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Research Recommendations – Examples and Writing Guide

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Research Recommendations

Definition:

Research recommendations refer to suggestions or advice given to someone who is looking to conduct research on a specific topic or area. These recommendations may include suggestions for research methods, data collection techniques, sources of information, and other factors that can help to ensure that the research is conducted in a rigorous and effective manner. Research recommendations may be provided by experts in the field, such as professors, researchers, or consultants, and are intended to help guide the researcher towards the most appropriate and effective approach to their research project.

Parts of Research Recommendations

Research recommendations can vary depending on the specific project or area of research, but typically they will include some or all of the following parts:

• Research question or objective : This is the overarching goal or purpose of the research project.
• Research methods : This includes the specific techniques and strategies that will be used to collect and analyze data. The methods will depend on the research question and the type of data being collected.
• Data collection: This refers to the process of gathering information or data that will be used to answer the research question. This can involve a range of different methods, including surveys, interviews, observations, or experiments.
• Data analysis : This involves the process of examining and interpreting the data that has been collected. This can involve statistical analysis, qualitative analysis, or a combination of both.
• Results and conclusions: This section summarizes the findings of the research and presents any conclusions or recommendations based on those findings.
• Limitations and future research: This section discusses any limitations of the study and suggests areas for future research that could build on the findings of the current project.

How to Write Research Recommendations

Writing research recommendations involves providing specific suggestions or advice to a researcher on how to conduct their study. Here are some steps to consider when writing research recommendations:

• Understand the research question: Before writing research recommendations, it is important to have a clear understanding of the research question and the objectives of the study. This will help to ensure that the recommendations are relevant and appropriate.
• Consider the research methods: Consider the most appropriate research methods that could be used to collect and analyze data that will address the research question. Identify the strengths and weaknesses of the different methods and how they might apply to the specific research question.
• Provide specific recommendations: Provide specific and actionable recommendations that the researcher can implement in their study. This can include recommendations related to sample size, data collection techniques, research instruments, data analysis methods, or other relevant factors.
• Justify recommendations : Justify why each recommendation is being made and how it will help to address the research question or objective. It is important to provide a clear rationale for each recommendation to help the researcher understand why it is important.
• Consider limitations and ethical considerations : Consider any limitations or potential ethical considerations that may arise in conducting the research. Provide recommendations for addressing these issues or mitigating their impact.
• Summarize recommendations: Provide a summary of the recommendations at the end of the report or document, highlighting the most important points and emphasizing how the recommendations will contribute to the overall success of the research project.

Example of Research Recommendations

Example of Research Recommendations sample for students:

• Further investigate the effects of X on Y by conducting a larger-scale randomized controlled trial with a diverse population.
• Explore the relationship between A and B by conducting qualitative interviews with individuals who have experience with both.
• Investigate the long-term effects of intervention C by conducting a follow-up study with participants one year after completion.
• Examine the effectiveness of intervention D in a real-world setting by conducting a field study in a naturalistic environment.
• Compare and contrast the results of this study with those of previous research on the same topic to identify any discrepancies or inconsistencies in the findings.
• Expand upon the limitations of this study by addressing potential confounding variables and conducting further analyses to control for them.
• Investigate the relationship between E and F by conducting a meta-analysis of existing literature on the topic.
• Explore the potential moderating effects of variable G on the relationship between H and I by conducting subgroup analyses.
• Identify potential areas for future research based on the gaps in current literature and the findings of this study.
• Conduct a replication study to validate the results of this study and further establish the generalizability of the findings.

Applications of Research Recommendations

Research recommendations are important as they provide guidance on how to improve or solve a problem. The applications of research recommendations are numerous and can be used in various fields. Some of the applications of research recommendations include:

• Policy-making: Research recommendations can be used to develop policies that address specific issues. For example, recommendations from research on climate change can be used to develop policies that reduce carbon emissions and promote sustainability.
• Program development: Research recommendations can guide the development of programs that address specific issues. For example, recommendations from research on education can be used to develop programs that improve student achievement.
• Product development : Research recommendations can guide the development of products that meet specific needs. For example, recommendations from research on consumer behavior can be used to develop products that appeal to consumers.
• Marketing strategies: Research recommendations can be used to develop effective marketing strategies. For example, recommendations from research on target audiences can be used to develop marketing strategies that effectively reach specific demographic groups.
• Medical practice : Research recommendations can guide medical practitioners in providing the best possible care to patients. For example, recommendations from research on treatments for specific conditions can be used to improve patient outcomes.
• Scientific research: Research recommendations can guide future research in a specific field. For example, recommendations from research on a specific disease can be used to guide future research on treatments and cures for that disease.

Purpose of Research Recommendations

The purpose of research recommendations is to provide guidance on how to improve or solve a problem based on the findings of research. Research recommendations are typically made at the end of a research study and are based on the conclusions drawn from the research data. The purpose of research recommendations is to provide actionable advice to individuals or organizations that can help them make informed decisions, develop effective strategies, or implement changes that address the issues identified in the research.

The main purpose of research recommendations is to facilitate the transfer of knowledge from researchers to practitioners, policymakers, or other stakeholders who can benefit from the research findings. Recommendations can help bridge the gap between research and practice by providing specific actions that can be taken based on the research results. By providing clear and actionable recommendations, researchers can help ensure that their findings are put into practice, leading to improvements in various fields, such as healthcare, education, business, and public policy.

Characteristics of Research Recommendations

Research recommendations are a key component of research studies and are intended to provide practical guidance on how to apply research findings to real-world problems. The following are some of the key characteristics of research recommendations:

• Actionable : Research recommendations should be specific and actionable, providing clear guidance on what actions should be taken to address the problem identified in the research.
• Evidence-based: Research recommendations should be based on the findings of the research study, supported by the data collected and analyzed.
• Contextual: Research recommendations should be tailored to the specific context in which they will be implemented, taking into account the unique circumstances and constraints of the situation.
• Feasible : Research recommendations should be realistic and feasible, taking into account the available resources, time constraints, and other factors that may impact their implementation.
• Prioritized: Research recommendations should be prioritized based on their potential impact and feasibility, with the most important recommendations given the highest priority.
• Communicated effectively: Research recommendations should be communicated clearly and effectively, using language that is understandable to the target audience.
• Evaluated : Research recommendations should be evaluated to determine their effectiveness in addressing the problem identified in the research, and to identify opportunities for improvement.

Advantages of Research Recommendations

Research recommendations have several advantages, including:

• Providing practical guidance: Research recommendations provide practical guidance on how to apply research findings to real-world problems, helping to bridge the gap between research and practice.
• Improving decision-making: Research recommendations help decision-makers make informed decisions based on the findings of research, leading to better outcomes and improved performance.
• Enhancing accountability : Research recommendations can help enhance accountability by providing clear guidance on what actions should be taken, and by providing a basis for evaluating progress and outcomes.
• Informing policy development : Research recommendations can inform the development of policies that are evidence-based and tailored to the specific needs of a given situation.
• Enhancing knowledge transfer: Research recommendations help facilitate the transfer of knowledge from researchers to practitioners, policymakers, or other stakeholders who can benefit from the research findings.
• Encouraging further research : Research recommendations can help identify gaps in knowledge and areas for further research, encouraging continued exploration and discovery.
• Promoting innovation: Research recommendations can help identify innovative solutions to complex problems, leading to new ideas and approaches.

Limitations of Research Recommendations

While research recommendations have several advantages, there are also some limitations to consider. These limitations include:

• Context-specific: Research recommendations may be context-specific and may not be applicable in all situations. Recommendations developed in one context may not be suitable for another context, requiring adaptation or modification.
• I mplementation challenges: Implementation of research recommendations may face challenges, such as lack of resources, resistance to change, or lack of buy-in from stakeholders.
• Limited scope: Research recommendations may be limited in scope, focusing only on a specific issue or aspect of a problem, while other important factors may be overlooked.
• Uncertainty : Research recommendations may be uncertain, particularly when the research findings are inconclusive or when the recommendations are based on limited data.
• Bias : Research recommendations may be influenced by researcher bias or conflicts of interest, leading to recommendations that are not in the best interests of stakeholders.
• Timing : Research recommendations may be time-sensitive, requiring timely action to be effective. Delayed action may result in missed opportunities or reduced effectiveness.
• Lack of evaluation: Research recommendations may not be evaluated to determine their effectiveness or impact, making it difficult to assess whether they are successful or not.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Research Recommendations – Guiding policy-makers for evidence-based decision making

Research recommendations play a crucial role in guiding scholars and researchers toward fruitful avenues of exploration. In an era marked by rapid technological advancements and an ever-expanding knowledge base, refining the process of generating research recommendations becomes imperative.

But, what is a research recommendation?

Research recommendations are suggestions or advice provided to researchers to guide their study on a specific topic . They are typically given by experts in the field. Research recommendations are more action-oriented and provide specific guidance for decision-makers, unlike implications that are broader and focus on the broader significance and consequences of the research findings. However, both are crucial components of a research study.

Difference Between Research Recommendations and Implication

Although research recommendations and implications are distinct components of a research study, they are closely related. The differences between them are as follows:

Types of Research Recommendations

Recommendations in research can take various forms, which are as follows:

These recommendations aim to assist researchers in navigating the vast landscape of academic knowledge.

Let us dive deeper to know about its key components and the steps to write an impactful research recommendation.

Key Components of Research Recommendations

The key components of research recommendations include defining the research question or objective, specifying research methods, outlining data collection and analysis processes, presenting results and conclusions, addressing limitations, and suggesting areas for future research. Here are some characteristics of research recommendations:

Research recommendations offer various advantages and play a crucial role in ensuring that research findings contribute to positive outcomes in various fields. However, they also have few limitations which highlights the significance of a well-crafted research recommendation in offering the promised advantages.

The importance of research recommendations ranges in various fields, influencing policy-making, program development, product development, marketing strategies, medical practice, and scientific research. Their purpose is to transfer knowledge from researchers to practitioners, policymakers, or stakeholders, facilitating informed decision-making and improving outcomes in different domains.

How to Write Research Recommendations?

Research recommendations can be generated through various means, including algorithmic approaches, expert opinions, or collaborative filtering techniques. Here is a step-wise guide to build your understanding on the development of research recommendations.

1. Understand the Research Question:

Understand the research question and objectives before writing recommendations. Also, ensure that your recommendations are relevant and directly address the goals of the study.

2. Review Existing Literature:

Familiarize yourself with relevant existing literature to help you identify gaps , and offer informed recommendations that contribute to the existing body of research.

3. Consider Research Methods:

Evaluate the appropriateness of different research methods in addressing the research question. Also, consider the nature of the data, the study design, and the specific objectives.

4. Identify Data Collection Techniques:

Gather dataset from diverse authentic sources. Include information such as keywords, abstracts, authors, publication dates, and citation metrics to provide a rich foundation for analysis.

5. Propose Data Analysis Methods:

Suggest appropriate data analysis methods based on the type of data collected. Consider whether statistical analysis, qualitative analysis, or a mixed-methods approach is most suitable.

6. Consider Limitations and Ethical Considerations:

Acknowledge any limitations and potential ethical considerations of the study. Furthermore, address these limitations or mitigate ethical concerns to ensure responsible research.

7. Justify Recommendations:

Explain how your recommendation contributes to addressing the research question or objective. Provide a strong rationale to help researchers understand the importance of following your suggestions.

8. Summarize Recommendations:

Provide a concise summary at the end of the report to emphasize how following these recommendations will contribute to the overall success of the research project.

By following these steps, you can create research recommendations that are actionable and contribute meaningfully to the success of the research project.

Download now to unlock some tips to improve your journey of writing research recommendations.

Example of a Research Recommendation

Here is an example of a research recommendation based on a hypothetical research to improve your understanding.

Research Recommendation: Enhancing Student Learning through Integrated Learning Platforms

Background:

The research study investigated the impact of an integrated learning platform on student learning outcomes in high school mathematics classes. The findings revealed a statistically significant improvement in student performance and engagement when compared to traditional teaching methods.

Recommendation:

In light of the research findings, it is recommended that educational institutions consider adopting and integrating the identified learning platform into their mathematics curriculum. The following specific recommendations are provided:

• Implementation of the Integrated Learning Platform:

Schools are encouraged to adopt the integrated learning platform in mathematics classrooms, ensuring proper training for teachers on its effective utilization.

• Professional Development for Educators:

Develop and implement professional programs to train educators in the effective use of the integrated learning platform to address any challenges teachers may face during the transition.

• Monitoring and Evaluation:

Establish a monitoring and evaluation system to track the impact of the integrated learning platform on student performance over time.

• Resource Allocation:

Allocate sufficient resources, both financial and technical, to support the widespread implementation of the integrated learning platform.

By implementing these recommendations, educational institutions can harness the potential of the integrated learning platform and enhance student learning experiences and academic achievements in mathematics.

This example covers the components of a research recommendation, providing specific actions based on the research findings, identifying the target audience, and outlining practical steps for implementation.

Using AI in Research Recommendation Writing

Enhancing research recommendations is an ongoing endeavor that requires the integration of cutting-edge technologies, collaborative efforts, and ethical considerations. By embracing data-driven approaches and leveraging advanced technologies, the research community can create more effective and personalized recommendation systems. However, it is accompanied by several limitations. Therefore, it is essential to approach the use of AI in research with a critical mindset, and complement its capabilities with human expertise and judgment.

Here are some limitations of integrating AI in writing research recommendation and some ways on how to counter them.

1. Data Bias

AI systems rely heavily on data for training. If the training data is biased or incomplete, the AI model may produce biased results or recommendations.

How to tackle: Audit regularly the model’s performance to identify any discrepancies and adjust the training data and algorithms accordingly.

2. Lack of Understanding of Context:

AI models may struggle to understand the nuanced context of a particular research problem. They may misinterpret information, leading to inaccurate recommendations.

How to tackle: Use AI to characterize research articles and topics. Employ them to extract features like keywords, authorship patterns and content-based details.

3. Ethical Considerations:

AI models might stereotype certain concepts or generate recommendations that could have negative consequences for certain individuals or groups.

How to tackle: Incorporate user feedback mechanisms to reduce redundancies. Establish an ethics review process for AI models in research recommendation writing.

4. Lack of Creativity and Intuition:

AI may struggle with tasks that require a deep understanding of the underlying principles or the ability to think outside the box.

How to tackle: Hybrid approaches can be employed by integrating AI in data analysis and identifying patterns for accelerating the data interpretation process.

5. Interpretability:

Many AI models, especially complex deep learning models, lack transparency on how the model arrived at a particular recommendation.

How to tackle: Implement models like decision trees or linear models. Provide clear explanation of the model architecture, training process, and decision-making criteria.

6. Dynamic Nature of Research:

Research fields are dynamic, and new information is constantly emerging. AI models may struggle to keep up with the rapidly changing landscape and may not be able to adapt to new developments.

How to tackle: Establish a feedback loop for continuous improvement. Regularly update the recommendation system based on user feedback and emerging research trends.

The integration of AI in research recommendation writing holds great promise for advancing knowledge and streamlining the research process. However, navigating these concerns is pivotal in ensuring the responsible deployment of these technologies. Researchers need to understand the use of responsible use of AI in research and must be aware of the ethical considerations.

Exploring research recommendations plays a critical role in shaping the trajectory of scientific inquiry. It serves as a compass, guiding researchers toward more robust methodologies, collaborative endeavors, and innovative approaches. Embracing these suggestions not only enhances the quality of individual studies but also contributes to the collective advancement of human understanding.

Frequently Asked Questions

The purpose of recommendations in research is to provide practical and actionable suggestions based on the study's findings, guiding future actions, policies, or interventions in a specific field or context. Recommendations bridges the gap between research outcomes and their real-world application.

To make a research recommendation, analyze your findings, identify key insights, and propose specific, evidence-based actions. Include the relevance of the recommendations to the study's objectives and provide practical steps for implementation.

Begin a recommendation by succinctly summarizing the key findings of the research. Clearly state the purpose of the recommendation and its intended impact. Use a direct and actionable language to convey the suggested course of action.

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How to formulate research recommendations

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• Peer review
• Polly Brown ( pbrown{at}bmjgroup.com ) , publishing manager 1 ,
• Klara Brunnhuber , clinical editor 1 ,
• Kalipso Chalkidou , associate director, research and development 2 ,
• Iain Chalmers , director 3 ,
• Mike Clarke , director 4 ,
• Mark Fenton , editor 3 ,
• Carol Forbes , reviews manager 5 ,
• Julie Glanville , associate director/information service manager 5 ,
• Nicholas J Hicks , consultant in public health medicine 6 ,
• Janet Moody , identification and prioritisation manager 6 ,
• Sara Twaddle , director 7 ,
• Hazim Timimi , systems developer 8 ,
• Pamela Young , senior programme manager 6
• 1 BMJ Publishing Group, London WC1H 9JR,
• 2 National Institute for Health and Clinical Excellence, London WC1V 6NA,
• 3 Database of Uncertainties about the Effects of Treatments, James Lind Alliance Secretariat, James Lind Initiative, Oxford OX2 7LG,
• 4 UK Cochrane Centre, Oxford OX2 7LG,
• 5 Centre for Reviews and Dissemination, University of York, York YO10 5DD,
• 6 National Coordinating Centre for Health Technology Assessment, University of Southampton, Southampton SO16 7PX,
• 7 Scottish Intercollegiate Guidelines Network, Edinburgh EH2 1EN,
• 8 Update Software, Oxford OX2 7LG
• Correspondence to: PBrown
• Accepted 22 September 2006

“More research is needed” is a conclusion that fits most systematic reviews. But authors need to be more specific about what exactly is required

Long awaited reports of new research, systematic reviews, and clinical guidelines are too often a disappointing anticlimax for those wishing to use them to direct future research. After many months or years of effort and intellectual energy put into these projects, authors miss the opportunity to identify unanswered questions and outstanding gaps in the evidence. Most reports contain only a less than helpful, general research recommendation. This means that the potential value of these recommendations is lost.

Current recommendations

In 2005, representatives of organisations commissioning and summarising research, including the BMJ Publishing Group, the Centre for Reviews and Dissemination, the National Coordinating Centre for Health Technology Assessment, the National Institute for Health and Clinical Excellence, the Scottish Intercollegiate Guidelines Network, and the UK Cochrane Centre, met as members of the development group for the Database of Uncertainties about the Effects of Treatments (see bmj.com for details on all participating organisations). Our aim was to discuss the state of research recommendations within our organisations and to develop guidelines for improving the presentation of proposals for further research. All organisations had found weaknesses in the way researchers and authors of systematic reviews and clinical guidelines stated the need for further research. As part of the project, a member of the Centre for Reviews and Dissemination under-took a rapid literature search to identify information on research recommendation models, which found some individual methods but no group initiatives to attempt to standardise recommendations.

Suggested format for research recommendations on the effects of treatments

Core elements.

E Evidence (What is the current state of the evidence?)

P Population (What is the population of interest?)

I Intervention (What are the interventions of interest?)

C Comparison (What are the comparisons of interest?)

O Outcome (What are the outcomes of interest?)

T Time stamp (Date of recommendation)

Optional elements

d Disease burden or relevance

t Time aspect of core elements of EPICOT

s Appropriate study type according to local need

In January 2006, the National Coordinating Centre for Health Technology Assessment presented the findings of an initial comparative analysis of how different organisations currently structure their research recommendations. The National Institute for Health and Clinical Excellence and the National Coordinating Centre for Health Technology Assessment request authors to present recommendations in a four component format for formulating well built clinical questions around treatments: population, intervention, comparison, and outcomes (PICO). 1 In addition, the research recommendation is dated and authors are asked to provide the current state of the evidence to support the proposal.

Clinical Evidence , although not directly standardising its sections for research recommendations, presents gaps in the evidence using a slightly extended version of the PICO format: evidence, population, intervention, comparison, outcomes, and time (EPICOT). Clinical Evidence has used this inherent structure to feed research recommendations on interventions categorised as “unknown effectiveness” back to the National Coordinating Centre for Health Technology Assessment and for inclusion in the Database of Uncertainties about the Effects of Treatments ( http://www.duets.nhs.uk/ ).

We decided to propose the EPICOT format as the basis for its statement on formulating research recommendations and tested this proposal through discussion and example. We agreed that this set of components provided enough context for formulating research recommendations without limiting researchers. In order for the proposed framework to be flexible and more widely applicable, the group discussed using several optional components when they seemed relevant or were proposed by one or more of the group members. The final outcome of discussions resulted in the proposed EPICOT+ format (box).

A recent BMJ article highlighted how lack of research hinders the applicability of existing guidelines to patients in primary care who have had a stroke or transient ischaemic attack. 2 Most research in the area had been conducted in younger patients with a recent episode and in a hospital setting. The authors concluded that “further evidence should be collected on the efficacy and adverse effects of intensive blood pressure lowering in representative populations before we implement this guidance [from national and international guidelines] in primary care.” Table 1 outlines how their recommendations could be formulated using the EPICOT+ format. The decision on whether additional research is indeed clinically and ethically warranted will still lie with the organisation considering commissioning the research.

Research recommendation based on gap in the evidence identified by a cross sectional study of clinical guidelines for management of patients who have had a stroke

• View inline

Table 2 shows the use of EPICOT+ for an unanswered question on the effectiveness of compliance therapy in people with schizophrenia, identified by the Database of Uncertainties about the Effects of Treatments.

Research recommendation based on a gap in the evidence on treatment of schizophrenia identified by the Database of Uncertainties about the Effects of Treatments

Discussions around optional elements

Although the group agreed that the PICO elements should be core requirements for a research recommendation, intense discussion centred on the inclusion of factors defining a more detailed context, such as current state of evidence (E), appropriate study type (s), disease burden and relevance (d), and timeliness (t).

Initially, group members interpreted E differently. Some viewed it as the supporting evidence for a research recommendation and others as the suggested study type for a research recommendation. After discussion, we agreed that E should be used to refer to the amount and quality of research supporting the recommendation. However, the issue remained contentious as some of us thought that if a systematic review was available, its reference would sufficiently identify the strength of the existing evidence. Others thought that adding evidence to the set of core elements was important as it provided a summary of the supporting evidence, particularly as the recommendation was likely to be abstracted and used separately from the review or research that led to its formulation. In contrast, the suggested study type (s) was left as an optional element.

A research recommendation will rarely have an absolute value in itself. Its relative priority will be influenced by the burden of ill health (d), which is itself dependent on factors such as local prevalence, disease severity, relevant risk factors, and the priorities of the organisation considering commissioning the research.

Similarly, the issue of time (t) could be seen to be relevant to each of the core elements in varying ways—for example, duration of treatment, length of follow-up. The group therefore agreed that time had a subsidiary role within each core item; however, T as the date of the recommendation served to define its shelf life and therefore retained individual importance.

Applicability and usability

The proposed statement on research recommendations applies to uncertainties of the effects of any form of health intervention or treatment and is intended for research in humans rather than basic scientific research. Further investigation is required to assess the applicability of the format for questions around diagnosis, signs and symptoms, prognosis, investigations, and patient preference.

When the proposed format is applied to a specific research recommendation, the emphasis placed on the relevant part(s) of the EPICOT+ format may vary by author, audience, and intended purpose. For example, a recommendation for research into treatments for transient ischaemic attack may or may not define valid outcome measures to assess quality of life or gather data on adverse effects. Among many other factors, its implementation will also depend on the strength of current findings—that is, strong evidence may support a tightly focused recommendation whereas a lack of evidence would result in a more general recommendation.

The controversy within the group, especially around the optional components, reflects the different perspectives of the participating organisations—whether they were involved in commissioning, undertaking, or summarising research. Further issues will arise during the implementation of the proposed format, and we welcome feedback and discussion.

Summary points

No common guidelines exist for the formulation of recommendations for research on the effects of treatments

Major organisations involved in commissioning or summarising research compared their approaches and agreed on core questions

The essential items can be summarised as EPICOT+ (evidence, population, intervention, comparison, outcome, and time)

Further details, such as disease burden and appropriate study type, should be considered as required

We thank Patricia Atkinson and Jeremy Wyatt.

Contributors and sources All authors contributed to manuscript preparation and approved the final draft. NJH is the guarantor.

Competing interests None declared.

• Richardson WS ,
• Wilson MC ,
• Nishikawa J ,
• Hayward RSA
• McManus RJ ,
• Leonardi-Bee J ,
• PROGRESS Collaborative Group
• Warburton E
• Rothwell P ,
• McIntosh AM ,
• Lawrie SM ,
• Stanfield AC
• O'Donnell C ,
• Donohoe G ,
• Sharkey L ,
• Jablensky A ,
• Sartorius N ,
• Ernberg G ,

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• GETTING STARTED
• Introduction
• FUNDAMENTALS
• Acknowledgements
• Research questions & hypotheses
• Concepts, constructs & variables
• Research limitations
• Getting started
• Sampling Strategy
• Research Quality
• Research Ethics
• Data Analysis

FUTURE RESEARCH

Types of future research suggestion.

The Future Research section of your dissertation is often combined with the Research Limitations section of your final, Conclusions chapter. This is because your future research suggestions generally arise out of the research limitations you have identified in your own dissertation. In this article, we discuss six types of future research suggestion. These include: (1) building on a particular finding in your research; (2) addressing a flaw in your research; examining (or testing) a theory (framework or model) either (3) for the first time or (4) in a new context, location and/or culture; (5) re-evaluating and (6) expanding a theory (framework or model). The goal of the article is to help you think about the potential types of future research suggestion that you may want to include in your dissertation.

Before we discuss each of these types of future research suggestion, we should explain why we use the word examining and then put or testing in brackets. This is simply because the word examining may be considered more appropriate when students use a qualitative research design; whereas the word testing fits better with dissertations drawing on a quantitative research design. We also put the words framework or model in brackets after the word theory . We do this because a theory , framework and model are not the same things. In the sections that follow, we discuss six types of future research suggestion.

Addressing research limitations in your dissertation

Building on a particular finding or aspect of your research, examining a conceptual framework (or testing a theoretical model) for the first time, examining a conceptual framework (or testing a theoretical model) in a new context, location and/or culture.

• Expanding a conceptual framework (or testing a theoretical model)

Re-evaluating a conceptual framework (or theoretical model)

In the Research Limitations section of your Conclusions chapter, you will have inevitably detailed the potential flaws (i.e., research limitations) of your dissertation. These may include:

An inability to answer your research questions

Theoretical and conceptual problems

Limitations of your research strategy

Problems of research quality

Identifying what these research limitations were and proposing future research suggestions that address them is arguably the easiest and quickest ways to complete the Future Research section of your Conclusions chapter.

Often, the findings from your dissertation research will highlight a number of new avenues that could be explored in future studies. These can be grouped into two categories:

Your dissertation will inevitably lead to findings that you did not anticipate from the start. These are useful when making future research suggestions because they can lead to entirely new avenues to explore in future studies. If this was the case, it is worth (a) briefly describing what these unanticipated findings were and (b) suggesting a research strategy that could be used to explore such findings in future.

Sometimes, dissertations manage to address all aspects of the research questions that were set. However, this is seldom the case. Typically, there will be aspects of your research questions that could not be answered. This is not necessarily a flaw in your research strategy, but may simply reflect that fact that the findings did not provide all the answers you hoped for. If this was the case, it is worth (a) briefly describing what aspects of your research questions were not answered and (b) suggesting a research strategy that could be used to explore such aspects in future.

You may want to recommend that future research examines the conceptual framework (or tests the theoretical model) that you developed. This is based on the assumption that the primary goal of your dissertation was to set out a conceptual framework (or build a theoretical model). It is also based on the assumption that whilst such a conceptual framework (or theoretical model) was presented, your dissertation did not attempt to examine (or test) it in the field . The focus of your dissertations was most likely a review of the literature rather than something that involved you conducting primary research.

Whilst it is quite rare for dissertations at the undergraduate and master's level to be primarily theoretical in nature like this, it is not unknown. If this was the case, you should think about how the conceptual framework (or theoretical model) that you have presented could be best examined (or tested) in the field . In understanding the how , you should think about two factors in particular:

What is the context, location and/or culture that would best lend itself to my conceptual framework (or theoretical model) if it were to be examined (or tested) in the field?

What research strategy is most appropriate to examine my conceptual framework (or test my theoretical model)?

If the future research suggestion that you want to make is based on examining your conceptual framework (or testing your theoretical model) in the field , you need to suggest the best scenario for doing so.

More often than not, you will not only have set out a conceptual framework (or theoretical model), as described in the previous section, but you will also have examined (or tested) it in the field . When you do this, focus is typically placed on a specific context, location and/or culture.

If this is the case, the obvious future research suggestion that you could propose would be to examine your conceptual framework (or test the theoretical model) in a new context, location and/or culture. For example, perhaps you focused on consumers (rather than businesses), or Canada (rather than the United Kingdom), or a more individualistic culture like the United States (rather than a more collectivist culture like China).

When you propose a new context, location and/or culture as your future research suggestion, make sure you justify the choice that you make. For example, there may be little value in future studies looking at different cultures if culture is not an important component underlying your conceptual framework (or theoretical model). If you are not sure whether a new context, location or culture is more appropriate, or what new context, location or culture you should select, a review the literature will often help clarify where you focus should be.

Expanding a conceptual framework (or theoretical model)

Assuming that you have set out a conceptual framework (or theoretical model) and examined (or tested) it in the field , another series of future research suggestions comes out of expanding that conceptual framework (or theoretical model).

We talk about a series of future research suggestions because there are so many ways that you can expand on your conceptual framework (or theoretical model). For example, you can do this by:

Examining constructs (or variables) that were included in your conceptual framework (or theoretical model) but were not focused.

Looking at a particular relationship aspect of your conceptual framework (or theoretical model) further.

Adding new constructs (or variables) to the conceptual framework (or theoretical model) you set out (if justified by the literature).

It would be possible to include one or a number of these as future research suggestions. Again, make sure that any suggestions you make have are justified , either by your findings or the literature.

With the dissertation process at the undergraduate and master's level lasting between 3 and 9 months, a lot a can happen in between. For example, a specific event (e.g., 9/11, the economic crisis) or some new theory or evidence that undermines (or questions) the literature (theory) and assumptions underpinning your conceptual framework (or theoretical model). Clearly, there is little you can do about this. However, if this happens, reflecting on it and re-evaluating your conceptual framework (or theoretical model), as well as your findings, is an obvious source of future research suggestions.

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• How to Write Discussions and Conclusions

The discussion section contains the results and outcomes of a study. An effective discussion informs readers what can be learned from your experiment and provides context for the results.

What makes an effective discussion?

When you’re ready to write your discussion, you’ve already introduced the purpose of your study and provided an in-depth description of the methodology. The discussion informs readers about the larger implications of your study based on the results. Highlighting these implications while not overstating the findings can be challenging, especially when you’re submitting to a journal that selects articles based on novelty or potential impact. Regardless of what journal you are submitting to, the discussion section always serves the same purpose: concluding what your study results actually mean.

A successful discussion section puts your findings in context. It should include:

• the results of your research,
• a discussion of related research, and
• a comparison between your results and initial hypothesis.

Tip: Not all journals share the same naming conventions.

You can apply the advice in this article to the conclusion, results or discussion sections of your manuscript.

Our Early Career Researcher community tells us that the conclusion is often considered the most difficult aspect of a manuscript to write. To help, this guide provides questions to ask yourself, a basic structure to model your discussion off of and examples from published manuscripts. 

Questions to ask yourself:

• Was my hypothesis correct?
• If my hypothesis is partially correct or entirely different, what can be learned from the results? 
• How do the conclusions reshape or add onto the existing knowledge in the field? What does previous research say about the topic? 
• Why are the results important or relevant to your audience? Do they add further evidence to a scientific consensus or disprove prior studies? 
• How can future research build on these observations? What are the key experiments that must be done? 
• What is the “take-home” message you want your reader to leave with?

How to structure a discussion

Trying to fit a complete discussion into a single paragraph can add unnecessary stress to the writing process. If possible, you’ll want to give yourself two or three paragraphs to give the reader a comprehensive understanding of your study as a whole. Here’s one way to structure an effective discussion:

Writing Tips

While the above sections can help you brainstorm and structure your discussion, there are many common mistakes that writers revert to when having difficulties with their paper. Writing a discussion can be a delicate balance between summarizing your results, providing proper context for your research and avoiding introducing new information. Remember that your paper should be both confident and honest about the results! 

• Read the journal’s guidelines on the discussion and conclusion sections. If possible, learn about the guidelines before writing the discussion to ensure you’re writing to meet their expectations. 
• Begin with a clear statement of the principal findings. This will reinforce the main take-away for the reader and set up the rest of the discussion. 
• Explain why the outcomes of your study are important to the reader. Discuss the implications of your findings realistically based on previous literature, highlighting both the strengths and limitations of the research. 
• State whether the results prove or disprove your hypothesis. If your hypothesis was disproved, what might be the reasons? 
• Introduce new or expanded ways to think about the research question. Indicate what next steps can be taken to further pursue any unresolved questions. 
• If dealing with a contemporary or ongoing problem, such as climate change, discuss possible consequences if the problem is avoided. 
• Be concise. Adding unnecessary detail can distract from the main findings. 

Don’t

• Rewrite your abstract. Statements with “we investigated” or “we studied” generally do not belong in the discussion. 
• Include new arguments or evidence not previously discussed. Necessary information and evidence should be introduced in the main body of the paper. 
• Apologize. Even if your research contains significant limitations, don’t undermine your authority by including statements that doubt your methodology or execution. 
• Shy away from speaking on limitations or negative results. Including limitations and negative results will give readers a complete understanding of the presented research. Potential limitations include sources of potential bias, threats to internal or external validity, barriers to implementing an intervention and other issues inherent to the study design. 
• Overstate the importance of your findings. Making grand statements about how a study will fully resolve large questions can lead readers to doubt the success of the research. 

Snippets of Effective Discussions:

Consumer-based actions to reduce plastic pollution in rivers: A multi-criteria decision analysis approach

Identifying reliable indicators of fitness in polar bears

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• How to Write Recommendations in Research | Examples & Tips

How to Write Recommendations in Research | Examples & Tips

Published on 15 September 2022 by Tegan George .

Recommendations in research are a crucial component of your discussion section and the conclusion of your thesis , dissertation , or research paper .

As you conduct your research and analyse the data you collected , perhaps there are ideas or results that don’t quite fit the scope of your research topic . Or, maybe your results suggest that there are further implications of your results or the causal relationships between previously-studied variables than covered in extant research.

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Table of contents

What should recommendations look like, building your research recommendation, how should your recommendations be written, recommendation in research example, frequently asked questions about recommendations.

Recommendations for future research should be:

• Concrete and specific
• Supported with a clear rationale
• Directly connected to your research

Overall, strive to highlight ways other researchers can reproduce or replicate your results to draw further conclusions, and suggest different directions that future research can take, if applicable.

Relatedly, when making these recommendations, avoid:

• Undermining your own work, but rather offer suggestions on how future studies can build upon it
• Suggesting recommendations actually needed to complete your argument, but rather ensure that your research stands alone on its own merits
• Using recommendations as a place for self-criticism, but rather as a natural extension point for your work

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There are many different ways to frame recommendations, but the easiest is perhaps to follow the formula of research question   conclusion  recommendation. Here’s an example.

Conclusion An important condition for controlling many social skills is mastering language. If children have a better command of language, they can express themselves better and are better able to understand their peers. Opportunities to practice social skills are thus dependent on the development of language skills.

As a rule of thumb, try to limit yourself to only the most relevant future recommendations: ones that stem directly from your work. While you can have multiple recommendations for each research conclusion, it is also acceptable to have one recommendation that is connected to more than one conclusion.

These recommendations should be targeted at your audience, specifically toward peers or colleagues in your field that work on similar topics to yours. They can flow directly from any limitations you found while conducting your work, offering concrete and actionable possibilities for how future research can build on anything that your own work was unable to address at the time of your writing.

See below for a full research recommendation example that you can use as a template to write your own.

The current study can be interpreted as a first step in the research on COPD speech characteristics. However, the results of this study should be treated with caution due to the small sample size and the lack of details regarding the participants’ characteristics.

Future research could further examine the differences in speech characteristics between exacerbated COPD patients, stable COPD patients, and healthy controls. It could also contribute to a deeper understanding of the acoustic measurements suitable for e-health measurements.

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While it may be tempting to present new arguments or evidence in your thesis or disseration conclusion , especially if you have a particularly striking argument you’d like to finish your analysis with, you shouldn’t. Theses and dissertations follow a more formal structure than this.

All your findings and arguments should be presented in the body of the text (more specifically in the discussion section and results section .) The conclusion is meant to summarize and reflect on the evidence and arguments you have already presented, not introduce new ones.

The conclusion of your thesis or dissertation should include the following:

• A restatement of your research question
• A summary of your key arguments and/or results
• A short discussion of the implications of your research

For a stronger dissertation conclusion , avoid including:

• Generic concluding phrases (e.g. “In conclusion…”)
• Weak statements that undermine your argument (e.g. “There are good points on both sides of this issue.”)

Your conclusion should leave the reader with a strong, decisive impression of your work.

In a thesis or dissertation, the discussion is an in-depth exploration of the results, going into detail about the meaning of your findings and citing relevant sources to put them in context.

The conclusion is more shorter and more general: it concisely answers your main research question and makes recommendations based on your overall findings.

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Suggestions for Future Research

Your dissertation needs to include suggestions for future research. Depending on requirements of your university, suggestions for future research can be either integrated into Research Limitations section or it can be a separate section.

You will need to propose 4-5 suggestions for future studies and these can include the following:

1. Building upon findings of your research . These may relate to findings of your study that you did not anticipate. Moreover, you may suggest future research to address unanswered aspects of your research problem.

2. Addressing limitations of your research . Your research will not be free from limitations and these may relate to formulation of research aim and objectives, application of data collection method, sample size, scope of discussions and analysis etc. You can propose future research suggestions that address the limitations of your study.

3. Constructing the same research in a new context, location and/or culture . It is most likely that you have addressed your research problem within the settings of specific context, location and/or culture. Accordingly, you can propose future studies that can address the same research problem in a different settings, context, location and/or culture.

4. Re-assessing and expanding theory, framework or model you have addressed in your research . Future studies can address the effects of specific event, emergence of a new theory or evidence and/or other recent phenomenon on your research problem.

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance  offers practical assistance to complete a dissertation with minimum or no stress. The e-book covers all stages of writing a dissertation starting from the selection to the research area to submitting the completed version of the work within the deadline. John Dudovskiy

Conclusions and Recommendations for Future Research

• First Online: 08 April 2021

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At the start of this thesis, we set out on a quest for process realism: viewing and representing processes as they really are, as distinguished from the speculative.

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Janssenswillen, G. (2021). Conclusions and Recommendations for Future Research. In: Unearthing the Real Process Behind the Event Data. Lecture Notes in Business Information Processing, vol 412. Springer, Cham. https://doi.org/10.1007/978-3-030-70733-0_10

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Donaldson MS, Mohr JJ; Institute of Medicine (US). Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis. Washington (DC): National Academies Press (US); 2001.

Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis.

• Hardcopy Version at National Academies Press

CONCLUSIONS AND DIRECTIONS FOR FURTHER RESEARCH AND POLICY

• Limitations of This Research

There are limitations to all sampling strategies and to qualitative research, in particular. The strength of this method was that the sample selection used input from a pool of reognized experts in the organization, delivery, and improvement of health care. Even with a pool of recognized experts, it is reasonable to expect that some high performing micro-systems were overlooked. It was also possible that less than high performing micro-systems were included. In fact, a concern was how to ensure that the micro-systems included in the study were high performing or successful micro-systems, and probes were included in the interview to assess what evidence micro-systems might offer to validate statements about their level of performance. We did not, however, seek validation from documents or other written materials. Although the intent of the sampling strategy was to study high performing micro-systems, a very small number of apparently negative cases were useful for comparison. More importantly, as expected, each site had some areas of very strong performance and other areas that were undistinguished, and they formed a natural cross-case comparison group. Although the sites were selected because of expert opinion, the database is limited by being self report. It is possible that the leaders of the micro-systems had an interest in making their micro-system appear to be better than it is, and we did not have any independent verification of their assertions. For this reason, we did not make any judgments about the validity of respondents' assertions and have limited the analysis to descriptive summaries and themes based on the respondents' own words.

TABLE 18 Micro-System Examples of Investment in Improvement

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TABLE 19 Micro-System Examples of Alignment of Role and Training

A second limitation of this study was that the interviews were not tape-recorded to provide a raw data “gold standard” for later reference. For this reason, we went to considerable effort to ensure the quality of note taking as described in the methods section, and we obtained respondents' consent to follow-up with them to clarify notes. Follow-up was necessary in only a few instances. The notes were voluminous and rich in detail.

A third limitation is that for most of the interviews, one respondent represented each of the forty-three micro-systems. A more comprehensive assessment would include interviews with at least one person from each of the key roles within the micro-system, including patients. Such tradeoffs in qualitative analysis between breadth and depth are inevitable, 31 but given that this was an exploratory study, we decided to include as many micro-systems as possible with follow-up in later studies.

Research currently underway will expand on this work by taking a more comprehensive look at individual micro-systems and the outcomes of care provided to determine if high performing micro-systems achieve superior results for patients.

• Directions for Further Research

This research has been exploratory in that it is the first systematic look at health care micro-systems. The power of the research is that it gave a voice to individual micro-systems and provided a way to explore them while creating constructs that may be generalizable to other micro-systems. It has begun the work of defining and characterizing health care micro-systems. The greater value of this analysis will be to go beyond the findings of this research to develop tools to help existing micro-systems improve and to replicate and extend the achievements of these micro-systems.

The basic concept of health care micro-systems—small, organized groups of providers and staff caring for a defined population of patients—is not new. The key components of micro-systems (patients, populations, providers, activities, and information technology) exist in every health care setting. However, current methods for organizing and delivering health care, preparing future health professionals, conducting health services research, and formulating policy have made it difficult to recognize the interdependence and function of the micro-system.

Further analysis of the database would likely yield additional themes. All can be the basis of hypothesis testing for continued work. For example, further work might establish criteria of effectiveness and test whether the features identified as the eight themes are predictive of effectiveness. More refined or additional questions might clarify aspects of the general themes that are critical. More intensive data gathering, for example, of multiple members of the micro-system, including patients could validate results and expand our understanding of these micro-systems.

Two questions were central as we undertook this study: (1) would the term micro-system be meaningful to clinicians in the field? (2) Would they participate and give us detailed enough information to draw inferences? The answers to both questions were clearly: Yes.

Overall, we discovered that the idea of a micro-system was very readily understood by all we interviewed. They had no difficulty in identifying and describing their own micro-systems and, when appropriate because they directed several (such as several intensive care units), differentiating among them in terms of their characteristics.

The study was assisted in its work by an extremely able and distinguished steering group and Subcommittee whose reputations in the field unquestionably enabled us to secure the participation of nearly all who were invited despite our requesting an hour and a half of a busy clinician's time. Many of those interviewed willingly went on for a longer than the allotted 90 minutes and sent us additional materials. Some who were interrupted by urgent clinical business rescheduled time to complete the interviews.

Although this was a selected—not a randomly sampled—group, and there was clearly great enthusiasm and of innovative work going on at the grass-roots level. Many of those interviewed expressed clear ideas about how they were reorganizing practices, their principles for doing so, and their commitment to an ongoing process. Respondents described their early limited successes or outright failures. We heard what had and had not been successful as they tried to disseminate their practices throughout their organizations. We believe there is much that could profitably learned and shared beyond the individual sites that has not been yet been pulled together by a unifying conceptual framework or effective mechanism for deploying what is being learned.

We were struck by two findings in particular: First, the importance of leadership at the macro-system as well as clinical level; and second, the general lack of information infrastructure in these practices. Micro-system leaders repeatedly stressed the importance of executive and governance-level support. This support was singled out repeatedly as a sine qua non to their ability to succeed. It was also apparent that although some steps have been taken to incorporate the explosion of information technologies that are being deployed for managing patient information, free-standing practices as well as much of clinical practice within hospitals have only begun to integrate data systems, use them for real-time clinical practice, or as information tools for improving the quality of care for a patient population. The potential is enormous, but as yet, almost untapped. They appear to be at a threshold of incorporating information technologies into daily practice. The potential created by the development of knowledge servers, decision support tools, consumer informatics 32 continuous electronic patient-clinician communication, and computer-based electronic health records puts most of these micro-systems almost at “time zero” for what will likely be dramatic changes in the integration of information for real-time patient care and a strong baseline for future comparison.

As research on micro-systems moves forward, it will be important to transfer what has been learned from research on teams and organizations to new research that will be conducted on micro-systems. For example, research that will be helpful includes information about the different stages of development and maturity of the organization, creating the organizational environment to support teams, socializing new members (clinicians and staff) to the team, environments that support micro-systems, the characteristics of effective leadership, and how micro-systems can build linkages that result in well-coordinated care within and across organizational boundaries.

• IOM Quality of Care Study

This study was intended to provide more than a database for research, however. It was undertaken to provide an evidence base for the IOM Committee on the Quality of Health Care in America in formulating its conclusions and recommendations. Because that committee was charged with the formulation of recommendations about changes that can lead to threshold improvement in the quality of care in this country, its members believed that it was extremely important to draw not only on their expertise and the literature but also on the best evidence it could find of excellent performance and to do so in a systematic way as exemplified by this study. As that study was not limited by type of health care, the goals of such a project necessitated drawing from a wide range of sites serving a variety of patient populations. It also suggests a sample size that for qualitative analytic methods was quite broad but not unwieldy. The number of sites interviewed—43—served these purposes well. We had several of each “kind” of micro-system (e.g., primary care, critical care) but they varied in location, composition, and in their own approaches to organizing and delivering care, thus providing a very rich database of observation. That report, which is expected to be published in early 2001, will use the responses and analysis described in this technical report to underpin its recommendations about how health care micro-systems, macro-systems, and other organizational forms that have not yet emerged, can improve their performance.

• Cite this Page Donaldson MS, Mohr JJ; Institute of Medicine (US). Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis. Washington (DC): National Academies Press (US); 2001. CONCLUSIONS AND DIRECTIONS FOR FURTHER RESEARCH AND POLICY.
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