our step-by-step guide to make the process more manageable:

1. Summarize your key findings

Start by summarizing your research and highlighting the key discoveries or emerging patterns. This summary will become the foundation of your implications. 

2. Identify the implications

Think critically about the potential impact of your key findings. Consider how your research could influence practices, policies, theories, or societal norms. 

Address the positive and negative implications, and acknowledge the limitations and challenges of your research. 

If you still need to figure out the implications of your research, reread your introduction. Your introduction should include why you’re researching the subject and who might be interested in the results. This can help you consider the implications of your final research. 

3. Consider the larger impact

Go beyond the immediate impact and explore the implications on stakeholders outside your research group. You might include policymakers, practitioners, or other researchers.

4. Support with evidence

Cite specific findings from your research that support the implications. Connect them to your original thesis statement. 

You may have included why this research matters in your introduction, but now you'll want to support that implication with evidence from your research. 

Your evidence may result in implications that differ from the expected impact you cited in the introduction of your paper or your thesis statement. 

5. Review for clarity

Review your implications to ensure they are clear, concise, and jargon-free. Double-check that your implications link directly to your research findings and original thesis statement. 

Following these steps communicates your research implications effectively, boosting its long-term impact. 

Where do implications go in your research paper?

Implications often appear in the discussion section of a research paper between the presentation of findings and the conclusion. 

Putting them here allows you to naturally transition from the key findings to why the research matters. You'll be able to convey the larger impact of your research and transition to a conclusion.

• Examples of research implications

Thinking about and writing research implications can be tricky. 

To spark your critical thinking skills and articulate implications for your research, here are a few hypothetical examples of research implications: 

Teaching strategies

A study investigating the effectiveness of a new teaching method might have practical implications for educators. 

The research might suggest modifying current teaching strategies or changing the curriculum’s design. 

There may be an implication for further research into effective teaching methods and their impact on student testing scores. 

Social media impact

A research paper examines the impact of social media on teen mental health. 

Researchers find that spending over an hour on social media daily has significantly worse mental health effects than 15 minutes. 

There could be theoretical implications around the relationship between technology and human behavior. There could also be practical implications in writing responsible social media usage guidelines. 

Disease prevalence

A study analyzes the prevalence of a particular disease in a specific population. 

The researchers find this disease occurs in higher numbers in mountain communities. This could have practical implications on policy for healthcare allocation and resource distribution. 

There may be an implication for further research into why the disease appears in higher numbers at higher altitudes.

These examples demonstrate the considerable range of implications that research can generate.

Clearly articulating the implications of research allows you to enhance the impact and visibility of your work as a researcher. It also enables you to contribute to societal advancements by sharing your knowledge.

The implications of your work could make positive changes in the world around us.

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What are Implications in Research?

• 3 minute read
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Table of Contents

Manuscripts that do not mention the implications of the study are often desk-rejected by journals. What constitutes the ‘implications’ of research, and why is it important to include research implications in your manuscript?

Research implications: An overview

Once you have laid out the key findings in your paper, you have to discuss how they will likely impact the world. What is the significance of your study to policymakers, the lay person, or other researchers? This speculation, made in good faith, constitutes your study’ implications.

A research paper that does not explain the study’s importance in light of its findings exists in a vacuum. The paper may be relevant to you, the author, and some of your co-workers. But it is unclear how others will benefit from reading it.

How can the findings of your study help create a better world? What can we infer from your conclusion about the current state of research in your field or the quality of methods you employed? These are all important implications of your study.

You cannot predict how your study will influence the world or research in the future. You can only make reasonable speculations. In order to ensure that the implications are reasonable, you have to be mindful of the limitations of your study.

In the research context, only speculations supported by data count as valid implications. If the implications you draw do not logically follow the key findings of your study, they may sound overblown or outright preposterous.

Suppose your study evaluated the effects of a new drug in the adult population. In that case, you could not honestly speculate on how the drug will impact paediatric care. Thus, the implications you draw from your study cannot exceed its scope.

Practical implications

Imagine that your study found a popular type of cognitive therapy to be ineffective in treating insomnia. Your findings imply that psychologists using this type of therapy were not seeing actual results but an expectancy effect. Studies that can potentially impact real-world problems by prompting policy change or change in treatments have practical implications.

It can be helpful to understand the difference between an implication of your study and a recommendation. Suppose your study compares two or more types of therapy, ranks them in the order of effectiveness, and explicitly asks clinicians to follow the most effective type. The suggestion made in the end constitutes a ‘recommendation’ and not an ‘implication’.

Theoretical implications

Are your findings in line with previous research? Did your results validate the methods used in previous research or invalidate them? Has your study discovered a new and helpful way to do experiments? Speculations on how your findings can potentially impact research in your field of study are theoretical implications.

The main difference between practical and theoretical implications is that theoretical implications may not be readily helpful to policymakers or the public.

How to Write Implications in Research

Implications usually form an essential part of the conclusion section of a research paper. As we have mentioned in a previous article, this section starts by summarising your work, but this time emphasises your work’s significance .

While writing the implications, it is helpful to ask, “who will benefit the most from reading my paper?”—policymakers, physicians, the public, or other researchers. Once you know your target population, explain how your findings can help them.

Think about how the findings in your study are similar or dissimilar to the findings of previous studies. Your study may reaffirm or disprove the results of other studies. This is an important implication.

Suggest future directions for research in the subject area in light of your findings or further research to confirm your findings. These are also crucial implications.

Do not try to exaggerate your results, and make sure your tone reflects the strength of your findings. If the implications mentioned in your paper are convincing, it can improve visibility for your work and spur similar studies in your field.

For more information on the importance of implications in research, and guidance on how to include them in your manuscript, visit Elsevier Author Services now!

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What are Implications and Recommendations in Research? How to Write It, with Examples

Highly cited research articles often contain both implications and recommendations , but there is often some confusion around the difference between implications and recommendations in research. Implications of a study are the impact your research makes in your chosen area; they discuss how the findings of the study may be important to justify further exploration of your research topic. Research recommendations suggest future actions or subsequent steps supported by your research findings. It helps to improve your field of research or cross-disciplinary fields through future research or provides frameworks for decision-makers or policymakers. Recommendations are the action plan you propose based on the outcome.

In this article, we aim to simplify these concepts for researchers by providing key insights on the following:  

• what are implications in research 
• what is recommendation in research 
• differences between implications and recommendations 
• how to write implications in research 
• how to write recommendation in research 
• sample recommendation in research 

Table of Contents

What are implications in research

The implications in research explain what the findings of the study mean to researchers or to certain subgroups or populations beyond the basic interpretation of results. Even if your findings fail to bring radical or disruptive changes to existing ways of doing things, they might have important implications for future research studies. For example, your proposed method for operating remote-controlled robots could be more precise, efficient, or cheaper than existing methods, or the remote-controlled robot could be used in other application areas. This could enable more researchers to study a specific problem or open up new research opportunities.   

Implications in research inform how the findings, drawn from your results, may be important for and impact policy, practice, theory, and subsequent research. Implications may be theoretical or practical. 1  

• Practical implications are potential values of the study with practical or real outcomes . Determining the practical implications of several solutions can aid in identifying optimal solution results. For example, clinical research or research on classroom learning mostly has practical implications in research . If you developed a new teaching method, the implication would be how teachers can use that method based on your findings.  
• Theoretical implications in research constitute additions to existing theories or establish new theories. These types of implications in research characterize the ability of research to influence society in apparent ways. It is, at most, an educated guess (theoretical) about the possible implication of action and need not be as absolute as practical implications in research . If your study supported the tested theory, the theoretical implication would be that the theory can explain the investigated phenomenon. Else, your study may serve as a basis for modifying the theory. Theories may be partially supported as well, implying further study of the theory or necessary modifications are required.  

What are recommendations in research?

Recommendations in research can be considered an important segment of the analysis phase. Recommendations allow you to suggest specific interventions or strategies to address the issues and constraints identified through your study. It responds to key findings arrived at through data collection and analysis. A process of prioritization can help you narrow down important findings for which recommendations are developed.  

Recommendations in research examples

Recommendations in research may vary depending on the purpose or beneficiary as seen in the table below.  

Table: Recommendations in research examples based on purpose and beneficiary  

If you’re wondering how to make recommendations in research . You can use the simple  recommendation in research example below as a handy template.  

Table: Sample recommendation in research template  

Basic differences between implications and recommendations in research

Implications and recommendations in research are two important aspects of a research paper or your thesis or dissertation. Implications discuss the importance of the research findings, while recommendations offer specific actions to solve a problem. So, the basic difference between the two is in their function and the questions asked to achieve it. The following table highlights the main differences between implications and recommendations in research .  

Table: Differences between implications and recommendations in research  

Where do implications go in your research paper

Because the implications and recommendations of the research are based on study findings, both are usually written after the completion of a study. There is no specific section dedicated to implications in research ; they are usually integrated into the discussion section adding evidence as to why the results are meaningful and what they add to the field. Implications can be written after summarizing your main findings and before the recommendations and conclusion.   

Implications can also be presented in the conclusion section after a short summary of the study results.   

How to write implications in research

Implication means something that is inferred. The implications of your research are derived from the importance of your work and how it will impact future research. It is based on how previous studies have advanced your field and how your study can add to that.   

When figuring out how to write implications in research , a good strategy is to separate it into the different types of implications in research , such as social, political, technological, policy-related, or others. As mentioned earlier, the most frequently used are the theoretical and practical implications.   

Next, you need to ask, “Who will benefit the most from reading my paper?” Is it policymakers, physicians, the public, or other researchers? Once you know your target population, explain how your findings can help them.  

The implication section can include a paragraph or two that asserts the practical or managerial implications and links it to the study findings. A discussion can then follow, demonstrating that the findings can be practically implemented or how they will benefit a specific audience. The writer is given a specific degree of freedom when writing research implications , depending on the type of implication in research you want to discuss: practical or theoretical. Each is discussed differently, using different words or in separate sections. The implications can be based on how the findings in your study are similar or dissimilar to that in previous studies. Your study may reaffirm or disprove the results of other studies, which has important implications in research . You can also suggest future research directions in the light of your findings or require further research to confirm your findings, which are all crucial implications. Most importantly, ensure the implications in research are specific and that your tone reflects the strength of your findings without exaggerating your results.   

Implications in research can begin with the following specific sentence structures:  

• These findings suggest that…
• These results build on existing body of evidence of…
• These results should be considered when…
• While previous research focused on x, our results show that y…

What should recommendations in research look like?

Recommendations for future research should be:  

• Directly related to your research question or findings  
• Concrete and specific  
• Supported by a clear reasoning  

The recommendations in research can be based on the following factors:  

1. Beneficiary: A paper’s research contribution may be aimed at single or multiple beneficiaries, based on which recommendations can vary. For instance, if your research is about the quality of care in hospitals, the research recommendation to different beneficiaries might be as follows:  

• Nursing staff: Staff should undergo training to enhance their understanding of what quality of care entails.  
• Health science educators: Educators must design training modules that address quality-related issues in the hospital.  
• Hospital management: Develop policies that will increase staff participation in training related to health science.  

2. Limitations: The best way to figure out what to include in your research recommendations is to understand the limitations of your study. It could be based on factors that you have overlooked or could not consider in your present study. Accordingly, the researcher can recommend that other researchers approach the problem from a different perspective, dimension, or methodology. For example, research into the quality of care in hospitals can be based on quantitative data. The researcher can then recommend a qualitative study of factors influencing the quality of care, or they can suggest investigating the problem from the perspective of patients rather than the healthcare providers.   

3. Theory or Practice: Your recommendations in research could be implementation-oriented or further research-oriented.   

4. Your research: Research recommendations can be based on your topic, research objectives, literature review, and analysis, or evidence collected. For example, if your data points to the role of faculty involvement in developing effective programs, recommendations in research can include developing policies to increase faculty participation. Take a look at the evidence-based recommendation in research example s provided below.   

Table: Example of evidence-based research recommendation  

Avoid making the following mistakes when writing research recommendations :  

• Don’t undermine your own work: Recommendations in research should offer suggestions on how future studies can be built upon the current study as a natural extension of your work and not as an entirely new field of research.  
• Support your study arguments: Ensure that your research findings stand alone on their own merits to showcase the strength of your research paper.   

How to write recommendations in research

When writing research recommendations , your focus should be on highlighting what additional work can be done in that field. It gives direction to researchers, industries, or governments about changes or developments possible in this field. For example, recommendations in research can include practical and obtainable strategies offering suggestions to academia to address problems. It can also be a framework that helps government agencies in developing strategic or long-term plans for timely actions against disasters or aid nation-building.  

There are a few SMART 2 things to remember when writing recommendations in research. Your recommendations must be: 

• S pecific: Clearly state how challenges can be addressed for better outcomes and include an action plan that shows what can be achieved. 
• M easurable: Use verbs denoting measurable outcomes, such as identify, analyze, design, compute, assess, evaluate, revise, plan, etc., to strengthen recommendations in research .   
• A ttainable: Recommendations should offer a solution-oriented approach to problem-solving and must be written in a way that is easy to follow.  
• R elevant: Research recommendations should be reasonable, realistic, and result-based. Make sure to suggest future possibilities for your research field.  
• T imely: Time-based or time-sensitive recommendations in research help divide the action plan into long-term or short-term (immediate) goals. A timeline can also inform potential readers of what developments should occur over time.  

If you are wondering how many words to include in your research recommendation , a general rule of thumb would be to set aside 5% of the total word count for writing research recommendations . Finally, when writing the research implications and recommendations , stick to the facts and avoid overstating or over-generalizing the study findings. Both should be supported by evidence gathered through your data analysis.  

References:  

• Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings.  Psychological bulletin ,  124 (2), 262.
• Doran, G. T. (1981). There’s a S.M.A.R.T. way to write management’s goals and objectives.  Manag Rev ,  70 (11), 35-36.

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Related Posts

What is IMRaD Format in Research?

What is a Review Article? How to Write it?

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What Are Implications in Research? | Examples & Tips

As a researcher, you know you need to provide a background for your study and a clear rationale and to formulate the statement of the problem in a way that leaves no doubt that your work is relevant and important. You also need to guide the reader carefully through your story from beginning to end without leaving any methodological questions unanswered. 

But many authors, when arriving at the end of their paper, run out of steam or lose the thread a bit and struggle with finding an ending for their work. Something can then appear missing, even if the discussion section summarizes the findings clearly, relates them back to the questions raised in the introduction section , and discusses them in the context of earlier works. A tired author who just made it to the end can often not see these missing elements and may finish off their paper with a conclusion section that is more or less a repetition of what has already been stated. After all, what more is there to be said? 

But as sure as the sun will rise again the day after you finally submitted, you will get your paper back from your supervisor or the reviewers with a comment that says, “implications are missing.” For a reader who is not as invested in every little detail of your design and analyses, the main questions that a paper has to answer are “why was this study necessary?” and “why are the findings of this study significant, and for whom, and what are we supposed to do with them now?” The latter are the implications of your work. 

Didn’t I explain the implications in my introduction section?

You will hopefully have already explained why and for whom your study is important. But you now also need to clearly state how you think your actual findings (which might differ from what you expected to find at the beginning) may be relevant and/or can be used in practical or theoretical ways, for future research, or by policymakers. These implications need to be based on your study’s parameters and results, and potential limitations of your methodology or sample should be taken into account to avoid overgeneralization. 

If you make the reader guess what the significance of your work might be or let them assume you don’t think that your work will be important for anyone except yourself and your colleagues who share your enthusiasm because they are working on the same topic, then an editor or reviewer might easily see that as a reason for a desk-reject. To avoid this, in the following, we will give you an overview of the different types of implications that research findings can have, provide some examples for your inspiration, and clarify where your implications should go in your paper. 

Table of Contents:

• Types of Implications in Research

Recommendations Versus Implications 

• Research Implications Examples 
• Where Do the Implications Go in Your paper?

Types of Implications in Research 

Depending on the type of research you are doing (clinical, philosophical, political…) the implications of your findings can likewise be clinical, philosophical, political, social, ethical—you name it. The most important distinction, however, is the one between practical implications and theoretical implications, and what many reviewers immediately notice and flag as an issue is when there is no mention of any kind of practical contribution of the work described in a paper. 

Of course, if you study a mathematical theory, then your findings might simply lead to the debunking of another theory as false, and you might need to do some mental gymnastics if you really wanted to apply that to a real-world problem. But chances are, in that case, your reviewers and readers won’t ask for a real-world implication. In most other cases, however, if you really want to convince your audience that your work deserves attention, publication, prizes, and whatnot, then you need to link whatever you did in the lab or found in the library to real life and highlight how your findings might have a lasting effect on your field (for example, methodologically), common practices (e.g., patient treatment or teaching standards), society at large (maybe the way we communicate), or ethical standards (e.g., in animal research). 

The question is not whether your findings will change the world, but whether they could if they were publicized and implemented—according to the Merriam-Webster online dictionary , the essential meaning of implication is a “possible future effect or result”. This possible result is what you have to identify and describe. And while being creative is certainly allowed, make sure your assumptions stay within realistic expectations, and don’t forget to take the limitations of your methodology or your sample into account. 

If you studied the genetic basis of a disease in some animal model, then make sure you have good reason to draw conclusions about the treatment of the same disease in humans if you don’t want to put off the editor who decides whether to even send your manuscript out for review. Likewise, if you explored the effects of the Covid-19 pandemic on higher education institutions in your country, then make sure the conclusions you draw hold in the context of other countries’ pandemic situations and restrictions and differences across education systems before you claim that they are relevant in a global context. 

Implications, as we already explored, state the importance of your study and how your findings may be relevant for the fine-tuning of certain practices, theoretical models, policymaking, or future research studies. As stated earlier, that does not necessarily mean that you believe your findings will change the world tomorrow, but that you have reason to believe they could have an impact in a specific way. Recommendations, on the other hand, are specific suggestions regarding the best course of action in a certain situation based on your findings. If, for example, you used three different established methods in your field to tackle the same problem, compared the outcomes, and concluded that one of these methods is, in fact, insufficient and should not be used anymore, then that is a recommendation for future research. 

Or if you analyzed how a monetary “Corona support program” in your country affected the local economy and found that most of the money the government provided went to Amazon and not to local businesses, then you can recommend that your government come up with a better plan next time. Such specific recommendations should usually follow the implications, not the other way around, because you always need to identify the implications of your work, but not every study allows the author to make practical suggestions or real-world recommendations.

Research Implications Examples

Clinical implications  .

Let’s say you discovered a new antibiotic that could eliminate a specific pathogen effectively without generating resistance (the main problem with antibiotics). The clinical implications of your findings would then be that infections with this pathogen could be more rapidly treated than before (without you predicting or suggesting any specific action to happen as a result of your findings). A recommendation would be that doctors should start using this new antibiotic, that it should be included in the official treatment guidelines, that it should be covered by the national health insurance of your country, etc.—but depending on how conclusive your findings are or how much more research or development might be needed to get from your findings to the actual medication, such recommendations might be a big stretch. The implications, however, since they state the potential of your findings, are valid in any case and should not be missing from your discussion section, even if your findings are just one small step along the way.

Social implications 

The social implications of the study are defined as the ability or potential of research to impact society in visible ways. One of the obvious fields of research that strives for a social impact through the implementation of evidence that increases the overall quality of people’s lives is psychology. Whether your research explores the new work-life-balance movement and its effect on mental well-being, psychological interventions at schools to compensate for the stress many children are experiencing since the beginning of the Covid-19 pandemic, or how work from home is changing family dynamics, you can most likely draw conclusions that go beyond just your study sample and describe potential (theoretical or practical) effects of your findings in the real world. Be careful, however, that you don’t overgeneralize from your sample or your data to the general population without having solid reasons to do so (and explain those reasons).

Implications for future research

Even if your findings are not going to lead to societal changes, new educational policies, or an overhaul of the national pension system, they might have important implications for future research studies. Maybe you used a new technique that is more precise or more efficient or way cheaper than existing methods and this could enable more labs around the world to study a specific problem. Or maybe you found that a gene that is known to be involved in one disease might also be involved in another disease, which opens up new avenues for research and treatment options. As stated earlier, make sure you don’t confuse recommendations (which you might not be able to make, based on your findings, and don’t necessarily have to) with implications, which are the potential effect that your findings could have—independently of whether you have any influence on that. 

Where Do the Implications Go in Your Paper? 

The implications are part of your discussion section, where you summarize your findings and then put them into context—this context being earlier research but also the potential effect your findings could have in the real world, in whatever scenario you think might be relevant. There is no “implication section” and no rule as to where in the discussion section you need to include these details because the order of information depends on how you structured your methods and your results section and how your findings turned out to prove or disprove your hypotheses. You simply need to work the potential effects of your findings into your discussion section in a logical way.

But the order of information is relevant when it comes to your conclusion at the very end of your discussion section: Here, you start with a very short summary of your study and results, then provide the (theoretical, practical, ethical, social, technological…) implications of your work, and end with a specific recommendation if (and only if) your findings call for that. If you have not paid attention to the importance of your implications while writing your discussion section, then this is your chance to fix that before you finalize and submit your paper and let an editor and reviewers judge the relevance of your work. 

Make sure you do not suddenly come up with practical ideas that look like they were plucked out of the air because someone reminded you to “add some implications” at the last minute. If you don’t know where to start, then go back to your introduction section, look at your rationale and research questions, look at how your findings answered those questions, and ask yourself who else could benefit from knowing what you know now.

Consider Using English Editing Services 

And before you submit your manuscript to your target journal’s editor, be sure to get professional English editing services from Wordvice, including academic editing and manuscript editing , which are tailored to the needs of your paper’s subject area. If you need instant proofreading or paraphrasing while drafting your work, check out our online AI Text Editor , Wordvice AI, which is trained on millions of words of academic writing data and tailored for research writers.

For more advice on how to write all the different parts of your research paper , on how to make a research paper outline if you are struggling with putting everything you did together, or on how to write the best cover letter that will convince an editor to send your manuscript out for review, head over to the Wordvice academic resources pages, where we have dozens of helpful articles and videos on research writing and publications.

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How to Write Implications in Research

• Implications definition
• Recommendations vs implications
• Types of implications in research
• Step-by-step implications writing guide

Research implications examples

What the implications of the research definition?

• Theoretical implications stand for all the new additions to theories that have already been presented in the past. At the same time, one can use a totally new theory that provides a background and a framework for a study.
• Practical implications are about potential consequences that show the practical side of things.

Recommendations VS Implications

• Implied content versus proposed writing. It means that an implication should provide an outcome from your study. The recommendation is always based on the outcome, along with your words as a personal opinion.
• Potential impact a study may have versus a specific act. When you are composing your research paper, your implications have the purpose of discussing how the findings of the study matter. They should tell how your research has an impact on the subject that you address. Now, unlike the implications section of the research paper, recommendations refer to peculiar actions or steps you must take. They should be based on your opinion precisely and talk about what must be done since your research findings confirm that.

What are the types of implications in research?

• Political implications. These are mostly common for Law and Political Sciences students basing implications on a certain study, a speech, or legislative standards. It is a case when implications and recommendations can also be used to achieve an efficient result.
• Technological implications. When dealing with a technological implication, it serves as special implications for future research manuals where you discuss the study with several examples. Do not use a methodology in this section, as it can only be mentioned briefly.
• Findings related to policies. When you have implemented a special policy or you are dealing with a medical or legal finding, you should add it to your policy. Adding an implications section is necessary when it must be highlighted in your research.
• Topical (subject) implications. These are based on your subject and serve as a way to clarify things or as a method to narrow things down by supporting the finding before it is linked to a thesis statement or your main scientific argument.

Step-by-step implications in research writing guide

Step 1: talk about what has been discovered in your research., step 2: name the differences compared to what previous studies have found., step 3: discuss the implications of your findings., step 4: add specific information to showcase your contributions., step 5: match it with your discussion and thesis statement..

Green energy can benefit from the use of vertical turbines versus horizontal turbines due to construction methods and saving costs. 

The use of AI-based apps that contain repetition and grammar-checking will help ESL students and learners with special needs. 

Most studies provide more research on the social emphasis that influences the problem of bullying in the village area. It points out that most people have different cultural behavior where the problem of bullying is approached differently.

If you encounter challenges in terms of precise replication, you can use a CR genetic code to follow the policies used in 1994. Considering the theoretical limitations, it is necessary to provide exact theories and practical steps. It will help to resolve the challenge and compare what has been available back then. It will help to trace the temporal backline. 

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Implications or Recommendations in Research: What's the Difference?

• Peer Review

High-quality research articles that get many citations contain both implications and recommendations. Implications are the impact your research makes, whereas recommendations are specific actions that can then be taken based on your findings, such as for more research or for policymaking.

Updated on August 23, 2022

That seems clear enough, but the two are commonly confused.

This confusion is especially true if you come from a so-called high-context culture in which information is often implied based on the situation, as in many Asian cultures. High-context cultures are different from low-context cultures where information is more direct and explicit (as in North America and many European cultures).

Let's set these two straight in a low-context way; i.e., we'll be specific and direct! This is the best way to be in English academic writing because you're writing for the world.

Implications and recommendations in a research article

The standard format of STEM research articles is what's called IMRaD:

• Introduction
• Discussion/conclusions

Some journals call for a separate conclusions section, while others have the conclusions as the last part of the discussion. You'll write these four (or five) sections in the same sequence, though, no matter the journal.

The discussion section is typically where you restate your results and how well they confirmed your hypotheses. Give readers the answer to the questions for which they're looking to you for an answer.

At this point, many researchers assume their paper is finished. After all, aren't the results the most important part? As you might have guessed, no, you're not quite done yet.

The discussion/conclusions section is where to say what happened and what should now happen

The discussion/conclusions section of every good scientific article should contain the implications and recommendations.

The implications, first of all, are the impact your results have on your specific field. A high-impact, highly cited article will also broaden the scope here and provide implications to other fields. This is what makes research cross-disciplinary.

Recommendations, however, are suggestions to improve your field based on your results.

These two aspects help the reader understand your broader content: How and why your work is important to the world. They also tell the reader what can be changed in the future based on your results.

These aspects are what editors are looking for when selecting papers for peer review.

Implications and recommendations are, thus, written at the end of the discussion section, and before the concluding paragraph. They help to “wrap up” your paper. Once your reader understands what you found, the next logical step is what those results mean and what should come next.

Then they can take the baton, in the form of your work, and run with it. That gets you cited and extends your impact!

The order of implications and recommendations also matters. Both are written after you've summarized your main findings in the discussion section. Then, those results are interpreted based on ongoing work in the field. After this, the implications are stated, followed by the recommendations.

Writing an academic research paper is a bit like running a race. Finish strong, with your most important conclusion (recommendation) at the end. Leave readers with an understanding of your work's importance. Avoid generic, obvious phrases like "more research is needed to fully address this issue." Be specific.

The main differences between implications and recommendations (table)

Now let's dig a bit deeper into actually how to write these parts.

What are implications?

Research implications tell us how and why your results are important for the field at large. They help answer the question of “what does it mean?” Implications tell us how your work contributes to your field and what it adds to it. They're used when you want to tell your peers why your research is important for ongoing theory, practice, policymaking, and for future research.

Crucially, your implications must be evidence-based. This means they must be derived from the results in the paper.

Implications are written after you've summarized your main findings in the discussion section. They come before the recommendations and before the concluding paragraph. There is no specific section dedicated to implications. They must be integrated into your discussion so that the reader understands why the results are meaningful and what they add to the field.

A good strategy is to separate your implications into types. Implications can be social, political, technological, related to policies, or others, depending on your topic. The most frequently used types are theoretical and practical. Theoretical implications relate to how your findings connect to other theories or ideas in your field, while practical implications are related to what we can do with the results.

Key features of implications

• State the impact your research makes
• Helps us understand why your results are important
• Must be evidence-based
• Written in the discussion, before recommendations
• Can be theoretical, practical, or other (social, political, etc.)

Examples of implications

Let's take a look at some examples of research results below with their implications.

The result : one study found that learning items over time improves memory more than cramming material in a bunch of information at once .

The implications : This result suggests memory is better when studying is spread out over time, which could be due to memory consolidation processes.

The result : an intervention study found that mindfulness helps improve mental health if you have anxiety.

The implications : This result has implications for the role of executive functions on anxiety.

The result : a study found that musical learning helps language learning in children .

The implications : these findings suggest that language and music may work together to aid development.

What are recommendations?

As noted above, explaining how your results contribute to the real world is an important part of a successful article.

Likewise, stating how your findings can be used to improve something in future research is equally important. This brings us to the recommendations.

Research recommendations are suggestions and solutions you give for certain situations based on your results. Once the reader understands what your results mean with the implications, the next question they need to know is "what's next?"

Recommendations are calls to action on ways certain things in the field can be improved in the future based on your results. Recommendations are used when you want to convey that something different should be done based on what your analyses revealed.

Similar to implications, recommendations are also evidence-based. This means that your recommendations to the field must be drawn directly from your results.

The goal of the recommendations is to make clear, specific, and realistic suggestions to future researchers before they conduct a similar experiment. No matter what area your research is in, there will always be further research to do. Try to think about what would be helpful for other researchers to know before starting their work.

Recommendations are also written in the discussion section. They come after the implications and before the concluding paragraphs. Similar to the implications, there is usually no specific section dedicated to the recommendations. However, depending on how many solutions you want to suggest to the field, they may be written as a subsection.

Key features of recommendations

• Statements about what can be done differently in the field based on your findings
• Must be realistic and specific
• Written in the discussion, after implications and before conclusions
• Related to both your field and, preferably, a wider context to the research

Examples of recommendations

Here are some research results and their recommendations.

A meta-analysis found that actively recalling material from your memory is better than simply re-reading it .

• The recommendation: Based on these findings, teachers and other educators should encourage students to practice active recall strategies.

A medical intervention found that daily exercise helps prevent cardiovascular disease .

• The recommendation: Based on these results, physicians are recommended to encourage patients to exercise and walk regularly. Also recommended is to encourage more walking through public health offices in communities.

A study found that many research articles do not contain the sample sizes needed to statistically confirm their findings .

The recommendation: To improve the current state of the field, researchers should consider doing power analysis based on their experiment's design.

What else is important about implications and recommendations?

When writing recommendations and implications, be careful not to overstate the impact of your results. It can be tempting for researchers to inflate the importance of their findings and make grandiose statements about what their work means.

Remember that implications and recommendations must be coming directly from your results. Therefore, they must be straightforward, realistic, and plausible.

Another good thing to remember is to make sure the implications and recommendations are stated clearly and separately. Do not attach them to the endings of other paragraphs just to add them in. Use similar example phrases as those listed in the table when starting your sentences to clearly indicate when it's an implication and when it's a recommendation.

When your peers, or brand-new readers, read your paper, they shouldn't have to hunt through your discussion to find the implications and recommendations. They should be clear, visible, and understandable on their own.

That'll get you cited more, and you'll make a greater contribution to your area of science while extending the life and impact of your work.

The AJE Team

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What are the Academic Implications of a Research Study?

Gain knowledge about the distinction between academic limitations and recommendations to successfully incorporate them into your research.

If you intend to write a research paper, you should be aware that you must provide a background story that will lead to the rationale behind the research, providing context and assisting in the formulation of the issue statement, aiming to leave no doubt about your work, demonstrating its relevance and importance, and stating all possible methodological questions.

However, it is not uncommon for researchers to lose momentum at the end and struggle to find the correct conclusion for their research. Despite the fact that the discussion properly explains the findings, connects them to the issues raised in the introduction, and investigates them in the context of past research, something may appear to be lacking. This frequently leads to the conclusion of a research that is similar to one that has already been expressed.

This results in a lack of academic implications when readers or reviewers fail to recognize the significance of your research. To avoid this, continue reading this article to learn more about the academic implications .

What are the academic implications?

Implications are the consequences of your research; you must describe exactly why you assume your actual results are relevant and/or might be employed in future research. Most importantly, your implications must be supported by evidence. 

These implications must be based on the details and outcomes of your research, and any limitations of your approach or sample should be recognized in order to avoid gross generalization.

Depending on the type of research you perform, the implications of your findings can be clinical, philosophical, political, social, or ethical. It is crucial to understand that the most essential distinction is between practical implications, theoretical implications and implications for future research.

Practical Implications

The term “practical” literally means “real outcomes.” The reality that would occur if certain circumstances were met is referred to as practical implication. Determining the practical implications of several solutions can aid in determining which ones deliver the intended results.

For example, when doing clinical research, these outcomes are more likely to be practical. Assume you’re doing a trial for a medicine that treats infection without generating organism resistance; the consequences in this situation are that illnesses can be treated more promptly than in the past.

Theoretical Implications

In contrast, the theoretical implication is a newly discovered addition(s) to current theories or establishing elements for new theories. Theory’s role in research is to propose fascinating and potentially promising subjects to focus on.

The ability or possibility of research to affect society in apparent ways is characterized by theoretical implications. For example, research on human relationships and how COVID affects them can theorize that humans are less likely to interact now they’ve been through COVID. 

However, be cautious not to extrapolate your sampling or data to the broader population unless you have compelling reasons for it.

Implications that require future research

If you discover that your findings do not result in social reforms, innovative pedagogical policies or medical changes, they may have vital implications for future research projects. 

This implies that if you discover anything that may have an impact on other research, you should discuss the implications. Just be careful not to mistake an implication as a recommendation.

Implications vs. Recommendations

In a research paper, an implication is a conclusion that can be deduced from the research findings and the significance of these findings; this does not immediately imply that you think your findings will change everything by tomorrow, but that you have reason to expect they could have an impact in a particular way.

Recommendations, on the other hand, are precise ideas based on your findings about the best way to proceed in a certain scenario. For example, if you discovered a better approach to deal with a certain type of data (that may be utilized in other topics), you would recommend they discard the previous method.

Simply defined, an implication is an implicit conclusion of your research, whereas a recommendation is what you recommend based on the facts. 

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• Published: 30 July 2024

Mutual implications of procrastination research in adults and children for theory and intervention

• Caitlin E. V. Mahy   ORCID: orcid.org/0000-0003-0925-611X 1 ,
• Yuko Munakata 2 &
• Akira Miyake   ORCID: orcid.org/0000-0003-4671-7843 3  

Nature Reviews Psychology ( 2024 ) Cite this article

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• Human behaviour

Procrastination is a prevalent form of self-regulatory failure familiar to most people. Although many consider procrastination innocuous as long as the deadline is met, it is associated with negative consequences in various life domains. Thus, it is important to understand why people procrastinate, what factors contribute to procrastination and what can be done to reduce procrastination. Most research on these topics has been conducted with adults, and the few developmental studies have been conducted independently from adult procrastination research. In this Review, we seek to bring these disparate lines of research into closer alignment and point out their mutual implications. Specifically, we discuss how studying procrastination developmentally highlights a need to reconsider a highly restrictive definition of procrastination dominant in adult research. We also suggest future directions for both adult and developmental research, including measurement, theoretical development and interventions.

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The authors thank Nicolas Chevalier and his lab group, Logan Fiorella, Daniel Gustavson, Flaviu Hodis, Michael Kane and Katrin Klingsieck for providing useful feedback on an earlier version of this article. The authors also thank Sofia Garibay and Adrien Ward for creating initial sketches for Fig.  1 .

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All authors were involved in conceptualization of this review, and the writing and editing of the manuscript involved a highly collaborative process between developmental psychologists (C.E.V.M. & Y.M.) and a cognitive psychologist studying procrastination in adults (A.M.). C.E.V.M. and A.M. wrote an initial draft of the Introduction. C.E.V.M. and Y.M. wrote the initial draft of the ‘Procrastination in children’ section. A.M. wrote the initial drafts of ‘Procrastination in adults’ and ‘Summary and future directions’ sections. A.M. and Y.M. wrote the initial draft of ‘Mutual implications’ section. All authors edited the draft of the manuscript and approved the final version of the manuscript.

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Mahy, C.E.V., Munakata, Y. & Miyake, A. Mutual implications of procrastination research in adults and children for theory and intervention. Nat Rev Psychol (2024). https://doi.org/10.1038/s44159-024-00341-w

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Implications for Future Research and Practice

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The present chapter turns to implications for future research and practice. Whereas the previous chapter outlined the key findings from the empirical investigation, this chapter situates the insights born of the empirical work against the broader literature on critical alcohol and other drugs research. The chapter explores several key implications, the limitations of this research, and the conclusion of this work.

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Home » Implications – Definition, Types, and Applications

Implications – Definition, Types, and Applications

Table of Contents

Implications

Definition :

Implications refer to the consequences, outcomes, or effects of a particular action, decision, or event. It involves a careful analysis of the potential effects of something before it happens or after it has occurred. In other words, implications are the logical or practical results of something.

Implications Synonym

Following are synonyms used as implications:

• Consequences
• Ramifications
• Repercussions
• Significance
• Interpretations
• Relationship
• Correlation.

Types of Implications

Types of Implications are as follows:

Material Implication

This is the standard form of implication used in propositional logic. It is often denoted by the symbol “→” and can be read as “if-then.” For example, “If it is raining, then the ground is wet” can be written as “p → q,” where “p” represents “it is raining” and “q” represents “the ground is wet.” Material implication is also used in first-order logic.

Logical Implication

This is a more general type of implication that includes material implication as a special case. In logical implication, the truth of the antecedent implies the truth of the consequent, but the converse may not be true. For example, “All cats are mammals” logically implies “Some mammals are cats,” but the converse is not true. Logical implication is used in predicate logic.

Material Equivalence

This is a type of implication that goes in both directions. It is often denoted by the symbol “↔” and can be read as “if and only if.” For example, “Two lines are perpendicular if and only if their slopes are negative reciprocals” can be written as “p ↔ q,” where “p” represents “two lines are perpendicular” and “q” represents “their slopes are negative reciprocals.”

Causal Implication

This is a type of implication used in causal reasoning. It asserts that if one event (the cause) occurs, then another event (the effect) will necessarily follow. For example, “Smoking causes lung cancer” is a causal implication.

Modal Implication

This is a type of implication used in modal logic, which deals with concepts like possibility and necessity. Modal implication asserts that if something is necessarily true, then something else must also be true. For example, “If it is necessarily true that all bachelors are unmarried, then it is necessarily true that some unmarried men are bachelors.”

Implication in set theory

In set theory, an implication can be defined using set notation. For example, if A and B are sets, then the implication “if x is in A, then x is in B” can be written as A ⊆ B, which means “A is a subset of B.”

Material Conditional Implication

This is a type of implication that is similar to material implication, but with some subtle differences. It is often denoted by the symbol “⊢” and is used in proof theory. For example, “p, q ⊢ r” means that if p and q are true, then r must also be true.

Counterfactual Implication

This is a type of implication that deals with hypothetical or imagined situations. It asserts that if something had been true in the past or if something were different in the present, then something else would necessarily be true. For example, “If I had studied harder, I would have passed the test” is a counterfactual implication.

Psychological Implication

This is a type of implication that deals with the psychological effects of one event on another. For example, “If a child is exposed to violence at a young age, they may be more likely to exhibit violent behavior later in life” is a psychological implication.

Applications of Implications

Implications are used in a variety of fields and applications, including:

• Mathematics: In mathematical logic, implications are used to describe the relationship between propositions. An implication is a statement that connects a hypothesis to a conclusion, such as “If p, then q.” Implications are used extensively in proof writing.
• Computer Science : In computer science, implications are used to describe the behavior of algorithms and systems. Implications are used in programming languages to define logical conditions, and in databases to describe relationships between data.
• Philosophy : In philosophy , implications are used to express necessary and sufficient conditions for certain concepts or beliefs. Implications are often used to form arguments, as they can help to demonstrate the logical consistency or inconsistency of a set of beliefs.
• Law : Implications are used in legal reasoning and analysis, especially in interpreting statutes and legal precedents. Lawyers and judges use implications to determine the scope and meaning of legal concepts, and to assess the validity of legal arguments.
• Science : In science, implications are used to make predictions and test hypotheses. Scientists use implications to describe the expected outcomes of experiments and observations, and to determine whether their findings are consistent with existing theories.
• Business : In business, implications are used to make strategic decisions and assess the potential outcomes of different courses of action. Business analysts use implications to evaluate market trends and customer behavior, and to identify opportunities for growth and innovation.
• Education : In education, implications are used to evaluate the effectiveness of teaching methods and educational programs. Educators use implications to assess the impact of different teaching strategies on student learning outcomes, and to design curricula that are tailored to the needs of different learners.
• Psychology : In psychology , implications are used to study human behavior and cognition. Psychologists use implications to explore the relationships between different variables, such as personality traits, emotions, and social behaviors. Implications are also used to develop and test theories about human development and mental health.
• Marketing : In marketing, implications are used to assess the potential impact of advertising and promotional campaigns on consumer behavior. Marketers use implications to determine the most effective ways to reach and engage with target audiences, and to measure the effectiveness of different marketing strategies.
• Communication : In communication, implications are used to understand the meaning and significance of different forms of communication, such as language, nonverbal cues, and media messages. Communication scholars use implications to explore the ways in which communication shapes social relationships, identities, and cultural values.

How to Write Implications

Writing implications involves identifying the potential consequences or outcomes of a particular action, event, or decision. Here are some steps to follow when writing implications:

• Identify the relevant information: Start by analyzing the information you have and identify the key points or issues. This will help you understand the implications of the decision or action being taken.
• Determine the potential consequences: Think about the potential outcomes of the decision or action. Consider the short-term and long-term effects, as well as the positive and negative consequences.
• Consider different scenarios : Try to anticipate different scenarios that may arise as a result of the decision or action. Consider how different stakeholders may be affected and what their reactions might be.
• Evaluate the implications: Evaluate the potential implications of the decision or action based on the information you have gathered. Consider the impact on individuals, organizations, and society as a whole.
• Present your findings: Present your findings clearly and concisely. Use data and evidence to support your conclusions and provide recommendations for next steps.
• Consider potential solutions: If the implications are negative, consider potential solutions that could mitigate the negative consequences. If the implications are positive, consider how to maximize the benefits.
• Review and revise: Review your implications and make revisions as needed. Ensure that your implications are clear, concise, and supported by evidence.

Importance of Implications

Implications are important because they help us to understand the potential consequences or effects of a particular decision, action, or event. They allow us to anticipate and prepare for possible outcomes, both positive and negative, which can inform our choices and decision-making processes.

Here are some specific reasons why implications are important:

• Decision-making : Implications help us to make better decisions by providing us with a clearer understanding of the potential consequences of our choices. By considering the implications of different options, we can choose the one that is most likely to lead to a positive outcome.
• Planning : Implications are also important in the planning process. By identifying the potential consequences of different scenarios, we can develop more effective plans that take into account the risks and opportunities associated with each option.
• Risk management : Understanding the implications of a particular decision or action can help us to manage risk more effectively. By anticipating possible negative outcomes, we can take steps to minimize or mitigate those risks, and be better prepared to handle any issues that arise.
• Communication: Communicating the implications of a particular decision or action can help to ensure that everyone involved is on the same page. By sharing information about potential consequences, we can ensure that everyone understands the risks and opportunities associated with a particular course of action.

When to use Implications

Implications are useful when you want to describe the consequences or results of a particular action, event, or situation. They are commonly used in academic writing, legal documents, and scientific reports to explain the potential impact of findings, policies, or decisions.

Here are some examples of when to use implications:

• In scientific research , implications are used to explain the potential applications or limitations of the study findings.
• In legal documents , implications are used to describe the possible consequences of a court ruling or decision.
• In business reports , implications are used to explain the potential effects of a new product launch, marketing strategy, or financial decision.
• In academic writing , implications are used to discuss the broader significance of research findings and to suggest future research directions.

Advantages of Implications

Some Advantages of Implications are as follows:

• Clarity : Implications provide a clear and concise statement of what follows from a given premise. By defining the relationship between the premise and the conclusion, they eliminate ambiguity and make the argument easier to understand.
• Rigor : Implications provide a rigorous framework for reasoning. They require that the relationship between the premise and the conclusion be logical and consistent, which helps to avoid fallacious reasoning and ensures that the argument is sound.
• Consistency : Implications help to ensure that arguments are consistent. By defining the relationship between the premise and the conclusion, they ensure that the argument is coherent and that there are no contradictions.
• Predictive power: Implications can be used to make predictions. By defining the relationship between the premise and the conclusion, they allow us to make predictions about what will happen in the future if certain conditions are met.
• Applicability : Implications are widely applicable across a range of domains. They can be used in mathematics, science, philosophy, and many other areas to make logical arguments and draw conclusions based on evidence and reasoning.

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Burt J, Campbell J, Abel G, et al. Improving patient experience in primary care: a multimethod programme of research on the measurement and improvement of patient experience. Southampton (UK): NIHR Journals Library; 2017 Apr. (Programme Grants for Applied Research, No. 5.9.)

Improving patient experience in primary care: a multimethod programme of research on the measurement and improvement of patient experience.

Chapter 12 conclusions, implications for practice and recommendations for future research.

• Conclusions

In Chapter 1 we outlined how, following the introduction of a wide range of quality improvement strategies as part of an overarching ‘clinical governance’ strategy in the late 1990s, there had been step changes in the management of major chronic diseases in the NHS. However, the ways in which patients experienced health care had not been given such a priority and the need for a rebalancing was seen by increasing attention to patient experience in policy documents, the routine publication of patient experience data, benchmarking of hospitals in relation to patient experience and even an (ill-fated) attempt to attach payments to patients’ assessments of their GP ’s care.

There has therefore been widespread acceptance that good patient experience is an important outcome of care in its own right and our work 304 and that of others 305 has shown that patient experience is a domain of quality that is distinct from, but complementary to, the quality of clinical care. Although an increasing number of surveys have been developed to measure patient experience, there has been equally widespread acceptance that these measures have not been very effective at actually improving care. 45 This is the background to our programme of work. Entitled IMPROVE , we aimed to find better ways of both measuring and using information on patient experience that would lead to improvements in patient care in both in-hours and out-of-hours primary care settings.

In the introduction, we described a range of ways of obtaining patient feedback on their care, including surveys, focus groups and analysis of complaints. In this programme, we have focused on the use of patient surveys as they are the dominant method currently used in the UK. However, in Chapter 10 we describe an exploratory trial of RTF , which moves away from the paper-based questionnaires that still dominate the measurement of patient experience in the NHS.

This programme had seven aims, each of which was tied closely to one work package of research. These aims were to:

• understand how general practices respond to low patient survey scores, testing a range of approaches that could be used to improve patients’ experience of care
• estimate the extent to which aggregation of scores to practice level in the national study masks differences between individual doctors
• investigate how patients’ ratings on questions in the GP Patient Survey relate to actual behaviour by GPs in consultations
• understand better patients’ responses to questions on communication and seeing a doctor of their choice
• understand the reasons why minority ethnic groups, especially South Asian populations, give lower scores on patient surveys than the white British population
• carry out an exploratory RCT of an intervention to improve patient experience, using tools developed in earlier parts of the programme
• investigate how the results of the GP Patient Survey can be used to improve patients’ experience of out-of-hours care.

The aims of the programme did not change during the 5 years of our research, although some details of the research were modified as the work progressed (we have summarised any changes in each individual chapter). We presented the results of our research under three broad headings and also use these headings in this conclusions chapter, namely:

• understanding patient experience data (aims 3 and 4)
• understanding patient experience in minority ethnic groups (aim 5)
• using data on patient experience for quality improvement (aims 1, 2, 6 and 7).

Understanding patient experience data

Patient surveys are now widely used in many countries, yet still comparatively little is known about what experiences lead patients to respond in particular ways in these surveys. What drives them to tick particular boxes and how do those responses relate to the care that they have actually received? We approached this in two main studies, one in which we asked patients directly about how they chose certain items on the questionnaire while showing them a video of their consultation (see Chapter 2 ) and one in which we compared their responses with those of expert raters using two standard instruments for assessing videos of consultations (see Chapter 3 ). The results of these studies have important implications for the interpretation of survey data, particularly data focused on patient evaluations of specific encounters with health-care professionals.

The first study (see Chapter 2 ) showed that, although patients readily criticised their care when reviewing GP consultations on video, they had been reluctant to be critical when completing a questionnaire after the consultation. Reasons for this included the need to maintain a relationship with the GP (including uncertainty about how confidential survey results would be) and their gratitude for the care that they had received from the NHS in the past. In addition, perceived power asymmetries made people reluctant to criticise their doctor. Patients were also disinclined to be critical when completing a questionnaire if they had actually received the treatment that they wanted. Overall, we concluded that patients find that questionnaires administered at the point of care may be limited tools for being able to feed back concerns about primary care consultations.

The second study (see Chapter 3 ) reinforced our conclusion from Chapter 2 that patient evaluations of consultations in surveys may present an uncritical view of the actual consultations. In this study videotapes of GP –patient consultations were assessed by four independent clinical raters. The results were striking. When trained raters rated communication within a consultation to be of a high standard, patients did the same (with one single exception). However, when trained raters judged the communication during a consultation to be of a poor standard, patients’ assessments varied from poor to very good. This finding again points to the reluctance of patients to criticise their doctor in questionnaire surveys. In the previous study the ‘gold standard’ was the patient’s own account of the consultation and in this study the standard was that of a trained external GP rater.

We do not think that these results mean that patient surveys cannot be used to assess the quality of general practice care. However, they do point to clear limitations. One of the concerns that GPs have about surveys (see Chapters 7 and 8 ) is that they are selectively completed by critical or grumpy patients and that survey results will therefore give a negative and biased view of their care. The results of the two studies described here suggest that the opposite is the case. Patients’ reluctance to criticise their doctor means that survey responses using evaluative type of questions are likely to give an overly positive view of their doctor’s care. This is one reason why there has been a move towards using report items in some survey instruments (though we do not know whether or not these suffer from similar problems). Because of this tendency for patients to choose the most positive response options, we suggest that absolute scores should be treated with some caution, as they may present an overly optimistic view of their care. However, this does not mean that surveys cannot be used to look at relative scores: scores from a GP that are lower than those of his or her colleagues and from GPs in other practices are likely to indicate a problem, even though high scores from other doctors or practices may conceal deficiencies in care in those practices too.

We also looked at how GPs rated their own consultations. GPs completed a form immediately after each consultation, using the same scale as the patients. GPs were certainly more inclined to criticise themselves than the patients were to criticise the care that they had received. This is entirely consistent with the findings from our subsequent interviews with patients. However, we found absolutely no correlation between patient scores and GP scores. Neither did we find any correlation between GPs’ own scores and those of expert raters who reviewed the consultations on video. GPs are clearly using different parameters when assessing their own performance, but we were not able to investigate this in more detail in this study.

When we spoke to GPs about their survey results (see Chapters 7 and 8 ), through both focus groups and face-to-face interviews, they reported how, although positive about the concept of patient feedback, they struggled to engage with and make changes under the current approaches to measurement. They also commonly expressed concern that patients would be critical of their care if they did not get what they wanted (e.g. an antibiotic prescription). This concern was borne out to some extent by our results. In our analysis of the assessment of nurses (see Chapter 4 ), a strong predictor of survey scores was whether or not patients wanted to see a nurse when they first contacted the practice. If they had wanted to see a GP but saw a nurse, the scores given to those nurses were much lower. We have no reason to think that the nurses’ communication was worse in those consultations and the low scores may therefore indicate a more general dissatisfaction of patients because of not having their original expectations met.

It is important to understand that, in line with the overall aims of the programme, the work in these two chapters focused on the assessment of communication in the primary care consultation (such as giving the patient enough time and explaining tests and treatments). Our conclusion that survey scores have more value in assessing relative performance than absolute performance of doctors may or may not hold true for other aspects of practice performance commonly assessed in surveys, such as difficulty in getting appointments, getting through on the telephone and waiting times. Patients’ reasons for not wanting to criticise their doctor may be less important when they assess what they regard as management aspects of the practice.

A second aspect of care that we identified as part of our programme of work relates to patients’ ability to see a GP of their choice. Although most of our research focused on communication, the results that we report in Chapter 4 have some important findings in relation to patient choice. 142 The results show that most patients have a particular GP who they prefer to see. It is sometimes suggested that this matters only for some population groups (e.g. not young people) but we found that this is not the case. Even among those aged 18–24 years, > 50% of respondents to the GP Patient Survey have a particular doctor who they prefer to see, rising to > 80% in those aged > 75 years. Disturbingly, a large percentage of people who have such a preference are unable to see the doctor of their choice. This percentage has risen from 30% to 40% from 2010 to 2015. One possible impact of this change comes from our analysis of data from patients who saw a nurse when they had originally wanted to see a doctor; they expressed considerable dissatisfaction with their subsequent consultation with the nurse. However, these data do not reflect what would have happened if patients had seen another doctor, just not the one of their choice.

Overall, patients express more negative opinions about choice of doctor than in any other part of the GP Patient Survey, something that may in part have got worse as a result of government policies to improve access. There is a clear tension between the ability of practices to provide rapid access and the ability of practices to provide continuity of care and data from our studies suggest that patients’ inability to see a doctor of their choice is a significant quality issue for the NHS.

Understanding patient experience in minority ethnic groups

In this part of our research, we focused our main work on survey responses from minority ethnic groups and on South Asian groups in particular. The general interest in minority ethnic groups is because they tend to report worse experiences using surveys in most countries studied, including in the UK. Our research on out-of-hours care in this programme ( see Chapter 11 ) replicated this result, with Asian and mixed ethnic groups reporting worse experiences than the white majority.

Our specific focus in the major strand of this research was on South Asian respondents because of the size of this group in England and the consistently low scores generated by this group in English surveys across both primary and secondary care settings. We focused on questionnaires competed in English; although the GP Patient Survey is available in 15 languages, a tiny minority of surveys are completed in languages other than English (typically < 0.2% of returns).

A number of potential explanations have been suggested for the lower ratings given by South Asian and other minority ethnic groups. Broadly, these relate to whether these groups of patients (1) receive lower-quality care or (2) receive the same care but rate this more negatively. 75 For example, such respondents might rate the same care more negatively if they have higher expectations or because they interpret the survey items and response options in different ways (such as being culturally less likely to check extreme options).

The last of these options was potentially the simplest to explore. Taking advantage of the large numbers of respondents available in the GP Patient Survey to examine the responses of South Asian groups using item response theory and allowing for a wide range of other sociodemographic characteristics (see Chapter 5 , Workstream 3 ), we found no evidence that South Asian respondents used the scales in a different way from white British respondents. Although these results do not provide conclusive evidence of equivalence in the way in which different respondents use the survey scales, they increase the likelihood that the worse experience reported by South Asian respondents reflects either differences in expectations or genuinely worse care. Our previous work 75 suggested that, for one aspect of care (waiting times), South Asian respondents might have higher expectations of care, implying that their lower scores on surveys might not be associated with worse care. We were able to advance our understanding of this complex issue considerably as a result of the research in this programme.

First, we showed that South Asian respondents to the GP Patient Survey tend to be registered in practices with generally low scores. This explained about half of the difference in reported experience between South Asian and white British patients (see Chapter 5 , Workstream 1 ) and identified that some practice effects were related to the ethnicity of the doctor (with minority ethnic doctors receiving lower scores for doctor–patient communication; see Chapter 5 , Workstream 4 ). However, these practice effects did not account for the low scores among South Asian patients, even though the differences were reduced when practices offered consultations in a South Asian language 172 (PhD project allied to our programme). Next, we showed that, far from being uniform across all population groups, the lower scores from South Asian patients were much more marked among older female respondents. It was therefore important in our subsequent work to ensure that these patients were represented in our research (see Chapter 5 , Workstream 2 ).

In video elicitation interviews with South Asian patients (see Chapter 2 ), we identified the same issues driving evaluations of communication in South Asian as in white British patients: their relationship with their GP (and others within the practice), their expectations of the consultation and a reluctance to criticise their doctor’s performance. The finding that South Asian patients are assessing broadly similar issues when completing questionnaires therefore still leaves unanswered the question of why scores from South Asian patients are low.

The final and most original part of this work provides insight into this (see Chapter 6 ). Here, we filmed 16 simulated consultations based on transcripts of real consultations using various combinations of white and Asian doctors and patients, with half scripted to be ‘good’ and half scripted to be ‘poor’. We showed three randomly sampled videos to each of 1120 people (half of whom were white British and half of whom were Pakistani, equally split between those aged < 55 years and those aged ≥ 55 years) and asked them to score the consultations using the communication items from the GP Patient Survey.

If the low scores reported by South Asian patients in real-life settings were the result of higher expectations on their part, then we would expect them to give lower scores in the experimental vignette situation. However, quite the reverse happened. When viewing the same consultations, South Asian respondents gave scores that were higher, indeed much higher when adjusted for sociodemographic characteristics, than those of the white British respondents. This suggests that the low scores given by South Asian patients in surveys such as the GP Patient Survey reflect care that is genuinely worse, and possibly much worse, than that experienced by their white British counterparts. This is consistent with the only previous study of this type in which predominantly written consultations were shown to people from different ethnic groups in the USA, with the conclusion being that differences in ratings were more likely to represent differences in care than differences in expectations or scale use. 81

There is a clear practice implication of this result: low scores from South Asian patients should be investigated as possible indicators of poor care. This is relevant to all settings, not just primary care.

Using data on patient experience for quality improvement

The results that we have discussed so far indicate that the results of patient experience surveys such as the GP Patient Survey can identify areas where there are important gaps in care that the NHS provides, such as patients being able to see a doctor of their choice. However, although patients tend to give very high scores for doctor–patient communication, these conceal significant negative experiences that patients describe when shown, and which independent observers can see in, recorded primary care consultations. These issues extend to minority ethnic patients and our research suggests that the negative scores that South Asian patients record (compared with those of white British patients) do represent genuine problems with care. This therefore brings us to the important issue of how data from patient surveys can be used to improve care.

Current national approaches to measuring patient experience, including communication, rely on practice-level assessments of care. In Chapter 9 , we outline the results of a patient experience survey that we conducted across 25 general practices, asking patients specifically about their experience of a particular consultation with a named GP . We found that practice-level scores for communication mask considerable variation between GPs within each practice, notably for those practices receiving poorer communication scores overall. Such ‘poorly performing’ practices, which may be identified as such through the national GP Patient Survey, may in fact contain GPs with communication skills ranging from very poor to very good. This has important implications for the use of national survey data to identify primary care practices and practitioners in need of improvement.

In Chapters 7 and 8 we describe the two studies in which we sought the views of GPs and practice staff on survey results, seeking to understand how they could better be used as quality improvement tools. Chapter 7 describes focus groups with practice staff following feedback of practice-level scores for patient experience and Chapter 8 describes interviews with GPs after we had conducted a survey in which they received individual feedback from surveys returned by patients whom they had seen in the surgery. In Chapter 11 , we describe how out-of-hours providers use data from patient surveys.

Broadly, staff in different primary care settings neither believed nor trusted patient surveys. Concerns were expressed about the validity and reliability of surveys (some practices have very low rates of response) and about the likely representativeness of those who responded. Some practice groups mentioned recent negative experiences with pay linked to survey scores as part of the QOF (a technicality of the payment schedule meant that payments could be reduced even though practice performance had improved). There was also a view expressed that some patients had unreasonable expectations: staff worked as hard as they could and could not be expected to respond to all patients’ ‘wants’. Some practices did describe improvements that they had made as a result of survey results. Those that were easiest to engage with related to practices’ office functions such as appointment systems and telephone answering systems. Addressing an individual doctor’s performance (e.g. communication skills) was much more difficult. Out-of-hours service staff were also concerned that service users did not understand the complex care pathways within urgent care settings and that this might lead to unrealistic expectations of what individual services were expected to deliver. Staff viewed surveys as necessary, but not sufficient. Clear preferences for more qualitative feedback to supplement survey scores were expressed as this provided more actionable data on which to mount quality improvement initiatives.

The doctors who we interviewed expressed markedly ambivalent views in discussing feedback from surveys. Although they had a number of concerns about individual doctor surveys (credibility, reliability, concerns about patient motivation), they also expressed positive views about the importance of patient feedback in monitoring and improving services.

These results led us to consider how patient feedback might be obtained in a way that would engage doctors more actively with patient survey results to stimulate quality improvement. We conducted a preliminary evaluation of RTF , using touch screens that patients could use to leave feedback following a primary care consultation. RTF was selected to address some of the problems identified by our research, such as providing practice feedback on a much more regular basis (e.g. fortnightly) and allowing practices the opportunity to add questions of their own to the RTF survey to increase the relevance of the results to their service.

As RTF has not been widely used, an exploratory RCT and qualitative study were conducted to answer questions about the feasibility of using RTF in real-world general practice, estimate likely response rates, obtain patient and staff views on providing feedback in this way and estimate the costs to a practice of introducing RTF. We also included facilitated feedback in one arm of the exploratory trial.

In the exploratory trial, only 2.5% of consulting patients left any RFT without prompting; however, if encouraged to leave RTF by staff, as many as 60% of patients did so. Encouragement was rare, with such encouragement provided in only 5% of > 1100 patient–staff interactions that we observed in reception areas. Of patients who used a touch screen to leave RTF, 86% found it easy to use and were positive about it as a feedback method. Lack of awareness of the screens and lack of time were the most common reasons given for not providing feedback.

Staff were broadly positive about using RTF and practices valued the ability to include their own questions in the survey. Practices that had open communication between staff members tended to be more positive about using patient feedback. Practice staff identified clear benefits from having a facilitated session for discussion of patient feedback and having protected time to discuss the results.

Had practices not been taking part in a research study, the cost of RTF to practices would have been substantial at > £1000 for the 12 weeks, with the bulk of the cost relating to provision of the equipment and analysis and feedback of the data collected from the touch screens.

Although the absolute number of patients providing RTF to each practice (> 100) was comparable to the number of respondents per practice in the national GP Patient Survey, we do now know how the considerably lower response rate in our RTF study (2.5%) would have affected the outcome of the patient experience surveys (it was not part of our study design to find this out). We do not know how representative or valuable the views of a small proportion of patients who respond are, just as we do not know how representative are the views of the very small numbers of patients providing the narrative feedback that is recorded on NHS Choices.

Considering these results together, we have been able to identify some clear learning to take forward into a future clinical trial examining the potential utility and effectiveness of RTF in informing service delivery in primary care.

• Implications for practice

The work that we have carried out over the 5 years of the programme grant has clear implications for practice. We summarise these here.

The importance of patient experience

Our research supports the continuing emphasis on obtaining patient experience feedback as an important means of informing NHS care. Although continuing effort should be invested in refining the most effective and meaningful mechanism to capture high-quality patient feedback, the key challenge is to provide primary care staff with the support and means to enable them to act on patient feedback.

The need for action on the quality of care for minority ethnic groups

There has been much speculation whether the lower scores reported by minority ethnic groups on numerous patient experience surveys are ‘real’, reflecting poorer quality of care, or are an artefact of the questionnaires used or higher expectations of care. We have now conducted a series of studies to progressively examine this issue to understand with greater certainty the major drivers of reported variations in care. Examinations of survey responses, interviews with patients and an innovative experimental vignette study combine to strongly suggest that it is the former: patients from South Asian backgrounds experience considerably poorer communication with GPs than their white British counterparts. It is of concern that survey results may be dismissed as artefactual when, in fact, they are likely to point to real areas of concern. Effort should be invested to ensure that lower scores from such groups on patient experience surveys in both primary care and secondary care are investigated as markers of poorer quality of care.

Patients give overly positive responses when rating their care

Our results show the difficulty that patients have in feeding back negative experiences in questionnaire surveys. This suggests that there is more work to be done in improving patient experience than might be suggested by the high scores that are commonly seen in patient surveys. However, patients’ reluctance to criticise a doctor or provider with whom they have to maintain an ongoing relationship will not be addressed simply by changing the survey method. Efforts should be made to ensure that providers and managers understand that absolute scores paint an optimistic picture of patients’ true views.

Surveys are not sufficient to fully capture patient feedback

Across primary and out-of-hours care settings, staff view patient surveys as necessary, but not sufficient. Alternative methods for gaining more qualitative feedback were commonly used to supplement survey scores, with free text often viewed as providing more actionable data than responses to standard survey questions. Taken alongside our findings on patients’ reluctance to criticise doctors through surveys and staff challenges to the credibility of surveys, we suggest that additional approaches are therefore needed to better capture aspects of patient experience that can be used to improve the quality of care.

The need for valid, reliable individual-level feedback for doctors

Despite the comments above, we have shown that there is substantial variation in performance within practices for aspects of care related to individual doctors (e.g. doctor–patient communication). Reporting patient experience at practice level masks this variation and makes it more difficult for doctors to relate to feedback. However, we have also shown that, if a practice has overall high scores for doctor–patient communication, it is very unlikely that such a practice contains a low-scoring doctor. In contrast, when a practice is low scoring, individual doctors may be high or low scoring. Therefore, if there are additional requirements for individual-level surveys, they could be focused on practices with low overall scores. Additionally, robust mechanisms are required to help practices, particularly lower-scoring practices, identify and support individual doctors whose patient feedback identifies areas of potential improvement.

We note that, at present, data are provided at practice level for the GP Patient Survey, scores are produced at practice level for the Friends and Family Test and GPs have to provide individual-level surveys to meet GMC requirements for revalidation. This results in considerable overlap and duplication and adds to the sense that these are ‘boxes to be ticked’ rather than sources of information that are valuable for improving care.

Patient surveys need to become more meaningful to staff

Our research shows that primary care staff in different settings are ambivalent about the value of patient surveys. Although believing in general about the importance of issues such as doctor–patient communication, they use every opportunity to challenge the credibility and reliability of scores produced by national surveys. This is not helped by their recent experiences, for example of a poorly conceived attempt to tie financial incentives to patient reports of waiting times to get an appointment 306 and the imposition of the Friends and Family Test, which is even regarded by NHS England as being of limited value for comparing health-care organisations. 60

On the whole, practices found it easier to engage with items on surveys that related to practice management (e.g. availability of appointments, ability to get through on the telephone) than to items that related to issues around communication between patients and clinical staff. Staff viewed surveys as necessary, but not sufficient, and expressed a clear preference for qualitative feedback to supplement survey scores as this provided more actionable data on which to mount quality improvement initiatives.

Immediacy of feedback, regularity of feedback and having some control over the questions asked were all aspects of our experiment with RTF that were valued by practices and had the potential to make feedback more useful. However, a number of important questions remain before RTF could be recommended as a replacement for postal questionnaires. We outline these in the next section on research recommendations.

The value of surveys in monitoring national trends

Despite some reservations about the value of national surveys as vehicles for stimulating quality improvement in general practices and out-of-hours services, they can be important for monitoring national trends. For example, the GP Patient Survey is the only source of data which demonstrates that, year on year, from 2010 to 2015, patients report that they have had increasing difficulty in seeing a doctor of their choice. Indeed, for out-of-hours services the GP Patient Survey is the only way to monitor such trends as individual services use very different tools and approaches, precluding comparisons. Additionally, patient feedback – particularly in secondary care – is used for organisational risk assessment and regulatory monitoring. However, when national surveys are used to monitor trends in care it is important that the questions stay the same. In contrast to questions in the GP Patient Survey related to whether or not patients are able to see a doctor of their choice, questions in the survey on access have undergone major changes, making it difficult to follow long-term trends. However, it should be noted that much smaller sample sizes are required to monitor national trends and comparable national surveys often include tens of thousands of participants rather than millions. Our work on out-of-hours care suggests some ways in which the current questions in the GP Patient Survey could be improved.

Development of surveys in out-of-hours care

Our work on the use of patient experience surveys in out-of-hours care highlights a number of areas requiring consideration. National quality requirements (NQR5) state that all out-of-hours services must audit patient experience but provide no information on how to do this. 307 In the absence of clear guidance on tools and approaches, many services are taking different tacks to both collect and act on patient feedback. As well as being inefficient in approach, with little consistency or shared learning, this also precludes national comparisons being made between providers. We suggest that NQR5 should be reviewed and tightened to avoid the duplication of effort occurring in different services.

Second, out-of-hours items from the GP Patient Survey are now being used for the purposes of CQC and National Audit Office monitoring of out-of-hours care. Our research in this area commenced prior to the launch of the CQC and providers knew little about the GP Patient Survey and expressed concern about the relevance of the out-of-hours items. Our research suggests that, subject to minor amendments, the GP Patient Survey is suitable for this kind of national monitoring of out-of-hours care; indeed, it is the only current approach suitable for monitoring, given the variation in approaches to patient feedback currently taken by service providers. However, although the GP Patient Survey enables the use of benchmarking, it is not sufficiently detailed to support quality improvement and as such is unlikely to replace the in-house methods and tools being used by providers. We also note that current presentations of GP Patient Survey data for out-of-hours care are at ‘commissioner’ level; as providers often cover more than one commissioner level, such analyses may not highlight problems occurring at the larger organisational level. Finally, to look at the performance of different out-of-hours providers on key patient experience measures, it is important that NHS England maintains a list of such providers to ensure oversight, which it currently does not.

Overall, large-scale postal surveys are likely to remain the dominant approach for gathering patient feedback for the time being, although refinements to this approach as well as the development of other modes are required to address the weaknesses that we have identified. We are aware that providers are experimenting with a wide range of other approaches, one of which ( RTF ) has been part of our research. Other methods include interviews and focus groups, online feedback, analysis of complaints, practice participation groups and social media. In the following section, we outline recommendations for research and identify the criteria that any new methods will need to meet to become useful quality improvement tools.

• Recommendations for research

The world of patient feedback is becoming increasingly diverse and complex, with standard patient survey approaches being supplemented by the use of tablets, kiosks, online feedback, including that provided by the NHS and by commercial organisations, analysis of complaints, the use of interviews and focus groups and practice participation groups. In addition, social media may come to play an important part in how patients choose their doctor and how they feed back on their experiences. Some of these new approaches are being evaluated in terms of their ability to provide more detailed information on what is needed to improve services, for example using patient narratives 308 and through the analysis of internet-based feedback. 309 , 310 However, despite the plethora of approaches to gathering patient feedback, our research demonstrates that there is a major deficit in taking action as a result of such feedback. Enabling and supporting providers to engage with and plan changes may require complex whole-system approaches, and our knowledge of what is most effective in this area is currently sparse.

Research is therefore needed into how gathering and acting on patient feedback may be best supported, across five key areas:

• How patient experience can be captured so that it more effectively identifies areas of performance that could be improved – this should include investigation of diverse methods of obtaining patient feedback to support patients to highlight poor care when necessary. An additional important area of work is how some of the issues highlighted within this report, such as patients’ reluctance to criticise, apply to different approaches to assessing patient experience using either rating-type or report-type questionnaire items.
• The system, practitioner and patient factors that influence poorer reported experiences of care in South Asian patient groups and how these may be addressed – this should include a particular focus on the impact of cross-cultural consultations.
• How information from patients can be fed back to clinicians and services in a way that appears credible to them – this should include evaluations of approaches to increase the plausibility of patient surveys, such as greater use of benchmarking and innovative ways of presenting and interpreting findings, as well as assessment of varying, tailored ways of presenting feedback to the different health-care professionals who might receive feedback on their care. Of additional relevance here is how clinicians are encouraged to reflect on their own performance and others’ assessments of this, with the aim of understanding where and how gaps in evaluations may occur.
• How services can be organised and managed in such a way that patient feedback is seen as a positive opportunity for improving services.
• What interventions are most effective in improving care when deficiencies in care are identified – the area where there is the greatest gap here is in doctor–patient communication, with our results showing that clinicians have great difficulty in even discussing deficiencies among their colleagues and that few effective interventions exist.

Our finding in the research on out-of-hours care that commercial providers had lower ratings for patient experience than services provided by the NHS is consistent with previous work suggesting that practices working under Alternative Provider Medical Services contracts, which are sometimes provided by the private sector, may provide worse care. 311 However, the circumstances in which commercial providers gain contracts for primary care services may be very different from those in other areas. The way in which the primary care workforce is configured is changing rapidly, with an increase in the proportion of salaried GPs, the development of GP federations and super-practices and an increase in the number of large-scale provider groups (owned both by commercial companies and by GPs). It is important that these changes should be monitored so that we understand their impact on quality of care.

Included under terms of UK Non-commercial Government License .

• Cite this Page Burt J, Campbell J, Abel G, et al. Improving patient experience in primary care: a multimethod programme of research on the measurement and improvement of patient experience. Southampton (UK): NIHR Journals Library; 2017 Apr. (Programme Grants for Applied Research, No. 5.9.) Chapter 12, Conclusions, implications for practice and recommendations for future research.
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• Open access
• Published: 08 August 2024

HPV vaccine behaviors and intentions among a diverse sample of women aged 27-45 years: implications for shared clinical decision-making

• Jennifer D. Allen 1 ,
• Nadia N. Abuelezam 2 ,
• Raviv Rose 1 ,
• Katelin Isakoff 1 ,
• Gregory Zimet 3 &
• Holly B. Fontenot 4  

BMC Public Health volume  24 , Article number:  2154 ( 2024 ) Cite this article

Metrics details

The Advisory Committee on Immunization Practices issued a shared clinical decision-making (SCDM) recommendation for HPV vaccination in persons aged 27–45. Since expanded eligibility for the vaccine was issued, little information has been available about HPV vaccine behaviors and intentions among women in this age group.

We conducted a cross-sectional online survey among women aged 27–45 years recruited through a Qualtrics™ respondent panel ( N  = 324) to answer the following questions (1) What is the prevalence of HPV vaccination among a diverse sample of adult women aged 27–45 years? (2) What are the characteristics of those who have or have not previously been vaccinated? and (3) What factors are associated with the intention to obtain the HPV vaccine among those who had never been vaccinated? Multivariable logistic regression analyses estimated adjusted odds ratios (AORs) and 95% confidence intervals (95% CIs).

Only 31.1% had at least one dose of the HPV vaccine. In multivariable analyses, those more likely to have been vaccinated were younger and were more likely to believe that the vaccine was effective. Of those unvaccinated or unsure, 54.8% indicated they were likely to get vaccinated in the future. Factors associated with future vaccine intention (compared to those not intending) included beliefs about vaccine testing, perceived likelihood of HPV infection, greater comfort in asking one’s provider for vaccination, and prior negative healthcare experiences.

Conclusions

Our findings suggest that many women in this age group are interested in HPV vaccination. While the recommendation is for SCDM rather than routine vaccination for all women in this age group, efforts to promote informed decision-making among mid-adult women may include educating women about the rigorous vaccine testing and approval process, their risk factors for HPV infection, and encouraging them to engage in SCDM with their medical providers. Targeted efforts to reach women who have had negative experiences with healthcare may also be needed.

Peer Review reports

Introduction

Despite the availability of primary prevention via vaccination, the human papillomavirus (HPV) remains the most common sexually transmitted infection in the United States (U.S.). Each year, approximately 14 million people in the U.S. are newly infected with HPV, and about 35,900 develop a new cervical or other HPV-related cancer [ 1 , 2 ]. Highly effective HPV vaccines have been available since 2006 and, until recently, were only approved for those aged 9 through 26 years by the U.S. Food and Drug Administration (FDA). In 2018, the FDA expanded its approval to include persons aged 27–45 years (“mid-adults”) [ 3 ]. Subsequently, in 2019, the Advisory Committee on Immunization Practices (ACIP) issued a shared clinical decision-making recommendation for HPV vaccination for mid-adults not previously vaccinated [ 4 ]. SCDM involves a discussion between patients and providers about the best available evidence for HPV vaccination, individual risks, and vaccine benefits versus potential harms to arrive at a mutually agreeable decision [ 5 ]. As this recommendation differs from routine vaccination that is recommended for younger women, there is a need to understand the extent to which the population of mid-adult women not previously vaccinated would prefer to be vaccinated with the knowledge that they are now potentially eligible [ 6 ].

While expansion of eligibility for the HPV vaccine among persons aged 27–45 years provides a significant step towards minimizing the potential burden of HPV-related cancers, uptake of the vaccine among populations for whom it had been previously recommended (routine recommendation for adolescents aged 11–13 years; catch up recommendation for those aged 18–26 years) has yet to meet the national goal of 80% series completion [ 7 ]. National data from 2018 show that only 65% of adolescents and 21.5% of women aged 18–26 had completed the recommended vaccine series [ 8 , 9 ]. Women not previously vaccinated but beyond the (previous) age limit of 26 years are now eligible for HPV vaccination. Despite the plethora of literature explicating factors associated with HPV vaccine uptake in general [ 10 , 11 , 12 , 13 ], there is limited research examining predictors among women ages 27–45 years, which may inform the SCDM process.

Our study was guided by tenets of the Theory of Reasoned Action, which postulates that behavioral intention is the strongest predictor of future behavior, barring environmental constraints. Intention, in turn, is shaped by attitudes, beliefs, subjective norms, perceived behavioral control, and environmental factors [ 14 ]. In this study, we examined attitudes and beliefs about vaccines (e.g., safety, efficacy), as well as the perceived risk of HPV infection and cervical cancer. For social influences, we examined perceptions of social pressure to be vaccinated, including the extent to which significant others (e.g., spouse, friends) support vaccination, and characteristics of the patient/provider relationship (e.g., trust, comfort). We assessed self-efficacy about requesting information or vaccination from one’s provider. We also evaluated environmental barriers, including vaccine cost and prior negative experiences with the healthcare system.

The objectives of this study were to answer three research questions (RQs): (1) What is the prevalence of HPV vaccination among a diverse sample of mid-adult women aged 27–45 years? (2) What are the characteristics of those who have or have not previously been vaccinated? and (3) What factors are associated with the intention to obtain the HPV vaccine among those who have never been vaccinated? Findings will guide healthcare provider vaccine communication strategies and efforts to promote SCDM about HPV vaccination among adult women.

Materials and methods

Participants.

We conducted an online survey of adult women between April 13, 2020, and June 8, 2020. Participants were drawn from the Qualtrics XM Panel, a database of potential online survey participants maintained by Qualtrics, XM and all respondents have already agreed to be contacted for research purposes. Criteria for inclusion were persons assigned female at birth, aged 27 to 45 years, resident of the U.S., and ability to read and understand English. Given documented differences in HPV vaccination across racial/ethnic groups [ 15 ], we oversampled women of minoritized racial/ethnic groups to produce a sample that was 25% Black, 25% Asian, and 25% Hispanic. A further sampling quota was set to recruit a sample that included 25% of respondents who identified as a sexual minority (e.g., bisexual, lesbian, queer, other). Study consent procedures were conducted electronically before the start of the survey (by clicking on a box indicating consent), participation was voluntary, and the standard Qualtrics XM remuneration ($6) was provided. This study was administered online and approved by Tufts University Institutional Review Board.

We utilized a number of existing measures on the survey (see supplementary file ). First, we assessed both prior receipt and future intentions to get the HPV vaccine, as well as key independent variables from our conceptual framework (i.e., attitudes/beliefs, social influences, self-efficacy, and barriers), as described below. All participants responded to questions related to demographics, vaccination status, and attitudes/beliefs toward HPV vaccination. Only those who reported never having had the HPV vaccine were asked about their future intentions to get vaccinated, and questions were asked to assess social influences, self-efficacy, and barriers toward future HPV vaccination.

Receipt of and intention to vaccinate . Using items from the Behavioral Risk Factor Surveillance System [ 16 ], we asked participants if they had ever received the HPV vaccine (yes, no or unsure). Those who had not been vaccinated or were unsure were asked, “How likely are you to get the HPV vaccine?” with responses on a 4-point Likert scale (“very likely” to “very unlikely”).

Attitudes and beliefs . To assess attitudes and beliefs about vaccines, we asked: [ 1 ] “Do you think vaccines are well tested before being made available to the public?” (yes, no, don’t know) [ 2 ], “In your opinion, how safe is the HPV vaccine?” (4-point Likert: “very safe” to “not at all safe”/ “don’t know” with higher scores indicating greater perceived safety) [ 3 ], “In your opinion, how effective is the HPV vaccine?” (4-point Likert, “very effective” to “not at all effective”/ “don’t know,” with higher scores indicating greater perceived effectiveness), and [ 4 ] “If you were making a decision about getting the HPV vaccine, how much would potential side effects influence your decision?” (4-point Likert, “a great deal” to “not at all,” with higher scores indicating greater concern about side effects). To assess perceived susceptibility to cervical cancer and HPV infection, we asked [ 1 ] “Compared to the average person your age, would you say you are” (“more likely to get cervical cancer,” “as likely to get cervical cancer,” “less likely to get cervical cancer”); and [ 2 ] “How likely are you to get HPV?” (4-point Likert, “very likely” to “very unlikely”/ “unsure”).

Social influences. To assess social factors that influence decision-making about getting the HPV vaccine, we asked, “How much would each of the following factors influence your decision?” Response options included: whether you have a spouse or long-term monogamous partner; how other people close to you might think about your decision; comfort and/or trust with [my] health care provider; and comfort and trust in seeking health care (4-point Likert, “a great deal” to “not at all” for each).

Self-efficacy. We assessed comfort with engaging in SCDM with health care providers by asking two items: [ 1 ] “How comfortable would you be asking your health care provider to give your information regarding the HPV vaccine?” and [ 2 ] “How comfortable would you be asking your health care provider to give you the HPV vaccine?” (4-point Likert, “very comfortable” to “very uncomfortable”/ “unsure/don’t know”).

Barriers. We assessed the extent to which cost and prior negative experiences with the healthcare system impacted vaccine decisions. Specifically, we asked: “If you were making a decision about getting the HPV vaccine, how much would each of the following factors influence your decision?” The factors listed were cost, insurance coverage, and previous negative health care experiences with response options on a 4-point Likert scale (“a great deal” to “not at all”).

Demographic Characteristics. Demographic characteristics were assessed using standard items from the Behavioral Risk Factors Surveillance Survey [ 16 ] and included: race/ethnicity [non-Hispanic (NH) White, NH Black, NH Asian, Hispanic and multi-racial]; age (27–29, 30–39, 40–49); income (<$34,000, $35–74,000, >$75,000, not sure); education (high school or less, college or some college, graduate degree); employment (employed, unemployed); and insurance status (public, private, none). We also assessed prior history of cervical cancer screening [ 1 ] “Have you ever had an abnormal Pap test?; [ 2 ] Have you ever had a positive HPV test?”; and 3) Have you ever been told by a healthcare provider that you had cervical cancer?” (“yes”, “no”, don’t know”).

Our analytic goals were to describe the prevalence of HPV vaccination among mid-adult women (RQ #1), identify factors associated with vaccination status (RQ #2), and examine factors associated with the intention to be vaccinated for HPV among those who had never been vaccinated (RQ #3). Descriptive statistics were tabulated for the total sample, previously vaccinated individuals (≥ 1 dose), and unvaccinated individuals (RQ #1). For RQ #2, we examined factors associated with already having received ≥ 1 dose of the HPV vaccine versus not having received any doses. For RQ #3, we focused only on those who had not received any doses of the HPV vaccine. For this analysis, we examined factors associated with falling into two categories: (1) those who report being very likely or likely to get the HPV vaccine and (2) those who report being very unlikely or unlikely to get the vaccine.

The data analysis was completed using SPSS Statistics Version 26 (IBM Corp., Armonk, NY). For RQs #2 and #3, Chi-squared tests were used to assess bivariate associations. For both RQ #2 and RQ #3, univariable logistic regression models were first run with each of the covariates. Then, stepwise selection was used in the multiple logistic regression analyses (slentry = 0.20 and slstay = 0.10); all covariates with association of p  < 0.10 were included, and p   ≤  0.05 was considered statistically significant in the final models. For the multivariable analyses, models were run to assess (RQ #2) factors associated with vaccination status and (RQ #3) factors related to intention to be vaccinated for HPV among those who had never been vaccinated. For these models, those who identified as NH Asian and multi-racial were combined due to the small sample sizes.

Sample characteristics, HPV vaccination prevalence (RQ#1), and factors associations with HPV vaccination (RQ#2)

A total of 324 women completed the survey. The majority were between the ages of 30 and 39 years (51.2%), identified as heterosexual (73.8%), had some college or a college degree (61.1%), and had health insurance (33.3% public, 51.5% private). Approximately half of the sample was married (46.6%). Due to the use of quota sampling, race/ethnicity was distributed relatively evenly (NH White 25.6; NH Black 23.58%; NH Asian and another race 27.2%, and 23.8% Hispanic). Only 31.1% ( n  = 101) of the sample reported that they had one or more doses of the HPV vaccine, and 68.9% ( n  = 223) reported not being vaccinated or being unsure about vaccination status. See Table  1 .

In the bivariate analyses, age ( p  < 0.001), health insurance status ( p  = 0.047), report of ever having had an HPV test ( p  < 0.01), and having been given a diagnosis of cervical cancer ( p  < 0.01) were associated with having had at least one dose of the HPV vaccine. Attitudes and beliefs that were significantly associated with vaccination status included perceived safety of the HPV vaccine ( p  < 0.001), perceived effectiveness of the HPV vaccine ( p  < 0.001), and perceived likelihood of HPV infection ( p  = 0.068) (Table  1 ).

In the multivariable analysis, those aged 30 years or older had lower odds of receiving the HPV vaccine compared to those aged 27–29 years (AOR = 0.50; 95% CI = 0.26–0.96). Women who expressed stronger belief in vaccine effectiveness had higher odds of being vaccinated than those who reported that they did not view the vaccine as effective or did not know about effectiveness (AOR = 2.75; 95% CI = 1.33–5.71) (Table  2 ).

RQ #3: Factors associated with the intention to obtain the HPV vaccine among those who had never been vaccinated or were unsure

Of the 223 participants who reported not being vaccinated, 6 did not complete the remainder of the survey items, so the final sample size for RQ #3 and RQ #4 was n  = 217. In bivariate analyses, women who intended to be vaccinated were those who reported having had an abnormal Pap test ( p  < 0.001) or positive HPV test ( p  < 0.05), stronger beliefs that vaccines are well tested ( p  < 0.001), believed that the HPV vaccine was safe ( p  < 0.001) and effective ( p  < 0.001), and perceived themselves to be more likely to get an HPV infection ( p  < 0.05). Furthermore, social influences [i.e., other people’s opinions ( p  = 0.08) and health care provider recommendation ( p  < 0.05)] a self-efficacy [i.e., comfort asking a health care provider for information about HPV vaccine ( p  < 0.01) and HPV vaccination ( p  < 0.001)], were more likely to report the intention to get vaccinated. In contrast, barriers [i.e., reporting that previous negative healthcare experiences would influence vaccine decision-making ( p  = 0.06)] were associated with lower future vaccination intentions (Table  3 ).

In the multivariable analysis, four factors were significantly associated with the intention to obtain an HPV vaccine. Compared with those who did not intend to be vaccinated, those reporting a belief that vaccines are well tested (AOR = 2.28; 95% CI = 1.12–4.63), that they were likely to get an HPV infection (AOR = 2.66; 95%CI = 1.16–6.05), and that they were comfortable asking a health care provider for the HPV vaccine (AOR = 4.53; 95%CI = 1.59–12.88) had greater odds of intending to be vaccinated. In contrast, those reporting that previous negative healthcare experiences would influence their HPV vaccination decision had lower odds of intending to be vaccinated (AOR = 0.40; 95% CI = 0.20–0.80) (Table  4 ).

The expansion of eligibility for the HPV vaccine to persons aged 27–45 years provides new opportunities to prevent HPV-related cancers, precancers, and genital warts. However, we found that less than a third of the women in this sample had received one or more doses of the HPV vaccine. Of those who were unvaccinated or unsure about their vaccination history, more than half reported that they were very likely or likely to accept HPV vaccination in the future.

Only a few national studies of mid-adult women (27–45 years) have been conducted since the change in ACIP guidelines [ 17 , 18 ], though several other studies have looked at both women and men [ 19 , 20 ]. Our finding that approximately half of those previously unvaccinated were willing to get the vaccine is similar to findings from other national surveys conducted since that time, which ranged from 33% among sexual minority women [ 21 ] and 43–54% among broader samples of women [ 13 , 19 ]. One study found that about 52% of individuals (both women and men) were willing to ask their providers for HPV vaccine information [ 13 ]. Studies have also found that perceived vaccine effectiveness, perceived safety [ 19 ], perceived vulnerability [ 19 ], and perceived likelihood of benefitting from the vaccine [ 22 ] were associated with willingness/intent to get the HPV vaccine in this age group. Our study provides new information about the relationship between prior negative healthcare experiences and HPV vaccination. This is notable since those who had negative experiences were 60% less likely to report they would be willing to be vaccinated.

Findings should be viewed in light of study limitations. First, this was a convenience sample from a Qualtrics™ panel, so the findings may not be generalizable to other populations. However, recent research has found that while participants recruited from online panels are not necessarily representative of the U.S. population, they are equivalently representative as traditional recruitment approaches [ 23 ]. Regardless, we recognize that those willing to complete research studies may be more likely to be receptive to health interventions than the general public. Additionally, we did not assess HPV vaccine intentions over a specific time frame, as is often done in “stages of change” models. Like most other studies in this field, vaccination status was assessed through self-report, which, while generally accurate among adults, is less accurate than status confirmed via medical records or vaccine registries [ 24 ]. We also acknowledge that some of the confidence intervals in our findings were wide. Therefore, findings should be interpreted with caution, as estimates may be unstable. Nevertheless, study strengths include the timeliness of findings vis-a-vis expansion of HPV vaccine eligibility, and the ability to compare across different racial/ethnic groups for whom there has been inadequate representation in prior research.

Implications for practice

Since SCDM, rather than routine HPV vaccination, is recommended for women in this age group, those not intending to be vaccinated may require no intervention so long as they are fully informed about the potential benefits of vaccination and their individual risk for infection and cervical cancer. However, prior studies indicate that most women do not know that there is now expanded vaccine eligibility [ 20 ]. Further, many women, especially those with lower levels of education and who are racially/ethnically minoritized, are not aware that HPV causes cervical cancer [ 25 ]. Although we did not assess knowledge of risk factors in this study, our finding that two-thirds of women were willing to be vaccinated and that being comfortable asking one’s healthcare provider for the vaccine suggests that efforts to build awareness and provide skills about engaging in SCDM with one’s provider may hold promise. These efforts will also likely require additional information about the rigor of HPV vaccine testing to promote confidence among some women. Targeted efforts may be needed to engage women who had prior negative experiences in the healthcare system, as they were 60% less likely to report that they would be vaccinated in the future. Existing evidence points to the role of medical mistrust in vaccine hesitancy in general [ 26 ], including HPV vaccination [ 27 ]. Building trust in the healthcare system will likely necessitate multilevel interventions, not only directed at individuals who have mistrust, but also to enhance trust with providers [ 28 , 29 ], as well as the trustworthiness of healthcare systems. Comprehensive efforts should also include provider-directed interventions, as the ACIP guidelines do not provide specific information about which patients may most benefit from vaccination. This is especially important since provider recommendation has been identified as the most influential factor in vaccine acceptance [ 30 ] and continues to be for this age group ( 21 ). Yet, in a recent study of primary care physicians, only 42% had recommended HPV vaccination to adults aged 27–45 years, and 57% were unsure about what to discuss during SCDM conversations [ 31 ].

The expanded eligibility of HPV vaccination for individuals aged 27–45 years has the potential to reduce cervical and other HPV-related cancers, as well as genital warts [ 32 ]. However, since a recommendation for SCDM for this age group differs from the routine HPV vaccination recommended for younger age groups, greater efforts to ensure awareness of expanded eligibility and potential benefits may be needed among patients and providers through a mutual discussion about vaccination. Our results suggest that many unvaccinated mid-adult women may be interested in receiving the HPV vaccine, and an even more significant number may be interested once efforts are made to increase their understanding of the safety, efficacy, and testing of the vaccine, as well as expanded eligibility.

Data availability

The data that support the findings of this study are available from the corresponding author, but restrictions apply to the availability of these data. The data are, however, available from the authors upon reasonable request.

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Acknowledgements

We wish to thank the study participants who shared their time and perspectives.

This work was supported by the Tufts University Office of the Vice Provost for Research (PI Allen). The funding agency had no role in the study.

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All study protocols and procedures were approved by the Institutional Review Board at Tufts University (protocol number: 00001954). All study activities were carried out in accordance with the relevant guidelines and regulations of the Declaration of Helsinki. Informed consent was obtained from all participants.

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JDA, RR, KI, NA have no competing interests. Outside of the current work, Gregory Zimet has received consulting fees from Merck for work on HPV vaccination and has served on external advisory committees for Moderna (COVID-19 vaccination) and Pfizer (meningococcal vaccination), and through Indiana University, has also received investigator-initiated grant funding from Merck related to HPV vaccination. Dr. Fontenot has also received investigator-initiated grant funding from Merck regarding adolescent vaccination. Drs. Fontenot and Zimet confirm that their funding source(s) have had no involvement in the conduct of this work. No other authors have conflicts of interest to report, nor competing financial interests.

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Allen, J.D., Abuelezam, N.N., Rose, R. et al. HPV vaccine behaviors and intentions among a diverse sample of women aged 27-45 years: implications for shared clinical decision-making. BMC Public Health 24 , 2154 (2024). https://doi.org/10.1186/s12889-024-18740-2

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DOI : https://doi.org/10.1186/s12889-024-18740-2

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